EUROPEAN SOCIETY FOR AGRONOMY

BOOK OF ABSTRACTS

VOLUME II: Theme 2 Agroforestry Session Divisions

Editors: M.K. van Ittersum G.E.G.T. Venner S.C. van de Geijn T.H. Jetten

FOURTH CONGRESS 7-11July , 1996 Veldhoven - Wageningen THE NETHERLANDS V H h I Published byES A Congress Office AB-DLO P.O. Box 14 NL-6700 AAWageninge n The Netherlands

Additional copies are availble from:

European Society for Agronomy (ESA) BP 52 68000 Colmar Cedex FRANCE Tel: +33 8972 4986 Fax:+33 8972493 3

©Europea n Society for Agronomy 1996 ISBN 90-73384-44-3

Cover designed byRuu d Verkerke Fourth Congress of the European Society for Agronomy

Chairman Dr. Hubert Spiertz (Chairman)

Scientific Secretariat

Dr. Siebeva n deGeij n (Chairman) Dr. Martinva nIttersu m Dr. Theo Jetten Dr. Kees Rijniersce Ir. Guido Venner Ruud Verkerke

Corresponding Address: AB-DLO P.O. Box 14 NL-6700 AAWageninge n THE NETHERLANDS Tel:+31 317 475700 Fax:+31 317 423110 Fourth ESA-Congress Board

Dr. Hubert Spiertz (Chairman) Prof.dr . Louise Fresco Dr. Siebeva nd eGeij n Prof.dr . Rudy Rabbinge Dr. Kees Rijniersce

Organising Institutes:

Research Institute for Agrobiology andSoi lFertilit y (AB-DLO)

CT. De WitGraduat e School forProductio n Ecology (WAU-PE)

Research Station for Arable Farming andFiel d Production ofVegetable s (PAGV)

The editors aregratefu l toNicolett e Matulessy, Loes Helbers, Martinva nZandvoort , Erikava n Harten andArmand aVersluij s forthei r assistance. ContentsVolum e II I

Contents volume II

Plenary introduction of Theme 2: Integrated and ecological agriculure. 403 P.Vereijken Amethodica l way ofprototypin g integrated and ecological arable farming systems (I/EAFS) ininteractio n with pilot farmers. 404

Session 2.1:Designin g farming systems: methodological aspects. 407 Introduction:J.M. Meijnard, W.A.H. Rossing Methodology for designing sustainable farming systems:prototypin g and model-based explorations in aparticipator y research setting. 408

H.Bürgi, W. Richner, A. Soldati,P. Stamp Minirhizotron and soilmonolit h comparison ofroo t distribution inpur e and mixed stands ofmaiz e and Italian reygrass. 410 N.Babich, I. Grichanov Ecological basis for sustainable pest management system. 412 C.Bockstaller, P. Girardin Use ofagro-ecologica l indicators for the evaluation offarmin g systems. 414 CS Butcher, K.B.Matthews, A.R.Sibbald Theimplementatio n of aspatia l land allocation decision support systemfo r upland farms in Scotland. 416 C.David, B.Fahre Amode l of on-farm agronomic monitoring applied in organic farming. 418 CA. Helander Arable farming systemresearc h project Logârden. 420 H. Hengsdijk, M.K. vanIttersum Towards sustainable land use inth erura l areas:th e need for designing new systems and technology. 422 F.Herzog, M.J.C. Brownlow Re-integrating perennials into agricultural landscapes - aconceptua l approach. 424 T.J. Koeijer,G.A.A. Wossink Farmer specific prototyping of sustainable production systems: aconceptua l framework. 426 E.A. Lantinga,R. Rabbinge The renaissance ofmixe d farming systems: awa ytoward s sustainable agriculture. 428 J.Nocquet, C. David, Y. Gautronneau Afarmin g system environmental assessment applied on organic farms and farmsi n conversion. 430 B.M. Somers Learning for sustainable agriculture. 432 A.M. Triboi, E. Triboi, B.A le ton Nitrogen dynamics and efficiency incroppin g systemswit h different inputlevels : agronomical, economical and environmental considerations. 434 M.K. vanIttersum, R. Rabbinge Production ecological concepts for the analysis and quantification of input-output combinations. 436 P. von Fragstein Organic arable farming - acontradiction ? 438 II Book of Abstracts 4th ESA-congress

F.G.Wijnands Environment exposure based pesticides selection. 440

Session 2.2: Resource use at cropping system level. 443 Introduction:P.C. Struik, F. Bonciarelli Resource use at the cropping systemlevel . 444

M.L. Bartosova,S. Kosovan Preliminary evaluation ofEPI C insimulatin g cropping systems at one Slovakian location. 446 A. Canarache Soilphysica l properties -soi lmanagemen t interactions ina suitablefarmin g system. 448 A. Castrignanô,G Convertini, D.Ferri, P. Greco Simulation of durumwhea t yield andN dynamicsb y CERES/wheat model ina alfisol of southern Italy. 450 A. Castrignanô,G. Convertini, D.Ferri, V. Rizzo,M. Rinaldi Grain sorghum in southern Italy: dynamic growth and nitrogen simulationb y CERES/sorghummodel . 452 E. Ceotto, M. Donatelli,R. Marchetti, P. Spallacci Nutrient balance at farm levelfo r cropping systems inth eP o Valley, Italy. 454 N. Colbach Modelling the influence of cropping system oninfectio n cycles and diseasebuild-u p for eyespot. 456 N. Colbach, J.M.Meynard Modelling the influence of cropping system ongen e flow from herbicide resistant rapeseed. Presentation ofmode l structure. 458 K. Debreczeni Responses ofwinte r wheat and maizet o NPK nutrient levelsi nlong-ter m fertilization trials. 460 J.-E. Delphin Theus e of porous cups for estimate theimpac t ofcroppin g systems onth e ground water quality. 462 S.V. Garibay, B. Feil Maizeproductio n in alivin g grassmulc h system. 464 P. Greco,G. Manzi Introduction ofa catch-crop of soybean in abienna l oriental tobacco-durum wheat rotation. 466 F.C.T.Guiking, D.M.Jansen Therol e ofmulchin g in cropping systems - synchronizing the release ofnutrient s and crop requirements. 468 M. Jedruszczak, M. Wesolowski, K.Bujak Soybeanyiel d and canopywee d infestation under different crop rotation systems (introductory investigations). 470 J. Kolodziej,K. Liniewicz The influence ofth e cover ofdifferen t cultivated plants onth egroun d water reserve (1981-1995). 472 J.W.A. Langeveld, G.B. Overbosch Nitrogen use and losses at (sub-)farm leveli nPoland . 474 P. Misa Energy balance ofcroppin g systems inth e sugar beet-growing region ofCentra l Moravia. 476 Contents Volume II III

G. Mikkelsen Ecological and integrated systems inDenmark . Internal resources in different systems and their potentials for use. 478 K.Petö Water and nitrogen interaction indifferen t cropping systems. 480 F.Piro, P. Greco Effect ofrotatio nwit hwhea t and catch-crops onphysica ltrait s ofXanth itobacco . 482 E.K. Pisulewska,T. Zajac,R. Witkowicz Intercroppping springtritical e withN-fixin g legumes as acomponen t of sustainable farming. 484 A. Pucaric,B. Varga Maize response to fertilizer nitrogen inmonocultur e and rotation systems onverti c amphygley inUppe r Sava Valley. 486 G. Richard, H.Boizard Modelling workability ofloam y soilsfo r seedbe d preparation. 488 G.M.Richter, A.J. Beblik, J.Richter Optimizing N fertilizer demand ofwinte r ryethroug h quantitative modelling - calibration and practical application. 490 P. Spallacci,E. Ceotto, R. Rapini,R. Marchetti Lucerne as a "nitrate scavenger" for siltycla y soilmanure d with pig slurry. 492 V. Stefan,I. Savulescu, H.V. Halmajan Cultivar mixture study onwhea t yield inRomania n conditions. 494 E.A. Stockdale, A. Agarwal, K.W.T. Goulding, S.C. Jarvis Quantification ofnitroge n dynamics inecologica l mixed farming systems. 496 C.O. Stockte, M. Cabelguenne, P. Debaeke Validation of CropSyst for water management at a sitei n south-western France. 498 S.A. Tarawali, J.W. Smith, M. Peters, L.Muhr, R. Schultze-Kraft, G. Tarawali Optimising land productivity incrop-livestoc k systemsb yintegratin g legumesi nth e lowland moist savannes ofwes t Africa. 500 A.M. vanDam, J. Vos, J. Wolfert, E.A.Lantinga, P.A. Leffelaar Growth and nitrogen accumulation ofwinte r rye as acatc h crop: model and experiment. 502 F.K. vanEvert, J.M. Baker CropSyst-with-objects 3.0:geared for comparison ofcomponen t models. 504 D. Ventrella, M. Rinaldi,V. Rizzo,F. Fornaro Water use efficiency ofnin e cropping systems ina wate r limited environment. 506 A. Wozniak Importance ofunderplan t crop and farmyard asmanure si nmonocultur e ofwinte r triticale. 508 K.D.Sayre Development of a sustainable bed-planting technology to allowreduced-tillag e and crop residue management infurrow-irrigate d wheat production systems. 510

Session 2.3:Resourc e usea t croplevel . 511 Introduction:A.J. Haverkort, M.J Minguez The efficient use ofwate r and nitrogen in arable farming inEurope : isther e scope for improvement? 512 IV Book of Abstracts 4th ESA-congress

A. Abad, J. Lloveras, A. Michelena Effect of soilnitrat e andN fertilizatio n onbrea d and durum wheat yield and quality and on residual N-NO3concentration s under irrigation inEbr o Valley (Spain). 514 L.G. Angelini,M. Mazzoncini, L. Ceccarini Changes inphot osyntheti c capacity associated with soilwate r depletion inmaiz e grown under conventional and minimumtillage . 516 M. Aydin Response of cotton to nitrogen andwate r ina subtropical environment. 518 P.Barberi, M. Ginanni,S. Menini, N.Silvestri, M.Mazzoncini Effect oftillag e systems onwee d presence and diversity in acontinuou s maize cropping system. 520 R.J. Bryson, W.S.Clark, N.D.Paveley Explaining theyiel d response ofwinte r wheat duet o fungicides byth e effects on green leaf area duration and radiation interception. 522 A.M. Castelao, M.J. Sâinz, M. Bujân Variation ofth e soilhumidit y ina n ecological culture of asparagus (Asparagus officinalis L.) inGalici a (N.W.Spain). 524 P. Castillon, A. Bouthier Correction ofzin can d copper deficiencies onmaiz e crops. 526 B. Chauvel,C. Angonin,N. Colbach Black-grass (Alopecurusmyosuroides Huds.) development and seed production inwheat . 528 B. Colomb,G. Fayet, C. Villette, M. Gigout, P.Dubrulle, D.Baudet Soil analyses and fertilizer recommendations. Software for soiltes t laboratories and extension services. 530 Z.M. Copchyk, A.Y. Maruhnyak Thereactio n of cultivars springbarle y to fertilisers and sowing rates ofth e seed under condition ofWes t Region ofUkraine . 532 F.J.De Ruijter, A.J.Haverkort Potato crop growth and nutrient concentration asinfluence d by soil-pHan d potato cyst nematodes. 534 G Deffune,A.M. Scofield, H.C.Lee, J.M. Lopez-Real, P. Simünek Influences ofbio-dynami c and organictreatment s onyiel d and quality ofwhea t and potatoes: thewa yt o applied allelopathy? 536 S.Demotes-Mainard, M.H. Jeuffroy Effects ofnitroge n deficiencies ongrai n set inwheat . 538 K.J.Doughty, C.Lewis, H.A.McCartney, G Norton, E.J.Booth, K. Walker Oilseed rape oilyiel d and quality inrelatio nt o fungal disease. 540 M. Durkic,M. Knezevic, I.Juric Relationship betweenwee d level and leaf area ininbre d maizelines . 542 JE. Fernandez, J.M.Murillo, F. Moreno, F. Cabrera, E. Fernandez-Boy Reducing fertilization for maizei n south-west Spain. 544 J. Fismes,P.C. Vong, A.Guckert Ammoniumthiosulphat e (ATS) as an environmentally friendly tool for N and Snutritio n ofrapeseed (BrassicanapusL). 546 E. Fotyma, M.Fotyma Water and nitrogen budget of springbarle y field. 548 M. Fotyma,E. Fotyma Water and nitrogen budget ofwinte r wheat field. 550 Contents Volume II V

M. Galan,N. Lisova High-yield varieties ofwinte r vetch andus e ofvariey-strai n technology for their growing. 552 M. Guiducci, P. Benincasa, M.Migni Effect ofnitroge n fertilisation onlea fphotosynthesi s and light absorption intobacco . 554 M. Jolânkai,Z Szentpétery,T. Szalai Variety specific weed tolerance -a ke yt o non chemical weed control. 556 M. Knezevic, I. Zugec,I. Juric, M. Durkic Soiltillag e as animportan t measure inwee d control for winter wheat(Triticum aestivum L). 558 J.Kren Possibilities ofusin gmodula r growth andplan thierarchica l structuret o evaluate resource usei n cereal growing. 560 J.Kren Comparison of ecological and conventional cropping practices ofcereal sunde r fertile conditions inCentra l Moravia. 562 M. Kruse, W. Aufliammer Evaluation of alternative grain crops in south-west Germany: nitrogen economy. 564 B. Kulig,W. Ziólek Productivity ofhors ebea ni nrelatio nt o the nitrogen fertilization. 566 A. Lange,H. W. Scherer Effect of sulphur nutrition onth e activity ofnitrogenas e and enzymes ofth e C- and N- metabolism of Viciafaba minor andPisum sativum. 568 F.Lasserre, B. Jouan,R. Rivoal Optimalus e of resistance for anintegrate d management program of cereal nematode populations. 570 N.Lisova, M. Galon,V. Patyka, M. Bezdushny, A.Pogorecky Use of associative diazotrophs for nitrogen nutrition ofgramineou s crops. 572 N.Losavio, N. Lamascese, F. Serio, A.V. Vonella Estimated radiation use efficiency on alternative cropsunde r typical mediterranean conditions. 574 M. Maiorana, R. Colucci, D.Ventrella Crop residues and soiltillage s management: effects on soil strength. 576 E.Nâdasy Study onth e effect ofN-fertilizer s ontota l nitrogen and nitrate content ofgree n pea and garlic. 578 J. Nagy,L. Huzsvai,J. Tamos, G.J. Kovâcs,I. Mészâros The effects ofirrigation , fertilization, tillage and plant density on corn {Zeamays L. ) yield. 580 L. Neudert, J. Kren Energetic analysis ofEuropea nwinte r wheat management practices compared at the DLG-Feldtagei n Germany. 582 D.J.Pantone, J.R. Kiniry Integrating weed-crop competition into aprocess-oriente d crop growth model: Evaluation of cocklebur competition with soybean. 584 F.Promayon, C.David Nitrogen nutrition management inwinte r wheat inorgani c farming. 586 R. Reau, C. Colnenne, D.Wagner Nitrogen fertilization needs ofrapesee d inautumn . 588 VI Book of Abstracts 4th ESA-congress

R. Richter,Z. Poulik, J. Rihmovâ Efficiency of different technologies for the application offertilizer s to cereals. 590 J.Rozbicki, W. Madiy, M. Kalinowska-Zdun, Z. Wyszynski Yielding ofwinte r triticale var. Presto under low input and intensive methods of crop management. 592 K.D. Sayre, C.van der Wilk Lower yield loss due to diseases innewe rwhea t varieties. 594 J. Schouls,G.O. Nijland Input, output andresidu e ofnutrients . 596 L.P. Simmonds,C.C Daamen,C.J. Pilbeam Factors influencing cropwate r use efficiency. 598 CO. Stockle,P. Debaeke Modelling crop Nrequirements : acritica l analysis. 600 F. Tei, A. Onofri, M.Guiducci Relationship between N-concentration and growth in sweet pepper. 602 A.J. Valentine, B.A. Osborne, D.T. Mitchell Effect ofmycorrhiza l infection onphotosyntheti c metabolism. 604 R. vanden Boogaard, K. Thorup-Kristensen Effects of defoliation ongrowt h of cauliflower. 606 P.E.L. vander Putten, G.Posca, J. Vos Effect ofnitroge n supply onlea fgrowt h and photosynthetic capacity inpotato . 608 M. Volterrani, M. Gaetani, N. Grossi, G.Pardini, S. Miele, G. Scalabrelli Ground cover invineyard swit h grass andlegum e species inpur e and mixed stands. 610 M. Wesolowski, M.Jedruszczak Yield of sugar beetusin g alternatives for farm yard manure. 612 W. Ziólek, B. Kulig Effects offolia r fertilization withnitroge n andmicroelement s on seed yield ofpeas . 614

Agroforestry Session 617

D. Auclair Alternative agricultural land usewit h fast growing trees: scientific bases andmode l for European agroforestry. 618 H.Breman, J.J. Kessler Thepotentia l ofagroforestr y for Sahelian countries. 620 J.G. Conijn Simulation oflon g term carbon dynamics and nitrogen yield of anagroforestr y systemi n a semi arid region. 622 J. Dauzat, M. Eroy, M.L. Girard Radiative climate modelling onvirtua l cococuts stands for predicting theligh t regimei n coconut based farming systems. 624 A.M. Heineman On station evaluation ofLeucaena, Calliandra, Gliricidia, Sesbania, Sennaan d Erythrina species inalle y cropping with maizei nwester n Kenya. Alon gter m experiment: 1988-1994. 626 Contents Volume II VII

A.M. Heineman Seasonal and longter m effects oîLeucaena leucocephala hedgerows and inorganic sources ofN and P onth e productivity ofmaiz e -bea n systemsi nwester n Kenya, with comparative nutrient use efficiencies of different fertiliser alternatives. Along term experiment: 1988-1994. 628 GM. Hoppe,A.R. Sibbald, J.H.McAdam, W.R. Eason, M. Hislop,Z. Teklehaimanot The UKnationa l network silvopastoral agroforestry experiment -a co-ordinated approach to research. 630 J.E. Lott, CR. Black,CK Ong Thephysiologica l constraints on crop growth indrylan d agroforestry. 632 J. Park, S.H.Newman Tree-soils interactions inpoplar-arabl e agroforestry systems. 634 M. vanNoordwijk Below- and abovegroun d resource capture in agroforestry systems. 636

Division 1: Crop physiology, production and management. 639

A.S. Alexieva,M. Kilifarska Investigating the airhumidit y inth e environment ofplant sb yusin g an electric thermal measuring transducer. 640 S.J. Crafts-Brandner, R. Hölzner,U. Feller Stromal enzymes inN-deficien t wheat: mRNAan d protein quantities. 642 T.Gebbing, H.Schnyder Is immobilzation ofpre-anthesi s reserves reflected indr ymatte r loss from vegetative plant parts ofwheat ? 644 T.Gebbing, H. Schnyder,W. Kühbauch Contribution ofpre-anthesi s reservest o grain filling ofsprin gwheat : assessment by 13 12 steady-state C02/ C02 labelling. 646 M.P. Guinchard, Ch.Robin Contribution of carbohydrates to winter survival and springregrowt h ofwhit e clover (Trifolium repensL .) . 648 H.Lipavskä, L.Nâtr Contribution ofi nvitr o plant culturest o the study ofminera lnutrition . 650 R. Maciorowski, S. Stankowski, G Podolska, A.Pecio Application of different functions to the description ofgrowt h ofbuckwhea t(Fagopyrum esculentum Moench). 652 I.Maurice, F. Gastal Anatomical and biochemical changes ofgras s leaves during development. 654 N.Mladenov, N. Przulj,N. Hristov, Y.Yan, S.Prodanovic, S. Vuckovic Studies onth e accumulation ofgliadi n proteins duringwhea t grain development. 656 R. Mosquera,E. Corral, A. Castelao, E. Lopez,C Moirón,A. Rigueiro, J. Villarino Comparison oftw o destructive methodsi nth e estimation ofgrasslan d production. 658 R. Mosquera-Losada, A. Gonzalez-Rodriguez Study ofno n destructive method ofdr ymatte ryiel d estimation indair yrotationa l system. 660 J.Pawlowska, D.Dietrych-Szóstak, A.Pecio Response ofbuckwhea t varieties grown on different soilst o dimetipin. 662 R. Pfarrer,U. Feller Influence ofinorgani c nitrogen on senescence and protein remobilization infla g leaves of maturing wheat grown onwaterlogge d soil. 664 VIII Book of Abstracts 4th ESA-congress

K.Streiff, A. Blouet, A.Guckert Water deficit and pollination potential ofwhea t (Triticum aestivum L). 666

Division 2:Agroclimatolog y and modelling. 669

V. Magliulo, F.De Lorenzi, L. Lustrini, A.Pitacco Estimating zero plane displacement and roughness parameters ina sunflower crop. 670

Division 3:Plant-soi l relationships. 673

A.S. Alexieva Results from aninvestigatio n onth e heatflux densit y in soil onth e base of thermoelectric and conductometric transducers. 674 N.P.Buchkina, T.S. Zvereva Relations between stability oftundr a soils affected bymechanica l impacts and plant community composition. 676 M. Bzowska-Bakalarz Factors determining thevalue s offerees needed for pulling out sugarbee t roots from the soil. 678 H.V. Halmajan,L. Ungurean, A. Dobrescu,V. Stefan,I. Savulescu Effect of soil compaction onnodul e structure in soybean. 680 J.Matula Evaluation ofpotassiu m status of soils. 682 M. Mazzoncini,E. Bonari,M. Ginanni, S. Menini,F. Sancarlo Earthworms presence as affected bytillag e system incla y soil. 684 L. Szabó Effect oftoxi c metals on the germinating ability ofwinte r wheat. 686 L. Szabó Trace elements supply ofth e arablelan d inHungary . 688

Division 4: Crop quality and post-harvest physiology. 691

F. Borowiec, E. Pisulewska, K. Furgal Mixed cereal-vetch forage asa silage crop insustainabl e farming. 692 J. Crnobarac, B. Marinkovic Effect of environmental factors, genotype and period ofharves t onpost-harves t ripening of sunflower. 694 M. Malesevic, Lj. Starcevic, D. Bogdanovic, N. Przulj Relationship between soilnitrat e content and grain protein content inmaltin g barley {Hordeum sativum ssp.Distichum). 696 I.Pâlinkàs Examination ofth e organic growth offive silag e maizevarietie s by applying statistical approaches. 698 V.J.H. Sewalt, J.W. Blount,R.A. Dixon Metabolic engineering ofligni nthroug h flux control inth e phenylpropanoid biosynthetic pathway. 700 Contents Volume II IX

Division 6: Agriculture-environment relationships. 703

J. Balik, P. Tlustos, J. Szakova, V. Vanek The effect of different forms of nitrogen fertilizers on the accumulation of cadmium and zinc in plant tissues. 704 L. Fodor Effect of toxic elements on the winter wheat on brown forest soil. 706 N. Kharitonov, M. Bulgakova, V.Pashova, I. Onuphrieva Growing the plants on the soil polluted by heavy metals. 708 D. Pavlikova, V. Vanek, J. Szakova, J. Balik The accumulation and distribution of cadmium, zinc and arsenicum by poppy. 710 V.A. Pozdnyakov, A. Kudums, I. Drizhachenko Heavy metals and differentiation of perennial grasses in the pathogen resistance character. 712 P. Tlustos, J. Balik, J. Szakova, D. Pavlikova The effect of soil remediation treatments on plant uptake of cadmium, zinc and arsenic. 714 H.M.G. van der Werf,C. Zimmer Evaluating the impact of pesticides on the environment using an indicator based on fuzzy coded variables. 716

Author index 719

Subject index 727

National representatives 734

ESA Executive committee 736 Plenary introduction ofThem e2

Integrated and ecological agriculture. 404 Book of Abstracts 4th ESA-congress

A METHODICAL WAY OFPROTOTYPIN G INTEGRATED AND ECOLOGICAL ARABLE FARMING SYSTEMS (I/EAFS) ININTERACTIO N WITH PILOT FARMS P. Vereijken, AB-DLO,P.O .Bo x 14,670 0 AA Wageningen, The Netherlands Introduction The European Union (EU) isfacin g an agricultural crisis with two major symptoms:deterio ­ ration ofrura l income and employment and deterioration of environment, nature and land­ scape.Th e basicmechanis m isa neve r ending intensification causing surplus production and price fall onth e one hand and ecological deterioration onth e other hand. Therefore, a crucial question for the Common Agricultural Policy (CAP) ist o alleviate the symptoms of intensifi­ cation onth e shortter m and tofind a sustainable solution onth e longterm . Inth e earlynine ­ ties,variou s EU-countries started promoting Integrated Farming Systems to alleviate the agri­ cultural crisis,whe n drastic reductions in inputs ofpesticide s and fertilisers were achieved with initial prototypes on experimental farms. Subsequently, in 1993th e EU-Commission invited the author to act ascoordinato r ofa networ k ofresearc h teams on Integrated Arable Farming Systems (IAFS). The setting up ofth e network should be combined with develop­ ment and standardisation ofth emethodolog y in aconcerte d action within thethir d EU framework programme for agricultural research called AIR. Most research teamsjoinin g thenetwor k develop IAFSprototype s feasible for the main group of farms. This groupmus t tryt o becompetitiv e onth e world market, based onhig h and effi­ cientproduction , andthi s gives only limited scope for pursuing non-marketable objectives such asenvironment , nature/landscape and sustainability of food supply. Therefore, amor e consistent integration ofobjective s isneede d for a sustainable solution ofth e agricultural cri­ sis. Consequently, many research teams also or exclusively develop anIAF S for the longterm , albeit that this IAFS isa sye t only feasible for pilot groups of farms. Contrary to short-term IAFS,thes e long-term IAFS place income/profit subordinate to environment, and relyo n ecologically-aware consumerswillin gt opa ypremiu m prices for food products with high added value and acredibl e label. The latter impliesth e sharing ofresponsibilit y byproducer s and consumers for amultifunctiona l and sustainable management ofth e rural areas. Social conversion to thismarke t model seemsth e only sustainable solution to end intensification and replace itb y asociall y controlled and ecologically responsibletechnolog y development, notwithstanding afree worl d market. Inth e long-term IAFS,Chemica l Crop Protection isfull y replaced by apackag e of non- chemical measures,t o achieve ambitious objectives inenvironment , nature/landscape and quality and sustainability of food supply. So,long-ter m IAFS are based moreo n ecological awareness andknowledg e than short-term IAFS. Therefore, ourprototype s of long-term IAFS aresimpl ycalle d EAFS(Ecologica l Arable Farming Systems),an d short-term IAFSar e refer­ red to asIAFS .However , it should be explicitly stated that EAFS are notth e same asth e organic farming systems that currently feature under anofficia l European label. Organicsys ­ tems canb e considered to be aforerunne r of EAFS, but they have no quantified objectives in environment and nature/landscape and asa result , theynee d to be considerably improved to become acceptable to themajorit y of consumers.Nevertheless , organic farming has a strategic significance to Europebecaus e it isth efirst exampl e ofth e market model of shared respon­ sibility of consumers and producers for the rural areas.Therefore , many research teams are collaborating with apilo t group oforgani c farms which have primarily been selected for their willingness to achieve moretha n isrequire d by current minimal guidelines ofth e EU organic label. Selected on a set ofgenera l and specific criteria, 22researc h teams from 14E U and 3associ ­ ated countries havebee n brought together intoth e network, sinceth e start in 1993. Together they invest more than 30 scientist years per annum inprototyping . This paper focusses ona methodical way of 5step s wehav e developed within the network asa common frame of reference for prototyping I/EAFS. The consecutive steps will bepresente d and illustrated by the state-of-the-art ofth eauthor' s own project onEAF S with agrou p ofpilo t farms (NL2) . Methodical way ofprototypin g I/EAFS (5 steps) Building on initial experience with anexperimenta l farm atNagel e (Vereijken, 1992)an d the input ofth eresearc h leaders from thenetwork ,prototypin g ofI/EAF Sha sbee nelaborate d ina Plenary introduction of Theme 2 405 methodical wayo f 5forma l steps (Vereijken, 1994, 1995),(Outlin e 1).Th e outcome ofthes e 5 stepsi sexpresse d inpart so fa n identity card for theprototyp et o facilitate the cooperation withinth e team andth e exchange with the other teams inth e network. Inth e full paper the 5 steps will be explained in more detail and illustrated byth e variouspart s ofth e identity card ofou rprototyp e EAFS for the central clayregio n in TheNetherland s (NL2) . Outline 1. Methodical way of designing,testing , improving and disseminating prototypes of Integrated and Ecological (Arable) Farming Systems (I/EAFS). (1) Hierarchyof objectives: making ahierarch y in 6genera l objectives, subdivided into 20 specific objectives asa base for aprototyp e in whichth e strategic shortcomings ofcurren t farming systems are replenished (Part 1 ofth e identity card ofa prototype) . (2) Parametersand methods: transformingth emajo r (10)specifi cobjective sint omulti-objectiv eparameter st o quantify them,establishin g themulti-objectiv e methods needed to achieve the quantified objec­ tives (Part 2o fth e identitycard) . (3) Designof theoretical prototype andmethods: designinga theoretica l prototypeb ylinkin gparameter st omethod s(Par t3 o fth eidentit y card),designin g methods inthi s context until they are ready for initial testing (Multifunctional Crop Rotation asmajo r method and Part4 ofth e identitycard) . (4) Layoutof prototype totest and improve: layingth eprototyp e out on anexperimenta l farm or onpilo t farms in anagro-ecologi - callyappropriat e way (Part 5o fth e identity card),testin g and improving the prototype ingenera l andth emetho d inparticula r until (after repeated laying out)th eobjectives , as quantified inth e set ofparameters ,hav e been achieved. (Part 6o fth e identitycard) . (5) Dissemination: disseminating theprototyp eb ypilo t groups (< 15farmers) , regional networks (15-50 farmers) and eventually bynationa l networks (regional networks interlinked) with gradual shift insupervisio n from researchers to extensionists. References Anonymous (1977).A n approach towards integrated agricultural production through integrated plant protection. I0BC/WPRS Bulletin no.4 , 163 pp. ElTiti ,A. ,Boile rE.F .& J.P .Gendrie r (1993).Integrate d production, principles and technical guidelines.Publicatio n ofth e Commission: IP-guidelines and endorsement. IOBC/WPRSBulleti n no. 16,9 6pp .ISB N 92-9067-048-0. Geier,B . (1991)(Ed.).IFOA Mbasi c standards oforgani c agriculture and food processing, 20 pp. Oecozentrum Imsbach, D-66696 Tholey-Theley (Germany). Gibbon, D. (1994).Farmin g systemsResearch/Extension :backgroun d concepts, experience andnetworking . In:Den t J.B.an dM.J . McGrego r (Eds.) Rural and farming Systems analysis. European perspectives. Proceedings ofth e first European Convention on Farming Systems Research and Extension, Edinburgh 1993:3-19.A B International. ISBN 0851989144. Rohling,N . (1994). Interaction between extension services and farmer decision making: new issues and sustainable farming. In:Den t J.B.an d M.J. Mc Gregor (Eds.) Rural and farming Systems analysis. European perspectives.Proceeding s ofth efirst Europea n Convention on Farming Systems Research and Extension, Edinburgh 1993: 280-291. AB International ISBN 0851989144 Vereijken, P.,C.A . Edwards,A E lTiti ,A . Fougeroux &M . Way(1986) .Repor t ofth e study group:Managemen t offarmin g systems for Integrated Control.IOBC/WPR S Bulletin no. 9. ISBN 92-9057-001-0. Vereijken, P.(1992) .A methodi c wayt o more sustainable farming systems,Netherland s Journal Agricultural Science(40):209-223 . Vereijken, P. (1994).Designin g prototypes. Progressrepor t 1 ofth e research network on Integrated and Ecological Arable Farming Systems for EUan d associated countries, 90pp . AB-DLO Wageningen (Netherlands). Vereijken, P. (1995).Designin g andtestin gprototypes . Progress report 2 of ofth e research network on Integrated and Ecological Arable Farming Systems for EU and associated countries,9 0pp .AB-DL OWageninge n (Netherlands). Session 2.1

Designing farming systems:methodologica l aspects. 408 Book of Abstracts 4th ESA-congress

METHODOLOGY FOR DESIGNING SUSTAINABLE FARMING SYSTEMS: PROTOTYPING AND MODEL-BASED EXPLORATIONS IN A PARTICIPATORY RESEARCH SETTING

J.M. Meynard1 and W.A.H. Rossing2

1 Unitéd'Agronomi e INRA-INA PG,F-7885 0Thiverval-Grignon , France 2 Dept. Theoretical Production Ecology, WAU,P O Box 430,670 0 AKWageningen , the Netherlands

Introduction In manypart s ofEurope , agriculture hasbee n very successful in increasing yieldspe runi to f area. Atth e sametime ,th eproductio n techniques that have beenemployed , haveresulte d in unwanted sideeffects : emissions of pesticides and plant nutrients, (in)organic waste,hig h energy consumption. Public concern isreflecte d in asuit e ofnationa l andinternationa l policy statements. More sustainable agricultural land userequire sproductio n systems which,i n addition toeconomi c objectives, cater toobjective s in areaso f environment, public health,rura l scenery andnature . Sincethes eobjective s are atleas tpartiall y conflicting, development of sustainable farming systems isequivalen t with searchingfo r acceptable compromises between objectives using all technology available.Wha t ensuesi sa proces s of negotiation about objectives and learning aboutproductio n techniques andthei rinteractio n with objectives. Thechalleng e for agriculturalresearc h ist o developmethodolog y tofacilitat e theseprocesse s and helpt odevelo ptechnologie s and systems thatenabl e combination of, todate ,conflictin g objectives. During the last decade,prototypin g andmodel-base d exploration haveemerge d aspromisin g approaches in sustainable farming systemsresearch . Prototyping involves application-oriented development of sustainable farming andcroppin g systemsi n collaboration with commercial farmers or atexperimenta l farms according toa methodica l approach (Vereijken, 1992).Model - based explorations have been conducted atth efiel d level anda tth e farm level, improving decision making (Meynard &Girardin , 1991) and exploring bio-physical possibilities for achieving economic and environment-oriented objectives (Rossing et al., 1996). From the case studies available todate ,fou r phases emerge indevelopmen t of sustainable farming systems:diagnosis , design, testing andimproving , anddissemination . We will discuss methodical aspects ofeac h phase and emphasize thedistinc t andcomplementar y roleprototypin g andmodel - based explorations play. Two illustrations will beprovided , oneo n cereal crops inFrance ,th e other on flower bulbdominate d rotations in theNetherlands .

Phase 1 - Diagnosis In contrast toadoptio n of traditional, discipline-driven, tactical innovations in the production process, achang e towards more sustainable production systems usually involves aturnaroun d in theentir e farm operation. Such strategicinnovatio n isonl ypossibl e when farmers and their social environment areawar eo f current constraints andmotivate d towardschange . Operating ina network asa mean st odea l with uncertainties associated withmajo r changesi nfarmin g practice often appearsessential . Often, registration andcompariso n of farm activities by farmers constitutes an important method toincreas e awareness. Research may enhance thediagnosi sphas e byanalysi so f existing production methods attw olevels .A t thefiel d level characteristics ofth e cropping systems areidentifie d which determine yields,quality , andenvironmenta l aspects (Doré et al., 1996).A t thefar m level agro-ecological and economic indicators areuse d toindicat e opportunities for change. The diagnosisphas e results in astrategi c alliance of "stakeholders"wit h Session 2.1 409 acommo n motivation toexplor e alternative wayso f agricultural production.

Phase 2 - Design Theproduct s of thedesig n phase are anumbe r of theoretical prototypes of sustainable cropping and farming systems.Th e process follows the steps of industrial design, starting with identification of theobjective s including unitsi n which thedesig n ist ob eevaluated , followed by appraisal of production techniques in terms of these objectives, and searching for blendso f production techniques which satisfy theobjectives .Th eresul t is aperspectiv e on development options based on the trade-off between e.g. economic and environmental objectives, which provides abasi s for selection of promising theoretical prototypes. Tools in thisphas erang e from interactive simulation systems,t oexper t systems and multiple goal linear programming models and are used as part of workshops. Research hasa synthesizing role,providin g information on production techniques andthei rrelatio n toobjective s in aneducationa l setting aimed at stimulating the design process.

Phase 3 - Testing and improving The theoretical prototypes thatemerge d from thedesig n phasear eevaluate d andimprove d with respect tocomprehensiveness , acceptability, workability, andeffectivity . Evaluation may be executed onexperimenta l farms, commercial pilot farms, or indecisio n rulebase d cropping systems experiments. While anexperimenta l setting enablescompariso n between alternative prototypes, important constraints on commercial farms may bedisregarded . Cropping systems experiments in which production methods are tested subject toconstraint s anddecisio n rules prevailing oncommercia l farms, contribute toimprovin g prototypes (Meynard &Girardin , 1991).

Phase 4 - Dissemination Dissemination of theregionall y adapted prototype requiresprocesse s and tools similar tothos eo f testing and improving, sincei n thisphas e theregiona l prototype isadapte d toloca lcondition s and individual constraints. Results of thediagnosi sphas erevea l thediversit y of farm constraints the prototypes have tob eadapte d to,an d provide support in thedisseminatio n phase. Approaches range from guided implementation of integral prototypes tointroductio n of components, such as integrated nutrient management. While in theproces s agronomic uncertainties havebee nmad e manageable,psychologica l and social uncertainties appear tob e still large in thisphase .Thus , in addition totechnica l monitoring, sustained attention for facilitating learning processes isneeded .

Conclusion Despite thegenera l distinction of four phases,w eobserv eimportan t differences in approaches between countries, both regarding the nature and therol e of agronomic research. Itwil l be necessary toincreas e methodical comparison andreciproca l enrichment in ordert oimprov e methodology for designing new and sustainable farming systems.

References Doré,T. , et al, 1996.A diagnosi s method on regional crop yield variations. Submitted to Agricultural Systems. Meynard, J.M. & Girardin, P., 1991.L e Courrier de l'Environnement de l'INRA 15:1-19. Rossing, W.A.H., et al, 1996.Betwee n market and environment: exploring options for environmentally friendlier flower bulbproductio n systems. Submitted toEuropea n Journal of Plant Protection. Vereijken, P., 1992.Netherland s Journal of Agricultural Science40:209-223 . 410 Book of Abstracts 4th ESA-congress

MINIRHIZOTRON ANDSOI LMONOLIT H COMPARISON OFROO T DISTRIBUTION INPUR EAN DMIXE DSTAND SO FMAIZ EAN DITALIA N RYEGRASS

H. Bürgi,W . Richner, A. Soldati, P. Stamp

ETH Zürich, Institute ofPlan t Sciences,ETH-Zentrum , CH-8092Züric h

Introduction The minirhizotron technique hasofte n beenuse d to non-destructivelyanalys eplan t root growth and dynamics,becaus e it isles slabour-intensiv e than destructive methods and allows the roots to berepeatedl y observed over longer periodso ftime .However , numerous studies withminirhizot - rons buried at an angle to the soilsurfac e have shown that auniversall y applicable calibration of minirhizotron root counts withroo t length densityi sno t possible (Smit et al, 1994).Fewe rcali ­ bration experiments have been carried out with horizontally buried minirhizotrons. Therefore, we compared root distributions determined using horizontally installed minirhizotrons and soilmono ­ liths inbot h pure andmixe d stands ofmaiz e (Zeamaize L. ) and Italianryegras s (Loliummultiflo- rumL.) .Th e latter system,Le .sowin gmaiz e into livingryegras s sods (Garibayan d Feil, 1996),i s propagated in Switzerland becausei tma yalleviat e problemsassociate d with traditional cropping of maize such as soilerosio n andnitrat e leaching.

Methods Plants were grown ina greenhous e inboxe s of7 5c mlength , 55c mwidt h and 90c m depth, which were filled with sandyloa msoi lt o abul k densityo f 1.2 Mgm"" 3. During filling, minirhizot­ rons were installed horizontally at depthso f 10,20,40 , 60,an d 80cm .Correspondin g to aplan ­ ting densityo f 10plant sm~ 2,maiz ewa ssow ni na ro wperpendicula r to theminirhizotrons . The ryegrass was sown at a densityo f 3g m -2,coverin g the entire soilsurface . After establishment of the ryegrass stands, a3 0 cmwid e strip inth e middle ofeac h boxwa skille d off usingRoundup® . For the mixed stand treatment only,maiz ewa ssow n inth eresultan t strip of exposed soilte n days after killing of the swards. To alleviatecompetitio n withth e maizecrop ,ryegras sregrowin g inth e strip wascut three times duringearl ygrowt h of themaize .Plant swer e harvested at the timeo f maize silking.Whe nth erecordin g of theuppe r sideso fth eminirhizotro n tubes with a Bartz®ca ­ mera system wascompleted , soilsample s (7.5c mlength , 6c mwidth , 5c mheight ) were taken fromdirectl y above the minirhizotron tubes to determine volumetric root length density. There were three replications.

Results Root length densitywa s greatest inth e mixed standsi nbot hth ero w and inter-row regions for all soildepth sexcep t 60c man d smallest inth ero w region under maize to adept h of 40cm . At greater depths, maizerootin g densitywa scomparabl e to that ofmixe d standsi nbot hro w and inter-row regions due to the more shallowroo t system ofryegras s(dat a not shown).Thes e verti­ caldistribution s ofroo t length densities were poorlyrepresente d byminirhizotro n root numbers, especially inmaiz e andmixe d standso f maizean dryegras s (Fig.1) .Rootin g density seemed to be significantly underestimated inryegras s at 10c m depth, and inmaiz e and the maize-ryegrass mix­ ture at depths from 10t o 20c m and below 60cm . Insimila r fashion, Andrene t al. (1993) found anunderestimatio n ofroo t growth usinghorizonta lminirhizotron si nth etopsoi l( 0-3 0 cm) under barley. Session2. 1 411

Inter-row region Row region

10c m 20c m 40c m EX3 60 cm ^3 80 cm

M MR M MR M MR Maize - Maize- Ryegrass Ryegrass Maize Ryegrass Figure 1. Depth distribution ofroo t length densityfrom soi lmonolith s (M) andminirhizotro nroo t numbers (MR) in the row andinter-ro wregion s ofpur e and mixed stands ofmaiz e andItalia nryegras s atth etim e ofmaiz e silking.

In agreement with the relationship between depthprofile s ofroo t length densityan d minirhizotron root numbers, there was aclos e overallcorrelatio n between these two parameters inryegras s only (r=0.92) (Fig. 2). The samerelationshi p waswea ki nmaize ,and ,correspondin g to the closer cor­ relation inryegrass , slightlybette r inth e mixed stands.Poo r correlations between monolith and minirhizotron data inmaiz e were alsofoun d byMajd i et aL(1992) .A mor eregula r horizontal distribution and amor e uniform growth direction of the highlybranche d ryegrassroot s inth e soil mayhav ebee nresponsibl e for thebette rcorrelatio n betweenroo t lengthdensit yan droo t num­ bersi nryegrass , but thishypothesi s and thelac k ofcorrelatio n inmaiz enee d further investigation.

Ryegrass Maize Maize- Ryegras s • X f : • • '. - y* *• * • • X X ? * • / • jir • X • Xm Î 3 f 2 .2 f m ~y^,' • ./ • i ' 0 1 2 ) 1 2 ) 1 2 3 number of roots (cm-2) number of roots (cm"2) number of roots (cm-2) Figure 2.Th erelationshi p between minirhizotron root numbers androo t lengthdensit yi n adjacent bulk soil in Italian ryegrass, maize, and themixtur e ofbot h species.Th eregressio n linesforce d through theorigi n are shown.

Conclusions Horizontally installed minirhizotrons did notreliabl yreflec t the verticalroo t distribution. Aswit h minirhizotrons installed at anangle ,ther e was anunderestimatio n ofrootin g densityi nth e topsoil using horizontal minirhizotrons. Overall,correlatio n between root length densityan d minirhizot­ ron root numbers was muchclose r inItalia nryegras scompare d with maize and the mixture of both species.

References Andren, O. et al., 1993.Swedis h Journal ofAgricultura l Research 23: 115- 126. Garibay, S.V. and Feil,B. , 1996.Thi sBoo k ofAbstracts . Majdi H. et al., 1992.Plan t and Soil 147: 127 - 134 Smit AL. et aL, 1994.Plan t and Soil 161: 289- 298 412 Book of Abstracts 4th ESA-congress

ECOLOGICAL BASIS FOR SUSTAINABLE PEST MANAGEMENT SYSTEM

N. Babich and I. Grichanov

All-RussianPlan t Protection Institute, Sh. Podbelskogo 3, St.-Petersburg-Pushkin 189620 Russia

Introduction Basisfo r sustainable pest management system isi n agroecology -th e appliedfield o f ecology, that study influence ofenvironmenta l factors (biotic and abiotic) on crop productivity, on structure and dynamics ofarabl e land associations and their feedback. Pest outbreaks are aregula r feature ofagricultura l ecosystems (Southwood and Way, 1970). Plant-herbivore interactions are an important component within agricultural ecosystem as herbivore animalsbecom e agricultural pests. Herbivores represent part ofth e consumer component ofth e ecosystem. Nevertheless, human-controlled agricultural ecosystems stilldevelo p under natural climate andweathe r conditions in accordance withbasi c ecological laws.

Overview 1. Influence ofth eweather . Onlycertai n weather conditions arefavorabl e for herbivore population growth, though it usually explains about 70%o fvariability , as inou r research on dynamics ofcommo n volepopulation s inNort h Caucasus region (Babich 1991). Climatic factors for all organisms work asregulator s ofthei r life cycles and activity rhythms. The phytosanitar y forecasts still can not bebase d onweathe r forecast, asit s accuracy isno t sufficient. Theweathe r forecast mistake willb emultiplie d inphytosanitar y forecast. So climatic factors areuse d not in the form ofweathe r forecast values, but asanalyse s ofup-to-dat e situation. This approach assumestha t vitality ofan y organism isforme d during its ontogeny, under impact ofth e environment, including climatic factors . 2. Plant-herbivore interactions. Interactions between grazing animals andthei r food plants are known to involve: (1)respons e offeedin g rate to the structure ofth e vegetation; (2) transfer of plant material to saprophages inth e form of faeces; (3) selective use of different plant speciesb y the grazers; (4) effects of canopy structure on photosynthesis rate; (5) differences between plant species inthei r response to grazing, (Newman E. 1993) (6) selection ofplant s specimens on earlier phenological phaseb ygrazer s (Bashenina, 1962;Abaturov , 1984 ;Babic h 1994). 3. Population cyclicity. Most ofphytophages ' populations in agricultural ecosystems show cyclicity, that means seasonal and annual fluctuations inpopulatio n density. Population dynamics of pest species isa resul t ofphenotypi c variability, caused incertai n periods ofa life cycle. This variability iscause d byclimati c factors and energy resource. Sometimes it isadaptive , but with the sameprobabilit y it willno t be adaptive for future season. That iswh y population dynamics depend on past conditions -whe n development occurs, and on future -wer e population willge t (Poliakov, et al. 1995).

Results offiel d experiments For acoupl e ofyear s common vole (Microtusarvalis Pall. ) -a rodent pest hasbee n studied. Its impact ismos t serious onwinte r wheat crops. It could be adopted that the most severe isthos e damage,tha t isregistere d on inhabited through the summer voles colonies, or noticeable spots of thinned out crops. Following calculation show how to make rough estimate of colony's density per 1 hectare ofcrops , briningt o economical significant winter wheat cropsloss . Accordingt o our preliminary data crops loss per one colony (L\k) -equals 70%i naverage . Square ofcolon y {S\k ) on phase of depression equals 10i 2 inaverage . Sow e cantr y to Session2. 1 413

estimate critical density ofcolonie s per 1 hectare(£) )tha t will lead to economically significant

crops loss (Ls) -le t it be 10% per hectare.

= SyrLA =12^i^i=i42.8 colonies/hectare, L\k 70% where D -critica l density of coloniespe r 1 hectare ',S\k~ average square of 1 colony;

Ls -economicall y significant crops loss (%);L\k - crops loss per one colony (%). When crops lossfrom on e colony isdetermine d we can estimate crops lossfrom th e field:

L\k-Dha f Sik where Lf- crops lossfrom th e field; L\k -crop s loss per one colony; Dha' density ofcolonie s per 1 hectare; S\k ' average square of 1 colony. Conclusions Ecological basis for sustainable pest management system isi nunderstandin g ofnatur e of phytophages' populations in agricultural ecosystems. Thevitalit y of organism isforme d during itsontogeny , under impact ofth e environment, including climatic factors .Pes t populations dynamics depend on past conditions -whe n development occurs, and on future -wer e population willget . In pest populations monitoring the climatic factors areuse d not inth e form ofweathe r forecast values, but asanalyse s ofup-to-dat e situation. Thepreliminar y results suggest that severity of common vole damage inwinte r wheat crops, should not be overestimated. Economically significant losseswil lbrin g pest attack, when rodent's population density exceed 100colonie s per 1 hectare. Themai n goal ofth e future study willb e improvement ofexistin g models ofdamag e of common vole, that should consider phase ofpopulatio n cycle, characteristics ofwhea t varieties inrespons e to grazing and preceding crops in crop rotations and impact of climaticfactors . We look forward to create a computerized version for the estimation of economical threshold ofdamage .

Thiswor k hasbee n supported by agran tfrom th e Department ofEnvironmenta l Sciencesan d Policy ofth e Central European University and the Higher Education Support Program.

References AbaturovB. D., 1984.Mlekopitajushi e kak element ekosistemy. M.Nauka , 280 s(i n Russian)/Mammal sa sth e element ofecosystem . M. Nauka, 280p BabichN .V. , 1991 Proc. ofConf . Agrometeorological resources and production processes, Kiev, (inRussian ) pp. 21-23 Babich N.V., 1994Proc . of 75th,Anniversar y American Mammology SocietyMeeting , Washington DC, pp. 14-15 BasheninaN. V., 1962Ekologiy a obyknovennoi poliovki, M. 310s . Newman E., 1993.Applie d Ecology, byBlackwel l Scientific Publications, 328p Poliakov I. Ya. ,Leviti n MM., Tansky V.l., 1995.Phytosanitarnay a diagnostika v integrirovannoi zashite rastenii. Moskva, "Kolos", 208 c. Southwood R. and Way 1970. Concepts of pest management, Rabb& Gurthri e (eds) N.C.St. Univ., Raleigh, pp. 110-120 414 Book of Abstracts 4th ESA-congress

USEO FAGRO-ECOLOGICA LINDICATOR SFO RTH EEVALUATIO N OFFARMIN G SYSTEMS

C.Bockstalle r ], P. Girardin 2

1 Association pour laRelanc e Agronomique en Alsace(ARAA) ,INRA , Laboratoire d'Agronomie, BP 507,6802 1Colma r Cedex,France . 2INRA ,Laboratoir e d'Agronomie, BP 507,6802 1 Colmar Cedex,France .

Introduction For thedevelopmen t of Integrated ArableFarmin g Sytems(LAFS )tool sar eneede d to evaluate the achievement of agronomic and environmental objectives, inorde r to optimizeth e system (Vereijken, 1992).Measurements , (e.g. nitrateconten t ingroun d water) are time consuming and costly, whereas models are often notadapte d for use atfar m level (Sharpley, 1995). Another solution ist ous e indicators,whic h help tointerpre t acomple x system (Girardin et al., 1996). Wepropos e a set of agro-ecological indicators (AEI)a s decision aid tools,t ohel pth e farmers to adapt their cultivation practices to IAFS requirements.

Methods The AEIvalue s range from 0t o 10.Th evalu e 7i sarbitraril y chosen torepresen t the achievement of "realistic"IAF S requirements. Avalu ebelo w 7indicate s thatthes e IAFS requirements areno t achieved and avalu eabov e 7indicate s thatth e fanner doesbette rtha n the "realistic" IAFS requirements. TheAE Iar e calculated with thedat a available on the farm (cultivation pratices recorded by the farmer, soil analyses, steady data such as field size, slope ...). Most ofthe m are calculated atth efield leve l andthe n weighted by thefield siz et o obtain a mean value atth efar m level. The calculation ofmos t ofthe m isbase d onth e comparison ofth e farmer's cultivation practices with IAFS recommendations. An example isgive n inBockstalle r et al. (1996). Several ofth eIA Eca n also beuse d toestimat e the impact ofth efarmin g system on the environment. We assumethat , in general,th eles s IAFS requirements aremet ,th egreate rth e negative impact onth e environment willbe .

Results Sofar , sixindicator s havebee n elaborated for the evaluation of: cropdiversity, cropsuccession, nitrogen,phosphorus, organic matter an d irrigation management. Indicators for: pesticide, energy, ecologicalstructures arebein gtested . The elaborated indicators were calculated in 1994an d 1995wit h datafro m anetwor k of 17 commercial arablefarms . Figure 1 showsa presentatio n which gives an overview ofth eresult sa t thefar m level, showingth ewea k and strong points of arablefarmin g systems asassesse d by IAFS requirements. For each indicator, resultsa tth efield leve l are available tohel pth e farmers take into account the differences between thefields. Thi s kind ofindicato r canb euse db y decision makerst ofollo w upth eevolutio n of cultural practices andth e influence of aagri - environmental policy as shown inFigur e 2fo r thenitrogen management indicator . The reliability of the AEI isteste d by means of aprobabilit y test (Girardin et al., 1996):th e relationship between anEA I and anenvironmenta l parameter is expected tob ei nth e form ofa probability area, delimited by aboundar y line. Thus,th eEA Ireflec t apotentia l environmental impact of the farming system. This is shown by Figure 3i n the case of thenitrogen management indicator. Girardin et al. (1996) emphasize that iti s alsonecessar y to validate theindicato rb y assessing the reaction ofth e potential users. The reactions ofth e farmers of thenetwor k were positive: 67%foun d them easy to understand. Session 2.1 415

Cropdiversit y IC Farmvalu ei n 1994 OMmanagemen t Cropsuccessio n -Farm valuei n 1995 Recommended value

Pmanagemen t Nmanagemen t

Figure 1.Exampl e ofus eo fth eagro-ecologica l indicators atth efar m level (90 ha:grai n maize, sugarbeet ,winte r rape,winte rwhea t) .

T3

7 8 9 10 11 12 13 14 15 16 17 Farmnumbe r Figure 2.Valu e ofth enitrogen management indicator in 1994an d 1995fo r the 17farm s ofth e network (1t o 13:France ; 14t o 17:Germany) .

Boundary line Probability area ASuga r beet DWinte r wheat OWinte r rape • Grain maize XSoybean

20 30 40 50 60 70 90 Nmin before winter (kg.ha1)

Figure 3.Probabilit y test of thenitrogen management indicator: relation of theindicato r toth e mineral nitrogen content in soil before winter (— : boundary line of theprobabilit y area(below)) .

Conclusion and perspectives Theagro-ecologica l indicators presented in this paper arefirst o f all aimed athelpin g farmers to adapt their cultivation practices to the IAFS requirements. For other production systems with livestock or vine, our indicators should be probably adapted and specific indicators developed.

References Bockstaller,C . etal. , 1996.A n example ofa n agro-ecological indicator: theorgani c matter management indicator. Book of Abstacts ofth efourt h ESA Congress, 7-11Jul y 1996, Veldhoven, TheNetherlands . Girardin, P. et al., 1996. Submitted for publication to Agriculture Ecosystems & Environment. Sharpley, A., 1995.Journa l ofEnvironmenta l Quality24:947-951 . Vereijken, P., 1992.Netherland s Journal ofAgricultur e Science40:209-223 . 416 Book of Abstracts 4th ESA-congress

THE IMPLEMENTATION OF A SPATIAL LAND ALLOCATION DECISION SUPPORT SYSTEM FOR UPLAND FARMS IN SCOTLAND

CS.Butcher1, K.B.Matthews2, A.R.Sibbald2

1 Overseas Development Administration, c/o FCO(Yaounde) , King Charles Street, London. 2 Land Use Division, Macaulay Land Use Research Institute, Aberdeen, AB9 2QJ, UK.

Introduction Upland farming systems form the interface between lowland farming areas, where agricultural land use decisions are dominated by economics, and hill areas where land use options are highly constrained by bio-physical limitations and nature conservation pressures. The importance of these upland areas is further emphasised by the increasing shift of UK and EU policy goals away from maximising agricultural production towards integrated economic, social and environmental goals. This policy shift provides incentives to alter patterns of land use in the uplands and places great importance on the study of land use options for upland farming systems to allow conflicting goals to be reconciled.

The computer based spatial land allocation decision support system (LADSS) being developed at MLURI has two roles. First it provides decision support for land managers by testing land allocation scenarios and suggesting possible combinations of land uses to meet their goals. Second it permits the analysis of farm scale land manager responses to policy change at UK and EU level. In both cases the land manager is the focus of the system.

LADSS specification and methods LADSS is implemented as a series of knowledge bases within Gensym's G2 real-time application development environment. LADSS thus has a modular structure, with data management, land use, impact assessment, and user interface modules. This structure facilitates the growth of LADSS capabilities by the addition of further land uses and impact assessments, or the substitution of existing modules by those developed within ongoing research. It also enables the customisation of the users' view and interaction with LADSS.

A LADSS spatial bio-physical database was collected for a MLURI Research Station in central Scotland. The database includes topographic, climatic and soil variables. The climatic parameters are derived from climate maps (Matthews et al., 1994). The topographic and soil data were field surveyed on a 100m sampling grid. The sample point is assumed to characterise the surrounding 1 ha area and leads to the grid based spatial representation currently used. In addition to these data further data were collected based on the perceptions of the manager of the Research Station. The fiscal data, market prices, grant rates and management costs required for the model were derived from standard UK sources (Hart, 1991; SAC, 1995).

The land use modules estimate for each land block the suitability, productivity and financial returns for each of ten land uses based on the bio-physical resources, management and grant regimes. These land uses are spring-barley (Dyson, 1992; Eagle et al., 1976; Sparrow et al., 1979), upland-sheep (Maxwell et al., 1993), suckler-cattle (Wright et al., 1996), two conifer and five broad-leaved tree species (Allison et al., 1994; Edwards et al., 1981; Pryor, S.N. 1988). In all cases the estimation of site suitability uses fuzzy membership functions (Burrough, 1989) to estimate the degree of suitability for the range of site factors. The functions are derived either from individual models or taken from the Session 2.1 417

MLURI LCA guidelines (Bibby et al., 1982). Existing data available for any location in the uplands or data easily derived from field survey have guided the choice of models used within LADSS. Fiscal returns are estimated on a revenue basis optionally including those grants available.

Allocations of land uses to individual land blocks may be made by the user directly and their parameters accessed. Otherwise the user may choose from the palette of available land uses and allocate user-defined percentages of the farm to land uses based on a hierarchy of priorities. The allocations made by the user or the rules are currently evaluated in financial terms. Net present value is used to integrate the expected returns from annual enterprises with those from forestry. The interest rate and the period over which the NPV is calculated are defined by the user.

Individual land use modules within LADSS have been verified as part of their development. Within LADSS each is further sensitivity tested to establish both the absolute sensitivity and relative importance of each input parameter. This analysis begins to allow the estimation of uncertainty associated with predictions made by the land use modules and prioritises data collection requirements for the operational use of LADSS.

Results LADSS has been used to demonstrate the potential role of the grant system in locking-in land use systems on a Scottish upland farm. A comparison of allocations made on the basis of a farmer perceived resource description and the objective surveyed using identical rules has also been made.

Future developments Ongoing developments include: rapid site characterisation methodologies based on remote sensing, ground survey and geostatistics; the use of a linked geographical information system to provide a full range of spatial data representations and analysis; an extended range of land uses; social and environmental impact assessments; and the implementation of explicitly goal driven land use allocation strategies.

References Allison, S.M. et al., 1994. Canadian Journal of Forest Research. 24:2166-2171. Bibby, J.S. et al., 1982. Land Capability Classification for Agriculture. MLURI, 75 p. Burrough, P.A., 1989. Journal of Soil Science 40:477-492. Dyson, P.E., 1992. Personal communication. SCRI. Eagle, D.J., et al., 1976. Using response curves to estimate the effect on crop yield and profitability. MAFF Technical Bulletin on Agriculture and Water Quality, 355-370. Edwards, P.N., et al., 1981. Yield models for forest management. FC Booklet 48, 32 p. Hart, C, 1991. Practical Forestry, 3rd ed. Alan Sutton Publishing Ltd. Matthews, K.B., et al., 1994. Climatic Change 28:273-287. Maxwell, T.J. et al., 1993. Grass and Forage Science. 49:73-88. Pryor, S.N. 1988. The silviculture and yield of wild cherry. FC Bulletin 75, 23 p. SAC, 1995. Farm management handbook. SAC, Edinburgh. Sparrow, P.E., et al., 1979. Journal of Agricultural Science 92:307-317. Wright, I.A., et al., Submitted 1996. The effect of grazed sward height and stocking rate on animal performance and output from beef cow systems. Grass and Forage Science. 418 Booko fAbstract s4t hESA-congres s

A MODEL OF ON-FARM AGRONOMIC MONITORING APPLIED IN ORGANIC FARMING

C David, B Fabre

ISARA, 31 place Bellecour, 69288Lyo n cedex 02,Franc e

Introduction The market for organicproduc e appears to be expanding but it ist o some extent limited by supplies. Although organicfarmin g isprofitable , the conversionfrom a non-organi c farming systemi sa period oftechnical , social andfinancial stress . AE U programme «Conversio n to organic stockless systems. On-farm research in SouthEas t France »wa s designed to appraise and resolve technical problemsdurin gconversio n to organic farming This paper presents an experimental model based on on-farm monitoring and mainly develops the methodological approach

Methods This experimental model isbase d on different hypotheses: 1.Th e agricultural production depends onnumerou s factors asenvironment , fanning and cropping system. Thegeneralizatio n of ane wtechniqu e should be adapted to this complexity. 2. The improvement oftechnique s isrelevan t only ifthe y are adopted byth efarmer s and adjusted to their situation (Lefort, 1988). Consequently, it isnecessar y to take into account the farmers' opinion aswel l asth e researchers' andth e advisers'. This iswh y an on-farm experiment approach hasbee n implemented. Thisexperimenta l design disseminated invariou s spots, sincevariou s circumstances will provide adapted models (Sebillotte, 1989). It isimportan t to combinethi styp e ofon-far m experiment with station experiments which allowsth eunderstandin g ofth ebiologica l processes (Debaeke et al, 1996). 3. The on-farm monitoring requiresa pluriannua l schemet o consider the climaticvariatio n and the time needed to adapt a newtechnique . The appraisal ofth e problems duringth e conversion requires a minimum ofthre eyear st o obtain a set of references.

We mixed sociological, economical andtechnica l approachest o assessth efeasibilt y of atechnica l improvement byusin g ametho d similar to thefarmin g system research and development (Billaze t al, 1983). The on-farm experiment isrepresente d (scheme 1)b yth e model developed byTriomph e (1988). Three networks are interrelated: 1.A far m network whereth efarmin g systems' changes are studied. 2. Afield networ k included inth e farm network where the main agronomic problems are considered. Two levelswer e distinguished, the cropping system andth ewhea t crop. 3. On selectedfields, trial swer e set upt o test relevant practices on winter wheat, concerning nitrogen nutrition and weed control. In a « social survey »,w e analyse the attitude of farmers towards conversion. Thetechnica l and economical monitoring providesinformatio n onbarrier s during conversion on farm level. Moroever, a study ofth eorgani c cereal market was carried on aregiona l levelt o appraise the potential of expanding. Session 2.1 419

Scheme 1 : Organic farming diagnosis in Drome Type ofproblem s

Adoption of Organic cereal Agronomical techniques market

Network 1 Network2 Farm diagnosis Field monitoring on Inquirieso n Farm and / cooperatives Technical and "Social Cropping Winter economical survey" monitoring systems wheat Network_3_ Experiment onweed s and __ niJrog_en_

Proposal for the improvement Proposal of techniques anddecisio n ofth econversio n support tools Actions onorgani c farming development

Conclusion From the results provided by the different networks, it can be concluded that this on-farm model is relevant. Several techniques tested in our network were spread to other farms. For instance, a new model for nitrogen management is now being used (Promayon and David, 1996). The number of conversions to organic farming has increased in this region since the programme started. Some of the references are already being used by advisers to facilitate the development of the organic farming.

References Billaz, M et al., 1983. Les cahiers de la Recherche-Développement, 1: 12-16 Debaeke, P et al,. 1996. DERF-APCA Comité potentialités, 87-98 Lefort, J.,. 1988. Les cahiers de la Recherche-Développement, 17: 1-10 Promayon, F. and David, C, 1996. 4th congress European Society of Agronomy Sebillotte, M, 1989. Approaches of the on-farm agronomist. Kasetsart University, Thailand. Triomphe, B , 1988. Les cahiers de la Recherche-Développement, 17: 11-20 420 Book of Abstracts 4th ESA-congress

ARABLE FARMING SYSTEM RESEARCH-PROJECT LOGÂRDEN CA. Heiander Agricultural Society, P.O.Bo x 124,S-53 22 2 Skara, Sweden

Introduction A large scale farming system research project started 1991a tth e research farm Logârden, Grästorp, (58°N , 12°0) Sweden. The main emphasis iso n development of anEcologica l Arable Farming System (EAFS) and of anIntegrate d Arable Farming System (IAFS).Th e total area for the experiment includes 60h ao farabl e land,th e sizeo feac h field isbetwee n 2.5 and 4.0 ha, see map ofth e farm below. Methods The farming system project at Logârden follows the methodology forfarmin g systems Experimental farm Logârden( S- l) research elaborated by aEuropea n research EAFS (22.0ha) network ina E U Concerted action (Nilsson, D 1994;Vereijken, 1994; 1995). D IAFS (28.0ha) The aimo f theproject , the main objective,i s CAFS (12.0ha) a sustainable andproductiv e food supply in I-VinCroprotatio n blocks combination with aminimu m of negative a-b Rotations with inpact onth e abiotic environment. The 75-50% cerials M Ecological management ofth eheav y clay soil (40-50% infrastructure clay) iscentral , aiming at optimum structure and biological activity inth etopsoil . A further aim isminimu m input of external energy by maximum use offarm-produce d bio-energy (fuel from rapeseed) and self-sufficiency in feed-stuffs (mixed farm). The methods usedfollo w the european shortlist (Vereijken, 1994).The y are used in the following order: 1.Multifunctiona l CropRotatio n (MCR) 2. Integrated/Ecological Nutrient Management (INM/ENM) 3.Minimu m Soil Cultivation (MSC), only IAFS 4.Ecologica l Infrastructure Management (EIM) 5.Inte ­ grated Crop Protection (ICP), only IAFS Figure 1. Map of Logârden showing the design 6.Far m Structure Optimisation (FSO). ofth e farming system research project. Table 1.Th e Multifunctional Crop Rotation atLogârde n Year Conventional Ecological Integrateda ) Integrated bt 1 peas peas peas peas 2 w-wheat w-wheat w-wheat w-wheat 3 oats set-aside oats (undersown) set-aside (grass/lucerne) 4 w-wheat rye w-wheat set-aside (grass/lucerne) 5 s-rape fieldbeans s-rape w-rape 6 w-wheat oats w-wheat w-wheat 7 oats set-aside oats (undersown) oats (undersown) 8 w-wheat w-rape triticale triticale Session2. 1 421

Thethre edifferen t parts ofth efarm , Conventionel (CAFS),Ecologica l (EAFS) and Integrated (IAFS)hav e different croprotatio n (see Table 1)usin g the Multifunctional Crop Rotation (MCR) Concept (Vereijken, 1994).Tabl e 2give sth epercentag e ofecologica l infrastructure inth e different systems. Table 2.Percentag e ecological infrastructure Conventional Ecological Integrated a) Integrated b) 0% 6% 6_% 6_% The evaluation ofth e systems isplanne d to use 11(EAFS ) or 12(IAFS ) ofth e multi-objective parameters onth e European list (Vereijken, 1994). Sofa r 8o fthes e actually have been used in the yearly evaluations.

Results Many ofth eresult s from the lastyea r are still under evaluation. Themos t interesting resultswil l bepresente d atth e conference. As an example the results from the analyses ofavailabl e Nmj„ at the start ofth e leaching period (nov.-dec.) inth e reference areas are given in Table3 . Table 3.Nitroge n Available Reserves (NAR) ink gha " ,afte r the indicated crop,a t start ofth e leaching period Year Conventional Ecological Integrated

NminSoil Crop NminSoil Crop NminSoil Crop 1992 39,8 w-wheat 75,9 green manure 55,9 s-rape 1993 57,9 s-rape 50,8 rye 31,3 w-wheat 1994 63,7 oats 42,3 fieldbean s 43,3 oats 1995 34,7 w-wheat 41,2 w-wheat 36,9 triticale

Conclusions Inth e Ecological Arable Farming System (EAFS)ther e has been alowe r yield level than expected. This isprobabl y caused by a lack of nitrogen during especially the early part ofth e growing season. The low level of available nitrogen is, atleas t partly, connected with aver y compact soil and thereby alo wmicrobia l activity. The compact soil can also cause losseso f nitrogen by denitrification under very wetcondition s (asdurin g June-95) . Weeds, insects and diseases have been asmalle r problem than expected, the use of mechanical weed control has been quite successful. The use ofexterna l inputs (pesticides and chemical fertilisers) inth e conventional farming in Sweden is very low compared to many western European countries. This means that there isno t much room for reduction offo r instanceth e pesticide use.A t Logârden hardly anyfungicide s or insecticides have been used inth e conventional part. The most obvious reduction hasbee n inth e useo fnitroge n fertilisers and inth eus eo f fuel for soil preparation. It is also very important torealis e that some of thepositiv e effects that are expected from a change of the farming system, into an ecological or into an integrated, are still to come.

References Nilsson, C, 1994.Integrate d farming systems research atAlnarp .Proceeding sNJ F symposium 'Integrated systems in agriculture', 1-3 December 1993Norway : 65-70. Vereijken, P., 1994. 1.Designin g Prototypes,Progres s Reports of Research Network on Integrated and Ecological Arable Fanning Systems for EU and associated countries.AB - DLO, Wageningen, 87p . Vereijken, P., 1995.2 .Designin g and Testing Prototypes, Progress Reports of Research Network on Integrated and Ecological Arable Farming Systems for EU and associated countries. AB-DLO, Wageningen, 90p . 422 Book of Abstracts 4th ESA-congress

TOWARDS SUSTAINABLE LAND USE IN THE RURAL AREAS:TH E NEED FOR DESIGNING NEW SYSTEMS AND TECHNOLOGY

H. Hengsdijkl and M.K. van Ittersum^»3

1 Research Institute for Agrobiology and Soil Fertility, P.O.Bo x 14,670 0 AA Wageningen, The Netherlands 2Departmen t of Theoretical Production Ecology, Wageningen Agricultural University, P.O.Bo x 430, 6700 AK Wageningen, The Netherlands 3 CT. deWi t Graduate School for Production Ecology, Wageningen, TheNetherland s

Introduction Environmental problems,a growing population density and an increasing demand for non- agricultural functions (recreation, nature, drinking water supply, etc.) inth e rural areas call for drastic changes in land use inth eNetherlands .Aim s of such 'sustainable' type of land use area n improved quality ofbot h agricultural products andproductio n methods and scope for non- agricultural functions. This processca n be moulded and steered by acombinatio n of rearranging land use and other resources at regional and farm level (socalle d systems designs) and new technologies to solve problems atfield, cro p or animal level. Inth e present study such systems designs and technologies atthre e levels of scale, -region , farm and field -ar e identified to realise particular land use aims.Th e study has been carried out for the intergovernmental research programme 'Sustainable Technological Development'.

Multifuntional land use and environmental pollution: conflicting aims The multifunctional character of land use and the different types of environmental problems (e.g. emission ofbiocide s and nutrients) require priority setting of goals. Moreover, expression of environmental pollution in different dimensions results inconflictin g information as illustrated in Figure 1i n whichth eN-suppl y inrelatio n to theN-outpu t andN-surplu s for different arable farming systems isanalysed . TheN-surplu s isdefine d asth e difference betweenN-suppl y and theremova l of nitrogen from the system (N-output) and equalsN-emission s andN-accumulatio n inth e system. Below acertai n critical N-supply theproductio n (interm s ofN-outpu t per ha) decreases strongly. Simultaneously, theN-surplu s expressed perhectar e still decreaseswhil eth e N-surplus expressed per kg ofN-outpu t increases. 250 Figure 1. N-output (—•—) , 'C02 N-surplus per ha (•••D...) and 200 P . 1 N-surplus perN-outpu t (--o—) i n a. 150 0.75 3 relation toN-suppl y for different in farming systems. EC=ecological z 100 . 0.5 3 farming system, IN=integrated Q. *J 3 farming system and COI, C02 = 50 0.25 O conventional farming systems.

150 200 250 300 350 400 N-supply(k gN/ha/yr )

This example shows that expression of environmental pollution intw o different dimensions,pe r unit of area or product, results inparadoxes . Optimalisation of land use for one aim, e.g. reducing the emission peruni t of area,ma y have implications for other aims,e.g . reducingth e emission Session2. 1 423 per unit ofproduct . In the search for new systems andtechnologie s it isimportan t to explicitize their consequences for various aims related to amultifunctiona l and environmental friendly land use.Fo r operationalization of sustainability adistinctio n between levels of scale isrequire d so that repercussions of intervention at one level of scale for other levels of scale canb e disentangled. The use oforgani c waste products from cities or farms as fertilizer cane.g . reduce nutrient surpluses at farm and regional level,bu t atth e field level emissions might increase because organic fertilizers are less efficient than chemical alternatives.

Systems designs and technologies Ina rapi d appraisal systems designs andtechnologie s atregional , farm and field level are identified that cancontribut et oth e realization ofdifferen t land useaims . Seven prospective systems designs andtechnologie s are identified that can potentially contribute to lower environmental pollution levels and realisation of non-agricultural functions inth erura l areas: Region: 1.Recirculation and reuse of manure and organic waste a sanima l feed or fertilizer can reduceregiona l nutrient surpluses. Farm: 2.Th e use of renewable energysources and energy management canreduc e the dependency of agriculture on fossil energy sources. 3. Expert-and management supporting systems ca n gaininsigh t inth e effect of operations on growth and development ofcro p and animal,natura l resource use,an d attainment ofnon-agricultura l functions (e.g.nature) . Field: 4.Sensor-and information technologyfo r location specific management to reduce fertilizer and bioicide use. 5. Upgrading oforganic fertilizers to ensure areliabl e working of nutrients and to harmonise the mix ofnutrient s with the crop requirements. Region/farm/field: 6.Monitoring systems t o measure and evaluate the environmental pollution of functions ofrura l areas at varioustempora l and spatial levels of scale. 7.Planningstechnology inwhic h different information flows are integrated to support thedecision-makin g processes concerning rural landuse . Current limited application ofthes e systems designs and technologies must be attributed to (i) the fact that cultural and economic boundary conditions are not fulfilled, (ii)uncertaintie s about the implications ofthei r application, and (iii) the lack of operational techniques atfield level . Therefore, the following research agenda is proposed.

Research agenda The consequences ofth e identified systems andtechnologie s should be explicitized ina n integrated framework sotha t interactions of varioustype s ofpollutio n and functions at different scales can be analysed. Aframewor k ispropose d in which step by step consequences and uncertainties ofth e identified systems designs andtechnologie s canb e assessed on basis ofth e land use aimspursued . Two case study areas differing in biophysical and socio-economic characteristics are used asa benchmark . The framework includes (i) aquantitativ e exploration of new systems andtechnologie s atvariou s levels of scale, (ii) communication ofresult so f step(i ) with stakeholders, (iii) development of systemsan d technologies with stakeholders, (iv) introduction and implementation of systems and technologies and (v)monitorin g and evaluation systems and technologies.

References Duurzaam landgebruik, definitiestudie, 1996.AB-DLO , PE-LUW, MiBi-RUL & Heidemij Advies B.V., DTO-werkdocument VDO(i nprep.) . 424 Book of Abstracts 4th ESA-congress

RE-INTEGRATING PERENNIALS INTO AGRICULTURAL LANDSCAPES A CONCEPTUAL APPROACH

F. Herzog', M. J. C. Brownlow2

'UFZ Centre for Environmental Research, PF 2, D-04301 Leipzig "Institut für Agrarökonomik, Universität für Bodenkultur, A-l 190Vienn a

Introduction Themechanisatio n and intensification of agriculture inEurop e have lead toa massiv e removal of trees and shrubs from agricultural landscapes.Thi sha s negative (agro-)ecological, aesthetic and cultural effects: losso fbiodiversit y and decrease of system stability, diminished attractiveness for recreation, destruction of landscapes which were part ofou r cultural heritage. Atpresent , there isconsiderabl e economic and environmental pressure to explore alternative non­ food uses for agricultural land.I n re-integrating perennials into landscapes,far m production can bediversifie d while positive environmental effects canb e obtained. Bydeliberatel y combining an­ nual andperennia l crops in agroforestry. modern sustainable land use systems can be developed.

Properties of agroforestry systems for industrialised countries Whereas tropical agroforestry aims at a sustainable intensification of production,agroforestr y in industrialised countries must be designed togenerat e environmental benefits, reduce the socio­ economic burdensassociate d with agriculture and maintain the income ofth e farmer. Land use systems must bejudge d according tothei r ecological, economic and socio-cultural properties (Lefroy et al, 1993).I n the figure, these properties are given for agroforestry when compared to monocropping -agronomi c properties areals o included.

Ecologicalproperties Economicproperties higher stability through • diversification diversity • lower „private efficiency" habitat for wildlife • higher„socia l efficiency" C02-fixation • widespread viability only when local cycling ofwate r and ecological benefits are financially nutrients rewarded /ecologica l losses are more ecological benefits penalised Agroforestry compared to monocropping AgronomicProperties Socio-culturalproperties interactions between trees high aesthetic valueo f and cropsca n be manipulated trees in landscapes lessflexibl e rotation cultural value oftree s some knowledge on trees is public acceptance, good required „image"o ftree s •mor e sophisticated / •n omor e „throw away" demanding management landscapes

Properties of agroforestry systems in industrialised countries Session2. 1 425

This simplified list is based onth e fundamental properties of complex systems compared to monostructural ones.However , the specific properties of any one agroforestry system depend on the design ofth e system, since the term agroforestry covers awid e range ofpossibilities . These ­ lection ofth e agricultural and tree components, andthei r combination in space and time arepar ­ ticularly crucial. Thene t environmental, social and economic characteristics ofthes e systemsar e then dependent onth e subsequent interactions between the system components. Under the current policy inth eEU ,agroforestr y tendst o offer environmental and socialbenefits , but usually (although notalways ) atth e expense of financial viability. These characteristics must not only be compared to existing monocultures, but also to other alternative land uses (both proposed and practised), such as fallows, non-food agricultural crops,afforestation , etc.,i norde r to properly understand the relative worth of agroforestry in solving the problems of agriculture.

Candidate systems for Western Europe Agroforestry waswidesprea d in Europe until the 19th century (e.g. Beil, 1839).Mos t ofth e sys­ tems were abandoned asa resul t of changing economic conditions and agronomic progress (e.g. fertilisation, mechanisation) (Brownlow, 1992).Remainin g systems aremostl y restricted to mountain regions and toth eMediterranean , some existi n westernEurop e aswell .The y form some of themos t precious landscapes in Europe and their preservation is apriority . Modern sys­ tems, however, have to address prevailing land use problems andtak e intoaccoun t modernprac ­ tices andconditions .Thi spracticall y excludes fruit production withhig h growingtrees ,th etre e component must rather be oriented towards wood production. The most promising systemsare : • silvopastoralism (trees and livestock):Trials ,predominatel y inth e UKan d France,ar e being carried out using hardwoods (e.g.Prunus avium, Pyrus communis, Gleditsia triacanthos,etc. ) onpastur e at densities between 50 and 400 trees/ha (e.g. Dupraz et al., 1994). • silvoarable systems (trees and crops):Alle y cropping with hardwood trees isals o tested inth e UK and France. An EU demonstration project „Farming with Poplars" seeks to spread this technology to other European countries. Silvoarable systems might beparticularl y valuable in reintroducing trees into areas dominated by arable farms such asth e cereal producing regions inFranc e andth e large arableco-operative s ineaster n Germany.

Conclusions Agroforestry systemsar ea potentia l means for re-integrating trees intoagricultura l landscapes. This could bring considerable environmental and social benefits incompariso n withmonocrop - ping, butth e financial viability of such systems iscurrentl y poor. Their adoption therefore de­ pends onfutur e comparisons ofproductio n systemsbein g based on„socia l efficiency" (Barbier, 1990),wher e external costs and benefits are internalised and environmental products/services are rewarded financially.

References Barbier E.B .(1990 ) in Prinsley R. T. (ed.) Agroforestry for sustainable production. Common­ wealth Science Council, London, 389 -404 . BeilA .(1839 )Aphorisme n überdi e Verbindung des Feldbaues mitde m Waldbaue oder Röder und Baumfeldwirtschaft. Frankfurt a.M., Andreaische Buchdruckereien, 89p . Brownlow M.J . C. (1992) Quarterly Journal of Forestry 86(3), 181- 190. Lefroy E.C . et al.(1992 ) in Hobbs R.J e t al.(eds. ) Reintegrating fragmented landscapes.Ne w York, Springer Verlag, 209 -244 . 426 Book of Abstracts 4th ESA-congress

FARMER SPECIFIC PROTOTYPING OF SUSTAINABLE PRODUCTION SYSTEMS: A CONCEPTUAL FRAMEWORK

T.J. de Koeijer1, G.A.A. Wossink2

'Department of Ecological Agriculture, WAU, Haarweg 333, 6709 RZ Wageningen, The Netherlands department of Farm Management, WAU, The Netherlands

Introduction In the near future Dutch agriculture must realise a strong reduction in the use of environ­ mentally damaging inputs in order to become more sustainable. Although the term "sustaina­ ble" has become popular, defining the term precisely and unambiguously is far from easy. Definitions abound, varying within context (Pandey et al., 1995). Hardaker (1995) gives five categories of sustainability in farming systems: technical performance; economic perform­ ance; quality of the natural environment; system resilience and adaptability; and human welfare and equity. One of the key elements for an optimal technical and economic perform­ ance and for curbing environmental stress, is an efficient production practice in order to reduce the amount of environmentally harmful inputs. For designing these efficient, sustainable production systems technical, economic and sociological insights must be combined. This paper presents a conceptual framework for addressing this issue.

Efficiency For a fruitful cooperation between different disciplines, knowledge of each others concepts of sustainability and efficiency is needed. In economy as well as in production ecology, an "increase in efficiency" means that a certain objective can be reached with less or cheaper inputs. Efficiency is a relative criterion and is expressed by the ratio between a desired or attainable productivity and the actually realized productivity. Productivity, indicates the amount of output which is produced with a certain amount of input. Efficient use of inputs can be looked at from different points of view: agronomically, ecologically and economically. Efficiency in the agronomicalpoin t of view can best be indicated as resource-use-efficiency,a term derived from De Wit (1992). It is measured in kg input per kg output. The ecologicalefficienc y of crop production is based on the use of renewable resources. Here, the self regulating capacity of natural systems is the central issue (Goewie et al., 1995; Lampkin et al., 1994). In this concept of efficiency the environmental burden is the main point. Because the environmental burden depends on all kinds of eco- physiological processes, the ecological efficiency is difficult to measure. According to Goewie et al. (1995) ecological efficiency should be expressed in kg input per unit of area. These authors state that low concentrations of artificial inputs per hectare refers to better chances for restoration of natural resources such as good soil fertility, soil structure and biodiversity (predators versus harmful organisms). However, in all agricultural production systems it is important to realize maximum profit. Maximum profit is realized when marginal costs equal marginal return. Hence, for economicefficiency th e price ratios of in- and outputs are decisive.

Conceptual framework The design of sustainable cropping systems which meet farm economical, agricultural and environmental objectives, requires insight into (a) the relations between cropping measures, environmental burden and the farmer's income and (b) the combination of economic, production ecological and sociological approaches. Session 2.1 427

The identification of new input-output combinations, which may contribute to a more sustainable agriculture, calls for the application of production ecological knowledge and insights which is derived from a combination of experiments and system analysis (Rabbinge et al., 1994). Therefore the first step in the design process is to assess input output combina­ tions for a given production situation based on production ecological insights. In the second step, these "potential" production sets are combined with farm economic considerations. These considerations include (a) profit maximization as the main objective, i.e. price ratio of outputs and inputs and marginal returns are decisive instead of average physical output input ratios, b) farm structural restrictions regarding labour and machinery, and c) uncertainty due to the variability of the natural environment. It is obvious that variability in agro-ecosystems plays an important role in practice and on farm level compared to controlled experiments and experimental plots. Sources of variation a farmer has to deal with in practice are found in the biotic and abiotic environment and in genetic resources (Almekinders et al., 1995). The result of the second step is a normative set of production techniques appropriate for a given production situation. Thus far the approach is normative: farmers are considered as a group of similar decision makers. The third step focuses more precisely on differences among farmers. Starting from insights from sociology and behaviourial economics the technology set as observed in practice is analyzed. In the normative approach it is assumed that (a) all farmers strive for profit maximization and (b) that all farmers have complete knowledge of prices and technical possibilities. In practice this is not the case, while in practice risk aversion or spare time also play a role and while farmers' knowledge will never be perfect. The three steps will result in differing levels of production. The highest level is the "labora­ tory" set resulting from the production ecological approach. The "blueprint" set from the normative economic approach is the next lower level. Finally, from the third step the "best practice" set of production techniques and the "average"se t can respectively be assessed. By measuring the differences between the levels followed by an explanation of these gaps, insight can be gained in what will be possible in practice and what the reasons are for not realising the potential level. With this knowledge of the four mentioned productivity levels and the explanation for the differences between them, optimal and in practice attainable production systems can be designed.

References Almekinders, C.J.M. et al., 1995. Netherlands Journal of Agricultural Science 43: 127-142. Goewie, E.A. et al., 1995. Hoe ecologisch kan de landbouw worden? AB-DLO Thema's 3, Wageningen. Hardaker, J.B., 1995. Farming systems perspectives on policy making and planning for sustainable agriculture and rural development, Rome: FAO (manuscript) Lampkin, N. et al., 1994. The economics of organic farming, an international perspective, CAB International, Oxon, UK. Pandey, S. et al., 1995. Agricultural Systems 47: 439-450. Rabbinge, R. et al., 1994. In: Rajan, A. and Y. Ibrahim (eds) Proceedings Fourth Int. Conference on Plant Protection in the Tropics, Malaysian Plant Protection Society, pp. 25-46. Wit, CT. de, 1992. Agricultural Systems, 40: 125-151. 428 Book of Abstracts 4th ESA-congress

THE RENAISSANCE OF MIXED FARMING SYSTEMS: A WAY TOWARDS SUSTAINABLE AGRICULTURE

E.A.Lanting a and R. Rabbinge Department of TheoreticalProductio n Ecology, Agricultural University, PO Box 430,670 0 AKWageningen , The Netherlands

Introduction During the last decades agricultural production systemshav edevelope d in North-western Europetha t waste inputs and are suboptimal inbiotechnica l andenvironmenta l terms.I nth e nearfutur e thiswil llea dt ounacceptabl e environmental andecological ,bu t alsoeconomica l and social effects (Rabbinge, 1992).Therefore , there isa nee d todevelo p and test alternative systems,whic h areacceptabl e in thelon g term.On eo f thepossibilitie s toreduc e thenegativ e effects of theincrease d specialisation andintensification , characterized by toonarro w crop rotations and anoverus e ofexterna l inputs likefertilizer s and biocides,i sa renaissanc eo f mixed farming systems atfar m orregiona l levels inwhic h products and services areexchange d between thedifferen t production branches.Th emai n advantages of mixed farming systemsare : - reduction of useo f external inputs and increase theirefficienc y through (i)us eo f home­ grown concentrates (lesspurchase d concentrates), (ii)mor eefficien t application of animal manure (lesswast eo f nitrogen and minerals), and (iii) broadening the croprotatio n (lessus e of biocides and higher yieldsdu e toles sproblem s with soil-borne pests and diseases); - betterutilizatio n of theavailabl elabou r and spreading of incomerisks .

Methods Onth eMinderhoudhoeve , theexperimenta l farm ofWageninge n Agricultural Universityi n Oostelijk Flevoland, twodifferen t prototypes of mixed farming systems are developed, optimized and tested: anintegrate d farm (135ha ;9 0dair y cows,6 0youn g cattle,6 0sheep ) and anecologica l farm (90ha ; 55dair y cows,6 0youn g cattle and bulls,4 0 sheep,20 0laying - hens).Bot h farms havethei r own sets of goals andconstraints .Th e production targetpe r haa t theecologica l farm is 80%o f that on theintegrate d farm asa naverag efo r milk,potatoe san d cereals.Th elocatio n ischaracterize d by agoo d loam soil with ahig h nutrient use efficiency andlo w irrigation needs.Measurement s atfar m level will starti n autumn 1996whe n both farms arefull y operational. In theforegoin g years the twoprototype s were designed andth e transition toth epresen t farms wasinitiated .Th eintegrate d type isdescribe d here according to its targets andconstraints . Nitrogen surplusi s used as an example for its perspectives.

Main targets and constraints on the integrated mixed farm 1) minimization ofth enitroge n (N) surpluspe runi t product; 2) minimization of theus eo f biocides per unitproduc t under thefertilizatio n regime resulting from target 1 and with theconstrain t of agoo d product quality atharvest ; 3) in the system therei sa variet y of crops moreo r less corresponding with the 'average' Dutch cattle and arable farms: grassland, maize, seed and warepotatoes , sugarbeets , winter and summer cereals, vegetables (onions,peas ,gree n beans,etc.) ; 4) nobar efield s until late autumn topreven t nitrateleaching ; Session 2.1 429

5) cultivation of potatoes and sugarbeet so n acertai n field upt oa maximu m of only oncei n every sixyear s toreduc e therisk s of soil-borne pests anddiseases ; 6) application of slurry only between late winteran d mid-summer toreduc e nutrient losses; 7) amount of purchased concentrates lesstha n 0.10 kgpe r kg milk,i.e . less than about 800 kgcow" 1y r* ,t orestric t nutrient inputs underth econstrain t of amil k production of about 8 000k gcow -1 yr1 and about 11 000 kgpe r hao f forages (grass,clover , maize,wheat) ; 8) with the exception of 4h apermanen t grassland surrounding thefar m buildings,th egras s inrotatio n isploughe d after twoo rfou r yearst opreven t nutrient accumulation inth esoil ; 9) a stocko f 60ewe si skep t toincreas epastur e utilization andconditio n (consumption of grass rejected bydair y cows,winte r grazing, 'biological' weeding in sown pastures); 10)sufficien t phosphorus (P) statuso f the soil (Pw-valueabou t 25); 11)weedin g in principle first through mechanical measures.

Results TheN an d P surpluses peruni t of acreage and the Nsurplu s perto n of milk are shown in the Table.I tillustrate s thepossibilitie s ofmixe d farming todecreas e environmental sideeffect s and toincreas e profit. This was alsoconclude d byD e Koeijer et al. (1995) in an environmental- economic analysiso f mixed crop-livestock farming. Thecontributio n on acountr y leveli s considerable asth edair y sectori sresponsibl e for about two-thirds of theN surplusi nDutc h agriculture.Th e negative Pbalanc e isdu e toth eai mt oachiev e asufficien t P statuso f thesoil . Current fertility inmos t of thefield s isfa r beyond thislevel .

Table.Calculate d nitrogen andphosphoru s surpluses excludingdepositio n on the integrated mixed farm (1996-2000; 50%forag e land) compared with thereferenc e year 1993(56 % forage land) andth eaverag eo f Dutch cattle andarabl e farms, 1985/1986(65 %forag e land).

KgN ha- 1 yr1 KgP ha" 1 yr1 KgN ton -1 milk The Netherlands (1985/1986) 217 11 37 Minderhoudhoeve (1993) 124 10 25 Integrated mixed farm (1996-2000) 33 -12 6

Conclusions Thecalculate d resultsillustrat e that nutrientlosse spe runi tproduc t and perh ama y bereduce d considerably by asoun d integration of thedifferen t production branches.I ti sinterestin g to notetha t when theresult s are translated toth eNetherland s asa whole ,tota l milkproductio n is almostth e samea sth ecurren t Dutch production volume (11millio n tonneso n 2millio n ha agricultural land,i.e . 550 0k g per ha). Onth eintegrate d mixed farm, themil k quotum equals 5 300k gpe r hafarmlan d of which only 50%i s used for growing forages. This confirms both the good production situation atthi s sitean d theperspective s for mixed farming systems.

References De Koeijer, T.J. et al., 1995.Agricultura l Systems 48: 515-530 Rabbinge, R., 1992.Proceeding s IOBC/WPRS Conference, p. 211-218. Pudoc, Wageningen 430 Book of Abstracts 4th ESA-congress

A FARMING SYSTEM ENVIRONMENTAL ASSESSMENT APPLIED ON ORGANIC FARMS AND FARMS IN CONVERSION

J Nocquet, C. David, Y Gautronneau

ISARA, 31plac eBellecour , 69 288Lyo n Cedex 02,Franc e

Introduction Organic farming ischaracterise d by alarge r consideration ofth e environment. In a EU research program « Conversion to organic stockless systems. On-farm research in Southeast France »,a farm network has been setu p invariou s organic farms and farms inconversio n (Gautronneau et al, 1994). One ofth e aimso fth e project isth e conception ofa farmin g system environmental assessment. The principal goal ist o evaluateth eimpac t on environment byorgani c farms or farms in conversion.

Methods The environmental assessment ofth e farming system demands athemati c approach inorde r to evaluate the holistic qualities ofdurabl efarm s (Nocquet et al, 1994 ,Nocquet , 1995). Two themes are formalised inrepl yt o the environmental case-studies ofth eregio n: - land management :landscap e quality and maintenance ofth ebiodiversit y , - control of pollutionrisks : diffus e pollution (nitrates, phosphates) and point pollution (animal waste storage) The method isbase d on fast, on-the-spot surveys and expert opinion (half ada y per farm). A limited number ofquantitativ e and qualitative indicators isdenned , accordingt o the environmental case-studies and farming system components. Thefarmin g system is divided into different sub-systems : the economic system, the livestock farming system, the forage system, the cropping system,th efixed productio n factors andth e decision-making system.

Results The results are presented inTable s 1 and 2. The environmental assessment ofeac h farm isbase d on the synthesis ofth e indicators. The mark isth e sum ofth e values ofal lth e indicators. It givesa level of environment-friendly practices.

Conclusions This method iseas yt o apply on site. The strengths and weaknesses ofth e farming system canb e detected rapidly. Inthi s survey, it hasbee n concluded that: - In general, organic farms had good practices for landscape management andth e control of pollution risks. Only one farm (1)wa sfoun d to have more problemstha n the other farms concerning land management. - On the other hand,th e environmental assessment ofth e farms inconversio n ismor e diversified. Two farms (9 and 14)ha d environment-friendly practices with land management and allth e farms more or less had problems withth e control of pollution risks.

References Gautronneau, Y. et al, 1994 Contrat AIR 3C T 93 0852, CEE DG VI/ CEREF-ISARA, 42p p Nocquet, J. et al, 1994. Cahiers Agricultures 3: 39-50. Nocquet, J, 1995 Annales dezootechni e 44, Suppl,338 . Session 2.1 431

Table 1 Control of pollution risks Indicators Organic farms Farms in conversion

6 3 7 10 2 4 1 9 14 13 15 17 16 12 Livestock farming system: - organic nitrogen pressure + + + + + = + + + + + + + - - animal waste storage + Cropping system : - N fertilisation + + + = +/= -N leaching risks + + - P fertilisation + + =/- + - pesticides + + + _ H i + i + • -toxi c waste + + ' + =/- = Equipment : type and state =/- +/= =/- +/= + + = +/= + Land structure + : + + + + + + + - - - Decision-making system : - environmental consideration + + + + + - + - -practice s planning + + + + + + + ASSESSMENT + + + + + (points) (8) (7) (6) (5) (4) (1) (-1) (3) (3) (2) (0) (-2) (-6) (-9) Legend: +: good (1 point), =: medium (0point), - : problem (-1 point)

Table 2. Land management Indicators Organic i arms Farms in conversion

6 3 7 10 2 4 1 9 14 13 15 17 16 12 Economics involment in + + = - + - + + + + maintenance of field pattern Forage system : - valorization of grassland + = + + + - - - valorization of shrubland + = + + + =/- - Cropping system : - crop diversity + + + + + - = + + + + - erosion risks ======+ - + - biodiversity +/= + =/- + +/= + =/- = +/= +/= = = + +/= Farm buildings and farmland : - integration of farm inth e + + + = + = - + + + + = - landscape - maintenance of farm + = + + = = + + + + + buildings - maintenance of farmland = + + = + - + + =/- = = = Decision-making system : - knowledge of environmental + + + + + = = + + + = policies - consideration of landscape + + + + + - + + =/- = = quality ASSESSMENT + + + + + - + + - - (points) (8) (9) (-1) (5) (7) (7) (-8) (7) (9) (0) (1) (1) (-5) (-3) 432 Book of Abstracts 4th ESA-congress

LEARNING FOR SUSTAINABLE AGRICULTURE

B.M. Somers free-lance social researcher, Hoofdweg 3,323 3 LH Oostvoorne, The Netherlands

Introduction Designing sustainable farming systems ison ething , farmers practising sustainable agriculture is another. For extensionists, thewor k ofRoger s (1983) has long been aguid e for understanding the speed and extent to which innovations arepu t into practise. Alsofo r sustainable agriculture, conceivable asa combination ofnove ltechnologie s and farming methods,Rogers ' work provides for achecklis t offactor s that influence the process ofdiffusio n among farmers. Some ofthes e factors point to the economic prospects and perceived risks inherent inth e innovation. Extensionists and policy makers are searching for meanst o speedu p therat e ofadoptio n of sustainable agriculture. However, sustainable agriculture isa complex innovation that seemingly lacks points ofimpac t for intervention. Compared to other types ofinnovations ,th eturn-ove r to sustainable farming systemsbear s risks onman yterrains . Therei sth e economicrisk o f cut-backs inyield san dinappropriat e marketing strategies;ther e are problemswit hpes t and disease management; on manyaspect sther e isa lac k ofknowledge . Moreover, the actual and perceived risksar eno t confined to economican dtechnologica l aspects. There are also social and political risks. The seriousness and sources ofth e environmental problems are constantly contested, which isals oth e casewit h normsan d penaltiest ofight th eproblems .Forerunner s in sustainable agriculturerisk th e distrust ofcolleague s who fear that proofs oflo w input agriculture willb e raised tillpolitica l norms. The social and politicalrisks tha t areinheren t ina turn-ove r to sustainable agriculture form strong impediments for itsintroduction . However, inthi s contribution I willrathe r not focus onth e problems, but on practical solutionstha t have alreadybee n found.

Conceptual background Studiesi ninnovatio n processes ingenera l and in sustainable farming systemsi nparticular , have takenplac ei na ninterpretativ e anthropological tradition aswel l asb ymethod stha t aima t finding statistical evidence. Somers and Röling(1993 )foun d that the introduction of sustainable farming systems differs from anadoption-of-innovatio n perspective. Because ofth e complexity of sustainable farming andth elac k ofpractica l knowledge, the introduction ofi t canbette r be described interm so flearnin gprocesses . AlsoBaye s pointst o theimportanc e oflearnin g processes inadoptio n ofinnovation s (Leathers et al, 1991;Lindne r et al, 1990). The so-called Baysian learning model isa n adaptive learning model. Crucial isth e notion that the perceptions offarmer s will changewhe nthe ygai n experience witha part ofth e innovation. Thismean stha t farmers haveth e possibility to try out one or more modules ofth e system, to try out thene w methodso n a part ofthei r farm, orhav e a choice concerningth eleve l ofinpu t ofa certai ninnovation . Bytryin gout , thefarme r gainsextr a information bywhic hh e can adapt hisorigina l perceptions about therisks o fapplyin g the innovation. He also experiences whether theinformatio n hego tfrom researcher s or extensionists isrelevan t for hisow nfar m situation. Thenotio n ofreducin g perceived risksb y doing coincideswit hKolb' s ideas about learningb y experience (Kolb, 1984).Kolb' s theory isincorporate d inman ymoder n management theories about 'learning organizations'. Relevant isth enotio n ofinteractio n between cognitiveprocesse s and acting. By shifting the perspectivefrom a (top-down ) adoption processt o a (bottom-up) learning process, alsoth epattern s ofinteractio n androle s ofactor sinvolve d willchange . Applyingthi snotio n to theagricultura l knowledge network, wewil lfind tha t roles, attitudes and Session2. 1 433 skillso f allactor s change when learning processes and supporting learning processes becometh e point ofdeparture .

Environmental co-operatives as acas e This shifting perspective iswel l illustrated byfive experiment s inDutc h agriculture, so-called environmental co-operatives. Environmental co-operatives areloca lgroup s offarmer s who search for wayst o realize environmental goalstha t are specific for their ownlocalit y and for theirtyp e of fanning. Often, they hold on-farm experiments inorde r to gain knowledge about environment, nature and landscape. Their aimsvar yfrom achievin g measurable values ofnatur et o minimizeth e input offungicides . In mycontributio n Iwil lhighligh t the experiences ofon e ofsuc hgroups , the working group soil-based horticulture under glass.Especiall y soil-based horticulture under glass isthreatene d bypolic y measures. Moreover, overth eyear sth eagricultura l research for soil-based horticulture was minimized infavou r ofhorticultur e on artificial substratum. Soil-based growers experience that they loose spacefo r manoeuvring and searching for solutions. Theythin k it of importance to quickly help develop new methods andtechnologie s under 'practical circumstances'. Bymean so fexperiment sthe ywil l- togethe rwit hresearcher s - search for environmental parameters that are specific for their situations andgai n knowledge on practical methods andtechnologies . For researchers inorde rt o support this learning process, theymus t have an open mind for knowledge other than scientific knowledge: theresearche r must gain experience inlearnin g systematicallyfrom innovation s that take place inpractic e already. They also must develop afeelin g for the policyrestriction s and risksfarmer s areworkin g under.

Conclusions Agrowin g number ofexperiment s showtha t farmers arewillin gt o contributet o amor e sustainable agriculture whenth e necessary conditions are created that facilitate learningprocesses . Conclusions are among others that: a) Theintroductio n of sustainable farming systemsi s encouraged whenth e systemsbea rth e possibility of learning bydoing . Amodula r construction of new technologies and methodswil lincreas e thewillingnes s offarmer s to takerisks; b) Agreate r interaction between researchers, extensionists and farmers isneede d bytakin g into account valuablepractica l experiences offarmer s -thi s requires amor e systematic apprehensionb y researchers offarmers ' experiences;c )Becaus e ofth e social and policial impediments, the development of sustainable farming systemswil lbenefi t from 'social' learning:group s of farmers settingthei r goals andfinding way st o realizethes e together.

References Kolb, DA., 1984.Experientia l Learning. Englewood Cliffs, New Jersey: Prentice Hall,Inc . Leathers, HD. et al, 1991. ABaysia n Approach to Explaining Sequential Adoption of Components of aTechnologica l Package, American Journal of Agricultural Economics 73(3): 734-742. Lindner, R. et al, 1990. Ates t ofBayesia nLearnin gfrom Farme r Trials ofNe wWhea t Varieties, Australian Journal ofAgricultura lEconomic s 34(1): 21-38. Rogers, EM., 1983.Diffusio n ofInnovation s (third edition).Ne w York: TheFre ePress . Somers, B.M. et al, 1993. Kennisontwikkeling voor duurzame landbouw (Knowledge development for sustainable agriculture). TheHague :NRLO . Somers,B.M. , 1994.Zoek - enleerprocesse n bij innovaties op het primaire agrarische bedrijf (Learning processes andinnovation s on primary agriculturalfirms). Th eHague :Ministr y of Agriculture, Nature and Fisheries Somers, B.M. (1995).Pla nva n Aanpak Werkgroep Telen in deGron d (Project soil-based glass­ house horticulture). Honselersdijk: Dutch Federation ofHorticultur e Studygroups . 434 Book of Abstracts 4th ESA-congress

NITROGEN DYNAMICS AND EFFICIENCY IN CROPPING SYSTEMS WITH DD7FERENT INPUT LEVELS: AGRONOMICAL, ECONOMICAL AND ENVIRONMENTAL CONSIDERATIONS. A.M. Triboi1, E. Triboi1, B. AletQn2 ^Station d'Agronomie INRA, 12avenu e du Brézet, 63039 Clermont-Ferrand, France. ^Chambre Départementale d'Agriculture 63, France. Introduction Nitrogen is the most important nutrient involved in growth and yield formation, in system productivity and in environmental variations. The adjustement of N supply to crop growth by N fertilizer and theefficienc y of N use may be variable according to the level of desired performances of the system and of the degree of uncertainty of environmental conditions (weather). Methods Dynamics of mineral N (NO3) in the soil profiles and total nitrogen in the aboveground plants were analysed during two years : 1993 (year 1)an d 1994 (year 2), in relation to crop growth and yield elaboration, on a rapeseed (Rs), wheat (Wh), sunflower (Sf), wheat (Wh) crop succession. One crop rotation at different stages was studied : Rs-Wh-Sf-Wh, Wh-Sf-Wh-Rs, Sf-Wh-Rs-Wh and Wh-Rs-Wh-Sf. Three input levels defined by yield objective were applied: a) an Intensive (I) or High-Input System to approach the potential yield ; b) an Adjusted (A) or Recommended System with inputs determined according to an actual crop potential ; c) an Extensive (E) or Low-Input System. To compare the N useefficienc y (Huggins & Pan, 1993) among cropping systems, some agronomical, economical and environmental indices were calculated. Results Results are presented in the Table. Table. Analysis of nitrogen efficiency at 3 input levels (I, Ao r E). Values are means (n = 4 crops per year or n = 2-4 values per crop).

1=N(F) 2=Y 3=N(G) 4=N(R) 1 5=CSN(H) N Fertilizer Yield % Grain N-uptake Non-Harvested Crop-Soil-N kg ha"1year " 1 (4 Crops) kg ha"1 N-Crop Residues at Harvest, kg ha"1 year1 . year 2 year 1 year 2 year 1 year 2 year 1 year 2 I 145 100 100 113 142 61 50 253 231 A 108 86 93 91 120 47 42 218 193 E 63 77 75 81 88 35 29 175 141

6=CN(W) 7=FUE 8=G-FUE 9=Nm(W)=Winte r Soil Nm Winter Fertilizer Uptake year 1 year 2 CropN Efficiency after under Bare Wh Rs Crops Grains Wh Rs Sf Wh Rs Soil I 55 99 1.26 0.88 (62) 33 125 45 69 27 51 A 49 64 1.39 0.97 (66) 29 73 40 61 22 52 E 28 60 1.85 1.34 (62) 28 66 45 60 21 30 Session 2.1 435

10=Nm(PH) 11=NM 12=NL(A)orNM 13=%N(G) max Postharvest N Mineralization Autumnal Leaching (-) Grain N-conc (Autumn)Soil Nm under Bare Soil(Sf) or Mineralization (+) 2 years Mean Wh RsSf before 15 April Wh Rs Bare soil Wh Rs Sf I 103 128 60 43 yearl 33 year2 + 17 +22 -66 2.35 3.59 3.24 A 68 94 76 45- 23 + 13 + 1 -19 2.18 3.33 3.12 E 71 75 52 55 29 + 18 +9 -30 2.12 3.32 2.94

Three input levels were compared. The annual mean fertilization for the 4 crops (4 different crops the same year : Wh after Sf, or Rs, or Wh after Rs, or Sf) was respectively 63-108-145 kg N ha"1 per year (1). The mean relative yield (2) was 76-90-100% and the Grain N-uptake 85-105-127 kg ha"1 per year. The nonharvested crop Residues N (4) were 32-44.5-55.5 kg ha"1 per year. The Fertilizer Uptake Efficiency (7 and 8) (or FUE, defined by Jenkinson et al, 1985 as the percentage of applied N taken up by the plants) wascalculate d for the total crops ((3+4)/l) and for the Grains (3/1). The low input system (E) gives the highest efficiency : FUE or G-FUE. The 1.34 Grain FUE value indicates that the N exported by grain in this extensive system exceeded the N fertilizer rate. The amount of mineral N (Nmin) in the soil profiles varies through the year. Some values seem to be interesting to point out : - Winter Soil Nm (9) was measured in January before the beginning of growing period and before N fertilization (Remy & Viaux, 1982). This Nm(W) depends on proceeding crop (Rs gives the highest values), and it depends also on the present crop : under Rs the lowest value was observed. Simultaneously, the Winter crop N (6) was determined, thus 9+6 gives the Winter Crop-Soil-Nitrogen (Appel, 1994 ; see 12). - Maximum postharvest (autumn) Soil Nm (10) is a good indicator of the decomposition and mineralization of crop residues (Muller & Mary, 1981). This Nm(PH) is higher for Rs (with about 80 kg N ha"1 from the leaves, unpublished results), than for Wh and Sf. - From the data obtained under bare soil until 15Apri l (sunflower is sown late), the N mineralization was estimated : 40-50 kg N the 1st year and 25-30 kg the 2d year. - The difference between the Nm(PH) and theWinte r Crop-Soil-Nitrogen can indicate 2 distinct mechanisms : under bare soil, the negative values show the Leaching of Nitrogen during autumn (with rain) ; under Rs or Wh, thepositiv e values indicate that the Mineralization is higher man Leaching. Probably, the N leaching ratedurin g the autumn period decreased in the order bare soil > wheat > rapeseed, because the mineral N amount in soil was reduced due to plant uptake (rapeseed > wheat) over autumn-winter period. Conclusions The intensive system has the highest yield and Grain N-concentration (13) but the lowest N efficiency and the highest risk of leaching. The adjusted and extensive systems are superior in terms of economic returns (non presented results) and environmental considerations. The extensive system presents the highest N productivity but the lowest grain quality. To improve efficiency of the cropping system, a better management of intercropping period and control of yield reducing factors (pests, diseases) are necessary. References Appel, T., 1994. Zeitshrift fuer Pflanzenernährung und Bodenkunde, 157: 407-414. Huggins, D.R. and Pan, W.L., 1993. Agronomy Journal, 85: 898-905. Jenkinson, D.S. et al, 1985. Journal of Soil Science, 36: 425-444. Muller, J.C. and Mary, B., 1981. CR Académie des Sciences, France, 67 : 808-902. Remy, J.C. and Viaux, P., 1982. 'Symposium on fertilisers and intensive wheat production in the EEC', London, 10Decembe r 1982: 67-92. 436 Book of Abstracts 4th ESA-congress

PRODUCTION ECOLOGICAL CONCEPTS FOR THE ANALYSIS AND QUANTIFICATION OF INPUT-OUTPUT COMBINATIONS

M.K. van Ittersum & R. Rabbinge

Department of Theoretical Production Ecology, Wageningen Agricultural University, P.O. Box 430, NL-6700 AK Wageningen, The Netherlands

Introduction Agriculture can be defined as the human activity in which energy from the sun is used for the production of sugars by using a set of inputs. This activity results in desirable outputs, such as grain or potatoes, and, inevitably, in undesired outputs, such as nutrient emissions. Numerous combinations of inputs and outputs are practised and possible in agricultural production systems. Production ecology studies the way agricultural production systems function and may function in relation to physical constraints and environmental factors. Important aims of production ecology are: i) the analysis of the relative importance of several growth factors and inputs to explain actual yield levels and resource use efficiencies and to open ways for improvement; ii) to quantify new input-output combinations for developing sustainable production systems. The basis of such analysis and quantifications is knowledge of basic processes at soil, field, crop and animal level. For a systematic analysis and quantification of agricultural input- output combinations various production ecological concepts have been developed.

Production level - desired output per unit area (Figure 1) Potential, attainable and actual production levels can be distinguished according to three groups of production factors: growth defining, growth limiting and growth reducing factors. Growth defining factors include factors that, at optimum supply of all inputs, determine growth and production from a plant's point of view: C02-concentration, radiation, temperature and crop and cultivar characteristics. Growth limiting factors comprise the essential abiotic resources water and nutrients; they are taken up, and some are incorporated in the plant. Growth reducing factors include weeds, diseases, pests and polluting substances.

Production situation - physical conditions at which production takes place (Figure 1) Input-output combinations are location specific. The location can be characterized by the production situation, i.e. the climate and soil conditions. The production situation is hard to manipulate and affects the potential production level or the required inputs to realize a particular production level. The other way around, agricultural activities hardly affect the production situation; only in the long run changes may occur (e.g. in organic matter content).

Target-oriented approach - adjustment of inputs to realize a particular output On the basis of knowledge of bio-physical processes the inputs for the realization of a certain output in a particular production situation can be quantified. This so called target-oriented approach is an important concept in exploring new land use options. Input-output combinations quantified with this approach discriminate between bio-physical and technical opportunities and socio-economic constraints and objectives.

Production techniques - complete set of agronomic inputs Production technique stands for the inputs and the way the inputs are applied to realize a particular production level in a certain production situation. Since substitution is possible between some inputs, for instance between labour, mechanization and herbicides, a production level in a particular production situation can be achieved with various production techniques. Session 2.1 437

Production orientation - aim of production activity that directs output and inputs The production orientation directs the output and input levels. Orientations for production activities could be a high soil productivity, high resource use efficiencies, low emissions per unit product and low emissions per unit area.

Example Table 1give s an example of four input-output combinations (production activities) for growing a crop rotation in a particular production situation. The production activities are characterized by two production levels and two production orientations and were quantified with the target-oriented approach. They were used in an exploration for future land use options in the European Union (Rabbinge & Van Latesteijn, 1992; De Koning et al., 1995).

, .production level Definingfactor s -CO* - radiation - temperature ' - cropcharacteristic s ! Limitingfactor s I -wate r - nutrients

: Reducingfactor s : -weed s - diseases ; - pests ' - pollutants actual : limited : actual

actual

bad production situation bad production situation good production situation (badclimat e / bad soil) (goodclimat e / bad soil) (goodclimat e / goodsoil ) Figure 1. Production situation, production levels and associated principal growth factors.

Table 1. Example of four input-output combinations characterized by two production orientations and two production levels for growing the rotation 'potato-wheat-sugar beet- wheat' in a region in the Netherlands. Inputs are quantified with the target-oriented approach.

Yield-oriented agric. Environmental-oriented agric.

Potential Water-limited Potential Water-limited Outputs (fresh tons hd'yf') Wheat 9.8 8.0 7.5 6.6 Potato 63 54 46 40 Sugar beet 76 66 67 58 Inputs (ha'yr') Irrigation water (106m3) 0.47 0.30 Nitrogen application (kg) 296 273 223 214 Production Pesticide (kg a.i.) 6.2 5.6 1.6 1.6 technique Labour (h) 38 30 35 30 Machines (ECU) 489 489 493 493

References De Koning, G.H.J, et al., 1995. Agricultural Systems 40: 125-151. Rabbinge, R. & H.C. van Latesteijn, 1992. Agricultural Systems 40: 195-210. 438 Book of Abstracts 4th ESA-congress

ORGANIC ARABLE FARMING -A CONTRADICTION ?

P. von Fragstein

University ofKasse l Faculty ofAgriculture , International Rural Development and Ecological Environmental Protection Department ofEcologica l Agriculture Nordbahnhoftstr. la D-37213 Witzenhausen

Introduction Ecological Agriculture isa growin g system inwhic hth e farm isconsidere d asa norganis m of nearly closed cycles (Köpke 1995). Although severely critized byKoep f (1980): "The separation of domesticanimal and clodwas one of themost momentous steps in thedevelopment of modern agriculturealthough itwas not theonly one that influenced soil fertility ina negativeway. " (p.55: "DieTrennung zwischen Haustier und Scholle..."), newtendencie s in ecological agriculture clearly indicatea highinteres t offarmer s for specialized, animal-independent organic farming systems. A successful crop growing inorgani c farming cannotb e managed without thecultivatio n of legumesbecaus e ofdistinc t restrictions for theN inputthroug h composts and organic fertilizers. Thedependenc e onth efunctionin g ofthat leguminous nutrient cycle iso f extreme importance for thewhol e system. N-fixation andN-losse sb yvolatilizatio n or leaching havegreate r influence upon the stockless system compared to amixe d system. Thecro p rotation isth e essential basis for anecologica l growing systembecaus e it hast o contributet o a satisfactory regulation ofth ewil dflora, a n equilibrated humusbalanc e and an optimized nutrient management (Heß 1990).

Ecological stockless Farms A questionnaire to the mainorganisation s ofEcologica l Agriculture inGerman y -a response of theEas t German GAAcoul d not be obtained -reveale d astonishing results •• Thebiodynami c organisation (DEMETER) that strictlyrequire s animalhusbandr y aspar t of biodynamicfarm s allowsvegetabl e growing enterprises as stockless systems. Contracts must assureth e import offarmyar d manuretha t hast o be composted and biodynamically prepared before use. •> There are three organisations -ANOG ,NATURLAND , andBIOLAN D - inwhic h 20 to 40% ofal lfarm s represent stockless systems. TheNort h GermanExtensio n Service- ÖKORING -i sclos et o 50 % ofal lfarm s practicing arable farming. •• The organisation specialized for winegrowin g and vine making -BO W- includes approximately 100% of stockless growing systemstha t isver y typical for special cropslik e fruits and grapes.

It isobviou s that East German organic farms tend to systemswithou t stocking or verylo w stocking rates because ofth ebi gfar m size,ver yofte n bigger then 500ha . Spohn (1993) interviewed nine stockless organic farmers and asked among others for their motivation to work intha t system. Hefoun d five dominant aspects:

1. main interests incro p growing, 2. no animal housings at theplace , 3. low rentability, 4. high (continuous) labour input, 5. ethicreasons . Session 2.1 439

Conclusions Regulation ofweeds • The cultivation offorag e crops cannot begive nu p due to theweakenin g effect to root weeds likethistle sb yth e repeated cuttings duringth egrowin g season. Humus management • Organic fertilizers, especiallyoff-far m composts canb eessentia l for the necessary recycling ofstabl e organic compounds inorde r to maintain sustainable soil fertility (providedthat continuousquality controls are made concerning unwanted concomitants). N-Management • Seed and forage legumes arecapabl et o provide sufficient N-reserves for a crop rotation or rotational segments either bycro p residueso rb yth etota l biomass(Hagmeie r 1986), • that potential canonl yb ebenefica l ifsit ean dgrowin g conditions suitth e requirements of the cultivated legumes, • strategies havet o bedevelope d and applied inorde r to minimize nutrient losses (Heß 1990, Justus et al 1990). General remarks •> It isobviou s that arablegrowin g systems areals odetermine d byessentia l elements ofcro p cultivation inmixe d systems,namel yth e forage crops(Hagmeye r 1986), •> There isn odoub t about the special importance offarmyar d manureo r composted FYM towardsth e maintenance of soilfertility . Off-farm composts are ablet o replace their function inarabl e systems(Fragstei n et al 1994, 199S). •• There isa nincreasin g tendency towards arablecroppin g systems, actually favoured byth e financial supports for conversion aspar t ofth eEU-wid e set-aside programme (Spohn 1993). -> Farms of intensive crops,i.e . vegetables, fruit trees orvine , traditionally belong to stockless systems. Even inbiodynami cfarm s that practice iscontinue d regardless the requested animal husbandry on agricultural farms.

Thecontradiction inquestion is not caused by the existence of organicarable farming, butby the contrastingstrategies of organisationswhich permit stockless organic gardening, but exclude organic arablefarming.

References Fragstein,P . von andH . Schmidt, 1994, 1995. N management ina n organic stockless crop rotation. AnnualRepor t I and Uo fEU-Projec t AIR3-CT93-0852, "Development and evaluation of organicfarmin g systems: The role oflivestoc k and agroforestry", 60 p. & 66p . Hagmeier, H.U., 1986. Über die Stickstoffversorgung von Winter-Weizenun d Winter-Roggen durch Leguminosenvorfrüchte, dargestellt anhand vonExperimente n aufeine mviehlo s bewirtschafteten organisch-biologischen Ackerbaubetrieb aufde r Schwäbischen Alb. Dissertation Universität Hohenheim, Stuttgart, 119 p. Heß, J., 1990.Mitteilunge n derDeutsche n Gesellschaft für Pflanzenbauwissenschaften. 3: 241- 244. Justus,M . and U. Köpke, 1990.Mitteilunge n derDeutsche n Gesellschaft für Pflanzenbauwissenschaften. 3: 187-190. Koepf,H.H. , 1980. Landbau -natur - und menschengemäß -Methode n und Praxis der biologisch- dynamischen Landwirtschaft. Verlag Freies Geistesleben,p.5 5 (quotation) Köpke, U., 1995. Warum organischer Landbau?In : Tagungsband 3.Wiss .Fachtagun g zum Ökologischen Landbau, (Hrsg) SÖLun d FGÖkologische r Landbau der Universität Kiel.,p . 13-19. Spohn, L., 1993. Viehloser Ökologischer Landbau. Diplomarbeit FHKreuznach , 117 p. 440 Booko fAbstract s4t h ESA-congress

ENVIRONMENT EXPOSURE BASED PESTICIDES SELECTION

KG. Wijnands

Research Station for Arable Farming and Field Production of Vegetables, P.O.Bo x430 ,N L820 0AK ,Lelystad , the Netherlands

Introduction The use of pesticides in current farming systems isextremel y high due to the almost exclusive choice of pesticides to correct for structural problems in the farm management such as insufficient crop rotation, susceptible varieties and high nitrogen inputs.Thi s is onlyone , however amajo r one, of the complex of problems that current farming is involved in. In reaction to these problems, Integrated Farming Systems (IFS)hav e been developed as acoheren t new vision on agriculture alongside other concepts asecologica l farming (EFS). Over the last 15 years these I/EFS systems that integrate potentially conflicting objectives concerning economy, environment and agronomy are being developed on experimental farms all over Europe. Inth e last 5year sthi s even has been done in co-operation with commercial farms; innovative pilot farms. The development of these systems ispresente d as acoheren t methodology called prototyping (Vereijken 1994, 1995).Appropriat e farming methods (comprehensive strategies built on different techniques) need to be developed orredesigned . Toppriorit y is given toth e design of amultifunctiona l crop rotation followed byth e nutrient management, the soil cultivation and the ecological infrastructure. All these methods are aiming at sustaining quality production with minimum external inputs and environmental hazards.Base d on prototyping research on experimental farms (Wijnands and Vereijken, 1992) and pilot farm (Wijnands, 1992) in the Netherlands it is shown what the role of crop protection is inthes e systems anda n innovative approach towards selection and evaluation of pesticides use is presented.

Methods The role of crop protection in an integrated system ist o sustain quality production by efficient control of the residual harmful species, with minimal use of well selected pesticides, giving priority to all non-chemical control options available.Th e selection of pesticides must bebase d on aquantitativ e appraisal of their impact on the environment, since the overall aim of sustainable farming systems is to minimise the exposure of the environment to pesticides in order topreven t short- and long term adverse effects on all species overall the biosphere. The Exposure of the Environment to Pesticides (EEP) is quantified byrelatin g the active ingredient properties Vapour Pressure, Half life time (DT50) and Kom (exchange coefficient water-organic matter) to the amount used. These properties are known under standardised conditions, since they are required values for the approval procedures (Linders et al., 1994).EE P quantifies the maximum risk of environment exposure to pesticides for the different compartments of the abiotic environment: water, soil and air. Itca n be used toevaluat e pesticide use or to select pesticides. EEP byfar m should targetedly be improved by a) substitution of the highest ranking compounds by non-chemical measures or lower ranked pesticides orb ) by reducing the used amount bya more appropriate dose orband-spra y or spotwise treatments. Session 2.1 441

Results Over the period 1986-1990th e input of pesticides in the integrated farm atNagel e (Development of Farming Systems experimental farm) was reduced with 60%,excludin g nematicides andb y 90% if nematicides are included, in comparison to the conventional system. The reduction wasa result of the Integrated Crop Protection strategy (nomajo r changes in available pesticides during this period).Th e integrated system in 1992reduce d another 70%o f the active ingredient useo f the integrated system during 1986-1990.Thi s was for the larger part due to substitution of old pesticides by "new"lo w active ingredient compounds.Fro m theconventiona l system in 1988 (representative for 1986-1990) toth e integrated system in 1992 (representative for 1992-1995) the active ingredient use andEEP-air , -water and -soil were respectively reduced byfactor s of 43 106, 215 and 254..Fo r active ingredients this means in terms of reduction %,98 %reductio n if nematicides are included. The selection of pesticides based on EEPobviousl y multiplied the effect of the ICP(reduce d use).Th epilo t farm Central clay group (9pilo t farms in the same area asth eNagel e farm) reduced the input of pesticides in kg activeingredien t and inEEP ,lik ea t Nagele, strongly. In 1993th e active ingredient input and the EEP was, in comparison to the farm- specific reference years 1987-1989,reduce d byrespectivel y factors of 6.5, 106,3 an d 5.Fo r active ingredients this means in terms of reduction %, 85%reductio n if nematicides are included.. It is shown that the quantitative EEP (Environments Exposure to Pesticides) parameter is an excellent evaluation and selection tool for pesticide use.

Conclusions IAFS prototypes asdesigned , tested and improved in the Netherlands on experimental farms for region-specific conditions showed economically and technically feasible possibilities to reduce the input of pesticides drastically and to almost minimise their environmental impact whilst maintaining soil fertility, minimising P/K/N mineral fertiliser input and controlling leaching ofN . The economic perspectives were equal to those of the "conventional" farming systems.Th e prototypes thus were readyfo r ates t and improvement phase with alimite d number of well- motivated practical farmers (38 farms from 1990til l 1993)..Simila r results as on the experimental farm were obtained. In 1993th e pre-requirements for large scale introduction were fulfilled and anew , large scale dissemination project, involving 450farmer s was started.

References Linders,J.B.M.J , et al.Pesticides : Benefaction or Pandora's box, asynopsi s of the environmental aspects of 243pesticides .Repor t no6791014 .Nationa l Institute of Public Health and Environmental Protection, Bilthoven Netherlands, 201 pp Vereijken, P., 1994. 1. Designing prototypes.Progres s reports of research network on integrated and ecological arable farming systems for EU- and associated countries (concerted action AIR3-CT927705). AB-DLO,Wageningen , Netherlands 87pp . Vereijken, P., 1995.2 .Designin g and testing prototypes. Progress reports of research network on integrated and ecological arable farming systems for EU- and associated countries (concerted action AIR3-CT927705). AB-DLO,Wageningen , Netherlands 76pp . Wijnands, F.G., 1992.Netherland s Journal of Agricultural Science 40(3):239-250. . Wijnands, EG. and P.Vereijken , 1992. Netherlands Journal ofAgricultura l Science40(3) :225 - 238. Session 2.2

Resource use at cropping system level. 444 Book of Abstracts 4th ESA-congress

RESOURCE USE AT THE CROPPING SYSTEM LEVEL

P.C. Struik1, F.Bonciarelli2

1 Department of Agronomy, Wageningen Agricultural University, Haarweg 333,670 9 RZ Wageningen, The Netherlands 2 Istituto di Agronomia Generale e Coltivazione Erbacee, Universita' di Perugia, Perugia, Italy

Introduction The basis of sustainable agriculture is a good crop rotation, adequate soil and water management, and proper husbandry ofth e different crops inth e rotation. Agronomically, farmers should aim at the minimum input of each production resource required to allow maximum utilization of all other resources. Consequently, above a certain minimum, higher inputs of aresourc e result in higher yields per unit area and are associated with higher efficiencies (expressed as output per unit of input) of other resources, but at the same time might cause large residues or emissions per unit area. Many processes relevant to resource-use efficiency (RUE) are so slow or long-lasting that they also have effects at the time scale of an entire rotation. This paper focuses on these processes.

Crop rotation Crop rotation is a more or less fixed pattern in the succession of crops on a certain field and thus a more or less fixed pattern of management and inputs. RUEs at the crop rotation level are not only determined by short-term efficiencies of component crops but also by long-term processes influenced by tillage, the different crops in the rotation and their management. The physical fertility is affected by each crop, the type and timing of cropping practices in each crop, and the measurements taken during fallow periods to improve the physical fertility. Chemical soil fertility is affected by fertilizer application; the effects of crops on nutrient fixation and mobilization, mineralization and losses of nutrients; the amount and quality of crop residues; andthei r rate of degradation. The higher the frequency of crops sensitive to soil-borne diseases or other biological stresses, the higher the need for crop protectants to control them. In contrast, the higher the frequency of crops with positive effects on beneficial organisms, the lower the need for crop protectants. It is difficult to set out general rules for a good crop rotation but alternating crops with contrasting effects on the physical, chemical and biological soil fertility isusuall y advisable.

Management strategies at the cropping system level (illustrated by a balanced N-supply) Differences among crops and their cultivars in recommended (economically optimal) applications and nitrogen use efficiency are large; residual N istherefor e very variable. Residual N will be lost or will have after-effects later in the rotation. At the cropping system level the efficiency of nitrogen is determined by the level of input, the form and timing of input, the efficiencies of utilization by the different component crops and the degree to which N remaining in the soil or in crop residues can be kept within the boundaries of the cropping Session 2.2 445 system and can be utilized by later crops. Efficiency is optimal when the following aims are met: i. maximum use of the nutrients supplied by adjusting the amount supplied to the demand, by synchronisation of supply and demand, and by synlocalisation (the nutrient is available where it can be taken up); ii. optimal use of crop residues, for example by maintaining the proper C:N ratio inth e soil; iii. maximum reduction of emission during the periods between the main crops, e.g. by growing catch crops or by incorporating straw. Microvariability inplan t and soil characteristics and their interactions is crucial for a proper management of nutrients. Part ofth e variability may persist, increase in time and interfere with other aspects of crop management. Managing variation istherefor e crucial for sustainable resource management atth e cropping system level.

Management strategies per link in the crop rotation (illustrated by a balanced N-supply) For nitrogen efficiency two crop types can be distinguished: crops without change in N-recovery with an increase inN-suppl y until the agronomically optimal level and crops with an decrease in N-recovery with an increase inN-supply . Beyond the agronomically optimal supply the recovery decreases with an increase in supply for both types. In all cases nitrogen residues are unavoidable. The type of fertilizer is relevant to the magnitude of and variation inth e losses.Th e dynamics ofN availability cannot be accurately predicted, not in time and not in amount whereas also crop growth and amounts ofN in crop residues are still unpredictable to a large extent. Crop residues will affect the soil fertility. Depending on their C:N ratio, soil characteristics, tillage and cropping practices, and weather the proportions of N lost or carried over to the next growing season vary considerably. The emissions can be reduced, albeit not to zero. If nitrogen emissions are kept extremely low, usually the chemical soil fertility is reduced in the long term. This may not be true for other nutrients.

Use of special crops to improve sustainability Growing of legumes (improving nitrogen and phosphorus availability); green manure crops (physical, chemical and biological soil fertility); lure, catch, trap and killing crops (biological control or suppression), cover crops (preventing soil erosion); and nutrient catch crops (keeping nutrients available for subsequent crops) can help to improve the sustainability of the cropping system. They have to fit in the sequence of main crops and should not interfere with necessary soil tillage. Especially their response to light and temperature in dependence of sowing date and their effects on water availability need further research to optimize their use.

Final remarks Tools for analytical study of and decision support on the effects of cropping system management on the productivity of each crop inth e rotation, ofth e environmental risks and of the sustainability of the cropping system are strongly needed. Investigations into options to maintain a short rotation of a crop with low self-tolerance by making use of non-chemical strategies to avoid yield-reducing conditions are also required. In practice, variation in RUE is strongly influenced by differences in "farming styles" among farmers, even under similar environmental conditions and financial returns. 446 Book of Abstracts 4th ESA-congress

PRELIMINARY EVALUATION OF EPIC IN SIMULATING CROPPING SYSTEMS AT ONE SLOVAKIAN LOCATION

M.L. -Bartosova , S. Kosovan

Department of Agricultural Systems,Universit y ofAgriculture , 949 76Nitra , Slovakia

Introduction Agriculture iscommonl y considered ason e ofth e most important non-point sources of ground waterpollutio n in Slovakia. Very little measured dataar e available to quantify the impacto f agricultural management onwate r pollution. Simulation models are research tools which canb e usedt o assess both the impact of agricultural management onth e environment and the agronomical outcome of different managements. Models must beevaluate d in each specific environment before using them in simulation studies. As a first approach to model validation, wecompare d data collected ona n on-going cropping systemexperimentwit h simulations run using the EPIC model.

Methods Theexperimen t was laid out atth e research station of DolnaMalant a (Nitra, Slovakia). Thedat a used refer to the years 1991-95.Th erotatio n studied isa 8 year s rotation, alfalfa -alfalf a - winter wheat -suga r beet- sprin g barley- commo n pea -maiz e- sprin gbarley . Each phase ofth e rotation was sown every year ina randomize d block design with four replicates. Fertilizers applied wereth e amountspe rh a commonly used inth e area until 1993,th e treatment no fertilization was added inth eyear s 1994-95. Weeds andpest swer e controlled by using pesticides.Meteorologica l data were collected ata loca l university weather station. Soil input parameters were estimated bymeasurement s on site.Th e EPICmodel ,versio n 3090,wa suse dt o simulate the cropping systems during theyear s 1991-95,withou t reinitializating soil variables.

Results The location of Dolna Malanta is characterized, withrespec t to rainfed agriculture, byth e amount ofaverag eyearl yrainfal l 533m m andb yth evalu eo faverag emonthl y windspeed 4.8 m/s. Inthes e conditions,th eprope r estimate ofbot h potential évapotranspirationan d water use byth e crops is extremely critical to simulate thewate r budget. Data available allowed onlya partial description ofth e system under study.Nonetheless ,th e data available were the onlyone s to makea first approac h to cropping system simulation by EPIC,lookin g mostly at model capability to adequately estimate year-to-year variability of grainyields . Calibration ofcro p parameters, becauseo flac k of data,wa s restricted to total heat units, in ordert o setth eprope r length ofth e biological cyclefo reac hcrop .

Maize- grain yield (t.h a ') Maize-above ground biomass (t.ha'1)

16 A • 91 -•- 91 14 A 92 • • 92 T3 & s^ 4) A 93 HO 12 A 93 X 94 • / 13 s' a - 1194 10 X 95 O 95 U /• 8 // • 94sil • 94n of IL 6 + 95sil + 95n of ] / - 94nof • 95nof 4 6 8 10 12 14 16 • 94silnof Measured yield Measured yield • 95silnof Session 2.2 447

1 Winter wheat yield (t.ha'1) Spring barley yield (t.ha' )

x 2 6 / • 91 a / m • 92 •o S 4 A 93 o / X94 2 X95 , / Û 0. 2 /^ '•95nof /"^ • n 2 4 6 2 4 6 Measured yield Measured yield

1 Alfalfa yield (t.ha ) Sugar beet yield (t.ha ')

x '~7 • 91 2 14 - O y/ D92 > 12 - •a / m A 93 • 94 su io - TJ 8 - « x 95 £ /k a 0. 6 - • 94nof • O 95nof 4 - ~—\ \ i i 0 2 4 6 8 10 12 14 4 6 8 10 12 14 16 Mesured yield Measured yield

Figure 1.Predicte d vs.measure d yield data (t.ha" )fo r crops grown inth e rotation. Legend: nof :n o fertilization; $:firs t year of alfalfa; sil:maiz e for silage

The underestimated yields of sugar beet, winter wheat and spring barley (Fig.1 ) wer e affected by water stress (low rainfall). Unacceptable results are the predicted maize and winter wheat yields in the year 1995 for no fertilized conditions.

Conclusions The discrepancies between predicted and measured data suggest thatth e default values ofEPI C parameters are not fully adequate for Slovakian conditions, someasuremen t to estimate model input parameters are needed to allow evaluating model capability to simulate cropping systems inth e conditions under study. It must bepointe d outtha t themode l estimates show often an overestimate of water stress,wherea s some validation studies conducted in different areaso f Europe showed that EPIC tends tounderestimat e water stress.

References Cabelguenne, M.e t al, 1988.Agronomie , 8 (6):549-556 Cabelguenne, M. et al., 1988.EEC ,Brussels , 24-25Novembe r 1988 Ceotto,E . et al, 1993.Agricoltur a Ricerca, 151-152:209-228 Williams, J. et al., 1994. 1984.Transact . ASAE, 27 (1):129-144 Williams, J., 1994.Th e EPIC model, U.S.A., U.S.Dept .Agric , ARS/ SWRL, 114 p. 448 Book of Abstracts 4th ESA-congress

SOIL PHYSICAL PROPERTIES - SOIL MANAGEMENT INTERACTIONS IN A SUSTAINABLE FARMING SYSTEM

A. Canarache

Research Institute for Soil Science and Agrochemistry, Bd.Marasti 61, 71331 Bucharest, Romania

Introduction Soil physical properties are recognized as one ofth e major factors determining soil productivity, crop yields, and sustainability offarmin g systems Results of determinations of soil physical properties inlon g term-field experiment are presented here.

Method Several long-term experiment fields, organized byvariou s research institutes and research stations inthi scountr y havebee n investigated. Undisturbed soil samples were collected. Bulk density, total and aeration porosity, saturated hydraulic conductivity, standard resistance to penetration, aggregate water stability, and dispersion were determined using classical analytical methods. Infiltration rate was determined inth efield usin g a single-ring infiltrometer. Asyntheti c "agrophysical index" (Canarache, 1978),whic h isth e average ofth e normalized data for 10 individual soil physical characteristics, hasbee n calculated. Resultswer efit i n aconceptua l model (Canarache, 1987, 1994) describing mechanisms ofchange s and interrelationships with some soil chemical properties and with crop yields. Regression analysis, linear and quadratic, aswel la s singlean d multiple, wasuse d to quantify the different mechanisms involved.

Results As shown inth eFigure ,five mai ntype s ofmechanism s are considered to be involved inth e changes affecting soil physical properties under long-term management techniques. Asixt h mechanism represents the feedback effects ofchange d soil physical properties on cropyields .

Directeffects of management onsoil physical properties (No.1 inth e Figure) result mainly from tillage practices and from traffic. Asa n example, in along-ter m experiment conducted at the Marculesti Research Station on avermi-calcaro-calci c Chernozem, grain maizebein g the crop (Canarache et.al., 1979), with various ploughing depths and reduced tillage, continuous or alternating from year to year, the following regression was obtained: 2 BD = 1.36 -0.0023*T cy -0.0013*T py - 0.000022*Tcy 2 2 - 0.000022*Tpy +0.00013*Tcy*Tpy (R =0.93* ) 3 where: BD -bul k density (g.cm" ), Tcy- tillag e treatment current year, Tpy -tillag e treatment preceding year (T representing the depth of ploughing incm , with zero conventionally used to describe no-ploughing treatments). Other results referring to deep loosening ofcompac t subsoil, zero-tillage, cultivation, aswel l ast o man-made compaction, areavailable .

Indirecteffects ofmanagement onsoil physical properties throughthe path management -soil chemicalproperties -soil physical properties (No.2+3 inth e Figure) are often noticed when fertilizers are applied. They are illustrated here with results from the Fundulea Research Institute for Cereal and Industrial Crops (haplic Phaeosem), for silage maize as acro p (Moga et al, 1986). The regression equations are: H =2.91 + .0060*M-0.076*N-0.0025*M2 +0.022*N 2+ 0.0011*M*N (R2 = 0.99**) AI= -5.3+3.54*H-0.54*H 2 (R2 =0.50* ) Session 2.2 449 where: H -humu s content (percent), AI -agrophysica l index, M- manur e (t.ha" ), N- nitrogen (kg.ha" 1). There are many results ofthi s type, for different soils, crops, and fertilizers.

Management techniques

i 4 2 —» Crop growth and yield 1 5 i <- 6a Soil chemical properties

I i I 3 <- 6b Soil physical prop erties

Figure. Conceptual model of management - soil -cro p interactions (see text for explanations)

Indirecteffects throughthe path management -crop growth - soil physical properties (No.4+ 5i n theFigure ) isa mechanis m less studied. Weexplai nthi s effect through abette r root development caused byadequat e soil management, and byth e effects the root system have on soil structure and on other soil physical properties. Crop rotation ison e ofth e management practices usually showing this mechanism. Results from an experiment with potatoes on ahapli c Phaeosem at the Secueni Research Station (Canarache et al., 1984) are presented here: Y =22.3 + 1.20*R+ 3.90*F-0.38*R 2-0.34*M*F (R2 = 0.96**) AI= 0.78 - 0.0021* Y+ 0.00037*Y2 (R2 =0.48* ) where: Y= yiel d (t.ha"1), AI- agrophysica l index,R -cro p rotation (number ofyear swit h other crops than potatoes), F- fertilizatio n (conventional figures used: zero for non-fertilized, 1fo r complete NPK fertilization). Other experimental data are available on different soils describing similar effects of preceding crops and ofcrop swit h specific improving effects.

Conclusion Data presented inthi s paper, and many similar data available, describe possible positive and negative effects of soil management onth e soil physical status, some ofth emechanism s involved, and could contribute to a sustainable soil management system.

Literature Canarache, A. , 1978. Stiinta Solului, 1:33-43 . Canarache, A., 1987.Du m Techniki CVSTS, Tabor (Czechoslovakia), pp.106-117 . Canarache, A., 1994. In: Trans. 15thWorl d Congress of Soil Science, Acapulco, 6a: 142-143. Canarache, A. et al., 1979. In: 50 Ani de Activitate Stiintifica inBaraganu l de Sud-Est, Marculesti (Romania), pp. 168-204. Canarache, A. et al., 1984. Technical Report, Institutul de Cercetari pentru Pédologies i Agrochimie (unpublished). Moga, I. et al., 1986. Analele Institutului de Cercetari Céréale siPlant e Tehnice, 53:211-236 . 450 Book of Abstracts 4th ESA-congress

SIMULATION OF DURUM WHEAT YIELD ANDN DYNAMIC S BY CERES/WHEATMODE L INA NALFISO L OF SOUTHERN ITALY.

A.Castrignanô 1, G. Convertira1, D.Ferri 1, P. Greco2.

1 Istituto Sperimentale Agronomico.Vi aC . Ulpiani, 5.7012 5BARI , Italy. 2 Istituto Sperimentalepe ri lTabacco . ViaF . Calasso, 3.7310 0LECCE , Italy.

Introduction Nitrogenfertilizer s shouldb e annuallyapplie d andwel ladapte dt o cropneed s aswel la st osoi l and climatic conditions.However , topredic t theprecis e cropN requirements , cropgrowt han d developmentprocesse si nrelatio nt owate r andN balance s shouldb e estimated. Simulation models areparticularl y useful toprovid e someinsight sint ofertilize r responsesi n different environments andthe yar eo fgrea thel pfo r optimizinglong-ter mmanagemen t strategies. To simulate N dynamicsadequately , amode l capable of describingth emajo r soilan dplan t transformations isrequired . TheCERESAVhea t modelwa schosen , asi tsimulate sgrowth , phenology, water andnitroge nbalance , andyield ;moreove ri tha swidesprea d applicability (Godwin andVlek , 1985).

Methods Afield tria l wasconducte d from 1988t o 1991o n asand ysoi l(Haploxeralf ) atth e Tobacco ExperimentalInstitute ,Lecce-Itary .Th e main soilcharacteristic s are:70 %sand ; 13%clay ; 1.3% 1 1 o.m.; 0.7 g kg" N , pH(H 20): 8.2; C.E.C.:13meq/10 0g ,NaHC0 3-extractableP :2 0m gkg" . Amongfiv e rotations incomparison ,th e biennialtobacco-duru mwhea t rotation without soybean ascatc h crop, fertilized, irrigated andmanage d accordingt otw otreatment s (highinpu t and low input)wa suse d tovalidat eCERE Smode lfo r wheat cropi ntw ocroppin gseason s(1986-87 ; 1988-89). The climatic conditions duringth etria lperio dwer ereporte d byGrec o eta l(1994) . Monthlysoi lsample swer etake na ttw o depths alongth esoi lprofil e (0-15; 15-40cm) .Eac h samplewa ssubsample dfo r moisture determination bydryin gi na nove n at 105°C andplace d ina nextractin g solution (1M KCl)a t 1:5 sousolutio nrati ofo r 2h ; filtered extractswer e analyzedwit ha Technicon Autoanaryzer, seriesI Ifo r N-NO3an dexchangeabl e N-NH, measurements accordingt ostandar dmethods .

Results Withregar d tophenolog y the observed maturity dates(Tabl e 1)wer e alwayslate rtha nth e predicted ones, eveni nth e 1986-87seaso nwhe nth ehig hinpu ttreatmen t data wereuse d to calibrate wheatgeneti ccoefficients . Thatprobabl y resultsfrom a weakness ofCERES/Whea t model(i nparticular , the genetic coefficient PS) to simulateth ephenolog y of durum wheati n hot-dryconditions ,typica lo f southernItaly . Onth e contrary, asfo r anthesis datematchin g between observed andpredicte dvalue swa sver ygoo di nth e 1986-87season , andth epredicte d datewa slate ri nth e 1988-89season .Fro m theestimatio n ofth emode l stress coefficients, that mightb e caused bynutritiona lan dwate r stresses, occurred atth e beginning of croppingcycl e anda tgrai nfilling stage , respectively. The prediction ofgrai nproductio nvalue swa salway squit egoo dbu t inth e 1986-87seaso n a severelodgin g(7 0percen t ofplants) , due to theparticula r sizeo fth e used durum wheat genotype, selected inou renvironmen t and characterized bya neve nyiel d duringth eyears , caused alos si ngrai nyield . Thusth e simulated valueswer ereduce d because themode l doesno t consider otherlimitin gfactor s thantemperature , water and nitrogen. The observedgrai nyield s (Table 1)wer e not statistically significant between the two treatments, because ofth emor e severelos s ofproductio n duet o the lodgingi nth e "high input" treatment. Session 2.2 451

Ngrai n content (%) was also estimated fairly well (Table 1)bu t anoverestimatio n (excepti n 1986-87seaso n for highinpu t data used for calibration) ofth emode lwa sobserve d for the"lo winput " treatment, probably causedb ynutritiona lan dwate rstresse s occurred atth e beginning ofea rgrowt h and duringth egrai nfilling . Thefitting o fgrai nN uptake (kgha " )wa s also verygoo d for both treatments and inbot hyears , whereasth e significant overestimation oftota lN uptake was verylikel yproduce d bya noverestimatio n oftota l biomass.I nFigur e 1 the observed and simulatedvalue so fN percentage inplan ttop s are compared. Itappear s that the modeloverestimates .

Table1 -Compariso no fprediction so fth e CERES/Wheatmode lwit haverage dobserve d datafrom experiments .

High level Input Low level input 1986-87 1988-89 1986-87 1988-89 Predicted Observed Predicted Observed Predkted Observed Predkted Observed Anthesis date 121 121 120 107 121 121 120 107 Maturity date 160 178 164 175 160 178 164 175 Grainyiel d( k g ha" ') 3446 3106 3251 3236 3411 3089 3210 3180 Kernelweigh t (g) 44.357 48.000 40.283 52.000 44.371 52.000 42.809 57.000 Grainspe r sq metre 11952 12000 9171 9840 11825 10500 8242 9660 Grainpe r ear 30.18 30.00 12.92 30.00 25.40 28.00 10.51 28.00 N Grain (%) 2.23 2.65 2.44 2.48 2.23 2.17 2.30 2.04 -1 Tot.N uptak e (k gN ha ) 149.6 102.9 157.0 121.8 126 103.0 107.2 96.6 GrainN uptake 97.1 94.6 90.2 92.3 76.1 77.0 73.8 74.5

6 z 5 t CO 0- 4 0 r- 3 "0 ..•*/ 0) 2 £ Obseived = 2.41 + 0.73 * Simulated

Figure 1. Observed versus predicted plant top N (%). The 1:1 fine and the regression une (observedv ssimulated ) aregiven .

Conclusions Theresult s show thatCERES/Whea t modelshoul db ebette r calibrated and eventually modified to adapti tt ohot-dr ycondition s in southernItaly .Nevertheless , italread yprove sa vali dtoo l for optimizingfertilizatio n and watermanagement ,becaus eth e experimentalresult sshowe dth e possibility toreduc eth eagrotechnica linputs .

References Godwin, D.C. et al., 1985. Simulation ofNitroge ndynamic si nwhea tcroppin gsystems . In:"Wheat growth andmodeling".W . Day andR.K . Atkin(Eds) . SeriesA :Lif e Sciences . New York, 86, 311- 330 ; Greco, P., et al., 1994.,Pro c3r dES ACongress , 696 -697 . 452 Book of Abstracts 4th ESA-congress

GRAIN SORGHUM IN SOUTHERN ITALY : DYNAMIC GROWTH AND NITROGEN SIMULATION BY CERES/SORGHUM MODEL

A.Castrignano , G. Convertira,D . Ferri, V.Rizzo ,M . Rinaldi.

IstitutoSperimental e Agronomico.Vi aC .Ulpiani , 5 70125BARI ,Italy .

Introduction Grainsorghu m isa C 4specie s withver yhig hphotosyntheti c efficiency, suitable tob ecroppe d in the environments of South Italy, characterized by intenseradiatio n levels.Hig hgrai nyield swer e obtained bothi nirrigate dfarm s and evendurin glon g dry seasons (Quaranta et al., 1987), probablybecaus e ofroo tmorphologica l andphysiologica l characteristics thatmak egrai n sorghum quiteresistan tt o drought (Marianian dDonatelli , 1983). Toge tmor einsight si nyiel dpotentia l andN dynamics ofsorghu m cropped insouther n Italy, the experimentalresult s ofa lon gter m trialwer e compared withth eprediction s of the CERES/Sorghum model (Virman ie t al., 1989).

Methods The silty-claysoi l(Typi cChromoxererts ) ofth e trialha d thefollowin g characteristics:40 %clay , 1 1 27%sût , 2%O.M. , 1.2 gkg" N , 75m gkg' NaHC03-extractableP , 1000pp m NILOAc- extractableK , 37meq/10 0 g C.E.C., pH=7.Monthl y soilsample swer e takeni nthre elayer s alongth eprofil e (0-20;21-40 ;41-6 0cm )a tFoggi a (southern Italy)durin g the croppingseasons : 1989an d 1991.Eac h soilsampl ewa ssubsample d for estimatingwate ran dnitrat e contents checkedb yextractio n with 1 M KClan d analyzed by automatic standard methods. In 1989als o weeklyplan tsample swer e collected for growth analysis. Thetria lconsiste d inth e comparison amongdifferen t croppingsystem s combined withtw o agrotechnicalinpu t levels, concerningsoi l tillage,fertilizatio n andwate rmanagemen t (conventional management ashig hleve lan dlow-inpu t management aslo wlevel) .I nthi swor k onlygrai n sorghum data(cv .N K 180), submitted toth e twoinpu ttreatment s and sowni nMa yi nth etw otria lyears , wereutilize dfo r simulation. The 1989dat afo r highinpu tleve lwer euse dt ocalibrat eth emode lgeneti cparameters , whereasth e remainingthre e data setswer euse dfo r validation.

Results Theresult s ofth e simulations arepresente d inTabl e 1.Th ebes tgoodness-of-fi t wasobtaine d for anthesisan dmaturit ydate si nbot hyears . The differences betweenpredicte d and observed sorghumgrai nyield swer eabou tth esam ei nbot hyear s (12-15 %), buti nth efirst on eth emode l overestimates, whereasi nth esecon d onei tunderestimate s inbot htreatments , asa consequence ofth eunderestimatio n ofth ekerne lweight . The different performances ofth emode li nth etw o years ofsimulation si sprobabl ydetermine d by different rainfall patterns:i . e.th e secondyea rwa s characterized by driermeteorologica l conditions (360 vs. 280m m onaverag e of watersuppl yi n thetw ocroppin gseasons ,respectively) . Asregard s N balance,i tappear s clearfrom Tabl e 1 that themode ltend st o overestimate bothgrai nN (%) and grainN uptake and underestimate totalN uptake, excepti n 1989fo r "lowinput " treatment. Animprovemen t ofmode lpredictio n as awhol e couldb e obtained byincreasin ggoodness-of-fi t of above-ground biomass. Onth e contrary aquit e goodmatchin gbetwee n observed and predictedvalue s of growth analysis (leaf areainde x"LAT' , stem andlea fdr yweigh tan d above-ground biomass "DM")wa sobtaine d with determination coefficients alwaysgreate r than0.97 . Asa nexample , inFigur e 1 thecompariso n between observed andpredicte d LAIan dD Mvalue sfo r thetw o treatments isshown . It appears cleartha t themode ltend st o overestimate above-ground biomass, mainlyi nth elo winpu t treatment and duringth efinal par t ofth e cropcycle . Session 2.2 453

Table 1. Comparison of predictions of the CERES/Sorghum model with averaged observed data. 1989 1991 Highleve l Lowleve l Highleve l Lowleve l Predicted Observed * Predicted Observed Predicted Observed Predicted Observed

Anthesisdat e 203 202 203 202 203 207 203 207 Maturitydat e 237 240 237 240 236 238 236 238 Grainyiel d( k g ha"1) 8097 7668 8000 7041 5026 5911 4657 5298 Kernelweigh t(g ) 0.024 0.023 0.024 0.024 0.015 0.020 0.015 0.017 Grainspe rs qmete r 33574 33750 33647 28739 33504 30359 31048 31031 Grainspe rea r 1119.13 1277.00 1121.57 1150.00 1164.81 912.00 1034.93 1015.00 Biomassyiel d(k gha" 1) 19162 20159 19081 16361 15448 14281 14750 18931 Grain N(% ) 1.94 1.67 1.89 1.50 2.88 1.90 2.70 1.77 Tot.N uptak e( k gN h a~ l) 198.4 209.0 191.9 162.0 183 222.0 162.3 196.0 GrainN uptak e " 157.5 149.0 151.0 123.0 144.7 131.0 125.5 109.0 *Use d forcalibratio n

DM (g ntf) LAI 2000 e

1600 S 4 1200 3 800 2

400 1

0 0 190 180 200 Ju««) day Julian day

Figure 1. Comparison of predicted and observed LAI and above-ground biomass during the crop cycle for each treatment (high andlo winpu t level).

Conclusions The results of the work show that CERES/Sorghum model is able to explain most of the observed variation inphenologjca l dates, yield and other growth variables. However, further studiesan d validations inrelatio n to soil andplan t components of N balance arerequire d toimprov e themode l performance.

References Mariani,G, Donatelli, M, 1983.LTnf . Agr.,39 , 11, 24991 - 24999. Quaranta, F., et al., 1987. LTnf. Agr, 43, 14,3 7- 41. Virmani, S.M. et al., 1989(Eds) . Modeling theGrowt h andDevelopmen t of Sorghum and Pearl Millet. Research Bulletin n° 12.(ICRISAT) . Patancheru, A.P. 502324, India. 454 Book of Abstracts 4th ESA-congress

NUTRIENT BALANCE AT FARM LEVEL FOR CROPPING SYSTEMS IN THE PO VALLEY, ITALY

E. Ceotto, M. Donatelli, R. Marchetti, P. Spallacci

Istituto SperimentaleAgronomico , Sezione diModena , VialeCadut i inGuerr a 134,4110 0 Modena, Italy

Introduction The accumulation of nutrientsi son e ofth e main environmental problems inarea s of intensive farming and livestock activities (Ivense t al., 1992;Loomi s and Connors, 1992). InNorther n Italy planesthi s problem istwofol d duet o the concentration of piglivestoc k and to the high amount of mineral fertilizers often applied. Manure constitutes aseriou swast e problem, duet o the uneven distribution of livestock facilities and suitable crop areas. Aprope r choice ofcro p rotation onth e one hand, and level offertilizer s applied onth e other hand, leadst o more sustainable land use. In order to gain afirs t insight onth e possible environmental sideeffect s of severalcroppin g systems a nutrient balancea t farm levelwa sperformed . Althoughthes e simplified balancesar elargel y incomplete for aprope r quantification ofpollutio n determined byth e systems, they helpi n identifying unacceptable situations.

Methods Acroppin g system trial started in 1993,a t location S.Prosper o (Modena), Low Po Valley, to assess the environmental impact ofcroppin g systems denned byfive cro p rotations and three input levels. The crop rotations compared were: - Sugarbeet-Wheat - Sugarbeet-Sorghum-Wheat - Sugarbeet-Maize-Maize-Wheat - Maize-Maize-Wheat - Soybean-Barley+Sorghumlat e sowing Crop rotations arebot h intim e and inspac e so eachphas e of crop sequences ispresen t every year. Sugarbeet-wheat rotation isquit e common inth e area duet o high income ofth e first crop, but it isno t suitablet o use pig slurry. Theintroductio n ofmaiz ean d sorghum inth e rotation leadst o increased possibilities for spreading animalwastes . The highest input level (A) isth e one often applied byth e farmer, inwhic h mineral fertilizers (nitrogen and phosphorus) are supplied inadditio nt o pig slurry. The reduced input level (B) relieso n pig slurry, mineral nitrogen supply isreduced , and nominera l phosphorus is supplied. Withth e minimal input level (C) only alimite d amount ofminera l nitrogen and phosphorus fertilizers isapplied . Nitrogen and phosphorus content inth e harvestable products and inth e aboveground residues were measured inth eyea r 1994. The animalsar e here considered beingbeyon d theboundarie s ofth e systems, so pig slurry isa n inputjus t likeminera l fertilizers. Crop residues arerecycle d within the systems so harvested products areth e onlyoutput s ofnutrients .

Results Theyiel d levels, and consequently thenutrien t uptake ofth e cropsfo r theyea r 1994, canb e considered onth e average for thisenvironment . Duet o the initial condition ofgoo d soil fertility, the yields obtained from input Cwer e closet o the ones obtained with the higherinputs . Situations ranging from trends ofaccumulatio n to trends of depletion are presented inTabl e 1. Session 2.2 455

Table 1.Nitroge n and phosphorus balances (kg ha'1year" 1) o fth e compared croppingsystems .

Rotation Sugar beet- Soybean- Sugar beet- Maize- Sugar beet- wheat barley+ sorghum- maize- maize- sorghum late wheat wheat maize- sowing wheat

Inputlevel s B B B B B Napplie d Mineral fertilizers 140 80 40 90 58 25 133 73 53 147 90 80 130 78 60 Manure 0 0 0 125 125 0 83 83 0 167 167 0 125 125 0 TotalN(T ) 140 80 40 215 183 25 217 157 53 313 257 80 255 203 60 Crop uptake YieldN(Y) 131 125 122 231 228 220 138 135 122 139 135 107 131 128 109 Abovegroundresidue sN 67 69 76 106 97 73 97 101 93 69 72 49 71 78 65

Tminu sY 9 -45 -82 -16 -46 -195 79 22 -69 174 122 -27 124 74 -49

P applied Mineral fertilizers 55 33 33 44 0 22 52 0 22 44 0 22 49 0 17 Manure 0 0 0 70 70 0 46 46 0 93 93 0 70 70 0 Total P (T) 55 33 33 114 70 22 98 46 22 137 93 22 119 70 17 Crop uptake Yield P (Y) 24 25 28 34 32 22 25 27 27 27 26 22 26 26 24 Aboveground residues P 9 10 9 17 14 8 16 17 13 9 11 7 9 12 9

T minus Y 31 8 5 80 38 0 73 19 -5 110 66 0 93 43 -8

* Negativevalue sfo rthi srotatio nar edu et oN fixed b yleguminou s crop.

Conclusions The amount offertlizer s often applied inth e area (input A)lead st o an accumulation of nutrients for most ofth e cropping systemsunde r study. Areduce d mineral nitrogen fertilization together with no phosphorus fertilization (input B) seemst ob eprofitabl e when manure isapplied . The limited nitrogen fertilization (input C),i fapplie d inth elon gterm , would inevitablylea dt o alowe r levels ofbot h yield and soil fertility. Some ofth e rotations seemt o bea feasibl e possibility for aneco-compatibl eus e of organic manure. The nutrient quantities recycled withinth e systemindicat etha t an alternative use ofcro p residues (i.e. for animalfeeding ) would allowth e distribution ofhighe ramount s ofanima lwastes . Investigations are inprogres s for the quantification ofnitroge n lost byvolatilizatio n and gainedb y rainfall inthi s environment, inorde r to enhanceth eprecisio n ofth e nutrient balances.

Acknowledgements PANDA Project, Subproject 2, Series2 ,Pape rNo .39 .

References Ivens,W.P.M.F . et al., 1992.Worl dFoo d Production. Herleen: OpenUniversiteit , 2:24 7p . Loomis, R.S. and Connor, D.J., 1992. Crop Ecology: productivity and management in agricultural systems. Cambridge University Press, 538p . 456 Book of Abstracts 4th ESA-congress

MODELLING THEINFLUENC E OF CROPPING SYSTEM ON INFECTION CYCLES ANDDISEAS E BUILD-UP FOR EYESPOT

N. Colbach

Station d'Agronomie, INRA, 17ru e Sully, BV 1540,2103 4 Dijon Cedex, France

Introduction Eyespot (Pseudocercosporella herpotrichoides (Fron) Deighton) is amajo r component of the foot and root disease complex of wheat. The fungus infects the stem bases.Th e models presented here,expres s the influence of cropping systems on infection cycles and on disease build-up during wheat growth. They contribute to choosecroppin g systems which minimise disease risk.

Methods The first trial design combined several previous and "pre-previous" crops and two soil tillage tools (one inverting soil,th e second not);i t wasrepeate d on two sites.Th e first site comprised 6 "pre-previous crop*previous crop*soil tillage" combinations in a2-block-design ; the second 4 combinations in a4-block-design .Th e second trial combined sowing date, sowing density, total nitrogen quantity and nitrogen fertiliser form (high vs.lo w ammonium content).Thi s design was repeated on four sites;eac h "sowing date*density*nitrogen quantity*nitrogen form" combination was replicated in a3 o r or4-block-design . On each plot, winter wheat was assessed for eyespot at four growth stages.Fo r each of the 74 "site*cropping system" combinations, the following kinetic equation wasthe n fitted to disease data: , _ 1 e y=percentage ofdiseased plants Cj=importance ofprimary cycle (c + 2) 1 +™ • e~ ' ' " t=sum ofdegree-days since sowing c2=importance ofsecondary cycle Thisequatio n was developed by Colbach andMeynar d (1995).I testimate s disease frequency as afunctio n of thermal time and the importance of two parameters associated toth e primary (from infectious crop residues) and secondary (from living diseased plants) infection cycles for each experimental treatment. For each disease infection cycle,th e following multiplicative model was then tested to estimate parameter value as afunctio n of environment andcroppin g system: £(c,)= EN•(SUxST)'SD" *TPb» N c •NFd (E)

E(Ci) = expected mean of parameter c,=ci or c2 January=end of autumn infection period). EN = effect of environment (=location*year). TP= tillers per plant SUxST = effect of the interaction of crop succession (pre-previous N = total nitrogen (kg/ha)=soil nitrogen + crop, previous crop) and soil tillage (inversion or non-inversion of mineralisation + nitrogen fertiliser soil layers). NF = form of nitrogen fertiliser ( percentage SD =sowin g date (sum of degree-days from sowing to 31s' of ammonium nitrogen).

Results Table 1 presents the significant effects of alinearize d version of equation (E) for parameter Ci; Table 2present s the significant effects of equation (E) for parameter c2.

Conclusion These models contribute tocompar e cropping systems (Figure).The y can also be used to develop cropping systems for which eyespot frequency stays below adiseas e threshold (Table 3) and thus tochoos e the one adapted to agive n set of technical, economic andenvironmenta l constraints:i f late sowing (10/11) ispossible , ahig h nitrogen quantity (and therefore ahig h yield objective) is acceptable. If however early sowing (25/10) isnecessary , the nitrogen amount must be reduced and adecreas e inyiel d of about 2500 kg ha' be expected. Session 2.2 457

Table 1: Model explaining cropping system influence on parameter ct associated with the primary infection cycle of eyespot (estimation of significant effects of equation E).Th e final model is: ln(c,) =constant + ln(EN) + In(SUxST) + a »ln(SD) +b »ln(TP) +c *ln(N) ESTIMATIONS FOR THE FACTOR 'environment' (EN) Environment Chartres A 92 Chartres B 93 Grignon 93 LaVerrièr e 92 Le Rheu A 92 Le Rheu B 93 estimation of effect -2.90 028 L08 ]20 L67 -1.32 ESTIMATION FOR THE COMBINATION 'crop succession x soil tillage'(SUxST) PREVIOUS CROP host lucerne+ray-grass non-host SOIL INVERSION no yes no yes no yes PRE-PREVIOUS CROP host 2.27 0.03 -5.86 -0.46 lucerne+ray-grass 0.81 -0.11 non-host 2.54 0.78 ESTIMATION OF THEPARAMETERS ASSOCIATED TO THE QUANTITATIVE VARIABLES QUANTITATIVE VARIABLE Parameter Estimation Sowing date (SD) 2.53 Tillers per plant (TP) -1.58 Total nitrogen amount (N) 2.60 r2=0,73. All effects presented in this table are significant at alpha=5%.

Table 2:Mode l explaining cropping system influence on parameter c2associate d with the secondary infection cycle of eyespot (estimation of significant effects of equation E).Th e final model is:E(c 2) = EN • TP" ESTIMATIONS FOR THE FACTOR 'environment' (EN) Environment Chartres A 92 Chartres B 93 Grignon 93 La Verrière 92 Le Rheu A 92 Le Rheu B 93 3 estimation of effect 4.18»10~ 3.44.10"3 9.29.104 4.32.10"3 3.60.10 3.27.10 ESTIMATION OF THE PARAMETERS ASSOCIATED TO THE QUANTTATIVE VARIABLES QUANTITATIVE VARIABLE Parameter Estimation Tillers per plant (TP) a 0.102 All values are significantly different from zero at alpha = 5% (multilateral test).

Table 3:Whea t managements Figure:Eyespo t development for various wheat permitting to keep eyespot level managements (A=sowing on 10/10a t 350grains/m 2 and a below 13% of diseased plants total of 300k g N/ha;B=o n 10/10wit h 240 grains/m2 and after anon-host/hos t succession 270k gN/ha ; C=on 10/10wit h 160grains/m 2 and 225k g followed by soil inversion for a N/ha;D=o n 11/10wit h 200 grains/m2 and 225k g N/ha) site favourable toeyespo t (Le % plants witheyespo t 100 Rheu 92) SOWING PLANTS TOTAL 2 • heading : DATE PERM NITROGEN on-set ." (kg/ha) 10/11 201 265 5/11 210 235 30/10 219 205 25/10 228 190

500 1000 1500 2000 sumo fdegree-day s sincesowin g

References ColbachN. and Meynard J.M. 1995. European Journal of Plant Pathology 101: 601-611. 458 Book of Abstracts 4th ESA-congress

MODELLING THE INFLUENCE OF CROPPING SYSTEM ONGEN EFLO W FROM HERBICIDE RESISTANT RAPESEED. PRESENTATION OFMODE L STRUCTURE

N. Colbach1 and J.M. Meynard2

1 Station d'Agronomie, INRA, 17ru e Sully, BV 1540,2103 4Dijo n Cedex, France 2Laboratoir e d'Agronomie, INRA-INAPG,Centr e deGrignon , 78850Thiverval-Grignon , France

Introduction The aim of the model ist o evaluate the influence of cropping systems on transgene escape from rapeseed crops in order to determine thoseregion s with ahig h dispersal risk and to propose cropping systems which limit geneflow . The model isrestricte d to rapeseed crops and volunteers; hybrids between rapeseed and otherBrassiceae areno t integrated.

Model organisation intim e and space Figure 1 shows anexampl e of spatial arrangement with: (a) fields on which various crop types succeed in time; (b) waysides and fieldedges ("borders"). Seven croptype s are distinguished: herbicide resistant (transgenic) or sensitive rapeseed, winter crops, spring crops, set-aside with natural regeneration, set-aside with autumn sown cover crop or set-aside with spring sown cover crop. Before a simulation, acro p and acro ptyp e succession are attributed toeac h plot.

Figure 1:Spatia l organisation of theplot s (E1-E4= fou r cornerso f • '• plot/; H|= borders; I I = fields) - " Crop successions constitute the first level of the temporal dimension. The second temporal level concerns annual rapeseed evolution, as volunteer orcro p plants,o n each plot, of which Figure 2 shows the general organisation. This annual evolution ishoweve r slightly modified according to crop and border types: (a) the compartment sownrape grains onl y exists for rape crops; (b)i n springcrops and springsown set-aside, the compartment adultplants is always nil because rape volunteers emerged after winter dono t haveenoug h time toflowe r before crop maturity; (c)o n set-asidewith natural regeneration and onborders , thepre-sowing grain stock an d thepost- harvestgrain stock ar e identical asn o soil tillage isdon e and thepre-sowing rapeseedlings an d deadgrains compartments areempty ; (d)becaus e of cutting on set-aside plots and borders,no t all the ramifications of an adultplant havetim e toproduc eflowers an dgrains. However , after cutting, adultplants can give rise to asecon d set of ramifications withflowers an d grains.

K 1 . ,. | . | post-sowing seeaimgs j 1 + •post-sowing dead grains '• sown rape grains flowers \"i— i imported pollen j T—-~ tr V L pre-sowing grain stock grains

k pre-sowing dead grains '•. I > • :harvested grains• ir post-harvest grains :pre-sowing seedlings • *__^\ l-L *: exported grains

Figure 2: Tempo rai organisât ion of annual rapeseec evolution imported grains Session 2.2 459

Relationship between temporal compartments For each compartment (grain stock, seedlings...) thenumbe ro findividual s per m2an d the proportions of each genotype arecalculated . Herbicide resistant and sensitive plants only differ in their response to the associated herbicide and inthei r fitness, i.e. the number ofviabl e descendants ofth e resistant phenotype compared toth e descendants of the sensitive phenotype. Inth ecompartmen tpost-harvest grain stock, grains aredistinguishe d according tothei r agean d their situation (superficial or deep layer).Grai n mortality depends on grain age,soi l layer and crop type.Th e grain movements between post-harvest and pre-sowing stocks depend on soil tillage asmodelle d by Cousens &Mos s (1990). Only grains from the superficial layer give riset o seedlings. Emergence rates depend on grain age,o ncro p type and, for pre-sowing emergence,o n stubble breaking. All pre-sowing seedlings aredestroye d when the soil istille d for sowing. The relationships between seedlings and adults,flower s and grains depend on rape density, herbicides (and therefore on rapephenotype) , crop density andcuttin g date.O n set-aside andborders , those plants having survived cutting can produce post-cutting ramifications. Genotype proportions of the new grains depend on parent genotype,fitnes s andth e rateo fallogamy . Pollen and grain dispersion are modelled by functions established by respectively Reboud etal. an dGasque z etal. (pers.comm.) .Bot h functions depend on plot co-ordinates (xi, x2,yi , y2).Grai n exportb y harvest tools only happens for rape crops.Afte r the simulation ofth e various stageso fyea rn, new values are attributed to the grain stock variables for year n+1.

Simulation Parameters were chosen according to literature (Leterme, 1985;Cousen s &Moss , 1990; Schlink, 1994) while awaiting trial results. Several kinds of output arepossible . Figure 3show s for instance the evolution ofresistan t and sensitive individuals (grains, seedlings, adults etc.) ona given plot with time whereas Figure4 presents the mean numbero fresistan t and sensitive grains for all plots over awhol e rotation. grains/m2 grains/m2 10000 r 4000 Allfield s Held 10 Figure4 :Mea n numbero fresis ­ m< A 3000 7500 tant (H) ^ sensitive( | |)

It In '1 n R '1 2000 grainsove ro f2 5 5000 IMM i MM M yearswit ha "set - i 1i MMM aside/rape/winter MMM 1000 * M MIM crop/springcrop / 1 i MM ' rape/wintercrop / 1 1• 1/ ' 1 I /' /' V' V u springcrop " rota­ V' VI V' Si tion (A=resistant rape on field 10an d sensitive 0 5 10 year 15 20 25 rape on all other fields and natural regenera­ Figure 3:Tota l ( )an dresistan t (—)rap e tion set-aside;B=resistan t rape on field 10an d grains ofth e post-harvest stock on field1 0 sensitive rape on all other fields and spring with a"regeneratio n set-aside/resistant rape/ sown set-aside; C=sensitive rape everywhere winter crop/spring crop/resistant rape/winter except every three times onplo t 10an d natural crop/spring crop" rotation regeneration set-aside). References Cousens, R. and Moss, S.R., 1990.Wee d Research 30:61-70 . Leterme, P., 1985.Thès eDoctora t del'Institu t National Agronomique Paris-Grignon, 112 p. Schlink, S., 1994.Dissertatione s botanicae 222,Berlin , 193 p. 460 Book of Abstracts 4th ESA-congress

RESPONSES OF WINTER WHEAT AND MAIZE TO NPK NUTRIENT LEVELS IN LONG-TERM FERTILIZATION TRIALS

K. Debreczeni

Pannon University ofAgricultura l Sciences, P.O. Box 71. H-8361Keszthely , HUNGARY

Introduction Long-term fertilization trials can provide reliable data for the wider understanding of crop- nutrient interrelations. There are several long-term fertilization trialsi nHungary ;th e results presented here arefrom th e network of National Long-term Fertilization Trials(NLFT ) which havebee n continued at 9 experimental sites. Thesetrial swer e established in 1967-69.Apar t from sitecharacteristic s which showthemselve s in yield levels, long-term (25-27years ) effects of fertilizer treatments directs our attention to differences in crop responses. Yield results showed that winter wheat responsest o phosphorus deficiencies were stronger than that of maize(Debreczen i and Debreczeni, 1994).

Methods Long-term effects of 10fertilize r treatments on grain yields ofwinte r wheat and maizewer e studied in multilocationfield experiment s (plot sizewa s 50-70 m2)a t 9 agro-ecological regions in four-year rotations of wheat-maize biculture. Crop rotations were initiated over asuccessiv e four year period alter 1967. Nitrogen fertilizer rateswer e gradually increasing by 50 kgpe rh a Nfro m 50t o 150,phosphoru s rates from 0 to 200k g P205 per ha and potassium rateswer e 0, 100an d 200 kg K20 per hectare. Codenumber s indicating the fertilizer rates are given inth e order of NPK. Fertilizer treatments given inthes e codenumber sselecte d for thisstud y were as follows: 000, 101,201,301, 111,211,311, 121,221 and 321. Evaluation oflong-ter m effects wasmad e by calculating the main averages ofgrai nyiel d results obtained for winter wheat and maize in each experimental year. Main averages ofyield swer eplotte d aszer o points and average differences obtained for individual treatments ascumulate d values aregive n inth efigure indicatin g either positive or negative values. These averages ofwinte r wheat and maize grain yields aregive n as 0value s of the x axis. The graphs are representing responses ofwinte r wheat and maizet o increasing fertilizer rates in the long-term scale i.e. after 4-8-12-16-20years . One experimental site, Bicsérd was selected for thispresentation . This experimental sitei s located in south-west of Hungary and hasa chernozem brown forest soil, FAO category: Luvicphaeosem . Main soil characteristics ofth e experimental soil are asfollows : Humus content 1.9 percent, pH in KCl 5.6, availablephosphoru s ( in AL-extract) 35 nig kg' P20?, exchangeable potassium (in AL-extract) 206 mgk g "' K20.

Results Main averages of winter wheat and maize obtained in the four year rotations inth e selected experimental site, Bicsérd are represented here. The main averages of grain yield resultswer e as follows: winter wheat 3.88 - 3.70 - 3.58 - 3.78 tons per hectare maize 7.12 - 6.97 - 7.0 - 9.55 tonspe r hectare, respectively. These main averages were plotted as 0 values ofth e x axisi n the graph (Figure I). Differences obtained for the individual treatments ascumulate d grain yield results(i n tonspe r hectare) ofwinte r wheat and maize aresummarize d inth eFigure . Session 2.2 461

Figure 1.Cumulate d grain yields of winter wheat and maize (tonspe r hectare)

Ü I CS (. R Ü

winter wheat maize

t/hn

From these results it can besuggeste d that adequate soil phosphorus leveli sa determinating factor in winter wheat yield. The observed crop responsest o phosphorus deficiency or nutrient imbalances could be reduced by Napplication , however, differences were stillremarkable .

Conclusions Cumulated yield differences are effectively representing crop responsest o long-term fertilizer effects. Responses ofwinte r wheat to balanced macronutrient fertilization were much stronger than that ofmaize . Thiswa s especially remarkable in case ofphosphoru s responseswhic h isrelate d to the formation of grain proteins. Increasing Nfertilize r rateswithou t P application markedly reduced grain yields of winter wheat but only moderate responsest o Pnutrien t imbalances were observed for maizeyields . Differences inyiel d responses were even marked inth e subsequent years, therefore it can be concluded that long-term effects may serve asmor e reliable information on crop responses for soil fertility evaluation.

References Debreczeni, B. and Debreczeni, K. (Eds.) 1994. Fertilization Research 1960-1990.Akadémia i Kiadó, Hungary. 411p . 462 Booko fAbstract s4t hESA-congres s

THE USE OF POROUS CUPS TO ESTIMATE THE IMPACT OF CROPPING SYSTEMS ON GROUND WATER QUALITY

J-E.Delphi n

INRA, Laboratoire d'Agronomie, B.P. 507,6802 1 COLMAR, France

Introduction Duet oth elarg eamount so ffertilize r andagrochemical suse di nintensiv eagriculture ,i ti simportan t toestimat e thequantit y ofpollutant s lost byleachin g andth econsequen t risks of ground water contamination. Theliqui dphas eo f soilsi susuall y collected from drainage water,fro m lysimeters, from bore-holes orfro m vacuumextractor s (porous cups).Thi slas t sampling method of the soil solution isvaluabl e becausei tca n beuse di n alarg erang eo f soiltype sexcep t for coarse textured ones.However ,rathe r largevolume so fwate rhav et ob ecollecte d for pesticide determinations.Th e aimo f thispape r ist oexamin eth epossibilitie s andth elimit so f theus eo fporou scup s for estimating nitratean datrazin elosse sb yleachin gi nth e field.

Methods Theexperimen t wascarrie d outi nth eRhin eplai n ona far m plotcroppe d with maize.N fertilize r (60 kgha" 1) and herbicide(atrazin e+ alachlore ,62 5an d240 0g ha' 1respectively ) wereapplie d atth e timeo fmaiz e sowing.A secon d application ofN (12 0k gha" 1) wasmad e onemont h later (25/05/95). 250 +67 5g ha" 1o f the sameherbicid e wasapplie d onJun e 1st.Th etota l rainfall plus irrigation was29 0m mfro m thebeginnin g of theexperimen t (06/06/95) toth een d of December. The experiment wasconducte d on aloam y soil :2 7 % clay, 68 %silt , 5 %sand , 1.8 % OM,p H7.5 . Theporou s cupswer einserte d horizontally at3 depth s (50,80,12 0 cm)fro m api tdu gi n the ground andrefille d after installation.The y wereconnecte d bya Teflo n tube (0 2mm )t oa 21 collectorplace d on the ground. A6 5k Patensio n wasapplie d for awee k :th eextracte d volume was measured and thenitrat ean datrazin econcentratio n weredetermine d onth ewate r samples.Th esoi l moisture wasmeasure d weekly byneutro n scattering. Atrazinei n the solution samples wasdetecte d byHPL C after extraction by C18-cartridges.Nitrat econcentratio n wasdetermine d bya spectrophotometricmethod .I tha dbee n showntha tn ointeraction s occurred between atrazine and theporou s cup (Perrin-Ganier et al., 1994).

000 -• 31.5 t^000*— ~+ o > Ä^——— ^ 30.5 *__^JW • -50cm c 2 o .—••""• • R = 0.40 ^ 29.5 u I 28.5 1 1 h 1 Figure1

20 40 J , 60, ,x 80 100 Mean volume of extracted volume(ml ) the soil solution ^34.5 extracted by the porous cups

400 600 800 1200 extracted volume(ml ) Session 2.2 463

Results Thevolum e of the soil solution collected inth e porous cups varied from 0t o 1200ml . The variation in the collected watervolum e between theporou s cups located atth e same depth was likely duet oth e difference of themacroporosit y ofth e soil closet oth eporou s ceramic andt oth e tightness of contact, although this contact was previously improved by putting mud on the bottom ofth e holebefor e the insertion ofth eporou s cup.Th evolum e of soil solution collected was related toth e soilwate rcontent . Thevolume s at 50c mwer e small (figure 1)becaus e ofth elo w water content throughout the experimental period ofth e soil layer which had ahig h water holding capacity (37vol . %). At 80an d 120c mth e amountscollecte d averaged 600 ml because ofth e higher soil water content inthes elayer san do fth e lowerwate r holding capacity ofth e soil (34vol . %). Themea n efficiency ofth e soil solution extraction was 30% . 20.0

15.0 Figure2 .Atrazin e M iu.10.u0 I - - A' * * contenti n thesoi l ^ n lf~l » P solution at 80cm (each symbolrepre ­ sents aporou s cup) —^—n&. H , 1 05/06 05/07 04/08 03/09 03/10 02/11 02/12 Date Thevariatio n in theN0 3 content of the soil solution between thedifferen t porouscup s washighe ra t thebeginnin g of theexperimen t (CV=25% )tha n atth een d (CV< 10%) , probably because ofth e heterogeneity of theN fertilize r application toth esoil .Th evariatio n inth eatrazin econten twa s highertha n for nitrate (figure 2) : byreaso n ofth eminimu mvolum eo f soil solution required for the pesticide analysis,th enumbe r ofduplicate d measurements wasno t sufficient for reliable statistical analysis. Contrary toth eresult s obtained by Hausen etal .(1975) ,th e N03 solution content was not dependento n theextractio n efficiency ofth eporou scu p buto nth e timean do nthei rpositio n inth e soil.

Conclusions Theefficienc y of waterextractio n byth eporou scu pwa slargel yrelate d toth e soilwate rconten t and probably toit scontac t with the soilan dth emacroporosit y of thesurroundin g material (presenceo f cracksan d soil spaces).A slightl ylowe refficienc y wasobtaine dwit hth emetho d usedi n this experiment (horizontally buriedporou scups ) incompariso n toth eclassica lmethod , but this technique allows allth ecroppin g operationst ob edon ei nth efield . Aminimu m number of 8-10 replicates isthe nnecessar y inorde rt oestimat eth epollutant s inth e soil solution with an acceptable precision (especially thepesticides) .Th eporou scup smus tb eplace d ata dept h where the uptakeo f water by thecro pdoe sno tlowe rth e soil moisture significantly below thewate r holdingcapacity .A t 50c mth ewate rvolume scollecte d wereofte n insufficient forpesticid eanalysis .I n order to estimate the amountso f pollutantslos tb yleachin g undercroppe dplots ,th eminera l Nan dpesticid e content of the soil solution sampled byth eporou scup sha st ob elinke d with theestimatio n of drainage water amounts usinga wate rbalanc emodel .

References Hausen, E.A., 1975.Soi l Science Society of America Proceedings. 39 :528-53 6 Perrin-Ganier, G. et al., 1994.Chemospher e2 9 :63-70 . 464 Book of Abstracts 4th ESA-congress

MAIZE PRODUCTION IN A LIVING GRASS MULCH SYSTEM

S.V. Garibay, B. Feil

Institute of Plant Sciences, ETHZ, CH-8092 Zurich, Switzerland

Introduction The midlands of Switzerland are characterized by a hilly topography and a cool, humid climate (= 1000 mm annual preciptation). The traditional cropping of maize (= maize sown in the bare, autumn-ploughed soil) is often associated with soil erosion, surface runoff of agrochemicals and nutrients, and nitrate leaching into the groundwater. Further problems linked to this maize cropping system are soil compaction and the development of herbicide- resistant weed populations. Most of these problems can be solved or at least alleviated if the maize is sown into a live cover crop sod. This contibution reports results of a three year field study (1991 to 1993) on the performance of silage maize under two cropping systems in which the maize was sown into living Italian ryegrass sods.

Methods Three maize cropping systems were compared: (1) maize sown into the autumn-ploughed, bare soil (plough tillage; PT); (2) maize planted into a live Italian ryegrass stubble. The grass strips between the maize rows were killed by applying a herbicide (chemically killed grass; CKG), and (3) maize planted into a live Italian ryegrass stubble. The grass strips between the maize rows were mechanically stunted by mulching (= mechanically suppressed grass; MSG).

The Italian ryegrass (Loliummultiflorum L. ) was sown in the August preceding the planting of maize. The grass was mowed and removed from the CKG and MSG plots in autumn and spring (6 to 13 d prior to planting the maize). Under PT, the grass stands were also cut in October and ploughed in autumn/winter with a mouldboard plough. The maize was sown with a one-pass minimum strip tillage seeder. The maize rows were 75 cm apart. The rototilled strips were 30 cm wide and 15 cm deep. In the CKG system, the grass strips between the maize rows were killed by a split application (2 x 30 g ha"1) of the herbicide Titus at the 1st and 2nd leaf stages of maize. In the MSG system, the grass was mulched with a mulching machine at the 1st, 3rd, and 6th leaf stages. There were two levels of nitrogen (N) supply: 110 kg N ha'1 (N110; mineral N in the soil from 0 to 90 cm depth as measured just before maize sowing plus row placed fertilizer N) and 250 kg N ha"1 (N250; as N110 plus two banded applications of 70 kg N ha"1 at the 4th and 6th leaf stages of maize). Maize samples were collected when 50% of the PT-treated plants had reached the 3rd, 6th, and 9th leaf stages and at pollen shedding and silage maturity. Leaf chlorophyll content was estimated with the SPAD 502 instrument from Minolta. Meter readings were taken on the uppermost fully expanded leaf, midway between the butt and tip and between the leaf margin and midrib.

Results and Discussion Despite large year-to-year fluctuations in the availability of water, the relative performance of the cropping systems was fairly consistent in the various years (Fig. 1). With N110, averaged across the years, the CKG system produced only 69% and the MSG system only 47% of the maize dry matter produced under PT. Sod-planted maize was markedly more responsive to an increase in the rate of N application than PT maize. Nevertheless, with N250, PT was still the most productive system: averaged across the years, maize grown in the CKG and MSG systems produced 94% and 85% of the dry matter that was produced under PT. The data Session 2.2 465 suggest that, with NI10 , N was more yield-limiting for sod-planted maize than for PT maize, even though additional N (on average 56 kg N ha"1) was applied to the CKG and MSG systems in order to set off the low mineral N content of the soil immediately prior to maize sowing. The seasonal patterns of some indicators of the N status of plants (leaf greenness and whole-plant concentrations of nitrogen and nitrate) under N110 in one representative year (1992) demonstrate that differences in the N status of conventionally cropped and sod-planted maize are already detectable at early stages of development (Figs 2a-c).

25 N110 1991 1992 20 N250

a 15 I

10

5

PT CKG MSG PT CKG MSG PT CKG MSG Fig 1. Shoot dry matter of silage maize under three cropping systems and two levels ot'N supply. Bars indicate LSD (0.05) values within the levels of N supply (a = LSD for Nl 10;b = LSD for N250).

Nitrogen concentration(%) Nitrate concentration (%) SPAD - ' l 1 ' 1 ' 1 - 0.9 5.25 a

4.00 - 'V - 0.6

2.75 i

\ i 0.3 1.50 4-, rV_ i —

0.0 0.25 " i 1 i , i , i - J i I . L_i L 300 600 900 1200 300 600 900 1200 300 600 900 1200 Growing degree-days [° Cd ;bas e temperature 8 °C]

Fig. 2. Cropping system effects on shoot nitrogen concentration (a), shoot nitrate concentration (b), and leaf greenness (c) under Nl 10. Vertical bars indicate LSD (0.05).

Conclusions The living mulch systems tested have markedly higher N requirements in order to reach maximum yield. Efforts to optimize these environmentally sound systems should focus on reducing the competition between maize and the cover crop for N. Promising approaches are the use of legumes as cover crops and an earlier suppression of the cover crop. 466 Booko fAbstract s4t hESA-congres s

INTRODUCTION OFA CATCH-CROP OFSOYBEA N INA BIENNIA L ORIENTAL TOBACCO -DURU M WHEAT ROTATION P. Greco, G.Manz i Istituto Sperimentalepe r ilTabacco ,vi aF . Calasso 3, 73100Lecce , Italy

Introduction Thecultivatio n oforienta ltobacco s islargel y praticsed incertai nmargina l areaso f Puglia, Southern Italy. Thehot , dryclimat eo fthes e areas, combined with poor and shallow soils,ar e unfavourable conditions for other crops. Therefore, at thispresen t time,tobacc o represents the onlysourc eo fincom efo r the localpopulation ,whic htraditionally , has always supplied abundant manuallabour . Thisrealit yha sle dt o the consolidation ofa cultivation systembased , either on continuous cropping oftobacco , or onbiennia lrotatio n oftobacco-duru m wheat, with negative effects onth e healthan d fertility ofth e soil(Rüssel , 1982;Toderi , 1991). Theseobservation s relatet o the results of6 experimentalyear s (1986-1991), and concern comparisons madebetwee n traditional biennialtobacco-duru m wheat rotation, andth e same rotation intensified with soybean catchcrop . Theai mo fthes etrial swa st o limitth e negative effects causedb ytire d soil, and atth e sametim e to investigate anylikel ypositiv e agronomic consequences onth etw o maincrops , duet o the effects ofintroducin gth e catchcrop .

Methods The experiment was conducted inth eyear s from 1986t o 1991a tMonteron i diLecc e (Lecce),o n a sandy soilbelongin gt o Haploxeralf family (Costantini etal, 1990). Twobiennia l rotations: tobacco-durum wheat andtobacco-duru m wheat+soybean (T-F and T-F+Sa), were compared in interactionwit htw o agrotechnic inputtreatment s (MA=mediumhigh ;MB=mediu m low, different infertilization , irrigation and soilmanagement ) ina split-plot designwit hthre ereplications . Theelementar y plotwa s 165squar emeters . Theclimati c environment ischaracterize d byhot-dr y summers andrainfal l restricted to the fall- winter period.

Results Thevariabl eclimati c conditions ofth etria lperio d exercised anotabl e influence on productive and commercialtobacc o parameters,bu t inopposit eways . Infact , whileth e production ofcure d tobacco (16%moisture ) diminisched inrelatio nt o theho t and dryyears , to aminimu m of 1,521 ha"1reache d in 1988,th e percentage ofleave s ofth ehighes t commercial value, (grade A+B) notably improved, with amaximu mrecorde d inth ethir d year, at aleve l of41,8 % ofA+B . Theabov edemonstrate stha t hot and dryyears ,if , onth e onehan d inhibit production, onth e other hand favour sun-curing processing,wit h positiveconsequence s ontobacc o quality. Statistical analysisindicate stha t theinteractio n "rotation x input levels"(figur e 1)i sdu e principallyt o the positive effects which occurbetwee n inferior input and rotation intensified with soybean. Betweenth e rotations compared, the oneintensifie d with soybean showed significantly superiorproductio n results, (+6%)whe n compared withtraditiona l rotation (1,841 ha") i nth e mediumlo winput streatment . Between agrotechnical levelslarg edifference s emerged (P=0,05), infavou r ofth e higherleve l(MA=1,91 1 ha"1; MB=1,65 tha" 1). Session 2.2 467

J

2

Figure 1.Interactio n "rotation x levelso f MA MB agrotechnical input" onth e production agrotechnical input oriental tobacco (16%DM )

Concerning durumwheat , significant production differences were recordedbetwee nth e two agrotechnical levels,wit hmor efavourabl e effects noted atlowe r mediumleve l(MA=3,30 1 ha"1; MB=3,501 ha"1). Asi nth e case oftobacco , the significance ofth e interaction "rotationsx level s ofagrotechnica l input" ist o benoted , indicatingtha t thebes t combination occursbetwee n the lowermediu mleve lan dth erotatio n intensified with soybean.

Conclusions Greater production potential introduced intotraditiona ltobacco-duru m wheat rotation, through the addition of soybean catch crop,beside s determiningpositiv e variations inbot hth e two principle cropsrotated , also contributest o thegros s saleable production ofth e entire rotation. Tobaccobenefitte d from theresidua l nutrients left by soybean, increasingth e production ofcure d leaves,whil eth e lower agro-technical levelimprove d the commercial characteristics and therefore manufacturing use.Regardin g durumwheat , thepresenc e of soybean greatly increased the effect ofth einferio r agrotechnical level,thu sgivin grise t o better production results comparedt o the higher level. Aboveall ,th e research underlined the agronomicvalidit y ofth e newrotatio n (T- F+Sa),which , ifonl ywithi nth elimitation so fth etria lperiod , seemst o producebette rresults , with reduced agronomic input, thus obtaining economic and energy resource advantages at lower levelo fenvironmenta l impact.

References Costantini,E.A.C . et al., 1990. Studio pedologico dialcun e aree sperimentali delnord , centroe sudItalia . AnnaliIstitut o Sperimentale Agronomico, XXI, Suppl.2 ,255-288 . Rüssel, E.W., 1982.I lterren o el apianta .Fondament i diagronomia .Edizion e italiana acur a diP . Paris,Edagricole ,Bologna , 564p . Toderi, G., 1991.Problem iconservativ i del suoloi nItalia .D aAgricoltur a eAmbiente , Edagricole,Bologna , 50-99. 468 Book of Abstracts 4th ESA-congress

THE ROLE OF MULCHING IN CROPPING SYSTEMS - SYNCHRONIZING THE RELEASE OF NUTRIENTS AND CROP REQUIREMENTS

F.C.T. Guiking and D.M. Jansen

Department of Agronomy, Wageningen Agricultural University, PO Box 341, 6700 AH Wageningen, The Netherlands

Introduction In scenarios for sustainable agriculture, mulch usually is given an important role; quantification of the effects is less clearly stated (Guiking and Stomph, 1995). The recycling or net input of nutrients through mulch is relatively easy to quantify. But a simple nutrient balance on an annual base can be misleading, even under a permanent cropping system, since release of nutrients from mulch is not synchronized with crop requirements. An example is given from the perhumid Atlantic Zone of Costa Rica, where palm heart is grown, a crop that is monthly harvested with concomitant production of leaf mulch. The cyclic fluctuation of the yield results in a cyclic, a-synchronic fluctuation of supply of recycled nitrogen, part of which is lost by leaching. The resulting situation is less favorable than predicted by a scenario where nutrient budgets are calculated on an annual base.

Methods Palm heart (Bactrisgasipaes HBK) is planted at 1 m x 2.5 m (4,000 plants ha '). Several shoots are maintained per plant. Under standard production practices the field receives a mulch of leaves from the crop at monthly harvests of growing points. The following differential treatments were included to quantify the effect of mulch on crop performance: removal of mulch, standard practice (i.e. leave the pruned leaves at the spot), and double the amount (pruned leaves from zero-plots added to these plots). To moderate the effect of removal of mulch concerning export of nutrients, treatments with N-fertilizer were included, viz. standard practice (being 6 applications of 33 kg N ha"1 yr"1), half the amount, and nil. Other nutrients (P, K, Mg) were added at standard plantation rate. Plot size was 5 m x 12.5 m (5 x 5 plants). All treatments were replicated 4 times in a randomized block design (total 36 plots). Monthly yield of palm hearts was recorded for 2 years. Leaf mulch produced was recorded at some selected plots at regular time intervals, and sent for chemical analysis.

Results The average annual production per hectare is about 18,000 palm hearts of about 1.1 kg fresh weight each; with 11%dr y matter this comes to a dry matter production of 2.2 t ha"1. The removal of nitrogen through the harvested product is 40 kg N ha_1 yr"1. The harvest of each palm heart is accompanied by the cutting of 0.7 kg (dry weight) leaf material, left as mulch. Since palm hearts are harvested at a given size, mulch production per harvested palm heart is fairly constant throughout the year. The return of nitrogen through this mulch amounts to 360 kg N ha"1 yr1, but monthly contributions vary from 15 to 50 kg N ha"1.

The experiment was laid out in an existing plantation which was heterogenous. After two years this still showed up in clear block effects. Variation within blocks could mask the effects of treatments; therefore the cumulative yield of the last 1.5 year was expressed as percentage of the cumulative yield of the first 4 months of the experiment. In this way a positive effect of N-fertilizer on yield was observed, in concordance with earlier experiments with this crop (Jongschaap, 1993; Roeland, 1994). Session 2.2 469

No effect of mulch on yield was observed, although the quantities of nitrogen involved are twice as high as those supplied through inorganic fertilizer.Th e explanation is sought in the cyclic character of the yield (in figure 1expresse d in number of palm hearts harvested per month), resulting in a cyclic production of leaf mulch.

The uneven distribution of mulch in time, results in an uneven supply of nitrogen in time, and - with the time lag due to decomposition - not geared to the requirements of the crop. The latter will show the same cycle, but some time ahead. Under the assumption that uptake of nitrogen by the crop is one month ahead, and that release of nitrogen from the leaf mulch is one month after application of the mulch, the resulting situation can be represented schematically as in figure 2: in some months release of nitrogen from the mulch is insufficient to meet crop requirements; but where more nitrogen is supplied than needed, losses through leaching are inevitable in a perhumid climate.

< 3000 \ | 60 cr Q_ \ r / \ Z / 'l /X 40 < 2000 \ \ X ', S / / \ \ / f --A 5 • < . / \ / *"--* 20 1000 o \/ or r ï1 Ï/ / w CO V 0 D 2 0 MAR SEP APR OCT MAR SEP APR OCT uptake of N by crop, kg/ha

-e- release of N from mulch, kg/ha

Figure 1 - Monthly yield of palm hearts, Figure 2 - Uptake of N by crop and nr ha"1 release of N from mulch, kg ha1

Conclusions Release of nutrients from mulch is not synchronized with crop requirements. Even for situations with a permanent crop cover, calculations of nutrient cycles at field level should not be based on annual data, but include the regular temporal variability. A consequence for practical purposes is that regular split-applications of fertilizers should be adjusted to the regular temporal variations in crop requirements and recycled nutrients.

References Guiking, F.C.T., and T.J. Stomph, 1995. The modification of soil processes by mulching in the humid tropics. In: Cook, H.F., and H.C. Lee. Soil management in sustainable agriculture, Wye College, University of London, p.383-386. Jongschaap, R., 1993. Palmito (Bactrisgasipaes HBK ) growth and management in the humid lowlands of the Atlantic Zone of Costa Rica. CATIE/AUW/MAG Phase 2, Report 60. Roeland, R., 1994. Palmito (Bactris gasipaes HBK) cultivation in the Atlantic and Northern Zone of Costa Rica. CATIE/AUW/MAG Phase 2, Report 86. 470 Book of Abstracts 4th ESA-congress

SOYBEAN YIELD AND CANOPY WEED INFESTATION UNDER DD7FERENT CROP ROTATION SYSTEMS (INTRODUCTORY INVESTIGATIONS)

M.Jedruszczak ,M .Wesotawsk ian dK .Buja k

Department Soilan dPlan t Cultivation,Agricultura lUniversity , 20-950Lublin , 13Akademick a Str., Poland

Introduction Soybean isbecomin g an important alternative cultivated plant inPoland . This is mostly due to good newpolis hcultivar s(Szyrmer , 1987; Konieczny et al., 1991) and rising new nutritional preferences of the society. Experiments on soybean growth with spécialiste crop rotations help to understand yield limiting factors and determine economic and habitat profits in Poland. Early soya was considered to yield well in monocultural system (Pendelton et al., 1973; Kahnt et al., 1985). Recently, however, higher productivity andothe rbenefit s resultingfrom inclusio n ofth eplan tint o croprotatio n havebee n appreciated (Johnson 1987; Clegg, 1992; Varvel et al., 1992; Lund et aio., 1993). This work was aimeda tevaluatio n of yield andwee dproblem so fsoybea ngrow ni nfour-fiel d rotationsystems .

Methods Fieldexperimen twa sestabishe d in 1993a tCzeslawic eExperimenta l Station (central-eastern Poland, 51° 19'N ,22 ° 16'E )o ngrey-brow n podzolicsoi lderive dfro m loess(1.3 0% o fhumus ,2 6m gP2O5 , 28m gK 20 and7 m gM gpe r 100g o fsoil ,5. 4pH )Th eexperimen twa slai dou ti na randomize d blockdesign . Soybeancv .Pola n(00 0mat .group )wa sgrow ni nfour-fiel d rotations:1-25% , 11-50%, ni-75%, rV-100%o fthi scrop . Sequenceo fplant si nth erotation swa sfollowing : I. potato-spring wheat-soybean-winter wheat;JJ .soybean-sprin gwheat-soybean-winte rwheat ;III . soybean-soybean- soybean-winterwheat ;IV .soybea nmonoculture . Thesoi lwa stille dconventionally . Soybeanwa s 1 1 fertilized with3 4kgN , 80k gP 205,an d 100k gK 20ha' .Farmyar d manure(3 000 0k gha" )wa s appliedt o everyfirst field o frotation ;al lfields wer elime dwit h250 0k gha" 1 CaOi n 1993.Soybea n was sowni nro w spacingo f2 0c ma tth een do fApri lan dth ebeginin go fMa yi nth eamoun t providing 100viabl esee dpe r 1 m2.Th eseed swer einoculate dwit hRhizobiu mjaponicum .Linuro nplu s metribuzin (500plu s35 0g ha" 1)wer euse dfo rwee dcontro lfollowin g thesowing . Soybeangrowin g seasoni n 1994wa sextremel yunfavorable : coolan dhumi dunti lth efirst hal fo fJune ,late r -ho tan d dry.Drough t lasted 60day san dcoincide d withreproductiv egrowt h stageso fsoybean ,R1-R 7(Feh r etal. , 1980).Growin g seasono fsoybea ni n 1995wa swar mwit hrain-fre e period of4 0 days from whensoybea nwa sformin g seeds(R5 )onwards .

Results Resultsar epresente d inTable s 1-3. Table 1. Seed yield, yield structure, nodulation, and plant densityjus t before harvesting (aver.1994-1995 ) Crop rotation Seedyiel d Pods 1000 seeds Nodule num­ Plant (soyabean %) (tha-1) number weight (g) ber per plant density per plant (m-2) I. (25) 1.74 13.4 115 0.4 81.5 II. (50) 1.84 14.1 119 0.9 77.8 III. (75) 1.92 15.2 118 4.0 73.0 IV. (100) 1.68 13.3 116 4.4 77.6 LSD(p=a0.05)acc . ns ns ns 2.5 ns Tukey Session 2.2 471

Table 2. Variability of seed yield, yield structure elements, nodulation, and plant density before harvesting inth e research years, 1994 and 1995 Crop Seed yield Pods number 1000see d Nodule number Plant density rotation (tha •1) perp i ant weight (g) perp i ant (m-2) 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 I. 1.04 2.43 10.9 16.0 104 126 0.3 0.6 71.0 92.0 II. 1.07 2.62 11.2 17.0 106 132 0.3 1.5 70.8 84.8 III. 1.15 2.68 12.0 18.3 104 132 1.5 6.5 70.2 76.0 IV. 0.98 2.37 10.2 16.4 104 127 1.3 7.4 67.2 88.0 Mean 1.06 2.52 11.1 16.9 104 129 0.8 4.0 69.8 85.2 LSD(p= 0.22 1.5 5.0 1.3 4.2 a 0.05)* *Acc. Tukey

Table 3.Number and air dry matter ofweed s in soyabean canopyjus t before harvesting Crop Weed number m"2 Air dry matter (gm~2 ) rotation 1994 1995 mean 1994 1995 mean I. 21.7 11.3 16.5 10.5 8.1 9.3 II. 19.8 9.4 14.6 7.0 5.6 6.3 III. 18.0 6.5 12.2 7.2 5.9 6.5 IV. 21.4 10.2 15.8 13.2 8.6 11.0 Mean 20.2 9.4 - 9.5 7.0 - LSD(p= 0. 3 ns ns ns a 0.05)* *Acc. Tukey

Conclusions Yieldo fsoybean ,grow ni nrotation so fincreasin gcontributio no fth ecro p (25%, 50%,75% » and 100%)di dno t differ statistically inth efirs t twogrowin gseason s(aver . 1994an d 1995).However , a tendencyfo r thehighes t seedyiel d andit sstructur eelement swa sobserve di nrotation swit h 50% and 75% ofsoybean . Significant increaseo fnodul enumbe rwa sfoun d inrotation swit h 75% and 100% of soybean(Tabl e 1).Long-lastin gdrough ti n 1994ha da substantia lnegativ einfluenc e onal l yield elementsstudie d (Table2 )an dwa sconduciv et oa nincreasin gwee dnumbe rpe runi tare a(Tabl e3) . Weedinesso fth esoybea ncanop ywa sth esam ei nal lrotation s(mai nwee d specieswer eEchinochloa crus-galliP.B . andEquisetum arvense L) . Completeevaluatio n ofth eeffec t ofth e thecro protatio n systemso nsoybea nyieldin gneed sfurthe r studies.

References Clegg, MD.,1992 . Agricultural Systems 39 (1):25-31. Fehr, W.R.et al., 1980. Special Report 80.E SIow a St. Univ., p. 11. Johnson, R.R., 1987. Soyabeans: Improvement Production and Uses.Agronomy 16:374-378 . Kahnt, G. et al,1985. Eurosoja 3:17-23. Konieczny, G. et al.,1991. Eurosoya 7/8:63-67. Lund, et al.,1993. Journal ofProductio n Agriculture 6(2):207-213 . Pendelton, J.W.et al.,1973.Soyabeans:Improvement Production and Uses. Agronomy 16:211- 237. Szyrmer, J., 1987.Bulleti n ofPan t Breeding and Acclimatization Inst. 164:25-35. Varvel, G.E. et al., Agronomy Journal 84(2):215-218 . 472 Book of Abstracts 4th ESA-congress

THE INFLUENCE OF THE COVER OF DIFFERENT CULTIVATED PLANTS ON THE GROUND WATER RESERVE (1981-1995)

J. Kolodziej, K. Liniewicz

Department of Agrometeorology, University of Agriculture, ul. Akaderaicka 15, 20-950 Lublin, Poland

Introduction In natural conditions and also canopies of cultivated plants there is a constant interaction between the plants cover and the microclimate in those canopies, and the microclimate in the soil. The aim of our paper was to establish the influence of the diverse plant cover and of the weather conditions on the dynamics of useful water reserve in the soil profile of 0- 110cm .

Methods The research was carried out in the years 1981-1995 in the Agrometeorological Observatory in Lublin-Felin (SE Poland

Results The results of the research show that in the entire soil profile the useful water reserve depended on the kind of plants, their stages of growth and the weather conditions. Under each plant and in each ten-day period the water reserve stated in mm was lower than on the bare fallow. In the first two layers of soil (0-25 and 25-60 cm) the smallest water reserve was observed under winter rye (during four ten-day periods) and under red clover (during theree ten-day periods). In the whole soil profile, i. e. in the layer 0-110 cm, the situation was a little different; the most cases (four ten-day periods) with the lowest water reserve were observated in the fields of winter wheat and winter rye. Generally speaking, water reserve decreased under all the plants from May to July with a trend towards the growth of values towards the end of the vegetation period (in July), which was caused by higher precipitation in that month and a gradual decline in the plants life activity (Kolodziej et. al., 1970, 1972; Kozminski, 1994; Samborski et. al., 1992, 1993). On the basis of statistical analysis of the examined phenomenon it was stated that in the period from the first then-day period in May till the third ten-day period in July, in the soil layer 0-25 cm, on the sigificance level of 0,05, the differences between the water reserves under the plants and on the bare fallow were not significant. In the 0-60 cm layer nine instances of significant differences were found; the majority of them in the third ten-day period of May and in the second ten-day period of July. Among the examined plants the majority of differences concerned winter wheat and winter rye. However, in the whole soil profile: from 0 to 110 cm, there were eleven instances of sigificance of differences; the majority in the second ten-day period in July. Most often the differences concerned winter wheat and winter rye. Session 2.2 473

The multiple regression equations where water reserve (W) was the dependent feature and precipitation (p), air temperature (t) and sunshine (s) were the independent features, were used in order to establish the relation between weather conditions and useful water reserve. The following equations were obtained for the respective layers: a) 0-25 cm W = 62,15 + 0,42p - 2,66t R2 = 39,5% (1); b) 0-60 cm W = 162,27 - 6,18t R2 = 32,8% (2); c) 0-110 cm W = 293,41 - ll,59t R2 = 40,2% (3). Explanation: p -atmospheri c precipitation (mm), t - air temperature (°C). From the presented comparisons it follows that the water reserve was formed to the highest degree by air temperature, next by the sunshine and precipitation. The equation for the whole soil profile contains the most information about the examined interrelations.

Conclusions Useful water reserves on fields of cultivated plants decrease with the passage of time during the whole vegetation period. The comparison between the water reserves under different plants and on the bare fallow proves that the water reserves on the bare fallow were always higher than under the cultivated plants. The analysis of the water reserve in the whole soil profile showed that the smallest reserve was most often found under winter wheat an winter rye. Significant correlations between water reserve and meteorological elements occurred in the 0-25 cm layer: precipitation (positive), temperature (negative), and sunshine (negative). In the other layers the correlations concerned temperature and sunshine.

Figure 1.Th ewate r reservei nth e 0-110cmsoi llaye ri nrelatio n to air temperature

mm 400 layer0-11 0 • 350 -

300 • • 250 • 4» • • • 200 r^-**. ^^ <•• % • • • • 150 • ^-1^^r-*-*^ W» • *• . • • • •• ** ^ • • 100 ^_* -^_* 50 • • • •••• •. 4.3 5.9 7.5 9.1 10.7 12.3 13.9 15.5 17.1 18.7 20.3 temperature(°C )

References Kolodziej, J. et al., 1970,Annale s UMCS XXV, 1: 1-20. Kolodziej, J. et al., 1972 AnnalesUMC S XXVII, 4:45-62 . Kozminski, C, 1994.Rocznik i AkademiiRolnicze j wPoznani u CCLVII:33-49 . Samborski, A. et al., 1993.Annale sUMC S XLVffl, 12:93-96 . Samborski, A. et al., 1993.Annale sUMC S XLVHI, 13:97-103 . 474 Book of Abstracts 4th ESA-congress

NITROGEN USE AND LOSSES AT (SUB)FAR M LEVEL IN POLAND

J.W.A. Langeveld and G.B. Overbosch Centre for World Food Studies, De Boelelaan 1105, 1081 HV Amsterdam, the Netherlands

Introduction High to very high nutrient losses in current agricultural practices have raised questions regarding their effect on the environment. Although there is clear need for policies aiming at a reduction of these losses (90 %o f ammonia emissions in the Netherlands originate from agricultural processes), there is much debate on their expected effect. Stringent measures that are necessary will influence economic and social conditions in agriculture where already major changes take place. Their effect will depend on the extent and type of losses, the place where they occur, and the assessed costs for abatement. The aim of this study is to provide information on nitrogen losses on private farms in Poland and options for their abatement.

Methods Most studies on nutrient losses in agriculture use farmgate or aggregated sectoral figures. In this study we calculate sub-farm flows to discriminate between livestock and crop sectors at farm level. Figures refer to farms in two districts in Poland (1992 data), that were selected to represent all private farms (cf Langeveld et al. (1995)). Nitrogen surplus in the livestock sector is calculated as the difference between animal feed on one side and animal products and manure on the other side. Nitrogen flows in manure were calculated as the difference between feed and animal products, corrected for losses in stables. The crop balance is defined as the difference between nitrogen imports (seed, deposition, fixation and anorganic fertilizers) and manure on one side, and crop products on the other side. It includes all losses occurring on fields. The farm balance is calculated as the difference between nitrogen imports and nitrogen in products sold (both at farm level). In order to assess the efficiency of nutrient use, Nutrient Use Efficiency (NUE) which is defined as the ratio of outgoing and incoming nutrient flows, was calculated for the animal and crop sectors as well as the farm level. Nitrogen losses are caused by volatization, leaching or run-off. Assessment of the latter two require detailed field analyses which were not available. Volatization was calculated using survey data combined with literature. Options for reduction of volatization were identified and their costs evaluated.

Table 1 Nitrogen flows at sector and farm level (kg N ha"1) Flow Livestock sector Crop sector Farm Input 83.4 201.2 144.9 Output 75.0 43.5 22.1 Surplus 8.4 157.8 122.7 NUE (-) 0.91 0.34 0.15 NUEa (-) 0.23 0.53 - a: excluding nitrogen in manure

Results Nitrogen surpluses are low in the livestock sector, but high in the crop sector and on the farm level (Table 1). The farm surplus is higher than that in 1991 (Sapek et al., 1993). This can be explained by higher fertilizer applications in 1992, while yields in both years were comparably low (1992 yield was depressed by drought). NUE at farm level is rather low for Session 2.2 475 both years (0.15). NUE of the livestock sector (1992) is very high as way manure is considered as an output. NUE of the crop sector is considerably lower. NUE figures for Dutch dairy farms are 0.14, 0.53 and 0.14 respectively (Aarts, pers. comm.). Exclusion of manure gives an indication of production efficiency using external inputs only. Adjusted NUE is 0.53 for the crop and 0.23 for the livestock sector. The latter figure is comparable to that for a Dutch experimental farm (Aarts, pers. comm.). Nitrogen volatization is calculated at 37 kg N ha"1 or almost 400 kg of nitrogen per farm (Table 2). This is 50 % more than in 1991 (Sapek et al., 1993). Most losses occur in the crop sector, especially during manure and chemical fertilizer application. Losses in stables and from manure storage are relatively small (20 %o f the total). Aggregation to the total private agricultural sector in Poland (14.2 million ha) gives a loss of 0.52 million ton of nitrogen. This seems reasonable, although somewhat high, if compared with estimations by Klaassen (1991a) who presented a range of figures: 0.33-0.47 million ton.

Table 2 Nitrogen volatization at farm level (kg N farm"1) Flow Livestock sector Crop sector Farm Stable/storage 82.9 - - Grazing - 10.1 - Manure application - 188.1 - Fertilizer application - 110.3 - Total 82.9 308.4 391.3

Abatement options include loss reduction in stables (stable adjustment, SA), manure storage (storage covering, SC) and manure application (injection or ploughing, IP). They represent considerable costs, as estimated by Klaassen (1991b). For the average farm in our survey (10.7 ha, 0.6 ha of grassland, 5 heads of cattle and 25 pigs), costs are estimated at 58,700 German Marks (once in 10 years) for SA and SC, and 525 Mark annually (IP). Expected volatization reduction rates of the measures is 50-65 % (SA), 10 % (SC) and 90 %(IP) .

Conclusions Farm surpluses are rather high due to high fertilizer application levels and low yields in 1992. Ammonia volatization estimations remain in line with expectations. Most losses occur during manure and fertilizer application. Losses strictly related to animal production (excluding manure application) are rather small. Abatement costs represent major investments for private farms in Poland, especially for the livestock sector where also reduction efficiency is lowest. Loss reduction in crop sector therefore needs to be given the higher priority.

References Klaassen, G., 1991a, Emissions of ammonia in Europe as incorporated in RAINS. Paper presented at the workshop 'Ammonia emissions in Europe: emission factors and abatement costs' at IIASA, Laxenburg, February 4-6 1991, 34 p. Klaassen, G., 1991b, Costs of controlling ammonia emissions in Europe. Status Report 91-02, 46 p. Laxenburg, IIASA. Langeveld, J.W.A. and G.B. Overbosch, 1995, Estimating nutrient surplus and nutrient use efficiency from farm characteristics. An application to private farms in two districts in Poland. Working Paper 95-03, 15 p. Amsterdam: Centre for World Food Studies. Sapek, A. and B. Sapek, 1993, Water Science Technology 28, 483-488. 476 Booko fAbstract s4t hESA-congres s

ENERGY BALANCE OFCROPPIN G SYSTEMS IN THE SUGAR BEET-GROWING REGION OF CENTRAL MORAVIA

P. Misa

AgriculturalResearc h InstituteKromëfiz , Ltd., Havlickova 2787, CZ- 7674 1Kromëfiz , Czech Republic

Introduction Atypica l feature ofCzec h agriculture inth e pastwa st o maintain relatively stable and balanced crop rotations. Thissyste m hasbee n basically destroyed duet o market relations and farmers have begun to focus on economic effectiveness. That hascaused , among others, considerable production specialization. Thepresen t statebring sdiscussion so nbot h productivity and sustainability and stability ofplan t cropping systems.

Methods Thisstud y isbase d on long-term stationary experiments carried out inth e sugar beet-growing region in Central Moravia, location ofth eAgricultura l Research Institute Kromëfiz, Ltd. Five cropping systems were compared: 1)eight-cours e crop rotation ofth e ecological cropping system inaccordanc e with IFOAMinstruction s (clover, winter wheat, potatoes, springbarley , triticale, pea, winter barley, oats), 2)nine-cours e crop rotation with the conventional cropping system (alfalfa, alfalfa, winter wheat, springbarley , sugarbeets , springbarley , winter wheat, silagemaize , springbarley) , 3) four-course Norfolk crop rotation (clover, winterwheat , sugarbeets , spring barley), 4) winter wheat continuous cropping, and 5)sprin gbarle y continuous cropping. For both continuous cropping systems four variants of organicfertilizatio n are studied (A- straw ploughed in, B- straw + green manure ploughed in, C- green manure, D- acontro l variant free of fertilization. Theindividua l systemswer e limited byth eplo t(field) . Inputs ofth e energy balance comprised only materials entering the system from outsideth e system, and outputs only materials that leaveth e system. That meansth e straw which remains inth efield t o beploughe d inwa s considered as material whose energy remains within the system and it isno ttake n asinpu t or output. In continuous cropping systemsstra w remains inA an d B variants; the balance does not includegree n fertilization inB and Cvariants . In the crop rotation ofth e ecological cropping system allth e by-products remain inth efield. Th e energy of organicfertilizer s applied to the systemfrom outsid ethi ssyste m (farmyard manure)wa sexpresse d usingthei r combustion heat. Energybalanc e was calculated for invested energy (e.g. fuel, fertilizers, pesticides, seed, machinery and labour) and total energy coming into the system (solar radiation + invested energy). In thevariants , effects ofcroppin g practices on some soilpropertie s (pH, humus content, etc.) are also examined.

Results The results are given in Tables 1 and 2. Taking into account the energy balance thebes t values were obtained inth e variants Can dD ofbot h continuous croppings (mainly the output energy/input energy ratio). Table 2show s effects ofthes e cropping systems onth e soil during 25 years ofth e experiment.

Conclusions To calculate the energy balance ofcroppin g systems some factors play an important role: 1)Methodologica l factors Definition ofth e system and its limits, and then the expression and inclusion ofth e energy from Session 2.2 477 organic fertilizers are particularly considered. Ifw etoo k into account onlyth e energy used for the production of organicfertilizer s and not theirtota l energy content, wewoul d obtain quite different results. 2)Problem s ofinterna l energy ofth esyste m The expression of energetic changes inth e system caused bysoi lprocesse s can indicate a limit of cropping system sustainability. Table 2 shows that good results ofsom ecroppin g practices can be achieved but this isassociate d with alos so f internal energy ofth e system. There is,however , a question how to include changes ofsoi lpropertie s inth e energybalance .

Table 1. Energy balance of cropping systems (MJ.ha -') variant inputs outputs O/l ratio O/I ratio

invested of which organic I = invested I = invested energy fertilization energy energy + SR CR in ecological S 25 087 16 363 76 150 3.04 0.00184 CR in conventional S 35 341 23 800 25 301 5.81 0.00495 Norfolk CR 39 681 29 750 146 425 3.69 0.00353 CC of w. wheat- A 19 755 94 795 4.8 0.00229 CC of w. wheat-B 21010 106 775 5.08 0.00258 CC ofw . wheat-C 21009 208 255 9.91 0.00503 CC of w. wheat-D 19 754 201 855 10.22 0.00487 CCofs.barley-A 16 039 93 850 5.85 0.00227 CCofs.barley-B 17 294 109 560 6.34 0.00265 CCofs.barley-C 17 293 166 185 9.61 0.00401 CCofs.barley-D 12 237 133 630 10.92 0.00323 CC= continuous cropping, CR =cro p rotation, S : system, A,B , C, D, =variant s ofC C SR= solar radiation = 41 400 087MJ.ha' 1

Table 2. Effects of cropping practices on soilpropertie s (chosen variants) 1970 1995 variant humus humus humic pH total N total N content content acids/ fulvic content content acids (%) (t.ha1) Norfolk CR 2.6 2.56 0.83 7.03 0.21 9.01 CCofs.barley-A 2.69 2.79 0.87 5.44 0.203 8.47 CCofs.barley-B 2.78 2.78 0.83 5.08 0.21 8.51 CCofs.barley-C 2.71 2.37 0.91 5.49 0.193 8.51 CCofs.barley-D 2.38 2.25 0.88 6.16 0.189 8.39

References Stout, B. A., 1992.Energ y inWorl d Agriculture, Volume 6. Elsevier Science Publishers, 367p . Kopecky, M., 1979. Odrûdovâ agrotechnika avyzivajarnih ojecmen e pro rüzné vyuzitivyss i koncentrace obilnin. Research report, VÛOKromëriz , 44p . Kudrna, K., 1985.Zemëdëlsk é soustavy Stâtnizemëdëlsk é nakladatelstvi, Praha, 49-89. Preininger, M., 1987.Energ yEvaluatio n ofProductio n Processes inPlan t Production. ISSM, Prague, 29p . 478 Book of Abstracts 4th ESA-congress

ECOLOGICAL AND INTEGRATED SYSTEMS IN DENMARK. INTERNAL RESOURCES IN DD7FERENT SYSTEMS AND THEIR POTENTIALS FOR USE.

Gunnar Mikkelsen.

Department of Soil Science. Research Centre Foulum, P.O. Box 23, DK-8830 Tjele.

Introduction In Denmark, ecological and integrated crop rotations have been designed and started in 1987 at three state research stations. The discipline is called Research in Cropping Systems. Different systems are designed for the different locations. The design is based on soil type, climatic possibilities and tradition for agriculture. The overall design is in correspondence with activities all over Europe, where a holistic approach is a key point for the research activities. A common feature of the research is to evolve systems not to compare systems. In integrated rotations, liquid manure is the main fertilizer. In rotations with forage crop production, liquid manure from cows is used and in rotations with production of small grain manure from pigs is used. The ammonium part of the manure is defined as 100% usable in the first growing season. The fertilization is then based on manure in amount of the crops need for potassium and phosphorus. Ammoniumnitrate is then used to adjust the nitrogen fertilizer level to 80 % of the recommended. A well designed crop rotation, including catch crops, will then be able to satisfy the crops need for nitrogen to optimal grow potential. The use of pesticides is kept at a low level by using a good crop rotation, variety mixtures, where it is possible, and keeping the nitrogen level low. A black list for chemicals based on their toxicity for humans and their persistens in soil is worked out to secure the farm manager and the environment. In the ecological rotations liquid manure is the only fertilizer. The amount is from one year cow on average per hectare. Peas and clover grass covers nearly half of the area other crops are barley, oat, fodder beet. As the rotation runs, clover grass will become the main nitrogen source for the entire rotation. The crop rotation, therefore, must take care of keeping nitrogen in the soil/plant environment instead of being leached. Weed control is mechanical by long finger harrows, hoeing machines and by hand hoeing. In grass and row cultures the main weed control is done. These fields are keeps absolutely clean in relation to weed. Pests and diseases are controlled by the crop rotation.

Methods Results from the rotation at Research Center Foulum will be presented. Foulum is situated in the middle of Jutland on a coarse sandy loam. One ecological forage crop rotation and two integrated rotations are situated here. The entire research area covers 26 hectare. Every field in all rotations is divided in two parts. A reference area and a research area. In the reference area a monitoring program for parameters as yield, fertilization, pesticide use, pests and diseases evaluates the agricultural practice in the long run. Before the project started a grid net of 40 m x 40 m was established, and in all interceptions, a so called "startcharacterization" was done. In the reference area this characterization is continued. In the integrated rotation nitrate leaching is measured. 16 ceramic cups are placed at one metres depth under the root layer. The nitrate concentration in soil water is measured every fortnight. The water movement is followed by neutron spreading technic. The leaching of nitrogen in kg per hectare is then calculated based on the amount of water percolating the soil and the nitrate concentration in the water. The evaluation of the nitrate leaching is then a function of the different treatments done in the field and the corresponding leaching. Data from 1989 up till 1995 are available. Session2. 2 479

Results In the integrated rotations the fertilizer level is based on yield expectations for the different crop in the rotation. The levels, therefore, some time when the growing conditions are suboptimal, because of the climate, become too high. Nutrient balances for single crops and for the entire crop rotation show, that in some years, it is very difficult to make a balanced fertilization. Also because the ratio between phosphorous and potassium in manure is different from the composition in plant material. Nitrogen fertilization is a combination of the mineral nitrogen in manure and ammonium nitrate. In years with normal growing conditions, there is balance in relation to mineral nitrogen but not in relation to the total input of nitrogen. The choice of fertilizer level at 80% of the recommended, and catch crops, should secure that use of manure do not create nitrogen leaching problems. In the ecological rotation the fertilization is based on manure and clover grass. The balance for potassium is very negative because of high yields and leaching of potassium, but in ecological farming it is difficult to import potassium to the farm. In the long run, then, potassium can be the growth limiting factor instead of nitrogen. In the rotation there is plenty of nitrogen because of fixation in clover grass. The balance for nitrogen both total nitrogen and mineral nitrogen is positive. Mainly because of nitrogen fixation which is an integrated part of the balance. The balance for phosphorous is neutral with the same output as input. The results for nitrate leaching show that in years when there is an effective catch crop in the field the nitrate leaching is very low. Winter wheat as a winter green crop has very little influence on the nitrate leaching. The concentration of nitrate in ppm is, for all years, kept under the EU - level at 50 ppm nitrate per litre. Anyway, the amount of leached nitrogen per hectare still can be high on sandy soils.

Discussion The fertilizer balances for the different crops and rotations will be discussed in the lecture. Nitrate leaching as a consequence of agriculture and how to reduce it, will be discussed. The holistic approach in relation to more traditional research results will be part of the discussion, too. 480 Book of Abstracts 4th ESA-congress

WATER AND NITROGEN INTERACTION INDIFFEREN T CROPPING SYSTEMS

K. Peto Department ofRura l Resource Management, Debrecen Agricultural University, PO Box: 36, H-4015, Debrecen, Hungary

Introduction The drought weather ofth e past years made cleartha t the available moisture, moisture -supply, and yield are in close correlation with each other (Debreceni, B. et al., 1983).In this paper I would liket o present some results concerning to water and nitrogen interaction in different cropping systems

Methods Onth eLâtoké p Experimental Station ofDebrece n Agricultural University amultivariat e trial was conducted byRuzsâny i atth ebeginnin g of 1980's. Debrecen is situated onth e Great Hungarian Plain, inth eEaster n part ofth e country, at 47^30 ' latitude and 21^30' longitude. Thehighes t contour lineo fth e region isa t 118m (Adriatic.) The soil ofth e experiments iscalcareou s chernozem. The clay content inth e cultivated layeri s 50% . Physical soiltype : medium heavy loam. Thewate r holding capacity (WHCmm) ofth e soil is32-3 4 vol. %. Inthes e experiment we studied three different crop rotation systems: winter wheat -maiz e (biculture), soya -winte r wheat -maize(triculture ) and maize monoculture at different levelso f fertilisation, irrigation andtillage . Wetoo k soil samplesfrom th e 200 cmdee p soillaye r separately ineac h 20 cm atth e beginning of vegetation period and measured the soilmoistur e content with gravimetric method. The soil samples were takenfrom thre e different: control, medium, highest, fertilisation level (Figures 1 and 2)from eac h replication

Results Crop rotation and preceding crop has amos t favourable effect onth e modification of soil water management. The highest soil moisture content inth e 0-200 cmlaye r mayb e measured bothi n early spring and the end ofvegetatio n period inwinte r wheat -maiz e (biculture) production system(Figures 1 and2) . In soya -winte r wheat -maiz e (triculture) and maizemonocultur e system ascompare d to the previous oneth e moisture content ofth e soil isles sb y 30-60 in early springtim e and by 50-100 mm atth e end ofvegetatio n period (Figures 1 and2) . There are differences among the effect ofth e sameprecedin g crops indifferen t cropping systems too (Ruzsânyi, L. 1973). The effect of soya on soil moisture was the samea sth e maizewhic h iscultivate d in monoculture. It means, that according to our measurements and calculations thewate r consumption ofsoy a was ashig h as or highertha n the water consumption of corn in our experiment. Onth e basis ofit s effect onth e water management of soil, soya should be considered with lessfavourabl e green crop value (Petö, K. et al., 1991). Comparing the different cropping systems we can conclude that the role of soil water balance became most important in soya -winter wheat-maize system. Thisrefer s to water deficiency relative to nutrient level (F2,F3 ) inthi s system during the vegetation period (Figure 1). In chernozem soil ofgoo d nutrient andwate r management the decisive agrotechnical factor isth e fertilisation, more specifically, N-fertilisatio n (Ruzsânyi L. et al., 1993). Session 2.2 481

The effect offertilisatio n increasing thewate r demand is,however , differentiated. It increased most the water demand ofwinte r wheat ofal l plants investigated. Depending on the previous crop(35-70 mm). Amount offertilise r inexces st o the demand ofplan t did not alter the water demand and did not affect the yield. Result ofth e investigation also proveth e strict connection between the effects offertilisatio n to increase the water demand and yield. Quantities offertilise r not increasing the water demand do not increase the yield either.

Table 1.:Sprin gan d post harvest moisture of0-20 0c m soillaye r and yield ofwinte r wheat plots per fertilisation intw o different crop rotations 1990 crop rotation Spring Post- harvest fertilisation levels Fl F2 F3 Fl F2 F3 Biculture 454.0 431.9 427.7 359.3 336.4 314.8 Triculture 430.0 427.0 413.0 326.8 299.8 294.8 yield kgha" 1 Biculture 2746 5181 5714 Triculture 3479 4321 4160 Legende: Fl: N0+P0+K0, F2:N100+P70+K8 0 F3:N200 + P140+K160 Table 2. Spring and post harvest moisture of0-20 0c m soil layer and yield ofmaiz e plots per fertilisation inthre e different crop rotations 1990 crop rotation Spring Post- harvest fertilisation levels Fl F2 F3 Fl F2 F3 Biculture 494.3 479.3 470.4 308.7 293.3 295.9 Triculture 463.5 428.9 444.5 316.0 307.2 289.7 Monoculture 421.2 412.5 377.9 313.9 298.0 267.1 yield kgha" 1 Biculture 7951 8584 8161 Triculture 7303 6343 6412 Monoculture 3547 4499 3531 Legends:Fl: N0+P0+K0, F2:N120+P90+K9 0 F3:N240 + P180+K180

Conclusions Comparing the biulture and triculture, we can concludetha t the effect of soil moisture onth eyiel d is more significant inth etricultur e than inth ebiculture . It can also be concluded that theyiel d ofwinte r wheat can beaffecte d more significantly byN - fertilisation inbicultur e than intriculture . In corn experiment the relation between the change of soil moisture content and fertilisation is more suppressed than that inth ewhea t experiment.

References Campbell, C. A. et al.,1987 . Can.J. Soc.Sci.Ottawa Ont. 67.3.457-472. Debreceni, B. et al., 1983.Th e relation between thenutritio n andwate r supply. Budapest. Petô, K. et al., 1991. Növénytermelés.40 . (6):535-541. Ruzsânyi, L. 1973.Növénytermelés.23 . (3):249-258 . Ruzsânyi L. et al., 1993. Növénytermelés.42.(l):85-94. 482 Book of Abstracts 4th ESA-congress

EFFECT OF ROTATION WITH WHEAT AND CATCH-CROPS ON PHYSICAL TRAITS OF "XANTHI" TOBACCO

F.Piro1, P.Greco 2

'present address:Istitut o Sperimentalepe r 1'Orticoltura,1-8408 9Pontecagnan o (SA),Italy . 2Istituto Sperimentale per ilTabacco ,1-7310 0Lecce ,italy. .

Introduction Tobacco monoculture isquit e usual in specialised areas ofproductio n for economicreasons . Reduction ofyiel d levels isamon g the shortcomings ofmonoculture . Short rotations with wheat, including catch-crops,hav e been studied through 1985-1991a salternative s to oriental tobacco monoculture (Lanza, 1988;Grec o et al., 1990;Grec o et al., 1994).Effect s ontobacc o physical traits relevant to manufacturing areher e reported.

Methods Monoculture oftobacc o ("Xanthi", oriental aromatic type) (T),th e same with a fennel catch crop (T+Fl), andtobacco-whea t rotations with catch-crops of soybean (T-W+Sy) or sorghum (T- W+Sm) were compared through theyear s 1985-1991 ona haploxeral f sandy loam inth e Salento area ofth eApuli a Region (Costantini et al., 1990).Al l cropping patterns wereteste d attw o levels ofcro phusbandry , differing indept h of soilplowing , levels ofNP K fertilization, and seasonal irrigation volume. Field design was asplit-plot , with husbandry levels in main plots and rotations in subplots,wit hthre ereplication s incomplet e blocks. Tobacco wastransplante d at spacings of 0,55 mb y 0,11m . Details of field procedures have been reported previously (Greco et al., 1994).Tobacc o dataher e reported refer toth e lasttw oyear so f experiment. Yield measurement and leaf grading were carried out on leaves conditioned at 16%RH . Lamina- midrib ratio was determined on samples of 20 middle leaves.Lamin a specific weight was determined on samples of 50middl e leafdisk so f2 2m mdiamete r after ovendryin g at 50°C for 48 h.

Results Incompariso n with monoculture, tobacco inrotatio n with wheat gavehighe r yields of cured tobacco,bu t lower leaf grades (Table 1).

Table 1. Effect of rotation and crop husbandry level on yield and grade of 'Xanthi' toDacco. Irai t and year Rotation and input level Cured yield Hercent gradesA+ B Middle leaf weight ton ha-1 • % g —Two m] Twrj— 1991 rggrj TSÏÏI— notation Tobacco-tobacco 1.17 1.47 53.0 40.6 4.5 5.6 Tobacco-tobacco+fennel 1.05 1.53 48.9 39.5 3.9 5.4 Tobacco-wheat 1.58 1.76 37.1 32.9 4.8 5.6 Tobacco-wheat+sorghu m 1.65 1.77 41.6 43.1 4.2 7.0 Tobacco-wheat+soybean 1.63 1.55 37.9 44.4 4.9 5.9 se. 0.07 0.02 2.50 5.8 0.1 0.6 Inputlevel high 1.43 1.81 43.2 34.9 4.5 5.7 low 1.40 1.41 44.3 45.2 4.4 6.1 s.e. 0.05 0.01 1.6 3.7 0.04 0.4

Thesam etren d was observed atbot h levels ofcro phusbandr y in 1990,whe n on average a 35% yield increase was matched by a 30%decreas e in grade;bu t in 1991 itwa s significant only atth e high level (Table2) . Session 2.2 483

Table 2. Interaction of rotation and crop husbansuaiiuid ry levey icvcl in 199i in 1i s 9 I. TraitanTrait a n rid hnchanHrhusbandrwy level C ure d yield % grades t ha ' A + B R otatio n high low high low Tobacco monoculture 1.5/ 1.36 4 5.3 3 5.9 Tobacco monocultur e + fennel 1.63 1.43 30.3 48.6 Tobacco-wheat 2.07 1.46 27.9 37.9 Tobacco-wheat + sorghum 2.13 1.14 33.3 52.9 Tobacco-wheat + soybean 1.68 1.42 37.9 50.9 0.1 3.9

The addition of catch-crops resulted in further yield improvements,excep t inth e case of soybean in 1991,bu t limited to a large extentth e fall inlea f grade. Rotation with wheat reduced lamina- midrib ratio in 1990an d leaf specific weight in 1990an d 1991 (Table3) .

Table 3. Effect of rotations and crop husbandry levels on cured leaf traits or 'Xanthi' tobacco. Lamina-midrib ratio Lamina specific weight (g m') Rotation and input level 1990 1991 1990 1991 Rotation Tobacco-tobacco 4.9 4.0 75.4 74.0 Tobacco-tobacco+fennel 4.1 4.0 79.2 73.8 Tobacco-wheat 4.1 4.0 70.1 57.8 Tobacco-wheat+sorghum 3.9 3.8 55.8 65.9 Tobacco-wheat+soybean 3.9 3.8 60.2 64.6 s.e. 0.02 0.2 2.9 3.6 Input level high 4.1 3.7 65.3 60.2 low 4.3 4.2 71.0 74.2 s.e. 0.01 0.1 1.8 2.3

Effects ofcatch-crop s on leaf specific weight were incosistent overth etw o years.Th e sorghum catch-crop appeared morebeneficia l for tobacco yield and mean leafweigh t than soybean,bu t only inon e year. Inclusion ofth e fennel catch-crop tomonocultur e did not shownoticeabl e or consistent effects, except a slight depression of leafweigh t and grade inon e year. Onth ewhole , the high level of crophusbandr y showed somepotentia l to increase yields,bu t atth e expenseo f leaf specific weight, lamina-midrib ratio and leaf grade.

Conclusions Xanthitobacc o is appreciated mainly for characteristics ofaroma ,whic h are enhanced by adr y climate liketh e egean and hillside, superficial soils of lowfertilit y (Wolf, 1962).Th e increase of soil fertility, asthroug h rotations andmor e intensive cropping ofregularl y fertilized cultures, risk diminishing the aromatic character ofth eleaf .Indee d the rotation with wheat, rising substantially the levels ofnitroge n fertilization, wasdetrimenta l for leafgrade .Howeve r such negative effect could be largely offset by low levels of crophusbandr y and by addition of catch- crops, which could consume some ofth e excess nitrogen inth e soil.

References Costantini, E.A.C. et al., 1990.Annal i Istituto Sperimentale Agronomico, 21, Suppl. 2,255-288 . Greco, P.e t al., 1990.Annal i Istituto Sperimentale Agronomico, 21, Suppl. 2,36-37 . Greco,P .e t al., 1994.Agricoltur a Ricerca 151/152,35-42 . Lanza, F., 1988.L'Informator e Agrario 44,57-67 . Wolf, F.A., 1962.Aromati c or oriental tobaccos. Duke University Press,Durham , NC. 484 Book of Abstracts 4th ESA-congress

INTERCROPPING SPRING TRITICALE WITH N-FIXING LEGUMES ASA COMPONENT OF SUSTAINABLE FARMING

E.K. Pisulewska, T. Zajac, R.Witkowic z

Crop Science Department, KrakowAgricultura l University, al.Mickiewicz a 21, Krakow, Poland

Introduction

When cereals are grown as intercrops with legume species, they generally yield similarly (Reynolds et al., 1994, Zaja_c et al., 1995) or less than they do in monoculture, and grain protein content is increased (Pisulewska, 1993 and 1995). Intercropping can also provide other benefits such as extra ground cover, and a substantial input of organic matter and N to the soil, thus becoming a sustainable approach to maintaining soil fertility. Our purpose was to compare grain yield and itsqualit y ofsprin gtritical e grown inmonocultur e and intercropped with legume species

Methods

Three precise field trials were conducted in different habitats in three provinces of Southern Poland, in the growing seasons 1987 - 1995. Total rainfall was recorded in the month April to August (Fig).

BKatowice 1994 QKatowice199 5 HNowySac z198 7ENow ySac z 1988| BNowySa.cz198 9H Krako w199 0 BKrako w199 1 BKrakówl992 Figure. Precipitation ingrowin g season at different sitesan d different years.

A two-factorial, split-plot arrangement of treatments in a randomized complete block design was used, with three or four replicates. The treatments were (1) spring cereal species and (2) the planting method (monoculture vs. intercropping with a legume plant). Both grain and legume species were well adapted to their habitats: I. Katowice province - brown soils, grain species - spring triticale and oats, legume species - Serradella; II. Nowy Sacz province - brown soils (on Session 2.2 485 loam), grain species - spring triticale and barley, legume species - red clover; III. Krakow province - chernozem on loess, grain species - spring triticale and spring wheat, legume species - field peas.

Results

Theresult s are presented inTable s 1 and2 .

Table 1. Grain and protein yield of spring cereals grown in monoculture and intercropped with legume species (average of2 or 3years) .

Province Species Grainyiel d (t * ha1) LSD Protein yield (kg * ha"1) LSD Monoculture Mixture p= 0.05 Monoculture Mixture p= 0.05 Katowice Triticale 1.69 1.91 n.s. 216 220 n.s. Oats 1.70 1.36 197 201 Nowy Sacz Triticale 3.29 3.86 n.s. 379 484 n.s. Barley 2.36 3.00 260 374 Krakow Triticale 6.02 4.97 n.s. 826 759 n.s. Wheat 5.82 5.48 777 769

Table 2. Grain yield, grain protein content, and protein yield of spring cereals, as affected by a type of soilan d growing season.

Province Year Grainyiel d LSD Protein content LSD Proteinyiel d LSD (t * ha') p= 0.05 (% D.M.) p= 0.05 (kg *ha 1) p= 0.05 Katowice 1994 1,98 0,09 14,66 2,22 256 31 1995 1,35 12.69 162 Nowy Sacz 1987 4,61 0,70 14,33 0,91 570 111 1988 3,97 13,70 469 1989 0,80 12,30 84 Krakow 1992 6,51 0,50 14,08 0,81 909 98 1993 5,51 13,84 764 1994 4,70 14,52 677

Conclusions 1. In the three experimental locations, triticale yields did not differ significantly from those of the reference cereals. In contrast, type ofsoi lan d growing season affected theyield s significantly. 2. Themetho d ofplantin g (monoculture vs. intercropping) had no statistically significant effect on the yields of triticale, although in Krakow province intercropping tended to decrease these yields. 3. Grain protein content and protein yields were significantly affected by growing season (total rainfall and itsdistribution) .

References Pisulewska E., 1993,Rocznik iA Rw Poznani u CCXLIII. Pisulewska E., 1995,Act aAgr . et Silv. Ser. Agr., vol. XXXIII. ReynoldsM . P.et al, 1994,Journa l ofAgricultura l Science, Cambridge, 123,17 5 183. Zajac T. et al., 1995,Fragment aAgronomica , nr 2(46) . 486 Book of Abstracts 4th ESA-congress

MAIZE RESPONSE TO FERTILIZER NITROGEN IN MONOCULTURE AND ROTATION SYSTEMS ON VERTIC AMPHYGLEY IN UPPER SAVA VALLEY

A.Pucaric , B. Varga

Faculty ofAgronomy , University ofZagreb , 10000Zagreb , Croatia

Introduction In intensivemaiz eproductio n thetyp e ofcro p inth e rotation usually isno t important aslon g as maize does not follow itself (Crookston et al., 1991, Raimbault et al, 1991). In such production systemsheav y use ofnitroge n leadst o environmental problems. To solve these problems alternative practices asrotation s inwhic h legume are included and lower nitrogen fertilization are recommended. (NAS, 1989). Our objective wast o determine maize response to appliedN i n different cropping systems on the heavy, poorly drained vertic amphygley in ahumi d climate.

Methods Acro p rotation study was established at Oborovo near Zagreb in 1991. The cropping treatments weremaiz e monoculture (MM) and 22 plots for seven rotations coded byth efirst lette r ofth e crops: SM, S-W-M.W-M . W-RC-M. S-W-RC-M. S-W-OR-Man d A-A-A-M (M=maize, S=soybean , W=w.wheat , RC= red clover, OR=oi lrape , A=alfalfa). Each crop ofever y rotation wasgrow n in everyyear . Identical split-plot experiments withfive replication s on maize plots were carried out from 1993 to 1995.Mai n plots werefive nitroge n rates (40 to 240, inM M 86 to 286 kg ha_1N)an d subplotstw o hybrids.Nitroge n was applied prior fall plowing atth e rate 40 (inM M 86) kg ha'1N to all plots. Rest ofth e nitrogen depending on N rates was applied before secondary tillage and side dressed twice. Ear leafsample swer e taken at anthesist o evaluateN status of maize. Yield was adjusted to grain moisture of 140g kg"1.Analyse so f variance for yield showed no significant interactions betwen N rate and hybrid and year ineithe r system. Thus,yiel d data are combined over threeyears , in A-A-A-M overtwo .

Results Resultsfo r maizegrai n yield arepresente d inth e Figure and for leafN inth eTable . The lowest yieldswer e observed inM Mbu t also in S-M and A-A-A-M rotations. When lowN rate of4 0 (86) kg ha"1wa s applied grain yield averaged only4.2 , 5.3 and 5.71 ha"1 inMM . S-M and A-A-A-M. respectively. Lower N plant status (23 g kg"1)tha n optimum (27 to 28 gkg" 1, Dumenil, 1961., Larson et al., 1977)ma yb e reason for low grain yieldsi nM M and S-M. After alfalfa maize had optimum leafN concentration indicating that some other "rotation effects" produced lowyield . Maizeyiel d responset o increased N rates was most pronounced inM M

Table. Maize leafN as affected by previous crop in different cropping systems and N rate

N rate, Cropping system kg ha "' MM S-M A-A-A-M W-M S-W-M W-RC-M S-W-RC-M S-W-OR-M Leaf N at anthesis, g kg"1 40(86)* 23 23 27 26 26 26 25 27 120(166) 25 25 29 27 28 27 27 29 160(206) 27 26 30 29 27 29 28 29 200(246) 27 27 30 29 29 30 28 29 240(286) 28 28 30 28 29 29 29 30 *number s inbracket s areN rates inMM . Session 2.2 487

WT o MM A S-M ..G....0 ^•••••A" •••&!• • ^9- x A-A-A-M o ,...*—' x-.4 f" -c

A S-W-OR-M x W-RC-M \s OS-W-RC-M

-•5

•+• •4- -f- "40 80 120 160 200 240 280 40 SO 120 160 200240 40 SO 120 160 200 240 NITROGEN RATE ( kg hd1 ) Figure. Maizegrai n yield response to N following different previous crops in cropping systems. Equations and R2 values: for MM y= 2,262+0,0233x-0,00002 x2, 0,99; for SM y= 4,414 + 0,0236 x-0,00004x2, 0,99; for A-A-A-M y= 4,778+0,0254x-0,00006x 2, 0,99; for W-M y= 6,248+0,0260x-0,00007x2, 0,96; for S-W-M y= 7,155+0,0196x-0,00005x2, 0,99; for W-RC-M y= 7,083+0,0115x-0,0002x2, 0,95; for S-W-RC-M y= 6,594+0,0132x-0,00002x2, 0,99; for S-W-OR-M y= 8,324+0,0090x-0,00002x% 0,98 In the dotted section ofth e lines measured yields are not significantly different. and then in S-M while in A-A-A-M yield significantly increased up to 160k gN ha"1.I n the rotations W-M and S-W-M wherewhea t wasth e previous crop and in W-RC-M and S-W-RC- M wherere d clover wasth e previous crop, atlo wN ratehighe r yields (7.2t o 7.8 t ha"1)wer e observed. Significant response to increased N ratewa s lesspronounced , up to 120t o 160k gN ha"1 and was stronger after wheat than after red clover. Oil rape in S-W-OR-Mrotatio n seemed to be aver ygoo d previous crop. At lowN rate of4 0 kgN ha"1lea fN was in optimum range and yield washig h and averaged 8.71 ha"1.Furthe r N rate increase gave no significant yield increase.

Conclusions On the poorly drained vertic amphygley the lowest maizegrai n yield and the greatest response to nitrogen fertilization was observed in monoculture and soybean-maize rotation and then after three years ofgrowin g alfalfa. After oil rape maizeyiel d was high and response to N was poor while after wheat and oneyea r red clover maizeyiel d and response to N were intermediate.

References Crookston et al., 1991.Agronom y Journal 83:108-113. Dumenil, L. C, 1961.Soi l Science Society of America Proceedings 25:295-298. National Academy of Science,Washingto n 1989.Alternativ e Agriculture. Larson, WE. et al., 1977. Corn Production. In Corn and Corn Improvement, ASA, Medison. Raimbault et al., 1991.Agronom y Journal 87:979-985. 488 Book of Abstracts 4th ESA-congress

MODELLING WORKABILITY OF LOAMY SOILS FOR SEED BED PREPARATION

G. Richard and H. Boizard

I.N.R.A., Unité d'Agronomie deLaon-Péronne , 02007 Laon CEDEX, France

Introduction Farm machinery and manpower often account for alarg e proportion ofth e running costs of farms innort h western Europe. Hence, they must beuse d as effciently aspossible . Oneo fth e major factor governingthi s efficient use isth e abilityt o predict soilworkability . Soilworkabilit y is often assessed subjectively byth e farmer asgoo d orbad , depending onth e soilwate r (vanWij k et al., 1988). There is anee d for abette r definition of soilworkabilit y sotha t the effects ofth etillag e timing on crop productivity canb e quantified. Soilworkabilit y mainly depends onth e soilwate r content, which determines the fragmentation ofth e seed bed andth e compaction ofth e sub-layers obtained after soiltillag e (Soane et al., 1981).Modellin gworkabilit y assumestha t soilwate r content canb e predictedfrom th e soil and the climatic conditions andfrom there , the resulting soil structure at soiltillag e asa functio n of soilwate r content and tillage characteristics. This paper presents theresult s of afield experimen t conducted inth e north ofFranc e onloam y soils (1)t o test anumerica l simulation model ofwate r and heat transport into the soil inwhic h the interactionsbetwee n soil and atmosphere are simulated and (2)t o establishth e relationships between superficial soilwate r content andth e aggregate sizedistributio n ofth e seed bed, deeper soilwate r content and thevolum e of highlycompacte d zonesunde r wheeltracks .

Methods Thefield experimen t comparing three cropping systemswa sbegu n in 1989i nMon s en Chaussée innorther n France (50°N, 3°E) in silt loam soilswhic h contained between 160-220 g clay kg"1. Spring crops (peas, sugarbeet , maize)wer e sown each year on different dates, consequently at various soilwate r profiles, with three levels oftyr e inflation pressure. Asoi lprofil e was done after each crop sowing. The severely compacted zones (Azones ) having amassiv e structure, no visiblemacropore s and ahig h cohesion were delimited manually. The effects ofwheelin g onsoi l compaction was expressed asth e percentage ofth e area ofth e cultivated profile immediately beneath wheel tracks that hadA zones incontac t with thebotto m ofth e seedbed . Aggregate size distributions were measured by sieving air-dried seed bed samples. Soilwate r content, water potential and temperature, and climatic conditions were measured continuously duringMarc h and April 1994t o calibrate the heat and water transport model of Chanzy et al. (1993) usedb y Richard et al. (1993) to studyth e soiltherma l regime asa functio n of soil structure. Thisi sa numerical model which calculates the changes inth efluxes a t the soil surface, the soilwate ran d temperature profiles asa functio n of climaticcondition s (solar radiation, airtemperature , air moisture, wind speed), andth e soil characteristics (albedo, roughness, bulk density, hydraulican d thermal conductivity, vapour diffusion, etc).

Results The soil structure resultingfrom see d bed preparation dependso nth e soilmoistur e and tyre inflation pressure. The percentage offine eart h (aggregate diameter <5 mm)decrease d inwe t conditions (Fig. 1).Th e percentage ofA area s increased with highertyr e inflation pressure inwe t conditions. Soilmoistur e limitsfo r seed bed preparation quality were defined. Session2. 2 489

- • m 60 • • S * *** : Figure 1 : «S-- Effects ofsoi lmoistur e onth e •« 20 • * ^ percentage ofaggregate s witha diameter <5 mmi nth e seedbe d n . i 1 i 1 • 1- * 0.15 0.2 0.3 Soil moisture 0-10 cm (g g-1 )

Thechang e in soil moisture with time in springwa sver y different asa functio n of soilcla y content. Water content gradients in soilwit h 16%cla ywer e lesspronounce d than those inth e soil with 22%cla y during drying. Thegradient s intoth e ploughed layerwer ewel l calculated byth e model after calibration ofth e relationships between the hydraulic conductivity andth e soil water content (Fig.2) .Nevertheless , the calculated changei ntopsoi l moisturewa sfaste r inth e soilwit h 22% clay and slower inth e soilwit h 16%cla ytha n the observed changes insoi lmoisture . The resultsfo r other drying periods inth e spring of 1994wer e similar.

~ d ! / i A i w I II ,' i Figure 2: u \' ' '\ ) A Observed (points)an d \l \s \ I A A calculated (lines) changes in soilmoistur e withtim e / \/ v inth eploughe d layerwit h 22% clay content

100 102 104 106 108 110 112 Dayo fyea r Conclusion Amode l simulating the change inth e water profile ofth e ploughed layer ofloam y soilsove rtim e invariou s climatic conditions wastested . The relationships between soilwate r profile and the resulting soil structure after seedbe d preparation were established. It wastherefor e possible to quantify the effect ofth etim e oftillag e onth e soilwate r profiles and on seed bed loosening and soil compaction. The length oftim e after arain yperio d until the first daywhe n seedbe d loosening ismaximum , orwhe n no severe compaction occurs canb ecalculate d asa functio n of soiltyp e and climatic conditions.

References Chanzy, A. et al.; 1993. Water Ressources andResearc h 29: 1113-1125. Richard, G. et al., 1993.Le s Colloques del'INRA , Paris, 67: 87-101. Soane, B.D. , et al., 1981.Soi l and TillageResearc h 1:207-237 . Van Wijk, A.L.M., et al., 1988. Impact ofWate r and External Forces on Soil Structure. Catena, Cremlingen, 129-140. 490 Booko fAbstract s4t hESA-congres s

OPTIMIZING N FERTILIZER SUPPLY OF WINTER RYE THROUGH QUANTI­ TATIVE MODELING - CALIBRATION AND PRACTICAL APPLICATION

G.M. Richter, A.J. Beblik, J. Richter

Dept. of Soil Science, Institut für Geographie und Geoökologie, Technische Universität, Langer Kamp 19c, D-38106 Braunschweig, Germany

Introduction Nitrogen fertilizer application still poses a problem to growers of winter rye. Its N demand is different from winter wheat and on sandy soils nitrate leaching in spring has to be consi­ dered, especially in catchments. Field trials were conducted to calibrate and apply a soil nitrogen dynamics and plant growth model. In detail the aims were (i) to calculate soil water and N supply, (ii) to find a crop specific growth curve and N concentration function and (iii) to compare yields at different fertilization systems (zero, farmer, extension, model).

Methods The N dynamics model (Kersebaum and Richter, 1991) simulates the water balance, N turnover in the soil and plant growth of winter wheat, the latter largely based on the SU- CROS approach (van Keulen et al. 1982). For the simulation climatic data (precipitation, mean air temperature, saturation deficit and sunshine hours) were available from a nearby weather station on a daily time step. In three years, soil (0-30, 30-60, 60-90 cm) and plant samples were taken at three different sites with sandy soil (95 % sand) to determine mineral nitrogen as well as dry matter and N content, respectively, at critical growth stages (EC 25- 28, 31,6 1 and 87). The temperature dependence of assimilation and the sums for the criti­ cal growth stages of winter rye were changed according to the literature (van Dobben, 1979; Kuhlmann, 1987; Römer, 1988; Kavanagh, 1992). The distribution of assimilates was fitted to the data collected at one site the first year and validated in the second year at all sites. An exponential function for the N concentration in the plant material was parametrized from measured N contents versus the phenologically active temperature sums. N fertilizer demand is calculated from the expected dry matter production according to predicted weat­ her (water availability, temperature and radiation) assuming unlimited N-uptake to meet the optimum N content also accounting for N supply from the soil and fertilizer.

Results straw without leaves ears o-« MEASURED *-* WW_MOD •-• WR MOD

E £< 40

'S 20

1 Apr 1 May 1 Jun 1 Jul 1 Aug 1 Apr 1 May 1 Jun 1 Jul 1 Aug

Figure 1: Measured vs. simulated dry matter with wheat (WW) and rye (WR) parameters. Session 2.2 491

Simulated soil water and mineral N contents principally agree within one percent and ±20 kgN ha"1 of measured values, respectively. The simulation of plant growth meets all impor­ tant phenological stages (EC 28, 31,61) . In agreement with long term observations (Römer, 1988) maturity of the grain (EC 89) is reached at lower temperatures than wheat. The growth curve and assimilate distribution of winter rye is significantly different from winter wheat (Figure 1), winter rye exhibiting rapid dry matter yield in April (EC 28 - 49). Dry matter yields can be predicted within 10 percent for several years at sites similar to that used for calibrating the model. At different sites, the dry matter yield may differ up to 30 percent due to local climatic conditions (frost, draught) which are not expressed in regional weather data and have to be accounted for using a site specific long-term yield potential.

Nopt'o r rye Ncriifo rwhea t •G MOD, CON - sto E - JFS E • O MOD, CON - «He D g S ZERO-N -stoD "d Figure 2: Measured N concentration "cô i \ (% d.m.) in the above ground dry 6 7 ^\ matter in the plots of ZERO-N and 1 e x~^ those fertilized ace. to CONventional and MODeled N requirement. e ™ 8 •---,..__ EC: 31 49 61 75 91 0 0 500 1000 1500 Phenolog.activ eTemp.- E(* Cdays )

Considering the rapid early growth of winter rye and the low N concentration of its grain (1.5% N) the fertilizer N has to be applied early, between EC 25 and 31.Fo r the period of tillering (EC 25-28) the N concentration must be maintained well above N^, for winter wheat (Figure 2), especially in production systems with low sowing density. On sandy soils 100 to 120 kgN ha"1 suffice to meet the N requirement for a 6 t ha"1 yield. Compared to conventional fertilization systems modeling plant growth and N uptake reduces the amount of N fertilizer by 20 to 30 percent without significant yield reduction of winter rye.

Conclusions • for winter rye dry matter production and distribution is different from winter wheat, • the exponential function for its optimum N content emphazises early N dressing, • temporal variation (10 yrs) of simulated yield and N demand is below 10 %, and • modeling improves the N balance without yield reduction.

References Kuhlmann F., 1987. Pflichtenheft für die Datenverarbeitung in der Pflanzenproduktion,DLG. Kavanagh S.E., 1992. Diss. Abstracts Intern. B, Science and Engineering, 52, 3370B-3371B. Kersebaum K.-C. and J. Richter, 1991.Fertilize r Research 27, 273-281. Römer G., 1988. Dissertation, Berlin, Techn. Universität, FB. Internati. Agrarentwicklung. van Dobben W.H., 1979. In: Alberda, Th. (Ed), Aula-boek 250. Het Spectrum, 313-396. van Keulen H. et al., 1982. In: Penning de Vries, van Laar (eds). Simulation of plant growth and crop production, 87-97. 492 Book of Abstracts 4th ESA-congress

LUCERNE ASA "NITRAT E SCAVENGER" FOR SILTY CLAY SOIL MANURED WITH PIG SLURRY

P. Spallacci1,E . Ceotto1, R. Papini2, R.Marchetti 1

1Istitut o Sperimentale Agronomico, Sezione di Modena, VialeCadut i inGuerr a 134,4110 0 Modena, Italy 2ISSDS, Firenze, Italy

Introduction The high concentration ofpi g livestock farms in somearea s ofth eNorther n Italy determines problems concerning theutilizatio n of nitrogen (N)from manures . Cropswit h highN content in theharvestabl e biomass offer achanc et o spread high amounts of animalwastes , avoiding negative environmental sideeffect s (Daliparthy et al., 1991).Th ehig hN needs oflucern e (Medicago sativa)ar eusuall y covered by symbiotic fixation whenther e islac k ofN inth e soil, but they canb efulfille d byth e substrate ifi t isric h enough inavailabl eminera l forms (Peterson and Russelle, 1991).Lucern e isa commo n crop inth epar t ofP o Valleywher e dairy cattle are reared for the "Parmigiano -Reggiano "chees eproduction . Therefore, lucerne canb ea n interesting alternative to excessive applications ofpi g slurryt o maize or other crops.

Methods Alucern e stand ("Garisenda" variety) was established insprin g 1993o n aVerti cUstochrep t soil at S.Prospero, Modena, inth e Low Po Valley. The second-year lucernewa streate d with increasing rates ofpi g slurry (Psl50, Ps300, Ps450 and Ps600 kgN ha"1 year"1) and a comparison with a mineralN supply asure a (F-150 and F-300 kgN ha"1 year'1) wa s also included. The design was a randomized complete block withtw o replications (plot size22.5x11. 5 m). Alltreatment s were splitted asfollows : 20%lat e inth e autumn, 30%a t the end ofth ewinter , 25%afte r the first forage cutting, and 25%afte r the second cutting. Thecro p was fully irrigated during the growing season with atota l amount of 120mm .Dr ymatte r yield andN content inth eforag e were measured for the five cuttings.Nitrat e and moisturefluctuation s were monitored inth e soil profile at various depths and times, sinceNovembe r 1993. Soil composite samples were frozen soon after collection and kept intha t wayunti l the analysis:nitrat eb y2 MKC l extraction and Technicon Autoanalyzer™determination ; moistureb ygravimetri c method.

Results Dry matter yield andN inforag e ofth elucern e did not show significant differences among treatments. The balance reported inTabl e 1 indicatestha t negativevalue s decreased when N application increased. Onlyth e supply of65 8k gN ha"1 from pig slurry determined a surplus ofN inth e system. However, nitrate inth e soilprofil e at the end ofth ebalanc e period did not increase, with respect to thebeginning , intha t case either.

Table 1.Nitroge n balance (kgN ha"1)fo r the second-year oflucern e stand Treatmem t Control F-150 F-300 Psl50 Ps300 Ps450 Ps600 N actually applied 0 150 300 173 340 500 658 N in lucerne forage 432 386 428 381 472 539 443 Difference: applied-removed -432 -236 -128 -208 -132 -39 215 Decrease of soil nitrate (*) 55 10 17 20 3 10 38 N fixed (-) or unaccountable (+) -377 -226 -111 -188 -129 -29 +253 (*) November 1994wit h respect to November 1993, in0- 1 msoi l profile Session 2.2 493

The soil nitrate monitoring over theyea r (Figure 1)showe d major increases asconsequenc e ofN applied at the end ofwinte r and after the second forage cutting. Theseincrease s appeared proportional to theN rate applied. No significant differences resulted from the sameamoun t ofN supplied by fertilizer or pig slurry. Nitrate contentswer e alwayslo w and not different among the treatments at the end ofth elucern e growing period (November 1994). Soil moisture monitoring (data not presented) pointed out that lucerne depleted soilwate r at the maximum of 1.6 mdept h reached late August.

11/93 12/93 1/94 2/94 3/94 4/94 5/94 6/94 7/94 8/94 9/94 10/94 11/94 Sampling date Figure 1. Soil nitrate (mgN kg"1)i nth e 0.0-0.2m soi l layer under different fertilizations Asdat a in Table 2 show, alltreatment s increased nitrate inth e 0.0-0.2 and 0.2-0.4m soi llayers , but onlyth e highest rate ofpi g slurry caused anincreas ei nth e 0.4-0.6 mlayer . Soilnitrat e at the depth from 0.6 to 1.0 m were never modified bytreatments , asfo r the depth from 1.0 to 2.0m (these data, not presented here, ranged from 0t o 4m gN kg"1a sindividua l samples, 97% of which werebelo w 2 mgN kg" 1). Table 2. Content of nitrate (mgN kg" 1)i nsoi l profile under lucerne, averagedfrom Novembe r 1993t o November 1994 Treatment Soil layer Sample number Control F-300 Ps300 Ps600 0.0-0.2 m 19 7.7 11.8 10.8 16.1 0.2-0.4 m 19 6.8 9.7 8.5 12.1 0.4-0.6 m 19 5.9 6.0 6.8 8.6 0.6-0.8 m 19 4.1 3.6 4.2 4.4 0.8-1.0 m 19 2.2 1.4 2.4 2.0

Conclusions The drymatte r yield andN removed inth e forage ofa second-year lucernewer e not influenced by the different fertilizations. TheN balance showed that N-fixation oflucern e seemst o decrease whenN application increase. Thetrend s of soilnitrat e duringth egrowin g season oflucern e and no accumulation ofnitrat e inth e soil profile showed that lucerne isa powerfu l and efficient "nitrate scavenger". Moreover, the deep root systeman d the highwate r requirements oflucern e reduced the probability ofleachin gevents . Thisbehaviou r ofth e lucerne stand seemst o providea feasible alternative in areaswher eth e agronomic utilization ofpi g slurry isa constraint . These results will becompare d to those obtained inth e subsequent year. Acknowledgements PANDAProject , Subproject 2, Series2 ,Pape r No.43 . References Daliparthy, J. et al., 1991. Agronomy abstracts. Annual meetings ASA-CSA-SSSA. Peterson, TA. and MP. Russelle, 1991. Journal of Soilan d Water Conservation, 5-6:229-235. 494 Book of Abstracts 4th ESA-congress

CULTTVARMIXTUR E STUDY ON WHEATYIEL D IN ROMANIAN CONDITIONS

V. Stefan, I. Savulescu, H.V. Halmajan

Bucharest University ofAgronomica l Sciences and Veterinary Medicine,Bd . Marasti nr. 59, 71331Bucharest , Romania

Introduction Economic situation ofRomani a influences croptechnologie s and some decisions inusin g harvest products. Thetransitio n to themarke t economy inRomani a isa difficul t and aver y complex process. Themai neffect s ofthi sproces s wereth eparcellin g out ofth eland , achang ei n farming and animalproductio n practices and adecreas e ofal lproductions . Eventh e associationswer e set up asa counterbalanc e to the parcelling ofth eland , it isdifficul t to usemoder ntechnologie s due to thebreakin gu p ofth eproperties . Alltechnologie s inputs(fertilizer s and pesticides) arever y expensive. Intenseutilizatio n ofth epesticide s inth e last period created somedisturbanc e in agricultural ecosystems, sometimesdeterminin gth e appearance ofpesticid e resistance forms of pests and diseases.Th eobjectiv e ofthi swor k wast o study one aspects of sustainable agriculture inwhea t (Triticum aestivum)technolog y (mixtureso fcultivars )whic hcoul d be an interesting solutionsfo r the present period from economical and ecological point ofview .

Methods The experiment were conducted underth efield conditions , inth efar m ofth e Bucharest University ofAgronomica l Sciencesan d Veterinary Medicine, on areddis h brown soil. Three Romanian cultivars (Flamura 85,Rapi d andDropia )wer e utilized inpur e andmixtur e culture. Two sowing dateswer e used: 20 October (the end ofoptimu m planting period inthi sregion ) and 5November . Plant densitywa s 550plant sm" 2.Folia r and earn diseaseproduce d byErysiphe graminis, andSeptoria sp .wer e controlled using Sportak- 45E C (prochloraz). Thetreatment s were applied inth e heading stage (10-2 inFeeke s scale, Soltner 1990).

Results Theresult sar e presented inth eTable . Thebes t resultswer e obtained for Rapid cultivar inal lth e experiments (planting datesan d fungicide treatment). Plant diseases dissemination varied according to the cultivars (pure or mixtureculture) , sowing date andfungicid e treatment. Therewa s apositiv e correlation between theresistanc et o thepathogèn efung i andth e grain yield (datano t shown).Fo r that reason the grainyiel d was significantly higherwhe n fungicide wasused . Onlytw o exceptions were noticed. For 20 October sowing date,th e mixtures of cultivars( Flamur a 85+Rapi d and Flamura 85+ Dropia) inno ntreate d experiment had (non significantly) higheryield scompare d to treated experiment. Inth e samecas eth emixture s ofth e cultivarsproduce d a significant higheryiel d than pure cultivation did. Theinfluenc e ofcultiva r mixtureso ngrai nyiel d is stronger inno n treated experiments. Session 2.2 495

Grainyiel d ofdifferen t wheat cultivarsgrow n inpur e and inmixtur e culture

Grainyiel d (tha" 1) Cultivars 20 October 5Novembe r Non treated Treated Non treated Treated Flamura8 5 5.00 c 5.46 b 4.28 b 4.74 c Rapid 5.50 a 5.59 a 4.51 a 5.23 a Dropia 4.77 de 5.02 b 4.45 a 4.99b Flamura 85 +Rapid 51.4a 5.36 b 4.11 cd 4.65 c Flamura 85+ Dropi a 5.17b 5.04 c 4.00d 4.77 c Rapid +Dropia 4.74e 5.68 a 4.54 a 4.75 c Flamura 85+ Rapi d +Dropia 4.87d 5.20 c 4.44 a 4.57d Meansi nth e samecolum nfollowe d byth e samelette r do not differ significantly P(>0.05).

Conclusions Someprinciple s of ecological agriculture (such asth emixtur e ofth e cultivars) couldb e a major chancefo r peasants farm to obtain positive results.Eve ni fth e quality ofmixtur ei sno tbette r than pure crop (but theyiel d ishigher) ,ther e isanothe r choice,becaus e moretha n ahal ffro m the Romanian livestock isfe d ina n extensivemanne r onth e peasant farms, where cerealsar eth emos t important feed.

References Soltner, D., 1990.Phytotechni e speciale. Colection "Sciences et TechniqueAgricoles" ,Angers . 496 Booko fAbstract s4t hESA-congres s

QUANTIFICATION OF NITROGEN DYNAMICS IN ECOLOGICAL MIXED FARMING SYSTEMS

E. A. Stockdale1,A .Agarwal 1,K . W.T . Goulding1 and S. C.Jarvis 2

Soil Science Department, IACR-Rothamsted,Harpenden , Herts.AL 52JQ .UK . 2 SoilScienc e Department, IGER-North Wyke,Okehampton ,Devon . EX20 2SB.UK .

Introduction Withina necologica lmixe d farming system,th e fertility-building grass-clover leyrepresent sth e mainsourc e ofnitroge n (N) for following arable crops.However , thereleas e ofN inform s anda t timeswhe ncrop s are ablet o utilize it efficiently isa ke yproblem . Wehav ebee n studyingN release and dynamics aspar t ofth e Organic Farming Study(OFS ) at DuchyHom eFarm , Tetbury. The OFS seekst o determine the economic, agronomic and ecologicalaspect s of sustainability and,ver y importantly, the interrelationships betweenthes e factors. DuchyHom eFar mi sa typica l UKmixe d farm withdairy , arable,shee p and beefenterprises ;th efirst field receive d organic accreditation in 1989whil e the last conventionallymanage d cropwa sharveste d in 1994.

Methods TheN dynamics ofa five yea r old grass-clover leyi nRe d Shedfield wer e quantified from ploughing (September 1994)t o theharves t ofth efirst winte rwhea t crop (August 1995).Fou r soiltype swer e identified inth efield (presente d inth etable) ;measurement s were made at 10m intervalsperpendicula r to soilboundaries ,t o account spatial variability. Percentage clover cover {Trifolium repens)an dN content ofth e grass-clover turfwer eassesse d before ploughing, N leaching losseswer equantifie d usingporou s cups,an d cropN uptake and soilminera l N were measured through spring and summer. Indiceso fpotentia lN mineralization (anaerobic incubation) andpotentia ldenitrificatio n (denitrifying enzyme activity,DEA ) were also measured inth e laboratory. These data wereuse d to compileN budgets for the soiltype s andth e whole field. Inaddition ,a simpl eN budget for thefield wa scompile dfrom th e available farm records.

Soilserie s identified inRe d Shedfield an d some ofthei r properties Soilserie s Position along transect Topsoil texture pH Haselor 5-55 m Clay/ clayloa m 7 Oxpasture 65-95 m Clayloa m 5.9 Waltham 105-155m Sandy (clay) loam 5.5 Oxpasture (gleyed variant) 165-225m Clayloa m 5.9

Results Thecove r ofclove r varied between 15an d 75% ;suc hvariatio n might be expected ina grazed field duet o heterogeneous excretary returns. Under UKcondition s the sward isestimate d to have fixed approximately 54k gN ha year"1 (Cowling,1982) .Th e grass-clover turf contained between 80 and 165k gN ha .Betwee nploughin g andth e onset of leaching approximately 40 kgN ha" 1 wasmineralize d inal lsoi ltypes . Throughout the leachingperio d (October-March) concentrations ofNO 3extracte dfrom th e porous cupsexceeede d the EEC limit for drinking waters (data arepresente d inth efigure); a spring emerging inth efield durin g January 1995 contained 12.5m gNO 3 -N1" ,als o slightly aboveth eEE C limit. The leachingpea k washighe r and earlier inth e sandy soilso fth e Waltham series. Cumulative leaching losses were not significantly different betweenth e soils:a naverag e of 129k gN ha' 1 was leached. The green wheat cropha d onlytake nu pbetwee n 2 and 10k gN ha" 1 overth e sameperiod . Session 2.2 497

Nitrate-N concentration (mg l"1) inwate r extractedfrom porou s cups at 50c mdept h in4 soil typesfrom Re d shed field

360 380 440 Julianda y 1994-1995 Haselor Oxpasture Waltham Oxpasture(g)

DEAmeasure d on soilssample d inMarc h 1995wa s significantly different between soils,Haselo r 90k gN h a day , Oxpasture andOxpastur e (gleyedvariant ) 48an d4 2k gN h a day" and Waltham2 5k gN ha"l day-1 " .Thes e ratesrepresen t thepotentia lfo r denitrification inth e soilan d are unlikelyt o have been achieved inth efield du et o lowtemperature s and a lack ofC an d N substrate. PotentialN mineralizatio n isals o significantly lower inWaltha mserie s soil.Tota lgrai n yieldsa t harvest were depressed byth e summer drought and were 1.2, 1.5, 1.3 and 2.11ha " on Haselor, Oxpasture, Walthaman d Oxpasture (gleyed variant) respectively.

Conclusions The datahighligh t the inefficient use ofN fixed durin g grass-clover leyphas e ofrotatio n inthi s cropping system. Aswidel yrecorded , the mainlos so fN isb yleachin g duet o the unsynchronized Nreleas e and cropuptake . Delayed ploughing andth eus e ofsprin g cropst o follow aploughe d leywoul d reduce theN loss (Phillips etal., 1995).Th e mainfeature s ofth e detailed budget were highlighted byth e simplebudget , but this involvedmuc h lessdat a collection effort. Suchsimpl e budgets canb ebuil t together to givewhol e farm nutrient budget, to increase our understanding of nutrient flows at farming system levelan d to better manageN flows t o minimise lossesan d maximiseplan t availability.

References Cowling,D . W.,1982. Biologicalnitroge nfixation an d grassland production inth eUnite d Kingdom. TheNitroge n Cycle. TheRoya l Society,London . 95-102. Phillips,L. , Stopes C.E . &Woodwar d L., 1995.Th e impact ofcultivatio n practice on nitrate leachingfrom organi c farming systems. SoilManagemen t inSustainabl eAgriculture , eds Cook H.F. &Le e H.C. WyeColleg ePress .488-496 . 498 Book of Abstracts 4th ESA-congress

VALIDATION OF CROPSYST FOR WATER MANAGEMENT ATA SIT EI N SOUTHWESTERN FRANCE

C. O.Stockle 1,M .Cabelguenne 2 andP .Debaeke 2

1Biologica l SystemsEngineerin g Dept., Washington State University, Pullman, WA 99164- 6120,US A 2INRA, Station d'Agronomie, BP27,3132 6Castane t Tolosan, France

Introduction Rainfall in the agricultural region around Toulouse, southwestern France,fluctuates fro m 400t o 800m m annually, concentrated during the winter months. Irrigation isrequire d to grow summer crops, and often supplementary irrigation isneede d for winter crops. Due to theerrati c natureo f rainfall, tools for strategic or/and tactical analyses of water management, such ascro p growth models, areneeded .Therefore , validation of the ability of models to simulate croprespons e to weather, soil, and water stress is important. This report summarizes work done to validate Cropsyst (Stockle et al, 1993;Stockl e et al., 1994)usin g datacollecte d by INRA at Auzeville (nearToulouse) ,France .

Methods Long-term experiments havebee n conducted inthi s location toevaluat e croprotation s at three input levels. Input level Iwa sunirrigate d andreceive d minimum fertilization; level IIreceive d limited irrigation andmoderat e fertilization; andleve l IIIreceive d full irrigation and fertilization. Three growing seasons were selected (1986,1989, and 1990),whic h corresponded todr y years, thus maximizing the severity of crop water stress.Thre ecrop s were simulated: maize, sorghum, and soybean. Biomass atharvest , grain yield, and seasonal ETwer e available for all years,crops , and irrigation levels.E Twa s estimated from aweekl y soil water balance based on neutron probe measurements. ETdat a for year 1990wer e found unreliable andno t used. For the simulations, weather and soil data, initial soil water content, and irrigation calendars wereinpu t as observed in the experiments. Cropparameter s were input asobserve d or asrecommende d inth e CropSyst manual (Stockle et al, 1993). Afe w parameters required calibration, which wasbase d on evolution of biomass,LA Ian d ET for input level III of each crop,availabl e for year 1986.

Results Figure 1 shows areasonabl e agreement between observed andpredicte d values,wit h a few noticeable outliers. Coefficients of determination arehigh , andregressio n lines areclos e toth e 1:1 line of perfect agreement. Experimental variability and some differences in the cultivars used for different years and input levels may explain some departures. Model failure to represent some underlying processes could not be evaluated with the available data. Statistical analysis (Table 1)confirme d areasonabl e model performance (Wilmott index of 1.0 implies perfect agreement).

Conclusions CropSyst was able toreproduc e cropgrowt h andyiel d observed in response to awid erang eo f water stress conditions for three crops in Southwestern France, indicating the feasibility of the use of themode l for water management applications inth e region. Session 2.2 499

Table 1.Statistica l comparison of observed and simulated biomass,yield , and ET for three crops and combinations of three years and three irrigation levels at Auzeville, France. Sorghum Soybean Maize Biomass Number of data points 8 9 Obs. average (kg/ha) 16684 .... 19038 Pred.average (kg/ha) 17280 .... 18370 RMSE/ Obs.averag e 0.067 — 0.143 Wilmott index 0.985 0.971 Yield Number of data points 8 9 9 Obs. average (kg/ha) 7601 2828 8026 Pred.average (kg/ha) 8060 2738 7494 RMSE / Obs.averag e 0.123 0.126 0.231 Wilmott index 0.963 0.975 0.958 ET Number of data points 5 6 6 Obs. average (mm) 372 412 416 Pred.average (mm) 407 440 410 RMSE/ Obs. average 0.139 0.097 0.039 Wilmott index 0.802 0.960 0.995 RMSE = Root Mean Square Error

^ 40 600 1-2 = 0.88 • / 1-2 = 0.91 a = 25.6 S 30 a =244 3 500 b = 0.98 //'A b = 0.86 n = 17 • ^ n = 17 J2 0 400 • // â1 0 300 • Sorghum • • Sorghum /A Soybean • Maize A Maize

0 10 20 30 40 200 300 400 500 600 Observedbiomas s(ton/ha ) Observed ET(mm )

15 • Sorghum r2 = 0.91 a = 284 r2 = 0.89 d 4 12 *S b = 0.87 a = 947 o b = 0.94 •-• &' TJ 3 n = 9 f/' n = 8 ,y7 • r2 = 0.84 'jf a = - 780 y '•3 3 b = 1.03 ••3 1 Soybean v *&~/y n = 9 u 0. /• " Maize 0 3 6 9 12 15 0 12 3 4 5 Observed yield (ton/ha) Observed yield (ton/ha) Figure 1.Graphica l comparison of observed andsimulate d data sets inTabl e 1.

References Stockle, CO. et al, 1994.Agricultura l Systems 46: 335-359. Stockle, CO. et al., 1993. Biological Systems Engineering Dept.,Washingto n State University, Pullman, WA, USA. 500 Book of Abstracts 4th ESA-congress

OPTIMISING LAND PRODUCTIVITY IN CROP-LIVESTOCK SYSTEMS BY INTEGRATING LEGUMES IN THE LOWLAND MOIST SAVANNAS OF WEST AFRICA

S.A.Tarawali1, J.W.Smith1, M.Peters12, L.Muhr2, R.Schultze-Kraft2 and G.Tarawali3 'International Livestock Research Institute (ILRI), UTA, Ibadan, c/o Messrs L.W.Lambourn & Co, Carolyn House, 26 Dingwall Road, Croydon, Surrey, CR9 3EE,UK 2University of Hohenheim (380), 70593 Stuttgart-Hohenheim, Germany Consultant, c/o ILRI, UTA, Ibadan, Nigeria

Introduction The lowland moist savanna of west Africa, covering 389 million ha of sub-Saharan Africa, is typified by annual rainfall of 600 to 1400 mm with 151 to 270 growing days (Jagtap, 1995). Cereal crops, grown by land-owning crop farmers predominate during the wet season; until recently, cattle keeping has been a separate enterprise with the animals relying on grazing rangelands, and crop residues after grain harvest. Nutrition, especially in the dry season is a severe constraint limiting ruminant productivity. Rising human population is forcing expansion of agriculture, meaning that even marginal soils are being cultivated for crops, and the luxury of long fallow periods to restore fertility (in the absence of inorganic inputs) to the inherently poor soils no longer exists. This inevitably forces a closer integration of crop and livestock enterprises,which , if appropriately managed has the potential to become synergistic. Research by the International Livestock Research Institute in Nigeria has focused on introducing forage legumes into these evolving systems to optimise land output in a sustainable manner. Experiments have been conducted to test the ability of such species to provide nutritious ruminant fodder, promote soil fertility, arrest soil physical degradation and reduce weed infestation in crop fields. This presentation summarises the major findings in these areas.

Methods Initial experiments focused on identification of the most appropriate forage legume species, for fodder use and included measurements of agronomic and quality parameters. The identified species were also assessed for their direct effect on cereal production. Management options to maximize the impact of forage legumes have been investigated and these include appropriate utilisation of different species depending on their phenology and selective weeding of crops in leguminous pastures to ensure maximum forage and grain yields. A collection of Aeschynomene histrix accessions has been investigated for their ability to reduce incidence of Striga hermonthica,a parasitic weed of cereal crops.

Results Forage legumes with better quality and much higher biomass than the natural vegetation can be grown in the Nigerian Savannas (Table 1). The natural, unimproved fallow consists mainly of grasses which for most of the year, cannot meet ruminant requirements. When maize is grown on land following forage legumes, substantial increases in grain yield are recorded (Table 2). Increases greater than 400 % reflect areas where the soil was so poor that grain yield from natural fallow plots was negligable. Smaller changes arose where soil was less degraded and fallow period was short or the legume areas were unweeded and grazed prior to the cropping. Crop management practices, such as selective weeding have been shown to ensure good forage quantity and quality following maize cropping (Tarawali et al., 1995). From a collection of 64 accessions of Aeschynomene histrix, 9 accessions were Session 2.2 501 identified with potential to give good forage and act as a trap crop for Striga hermonthica (Merkel, unpublished).

Table 1. Maximum forage quantities and qualities of promising forage legumes, and natural fallow in the Nigerian moist savanna.

Species Accession Dry forage % crude %in sacco References number tha-' protein digestibility Aeschynomene histrix ILCA 12463 12.5 13 52 Tarawali, 1994; Peters,unpub . Centrosema brasilianum ILCA 155 4.5 15 48 Tarawali, 1991;Peters , unpub. Centrosema macrocarpumClAT 5713 3.9 18 51 Muhr, unpub.; Peters,unpub . Centrosema pascuorum ILCA 9857 4.8 13 51 Tarawali, 1991;Peters , unpub. Centrosema pubescens ILCA 152 4.0 20 50 Muhr, unpub.; Peters, unpub. Chamaecrista rotundifolia ILCA 10918 7.0 11 47 Peters etal., 1994;unpub . Stylosanthes guianensis ILCA 164 13.6 11 52 Tarawali, 1994; Peters, unpub. Stylosanthes guianensis ILCA 15557 3.3 11 59 Tarawali, 1994; Peters, unpub. Stylosanthes hamata ILCA 75 6.2 11 49 Peters etal., 1994;unpub . Stylosanthes hamata ILCA 15876 4.8 12 48 Tarawali, 1995; Peters,unpub . Natural fallow 6.5 4 30 Peters etal., 1994 ; Muhr.unpub.

Table 2. Increases in maize grain yield (with no added N fertilizer) following forage legumes as compared to natural fallow. (History refers to the age of the forage legume prior to cropping the maize (year); ungrazed = weeded experimental plots; grazed = unweeded, grazed pastures)

Species Accession History % increase in maize grain References number year/type yield over natural fallow Aeschynomene histrix ILCA 12463 3/ungrazed 733 Tarawali, 1994 Centrosema macrocarpum CIAT 5713 1/ungrazed 27 Muhr, unpub. Centrosema pascuorum ILCA 9857 3/grazed 50 Tarawali et al., 1996 Centrosema pascuorum ILCA 9857 3/ungrazed 600 Tarawali, 1994 Centrosema pubescens ILCA 152 1/ungrazed 69 Muhr, unpub Chamaecrista rotundifolia ILCA 10918 3/grazed 251 Tarawali et al., 1996 Stylosanthes guianensis ILCA 164 3/ungrazed 811 Tarawali, 1994 Stylosanthes guianensis ILCA 15557 3/ungrazed 1166 Tarawali, 1994 Stylosanthes hamata ILCA 75 3/grazed 94 Tarawali et al., 1996 Stylosanthes hamata ILCA 75 3/ungrazed 466 Tarawali, 1994 Stylosanthes hamata ILCA 15876 3/ungrazed 750 Tarawali, 1995

Conclusions By integrating forage legumes into farming systems in the moist savannas of west Africa, both ruminant and crop yields can be maintained, without detriment to the environment.

References Jagtap, S.S., 1995. Moist Savannas of Africa. Potentials and Constraints for Crop Production. Ed. B.T.Kang et al UTA, Ibadan, Nigeria, p. 9-30. Peters, M. et al., 1994. Tropical Grasslands 28: 65-73 Tarawali, S.A., 1991. Tropical Agriculture (Trinidad) 68: 88-94 Tarawali, S.A., 1994. Journal of Agricultural Sciencel23: 55-60 Tarawali, S.A., 1995. Australian Journal of Experimental Agriculture 35: 375-379 Tarawali, G. et al., 1995. Soil Management in Sustainable Agriculture. Ed. H.F. Cook et al Wye College, UK. p. 435-443. Tarawali, S.A. et al, 1996. Journal of Agricultural Science, in press. 502 Booko fAbstract s4t hESA-congres s

GROWTH AND NITROGEN ACCUMULATION OF WINTER RYE AS A CATCH CROP: MODEL AND EXPERIMENT

A.M. van Dam1, J. Vos2,J .Wolfen 1, E.A. Lantinga1 and P.A. Leffelaar1

Wageningen Agricultural University,l Dept. ofTheoretica lProductio n Ecology. 2 Dept.o f Agronomy. P.O.Box 430, 6700 AKWageningen , The Netherlands.

Introduction Cultivation ofcatc hcrop s after theharves t ofth emai n crop,i nth eotherwis e fallow autumn and winterperiod , canreduc eN leaching .Fiel dexperiment s showa larg evariatio n incatc hcro pN uptake for different sowing dates,cro p species andlocations .Th e aimo f our study ist o explain this variation andt o assess how much Nca nb etake n upb y catch cropsunde r various conditions. Tothi s aim,a nexplanator y simulation modeli sdevelope d tocalculat e catchcro p growth andN accumulation. Iti scouple d toa soi lwate r andnitroge n modelt oestimat eth eeffec t onN leaching . Thispape rpresent sth emode lfo r potentialgrowt ho fwinte rry e(Secale cerealeL. )a sa catc h crop. Iti steste d with results of a field experiment.

Methods Thecro p growth model isbase d on SUCROS (Spitters et al., 1989),a suse d for simulation of growth ofwinte rwhea tb y Groote tal . (1991).Th efollowin g adaptationswer emade .Th ery e cropi smodelle d inth evegetativ e phase;th e shootsconsis t ofleave sonly .Th eN concentratio n in the shootdecrease sexponentiall y withth etemperatur e sumafte r cropemergence , approachinga level of 2.47 %abov e 1400 °Cda y (basetemperatur e is0 °C).Th eN concentratio n inth eroo t isa fixed fraction (0.46)o f theconcentratio n inth e shoot.N i sassume d not tolimi t growth: Nuptak e isdetermine db yth ecro pdemand .Lea f areainde xi sa linea r function ofth eamoun to forgani cN inth e shoot.Temperatur e andradiatio n levels duringlea f development determineth eligh t saturated assimilation rate(Sheeh y et al., 1980).Assimilatio n is independent of theN concentratio n inth e shoot. Aconstan t fraction (0.124) of assimilates isallocate d toth eroots .Th erat e ofN uptak erises withtemperatur et o amaximu mvalu ea toptima ltemperatures .Leave sliv edurin g afixe d lifespan: 443 °Cdays .Cro p growthwa s parameterised withresult s from afiel d experiment. Cropgrowt h andN uptak e were simulated using weather datafro m Wageningen, the Netherlands. Simulation results arecompare d witha nindependen t datase tfro m afiel d experiment in Wageningen, inwhic h winter rye (cv.Halo ) was sown in a sandy soil on 21Augus t 1992.I t was fertilised by 50k gha -1 N, supplied ascalciu m ammonium nitrate,a t sowing,an db y 25k g ha-1N at 14,28 ,4 2 and6 3day s after sowing.Plan t shoots androot s were sampled regularly to determine weights,N concentration s andlea f area.

Results Thetrend s inroo t and shoot biomass (Figure la),cro pN conten t (Figure lb) and leaf areainde x (Figure lc) arewel l simulated.Th ebiomass ,amoun t ofN i n thecro p andlea f areaincreas e until theen d of October. After that,ther e is ane t decrease in shootbiomass ,N and leaf area index, because shootgrowt hrat ei slowe rtha n shootdeat hrat eunde rwinte rconditions .Th elowe r growth ratei sexplaine d by adecreas e inth eligh t saturated assimilation ratei nth e secondhal fo f October (Figure Id), and lowerradiatio n andtemperatur e levels (datano tshown) . Levels of shoot androo tbiomas s are somewhat overestimated, whereas the amount of cropN i s underestimated. This impliestha t theN concentratio n that wasimpose d inth e model,i sto olo w for thiscrop ,grow n ata ver y highfertilisatio n rate.Th eligh tsaturate d assimilation ratefluctuate s in time,reflectin g fluctuations intemperatur e andradiatio n intensity during growth ofth eleaves . Session2. 2 503

Conclusions The model simulatestrend s in growth ofroo t and shootbiomass ,an dN accumulatio n well,bu t predictions ofth eexac t amounts can still beimproved . Themode lwil lb efurthe r validated. To explain the nitrogen accumulation bycatc h cropsi nagricultura lpractice ,th emode l willb eadapte d to simulate the Nlimite d growth of ryean dothe rcatc h crops.Model s for soilN dynamic s under autumn andwinte rcondition s andfo r watertranspor t aredevelope d toasses sth eeffec t of catch cropcultivatio n on Nleaching .

4500 Figure 1.Tim ecourse s of simulated (lines) andmeasure d (symbols) variables during the catch crop growing season. a.Biomas s (dry weight) of shoots (thinlin ean dclose d symbol) and roots (thicklin ean d open symbol) b. Amount ofN i nth ecro p c.Lea f areainde x d.Ligh t saturated assimilation rate (AmaxXmodelle d according to Sheehy et al. (1980),calibrate d withdat a from VanDa m(1994) .

References Groot, J.J.R. et al., 1991. Fertilizer Research 27: 261-272. Sheehy, J.E. et al., 1980. Annals of Botany 46:343-365 . Spitters, C.J.T. et al., 1989. In: Rabbinge,R . et al. Simulation and systems management incro p protection: 147-181. PUDOC, Wageningen. Van Dam, A.M., 1994. Proceedings 3rd ESA Congress, Abano-Padova: 264-265.

date 504 Book of Abstracts 4th ESA-congress

CROPSYST-WITH-OBJECTS 3.0: GEARED FOR COMPARISON OF COMPONENT MODELS

F.K. van Evert1 and J.M. Baker2

'Department of Soil, Water and Climate, University ofMinnesota , 1991Uppe r Buford Circle, St. Paul, MN 55108,US A 2USDA-ARS, University ofMinnesota , 1991 Upper Buford Circle, St. Paul, MN 55108,US A

Introduction One ofth e design goals of CropSyst wast o determine howth e performance of a cropping systems simulation model would beinfluence d by different models of acomponen t ofth e system (VanEver t et al., 1994;Va nEvert , 1992).A CropSys t simulation model therefore consists of component models which interact through anarro w and well-defined interface (McCown et al., 1996; Van Evert et al., 1994;Va nEvert , 1992;Crosb y et al., 1990).Thi s ison e ofth e tenets of object-orientation and, inprinciple , it opens the road for combining and comparing component modelstha t were developed by different groups. In practice, the fact that not allgroup s useth e sameprogrammin g language hasmad ethi s lesstha n straightforward. Inthi s paper, we examine the usefulness ofdynami c link librariest o ease, inconjunctio n with object-orientation, the integration of component modelswritte n indifferen t programming languages. Model performance isjudge d via acompariso n with observations made inexperiments . Some of the descriptive data of an experiment are required byth e model asinput . Asimulatio n model then generates a large amount of output which relates to the sameexperimenta l units that observations were made on. The logical connection between observations, model input and model output makes it desirable to managethe m together. In the second part ofthi s paper, we consider the use of adatabas e for this purpose.

Methods In CropSyst, all modeled real-world processes are represented in one ofth e component models. Component models are controlled through the procedures Initialize(), CalcRatesQ and UpdateState (). Component models communicate with each other via messages through the central message handling mechanism. Each component model implements aprocedur e RequestQt o request an item and aprocedur eRespondQ to supply an item inrespons e to areques t (Fig. 1). Thus, a component model needst o implement onlyfive procedure s to integrate with CropSyst. Component models written indifferen t languages can communicate as long asther e is a standard interface for these procedures. Dynamic link libraries (DLLs) provide such an interface because they contain executable code that (when compiled withth e STDCALL directive) is largely independent ofth e source code language. CropSyst iswritte n inDelph i 2.0 (Borland, 1996) for Windows 95.W euse d Powerstation 4.0 (Microsoft, 1995;othe r compilers provide similar capability) to compile several existing modelswritte n inFortra n andus e them in CropSyst. Figure 1.Component s communicate via messages Messaging through the messaging mechanism. When the mechanism crop component requests information (1), the messaging mechanism queries each ofth e other component models intur n (2,3). Inth e Figure, the soil component is ablet o supply the requested information (4) which isrange-checke d byth e

| Weather ] [ Crop | ( Soil | messaging mechanism before it ispasse d to the crop (5). Session2. 2 505

Each component model requires inputs at thebeginnin g ofth e simulation run. Some ofthes e inputs, such asth e planting date of acro p and the amounts of irrigation water applied, form part ofth e descriptive data ofth e experiment being simulated. We designed and implemented a general, stand-alone experiment database from which component models can extract these kinds of information. The database consists ofa set ofParado x tables (Borland, 1994)whic h are accessed efficiently from aDelph i application through theBorlan d Database Engine (Borland, 1995). Access routines could alsob e compiled intoDLL s for use from programs written in other languages. The experiment database stores all observations relativet o experimental units such astreatments , plots, and sampling locations. The database design permits anunlimite d number of linksbetwee n these units, sotha t atreatmen t mayb e allocated to anynumbe r ofplots ;plot sma yb e nested within other plots to any depth; and awid evariet y ofdesign s (e.g. unbalanced; Latin-square) can be accomodated. Because simulation output relates to the same experimental units that the experimenter collected data on, it can be stored conveniently inth e samedatabase .

Results CallingDLL s compiled with PowerStation from aDelph i application gave no problems. Some modification of existing models isrequire d before they answer to the CropSyst interface. For a well-structured model, this modification does not require much work. One restriction istha t interaction between component models islimite d to the one-day time step that CropSyst uses. Theus e of adatabase , even though its design isstil l relatively immature, hasprove n useful. For example, havingbot h experimental data and simulation results available inth e sameforma t made it easyt o develop a simple graphing application that automates the process of comparing the two.

Conclusions Monteith (1994) has exhorted modelers to remove from crop models 'components that contribute noise rather than numerical precision to thefinal output' . Applied to cropping systemsmodels , this could betranslate d to usingthos e component modelstha t most improve theprecision/nois e ratio ofth e systems model inwhic h they are used. Whileth e previous version ofCropSys t could already be used to compare component models, this capability hasno w been extended to include models written indifferen t programming languages. Such a comparison ismad e even easierb y CropSyst'sintegratio n with an experiment databaset o allowfo r rapid setup ofinpu t data and joining of measured and simulated performance.

References Borland International, Inc., 1994.Parado x 5.0. Scotts Valley, CA,USA . Borland International, Inc., 1995.Borlan d Database Engine. Scotts Valley, CA,USA . Borland International, Inc., 1996.Delph i 2.0. Scotts Valley, CA, USA. Crosby, C.J., et al., 1990. Asimulatio n modeling tool for nitrogen dynamics using object- oriented programming. AI Applications in natural resource management 4:94-100. McCown et al., 1996. APSIM- A nove l software system for model development, model testing and simulation in agricultural systems research. Agricultural Systems 50:255-271. Microsoft Corporation, 1995.Powerstatio n 4.0. Redmond, WA,USA . Monteith, J.L., 1994. The quest for balance incro p modelling. p25 inAS AAbstract s 1994. VanEvert , F.K., 1992. Pullman, WA,USA , PhD Thesis, University ofWashington , 83p . Van Evert, F.K. et al., 1994. CropSyst: acollectio n ofobject-oriente d simulation models of agricultural systems. Agronomy Journal 86:325-331. 506 Book of Abstracts 4th ESA-congress

WATER USEEFFICIENC Y OFNIN E CROPPING SYSTEMS INA WATE R LIMITED ENVIRONMENT

D. Ventrella, M. Rinaldi, V.Rizz o andF . Fornaro

Istituto SperimentaleAgronomico , ViaC . Ulpiani 5, 70125 Bari, Italy

Introduction InMediterranea n areas,wher e amount and distibution ofwate r supply are major determinants of cropyield , the choice ofa cropt o insert ina rotatio n must be considered taking into account the abilityi nwate r suction, lenght ofcro p cycle, productivity, effects on following crop and, mainly, water use efficiency in saleableyiel d production.

Methods Ninecroppin g systems (Table)wer e compared ina long-ter m trial (1986/87 - 1993/94)carrie d out atFoggia , Southern Italy (lat. 41° 27"N , long. 3°04 "E) . The soili sa vertisoi l (Typic Chromoxerert)wit h agoo d fertility; typical values ofvolumetri c water content atfield capacit y and permanent wilting point were 42%an d 21%, respectively. 1 1 1 Fertilizer amount was, except for soybean, 150k gN ha" ,20 0 kgP 205 ha" an d 50k gK 20 ha' ; irrigation water was delivered at Dw (winter sowing) only if severewate r stress occours, while about 200-400 mmpe ryea rwa sapplied , depending on soilmoisture , to the othercrops . At harvest, saleableyiel d (roots for sugarbeet ) and aboveground dry matter were measured for each crop andthe nyearl y added up for each rotation. Soilwate r content at 0-60 cmdept hwa s Table 1- Rotation s in experiment. measured at 7-dayinterval swit hgravimetri c Crops Abv. Figl methods. Seasonal water use (WU)wa s Durum wheat W a calculated for each crop andthe n for each Dw + sorghum W+G d rotation using ahydrologica l balance inwhic h Dw + soybean W+Y d runoff and deep percolation were neglected. Dw - sugar beet W-B b Water use efficiency for aboveground dry Dw - sunflower W-F b matter (WUEb) and for grain yield (WUEy) Dw - sorghum W-G b were calculated asth e ratio ofdr y matter and Dw+ soybean - sugarbee t W+Y-B c grain yield to seasonal WU. Further information Dw + soybean - sunflower W+Y-F c onexperimenta l design and crop management Dw + soybean - sorghum W+Y-G c are reported byRizz o et al. (1993).

Results Therainfal l inth e period investigated waslowe rtha n thelon gter m average (430 vs 585m m year"1)especiall y in 1991 and 1993. Atth e sametim ewate r resources were reduced because of lowering ofth ewate r table, sinceth e amount of irrigation water supplied decreased through years. TheW U decreased duringth e 8year s oftrial , particularly between the 1990 and the 1992 showing alarg evariabilit y inth e 1-yearan d 2-year rotationswit h summer catch cropstha t grow during aperio d characterized byver y high evapotranspirative demand and water requirement (Fig. 1). Besidesth e "W"rotatio n with 332 mmyear" 1, alsoth e "W-G" and the "W-F"rotation s with seasonal WU ofabou t 415 mm, represent reduced cropping systemswit h alo w water consumption. Inth efigur e 2w e can note thevariabilit y of "W"fo r WUEy parameter because ofth e influence of drought during reproductive phase on harvest index of durum wheat (Passioura, 1977). The rotations with sugarbee t had ahig h meanWUE y (thankst o ahig h harvest index) the samewa s Session 2.2 507

1000 true for grain sorghum which isals o aresul t of a positive effect of sorghum on following durum wheat (Di Bari et al 1993; Rinaldi eta l }•••••* 1994). 800 /\ \ Experimental data of WUEbvarie d less among / \ •• / yearstha n WUEy. The rotations with grain Y \\ - •••' d"1 sorghum, either as main or catch crop, were § 600 .- / the most efficient inwate r use (C4 crop) with \ 1 1 / h^-j a meanvalu e of 31.2 kg ha' mm' . The IV A \\ \ \ / addition of soybean in 1-yea ran d 2-year / rotations generally reduced the WUEb values 400 / Y"--f-""" because ofth e low productivity ofbiomas s ina h* y soybean catch crop. \ /* 200 87 88 89 90 91 92 93 94 Year Figure 1- Seasonal water use of different crop rotations (see tab. 1)

2 WUEy 1.5 I ï _ ï ï Ï ï ï 0.5 I 2 I WUEb § 1.5 ï ï 1 —I— —-_-- __.__J.____ M ---_•-- ï Ï ï 0.5

W W+ G W+ Y W-B W-F W-G W+ Y- B W+ Y- F W+ Y-G Rotation

Figure 2- Water use efficiency index: for WUEy 9.2 Kg ha"1mm" 1= 100;fo r WUEb 26.2 Kg ha"1mm" 1 = 100.

Conclusions In thetria l environment, with hot-drought summer, the incomplete availability ofwate r supply, the use of catch crops, especially soybean, reduced theWUE b ofwhol e cropping systems. The rotations with grain sorghum, showed ahig h water use efficiency or had positive effects on next durum wheat crop. References DiBari, V. et al., 1993.Agricoltur a Ricerca, 151/152, 15-22. Passiuora, J. B., 1977.J . Australian Institute Agriculture Science,43 , 117-120. Rinaldi, M., et al., 1994.Proceeding s 3rd ESA Congress, 740-741. Rizzo, V. et al., 1993. Agricoltura Ricerca, 151/152,57-68 . 508 Book of Abstracts 4th ESA-congress

IMPORTANCE OFUNDERPLAN TCRO PAN DFARMYAR DA SMANURE SI N MONOCULTURE OFWINTE R TRITICALE

A. Wozniak

Department Soilan dPlan tCultivation ,Agricultura lUniversity ,20-95 0Lublin , 13 Akademicka Str., Poland

Introduction Monocuhuralgrowin go fwinte rtritical elead st o adecreas ei ngrai nyiel dan delement so fyiel d structure(Pawlowsk ian dWozniak , 1994;Wozniak , 1993).I nthes econdition sincreasin gweedines s andsusceptibilit yt o culmbas edisease sar eals oobserve d(Kus , 1993;Wozniak , 1995).I tha sbee n suggestedi nth eliteratur e(Laskowski , 1972;Rosza k etaL , 1982)tha tgrowin go fgreen-manur ecrop s andplant spreventin goccurrenc eo fdisease san dpest si sa neffectiv e method oflimitin gth egrai nyiel d declineo fcerea lcrop sgrow ni nmonoculture . Inthi swor kth einfluenc e ofplowin gunde ro fgreen - manureintercrop san dfarmyar d manureo ngrai nyiel dan dsom eelement so fyiel dstructur eo fwinte r triticalewa sevaluated . Theeffectivenes s offungicide suse dwa sals oestimated .

Methods Fieldexperimen twa sestablishe di n 1988a tUhrus kExperimenta l Stationo fLubli nAgricultura l University.Presente dresult swer ecollecte di n 1991-1994.Th eexperimen twa sestablishe di n a randomizedbloc kdesig nwit h37. 5m 2plot si n4 replications .Th esoi luse dwa srendzin a ofligh tloa m texture.Th esubject so fth eexperimen twere : I.Regeneratio n ofsoi lb yth eus eof : (A) farmyard manure(FYM )- 30 1ha" 1 plowedunde rever y4 year s; (B)FY M-15 1ha" 1 plowedunde rever yyear ; (C)undersow ngreen-manur e Serradella(Ornithopus sativus L.) plowe dunde ryearly ;(D )undersow n green-manure Italianryegras s{Lolium multiflorum v. westervoldicum Wittm.)plowe dunde rever y year. H Plantprotection :(a )withou tfungicide s (control) ; (b)wit h theapplicatio n offungicides . Green-manure cropsLe .Serradell aan dItalia nryegras swer eundersow nt otritical ei nth eamoun t of4 0 kgha" 1betwee n 15than d30t hApri ldependin go nth eyea ro fstudy .FY Mwa suse d everyyea ro r everyfou ryear so nth estubbl ean dplowe dunde rb yskimmin gan dthe nb ypresowin gplough .Winte r triticalecv .Boler owa ssow ni nth eamoun t of40 0germinatin gseed sbetwee n 20than d25t h September. Thisabstrac tinclude sonl ymea nvalue so fgrai nyiel dan delement so fyiel dstructure , obtainedi nth eyear s 1991-1994.

Results Plowingunde ro f 15 or30 1ha" 1 of FYMprove dt ob eth emos teffectiv e methodo fsoi lregeneratio n withmonocultur e ofwinte rtriticale .Th egrai nyiel do ftritical eobtaine d onthes eplot swa s20 %highe r thantha t obtained onplot swher egreen-manur eItalia nryegras sa saftercro p wasplowe dunde r(Tabl e 1).Fungicide suse dfo r plantprotectio n showedt oris eth egrai nyiel db y7-8% ,bu t onlyo nplot swher e FYM(30 1ha" 1) andSerradell aa saftercro p wereplowe dunder .Yiel dstructur eelement s(numbe ro f earspe r 1 m2,weigh t 1000grains ,numbe ro fgrain spe rear )wer ehighes to nth efarmyar d plowed underplots .However , application offungicide s showedn osubstantia leffec t onth evalue so fthes e yieldelements .

Conclusions Thedeclin eo fgrai nyiel do fwinte rtritical emonocultur e canb epartl ycounteracte db yapplyin g farmyard manure.Plowin gunde ro fgreen-manur e Serradella asaftercro p producedwors eresult san d thato fItalia nryegras sshowe dt ob eth eleas teffectiv e method. Thiswa sdu et o smallyiel do fgree n mass( 6-10 1ha" 1)produce db ythes eaftercrop s andincrease dsusceptibilit yt o culmbas ediseases . Session 2.2 509

Fungicidesuse d inthes econdition s showedn oessentia l effect onth egrai nyiel d andcro pyiel d elementsstudied .

Table 1.Grai nyiel do fwinte rtritical ean dsom ecro pyiel delement s(mea no f4 years )

Soil Plant Grain Ear number 1000grain s Grain number regeneration protection yield per m2 weight (g) per ear method tha"1 A-FYM no fungicides 3.8 461 38.9 41.8 fungicides 4.1 453 39.1 41.8 301 ha1 mean 4.0 457 39.0 41.8 B-FYM no fungicides 4.1 462 38.0 40.4 fungicides 4.1 451 38.8 41.3 15tha_1 mean 4.1 457 38.4 40.8 C - under- no fungicides 3.4 423 37.5 40.5 sown fungicides 3.7 418 37.8 41.5 serradella mean 3.5 420 37.6 41.0 D -unde r - no fungicides 3.3 416 37.8 38.9 sown fungicides 3.2 412 38.4 38.1 Italian mean 3.3 414 38.0 38.5 ryegrass LSD (p=0,05) 0.2 15 1.2 1.9

References Kus, I, 1993.Wyd . IUNG,Pulawy . Laskowski, St.,1972. Zeszyty Problemowe PostepówNau k Rolniczych, 137 :121-128 . Pawlowski, F., Wozniak, A.,1994. Fragmenta Agronomica, 3 : 40-45. Roszak, W., et al., 1982.Rocznik i Nauk Rolniczych, ser.A, 105,2 : 97-105. Wozniak, A.,1993 . Fragmenta Agronomica., 4 : 45-46. Wozniak, A,1995. Annales Univ. Mariae Curie-Sklodowska, sec.E, vol.L,3: 13-20. 510 Book of Abstracts 4th ESA-congress

DEVELOPMENT OF A SUSTAINABLE BED-PLANTING-TECHNOLOGY TO ALLOW REDUCED-TILLAGE AND CROP RESIDUE MANAGEMENT IN FURROW-ntRIGATED WHEAT PRODUCTION SYSTEMS K. D. Sayre CIMMYT, Apdo. Postal 6-641, 06600, Mexico D.F., Mexico Introduction Irrigated wheat (flood or furrow irrigated) accounts for nearly 35% o f wheat area and about 45% of total production in developing countries. In south Asia alone (India, Nepal, Pakistan, Bangladesh and Nepal), nearly 25 million ha of irrigated wheat are grown and an additional 13 million ha are sown in China. Sizable areas are also grown in other developing countries including Turkey, Afganistan, Iran, Egypt, Sudan, Nigeria, Mexico and Chile. A substantial part of this irrigated wheat is grown in rotation with other upland crops such as cotton, soybean, maize and sorghum using surface irrigation. Such production systems have been largely by-passed by technologies that allow reductions in conventional tillage practices and/or opportunities to manage crop residues without resorting to costly incorporation, removal or, most commonly, burning. Wheat agronomists at CIMMYT have initiated research to develop a furrow-irrigated reduced-till bed-planting system (FIRBS) to overcome these limitations based on the conventional-tilled wheat planting system on beds currently used by farmers in northwest Mexico.

Methods Several trials have been initiated over the past four years comparing furrow-irrigated wheat- maize systems planted on 75 cm beds with either conventional tillage with beds reformed for each crop or with superficial reshaping of the beds at the time of crop establishment without tillage. Variable crop residue management practices are being tested including incorporation, burning, partial removal and complete retention. Nitrogen management is also being evaluated for each tillage and crop residue management strategy and N-uptake patterns are being assessed. Disease and weed interactions with these treatment effects are also being monitored. Adaptations to available seeding and bed-shaping equipment have made it possible to plant two or three rows of wheat on each bed with reduced tillage in the presence of sizable quantities of crop residues (6-8 t/ha).

Results The trials have shown that wheat can be successfully planted on beds occupied by the previous summer crop (either maize or soybean) with the only tillage before wheat planting being a minor reshaping of the summer crop's beds with full retention of crop residues. Proper management of the crop residues can reduce their interference with irrigation in the furrows between the beds. Maize and soybean planted similarly after wheat have been satisfactorily established with an apparent advantage to both crops yields when the previous wheat crop's residues are left in place, perhaps due to better moisture retention during the hot summer. The bed system also offers advantages for N placement and timing that enhance nutrient use efficiency especially in the presence of crop residues.

Conclusions The strategy of using a bed-planting system as a basis to reduce tillage and manage crop residues for surface-irrigated production systems that include wheat offers many new and useful approaches to develop potentially more sustainable crop management practices. The opportunity to use this technology is relevant to farmers in both developed as well as developing countries. Session 2.3

Resource use at croplevel . 512 Book of Abstracts 4th ESA-congress

THEEFFICIEN T USE OFWATE R ANDNITROGE N IN ARABLE FARMING IN EUROPE:I S THERE SCOPE FOR IMPROVEMENT ?

A.J.Haverkor t and M.I. Minguez

DLO-Research Institute for Agrobiology and Soil Fertility (AB-DLO) P.O.Bo x 14670 0 AA Wageningen, TheNetherland s 2 Depto Produccion Vegetal: Fitotecnia. E.T.S.Ingeniero sAgronomos . Universidad Politecnica deMadrid , Ciudad Universitaria 28040 Madrid, Spain

Introduction Consumers,producer s and scientists are aware that agricultural products should be produced such ast o optimize the use of natural resources and minimize emissions to the environment. To obtainpotential yields in anenvironment , resources, notably nitrogen and nutrients should be applied atrate swhic h are both economically and environmentally unacceptably high. Currentattainable yield by farmers, although economically feasible, may beunsustainabl e atth e long term asfo r the food and export requirements for Europe onth e whole, ground water isthreatene d because of contamination with nitrogen and because of depletion ofthi s resource atth e expense ofnatura l ecosystems.A growing proportion of food, following consumer demands is produced without chemical fertilizers andbiocide s butth eattainable organic yields are lowertha n current yields andthei r resource-use efficiency isamenabl e to debate. Thispape r evaluates the variousyiel d levels in arable farming interm s ofthei r resource use and resource-use efficiency with emphasis onth eus e of water and nitrogen and inrelatio n to solar radiation that varies from northern summer and southern summer andwinte r growing seasons.

Resource-use efficiency Potential (P),attainabl e (A)an d organic (O)yield s canb e expressed interm s of resource availability (water (W),sola r radiation (R) and nitrogen (N) and resource-use efficiency E(Ep ,E A and Eo),i.e . grams ofdr y matter produced per unit resource used by the crop,e.g . per litrewate r (WUEP, WUEA and WUEo),pe rmegajoul e intercepted solar radiation (RUEp, RUEA and RUEo) orpe r go f nitrogen taken up by the crop (NUEp, NUEA andNUEo). .Fres h crop yield (Y) isthe n expressed as Y=W(RorN)x WUE (RUEor NUE) x HI/DMC where HI isth e harvest index and DMC isth e dry matter content ofth e harvested produce. The greater the availability of aresource ,th e lower itsefficiency . De Wit (1992) referring to the optimum law of Liebscher (1895) argued that, as aproductio n factor which is inminimu m supply contributes moret o production the closer other production factors are closet o their optimum, strategic research should be into the minimum of eachproductio n factor needed to allow maximum utilization of all other resources.

Growth influencing factors Temperature, solarradiatio n and crop species or cultivar are the main growth defining factors determining the lengths ofth e available growing season and actual growth cycle andhenc eth epotentia l yields. In Europe, solar radiation isfurthe r from but water supply isneare r to itsoptimu m inth e Norththa n inth e South, hence theRUE P isgreate r innorther n Europetha n in Mediterranean solar conditions and, following Session 2.3 513

Liebscher's Law also the WUEPan dNUE P.Actua l yields are mainly limited by the availability of water and nutrients, especially nitrogen. Although actual yields may be higher inth e South than inth eNort h because ofhighe r radiation levels,th e lower RUEA, combined with lower availability ofwate r reduceth e efficient use of water and nitrogen unless their supply is strategically timed. Inorgani c farming, yields are often lower than incurren t systems because ofa reduce d availability ofminera l nitrogen and because of yield reducing factors such aspests ,disease s and weeds further reducingyields ,henc e WUEo andNUE oar e lower.

Increased efficiency through physiology and management To meetth e currrent European domestic and export demand for agricultural production options are formulated such asrealizin g it by optimizing all resources within limited space(d e Wit, 1992,WRR , 1992). Spreadingproductio n over Europe to make best use of available precipitation and ground water and to reduce local emission ofnitroge n or byproducin g inorgani c farming systems without input of chemicals is discussed. Using the concept of optimizing W,N,and Ran d WUE,NU E and RUE weno w can calculate how changes of cropphysiology , management and environment (climate change) influence the use ofth e resources,depletio n and emission.

Advances have beenmad e inmaximizin g theus e ofavailabl e resources and increasing theresourc e use efficiencies in selection of cropspecie s (C4/C3-plants)an d breeding for adaptation to adverse conditions such as drought, hightemperature s and climate change.Crop management practices, however, matching crop cycles with periods of lowevaporativ e demand (Loomis, 1983),respons e farming (Steward, 1988),concentratio n of limiting resources such as strategic irrigation and application of fallow (Loomis and Connor, 1992)an d organic farming techniques may have far greater immediate impact. Themos t efficient use of water and nitrogen is supplying them suchtha t yields areclos et opotential , solarradiatio n defined yields,provide d that the financial rate ofretur n of eachuni t of water and nitrogen added is still positive. Environmental (water conservation and contamination) constraints and market demands (for products from organic farming), however, often require supplies belowth e economic rate.Th e quantitative approach implying resource availability and use efficiency offers scopefo r optimizing yields giventh e ecological and economic constraints. This approach also provides the quantitative information needed to prescribe irrigation aswel l as fertilization.

References De Wit, C. T, 1992.Agricultura l Systems: 40:125-151. Liebscher, G., 1895.Journa l fur Landwirtschaft 43:49. Loomis, 1983. In:H.M.Taylor , W.J.Jorda n and T.S. Sinclair (Eds)Limitation s to efficient water use in cropproduction . Am. Soc. ofAgr . Madison WL346-373 Loomis,R.S .an d D.J. Connor, 1992.Cro pEcology :productivit y and management in agricultural systems. Cambridge university press,Cambridge , 538pp . Steward, J.I., 1988.In :F.R . Bidinger &C . Johansen (Eds) Drought research priorities for the dryland tropics. ICRISAT, Patancheru, India:p p 131-150. WRR, 1992.Groun d for choices. Reports to Gouvernment. SDU the Hague, 147 pp. 514 Book of Abstracts 4th ESA-congress

EFFECTO FSOI L NITRATEAN DN FERTILIZATIO N ONBREA DAN DDURU M WHEATYffiL D ANDQUALIT Y ANDO NRESIDUA L N-N03 CONCENTRATIONS UNDER IRRIGATION INEBR OVALLE Y (SPAIN).

A. Abad,J .Lloveras ,A . Michelena

Universität deLleida-IRTA .Alcald eRovir aRour e 177,25198Lleida . Spain

Introduction Nitrogen is normally ake y factor inachievin g optimumcerea l grainyield s andwhea tbakin gan d pastaqualit y (Hadjichristtodoulou, 1979;Beau x andMartin , 1984).Howeve rapplyin g too much is not onlyuneconomic ,bu tals o significantly increasesth eamoun t ofminera l Nwhic h could be subsequently lost toth eenvironmen t (Chaney, 1990;Alco ze t al. 1993).

Methods Nitrogen fertilization trials were conducted inLleid a (Torregrossa, 1993-95an dBell.llo c 1994-95) Spain, on Typic Xerofluvent soilswit h different initial soil N-N03 contents,t o study theeffec t ofN fertilization onbrea d and durumwhea tyiel dan dquality , and onsoi lresidua l N-N03 after harvest. Theexperimenta l design was split-split-plot with 8 treatments of Nfertilization ; in 5o fthe m différents rates of N(0 , 50, 100, 150an d 200k gha~l )wer e applied intw ocomplementar y stages:a t sowing (50k gha~l , except inth e rate0 ) and at shooting. Inth e other 3treatment s thetota l rate (150an d 200k gha~l ) wassplitte d in 3applications : at sowing (50k gha'1) , at shooting (50an d 100k g ha"l), anda tfla g leaf stage asa folia r spray (urea, 50K gha~l )o rt oth e soilsurfac e (50k g ha"l). Two varieties of bread wheat andtw o of durum wheat wereuse d in4 replicates .N treatment s were main factors and varieties split factors. Plots wereo f 8.4m ^ with eightrow s spaced 12c m apart. Theharveste d grain was measured for yield,protei n content, test weight and sedimentation test(SDS) .Bakin g quality (W,P an dL ,evaluate d withth eChopi n alveograph) was measured in bread wheat, andyello w pigments andgrai n vitreousneuss in durumwheat . Soil cores were collected at seeding, at shooting and after grain harvest from each plot at 2depth s (0t o 30an d 30t o6 0cm ) toevaluat e soil N-N03 content.

Results Theagronomi c andqualitativ e results (means ofth etw o cultivars of eachwhea t type,brea d and durum) are summarized inFigure s 1 and 2. Grain yield differences amonglocalitie s weremos t obvious atth ehighes t soil Nlevel .I n Bell.lloc(hig hinitia l soilnitrat econtent) ,grai n yield didno t increaseb y Nfertilization , but inTorregross a (withlo w soilnitrat econtent ) grain yield clearly raised with Nfetilization . Late application of Ndi dno t increase grain yield.Grai nprotei n content significantly increased withN fertilizatio n inal lyear s and localities.I ngeneral , inan ylocation s late foliar application of Ni nth e 200k gha~ l treatment did not increase grain protein content compared withth e samerate s of Napplie d atsoi la tshooting ; however, late application ofN a tth e 150k gha' 1 treatment increased grain protein compared withth e samerat eo f Napplie d atsoi la t shooting.Tes tweigh tdecrease d with Napplicatio n inal l years andlocalities .Qualit y parameters, W andL alveograph , increased byN fertilizatio n in alllocation s andyears ,bu tmainl y inth e fields withlo w initial nitrate content (Torregrossa, 1995).P alveograp hwa sno t affected either by year, location orN rates .Duru m wheat quality,measure d asyello w pigments and vitreousneuss, increased withN fertilization , except vitreousneuss inBell.llo c thatha d high vitreousneuss at allth e rates of N;possibl y duet oth ehig h soilnitrat e contentan d low grain yields.N oeffec t in durum wheatqualit ywa sfoun d bylat eapplicatio n ofN .I nbot htype so f wheat SDSincrease d withN fertilization inal lyear s andlocalitie sbu t SDSwa sno taffecte d bylat e Napplications .Soi lnitrat e contentafte r harvest increased inal llocation s andyear sb y aplication of nitrogen fertilization. Session 2.3 515

Vltreousmeus«(% ) Protein content (%) L(mm) -•—•- :if^ y

100 150 200 100 150 150 50 100 15020 0 10015 015 0 «50 «50 «50 «50«5 0«5 0 kgN/h a kgWh «

Torreqrossa-94 Torregrossa-95 Bell.lloc-95 Figure 1.Effec t of nitrogen application on grain yield, protein content (means of bread wheat and durum wheat), alveograph W and L (in bread wheat), yellow pigments and vitreousneuss (in durum wheat) in two locations of Ebro Valley: Torregrossa (1994-1995) and Bell.lloc (1995). Five nitrogen rates were applied (0, 50, 100, 150 and 200 Kg ha-1; splitted in 50 at seeding and the rest at shooting, except for the rate 0) plus three other N treatments (of either 150 or 200 kg ha"') in which 50 kg N ha"' was applied at flag leaf stage as a foliar spray (100+50u and 15O+50u) or to the soil surface (150+50s).

Figure 2. A) Soil N-N03 content at shooting (mean of all treatments) in Torregrossa (1994 and 1995) and in Bell.lloc (1995) in 0 to 60 cm of depth. B) Effect of nitrogen application on soil N-N03 content after harvest in Torregrossa (1993-195) and in Bell.lloc (1995). Five nitrogen rates were applied (0, 50, 100, 150an d 200 Kg ha"1, splitted in 50 at seeding and the rest at shooting, except for the rate 0) plus three other N treatments (of either 150 or 200 kg ha*1) in which 50 kg N ha"1 was applied at flag leaf stage as a foliar spray (100+SOu and 150+50u) or to the soil surface (150+50s).

Conclusions Nfertilizatio n increased yield andqualit y ofduru man dbrea d wheatbu t alsoincrease d soil N-N03 content after harvest. Yieldreache d aplatea u before wheatqualit y parameters. Inth eclimati c conditions ofth eEbr oValle y with alo wsumme ran dwinte rrainfall , soil withhig hN-N0 3conten t can supply most of thenitroge n needed byth ecro pan dconsequentl y lowerrespons et oN fertilization canb eexpecte d

References Alcoz, M.M.e t al, 1993.Agronom y Journal 85: 1198-1203. Beaux, Y.an d Martin, G., 1984. I.T.C.F.Journée stechniques . Chaney, K., 1990.Journa l of Agricultural Science 114:171-176 . Hadjichristtodoulou, A., 1979.Eyphytic a 28:711-716 . 516 Book of Abstracts 4th ESA-congress

CHANGES IN PHOTOSYNTHETIC CAPACITY ASSOCIATED WITH SOIL WATER DEPLETION IN MAIZE GROWN UNDER CONVENTIONAL AND MINIMUM TILLAGE L. G. Angelini, M.Mazzoncini , L. Ceccarini Department of Agronomy, University of Pisa, ViaS .Michèl edegl i Scalzi 2,5610 0Italy . Introduction In recentyear s thefeasibilit y of replacing conventional tillagesystem s with minimum tillagean d no-till techniques indifferen t agricultural areaso f Italy havebee nconsidere d (Caliandro etal. , 1992;Bonar i etal. , 1992;Bonar i etal. , 1994;Bonar i etal. , 1995;Angelin i et al., 1995).Th e main goal of research on thissubjec t included anevaluatio n of theeffect s of alternative tillage techniques on factors such as soil fertility, soil erosion andcro pyield . Littleeffort s havebee n madeo n theimplication s of continuous superficial tillageo nth e photosynthetic responses and water-use efficiency of plants grown inrainfe d systemso f Mediterranean areas,wher ewate r is themai n limiting factor tocro pyield .Therefor e wemonitore d leaf gasexchange s of maizeunde r a periodo f increasing waterstres si ncrop sgrow nwit h conventional (CT)an d minimum-tillage (MT). Methods Leaf gasexchange s of maize werestudie d over twoseason s in along-ter m tillage trial onloa m soil,o n which tillage treatmentscomparin g minimum tillage(10-1 5c m deepdis k harrowing- MT) with aconventiona l tillage (ploughing toa dept ho f 50c m -CT ) had beenestablishe d more than 10year sbefore . Rainfed maizecrop s (cv.Aida ,FA O500 ) werestudie d in field experiments carried out inCentra l Italy (43°40'N ; 10°23'E ;3 mabov e sealevel) . Thecrop s were sown on3 0Ma y 1991 and 28Apri l 1992.Plan tdensit y was 80,000 plants ha"1. Before planting, phosphate and potassium fertilizers wereapplie d ata rat eo f 150k gP2O 5ha- 1 (superphosphate) and 150k gha -1(potassiu m sulphate).Th e plots received 200 kgha- 1o f nitrogen (29-0-0a sliqui d N) split in twodose s of 100k gha -1each , applied ten daysan d one month after emergence.Th emai n management practiceswer ei naccordanc e with theordinar y agronomic practices used in Central Italy for maizecrops . Leaf gasexchang e measurements were takenove ra perio d of increasing soil water deficit naturally experienced during thedr yseaso n of 1991an d 1992whe n plants were in thevege ­ tative(fro m 2 to4 stageso f growth,correspondin g tocolla ro f 8than d 16thlea f visible respectively, according toHanway , 1963)an di nth ereproductiv e (from 4 to6 , thelas t corresponding to 12day s after 75% silked) growth phaserespectively . Gasexchange s characteristics were measured for youngest fully expanded leaves using aportabl e open differential system (ADC LCA,Hoddesdon , UK).Al l measurements wereconducte d in themid - parto f theda y when irradiance wassaturatin g (>1800pi molmV 1) and air temperature ranged from 30-37°C. Changesi n gravimetric soil waterconten t (from 0t o5 0c m in 10c m increments) were examined. Results Changesi n thesoi l waterconten tthroughou t theentir eprofil e were not significant different between thetw otillag e systems (Figures 1 and 2).I neac hyea r nosignifican t differences were found between thetw otillag e techniques in CO2assimilation , transpiration ratean d stomatal conductance (gs)a ssoi l wasgettin g dried (Table 1). Duringth e vegetative growth (1991) phase an increase in leaf temperature,a decrease intranspiratio n ratean d a strong depression of net photosynthesis wereobserve d asth e soil was gettingdried . Stomatal conductance was reduced by>20 % by soil dried and water useefficienc y by50% . During reproductive growth (1992), photosynthesis values remained more stablea swate r stressincrease d due to higherlea f Session 2.3 517

conductance values.Transpiratio n ratesincrease d andth ewate rvapou r gradient between thelea f and airwa s substantially lower than before. Conclusions The photosynthetic response andth ewater-us e efficiency of maizeleave s wereno t affected by tillage tecniques. Forth etw oyear schange s inth ega sexchang eparameter s associated with soil waterdepletio n wereobserved . According toHenso n etal . (1983) stomata of maizeappea r to respond tochange s insoi l waterconten t ina differen t waydurin g plantdevelopmen t Wateri s conserved by midday stomatal closuredurin g the vegetativephase so f development, but after flowering, assimilation ismaximize d atth eexpens eo f increased waterconsumption , due to stomataremainin g atleas tpartl y open. 0' 1991-CT 10'

?»• Wiltingpoin t Fig. 1 - 1991 Soil ^30- Wilting point f i waterconten t in the 0- ü40 *\k ' 60 cm layer in CT and -B-107/91 's\ •= 50- -*- 17*7/91 'r* — 50- MT and during a ••••307/91 O 60- • period of increasing water deficit

10 M 30 « Soil water content (m 100 m "') Soil water content (m 100 m' )

1992- MT 10. i* t 1992-CT J 10' •-, \ \ 20 . Fig. 2 - 1992 Soil Wfflmgpoint ; Wjlting point ?»- ' ) 30 . ; k V waterconten t in the 0- S 30- { 60 cm layer in CT and •• \\ 40. ß cl40' '• V \\ MT and during a 50. "° 50- -a-2775/92 i —•-27/5/92 i \ period of increasing -•-107/92 < —*- 10/7/92 O 60- * 60. m waterdeficit . •••• 28/7/92 • •-«--287/92 \1 70- , ,1 0 , , 20 30 J « Soil water content (m 100m"3) Soil water content (m 100 m )

Table1 -Mea nvalue so f netphotosynthesis ,transpiration ,wate rus eefficiency , stomatal conductance'(gs)an dlea f to air temperaturerati o(Tleaf/Tair )affecte db yconventiona l(CT) an dminimu mtillag e (MT).

Net photosynthesis Transpiration Waterus e efficiency VPD Tleaf/Tair (^mol nvV1) (mmol nrV1) (mmol/mol nvV) (KPa) (molnrV) 1991 stage3 CT MT CT MT cr MT cr MT CT MT CT MT 2 35.10 32.76 9.71 9.21 3.58 3.51 2.48 2.54 0.415 0.396 0.97 0.97 3 17.54 17.09 7.62 7.72 2.28 2.22 2.08 2.33 0.381 0.371 0.98 1.00 4 15.53 15.79 8.68 8.72 1.79 1.81 2.93 3.07 0.353 0.310 0.99 0.99 1992 stage0 4 35.80 33^92 7.79 7.53 4.59 4.07 2.47 2.63 0.339 0.307 1.00 1.01 5 34.83 33.07 9.26 9.02 3.76 3.66 2.25 2.64 0.460 0.373 0.98 0.99 6 29.19 31.49 11.17 10.92 2.61 2.87 1.95 1.76 0.653 0.630 0.95 0.94 "Ha nway . 1963 References Angelini, L.G., et al., 1995.Proceeding s Xth International Photosynthesis Congress, Montpellier, France, pp46-50 . Bonari, E., et al., 1992. Informatore Agrario 1:11-25 . Bonari, E., et al., 1994. Proceedings 3rd ESA Congress,Abano-Padova , Italy, pp. 636-644. Bonari,E. , et al., 1995.Soi l Tillage Research 33: 91-108. Caliandro, A., et al., 1992.Rivist a di Agronomia,26 ,3 : 215-222. Hanway, J.J., 1963.Agronom y Journal,55:487-491 . Henson, I.E., et al., 1983.Annal s of Botany, 54:641-648. Toderi, G.,e t al., 1986.Rivist ad i Agronomia 2-3:6-13. 518 Book of Abstracts 4th ESA-congress

RESPONSE OF COTTON TONITROGE N ANDWATE R IN A SUBTROPICAL ENVIRONMENT

M.Aydi n

Department of Soil Science,Facult y of Agriculture,Mustaf a KemalUniversity , 31040-Antakya, Turkey

Introduction Cotton ison e ofth e most responsive cropst o irrigation aswel l ast o nitrogen applications. Therefore, the most appropriate combination ofnitroge n rates and irrigation schedules should be experimentally determined and practiced (Alie t al., 1974;Vorie s et al., 1991). For this purpose,a multifactorial experiment was carried out inthre e different locations of asubtropica l region.

Methods Thefield experiment s were established at Adana,Hacial i and Tarsuswhic h are located inth e ÇukurovaRegio n - Southern Turkey. Theexperiment swer e conducted during 1983-1986. The soilsa tth e experimental sitesar e VerticLuvisol san d / or Chromic Vertisols(Aydi n et al., 1993; Dinç et al.,1991). The siteshav e aMediterranea n climatewit h mild rainywinter s and hot dry summers. Cotton (Gossypium hirsutum L. cv."Carolin a Queen 201/971-1518") was planted at theen d ofApri l and harvested between mid-September and mid-October. Soilswer e fertilized 1 with 80k gP 205 ha" (Yesüso ye t al., 1989). Theplan t population densitywa s about 70,000 plants perhectar e with adistanc e of 80c mbetwee n rows. Combinations offive differen t levelso f 1 nitrogen applications (N0,Ni , N2, N3, N4, which correspond to 0, 120, 160,200 ,24 0 kgN ha' ) andthre e different levelso fsoi lwate r content (Ii, I2,13,whic h represent theirrigations , when the availablewate r in 0-120 cm ofth e soilprofil e was depleted to 20%,40% ,60 %o fth e maximum available) wereuse d asth etreatments , which wereapplie d to thefields a srandomize d complete block designswit hthre e replications (Güzele t al., 1983). Cotton plotswer e equipped with tensiometers, gypsum blocks,acces stube s for neutron probe, soilwate r samplersan d piezometers. Thewhol e ofth e nitrogen fertilizer was applied at onetim e after emergence. The irrigation water wasapplie d byfurrow s (Aydin et al.,1989) . Thewate r consumption of cotton wasdetermine d byobservin g changesi n soilwate r content. In the presence of awate r table,th e contribution ofthat to thewate r consumption wascalculate d with the aid of known hydraulic functions (Aydin, 1994). Thetota lyield so fseedcotto n werebase d on the sum of allharvest s for each year. Thequalitativ e analyses of cottonfibres wer e accomplished.

Results Results are summarized inth e Table. The effects ofnitroge n rates and nitrogen-water combinations onth eyiel d ofseedcotto n weresignificant . Theyiel d response curveso r production functions of cotton to nitrogen were obtained for each offou r years. Then the four yearso f data werepoole d and acomposit e function wasfitted t o the pooled data, becausether e was nota significant between-year variation bytreatments . Theregressio n equations ofth e seedcotton yields (Y=kg ha"1)o n nitrogen rates(X=k gN ha"1)ar e presented below: Y= 2460.6+17.3 1 X-0.055 X2 R2= O.995" (^significant atP < 0.01) for Adana 3133.5+14.01 X-0.050 X2 R2= 0.979" for Haciali Y= 2706.7 + 8.02 X- 0.029X •2 R2= 0.887" for Tarsus Session2. 3 519

Table.Effect s ofnitroge n and water treatments on cotton production atthre e locations

Results and/or suggestions Locations (Four -yea r means) Adana Haciali Tarsus (Bajada) (Bottom lands)

1 -Nitrogen rateswit hhighes t yields(k gN ha" ) N2=160 Nj=120 Ni=120 -The availablewate r level,i nth e soilprofile , atwhic h irrigation wasfavourabl e I2=40% Ii=20% Ii=20% -Seedcotton yield (kgha" 1)a tth emos t appropriate combination oftreatment s (three-replication means) 3820 4093 3250 atN 2I2 atN1I 1 atNjI, -Effects ofnitroge n rates and irrigation regimes onth e quality of fibres Non-significant -The amount ofwate r applied perirrigatio n (mm) 90 150 110 -Number ofirrigation s per season 5-6 3-4 2-3 -Seasonal water consumption (mm)a tth esuitabl etreatmen t 730 678 955 -The contribution ofwate r table (mm)t o thewate r consumption - 600 - Recommendable soilwate r potential (kPa) for determining timeo firrigation , and installation depths oftensiometer s (cm) -70 kPa -65 kPa -65kPa at 30 cm at6 0c m at 60c m (-50 kPa forfirst irrigation ) -The lowest and highest concentrations ofnitrate- N inth e soilwate r (mgN L" 1)extracte d from 120c m depth of soils 8-19 28-35 24-37

Conclusions Thecotto n crop responded wellt o application of 120k g N ha'1 atal llocation s and continued to showincrease si n yield at application of 160k gN ha"1o n Adana soils.Whe nth e available water in0-12 0 cm of the soil profile wasdeplete d to 40%,irrigatio n appeared to beth esuitabl e treatment atth e most appropriate nitrogen rate (160k gN ha' 1) for the Adana soils. InHacial ian d Tarsus, irrigation wasfavourabl e when the availablesoi lwate r was reduced to 20%,an d application of 120k gN ha"1 was optimum. When soilwate r potential at 30 cmsoi l depth decreasest o -70 kPa duringth e irrigation season, 90 mm irrigation water should be applied on Adana soils.I f soilwate r potential at6 0 cm depth decreasest o -65kPa , 150an d 110m mwate r should be applied on Haciali and Tarsus soils,respectively . The seedcotton yieldswer e lower at Tarsustha n atth e other two experimental sites,partl y duet o the presence of awate r table, close to therootin g zone. In general, nitrate concentrations in soilwate r extracted from different depths ofsoi lprofile s did not differ significantly between treatments. However, concentrations of nitrate-N at 120c m depth of soilsma yindicat e possible environmental and economical problems to be encountered inth e future.

References Ali,A . et al., 1974.India n Journal ofAgricultura l Research 8:83-88 . Aydin,M. , 1994.Irrigatio n Science 15:17-23. Aydin,M . et al., 1989.Proceeding s of 10th Congress of Soil Science Society ofTurke y 5:28/1-10 Aydin, M. et al., 1993. Zeitschrift fur Pflanzenernaehrung und Bodenkunde 156:441-446. Dinc,U . et al., 1991.Caten a 18: 185-196. Güzel,N . et al., 1983.Turkis h Journal of Agriculture andForestr y 7: 185-191. Vories,ED . et al., 1991. Irrigation Science 12:199-203 . Yesjlsoy, M.S. et al., 1989.Proceeding s of 10th Congress of Soil Science Society of Turkey 5:35/1-10. 520 Book of Abstracts 4th ESA-congress

EFFECT OF TILLAGE SYSTEMS ONWEE D PRESENCE AND DIVERSITY INA CONTINUOUS MAIZE CROPPING SYSTEM

P. Barberi1, M. Ginanni2, S.Menini 2,N . Silvestri2, M. Mazzoncini2

'Centra Interdipartimentale diRicerch e Agro-Ambientali "E. Avanzi",Universit y ofPisa , Italy 2Dipartimento diAgronomi a eGestion e dell'Agro-Ecosistema, University ofPisa , Via S.Michèl e degli Scalzi 2, 56124 Pisa, Italy

Introduction Intensive production systemsfo rfield crop s have raised public concern because of increasing costs and environmental hazards (Sharpley et al., 1994; Clements et al., 1995). Less intensive cultural practices, such asth e adoption oftillag e systems alternative to deep ploughing, should therefore befostered . Ashallowe r tillage depth islikel yt o modify the weed flora spectrum of crops. Limited soil disturbance mayresul t inincreasin g weed number and inhighe r percentage of perennial weedswithi n weed communities (Froud-Williams, 1988).Moreover , the effect oftillag e systems onth e density and composition ofth e weed flora dependsupo n crop sequence and length ofrotatio n (Ziliotto et al., 1992). Afield tria l was carried out inCentra l Italy to investigate onth e effects of different tillage systems onwee d density and structure ofa continuous maize cropping system.

Methods Seventillag e systems for a continuous maizecroppin g system were compared since 1990 ona n alluvial loamy soil (Typic Xerofluvent). Tillage systems were: 50 cm deep ploughing (P50), 25c m ploughing (P25), 25 cmploughin g + subsoiling (P25 +S), 50 cm chisel ploughing (C50), minimumtillag e (MT), 50 cmploughin g following minimumtillag e (P50/MT), and minimum tillage following 50 cmploughin g (MT/P50). The effect oftillag e systems on maizewee dflora was evaluated after afour-yea r period during which allplot s received the same herbicide treatment (post-emergence spraying of dicamba 1 1 ha'1). Weeds were counted by species at maize fourth leafstag e (23 May 1994)jus t before herbicide application. The structure ofwee d communitieswa s outlined bymean s ofth e Shannon-Wiener H' diversityinde x (Mahn et al., 1979), computed as: s with hi=pi• In(1/pj) , where ft isth eRelativ e Abundance Index ofeac h ofth e S H'= £ h; weed species present. TheRelativ e Abundance Indexwa s computed as: relative i=l density + relative frequency/2 (Derksen et al., 1993).Fo r each tillage system, the cumulative h;value s were plotted versusth e number of speciessorte d in decreasing order of importance. Before analysis ofvariance , total weed densities and Relative Abundance Indices weretransforme d as^(x+1 ) and arcsiny(x) respectively, to increase homogeneity ofvariance .

Results Thelac k of soil inversion (MT) resulted in highertota l weed density (Table 1)an d in higher presence ofCynodon dactylon (L. )Pers . (Table 2). InM T and C50 this species washighl y dominant, thus reducing the diversity index ofth ewee d flora, as shown inth eFigure . Deep ploughingwa s characterized by ahig h density oîXanthium strumariumL . (Table2) .

Conclusions Although the decrease intillag e depth caused higherwee d presence, itseffec t on thewee d structure seemed limited. The establishment offe w and aggressive weed species observed inal l tillage systems after four years oftria l islikel yt o be aresul t of continuous cropping. The low diversity ofwee d communities might lead to severe weed control problems inth e oncomingyears . Session 2.3 521

Table 1.Tota l weed density recorded at maize fourth leaf stage in 1994 for each tillage system. Tillage system Weed density (plantsm" 2) P50 9.2 c P25 25.0b P25 +S 7.7 c C50 21.0b MT 45.3 a P50/MT 16.5b e MT/P50 41.5a Values labelled with the same letter areno t significantly different atP s 0.05 (DMR Test)

Table 2. Relative Abundance Indices ofth ewee d species found inth etillag e systems. Tillage system Relative Abundance Index (%) Convolvulus Cynodon Equisetum Xanthium Others* arvensis dactylon arvense strumarium P50 37.6 ab 18.5c 0.0 b 43.9 a 0.0 n.s. P25 47.2 a 40.5b 10.3b 1.9 b 0.0n.s . P25 +S 37.3 ab 20.9 c 32.6a 9.2 b 0.0 n.s. C50 4.5 c 72.2a 8.3 b 8.6 b 1.6 n.s. MT 14.1b e 72.9a 2.5 b 7.2 b 0.8n.s . P50/MT 31.1 ab 59.7a b 0.0 b 7.4b 0.4 n.s. MT/P50 30.6 ab 63.5 ab 4.7b 1.2b 0.0 n.s. *Chenopodium album,Phalaris canariensis,Rumex crispus, andSolanum nigrum. Within each column, values labelled with the same letter areno t significantly different atP < 0.05 (DMR Test),n.s . = not significant.

Diversity indices of maize weed flora. P50 = 50 cm ploughing, x P25 = 25 cm ploughing, P25+S •a 0 c = 25 cm ploughing+ subsoiling, C50 = 50 cm chisel ploughing, : Ï5 0 MT = minimum tillage, P50/MT > 50 cm ploughing following mi­ -a nimum tillage, MT/P50 = mi­ a> 0 nimum tillagefollowin g 50 cm ploughing. 2 3 4 5 6 7 Numbero fspecie s -»P50 -B-P25 P25+S ^C50 • MT -©•P50/M T - -MT/P5 0 References Clements, D.R. et al., 1995.Agriculture , Ecosystems and Environment 52: 119-128. Derksen, D.A. et al., 1993.Wee d Science 41: 409-417. Froud-Williams,R.J. , 1988.In : Weed management inagroecosystems : ecological approaches. CRCPress ,Boc aRaton , 213-236. Mahn, E.G. et al., 1979. Agro-Ecosystems 5: 159-179. Sharpley, A.N. et al., 1994. Soil and Tillage Research 30:33-48 . Ziliotto, U. et al., 1992.Rivist a diAgronomi a26 : 241-252. 522 Book of Abstracts 4th ESA-congress

EXPLAINING THEYIEL D RESPONSE OF WINTER WHEAT DUE TO FUNGICIDES BYTH EEFFECT S ONGREE N LEAF AREA DURATION AND RADIATION INTERCEPTION.

R.J .Bryson 1, W. S. Clark2 and N.D . Paveley3.

!.ADA SAnste y Hall,Mari s Lane,Trumpington . Cambridge. CB22LF . 2. ADAS Cambridge, Brooklands Ave., Cambridge. CB22BL . 3. ADASHig h Mowthorpe, Duggleby, Malton, North Yorks.Y01 7 8BP.

Introduction. Cropyiel d is predominantly determined by the ability of thecro pt o intercept light energy and utilise itfo r growth (Hay &Walker , 1979). Potential yield canb erelate d tobot h thecrop s green area index (GAI) and incident solar radiation through anequatio n derived from Beers Law (Monteith &Unsworth , 1990).Th e Beers Law analogy implies that there is anoptima l canopy sizefo r growth atwhic hth ecos t of protecting afurthe r increment incanop y sizewil l prove uneconomic (Sylvester-Bradley etal., 1995).Th e aimo f this poster is to show thatth e protection of yieldb y foliar fungicides canb ebette r explained by monitoring the loss of light intercepting green leaf area than by assessments of percentage disease alone.

Materials and Method. Experimental plots (1.8mx 24m) of theyello wrus t susceptiblecultivar , Slejpner, were arranged in afull y randomised factorial design in twoblock s atADA STerrington , Norfolk. Sixty one spray treatments were applied asa 1,2 o r 3spra y programme applied at any of four timings at four doserates .Diseas e assessments werecarrie d out weekly on 10randoml y selected main shoots.Diseas e was assessed as apercentag e of thetota l leaf area expressing symptoms (Anon, 1976).Leave s were assessed in asimila r way for thepercentag e of green leaf area present. Actual greenlea f areaswer edetermine d inth efiel d using measurements of leaf length andwidt h inconjunctio n with afor m factor (0.83) asdescribe d by Gaunt &Bryso n (1995). Shoot number perm 2 were determined by shoot counts onfiv e randomly selected 1.0m rows perplo t atGS75 . Total incident radiation (MJm2) was measured using adom esolarimete r supplied by Delta-T (Cambs.).

Results. Crop yield (tha" 1)wa s found to relatepoorl y tobot h thepercentag e of yellow rust symptoms on leaf 2a t GS75 (Fig. 1) and the area under disease progress curve (AUDPC) (Teng, 1983) onlea f 2 (Fig.2) .Health y area duration (HAD) (Waggoner &Berger , 1987) of leaves 1-3 from GS39 was found torelat e to crop yieldb y acurvi-linea rrelationshi p (R2= 0.83 ) (Fig.3) .Thi s relationship,b y analogy toBeer s Law, takes account of the amount of green area available for light interception butno t the amount of intercepted radiation. Thehealth y area absorption (HAA) (Waggoner &Berger , 1987) of leaves 1-3 from GS39 inth etreate d andcontro l canopies related linearly tocro p yield (R2= 0.83 ) when thecanop y extinction coefficient, k, was assumed tob e 0.5 (Monteith, 1976).

Conclusion. In this trial themeasuremen t of the duration of green leaf area from GS39, andhenc ea n estimation of accumulated radiation intercepted by green tissue,relate d wellwit h final yield (R2 = 0.83). Thepotentia l yield of acro p is directly related to solar radiation and agronomic Session 2.3 523

conditions, such asfertilise r applications. Whilst percentage disease assessments may be useful infungicid e efficacy trials they take no account of thephysiolog y of the growing crop. They are therefore are of limited use in fungicide experiments where anunderstandin g of yield loss is required. This preliminary study demonstrates that amor e detailed understanding of the growing crop isessentia l for the analysis and interpretation of the effects of fungicide treatments for the protection of crop yield. It isbelieve d that further analysis of data from similar multi-site experiments carried out in 1994an d 1995wil l support the findings presented in this poster.

12 12 T ~ 10 0 O 10 <«& O ra _ « £ § 8 O Ü 2 6 ! oo S" 6 f o o a> 4 O * 4 -i- •>. 2 J x 2 o 4- 0 ; 1 1 ! 1 1 0 10 20 30 40 50 0 200 400 600 800 1000

% yellow rust AUDPC Fig. 1.Mea n %yello w rust v's yield (t/ha) Fig. 2.Mea n AUDPC v's yield (t/ha)

— H 100 150 200 250 550 HAD (GS39)

Fig. 3 Mean HAD v's yield (t/ha) Fig.4.Mea n HAA v'syiel d (t/ha).

References. Anonymous, 1976. Manual of Plant Growth Stage and Disease Assessment Keys.MAFF .U K Gaunt, R. E.et al. 1995.Aspect s of Applied Biology 42:1-7 Hay, R. K. M.et al. 1989.A n Introduction to the Physiology of Crop Yield. Wiley &Sons .N Y pp292. Monteith, J. L 1976. Vegetation and the Atmosphere. Vol. 2.Academi c Press, London Monteith, J. Letal. 1990.Principle s of Environmental Physics. Edward Arnold. London. Sylvester-Bradley. R.etal. 1995.A Vita l Role for Fungicides in Cereal Production. SCI p43-56 Teng. P. S. 1983Phytopatholog y 73:1587-1590 Waggoner. P.E .etal. 1987 Phytopathology 77(3):393-398. 524 Book of Abstracts 4th ESA-congress

VARIATION OF THE SOIL HUMIDITY IN AN ECOLOGICAL CULTURE OF ASPARAGUS (ASPARAGUS OFFICINALIS L.) IN GALICIA (N.W. SPAIN)

A. M. Castelao1, M.J . Sâinz1, M. Bujân2 iDepartamento deIngenierî aAgroforesta l yProductio n Vegetal,Faculta d deVeterinaria , Universidad deSantiag o deCompostela , E-27002 Lugo,Spai n 2Departamentod eBiologi aVegetal , Universidad deSantiag o deCompostel a

Introduction InSpain , 25397 ha of land werecultivate d with asparagus in 1992 (M.A.P.A., 1994),mainl y underirrigate d conditions. InGalici a (NW Spain),thi scro p isalmos t unknown, only 2h abein g devoted toth ecultur e underirrigatio n that year. However, asparagus could bea n interesting plant todiversif y the agricultural productions in theproces s thatth egalicia n ruraleconom y must follow tofit th erequirement s of theAgricultura l Politics of theEuropea n Community. Inthi s work,w estudie d thevariatio n ofsoi l volumetric humidity (Hv) in afiel d ecologically cultivated with asparagus without irrigation.

Methods Thestud y wascarrie d out inGalici a (NW Spain)i n 500m 2 of anecologica l cultivation of asparagus (Asparagus officinalis L.) cv.Cit o in thethir d year of production. Theregio n hasa humidclimat e andth ecultur eha d neverreceive d irrigation.Th ecultivate d soilwa sa humi c cambisol with the following characteristics: sandy loam texture,pH(H20 ) 5.26,organi c matter 4.68%, soilfield capacit y 17.8%an d soil wilting point7.5% . Cattlemanur eapplie d inautum n 1994wa sth eonl yfertilizatio n treatment received byth eplants . Noherbicid e wasapplie d and thecultur e wasstrongl y invaded by weeds (Bujân et al., 1995).I n February 1995,th eridges wer e formed and theasparagu sharves t carried outfro m late Marcht o lateMay .Afte r harvesting, sixteen equalplot s of 21m2 wereestablishe d in thecultivate d surface. Humidity measurements were made weekly, from June to November in 1995,wit ha Trase System usingth eTim e Domain Reflectometry (TDR) technique (Toppe t al., 1982). Waveguides of 15, 30,45 and 60c m length wereburie d ineac h plot toevaluat e thewate r content and todetermin e irrigation needs of theasparagu sculture .

Results Means +s.e.m .o f the %volumetri c humidity arepresente d in the figure (f.c.= soil field capacity, w.p.= soil wilting point).Dat a showed two cycles of water deficit, onelastin g from July to August with astron g drought (thevolumetri c humidity reaching valuesunde r thewiltin g point of thesoil ) and asecon d one,no t thatstrong , in October, which wasparticularl y observed upt o 15c m depth (thevolumetri c humidity showing valuesnea r thewiltin g point of thesoil) . The second cycle followed aperio d of soil rewetting duet oth erainfal l beginning onth e 6tho f September. Anearb y metereological station (situated 3k m far from the asparagus field) registered 149m m of precipitation in September. Thesand yloa m textureo f thecultivate d soil favoured aquic k drainage after the rainfall. Session2. 3 525

Beginningo f 30 -i rainfall -G— 0-15 cm -H— 0-30 cm -m— 0-45 cm 25 - -fl— 0-60 cm

ö 20- — H- i• c

S 15-

10 - _ w.p .

5 -

1 ' 1 ' 1 ' 1 I ' I M) bO bo CU OH a. •g 3 3 3 3 Ci a; r, r, 3 3 3 (fi en O 0 0 tr> 0(f0i in >*> rH 8 Si \c 8 rH es o r-4 a r-l DATEO FMEASUREMENT S

From November on, together with the lowering of temperature, rainfall again started, the soil finally reaching water saturation conditions. In November, 230 mm of total precipitation were measured.

Conclusions Although the asparagus cultivation was carried out in a humid region of Spain, our results let advise the establishment of an irrigation system to increase asparagus yields and help the plant to withstand the strong drought during July and August. The agronomic situation is in a way similar to that found in the more productive areas of asparagus in Spain, where irrigation is a common practice during summers characterized by high temperatures and a strong drought. In future work, we intend to study the effects of irrigation on asparagus yields under ecological cultivation.

References Bujân, M. et al., 1995. Actas del Congreso 1995 de la Sociedad Espanola de Malherbologia, Huesca (Spain), 83-86. M.A.P.A., 1994. Anuario de Estadistica Agraria 1992. Ministerio de Agricultura, Pesca y Alimentación (M.A.P.A.), Madrid, 679 p. Topp, G.C. et al., 1982. Soil Science Society of America Journal 46: 678-684. 526 Booko fAbstract s4t hESA-congres s

CORRECTION OFZIN C AND COPPER DEFICIENCIES ON MAIZE CROPS

P. Castillon, A. Bouthier

ITCF -3145 0Bazièg e -Franc e

Introduction Maize iswel l known for its sensitivity mainly to zinc deficiency but also to copper and manganese deficiencies (Loué, 1993). Sosom e growers systematicaly supply their maize crops with zinc or several blended micronutrients. However micronutrients deficiencies areno t veryfrequen t and often transitory. Inman y trials carried out inth e south-west of France,zin c supply did not increase themaiz e yields despite obvious zinc deficiency symptoms onth eyoun g crops.Therefor e supplying systematically the maizecrop s withmicronutrient s isno t always profitable. Onth e contrary whenth e supply isno tjustifie d one might fear the competition between zincan d copper absorptions. This antagonism hasbee n demonstrated in laboratory conditions with excised barley roots (Schmid et al., 1965),o n cotton leaves(Bowe n etal. , 1969)an d with isolated cuticles (Charnel etal. , 1982).Bu t infield condition s itha sbee n observed that zinc applied on agrasslan d increased copper bio availability inth e soil and improved Cuan d Zn nutrition ofth e Ray-Grass (Dejou etal. , 1985).Reciprocall y applying copper increased Zincbi o availabililty and Cuan d Znnutrition . Therefore wewondere d whether this interaction could occur onmaiz e infield conditions . In ordert o investigatethi sproblem ,field trial s onmaiz e crops were carried outi nth e south-west ofFranc e from 1985t o 1995.

Methods Fivetrial swer e carried out in silty clayey or silty sandy soils whose main characteristics are shown in Table 1.

Table 1.Mai n characteristics ofth e soils Trial Year Clay Silt Sand O.M. pHwate r CuEDT A ZnEDT A % % % % mg.kg"1 mg.kg"1 1 1985 24 53 23 2.0 7.3 0.1 0.7 2 1986 25 45 30 2.1 6.6 0.1 0.9 3 1986 28 46 26 2.5 8.0 1.1 0.6 4 1987 22 52 26 2.0 7.3 2.9 2.5 5 1995 10 37 53 4.8 5.7 2.3 2.0

Except soil number 3whic h isweakl y calcareous, allth e others are originally acid but in soil 1,2 and 4 liming has araised soil pH above 6.2.Thi s isconsidere d aworsenin g factor for the Znbi o availability especialy for the soilswit hlo wextractabl e Zn (Dartigues et al., 1967).Furthermor e it hasbee n found that copper deficiency can occur onwhea t when CuEDTA/O M< 0. 5 (Laurent et al., 1989),whic h isth e case for soils 1,2 ,3 an d5 . Fourtreatment s were compared inrandomize d blocks (3 or4 ) designs :control , Zn, Cuan d Zn+ Cu.I n soils 1,2 ,3 an d 4, 5-7.5 kgha" 1rat e ofZ nan d Cu from sulphates were supplied at sowing. Intria l 5,0.7 0 kg Znha " and 0.75 kg Cuha " from sulphates were sprayed atth e9 leaves stage.I nth eZ n+ C utreatmen t ofal lth etrials ,Z nan d Cuwer eapplie d separately butth e same day. Session2. 3 527

Results Grain yields for trials 1,2 ,3 an d 4 anddr y matter yield for trial 5ar epresente d in Table2 .

Table 2.Effec t of Cuan d Zn supplies onth eyiel d ofmaiz e( tha " dry weight) Soils Control Differences between treatments andth e control Cu Zn Cu+ Z n 1 10.36 0.55 (S) 0.91 (S) -0.31 (NS) 2 9.96 0.83 (S) -0.85 (S) -0.65 (S) 3 10.15 -0.12 (NS) 0.01 (NS) -0.23 (NS) 4 9.35 -0.10 (NS) 0.34 (NS) 0.26 (NS) 5 12.31 1.09 (S) 1.46 (S) 0.65 (NS) (S) :significan t atP < 0.10 , (NS) : non significant

Except for thetrial s 3an d 5fo r Zntreatmen tth eresult s were ingoo d agreement withth e soils' characteristics since Cuan dZ n supplies increased the maizeyiel d only onth e soilswher e Cu and Znbi o availability were considered low. Wherether e weren o responsest o Cuan dZn , Cu+ Z nha d noeffec t onth eyields . Where Cu and/orZ n increased theyield , Cu+ Z nha d no effect or significantly decreased theyield . Besides intria l 2wher e only copper was deficient Zn and Cu+ Z n decreased themaiz eyield .

Conclusions These trials confirm the existence of copper and zincantagonis m that can occur in field conditions whenthes e elements are supplied to the soil or sprayed onth e leaves.Therefor e the diagnosis from soil analysis isimperativ e before supplying amaiz e cropwit h Cuo r Znbecaus e a wrong choice ofth e element canworse nth e actual deficiency as shown intria l2 . Furthermore Copper and Zinc should never beassociate d inth e same application. Inth e caseo f double deficiency Cuan dZn ,th e supply ofthi stw o elements should bedissociated . For example,Z n could be supplied to the soilbefor e sowing (5k gha " Zn) and copper sprayed atth e 8 to 10leave s stage (0.5 kgha ' Cu).

References Bowen, J.E.e t al. 1969.Plan t physiology 44 : 255-261. Charnel,A . et al. 1982.Journa l of PlantNutritio n 5 : 153-171. Dartigues, A. et al 1967.Annale sAgronomique s 18(3 ) : 285-299. Dejou, J. et al. 1985.Agronomi e 5(9 ) :841-850 . Laurent, F.e t al. 1989.Le s oligoéléments etl esol .Ed .Frontières , Fr. :97-107 . Loue,A . 1993.Oligoélément s en agriculture.Ed .Nathan , Paris : 283-308. Schmid,W.E . etal . 1965.Physiologi a Planturum, 18 :860-869 . 528 Book of Abstracts 4th ESA-congress

BLACK-GRASS (Alopecurus myosuroides Huds.) DEVELOPMENT AND SEED PRODUCTION IN WHEAT

B. Chauvel ', C. Angonin 2, N. Colbach '

1Statio n d'Agronomie, INRA, 17 rue Sully, BV 1540, 21034 Dijon Cedex, France 2 Laboratoire de Malherbologie, INRA, 17 rue Sully, BV 1540, 21034 Dijon Cedex, France

Introduction Alopecurus myosuroides is a frequent and harmful annual weed of winter crop rotations in France. To understand and to prevent the spread of this weed, its biology must be better known. The aim of this work was to study its growth and development as influenced by interspecific competition and nitrogen nutrition.

Material and methods All techniques besides the experimental factors (Table 1) were identical. The "competition" factor compared A. myosuroides potential growth and development to that in competition with wheat (cv. Soissons sown at 280 grains m~2).Th e "nitrogen" factor compared the impact of early- starting (NO) and late-starting nitrogen deficiencies (Nl) with a non-deficient situation (N3). Plots were sown on 29 September 1993. Vegetative (plant m"2, tillering, shoot dry matter) and reproductive variables (ears plant"1, ear length, grain viability, ear dry matter) were measured on the A. myosuroides plants of a 1.5x 0.36 m"2 area for each plot. The number of spikelets was counted on 60 randomly chosen ears per plot and a relationship with ear length was estimated to predict spikelet number on all plants.

Factor Competition X Nitrogen fertiliser (kg ha') * Table 1• Factors combined stage 24* stage2 5 stage 31 in a 4-block-design in Levels A A. myosuroides NO 0 0 0 Dijon ('36 kg ha'of AW A. myosuroides Nl 60 0 0 mineral soil nitrogen. * + winter wheat * N3 60 40 60 according to Zadoks etal. (1974). *a t 280 grains m2 Results The number of spikelets per unit of ear length was constant between treatments; there was a mean of 20 spikelets per cm of ear length which is consistent with Naylor (1972) . Emergence of A. myosuroides was not influenced by experimental treatments (Table 2). Tillering was affected by early nitrogen deficiency (less tillering for NOtha n for Nl and N3) in combination with competition with wheat. This nitrogen effect was stronger if there was competition. Plant height was only reduced by early nitrogen deficiency. Even after the tiller number per plant was fixed, dry matter accumulation was still influenced by competition and slightly by nitrogen deficiency (as shoot dry matter is positively correlated to the tiller number), both by early and late deficiencies. Similarly, even for a given tiller number, the total number of ears per plant was affected more strongly by competition than by nitrogen deficiency (Table 3). If there was no competition, the number of ears was reduced only by late nitrogen deficiency (less ears for NOan d Nl than for N3); in case of competition, early deficiency also reduced the ear number. Less ears ripened in case of competition. Despite its strong correlation with the number of ears, the number of spikelets per plant was still affected by competition and both early and late nitrogen deficiency. However, total ear dry matter depended almost entirely on the number of ears. Grain viability depended both on competition and nitrogen; it was increased by competition and reduced both by early and late deficiencies. Session 2.3 529

Conclusions Competition always had astronge r effect than nitrogen deficiency; the impact of the latter was often increased if there was interspecific competition. Competition had an impact whatever the period during which theA. myosuroides components weredetermined . Early nitrogen deficiency mostly reduced early growth and development components such astillering ; late deficiencies affected late characteristics such the total number of ears for agive n number of tillers. Nitrogen deficiencies had no impact on ripening of ears.

References Naylor, R.E.L., 1972,Journa l of Applied Ecology 9: 127-139. Zadoks, J.C. et al., 1974.Wee d Research 14: 415-421.

Table 2.A. myosuroidesvegetativ e growth and development. A.Mean s per treatment. FACTORS A. myosuroides CHARACTERISTICS Competition Nitrogen Plants m' Tillers plant"1 Plant height (cm) Shoot dry matter per plant (g plant"') A. myosuroides NO 28 53 97 24 Nl 35 52 101 26 N3 36 64 108 24 A. myosuroides NO 38 8 88 2 + winter wheat Nl 27 52 103 3 N3 30 64 114 5 B. Level of significance of factors andcovariables . ns = effect not Factors and Plants m" Tillers plant" Plant height Shoot dry matter per significant at a= covariables (cm) plant (g plant') 5% * ** *** V 0 0.92 0.58 0.93 **** = significant Competition ns **** ns *** atcc=5%, 1%, Nitrogen ns ** ** * 0.1%, 0.01%. * Plants m"~ **((negativn e correlation) ns ns for significant 1 Tillers plant" ns **((positivt e correlation) factors and covariables.

Table 3.A. myosuroidesreproductiv e growth and development. A.Mean s per treatment. FACTORS A. myosuroides CHARACTERISTICS Competition Nitrogen Number of Number of ripe Spikelets ear ' Grain Ear dry matter per ears per plant ears per plant viability (%) plant (g plant"1) A. myosuroides NO 44 32 5811 0.31 4.17 Nl 44 27 4391 0.31 3.58 N3 49 25 4092 0.41 2.89 A. myosuroides NO 8 5 604 0.35 0.30 + winter wheat Nl 11 6 878 0.48 0.19 N3 13 6 994 0.57 0.36 B. Level of significance of factors andcovariables . Factors and Total number of Number of ripe Grains ear" Grain Ear dry matter per covariables ears per plant ears per plant viability plant (g plant" ) r2* 0.93 0.91 0.93 0.40 0.88 Competition *** **** **** * ns Nitrogen * ns * * ns Tillers plant *** (positive corr.) Total ears plant"' ** (positive corr.) **** (positive corr.) Ripe ears plant"1 *** (positive corr. •) ns = effect not significant at a=5% . *, **, ***, **** = significant at a= 5%, 1%, 0.1%, 0.01%. *fo r significant factors and covariables. 530 Book of Abstracts 4th ESA-congress

SOILANALYSE S ANDFERTILIZE R RECOMMENDATIONS. SOFTWARE FOR SOIL TESTLABORATORIE S AND EXTENSION SERVICES. B. Colomb1, G. Fayet2, C. Villette3,M . Gigout2, P.Dubrulle 4, D. Baudet1 1INRA, Laboratoire d'Agronomie, BP27 ,3132 6Castane t Tolosan Cedex, France 2 EMRA, Laboratoire de Génielogicie l Nancy, France 3 SAA, Laboratoire d'analyse des solsLaon , France 4 INRA,Laboratoir e d'Agronomie Laon, France Introduction DEMETER is asoftwar e package designed to improve and facilitate, from regular fertility control based on soil analysis, fertilizer decision-making atth efiel d level, for farm managers using aconventiona l cropping systemi n temperate orMediterranea n areas.Al l nutrients of agronomic relevance other than N and Sar econsidere d :P ,K ,Mg ,Ca ,B ,Zn , Cu, Mn. We concentrate this presentation onth e three major macro or secondary elements. Methods Agronomic principles: The following main parameters are considered: 1/Cro presponsiveness : crops are classified asdemandin g crops (e.g . sugarbeet , potato, forage maize...) or non-demanding crops (wheat, grain maize...),accordin g to their responsiveness (significant yield changes) tonutrien t inputs asminera l fertilizer. 2/ Soil nutrient levels:extractabl e nutrient levels arerate d inthre eclasse s (low,medium , high). The lower threshold value refers to non-demanding crops,th e upper one to demanding crops. Calibration follows ametho d described byMore l et al. (1992).Ther e is noconstrain t concerning the analytical procedures which are under the control of the laboratory and chosen from among State or EUrecommende d lists (AFNOR, ISO ...). 3/ Soil ability to transform added nutrients into non- orpoorl y plant-available chemical compounds ort o affect physico-chemical status israte d inthre e main classes (moderate, medium to high, very high to extremely high),whateve r the analytical method (e.g.kineti c isotope exchange for P,Va n derMare l for K...). If analytical data are not available, soil survey results may be used. Threshold values for nutrient levels and fixation capacity for elements are specified and associated with any homogenous agronomic area defined by the user of the system. Then, depending onth e values of these criteria,field b yfield an d yearb y year, recommended amounts of nutrients to be applied wouldb e0 , fc, fe, ormax(fc , fe) where fc isth e amount of nutrient to be added to ensure production of the intended crop,an d fe is the amount to compensate for annual nutrient losses.Amount s (fe) of nutrients lost every year are calculated by adding up leaching and cropremoval s andmultiplyin g resultsb y coefficients related to fixing capacities of the soil towards theelements . The function which enables fc tob e calculated for Pan d Ki s : fc =a + uPr b (1 -Cs )/ C u where Pr represents themaximu m nutrient uptake during the growing period andrequire d for the expected yield; Cs describes the fraction of cropnutrien t demand which is supplied by the soil (when fertilizer is added);C u refers to fertilizer efficiency. The other parameters a, uan db are required to calibrate the function against reference datafro m field studies of cropresponse s to fertilizer input conducted in representative agronomic situations.A sensitivit y analysis has shown that Cs and Cu parameters areth e most important factors influencing fc. So,an y information orne w knowledge concerning both criteria should be adequately incorporated in the systemthank s toempirica l rules,takin g into account soil and crop characteristics. Session 2.3 531

Software description:DEMETE R consists of five independentparts : 1/A databas e designed to handle soils,cro p characteristics, composition of animal manures or urban wastes, identification of analytical procedures, threshold values for extractable elements and various criteria used for diagnosis orevaluatio n of nutrient requirements. 2/ Acor e program to perform allcalculation s required for nutrient ratings and prescriptive information processing. 3/ AGraphica l User Interface to update thedatabas e andt o tune agronomic parameters. 4/ Arul e interpreter allowing the evaluation of input data (other than the analytical data) from the environmental conditions,fiel d characteristics andcroppin g system features. For example it enables statements such as ''i f soil texture isloamy-san d and if one crop out of two is irrigated, then P-Olsenthreshol d values are 12an d 20m gP kg- ' soil". 5/ Acollecto r of the flow of output information allowing production of any kind of reports and connection with alinea r equation system solver tooptimiz e fertilizer use at farm level. The software was developed using the Object Oriented Analysis -Recursiv e Design method (Shlaer andMellor , 1988),a C+ +compile r and someC+ + libraries. Particular attention was paid to quality criteria, portability and extensibility to new algorithms.Th e different parts of the application may evolve -a sregard s their technical aspects -independentl y from one another. Results The information allows the farmer to answer theprimar y question that emerges when acro p has been chosen for afield, takin g into account itsresponsivenes s andth efield fertilit y features :i si t necessary to addnutrient s ?I f the answer isyes ,furthe r questions follow: why ?(to meet crop demand and/or to restore the fertility level to itsbasi c value),ho w much ?(amount s expressed in entirely soluble chemical form), inwha t ways ?(preferre d or highly recommended chemical forms of nutrients,timin g andincorporatio n requirements).Whe nther e is sufficient certainty that there willb e no loss of yield and nofal l of nutrient availability below aminimu m level,th e system clearly indicates for how long nutrients mayb e withheld, which ranges from 1 to 3year s depending on nutrient availability level, fixing capacity of soil,an d crop responsiveness. Furthermore, from intended applications of farmyard manure,industria l or urban wastes tob e usedb y the farmer during the next four years of the crop succession, DEMETER computes actual amounts of P, Kan dM g (used in making assessment of thepotentia l for nutrient lossi n agricultural runoff), maximum amounts of nutrient available for anycro p 1,2 o r 3year s after soil incorporation (tob e deduced from nutrient requirement to forecast mineral fertilizer amounts) and annual average nutrient input (contribution to long termnutrien t balances).

Conclusions DEMETER delivers relevant information in the form of a set of rules and indicators tob e used for fertilizer decisions by farmers for four successive years whatever the crops.I ti s usable for extensive or intensive cropmanagement , depending onth eway si twil lb e adapted andtune db y the users.Th e system was primarily designed for soil testing laboratories and extension services which intend to process numerous soil analyses originating from large and variable cropping areas. From the user's point of view,DEMETE R shows ahig h level of flexibility, allowing accurate customizing for any agronomic area. On the longter m this new system isexpected , if adequately fed with accurate references and widely used, toenhanc e the economic return and reduce detrimental effects on the environment of nutrient inputs. References Morel C.e t al., 1992.Agronomi e 12:565-579 . Shlaer S. and Mellor S., 1988.Object-Oriente d Systems Analysis. Prentice Hall.25 1p . 532 Book of Abstracts 4th ESA-congress

THE REACTION OF CULTIVARS SPRING BARLEY TO FERTILISERS AND SOWING RATES OF THE SEED UNDER CONDITION OFWESTER N REGION OF UKRAINE

Z.M. Copchyk and AY. Maruhnyak

Institute ofAgricultur e and AnimalHusbandr y ofWes t Region ofUkraine . Obroshyn L'viv region 292084 Ukraine.

Introduction The spring barley at the Ukrainetake s theth e second place after winter wheat and on average (1991-1994 )th e sown area amounts 3.4 millionhectare s and grain yields 2.83 t ha"1 .Th emos t powerful growing area ofgrai n springbare yi sth ewester n part, where sowing areamad eu p0.5 - 0.6 millionhectares . Here soils-climatic conditions allowt o obtainth e best grain brewing quality. Important meaning inth etechnolog y growing ofth e spring barley isth e application ofminera l fertilisers (Copchyk et al. 1979, 1985, 1989).Besides , applyne w moreproductiv e cultivars and sowingrate s spareth elarg e attention (Copchyk et al., 1978).

Methods The investigations ofth e institute (vil. Stavchany, nearL'viv ) byfield trial swer e conducted in 1994-1995 on dark grey sandy-loam soil. Predecessor were row crops (potatoes and fodder beets). Two cultivars -Rolan d and Nadiya (Nadiya created byinstitut e and ispresentl y under state straintestin g inUkraine) ,fou r rates (0,N3 0 P30K30 , N60 P60 K60, N90 P90 K90) and three sowing rates (4, 5, 6, millionviabl e seedspe r hectare) were studied infou r replications. The mineral fertilisers (asnitroammofosca ) respectively scheme offield tria lwer e applied. The density of seedlingwa s calculated and the plants for definition ofth e sctructure yield were chosen. The grain yield (14%) was estimated, 100-seed mass,protei n and starch content were measured.

Results Theminera lfertiliser s influence positivelyo ngrai nyield .The ygav eincreas egrai nyiel dfo r cv.Rolan d 0.51-1.18an d cv.Nadiy a0.56-1.41 1ha" 1.Th ecultivar sresponde d different to mineralnutrition . Highestgrai nyiel dbot hcultivar swa sobtaine dunde rminera lnutritio nN9 0P9 0K9 0o nal lsowin g rates. Thecultivar sresponde d different tominera lnutrition . Iffo rformatio n grainyiel di nrang e3.2-3. 5 tha" 1 cv.Nadiy afertilise r rate sufficient wasN3 0P3 0K3 0fo r cv,Rolan d iti sN9 0P9 0K90 .Bette r fertiliser ratefor v cv.Nadiy awa sN30-6 0P6 0K60 ,fo r cv.Rolan dN60-9 0P9 0K90 .Thos e fertiliser rateswer emos t economicaladvisabl ebecaus ethe yprovide d highestincreas eo fgrai no n 1 kgNPK .

Theyiel d andquality ofgrai nth e cultivars depending onfertiliser s and sowing rates, 1994-1995. Control N30-P30-K30 N60-P60-K60 N90-P90-K90 Sowing rate (mlnha" 1) 4 6 4 6 4 6 4 6 Cultivar Roland Grain yield (t ha"1) 2.16 2.29 2.67 3.00 3.03 3.26 3.28 3.47 Protein contant (%) 11.1 10.5 11.1 10.8 11.7 11.5 12.3 11.8 Starch content (%) 58.5 60.6 57.1 58.0 56.0 58.0 56.4 58.0 Cultivar Nadiya Grain yield (t ha"1) 2.62 2.90 3.18 3.50 3.70 3.99 4.03 4.20 Protein contant (%) 10.4 10.0 10.6 10.4 11.3 11.0 11.5 11.2 Starch content (%) 60.8 62.0 59.1 61.2 59.1 59.5 57.8 59.3 LSD 0.05. For cultivars 0.22; for fertliser 0.2;fo r sowing rates 0.15. Session 2.3 533

Increasingsowin grate sfrom 4 t o 6millio nviabl eseed sha" 1 increasedgrai nyiel dbot hcultivar so nal l variantso fminera lnutrition . However, moreadvisabl esowin grate swer e4- 5millio nseed s ha"1. Data structuregrai nyiel d showo nth epositiv eeffec t ofminera lfertilise r onmas san dnumbe r ofgrain s perear ,numbe r ofear spe rsquar emeter , 1000-grainmass ,numbe ro fgrai npe rear ,mas so fgrai npe r earan dincrease d number ofear spe rsquar emeter . Theprotei n contenti nth egrai nbarle yincrease d withincreasin gth eleve lo ffertilise r nutritionan ddecrease dwit hincreasin gdensit yplants , starch content onth econtrary . Thegrai nbarle ycv .Nadiy acharacterise d smallerprotei n content andhighe r starchconten ti ncompariso nt o cv.Roland , thati spointe d onit sbette rbrewin gquality .

Conclusions Ast o grainyiel d atwester npar t ofth eUkrain ecv .Nadiy aprevaile dfrom cv .Rolan dfrom 0.4 5 to 0.811ha" 1.Thi scultiva r alsobette rresponde dt o applicationo fth eminera lfertilisers . Bettero f fertilisers ratefo r cv.Nadiy awa sN30-6 0P6 0K60 ,fo r cv.Rolan d -N60-9 0P9 0K9 0unde roptima l sowingrate s4- 5millio nviabl eseed spe rha .Th ecultiva r ofth e springbarle yNadiy acharacterise d betterbrewin gqualit yo fgrai ni ncompariso nt o cv.Roland .

References Copchyk, Z.M. et al., 1979. production of smallgrain s inth eregio n normal and axcesseable of moisture Kyiv"Urozhai" : 94-119. Copchyk, Z.M. et al., 1985.Journa l ofth e news ofagricultura l science 2:45-47 . Copchyk, Z.M. et al., 1979.Variety' s agrotechics of smallgrai n Kyiv"Urozhai": ;228-242 . Copchyk, Z.M. et al., 1979.Proceeding s Institute ofAgricultur e andAnima lHusbandr y of Western Region ofth eUkrain e 23: 22-24. 534 Book of Abstracts 4th ESA-congress

POTATO CROP GROWTH AND NUTRIENT CONCENTRATION AS INFLUENCED BY SOIL-PH AND POTATO CYST NEMATODES

F.J. deRuijte r &A.J . Haverkort

DLOResearc h Institute for Agrobiology and SoilFertilit y (AB-DLO), P.O.Box 14,670 0A A Wageningen, the Netherlands

Introduction Infection by potato cyst nematodes {Globoderapallida) isassociate d ingenera l with reduced concentrations ofnitrogen , phosphorus and potassium inth e foliage. Trudgill (1987) found that NPK-fertilisation increased yield stronger at hightha n at lownematod e densities, indicating that nematodes induce nutrient deficiency. Asphosphoru s ison e ofth e elements most likelyt o limit the growth ofnematod e infested plants (Trudgill, 1980), we studied the effect ofpotat o cyst nematodes in combination withphosphat e fertilisation and soil-pH. Here we focus onth efirst par t ofth e growing season.

Methods The experiment was carried out in 1995 on asand y soilwit h cultivar Mentor. Previously, different levels of soil-pHwer e established bylimin g and current soil-pH-KClwa s 4.8 and 6.1. Different levelso fnematod e densitywer e established by soilfumigatio n and plotswer e split into two levels ofP-fertilisation , 0an d 225 kgP pe r hectare. All plots received 230 kgN and 125 kgK pe r hectare. Effects ofth e different treatments on phosphorus availability indexP w and on nematode population density are shown inTabl e 1.Tuber swer e planted on April 21 and the crop was harvested on June 21.

Table 1.Effect s ofphosphat e application onPw-valu e and of soilfumigatio n onth e number of livingjuvenile s per gram soil at two pH-levels.LS D for comparison ofal lmeans . treatment pH-KCl LSD 4.8 6.1 phosphorus index (Pw) non-fertilised 62 47 fertilised 84 62 7 population density fumigated 5 6 non-fumigated 47 25 9

Results Thetreatment s ledt o differences intota l dry matter production and affected concentrations ofN , P and Ki nth e leaves (Table 2). On fumigated soil, the reduced yield at pH 6.1withou t P-fertilisation appeared to be caused byphophoru s limitation asleaf- P concentration was near the deficiency level of 3.0 (Walworth and Muniz, 1993)an d P-fertilisation increased leaf-P concentration and yield. Leaf concentrations ofN and Khardl y differed between the soil-pH or P-fertilisation treatments onfumigate d soil. Nematodes significantly reduced total drymatte r production and leafnutrien t concentrations (Table 2). The effect ofnematode s could largely be attributed to P-limitation, as leaf-P concentrations similart o that ofth elimitin g concentration of 'pH 6.1withou t P-fertilisation on fumigated soil' gave similaryields . Lower leaf-P concentrations showed afurthe r yield decrease. Session2. 3 535

However, not all damage bynematode s could be attributed to P-limitation. At pH4. 8 withP - fertilisation, leaf-P concentration was near sufficiency levels (Walworth and Muniz, 1993)bu t dry matter production ofnon-fumigate d treatments was reduced. Leaf-N concentrations were reduced by high levels ofnematode s but the reduced dry matter production could not be attributed to nitrogen limitation, asvariatio n inP-fertilisatio n and soil-pH resulted inlarg e differences indr ymatte r production at equal leaf-N concentrations. High levels ofnematode s decreased leaf-K concentrations but the highest dry matter production levels hadth e lowest leaf-K concentrations, indicatingtha t dilution ofK too k place. Thelowes t leaf-K concentrations were close to the deficiency level and may explain the reduced dry matter production onnon-fumigate d soil at pH4. 8 without P-fertilisation.

Table 2.Effect s of soil-pH, phosphate fertilisation and soil fumigation ontota l drymatte r production (g m"2)an d leafnutrien t concentrations (g kg"1),6 1 days after planting. LSD = least significant difference (P=0.05), value inparenthese s isfo r comparison within the sameleve l of fumigation. pH4.8 pH6.1 P- P+ P- P+ total dry matter (gm" 2) fumigated 288 293 182 253 non-fumigated 198 222 111 164 LSD 39 (32) 58 (52) leafN-concentratio n (gkg" 1) fumigated 59.2 58.2 54.6 56.4 non-fumigated 49.6 53.4 49.8 50.2 LSD 2.9(3.1) 2.9(3.1) leafP-concentratio n (gkg" 1) fumigated 5.68 6.30 3.77 4.64 non-fumigated 3.90 5.17 3.13 3.99 LSD 0.50(0.57) 0.49 (0.43) leafK-concentratio n (gkg" 1) fumigated 47.8 51.6 51.8 55.0 non-fumigated 40.2 40.5 46.5 44.3 LSD 7.4 (8.8) 4.6 (4.2)

Conclusions We conclude that potato cyst nematodes affect nutrient uptake, leadingt o reduced concentrations ofN , P and Ki nth e foliage that may cause nutrient deficiency. Which element becomes deficient depends onth e availability inth e soil. Asw e found most effects ofphosphoru s at relatively high Pw-values inth e soil, we expect phosphorus, ingeneral , to limit early crop growth when infected bypotat o cyst nematodes.

References Trudgill, D. L., 1980.Nematologic a 26: 243-254. Trudgill,D .L. , 1987.Plan t and Soil 104: 235-243. Walworth, J. L. &Muniz , J. E., 1993.America n Potato Journal 70:579-597 . 536 Book of Abstracts 4th ESA-congress

INFLUENCES OFBIO-DYNAMI C AND ORGANIC TREATMENTS ON YIELD AND QUALITY OFWHEA TAN D POTATOES: THEWA Y TOAPPLIE D ALLELOPATHY?

G.Deffune' , A.M. Scofield,H.C .Lee ,J.M .Lopez-Rea l andP .Simünek 2

SustainableAgricultur eResearc h Groupan dBiologica l SciencesDepartment . WyeCollege ,Universit y ofLondon ,Wye ,Ashford , KentTN2 5 5AH,Fax :(01233 ) 813320,U.K . 'E-mail: [email protected]

Introduction Manyorgani csubstance shav eallelopathi ceffect s inagroecosystem s(Rice , 1984).Th eso-calle d biodynamic(BD )preparation swer eth efirst se to fplan t extractsan d solutionswidel yuse di nwha tca n beregarde d asapplie dallelopath yi nfarmin g systems(Deffune , 1990).Thi smetho d hasbee n succesfully usedb yBrazilia nfarmer s (Pioe tal , 1984)an dhold sa grea t potentialregardin g biodiversity,fo rth ediscover yo fne wsource so factiv eprinciple so ringredient s(Almeida , 1988).A PhDresearc hprojec t toinvestigat ethes eeffect s andtechnique si susin gsprin gwhea t(T. aestivum, var. Canon)an dpotatoe s(S. tuberosum,vars .Car aan dPentlan d Crown)i nfield trials ,supplemente db y glasshousean daxeni cexperiments .Cro pyiel dan dhealth ,nutritiona lan dkeepin gqualitie so fproduc e aswel la ssoi lchange sar eth eparameter sevaluated .

Methods Randomized completebloc k blind experiments,wit h secret codes for both compost, soilan d spray treatments: A=control, A+= chemical fertilizer and foliar spray, B&C=blind BD& Organic , using 60 T ha"1o f standardized compost treated with preparation sets and spraysblind-labelle d B&C. Double-blind re-coding ofwhea t sampleswa suse d for quality assessment of grain and flour.Successiv e cropping seasons (1993-95) areuse d to check for cumulative effects, with crops cultivated in spring/summero f 1993-95 and rotation with rye/vetch mixture for green manurean d weed control (1994). Thebiomas swa s left asmulc h inB& C plots and removedfrom th e control plots. Thetreatment s were Bio-dynamic preparations applied asfollow s (KoepfH He t al., 1976): 1.Fiel d sprays -use d in sequence and additional to compost treatments: • P500 soil spray (17m lm" 2),fermente d cow manure, stir-diluted 3.3 g l"1. • P501 plant spray (138 mlm" 2),silic adynamize d 83m gl _1(5gpe r 60 1). • Nettle water 2% Urticadioica (planta tota) 138m lm" 2; 1st month • Equisetumarvense decoctio n 1%stir-diluted , 138m l m"2. • Kieselguhr(diatomaceou s earth) 0.5% stir-diluted, 138m l m"2. 2. Compost additives P502 to P507 (200mg m"3):Achilea millefolium - flowers ,Matricaria recutita- flowers , Urticadioica- plant atota , Quercus robur- bark , Taraxacum officinale- flowers and Valeriana officinalis- flowers ' liquid extract. 3. Mixed spray (blind coded)fo r tilled soilmanure d withuntreate d standard compost in 1993 (1st year)trials : P500 (200g per 60 1) + P502-P506 (4g per 60 1 = 66.7 mgl" 1)+ P50 7 (4ml per 601). 4. Inth e second year (1994), whileth efirst yea r plots wereunde r green manurerotation , two additional field trials ofwhea t &potatoe s were set in split-plot designsbetwee n the samesoi l treatments andfive sprays : 10% solutions of Urticadioica, composts B and C;a mimi c concentration Murashige & Skoog saltsnutrien t solution and awate r control. 5. Inth ethir d yearth e successivecroppin gplot swer ere-plante dwit hwhea t &potatoe s under split- plot designsbetwee n the four soiltreatment s andtw o blind-sprays, with and without P501 silica.

Results Contrastso finteres t (Pearce, 1992)sho w statistically significant differences asfollows : Session 2.3 537

1Whea t -A v sB& C andA +v sB& C inbot hgrai n andbiomas syield san dqualit yi nterm so f ThousandGrai nWeigh t(TG W )an dbakin gpropertie s(HFN* -Hagber gFallin gNo.) .A +ha dhighe r yieldbu t lowerqualit y thanth eothers .Th eB Dtreatmen t showedoptima lHFN*(249.83 )wit ha lowe r phosphorus**conten ttha nth eOrgani c(th ehighes ti nP) ,whil eothe relemen tlevel slik eCa ,K , Na, N03 andAs hdi dno tvar y significantly. 2.Potatoe s- A+v sB&C ;yield sdi dno tdiffe r indr yweigh t andA +potatoe sha dth elowes tdr y matterconten t " after a6 mont h storageperiod . B&Chav eals oshow nbette rconservation *(les s "spraing"i.e .tissu edarkening) .B v sC ; Bha da highe ramoun t of"chats" *(tuber ssmalle rtha n40mm ) than C.Ther ewer eoveral l differences betweentreatmen t systems* andvarieties*** .

HFN scores: below 150 =stick y bread; between 200 & 300 = acceptable; 300 plus = dry bread.

| Ideal: 250

Contrasts: A+vsO, BD (FProb-0,0308); O vs BD (FProb= 0,0105)

Control (A) Agrochemical (A+) Organic (O) Biodynamic(BD) Figure: Baking quality of spring wheat "Canon", usingHagber g FallingNumbe r (inverse ofalpha - amylase activity), comparing four treatment systems indouble-blin d RCBfield trial s (1993).

Conclusions Significant qualitydifference s betweenBio-dynami c andOrgani ctreatment sindicat eth epresenc eo f allelopathic stimulationb yth eB Dpreparations ,showin gth ewa yt odetec tthes esubtl eeffect s (Smith, 1993).Muc hhighe r soilnitrat elevel si nth epositiv econtro l "A+" plotsdi dno tincreas eproportionall y theyields ,bu t significantly relatet olowe rqualit yi nbot hwhea tan dpotatoes .Result ssho wth e possibilityt oimprov ecro pyiel d andqualit yo fproduce , through simple and environmentally adequatetechniques ,directl yavailabl et ofarmer s (Reganold etal , 1993).

References Almeida,F.S .(1988) .A alelopati a ea splantas .Circula rn°53 ,IAPAR ,Parana ,Brazil ,6 0 p. Deffune, G. 1990. MScDissertation , WyeCollege , 1-28. Koepf,H.H . et al, 1976.Bio-dynami cAgriculture : anintroduction ,4 :206-224 . Pearce, SC 1992. Experimental Agriculture 28: 245-253. Pio, D.M. et al.,1984 .Lebendig eErd e 6: 269-274. Reganold, J.P. et al, 1993. Science 260: 344-349. Rice, EL. 1984. Allelopathy, Academic Press, Orlando, 10: 266-291 Smith,R.L . 1993.Journa l of Applied Nutrition, 45(1): 35-39.

PhD Student sponsoredb yCNP Q- th eBrazilia nNationa lResearc hCouncil . PhD Student -Departmen t ofFoo d Technology,Mende lUniversity , Brno, CzechRepublic . 538 Book of Abstracts 4th ESA-congress

EFFECTS OFNITROGE N DEFICIENCIES ONGRAI N SETI N WHEAT

S.Demotes-Mainard ,M.H . Jeuffroy

Institut National de laRecherch eAgronomique , Laboratoire d'Agronomie, 78850 Thiverval- Grignon, France

Introduction Muchvariatio n ingrai n yield ofwhea t cropsi sclosel y associatedwit hvariatio n inkerne l number peruni t land area (Midmore etal, 1984).I t isthu s important tostud yth eeffect s of the different factors affecting kernelnumber .Th eeffect s ofplan tnitroge n nutrition ongrai n set arestil lno t well known.Th eai m of thisexperimen t wastherefor e tostud y inwhea t therelationship s between theN suppl y toth eplant ,an dparticularl y toth eear ,an dkerne l numberpe rea ri nsituation so f nitrogen deficiencies.

Methods Winterwhea t cv.Soisson swa sgrow n inth efield nea rPari sfo r oneseason .N fertilize r was brought atdifferen t datesan drate s inorde rt oachiev e 8experimenta l treatments:on e control treatment (Nno n limiting),an dseve ntreatment swit hnitroge n deficiencies (Fig. 1). The beginning ofperiod s ofN deficienc y wasdate db yweekl y measurements ofth econcentratio n of nitratesi nth ebas eo fth estem so fmai nshoot s(Justes ,1993) .Accumulatio n ofdr ymatte ran d nitrogen inear so f main shootswa smeasure d twicea wee k until anthesis.Kerne l numberwa s counted at harvest. degree -days from sowing(b : ase 0*C) 850 900 950 1000 1050 1100 1150 1200 1250 1300 1350 1400 dates 18/3 26/3 8/4 28/4 1/5 6/5 Treatment c. Nl N2 N3 N4 N5 N6 N7

Fig. 1.Experimenta l treatments.Bol d linesrepresen t periodso fnitroge n deficiency, dotted lines periodso f non limitingnitroge n nutrition.N deficiencie s oftreatment s Nl, N2,N 3an d N4laste d until harvest.Beginnin g of stem elongation:95 0degree-days , anthesis: 1644 degree-days.

Results anddiscussio n Thetreatment s induced different kineticso f accumulation ofbiomas san d Ni nth eea ran d affected kernel number perear .Ther ewa sa significan t linearrelatio n between thenumbe ro f kernels perea ran d eardr yweigh t atanthesi s(Fig .2 ,dotte d line,r 2=0.96,df=6) , showingtha t N deficiencies affected kernelnumbe rpe rea rlargel y throughthei reffec t oncarbo n assimilates supply toth eear .However , for alltreatment s thatha dbee nsubjecte d toN deficiencie s kernel numberpe r earwa s lower thanexpecte d accordingt oth ecurvilinea r regression (Fig.2 ,bol d line) between kernel numberan dea rdr yweigh t established by Gatean d Grimaud (1989) ona wid e rangeo f varieties and growingcondition s inno nlimitin gN nutrition .Th e fact that thenumbe ro f Session 2.3 539 kernelswa slowe r underN deficiencie s thanexpecte d inno n limiting Nnutritio n (curvilinear relation) isconsisten t withth eresult so fAbbat eet al. (1995). Thedifferenc e between the observed number ofkernel spe rea ran dth evalu e expected according toth eregressio n of Gatean d Grimaud canb einterprete d asa direc t effect of Ndeficienc y on kernel number.Thi sdifferenc e islinearl y correlated (r^O.64,df=6 ) toth econcentratio n of Ni n the eara tth ebeginnin g of theperio d of linearaccumulatio n ofN i nth e ear(138 0 degree-days after sowing)(Fig .3) ,suggestin g that thisdirec t effect of Nshortag ewa sdetermine d ratherearly , before therapi d growth of theear .

§«

r£2

150 200 250 300 350 400 Eardr yweigh ta tanthesi s(m gear -1)

Fig.2 .Relationshi pbetwee n eardr yweigh t atanthesi san dkerne l numberpe r ear. Barsrepresen t ±standar d deviation. Dotted line:linea rregressio n onth eexperimenta l data. Bold line:regressio n established by Gatean d Grimaud (1989)o ncrop sgrow nwithou t N deficiency.

2.7 2.9 3.1 3.3 3.5 3.7 N concentrationo fth eea r(% )

Fig.3 .Differenc e between thekerne lnumbe rpe rea rpredicte d byth eregressio n of Gate and Grimaud (1989)an dth eobserve d kernel number,plotte d against Nconcentratio n of theea r atth e beginning of theperio d of linearaccumulatio n ofN i nth eea r

References Abbate,P.E .et al, 1995.Journa l ofAgricultura l Science,Cambridg e 124:351-360 . Gate, P.et ai, 1989.Perspective sAgricole s 132:18-30. Justes,E. , 1993.Thès ed edoctorat , ESTAP-G ,227p . Midmore,P.M. ,et al, 1984.Fiel d CropsResearc h 8:207-227. 540 Book of Abstracts 4th ESA-congress

OILSEED RAPE OIL YIELD AND QUALITY IN RELATION TO FUNGAL DISEASE

K. J. Doughty', C. J. Lewis1, H. A. McCartney1, G. Norton2, E. J. Booth3, K. C. Walker3

'Department of Crop and Disease Management, IACR-Rothamsted, Harpenden AL5 2JQ, UK. department of Applied Biochemistry and Food Science, University of Nottingham, Sutton Bonington Campus, Loughborough LE1 2 5RD, UK. Scottish Agricultural College, Craibstone Estate, Bucksburn, Aberdeen AB21 9YA, UK.

Introduction Oil produced from rapeseed in Europe is currently used mainly for food, but it can also be used for an increasing number of industrial applications. The fatty acid composition of the oil is a major determinant of quality for both end-uses, hence the importance of an agronomic approach that maintains the yield of the desired component(s). Fungal pathogens of rape can reduce dry matter yield substantially, but little is known of their effect on seed oil content and quality. Economic and environmental constraints preclude the prophylactic application of fungicides to rape, so they should be used only when likely to improve yield and quality. To investigate the stability of quality under 'low-input' conditions (at least with regard to crop protection), we measured the oil content and fatty acid composition of seed from a range of conventional cultivars grown with and without fungicides.

Methods Seed samples of double-low winter rape were obtained from three experiments done at two sites in the UK during 1994-5. At IACR-Rothamsted (IACR), two cultivars were grown in replicated plots that were either inoculated at the beginning of the season (by applying contaminated rape straw), or treated with fungicides in autumn, spring and summer to control disease. At SAC-Aberdeen (SAC), eighteen cultivars were grown without replication in plots that were either treated with fungicides (following a similar programme) or left untreated. Analyses were made of disease incidence at both sites, and of the effects of disease on plant growth and canopy structure at IACR. In addition, individual plants infected withSclerotinia sclerotiorum(ste m rot) were collected from plots at IACR shortly before harvest. Seed samples from all sources were dried, cleaned and analysed for thousand seed weight, oil content and fatty acid composition at the University of Nottingham. IACR samples were also graded for seed diameter, and the different grades were then re-analysed for oil content.

Results Fungicide-treated plots were characterised by later-developing and less severe epidemics of most diseases. Compared with fungicide-treatment, inoculation typically led to reduced plant populations, delayed flowering and, eventually, patchy maturation on the more highly- branched surviving plants. Inoculated plots produced dry matter yields up to 1t ha' (approx. 25%) lower than those from corresponding fungicide-treated plots. Of the diseases recorded, light leaf and pod spot (Pyrenopeziza brassicae) and dark leaf and pod spot(Alternaria brassicae &A.brassicicola) were those most closely associated with these effects. Seed from inoculated or untreated plots usually had a lower oil content than that from corresponding fungicide-treated plots. In the SAC experiment, seed oil content at harvest was associated with the severity of earlier light leaf spot infection, irrespective of whether plots had been treated with fungicides (Figure 1). The oil- and protein-contents of seed dry matter were generally inversely related, seed from heavily-diseased plants having a higher protein content. The lower oil content of samples from inoculated plots was associated with smaller Session 2.3 541 seeds, and oil analysis of graded samples showed that seed from inoculated plots contained slightly less oil than seed of similar diameter from fungicide-treated plots (Figure 2).

r= -0.498 ,PO.0 1

Figure 1. Relationship between disease severity (April) and oil content (harvest) in fungicide- treated and -untreated plots of - -i + t- eighteen cultivars (SAC). Oil 10 15 20 30 25 analysis after Soxhlet extraction. Lightlea fspo tseverit y (%)

IFungicide-treate d •Untreated

C C O

Figure 2. Association between seed size and oil content of cv. Capricorn, as affected by disease > 2.4 mm 2.0 -2. 4 mm 1.7 -2. 0m m (IACR). Oil analysis by NMR. Seed diameter grade

Disease also caused marked changes in the fatty acid composition of the oil. Seed from heavily-diseased plots generally contained less oleic acid [18:1], but more polyunsaturated fatty acids (linoleic acid [18:2] and a-linolenic acid [18:3]). Oil from plants that were girdled by stem rot had the same composition as that from uninfected plants with respect to the major fatty acid components [16:0, 18:1, 18:2 & 18:3] but it contained more eicosenoic acid [20:1]. Erucic acid [22:1] and hexadecatrienoic acid [16:3] were only present in the oil of the infected plants.

Conclusions The results confirm that, as well as reducing the dry matter yield of oilseed rape, severe disease can further affect oil yield by reducing seed oil content, mainly through an effect on seed size. They also indicate that particular diseases can affect oil quality via specific changes in fatty acid composition. A combination of cultivar disease resistance and the directed, economic use of fungicides appears to be essential if processors are to be supplied consistently with a product of the appropriate quality, and will be a precondition for the success of future industrial rape crops.

Acknowledgement This work is being funded by the United Kingdom Home-Grown Cereals Authority 542 Book of Abstracts 4th ESA-congress

RELATIONSHIP BETWEENWEE D LEVELAN D LEAF AREA IN INBRED MAIZE LINES

M. Burkic,M . Knezevic, I. Juric

Faculty ofAgriculture ,P.O . Box 117, 31000 Osijek, Croatia

Introduction Themoder n maizeproductio nprefer s anintegrate d cropprotectin g system ofwee d controlb y meanso freduce d herbicide application (Prasad et al., 1990; Blair et al., 1993;Pimente l et al., 1993; Ford et al., 1994). Development andus e ofa nintegrate d system ofwee d control requires detailed information on crop-wee d interactions,includin gth eimpac t ofth erelativ e competitive ability ofth e crop during different phases of development onwee d growth, (Tollenaar et al., 1994). The aimo fthi sresearc h wast o determineth e effects ofth emechanica l and chemicalwee d controlwit hreduce d herbicide use onlea f areainde x and seedyiel d ofth e maizelin eo n different types of soili nEaster n Croatia.

Methods Fieldtrial swer e conducted on eutric cambisol (EC),luviso lpseudogleyi c (LP), andluviso l(L ) soiltype so ntw o inbred maizelines : male "OS 1-44" and female "OS 36-16"fro m 1993tol995 . Fivemechanica l and chemicalwee d control systemswer e asfollows : 1.on einterro w cultivation; 2. oneinterro w cultivation +tw ohoeings ; 3.mixtur e ofmetolachlo r + atrazine(180 0+ 1200g ha"1)pre-em . broadcast; 4. mixture ofmetolachlo r + atrazine(90 0 + 600 gha" 1)applie d inbands ; 5.rimsulfuro n (60 gha" 1)post-em . Thetria lwa s setu p asa split-spli tplo t design in four replications. Theinbre d lineswer e sown from thethir d decade ofApri lt o thefirs t decade ofMa y every year. The surface of eachplo twa s44. 8 m2. Weednumbe r andwee dbiomas s ofeac h specieswer e estimated by counting andweighin gth eplant spe rm 2, 60t o 65 days after sowing. Leaf areainde x valuesfo r female andmal e lineswer e estimated onth ebasi s ofth etota llea f number offive plant sfro m eachvarian t randomly selected shortly after silking. Cropswer e harvested atth e end of September. The seed yieldvalue s ofth e female line,havin g 14%o f moisture, are giveni nt ha" 1.

Results Weed control andsee dyiel d arepresente d inth etabl e andLA Ivalue sar e shown inth e figure.

Table. Number ofweed s(m 2) andsee dyiel d( tha" 1)i n 1993-1994

Eutric cambisol Luvisol pseudogleyic Luvisol Mean Treat­ No. of Seed No. of Seed No. of Seed No. of Seed ment weeds yield weeds yield weeds yield weeds yield 1 185.3 1.22 33.8 2.94 57.9 2.23 92.3 2.13 2 30.6 3.14 12.6 3.62 27.1 3.32 23.4 3.36 3 75.8 2.31 5.3 4.16 16.2 3.38 32.4 3.28 4 96.7 1.57 12.4 3.51 20.4 3.15 43.2 2.74 5 70.1 2.02 7.5 3.47 30.3 3.11 36.0 2.87 Mean 91.7 2.05 14.3 3.54 30.4 3.04 45.5 2.88 Session2. 3 543

Figure. Influence ofmechanica lan d chemicalwee d control onlea fare ainde xi nmal e(• )an d female (D)maiz e lines.EC ,L P and L: soiltypes ; 1-5 mechanical and chemicalwee d control treatments. 1993

1994

Leaf area index C LAI ) ...•iTwniiiiitiBfl^^"-^^^

3.6 i|l|]ffl[|J]|M L»aiiÉi8lBgB 3^••fctoftS4t^sT*1^**J,^Ä'*-r BHmBjiZS&Ml^^^B^ """"-•J 3-* 3.2. fSraH^m^äf^^ 2.8 ÏSra§@ffift iB •^^M^^H^^B*-^!!^ 3.2 2.4 I^JSLB^S^^B H^^H^^BH^p^iÄ^fiteC^"'^^ 2.8 •2. yjÊjk ^^BBKH^ ~:äEhr^*Z—ff Z4 2 L6 Hffi l^^^^^l HH^^ufflHJI^H SÊh^Lfa^Y L6 L2 WBkH^^^v^ l V-^^1^^9^HH^H|HV fsÊJËÊËm*™? o.s ^ffVgl^^B^gg S JmMBF^-.rigm^--"dSI^B- ••M^^^Mi L2 <"*st*».^^ H w x DÉ^H BaalJR^fcad^ ^ as *-** L*>^r ^i;-\ is3 * ;^^H^^V^ ^^^^H^^^r^?^*,,-e ^? J_ *** 5?l^^^Eti^^^B^^^ ^4 L ^^^^^H^^^^**^ 3 ^^^S^*"^ 2 BC; i

Conclusions Leaf area index,wee d number andsee dyiel d depend onth e soilcharacteristics , climatic conditionsi nth e growth seasons andwee d controltreatments . Leaf area index wasi nnegativ e correlation with weed levelo n alltype so fsoil . Thelowes t LAI and seed yield valueswer e determined inth evarian t with thehighes t weednumber , i. e.wit h one interrow cultivation(1) . Variantswit h one interrow cultivation +tw o hoeings (2) andmixtur e ofmetolachlo r+ atrazine (1800+ 1200 gha" 1)pre-em. , appliedbroadcas t (3) gavea significantl y lower weed number, higher LAI andhighe r yield (P<0.01). Thehighes tyiel d (3.541ha" 1)an dhighes t LAI values (2.21)wer e determined onluviso lpseudogleyi c soil.

References Blair, A.M. etal. , 1993.Brighto n Crop Protection Conference, 985-990. Ford, G.T. etal. , 1994.Wee d Technology, 8: 124-128. Pimentel, D.e tal. , 1993.Agjcultur eEcosystem san dEnvironment , 46:273-278 . Prasad, T.V.R. etal. , 1990. Mysore Journal ofAgricultura l Sciences, 24: 39-44. Tollenaar, M. etal. , 1994.Agronom y Journal, 86:591-595 . 544 Booko fAbstract s4t h ESA-congress

REDUCING FERTILIZATION IN MAIZE IN SOUTH-WEST SPAIN

J.E. Fernandez, J.M. Murillo, F. Moreno, F. Cabrera, E. Fernândez-Boy

Instituto de Recursos Naturales y Agrobiologia (IRNAS, CSIC) Apartado 1052, 41080-Sevilla (Spain)

Introduction In many areas of South-West Spain where maize is intensively cropped, the worrying increase of nitrates in groundwaters detected in the last years has led to a marked interest in the possibilities of reducing fertilization. This paper shows the crop response of maize cropped consecutively for five years under Mediterranean management practices, using two different fertilization rates: that widely used by the farmers (500 kg N ha"1 yr"1); the other one third of it (just to cover the N crop requirements).

Methods The experiments were conducted in SW Spain (37.2° N, 6.1° W). Maize (cv. Prisma) was cropped in a 0.1 ha experimental plot from 1991 to 1995 (March to August, 75,000 plants ha"1, 50 mm weekly furrow irrigation). The plot was divided into two 450 m2 subplots, to establish two N fertilization treatments. Subplot A had 510 kg N ha"1 yr"1, a rate widely used in the area. Subplot B, had 170 kg ha"1 yr"1 (28% of the N applied some 10 days before planting, and the rest on two occasions, at about 45 and 75 days after planting). Drainage and nitrate leaching in each subplot were monitored throughout the experimental period (Fernandez et al., 1994). Crop height, leaf area index and phenological state were monitored every 7-10 days. Yield parameters and nutrient concentrations in Kernel were also measured (Murillo et al., 1992).

Results Results are presented in Tables 1an d 2, and in the Figure.

Conclusions It can be concluded that the reduction in fertilization caused no reduction in final crop development and production. The only difference was that N concentrations in the kernels were found to be higher for the higher fertilization rate. The reduction of crop performance throughout the experimental years may be due to the negative effects of monocropping (Bhowmik et al. 1982). The high fertilization rate in subplot A gave high N03-N contents below the root zone, the excess not being taken up by the crop but temporarily incorporated into the soil organic matter, as observed by Fernândez-Boy (1994). Therefore, not only can crop performance be maintained with lower fertilization rates, but a significant reduction of N03-N pollution of groundwaters is achieved.

References Bhowmik P.C. et al., 1982. Agronomy Journal 74: 601-606. Fernandez, J.E. et al., 1994. International Conference on Land and Water Resources Management in the Mediterranean Region. 4-8 September, Valenzano, Italy. Vol. I Water Resources management, pp 327-340. Femändez-Boy, E., 1994. PhD Thesis, University of Seville, 251 p. Jones, J.B. et al., 1990. In: Soil Testing and Plant Analysis, ed Westerman R.L. Soil Science Society of America Inc, 521-547 pp. Session 2.3 545

Murillo, J.M. et al., 1992. Communications in Soil Science and Plant Analysis, 23: 1767- 1779.

Table 1. Mean values of plant height (cm), leaf area index (LAI), ear weight (g), 1000 kernel weight (g) and total grain yield (Mg ha'1) (at 10% moisture). N rate in kg N ha"1 yr'.

Plant Ear 1000 kernel Year N rate height LAI weight weight Yield

1991 510 291 a 5.45 a 209 a 314 b 13.0 170 294 a 5.37 a 214 a 334 a 13.2

1995 510 154 b 3.24 a 129 b 281 a 8.3 170 167 a 3.36 a 156 a 288 a 9.9

Table 2. Concentrations of N, P, K (g kg"1) and Fe and Zn (mg kg"1) in kernels (mean values on a dry matter basis). N rate in kg N ha"1yr" 1.

Year N rate N P K Fe Zn

1991 510 13.1a 2.80 a 3.38 a 26 a 21 a 170 12.3 b 2.60 b 3.24 b 32 a 19a

1995 510 12.1a 2.30 a 4.50 a 15 a 15 a 170 10.3 b 2.50 a 4.50 a 20 a 16 a

(*) 10.0-25.0 2.0-6.0 2.0-4.0 30-50 —

(*) = Normal ranges for corn kernels (Jones et al., 1990)

60 Figure. Water and NO,,—N 40 contents of the soil at 0.8 - 1 m depth (below 20 is dry the root zone) in subplots crop period nerïód Ta^n7 period _T" 0 A (•) and B (o), from March 1993. The arrows represent

BO deep fertilization (day -13) and two top dressing ferti­ I lizations (days 43 and 77) CO K O (day 0 = planting date, 0 ,jCP T*P -#P •$& 24 March). Day after planting 546 Book of Abstracts 4th ESA-congress

AMMONIUM THIOSULPHATE (ATS) AS AN ENVIRONMENTALLY FRIENDLY TOOL

FOR N AND S NUTRITION OF RAPESEED {Brassica napus L )

J. Fismes, PC Vong, A. Guckert

Laboratoire Agronomie et Environnement ENSAIA-INRA, 2, avenue de la Forêt de Haye, BP 172, 54 505 Vandoeuvre lès Nancy, France Introduction For its inhibitory action on nitrificatin and urease activity, the ammonium thiosulphate (ATS) is commonly used in combination with liquid urea ammonium nitrate (Janzen et al, 1984; Goos, 1985). Moreover, because the ATS contains a double source of N and S, its utilization in conjunction with other fertilizers would contribute to a better uptake of these two elements by the plants. Our aim was to examine the influence of ATS-amended fertilizers on fate of N and S in the plant-soil system and on the quality of oilseed rape (due to S-uptake and N-regulatory effect). This plant was chosen because of its high demand of S.

Methods A double O spring rape was used in a pot experiment in growth chamber. A calcareous soil (rendzina) was selected; this soil was collected from the Ap horizon (0-20 cm), air-dried, sieved (2 mm) and fertilized at a rate of 200 kg N ha-1 applied as ammonium nitrate (AN),urea and cattle slurry, and 75 kg S ha-1 as ATS (283 kg ATS ha1). The experiment consisted of 7 treatments (AN+ATS, urea+ATS, slurry+ATS, AN, urea, slurry and control) with 5 replicates per treatment. The growth conditions were : 14 h day at 16°C and 10 h night at 12°C from sowing to flowering, 16 h day at 21°C and 8 h night at 16°C from flowering to maturity, 250 |0,mol nr2 s_1 light intensity and 70% air humidity. The pots were sampled at "rosette" stage (one month after cultivation), at flowering and at seed maturity. The plants were separated from the soil. For soil + samples, the inorganic N (NH4 , N03) was determined with 1M KCl extraction by distillation, 2 and the inorganic S (S04 -) with 0,01 M CaCl2 by turbidimetric method. The plants were separated into leaves, stems, roots, pods and seed; after determination of the fresh and the dry matter, the different plant parts were ground and analysed by auto-analyser NA 1500 for total N and S content.

Results The ATS reduced significantly the amount of nitrate in soil by 50% one month after application (Table 1); these results confirmed the significant effect of ATS as an inhibitor of nitrification. Similarly, we observed a decrease of total inorganic N content (Table 1) in the soil treated with AN+ATS, urea+ATS and slurry+ATS (-4.9, -8.2 and -8.3 mg N kg"1 soil respectively); this indicates that ATS had also a high efficiency with slurry, and that N would be immobilized in the soil after ATS application.

Table 1- NQ3-N, NH4-N and total inorganic N in soil (mg N kg'1 soil) at "rosette" stage Treatments AN+ATS AN Urea+ATS Urea Control Slurrv+ATS Slurry Control SI N03-N 3.77 b 8.51 a 4.09 b 9.04 a 7.68 ab 39.00 b 47,28 ab 56,31 a NH4-N 4.03 b 4.23 b 3.89 b 7.15 ab 9.83 a 8.95 b 14,81 a 13,74 a Total inorganic N 7.80 c 12.74 ab 7.98 be 16.19 a 17.51 a 47.95 b 62,09 ab 70,05 a The results are given as means. Different letters within the same row (horizontal) indicate that values are significantly different at p=().05accordin g lo Tukcy test Session 2.3 547

An excessive N/S ratio enhanced vegetative growth and suppressed pods and seed production due probably to an excessive N assimilation and an accumulation of toxic N metabolites (Janzen et al, 1984) :n o seed was obtained with AN and urea treatments. The total N exported by the plants at maturity increased significantly when ATS was applied (Figure 1); the higher effect with urea than with AN could be probably due to a double action of ATS on urease activity and on nitrification. The total N content in aerial parts at different stages of growth showed a transfer of N from vegetative parts to seed at maturity (data not shown). Used as a source of S, the ATS contributed, via a rapid oxidation to sulphates in the soil, to increase significantly the total S exported by the plants (Figure 1).Wit h slurry the S content was higher than with other fertilizers.

Figure 1- Total N and S exported by the plants at maturity (mg N plant"1 and mg S plant"1) a Control UAN „ 80- b AN AN+ATS I 60 U o, U+ATS 40 Control SI 20 SI Sl+ATS 0 1stexperimen t 2ndexperiment . 1stexperimen t 2ndexperimen t Different letterswithi na nexperimen t indicatetha tvalue sar esignificantl y different atp=0,0 5accordin gt o Tukey test

The results show an improvement of seed yield when ATS was added to fertilizers (Table 2), and the seed yield is maximum with slurry, corresponding to maximum N and S exported by the plant. In accordance to Zhao et al (1993), N and S addition increased seed yield and oil content with AN and urea, increased seed yield but also glucosinolates (GLS) content with slurry, and decreased oil content with slurry; this resulted from the important elevation of alkenyl GLS found with slurry+ATS (data not shown). The alkenyl GLS is derived from methionine and S present in pods contributes significantly to seed metabolites synthesis (Fieldsen et al, 1994).

Table 2 - Seed yield, oil and glucosinolates (umol g"1 of dry seed) contents Treatments AN+ATS Urea+ATS Control Slurry+ATS Slurry Control SI Seedyiel d (gpof' ) 1.01 a 1,29 a 0.67b 1,37 a 1,16a 0,80 b Oilconten t( %o f DM) 45.95 47.40 43.00 40.70 42,30 42.90 GLS content 8.2 8.5 7.9 13,5 8.9 8.9

Conclusions ATS reduced significantly the amount of nitrate in soil, but this retarding effect was observed only within a short period of about one month during which nitrogen seems to be predominantly immobilized in the soil. The application of N and S in a balanced proportion is important for plants development and seed production :th e level of GLS is mostly conditioned by the S metabolized within the period of pods development. Further investigations of soil organic N, and determination of the optimum ATS rate and the optimum N/S ratio are needed to confirm ATS efficiency on oilseed rape.

References Fieldsen, J. et al., 1994. Annals of Applied Biology 124 : 531-542 Goos, R.J., 1985. Journal of Fertilizer Issues, Vol. 2, Number 2 : 38-41 Janzen, H.H. et al., 1984. Soil Sciences Society American Journal 48 : 100-112 Zhao, F. et al., 1993. Journal Science Food Agriculture 63 : 29-37 548 Book of Abstracts 4th ESA-congress

WATER ANDNITROGE N BUDGET OFSPRIN G BARLEY FIELD

E. Fotyma, M. Fotyma

Institute of Soil Science andPlan t Cultivation, Osada Palacowa IUNG, 24-100 Pulawy, Poland

Introduction Spring barley isth ethird , after winter wheat andrye , most widespread cereal crop inPoland . The barley yields are muchlowe r though duet o often occuring spring droughts and poorer ability to transform nitrogen into grain biomass.A si nparale lwor k concerningwinte rwhea t (Fotym a M. et al, 1996)th e aim ofthi s onewa st o estimateth eproductiv e water consumption and thenitroge n uptakeb y springbarle y grown ontypica lsoi li nPolan d andfertilize d with different doseso f nitrogen.

Methods Springbarle y was grown inth eyear s 1993 - 1995i n four course crop rotation rape -winte r wheat- sugar beet (o nFY M )- sprin gbarle y fertilized withnitroge n inth e doses 0, 20, 40,60 , 80an d 100k gN ha" 1. Soilcharacteristi c ,th e extent offiel d measurements andth e methodso f dateprocessin g werepresente d inth epape r concerning winter wheat (Fotym a M. et al., 1996).

Results The most favourable water conditionswer erecorde d in 1993( Figur e 1 ).

13S US 1«2 1H 1*9 171 1» 117 194 202 2» lit 1» 144 1(2 1» 1W 172 190 IS« 192 200 207 214

Julian day* Julian day*

lETp -water - water depletion depletion

14« ISS 1S4 171 17« 191 191 209 213 Figure 1.Depletio n of available water by Julianday * springbarle y from the layer 0- 60c m Session 2.3 549

In 1993th e soilwate r depletion exceeded the depletionlimi t inMi d July only. The lowest yield of barley grain (Table )wa srecorde d in 1995whic h canb e explained by water deficit occuring already inMi d June. The daily actualévapotranspiratio nrat e ofsprin gbarle y was 3.8 mm/day in May, 5.0 mm/day inJun e and3. 3 mm/day inJul y independently onth enitroge n doses. Actual évapotranspiration washighe r from thepotentia l oneb y 10- 4 0 %i nMa y and June and lowerb y 15- 35 %i nJuly . Theproductiv e water consumption depends strongly onnitroge n doses (Table ) and generally exceeded thevalue sfoun d for winterwheat . Therelatio n between spring barley grainyield , nitrogen uptake andfertilizer s dosesi spresente d onFigur e 2 asa thre e quadrant diagram. The diagram contains allmos timportan tparameter s ofnitroge n efficiency and utilization includingth euni t uptake ofthi s elementpe r 100k go fbarle y grain (right , lower quadrant ). This unituptak e isshow n in Table aswel l for grainyiel d the sake of good confrontation withth e datefo r winter wheat (Fotym a M. et al., 1996) . Theuni t uptake ofnitroge n increased withincreasin g doses of fertilizers butwa s generally lower than the uptake by winter wheat.

N rate N uptake kg/ha kg/ba 100 80 60 40 20 0 120 140

•ffidtncv rat« utiJJzalion aoronom, chvslotoo, 41.4 60.4 93.1 40-20 32 3 44.1 73.2 90-40 22.7 35.B »3.4 60-90 13.1 24.5 53.4 1»*«. 3.5 7,«., 44.3 Figure 2. Thethre e quadrant diagram of

N r nitrogen efficiency for springbarely . kg/bi

Table. Water andnitroge n efficiency insprin gbarle y cultivation Characteristic dose ofnitroge n fertilizers kgN ha' 1 0 20 40 60 80 100 grainyiel dt/h a 3.62 4.46 5.10 5.56 5.82 5.89 field water consumption May - Julymm/10 0 kg ofgrai n 8.79 7.08 6.09 5.72 5.46 5.27 uptake ofnitroge n kgN/10 0k g ofgrai n( + straw) 1.95 1.96 2.00 2.06 2.16 2.28

Conclusions Springbarle y showshighe rwate r demandsi nvegetatio n season andlowe r nitrogen utilization capacity thanwinte r wheat. Thehighes tyiel di si nth erang e of 0.75 ofwinte r wheatyield . For achievingthi syiel dth ewate r supply ofabou t 300m mi nMa y -Jul y andnitroge n supply of 130 kgN ha" 1fro m the soil andfertilizer s isa must .

References Fotyma M. et al., 1996.Boo k ofAbstract s4t hES A Congress Veldhaven the Netherlands 550 Booko fAbstract s4t hESA-congres s

WATER AND NITROGEN BUDGET OFWINTE R WHEAT FIELD

M.Fotyma , E. Fotyma

Institute of SoilScienc e andPlan t Cultivation, Osada Palacowa IUNG, 24-100 Pulawy, Poland

Introduction Theproductivit y ofwinte r wheat dependsmainl y onwate r supply from soilreserve s andfrom rainfall invegetatio nperio d aswel la so nnitroge n supply from soil and fertilizers. The relation of actual to potential yield isproportiona lt oth erelatio n of actualt o potential évapotranspiration (Sarnacka,1983) andt o thenitroge nnutritio n status of crop. Therei sa close correlation between water andnitroge n supplybecaus eth e efficiency of thesefactor s dependsver y much on each other. The aim ofth ewor k wast o estimateth eproductiv e water consumption andth enitroge n uptakeb y winterwhea t grown ontypica l soili nPolan d and fertilized with different doses of nitrogen.

Methods Thewate r andnitroge n budgetwa scalculate d for thewinte r wheatgrow n in 1993 - 1995i n field experiment on sandy loamunderline d from 50 cmb y loam .I nth euppe r layersfield wate r capacity was23. 8 %van dwiltin gpoin t 6.4 %v.Th e figures for deeper layer were 33.0 and 13.3 %v.respectively . In afactoria l experiment nitrogen fertilizers were applied inth e doses 0, 25,50 , 75, 100an d 125k gN/ha . Fromth ebeginnin g ofMa yunti lth eharves t the content ofwate r was measured inth e soilprofil e 0-10 0 cmi nweekl y intervalsb y means ofneutro n probe provided with dateprocessor . Potentialévapotranspiratio nwa scalculate d accordingt o Górski's( 1995) equation. Theresult swer epresente d infor m ofisopleth s andth ewate r depletion diagrams. The depletion of soil availablewate r was compared to so called water depletion limit eg. the value which doesno t influence negatively the crop yield. Therelatio n between winter wheat grainyield , nitrogen uptake and fertilizer doseswa spresente d infor m offou r quadrants diagram ( Fotyma E. et al, 1995 ). From thisdiagra mth euptak e ofnitroge npe r 100k g of grainwit h corresponding yield of strawwa s calculated.

Results Thecours e ofth e isopleths showedtha t the depletion ofsoi lmoistur e by winter wheat waslimite d to the soillaye r 0- 60 cm .Consequentl y by constructing the moisture exhaustion diagramsthi s soillaye r was recognized only (Figur e ). The daily actual évapotranspirationrat e ofwinte r wheat canopy wasindependen t onth e doses of nitrogenfertilizer s andth e mean values for the years 1993- 1995 equaled to 4.0mm/da y inMay , 4.5 mm/day inJun e and 3.0 mm/day inJuly . Thisindependenc y onnitroge n doses canb e explained byhypothesi stha tth e sum of evaporation andtranspiratio n isconstan t no matterho w dense the crop canopy is. InMa y and June actual évapotranspirationrat ewa si nth erang e 0.9 -1.3 ofpotentia l one calculated accordingt o Górski. InJul yth erati o ofactua lan dpotentia levapotranspirati o was0. 7 only. Theproductiv e water consumption per 100k g ofwinte rwhea t grain depends significantly onth enitroge n doses(Table) . Inth etreatmen t withmaxima lnitroge n dose( 125k gN /ha )winte rwhea t consumed 60 %o fth e wateruse d for production of 100k ggrai ni nth e controltreatment . In allfertilize r treatmentsi n comparison to thetreatmen t with 125k gN/h awinte rwhea t wasundernourishe d inrespec t to nitrogen. Inth e controltreatmen tnitroge nnutritio n index (Lemaire et al., 1989 )wa s only 0.6 which meanstha t the actualnitroge n concentration was4 0 %les sthe nth e critical one. Theuptak e ofnitroge n increased with increasing doses ofminera lfertilizers . Newertheless even inth e treatment withth ehighes t dose ofnitroge n theuni tuptak e ofthi s element was only 2.4 kg N/100 kgo fgrain . Session2. 3 551

124 131 138 145 151 1» 1M 171 112 1S7 1M 202 201 Julian days

• ETp -water - water • ETp -water - water depletion depletion depletion depletion limit limit

US 138 144 ie: 1» 1M 1TZ 177 HC 102 200 207 Julianday s -water -water Figure.Depletio n ofavailabl ewate rb y depletion depletion limit winterwhea t from thelaye r 0 - 60c m

Table.Wate r andnitroge n efficiency inwinte rwhea t cultivation Characteristic dose of nitrogen fertilizers H Nha"1 0 25 50 75 100 125 grain yield t ha"1 4.49 5.45 6.27 6.95 7.49 7.88 field water consumption May-July mm/100 kg of 6.81 5.58 4.72 4.59 4.17 4.04 gram uptake of nitrogen kg N/100kgofgrain( + 1.9 2.0 2.1 2.2 2.3 2.4 straw )

Conclusions InMa y and Juneth e actual évapotranspirationrat e ofwinte r wheat canopy issomewha t higher than thepotentia lévapotranspiratio n( accordingt o Górski)an d the depletion of availablesoi l water beyond thelimi ti softe n arestrictiv e factor of cropyield . The actual évapotranspirationi s independent onnitroge n doses appliedt o winterwhea t whileth ewate r consumption per 100k go f grain decreased with increasingnitroge n doses. The uptake ofnitroge npe r 100k g ofgrai n increasesproportionall y withfertilize r dosesbu t eveni nth etreatmen t with 125k gN/h a doesno t reachth eluxur y limit. Theprerequisite sfo r highyiel d iswate r supply inMay-Jul y over 300m m andth enitroge n supply of about 200 kgN ha" 1.

References Fotyma,E . et al., 1995.Fertilize r Research: 1-4 Górski,T. et al, 1995.Rocznik iA RPozna n 140:227-243 Leinaire, G., et aL 1992.Proc. 2end ESACongress:98-9 9 Sarnacka, S., 1983.Zeszyt y Problemowe Post. Nauk Rolniczych 277:219-226 552 Book of Abstracts 4th ESA-congress

HIGH-YIELD VARIETIES OF WINTER VETCH AND USE OF VARIETY-STRAIN TECHNOLOGY FOR THEIR GROWING

M. Galan,N.Lisov a

Research Institute of Agriculture and Cattle-Breeding ofWes t Region UAAS, Lviv-Obroshyn 292084, Ukraine

Introduction Thewinte r hairy vetch (Vicia villosa Roth) is the important source of protein and used for feeding ofth e animals. In the combined sowing of vetch with winter wheat, rye, barley, ryegrass, triticale for green feed has ensured the production of green mass up to 35.0- 45.0 t ha' . The inoculation of vetch with theRhizobium strains infield condition s increased significantly yield of the vetch -gramineou s mixture ,the total and digestible protein content. However, highest potential for increase ofth e vetch yields has the breeding of varieties and adaptive, complementative Rhizobiumstrains .

Methods The field experiments were conducted in 1991-1995 with winter hairy vetch on dark-grey soil at Experimental Station near Lviv. The mineral fertilizers were:N 20P60K60. The varieties of vetch, Shyrocolysta, Vusata, Fascialform, Tetraploidform, were created by the inducted (chemical) mutagenesis method from the winter hairy vetch variety Stavchanca (Galan, 1988). The seeds of vetch were inoculated with Rhizobium leguminosarum bv. vicae strains that were isolated from root nodules of the vetch varieties and forms (Kurchak et al., 1990). Fresh weight of the vetch-wheat mixture was measured at the blooming period. The experimental date havebee n statistically processed by dispersion analysis.

Results Results are presented inth e Table andFigure .

Yield ofgree n masso f the hairy vetch varieties Number Green mass,t ha"1 Dry Variety field vetch experi vetch- mass, ments wheat vetch tha-1 mixture pure Stavchanca 6 33.9 17.8 2.7 Shyrocolysta 8 44.4 21.3 3.3 Vusata 5 35.2 168 2.6 Fascialform 5 35.5 17.3 2.8 Tetraploidform 4 43.7 22.9 3.5

We have selected four mutant forms (varieties) of hairy vetch with altered stem and leaf phenotypes as well as tetraploid form. The plants of Vusata variety are characterised by total reduction of leaves to the tendrils during the flowering. This variety has a good productivity of green mass and seeds. Mutant plants with fascialitied and thickened stem Session 2.3 553 have an axial type of floscule position. They have also partial growth determination of the main stem and second order shoots. Such plants have very good productivity of the green mass. The tetraploid mutant is characterised by increased sizes of all organs and it has high potential of the fooder productivity. Plants of the variety Shyrocolysta have an enlarged leaf surface.

Green mass 10

610 622 1-11 1-32 1-42 4-31 R.leguminosarumstrain s

|Vusat a Q Tetraploidform Fascialform Shyrocolysta Stavchanca

Figure. TheRhizobium strai n specification of symbioses with winter hairy vetch varieties (gree n mass additiont o non-inoculated plants, t ha"1) .

Conclusions The multi-year investigations showed high potential of the yield capacity of novel winter hairy vetch varieties in soil-climatic conditions of West Ukraine. The efficiency of vetch -Rhizobium symbioses was determined to a marked degree by the variety and strain genotypes complementation. The inoculation of the vetch varieties with adaptive and complementative Rhizobium strains increased the yield of the vetch-wheat green mass mixturewit h 2.3 to 8.8t ha1.

References Galan, M., 1988. Selektia i Semenovodstvo6 :'32-35 . Kurchak, O.et al., 1990. Bull. VNIISCHM 53: 18-21. 554 Book of Abstracts 4th ESA-congress

EFFECT OF NITROGEN FERTILISATION ONLEA F PHOTOSYNTHESIS AND LIGHTABSORPTIO N IN TOBACCO

M. Guiducci, P.Benincasa , M. Migni

Istitute ofAgronomy , University of Perugia, BorgoX XGiugn o 74,0612 1Perugia , Italy

Introduction Cropbiomas sproductio n can beconsidere d asa direc t function of the product of the amounto f photosynthetically activeradiatio n absorbed (PARa) by acro p and the canopy radiation use 1 efficiency (RUE =mo l C02 mol PARa) (Monteith, 1977).Nitroge n (N) fertilisation can affect both PARa and RUE,mainl y asa consequenc e of itseffect s on canopy size and structure and on leaf photosynthetic activity (netC0 2 assimilation rate of leaf area unit) (Giménez et al, 1994; Sinclair and Horie, 1989).Thi s iso f particular interest in tobacco,wher ecro p productivity has to bejoine d to the quality of thecommercia l product, which depends, interalia, o nlea f content of N-compounds.A fiel d experiment wascarrie d outi n 1995i n central Italy in order to investigate in tobacco theeffec t of Nfertilisatio n onlea f Nconten t and photosynthesis ando n canopy light environment.

Methods In acompletel y randomized block design with4 replicates, 2treatment s werecompared : NO (no Nfertilization ) and N90 (90k g Nha 1 attransplanting) .Tobacc o (Virginia, cv K394) was transplanted on 23May , ata densit y of 2plant s nr2. Allo f thecomponent s of crop light balance were determined continuously throughout the dayb y using several quantum sensors, according toGuiducc i and Marroni (1992).Lea f area index (LAI) wasdetermine d destructively by harvesting allleave s from 4 plantspe r plot and measuring their area with alea f area meter. Leaf netassimilatio n vsphotosyntheticall y photon flux density relationship (Avs PFD ) was determined at around noon in several leavesfro m lower (L),mediu m (M) and upper (U) layers of thecanopy , byusin g aportabl e gasexchang e device (ADC-LCA3). The Nconten t of the abovementione d leaveswa s then determined destructively bya Kjeldha l method. Measurements wereperforme d during 4consecutiv e days (from 31Jul y to 3August )jus t before topping.

Results Daily PAR absorption (Table 1;Fig . 1)wa s higher inN9 0tha n inN O (+19%),mainl y asa consequence of higher LAI values of the former (+46%). On the other hand, NO showed ahighe r portion of LAI directlyli tb ysunbea m (LAIs/LAI) and, therefore, amor e uniform distributiono f light inside the canopy, which generally involves positive effects oncro p photosynthesis (Hay andWalker , 1989;Guiducc i and 2000 Benincasa, 1995). 2 Specific leaf Nconten t (SLN, gN nr of leaf) was affected by 1500 - Nfertilisatio n and leaf position. SLN of L,M an d Uleave s was (±s.e.) i n order 1.22 (± 0.11), 1.41 (±0.03 ) and 1.53 (± 0.20) g nr2 in NO,an d 1.93 (+0.10) , 2.12 (± 0.12) and 2.40 1000 (± 0.09) g m-2i nN90 . ~ 500 Table 1. PARabsorptio n (PARa, % ofinciden t PAR), total(LAI ,m 2nr2)an dsunli t(LAIs/LAI )lea f areainde xi nN O andN90 . s.e. = standarderro r PARa LAI LAIs/LAI NO 75.3 2.74 0.493 Fig.1. Incident (—) and N90 89.7 4.00 0.334 absorbed PAR in NO (O) s.e. 2.62 0.09 0.034 andN9 0(• ) on2 August . Session 2.3 555

Nfertilisatio n and leaf position also affected the Avs PF D response curve (Fig. 2),especiall y in terms of assimilation at saturating irradiance levels(Amax) . Within each leaf position,Ama x values were always higher inN9 0 than inNO .I n both treatments, L leaves showed the lowest valueso f Amaxi ncompariso n to M andU leaves. A smaller effect was observed on apparent quantum efficiency (O) and dark respiration rate (R) (data notshown) . Only in NO a 1000 2000 0 1000 2000 remarkably higher <ï>valu e ofU incident PFD (pmolPhoton s mV) leaves (0.031± 0.0039 ) was Fig.2 .A vs PF Drelationship s inleave so fth euppe r (•) recorded with respect to M andL medium (O) and lower (•) canopy layer of treatments leaves (0.020± 0.0059 on NO (left) andN9 0 (right). average). Amaxwa s clearly linked to SLN.Th e asymptotic relationship between leaf Amaxan d SLN (plotted 25 - 0 over all treatments and leaf positions) showed agoo d fit in alogisti c model, similar to thatindicate d for 20 - A 0 other C3crop s (Fig. 3) (Sinclair and Horie, 1989; Connor et al.,1993) . 15 °7 On thecontrary , no relationship was observed between and SLN and between R and SLN, 10 - / ° although possible linkages could have been partly /0y =25 -Y.-^fr-"D-1 masked by the acclimation of U,M andL leave st o 5 - Q different levels of PAR. 1 1 1 1.0 1.5 2.0 2.5 Conclusions SLN (g m') Nfertilisatio n increased both crop PAR absorption Fig. 3.Logisti crelationshi pbetwee n leaf Amax and SLN plotted over all and photosynthesis of sunlit leaves,bu tinvolve d a treatments and leaf positions. decrease of theLAIs/LA Iratio . Leaf Amaxwa s Equationi nfigure (R^O.866) . strictly related to SLN, which increased withN fertilisation and leaf position. Further experiments are needed, after this preliminary result, to accurately investigate theeffect s of Nfertilisatio n on thecondition s affecting leaf and crop photosynthesis of tobacco, in order to model crop yield performance.

References Connor, D.J., et al, 1993.Australia n Journal of Plant Physiology 20: 251-263. Hay,K.M . andWalker ,AJ. , 1989. Introductiont oth ephysiolog yo fcro pyield .Longman ,UK , pp. 292. Giménez, C, et al, 1994.Fiel d CropsResearch , 38: 15-27. Guiducci, M., and Benincasa, P., 1995.In :P .Mathi s (ed.).Photosynthesis , from light to biosphere. Kluwer Academic,Th e Netherlands,Vol .IV ,613-616 . Guiducci, M., and Marroni,M.G. , 1992.Rivist a diAgronomia ,26, 4 suppl,616-622 . Monteith, J.L., 1977.Philosophica l Transactions of the Royal Soc. of London B281: 277-294. Sinclair, T.R., and Horie,T. , 1989.Cro p Science, 29: 90-98. 556 Book of Abstracts 4th ESA-congress

VARIETY SPECIFIC WEED TOLERANCE -A KE Y TONO N CHEMICAL WEED CONTROL

M. Jolânkai1, Z. Szentpétery^, T. Szalai^

1Hungaria n Academy of Sciences,Nâdo rutc a 7., 1051Budapest , Hungary 2 GödöllöUniversit y ofAgricultura l Sciences

Introduction Varieties offield crop sbelongin g to different genotypes show different responses to weed populations (Cox and Jackson, 1949). Apart of extremities concerning weed canopy, there isa dynamic, naturallybalance d coenosysincludin g weeds andth e crop produced in alfields.l Weed s reduce cropyield ssinc ethe y compete with cropsfo r essential sources oflif e (Jolânkai, 1995). There arethre e major factors influencing the competition betweenfield crop s andwee d populations: water utilization, nutrient uptake andth evegetativ e growth dynamics. The latter can be considered asa mai n characteristic ofa coenosys, since any component ofthat which mayhav e a different chance for growth willdominat e and soobstruc t both physically and physiologically its neighbouring plants (Sprague, 1959,Maas , 1970).Apar t ofthes ether e isa wid erang e of other factors wich mayinfluenc e alterations ofa coenosys (eg. diseases, epdemicsan d gradations etc), howeverthes e aremor eoccasional . Withinfield cro p speciesther e are significant varietal differences inwee d tolerance (Ubrizsy, 1962,Jolânka i et al., 1992, 1995). In our research winter wheat varietieswer e examined under various agronomic conditions to determine weed tolerance characteristics.

Methods In athre e year herbicide provocationfield tria l atNagygombos , Hungary (1993-1995), sixwhea t varieties representing different genotypes wereteste d under exposed and protected conditions on smallplot swit h four replicates. Threetype s ofherbicid e treatments (fluroxipir, bromoxinyl and dicamba ai.)wer e applied in comparison withuntreate d "weedy" and hand picked "weed proof' controls. Weed populations weresorte d intotw o major groups accordingt o the level ofthei r occurence. Themos tfrequen t weed species areliste d inth etable .

Table 1. Major weed species observed on experimental plots

High occurencewee d species Low occurencewee d species

Bilderdykia convolvulus Fumaria officinalis Capsella bursa-pastoris Viola arvensis Stachys annua Chenopodium album Matricaria inodora Adonis aestivalis Conium maculatum Sinapis alba Lathyrustuberosu s Lamium amplexicaule Stellaria media Sonchus arvensis Thlaspi arvense Lactuca spp. Galium aparine Cannabis sativa Papaver rhoeas Convolvulus arvensis

Plant growth, yield components and grain yield of each experimental treatment were evaluated and weed tolerance ofvarietie swa s determined. Session 2.3 557

Results and conclusions Themagnitud e ofwee d populations has shown significant differences. Allwee d control treatments including chemical and mechanical applications had aninfluenc e inwee d development. Herbicide treatments had aboutfifty pe r cent, whilemechanica l applications had anearl y hundred per cent effect concerning weed reduction. Thelatte r canb e considered asa leve l oftota l weed extinction. High weed canopieswer e observed inth e case ofuntreate d controls only (Table2) .

Table 2. Effect oftreatment s onth enumbe r ofweed spe r plot

before after treatment treatment untreated control 6.8 6.0 weedproof control 6.5 0.1 herbicide applications 6.7 3.3

Yieldfigures wer e affected byth e experimental treatments. Yield reduction ofwhea t varietiesi n high weed canopieswa s calculated relativet o yieldfigures o fhandpicke d weedproof controls. Wheat cultivarshav e shown avariet y specific yieldresponse . Figure 1.show sth e magnitude of yield lossesinduce d byhig hwee d canopies.

Mv18 Mv19 Mv21 Mv22 Mv23 Fatima

Figure 1. Yield reduction ofwhea t varietiesi nhig hwee d canopies

Theresult s obtained suggest varietal differences concerning weed tolerance. The extent ofyiel d lossesbetwee n varieties had arang efrom on et o four fold which issimila r to the results ofMaa s (1970). According to the study Martonvasari 19an dMartonvasar i2 1whea t varietieswer e proved to haveth ebes twee dtoleranc eabilities .

References Cox, J.F.and Jackson, L.E. 1949. Crop management and soilconservation.Joh nWile y& Sons, New York. Jolânkai, M.andLövei , I. 1992.Büzafajta k herbicidérzékenysége. Növényvédelmi Forum, Keszthely, 20p . Jolânkai, M. et al., 1995. Sustainability in agricultural development, 41st EAAE Seminar,Gödöllö, Proc. 27-30 pp. Jolânkai, M. 1995.Cro p production. Printorg Publishers, 70-75pp . Maas, G. 1970.Übe r dieEinflu ß von Herbiziden aufdi e Standfestigkeit von Getreide. Zeitschrift für Pflanzenkrankheit. Sonderdruck 5. Sprague,H.B . 1959.Grasslands . American Association for the Advancement of Science, Washington D.C. Ubrizsy, G. 1962.Vegyszere s gyomirtâs.Mezögazdasag iKiadó , Budapest. 558 Book of Abstracts 4th ESA-congress

SOILTILLAG E AS AN IMPORTANT MEASURE INWEE D CONTROL FOR WINTER WHEAT ( TRITICVMAESTWUML. )

M. Knezevic, I. Zugec, I. Juric, M. Burkic

Faculty ofAgriculture , P.O.Bo x 117,3100 0 Osijek, Croatia

Introduction Weed controli sth emai n reason for soiltillage .Reduce d tillage orno-tillag ebring sabou t major changesi nwee d communitiesb y influencing species composition, relativeimportanc e of individual species,an drate so fpopulatio n growth (Weston, 1990; Coffinan et al., 1992).Wee d communitiestha t evolve as resultso f adaption of suchpractice snee dno t to be more difficult to controltha nthos ewit h conventionaltillag e(Swanto n et al., 1991). In addition to herbicides, some tillagedegree sar erequire dfo r weed controli nwhea t (Miller et al., 1985;Hum e et al., 1991).Th e objective ofthi swor k wast o identify tillage systems asa culturalmethod , which could provide opportunitiest o reduceherbicid eusag e onwinte r wheat.

Methods Fieldtrial swer e conducted onhumogle y soiltyp ei nEaster n Croatia duringtw owinte r wheat seasons, 1993-94 and 1994-95.Whea t wasplante d after soybeani nbot h years.Fiv e soiltillag e systemswer etested : 1.conventiona ltillag e (ploughing, disk-harrowing)-CT; 2. disk-harrowing - DH; 3.tillag eb y amultitille r with chisel- MT ; 4.n oploughing , seedbed preparation + sowingb y arotose m -R, and 5.ploughing ,seedbe d preparation + sowingb y arotose m -P K Floristical observations of eachplo twer e madei nApril ,Ma y and June on 1440m 2(24 0m x 6m) . Theplot s hadneithe r beentreate d byherbicides ,no r fertilized. Weedplant s and air drywee d biomasswer e counted andmeasure d from 0.25 m2plot si n 20replications ,respectively . Grain yields ofwhea t were determined byhan dharvestin g samples(0.2 5 m2, 20 samplespe r tillagetreatment ) thatwer e collected shortlybefor e thefinal harvest . Alldat a were subjected to analysis ofvariance . Rainfall and airtemperature s duringth e growing seasons(October-July ) were 638m m and 9.6°C in1993 - 94, and 656m m and 11.4°C in 1994-95.Bot h growth seasonswer e extremely unfavourable for wheatproduction . Theseaso n of 1993-94wa scharacterize d by along , cold andwe t autumn, whereasth eperio dfrom th eheadin gt o thematurit y stage,Ma y and June,wa s extremely dryan d warm. Onth e otherhand , thewhol e season of 1994-95 wasrathe r wet and cold.

Results Weednumbe r andwee d biomasswer e significantly (P<0.01) influenced by season (Table).Mea n weedbiomas swa s71 2k gha" 1an d 106k gha" 1 in 1994 and 1995,respectively . Themai n species were annualbroad-leave d weedsi nbot h years:Anagallis arvensis (scarletpimpernel) , Ambrosia artemisiifolia (common ragweed), Chenopodium album(lamb' s quartersgoosfoot) , Fallopia convolvulus (dull-seed cornbind), Galium aparine (catchweed), Papaverrhoeas (commo n poppy),Polygonum persicaria (spotted lady'sthumb) , Thlaspi alliaceum( garli cpennycress ) and Violaarvensis (fiel d violet). Weedbiomas sunde r DHtillag ewa s significantly higher (P<0.01)i n both years, compared to other systemswit hth e exception ofM Ti n 1995. TheM T treatment producedhighe r weedbiomas stha n R (P<0.01 ) aswel la sC T andP R (P<0.05 ) treatmentsi n 1995.Th elowes twee dnumbe rwa sunde r Rtillag esyste mwit h significant differences (P<0.01) compared to othertreatment s inbot h years. Onth e otherhand ,value s ofwee dbiomas si nR treatment were significantly lower (P<0.01)onl yi nrelatio nt o DHtillag e inbot h years, aswel l Session 2.3 559 aswit hrespec tt o MT tillagei n 1995. The described differences between othertillag etreatment s wereno t significant. Under DHtillag e alarg enumbe r of Galium aparine, Anagallis arvensis and Violaarvensis was stimulated to emerge.Ambrosia artemisiifolia an dPolygonum persicaria populations showed atendenc y to increaseunde r PRtillag etreatment , which wasindicate db y theirhighe rplan t densities, compared to the othertreatments . Weedbiomas sdat a indicatetha ta relatively highnumbe r ofmentione d specieswa sno t competitivewit hth ewhea t crop.

Table. Weednumber , weedbiomas san dwhea t grainyiel d

Tillage Weednumbe r Weed biomass Grainyiel d treatment m"2 kg ha' kg ha' 1994 1995 1994 1995 1994 1995

CT 46.8 9.6 664 64 3.990 5.000 DH 70.6 9.8 980 176 3.480 4.310 MT 61.4 7.4 684 141 3.420 4.300 R 11.4 4.0 575 29 4.110 3.750 PR 48.0 11.6 652 80 4.190 4.780

SEM 3.5 1.2 8.1 23.2 248 19 LSD (0.05) 9.8 2.9 168 54.4 580 240 LSD (0.01) 13.0 4.2 211 81.7 770 350

Conclusions Preliminary results showedtha t differences inth e composition ofwee d community exist induced by varioustillag e systems. Onth ebasi s ofwee d levels,th efive tillag e systemscoul db eranke di n adecreasin g order asDH , MT,PR , CT and R, althoughth e differences wereno t always significant. Weed infestation levelswer e generally low,havin gn o greatinfluenc e onwhea tyields , whichwer e much more influenced byweathe r conditions.

References Coffman, C. B. et al., 1992.Agronom y Journal, 87: 17-21. Hume,L . et al., 1991.Canadia n Journal ofPlan t Science, 71: 783-789. Miller, S.D . et al., 1985.Nort h Dakota FarmResearc h Publication 43: 11-141, Experimental Station, Fargo,N D Swanton, C. I. et al., 1991. Weed Technology, 5: 657-663. Weston, L. A., 1990. Weed Science, 38: 166-171. 560 Book of Abstracts 4th ESA-congress

POSSIBILITIES OF USING MODULAR GROWTH ANDPLAN T HIERARCHICAL STRUCTURE TOEVALUAT E RESOURCE USEI N CEREAL GROWING

JanKfen

Agricultural Research Institute Kromëfiz, Ltd., Havlickova 2787, CZ-767 41 Kromëfiz, Czech Republic

Introduction White (1979, 1984)an d Porter (1983a,b )demonstrat e thatplant s can be studied as developing modular systems andthei r growth described analogically toprocesse s ofth epopulatio n type. Thus, anindividua l plant may be considered ascomprisin g cohorts ofmeristem s of different age and growth intensity. The other important feature that must be considered in morphological studies isth ehierarchica l structure with branching at various levels (Arber, 1941). The cohorts ofmodule s are designated asmetapopulation s (White, 1979).T oconside r the plants as systems hierarchical indesig n and built upi n a modularwa y simplifies thedescriptio n ofplan t form. Using this approach the knowledge ofplan t morphology, physiology and ecology canb e synthesized: 1)Dynamic s of formation and reduction of cerealyiel d components (shoots and grains) per unit areao fth e stand which isanalogica l to growth processes ofnatura l populations (Miyagawa, 1983;Kfen , 1985, 1987). 2)Highe r determination of growth and development of modular units in comparison with entire plants.Th egrowt h and development ofth eentir e plant consist ofa serieso fgrowt h and development stages ofmodule s some of which overlap each other (Malet, 1979). 3)Hierarchica l structure ofplant s and intraplant competitive relationships affecting aleve l of modular differentiation inplan t responses to environmental resources. Plants can be understood ascohort s of autonomous mutually competitive units (White, 1984). 4)A larg enumbe r of random effects which influence plant and module growthi n the stand (Knight, 1983). Weight distribution ofproductiv e stems or grains inmaturit y is,therefore , close tonorma l distribution (Kfen, 1985; Kfen et al., 1992). Incereals ,tiller s (shoots) and grains can beconsidere d asth emodule s which correspond toth e plant nature and practical purposes. The final size of stems isinfluence d by one hierarchical level.Th e final size ofth e grain isinfluence d by 2t o 5hierarchica l levels depending onth e inflorescence morphological structure.

Methods Singleproductiv e stemsan d grains inextensiv e sampleswer eweighe d (thenumbe r ofmeasure d units in samples ranged from 100t o 3,000). They weretake n among chosen variants of field experiments withwinte r wheat and oats covering differences in sowing date, seeding rate, nitrogen rate,an d agrobiological properties (adaptation) of varieties (Kfen, 1987;Kfe n etal. , 1992).Fo rthes e sets ofvalue s standard characteristics ofvariabilit y were calculated (mean, maximum andminimu m values,range ,variance ,standar d deviation, coefficient of variation, skewness and standard error of skewness). Separation ofth e variability in shoot and grain weight caused by intraplant competition from their entirevariabilit y inth e stand wasperforme d by testing significance of skewness.

Results There are interplant relationships inth e population. The distribution of seed or seedling weight is usually symmetric (skewness 013= 0) an d closet oth e normal distribution (seefigure) . Atth e end ofth e growth, theplan t weight distribution ischaracterize d by anL-shap e corresponding toa Session 2.3 561 apossitiv e value ofth e skewness (a3 > 0) asth eresul t of anexponentia l character of the growth (Koyama et al, 1956). In the metapopulation, the distribution ofmodul e weight is asymmetric (log-normal or exponential) atth e beginning ofthei r growth which isgive n by time sequences of modules (tiller or grain) formation. Atth e end ofth e growth, the distribution ofproductiv e stems and grains isclos et o the normal one.Th e weight of modules is influenced by both inter-an d intraplant competition. The intraplant competition among modules,whic h resulted from crop reactions toth e environment, modify thevariabilit y and the skewness ofthei r weight distribution. Apositiv e value of skewness (I) indicates unfavourable conditions.A zer o valueo f skewness (II) indicates prevailing random relationships inth e metapopulation, i.e. the intraplant competition does not occur, the variety is adapted to the conditions.A negativ e value of skewness (III) indicates favourable conditions when alsoth e later formed modules reach the similar weight (or size) asth e early formed ones.

Population of plants dying out surviving a, > 0

weight (size)

Metapopulation of modules (shoots or grains) a3>0 a3=0 a3<0 ,a,> 0 dying out ^^ surviving IA II X m '

weight (size) Growth beginning •Tim e Differentiation period •Tim e Growth end Conclusions Theanalysi s of variability in metapopulations of modules in cereal stands and separation of variability components caused by intraplant competition enablet o evaluate: - resource use (i.e.productio n factors ofth e location and inputs supplied by management practices), aswel l asth e influence of growth limiting factors, - utilization of variety biological potential.

References Arber, A., 1941. Biological Reviews 16: 81-103. Kira, T., 1953.Journa l of the Institute of Polytechnics, Osaka City University, D4: 1-16. Knight, R., 1983.Australia n Journal of Agricultural Research 34 (3):219-228 . Koyama, H. et al., 1956. J. of the Institute of Polytechnics, OsakaCit y University, D7:76-94 . Kren, J., 1985.Rostlinn â Vyroba 31(10) : 1045-1054. Kren, J., 1987.Universit y of Agriculture Brno,Th e Czech Republic, PhD Thesis, 134p . Kren,J . et al., 1992.Grai n growth in oats:experimentatio n and modelling, CABO-DLO report 165, 132 p. Malet, Ph., 1979.Annal s of Agronomy 30 (5):415-430 . Miyagawa, S., 1983.Bulleti n ofNationa l Institute of Agricultural Sciences, Ser.A , Yabete Ibaraki, Japan, 30: 1-30. Porter, J.R, 1983a.Ne w Phytologist 94: 183-190. Porter, J.R., 1983b.Ne w Phytologist 94: 191-200. White,J. , 1979.Annua l Review of Ecology and Systematics 10:109-145 . White,J. , 1984.Perspectiv e on plant population ecology, ed. Dirzo,R . and Sarukhân, J., Sinauer Associates INC.,Massachusetts , USA, 15-47. 562 Book of Abstracts 4th ESA-congress

COMPARISON OFECOLOGICA L AND CONVENTIONAL CROPPING PRACTICES OF CEREALS UNDER FERTILE CONDITIONS IN CENTRAL MORAVIA

JanKren

Agricultural Research Institute Kromënz, Ltd. Havlickova 2787, CZ-767 41Kromènz , Czech Republic

Introduction The aim ofth e research was to compare the conventional and ecological variants ofcerea l management practices infield experiment s whichwer e carried out inth e fertile sugar beet growing area. The management practiceswer e compared for: yield level, yield structure, variable costs, profit per hectare and perto n ofproduction , balance of energy.

Methods The analysed data havebee n obtainedfrom th efield experiment s ofth e Agricultural Research Institute Kromènz, Ltd. inth eyear s 1992-1995, except ofry e and triticalewhic h were grown in 1994an d 1995 only. The inputs in conventional variantswer e equalt o thoseuse d in practical cereal growing inth e sugar beet growing area. The inputs in ecological management practices corresponded to the IFOAMrules . The actual priceso fth e labour and theinput swer euse d for the economic analyses ofcerea l management practices. To compareth e conventional and the ecological crop management practicesth e variants(1- 5 for each crop) wereuse d which had the sameforecrop , variety, sowing date, sowing rate andth e way ofstan d establishment. The sizeo f harvesting plotswa s 8m 2 infou r replications. The seed for sowing ofth e ecological variantswa s not dressed with any protectant. Economic evaluation ofresult swa smad e on thebasi so fvariabl e costswhic h corresponded to the inputs in crop management practices conducted inth efield experiments . Since other variable costs (i.e.whic h were not measured) and especiallyfixed cost swer e not included inth e calculation, the comparison ofprofi t and profitability in conventional and ecological management practices was expressed in relative values (%). The energy consumption inth e crop management practiceswa s calculated according toth e method and equivalents ofenerg y inputsi n crop production used inth e Czech Republic (Preininger, 1987).

Results Table 1. The comparison ofgrai n yields achieved in conventional and ecological cereal crop management practices Conventional Ecological management practices- %o f Cereal crop management practices conventional variants grain yield (t.ha1) grain yield range Winter wheat 8.74 79.1 55.6-105.4 Rye(1994-9 5 only) 6.58 76.4 63.4- 91.7 Triticale (1994-95 only) 7.84 68.8 61.0-77.7 Winter barley 6.46 89.0 66.5 - 106.2 Spring barley 7.80 66.2 51.5-88.5 Oats 6.69 72.9 28.2- 116.0 The ecological crop management practices resulted inth e lower number of productive stemsan d grains per stand unit area and inlowe r grain yields. The lower stand density in ecological growing was connected with higher 1000-grain weight. On the contrary, inth e denser conventional variantsth e lower values of 1000-grain weight were observed. This phenomenon Session 2.3 563 can be explained asa resul t of larger branching on alllevel s of plant morphological structurei n conventional variants (higher number oftiller s per plant and grainspe rspike) . Table 2. The inputs of ecological management practices (conventional variants=10 0% ) Cereal crop Variablecost s per Energy consumption per hectare ton ofgrai n hectare ton ofgrai n Winter wheat 76.1 96.3 34.4 42.3 Rye 58.7 76.8 31.5 41.2 Triticale 56.6 82.3 33.8 49.1 Winterbarle y 76.6 86.1 32.1 36.1 Springbarle y 91.0 137.6 56.4 85.3 Oats 90.0 123.4 54.3 74.5 Table 3.Th e economic characteristics of ecological management practices (conventional variants= 100%) Cereal crop Profit per hectare Profit perto n ofgrai n Profitability Winter wheat 80.7 102.1 106.1 Rye 94.5 123.6 161.2 Triticale 81.2 118.1 142.9 Winter barley 112.0 125.8 146.3 Springbarle y 54.9 82.9 60.5 Oats 44.3 60.7 48.3

Conclusions a)I n ecological crop management practicesth e input variable costswer e reduced by 9- 43 % and theinput s of energy by4 6- 69% (Table 2). Thesevalue s ofenerg y inputs reduction resulted from restrictions inusin g chemical fertilizers and pesticidesi n ecological growing. Similar results were alsopresente d byAlföld i et al. (1994) and Abdulhamid (1994). b) The cereal crops differ in sensitivity to reduced inputsi n cropping practices (Table 1).Th e lowest response was observed inwinte r barley duet o itslowes t grain yield in conventional growing. By contrast, springbarle y and oats demonstrated thehighes t sensitivity. Generally, in ecological growing winter cereals achieved better resultstha n springcereals . c)I n winter cerealsth e ecological crop management practices resulted inth e higher profitability ofinpu t variable costs and inth e lower costs per ton ofproduce d grain (Table2 and 3). Onth e contrary, the higher profit per hectare was reached in conventional cropping practices (except winterbarley) . d) The energy output/input ratio in ecological variants was almost two times higher inwinte r cereals and 1-1.5 time higher in spring cerealstha n in conventional growing. e) There are some possibilities of economically effective cereal growing inth e Czech Republic using ecological crop management practices in small farms. Usingth e low-input practicesi n marginal areas, winter cereals canb e grown for production ofbioethano l orfo r above-ground biomass combustion.

References Abdulhamid, T.S .S. , 1994.Proceeding s ofth e 3rd Congress ofth eEuropea n Society for Agronomy, Padova University, 18.-22. September 1994, 648-649. Alfbldi, Th.et al., 1994.Proceeding s ofth e 3rd Congress ofth eEuropea n Society for Agronomy, Padova University, 18.-22. September 1994, 650-651. Jones, MR., 1989. Agricultural Systems 29:339-355 . Preininger, M., 1987.Energ y evaluation ofproductio n processesi n plant production, ISSM Praque, 29p . 564 Book of Abstracts 4th ESA-congress

EVALUATION OF ALTERNATIVE GRAIN CROPS IN SOUTH-WEST GERMANY: NITROGEN ECONOMY

M. Kruse and W. Aufhammer

Institute for Crop Production and Grassland Research, Hohenheim University, Fruwirthstraße 23, D - 70599 Stuttgart, Germany

Introduction Amaranth (Amaranthus spp.), quinoa {Chenopodium quinod) and buckwheat(Fagopyrum esculentum)ar e crops producing grains with high nutritional value. These crops are supposed to make lower demands on environmental factors than most of the well known crops (Espig, 1989). According to their specific demands on climatic conditions they differ in sowing dates and vegetation periods (Aufhammer et al., 1995) and subsequently in growing conditions and nitrogen (N) supply. Very little is known about N-uptake and use of accumulated N of these crops. Thus, the aim of the present study was to compare the N-uptake and the N-utilization of these three species grown for grain production. The well known cereal crop oat which needs a similar vegetation period and which produces grains of comparable nutritional value was included in the experiment as a standard of comparison.

Methods Field experiments were conducted in 1994 and 1995 at the experimental station Ihinger Hof (near Stuttgart in southwest Germany; mean temperature: 8°C; precipitation: 700 mm). They comprised the species amaranth, quinoa, buckwheat and oat. Two genotypes of each crop were cultivated on two levels of crop density and three levels of nitrogen fertilization. During 1 crop development N^-content of the soil in 0 - 0.9 m (kg N03-N ha ) and nitrogen uptake in above-ground parts of the plants (kg N ha' ) were recorded at five dates. Hand harvested and threshed grain yield (t ha1) and its nitrogen concentration (%) were measured at harvest. Furthermore the following parameters were calculated:

N-Harvestindex (NHI) = 100 x grain N~uPtak^ above ground N-uptake physiological N-efficiency (pNE) = 9ram yield above-ground N-uptake

N-fertilization-efficiency (NFS) = additional N-uptake caused by N-fertilization N-fertilization

N-yield-efficiency (NYE) = additional 9rain Vield caused by N-fertilization N-ferilization

Results Dates of field emergence and N^-values at these dates are given in the table. Field emergence problems of amaranth prevented the realization of the high crop density level of amaranth, cultivar K 343, in 1995. So results of amaranth are only presented for a low crop density level. From emergence to 4-6-leaf-stage N,,^-values under amaranth and quinoa crops raised to above 100 kg N ha' because of their very slow initial development combined with a low N-uptake during this period. This was not true for buckwheat and oat. Under these crops N^-levels decreased after emergence. Without N-fertilization amaranth exceeded the other Session 2.3 565

Table: Species mean values of parameters of nitrogen economy (means across of nitrogen- fertilization levels and crop density levels ). Species Oat Amaranth Quinoa Buckwheat

Date of field emergence 22.4.1994 26.5.1994 4.5.1994 30.5.1994 8.4.1995 8.6.1995 23.5.1995 18.5.1995

Nmin in soil at field emer­ 1994: 38 1994: 55 1994: 54 1994: 70 gence (kg N ha"1) 1995: 58 1995: 84 1995: 70 1995: 76

Hand-harvested grain yield 3.58 2.41 2.73 1.45 (t ha1) N-uptake (kg N ha ') 134.1 141.6 115.1 90.1 physiological N-efficiency 27.00 13.8 22.5 16.7 (kg grain kg N"1) N-Harvestindex (%) 59.8 35.5 48.4 36.2 N-fertilization-efficiency (%) 54.7 62.00 59.2 61.4 N-grain yield-efficiency 7.50 3.88 9.55 4.18 (kg grain kg N"1) crops in N-uptake until harvest (amaranth: 150; oat: 100; quinoa: 80; buckwheat: 70 kg N ha"1). The ranking of the species in N-uptake was not influenced by N-fertilization. During vegetation period significant differences between levels of N-fertilization in soil-N^ were obtained with all species except amaranth. They occured with quinoa only until heading, with buckwheat and oat almost during the whole vegetation period. The use of N accumu­ lated by the plants, described by pNE and NHI, was best with oat and worst with amaranth and buckwheat. N-fertilization significantly affected NFE of amarant only. With this crop it raised to 92.2% when an additional late dressing was given but was 34,7% with early dressing. The NFE of the other species tendentially decreased slightly with increasing N- fertilization. Quinoa had the highest value of NYE, amarant and buckwheat the lowest.

Conclusions Amaranth seems to have a higher capability to take up soil N and late dressed fertilizer N than oat. But its low values of pNE, NHI and NYE show a low utilization of the N taken up. The N-utilization was also low for buckwheat, but in contrast to amaranth the N-uptake of this crop seems to be quite limited. The N-uptake of quinoa was similar to oat, its translocation was between oat and the other crops. Breeding genotypes with a better transfer of dry matter and N to the grain can ressolve this disadvantage, and perhaps increase the relatively low grain yields. The use of N-fertilizer to increase grain yield of quinoa was more efficient than that of oat, showing that this crop may be more interesting for high-input than for low-input cropping systems. Problems of amaranth and quinoa with very high Nmin-values in June can perhaps be resolved by later fertilizer dressing and more uniform crops.

References Aufhammer, W. et al, 1995. Die Bodenkultur 46(2): 125-140 Espig, G., 1989. Entwicklung und ländl. Raum 6:6-9 566 Book of Abstracts 4th ESA-congress

PRODUCTIVITY OF HORSE BEAN IN RELATION TOTH E NITROGEN FERTILIZATION

B.Kulig, W.Ziolek

Department of Crop Production, Agricultural University, Al Mickiewicza 21, 31-120 Krakow, Poland

Introduction Nitrogen belongs to the components having the largest influence on plant yield. In leguminous crops the effectiveness of itsusag e depends on many factors, among them: N-mineral contenti n soil, chemical form offertilizers , rate, term and way ofusage , cultivars and theRhizobium strai n (Eaglesham et al., 1983;Koc h et al., 1984; Mytton et al., 1977). The urea foliar spray limited activity ofnitrogenas e to the lower degree (Kocoh, 1993) and causes the increase of seedyiel d (Day et al,1979 ; Kocoh, 1993). The research purpose was an investigation ofth e response to N-fertilization of cultivars differing in morphology.

Methods Infield experiment s made on degraded chernozem soil atth e Agricultural Experimental Station near Krakow (south Poland) the authors tested in the years 1993-1995 the response oftw o horse bean cultivars: Nadwislahski and Tibo to nitrogen fertilization: O, 20, 40 kg Nha" 1- applied pre- sowing and 40* kgN ha"1(2 0 kg pre-sowing + 10k gb yfolia r spray before plants start flowering + 10k gb yfolia r spray to the seed filling). The phosphorus and potassium fertilization in therate s 1 100k g P20, and 140 kg K20 ha" wa s applied before horse bean sowing. The agricultural measures were carried on according to the horse bean requirement. An estimation ofth e effect of the investigated factors was made on the base of seed yield and ofth eseparat e components of yield structure (the number of plantsbearin g seeds per unit ofarea , the number of seeds per plant, the mass of 1000seeds) .

Results

^

Figure 1.Hors e bean yield in dependence ofth e investigated factors Session 2.3 567

The average seed yield inth e conducted research was3.6 1t ha"1 .Examine d factors did not actually influence the seed yield however the Nadwislanski cultivarwit h undetermined growth rhythm had a 21% higher yield than the Tibo cultivar (self-determinate). The climatic conditions in different years had high influence on horse bean seed yield (Figure 1).I t resulted in interaction between years and cultivars aswel l asN-fertilization . Nitrogen fertilization caused ayiel d increase in 1995 only, whereas in the remaining years itsnegativ e influence on seed yield could be observed. In the conducted experiment the Nadwislanski cultivar was characterized (in comparison to Tibo cultivar) by4% increase inth e 1000see d mass, the number ofpod swa s 15% higher and the number ofplant s per m2wa sb y 15%> lower (Table 1).

Table l.The effect ofth e investigated factors on theyiel d structure components

Cultivars N treatment (k ;gN ha" ') Means Nadwi­ Features Tibo Control slanski 0 20 40 40* Mass of 1000seed s (g) 446 429 441 446 428 435 438 No. pods per plant 7.38 6.31 7.51 6.73 6.82 6.98 7.01 No. seeds perpo d 3.04 2.64 2.81 2.91 2.81 2.82 2.84

2 No. plantsm" 51.4 60.7 55.8 55.5 57.6 55.3 56.1

Conclusions In the conducted research the Nadwislanski cultivar showed ahighe ryiel d asa resul t ofth ehighe r mass of 1000seeds , number of pods and number ofseed si nth e pod. The seed yield depended on the climatic conditions inth e particular year of research. The interaction between yearsan d cultivars waswident,th e samewa stru e for years and N-fertilization. Nitrogen application on good soils before sowing aswel l aspartiall y before sowing, partially asfolia r spray, is insufficiently effective and can even cause yield reduction.

References DayJ.M . et al,1979 . Journal of Agricultural Science, Cambridge 93: 629-633. Eaglesham A.R.J.et al, 1983. Agronomy Journal 75:61-66 . Koch K. et al., 1984.Kali-Brief e 17(l):53-58. Kocoh A.,1993. Fragmenta Agronomica 4: 169-171. Mytton L.R.et al., 1977.Euphytic a 26: 785-791. 568 Book of Abstracts 4th ESA-congress

EFFECT OF SULPHUR NUTRITION ON THE ACTIVITY OF NITROGENASE AND ENZYMES OF THE C- AND N-METABOLISM OF VICIA FABA MINOR AND PISUM SATIVUM

A. Lange and H.W. Scherer

Institute of Agricultural Chemistry, University of Bonn, 53115 Bonn, Germany

Introduction Studies with different legumes have shown that the depression of the biological N2 fixation (BNF) under conditions of insufficient S supply is often correlated with a decrease in the formation of nodules as well as with lower N contents in the above grown plant parts. For this reason it may be assumed that N2 fixation is directly influenced by S deficiency. Therefore the objective of our experiments was to study the influence of S nutrition on the nitrogenase activity and the activity of different enzymes, involved in the C- and N-metabolism of nodules.

Methods In a pot experiment with the mixture of quartz sand and the top soil of a luvisol derived 1 1 from loess (2:1; 11 kg pot" ) two S rates (0 and 200 mg S as S04' pot" ) were applied to Viciaf aba minor and Pisum sativum. At two and three times, respectively, (for more information see figures) the nitrogenase activity was determined using the acetylene reduction (AR) method after separating the tops of the plants from the roots with the nodules and rinsing the roots with tapwater. The assay to determine the activity of different enzymes in the cytoplasm of the nodules (malate-dehydrogenase [MDH], PEP-carboxylase [PEP-C], glutamate-synthase [GOGAT]) was performed after extraction of the isolated nodules spectrophotometrically, monitoring the oxidation of NADH at 365 nm. Conditions for enzyme assays were described previously (Duke et al., 1975; 1976; Groat et al., 1984).

Results With both legumes the reduction of acetylene pot"1wa s significantly reduced under S deficiency conditions (Fig. 1). With Viciaf aba minor this decrease may be explained with the decrease of the specific nitrogenase activity (AR g'1 dry matter of nodules). With Pisum sativum the decrease was further caused by a reduced nodule formation. The results also demonstrate that with both legumes the activities of key enzymes of the C- and N-metabolism, based on g fresh weight of nodules, significantly decreased under S deficiency conditions (Fig. 2). However the influence of S nutrition on the activity of MDH and PEP-C was more pronounced as compared with GOGAT.

Conclusions Finally it is stated that with both grain legumes the activity of enzymes, concerning N2 fixation, is reduced in early stages of S deficiency, that means before S deficiency symptoms or yield reduction appears.

References Duke, S.H. et al., 1975. Physiologia Plantarum 34: 8-13. Duke, S.H. et al., 1976. Plant and Cell Physiology 17: 1037-1044 Groat, R.G. et al, 1984. Crop Science 24: 895-898 Session 2.3 569

•thylana In mg/pot — n--i Vicia faba Pisum sativum z 1 .s

-1

o.s

o othylsno In mç//a dry wt. nodules * n-1

Figure 1.Influenc e of Ssuppl y on nitrogenase activity of Vicia faba minor and Pisum sativum (means with the same letters are not significantly different)

U/g fresh wt. nodules U/g fresh wt. nodules ooo Viciafàbà : Pisùpi sativum :

• * *** ' " *^<^; MDH 100 rvtDH 100

10 10 : : : ; ; : I4-: : ; ;( ;**: : ; : : : PEP-C r . . . :-^~-^. PEP-C ** 1 : : ' - - - •'-—-Ï-^: GOGAT

— 0 mg S -1- 200 mg S 0,1 1 5 20 25 30 35 40 45 50 55 60 65 70 15 20 25 30 35 40 45 50 55 60 65 days after planting days after planting Figure 2. Influence of Ssuppl y on the activity of enzymes of the C- and N- metabolism (* LSD 5 %; " LSD 1% ; *" LSD0, 1% ) 570 Book of Abstracts 4th ESA-congress

OPTIMAL USE OF RESISTANCE FORA N INTEGRATED MANAGEMENT PROGRAM OF CEREAL NEMATODE POPULATIONS

F. Lasserre"3', B.Jouan 1,R . Rivoal2

1INRA, Service deRecherche s Intégrées enProduction s Végétales,2Laboratoir e deZoologie , BP 29 35650 LeRheu , France 3Presen t address: INRA, Laboratoire d'Agronomie-Environnement, ENSAIA, BP 172 54505 Vandoeuvre-les-Nancy, France

Introduction The aim ofthi s study wast o develop proposals for an integrated management programme to control nematode populations ina cerea l agro-ecosystem. Previous research hasbee n carried out to develop control means against the cyst cereal nematode,Heterodera avenae, a srotations , resistant varieties, weak hosts and nematicides (Rivoal &Cook , 1993).N o work had been ever made on integrated control ofth e cereal nematode community.

Methods The study was done ina lon g term experiment (1982-1993) located at Argentan (Orne, France) on soil infested byH. avenae, Ha l1 pathotype. Rotations weredesigne d to establishH. avenae densities above (rotation A) or below (rotation B)th e damagethreshol d (5 larvae/ g of soil),b y cropping respectivelyH. avenae susceptibl e cv.Peniart h (A) or resistant cv. Panema (B) oats at high frequency (70%) ina pai r of36 0 m2(6x60m ) stripsfo r 12consecutiv eyears . First, we studied population dynamicsof// , avenaean dPratylenchus neglectus, a secondary nematode species.H. avenaepost-cultur e densitieswer e assessed through samples often soil coreswhic h weretake n from each offou r equidistant 10m 2(2x5m ) areas, alongth e middleo f each strip inOctobe r of eachyea r after ploughing. Both nematode root densities were estimated at 2-node stage from two parallel 0.50 mrow s (0.20 m2) atfive point s 10m apar t along the middleo feac h strip.Nematod e extraction from roots and soili sdescribe d byRivoa l etal (1995). Secondly,fifty cyst sof// , avenaewer e collected ineac h rotation in October 1990 and 1992 for fungal parasitism assessment with Crump's method (Crump, 1987). Finally, possible selection ofa resistance-breakin g pathotype was checked inrotation s Aan dB . For this, soil samples were taken from 4 m2(2x2m ) areas, the center ofthes e areasbein g 5 m equidistant and the areasbeginnin g 7.5 mfro m the end of each strip. Each ofthes e 10 samples were divided inthre ePV C tubes sown with apregerminate d seed ofresistan t Panema. Activity of the nematode wasmonitore d byit sdevelopmen t on 3cv . Peniarth controls. Numbers ofwhit e females were assessed at the 1-2 node stage ofplan t growth after washing theroots .

Results Nematode population dynamics are presented inth e table andth e figure.

Heteroderaavenae an d Pratylenchusneglectus populatio n densities (nematodes per g ofroot )i n wheat Arminda at 2-node stage grown after susceptible (rotation A)o r resistant (rotation B)oats .

rotation 1991 1992 Pratylenchus neglectus A 129.6(38) a 565.3 (280.9) a B 407.0 (69.2) b 1594.2(601.2) b Heterodera avenae A 62.5(19.7) a 90.2(30.5) a B 0.3 (0.7) b 53.8(19.5) b Means per column (standard deviation) ofreplicate sfollowe d byth e same letter are not significantly different at P<0.05 byth eNewman-Keul stest . Session 2.3 571

Year 1982 83 84 85 86 87 88 89 90 91 92 93 Rotation A S S S R S : S S S S S S S Crop' oat wheat oat maize oat oat wheat oat oat wheat wheat oat Rotation B R S R R R R S R R S S S Heteroderaavenae populatio n dynamicsi nrotation s differing inth e frequency ofresistan t (R) and susceptible (S) cereal crops. Each point represents the mean of4- 5 replicates. Vertical bars show standard error ofth e mean.

Fungal parasitism of cysts, especially by Verticillium chlamydosporium, was much more prevalent inrotatio n A(32. 3 % in 1990, 25.5%i n 1992)tha n inrotatio n B (9.5%i n 1990, 4.1% in 1992). In pots of soil sampled from rotation Bfo r selection pressure study, aconsequen t number ofH. avenaewhit e females developed on resistant cv.Panem a (mean of6. 3 females per plant) whereas quite no female was found inrotatio n A(mea n of0. 2 per plant). Thenumbe r offemale s in rotation B varied with the position alongth e strip:maxima l numbers werefoun d at 22.5 and 27.5 m(respectivel y means of20. 0 and 10.3 females per plant) from the end ofth e strip.

Conclusions There were important consequences oflon gter m cropping with theH. avenae resistan t oat variety cv. Panema. Decrease of densitiesof// , avenae was associated with aproliferatio n ofP. neglectuswhic h could reach damaging levels.Extremel yrapi d re-establishments of//, avenae populations was observed on susceptible wheat grown for two years after the resistant oat. The incidence of endoparasitic fungi asV. chlamydosporium was also reduced, which played amai n role inpermittin g rapid re-infestation. Long term use ofth e resistance also led to the selection ofa resistance-breaking pathotype ofth e cyst nematode onPanema , localized speciallyi n one part of the strip. Allthes e phenomena showed that the longter m use ofhighl y effective resistance could provoke deep modification ofnematod e populations. Thisshoul d be taken into account when devisinga strategy for optimal use of resistance, with combinations ofpartia lresistances , rotations ofgene s and mixtures of isogenic lines and this contributed to abasi so f integrated management programs ofnematod e populations.

References Crump, D.H., 1987.Nematologic a 33:232-243 . Rivoal, R. and Cook R., 1993.Nematod e pests ofcereals .In. Evans K., Trugdill D.L.& Webster J.M. (eds), Plant parasitic nematodes intemperat e agriculture, CAB International, Wallingford, 259-303. Rivoal, R, et al., 1995.Nematologica , 41: 516-529. 572 Book of Abstracts 4th ESA-congress

USE OFASSOCIATIV E DIAZOTROPHS FOR NITROGEN NUTRITION OF GRAMINEOUS CROPS

LisovaN' , GalanM. 1,Patyk a V.2,Bezdushn y M.1,Pogoreck y A.'

'Institute of Agriculture and Cattle-Breeding UAAS, 292084 Lviv -Obroshyn , Ukraine 2Departament of SoilMikrobiology , Institute of Agriculture UAAS, 334080 Gvardejsky, Crimea, Ukraine

Introduction Nitrogen fixation associated with the roots of gramineous plantsha sbee nreporte d previouslyb y Dayan dDoberejne r(1976) .Extensiv e investigation during the last years hasshow ntha tinoculatio n ofcerea lcrop swit hdifferen t diazotrophsimprove d theplan tgrowt h andproductivit y inman ycase s ( Okon, 1985;Pacowsky , 1988;Belimo ve t al',1994 ;Lisov ae t al,1995) .Th epositiv ebenefit s from inoculationwit hdiazotroph shav ebee nattribute dt o severalmechanism ssuc ha sbiologica l nitrogen fixation and increased root uptake capacity because of enhanced root development and root hair formation in responce to production by bacteria of plant growth hormones (Harari et al., 1988; Zimmer and Bothe, 1988; Strzelczyket al.,1994).

Methods The sensibilityo fcerea l crops(winte rwheat , rye,maiz ean doat )t o inoculationwit hassociativ eN 2- fixing bacteria belonging to Azospirillum, Flavobacterium, Agrobacterium, Enterobacter was studied infield experiments . Allassociativ e diazotrophs werepositiv ei na nacetylen e reduction test (nitrogenfixatio n activity). Thetrial swer econducte d at the Stavchany Experimental Stationnea r Lvivo ndark-grey , podsolic soils.Fertilizatio nlevel swere :P^K^ , butfo r maize-P^K^.Th elevel s ofN 2-fixation inroo t zone ofplant s were measured by acetylene method. The yield of the green biomass was analysed: maize- in milk-wax ripeness period; oat - inflowerin g period.

Results Results arepresente d inTable s 1,2,3.Fo r rye (varietyBelta )th ehighes t grainyiel d was obtained withAzospirillum sp . inoculation ( 5,3 t ha1; without inoculation -4, 3 t ha1).

Table 1.Grai n yield andyiel d components ofwinte r wheat variety Kyjanka with diazotrophs inoculation

shoots gram grain 1000 grain Inoculation treatment number number mass, grain yield, perplan t perplan t g plant mass, g t ha-1 1withou t inoculation 3.8 117.5 6.1 47.6 4.3 2.Agrobacterium 3.9 110.2 6.9 48.6 4.5 3 Enterobacter 4.1 116.8 7.9 49.0 4.8 A Azospirillum 4.2 112.7 7.2 48.6 4.8 5.mixture2+3+ 4 4.6 113.0 7.7 49.0 4.8

LSD005 0.4 5.2 0.97 1.0 0.44 Session 2.3 573

Table 2. The influence of inoculation with'associativ e diazotrophs on biomass (dry matter) yield of maize (hybrid Juvilejny 70), in tons ha1.

Nitrogen rate(with without inoculation Agrobacterium sp. Flavobacterium sp. P90K90 ) 1994 1995 1994 1995 1994 1995 without fertilizers 8.7 7.9 8.7 8.6 8.7 9.0 0 8.8 7.8 8.7 9.3 9.5 9.5

N30 8.9 8.9 9.2 9.6 9.6 9.5 N60 9.5 9.7 9.7 10.4 10.3 10.3 10.3 9.8 10.3 10.8 11.0 11.0 NM

LSD„„5 0.41 0.51 0.22 0.37 0.22 0.37

Table 3. The effect of inoculation with Enterobacter sp. on grain yield of different oat varieties, 1992-1994. Inoculation Grain, t ha1, rate,cel l ml1 Lvivsky early Bug Ô 4~8 5~Ö 2-109 5.1 5.4 4-109 5.3 5.2 6-109 5_1 5_2

LSD005 0.29 0.29

Conclusions Under field conditions it was shown that the inoculation with associative diazotrophs of the cereal plantsincrease d the green mass yield and grain yield. Inwinte rwhea tinoculatio nwit h Enterobacter and Azospihllutn has the highest influence on grain yield. Our results show on important role of the associative diazotrophs in nitrogen nutrition of cereal crops growing in West Ukraine. Nearly 30% of the nitrogen may be taken in place of mineral nitrogen in nutriment of the maize because of inoculation with associative diazotrophs. The highest nitrogen fixation at roots zone of maize plants was found in the variant with inoculation Flavobacterium sp. (5-6 times as large as control). On the basis ofth e obtained results in trials with oat it can be concluded that it isth e cultivar sensibility to inoculation with Enterobacter, the variety Lvivsky early was more sensibility to inoculation.

References Belimov, A.et al.,1994.Mikrobiology 63:900-908. Day, I.M.,Doberejner, J,1976. Soil Biological Biochemistry. 8:45-50. Harari, A. et al., 1988. Plant and Soil 110:275-282. Lisova, N. et al.,1995.Fragment a Agronomica 2(46):116-117. Okon, Y.,1985.Trends in Biotechnology 3:223-228. Pacovsky, RS,1988. Plant and Soil 110:283-287. Strzelczyk, E.et al.,1994. Microbiological Research. 149:55-60. Zimmer W.,Bothe H. 1988. Plant and Soil 110:239-2477. 574 Book of Abstracts 4th ESA-congress

ESTIMATED RADIATION USE EFFICIENCY INALTERNATIV E CROPS UNDER TYPICAL MEDITERRANEAN CONDITIONS

N. Losavio,N . Lamascese, F. Serio, A.V. Vonella

Istituto Sperimentale Agronomico, Via C. Ulpiani 5, 70125 Bari, Italy

Introduction Crop biomass accumulation canb e described as afunctio n ofth e quantity of Photosynthetically Active Radiation (PAR) intercepted byth e canopy, that is,th e efficiency withwhic h the radiant energyi stransforme d into biomass (Gallagher et al., 1978). Somefunctiona l models usethi s approach to simulate crop biomass accumulation (Charles-Edwards et al., 1986). Thispape r examinesth e growth offou r alternative crops (part ofth e"PRisCA "Project , ofth e Italian Ministry ofAgricultural , Alimentary andFores t Resources) interm s ofradiatio n interception andth e efficiency ofutilizatio n of intercepted light (radiation use efficiency, RUE)i n drymatte r production.

Methods Field studieswer e conducted at Metaponto in Southern Italy (Lat 40°24 ' N, Long 16°48 'E ) duringth e 1993 season. Crops ofkena f{Hibiscus cannabinusL) , sweet sorghum {Sorghum bicolorL .Moench) ,grai n sorghum {Sorghum vulgare L.) andJerusale m artichoke {Helianthus tuberosusL. ) weregrow n on acla y loam soil (Typic Epiaquerts according to the Soil Taxonomy) on plots adequately irrigated (re-establishing the calculated évapotranspiration onth ebasi so f agrometeorological data) and with large amounts of fertilization. Thetota l aerial drymatte r and leaf area index evolution were measured once every 10day s (from 10day safte r emergence) on a sample of 5plant sfo r eachblock . Total solar radiation, rainfall, Class-Apa n evaporation and other standard weather conditions were continuously recorded ina meteorologica l station near to the experimental site. Usingth eterminolog y proposed by Charles-Edwards (1982),th e simplest form of model for crop dry matter production isD M= G PAR i =€F0.48Rs, where DM isdr y matter production per unit ground area; F,th e fraction of light intercepted, PARi,th e daily intercepted PAR and Rs,tota l solar radiation, and G isth e efficiency with which the crop transforms light energy into dry matter. F (1 -e

Results LAI,measure d duringth ebiologica l cyclefo r thefou r cropsexamined , is shown inFigur e 1.Th e highest value ofLA I inabsolut e (7.8) was measured inth e grain sorghum 53day s after emergence. Theaccumulatio n ofdr y matter (Figure 2),alway s increased duringth e biological cycleo fth e four crops until reaching the maximum value at the harvest.Thehighes t quantity ofdr y matter wasobtaine d in sweet sorghum (3430g m"2)whil eth e kenaf produced the lowest quantity (1502 gm"2). TheRU E was estimated from alinea r regression between cumulated PARi and dry matter (Figure 3). Our results showtha t sweet and grain sorghum haveth e highest values ofRU E (3.1 and 3.0 g ML1, respectively);th e Jerusalem artichoke, onth e contrary, for itslon g biological cycle, hasth e lowest value. Session 2.3 575

b

6

3" j / [/ i Figure 1.Lea fare ainde xfo r sweet sorghum 2 (1), grain sorghum (2),kena f(3 ) andJerusale m articoke (4) 0 40 60 80 100 120 140 160 DAYSAFTE HEMERGENC E

4000

3000

E S 2000 3: a Figure 2. Drymatte r timetren d ofaeria l 1000 part for sweet sorghum (1),grai n  sorghum (2),kena f(3 )an d ig 4 j/s 0 Jerusalem articoke (4) 20 40 60 80 100 120 140 160 DAYSAFTE R EMERGENCE

3600 .1

3000

_ 2400 Figure 3.Relationshi p between accumulated 'E S 1800 aerial drymatte r and intercepted photosyntetically active radiation ° 1200 for sweet sorghum (1),grai n sorghum (2),kena f(3 )an d 600 Â Jerusalem articoke (4) 0 200 400 600 800 1000 1200 1400 PARI (Mjni !)

Conclusions This study has shownthat , ina Mediterranea n environment, amongth e four alternative crops under comparison, eachgrow n under non-limiting water and nutrient conditions,th eRU Ei n sweet sorghum andgrai n sorghum, ishighe r than that reported inliteratur e for crops classified as C4plants .

References Charles-Edwards, DA., 1982. Academic Press,Nort h Ryde,N.S.W. , 161p . Charles-Edwards, DA. et al., 1986. AcademicPress , Sydney, 235p . Gallagher, H.N. et al., 1978.Journ . Agriculture Ski.,Camb . 91: 47-60 576 Book of Abstracts 4th ESA-congress

CROPRESIDUE S AND SOIL TILLAGE MANAGEMENT: EFFECTS ON SOIL STRENGTH

M. Maiorana, R. Colucci, D. Ventrella

Istituto SperimentaleAgronomico , ViaC . Ulpiani, 5 , 70125Bari , Italy

Introduction In Southern Italy, durum wheat isa widesprea d crop,bot h inrotatio n with industrial crops (sunflower, sugar beet, etc.) and incontinuou s cropping. Thewhea t residues are normally burned. Sinceth e use ofmanur e isb y now very scanty and the progressive worsening of soil fertility cannot be counterbalanced applying ever higherlevel s ofminera l fertilizers for economic and ecological reasons, the ploughing ino f straw and stubble seemst o beth e most suitable agronomic technique, alsobecaus e ofth e positive effects that it can have on some chemical, physical and hydrological characteristics ofsoil . With the aim ofmakin g a contribution to these issues, this Institute undertook a long-term research onth e ploughing ino f crop residues, in comparison with their burning (Maiorana et al., 1992). Thispape r evaluates the effects ofthes etreatment s on soil strength, soil moisture and on water infiltration rate atth efifth yea r oftrial .

Methods The research iscarrie d out since 1990i nFoggia , atypica l wheat-growing area of Southern Italy, on a silty-clay soil (Typic chromoxerert,fine, Mesic ) ofalluvia l origin. The climate isclassifie d as"accentuate d thermomediterranean", by Unesco-FAO, with scanty rains (440 mmpe ryear , mean ofth e last ten years), concentrated mainly inth ewinte r months. On plots of200m 2 each, laid out in a split-plot design with 3blocks , 2 soil tillage depths (Dl= 40-45 cm,b ytraditiona l moulboard ploughing;D 2= 20-2 5 cm,b y surface disc-harrowing) and 2 ways of straw disposal (B =burning ; I= incorporation) are compared ina continuous dryland cropping of durum wheat. The soiltillag e isth e main factor, the straw disposal the split factor. The soil strength was evaluated, inJanuary , February, March and April, 1995,i nabou t 0-50 cm layer, using aBus h recording penetrometer (Findlay, UK). The readings weretake n at 3.5 cm depth increments up to thetota l lenght of 52.5 cm. Ten measurements were made for each block. Sinceth e penetrometer resistance mayb e affected by soil moisture (Vyn and Raimbault, 1993), the soilwate r content at 3 depth layers (0-20, 21-40an d 41-60cm )wa s determined gravimetrically, at the sametim e of penetrometer measurements. Besides, thewate r infiltration ratewa s determined bya double cylinder method. Thevalue s of soil moisture and soil strength were submitted to analysis ofvarianc e (AOV);th e firstste p of reading of penetrometer was not considered, because it was completely unreliable (the penetrometer did not allow for complete support ofth e probe onth esoil) .

Results Tobette r evaluate the effects ofth etreatment s on soil strength, even the cone resistance values obtained inth efirst year , at thebeginnin g ofth e research, were submitted to AOV; as onlyver y smalldifference s were found amongthem , and then thewhol etria lfield wa s characterized by fairly homogenous soil strength, they are not reported inthi s paper. Figure 1show s thetren d of penetrometer resistance values for the different treatments. Themos t marked effects were determined by soiltillag e (Fig. 1A) . In fact, alesse r soil compaction was observed with the deeper tillage (Dl), especially starting from adept h of about 35 cm. The influence of different ways of straw treatment, onth e other hand, was negligible (Fig. IB). Ploughing inshowe d soil strength values slightly lower than those achieved with burning. The Session 2.3 577 superiority ofD l treatment isconfirme d byth e"soi l tillagex cro p residues treatments" interaction (Fig. 1C): infact , the significantly best responses are those ofID 1 and BDI treatments.

Cone resistance (kPa) Coneresistanc e (kPa) Coneresistanc e (kPa) 1000 1500 2000 2500 3000 3500 4000 0 500 0 500 1000 1500 2000 2500 3000 3500 4000 0 500 1000 1500 2000 2500 3000 3500 4000

Dl O 10.5 \ M—°~

17.5

24.5

31.5 V \— ***

37.5 \ \^ ***

44.5 Ö n*** 0 51.5

Figure 1 - Soil strength profile according to soil tillage (A),cro p residue treatments (B) and "soil tillage x crop residue" interaction (C) (*,**,***significan t difference at the0.05,0.01 , and 0.001 probability levels,respectively) .

Onth e contrary, the effects ofth etreatment s on soilmoistur ewer ever y scanty and not significant to the AOV. The influence that soil moisture canhav e on soil compaction hasbee nthe n studied; the analysis ofth e data showed arelationshi p ofth e inverse linear typebetwee n these two parameters, but only considering the straw treatments (Fig. 2).Particularly , this relationship was more evident with the crop residues burning (R2=0.871 )tha n with their incorporation (R2=0.372) . Instead, no relationship resulted for thedifferen t tillage systems. Referring to the water infiltration rate, the highest valueswer e observed inth e plots submitted to crop residues incorporation 1 Soil moisture (gg- 1) (7.1 cmh" vs. 5.5 ofburning ) and inthos e Figure 2 -Influenc e of soilmoistur e on soil strength inth e with deeper soiltillag e (6.8 vs. 5.8 cm h"' for 0-60 cm layer. shallowtillage) .

Conclusions Although the effects ofcro p residues ploughing ino n somephysical-hydrologica l parameters of soil can appear after manyyears , the results obtained with this research have shown that tillagea t 40-45 cm, especially with the straw incorporation, determined a lesser soil strength and a higher water infiltration rate. Withthes etreatments , therefore, even inpresenc e ofa silty-clay soil,i t seemspossibl et o obtain agreate r permeability and abette r soil structure.

References Maiorana, M. et al., 1992.Proc . 2nd ESA Congress, Warwick Univ.: 100-101. Vyn, T.J. and Raimbault, B.A., 1993.Agronom y Journal 85: 1074-1079. 578 Book of Abstracts 4th ESA-congress

STUDY ON THE EFFECT OF NFERTILIZER S ON TOTAL NITROGEN AND NITRATE CONTENT OF GREEN PEA AND GARLIC

E.Nâdasy Department ofAgrochemistry , Pannon University ofAgricultura l Sciences, 57Deé k St. H- 8360 Keszthely, Hungary

Introduction One of the main consequences of intensive Nfertilizatio n isth enitrat e accumulation often causing health problems. Thequantit y and form ofN fertilizer s arever y important factors ofnitrat e accumulation. Thisproble m isver y important atvegetables , becausethe y are generally consumed immatuiately and uncooked besidesthe y areusuall y manured to thehighes t degree. The aim of our experimentswa st o study thechange so fth enitroge n and nitrateconten t ofgree n peaan d garlicusin g different Nfertilize r forms at increasingrates .

Methods The experiments were set up in 5-kilopot s onbrow » forest soil( N:2.4 mgkg"' , pH(KQv6.82, humus: 1.8%) under greenhouse conditions in four replicates. Petit Provencal green pea variety and garlicwer e used withfive increasin g doses(40 , 80, 160, 320, 640m gN kg"' soil) of tliree N fertilizers: NH4N03(32% N),(NH 4)2SO4(20.5% N) and Ca(N03)2 (7.6%N) . Treatments were alsogive n 120m g P2O5 and 200 mgK 20 kg"' soil. Water wasdose db y weight usingirrigatio n asfa r as60 %o f water capacity.Thepe a experiment was carried out duringeigh t weeks. Samples were collected at three growth stages(4 . 6. 8.weeks ) from the leaves and inth e eight-week age from theseeds . Garlicwa sgrow n upt o seven weeksthe n we collected samplesfro m theleave s and bulbs. Thenitroge n content ofsample s wasdetermine d with sodium-hypo-bromite titration with dead-stop indication, the water soluble nitrate content of dry matter from the 1:800rat e water extract with photometric method using N-(l-naphtyl)-ethylene-diamin e andsulphanilamid e asreagents .

Results Resultsar e presented in Figures 1-4.

180 160 140 20 OO 8week-Ca(N03)2 V 80 Leaf-Ca(N03)2 8 week (NH4)2S04 LeaHNH4)2S04 60 8 week NH4N03 Leaf-NH4N03 _ 4 week Ca(N03)2 40 Bulb-Ca(N03)2 / 4week (NH4)2S04 20 Bulb (NH4)2S04 4 week NH4N03 Bulb NH4N03 0 O 40 80 160320340 N doses (mg kg soil) N doses (mg kg soil)

Figure 1.Effec t of N fertiliters on nitrate Figure 2. Effect of Nfertilizer s 011 nitrate content of green pea content ofgarli c Session 2.3 579

10i

Figure 3. The N content of green pea

40 80 160 320 H doses (mg kg"soll )

Leal 4thwee k

Leaf 6thwee k E ss -o Leaf 8thwee k

Seed Figure 4. The N content of garlic 160 N doses (mg kg soil) Conclusions It was established that the nitrogen content in the leaves of green pea increased with the higher N doses, but it was decreased when the plant became mature. N concentration in the seed was high in all treatments (3.42-5.60%) and rised continuously applying greater N rates. The nitrate content of green pea leaf-samples was low and it decreased during vegetation period. The seed had no measurable nitrate content at all. The results indicate that the nitrate accumulation of Petit Provencal green pea variety is low ( 200 mg kg-1 dry matter). Comparing the effect of the applied N fertilizers on the realization of the nitrogen and nitrate content of the plant it was established that the different N fertilizers did not changed nitrogen content of pea samples significantly. Nitrate content of the four-week leaves was significantly increased after using NFI4NO3 compared to the other two fertilizers. The nitrogen content in the leaves of garlic was higher than in the bulb and it also was increased by the maximum N doses. The nitrate content of garlic rised with the increasing fertilizer doses, but its rate WAS low both in leaves und bulbs. The young garlic did not Accumulate nitrate in great quantities. We bad no significant differences between effect of applied N fertilizers both on the nitrogen and the nitrate content of the plant. References Duvvalda J.G. et al. I987. Scientia Horticulturae 3-4, 161-173 p. Fiileky, Gy. 1970. Agrochemistry and Soil Science Hungary 3. 339-345 p. Smukalski, M. et al. 1991. Archives of Agronomy and Soil Science 6. 459-467 p. Terbe I. et al, 1986. I.Lippay Jânos Conference Budapest Proceedings 125-131 p. Thammné, f 1987-1988. Agrochemistry and Soil Science Hungary 36-37. 323-337 p. 580 Book of Abstracts 4th ESA-congress

THEEFFECT S OF IRRIGATION, FERTILIZATION, TILLAGE AND PLANT DENSITY ON CORN (Zea Mays L.)YD3L D

J. Nagy' , L. Huzsvai\ J. Tamâs' , G.J. Kovâcs2,1. Mészâros3

'AgriculturalUniversity , Debrecen, Hungary 2ResearchInstitut e for Soil Science and Agricultural Chemistry ofth e Hungarian Academy of Sciences,Budapest , Hungary, 3L.Kossut h University, Debrecen

Introduction Theyiel d ofa plan t culture depends not onlyo n ecological, genetic andtechnologica l factors, but on their interactions aswell . In research, the evaluation ofbot hth e individual effects ofth e factors and theirjoin t effects arenecessary . Thejoin t effects ofdifferen t plant cultivation factors were estimated byGyörff y (1976),wh o found that thelarges t yield increasei sachieve d when the most significant plant cultivation factors are atthei r optimal levels. The crucial effect offertilizatio n on theyiel d of corn hybridswa s shownb yBerzseny i (1993). Thoseinteraction s which involved environmental effects proved to beth emos t significant.

Methods At the ArableLan d Experimental Farm ofth eDepartmen t ofCro p Production andLan d Use we examined the effect ofplan t cultivation factors onth eyiel d of corn. Our multifactorial experiments allow for the evaluation ofth e effects offertilization , plant density and irrigation (allwit h two variants). In our experiments we had adjacent irrigated and non-irrigated blocks (5376 m ). The former were provided water inth efollowin g amounts, enought o satisfy the plant's demand for water: 1990,100 mm; 1991,6 0 mm; 1992, 170mm ; 1993, 120mm ; 1994, 110mm . These major blockswer e then subdivided for eachhybrid ; inturn , thesewer e divided to allow for different fertilizer/plant densitytreatments . In all,ther ewer efou r random repetitions ofeac h combination of treatments, each on a44 8 m plot. Our experiment was supported byth eNationa l ScienceFun d (T 017047). The statistical modeluse d was aimprove d adaptation ofBox-Wilso n (1951)methods . The data were evaluated using analysis ofvarianc e methods (Svab, 1981;John , 1971). The method was used to stabilizeth evarianc e ofth e cells.Maximu m likelihood methodswer euse d to disaggregate the variance components. Amixe dfixed-random effect s modelwa suse d to estimate the effects, as suggested byHuzsva i (1994). Thejoin t effects ofirrigation , plant density and fertilization were quantified using ANOVAmethods .

Results When evaluating the data onlyeffect s and interactions not related to weather and interactionsvali d everyyea r were examined. Symmetric effects ofth etreatment s were estimated inrelatio n to the major average ofth e experiment. Themode l design canb e seeni nTabl e 1,whic h includesal l treatments and the interactions between irrigation and fertilization and plant density and fertilization. Thesetw o interactions were not related to weather and the direction ofthei r effect wasth e same eachyear . The congruency ofth e direction ofth e effects doesno t mean a congruency ofthei r degree. For the evaluation ofth e significance ofth e effects atwo-side d symmetrical test wasused . The statistical significace ofth etes t canb efoun d inth e last column of Table 1.Durin g the 5yea r period the major average ofth e experiment was 8.21 ha'1, avalu ewhic h serves as a comparison point for the treatment averages. Theyiel d increase duet o irrigation was 869 kg/ha, and without irrigation theyiel d decreased byth e sameamount . The effect ofirrigatio n was significant at p=0.001. The effect of plant density was 185k g ha"1Changin gth etreatment s inth e same direction increases their effect on yield. Our research results correspond withthos e of Györffy(1986) and Session2. 3 581

Berzsenyi(1993): varying theus e ofon efacto r inplan t production willno t achieveth e most favourable result. Interventions inproductio n areno t independent ofeac h other; varying one factor should be accompanied byvariatio n of others so ast o produce most efficiently. During the 5year s lower plant density (60,000 ha"1) was morefavourabl e for the achievement ofhig hyields ;a plan t density of 80,000ha' 1 density resulted ina fal l inyiel d duet o the drought years analyzed. High density planting involvesgrea t risks. The effect ofplan t density was significant at p=0.05.B y examining the effect offertilizatio n we havecom et o the conclusion that no fertilization resultsi na considerable yield loss(154 1k g ha'1)whil e applying afertilize r dosage of 120k gN + 90 kgP2O 5 + 105 kgK2 Oincrease s yield by a similar amount. Fertilization hadth ebigges t effect on yield every year. This effect was significant at p=0.001.

Table 1.Result s ofth e analysis ofvarianc e components (Debrecen, 1990-1994) Treatments Estimated Dispersion Significant atp Fix 8.159 0.093 0.000 Tillage 0.560 0.093 0.000 Irrigation -0.869 0.093 0.000 Plant density 0.183 0.093 0.048 Fertilization -1.541 0.093 0.000 Irrigation x Fertilization 0.448 0.093 0.000 Plant densityx fertilization 0.151 0.093 0.100 Replicates * 0.000 * 0.000 Test parameter = -2 • Log X -- = 2557,5

Conclusions After an evaluation ofcro p production factors (tillage, irrigation, plant density and fertilization), the individual effects ofeac h factor andth einteractio n between irrigation and fertilization and that between plant density and fertilization proved to be significant. Onth ebasi s ofou r experimentsw e have established that these two interactions arepositive , independent ofth e weather conditions, and that the direction ofthei r effect isth e sameeac hyear , but the degree ofthei r effect varies. The results indicate that theplan t cultivation factors arerelate d to each other. The irrigation - fertilization and plant density -fertilizatio n interactions arepositive , and accordingly allthre e factors havet ob e adjusted simultaneously when production levelsar e changed. When disaggregating the variance components, the major averages showed amid-tec h levelo fproduction . When considering a shift to low-input production it should be considered that adecreas e inth eus e of oneproductio n factor reduces the effects ofth e others;relativel y high amounts invested inth eothe r factors willno t be effective. No matter what production leveli stargete d the most favourable interactions ofwater , nutrient supply and plant density havet o be simultaneously assured.

References Berzsenyi, Z., 1993.Plan t analysis inmaiz eproductio n research. Doctoral dissertation, Martonvâsâr.1-150 . Box, G.E.P. andWilson , K.B., 1951.O nth eExperimenta l Attainment ofOptimu m Conditions. Journal ofth e Royal Statistical Society. SeriesB .13.1 . Györffy, B., 1976.Evaluatio n ofcro p production factors affecting theyiel d ofmaize . Agrârtudomânyi Közlemények 35,pp .239-266 . Huzsvai, L., 1994. Comparison ofbiométri emethod s ofexperiment s incro p production andtillage . Ph.D. Thesis,Debrecen .1-145 . John, P.W.M., 1971.Statistica l Design and Analysis ofExperiments . New York, McGraw-Hill. Svâb, J. 1981., Biometriemethod s inresearch . MezögazdasägiKiadó ,Budapest .1-55 . 582 Book of Abstracts 4th ESA-congress

ENERGETIC ANALYSIS OF EUROPEAN WINTER WHEAT MANAGEMENT PRACTICES COMPARED AT THEDLG-FELDTAG E IN GERMANY

LubomirNeudert1, Jan Kren1,2

1 Departmnet of General Plant Production, Mendel University of Agriculture and Forestry Brno, Zemëdëlskâ 1,CZ-61 3 00Brno , Czech Republic 2 Agricultural Research Institute Kromëfiz, Ltd.,Havlickov a 2787,CZ-76 7 41Kromëfiz , Czech Republic

Introduction Comparison of European winter wheat management practices isa traditiona l part of the international agricultural exhibition DLG-Feldtagewhic h ishel d by the German Agricultural Society (DLG -Deutsch e Landwirtschaft Geselschaft) always in adifferen t federal country of Germany bi-yearly. The aim of the demonstration experiments ist o showcroppin g practices of winter wheat in federal countries of Germany and advanced European countries,t o evaluate the economic aspectso fmanagemen t practices based oninpu t variable costs,grai nyiel d and its quality. Since 1992,th e Agricultural Research Institute Kromëfiz, Ltd.ha s alsoparticipate d in thisundertaking . Thepape r isfocuse d onth e evaluation of energy balance ofteste d management practices and comparison of resultswit hth e economic evaluation published previously (DLG, 1994;Roßber g et al., 1995).Th e evaluation ofth e energy use ison e ofth e important objective criteria of agricultural production efficiencies. Energy balance covers astabl eutilit y valueo f agricultural products, it is less subjected to various market fluctuations and enables to compare both different production kinds and considerably different production practices. The analysiso f energy balance may be,therefore , complementary to economic analyses (Jones, 1989).

Methods DLG-Feldtage'94wer e held onth e farm Oberbigelhof inBa d Rappenau neer Heilbronn. Twenty-twomanagemen t practices ofwinte r wheat wereteste d on small-plots (10 m with isolation strips 0.5 mwide ) field experiments infou r replications. During the growing season, the stand wastreate d based on recommendations ofrepresentative s ofth e participating organizations. Costs for alltreatment s were recorded and after the harvest, the profit per lha was calculated for the economic evaluation by the accounting system used in Germany (Roßberg et al., 1995). The direct and indirect energy consumption was determined for each management practice using the standard methodology (Preininger, 1987;Stout , 1992). Both the energy for the production ofth e crop inth efield an dth e energy needed to produce machinery, inorganic fertilizers and pesticides were included.The influence of aforecro p and effects of organic fertilization were not included in calculations.

Results The average grain yield was 7.65 t ha" ' and itsvariabilit y evaluated byth e coefficient of variation (c.v.)was 7.73%. The average level of inputs (variable costs) was 1,083.90 DMha" 1 (c.v. = 12.05 %). The average energetic equivalent of inputs was 22.15 GJha" 1 (c.v.= 11.92 %). The variable costs perto n of grain was 139D M (c.v. = 13.59 %). The consumption of energy per ton of grain was 2.84 GJ (c. v = 13.56 %). According to the proportion ofth etota l energy the individual inputs ranked as follows (Figure 1): 1.fertilizer s (68%), 2.machine s (20 %), 3.seed s (10 %), 4.pesticide s (1.2 %), 5.labou r (0.8 %). The order of input items differs according to the costs (Figure 1): 1.machine s (38 %), 2.fertilizer s (17%), 3. pesticides(16. 5 %), 4. seeds (15 %), 5.labou r (13.5 %). Theorde r ofth e input items according to the costs per 1 GJ o f energy was as follows: 1.labou r Session 2.3 583

(901DM), 2.pesticide s (718 DM), 3.machine s (92 DM), 4. seeds (76 DM), 5.fertilizer s (12 DM).Differen t approaches used by the representatives ofth e participating organizations resulted inth evariabilit y of input itemsi nth ese to f2 2evaluate d cropmanagemen t practices.Th e individual input items (seeds,fertilizers , pesticides, machines, labour) expressed in both GJan d DMdiffe r inth e value ofth e coefficient of variation (Figure 2).I t mayb e supposed thatth e low valueo f coefficient of variation indicates the lowpossibilit y of input item modification (i.e. small chance of input reduction). Onth e contrary, the higher value of coefficient of variation indicates thepossibilit y alarg e range of input item modification (i.e.th e input item may be reduced by the optimization of management practices). From thispoin t of view, the inputsi n winter wheat crop management practices may bereduce d byreasonabl e application of pesticides and fertilizers.

Figure 1.Percentag e of input Figure 2.Th e coefficients of variation of input items in items proportion the set of 22 winter wheat management practices 100% 60 .

50

• seeds •fertilizers % 30 D pesticides D machines M •• =•• labour GJ DM

Conclusions The international comparison ofwinte r wheat management practices has showed: 1)Th emanagemen t practice should beconsidere d as acomple x of optimized cropping treatments „tailored " for certain regional agroecological conditions. 2)T o improve the economic effects ofwinte r wheat growing the highest possibilities are in reasonable pesticide and fertilizer using. The rational application of pesticides has only small effects on input energy reduction. The balance ofenerg y mayb e mostly influenced by optimization of nitrogen fertilization. 3)Furthe r increasing the effectiveness of winter wheat management practices will need to develop diagnostic methods, signalization and quality advisory services which facilitate fast responses (using cropping treatments) to varieties with different agrobiological properties andt o weather conditions in individual years.Th e materialized inputs (seed, fertilizers, pesticides,an d growthregulators ) may be saved during the growing season inthi s way.

References DLG, 1994.Vergleic h europäischer Winterweizen-Anbauvervahren,Feldtagebücher , 24p . Jones, M.R. , 1989.Agricultura l Systems 29:339-355 . Roßberg, R. et al., 1995.DLG-Mitteilunge n 110: 18-23. Preininger, M., 1987. Energy evaluation of production processes in plant production, ISSM Prague, 29p . Stout, B.A. , 1992.Energ y inworl d agriculture, Vol. 6,Elsevie r Science Publishers, 367p . 584 Book of Abstracts 4th ESA-congress

INTEGRATING WEED-CROP COMPETITION INTOA PROCESS-ORIENTE D CROP GROWTH MODEL: EVALUATION OF COCKLEBUR COMPETITION WITH SOYBEAN

1 2 D. J. Pantone ,J . R.Kinir y

Blackland Research Center, Texas A&MUniversity , Temple, Texas 76502,US A Grassland, Soil &Wate r Research LaboratoryLaboratory, USDepartmen t ofAgriculture , Agricultural Research Service, Temple, Texas 76502,US A

Introduction Models that predict the performance of acro p based oncro p andwee d densities are particularly valuable in agronomy where cropyiel d losses canb eestimate d and weed management practices can be developed. Process-oriented models ofplan t competition haveth epotentia l to change the way crops are grown and weeds aremanaged . Recently, ageneral ,process-oriente d model, ALMANAC (Agricultural Land Management Alternatives withNumerica l Assessment Criteria), which simulates competing plant species,ha s beenproduce d byUSDA-AR S scientists at Temple, Texas (Kiniry et al., 1992)usin g technology derivedfrom th e EPIC (Erosion/Productivity Impact Calculator) model (Williams et al., 1989). ALMANAC simulates weed and crop growth and development, including competition for light, nutrients and water. Plant growth simulation models areimportan t botha sbasi c research devices and as applied decision-making tools. Asresearc h devices,plan t growth models allow researchers to easily simulate many different scenarios thatwoul d be difficult, ifno t impossible, to construct inth e field. In addition, plant growth models allow researchers to identify basic research areas that need further investigation for developing anin-dept h understanding of growth processes. Previously, most models ofplan t competition were based onempiricall y derived density-yield relationships (Pantone et al., 1991). Modelstha t predict crop yield based onempirica l density- yield relationships are of limited utility due tovaryin g edaphic and climatic conditions. In contrast, process-oriented models can simulate crop growth with different soils, rainfall, fertilization, temperatures, andradiation . Theprimar y object ofthi s project wast o evaluate a process-oriented simulation model ofweed-cro p competition (ALMANAC) using cocklebur (Xanthium strumarium L.) asth e weed and soybean [Glycine max(L. )Merr. ] asth e crop.

Methods ALMANAC is aprocess-oriente d model that simulates water balance, nitrogen and phosphorus use, and crop growth based on light interception. Themode l uses Beer's law (Monsi et al., 1953) andth e leaf area index (LAI) ofth e total canopy to simulate light interception by the leaf canopies. Using the system of Spitters et al (1983),th e model dividesth e intercepted light between the competing plant species. Yield production ispredicte d onth e basis of a modified harvest-index approach. Climatic input parameters consist of solarradiation , maximum and minimum temperatures, and rainfall. All inputs are ona dail y time step. Soil parameters contain soil water characteristics andnutrien t levels. During 1993, 1994, and 1995fiel d studies were used to evaluate the impact of aweed , cocklebur, on soybeanyield s onth e Blackland Prairie of Texas. The soil was aHousto n Black clay (fine, montmorillonitic, thermic Udic Pellustert). The experimental design was apartia l additive arrangement (Rejmanek, 1989)wit h weed densities of 0, 0.5, 1,2 ,3 ,an d4 cocklebur plants m" . Soybean wasplante d inrow s spaced 69 cm ata constant crop density of 30plant s m"2. TheALMANA C model was used to predict crop yields Session2. 3 585 for each year. Crop monocultures were used ascontrol s to evaluate the effect of weed-crop competition on crop yield. The main model prediction of interest was crop yield under weed-free and weedy conditions. The focus was oncomparin g model simulations ofth eeffect s of cocklebur to actual field measurements. Cocklebur was selected because it is one ofth e primary weed species of economic importance inth e United States (Jordan, 1992).

Results Results of model simulations and field experiments arepresente d inth eTable .

Simulated and measured soybean yield (tha ") fo r eacho f sixwee d densities (plants m"2)durin g 1993, 1994,an d 1995

Weed Density 1993 1994 1995

Simulated Measured Simulated Measured Simulated Measured

0 1.96 2.14 1.97 2.45 1.96 2.33 0.5 1.86 1.43 1.68 1.50 1.71 1.67 1 1.58 1.25 1.16 1.14 1.26 1.42 2 0.97 1.01 0.65 0.96 0.72 1.30 3 0.81 0.85 0.54 0.71 0.56 0.94 4 0.78 0.70 0.48 0.72 0.53 0.73

Conclusions Results of model simulations correspond relatively closet o measured field data. The model tended tounderestimat e theyiel d ofth ecro pi nmonoculture . During 1994 and 1995,th e simulated yields atth e highest weed densities (3an d4 plant sm ") wer e lower than that observed inth e field. However the model did not consistently underestimate theyields , andfield measurements ofman y intermediate weed densities were fairly accurate. The results presented are not an independent validation ofALMANAC , butrathe r ademonstratio n ofmode l performance under similar environmental conditions over arang e ofyears . In conclusion, ALMANAC isa versatil e model which canreasonabl y simulate cocklebur-soybean competition over arang e of weed densities. The inputparameter s are easily derived and dono t necessitate further details on leaf anglestha t individual leaf simulation would require. The model provides theuse r with anefficien t tool for assessing the impact ofweed so n crop yields and for management optimization related to weed control.

References Jordan,N . 1992. Weed Science 40:614-620 . Kiniry, J.R. et al., 1992. Transactions ofth e American Society ofAgricultura l Engineers35 : 801-809. Monsi, M. et al, 1953. Japanese Journal of Botany 14:22-52 . Pantone, D.J. et al., 1991. Crop Science 31: 1105-1110. Rejmanek, M. et al., 1989. Weed Science 37: 276-284. Spitters, C.J.T. et al, 1983. Aspects ofApplie d Biology 4: 467-483. Williams, J.R. et al., 1989. Transactions ofth e American Society ofAgricultura l Engineers 32:497-511. 586 Book of Abstracts 4th ESA-congress

NITROGEN NUTRITION MANAGEMENT INWINTE R WHEATI N ORGANIC FARMING

F. Promayon, C David

ISARA, 31 placeBellecour , 69288Lyo n Cedex 02,Franc e

Introduction Nitrogen nutrition inorgani c farming depends essentially on soil contribution. TheN management affects wheat yield,bakin g quality and occasionally the environment bygroun d water pollution. The aim ofthi s research ist o evaluate soil nitrogen fertility asaffecte d bycro p rotation and fertilisation practices

Methods Nitrogen management was estimated bythre einterrelate d networks (farm network,field networ k andtrials ) on organic and conversion stockless farming systems. Farmers' practices were identified on 17farm s by survey (Promayon, 1995). Each year, anon-far m agronomic monitoring was established on 15fields selecte d ontw o criteria: the cropping systeman d the type of soil. On somefields, severa limprove d nitrogen management wereteste d incompariso n with farmers' practices The crop yield build up was assessed using acro p diagnosis (Meynard and Sebillotte,1993). Yield components (tills,spike ,grai n m"2,4 times) ,N-conten t (%,4 times ) andgrai n protein level (%) were measured. The« grai n number index» (GNI ) and « nitrogen nutrition index »(NNI ) (Greenwood et al., 1991)wer eused . The GNI relatesth erati o between the observed number of grain m2 to theupmos t potential per cultivar TheNN I relatesth e ratio between the observedN uptake to optimalN uptake which quantifies the nitrogen deficiency (4 times:Feeke s 2-3;4 ; 6;8) . The nitrate test wasteste d to detect N-deficiency (concentration ofth e « stembas e extract» Justes, 1993)

Results Two types offarmers ' practices are identified to improve nitrogen nutrition: fertilisation practices on wheat and fertility building bylegume s or green manures incro p rotation. In our network, four groups havebee nidentifie d (Table 1):

Table 1. Nitrogen management practices multiannual legumes> 35 % annual legumes< 50 % nogree nmanur e possiblegree nmanur e regular Nfertilisatio n inautum n possibleN fertilisatio n inautum n possibleN fertilisatio n insprin g systematic N fertilisation insprin g fertilisation in spring< 3 0k g N ha"1 totalfertilisatio n <6 0k gN ha"' * TypeI Typem fertilisation in spring> 50k g Nh a ' total fertilisation >60k g N ha" ' Typen TypeI V

* efficient kgN ha" (assessment with Ziegler and Masson efficiency coefficient, 1990) Session 2.3 587

There isa statistical relation between the NNI (measured at Feekes 8) and theNG I (r =0,69) (Figure 1) Nevertheless, it isimpossibl e to define athreshol d (under this level, nitrogen deficiency has automatically an influence on wheat yield ,Justes , 1993).

Figure 1:Relationship between NNI and NGI stem elongation (Feekes 8)

0,90

0,80

0,70-- • Type I 0,60-- • Type II GNI 0,50 AType III

0,40 O Type IV

0,30

0,20 0,20 0,30 0,40 0,50 0,60 0,70 NNI Conclusions TheNN I levelswer eunde r 0,85 and decreased duringth e stem elongation. Fieldswit ha n important soilN-conten t inFebuar y (> 70 kgN ha"1)an d afavourabl e soil structure had good N nutrition and thebes t results during tillering (tillers per plant> 1,5 ,NN I >0,8) . Other explanation factors are lucerne asth e preceding crop (type Ian d II) and an earlier N fertilisation The nitrogen deficiency wasthoroughl y observed from thebeginnin g of stem elongation. Nitrogen input byannua l legumes or green manure (type III and IV)wa s insufficient to ensure satisfactorily nitrogen nutrition. Manure spread inautum n or at thebeginnin g of spring facilitated yield build up. However, there isn o statistical relationship between N-fertiliser quantity andth e NNI. The efficiency ofmanur e application depends on thetyp e of source and the quality of spreading. The mineralisation rate,th e absorption and the efficiency were dependent on the soil structure, water resources and weeds competition. Despite the lowN-conten t level,th e number ofth e grain m"2 was over 60%o fth eupmos t potential obtained innon-organi c agriculture which canb e explained bya n important N-efficiency. Thisoccurre d when theN-applicatio n improved theNN I during the stem elongation. Water and nitrogen deficiency during grainfilling an d pathogenic infestation at early stage influenced the accumulation ofth e different classes ofprotein sb y a decrease and a modification ofth e protein pool Baking quality and grain protein level were insufficient. The nitrate test cannot be used to control theN-fertilisatio n because crops are alreadyN deficient and this indicator ofN crop status does not allowt o quantify the level ofN deficiency. Further research will provide information onth e possibility to use theNN I for N-fertilisation monitoring.

References Greenwood, D. J. et al., 1991.Annal s ofBotany , 67: 181-190. Justes,E. , 1993.Paris , FR, Thesis, Institut National Agronomique Paris-Grignon, 227p . Meynard, JM and Sebillotte, M, 1993.L epoin t sur l'élaboration du rendement, EdsINRA , Versailles Promayon, F , 1995.Paris , FR, Ing Dipl, Institut National Agronomique Paris-Grignon, 59p . Ziegler, D and Masson, E ., 1990 Perspectives agricoles 145:79-86 . 588 Booko fAbstract s 4thESA-congres s

NITROGEN FERTILIZATION NEEDS OFRAPESEE D IN AUTUMN

R.Reaul , C. Colnenne^, D.Wagner ^

1Centr e Technique Interprofessionnel des Oléagineux Métropolitains, 174 ave Victor Hugo, 75116 Paris, France 2ISA, Lille, France

Introduction In Europe, winter rapeseed is one of the rarefiel d crops receiving anitroge n (N) fertilization before winter. Forman y farmers, Nfertilize r supply is good when oilseed rape growth results are higher. Although, these Nsupplie s are not generalized, they raise problems for they are applied just before aperio d of too much water, when risks of nitrate losses and pollution are high.T o study the interest of Nfertilizatio n before winter, we analysed yield response todifferen t spring fertilization rates versus autumn fertilization.

Methods 12multiloca l experiments were carried out in different French regions for two years.Eac h experiment was laid out in a split plot design with two factors and four replications.Th e first factor was the seedbed Nfertilizatio n rate, with 2 levels: 0 and 50 (or 80)k g N ha-1. The second factor was topdressin g spring fertilization rate, with 5levels :0 , X-50,X , X+50, X+100k g Nha~ l; X bein g calculated for the whole experiment with abalanc e method adapted for oilseed rape (Reau et al, 1994, 1995). Autumn nitrogen utilization wasestimate d with the Coefficient of Apparent Utilization (CAU) calculated from the difference between Nconten t at the end of winter with and without Nautum n fertilizer, divided by autumn Nfertilizatio n rate (deWit , 1953). The yield was measured harvesting 50-100 m2 ineac h plot. Statistical analysis was realized with SAS and the means were compared with the Newmann and Keuls test (ct=0.05).

Results The results showed that generally Nfertilizatio n before winter has noconsequenc e on the yield potential, on condition that spring fertilization is suficient (Figure la, b):ther e wasn o significant difference between the maximum yields for plots with and without seedbed N fertilizer in 11ou t of 12trials , aspresente d inth e table. These results confirmed that temporary nitrogen deficiencies in autumn have no effect on oilseed rape yield. Wenote d one exception to this rule: in the north of France, when the photosynthetic active radiation was limited before flowering, nil seedbed Nsuppl y reduced biomass obtained in winter and then, spring growth was insuficient toreac h the yield potential despite ano n limiting Nfertilizatio n in spring (Figure 1c) . When Nsprin g rate was too low toreac h potential yield, spring fertilizer was alimitin g factor for the yield. The effect of Nfertilize r before winter depended on Nutilizatio n in autumn. When Nutilizatio n was low, yield response to low total Nrat e was higher without Nfertilize r before winter because of abette r utilization of N fertilizer in spring (Figure la). When Nutilizatio n was ashig h as in the spring, there was no difference of yield (Figure lb). Session 2.3 589

Table. Rapeseed yields after different N-treatments in 12trials .

Maximum yield (t ha"l) Yield at nil sprir g rate (tha"')

Seedbe 1 N fertilizer no yes Stat, test no yes Stat, test

Trial CAU

1 0 4.16 4.34 NS 2.52 3.02 S 2 0.3 3.77 3.81 NS 0.96 1.21 NS 3 0.3 3.07 3.04 NS 2.27 2.61 NS 4 0.4 3.36 3.39 NS 2.03 2.11 NS 5 0.7 4.77 4.93 NS 2.31 2.56 S 6 0.8 4.69 4.87 NS 1.50 2.27 S 7 1 3.84 4.06 NS 2.39 1.98 s 8 1.1 3.17 2.89 NS 1.65 2.03 s 9 1.2 4.64 4.21 NS 2.31 2.74 NS 10 1.2 3.99 3.93 NS 2.99 3.34 s 11 1.4 4.77 4.80 NS 2.30 3.09 s 12 0.5 4.68 5.01 S 2.61 2.81 NS

yield( t/ ha ) C

ab _4 c Jm^Hl ab , a ,

• e K ni]seedbe dN nil seedbedN 4* 50seedbe dN seedbedN

0 0 i 0 0 80 160 240 260 290 310 340 390 0 50 165 215 265 315 365 0 50 120 170 220 270 320 total N fertilizer total N fertilizer total N fertilizer Figure 1.Yiel d response of rapeseed to Ntreatment s in trials 2, 6an d 12.

Conclusions Generally, in the main production area of oilseed rape in France, Nfertilize r utilization is rather low in autumn (Merrien et al, 1996;Rea u et al, 1996), sotha t splitting totalN fertilizer between autumn and spring isno t efficient. Nowadays Nfertilizatio n before winter isno t recommended in France. However, under certain circumstances, when the yield potential may be affected by the state of rapeseed growth in winter, the interest of Nsuppl y during autumn could be justified. For this, we have tounderstan d better, and explain the possible effect of rapeseed state in winter on setting-up of rapeseed yield.

References de Wit CT., 1953. Versl. Land-bouwk. Onderz. Agricultural Research Report, 59(4),7 1p . Merrien, A.e t al, 1996.Paris ,France , Oléoscope spécial 20:7-15 . Reau, R. et al, 1994.Paris ,France , Oléoscope 19: 22-23. Reau, R.e t al, 1995.Cambridge , UK, 9th international rapeseed congress 1:317-319 . Reau, R. et al. 1996.Paris , France, Oléoscope spécial 20: 16-27. 590 Book of Abstracts 4th ESA-congress

EFFICIENCY OF DIFFERENT TECHNOLOGIES FOR THE APPLICATION OF FERTILIZERS TO CEREALS

R. Richter, Z. Poulîk, J. Rikanovâ

Mendel University of Agriculture and Forestry, Brno, Czech Republic

Introduction With regard to a decrease of nutrient consumption in fertilizers it is more and more important to take any measures which could improve the utilization of individual nutrients. As one of such measures it is possible to mention a local application of fertilizers, the aim of which is to accumulate fertilizer particles into a certain depth of soil in such a way that the nutrients could be absorbed by plants in the most efficient manner. It is not always required to increase yields of the corresponding crop but to reach the same or even better efficiency of nutrients supplied in a lower dose of fertilizer. Recently, this problem was studied e.g. by Leikam et al. (1983), Malhi and Nyborg (1985), Randall and Hoeft (1986), Matzel and Suntheim (1988), Mulla et al. (1992) and others. The aim of this study was to test the effect of a pelleted multi-component fertilizer Synferta P 16containin g N:P205:K20 (16:12:12) when using different methods of application on the major yield parameters of spring wheat as well as on chemical composition of kernels and straw.

Methods Experiments were carried out in pots containing medium heavy soil with pH/KCl 6.2 and with the following contents of available nutrients (Mehlich II): P - 89 mg.kg"1, K - 175 mg.kg', Ca - 1514 mg.kg1 and Mg 223 mg.kg"1. In this experiment, partly the different doseso f fertilizers (i.e. 5 variants: Variant 1- no fertilizers; Variant 2 -0. 2 g N, 0.15 g P205 and 0.15 g K20 per pot; Variant 3-0.4gN,0.30g P205 and 0.30 gK 20 per pot; Variant 4 -0. 6 g N, 0.45 g P205 and 0.45 g K20 per pot; Variant 5 - 0.8 g N, 0.60 g P205 and 0.60 gK 20 per pot) and partly various methods of fertilizer application (i.e. 3 variants: Variant 1- application into the depth of 2 - 3 cm; Variant 2 - application into the depth of 5 - 6 cm and Variant 3 - application within the whole soil profile in the pot) were tested. The obtained results were statistically analyzed using the method of variance analysis.

Results The obtained results are presented in Figures 1an d 2. The application into the depth of 5 - 6 cm showed to be the most suitable because the nutrients were accumulated near to the active surface of the fully developed root system of plants. The worst results were obtained after mixing the soil with the fertilizer because the nutrients were too dispersed and their accumulation in the active root zone was insufficient. As far as the other yield parameters were concerned (i.e. number of fertile tillers, number of kernels per pot and yield of straw), they were affected more than the yield of grain by the increasing doses of nutrients; however, the differences were statistically significant in some cases only. Changes in the number of fertile tillers were manifested more in the yield of straw than that of grain. The content of N and, partly also, of Ca in kernels increased with the increasing doses of nutrients while those of P, Kan d Mg did not show any marked changes. A local application Session 2.3 591 of the fertilizer increased the accumulation of Kan d Ca in kernels, decreased the content of P and did not change the levels of N and Mg.

depth 2-3cm depth 5 —6t= m uhole profile?

yi eld of strau L^II el cd of gr .ai n

Figure 1. Yields of grain and straw in spring wheat (g per pot)

3.5 r ;

dept h 2 —3dm depth 5 —«Scr m uhole prof- H tig

Figure 2. Contents of macronutrients in grain (%)

Conclusions Both yield parameters and content of the major part of principal nutrients in grain of spring wheat were favourably affected by a local application of a multi-component fertilizer Synferta P 16, especially after its application at the depth of 5 - 6 cm. The obtained results demonstrated that after the application of fertilizers at a certain depth it is possible to reach the same production efficiency even with a lower dose of nutrients.

References Leikam, D.F. et al., 1983. Soil Science Society of America Journal, 47: 530-535. Malhi, S.S. and Nyborg, M., 1985. Agronomy Journal, 77: 27-32. Matzel, W. and Suntheim, L., 1988. Charakterisierung pflanzenverfugbarer Nährstoffe im Boden. Berlin, AdL der DDR: 255-260. Mulla, DJ. et al., 1992. Agriculture, Ecosystems and Environment, 38: 301-311. Randall, G.V. and Hoeft, R.G., 1986. Crops Soils Magazine, 38: 17-22. 592 Book of Abstracts 4th ESA-congress

YIELDING OF WINTER TRITICALE var. PRESTO UNDER LOW-INPUT AND INTENSIVE METHODS OF CROP MANAGEMENT 12 11 J.Rozbicki , W.Madry , M.Kalinowska-Zdun , Z.Wyszynski Department of Plant Production, Warsaw Agriculture University - SGGW, 02-528 Warsaw, Rakowiecka 26/30, Poland SGGW, Warsaw, Poland

Introduction Sustainable agriculture needs reduced fertiliser and pesticide use in cropping systems. Triticale may be an attractive alternative to wheat, barley or rye for feed grain as a low-input crop because of its greater disease resistance (Naylor et al., 1993; Wolski, 1989). The goal of this study was to evaluate winter triticale yielding and grain quality as influenced by a reduction of nitrogen fertilizer use and omission of pesticides (excluding herbicides) in intensive crop management as in the work of Easson (1995) with winter wheat.

Methods o The date used come from the multifactorial experiment 2 conducted at Chylice Experimental Station (52,5° N) in 1992-1994.The experiment tested the effects of the following eight factors, each at two levels : sowing date (20 September, 10October) , nitrogen (N) level (150, 90 kg N ha'),pattern of N application (split 40+ 60% , 100%), timing of N (BV-beginning of vegetative growth, growth stage 25-27 according to Zadoks et al., (1974)), growth regulator (Chloromequat - 3 1 ha , 0), foliar fertilizer (Insol - 11 ha"1, 0), summer fungicide (Folicur BT - 11 ha~',0) and insecticide (Decis -0,2 5 1 ha"1, 0). Winter triticale was sown on a very good rye complex after spring wheat, grown as a second cereal. Grain yield per plot, grain protein content, disease infestation and post-harvest residual soil nitrogen content were observed. Analysis of variance for all data was carried out.

Results Grain yield was significantly reduced (7.9-10.5% ) at the lower N rate (Table),due to a reduction in ear number and grain number per ear (data not shown).There was also a significant reduction in protein content at the lower rate of applied N. Post-harvest residual soil N was higher at the higher rate of applied N (Rozbicki et al., 1995). Non-application of the growth regulator caused the significant decrease in the grain yield but a small but still significant increase in protein content.Wit h the exception of timing of N, where yield was higher and protein lower with the earlier application, the other factors did not lead to significant changes in grain yield except for a small positive effect (6.1%) of the fungicide in 1992 only. Leaf spot of winter triticale (in DC 85) in 700% James Scaleo n the untreated plots was on average 5.9% on the flag leaf, 16.2% on the next eldest and 22.8% on the next leaf (Rozbicki et al.,1996) . Session 2.3 593

Table. Means of grain yield (t ha ) and protein content( %) in grain, estimated at two levels for each factor in the experiment

grain yield ( t ha ') proteini content of grain (%)

Factors and treatments 1992 1993 1994 1992 1993 1994 Dose of nitrogen 150 kg N ha ' 7.10* 8.09* 6.85* 11.3* 12.2* 10.4* 90 kg Nha" 1 6.38 7.45 6.13 9.8 10.7 9.2 Division of nitrogen 60+4 0% 6.69 7.78 6.43 10.8* 11.6* 10.1* 100% 6.78 7.76 6.55 10.4 11.3 9.5 Timing of nitrogen BV 6.84* 7.92* 6.54 10.2* 11.0* 9.2* DC 25-27 6.63 7.62 6.43 10.9 11.9 10.4 Growth regul.- Chloromeqwat 3 1 ha 6.93* 7.86* 6.65* 10.4* 11.3* 9.9 none 6.55 7.68 6.33 10.7 11.6 9.7 Foliar fertilization - Insol 11 ha ' 6.77 7.83 6.38 10.6 11.5 9.9 none 6.69 7.71 6.60 10.5 11.4 9.7 Summer fungicide -Folicur BT 11 ha 6.94* 7.83 6.53 10.5 11.5 9.7 none 6.54 7.71 6.45 10.6 11.4 9.9 Insecticide - Decis 0.25 1 ha ' 6.78 7.86 6.51 10.5 11.5 9.9 none 6.70 7.68 6.47 10.6 11.4 9.7 LSD 0.05+ 0.22 0.18 0.20 0.23 0.27 0.30 LSD is calculated to test the differences of the means at both levels of every factor * the difference of means for both levels of a given factor is significant at the level 0.05

Conclusions The observed reduction in grain yield caused by the lower nitrogen fertilizer application rate was relatively large (about 10%) on average over the three years, but omitting pesticides only coused a slight decrease in this trait. Low-input management of winter triticale may be effective in reducing the environmental impact. In the light of our investigation, winter triticale seems to be a crop that may be grown under low-input management without problem of greatly decreased grain yield and quality. This species could therefore be recommended for growing more widely in sustainable farming systems.

References Easson D.L., 1995. Journal of Agricultural Science Cambridge 124: 343-350 Naylor R.E.L. et al., 1993. Journal of Agricultural Science Cambridge 120: 159-169 Rozbicki J. et al., 1995. Annals of Warsaw Agricultural University, Agriculture 29: 51-58 Rozbicki J. et al., 1996. Roczniki Nauk Rolniczych Séria A (in press) Wolski T., 1989. Lublin, Poland, Proceeding of Triticale Conference 9-21 Zadoks et al., 1974. Weed Research 14: 415-421 594 Booko fAbstract s4t hESA-congres s

LOWER YIELD LOSS DUE TO DISEASES IN NEW WHEAT VARIETEE S

K.D. Sayre' and C. van der Wilk2

1 CIMMYT, Mexico D.F., Mexico 2 Department of Agronomy, WAU, PO Box 341, 6700 AH Wageningen, The Netherlands

Introduction The Centro Internacional de Mejoramiente de Maiz y Trigo (CIMMYT) gives high emphasis to genetic resistance to prevalent, important diseases (Sayre et al, 1991, unpublished report) and the yield potential of bread wheat (Triticum aestivum L.). Periodic evaluation of this genetic improvement is carried out, to identify traits that may require increased efforts by breeders (Cox et al., 1988).

Methods A historical set of ten bread wheat varieties developed from germplasm from CIMMYT and released between 1962 and 1989 in Mexico and other developing countries as well as 10 advanced CIMMYT lines were grown under optimum management conditions on the CIMMYT experiment station at El Batan both with and without disease control. Leaf rust was scored regularly. The chlorophyll content of the flag leaf was determined with the Chlorophyll Meter SPAD-502. The SPAD values of this meter correspond to the amount of chlorophyll present in the leaf calculated on the basis of light transmitted by the leaf (Spectrum Technologies INC. 1989).

Results Results are presented in the following figure and tables.

2 8000- OÜ -4.8 • 10000 + 26.87 • year 6000- a 3 4000- > 2 2000- 1.5 • 100000+ 78.9 3 • year <

1960 1965 1970 1975 1980 1985 1990 1995 YEARO FVARIET YRELEAS E O actual yield - control -predicte d yield - control O actual yield - no control -predicted yield - no control

Figure. Yield trend with and without disease control

Table 1. The correlation between grain yield and yield components. grain yield (kg ha"1) yield components

spikes m'2 grains m-2 grains spike'1 kernel weight with control 0.433* 0.582*** 0.330 0.180 without control 0.454** 0.673*** 0.539** 0.843* Session 2.3 595

Table 2. The correlation between kernel weight and chlorophyll content of the flag leaf during grain filling, with and without disease control. kernel weight (g) chlorophyll content

01/08/95 11/08/95 21/08/95 31/08/95 with control -0.096 0.242 0.339 0.014 without control 0.491** 0.680*** 0.628*** 0.580***

Table 3. Grain yield and percentage yield loss. genotypes grain yield (kg ha'1) yield loss (%)

with control without control

Pitic 62 4698 1387 70.48 Lerma Rojo 64 4532 1981 56.29 Jupateco 73 5553 1501 72.97 Pavon 76 5702 3994 29.95 Seri 82 6012 3096 48.51 Opata 85 5982 2826 52.76 Super KAUZ 88 6305 4092 35.09 Galvez 87 5332 3658 31.40 Temporalera 89 5367 2708 49.55 Culiacan 89 5673 3903 31.19 BOW/GEN//DERN 5048 4500 10.85

Conclusions Difference for rust resistance between genotypes was significant (p

References Cox, T.S. et al., 1988. Crop Science 28 :756-760. Spectrum Technologies INC, 1989. Chlorophyll Meter SPAD-520. Minolta Camera Co., Ltd. Plainfield, USA. 23 p. 596 Booko fAbstract s4t h ESA-congress

INPUT, OUTPUT AND RESIDUE OF NUTRIENTS

Schouls, J." and G.O. Nijland 2)

" Department of Agronomy, and 2) Department of Ecological Agriculture, WAU, Haarweg 333, 6709 RZ Wageningen, The Netherlands.

When studying the issue whether in crop production intensification or extensification is advisable, the relations between input, output and residue of nutrients are of great relevance, as are markets and prices. In recent studies, a S-course of the output curve has been demon­ strated when various nutrients are increased proportionally (e.g. De Wit, 1992). In that case, rather high levels of nutrients are advisable thus minimizing residues. These results appear to follow from accepting the Mitscherlich model for the relation between amount of output and amount of nutrient.

However, we found a Michaelis-Menten curve of response of both uptake to input and yield to uptake, both single and in proportional combination, on theoretical and empirical basis as more appropriate (Nijland et al., 1996). As Figure 1demonstrates , it is clear and easy to distinguish - if represented reciprocally - the different patterns of the different lines repre­ senting the relations between input and output according to Mitscherlich, Liebscher (to be approached with a Michaelis-Menten relation) and Liebig. The highest productivity of a nu­ trient is in case of a Michaelis Menten relation established at zero input of external nutrients. With increasing input, marginal productivities always decrease.

The lowest residues may be expected when just producing with the internally available nutrients both from biological fixation and deposition. Assuming a Michaelis-Menten relation, residues per kg product will increase strongly at higher levels of (proportionally) applied nutrients. At low input level a nearly constant residue per kg product is found in many cases (data of Chaney, 1992), if yields and residues are almost proportional. In exceptional cases we observed decreasing residue per kg product at increasing nutrient input in the lower range of input, where apparently the greater size and activity of the root system, induced by applying more nutrients, utilized the available nutrients better. Besides, losses from large soil stocks will be relatively bigger than from small ones. Even in case of a linear relation between input and output, increasing absolute and relative residues are found when producing a certain amount of product with more nutrients of one kind per unit area.

From an economic viewpoint, one prefers the input level, at which the difference between output revenue and variable costs is maximal. This Gross Margin and the ecological productivity (output per kg internal + external input) do not have their maximum at the same level of input, neither in the Mitscherlich nor in the Michaelis-Menten model. Comparing both models, the discrepancy between ecological and economic optimum appears largest in the Michaelis-Menten model. Because of the low prices of nutrients in Western countries the highest economic productivity occurs at very high nutrient levels. Ecologically a low level is advisable. Thus a political consideration of this issue is necessary.

Relations between input, output and residue are different on different soils. In case of a surplus of area, the issue whether to produce intensively on a small area or extensively on a large area has yet wider dimensions (such as labour, food and nature). Our studies indicate that higher levels of nutrients are ecologically more feasible on the better soils than on the less fertile soils. Taking soils out of production will be rarely expedient, when aiming at the highest ecological productivity, since soils in Western Europe generally have a relative high internal availability of nutrients. However, other aspects as minimal total emission and maximal economic yield will generally be considered as important. Actually, all inputs as well as all outputs and secondary effects should be considered simultaneously. Session 2.3 597

MITSCHERLICH INVERSE

YIELD in ton ha J/ton per ha 10 10

0 kg N ha-' 100 0 l/kg N per ha 1

MICHAELIS-MENTEN INVERSE

100 0.0

LIEBIG INVERSE

100 0.00 0.05 Figure 1. The theoretical relation between output and input of nitrogen (left) at 4 levels of phosphor, according to Mitscherlich, Liebscher and Liebig, with (hypothetical) initial response coefficients (nitrogen: 200 kg/kg N; phosphor: 2000 kg/kg P); the relation between the inverses of the same variables (right). The numbers in the first graph refer to the amounts of Phosphor in kg per ha applied.

References Chaney, K., 1990. Journal of Agricultural Science, Cambridge. 114: 171-178. Nijland, CO., et al.,1996 . The relation between nutrient application, nutrient uptake, production and nutrient residues. Wageningen Agricultural University Press (submitted) Wit, CT. de, 1992. Agricultural Systems 40: 125-151. 598 Book of Abstracts 4th ESA-congress

FACTORS INFLUENCING CROP WATER USE EFFICIENCY

L.P. Simmonds,C.C . Daamen, C.J.Pilbeam

Department of Soil Science, The University of Reading, POBo x 233,Whiteknights , Reading, UK

Introduction In many areas of the world, the loss of water through direct evaporation from the soil surface (Es) is amajo r component of the water balance of cropped fields, and is often an important factor contributing to low water use efficiency (defined ascro p productivity per unit of water lost through évapotranspiration). Intensification of crop production (for example, using fertilisers, denser planting and improved varieties) in such environments has often resulted in increases in yield, with areductio n in Es often being presumed to beth e factor responsible for the increased water availability toplants .

There has been much recent progress in understanding the factors controlling evaporation from sparse vegetation (embodied in comprehensive Soil-Vegetation-Atmosphere Transfer models which incorporate soil water and heat dynamics, plant hydraulics and aerodynamic transfer processes within plant canopies). The objective of this paper is to apply such understanding to identify the mechanisms by which improved crop management might reduce Es, and to evaluate the magnitude of the potential for reducing Es in agive n environment. The analysis presented here isbase d on the use of the 'SWEAT' SVAT model (Daamen and Simmonds, 1996).

Methods and Results Examples based on field measurements of Es using microlysimetry (following the criteria setou t by Daamen etal, 1993) in Kenya, Niger, Syria and theU K arepresente d to illustrate howi n different environments, the presence of acro p can reduce Es via the following mechanisms: • shading by foliage reducing the radiation penetrating toth e soil surface • foliage influencing the aerodynamic transfer of vapour away from the soil surface • root water uptake drying the near-surface, thereby reducing the water supply for Es Inparticular , it is shown that in environments with alarg e evaporative demand, infrequent rainfall, and soils of low unsaturated hydraulic conductivity (e.g. sandy soils in Niger) there isa remarkably small reduction inE s (c. 10%) in intensively cropped soils in comparison with bare soils. This reduction is attributable primarily to water uptake by roots rather than by thedirec t effect of the canopy on evaporation from the soil surface. Atth e other extreme (e.g. winter rainfall, Mediterranean climates) areenvironment s with frequent rain and low evaporative demand during the rainy season. In such environments, especially with conductive soils, shading by foliage can cause asubstantia l reduction inE s.

A simple soil evaporation model ispresente d which can beuse d with readily-available daily synoptic meteorological data to assess, for agive n environment, the extent to which changing the characteristics of acro p (leaf area index, canopy height and root distribution) influences Es.Th e model isi n the form of aModifie d Two-Stage Evaporation Model (MOTSEM), based ontha t described by Daamen, Simmonds and Sivakumar (1995).Durin g the 'demand-limited' phase when the surface is wet, Esoccur s at apotentia l rate that is derived from the Penman equation, where the radiation and aerodynamic terms of the Penman equation are influenced independently by the crop canopy. During the 'supply-limited' phase,E s iscalculate d from knowledge of the soil desorptivity (which can beestimate d from measurements of Es from bare soil, orels e Session2. 3 599 estimated from soil texture), with account taken of the extent to which the surface layers are dried by root water uptake. Examples are given of typical ranges of values for the three crop coefficients that are required asmode l inputs.

An analysis of the measurements from Kenya, Niger and the UKusin g MOTSEM shows thatE s can contribute between 30%an d 90%o f thetota l evaporative loss from acroppe d field through a growing season. There isevidenc e of considerable variation between environments in the extent to which crop water use efficiency can be improved through reduction of Esb y improved crop management. There was agoo d correlation between the seasonal rainfall and the proportion of total evaporation that is transpiration. The relatively large contribution from Es in low rainfall environments is attributed mainly toth e shallower depth of wetting. In environments with similar rainfall, those with frequent, small rain events lose substantially more water through Es than when rain arrives in infrequent, largeevents .

Finally, SWEAT is used to examine the question of whether reduction in direct evaporation from the soil surface is offset, in part, by enhanced transpiration as aconsequenc e of localised advection processes driven by the soil surface becoming hotter. Examples (supported by measurements of sapflow ) demonstrate that this enhancement of transpiration occurs (asmuc h as 25%enhancemen t in the case of atal l millet crop in Niger with leaf area index of 0.5). However, the magnitude of the enhanced water loss through transpiration on auni t land area basis is generally very much smaller than the reduction inE s.

Conclusions It isshow n that environments differ widely in the extent to which direct evaporation from the soil surface can be reduced by the presence of vegetation, and that the mechanisms responsible for the reduction in Es also vary. Amode l is proposed that could form the basis of asimpl e classification scheme that takes account of the amount and distribution of rainfall, evaporative demand and soil type in order to identify environments where there is greatest scope for reducing direct evaporation from the soil surface though improved crop management practices.

References Daamen,C.C .e t al., 1993.Agricultura l andFores t Meteorology65:159-173 . Daamen, C.C. et al., 1995.Agricultura l Water Management 27:225-242. Daamen, C.C. et al., 1996.Wate r Resources Research. In Press (accepted 19/1/96). 600 Booko fAbstract s4t h ESA-congress

MODELING CROPN REQUIREMENTS : ACRITICA L ANALYSIS

C. O. Stockle1 and P.Debaeke 2

'Biological Systems Engineering Dept., Washington State University, Pullman, WA99164-6120 , USA 2INRA Station d'Agronomie, BP27, 31326Castane t Tolosan, France

Introduction Simulation models are increasingly used for prediction of crop production and environmental impact in response towate r availability andN fertilization . Thepredictio n of cropN requirements, both in terms of total requirement aswel l as itsdistributio n throughout the growing season is important.

Arevie w of approaches utilized to estimate crop Nrequirement s in several crop models was done. We selected four that wererepresentative : AFRCWheat2 (Porter, 1993),Dais y (Hansen et al., 1991),EPI C (Sharpley andWilliams , 1990),an d CropSyst (Stockle and Nelson, 1996). The mostcomplet e approaches include the definition of three characteristic plant N concentration curves: amaximu m (Nmax), acritica l (Ncrit),an d aminimu m (Nmin) concentration. Plant growth is not limited if plant concentrations are ato r aboveNcrit , while Nmax establishes the maximum crop Ndemand . Below Ncrit, plant growth is reduced, stopping completely whenN concentration reaches Nmin. Somemodel s (e.g.,EPI C andAFRCWheat2 ) do not include Nmax, limiting maximum Ndeman d toNcrit . This is unlikely toresul t inprope r simulations considering that asubstantia l amount of Nca nb e stored aboveNcrit .

Plant Nconcentratio n isno t constant but decreases with time, and sod oth e three concentration curves. To describe this process, some models decrease the curves as afunctio n of crop growth stage (AFRCWheat2), the fraction of the cycle (EPIC),o r asa functio n of thermal time (Daisy). Research has shown thatNcri t decreases with increasing plant mass according to an allometric equation (Salette and Lemaire, 1981,Greenwoo d et al., 1990),usuall y referred to asth e growth dilution law. This approach hasbee n tested with field data and shown able to discriminate between well-supplied andN-deficien t crops (e.g.,Juste s et al., 1994,Plénet , 1995). Furthermore, single allometric equations for C3an d C4crops ,respectivel y havebee n proposed (Greenwood et al., 1990). Similar equation forms mayb e used for Nmax and Nmin. A generic implementation based onthi sconcep t hasbee n recently introduced to the CropSyst model (Stockle and Nelson, 1996).

Methods Experimental data collected for wheat atth e INRAstatio n in Auzeville, France was used to compare the four modeling approaches. This included plant Nconcentration , biomass, thermal time, and growth stages throughout the growing season, and final biomass,N content , and yield atharves t of wheat plots grown with different levels of available N. Data were analyzed to separate N-limited and non-limited plots.

Results Figure 1 compares theperformanc e of the four models.Th e method in AFRCWheat2 tends to discriminate well (Ncritcurv eproperl y separating N-limited from non-limited data points),wit hproblem s between growth stages 30an d40 %an d towards the end of thecycle . Performance of theEPI C model is less acceptable.Bot h models share the sameproble m of the Session 2.3 601 lack of Nmax definition. The Daisy model includes the three characteristic curves,bu t its performance is thewors t of all methods tested. The method based on biomass increase (CropSyst) was able tobette r represent crop Nrequirements . This method is only valid until flowering, requiring specification of ending values for the three curves at maturity, which are approached linearly after flowering.

Conclusion The use of thegrowt h dilution concept provides asoli dbas et odetermin e characteristic plantN concentration curves throughout the growth cycle,whic h are fundamental for proper simulation of crop Ndeman d and crop response to limited nitrogen.

20 40 60 80 100 500 1000 1500 Growth stages(% ) Degree Days

CropSyst £ <»

1 il D *

•"•^.fia?.

0 0.2 0.4 0.6 0.8 0 3 6 9 Fractiono fth ecycl e Aboveground biomass (Mg/ha)

Figure 1.-Compariso n of four models to estimate characteristic plantN concentratio n curves withwhea t data from N-limited andnon-limite d plots atAuzeville ,Franc e (Symbols:ope n =N limited, close =N no n limited;Lines :dashe d =Nmax , solid =Ncrit , dotted =Nmin) .

References Greenwood, D.J. et al., 1990.Annal s of Botany 66:425-436 . Hansen, S.e t al., 1991. Fertilizer Research 27:245-259 . Justes,E . et al., 1994.Annal s ofBotan y 74:397-407 . Plénet, D., 1995.Doctora l Thesis,Académi e deNancy-Metz , Porter, J.R., 1993.Europea n Journal of Agronomy 2:69-82 . Salette, J. and G.Lemaire , 1981. CRAcad . Sei. Paris 292,267-281 , Institut National Polytechnique deLorraine ,France . Sharpley, A.N. and J.R. Williams, 1990.USD A Tech. Bull.No .1768 . Stockle, CO. and R. Nelson, 1996.Biologica l Systems.Engineerin g Dept., Washington State University, Pullman, WA. 602 Book of Abstracts 4th ESA-congress

RELATIONSHIP BETWEEN N-CONCENTRATIONAN D GROWTH IN SWEET PEPPER

F. Tei, A. Onofri, M Guiducci

Institute ofAgronom y -Universit y ofPerugia , Borgo XXgiugn o 74, 06121 Perugia, Italy

Introduction Crop growth rate isreduce d when nitrogen concentration within plant dropsbelo w a certain threshold level,tha t isdefine d asth e critical nitrogen concentration. This concentration decreases asplan t biomassincreases , following a similar relationship for several C3crop s (Greenwood et al., 1990). ConsideringN-deficien t plants (i.e.wit h nitrogen concentrations lower thanth e critical levels), relativegrowt h rates havebee n found to belinearl y related to N concentration within plant (Âgren, 1985; Lemaire et al., 1990). Theabov e mentioned relationships have been studied for several crops,bu t notye t for sweetpepper , that presents someparticula r characteristics, such aslo wplan t density, widero w spacing, lowlea farea , early development and high sink strength of fruits. The aimo fthi spape r wast o studyth e relationship between %N and growth infield grow n sweet pepper.

Methods Field experiments on sweet pepper, cvHeldor , were carried out in 1991an d 1992a t Perugia (Italy, 43°N , 165m a.s.1.) .I n each experiment arang e ofN fertiliser levels (0t o 300 kg ha-1) was applied and plant dryweigh t (leaves, stemsan d fruits, excludingfibrous roots ) wasweekl y recorded duringth egrowt h cycle,unti l thefirst commercia l fruit harvest. The nitrogen content (%N inplan t drymatter ) was determined by aKjeldah l method. Aspropose d by Greenwood et al. (1991), datawer euse d to calculate the growth rate coefficient KX(F) and, afterwards, the relativegrowt h rate, as:RGR(F,t) =K X(F) I [x+W(F,t)] whereRGR(Fj) isth e relativegrowt h rate, dependent onfertilise r level(F) an dtim e (t,hereb y expressed interm s of accumulated degree days,wit h T|,ase = 12°C),K X(F) isth e growth rate coefficient (constant for a substantial period ofgrowt h at each level ofN fertiliser), x isa constant (set at 1,b ypreliminar y analysis) and W(F,t) isplan t dryweigh t int ha"1. Theminimu mleve lo fN fertiliser maximizingth egrowt h rate coefficient wasidentified ; the nitrogen contents recorded for thisfertilise r level atth e different harvesting timeswer e regarded asth e critical nitrogen contents for sweet pepper. Conversely, plantsgrow n at fertiliser levels lower thanth e above mentioned were assumed asN-deficien t plants. For these plants, the relationship between plant growth and %Nwa s studied byregressio n analysis.

Results Inbot h years, the critical %Nwa sfoun d to be at afertilisatio n level of 150k gN ha"1 (datano t reported);therefore , fertilisation levelsu p to 75k gN ha-1 were considered insufficient to meet crop demand (N-deficient crop). Inthi s case,th erelationshi p between %N and relative growth rates (Fig.1)wa s linear inbot h years (R2 = 0.963i n 1991 and 0.883 in 1992)wit h curves showing similar slopes (0.00333 ± 0.00017 in 1991an d 0.00305 ± 0.00035 in 1991)bu t different intercepts (about 1.5 %N in 1991an d about 2.0 %N in 1992).I t hast o be mentioned that the intercept representsth eminimu m% N atwhic hgrowt hjus t takesplace ;th evalue s obtained for sweet pepper seemed to be highertha nthos e observed for other crops (Greenwood et al., 1991). Duet o the different intercepts, for agive n% N inth ewhol e plant,RGR valueswer e higher inth e first thani nth e second year. Thisca nb e explained by differences intransplantin g dates (16 June 1991 and 25Ma y 1992) and, subsequently, in environmental conditionstha t promoted ahighe r drymatte r and nitrogen allocation inth e leaves in 1991, with respect to 1992, as shown inFigur e 2. Asa result , in 1991, Session 2.3 603 at the last samplingcit e the axp shewedhi^ie r IÄE (2.4v s 1.3, cna«3ge), Hgt. irtsaaçtiai (70% vs 48% of inxmirgladiari m enauaage) , radiatimus e eÊEkdsxy (1.9 vs 1.5 gd wMJ" 1) and, as aconsequence , higher dry matter yield (5.9v s2.6 1ha" 1). WhenN allocation was taken into account and RGRs were plotted against theNi eaves/Nwholeplan tratio , the relationship proved to follow the samelinea r pattern inbot h years (Fig.3) , accounting for agrea t part of data variability (R2 = 0.928). This seemst o indicatetha t when storage organs (such asfruits ) compete with leaves for N allocation, %N cannot adequately explain variations inRGRs .

0.012 1.0 • 1991 — 0.010 o 1992 0.8 "3 0.008 a: J13 0.6 Ü 0.006 PS 0.4 0.004 t. 0.2 0.002 Z 0.000 , i 0.0 2 3 4 0.0 0.2 0.4 0.6 0.8 %N %N Nieaves/ Nwhol e Figure 1.Linea r relationship Figure 2. Linear relationship Figure 3.Linea r relationship between %N (whole plant) between %N(whol eplant )an d betweenth e ratioNi eaves / andRG R inN-deficien t the ratioNi eaves/N wholeplan t Nwholeplan tan dRG R inN - sweet pepper in 1991an d inN-deficien t sweet pepperi n deficient sweet pepper. 1992. 1991 and 1992. The relationships between critical %N and plant dryweigh t for 1991an d 1992ar e presented in Figure 4. In 1991th e relationship proved to follow rather closely the one proposed by Greenwood et al. (1990) for other C3crops . Otherwise, in 1992th e observed critical %N levelswer e sensibly lowertha nthos e calculated byth e above mentioned authors, duet o the lowerN allocation onleaves .

Conclusions Alsoi nswee t pepper, therelationshi p between %N and £ RGRs proved to belinea r inN-deficien t plants. However, factors related to environmental conditions or cropping technique can promote changes on allocation pattern of N, that mayi ntur n alterth e relationship between %Nan d 1 RGR. For thisreason , thegenera l relationship between 0 12 3 4 5 6 critical %N and plant biomass proposed by Greenwood et 7 8 al(1990 )fo r other C3crop s mayno t always hold for Dry weight ( t ha' ) sweet pepper. Figure4 .Relationshi p between plant Furthermore,th e minimum% Nfo r growth seemedt o be dryweigh t and critical %N observed rather high inswee t pepper, with respect to other C3 for sweet pepper in 1991an d 1992, crops andtende d to increase asth eN allocated to leaves incompariso n with that proposed by decreased. Greenwood et al. (1990). References Âgren, G.I., 1985.Physiologi a Plantarum 64: 17-28. Greenwood, D.J. et al., 1990.Annal so fBotan y 66: 425-431. Greenwood, D.J. et al., 1991.Annal so fBotan y 67: 181-190. Lemaire, G. et al., 1990.Firs t CongressESA ,Paris , 1 O05 . 604 Book of Abstracts 4th ESA-congress

EFFECT OF MYCORRHIZAL INFECTION ON PHOTOSYNTHETIC METABOLISM A.J . Valentine, B.A . Osborne, D.T . Mitchell Department of Botany,Universit y College Dublin, Belfield, Dublin 4,Ireland . Introduction Although theeffect s of mycorrhizal infection on nutrient acquisition byroot sar e well-documented (Marschner, 1995), less is understood about their consequences for photosynthesis by shoot tissues. Previous studies have indicated that mycorrhizal stimulation of photosynthesis can either be dependent orindependen t of any improvement in the nutrient statuso f shoot tissues (Wrighte t al., 1995;Fa y et al., 1996).I n order to examine this question in more detail we have investigated the effect of arbuscular mycorrhizal infection on photosynthesis of cucumber grown ata rang eo f irradiances.

Methods Plants of cucumber (Cucumissativus L. var. Telegraph Improved) were grown in sterilised sand at a phosphorus supply (0.13 mol m~3) shown in earlier experiments to be associated with a stimulation of the maximum rate of photosynthesis under ambient irradiances. The material was inoculated with live (+AM) or autoclaved (-AM) Glomus mosseae (strain YV, Microbio Ltd., UK) and grown atirradiance s of 10,45, 75an d 100%o f the ambient lightlevel . Measurementso f the response of photosynthesis to instantaneous variations in irradiance or intercellular CO2 concentration were made at a temperature of 25°C and a vapour pressure deficit of ~1.5kPa on intact leaves using a CIRAS infra-red gas analyser (PP Systems, Hoddeston, UK) and a thermostatted leaf chamber. Leaf Nwa s determined using amodifie d microkjeldahl technique and P was analysed on sulphuric acid digests by the method of Murphy and Riley (1962).Th e extent of mycorrhizal infection and the proportion of different mycorrhizal components (vesicles, arbuscules and hyphae) peruni troo t length wasestimate d using amodifie d lineintersec t technique (Brundrett, etal, 1994).

45%

D r OOO O 100%n p o

1 1.5 Irradiance (mmol m~2 s~l)

Figure 1:Th e photosynthetic response to irradiance (X=400-700nm) by cucumber (Cucumis sativus L. var. Telegraph Improved) plants grown at 0.13 mol m~3 phosphorus and varying percentages (10%, 45%, 75%, 100%) of ambient light. At each light level, the plants were inoculated with eitherliv e (•) ordea d (O)arbsucula r mycorrhizal inoculum. Session 2.3 605

N g vesicles 60- 1O • arbuscules O e 40- H hyphae c C e O 20- a. • • • e o 0- 1 i 1u D L D Ly D L Du 10 45 75 100 Treatment Figure 2:Percentag e of mycorrhizal components present inth eroo ttissu e ofcucumbe rplants .Th e host cucumbers were grown at 0.13 mol m~3phosphoru s and varying degrees (10%,45% , 75% 100%)o f ambient light. Ateac h light level,th e plants were inoculated with either live (L)o rdea d (D)arbsucula r mycorrhizal inoculum. Mycorrhizal enhancement of the maximum rate of photosynthesis (Pm) was dependent on irradiance with a greater enhancement at the higher growth light levels, although this was not dependent on leaf No rP level s (Fig. 1).Examinatio n of the underlying factors responsible for the stimulation of Pm indicated that this was aconsequenc e of both an increase inelectro n transport activity and carboxylation capacity. Whilst consistently higher (30-60%) levels of infection were found in+A M plants thiswa sno t directly related toth eexten t of enhancement ofP m. +AMplant s grown at 10, 45 and 75%o f ambient irradiance had similar total levels of infection (Fig. 2), but different values for Pm (Fig. 1). Of the mycorrhizal components examined, the proportion of arbuscules, correlated best with the degree of enhancement of Pm (Fig. 2,y=0.353 x +3.80 1; r^= 0.906, P< 0.05). Conclusions This work confirms that mycorrhizal infection can have asignifican t stimulatory effect on Pm. As the enhancement of Pm was independent of leaf N or P or the total level of infection, but dependent on irradiance, suggests that this is due to a'sink ' effect, which isrelate d specifically to the arbuscular mycorrhizal component. At amechanisti c level the enhancement of Pm caused by theremova l ofend-produc t limitations tophotosynthesi s appearst ooperat e viaadjustment s inbot h electron transport andcarboxylatio n reactions. References Fay, P. et al., 1996. New Phytologist (in press). Brundrett, et al., 1994.Practica l methods in mycorrhizal research. Mycologue Publication, Guelph, Ontario. Marschner, H. 1995.Minera l nutrition of higher plants. Academic Press,London , 889pp . Murphy, J. and Riley, J. P., 1962. Analytico Chimica Acta 27: 31-36. Wright, D. P.e t al., 1995.Aspect s of Applied Biology 42:109-115 . 606 Booko fAbstract s4t h ESA-congress

EFFECTS OF DEFOLIATION ON GROWTH OF CAULIFLOWER

R. Van denBoogaard , K. Thorup-Kristensen

Department ofFrui t and Vegetables, Danish Institute ofPlan t and Soil Science, Kristinebjerg- vej 6, DK 5792 Ârslev,Denmar k

Introduction To develop cropping systemswher evegetable s aregrow n with areduce d amount ofchemi ­ cals,w enee d knowledge onthei r growth under sub-optimal conditions.Model s can help to integrate the different aspects ofcro pgrowt h in such systems, and can helpt o improve crop protection strategies. Present plant growth models generally describegrowt h under optimal conditions. However, models are needed that can appropriately describe plant growth under sub-optimal conditions. Pests and diseaseswil laffec t aplant' s leafare aan d bytha t itsgrowth . Therefore, we have studied the effect ongrowth , yield and development oflea fremova l at different times, and ofremova l of old (source) oryoun g (sink)leave s in cauliflower.

Methods Plants were grown on a sandyloa m at ÂrslevResearc h Centre inDenmar k (55°18TST,10°27'E). Row and plant spacing were 0.5 man d 0.6 m, respectively. Pest and disease control, fertilisa­ tion and irrigation were according to guidelines ofnorma l production. Leaf area was measured using aDelta- T area meter. Weightswer e determined before and after oven-drying at 80°C for 24 hours. Total-N, nitrate-N, sugar and starch concentrations were measured onth e dry material.

Results Thetabl e shows anexampl e ofth e effect of defoliation ongrowt h and yield. When leaf area was reduced with up to ca. 70 %,final cur d weight ofth e defoliated plants was only reduced byu p to ca. 30%.Defoliatio n duringth e curd induction phase generally affected curd yield lesstha n defoliation duringth e curd growth phase.B y weekly samplings after defoliation, it was found that after the leafdamag eth e loss oflea fare a was compensated by increased leaf growth, but that this was atth e cost of reduced stem growth. The drymatte r percentage ofth e plant, and the sugar and starch concentrations inmidrib s and stems of damaged plants were reduced, showing that probably remobilisation of stored assimilates from midribs and stemst o leaves took place. Although leaf area per unit plant weight was much reduced inth e damaged plants, the relativegrowt h rate of damaged plants was similar to that of control plants. This showed that thene t assimilation rate ofth e remaining leaf area was increased. The results also showed that curd growth was delayed after defoliation, and thus alonge r growing period diminished curd yield losses indefoliate d plants. Session 2.3 607

Table 1. Growth of cauliflower cultivar Plana in afiel d experiment in 1995.Plant s were partially defoliated at four different times duringgrowth . The length ofth e growing period was 69 days.Plantin g date was 5Jul y andfinal harves t was at 12 September.

Defoliation Harvest Time Leaf Growth LeafAre a Leaf Plant Curd Type Stage Before After Reduction Area DW DW Reduction 2 2 (days) (m ) (m*) (%) (m ) (g) (g) (%)

Control 1.88 272 84 20 6 Oldest Curd Induction 0.18 -» 0.05 72% 2.00 248 68 19% 36 10Oldes t Curd growth 0.96 -* 0.36 63% 1.61 209 63 25% 47 10Oldes t Curd growth 1.57 -» 0.65 58% 1.41 220 74 12% 55 11Oldes t Curd growth 2.17 -> 1.06 51% 1.20 198 59 30%

Conclusions An increased rate oflea fgrowt h and areductio n in stem growth after defoliation, associated with remobilisation ofassimilate s stored in stems and midribs, compensate the loss oflea fare a in cauliflower. Due to this compensation and the increased length ofth e curd growth phase, only smallreduction s inyiel d compared to theleve l oflea fdamag ewer e found. Effects ofdefoliatio n mayb e different under other climatic conditions. Development of cauliflower mainly depends ontemperature . High temperatures during curd induction willlea d to alon g curd induction phase and a large number ofleave sforme d (Grevsen and Olesen 1994).Du et o hightemperature s duringth e '94 and '95 seasons, plants developed largelea f areas. Therefore, leafare a mayno t havebee n limiting growth, despite removal ofmor etha n half ofth e leafarea . In '96 wewil l conduct experiments from early spring onwards, to investigateth e effects ofdamag e at alowe r temperature and lower leafarea . The results ofth e present and further studies, showing the sensitivity ofyiel d to defoliation at different times during crop development and theunderlyin g physiological processes, willb e used in amode l describing cauliflower growth and development, which willb e linked with pest and disease models. Thismode l can form thebasi s of decision support systems for integrated pest management invegetables . Themode l willtak e account ofth e changed physiology and development of damaged plants, such asa n increase inth e duration ofth e growing period and remobilisation of stored assimilates.

References K. Grevsen and JE. Olesen 1994Journa l ofHorticultura l Science 69,755-766 . 608 Book of Abstracts 4th ESA-congress

EFFECT OF NITROGEN SUPPLY ON LEAF GROWTH AND PHOTOSYNTHETIC CAPACITY IN POTATO

P.E.L. van der Putten1, G. Posca1'2, J. Vos

Department of Agronomy, WAU, Haarweg 333, 6709 RZ Wageningen, The Netherlands Università della Basilicata, Potenza, Italy

Introduction Nitrogen supply primarily affects the rate of leaf expansion and the total number of leaves in potato (Solanum tuberosum L.). The photosynthetic capacity, Pmax, measured at saturating irradiance, often shows a direct relation with the concentration of nitrogen in leaf dry matter (Marshall and Vos, 1991). However, at low levels of irradiance, there is no association between the rate of photosynthesis on the nitrogen concentration. It is not efficient for a plant to keep nitrogen in weakly illuminated leaves. Hirose and Werger (1987) found that (re)allocation of nitrogen in the plant canopy is such that the distribution is often close to the one optimal for maximal production. Mutual shading is more severe in nitrogen-rich crops than in nitrogen-deficient crops. The hypothesis is that this influences life spans of leaves and nitrogen (re)allocation. Often, life spans in N-rich crops are shorter than in N-deficient crops. We examine in experiments the effect of the level of irradiance (or actually: shade) on (i) the change with time in Pmax and nitrogen concentration of individual leaves, and (ii) the allocation of carbon and nitrogen in the plant. Nitrogen supply itself was included as an experimental factor. In two experiments (to be reported elsewhere) we observed that Pmax of leaves was lower in the treatment with non-limiting nitrogen supply than for a moderate rate of N supply. Yet, the high-N plants had larger leaves and grew faster than the low-N plants (spaced plants). The objective of the experiment reported here was to analyze leaf growth and Pmax for a wide range of N supply. The particular interest was to understand under which conditions decline in Pmax can occur for increase in N supply.

Methods Seed potatoes were planted on June 8, 1995 in sand in 20 litre pots. The greenhouse was kept at 18/12 °C day/night (12/12 h). Plants were spaced and put in six randomized blocks. Treatments were five levels of nitrogen supply (Nl - N5). Nutrients were supplied every 10 days, starting at one week after emergence. Treatments Nl - N5 received 1, 2, 4, 6 and 8 g nitrogen per pot, respectively. Changes in leaf length and maximum width were recorded in situ for main stem leaf numbers 4, 6, 8 and 10 (numbers counted acropetally). Leaf areas (A; cm ) were calculated from recordings of leaf length (L; cm) (from the stem till tip of terminal leaflet) and width (W; cm) using: A = 0.45 LW (r2 = 0.99; SE = 0.006). Leaf area growth was fitted to the logistic equation: A = c/ (1 + exp("b (x •m)) ) (Eqn 1), where x is leaf age since appearance (days), c is the maximum leaf area (asymptote; cm2), and b and m parameters. Fits generally showed r values of 0.99. Effects of N supply were evaluated by ANOVA on the values of c and mr. (mr=b.c/4 = maximum expansion rate). Photosynthesis rates were measured using ADC portable equipment. Recordings were made for main stem leaves 8 and 10 on 31, 38, and 45 days after emergence (DAE). Irradiance in the cuvette at the level of the leaf was 1200 uE m"2 s"1 (PAR).

Results Maximum leaf expansion rate and full-grown leaf size (Table 1) increased with nitrogen Session 2.3 609 supply, although the differences between N3 - N5 were not significant for each leaf layer. Nitrogen effects increased with leaf number. More than 90 per cent of the variation in maximum leaf sizes (c) was accounted for by variation in mr, implying that the expansion rate rather than the duration of expansion determined leaf size (cf. Vos and Biemond, 1992). Pmax declined Table 1. Effects of nitrogen supply on maximum, mature leaf area with leaf age from (cm ) obtained by fitting Eqn 1t o data on leaf expansion. Means ca 0.95 to 0.55 (within leaf numbers) followed by different letters are significantly mg C02 m'2 s"1. different (P <0.05) . Examining the data from both Leaf Nitrogen treatment leaf numbers, no number Nl N2 N3 N4 N5 consistent, statistically 4 156a 181ab 235bc 246c 232bc significant effects 6 154a 226b 282c 350d 375d were apparent of 8 166a 262b 284bc 33le d 380d nitrogen treatment 10 146a 229b 277bc 352d 310cd on Pmax and its change with time (Fig. 1). On 50 DAE, N content increased from 0.93 g plant"' i-n1 Nl to 4.35 g plant"1 in N5. Plant dry weight increased from 52 g in Nl to an average value of 110 g plant" for N3, N4 and N5. -1 „ ,___ „™ __-2_--U -a- N1 Pmax

N2

-°- N3

N4

N5

35 10 15 20 25 30 35

Time after leaf appearance (d) Time after leaf appearance (d) Figure 1. Pmax versus leaf age, (a) leaf number 8, (b) leaf number 10.

Conclusions 1. Up to a maximum in response, leaf sizes were larger for higher rates of nitrogen supply, primarily through increased leaf expansion rate with more nitrogen. 2. There were no systematic effects of nitrogen supply on Pmax. 3. The experiment offered no explanation for earlier observations of lower Pmax in leaves of plants with ample supply in nitrogen than for moderate levels of nitrogen supply.

References Hirose, T. and Werger, M.J.A., 1987. Oecologia 72:520-526. Marshall, B., and Vos, J., 1991. Annals of Botany 68: 33-39. Vos, J. and Biemond, H., 1992. Annals of Botany 70: 27-35. 610 Book of Abstracts 4th ESA-congress

GROUND COVER INVINEYARD S WITH GRASS AND LEGUME SPECIES IN PURE ANDMIXE D STANDS

M. Volterrani1, M. Gaetani1,N . Grossi' ,G . Pardini1, S.Miele 1, G. Scalabrelli2.

'Dipartimento diAgronomi a e Gestione dell'Agro-Ecosistema, University ofPisa , Italy. 2Dipartimento diColtivazion e eDifes a delle Specie Legnose, University ofPis aItaly .

Introduction Grass covers invineyard s are graduallybecomin g morewidesprea d inCentral-Norther n Italy. Thismanagemen t schemereduce s soilerosio n andlead st o anincreas e in soilorgani c matter, total nitrogen, water holding capacity and structure stability aswel la s adecreas e inbul k density (Morlat et al., 1993). Onth e other hand, grass-vine competition causes areductio n invin e vegetative growth andproductio n (Haynes, 1980;Lombar d et al., 1988). Byseedin g particular crops growers could achievemor etargete d resultstha nusin gth e spontaneous weed covers.Th e purpose ofthi sresearc hwa s to compare different vineyard soilmanagemen t techniques.

Methods Trialwa s carried out inRispescia , near Grosseto (Italy). 24differen t soilmanagemen t schemeswer e compared: - 3withou t seeding: straw mulching,tillage , spontaneous weed covers; - 7pur e grass stands -7 pur e legume stands Agrostisstolonifera L . "Carmen"(As) Lotuscorniculatus L. "S. Gabriele" (Lc) Bromuscatharticus Vahl "Cabro" (Be) Medicagolupolina L. (Ml) Dactylisglomerata L. "Dora" (Dg) Trifoliumfragiferum L. "Palestinese" (Tf) Festucaarundinacea Schreb. "Apache"(Fa) Trifolium repens L. "Tamar" (Tr) Festuca ovinaL . "Bornita"(Fo) Trifolium subterraneum L. "Clare" (TST) Festucarubra L . "Artist" (Fr) Trifolium subterraneum L. "Mount Barker"(Tsn) Loliumperenne L. "Ovation"(Lp) Trifolium subterraneum L "Dalkeith" (TSUI) - 1 mixed grass stand :L p "Bianca"(25%);Poapratensis "Mosa"(40%);F r "Commodore"(35%) - 2 mixed legume stands :Tr+Tsj; Ml+Tsj ; -4 mixed grasses andlegum e stands: Fa+Tsj; Fo+Tr; Fa+Lp+Tr+Tsj; Fa+Lp+Fo+Tr+Tsj+Ml. Seedingwa s carried out on20 thNovembe r 1994. Arandomize d block designwit h 4 replications was adopted. Theplot swer e mownthre etime st o aheigh t of7 cm .I n eachplot , area covered by the crops andweed swa srate d subjectively atfive differen t timesdurin g the year. In April 1995, height andfresh biomas sproductio nwer e measured. In Aprilan d October 1995, inmixe d stands thepercen t of each specieswa s determined. Atharvest , vineswer e evaluated for cane length and berryyield .

Results Duet o theparticularl y dryJune-Augus t period, theherbaceou s covers dried up even ifFo , Fa, Dg, Tr and Lcachieve d green ground cover over anare a ranging between 1%an d 7%. During the other months ofth e year spontaneouswee d covers showed amea n ground cover valueo f 73% (Tab.1). Amongth e seeded species,th e most successfully grass standswer e Be, Fa, Dgan d Lp, together withth e legume species Tr and above allTs . Inth e mixed grass stand Lpwa s found to bepredominan t (Tab.2).Th emixe d standTr+Ts iwa s composed almost exclusivelyo f TSTi n spring,bu t inth e fall abette r balancewa s achieved. Ml,F o or Fawher e absent or present ina minimalproportio n inth e mixed stands.Th emixe d stands of grassesan dlegum e species showed a marked predominance ofth elatter , while Lpwa s found to beth e most competitive grass.Fres h biomasswa sparticularl y elevated in TST, the4 and 6cro p mixed stands and TSTT,wit hvalue s ranging between 11.7an d 18.6k g m"2. Weed coverfresh biomas s also exceeded 10k gm~2 . Session 2.3 611

Greatest height wasrecorde d inth e TST, Bean dwee d cover treatments, withvalue s closet o 25 cm. Amongth ewell-establishe d species, the lowest valueswer e found inF a (8 cm),L p( 9 cm) and inth e mixed grass stand (8 cm).Soi lmanagemen t techniques exerted a significant effect on vinevegetativ e growth andproduction . Overall competitionwit h ground cover causeda reduction incan e growth and yield. Thiswa sparticularl y evident inBe , Tr andFa ,wher e cane lengthwa s 26, 23 and 21 % lower respectively, ascompare d to tillage.Th epercen t decreasei n yieldrange d between 20 (Be) and 29%(Fa) .I n contrast, straw mulching stimulated cane growth (+70%) andberr y yield (+59%). Tab. 1 -Mea n Crop (C) and Weed (W) ground Tab. 2Mixe d stands composition (%) cover, Fresh Weight (FW), Height (H). inApri lan d October

(C) (W) (FW) (H) April 1995 z kgm" < •c m 75L p OPp 25F r Straw mulching 0 12 - - 4Tr 96 Ts! Tillage 0 23 - - Weed cover 73 0 10.2 25 0M1 100 TST As 11 53 1.0 2 5F a 95 TST Be 78 10 5.6 25 6Fo 94T r Fa 61 22 2.6 8 2F a 12 Lp 7Tr 79 TST Fr 21 54 2.7 7 lFa 15 Lp 3Fo 4Tr 77TsT0Ml Fo 18 48 0.6 4 Dg 71 14 1.8 14 Lp 79 12 3.5 9 Tf 36 33 1.3 11 Ml 20 47 2.4 4 Tsi 83 9 18.6 24 October 1995 Tsn 87 8 13.1 21 Ts III 62 24 5.1 21 88L p OPp 12 Fr Tr 61 17 6.8 14 Lc 37 34 2.1 7 34T r 66 Ts! Lp+Pp+Fr 71 16 5.3 8 0M1 100 TST Tr+TsT 79 10 7.7 25 2F a 98Tsj Ml+Tsj 76 11 8.6 26 4Fo 96T r Fa+Ts! 80 12 15.9 25 lFa 10 Lp 27T r 62Tsj Fo+Tr 55 18 4.5 14 lFa 15 Lp 0 Fo 28 Tr 56 0M1 Fa+Lp+Tr+TsT 78 11 15.0 20 TsT Fa+Lp+Fo+Tr+Ts r+M178 12 11.7 19 LSD (PO.05) 15 11 4.8

Conclusions Duringth efirst tria lyea r the most successfully established specieswer e Ts, Tr, Lp, Be, Dg and Fa.Mixe d standsdi dno t lead to greater ground cover as compared to pure stands.Th e grasses species showed lower height and lower biomassproduction . Vinesi ncompetitio nwit h ground cover crops showed decreased yield (asmuc h as 29%lowe r as compared to tillage),wherea s mulchingwa s found to enhancevegetativ e growth andyield .

References Haynes, R.J., 1980. Agro-Ecosystems, 6:3-32. Lombard, P. et al., 1988. Proc. 2nd International Cool Climate Viticulture and Oenology Symposium, Auckland, New Zealand: 152-155. Morlat, R. et al., 1993.Progrè s Agricole et Viticole ,110, 19:406-410 . 612 Book of Abstracts 4th ESA-congress

YIELD OF SUGAR BEET USING ALTERNATIVES FOR FARM YARD MANURE

M. Wesotowski, M. Jedruszczak

Department Soil and Plant Cultivation, Agricultural University, 20-250 Lublin, Akademicka13 , Poland

Introduction Biological properties of root crops (root s isth eyiel d which wastake n away from the soil )an d technology ofthei r cultivation impoverish the reserves of soil organic matter (Fotyma, 1988). This impliesth e need to supplement it inth e from ofmanures . SinceFar m Yard Manure (FYM) production islimited , substitutes which could replaceFY M in field management are in demand. Sofar , experiments have proved that properly prepared cereal straw or green manure from other plants, especially ofleguminou s crops, canreplac eFY Mwithou t detrimental effects to the humus management of soil and itsphysica l and chemical properties (Ceglarek et al., 1985;Fotyma , 1988; Gruczek, 1994;Pawlowsk i et al,1988;Pawlowsk i et al., 1991) The response of sugar beet - traditionally planted with FYMi nPoland - to the manuringb yusin g cereal straw and stubble catch crops, asth e substitutes ofFY Mwa s investigated.

Methods Thefiel d experiment was conducted in CzeslawiceExperimenta l Station (middle-east Poland) according to arandomize d complete blocks design method infou r replications in 1992-1993. The manuring methods were thetreatment s ofth e experiment.The y were: A.NP K (in kg ha~l, N= 1 1 140,P 2O5=90, K.2O=180);B .Farmyar d manure (30t ha" ) +NPK ; C. Cereal straw (9t ha" ) + NPK; D. Cereal straw (9t ha"1) + 1%o fN b y straw weight +NPK ; E. Catch crop I,field bea n + field pea (2.11ha" l on drybasis) ;F . Catch crop II, white mustard (2.2 Mg ha~l on drybasis).Th e mineral fertilizers were applied in spring, halfo fth eN rateduring seedbed preparation and another one after thinning of sugarbeet . The dose ofth e fertilizers wasth e samei n alltreatments . Sugar beet wasgrow n after cereal crops. The experiment was performed on Orthic Luvisol derived from loess. The soil has neutral reaction and isrelativel y rich inP ,K , Mg and humus (moretha n 2%) and isfre e of sugar beet-root eelworms.Mea nyearl y precipitations and airtemperatur e were 530 mman d 7.3°C, respectively. Thecorrespondin g values for the growing season (IV-X) are404m m and 13.2°C.

Results Results are presented inTabl e 1 and2 .

Table 1 Yield of roots and leaves and saccharinity of sugar beet Kind of manure Yield in t per ha Saccharinity roots leaves conversional (%) sugar

A.Without manure * 79.8 44.3 15.9 19.9 B. Farmyard manure 85.2 52.4 16.3 19.1 C. Straw 77.6 45.0 15.0 19.4 D. Straw + 1%N 80.6 48.4 15.6 19.4 E. Catch crop I 80.5 48.9 15.8 19.6 F. Catch crop II 84.2 48.0 16.5 19.6 *NPK only Session2. 3 613

Although the differences in sugar beet parameters among the experimental treatments were not statistically significant (acc.Tukey) there were some clear tendences. The highest yield of sugar beet roots being 85.2 t ha'1 was obtained from the plots with application ofFY M (B) (Tablel). Only slightly lower yield wasfoun d intreatmen t with ploughing under white mustard (F) where sugar beet yield was reduced only by 1.5% relative to plots with FYM. The yieldsfro m plotswit h other manures were much lower. The substitution ofFY Mb ycerea l straw (C,winter barley -1992 and winter wheat -1993) gaveth ewors t result. Thehighes t yield of sugar beet leaves equalled 52.3 t ha"l was obtained, aswit h roots, from the plots withFYM . Thisyiel d was reduced by 14 to 15% intreatment s without any manure (A) and with only straw (C) ( Tablel). The saccharinity of sugar beets,tha t isnoteworthy , wasalmos t inversely correlated withjoin t yield ofroot s and leaves. Finally, the lowest sugar content was recorded intreatmen t with FYM (B) and the highest one intha t without any manure (A).However , the conversional biological yield of sugar was the highest on FYM (B) and mustard (F)treatments .

Table 2 Fresh weigt of singleroo t and number ofnorma l and forked roots of sugar beet Kind of manure Mass of root Number of roots per 10 sq. m (g) normal forked

A. Without manure * 1300 56 6 B. Farmyard manure 1367 56 7 C. Straw 1195 59 6 D. Straw + 1% 1191 63 6 E. Catch crop I 1272 57 7 F. Catch crop II 1315 57 7 *NP K only

The mass of single root was the highest intreatment s with FYM (B) and white mustard asth e stubble catch crop (F), with equal numbers offorke d roots, unfortunately over 12%.Th e lowest values ofth e yield parameters were onth e plots with application of straw (C) and straw + 1% N (D), Table 2. Thus this indicates the productivity ofsuga r beet was principally dependent on the weight ofth e individual roots, sinceth e total number ofroot s per 10m~ 2 was similar inal l treatments.

Conclusions Two year studies revealed that sugar beet yield was not statistical significantly affected by manuring methods. However, thegree n masso fwhit e mustard (asa stubble catch crop) canb e the best alternative manuret o the FYM ingrowin g of sugar beet on loess soil inth e midde-east Poland, free from sugar beet-root eelworms. Productivity of sugar beet on the soil enriched with thisgree n manure was similar to that intreatmen t withFYM ,whic h was relatively high. Sugar beet was least productive on the plotswit h ploughing under straw without addition ofN . In this caseth e yield was even lower than that from plots with mineral fertilization without any manure.

References Ceglarek, F. et al. 1985. Zeszyty Naukowe WSRP w Siedlcach, seriaRolnictw o 5:23-33. Fotyma, M. 1988. Zeszyty Problemowe Postçpow Nauk Rolniczych 311: 205-215. Gruczek, T. 1994. Fragmenta Agronomica 2:72-82. Pawtowski, F. et al. 1998.Zeszyt y Problemowe Postçpow Nauk Rolniczych 331: 217-226. Pawlowski F. et al. 1991.Material y Vseminariu m ptodozmianowego. Cz. II. ART 01sztyn:116- 119. 614 Book of Abstracts 4th ESA-congress

EFFECTS OF FOLIAR FERTILIZATION WITH NITROGEN AND MICROELEMENTS ON SEEDYIEL D OF PEAS

W.Zioiek, B.Kulig

Department of Crop Production, Agricultural University, Al. Mickiewicza 21, 31-120 Krakow, Poland

Introduction Theissu e ofusin g increased rates of nitrogen in leguminous crops isquit e controversial. Iti s thought that they limit fixation of the atmospheric nitrogen (Glazewski, 1975; Jasiiîska et al., 1983) but newer research indicates there isusefulnes s in applying higher nitrogen rates for the new, high yielding cultivars (Wojcieska et al., 1993).Nitroge n can beuse d for foliar spray ina composition with microelements before plants startflowering (Pode , 1983;Rhoden , 1983) The research confirmed the positive influence of such treatment on the seed yield, protein content, and on the yield structure elements ofpea s (Ziólek et al., 1996).

Methods In theyear s 1992-1994field experiment s made on degraded chernozem soilswer e carried out at theAgricultura l Experimental Station near Krakow. The investigation included: two peas cultivars - Ramir and Rubin differentiated ast o morphology and biology, threemulticomponen t microelement fertilizers (Agrosol-S, Insol-6, and Mikrovit-1), applied before plants start flowering, and nitrogen fertilization (O, 20, 40 kgN ha"1). The phosphorus and potassium 1 fertilization in the rates 100 kg P205 and 140k gK 20 ha" wa s applied before sowing ofth epea s An estimation of the effect of the investigated factors wasmad e on the base of seed yield and of the separate components ofyiel d structure (the number ofplant sbearin g seeds per unit ofarea , the number of seeds per plant, the mass of 1000seeds ) aswel l asth e content and yield of crude protein.

Results

Ramir Rubin Aoroao(-S InaoW MikroviM Cultivars

Figure 1.Th e effect of investigated factors on the yield ofseed s and crude protein ofpea s Session2. 3 615

The seed yield and protein analysis indicates that Rubin with the ordinary foliage wasth ebette r yielding cultivar (Figure 1).Ther e was interaction between the research years and the cultivars, dozes of nitrogen and microelements fertilizers. That gave evidence ofth e strong influence of climatic conditions on the peas yield. Increased level ofnitroge n fertilization up to 40 kg Nha" 1, with application of ahal f dose asfolia r sprayjointl y with the microelement fertilizers contributed to higher seed yield and to amuc h higher degree- to protein yield. Among the compared microfertilizers Mikrovit and Agrosol were themos t beneficial for the seed and protein yield of peas. There was interaction between the nitrogen dozes and theyiel d structure components (number of plantspe r m2, the mass of 1000 seeds and the number seeds per plant) in the investigated cultivars (Table 1).Increase d seed yield ofRubi n cultivar was associated with an increased number ofplant s m"2an d the mass of 1000seeds . The above features were strong effected with the fertilizer dose of 20k g Nha" 1an d 20+20 kg Nha" 1an d the microfertilizers Mikrovit and Insol. The number ofseed sfro m a plant was increased byth e higher dose of nitrogen used ahal f asfolia r spray plusMikrovit .

Table 1.Yiel d structure elements in relation to the investigated factors

Cultivars kg Nha" 1 Microelements fertilizers Mea- Ramir Rubin Control 20 20+20 Control Agrosol- Insol-6 Mikrovit- Features S 1

Mass of 1000 seeds 199 227 209 216 213 216 210 212 213 213 No. plantm" 2 56.1 61.2 58.3 59.7 57.9 58.6 58.7 58 59.3 58.6 No. seeds per plant 28.8 25.1 26.3 26.3 28.1 26.4 27.2 26.1 28.0 26.9

Conclusions The results ofth ethre e yearfield researc h on peas entitlet o draw thefollowin g conclusions: 1.Th e climatic conditions have crucial influence on peayields . 2. The pea cultivar of ordinary foliage ensured the highest yield of seeds and protein. 3. From allth e yield structure elements -th e number of plantsbearin g seeds and the mass of 1000 seeds- areth e major factors modifying peayield .

References Glazewski, S., 1975.Pamietni k Pulawski 64: 167-189. Jasihska, Z, 1983.Zeszyt y Naukowe ARw e Wroclawiu: 141, 125-133. Pode, W.D., 1983. Agronomy Journal 75: 195-200. Rhoden, E.G., 1983.Agronom y Journal 66: 173-178. Wojcieska, U. et al., 1993.Fragment a Agronomica 4: 175-176. Ziólek W. et al., 1996. Acta Agraria et Silvestria, series agraria XXXIV,60-72. Agroforestry Session 618 Book of Abstracts 4th ESA-congress

ALTERNATIVE AGRICULTURAL LAND USE WITH FAST GROWING TREES: SCIENTIFIC BASES ANDMODE L FOR EUROPEAN AGROFORESTRY

Daniel Auclair INRA- CIRAD,Unit é demodélisatio n desplantes , BP. 5035, 34032 Montpellier cedex 1, France

Introduction Aresearc h project oriented towards the development of extensive land-use systems, adapted to environment and market requirements, was initiated in 1993b y 18researc h and development institutesfrom si xEuropea n countries, with thefinancial hel p ofth eEuropea n Commission. It aims at diversifying the intensiveuse s ofagricultura l land with fast growing trees. They are planted atwid e spacings in order to produce high quality timber andt o allow agricultural activities. The specific objective ofth e research project ist o develop anintegrate d agroforestry modelling system devoted to simulation and decision-making for farmers, land-owners, andlan d managers. It includestechnica l aspects and integrates biological and economic data.

Methods Research isbein g developed ontw o mainaspect s (Figure 1): 1. A study of the technical and scientific bases of agroforestry systems management, conducted through aEuropea n network offield experiments : • sitecharacteristic s ofavailabl eagricultura l land andtre e growth potential, • choice oftre e genotype, tree establishment and management techniques, • impact of agroforestry techniques ontre e growth, form, and wood quality, • agriculturaltechnique s and rearing systems adapted to agroforestry, • interaction processes between tree—microclimate—crop orpasture—soil—animal . 2. The integration ofthes e data ina n agroforestry modelling system, aimed at predicting mean- term and long-term consequences ofth e adoption of agroforestry systems, at micro- and macro- economic levels.Biophysica l models havebee n developed for tree and agricultural components and their interactions, and linked to abiologically-base d economic modelling system. Social and environmental aspects are alsobein g investigated.

Practical results Agrea t number of scientific results (Auclair, 1996a)hav e been obtained through the individual tasks ofth eprojec t (arrows pointing outwards infigure 1) .The y havebee n summarized by Auclair (1996b). Themai n practical results areth e following: • Tree damage and mortality, duet o livestock or wind, result from inappropriate rearing systems (overstocking), misadapted tree- shelters, or increased sensitivity oftree s to wind duet o growth modifications withintree - shelters. • New tree-shelters havebee n designed, which improvetre e growth and form. Figure 1. General description of the project: • The impact ofweedin g is extremely important inth efirst years , and interactswit h individual tasks provide results (outwards) and water and nutrient cycling. data for the modelling tasks (inwards), which form the main core ofth e project. Agroforestry Session 619

• Growth ofa give n species within thetree-shelter s ishomogeneou s on each study site, buta t later stages the site/genotype interaction predominates and inter-tree variability becomesver y high. Diameter growth increases andH/ D ratio decreases during theyear s after emerging. • In most experimental plots, there isn o evidence oftota l annual pasture production being reduced byth e presence oftree s ofu pt oeigh t years old atdensitie s ofu pt o40 0 stems ha" . • Widetre e diameter growth increments produced on agroforestry plots havea negativ e effect on the quantity ofhear t wood, thus ontimbe r quality (ofPrunus avium). • Greater pasture growth was observed belowtree s than inth e open during dryweather . • Sheepgrazin g behaviour ismodifie d among treesa twid e spacing. Animals are attracted toth e trees, resulting ingreate r foot pressure inth e area immediately around them. Thiscoul d explain differences in soil compaction and tree survival. • Important parameters forth ebio-economi c model areth e duration ofth e intercrop orth ewidt h between tree plantation lines. Intensified agricultural management may significantly improve economic return, however important questions concerning competition between trees and crop remain insufficiently answered.

Modelling Afield-based bio-physica l model describing asilvopastora l system—ALWAYS—has been developed (Bergez and Msika, 1996, see figure 2).I tha sbee n linked to theBEAM economic module (Thomas etal. , 1994), and isno w undergoing the calibration and validation processes with the data obtained by other R&D institutes in other regions. BIOPHYSICAL SYSTEM MANAGEMENTSYSTEM S Figure 2. Summary of the bio-economic modelling system. Five compartments— two physical and threebiological—ar e in interaction inth e biophysical model. Management modifies the biophysical inputs and economic outputs.

Conclusions Thetechnica l results stress theimperativ e necessityt o usehig h quality plant material, adaptedt o the site,t ocontro l the herbaceous layer during tree establishment, andt opractis e pruning operations early. The modelling system developed hereha su pt ono wbee n used primarily as a research and education toolt ohel punderstan d processes driving complex land-use systems.I t also haspractica l applications forfarmer s and land managers. Extensions areunde r studyt o account forintroductio n ofagroforestr y practices atth e farm and landscapelevel .

References Auclair, D., (ed.) 1996a. Alternative agricultural land-use with fast growing trees. Third annual report, European Commission, D.G.VI. 471 p. Auclair, D., 1996b. InM . Etienne(ed. ) Temperate andMediterranea n silvopastoral systems of western Europe. INRA, Versailles, pp. 195-206. Bergez, J.É., 1996.I nM .Etienn e (ed.), op.cit., pp.207-220 . Thomase tal. , 1994. Agroforestry Forum 5(2):65-72 . 620 Booko fAbstract s4t h ESA-congress

THE POTENTIAL OFAGROFORESTR Y FOR SAHELIAN COUNTRIES

H. Breman1 &J.J . Kessler2

iDLO Institute for Agrobiology and Soil Fertility AB-DLO, PO Box 14,670 0 AAWageningen . 2Englaan 8, 6703 EW, Wageningen, the Netherlands

Introduction Withth e aim of optimizing resource use in semi-arid regions,th e surplusvalu e ofwood y plantsi n relation to water and nutrient availability hasbee n estimated. Chances for effective useo f agroforestry inth e Sahel havebee n identified and defined, taking farmers goal, soiltyp e and climate into account.

Methods A synthesis of moretha n 500 publications about woody plants in agroecosystems, with an emphasis onth e Sahel, hasbee n interpreted usingth ebasi c analysis of primary production in Sahelian countries (Penning de Vries &Djitèye , 1991). Taking light absorption bywood y plants into account, animpressio n hasbee n obtained about the maximum profit inrelatio n to water and nutrient availability for herbaceous neighbours (crops or rangeland). Asimulatio n model hasbee n elaborated, which will make it possiblet o do much more detailed estimations (Conijn, 1995). Fieldwork inth e southern Sahel ofMal i made it possiblet o test some ofth e conclusions about the surplusvalu e oftrees , on process level aswel l asth e overall influence on soil and vegetation concernes (Groot etal., i npress) .

Results Theresult s arepresente d inTable s 1an d 2.

Conclusions Though processes havebee n identified through which woody species improveth e availability of nutrients and water, it isno t easy for farmers to exploit this surplusvalue : - surplusvalu ei slo wwher e most needed, inmargina l areas; - woody species compete with crops or herb layer; - labour intensitivity ishigh . Nevertheless, thefollowin g chances for effective use of agroforestry havebee n identified: 1.Chance s for agroforestry in sylvopastoral systems - In case ofwate r limited production, woody cover ashig h aspossibl e for maximum sustainability (erosion control). - In case of nutrient limited production, woody cover 15-20%;unpalatable , homogeneously distributed trees, with high ratio trunk height / crown diameter, for optimum animal production. - For maximum animal production fodder banks ofhighl y palatable woody species at locations representing optimum growth conditions and high niche differentiation for woody plants. 2. Chances for agroforestry incroppin g systems - Windbreaks useful to improve crop establishment on sandy soilsi ndries t parts ofare a with nutrient limiting growth (Sahel), where superficial ground-water table isavailabl e - In more humid areas of semi-arid region (sudanian savannah), maximum crop production with woody cover of 15-20% ofhomogeneousl y distributed trees, with high ratio trunk height / crown diameter and with restricted exploitation. With fertiliser benefits higher than without! Agroforestry Session 621

3. Favourable economic conditions Agroforestry potential positively correlated with wood and fruit prices, negatively withwages . Subsidised agroforestry hast o be considered inth e upper course ofrive r basins, invie w ofth e buffering functions provided bywood y plants. Agroforestry reduces the necessity of subsidies on external inputs, invie w ofth e improved efficiency ofth eus e ofwate r and nutrients.

Table 1.Effect s ofwood y plants onwate r availability Process Sahelian zone savannah rainfall interception - - stem flow + ++ improved soil structure: less run-off* + +++ improved storage capacity soil* 0 + transpiration ofwood y plants - - micro-climatic changes* + + hydraulic lift * 0 0 uptakeb y deep roots + ++ 0 negligible effects; +, ++, +++ water availability increaseswit h 10-50, 50-100 or >100 mm yr*; - decreased water availability, *perhap s positive influence on herbaceous plants

Table2 . Effects ofwood y plants on nutrient availability Process Sahelian zone savannah redistribution lateral roots + ++ wind + + animals + + reductionof losses decreased wind erosion + + -water erosion 0-+ +-++ -leaching + +++ -fire + + recycling: -internal + ++ -external + ++ enrichment uptake byta p roots 0 + nitrogen fixation 0 + P-uptake through mycorrhiza 0 + 0 negligible effects; +, ++, +++ N increase 1-5, 5-10 or >10 kg ha-1 yr-1; Pincreas e 10%o fN increase

References Breman, H. &J.-J . Kessler, 1995.Wood y plants inagro-ecosystem s of semi-arid regions (witha n emphasis onth e sahelian countries). Advanced Series inAgricultura l Sciences 23. Springer- Verlag, Berlin. Conijn, J. G., 1995.Rapport s PSS no. 12.Proje t PSS. 1ER,Bamako , DAN-UAW, Wageningen, AB-DLO,Wageningen/Haren . Groot, J.JR., etal (in press). Utilisation des éléments nutritifs et de l'eaupa r Acacia seyale t Sclerocarya birrea. In: Breman, H. &K . Sissoko (Eds). Intensification agricole au Sahel, KARTHALA, Paris. 622 Book ofAbstract s 4th ESA-congress

SIMULATION OFLON G TERM CARBON DYNAMICS AND NITROGEN YIELD OF AN AGROFORESTRY SYSTEM INA SEMIARI D REGION

J.G Conijn

Department of Grassland and Vegetation Science, AB-DLO, PO Box 14, 6700 AAWageningen , The Netherlands

Introduction Intropica l areas, agroforestry systems areuse d because ofthei r potential to maintain soil organic matter at higher levels compared to monoculture cropping systems of annual species. Higher soil organic matter levelshav e apostiv e effect on plant production, especially inlo w input systems. Onth e other hand trees mayreduc eth eyiel d ofth eunderstore y species by competing for limiting resources. To investigate the relation between soil organic matter level and grass yield, a simulation study hasbee n carried out, inwhic h 4 grass production systems ina semi arid region are compared.

Methods Themode l RECAFS (Conijn, 1995) calculates the absorption of light, water and nitrogen bya n annual grass species and atre e species both inmonocultur e and ina mixed stand and the dry matter production ofbot h species as afunctio n ofth e absorbed resources. Asoi lwate r and asoi l nitrogen balance havebee n included. The model also simulatesth e dynamics of carbon and nitrogen inth e soil organic matter. Thetim e step ofintegratio n ison e day. Thetre e population, as described inth e model, ishomogenuousl y distributed. Themode l hasbee n parameterised with soil and plant data, characteristic for the semi arid region ofWes t Africa. Thefollowin g grass production systems have been simulated :agroforestr y without tree pruning (AF), agroforestry withtre e pruning(AFp) ,gras s monoculture with continuous cropping (GM) and grass monoculture with fallow years (GMf). Aperio d of 30year s hasbee n simulated, using actual weather data from Segou inMali . Total crown cover inbot h agroforestry systemsvarie s between 15an d 18% andth e leaf area index ofindividua l trees equals on average 4 and 1 rcfi- m~2 for unpruned and pruned trees, respectively. Inth e agroforestry systems onlygras s biomass is removed from thefield. I n case ofpruning , tree branches are lopped inth e dry season to keep the trees at constant size.Fallo w years havebee n simulated byincorporatin g grass biomass into the soil atth e end ofeac h third year. All production systems havebee n fertilised with inorganic nitrogen (50 kg ha"' yr"') and with other nutrients at unlimiting supply rates.

Results For both grass monoculture systemsth e amount of carbon inth e soil organic matter declines stronglyt o 38% (GM) and 65 % (GMf) ofit sinitia l level after 30years , whereas inth etw o agroforestry systemsth e initial level of carbon inth e soil organic matter canb e maintained during thisperio d (Figure 1).Th e amount ofnitroge n inth e harvested grass, produced inth e agroforestry systemwithou t tree pruning (AF) and averaged overth e entire simulation period, is almost half oftha tfrom th e monoculture systemwit h continuous cropping (GM) :4 2 and 72k g ha~l yr 1,respectivel y (Figure 2). Inbot h other production systems annual nitrogen yieldshav e intermediate values of 52(AFp ) and 51(GMf ) kg ha"' yr"V Agroforestry Session 623

Csom(kg/ha ) Nyiel d(kg/ha/yr ) 25000 GM 80

20000 60

15000 -- GMf AFp GMf 40 'AF 10000 GM 20 5000

1949 1959 1969 1979 -500 -400 -300 -200 -100 0 100 dCsom(kg/ha/yr )

Figure 1.Simulate ddevelopmen to fth eamoun t Figure 2. Averageannua lnitroge nyiel da sa ofcarbo n in the soilorgani cmatte r(Csom) .Se e function ofth eaverag eannua lchang ei nth e textfo rexplanatio no fth eabbreviations . amounto fcarbo ni nth esoi lorgani cmatte r (dCsom).

Conclusions In general, the simulated results show apositiv e relation between nitrogen yield and loss of soil organic matter inth e 4 grass production systems at acertai n level ofnutrien t input. Apparently, part ofth e production capacity ofth e ecosystem isneede d to maintain organic matter inth e soil and cantherefor e not beuse d for grass production. Thedifferenc e inorgani c matter loss between the agroforestry system with tree pruning (AFp :5 6k g ha'1 yr~l) and the monoculture system withfallo w years(GM f :23 3 kg ha~l yr~l)i smainl ycause d byth e difference in decomposition rates ofherbaceou s and woody plant litter. Tree pruning is aver y effective way to favour grass production in agroforestry systems (increase ingras s nitrogen yield is2 5 % relativet o unpruned trees), without risking high carbon lossesfro m the soil.However , ifth e prunings areremove d from thefield, soi l organic matter levelsma y decline much stronger. The effect ofunprune d trees on grass production, illustrated byth e strong decline ingras s nitrogen yield inth e agroforestry system AFcompare d to the grassmonocultur e GM, iscorrelate d to the poor soilconditions , where competition for limiting resources isintense .Nich e differentiation isno t possible, because most nitrogen andwate r isavailabl e inth euppe r soillayers , inwhic h most roots ofbot h species canb efound . Next challengei sno wt o find situationswher ehig hyield s andhig h soil organic matter levels coincide asmuc h aspossibl eb yminimisin gth e competition for limiting resources.

References Conijn, JG., 1995.RECAF S :a mode l for resource competition and cycling in agroforestry systems. Model description and user manual. Rapports PSS no. 12.Proje t PSS. 1ER,Bamako , DAN-UAW, Wageningen, AB-DLO, Wageningen/Haren. 101pp . & appendices. 624 Book of Abstracts 4th ESA-congress

Radiative climate modelling on virtual coconut stands for predicting the light regime in coconut based farming systems J. Dauzat1, M. Eroy2, M.L. Girard 1 CIRAD/GERDAT Modelling Unit, POBO X 5035, Montpellier, France Davao Research Center / Philippines Council Authority, Philippines Introduction Anaccurat e modelling ofth e PAR regime isessentia l to predict the behavior of intercrops in agroforestry systems. This isespeciall y true in coconut based farming systems where itha sbee n demonstrated that, inth e absence of strong water deficit, the intercrop yields aremor e or less proportional toth e available PAR. SO far thepertinenc e ofthi smodellin g needs arelevan t description ofth e vegetation. The method described herein consist in performing numerical radiative simulations onthre edimensiona l computer mock-ups. Methods The geometrical andtopologica l features ofplant sar emodelle d in ordert o create aparamete r file which isuse d by the AMAP software to generate apopulatio n ofplan t mock-ups consistent with the observed population (Reffye et al., 1995).I nthi s study three age groups of Laguna Tall coconutshav e been observed atth e Davao Research Center. Acomplet e description ofth e trees has been worked out :height , diameter, inclination oftrunks ;numbe r of fronds pertree , phyllotaxy, rachis-petiole length and curvature;numbe r and position of leaflets onth e rachis and their geometry. The data have been modelled accounting for the inter- and intra-tree variability and the results used to generate stochastically coconuts ofeac h age group.Prune d trees have also been simulated by limiting their frond numbert o 18(Figur e 1).Th e generated treeshav e then been set upt o create stands ofdifferen t densities with atriangula r ora squareplantin g pattern. Additional densities havebee n obtained bythinning .

Figure 1.Simulate d mock-ups of2 0 (unpruned / pruned), 5an d 40yr . (unpruned /pruned ) trees. Numerical radiative simulations have been performed with specific programs (Dauzat, 1989): - the MIR program which calculates the interception of incident radiation; - the TRANSRAD program which calculates themultipl e scattering within the stand. Thefinal output s in concern here areth e average PAR transmission rate ofth e stand and ama p of thetransmitte d radiation atth e soil level. Agroforestry Session 625

Results Satisfactory simulations oftransmitte d PAR havebee n obtained for the 5, 20 and 40 years old observed coconut stands. The diurnal evolution ofth etransmitte d PAR was also correctly restituted (Figure2) .

50 600 x.x.. 40 -\ « S 400 30 I u i 'S S X 20 .VA VAj fe 200 i i s s 10 k-S" g 1 1; ' OH 0 E 1 0 20 40 5 7 9 11 13 15 17 age groups timeo fda y (h) Hmeasure d Üsimulate d X measured simulated Figure 2. Left: averaged values on severaldays . Right: daily evolution for 20yr . old stand.

Further results obtained byvaryin g the stand density (Figure 3)lea d to the conclusion that the lighttransmissio n isappreciabl ya linea rfunctio n ofth etre e density irrespective ofth e planting pattern. Pruning the lower fronds strongly increases the light transmission and itseffec t is comparable to adensit y reduction ofabou t onethird . Because the coconut crown developmenti s normally maximal between 15an d 30years , the PAR transmission islowe r under 20year sol d trees. Therefore the management ofintercroppin g must be argued against the age ofth etrees .

60

X < - thinned stands *• pruned trees 50 50 - D "'*-•- pruned trees m A. 2 40 X. A 40 -I • •A A •~ _ 30 - 30 • Atriangula r design • square design A - 20 - • 70- 70 90 110 130 150 90 110 130 150 170 treesha" 1 treesh a

Figure 3. Light transmission rates vs. density under 20 (left) and 40yr . (right) coconut stands

Conclusions An original approach was successfully usedt osimulat eth e light transmission under 3 coconut stands. The use of computerized coconut mock-ups associated with specific radiative programs ensuretha t the simulations performed for other densitiesremai nvali d aslon ga sth e tree architecture isno t deeply modified. Theresult s show how light transmission canb e fitted by thinning astan d orprunin g the lower fronds ofth e trees. If it isascertaine d that the latter practice has no long term detrimental effect onth e coconut yield,i tcoul d be adopted as an efficient cultural management forintercopping .

References Dauzat, I, 1989. Oléagineux 49 (3): 81-90. Reffye (de), Ph. etal. , 1995. Agroforestry Systems 30: 175-197. 626 Book of Abstracts 4th ESA-congress

ON-STATION EVALUATION OFLEUCAENA, CALLIANDRA, GLIRICIDIA, SESBANIA, SENNA ANDERYTHRINA SPECIES INALLE Y CROPPING WITH MAIZE IN WESTERN KENYA. A LONG TERM EXPERIMENT: 1988- 1994

A.M.Heineman

Oxford Forestry Institute, University ofOxford , South ParksRoad , 0X1 3RB, Oxford, U.K.

Introduction Leucaena,Calliandra, Gliricidia, Sesbania, Sennaan dErythrina wer e evaluated in alon g term alley cropping experiment with maize (Heineman, inpreparation) . Themai n objective ofth e study wast o determine which species had positive or negative effects on maizeyield s and why. Species choice isknow n to influence the productivity ofindividua l components and overall sustainability ofth e system.Farme r managed experimental alley croppingha s sofa r not worked inwester n Kenya. Socio-economic incompatibility ofth etechniqu e vis-a-vis local expectations wasidenti ­ fied asth emai n cause (Shepherd etal., submitted; Swinkelset ai, submitted). This interpretation might be correct for the specific alleycroppin g designsused , but this conclusion does not seem to havegenera l applicability. Alley cropping must perform satisfactorily from abio-physica l point of viewbefor e iti sconsidere d for end-user adaptation and adoption. Farmers should onlypartici ­ pate inth e process of species selection, when uniformity inresearc h protocols and methodo­ logical compatibility across sitesi sguaranteed . Long-term species evaluation experiments are essential indevelopin g bio-physicallyfunctiona l alleycroppin g systems. Each species isthough t to cause a specific response inmaize , which isth e outcome ofth ebalanc e of all complimentary and competitive interactions. Trees should beidentifie d which perform the desired functions best, i.e. nitrogenfixation, nutrien t cycling, deepnutrien t capture, efficient nutrient transfer and redu­ ced leaching and erosion. At the sametime , theymus t not beto o competitive with maize for light, water and nutrients. Bio-physically efficient resource sharingbetwee n trees and crops isa mandatory prerequisite for successfully practising alley cropping, both inon-statio n and on-farm evaluation programmes. An agroforestry system that does not lead to better crop yieldswil lno t be perceived byfarmer s as anattractiv e innovation,fit fo r adoption.

Methods Arandomise d complete block (RCB) design with 8treatments , replicated 4 times was used. Tree seedlingswer e planted inApri l 1988i ndoubl e rows in eachplot s (14,286 trees ha"1) except the controls. In on-farm trials,tre e densities aretypicall y 50t o 75% lower. Trees were managed as hedges after oneyear , leafbiomas s was on average appliedfive time s ayear . Maizewa s sown twice ayea r (47,619 plants ha"1) for five years. The quantities ofN , P and Kapplie d inlea f mulch and the corresponding quantities ofN , P andK remove d incro p harvest were calculated, usingpartia l nutrient budgeting techniques. Between plot interactions are apotentiall y disturbing factor inth e determination ofyields . Consideringthis ,tw o strategies werefollowed . Polyethylene meshroo t screenswer e inserted around control plotst o prevent penetration byroot s from adja­ cent plots. In addition, a calculation technique wasuse d to verify whether the performance inan y treatment was modified byundesirabl e root competitionfrom neighbours . In avali d trial, treat­ ment related variation inmaiz eyield s should beth eresul t of differences inth e magnitude and the sign(+ , -) ofth e nutrient balances. Control yieldswil ldeclin erapidl ywhil eit snutrien t balances become progressively more negative. In alley cropping, maizeyield swil lultimatel y depend on the balancebetwee n positive and negative interactions between trees and crops. In this study, the result ofth e competitive and facilatory forces inalle ycroppin g treatments were expressed in terms ofvariatio n intreatmen t related nutrient use efficiency (NUE). Agroforestry Session 627

Results Species differed widely inlea fan dwoo d production astree s in 1988an d ashedge s in 1989t o 1993. Theamoun t ofN , P andK recycle d to alley cropped maizevi alea fmulc hvarie d signifi­ cantly. The application oftre e biomassresulte d inhighe ryield s ofalle ycroppe d maize, compared to the persistently low anddeclinin g yieldsi nth e 'maizeonly 'controls . The efficiency withwhic h alley cropped maizewa s ablet o utiliseth e additionally recycled nutrientsvarie d between species. Moderately productiveN fixing Gliricidiasepium an dEtythrina caffraha d highNUE's . High biomass production in Calliandra calothyrsus led to competition for water with maize and nega­ tively influenced itsNUE . Unintentional below-ground interaction between adjacent plotswa s ruled out as acaus e for the observed treatmental differences and was also not the cause ofth e consistently low control yields. Thus,th e experimental resultswer e not caused bydesig n arte­ facts. Longter mnutrien t budgets confirmed that minimumamount so fN , P andK mus t be recycled to cause positiveyiel d responses inmaiz e(no t achieved inS.siamea) but alsotha t ifa species isto o productive, the balance inalle y cropping can shift from net complimentarity to net competition (e.g. C.calothyrsus). These resultswer euse d to design apo t experiment to deter­ minewhethe r the differences inrecycle d N, P andK (varyin g upto fourfold) could behel d responsible for the observed yield patterns. The observed variation infiel d NUE valueswa s confirmed inth e pot experiment, inth e absence oftre e roots,bot h in sequence and approximate magnitude. Theresult sfro m thefield an dpo t studieswer epositivel y correlated, using simple linear regressions. LowNUE' s oftree-cro p combinations inth efield corresponde d wellwit h low NUE's ofidentica l tree leaf- seedling maize combinations inth e pot experiment andvic eversa . Speciesvarie d significantly infolia r polyphenol concentrations (Palm, 1995).Hig h polyphenol concentrations contributed to arelativel y lowNU E inalle ycroppin g with C.calothyrsus and low polyphenol concentrations inG.sepium andE.caffra wereassociate d with highNUE's .

Conclusions L.leucocephalaan d C.calothyrsus havetraditionall y been used inalle y cropping inwes t Kenya. Farmer adoption ofth etechniqu e inwester n Kenyawa s probably inpar t disappointing because thebio-physica l modalities of species choice and management were not yet wellunderstoo d when thetrial swer e designed and executed.L.leucocephala an d C.calothyrsus canresul t in lowNUE' s because competition with maizei susuall yno t sufficiently controlled. Lesscompetitiv e treeslik e G.sepium andE.caffra arebette r choices inmanagin gth e delicate balancebetwee n competition and complimentarity. Doing exploratory pot trialsbefor efield trial s are started might bea cost effective way to reduceth e long list ofpotentia l treesfo r alley cropping. Then, fewer species need to be considered inth e often lengthy and expensiveproces s offield experimentation . Com­ plete characterisation of selected tree species should aid inth eformulatio n of minimum nu­ tritional requirements for tree leaves, including the effects of anti-nutritional compounds (poly- phenolics), which canmodif y leafdecompositio n andnutrien t releasepatterns . Theeffec t ofvary ­ ingth e mulching rates canb eteste d inpot swit h representative soil mixtures, and may givein ­ dications about minimumtre e densitiest o achieve positive nutritionalbenefit s inassociate d crops. References Heineman, A.M. (in preparation). Crop production and soil changes inalle y cropping systemsi n the highlandso fEas t Africa: Critical interactionsbetwee n system components. Oxford, UK, Ph.D. Thesis, University ofOxford . 250p . Palm, C.A. 1995.Agroforestr y Systems30: 105-124. Shepherd, KD. etal. (Submitte d to Experimental Agriculture). Adoption potential of hedgerow intercropping inmaize-base d cropping systemsi nth ehighland so fwester n Kenya. I. Back­ ground and economic evaluation. Swinkels, R. etal. (Subm.Exp.Agr.) Adoption potential of hedgerow intercropping inmaize - based cropping systems inth e highlands ofwester n Kenya. II.Economic and farmers' evaluation. 628 Book of Abstracts 4th ESA-congress

SEASONALAN DLON G TERM EFFECTS OFLEUCAENA LEUCOCEPHALA HEDGEROWS AND INORGANIC SOURCES OFN AN D PO N THE PRODUCTIVITY OFMAIZ E - BEAN SYSTEMS INWESTER N KENYA, WITH COMPARATIVE NUTRIENT USE EFFICIENCIES OFDIFFEREN T FERTILISER ALTERNATIVES. A LONG TERM EXPERIMENT: 1988- 1994 A.M.Heinema n Oxford Forestry Institute, University ofOxford , South ParksRoad , 0X1 3RB, Oxford, U.K.

Introduction Many soilsi nth e highlands ofEas t Africa are depleted of soilnutrients , particularly N and P, asa result ofdecade s ofsubsistenc e farming without adequate nutrient management. Cropyield sar e very low. They can onlyb e stabilised and soilfertilit y restored byreturnin g to the soil the equivalent or more of seasonallyremove d nutrients in crop harvests and through other losses. East African economies cannot base subsistence farming inlarg e part on imported inorganic fertilisers. Agroforestry techniques, wherebytree s are used to recycle nutrients,fix atmospheri c N and reduce nutrient losses should also beconsidere d to achievebette r subsistence agriculture. However, it isals orecognise d that trees mayno t be ablet o fully provideth e quantities ofN , P andK t o make subsistence cropping systems selfsufficien t innutrien t requirements. Maizei s often fertilised byfarmer s inwester n Kenya with small amounts ofN and P inth e form of diammoniumphosphate (DAP) and calciumammoniumnitrate (CAN), normally well below the recommended dosage. Agroforestry and inorganic fertilisers both have arol et o play inth e search for better balanced nutrient budgets inmaiz ebase d systems. Analle y cropping experiment was carried out between 1988an d 1994. Its main objective wast o compare the seasonal and long- term crop responses to pure and combined use ofL.leucocephala mulch and DAP/CAN fertiliser.

Methods A split plot design was used with4 main plots (maize monocrop, maize-bean intercrop, maize- L.leucocephalaalle ycro p and maize-bean-Z.leucocephala alleyintercrop ) and 3 sub-plots (no fertiliser, 30 kgN ha'1 + 15k gP ha' 1, 60k gN ha" 1 + 30k g Pha' 1). The 12treatment s were replicated 4time s (Sub-plot treatment size: 5.0 x 7.5 m).L.leucocephala was planted inApri l 1988 (density: 10,667tree s ha"1). Cropswer e sown twice ayea r inApri l and September from 1989t o 1993. Hedgeswer e cut 2t o 3time spe r season, leaves appliedt o the crops and wood removed. Yield calculations were int ha"1 dry matter on an equal area basis, recognising that hedges occupied 20 % ofth e land area inalle y cropping plots. Partial nutrient budgets were constructed for N, P and K. Theyillustrate d for each alleycroppin gtreatmen t the relationship between nutrients recycled through the hedges and the corresponding additional nutrient harvest inmaiz e and beans.Fo r theunfertilise d 'maize only'treatment , similar budgets showed how much N, P and Kcoul d beremove d without organic or inorganic inputs (figure 1).I nth e DAP/CAN fertilised systems,budget s showed relationships between additionalDAP/CA N inputsan d permitted nutrient exports incro p removals.B y comparing mulched, DAP/CAN and unfertilised treatments, the relative maizeyiel d contribution ofL.leucocephala mulch and DAP/CAN was determined. By comparing long-term yield trends across cropping systems,th e nutrient use efficiency (NUE) ofL.leucocephala mulch, DAP/CAN orth e combination was calculated.

Results Maizeyield si n allcroppin g systems declined between 1989an d 1994becaus eth e site was former pasture and resident soilfertilit y declined asth e cumulative quantity of nutrients exported increased overtime . L.leucocephala systems were on average asproductiv e as maize mono crops or maize-bean intercrops, although maizepopulation s inalle ycroppin g systems were 20 % lower, Agroforestry Session 629

because ofth e replacement of 1 inever y 5maiz erow s bya L.leucocephala row. Themulc h additions to maize in alley cropping directly benefited individual maizeplants . Theygre w taller, stored more nutrients and produced more grain, compensating for the loss inplan t population. Thebeneficia l effect ofth e mulchbecam e less significant asinorgani c fertiliser levels increased. On average, it required 3time sth e equivalent amount ofinorgani cN to obtain equivalent maize yield effects through mulched N applications. Theaverag e nitrogenNU E of maize, when receiving N viaL.leucocephala was 14% , thus requiring 28 kg ofmulc h (N = 3.56 %) to export 1k g ofN inmaiz eyields . TheN use efficiencies for DAP/CAN inth e absence ofmulc hwer e considerably higher (figure 1).Simila rresult swer e achieved with regardsP use efficiencies.

Conclusions The results suggest that alley cropping NUE's were low, becauseth e positive effects ofmulc h were off-set by some competition between trees and crops. Hedges must reach aminimu m mulch productivity in order to beeffectiv e but excessive production willlea d to increased competition. Only ifhedge sexer t no competitive pressures on maize,NUE' s mayapproac h those of inorganic fertilisers. Alley cropping isi nterm s ofyiel d advantage particularly attractive ifinorgani c N andP are too expensive to be economic. This experiment was not sited on a slope, thusth e soil conservation effect ofth e hedges could not be demonstrated. Traditional maize mono crops on slopes without adequate nutrient management decline inproductivity , because loss ofto p soil aggravates the decline inproductivit y asa resul t ofnutrien t exportsi ncro p removals. Therefore alley cropping islikel yt o bemor e attractive on slopestha n onflat land san d most attractive when purchased fertilisers areunaffordable . Thelong-ter m results, on whichthi s abstract arebase d (Heineman, inpreparation ) offer considerable scopet o design factorial experiments to determine what the preferred combination oftre e leafmulc han d inorganic fertilisers should bet o restore soilfertility , stabilise crop yields and suit the specific needs offarmer s on soilso fknow n fertility. Figure 1

800 Actual N out

111 Max.possible N out

Min.possible N out

— -a I s

400 800 Total N applied via inorganic fertilisers (kg/ha) between 1988 and 1993

Note: Also shown is the maximum and minimum amount ofN that would have been exported if the N use efficiency of the fertilisers had been 100 % and 0 % (coded: Max.possible N out, Min.possible N out, respectively)

References Heineman, A.M. (inpreparation) . Crop production and soil changes in alley cropping systemsi n the highlands ofEas t Africa: Critical interactions between system components. Oxford, UK, Ph.D. Thesis, University of Oxford. 250p . 630 Book of Abstracts 4th ESA-congress

THE UK NATIONAL NETWORK SILVOPASTORAL EXPERIMENT - A CO-ORDINATED APPROACH TO RESEARCH

G MHoppe 1, AR Sibbald2, JH McAdam 1,W R Eason3, MHislop 4an dZ Teklehaimanot 5.

'Department ofAgricultur e for Northern Ireland, Belfast, BT9 5PX,UK . 2MacaulayLan dUs eResearc h Institute, Aberdeen, AB9 2QJ,UK . 'institutefo r Grassland and Environmental Research, Aberystwyth, SY23 3EB,UK . "ForestryCommission ,Roslin ,EH2 5 9SY,UK . 5UniversityColleg eNort h Wales,Bangor , LL57 2UW,UK .

Introduction European Union land usepolic y iscurrentl ytargete d at reducing levels ofagricultura l surplus and reducing a substantial timber product deficit. Therei sals o interest in sustainable land use systems whichgenerat e multipleproducts , enhancelandscap e diversity andincreas ebiodiversit y withinth e natural environment. Theintegratio n ofagricultur e andforestr y practices onth e samelan d areai n agroforestry systems offer anopportunit y for aphase d reduction inagricultura l production combinedwit hhig hqualit ytimbe r production, afforestation and increased habitat diversity within the landscape. Until relatively recentlyther e hasbee n littleresearc h carried out on such systemsi n temperateEurop e andthi spape r outlines aco-ordinate d approach which hasbee ntake n within theUK .

TheU K agroforestry research discussion forum Inwester n Europe andth eU Ki nparticular , agroforestry canb e seena sdevelopin g alongtw o lines- silvoarable systemswher etre e rows areintercroppe d with an arable crop and silvopastoral systemswher e stock grazepastur e between widely spaced trees.Neithe r system ispractise d to anygrea t extent inth eU Kan d research on agroforestery systemsi srelativel y recent (Sibbald et al, 1990). Agroforestry systems represent complex interactionsbetwee n the individual components andresearc h has primarily concentrated on quantifying productivity with lesser resources directed towardsth e investigation ofecologica l interactions. Recent interesti n agroforestry research inth eU K started inth e early 1980'swit hth e publication ofa numbe r of modelse.g . alowlan d model byDoyl e et al.(1986) . It wasrecognise d that the necessary biological research to verify these modelswoul d be resource demanding andwoul d requirea collaborative approach. Asa consequence ofthis , aninforme d group of scientistslargel ywithi n theU Kforme d theU KAgroforestr y Research Forum in 1985. TheForu m debates specific areas ofresearch , agreeso n a collaborative approach and co-ordinatestw o national network experiments, thelarges t ofwhic h isth eNationa lNetwor k Silvopastoral Experiment.

The national network silvopastoral experiment (NNE) Inthi s experiment acommo n set oftreatment s -thre e replicates ofprotecte d Sycamore,Acer pseudoplatanusa ttw o agroforestry spacings(10 0 and 400 stemsha" 1), awoodlan d control planted at 2500 stemsha" 1 and agrazin g control inplot s 0.4-1 Ohasiz e- are adopted at each of sixU K sites- Aberdeen , Scotland (MLURIan dF C -funde d byth e Department ofAgriculture , Environment andFisherie sfo r Scotland);Nort h Wyke, SWEnglan d &Bronyd d Mawr, SWale s (IGERan d FC -funde d byMAFF) ;Bangor ,N Wale s(UCN W funded); Loughgall& Broughshane, N Ireland (DANIfunded) . The sitesrepresen t awid e range ofpastur etype sfrom 20yea r old swards(th eMLUR I site)t o those sownth eyea rprio r to thetrial s commencing (the DANI,Loughgal l site).Managemen t protocols havebee n agreed for sheep-grazed pasture managed to aconstan t sward height profile. Treesar egive n standard protection and pruning,an d Agroforestry Session 631

an integrated measurement, recording and analysisprogramm e isadopte d to quantify all aspects ofth e output ofth e system (Sibbald et al., 1990; Eason et al., 1994).Dat a ontre e height and diameter, eweperformance , lambgrowt h and output, stock carrying capacity and standard pasture and climatevariable s are analysed on abetween-sit e basis, andpublishe d eachyea r (Sibbald et al., 1995).A t all sites additional treatments -usuall yvariant so ftre e speciesan d spacing -hav ebee n planted to suit local research requirements e.g. Ash,Fraxinus excelsior, planted atth eDAN ILoughgal l site. It iso fparticula r interest to notetha t 5year s after introduction ofth e systems,anima l production hasno t been significantly reduced byan yo fth e agroforestry treatments (Hoppé et al., 1995).

Ecological interactions Additional information on some aspects of ecological interactions occurring within the system has been collected on a sporadic basis from most of the sites. This has included avifauna recording, invertebrate sampling and floristic diversity monitoring, all to protocols that are agreed at the regularNN E managersmeetings .

NNE co-ordination and management To co-ordinate and manageth e experiment, the managerso fth eNN E sitesmee t on at least two occasions eachyea rt o discussprogress , problems, modification ofth e appropriate protocols and joint analysis andpublicatio n ofth e data. Meetings arehel d on arotationa l basis,on emeetin g (held inJuly )coincide swit hth e annualU K agroforestry research discussion forum meeting.

EU -ALWAY S project In 1993th eNN E wasinclude d ina bi dfo r a4-yea r research programmet o investigate alternative landus ewit h fast growing trees(Se eAuclair , thisconference) . The overall aimo fadditiona l scientific research carried out onth e network sitesi st o contributet o biophysical and bioeconomic modelso fagroforestr y systemswhic h help support their adoption on aEuropea n scale. Aswel l as the standard data set,th eNN E iscontributin g data ontre e root growth and canopy architecture, microclimate modification and sward diversity.

Future Despite separate site funding, theNN E has largely maintained the integrity ofit smanagemen t and scientific output sinceit sconception . Thisha sbee nwidel y recognised and hasresulted , for example,i nth e attraction ofE U and other external funding. Asignifican t number of post­ graduate research studentsus eth e sitest o study moredetaile d aspects ofth ebiologica l interactions. Thisbasi c sciencebas ehelp st o underpin the applied nature ofth ewor k and provides added valuet o the sponsors ofth eNN E sites interm s ofscientifi c outputfrom thei r investment. Thenex t stagemus t bet o translateth eresearc h into demonstration and practice on commercial farms. InN.Irelan d a serieso fon-far m demonstration sitesar emanage d bylan d owners(wit h DANI support) to incorporate thebasi cresearc hfindings o fth eNN E and demonstrate that silvopastoral systemsca nb e aviabl elan d use option onlivestoc k farms inth eUK .

References DoyleC . J., et al., 1986.Agricultura l Systems 21: 1-32. Hoppé G. M, et al., 1995.Agroforestr y Forum 6(2) : 19-22. EasonW R , et al., 1994.In : L. O.Fresc o et al.(Ed. ) Thefutur e ofth eLand : Mobilising and integrating knowledge for land useoptions . JohnWile yan d SonsLimited : pp 123-128. Sibbald A.R , et al., 1995.Agroforestr y Forum 6 (1): 5-8. Sibbald A.R , et al., 1990.Agroforestr y Abstracts 3: 149-164. 632 Book of Abstracts 4th ESA-congress

THE PHYSIOLOGICAL CONSTRAINTS ON CROP GROWTH IN DRYLAND AGROFORESTRY

J.E.Lott1'2,C.RBlack 1 andC.K.Ong 2

1.Universit y ofNottingham , Department ofPhysiolog y andEnvironmenta l Science, SuttonBoningto n Campus,Loughborough , LE12 5RD. Fax:0115-951-633 4 E. Mail: [email protected] 2. International Centre for Research inAgroforestry , PO Box 30677, Nairobi, Kenya. Fax:252-2-52100 1 E. Mail: [email protected]

Introduction Agroforestry hasth epotentia l to alterth ephysiologica l constraints imposed on crops growing inwater-limite d environments inway s which mayo r mayno t bebeneficia l for cropyield . Thisexperimen t was set upt o establish how an overstorey agroforestry system altersth emicroclimati c conditionsexperience d byunderstore y cropsan d whether thecro p physiological responses aremodifie d byth epresenc e oftrees .

Methods Thisexperimen t wascarrie d out at ICRAF's experimentalfield sit ea t Machakos,Kenya , using6 - 8m tal l Grevillearobusta tree splante d at a 3b y 4m spacin g and intercropped withmaiz ean dbean so r cowpea. Theclimat ei ssemi-ari d witha bimoda l annual rainfall of 750mm . Microclimatic parameters weremeasure d at concentric distancesfrom th e treesan dthei rinfluenc e onth etranspiration ,photosynthesis , phenology andyiel d ofth e understorey crop wasexamined .

Results Treeshad edecrease d themea ndiurna ltemperatur e rangeexperience d byth ecro p from 24 °C inth e solecro pt o 14 °Ci nth e agroforestry system;maximu m temperatures were also 7° Clowe r inth elatte r treatment. Asa result , thermal time accumulated at a much slowerrat e inth e agroforestry treatment, causing considerable delaysi nplan t development. Thisdela yha d two significant effects; the abilityo fth ecro p to compete with thetree sfo r water was compromised because ofth e slower development ofth e root system, whileextensio n ofth egrowin g seasonincrease d theperio d available for evaporation of soilwater . Sincetre e shadeonl yreduce d soil evaporation from 50t o 45% oftota l rainfall, theoveral leffec t wast o increase evaporative losses duringth e cropping season.

Thetree swer eperiodicall y pruned duringth eexperimenta l period to maintain a2 5 to 35% reduction intota l radiation reachingth eunderstore y crop. Thisreductio n inradiatio n wasexpecte d to havever ylittl eeffec t on crop productivity sincemeasurement s ofth e light response ofmaiz egrow nunde r artificial shade nets illustrated that photosynthetic ratewa shardl y affected upt o a35 % reduction inPA R (Figure 1). However, when the photosynthetic light responses ofbot hC 3 andC 4 crops grown under thetre e canopy were examined, therate swer efoun d to beonl yhal fo fthos e ofth ecorrespondin g sole cropan d Agroforestry Session 633 light saturation occurred at 30% offul l sunlight. Thissever ereductio n in photosynthetic activityma yreflec t acombinatio n ofwate r stressan d the poorer spectral qualityo fth e radiation under thecanopy .

2200 PAR(umo lm 2 s" 1) Figure 1. Light response ofmaiz egrow n asa solecro p inful l sunlight or artificial shade and ina n agroforestry system.

-r 0.50 1 ' Solecrop J ^ f Ü 0.40- • . . « Agroforest f o / / isr 0.30- 25% shade • / / / 2 ' . s 0.20 • , — - 50% shade • . / / JS §• 0.10' ''' '^ 2 1 o I 1 / ,A —i 1— —i 4 6 8 10 12 Transpiration rate(mmo l m2 s') Figure 2. Water use efficiency ofmaiz egrow n asa sole crop inful l sunlight or artificial shadean d ina n agroforestry system.

Thewate r useefficienc y ofcrop sgrow ni nth eagroforestr y systemwa simprove d relative to the solecro p(Figur e2) , but thiswa sinsufficien t to compensatefo r the severe reduction inth e quantity ofwate r availablet o thecrop . In addition, competition for water between thetree s and cropsresulte d inmor efrequen t and severe crop water stress.

Conclusions Theinformatio n obtained canb euse d to identify areas offutur e technological development through the selection ofbette r species combinations andimprove d breeding and management practices to encourage positiveinteractions .

This workwa s supported by theOversea s Development Administration under contract R5810. 634 Book of Abstracts 4th ESA-congress

TREE-SOIL INTERACTIONS IN POPLAR- ARABLE AGROFORESTRY SYSTEMS J.Park 1 and S.M. Newman2

1 Department ofAgriculture , TheUniversit y ofReading , Earley Gate, P.O.Bo x236 , Reading, UK, RG62AT . 2 Biodiversity International Ltd, 35Nelso n Street, Buckingham, UK, MK18 IDA

Introduction Issues associated with soilhealt h and the effect agriculture has onth e soil are becoming ofincreasin g interest insustainabl e systemsresearc h (Haberern, 1992; Thomson, 1992). Silvoarable systems mayoffe r thepotentia l to improve soilqualit yb y increasing the amount and changingth e distribution ofcarbo n in soilwhils t maintaining the productive capacity ofth e system. Apoplar-arabl e system inBuckinghamshire.U K forms the basisfo r this research inwhic h tree-soil interactions are quantified in relation to thelatera l distance from tree alleysbase d on measurements ofcarbo n inbot h the surface and sub surface horizons.

Methods The research described isbase d upon a silvoarable agroforestry trial established in March 1988.Th e soil onth e 4h a sitei sa river alluviu m (Fladbury series;Avery ,1980) , clayey silt classified grade 3whic hha sbee n subject to a conventional arable rotation. Poplar trees (P.trichocarpa x deltoïdes) belonging to the clonesBoelar e and Beaupré (Potter, et al., 1990) are planted inrow s at 14m interval s acrossth efield . Following plantingth etree s established quickly and started to influence annual crop growth (Table 1).I t was hypothesised that thiswa s due inpar t to changes in soilpropertie s in these arable alleys. To quantify the soil effects anumbe r ofrelate d measures havebee n undertaken (Park et al,1994) . In October 1995 aserie s of soiltransect s were sampled (within row, lm, 3man d 6mfro m thetre e bases) at two soil depths (0-15 and 15- 30cm). Thesewer e analysed usingth elos s onignitio n method to provide information on soil carbon at different distances from thetre e (Table2) .

Results Table 1.Diamete r at Breast Height (DBH) and Top Height (TH) Measurements for Poplar trees since establishment in 1988.Mea n Annual Increment (MAI) isth e 1994 height dividedb y7

Year DBH(cm ) TH(m )

1988 - 2^67 1989 - 4.34 1990 6.3 6.60 1991 9.4 9.25 1992 13.1 11.79 1993 16.8 13.8 1994 19.4 15.6 MAI 2.7 2.2 Agroforestry Session 635

Table 2. Average soil carbon values (%) at different distancesfrom th etre e rows and attw o depth.

In row lm 3m 6m

0-15cm 3~36 343 3~TÏ 2.99 15-30cm 2.65 2.60 2.03 2.36

Table 2 illustrates agenera l trend ofdecreasin g carbon levelsi n samples further from thebas e ofth etree . However, the only significant difference isi nth e surface 15cm between those samples takenwithi n thetre e rows andthos etake n at 6m (p<0.011) . As expected at each distancefro m thetre eth e soili nth e surface 0-15cm contained a significantly (p<0.010)greate r amount ofcarbo n than that inth e sub-surface soil (15- 30cm).

Discussion and Conclusions The soil carbon sampling presented hereform s part ofa no ngoin g monitoring programme (Newman, 1994;Par k et al., 1994).Recen t sampling supports earlier work which suggeststha t poplar trees caninfluenc e soilpropertie s ina relativel y short period oftime , although continued monitoring isrequire d to provide a clear picture of these changes intim e and space. Data collected on soil carbon are presently beinguse d inth e construction of amode l of carbon flow and distribution in silvoarable systems. Thistoo l willb euse d to exploreth eusefulnes s offas t growing trees inaddin g carbon to arable systems andth eimplication sthi sma yhav efo r future productivity.

References Avery, B.W. 1980 Soil Classification for England and Wales. Soil Survey Technical Monograph 14,Harpenden , UK Haberern, J., 1992.Journa l of Soilan dWate r Conservation. 47(1):6 Newman, S.M., 1994Popla r Agroforestry Studies. Farmer Centred Agroforestry Research and Development inEaster n China, Biodiversity International, Buckingham. Park, J., et al. 1994 Agroforestry Systems. 25, 111-118. Potter, C.J., 1990. Theintroductio n ofimprove d clones from Belgium. Forestry Commission Information Note 181. Thompson, T.R.E., 1992.Biologist . 39(1): 33-34 636 Book of Abstracts 4th ESA-congress

BELOW- AND ABOVEGROUND RESOURCE CAPTURE IN AGROFORESTRY SYSTEMS

M. van Noordwijk

International Centre for Research in Agro-Forestry, ICRAF-S.E.Asia, P.O.Box 161, Bogor 25001, Indonesia

Introduction Depending on one's definition, agroforestry includes a broad range of land use systems that integrate trees, crops and grasses in the landscape. Trees play a directly productive and/or a supportive role, via effects on soil fertility, soil water balance, microclimate and/or pest and disease incidence. In temperate zone agriculture the major part of traditional agroforestry systems no longer met farmer's targets and has been replaced by simplified systems and landscapes, but new versions of agroforestry are re-invented, based on a direct production value of well-managed trees. In the tropics there is still scope for trees in a supportive role, although competition with crops and grasses makes it unlikely that trees can be maintained that do not have any direct value for the farmer (Van Noordwijk and Purnomosidhi, 1995). A generic view on tree-soil-crop interactions is needed to evaluate the huge variety in agroforestry systems in all there locally adapted forms. A simple equation was developed for quantifying tree-soil-crop interactions (I), distinguishing between positive effects of trees on crop yield through soil fertility improvement (F) and negative effects through competition (C) between tree and crop for light, water and nutrients (Sanchez, 1995). In its simplest form, the tree - crop interaction (I = F - C) is positive and hence the combined tree-crop system may be attractive if F > C, and not if F < C. The simple equation (I = F - C) needs to be expanded to separate the various positive and negative interaction terms directly and to develop a process-based model on water, nutrient and light capture in agroforestry systems (WaNuLCAS) which can be used to 'understand' and thus extrapolate the results (Table 1).

Table 1. A three-step approach to analysis and synthesis of tree-soil-crop interactions

Y, = Y0 + F. + F„ + C + M Crop yield Crop yield Direct Long term Competi- Competi- Micro- in in fertility fertility tion for tion for climate interaction monoculture effect effect light water and effects nutrients

/. Experimental +/ - Mulch Residual +/ - Root transfer effect vs Tree barriers trial pure crop removal, control + root barriers

2.Process-level Litter Functional Canopy Root understanding quality, SOM shape, architec­ mineraliza t fractions light ture ion rates (Ludox) profiles (fractal ?)

3. Synthesis model W A N U L C A S Agroforestry Session 637

Methods A long term hedgerow intercropping trial in Lampung (Indonesia) of the 'Biological Manage­ ment of Soil Fertility' project, in cooperation with Brawijaya University (Malang, Indonesia) is used (Van Noordwijk et a/., 1995). On part of the plots all hedgerows were removed. The fertility term was estimated from the yield on these plots minus that in the pure-crop control. The competition term is based on the yield contrast between these plots and that in alleys.

Table 2. Terms of the tree-soil-crop equation for maize in 6'th year of hedgerow intercropping experiment in Lampung (Indonesia); F = fertility effect, C = competition effect, I = overall interaction; data are expressed as percentage of monoculture crop yield (2.6 Mg ha' of grain)

Tree species F C I

Leucaena leucocephala 152 -159 - 7 Calliandra calothyrsus 120 -115 + 5 Peltophorum dasyrrachis 58 -26 + 32 Flemingia congesta 37 -89 -52 Gliricidia sepium 19 -60 -41

Results The components F and C, as well as the overall interaction term I, differed clearly between five species of hedgerow trees (Table 2). Only the local species Peltophorum dasyrrachis gave a positive overall effect on crop yields. Its positive overall effects is not based on positive F terms, but rather on moderately negative C terms.

Discussion Part of the 'fertility' effect of the tree is based on light, water and nutrient resources which the tree acquired in competition with the crop (Fcomp); another part may have been obtained in complement to resources available for the crop (F„oncomp), e.g. from soil layers to which the crop has no access or at times that the crop is not active. Furthermore, part of the resources acquired by the tree in competition with the crop are recycled within the system, and may thus be used by a future crop (Crecycl). Tree products which are not recycled (Cnoniecyd), may have direct value for the farmer. One may argue that Fcomp is based on the same resources as Crœyci- The question whether or not a tree-crop combination gives yield benefits then depends on: 1) the complementarity of resource use (Fnoncomp), 2) the efficiency of the recycling, and 3) the value of tree products based on Cnonrecycl relative to the value of crop products which could have been produced with these same resources. Integration models on above- and be­ low-ground resource capture and recycling, such as the Wanulcas model allow the explora­ tion of a wide array of management options and predict effects of soil and climate parameters on the performance of tree-crop combinations, ranging from simultaneous 'hedgerow inter­ cropping' to sequential 'improved fallow' systems.

References Sanchez, P. 1995 Agroforestry Systems 30: 5-55. Van Noordwijk, M. and P. Purnomosidhi, 1995. Agroforestry Systems 30: 161-173. Van Noordwijk, M. et al. 1995 In: R.A. Date et al. (eds) Plant-Soil Interactions at Low pH: Principles and Management. Kluwer, Dordrecht: 779-784 Division 1

Crop physiology, production and management. 640 Book of Abstracts 4th ESA-congress

INVESTIGATING THE AIR HUMIDITY INTH E ENVIRONMENT OFPLANT S BY USING ANELECTRI C THERMAL MEASURING TRANSDUCER

S.Alexieva , M. Kilifarska Institute of Soil Science and Agroecology, 7, Sh.Bankja Str., PB 1080, Sofia Bulgaria

Introduction The relative humidity represents the relation of the partial pressures between the saturated water vapour andth e unsaturated air with water vapour under adistinc t temperature. Conditions exist, under which thewate r vapour diffusion mayb e caused by atemperatur e gradient [Philip, 1957] Such possibilities of similarity determine an error which is not larger than the methodical errors of the well known principle solutions when measuring the humidity. The aim of the investigation wast ocreat econditions , under which it would bepossible ,throug h atemperatur e gradient and some border conditions, to elaborate ametho d and aschemati c solution for measuring the air humidity.

Methods The method of aheate d thermosensitive element ison e of the possible variants for determining the relative air humidity ç. Grounds for this is the relation between the thermal conductivities of J a saturated water vapour Av and that of air which isunsaturate d with water vapour A, [Philip, 1957].A v= (p. X* (1).Compare d to the thermal conductivity of the dry air Xa under isothermic conditions and temperatures in excess of 40°CX v begins to grow rapidly and its role inth e thermal transfer becomes dominant. This means that under given border conditions Xv will depend both on the temperature gradient and on the humidity. If in asuitabl e volumea temperature gradient isdevelope d which would cause a gradient in the water vapourpressure , then this ismandatoril y connected with ahea t transfer. This water vapour stream, with acertai n approximation, isproportiona l to the transfered heats i.e., it ismathematicall y tied to an increase in the thermal conductivity of the volume. On this basis,th e effectivity of thermal conductivity Xe in this volume may be taken as an aggregation of twoparts ,namely : Xe= X a +X v(2) .Th e relations (1 ) an d (2) arethermophysica l regularities and abasi s for creating an electrothermal device for determining the relative humidity of the air. For the experimental determination ofA v and the relative airhumidit y connected with it, in agive n volume is needed to be developed a temperature gradient toward the ambient temperature, while Xa of the dry air will serve as abasi s of comparison. Figure 1 illustrates the dependences XeX v and X', of the relative air humidity in the 0t o 100%range , apressur e of 105Pa and 50"Ctemperatur e in the investigated volume.Th e 1 Xa for this temperature isX a =2.91 [W.m'.K ]. The fact that acomparativ e method is applied for measuring renders possibilities for increasing the precision, because the disturbing factors, namely, temperature changes and velocity of the air stream have been eliminated. These, normally, give rise to noninformative disturbances .Thethermosensitiv e elements in the device are two silicon transistors with metal bodies and similar characteristics. The first one isa measuring transistor, while the second serves as acomparativ e one.Th ebod y of the measuring transistor isperforate d while the second one is hermetically closed. The two transistors must preferably beplace d next toeac h other in order tob e found under the same atmospheric conditions: ambient temperature, air stream velocity and relative humidity. The thermosensitive elements areheate d to nominal power from the source of direct current voltage E,whic h guarantees a50" Ctemperatur e of the crystal. One of thep -n transition of each one of the transistors serves for heating, whileth e other one isthermosensitiv e toth e heat release in adr y air and in the investigated medium. The thermosensitive p -n transistors are connected toa Division1 641

W/m K 1 O"3 OP K K ^V, A, X, cri P^>Î •\Ur 29.2 K \ S »T, '^ -Ä> u«>.t I OP |u*) 29.1- ^, M .-"X DA i© y Kt= -[2 + R1/R3(1+ U0/U(pt)] / "V&" MO 0 20 40 60 80 100

Results 1. With the elaborated electrothermal device at minimal power (30 mW) and 50°C heating of the thermal elements is significant sensitivity and preciseness achieved as a result of the use of temperature sensitive p - n transistors. 2. The effect of the ambient temperature is compensated through change in the coefficient of amplifying of an operational amplifier, whose exit is graduated directly to indicate the relative humidity. The meteorological analysis, recording the effect of the factors disturbing the measuring gives the following results: 1.Th e methodical error at a calibrated temperature 20"C and a relative humidity 50 % is 1 %. 2. The additional errors from the change in the ambient temperature above and below the calibrated one are recorded thus: - in the temperature range 20-40"C the error increases by 2 %; - in the temperature range 10 - 20"C the error increases by 2.5 %; - for temperatures below 10"C the conditions of thermal transfer deteriorate strongly and the error increases as compared to the above ones.

References Philip, J. R., 1957. Journal of the Meteorological 14: 359 - 366. 642 Book of Abstracts 4th ESA-congress

STROMAL ENZYMES IN N-DEFICIENTWHEAT : mRNA AND PROTEIN QUANTITIES

S. J. Crafts-Brandner1, R Holzet, U Feller2

1TJSDA/ARS, Western Cotton Research Laboratory, 4135E . Broadway Rd, Phoenix, AZ85040 , U. S.A . 2Institute ofPlan t Physiology, University ofBern , Altenbergrain 21, CH-3103Bern , Switzerland

Introduction Nitrogen isremobilize d from senescing leaveso f cerealsan dtranslocate d to sinks(e.g . developing leaves, maturing grains). Ahig h percentage ofth e nitrogen present inth e mesophyll cellso fwhea t islocate d inth e chloroplasts (Peoples et al., 1988).Durin g leaf senescence, the photosynthetic capacity declines,protein s are degraded andbreakdow n products (amino acids) canb e exported viath e phloem (Crafts-Brandner et al., 1990,Felle r et al., 1994). It iswel l known that nitrogen deficiency accelerateslea f senescencei nintac twhea t plants,bu t the sequence ofevent si sno t yet satisfactorily identified. Inthi s study we determined the coordination between the abundances of ribulose-l,5-bisphsophate carboxylase/oxygenase (rubisco), rubisco activase and phosphoribulokinase (Ru5Pkinase ) and their respective transcripts (rbcS, rca and prk for rubisco small subunit, rubisco activase and Ru5P kinase, respectively). The chloroplast ATP-dependent proteolytic system Clpha srecentl y been described (Shanklin et al., 1995). The Clpproteas ei s composed oftw o unequal subunits (ClpP and ClpC). ClpP (proteolytic subunit) isencode d inth e plastome, while ClpC (ATPase subunit) isnuclear-encoded . Thefunction s ofthi s proteolytic systemar eno t yet identified. Especiallyth e role ofthi sproteas e inth e remobilization of chloroplast proteins during senescence isope nt o discussion. Thetranscrip t levelsfo r these two subunits(clpP an dclpC) wer equantifie d inth e second leaf ofN-stresse d wheat plants and of control plantsthroughou t the experimental period.

Methods Winter wheat (Triticum aestivum L., cv. Arina)wa sgrow n hydroponically (8plant s per pot containing 1L aerate d nutrient medium) ina culture room with alight/dar k cycle(1 4 hlight/1 0h darkness). Thenutrien t medium according to Hildbrand et al. (1994) wasuse d at half-strength prior to thebeginnin g ofth e experiment. After full elongation ofth e second leaf (14 d after imbibition),th e experiment wasstarte d andth eplant swer etransferre d to full strength nutrient medium for controls (+N) ort o nitrogen-deficient nutrient medium (-N). The second leafwa s sampled 0, 4, 8, 13,an d 18day safte r full leafexpansion . Thelea f sampleswer e extracted and analyzed for mRNA quantities (Northern blotting), protein quantities (SDS-PAGE and Western blotting),tota l RNA, total protein and chlorophyll.

Results Beginning at thetim e ofmaximu m leaf elongation there was adeclin e inth etota l RNAan d protein contents;th e declineswer e enhanced by removing Nfro m the nutrient solution. These results suggested that senescence ofth e second leafwa sinitiate d for both controls and N-stressed plantsnea rth etim e ofmaximu m leafelongation . In contrast to total RNAan d solubleprotein , chlorophyll levelsremaine d high duringth e experimental period. These results indicatetha t chlorophyll maydeclin e rather slowly and maytherefor e not be a suitable indicator for leaf senescence. Thepoo r correlation between chlorophyll content and senescence initiationi s consistent with previousreport s (Hensel et al., 1993,Smart , 1994).Th e quantity ofrubisc o closelyparallele d the declinei n soluble protein for controls and N-stressed plants. Rubisco activase quantity also declined for controls and to agreate r extent for N-stressed plants. In Division 1 643 contrast, Ru5P kinase quantity remained relatively stable over the 18-dayperio d for controls and evenunde r N-stress the protein was much more stable than rubisco and rubisco activase. Declines in rubisco quantity for both controls and N-stressed plants were associated with alarg e declinei n therbcS transcrip t per unit fresh weight within 4 daysafte r maximum leaf elongation. Rca transcript quantity remained highthroughou t the samplingperio d andwa sonl y slightly influenced by N-starvation. Prktranscrip t levels declined after full leaf expansion lessrapidl y than those for rbcSan d morerapidl y than those for rca. In contrast to rbcSan d rca,the prk transcript level remained higher inleave s ofN-deficien t plantstha n incontrols . Thetranscript s for clpPan d clpC were present throughout the sampling period, but after full leaf elongation a slight decrease was observed for clpC, whilefo r clpP anincreas e to thethree-fol d levelwa s detected. The transcript levelsfo r the Clp subunitstende d to be lower inleave s ofN-stresse d plantstha ni ncontrols , but the overall time courseswer e not markedly affected byth eN status. The expression ofthi s proteolytic system was apparently not restricted to senescence suggesting so far unknown physiological functions ofthi s protease throughout leaf development.

Conclusions Leaf senescence inyoun gwhea t plants started nearth etim ewhe nth e leafreache d itsmaxima l length. Oneo fth e senescence symptomswa sth e precipitous declinei nrbc S transcript quantity, whichwa s paralleled bya decrease inth e quantity ofrubisc o protein. For the other stromal enzymes investigated (phosphoribulokinase and rubisco activase),th etranscrip t and protein quantitieswer e not closely correlated. Asjudge d byth eprotei n and transcript quantities, the senescence program inleave s ofN-stresse d wheat plantswa s similar to that of control plantswit h adequate nitrogen supply, but thetim e courses differed (accelerated senescence underN-stress) . Thetw o Clp subunits were constitutively expressed and not only during senescence. Therefore Clp isno t a senescence-specific protease. However, it cannot be ruled out that Clp isinvolve d in some wayi nth e remobilization of chloroplast proteins during senescence. The mechanisms involved inth e degradation of stromal proteins andth e control ofthes e processes are not yet clear and lead to challenging questions for future experiments.

References Crafts-Brandner, S.J. et al., 1990.Photosynthesi s Research 23: 223-230. Feller, U. et al., 1994.Crititca l Reviews inPlan t Sciences 13: 241-273. Hensel,L.L . et al., 1993.Th ePlan t Cell 5: 553-564. Hildbrand, M. et al, 1994. Journal ofExperimenta l Botany 45: 1197-1204. Peoples, M.B. et al, 1988. Senescence and Agingi nPlants . LD. Noodén and A.C. Leopold (eds), Academic Press, San Diego, pp. 181-217. Shanklin, J. et al., 1995.Th ePlan t Cell 7: 1713-1722. Smart, CM, 1994.Ne w Phytologist 126:419-448 . 644 Book of Abstracts 4th ESA-congress

ISMOBILIZATIO N OFPRE-ANTHESI S RESERVES REFLECTED IN DRY MATTER LOSS FROM VEGETATIVE PLANT PARTS OF WHEAT?

T. Gebbing1'2, H. Schnyder1'2

1Institu t für Pflanzenbau, Universität Bonn, Germany 2Lehrstuh l für Grünlandlehre, TU München, 85350 Freising,German y (present address)

Introduction The importance ofreserve s in vegetative plant parts as asourc e of assimilate for grain filling of wheat has been studied and discussed controversially for many decades (for arevie w of the subject cf. Schnyder 1993).Reserve s already present at anthesis have received particular attention, because they may buffer grain yield against adverse conditions for photosynthesis during the grainfilling perio d (e.g.Bidinge r et al. 1977).Balanc e sheets of dry matter (DM)o f the vegetative above-ground plant parts havebee n used most frequently for estimation of reserve contributions to grain filling. Intha t approach the net loss of DMfro m vegetative above-ground plant partsbetwee n anthesis and grain filling isequate d withth e contribution of pre-anthesis reserves tograi n filling (Gallagher et al. 1976).Althoug h the method hasbee n subject to criticism (cf Schnyder 1993) the underlying assumptions have not been tested comprehensively. One of the most critical assumptions istha t changes in DMo f vegetative plant parts between anthesis and end Ofgrai n filling are due exclusively to storage and redistribution of assimilates. The identity of themajo r compounds mobilized during grain filling iswel l known. Starch is insignificant (e.g. Kiniry 1993),bu t large amounts of water-soluble carbohydrates (WSC,e.g . Kühbauch et al. 1989) and proteins (e.g. Austin et al. 1977,Spiert z et al. 1978) mayb e mobilized invegetativ e plant parts during grain filling of wheat.Th e objective of this study was totes t whether DM lossfro m vegetative plant partsbetwee n anthesis and grain filling accurately reflected mobilization of WSC andprotei n in wheat grown with differential nitrogen supply.

Methods In 1991an d 1992singl e plants of two spring wheat cultivars (cv Kadett and Star) wereestab ­ lished outdoors with two levels of Nfertilize r supply (24o r4 8 mgN pe r plant) at adensit y of 320plant s m'2.A t anthesis selected sets of uniform plants were transferred to agrowt h cabinet. Growth conditions were sett oreproduc e the local longter m average of weather conditions. Plants were sampled atanthesi s and atth e end of grain filling. Tillers were severed near soil level and assigned toth e main tiller or lateral tiller fraction. Main tillers were dissected into ear, leaf blades, leaf sheaths and stem. In 1992th eroot s plus crown were also sampled. After freeze drying main tiller ears were threshed by hand and separated intoth e grain and non-grain fraction (ear structures). Samples were weighed after drying, ground in abal l mill and analysed for WSC and Ncontent . Protein content wasestimate d asnitroge n content times 6.25.

Results Total loss of DMfro m above-ground vegetative plant parts between anthesis and grain maturity was 161m g per main tiller in 1991an d 389m gpe r main tiller in 1992(c f Table).Thes e losseso f DM significantly underestimated the mobilization of reserves (WSC and protein). On average of the different treatments reserve mobilization was 200% of the net loss of DM in 1991an d121 % in 1992.Ne t mobilization of WSC and protein was equivalent to 16-31% of grain yields (data not shown). Underestimation of reserve mobilization bybalanc e sheets of DM was Division 1 645

Table:Ne t loss of DM,protei n andwater-solubl e carbohydrates (WSC) from vegetativeplan t parts of spring wheatbetwee n anthesis andgrai n maturity. Data are means of twocultivar s and two nitrogen fertilization treatments.Negativ e values indicate accumulation of biomass.

DM Protein WSC -- net loss, mg per main tiller - Leaf blades 1991 57 55 7 1992 92 72 12 Leaf sheaths 1991 100 26 51 1992 107 27 74 Stem 1991 50 29 119 1992 244 33 219 Ear structures 1991 -46 24 12 1992 -54 24 12 — net loss, mg per plant — Roots plus crown 1992 292 25 42 mainly related to continued synthesis of structural compounds in stems and ears structures after anthesis. This process had amaskin g effect onreserv e mobilization asestimate d from balance sheets of DM.Further , although there were significant effects of cvs and Nfertilize r treatments onreserv e mobilization (data not shown),thes eeffect s were not apparent inbalanc e sheets of DM. Aclos e correspondence between mobilization of reserves and DM loss was only observed in leaf blades and leaf sheaths.D Mlos s from theroot s plus crown fraction was4. 4 times higher than could be accounted for by mobilization ofWS C andprotein . This was likely due to death and decay of roots.Reserv e mobilization in 1992wa s much higher than in 1991.Thi s effect was primarily due to higher pre-anthesis WSC accumulation. On average of years, cvs and N fertili­ zation treatments 80%o f the protein and 88%o f theWS C present in above-ground vegetative plant parts atanthesi s was mobilized during grain filling. Stems,lea f sheaths,lea f blades and ear structures contributed 21, 18,44 and 17%t oprotei n mobilization and 66,25, 4 and 5%t o WSC mobilization. These relationships werelittl e affected by cultivar andN fertilization.

Conclusions Pre-anthesis reserve mobilization wasno t accurately reflected inbalanc e sheets of DM of the above-ground vegetative plant partsbetwee n anthesis and grain maturity. Balance sheets of dry matter significantly underrated WSC andprotei n mobilization.

References Austin, R.B.e t al., 1977.Journa l of Agricultural Science 88: 159-167 Bidinger, F.e t al., 1977.Natur e 270:431-43 3 Gallagher, J.N. et al.,1976.Natur e 264: 541-542 Kiniry,J.R. , 1993. Agronomy Journal 85:844-84 9 Kühbauch, W.e t al., 1989.Journa l of Plant Physiology 134:243-25 0 Schnyder, H., 1993.Ne w Phytologist 123:233-24 5 Spiertz, J.H.J,e t al., 1978.Netherland s Journal of Agricultural Science 26: 210-231 646 Book of Abstracts 4th ESA-congress

CONTRIBUTION OFPRE-ANTHESI S RESERVES TO GRAIN FILLING OF SPRING 13 2 WHEAT:ASSESSMEN T BY STEADY-STATE COƒ C02 LABELLING

T. Gebbing1'2, H. Schnyder1'2, W. Kühbauch1

'institut für Pflanzenbau, Universität Bonn, Germany Lehrstuhl für Grünlandlehre, TU München, 85350Freising ,German y (present address)

Introduction In wheat (aswel l asi n other determinate crops) grain filling takes place during the last phaseo f the life cycle of the plants. Grains are filled while thephotosyntheti c apparatus is senescing. Fromthes e relationships one should suspect that grainyield swoul d vary strongly according to the environmental conditions during grain filling. Interestingly, however, grain yields seemt ob e buffered considerably. Animportan t role of pre-anthesis reserves inbufferin g grain yields against adverse conditions during grain filling hasofte n beendiscussed . However, the methods used to assessreserv e contributions to grain filling havebee n subject tocriticis m (e.g. Schnyder 1993).I n most studiesth epre-anthesi s reserve contribution wasequate d with the loss of dry matter (DM) from above-ground vegetative partsbetwee n anthesis andgrai nmaturity . This procedure may result in significant errors (Bidinger et al. 1977,Austi n et al. 1977,Gebbin g et al. 1996).I n afe w studies (e.g. Bidinger et al. 1977,Austi n et al. 1977) 14C pulse-labelling of photosynthate wascombine d with growthanalysis .Thi s approach likely gives more accurate results.Ideally , however, all reserve pools should be labelled uniformely, aprerequisit e not met inpulse-labellin g studies. In the present study steady-state labelling of all photosynthate-C fixed during thepost-anthesi sperio d wasuse d todetermin e thecontribution s of pre- ('non-labelled C') andpost-anthesi s photosynthate ('labelled C' inmatur e grains) to grain filling of wheat. Comparison withbalanc e sheets of reserves (water-soluble carbohydrates (WSC) and protein) in vegetative plant partsbetwee n anthesisan d grainmaturit y allowed an assessment of the apparant efficiency of pre-anthesis reserve utilization in grain filling.

Methods Forinformatio n onplan t growth and sampling procedures cf Gebbing et al. (1996).Briefly , in 1991an d 1992 single wheat plants wereestablishe d outdoors in pots.A t anthesis plants were transferred to agrowt hcabine t and allphotosynthat e fixed duringth e grain filling period labelled 13 12 with a C02/ C02mixtur e asdescribe d by Schnyder (1992).Isotop e composition of mature grain-C was analysed by isotope ratio mass spectrometry. Pre-anthesis photosynthate (i.e.pre - anthesis reserves) in mature grains wascalculate d from grainmass ,C concentratio n and the fraction of non-labelled Cderive d from Cisotop ecompositio n of mature grains.

Results Grain yields were similar inbot h years but thecontribution s of pre-anthesis reserves to grain filling differed greatly (Table).Thi s effect wasmainl y duet o higher pre-anthesis WSC accumulation in 1992(Gebbin g et al. 1996).Contribution s ofpre-anthesi s reserves tograi n filling ranged between 13an d 28% of mature grain mass andwer e higher at the low N fertilizer level inbot h years.Th e pre-anthesis reserve contribution to grain filling was closely related to the amount of reserves mobilized during grainfilling . Theaverag e apparent efficiency for conversion of mobilised pre-anthesis reserves into grain mass was high (86%,c f Figure). This efficiency estimate would beles s if losso f WSCan dprotei n from roots after anthesis were also included inth ecalculatio n (approx. 81%)o ri fturn-ove r of pre-anthesisWS Cb y post-anthesis photosynthate had occurred (approx.80%) . Division 1 647

Table:Mai n stem grain yields and pre-anthesis reserve contribution (±1SD) to grain filling of two spring wheat cultivars grown with differential nitrogen supply.

Year N supply Cultivar Grain yield Contribution of pre-anthesis reserves to grain filling (mgN pe rplant ) mg per main stem % 1991 24 Kadett 1434 227 +24 15.8 48 Kadett 1673 173 ±17 10.4

24 Star 1897 354 ±42 18.7 48 Star 2132 278 ±20 13.1

1992 24 Kadett 1439 408 ±45 28.4 48 Kadett 1829 359 ±17 19.6

24 Star 1747 489 ±25 28.0 48 Star 2000 428 ±34 21.4

600

<1> *i CO y=0.86x a 2 aCO C3 r =0.90 t« H 400 - _c U § u, u Alo wN Ka <4^ o 200 - c Ahigh NK a o vi c • lowN St ca o o. M a highN S t

Conclusions Pre-anthesis reserves wereutilize d efficiently andcontribute d significantly tograi n filling of non-stressed spring wheat.

References Austin, R.B.e t al.,Journa l of Agricultural Science8 159-167. Bidinger, F.e t al., 1977.Natur e 270:431-43 3 Gallagher, J.N. et al.,1976. Nature 264: 541-542 Gebbing, T.e t al., 1996.thi s volume Schnyder, H., 1992.Plant a 187: 128-135 Schnyder, H„ 1993. New Phytologist 123:233-24 5 648 Book of Abstracts 4th ESA-congress

CONTRIBUTION OFCARBOHYDRATE S TOWINTE R SURVIVALAN D SPRING REGROWTHO FWHIT ECLOVE R(Trifolium repens L.)

M.P. Guinchard, Ch. Robin

Laboratoire «Agronomie etEnvironnement» , ENSAIA-INRA,B P 172- F-5450 5 Vandoeuvre les Nancy, France.

Introduction White clover {Trifolium repensL. ) isth e most important pasture legume in regionswit h acool , temperate climate. The persistence ofwhit e clover ispartl y determined by the winter survival and spring regrowth. Starch isaccumulate d in leavesan d stolons during autumn (Vez, 1961; Guckert et al, 1983) and hydrolysed intofre e sugars during winter. But the role ofthos e reserves onth ewinte r survival and spring regrowth is notwel l understood. The aim ofthi s study wast o determine the contribution of carbohydrates reserves ofth e stolons onwhit e clover morphogenesis. Twocultivar swer eteste d (Huia and Aberherald) in ordert oisolat e genetics traits ofwinte r survival.

Methods The experiment was conducted in controlled conditions on plants pre-acclimated to low temperatures (10/4°C day/night) before they were submitted to chilling conditions (5/0°C day/night). After 28 days of chillingtreatment , all theleave s were cut and plantswer e submitted to aregrowt h period by raising the temperature of 2°Cpe r day until the 20/15°C day/night conditions were obtained. Controlled treatment consisted of setting the plants at 20/15°C immediately after the acclimation until theen d ofth e regrowth period. Thephotoperio d was 10h at250mmol.nr 2.s-1, with arelativ e humidity of 70%. Leaf appearance rate, leaf area, petiole length and stolon starch contentwer e determined atth e end ofth e chillingtreatment , and after the regrowth period on treated and controlled plants. Starch was analysed with ßamyloglucosidase at 55°C and enzymatically determined (Bergmeyer et al, 1974).

Results Chilling decreased significantly the leaf appearance rate,th epetiol e length and the leaf areaan d the stolon starch content inbot h cultivars (Table 1).Durin g the chilling treatment, Aberherald produced larger leavestha n Huia. During the regrowth period, the stolon starch content decreased both in controlled and in plants of the chillingtreatment . Atth e end ofth e regrowth period, Aberherald showed bigger leaves and ahighe r stolon starch content whereas therewa sn o difference between thetw o cultivars in the leaf appearance rate.

Conclusions We confirmed previous studies showingtha t starch accumulated in stolons ofwhit e clover during autumn ishydrolyse d during acol d period and during the regrowth (Guckert et al, 1983; Bertrand etal , 1991).Th ecultiva r Aberherald produced bigger leaves than Huia duringth e regrowth following chilling but nodifference s were observed between cultivarsi nth elea f appearance rate. Ahighe r dry matter and therefore abette r yield could be expected in spring for cv. Aberherald. This better production can be attributed to thehighe r stolon starch content atth e end ofth e chilling treatment and atth e end ofth eregrowt h period. Division1 649

Table 1.Lea f appearance rate,petiol e length,tota l leaf area and stolon starch content ofwhit e clover (cvHui aan d Aberherald) atth e end ofth e chilling (5/0°C)an d control (20/15°C) treatments and atth e end ofth e regrowth period.

CONTROL (20/15°C) CHILLING (5/0°C)

Huia Aberherald Huia Aberherald

Leafappearanc erat e(leaf.d -1) Chilling 0.27 0.27 0.02 0.02 Regrowth 0.21 0.27 0.18 0.21

Petiolelengt h perplan t(mm ) Chilling 855 860 179 201 Regrowth 140 161 138 192

Total leaf area(cm 2.pl._1) Chilling 71 89 20 31 Regrowth 16 23 17 23

-1 Stolon starch content (mg.g ! DW) Chilling 67 92 25 39 Regrowth 30 47 9 13

References Bergmeyer, H.U. et al., 1974.Method s of enzymatic analysis (H.U.Bergmeyer , ed), Academic Press,Ne w York, 3 :625-631 . Bertrand, A. et al., 1991.CanadianJourna l ofPlan t Science 71 : 737-747. Guckert, A. et al., 1983.Supplémen t del arevu eFourrage s 94-95 : 61-86. Vez,I , 1961. Bulletin delà SociétéBotaniqu e Suisse 71 :118-173 . 650 Book of Abstracts 4th ESA-congress

CONTRIBUTION OF IN VITRO PLANT CULTURES TO THE STUDY OF MINERAL NUTRITION

H.Lipavskâ , L.Nât r

Department of Plant Physiology, Faculty of Science, Charles University, Vinicnâ 5, 128 44, Prague 2, Czech Republic

Introduction In vitrotechnique s are used inman y fields concerning plantbiology . They also allow to exposeplant st o specific conditions and determine the plant response that cannot be observed in vivo. One of thesepossibilitie s is supplying theplan t with exogenous sugars, which enables to support growth of nongreen organs or isolated cells, but also uncoupling of processes that are mutually dependent inintac t plant viaphotosynthesis .

Methods The changes in chlorophyll content (Arnon, 1949) and drymatte r accumulation and allocation were determined in in vitrogrow n rape (Brassicanapus L.).Plant swer e grown 21 dayso n LS media(Linsmaie r etal, 1965)wit h 0, 1 and 3 % sucrose (treatment 1,2 , 3) and on the medium without inorganic nitrogen, with 1 or 3% sucrose (treatment 1-N,3-N ) and onL S medium with 1-10%sucros e (chlorophyll content determination) under dark and light conditions (16 h photoperiod, 550 umol m"2s"') .

Results The enhanced availability of sugar induced an increase inth e plant chlorophyll content (Fig. 1), although itwa sreporte d that high sugar concentration in the medium restricts chlorophyll synthesis in isolated cells (Neumann, 1973).

Fig.1 : Effect of exogenous sugar supply from the medium on the chlorophyll content in rape plants grown o 1 23456789 10 invitro SZ o sucrose concentration in the medium [%]

This effect might be connected with preferential dry matter allocation to root favouring the nitrogen availability and thus promoting chlorophyll synthesis. In light the total dry weight ofplant s grown with sucrose inth e medium and without inorganic N (-N) wasnearl y the same asi n the corresponding treatment with full N supply (Fig.2). Division 1 651

The dry matter allocation, however, differs remarkably. In both cases - in light and dark - the shoot/root ratio decreased with increasing concentration of sugar inth e medium, and further decrease was brought about byN deficiency (Fig.3).

Fig.2: Dry matter accumulation in rape grown in vitro on different 0 1 3 N1-N N3-N sucrose and nitrogen concentration treatment inth e medium.

o o Fig.3: The shootroot ratio in rape grown invitro on different sugar and nitrogen concentration in the medium d&M 0 1 3 X1-N X3-N treatment Conclusion The non-limiting exogenous sugar supply in combination withN deficiency strongly promoted root system development. Total dry weight of-N varianti n dark even exceeded thetota l dry weight of+N plants grown on the samesuga r concentration. It isobviou stha t invitro cultivation enabling longter m exogenous sugar supply from the medium offers new possibilities to study mineral nutrient effects bypassing their modulation of photosynthesis.

References Arnon, D.I., 1949.Plan t Physiology 24: 1-15 Linsmaier, E. etal., 1965.Physiologi aPlantaru m 18: 100-127 Neumann, K.-H., 1973.Plan tPhysiolog y 51: 685-690 652 Book of Abstracts 4th ESA-congress

APPLICATION OFDIFFEREN T FUNCTIONS TOTH EDESCRIPTIO N OF GROWTH OFBUCKWHEA T(FAGOPYRUMESCULENTUM MOENCH)

R. Maciorowski ,S . Stankowski1, G. Podolska2, A.Pecio 2

Department ofBiometry , Academy ofAgriculture , Slowackiego 17,71-43 4 Szczecin, Poland IUNG Pulawy, OsadaPalacowa , Poland

Introduction Forth e sake of common application of mathematical modelling in agricultural sciences, attempts of approximation of growthprocesse s by means of different mathematical functions become particularly important. From among many mathematical growth functions, the sigmoid curves withasymptoti c valueo f final size,hav efoun d arelativel y largeapplicatio n inth e description of completed growth processes (Causton et al., 1981;Hunt , 1982;Ramachandr aPrasad , 1992).I n thispaper , ausefulnes s of someS-shap ecurve sfo r description ofaccumulatio n ofplan t dry matter ofbuckwhea t (Fagopyrum esculentum Moench)wa s tested.

Methods The glasshouse experiment was carried out in 1992-1994 years in IUNG Pulawy. The objects of research wereplant so fbuckwhea t cv.Hruszowska . Theplant swer e grown inoptima l conditions offertilizatio n (N,P ,K m g andmicroelement s Fe,B ,Mn , Cu) and soil humidity, in Mitscherlich's potswhic h contained 7k gloa m soilmixe d with 2k gglas s sand.Th edr y matter of greenpart s ofplant s was measured every ten days.Th emea n yearly values of measurements obtained from 15plant s (3pot swit h 5plant s each) were used in further calculations. Constant parameters of theestimate d equations (Richard -[R], Simple logistic-[L],Gompertz-[G] , Janoschek-[J]) were determined numerically, using the quasi-Newton algorithm according to STATISTICA package.Afte r that, other characteristic parameters ofth e growthfunction : initial valuew 0, coordinates ofth e inflection point offunctio n graph (t;,w, )an d characteristic for that pointmaxima l theoretical growthrat e(dw/dt) max,wer ecalculate d according topreviou s studies (Zelawski et al., 1980,Gregorczyk , 1994).A s ameasur e offit precisio n oftheoretica l curvest o the empirical data,th eresidua l sum of squares S(WJ -Wj ) (where:w - empirica l values,w - theoretical values,j -numbe r ofmeasurements ) and correlation coefficient Rwer euse d (Maciorowski, 1995). Results Results are presented inth e Table and inFigure s 1 and2 . The characteristic parameters ofth e investigated functions, describing the accumulation ofplan t dry matter of buckwheat

Function w0 t, w, (dw/dt)max R S(WJ-WJ) [g] [day] [g] [g day"1]

[R]w=24.40(l+959.9e-0128t)1/(1-2104) 0.049 52.9 12.4 0.796 0.99 1.01 [L]w=24.46( l+631. 7e" 0123')" ' 0.039 52.5 12.2 0.751 0.99** 1.12 00768t [G]w=25.3 6exp(-38.3 9 e" ) 0 47.5 9.3 0.716 0.98** 4.00 [J]w=24.14(l-exp(-0.0176 4411441)) 0 0 53.7 13.0 0.707 0.99** 1.76 Division1 653

Figure 1.Th e investigated curves ascompare d with the experimental points.

.-y!/ ' vC--- Figure 2.Th e theoretical curves ^^>

References Causton D. R. et al., 1981.Th ebiometr y ofplan t growth, E. Arnold Publishers, London, 257p . Gregorczyk A., 1995.Act a Societatis Botanicorum Poloniae 1:5-7 . Hunt R., 1982.Plan t growth curves.Th e functional approach to plant growth analysis. E. Arnold Publishers, London, 248p . Maciorowski R. et al., 1995.Biulety n IHAR 194/195: 72-81. Ramachandra Prasad T.V . et al., 1992.Journa l Agronomy &Cro p Science 168:208-212 . Zelawski W.e t al., 1980.Act a Physiologiae Plantarum 2: 187-194. 654 Book of Abstracts 4th ESA-congress

ANATOMICAL AND BIOCHEMICAL CHANGES INGRAS S LEAVES DURING DEVELOPMENT

I.Maurice , F. Gastal

INRA, Station d'Ecophysiologie des Plantes Fourragères, 86600 Lusignan, France

Introduction Several physiological aspects of leaf growth oftall fescue (Festuca arundinacea Schreb.) have been described, mostly inyoun g leaves emerging from the sheath ofolde r leaves: anatomy, cellular dynamics (MacAdam et al., 1989),C metabolis m (Schnyder et al., 1987),N metabolism (Gastal et al., 1994),an d secondary cell wall deposition (MacAdam, 1988).Th e objectives ofou r study were to examine how some ofthes e aspects maychang e during leaf development, and to evaluate possible consequences for the costso f synthesis andth e quality of various segments of theleaf .

Methods Tillers oftall fescue were cutt o leavea 5 c m stubble,pu t inpot s containing sand and placed under controlled conditions.The y were allowed to grow for 19day sthe n were transfered to 1 hydroponics at21°C , 80%RH ,continuou s light (400 umol.m'ls" PPFD) and 7.5 mM N03 solution. After 15days ,tiller swhic h fastest growing leaf wasabou t to emerge into light were identified. Leaves from thispopulatio n wereharveste d after 0,2,4 , 6an d 8days . The leaves were cut into segments of 5, 10an d 20m m from baset otip . Onepar t ofth e samples was dried, weighed and analysed for fibres andminera l content withth e TDF method (Proskye t al., 1985),th e resultsbein g expressed asa weigh t ofenzymati c digestion residue. Theothe rpar t wasuse d to measure the width andth e areao f cross-sections. Leaf elongation rate (LER)wa smeasure d daily.Longitudina l distribution ofrelativ e growth rate (REGR) was assessed bymakin gfine hole s inth e growth zone (Schnyder et al., 1987).Thus ,w e were able to calculate thepathline s (i.e . lines ofdisplacement ) ofelement s along the leaf (dotted lines on Figs.3 an d4) .

Results LER averaged 1.3 mm.h"1throughou t theexperiment , andth e length ofth e growth was consistently 30-35mm .Fo reac h sampling date,th e width ofth e leaf increased along the growth zone (Fig. 1).Afte r amaximu m or aplatea u beyong the end ofth e growth zone,widt h decreased towards the tip.Th ewidt h of asegmen t leavingth e growth zone increased from day 0t o 8,bu t the increase wasmuc h less after day4 . This canb erelate d toth e size ofth e apical meristem, whichprogressivel y surrounds the apex, causing the leaf width toincrease . Average thickness (Fig. 2)wa s obtained bydividin g the areao fth e cross-sections by width Fig 1:Tim e course ofwidt h Fig 2: Time course ofaverag e thickness

DayO Day 2 Day 4 Day 6 Day 8

SO 100 150 200 250 300 50 100 150 200 250 300 Distance from leaf base (mm) Distance from leaf base (mm) Division 1 655 measured onth e sameleaf .A s forwidth , average thickness increased along the growth zone, but Fig3 :Tim ecours eo fdensit y inth eothe rpart so fth e leaf,th epatter no f thickness changes was different from that ofwidth . Fromth etip ,thicknes s increased markedly at first, then showed aslower ,bu tsteady , increase towards thebase .Thi s shows thatth emeriste m was still a, thickening, whereas itha d stopped widening. We also measured theheigh t ofridge s ofou rcross - • Day 2 sections,an d found thatth eincreas e in thickness A Day 4 • Day 8 nearth een d ofth e growth zone wasmainl y duet o anincreas e inth ethicknes s ofth emid-ri b (three 50 100 150 200 250 300 vascular bundles combining into oneridge) . Distance from leafbas e(mm ) Fig.3 show stha t foreac h day, drymatte r density decreased alongth eelongatio n zone(0-3 5mm) a s Fig 4: Enzymatic digestion residue elongation results from awate r influx that exceeds drymatte r deposition, andi tincrease d alongth e maturation zone (35-100 mm),a ssecondar y cell wall deposition and chloroplasts development occurs (MacAdame tal. , 1989).Nea rth eti p ofth e leaf, drymatte r density decreased. Dry matter density also increased withtime ,no tonl yi n growing ormaturin g parts ofth e leaf,bu tals oi n mature ones,a sshow nb yfollowin g the pathlines ofindividua l elementswit htim e (Fig. 3). 100 150 200 250 300 Theresidu e ofth e enzymatic digestion (Fig.4) was Distance from leaf base (mm) lowi nth e growthzone ,thoug hi tincrease d onda y 8,a scel l division must slow down. Thepathline s ofelement s indicate thatth erat eo fentr yo f fibres and minerals was highwithi nth ematuratio n zone,the n stopped around 100m m fromth e base.

Conclusions Drymatte r accumulated withtim e allalon gth e leaf.Ther emus t have beena nentr y ofsolubl e material, asth eresidu e ofenzymati c digestion couldno taccoun t forth e increase indr y matter beyond 100m m from the base.A tthi s point, segments were mature andha d emerged fromth e sheaths,s othe y would beabl et ophotosynthesis e andreduc enitrates .I ti slikely , especially under continuous light,tha t aconsiderabl e parto fthes e assimilates werebein g stored. Therefore, analyses ofwate r soluble carbohydrates andth e reducedN fraction arebein g donet oattemp tt o accountfo rthi s phenomenom. Successive segments increase inwidt h andthicknes s andbecom e denser. This implies thatth e costso fproductio n peruni t length oflea fmus t increase.Th e fact thatth e proportion ofnon - digestible material decreases withtim eha s implications forforag e quality and should be studied further.

References Gastal etal. , 1994.Plan t Physiol. 105:191-197 . MacAdam, 1988.Columbia , Missouri,Ph DThesis ,Universit y ofMissoury , 132p. MacAdam etal. , 1989.Plan t Physiol. 89:549-556 . Prosky etal. , 1985.J .Assoc .Off . Anal.Chem .68(4) :677-679 . Schnyder, H. etal. ,1987 .Plan t Physiol. 85: 290-293. Schnyder, H.e tal.,1987 . Plant Physiol. 85: 548-553. 656 Book of Abstracts 4th ESA-congress

STUDIES ONTH EACCUMULATIO N OFGLIADI N PROTEINS DURING WHEAT GRAIN DEVELOPMENT

N. Mladenov1, N. Przulj1,N . Hristov1, Y. Yan2, S.Prodanovic 3, S.Vuckovic 3

1Institut e ofFiel d and Vegetable Crops, 21000Nov i Sad, M. Gorkog 30,Yugoslavi a 2Southwes t Agricultural University, Chonqing, China 3Facult y ofAgriculture , Belgrade, Yugoslavia

Introduction Protein accumulation during different grain developmental stagesi sa nimportan t area inwhea t physiology and cultivation research. It iswell-know n that thebread-makin g quality ofwhea t is related to bothprotei n concentration ofgrain s andth e quality ofprotei n (Finney et al., 1948). Gliadinspla yimportan t rolei n determination ofbread-makin g qualitybecaus ethe y give extensibilityt o abrea d dough (Payne et al., 1984).Damidau xe t al.( 1978 )hav e studied the relationshipsbetwee n gliadin components andviscoelasti c properties ofduru mwhea t andthe y havefoun d aconsisten t relationship between thepresenc e ofparticula r gliadin components and quality ofgluten . Someinvestigation s on differential protein accumulation during grain development were carried out (Bushuk, 1971;Peltonen , 1992). In order to improve our knowledge ofwhea t storageproteins ,w efurthe r exploreth e accumulation traits ofgliadi n proteins during 12developmenta l stages ofgrai n filling intw o wheat cultivars.

Methods Materialsinclud etw o winter wheat cultivars:Prim a andN SRana-2 ,whic h wereplante di n 1995 atNov i Sad. Twelve grain developmentalperiod s studied werethos e initiated after pollination. Earswer e collected 2, 9, 14, 19,23 ,26 ,29 , 33,35 ,39 ,4 1 and 44 days after pollination. Gliadin electrophoresis was carried out according to theprocedure s ofLookhar t et al. (1978) andMetakovsk y et al. (1991)wit h somemodifications . Nine %Polyacrylamid e gel wasuse d for gliadin separation. Single seedwa s extracted with 70%aqueou s solutions of alcohol (150 (0.1 [seed1]) for about two hours.Fo r electrophoretic separation, 20 JJ.1 sample solutionswer eused . The electrophoretic apparatureuse dwa s DYY-III28Avertica l gel former with twelve gel slots(13 5 x 100x 1.5 mm).Electrophoresi s wasperforme d ata constant voltage (380V) for two and ahal fhour s at atemperatur e not exceeding 25°C.Whe n the second purple marker dyeban d ofmethy lgree nha smigrate d to the end ofth e gel,th e power wasturne d off, andth e gelwa sfixe d in 10%Tr iChloro-Aceti c acid (TCA)fo r anhal f hour and stainedwit h 0.04% Coomassiebrillian t blue R250 in 10%TC Afo r 24hours . Gliadin electrophoregramswer e determined onth ebasi s ofmetho d ofBushu k et al. (1978).

Results Results arepresente d inFigure s 1 and 2. Therapi d accumulation ofgliadi nprotein swa s observed in a short period (about 5days) ,namel y 19-23 daysafte r pollination. After 23 dayso f pollination, allgliadi n bandsbecam evisibl e onth e electrophoregrams andth e relative intensities ofal lband sreache d to the maximum. However,from 2 3 dayst o full maturity of grains,ther e existed smaller differences inrelativ eintensities , suggesting thatth e contents of gliadin componentshav e asligh t increase inthi speriod . Division 1 657

Number of sample 1 2 3 4 5 6 7 8 9 10 11 12 Figire. 1. Diagram;o fghadmetoroplioregiai ™ 0- atdiffavai t graindewloptiHta l stagesi nPnn m 10- Numbero fsampl ean dday safte r polimtion: 20- I. 2day s 2 9days 30- 3. 14day s 40- 4. 19day s 50- 5. 23 days = 6. 26day s 60- 7.2 9day s 70- 8.3 3day s 80- 9.3 5day s 10.3 9day s 90- II. 41day s 100- 12 44day s

Number of sample 23 4 567891 Figure, 2.Diagram so fgBadi nelectrophoregram s 0- R atdifferen t gramdevelopmenta lstage si nN SRana- 2 e 10- Numbero f samplean dday safte r pollination: 1 a 2°- 1.2 day s 2. 9day s ! 30- 1 3. 14day s v 40- 4. 19day s e 5.2 3 days 50- 6. 26day s m 60- o 7. 29day s b 70- 8. 33day s | 80- 9.3 5day s 1 10.3 9day s 90- t 11. 41day s y 100- 12.4 4day s

Conclusions In this work the accumulation of gliadin proteins during wheat grain development was studied. It was found that after 14day so fpollinatio n some gliadinband sbega n to appear. Furthermore, some gliadin components appear earlier than others,whic h is related to then- intensities. Generally, more intensiveband s appeared earliertha n lightbands .

References Bushuk, W. et al., 1978.Canadia n Journal ofPlan t Science 58:505-515 . Bushuk, W., 1971.Cerea l Chemistry 48:448-455 . Damidaux, R. et al.., 1978.Hebdomeda l Seanceso fAcadem y of Sciences, SeriesD , 287: 701-704. Finney, K. F., 1948. Cereal Chemistry 25: 291-312. Lookhart et al., 1982.Cerea l Chemistry 59: 178-181. Metakovsky, E. V. et al., 1991.Journa lo fGenetic s &Breedin g 45: 317-324. Payne, P. I. et al., 1984.Philosophi c Royal Society, SeriesB , 304:359-379 . Peltonen, J. et al., 1992.Finla nAgricultura l Science 1:499-506 . 658 Book of Abstracts 4th ESA-congress

COMPARISON OFTW ODESTRUCTIV E METHODSI NTH EESTIMATIO N OF GRASSLANDPRODUCTIO N

R.Mosquera ,E .Carrai ,A .Castelao ,E .Lopez ,C .Moirón ,A .Rigueiro ,J .Villarino .

Departamentod eingenierl aAgroforesta l yProductio nVegetal . EscuelaPolitécnica .Superior . 27002 Lugo.Spain .

Introduction Themos timportan twa yo f measurement ofgrasslan dproductivit y isprobabl yth eestimatio n ofdr y matterproduction . Therear esevera lmethod sestimat edr ymatte rproductio n whichca nb edivide di n destructive andnon-destructiv emethods .Destructiv emethod susuall yar emor eexac ttha nnon ­ destructive methods.Destructiv e methodsconsis to fcuttin ga predetermine d area.Th esiz eo fthi s areai son eo fth emor eimportan t decisionsfo r drymatte rproductio n estimation,a swel la ssampl e number.Large rcu tarea sar emor eprecis etha nsmalle rone sfo r drymatte rproductio n estimation becausevariabilit yi sreduced ,bu tth eharveste darea sca nno tb egraze di ngrazin gexperiment san d forthi sreaso nsampl esiz eshoul db ea ssmal la spossible .Th eobjectiv eo fth epresen texperimen t wast oevaluat etw osampl e sizesfo r estimate grassproduction .

Methods Twodestructiv emethod sfo restimatin ggrasslan dproductio n arecompare d ina establishe d experiment.. Thefirs t methodteste di susuall yuse dwhe nsimulatin ggrazin gexperiment s(smal lplo t experiments(Mosquer aan dGonzalez , 1996)), andth e secondon ei suse d inorde rt ostud ymor e frequently the grasslanddynami cparameter s(mea nan dinstantaneou s growthrate )becaus ei ttake s lessare aan dtherefor e moresample sca nb etake n(Mosquera , 1993). Theexperimen twa sconducte d inGalici a(N Wo fSpain) ,an di ti sa silvopastora l simulation. Main plotsize swer e 16 x 12squar emeter san d includedtw odifferen t grassmixture s(folium perenne + Trifolium repens + Trifoliumprantense andDactylis glomerata + Trifoliumrepens + Trifolium pratense), threedifferen t typeso ffertilizatio n ((40unit so fNitrogen )organi cfertilizer , inorganic fertilizer andn ofertilization) , twotre especie s(Betula celtiberica an dPinus pinaster) andthre e replicas.Th efirs t methodapplie dwa scu ta nare ao f2 x 5 squar emetre spe rplo tan dth esecon don e consistedo ffou r sampleso f0, 3x 0, 3squar emetre sobtaine da tth esam etime .Mean sfrom eac h treatment andmetho dwer ecalculate d anddifferen t relationships weremade .3 6an d 144sample s wereuse di nth efirst an dsecon dmetho drespectively . Linear,logarithmi c andquadrati c relationships wereteste d inorde rt ostud yth erelatio nbetwee nmethods .

Results Thelinear ,logarithmi can dquadrati cregression so ftw omethod sar eshow ni nTabl e 1.Linea ran d quadraticregression scoul db esee ni nFigur e 1. Theproductio n rangewa sfrom 114 0t o355 3k gpe r ha.Th ebes tfit betwee n methodswa sdescribe db ya quadrati cregressio n(r=0,85 )althoug h thelinea r regressionwa sgoo dto o(r=0,81) .Value sreporte d from quadratican dlinea rregression sar eno t different atintermediat e drymatte rproductio n (rangebetwee n 1700an d2800 )an ddifference s were shownwhe nthi sparamete rros e(above ,30 0k gD M/ha) .D Mvalue sfrom 0. 3 x0. 3m metho d between 1500an d200 0k gDM/h acorresponde dt o 1500t o250 0an dtolOO Ot o280 0fo r linearan d quadraticregressio n with2 x 5 m method ,respectively . However,highe rproductio nvalue sfo r0. 3 x 0.3 methodbetwee n200 0an d300 0k gDM/h awer erelate dwit h 800k gDM/h amor ewit h2 x 5 m method. Differences betweenmethod scoul db eexplaine d becausewhe ndr ymatte rproductio nros esmalle r sizesample swer eassociate d withhighe rgras sheigh tan di ti sver ydifficul t tolimi tth esquar e borders,an davoi dborde reffects . Biggersiz esample sar eles saffecte d byth eborde ran dthi s Division1 659 problem isavoided .A nare ao f 1 cmborde rmean ta 12%an d 1 %borde ro ftota lare a for small(3 0 x3 0cm )an dbigge r(50 0x 20 0cm )sample .A nothe rreaso ncoul db etha tth eusua lvariabilit y associatedt ograsslan dare ai shighe rwhe nproductio nrise san d iscompensate d insample swit h largearea sbecaus e lower andhighe rproductiv e areasar erepresente d inth e samesample ,whic h doesno toccu rwit hsmalle rsamples .Relativ evalue so fbot hmethod sshowe dtha thighes t production valueswit h0. 3x 0. 3m method swer erelate dt ohighes tproductio nvalue swit hth e2 x 5 m method .

Table 1. Linear,quadrati c andlogarithmi cregression sbetwee nD Mfrom 5 x 2 m metho dan d DM' from 0.3x 0. 3metho d Model Parameters a b DM= a + bDM ' -1356 1.93 0.81 DM= a + bDM '+ cDM' 2 -9247.5 9.44 0,0017 0.85 LDM=a+ bDM ' -29230 4181.16 0.84

Tm DM/Ha

33 375 Tm DM/ha Figure 1. Linearan dquadrati cregression sbetwee nth etw odestructiv emethods .X axi srepresent s DM/hao f0. 3xO. 3 methodan dY axi sDM/h ao f2 x 5 m method .

Conclusions Alarge rsampl esiz erepresent sbette rth eproductio nheterogeneit y inth ecu tare atha nsmalle r samples,bu tdestro yto omuc harea .Difference s betweenmethod sincrease d above200 0k gDM/ha ,a rangeassociate dwit hlo wgras squality ,an dtherefor e itshoul dno tb euse dwit hgrazin gexperiments , whereth esmal lare asamplin gmetho d shouldb euse .A nimportan tcorrelatio nbetwee nrelativ e valueso fproductio n resultsfo rth etw omethod swer efoun d andbot hmethod sca nb euse d dependingo nobjectives ,variabilit y andavailability .

References Mosquera,R. , 1993.Producció ny manej od eforraje s enu ssistem ad eproducció n lechero.Tesi s Doctoral. Universidad de Santiagod eCompostela . 295p p Mosquera, 1996.Efect o del afertilizació n nitrogenada ypotâsic asobr el acomposició n quimicad el a pradera. Actasd el aSEE P(e nprensa) . 660 Book of Abstracts 4th ESA-congress

STUDYO FNO NA DESTRUCTIV E METHODFO RDR YMATTE RYIEL DESTIMATIO N INDAIR Y ROTATIONALSYSTEM .

M.R.Mosquera-Losada' ,A .Gonzalez-Rodriguez 2

'Departamentod eIngenieri aAgroforesta l yProducció nVegetal .Escuel aPolitécnic a Superior.2700 2 Lugo.Spai n 2Centrod eInvestigacione sAgraria sd eMabegondo .Apartad od eCorreo sn ° 10.L aCoruna . 15080 Spain.

Introduction Theus eo fheigh ta sa predictin gmetho do fD Mfo rpastur eyiel dhelp sth efarme rt omanag ehi sow n landfo rmil kproduction . Iti sa neasy ,chea pan dno ndestructiv etechniqu efo rdecidin gth etarge t DMfo rth ecow smovemen t inth erotationa l systems.D Man dheigh trelationshi pi sno tconstan t throughth eyea rbecaus e iti saffecte d bydifferen t density,s opastur ewit hlo wdensit yshoul db e 1 or 2c mhighe ri norde rt oachiev eth esam eD Mtarge ttha nhighe rdensit ypasture s(Wright , 1985). Heightan dD Mrelationshi pshoul db estudie di nth edifferen t seasonsbecaus eo fdensit ychange s throughth eyea ra swel la spastur eproductivit y (Mosquera, 1995).

Methods Sampleswer etake n inpasture sgraze db ydair ycow si nGalici a(North-Wes to fSpain) . Cowswer e managedi na flexibl e rotational system(Mosquera-Losada , 1993).A rising-plate swar dstic kmetho d wasuse di norde rt odetermin eth eswar dheight . Itconsiste d ofa plat ewhic h hasa scal efo r height determination asdescribe db yFram e(1981) .Th edr ymatte rproductio n wasestimate d byth ecu to f five 0,33x 0,3 3m area swit hbatter yoperate d shearst o2, 5c mabov egroun dbefor e and after grazing. Sampleswer edrie dan dweighe dindividually . Heightwa sestimate d inth esamplin gare a beforecutting .Th ecorrelation swer estudie ddurin gthre eyear s(1989,199 0an d 1991)an dthre e periods(spring ,summe ran dautumn) .Differen t linear,quadrati can dlogarithmi cmodel swer e fitted toth edata .

Results Thestudie drelationship sbetwee nD Mproductio n andheigh tar epresente d inTabl e 1. Therewa sa highcorrelatio nbetwee n heightan dproductio n asfoun d byO'Sulliva net al. (1987).Linea r relationshipha dth ehighes tcorrelatio ncoefficien t (0.78,0.91an d0.7 3fo r spring,summe ran d autumn,respectively )a swel la sth equadratic . Bestrelationship s werefoun d inth esummer ,sprin g andautum ni nthi sorder . Linearregressio nha dsimila rslope sfo rth ethre e studiedperiods ,howeve r changesi ndr ymatte rpe rcentimetr ear ehighe ri nth esprin g(153 1k gha" 1) andautum n(138 8k gha " ')tha ni nth esumme r(113 4kg"' )a ta targe theigh to f 10 cmrecommende db yMayn eet al. (1984). Thishighe rdr ymatte rchang efo rever ycentimetr e canb eexplaine db yth e fact thatth egrasslan d is lessdens edurin gth esprin g andautum ntha n duringth e summer(Mosquera-Losad a andGonzalez - Rodriguez, 1994). Linearcorrelatio nwa ssimila rt otha tfoun db yHode net al. (199 1) wit hdair ycow s ata stockin grat eo f2. 3cow spe rha .O nth eothe rhand ,offere d pastureproductio n wasver ysimila r forquadrati cregression sfo rth esam etarge t height(1487,149 7an d 1348 kgha" 1 for spring,summe r andautumn ,respectively) .Linea rrelationshi p ispreferre d inspit eo fhavin gth esam evarianc e explainedtha nquadrati cregressio n becauseo f thesimplicity . Division 1 661

Table 1. Drymatte r (DM, kg/ha)an dheigh t(H , cm)relationshi p inth ethre estudie dperiod s(spring , summeran dautumn )an dmea no fth ethre eyear s Model Parameters r RSD a b c Spring DM = a bH -49.1 155 - 0.78 419 DM= a bH cHz 142 116 1.85 0.78 419 LDM=a bH 6.13 0.1 - 0.81 - DM=a- bLH- cLU1 1514 -1647 715 0.77 423 LMS=a bH cH2 5.67 0.2 -0.004 0.82 - LMS=a bLH+cLH 2 5.10 0.85 0.04 0.83 - Summer DM = a +b H 176 131 - 0.92 343 DM= a + bH +cH 2 93 145 -0.46 0.92 343 LDM= a +b H 6.44 0.07 - 0.85 - DM= a + bLH +cLH 2 1373 -1361 618 0.92 348 LMS== a + bH + cH2 5.93 0.16 -0.002 0.89 - LMS== a + bLH+cLH2 4.49 1.50 -0.11 0.91 - Autumn DM = a +b H 1.41 139 - 0.73 276 DM= a bHH ctf 792 -52.41 10.810.7 5 269 : LDM =a -bH 6.04 0.11 - 0.69 - DM= a + bLH+ cLH 2 5016 -4936 1457 0.75 267 LMS==a+bH+cH 2 6.29 0.05 -0.0030.6 9 - LMS== a+ bLH+cLH 2 8.65 -2.59 0.84 0.70 - Conclusions Agoo drelationshi pbetwee nD Mproductio nan dheigh ti ndair yrotationa l systemswa sfound . Linear correlationshipwa spreferre d to quadratican dlogarithmi c(i nspit eo fhavin gth esam evarianc e percentageexplained )becaus eo fsimplicity .

References Frame,J. , 1981. Herbagemass .I n"Swar dmeasuremen t handbook"Hodgso ne tal .(Eds )Grasslan d SocietyHurle yBr . Pp:39-69. Hoden,A . etal. 1991. Journal ofAgricultura l Science,Cambridge , 116,116417-428. Mayne,CS. ,et al.. 1984.Gras san dForag eScience , 42:59-72. Mosquera,R. , 1993. Produccióny manej od eforraje s enu ssistem ad eproducció n lechero.Tesi s doctoral.Universida d deSantiag od eCompostela . 295p p Mosquera,R . etal. 1995 .Estudi od el acomposició nbotanic ae nsistema slechero ssometido sa distintacarga .Congres o 1995d el aSocieda dEspanol ad eMalherbologia . O'Sullivan,M . etal, 1987.IrishJourna lAgricultur e Research, 26:63-68. Wright, I.A., 1985.Forag eheigh tan dmas si nrelatio nt ograzin gmanagement . En"Emergin g technologyan dmanagemen t forruminants" .Eds .F.H .Baker ,M.E . Miller,M.E .Westuins sPres sfo r WintockInternationa l Boulder,co:341-348 . 662 Book of Abstracts 4th ESA-congress

RESPONSE OFBUCKWHEA T VARIETIES GROWN ON DIFFERENT SOIL TO DIMETIPIN

J.Pawlowska, D.Dietrych-Szóstak, A.Pecio

Institute of Soil Science and Plant Cultivation OsadaPalacowa , 24-100Pulawy , Poland

Introduction Buckwheat isregarde d asa one ofth e mostvaluabl e cereal crops duet o nutrients in itsseed s such as K, P, easily assimilable protein, Fe, Cu and vitamins. The seedsals o contain rutin, which isuse db y pharmaceutics (Kusiorska et al., 1993). The acreage ofbuckwhea t cultivation extends on various soils. The reasons for buckwheat yielding deceptiveness result mainly from itsgenetic s and biology. In order to advance and equate seedripening th e dimetipin growth regulator hasbee n used for several years.I n previous studies some differences in di- and tetra-ploid buckwheat varieties response to the chemical werefoun d (Ploszynskie t al., 1993;Dietrych-Szósta k et al., 1994; Dietrych-Szóstak et al., 1995). Thepoin t ofth e presented studywa st o determine the differences between buckwheat varieties (under various soil conditions) responset o dimetipin.

Methods The experiment was conducted on plotsfilled wit h the eight different types of soils(Tabl e 1)occurin g inPolan d the most frequently.

Plot nr Soiltyp e Soil suitability complex

1 black earth verygoo d wheat complex (1) 2 brown alluvial soil good wheat complex (2) 3 brown soil developed good wheat complex (2) from loess 4 typical brown soil verygoo d rye complex (4) 5 limestone soil defective wheat complex (3) 6 typical brown soil good ryecomple x (5) 7 acid brown soil weak rye complex (6) 8 acid brown soil verywea k ryecomple x (7)

Plotswer e fertilized according to standards (Dietrych-Szóstak et al., 1994).Tw o buckwheat varieties weretested : diploid-Koraan d tetraploid-Emka. Buckwheat plantswer e sprayed once with Harvade 25F (500 g dimetpin/ha) atth ebeginnin g offul l ripening. The control plantswer e treated atth e same timewit h distilled water. Plantswer e harvested atth e full ripening. Yield were analyzed (g/conted per plant) aswel l asprotei n in nuts (%N x 6.25) inautomati c Contiflo system. Division1 663

Results Results are presented in the Table2 .

Yield ofbuckwhea t seeds and protein content inbuckwhea t nuts subject to soil conditions after dimetipin application

Plot Weight ofseed s Protein nr Control Dimetipin Control Dimetipin Kora Emka Kora Emka Kora Emka Kora Emka

1 0.82 0.55 1.93 1.17 12.5 12.3 11.9 12.6 2 1.04 0.79 2.15 1.16 12.6 12.8 12.1 12.3 3 0.86 0.80 2.83 1.52 12.1 13.1 13.4 13.8 4 1.02 0.94 3.03 1.88 12.6 12.7 12.8 13.2 5 0.40 0.44 0.53 0.80 11.1 11.6 11.8 12.6 6 0.81 0.58 2.14 1.40 10.6 11.1 11.6 12.5 7 0.22 0.24 0.59 1.28 11.6 12.4 12.1 12.9 8 0.23 0.30 0.53 1.03 11.9 12.1 11.6 12.5

The seed yield ofbot h buckwheat varieties significantly increased after dimetipin treatment duet o seed shape improvement. In case of diploid varietyKora , which created more tillers differences were moretangibl e than inth e case oftetraploi d Emka. Onbette r soils(comple x nr 1,2 , 3,4 , 6) the effect was much more cleartha n on the poorer soils(comple x nr 5, 7, 8) and the seed yield per one plant of Kora was higher than theyiel d ofEmka . On poorer soilsEmk a was more productive.

Conclusions Growth regulator dimetipin increasesbuckwhea t seedyiel d by equalization ofripening tim e and seed shape improvement. The results confirm the previous study ofDietrych-Szósta k et al.,1994. Before making adecisio n to apply dimetipin, the genetic features ofbuckwhea t varieties should betake n into consideration. The seed yield ofdiploi d variety washighe r on better soils,tetraploi d one - on poorer soils.

References Dietrych-Szóstak, D.,Pawlowska , J.,1994.Fagopyrum 14:59-61. Dietrych-Szóstak, D., Pawlowska, J.,1995.BiologicalBulleti n ofPoznan , Poland, 32:31p. Kusiorska, K.et al.,1993. Acta Academiae Agriculturae acTechnica e Olstenensis 56:229-237. Ploszynski, M. et al.,1993.Materiafy XXXIII Sesji Naukowej Institute ofPlan t Protection ofPoznan , 194-197. 664 Book of Abstracts 4th ESA-congress

INFLUENCE OFINORGANI C NITROGEN ON SENESCENCE AND PROTEIN REMOBILIZATION INFLA G LEAVES OFMATURIN G WHEAT GROWN ON WATERLOGGED SOIL

R. Pfarrer, U.Felle r

Institute ofPlan t Physiology, University ofBern , Altenbergrain 21, CH-3013Bern , Switzerland

Introduction Various stresses, such asnutrien t depletion, drought, heat or waterlogging can influence senescence inplant s (Noodén, 1988).Waterloggin g causes oxygen deficiency and affects the availability ofnutrient s for the plants (Ponnamperuma, 1984).Limite d oxygen availability inth e soilalter sth e energy metabolism inplan t roots (Reggiani et al., 1985;Sagli o et al., 1980). Waterlogging duringth e grainfilling perio d mayreduc euptak e ofnutrient s byth e roots and translocation ofnutrient sfrom senescin g leavest o the maturing grains and asa consequenc e also grainyiel d (Cannell et al., 1980; Stieger et al., 1994a; Trought et al., 1980;Watso n et al., 1976). Plant roots aretherefor e directly influenced bywaterlogging , whereasth e shoot mayb e affected indirectlyb y changes inroo t activities and inth e composition ofth exyle msap .Protei n remobilization isaccelerate d inwhea t leaves onflooded soils . The supply ofnutrient s to the soil can modify plant responses to waterlogging. Nitrogen can alleviateth e adverse effects of waterlogging on shoot growth, but nitrogen alone could not improve shoot growth ifth e supply ofothe r ionsbecam e limiting (Woodford et al., 1948;Garcia-Nov o et al., 1973;Drew , 1991). Inth ewor k presented here, theinfluenc e of additional inorganic nitrogen onlea f senescence and protein remobilization was investigated inwinte r wheat {Triticum aestivum L., cv. Arina)grow n onwaterlogge d soil.

Methods Winter wheat {Triticum aestivum L., cv. Arina)wa s grown inlarg e polyethylene pots (0.36m diameter, 0.38 mhigh ) embedded inth efield. Th e soili nintac t pots wasflooded permanentl y from anthesist o maturity, while incontro l potswit h holes inth ebotto m the soilwa s well aerated throughout the maturation period (aerated controls). Nitrate (chloride for controls)wa sfe d viaa flap into the stembelo w theflag lea fnod e (10 mlsolutio n per plant, containing 10m MCa(NOs) 2 or 10m MCaCl 2). Feeding started atth e sametim ea s flooding. Each leaflamin a was homogenized in 10m l2 0 mM sodium-phosphate buffer pH 7.5 witha polytron mixer. Thehomogenat ewa sfiltrated throug h Miracloth (Calbiochem, SanDiego ) and wasuse d directly for chlorophyll determination and after centrifugation for the quantification of soluble proteins andfree amin o acids inth e supernatant (Stieger et al., 1994ban d references therein).

Results Thefresh weigh t ofth eflag lea flamin awa s reduced inal lflooded plant s ascompare d to control plants onwel l aerated soil. Thiseffec t was lesspronounce d when theflooded plant swer e fed with additional nitratevi a a stemflap belo w theflag lea fnode . Flag leaf senescence -a sjudge d byth e net protein and chlorophyll degradation -wa s accelerated inwhea t plantsb yflooding. Th e losso f chlorophyll and protein started later and proceeded more slowlyi nth eflag lea flamin a of plants fed with additional nitrate, while chloridewa stotall y ineffective. No major increase inth e content offree amin o acids inth eflag lea flamin awa s observed during therapi d senescence caused bywaterloggin g inabsenc e ofadditiona l nitrate. Thisresul t indicates that thefree amin o acids, derivingfrom protei n catabolism, were efficiently exported via the phloem. Onth eothe r hand,th e level offre e amino acidsincrease d initiallyi nth eflag lea flamin a Division 1 665

ofplant sfe d with additional nitrate and decreased againtw o weeks after thetreatment . Theleve l of solubleprotei n was higher inth eflag lea flamin a of plantsfe d with additional nitrate than inth e other treatments (chloride feeding / no feeding) onflooded soil . Thisresul t indicatestha t the additional nitrate was at least partially assimilated and used for amino acid and protein synthesis. In summary, calcium nitrate fed via stemflap belo w theflag lea fnod epartiall y compensated inth e flag leaflamin a the senescence promoting effect ofwaterloggin g while calcium chloridewa s not effective. These findings indicatetha t inorganic nitrogen (nitrate) influenced inthes e plantsth e time course of senescence, whileth e accompaning cation (calcium) or another anion (chloride) caused no major effect.

Conclusions Nitrification isreduce d and denitrification is stimulated insoil sunde r hypoxia, causing higher ammonium (mainly sorbed to soil particleswit h cation exchange properties) and lower nitrate contents. In general, inorganic nitrogen isles savailabl e for crop plants grown onflooded soi lan d may cause anticipated senescence. Nitrate fed ina hig h concentration directly intoth exyle m below theflag lea fnod e delayed the rapid senescence inth eflag lea flamin a afterflooding. Thi s result indicatestha t theflux o finorgani c nitrogent o thelea fca n serve asa signali nth e system. However, the effect ofwaterloggin g was onlypartiall y compensated byadditiona l nitrate, indicating that other signalsfro m the roots (e.g. phytohormones) are still effective (Neumann et al., 1990). Therefore inorganic nitrogen mayb e arelevant , but not the onlyregulatin g factor in this system.

References Cannell, R. Q. et al., 1980.Journa l of Science ofFoo d and Agriculture 31: 117-132. Drew, M. C, 1991. In" Plant life under oxygen deprivation" (Eds. Jackson, M. B. et al.), Academic Publishing, TheHague , 303-316. Garcia-Novo, F. et al., 1973.Ne wPhytologis t 72: 1031-1039. Neumann, D. S. et al., 1990.Journa l ofExperimenta l Botany 41: 1325-1333. Noodén, L. D., 1988.I n"Senescenc e and agingi nplants " (Eds.Noodén , L. D. et al.), Academic Press, SanDiego , 1-50. Ponnamperuma, F. N., 1984.I n"Floodin g and plant growth" (Ed. Kozlowski, T. T.), Academic Press, London, 9-45. Reggiani, R. et al., 1985.Journa l ofExperimenta l Botany 36: 1698-1704. Saglio, P. H. et al., 1980.Plan t Physiology 66: 1053-1057. Stieger, P. A. et al., 1994a. Plant and Soil 160:87-95 . Stieger, P. A. et al., 1994b.Plan t and Soil 166: 173-179. Trought, M. C. T. et al., 1980.Plan t and Soil 56: 187-199. Watson, E. R. et al., 1976. Australien Journal ofExperimenta l Agriculture and Animal Husbandry 16: 114-122. Woodford, E. K. et al., 1948.Annual s ofBotan y 12:335-370 . 666 Book of Abstracts 4th ESA-congress

WATER DEFICIT AND POLLINATION POTENTIAL OFWHEA T(Triticum aestivum L.)

K. Streiff, A.Blouet , A.Gucker t

Laboratoire Agronomie-Environnement /INR A EcoleNational e Supérieure d'Agronomie et desIndustrie s Alimentaires 2, avenue del aforê t deHaye , 54 500Vandoeuvr e lèsNancy , France

Introduction The recent use of CHA (Chemical Hybridizing Agent) has allowed the commercial production ofhybri d wheat. Butth e success of hybrid seed production depends greatly onth e aptitudeo f thepollinato r variety to spread alo t ofviabl e pollen grains. Many environmental factors affect thepolle n quality and quantity (Stephenson et al., 1992).On eo fth emajo r factor seemst ob eth e water stress (Saini and Aspinall, 1981).

Methods After 6week s ofvernalization , individual plants ofwinte r wheat (var. Virlor) developed ina growth chamber with constant day/nighttemperatur e (respectively 16°Can d 12°C) , 75% relative humidity and 16hour s daylength (500 u.mol.m-2.s-l) . Plants were grown in individual pots containing a mixture of peat, sand and perlite (50/30/20,v/v/v) . Plantswer e subjected to a shortwate r deficit bywithholdin g the water supply during pollen meiosis. Pollenviabilit y was investigated by microscopic examination of pollen stained with a solution of FDA (Heslop-Harrison andHeslop-Harrison , 1970).A coloratio n with DAPIwa suse dt o test the nuclear conformity ofpolle n grains(Colema n and Goff, 1985). Todeterminat e anther length and number of pollen grains per anther, 10anther swer e analysed by the method suggested by DeVrie s (1974). Totes t the germinability ofpolle n grains, excised stigmas from emasculated flowers were transferred topetr i dishes containing a medium ofBrewbake r andKwac k (1963) and were pollinated. Thepercentag e ofgerminate d pollengrain s was determinated after astainin gwit h anilin blue (Kho and Baër, 1968). Datawer e subjected to statistical analysis using the procedure onewa y ANOVA of the SYSTAT package. Means were compared by the Tukey test .Values significantly different (p=0,01) are indicated by a different letter.

Results 0 »=«=

•a g -I a rewatenng

-3 o- 2 4 6 8 10 12 14 16 Days from withholding water supply Figure 1.Cours e ofth e 7th leaf water potential. Open symbols represent the control values.Eac h value isa mea n of 5repetitions . Vertical bars indicate the standard deviation. Division 1 667

The water potential ofth e leaf decreased slowly and it reached -2 MP a duringth e stage of pollen meiosis.

Table 1. Effect s ofwate r stresso n the plant height and on pollen production .Eac h value isa mean of 10repetitions . Treatment Plant height Number of Anther length Number ofpolle n (cm) spikeletspe r spike (mm) grains / anther Control 47.4 a 19,8 a 3,18 a 2580 a Water stress 36.5 b 18,2 b 2,66 b 1820 b

All the measured parameters were significantly affected by thewate r stress (Table 1).Th e height ofth eplan t was reduced by 23% . This is particularly unfavourable for the hybrid seed production because itha s been showed that thepolle n transport was betterwhe n the pollinator plantswer ehighe rtha nth e male sterileon e(D eVries , 1972). Thenumbe r ofpolle n grains per anther decreased alsob y 29% whe n the plantswer e stressed.

Table 2 . Effects ofwate r stress on the pollen quality. Each value isa mea n of 10repetition s Treatment Pollen viability (%) Pollen conformity (%) Pollen germinability (%) Control 81.8 a 91,3 a 22,9 ±15 Water stress 62.9 b 71,2 b 8,3 ±9,8

The pollen quality was also strongly affected by thewate r deficit (Table 2). Thepercentag e of nonviabl e and nuclear abnormal pollen grains increased by 20% o n stressed plants. These results agreed with those found by Saini and Aspinall (1981). The effects onpolle n could be attributed toa n increase in endogenous abscissic acid (Morgan , 1980; Saini et al., 1984). Water stress reduced thepolle n germinability non significantly by 63% . Finally, the production ofviabl e pollen per spike (i.e . thepollinatio n potential) was reduced by 50% on stressed plants.

Conclusions This study showed that even ifth ewate r deficit lasted only 7days ,th epollinatio n potential was strongly affected. And, in thefield, i tha sbee n showed that the limitingfacto r for the hybrid seed production was the quantity ofviabl e pollen disseminated (Khan et al, 1973). So,i n countries wherewate r stress can occur during the sensitive stage ofpolle n meiosis, itwoul d be necessary to irrigate in ordert o optimizeth e hybrid seed production.

References Brewbaker, J. L. and Kwack, B.H., 1963.Polle n physiology and germination-International symposium. University ofNijmegen . Ed. H.F .Linskens , 143-151. Coleman, A.W . andGoff , L. J, 1985.Stai n Technology 60 :145-153 . De Vries,Ph. , 1972.Euphytica2 1 :185-203 . De Vries,Ph. , 1974.Euphytica2 3 :11-19 . Heslop-Harrison, J. andHeslop-Harrison , Y., 1970. Stain Technology 35 : 225-227. Khan, M.N . et al., 1973.Cro p Science 13 : 223-226. Kho, Y. O. and Baër,J. , 1968.Euphytic a 17 : 298-302. Morgan, J. M., 1980.Natur e 285 : 655-657. Saini,H . S.an d Aspinall, D. 1981.Annal s ofBotan y 48 : 623-633. Saini,H . S.e t al., 1984.Australia n Journal ofPlan t Physiology 11 : 243-253. Stephenson, A. G. et al., 1992. Ecology and evolution of plant reproduction :a ne w approach. Wyatt R. (Ed), Chapman and Hall,Ne w York, 119-136. Division2

Agroclimatology and modelling. 670 Book of Abstracts 4th ESA-congress

ESTIMATING ZERO PLANE DISPLACEMENT AND ROUGHNESS PARAMETERS IN A SUNFLOWER CROP

V.Magliulo 1,F .D eLorenzi 1,L . Lustrini1, A.Pitacco 2

1 CNR-IrrigationInstitute , P.O.Bo x 101,-80040 - S. Sebastiano al Vesuvio (Naples), Italy 2University ofPadova, Via Gradenigo,6 -35131- Padova, Italy

Introduction Roughness lenght (zj and zeroflux plan e displacement height (DJ are required parameters for both crop modeling and irrigation scheduling purposes (Smith et al., 1991). Wieringa (1992) recently reviewed roughness estimatesfo r various crops and terraintypes . Reported values for cropsrange d between 0.05 and 0.18(a s afunctio n ofcro p height), but no papers deal with sunflower, and few authors monitored the above parameters covering aful l growth cycle. The present paper reports data for a sunflower crop startingfrom a heigh t of0. 5 munti l maturity

Methods Asunflowe r crop(c vMimosa' ,maturit ygrou pI )wa ssow ni nVitulazi o(Caserta , Southern Italy)o n June 13, 1995a ta densit yo f5. 5plant spe rsquar emeter .Fertilizatio nconsiste d of20 0k gTon spe r hectareo fure aan d 500k gpe rhectar eo fsuperphosphate ,broadcas tbefor e sowing.Th ecro pwa s cultivatedfollowin g establishment. Itwa snecessar yt oappl yirrigatio n atregula rinterval sdurin gth e cycleo fth ecrop .Volumetri csoi lwate rconten tthroughou t theexperimen t wasassesse d bymean so fa neutronprobe .Th efiel d hada surfac e areao f2. 5h aan dth erow swer e spaced 0.75 mapar tan d orientednorth-south . Thefetc hi nth eprevailin gwin ddirectio n (south-west)wa sabou t 120m . A commercialapparatu s(Bowe nrati osystem ,Campbei lSei .Ltd , Shepshed, UK)wa suse d to monitor temperaturean dvapo rpressur ea ttw oheight si nth ecanop yboundar y layer.T oasses senerg ybalanc e equationterms ,measurement so fne tradiatio nwer emad ea t 1 mheigh tabov eth ecanop ywit ha Fritschen-typene tradiomete r(Mode l 3032,Weathertronics , West Sacramento, California, USA), soil heafluxt wit htw oplate s(HFT-1 ,Rebs ,Seattle ,Washington )an d meansoi ltemperatur e inth esoi l layerabov eth eplate swit hthermocouples .Win dprofile s wereestablishe db ymonitorin gwin d speeda t four heights,0.2,0.4,0.8,1. 6m abov eth eto p ofth ecanopy ,b yAM10 1lo wtreshol d cup anemometers(Vecto rInstruments ,Rhyl ,Unite dKingdom) .Al lmeasurement swer eperforme d by a 21Xmicrologge r(Campbel l Sei.Ltd , Shepshed,U.K. )a tmaxima linterval so f 10second san dth e averagesstore d every3 0minutes .Cro pheigh t (He) andLA Iwer emonitore d atregula r intervals visuallywit ha meter ,an dwit ha nLAI-200 0Plan tcanop yanalyze r(Li-COR ,Lincoln , Nebraska, USA) respectively.Dat awer efiltere d bydeletin grecord sfeaturin g limitingfetc h and awin d speed atth eto p heightlowe rtha n 1.5 m-sec'. Onlyprofile s established inneutra l conditionswer econsidered , sotha t situationswit ha Richardso nnumbe r> 10.01 J wereals opurged . Thelowes t height wasdiscarde d whenfallin g outsideth elogarithmi csublayer ,accordin gt oRaupac h etal .criterio n(1980) . Survivingobservation swer eprocesse d ina worksheet , byth emea no ftw o macros.Th efirst on ewa s aimedt o producegraph so fth ewin dprofile s toevidenc eanomalies .Th esecon d macrowa suse dt o calculatezer oflu xplan edisplacemen t (DJ androughnes slengh tfo r momentum (zj withth egraphica l approach. Thelogarith m ofth edistance sabov eth ezer oplan edisplacemen t level wereregresse d against wind speeds,fo r 6differen t valueso f5, spanning0.7 , andth evalue so fth eregressio n coefficients correspondingt oth ebes tfi t (evaluated onth ebasi so fth er 2)wer eselected . Thevalu eo fdelt ause d wasthe ntake na sth eestimat eo fD, andth eintercep t asth elogarith m ofz 0.Th eprocedur e was then Division 2 671 repeated,i na secon d step,fo reac hgrou po fth eD parameters ,thi stim ewit h6 value so f<5,spannin g thevalu epreviousl y found.

Results Dan dz 0 parametersestimate dbetwee nDa yo fYea r(DOY ) 199an d25 8ar ereporte d inth efigure. A maximumcro pheigh to f2. 2m an dLA Io f4.5 9wer ereache do nDO Y235 , declining thereafter Dwa sa decreasin gfraction o fcro pheigh tthroughou t theexpeiimen t(fro m 0.8He t oabou t 0.73), but thecorrelatio nwa spoo r(r=0.34) .Z 0increase dfrom abou t0.0 4t oalmos t0.1 2He (r=0.56) . No correlationfo ran yo fth e2 parameter swa sfoun d withwin ddirection , sotha tth eeffec t ofro w orientationwa sunimportant , sinceth ecro pwa sa fairl yunifor m surface alreadywhe nLA Iwa s 2.0 (Hc=0.9m) .

1.6 1.4 -| 1.2 1.0 E 0.8 0.6 0.4 0.2 0.0 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 DZO +D crop height (m)

Figure:Calculate dD an dz 0parameter sa sa functio n ofcro pheight .

Conclusions Dan dz 0parameter sfo ra sunflowe r croprangin gi nheigh tbetwee n0. 5an d1.8 5m ,resulte da decreasingan d increasingfraction o fcro pheight ,respectively .Th epropose d relationshipsar eth e following: D[m] =-0.092+0.154 He 1^=0.43 z„[m] = -0.097+0.671H e 1^=0.79

References Smith,M .e tal. , 1991.Repor t ofth eexper t consultation onprocedure sfo rrevisio no fFA Oguideline s forpredictio no fcro pwate rrequirements .UN-FAO ,Rome ,Italy , 54p. Wieringa,J. , 1992. BoundaryLaye rMeteorology , 63:323-363 . Raupach,M.R . etal. , 1980. BoundaryLaye rMeteorology , 18: 373-397. Division3

Plant-soil relations. 674 Book of Abstracts 4th ESA-congress

RESULTS FROM AN INVESTIGATION ON THE HEATFLU X DENSITY INSOI L ON THEBAS E OFTHERMOELECTRI C AND CONDUCTOMETRIC TRANSDUCERS

S.Alexiev a Institute of Soil Science and Agroecology, 7, Sh.Bankja Str., PB 1080,Sofi a Bulgaria

Introduction The heat flux density q in the root zone soil layer generalizes the kinematics of the liquid soil phase which includes not only moisture but also easy soluble compounds presenting mineral salts. The isothermity of the soil profile and the intensity of thermomoisture exchange give areaso n the moisture migration andth e salts dissolved in itt o be followed. On the other hand this makes itpossibl e to reach adecisio n upon preserving the water balance through an alternation of awel l cultivated upper layer and amor e dense lower one [Globus, 1983].

Methods The temperature gradient (gradT) i n the root zone is measured by cylindrical drill with thermoelectric battery, whose heat terminals are at adept h 50cm . The generated thermoelectric tension from the battery E is gauged by nanometer type "Keitly" model 197- sensitivit y 10nv . Thetemperatur e difference A Ti scalculate d from this read values of E(E = k.A T). By meanso f conductometrical transducers placed at given sections in the soil profile theelectrica l resistance Reo f each section is measured. On the base of the electrothermal analogy the heat resistanceRt andth e measured Rear e comparable according to the expressions: R=AT/P (1) andP = Re.I2 (2), where:/ -th e direct current of the ohmmeter for the respective band; P -electrica l power. After differentiation of (1 ) an d (2) could be determined AP/AT= \IRt = AAS, /Al,, (3) where: A isth e heat conductivity of the soil type, and 5, and /( -hea t surface and heat line of the investigated section. Replacing the expression for A from (3) it results in the following dependency for the heat flux density in Fourier principle q =-(A/Rt)gradT, (4) where A- coefficien t and is defined by the size of the investigated section. In the summer of 1995th e following measures on a soil type leached chernozem of amaiz e crops under conditions of no watering were made: - for A Twit h thermobattery of 25thermocoupl e (chromel -alumel ) whose heat terminals are at /= 5 0c m and the cold ones,throug h athic k -walle d pipe, are under conditions ofa surface temperature; the values for grad Tar e calculated by the measured E of the thermobattery with a nanometer; -b y the conductometrical transducer and aohmmete r Re and the current are substituted in theexpression s (1),(2 ) and (3) iscalculate d and qfro m (4).

Results The heat flux density (thermodiffusion) calculated with formula (4) generalizes the migration of the liquid soil phase in which gradT play s extremely important part, especially the values over 0.2"C.cm' . Under higher values of grad Tth e thermodiffusion reaches layers under 50c m (Figure 1 -curv e lines 1,2) .Th e level of the stationary soil profile, however, depends on the influence of the moisture gradient (Figure 1 -curv e line3) . Division 3 675

The lower values ofgrad Tdefin e the ceasing of the thermodiffusion till /= 20c m (Figure 1 -curv e lines4 ,5) .

Table 1.Th e measured values by the thermoelectrical and the conductometrical transdusere

Date 22.06.95 30.06.95 6.07.95 10.0795 23.08.95 E[mV] 0.536 0.398 0.613 0.035 0.134 Re[kQ] I = 10 cm 1.19 1.5 1.1 1.55 11.1 Re[kQ] I = 30 cm 4.7 14.3 21 50 72 Re[kQ] I =50 cm 186 136 50 136 392 Calculated values

grad T 0.27 0.2 0.31 0.02 0.07 ["C/cm] q I = 10 cm I — 10 cm I = 10 cm I =10 cm I =10 cm [W/cm] 1-76 2.4 1.76 2.48 0.71 IQ'3 I = 30 cm I = 30 cm I = 30 cm I = 30 cm I = 30 cm 0.3 0.92 0.02 0.03 0.05 I = 50 cm I = 50 cm I = 50 cm I = 50 cm I = 50 cm 0.12 0.9 0.03 0.09 0.03

4[W/cm2].10"3 gradT[ C/cm]

Figure 1.Th e dynamical of q in the different layers depending on gradT

50 / [cm]

References Globus A.M. , 1983.Physic s of non-isothermal soil moisture transfer.Monograph: Hydrometeoizdat, Leningrad, 260p . 676 Book of Abstracts 4th ESA-congress

RELATIONS BETWEEN STABILITY OFTUNDR A SOILSAFFECTE D BY MECHANICAL IMPACTS AND PLANT COMMUNITY COMPOSITION

N.P. Buchkina, TS. Zvereva

Agrophysical Research Institute, 14Grazhdansk y prospect, St.Petersburg 195220 Russia

Introduction Agricultural lands inth etypi ctundr a ofth eYama lPeninsul a are pastures for the reindeers. Decreasing the areas ofpasture s asrelate d to arapi d development ofth egas -an d oilfields causes higher mechanical impacts onth e remaining agricultural territories. The study reported herewa s conducted to ascertain amechanica l stability ofth e cryogenic peaty soilsan d cryozems with different composition ofplan t communities.

Methods The mechanical stability was considered asa nabilit yo f soilst o resist both normal and shear stresses induced byth etracke d vehicles. The shear and normal stress resistances of soilswit h different plant communities were determined using aAmarjan' s vane device (Amarjan, 1990)an d aReyjakin' s penetrometer (Bahtin, 1969).Th emorphologica l properties, moisture content, bulk density, andtextur e ofth e soilsstudie d weremeasure d byconventiona l methods (Vadjunina et al., 1986). The coefficients ofresistanc e were calculated onth e basis ofdat a on strength properties (shear and normal stress resistances), depth ofth e seasonally-thawed layers and organogenic horizons, locations ofbiogeocenosi s on arelief . Arang e ofvariation s inth e parameters studied (except alocatio n on arelief ) was established using a 10-estimates scale. The visual investigations were used to evaluate the location ofbiogeocenosi s on arelief . The dimensionless coefficients of resistance (P) were calculated usingth e following formula:

PeXlOO P = —,

where Pe - a sum of estimatesfo r the parameters ofbiogeocenosis ;

Results Inth e soilso ftypi ctundr a ofth eYama lPeninsula , the normal stressresistance s ranged from 0.5±0.1to4.5±1. 3 MPa. Thesevalue swer e defined onlyb y soilpropertie s (moisture content, bulk density, andtexture) , ifthes e soilsha d aver y poor plant cover. Inthi s case, the loamy cryozems and cryogenic peaty soilsshowe d thegreates t and lowest normal stress resistances ranging from 2.6±0.5 to 3.5±0.6MP a and from 0.9±0.2 to 1.7±0.3Mpa , respectively. The thixotropic horizons of mineral soilsha d alowe r normal stress resistance (by 20-40%) compared to theunthixotropi c horizons. Apresenc e ofrhizom eplant s (Carexsp., Eriophorum sp.) inth e plant communities ledt o increasing the normal stress resistances by 12-15% and 22-30% inth e upper horizons of loamy and sandy cryozems, respectively. Inth e profiles of cryogenic peaty soils, the root horizons had essentially greater normal stress resistance than those without roots. Similar relationships were observed for the soil shear resistance which also was defined by physical properties of soilswit h apoo r plant cover. Inthi s case,th e cryogenic peaty soils showed the lowest abilityt o resist shear stresses. The shear stress resistance ofthi s soil ranged from 1.7±0.1t o 2.5±0.5 kPa atth e highan dlo wvalue s ofmoistur e content. The highvalue s of shear Division 3 577

stressresistanc e of3.0±0. 2 kPawer e determined inth e dried loamy cryozems. The highest values of shear resistance inth e cryogenic peaty soils (3.2±1.2 kPa) and waterlogged loamy cryozems (3.1±0.8 kPa) were induced byth e rhizome plants inth ephn t community composition studied. These soils indicated the same ability to resist the shear stresses as compared to the dried loamy cryozems.

Conclusions The coefficients of resistance can rangefrom 5 t o 100.I nth e soilso ftypi ctundr a ofth eYama l Peninsula, these coefficients were equal to 31-69. Based onth e values ofcoefficient s ofresistance , thetundr a soils studied were divided into five groups. The cryogenic peaty soilso fth e sedgebog swit hthic k rhizomehorizon s had the highest resistance to mechanical impacts (P= 62-69),whil eth e cryogenicpeat y soilso fth e sedge-moss bogs and the dried clay loam cryozemswer e included intoth e second group (P= 54-61). The loamy sand and loamy cryozemswit h rhizome plants, the cryogenic soilswithou t root horizons and the peaty cryozemswer e grouped intoth ethir d group (P =46-53) . The fourth group included the cryozems formed on slope andflat site swit h shallow organogenic horizons (P= 38-45). The lowest resistance was observed inth ewaterlogge d cryogenic peaty soilswithou t rhizome plants (P = 31-37).

References Amarjan, L.S., 1990.Propertie s ofunconsolidate d grounds and methods ofthei r studies, Moscow, 254 p. (inRussian) . Bahtin, PU., 1969. Studies onmechanica l and engineering properties ofmai ntype s of soilsi n USSR, Moscow, 271 p. (inRussian) . Vadjunina, A.F. et al., 1986.Method s ofinvestigation s of soilsphysica l properties, Moscow, 416 p. (inRussian) . 678 Book of Abstracts 4th ESA-congress

FACTORSDETERMININ GTH EVALUE SO FFORCE SNEEDE DFO RPULLIN GOU T SUGARBEE TROOT SFRO MTH ESOI L

M.Bzowska-Bakalar z

Institute of Agricultural Mechanization, University of Agriculture, 20-612 Lublin, Gieboka Street 28, Poland

Introduction From the viewpoint of cultivation, harvest and transport processes of sugar beets, the main physical traits ofroot s are geometrical dimensions, height of root protruding over the soil surface and force for pulling the inexcavated roots out ofth e soil (Byszewski et al, 1978). The limit values ofthes eforce s areth e basicparameter s for working out the constructional needs of agricultural machines. The influence of meteorological and soil conditions on geometrical dimensions of roots and onthei r growth over the soilsurfac e isknown . Neverthless, no researches into the direct influence ofthos e conditions on the pulling out force value have been madeyet . (Bzowska - Bakalarz et al, 1987).

Methods The value offorce s for pullingou t sugarbeet sF wwa s estimated for three varieties cultivated at two nitrogen fertilization levels. The plants were cultivated on the sametyp e of soil (loess) with the same agrotechnical measures. Inyear s 1981-1983 the correlation between the pulling out force value and the root shapes and dimensions was examined. In 1984 and 1985 the pulling out force values were measured for onlytw o varieties (Table l).The experiment was carried out in 50 replication. An instrument equipped with 1stclas s ofprecisio n dynamometer, earlier described by the author (Bzowska -Bakalar z et al, 1987) wasuse d inth e experiment. Soil moisture and soil strength were measured in allexperimenta l plots(Fig . 1).Th e description of meteorological conditions wasbase d on the data from the local meteorological station' and thus the Sielianinov coefficient(SC) for the thirty-days period before harvest was evaluated (Molga, 1972).

Soil strenght [MPa] 3 4 5 6 7 10 11 0 ^\ 1983 1982 50 SC-0.12 SC-0.61 M - 2.69% M - 5.15% I 100 ~^s \ • 1981 •>>^^^ 1985 ""-»^ \ £ 150 • SC- 1.51 •"*.. \ SC- 1.24 "~^-^^^^ \ • M - 9.98% •»> L M- 15.69% 1984 "• "K^_—-. Q200 \ \K SC-2.55 250 ^ "--.._ M - 14.7% 300 -V. Fig.1.Th ecurve so fchange so fsoi lstrength ; SC-Sielianinovcoefficient , M-soil moisture

Results In the Table 1 average values ofmeasure d forces for particular combinations are presented. The average values ofthes eforce s amounted from 272.5 N to 794.3 N, and they were very differentiated, which was duet o high variation coefficients (w) and standard deviations (Se). Asth e author's research implies, the values ofth eforce s for pulling out the roots are correlated with maximum root diameter (D) [correlation coefficient 0.3855] and length (L) [correlation coefficient 0.4568]. Significantly lessforc e was needed (by 11.5%)fo r pulling out the roots of multi-seed AJ3 variety with shorter roots than for pulling out the roots ofmono-see d varieties. Division3 679

The variety differences in force values for pulling out the roots are related to the variety differences in root dimensions (length and diameter ofth e root) but,first o f all,the y are correlated with the soil moisture and strength. Asignificant , but not consistent, effect of nitrogen fertilization dosebot h on the root dimensions and onth e force valuesF wwas noted.

Table.1 . Thevalue so fth eforce s Fw [N] neededt opul lou tsuga rbee tfro mth e soil Study object Average^ [N] LSD[N] Estimation of error

Variety: AJ3 489,63 PN Mono 1 44,21 552,21] .55,94 S = 231,37 N PS Mono 4 e 537.94J w= 43,91% Fertilization N [kg/ha]: 160 527,81 - 280 526,05 In 1981 r.: 160 289,16 280 327,94 .38,78 28,81 In 1982 r.: 160 652,00 280 515,00 • 137,00 67,22 In 1983 r.: 160 642,25 280 734,53 .92,28 53,53

Years: 1981 308,55 .275,28 1982 583,83 .339,84 44,21 1983 688,39 .104,56 Variety: PN Mono 1 375,46 •23,54 21,89 PS Mono 4 399,00 Se = 136,92 N Years: 1984 w = 35,3% 483,54 •72,63 21,89 1985 350,91 « -Significant difference; LSD- theLeas tSignifican t Difference For instance, in 1982, the roots ofplant s cultivated athighe r fertilization doses (280kg/ha ) were shorter and the forces for pulling outth e roots were lower. So,fertilizatio n level influenced the root dimensions (length and diameter) and had an effect on the values offorce s for pulling out the inexcavated roots. The ranking ofth eyear s according to soil strength (high strength atth e depth corresponding to the root length) aswel l asth e forces for pulling the inexcavated roots out ofth e soili sgive n in Table2 . Table 2.Th eforce sfo rpullin gth e inexcavatedroot s outo fth e soil Year Force for pulling out the roots 1983 the highest soil strength 688.39 N 1982 583.89 N 1984 423.54 N 1985 350.91 N 1981the lowest soil strength 308.55 N Conclusions Asa resul t ofth e studies it can bestate d that the most significant factor affecting the values ofth e pulling out forces are soil properties (strength and moisture). The variety and the nitrogen fertilization level are secondary factors that determine only indirectly the values ofthes e forces by variability ofroo t dimensions (length and diameter).

References Byszewski, W. et al., 1978.Zesz . Probl. Post. Nauk Rol. 203:391-39 7 Bzowska-Bakalarz, M. et al., 1987.Zesz . Probl. Post. Nauk Rol. 316: 9-24 Molga, M, 1972.Meteorologi a rolnicza, PWRiL, Warszawa, 200p. 680 Book of Abstracts 4th ESA-congress

EFFECT OF SOIL COMPACTION ONNODUL E STRUCTURE IN SOYBEAN

H.V. Halmajan, L. Ungurean, A.Dobrescu , V. Stefan, I. Savulescu

Bucharest University ofAgronomica l Sciences and Veterinary Medicine,Bd . Marasti nr. 59, 71331Bucharest , Romania

Introduction Research reports (Tricot et al., 1990,T u andButter , 1988) have shown opposite effects ofsoi l compaction on nodulegrowt h andnitroge nfixation in soybean (Glycine max) and pea (Pisum sativum). In our previous experiment soil compaction enhanced nodulation and did not affect the pod yield (Halmajan et al., 1995). Theobjectiv e ofthi swor k wast o observe the effect ofsoi l compaction on nodule structure inlon g and short day-length growing conditions andth e influence ofcarbo n addition onnodulatio n incompacte d soil.

Methods Soybeanplant swer e grown inglasshous e conditionsi n 1995,wit htw o levelso fsoi l strength: no compaction (1. 1 g cm"3)an d strongly compacted (1. 6 g cm"3).Th e seedswer e sown intw o different periods(o n the 25Apri l for springplantin g and onth e 20 August for summer planting). Theplant swer e harvested inmi dpo dfilling stag e (early July and respectively early October). The seedswer e inoculated withBradyrhizobiu mjaponicu m USDA 110. Two weeksbefor e seedingi n spring planting case, 1.5 g Ca s sucrosepe r kilo of soilwer e added to the soil. The structure of noduleswa s observed using anopti c microscope (M.C. 7).Paraffi n sectionswer e obtained using Heidenhein's method (Sass, 1966).

Results Results are presented inth eTable . Total nodule number aswel l asnodule s dryweigh t tended to be enhanced by soil compaction for both sowing periods. Soybean nodulation wasmuc h higher insprin g planting. Plant metabolism was also influenced byplantin g dates, physiological measurements registering higher values for springplanting . Thelarge rvalue so fnodul edr yweigh t incompacte d soilar e sustained byio n content andrespiration . Photosynthesis andtranspiratio n had different trends according to the planting period. The shape andth e structure ofnodule swer e observed. The nodules had aroun d shape.Nodul e diameter wasbigge r inno ncompacte d soili n spring planting and incompacte d soil in summerplanting . Large differences were observed inth e anatomic structure, wheretw o trends were noticed. Thefirst on e istha t the soiltreatmen t strongly influenced the development ofth e parenchyma andth eperider m cellsa swel l asth e cellwall sdiamete r ofth e endodermis and ofth e infected cells containing bacteroids. Duet o the soilpressur e incompacte d soil, the parenchyma andth e peridermtissues , whichhav e protective functions, are muchmor e developed. Also the sclereidsfrom endodermi s arelonge r incontrol , but cellwall sar ethicke r incompacte d soil. The infected cells containing bacteroids are larger inth enodule sfro m the compacted soil,th ebigges t difference being noted for the diameter ofth e nuclei. The second trend istha t nodule sizewa s correlated withth e dimensions ofth e cellsinvolve d inoxyge n regulation ("subcortex" and interstitial cells).Interstitia l cellsdivid eth e nodule insevera l parts,bein g important oxygen regulators. They arelonge r inbigge r nodules. "Subcortex" cells(Da ye t al., 1991),whic h areals o involved inoxyge n regulation, acting asa physica lbarrier , are smaller inlarge r nodules. Division 3 681

Soilcompactio n and planting dateinfluenc e onplan t development and nodule structure in soybean

Thevariabl e Springplantin g Summer planting Control Compact Compact Control Compact + Carbon

Extract conductivity (usg' 1) 1200b 1500a 1470a 850n 950m 1 1 Respiration (mgC0 2 kg" h' ) 450b 544a 557a 527 n 630m Photosynthesis (mlO 2 dm"2 h"1) 627a 229c 319b 265n 313m Transpiration (mg dm'2h" 1) 259c 268b 333a 447 m 280n Nodule number perplan t 72c 102 b 148 a 16n 27m Nodule dryweigh t perplan t (g) 0.28 c 0.41b 0.58 a 0.09 n 0.17m Nodule diameter (mm) 3.8 a 3.1b 2.4 c 1.1 n 1.7m Parenchyma +perider m cells(urn ) 28 b 60a 54a 80 n 120 m Endodermal cells (sclereids) length (urn) 83a 65 b 50c 52 m 37 n width (urn) 60a 56 a 40b 48 m 28n cellwal l diameter (urn) 4b 10 a 9a 3n 5m Subcortex cells (urn) 127 b 150 a 150 a 61m 47n Cellscontainin g bacteroids length (urn) 36b 46a b 60a 32 m 36 m width (urn) 36a 34a 38a 26 m 34m nucleusdiamete r (urn) 5.7b 7b 11.8a 8n 12 m Length ofinterstitia l cells(urn ) 28a 24a 24a 12 n 18 m Meansi nth e samero w followed byth e samelette r areno t significantly different atP <0.05 .

Conclusions Irrespective ofth eplantin gdate , soiltreatmen t (compacted and noncompacted ) induced different noduleformatio n and development (number, dryweigh t and structure) onth e soybean taproot system. Carbon addition increased verymuc h nodulenumbe r and nodule dryweight , but the structure ofth e noduleswa s less affected.

References Day,D.A . et al., 1991. Plant Physiology and Biochemistry 29: 185-201. Halmajan, H.V. et al., 1995.Proceeding s of The Second European Conference on Grain Legumes, Copenhagen, 68-69. Sass, JE., 1966.Botanica lMicrotechnology . IowaUniversit yPress , 218p . Tricot, F. et al., 1990.Proceeding s of TheFirs t ESACongress ,Paris , 51-53. Tu,J.C . et al., 1988.Horticultura l Science23 : 722-724. 682 Book of Abstracts 4th ESA-congress

EVALUATION OFPOTASSIU M STATUS OF SOILS

J. Matula

Research Institute of Crop Production, 16106 Prague 6, Czech Republic

Introduction The intensive andunbalance d application offertiliser s duringth e lastfe w decades inth e Czech Republic, hasresulte d inbot h an excess and alarg erang e ofpotassiu m levelsi n soils, causing an imbalance of other nutrients, especially a deficiency ofmagnesium . Recently, however, the consumption ofindustria l fertiliser has decreased dramatically. Therestoratio n of appropriate levels ofpotassiu m in soils isth e keystone to balanced soilfertility , which isneede d for maintainingbot h profitability and high dietary quality ofcrops , aswel l asrespec t for the environment.

Methods Two approaches wereuse d to evaluateth e potassium reserve ofsoils : (a) acorrelatio n study between ordinary soilpotassiu m tests and concentration ofpotassiu m in soil solution, and (b)a growth chamber study ofth ebioavailabilit y ofpotassium . Thefirst researc h was conducted witha set of 349soi l samples, taken from plough depth of different sites in the Czech Republic. Thesoil s were analysed byth e method Mehlich 2 ((Mehlich , 1978) and the KVK-UF method (Matula, Pirkel, 1988);th e soil solution being separated from water saturated soilpast eusin g centrifugation. For the growth chamber study, spring barley (cv Akcent) was grown in 600g of soilpe rpo t (from arang e of 20soil s of markedly different agronomic qualities) over four weeks, using 3replicate s of each soil. The growth regimewa s 16h/20°C days at an effective photosynthetic radiation of 500 umol m"V and 8h/15° C nights,wit h fertiliser (asa solutio n of NH4NO3)adde d in 6 dosest o provide 150m g ofN pe r pot during cultivation. The shoots were harvested after 28 days,immediatel y dried at 65°C (to constantweight ) and analysed for nutrient content byroutin e procedures. To evaluate the appropriate level ofpotassiu m in soil, the index efficiency (IE) ofpotassiu m was used (Matula,1985) , calculated byth e formula: IE =dr y matter yield of shoots /% K i n shoots. Data were statistically analysed using regression analysis software (Statgraphics, version 7, Manugistics, inc,USA) .

Results The possibility to predict potassium concentration in asoi l solution (from more easily measured soiltestin g parameters) isshow n inth e Tablebelow .

Table. Correlation between K concentration in soil solution and parameters of two soil tests Soil testing parameters Correlation coefficients Models (n = 349) Linear Multiplicative Mehlich 2 [mgK/kg] 0,5250 0,5413 Ratio K/VCa+Mg (Mehlich 2) 0,5757 0,5911 KVK-UF [mgK/kg] 0,5778 0,5911 Ratio K/VCa+Mg (KVK-UF) 0,6192 0,6208 % ekv. K saturation CEC (KVK-UF) 0,7511 0,7676

The closest relationship suitable to predict the concentration of potassium inth e soil solution from current data ofsoi ltestin g methods,wa s found after transformation ofth e values of exchangeable Division 3 683 potassium (determined by method KVK-UF) into its equivalent saturation of cation exchange capacity, followed by the ratio K/VCa+Mg. The best correlation between soil potassium and potassium content in plants was found in the case of exchangeable potassium in soil. Any other adjustments of exchangeable potassium by other characteristics of soil (i.e. K concentration in soil solution, K- reserve determined by method of boiling nitric acid extraction, KT fixation capacity), did not improve the correlation of relationships.

110

100

x a> 90 9865 •o c 80

70 -

ID 60

50 o a. 40

30 -

20 0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 Exchangeable potassium in soils determined by KVK-UF

Figure. The use of the concept of potassium efficiency index, to define the suitable level of potassium in soil.

The scatter diagram suggested that these sets of soils can be classified into three groups (A, B, C) due to their different desorption characteristics and buffering power. From the shape of the curves the effective levels of potassium were estimated: 70, 140 and 220 mgK.kg"1 respectively, for soil groups A, B, C.

Conclusions The possibility of predicting the potassium concentration of soil solutions from more easily measured parameters of routine soil testing, can contribute to optimise the potassium status of soils together with parameters of water regime of the exact plot. The short-term plant soil trials in a growth chamber enabled to distinguish of soils of different potassium availability when the concept of potassium efficiency index was employed.

The research was supported by GA CR through the project 503/94/0021

References Matula, J. - Pirkl, J. 1988. AO c. 272804, Praha, Üfad pro vynâlezy a objevy Matula, J. 1989. Rostlinnâ Vyroba, 35 (12) : 1283-1292 Mehlich, A. 1978. Communications in Soil Science and Plant Analysis, 9, 6 : 477-492 684 Book of Abstracts 4th ESA-congress

EARTHWORMS PRESENCE ASAFFECTE D BY TILLAGE SYSTEM INCLA Y SOIL

M.Mazzoncini , E. Bonari, M. Ginanni, S.Menini , F. Sancarlo

Dipartimento di Agronomiae Gestion e dell'Agro-Ecosistema, University of Pisa,vi a S.Michèl e degli Scalzi 2, 56124 Pisa, Italy.

Introduction Fragmentation of organic matter, channelling andmixin g of soil components are keyrole sb y whichearthworm s increase microbial decomposition activity, soilmacroporosity , movement of air andwate r inth e soil matrix and aggregate stability. Earthworms presence isver y important in sustainable agricultural systems based upon nutrient cycling stimulation and conservation tillage techniques.I nthi s cases,earthworm s mayalleviat e compaction ofuntille d soilb yburrowin g and may facilitate residue incorporation into the soil.Man yresearcher s (House et al., 1985;Macka y et al., 1985) found that the adoption of conservation tillagetechnique s (reduced and no -tillage ) increase earthworms and arthropodspresence .

Methods Afiel d experiment was carried out from December 1994t oNovembe r 1995t o monitor earthworms presence on acla y soil (Tipic Xerothent) of ahill y site representative of Central Italy where shallow ploughing (25-30 cm -CT),dis k harrowing (10-15 cm -RT ) and notillag e (NT) were compared in alon gter m experiment. Theexperimenta l design was arandomize d complete block. Since 1991duru m wheat (Triticum durumL. )wa scultivate d asmonoculture . Durum wheat was sown 14.10.1994;herbicide s were sprayed 2.12.1994 (chlortorulon) and 22.3.1995 (dichlofop -methyl) .Afte r wheat harvest, CTan d RTwer e performed on 1.8.1995an d 19.10.1995 respectively. Earthwormspresenc ewa smonitore d onfive dates : 15.12.1994, 16.03.1995,22.05.1995 ,22.09.199 5 and 26.10.1995.A t each datetwelv e soil cubic samples were extracted from each tillage system bymean s ofa spade after having dug atrenc h to isolate the soilbloc k to sample; sampleswer e cubes of standardized volume(3 0 x 30 x 30cm) .Soi l samples were placed on ablac k plastic sheett o improve thevisua l detection of earthworms and than crumbledby hand. After extraction earthworms were plunged and conserved ina hydro - alcoholic solution (90%).Afte r three dayso f conservation, earthworms were counted, weighed and classified bymean s ofa binocula r microscope.

Analysis of variance Total earthworms O. complanatus A. rosea Treatments m"2 biomass m"2 nv2 Tillage system ** n.s. Sampling date n.s. ** Interaction n.s. ** n.s. n.s. **significantatPs0.05

Results Bothtota l number and total biomass ofearthworm s were affected bytillag e systems and sampling date,a s shown inth e Table. On an average, earthworms number found inN Tplot swa s 5 and 2.6 fold greater than that of CTan d RTrespectivel y (Figure 1).N o significant differences were observed between CT and RT.Variation s in earthworms population density among samplingperiod s seem tob erelate d to seasonal climatic changes.Earthworm sbiomas swa s influenced bytillag e systems only in December and March while no significant differences were found inMay , September and October probably duet o the preponderant presence ofjuvenil e Division3 685

individuals, whoseweigh t is limited. When the effect of tillage system was significant, earthworms biomass was greater underN Ttha nunde r CTan dR T (Figure 2).Th etw o dominant speciesrecorde d inal l tillage systems during the whole sampling period were Allolobophorarosea (Savigny , 1826)an d Octodrilus Eec Mr. My Spt. Oct. Man complanatus (Dugès, 1828). Tillage systems influenced the Figure 1. Total earthworm density recorded at each behaviour ofthes etw o species samplingdat ei nth ethre etillag esystems . CT=conventional differently. Infact , while O. tillage, RT= reduced tillage,NT = no-tillage.Bar s labelled complanatus density was greater withth esam elette rar eno tsignificantl y different atP<0.0 5 withN T (22.8 individuals m"2 on (DMRtest) . average)tha nwit h RTan dC T (8.0 and 1.9 respectively),A. roseapresenc e wasaffecte d only by sampling date.

Conclusions Soil matrix modifications related to CTan d RTreduc e earthworms abundance with respect toNT . Therespons e of earthworms speciest o tillage systemsvar yi n relation to their customs. Species such asO. complanatus, which May Sept. live inminera l soilbu tfee d on soil surface residues (anecic species) „. „ „ ^ . j . , , . . . . i seemt ob emor e sensitivet oan y Figure2 .Tota learthwor mfresh biomas srecorde da teac h .. ,. , ... ° ,. , , . „ . ,.„ , soil disruption du et otillag i e thait n samplin v &g date in the three tillage systems. , . . . . „~ .. , t.,, nT, j , ..,, x™ endogeic species sucha s A. rosea CT=conventional tillage, RT= reduced tillage,NT = no- (c * gt J j9Ç2. w ^ ^ tillage. Values labelled with the same letter are not „„„ „, V ' /_ '' • -c *i A-tv L *n nnc/icn. +\ 1992).Th eburrow so fO. significantly different at P<0.05 (LSDtest) . , , . .. ^ r ° J v complanatus, largertha nthos eo f A. roseaan d more vertically oriented, mayfacilitat e water infiltration andreduc e soil erosion. As aconsequence , O. complanatus presence mayb eusefu l for NT system inhill y clay soils characterized by lowhydrauli c conductivity. References CurryJ . P.e t al., 1992.Soi l Biology and Biochemistry 24: 1409-1412. House, G.J. et al., 1985.Soi l and Tillage Research 5:35 1 -360 . Mackay A.D et al, 1985.Soi l Biology andBiochemistr y 17:85 1 -857 . Wyss E. etal , 1992.Soi l Biology and Biochemistry 24: 1635-1639. 686 Book of Abstracts 4th ESA-congress

EFFECT OF TOXIC METALS ONTH E GERMINATING ABILITY OF WINTER WHEAT

L. Szabó

AgriculturalUniversity , Faculty ofAgronomy , Department of Crop Production, Gyöngyös Hungary

Introduction Nowadays, asenvironmenta lpollutio n isbecomin g ahug eproblem , more andmor e attention is paidt oth epotentiall y toxicmatters , and, amongthese , aparticula r attention shouldb epai dt o the dangers associated withheav y metals. Soilswit hhig hheav y metal contamination indicatea fundamental environmentalproble m since many elements,remainin g inth etopsoil , havea potentially polluting effect (Szabó andKâdâ r 1994a, Szabó andKâdâ r 1994b, Szabó 1995a, Szabó 1996a). Soilcontaminatio n makesi timpossibl et o growfoo d cropsi nth e area in question. Anotherproble m canb etha tth etoxi c element accumulates inth e seed asa consequence ofth e heavy metalloa d onth e sou,whic h isdetrimenta lt oth e germinating ability ofth e seed. The objective of our experimentwa st o find outho wth egerminatin g ability ofwinte r wheat seeds changedi fthe y weregrow n on soilstreate d withheav y metals.

Methods The experiment was set onbrow n forest soilpron et o acidification (pH 6.5) inth e autumn of 1994. Number oftreatment swa s 24( 8 elementstime s 3 doses). With 3 series,numbe r of allplot swa s 72. The elementsapplie d wereA L As, Cd, Cr, Cu, Hg,P b andZn . The doses of application were 0/30, 90,27 0 kg/ha aspe r element. Winter wheat "Mv25 " wasuse d asa nindicato r crop. Seeds weregrow n on contaminated plots,harveste d andteste d for germination. Germination test was carried out accordingt oth eHungaria n Standard MSZ 6354-3: 1992.4x10 0whea t seeds/plot wereplace d out for germination in an environment ofcrep efilter pape r soaked with distilled water at20° C temperature.

Results Duringth e experiment the seedsevaluate d were divided into four separate classes as defined below: - healthy seedswit hnorma l germination, - swollenseed swit hn o germination, - rotten seeds, - infertile seeds. Onth euntreate d controlplots , germinating ability (rate) ofth ewhea t seedswa s ashig h as97. 3 %. Whentreate d with Cd,Pb ,Hg ,A s orAl , germinating abilityprove d somewhat poorer as compared toth e controlplots , varyingbetwee n 95 and 96 %wit h minimal differences between doses. Amongth e 8elements , only Cu, Cr andZ nproduce d aharmfu l effect on germinating ability (see Table). Iti sclea rfrom th e Tabletha tZ nprove d to bemos t harmful for the germinating ability ofwhea t seedsa sdescribe d by the mean of 91.8% ofth e 3treatments . Iti sclear ,too , that germinating ability decreasesparallell y withincreasin g doses ofZn .A s comparedt o the control of97. 3 %, germination ratewa s 94 %an d 90.5 %b ytreatment swit h 30kg/h a and 270 kg/ha, respectively. With Cu,th egerminatio n rate fell also from 95.6 %t o 91 %wit h increase ofth e dosiso f treatment. With Cr, germination percentages were 96 %(3 0kg/ha )an d 92.5 %(27 0 kg/ha). Division 3 687

Ratio ofrotte n seedsprove d 6-7.5 % at 270 kg/haleve l oftreatment , which is3- 4 times ashig h as inth e control. Thisfac t gives evidence ofth e germ killing effect ofth e 3meta lsalts .

Table. Effect of soil treatment with different doses of different heavy metals on the germinating ablihty ofwinte r wheat seeds

Element Doses of heavy metals Mean 30 90 270 healthy seeds with normal germination, % Cu 95,6 92,5 91 93 Cr 96 94 92,5 94,2 Zn 94 91 90,5 91,8 Control 97,3 swollen seeds with no germination, % Cu 0,2 - - 0,1 Cr - - 5 1,7 Zn 0,2 - - 0,1 Control - rotten seeds, % Cu 2,5 6 6 5 Cr 2,8 4 6 4,3 Zn 5 6,6 7,5 6,4 Control 2,5 infertile seeds, % Cu 1,7 1,5 3 2,1 Cr 1,2 2 1,5 1,6 Zn 0,8 2,4 2 1,7 Control 0,2

Conclusions Gettingint oth e soil,heav y metalsma ybecom e detrimental(harmful ) toth e organismslivin gi n the soil, and, assuch ,t o the germinatingplant . Ourinvestigatio n underlinestha t the application of different doses of different heavy metalsha s animpac t onth e germinating ability ofth e wheat seed grownthere . Bytreatment swit h Cu, Cr or Zn, germination rate ofth e seedsbecam e reduced by 3-5 %.Mor e elevated dosesresulte d inmor e reduced germination rates. Germ killing effect of the 3meta l saltsi sevident . Cd, Pb,Hg ,A san dA ltreatment s gavever y similarresult st oth e control, and also, effect ofth e different dosesprove d to be almost equal.

References Sâri,P. , 1996.Nehézfémekke l végzett kisérletek eredményeibarn a erdötalajon. Tudomânyos DiakköriDolgozat , GATE MezögazdasagiFöiskola iKar , Gyöngyös, 53.p . Szabó, L. andKâdâr , I., 1994a. Nehézfémek atalajban , növényben. Agrarökonómiai TudomânyosNapok , GATE MezögazdasagiFöiskola i Kar, Gyöngyös, 2. kötet, 419-422.p . Szabó, L. andKâdér , I., 1994b. Effect ofheav y metalloan d on soilan d erop. XXXVI. Georgikon Napok, PATE Keszthely, 146-153. p. Szabó,L. , 1995a. Nehézfémek viselkedése atalaj-növén y rendszerben, MüszakiKémia iNapok , MTAVEA B Veszprém, 64-66.p . Szabó, L., 1995b. Talajok mikroelem ellâtottsâgânak kömyezeti összefüggései, GATE Fleischmann Rudolf MezögazdasagiKutat ó Intézet, Kompolt, 56-61.p . 688 Book ofAbstract s 4th ESA-congress

TRACE ELEMENT SUPPLY OF THE ARABLE LAND IN HUNGARY

L. Szabó

Agricultural University, Faculty ofAgronomy , Gyöngyös, Hungary

Introduction Thepurpos e ofth e study wast o obtain agenera lpictur e ofmicronutrien t status,t o locateproble m areaswit h deficiency and excess, andt o giveguideline sfo r solvingth eproblem s inpractice . The project wasstarte d atth e end of 1974i n cooperation with FAO andwa sfinanced b y the government ofFinland . Altogether 30 countriestoo k part inth eprojec t by collecting and sending soilan dplan t samplesfo r analysist o thelaborator y ofth e Institute of Soil Sience,Finland .

Methods Wheat andmaiz ewer euse d asindicato r crops.Whea t sampleswer etake n atmid-tillerin g stage, maize samples atth e 4-6 leaf-stage withparalle l sampling ofth e soilfro m plowlayer. The soil availabletrac e elementswer e determined generallyb y using extradants AAAc+ EDT A (Lakanen andErviö , 1971). Theplan ttota l element content was determined asfollows :

B -azomethin- Hmetho d Ca,K , Mg,P , Cu, Fe,Mn ,Mo ,Zn , Co -dr y ashing +HC l solved Cd,P b -we t ashingwit h ccHNO 3 Se- dr y ashingwit h Mg(NÛ3)2 asdescribe d by Siemer/Hagemann

The25 0 samplingsites ,includin g 144wheat-soi l and 106maize-soi l sitesi nHungar y werewel l distributed acrossth e country and soilpropertie stherefor e varied widely. Abouthal f ofth esoil s sampled were classified asPhaeozem s (n=125).Mai n soiltypes commonly found were chernozems(n=46) ,Luvisol s(n=25) ,Vertisol s(n=15) , Cambisols(n=10 ) and others (n=29). The texture,pH , CEC,E C and CaCC"3equivalen t showed on averagevalue s asthos e ofth e internationalmateria l(n=3783 )an dth erange s ofvariatio n were almost aswid e asthos e internationally. Organic matter content inHungaria n soilsi srelativel y high andmor e uniform.

Results TheHungaria n soilsan d crops contained highN , Ca andP values andwer e amongth e three highestnationa lmea n valuesrecorde d inthi s study. The exchangeable K contents ofmos t Hungarian soilswer ewel lbelo wth einternationa lmean . The average level ofK fertilization in Hungary wasexceede d onlyb ytha t ofBelgium . Thisi slikel y to explainth eunagreemen t between theK content of soilsan dplant sa swel l asth ewid evariatio n ofK %i nplants . Exchangeable Mg contentso fsoil san dcrop swer ever y closet o theinternationa l averagebu thig hM g contentsar e typical ofHungaria n maize.Accordin gt othes e data arespons e to Mgfertilizatio n seemsunlikel y (acid sandy soilshav elo wM g status,bu t withn o maizeproduction) .

Boron. TheB status ofth e soilsan d corresponding plantswer ei ngenera l at asatisfactor y level. Copper. Theplant/soi l Cu contents corresponded closely to therespectiv e internationalvalues . Iron. Ingeneral ,th eF e status ofHungaria n soilsan dplant s seemst o be quitenormal . Manganese. The soil/plantM nvalue svar y widelybecaus e ofth evaryin gp H ofth esoils . Molybdenum. The soil/plantM o valuesvar y widelyparalle l withth e varyingp H ofth esoils . Zinc.Hungar y isamon gth e 7-9 countrieswit hth elowes t mean soilan dplan tvalues . At some locationsrespons e to Znfertilizatio n canb e expected. Division 3 689

Cadmium. About half ofth e Cdvalue sfal l inth ehighes tplant/soi l zone andth e other halfi nth e middle zone. The variation ranges ofbot hplan t Cd and soilC d are relatively narrow. Lead. Onlythre e countries (Belgium, Italy andMalta )hav ehighe r Pb median valuestha n Hungary. Cobalt. Theplant/soi l Comedia n isclearl y onth ehig h sidei nth e international Cofield, bu t there isconsiderabl e variation in Co data. Selenium. Hungary shows averagevalue sfo r the Sestatu s ofsoils .

Conclusions TheHungaria n soilsinclude d inthi sFA O study varied widely with regard to texture, pH, CEC, EC, CaC03 equivalent and somewhat lesswit h regard to OM content. TheN , Ca and P contents of soilsan dplant swer e generally high. Most ofth e K andM g contents of soilswer e below the international averagebu tthos e ofplant swer e ata n averageleve lo r above. The soil andplan t contents ofmos t macronutrients variedwidely ,partl y because ofgenerall y highthoug h varyingN , P, Kfertilize r application. Themicronutrien t contents of soils/plantswer e commonly atth e "normal"internationa l level:B slightly onth ehig h side,bu t Cu,Fe ,Mn ,Mo ,Z nwer e onth elo w side. Compared to other micronutrientsth e variation rangesfo r B andM n arewide ,bot h low andhig hB and Mnvalue s wererecorded . Concerningth ene w analytical data, Cd andP b soilan dplan t data indicatehighe r contaminationi n acidregions ,whil e Co and Sestatu sseem st o be at asatisfactor y level(Sülanpää , 1982, Sülanpää and Jansson, 1992). Otherinvestigation swithi nth e lasttw o decadesi nHungary , both soil andplan t analyses and field trialswit h microelements, support thefindings quote d above. Good responses could often be recorded by applications of, first of all,Z nfertilizers . Invineyards ,ther e isa nee d for Fe,M n and Zntreatments . Not much isknow n yet aboutth e contamination of soilsan dplant swit h harmful elements andtoxi cheav y metals. However, there seemst o be ahig h Cd and Pbloa d inHungar y which endangersth ewhol e soil-plant-animal-human food chain(Kâdâr , 1993, 1994, 1995, Szabó andKâdâr, 1994a, Szabó andKâdâr , 1994b, Szabó, 1995a,b)

References Kâdâr, I., 1993.Agrokémi a esTalajtan . 43:291-304. Kâdâr, I., 1994.Act a Agronomica Hungary 42:155-161. Kâdâr, I., 1995.Contaminatio n ofth e soil-plant-animal-human food chainwit h chemical elements inHungary . Regicon Kft. Nyomda, Kompolt (Handbookprinte d inHungarian) . Lakanen, E. and Erviö,R. , 1971. Acta Agronomica Fennica 123:223-232. Sülanpää,M. , 1982.Micronutrient s andth enutrien t status of sous: agloba lstudy . FAO Soils Buüetin. N. 48.Rome . Sülanpää,M . andJansson , H., 1992. Status of cadmium,lead , cobalt and selenium in sousan d plants ofthirt y countries. FAO SousBulletin . N. 65.Rome . Szabó,L . and Kâdâr, I., 1994.Nehézféme k atalajban , növényben. In: IV. Agrarökonómiai Tud. Napok. Szerk: Magda, S. -Radó , A. 2:419-422. Gyöngyös Szabó,L . andKâdâr , I., 1994.Effec t ofheav y metal load on sou and crop. XXXVI. Georgjkon Napok PATE. Georgjkon MezôgazdasâgtudomânyiKar , Keszthely, 146-153. p. Szabó,L , 1995.Nehézféme k viselkedése atalaj-növén y rendszerben. MüszakiKémia iNapo k MTA VEAB Veszprém, 64-66.p . Szabó,L. , 1995.Talajo k mikroelem eUâtottsâgânakkörnyezet i összefïiggései. GATE Fleischmann RudolfMezógazdasag jKutat ó Intézet Kompolt, 56-61.p . Division4

Crop quality and post-harvest physiology. 692 Booko fAbstract s4t hESA-congres s

MIXED CEREAL-VETCH FORAGE ASA SILAGE CROP IN SUSTAINABLE FARMING

F. Borowiec1,E . Pisulewska2, K. Furgal1

1Anima lNutritio n Department, KrakowAgricultura l University, 30 -05 9 Krakow, Poland 2 CropProductio n Department, KrakowAgricultura l University, 31-120Krakow , Poland

Introduction Cereals, grown on arable lands, are increasingly used as green forage or silage crops for ruminants (McCartney, 1993). Intercropping cereals with legume species improves the nutritive value ofresultin g forage and benefits cropping systems, mainly by increasing soilN supply for the next crop (Ostrowski, 1993). In the environmental conditions of Southern Poland, intercropping cereals with legume species is cosidered to be an alternative to maize as a silage crop, in small sustainable farms. Methods The forages of winter cereals (rye, wheat, and triticale) and their intercrops with hairy vetch as well as forages of spring cereals (wheat and triticale) and their intercrops with spring vetch were used. The vetch was planted at 0, 30, and 60% of the recommended rate. The forages were harvestedfollowing th e stage of shooting (cereals) and at the begining of flowering (vetch). The material was swathed, chopped 2-3 cm, and ensiled in 6L-plastic containers (0.7 kg fresh matter per L), in four replicates. The fresh and ensiled material was anaysed for gross chemical composition (Kaminski et al, 1995) and water-soluble sugars (Deriaz, 1961). In addition, the fresh forages were analysed for their buffering capacity (Playn & McDonald, 1966), and the ensiled forages for VFA, on a Varian -3400 gas-chromatograph, and ammonia. The silages were evaluated according to Flieg& Zimme r(Kaminsk ie t al., 1995). Results Ensiling the same cerealswit h hairy or spring vetch improved the ensiling process and the quality ofth e silages, on the condition that the percentage (wt/wt) of vetch in the ensiled forage did not exceed 50%(Tab . 1.). Conclusions 1.Th emixe d forages of spring and winter cereals with vetch, containing lesstha n 50%(wt/wt ) of vetch, produce silageso f good quality and high nutritive value (i.e. an improved energy :protei n ratio). 2. The cereal-vetch forages due to their environmental and technological quality are a viable sustainable alternative to maize asa silagecrop , insmal l farms.

References Deriaz, RE., 1961. Journal ofth e Science, Food, and Agriculture, 2: 152-160. Kaminski,J . et al., 1995.In : „Methods inAnima lNutrition" ,Krako wAgric . Univ., 1995. McCartney, D.H. et al., 1993.Jorna l of Animal Science, 71: 91-96. Ostrowski,R.,1993 . RocznikiNaukow eZootechniki , 20. 157-169. Playn, M.J. et al.,1966. Journal ofth e Science, Food, andAgriculture , 17: 264-268. Division 4 693

II o aû at o £• c: O 4J U o. > > 8 0 ba d

78.0 goo d 96.0 ver y goo d o o o 23. 0 poo r 32. 0 poo r 76. 0 goo d 72. 0 goo d 88. 0 ver y goo d 63. 0 goo d 96. 0 ver y goo d 96.0 ver> ' goo d 63. 0 goo d 64. 0 goo d 98. 0 ver y goo d 59. 0 satisfactor y r- C-J (N 4> rs 00 00

OO Os O <- - rs *>. O* P-s »o. r- m ai sO sO O ci — —' ö 2 o © 2 ö ö Vi' vi o r-" ó ö c/3 2 CQ Q 'ao 4J o o o r- -t ri O ei f*l OON «Ti — Os 'O n t —' vi 00 -^ Os •*" r- r-1 os o r-' so' (N •**• r-i so sO C\ od —! vi S (N m fN N n \o — — rs -" fs) N < < — m 00 o so vs •*• so CN M €N ^ Tf ^ OS ^ » * o O M "O

X (S N sO vi r- os C4 -t OS — —• ir\ Vi © <^| o. ** -*' -*' *ri ^t Tf "* •*' Tf -*" •* Tf •*" •* -^ -T ^ -^

I 2 ^ — VÏ r- --^ _ n « 00 m so — Os Os "^ «^ M "". s sO —•

os r- VÏ W-l CS f! vs r- r-

V> sO © Oh ^ m -f r-i fN vi r- Vi Os o n fNoo vi SO Os' © -" K os — r-' hooi ö r- v-i sO © 00 v> vi «n Ci m r-j •^r •* r-> Do - s© so m 00 «n m os r- Tf gkg ' matte r

- ">. r~ w-l «*> OO SO Vi — — oo -* vi r- — — © 00 — so - r*-' vi oo sd Ö C-* Cs r- -t -»• os' r-' —• Os' © ei ci ^ fN m m (N r-i -t (N m t- fN m -*t

g D M n vi wi capacit y Bufferin g mleqv/10 0

^ O Wl ^O — oo od r- t*i •*• m Os r- r- os 9 SO Tf so rs r- H fN OS rJ (N — (N »ri os ö so" r-' :o'd fsi vi «ri Ïl3 00 so •* — r- vs. Os so Vi re 4J » •* vs su ^* r*ï SO so (N 00 Vi so in o O o so ri af 2 w ri >o' •*»•" (N O' ö so K Os m vi Os' 00 00 rsî © i-î vC N N »ri vi es) SO —« O Vi (N —« sO —• 00

m ci r4 •* »n Nnx rs t- » N ce - -1 -H -H (N sq

J= s JS {J OX 0 - u >P "s? IN s r- r- vs J o ds -1 (NO -i, 00 sO vi r^ os' r-" —. m — ^ M t sO ?3 vo2ä fi Ä JS s ^- «1 s U CJ u u o 0 - u u w S« ,o ï S o > > > > « w -o a a + + o + + T3 > > ^? "™ x° NP s V 0s- 0s- + + « > > 0 - -s© s? s s i ^ + + S » ^ ^S. 0 - 3 _VJ + + o *" ^ i O fN -O so vi © «rî o* © r- r- e S N» *^ O^ O vi 00 f o** — VI —' Ö .. o « -*. ü « Ü — 00 vs S O 30 O LU ^ wi o r- oo *r>->e "r0t0 rt s O C . —. m •* 5- 2i — oo so o cj y « s? s» w 3 v o> i> u .0 .§ S « s o s ja Ü j> •c -H "H J3 J5 Ä H H H c 3 .§. 1 S SS? H H H Al H H fS 694 Book of Abstracts 4th ESA-congress

EFFECT OF ENVIRONMENTAL FACTORS, GENOTYPE AND PERIOD OF HARVEST ON POST-HARVEST RIPENING OF SUNFLOWER

J. Crnobaracl, B.Marinkovic l

^Faculty of Agriculture, Institute of Field and Vegetable Crops, Dositeja Obradovica 8, 21000 Novi Sad, Yugoslavia

Introduction It isnecessar y to be familiar with dynamics of seed maturation and post-harvest ripening for thepurpos e of shortening breedingprocesses .Th e objective ofthi s study wast o determine the earliest time of acquiring high and stable reproductive ability ofth e sunflower seed as influenced by different environments andgenotypes.Accordin gt oNikolajev a (1982),th e sunflower ischaracterize d bywea k dormancy, due to low embryo activity and low permeability ofth e grain coat.Th e latter isals o emphasized by Chandler et al.(1985), Csresnyes (1979)an d others.Dormanc y occurs 19-21 days after fertilization (Fursova, 1989).Accordin g to Voskobojnik et al. (1989),th e beginning of seed filling is atth e sametim eth e beginning of dormancy, because ofth e accumulation of inhibitors andhardenin g ofth e grain coat.

Methods In athree-yea r trial established both in afiel d and agreenhouse ,th eharves t ofth e mother component ofth e hybridsNS-H-2 6 andNS-H-2 7 andth e variety VNIIMK-8931, which started 10an d ended 52Day s After the Beginning of Flowering (DABF),wa sperforme d eachthir d day. Beforehand, the plants were marked with respect toth e beginning ofthei r flowering. The seed obtained wasteste d for its germination inroll s of filter paper 15,20 ,25 ,30 ,40 , 50,60 , 80an d 100day s after the period ofharvestin g to determined seed dormancy. The data were statistically processed as athree-factoria l split block design.Nevertheless , sincether ewer e actually five factors (years, environments, genotypes,tim e ofharves t and dormancy),tw o ofthe m were left out by means ofusin gth e mean values ofthei r treatments .Afte r the effect ofth e factors was estimated usingth eF-test , the degree ofa particula r factor's influence ongerminatio n was determined onth e basis ofth epercentag e share of its sum square inth e total sum square .Wit h regard toth e average ofth e rest ofth e factors, the dynamics of germinability duringth e stageo f maturing andpost-harves t ripening waspresente d as aContou r plot (Origin 3.5).

Results Accordingt oth e F-test, allteste d factors were significantly effective. The harvesting period showed to bedecisiv e factor on since its share intota l variability ofth e trial was80.4 - 82.4%. The share ofpost-harves t ripening was 9.9-10.1% while the share of other factors (year, agroecological environment and genotype) ranged from 0.5 to 0.1%. The germination over90 % isachieve d 19DAB F andwit h seed moisture of 69.3%. Atfirs t harvest, the period needed for post-harvest ripeningwa sa 100day swhil e atth e end ofth eharves tperiod , itdecrease d to 25 days.Th e earliest seedvitalit y is achieved 51t o 58 days after flowering (the sum of dayst o harvest and days for dormancy).Th e optimum harvest period is 25t o 31DAB F inwhic h case post-harvest ripening lasts 25t o 30day s(Fig.1.) .I n greenhouse the seedharveste d upt oth e 28th DABFha s less moisture and shorter period ofpost-harves t ripening.Th e seed harvested in 1985, which wasth ewarmes t year, hadth e fastest maturation, butweakes t post-harvest ripening because ofhighe r germination level atth e beginning ofharvest . The variety VNIIMK-8931ha d higher germination rate and shorter period ofpost-harves t ripening thanth ehybrids , althoughth e water concentration washighe r than inhybrid s inth e period ofharvestin g (Fig.2.). Division4 695

Conclusions Theharvestin g period andth epost-harves t ripening wereth etw o decisivetria l factors. The duration ofdormanc y duringth e first harvests was 100 days,whil e at the end ofth eharvest , it decreased to 25days . The earliest satisfactory seed germination isachieve d 51t o 58 day afterflowering. Th e optimum harvest period is2 5t o 31DABF , inwhic h casepost-harves tripening last s 25t o 30days . Thefastes t maturation was observed inth e seed from the greenhouse andtha t from thefield i nth e warmest year. However, these seedsha dth eweakes t post-harvestripening, becaus e ofa highe r germination level atth ebeginnin g ofharvesting . Thevariet y VNIIMK-8931ha d ahighe r germination rate and a shorter period ofpost-harves t ripening than thehybrids .

Fig. 1. Effect of harvesting period on sunflower seed germination inth e period of post-harvest ripening

Harvest (days after the beginning of flowering)

Fig. 2. Differences between the rate ofsee d germination affected by year, environment and genotype

. JTfci. AVERAGE YEAR "F"

WARM EST YEAR I'M ~i—i—|—i—i—|—i—i—|—i—i—|—i—i—|—i—i—|—i—i—r- FIELD

10 — o L_iWt_...L.

GREENHOUSE I'M T—I—I—I—I—|—I—I ' ' T I ' ' I ' ' I ' ' I -1 I I T' ' I ' ' I ' ' I VNIIMK-8931

30 20 10 — 0 ,-O.JKS. -L ..i._. L_ •10 — i—]—i—i—|—i—i—|—i—i—|—i—i—|—i—i—|—i—i—|—i—i—|—i—i—|—i—i—|—i—i—|—i—;—|—i—i—|—i—i—]—;—i—|—r 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 Harvest (days after the beginning of flowering)

Dormancy (days afterthe period of harvesting 15 I I 20 ^m 25 MM 30 MM 40 ^^ 60 | References Cseresnyes, Z., 1979: Seed Science and Technology 7(2) : 179-188. Chandler, J.M. et al., 1985:Cro p science 25: 356-358. Fursova, D. B., 1989:Tehnicesk e kulturi 1:8-9 . Nikolaeva, M.G., 1982:A t Kann, A.A., :Physiolog y andbiochemistr y of dormancy and germination of seed, "Kolos",Moskva : 72-96. Voskobojnik, L.K. et al., 1989: Sb.N . I. rabot "Semenovedenije istandardizacij a maslicnih kultur", VNirMK, Krasnodar: 35-38. 696 Book ofAbstract s 4th ESA-congress

RELATIONSHIP BETWEEN SOIL NITRATE CONTENT ANDGRAI N PROTEIN CONTENT INMALTIN G BARLEY (HORDEUM VULGARE ssp DIST1CHVM) M. Malesevic1*,Lj .Starcevic 2', Bogdanovic Darinka2),N . Przulj" 1)Institut e ofFiel d andVegetabl e Crops, 2100 0Nov i Sad,M .Gorko g 30, Yugoslavia 2)Facult y ofAgriculture , Novi Sad, Yugoslavia Introduction: Malting barley grain of good quality isver y difficult to attain on fertile soils, such as chernozem. The primary indicator of quality in malting barley is protein content. Grain protein content and protein structure are especially variable in semi-arid climatic regions, such as the Vojvodina Province. Under thesam e conditions, protein content is somewhat higher in winter than in spring malting barley. Thereaso n for this, in addition to genotype properties, can be that thetw o forms have growing seasons of different length (01 October - 25Jun e inwinte r and0 1 March - 05Jur y in springbarle y (Malesevic et al., 1992). Aresul t of this is a different capacity of the root system to utilize N, P, K, water and other substances. Since the root system of winter barley develops deeper into thesoi ltha n that ofsprin gbarle y (Garz et al., 1983), theeffec t ofresidua l N ongrai n yieldan dqualit yi sgreate ri nth e former. Onth eothe rhand , theNO3- N content and distributioni n thesoi l depend onclimati c factors, upunti l thebeginnin g ofintensiv e Nuptake . Inbarley , protein synthesisi sdependen t ontemperature s duringth eheadin g -maturin g period andth eleve l of N03- N supply (Foster etal. , 1987). Methods: The effect of N ongrai n yield and quality in winter and spring malting barley was studied inth e period between 1985 and 1995.Th etrial swer e conducted ona chernoze m sourich i nN , Pan d K. Atth eFe- 2stag e (Feekes - scale), thefollowin g fertilizer N (Nf) rates were applied: 0, 30,60 ,9 0 and 120 kgha" 1. Prior to this, Nmin content wasanalyse d up to the depth of 120 cm. After the harvest, grain protein content was determined (% N x 6.25). The connection between particular parameterswa s determined usingcorrelatio n andregressio nanalysis . Results: NO3-Nsum s significantly varied ona yea r toyea r basis. Theprotei n content in theNf Otreatmen t wasshow nt ocorrelat e withth esu m ofNO3- Ni nth esoi l(u pt o 120c mi nwinte r and6 0i nsprin g 1 barley) atth een do f winter (Table 1).Addition s of Nf (30... 120k gha' ) affected thegrai n yield andprotei n content, theexten to fchang edependin g onth eleve lo fNO3- N(Figure s 1an d 2). Table 1.Relationshi p betweenN03- N inth e soilan dgrai nprotei n contenti ntretmen t withn oN .

Maltingbarle y Proteini n NO3-N sums,k gha" 1, soil depth grain (%) NO 0-60 0-90 0-120 60-90 90-120 Winterbarle y 12.9 67 101 143 34 72 Corr. coeff. 0.44 0.75** 0.87** 0.71* 0.65* Springbarle y 11.9 61 100 129 39 65 Corr. coeff. 0.95** 0.79** 0.67* 0.59 0.61 *, **significan t at0.0 5an d0.0 1 (n= 11 )

According to these results, it may be concluded that the grain protein content could be well predicted before the harvest (Figure 2). The control of soil nitrate N could help avoid the cultivation ofmaltin gbarle yi nsoil swit h excessive NO3-Nlevels . Division 4 697

1 Figure 1.Effec t ofN0 3-N sums(k gha )i nsoi l0-6 0c mfo r springan d0-12 0c mfo r winterbarle y andN-fertiHze r onyiel dan dprotei ncontent . Yield Yield 180 % | Springbaile y | 160 ——•" <40 <130 140 0-60c m 130-150 120 100 N. 40-60 80 No >60 >150 60 30 60 90 120 150 120 150 Nf.kgh»-1 NCk gh a" I Proteinconten t Proteinconten t 16 16

120 150 Ntkgha '

Figure2 .Relationshr pbetwee nN0 3-Ni n soil(0-6 0 cm springbarley ,0-12 0 cmwinte rbarley ) and grainprotei nconten ti nmarrin gbarley . Proteincontent ,(% ) 16 15 | Springbarle y | " | Winterbarle y | 14 13 12 •^^^ " 12.5 0-60 cm f ^ 11 10 9 y= 6.2 4+ 0.094 x y= 8.5 9+ 0.028 x 8 r= 0.954* * r= 0.864* * 7 30 60 90 120 150 180 210 NO 3 N.kgha '' Conclusions: Ourstud yha s shownmaltin gbarle yt ob ever ysensitiv et oresidua l Nmin. Overall status ofNO3- N hasha d agreate r influence onprotei n contenttha nth efertilize r N. References: Foster, E., et al., 1987.I n "Nutritional Quality of Cereal Grains" (Ed. Olson R A and Fray K S), PubMediso n Wisconsin, USA, pp337-396 . Garz, J., et al., 1983.Wissenschaftlich e Zeitschrift Univ. Haue 4:99-110 . Malesevic, M, et al., 1992. In "MaltingBarle y and Malt" (Ed Lazic V) Faculty of Agricult. Novi Sadp p 14-52. 698 Book of Abstracts 4th ESA-congress

EXAMINATION OF THE ORGANIC GROWTH OF FIVE SILAGE MAIZE VARIETIES BY APPLYING STATISTICAL APPROACHES

Istvân Pâlinkâs

Senior Lecturer, Candidate of Agrarian Science, UASG College of Agriculture, Gyöngyös

Summary From the points of view of feeding and knowledge of varieties, we deem important to examine how and to what extent the nutritive values accumulate in the fodder-plant during its growth, in relation to time elapsed. In order to determine this, we conducted an experiment in the site of the model farm of College of Agriculture in 1994, involving 5 varieties (Variety 1: Pioneer 3965A MTC, variety 2: Pioneer 3732 SC, variety 3: DEMA-210 TC, variety 4: SzDC-488, variety 5: HS-50) of silage maize so that we can describe the process of their development in time (organic growth) in possesion of adequate data, in form of trend functions.

We described the 15-member condition-time tendency resulting from the examined parameters /height (cm), raw protein x 10 (kg tonna), dry substance x 102 (MJ tonna"1), net energy content x 10 (MJ tonna" )/ of the individual varieties under survey, by applying cubic trend functions. The reason why we used cubic function differring from the special literature where the change is depicted by exponential function, by growth stages, is that, this way, by one function, the organic growth of the individual nutritive values can be provided as being easier to handle and better matching, in respect of both growing and declining phases, at a time. We 2 3 provided the trend functions in the following form: Yy = b0+br t+b2- t +b3- t where t means the time in terms of weeks.

Our Figure attached hereto shows the trend and diagram of all examined factors for the variety 1, selecting the trend values and emasuring units so that they can be depicted in a system of co-ordinates. From them, one can monitor the development of the individual nutritive values in time, the place and size of its maximum and the proposed interval for harvesting.

In appointing the interval for harvesting, we applied the basic principle accepted by the special literature whereas the silage maize is advisable to be harvested from the point of view of feeding when its dry substance content is between 35 and 40%. By varieties, it takes place in the following intervals (weeks):

variety 1 11.9 < t < 13.1 variety 2 12.5 < t < 13.8 variety 3 12.4 < t < 13.5 variety 4 12.7 < t < 14.15

As regards variety 5, this did not occur in the period under survey since this is a late repening, long growing variety: its dry substance content was of 33.7% at the 15th sample-taking. Division 4 699

Values

4 1 1 Time 2 3 4 5 6 7 9 10 11 12 13 14 15(weeks )

•HEIGH T(cm ) RAWPROTEI Nx 10 (kg/tonne) -DRY SUBSTANCEx 10 (kg/tonne) NETENERG YCONTEN Tx 10 (MJ/tonne)

Trends of maize for silage (variety 1)an d their diagram 700 Booko fAbstract s4t hESA-congres s

METABOLIC ENGINEERING OFLIGNI N THROUGH FLUX CONTROL IN THE PHENYLPROPANOID BIOSYNTHETIC PATHWAY

Vincent J.H. Sewalt, Jack W.Blount , Richard A.Dixo n

Plant Biology Division, The SamuelRobert sNobl eFoundation , P.O.Bo x 2180, Ardmore, Oklahoma 73402, USA

Introduction Forage lignin content and composition are under control ofsevera lgene s inligni n biosynthesis and are, therefore, amenablet ogeneti c engineering (Figure 1).W eai ma treducin g lignin concentration orligni n methoxylconten t inalfalf a to increaseth e nutritional value ofthi s forage legumeimportan t toth e dairy industry. Wehav e demonstrated thepotentia l formetaboli c engineering ofth e ligninpathwa y by suppression ofphenylalanin e ammonia-lyase(PAL ) or caffeic acid O-methyltransferase (COMT) intobacc o (Elkinde tal. , 1990; Batee tal. , 1994; Nie tal. , 1994). Inaddition , tobacco plantswit h suppressed cinnamate4-hydroxylas e (C4H) and caffeoyl CoAO-methyltransferas e (CCOMT) havebee n generated (Masoud etal. , unpublished; Sewalte t al. unpublished). To investigate which enzymes constitute physiological control points in phenylpropanoid and ligninbiosynthesis , selected transgenic plantswit h down-regulated PAL, C4H, and COMTwer e analyzed forligni n characteristics.

Phenyalanine "°yP «>y.° V "S"0 ™^° PAL1 C4HX Ç3H XCOMTI _FSH. f COMT CinnamicAcid^O ß^L^ tCl.^ HO-^QCH, c^o^f "COM, CH OH CH CH CH 4CL 4CL 4CL

CCA-SO CcA-S O CoA-S O «-SO CoA-S O

, fccoAHjCCOM X j^ CCOMT[ ^ p o~~ 6"'""""'""*jo '"*j o Y Y^CH Y°CHj HO^f^CCH, CHjO Y^CCH, Phytoalexins OH CH en OH OH

Peroxidase Lignin Figure 1.Ligni nbiosyntheti c pathway Methods Plant material originated from several independent transgenic experiments. PAL phenotypes evaluated were control, severely sense-suppressed (primary transformants), recovering from sense-suppression (T5 plants), and sense-suppressed plants turned into PAL-overexpressors (Bate et al., 1994;Howie s etal. , 1996). C4H phenotypes were primary transformants, generated by introducing anti-sense and sense C4H constructs into control plants (Masoud etal. , unpublished). COMT-suppressed plantswer e obtained byantisens e expression (Nie tal. , 1994);plant s evaluated were controls, primary transformants, and Tl-progeny from one ofth e transformants. Middle stem sections (internodes 10an d 11fo rPA L and COMT plants, internodes 8t o 11 for C4H plants) were sampled and ground under liquid nitrogen. PAL, C4H, and COMT activities were confirmed accordingt ostandar d procedures. Freeze-dried material wasuse d forisolatio no f cellwall susin g the detergentfiber procedure , and subsequent determination ofKlaso n lignin (modified from Kaar etal. , 1991) and lignin methoxyl groups (TAPPI, 1972). Division 4 701

Results Suppression ofPA L and C4H activitiesresulte d inplant swit h substantially reduced lignin concentration (50%an d 65%o fwild-type , respectively). SeverelyPAL-sens e suppressed plants produced low levels ofligni nwit h drastically increased methoxyl content, indicative of a shift from predominantly guaiacyl-typeligni nwit h small amounts of syringylunit st o almost exclusively syringyl-typelignin . Contrary to the situation with severePAL-suppression , lignin methoxyl content was not affected by suppression of C4H. Overexpression ofneithe r enzyme resulted in changes inlignin , indicative of downstream control points inth e ligninbiosyntheti c pathway.

Figure2 .Ligni nconcentratio nan d methoxylconten ti ntobacc o plants DKL BOCH3 jCOMT ^ <£, down-regulated inCOM T COMT suppression resulted in slightlyreduce d lignin concentration (80-95%o fwildtype ) but with aconcomitan t increase inligni nmethoxy l content (Figure 2). The effects ofmoderat e COMT suppression reported here agree withpreviousl y published results obtained with lessrigorous lignin analyses (Ni et al., 1994),bu t are atvarianc ewit h the effects of severeCOM T suppression (reduced syringyl:guaiacylratio , noreductio n inligni ncontent ) reported by other groups. The variable resultsfrom differen t COMT-antisense experiments canb epotentiall y explained byth e existence of parallel methylation pathways involvingfree hydroxycinnami c acids or their CoA thiolesters inwhic h distinct enzymes, COMT and CCOMT, catalyzefunctionall y identical reactions.

Conclusions Although the most drastic results are obtained byPA L or C4H suppression, lignin manipulation via suppression ofO-methyltransferase s bears more practical relevance for forage improvement duet o possible pleiotropic effects associated with altering enzymatic steps earlier inth e phenylpropanoid pathway. Our current transgenic approach isth e separate and simultaneous down-regulation ofCOM T and CCOMT intobacc o and alfalfa to dissect the relative importance or redundancy ofth e two enzymes, and to obtain amor ethoroug h suppression ofOM T activity.

References Bate et al., 1994.Proceeding s ofth eNationa l Academy of ScienceU.S.A . 91:7608-7612 . Elkind et al., 1990.Proceeding s ofth eNationa l Academy of ScienceU.S. A 87, 9057-9061. Howies et al, 1996.Proceeding s ofth eNationa l Academy of ScienceUS A (inreview) . Kaar et al., 1990. Journal of Wood Chemistry and Technology 11:447-463 . Ni et al., 1994. Transgenic Research 3: 120-126. TAPPI, 1972.Methoxy l content ofpul p andwood . T20 9 su-72,TAPPI , Atlanta GA. Division6

Agriculture-environment relationships. 704 Book of Abstracts 4th ESA-congress

THE EFFECT OF DIFFERENT FORMS OF NITROGEN FERTILIZERS ON THE ACCUMULATION OF CADMIUM AND ZINC INPLAN T TISSUES

J. Balik, P. Tlustos,J . Szakova, V. Vanek

Department ofAgrochemistr y andPlan tNutrition , Czech University ofAgricultur e inPrague , 1652 1Pragu e 6 - SuchdoL,Czec h Republic

Introduction Therat e ofnitroge n fertilizers andthei r forms have animportan t effect onth e composition ofsoi l solution and composition of cations(macronutrients ) inplan ttissue s( Bali k et al., 1990) . Therefore theinfluenc e of different nitrogen fertilizers onth e accumulation ofC d andZ ni nplant s was studied.

Methods Threeyea r ( 1992 - 1994)mode lpo t experiments wereuse d inthi sstudy . Two cropswer e planted on different soils. Oatwa splante d at soilPrestano v andmaiz e atsoi lCerven y Ujezd. Oat washarveste d assilag e crop( about 28% d. w.) andmaiz ea tplan theigh t of 100c m( about13 % d.w.).

Mainparameter s ofuse d soils Soil- Prestanov Soil- Cerven y Ujezd Soiltyp e OrticLuvisol s OrticLuvisol s Soiltextur e sandy loam loamy pH/KCl 5.1 6.7 Cox.( %) 2.30 1.35 CEC (mval/lOOg) 23.0 14.8 V(%) 55.7 94.6 Cd (HN03) (mg.kg"1 ) 0.50 0.20 Zn (HN03) (mg.kg" ) 54.2 36.7 Cd (TOT) (mg.kg ' ) 0.57 0.27 Zn (TOT.) (mg.kg"1 ) 128.4 73.5

Ammonium sulphate (SA),ure a (V), ammonium nitrate (AN), calcium nitrate (CaN), and sodium nitrate (NaN) were used asnitroge n fertilizers. Chemical compounds were applied as soil solution andmixe d thoroughly with the soilbefor e the sowing of grains. Rate of applied nitrogen was 300 mg.kg"1 ofsoilforoat and 800mg.kg" 1fo r maize.

Results Experiments showed nonsignificant effect of applied fertilizers on the yield of both crops. The maize slightly increased yield on the ammonium sulphate treatment. Figures 1an d 2 showed the increased Cd andZ n concentration inbot h growingplant s attreatment s of acid derived fertilizers. Plant uptake of N03" caused the release of OH"int o soil solution. The hydroxyl anion together with rest of calcium in the soil solution led to higher pH at the treatments of calcium and sodium nitrate. Opposite processes were observed after application of ammonium sulphate. Soil pH dropped in 4.49 at (SA) treatment and rose on 5.36 at (CaN) treatment after the oat harvest. The results of maize experiment confirmed the same pattern. pH was 5.43 at (SA) and 6.70 at (CaN) treatmens. Significant pH differences were mainly caused by high nitrogen rates in pot experiments. Eriksson ( 1990 ) found higher concentration of Cd in ryegrass, wheat and oat after apphcation of acidfertilizer s and Wu et al. (1989) at ryegrass experiment. Results of Balik et al.( Division6 705

1994) confirmed the lower Cd uptake by spinach using mild extradant ( 0.01 mol.1 CaCl2) • The content of available soil Cd was lower at (CaN) treatment compared to (SA) treatment.

Figure1 The Cd concentration (bars) in plants and pH-KCI in soil

100%= 52 8 ppb 100%=803ppb 120 100 rM o 5.5 * 60 X Q. m 5 40- %

20- $111 1^1 AN SA CaNNaN SA V CaN

Figure2 The Zn concentration in plants

100%=82ppm 100%=169ppm

AN SA CaN NaN SA V CaN Conclusions Three year model pot experiments were used for study ofbehaviou r of different forms of nitrogen fertilizers on the Cd and Zn uptake by oat and maize. Application of ammonium sulphate and ammonium nitrate caused the lugher accumulation of Cd and Zn in plant tissues. Calcium nitrate and ammonium nitrate treatments showed opposite effect inbot h plants.

References Balik, J. etal., 1990. Proc. Stickstoff-Dungemittel-Boden-Pflanze, Praha: 84-88. Balik, J. et al., 1994. Prague, Czech Republic, Report 01, Czech University ofAgriculture ,262p . Eriksson, J.E., 1990. Uppsala, Sweden, PhD Thesis, 120 p. Wu, Q. T. et al., 1989. Paris, France, CR. Acad. Sei., 309, s. Ill: 215-220. 706 Book of Abstracts 4th ESA-congress

EFFECT OFTOXI C ELEMENTS ONWINTE R WHEAT ON BROWN FOREST SOIL

L. Fodor

GödöllöUniversit y ofAgricultura l Sciences, College ofAgricultur e Gyöngyös Mâtrai St. 36, 3200 Gyöngyös, Hungary

Introduction The contamination ofth e agricultural environment and arable land withheav y metals and other possibletoxi c elementsi smor e andmor e dangerous. Thepollutant s come from metal-mining, industrialproduction , traffic, industrial and communalwast ewaters , acidrains , etc. (Csathó, 1994, Szabó, 1995). Thetoxi c elements appear inth e soilan dwate r andthe y become available for theplants . The cultivaited plants - asprimar y and secondary biomass - serve ashuma n food directly orindirectly . It'sver y importantt o knowho wth etoxi c elementsca nmov e inth e soil,i n whatwa ythe y getint oth eplant s andi nwha t quantitiesthe y accumulate inth e vegetative and generative organso fth eplant s(Szab ó et al., 1994,Kâdâr , 1995). Relationbetwee n toxic elements, soilan dplan tma y be studied in anobjectiv e manner on arable land. The aim ofou r experiment ist o describeth e effects of sometoxi c elements onbrow n forest soils, cultivated plants andthu s onth e food chain.

Methods Thisi sa field study , wichi sbein g conducted on aslightl y acidbrow n forest soil(pH=6,2 ) atth e CollegeFar m in Gyöngyös. The experiment isconducte d in split-plot designwit h three replications on 35m 2field plots . Effects of 8toxi c elements(Al ,As , Cd, Cr, Cu, Hg,Pb ,Zn ) were examined ontre e levels(0/30 , 90, 270k g element • ha"1)usin g soluble salts. Thefirst yea r (1985)w euse d winter wheat asa tes tplant . Toxic effects and effectiveness oftreatment s were appraised and analysed duringtillerin g andharvest . Freshweigh t ofgree n shoot sampleswa s determined andth etoxic element content ingree n sproutswa sanalyse d by ICP-technique. At harvest the grainyiel d was determined on eachplot .

Results

Results ofth efirst yea r ofth e experiment arepresente d intable s 1 and2 .

Table 1.Effec t oftreatment so n element content ingree n sprout duringtillerin g

Symbol of treatments1 % element •ha1 LSDS-A Mean elements 0 30 90 270 element content in green sprout mg kg1 Al 135 - 208 74 n.s. 139 Zn 31 34 38 39 9 37 Hg 0 5 19 86 25 37 Cu 8 9 8 11 3 9 As 0,0 0,4 2,0 2,8 1,2 1,7 Cd 0,1 1,0 1,7 2,2 0,9 1,6 Cr 0,5 4,6 2,7 13,1 8,8 6,8 Pb 0,5 1,7 2,6 3,0 2,7 2,4 Division 6 707

Table 2. Effect oftreatment s on fresh matter duringtillerin g and on grain yield at harvest

Symbolo f treatmentsk g elementpe rh a LSD5% Mean elements 0 30 90 270 2 greensprou tgpe r m Al 1357 - 981 1059 1132 Zn 1357 1294 910 890 1031 Hg 1357 1119 1244 989 1117 Cu 1357 1019 503 160 561 As 1357 903 799 760 397 821 Cd 1357 1179 1224 948 1117 Cr 1357 1116 1153 1096 1122 Pb 1357 985 602 397 661 grainyiel dt pe rh a Al 4,88 - 4,80 4,40 4,69 Zn 4,88 5,45 4,72 4,19 4,79 Hg 4,88 5,42 4,35 5,13 4,97 Cu 4,88 5,19 4,90 2,65 4,24 As 4,88 5,34 4,43 3,31 1,3 4,36 Cd 4,88 5,18 5,11 4,80 5,03 Cr 4,88 5,10 5,17 4,61 4,96 Pb 4,88 4,79 4,32 2,48 3,86

Conclusions Toxic effects of Cr, Zn, Ag, Cu could betrace d duringbot h tülering andharvesting . Cd, As,H g and Cr showed considerable enrichment ingree n sprout, which demonstrated their intense mobility on slightly acidbrow n forest soil. Inth e case ofhighe r Cd, Cr,As , Hg contaminationsth e green sproutso fwinte r wheat are qualified astoxi c accordingt o Hungarian standard (4/1990.(II . 28.) MEM decree) sothe y musn't beuse d as fodder-crop.

References Csathó, P., 1994. Contamination ofth e environment withheav y metals andit sconsequence s on agriculturalproduction , MTA TAKI, Budapest, 176.p . Kâdâr, I., 1995.Contaminatio n ofth e soil-plant-animal-human food chainwit h chemical elements inHungary , MTA TAKI, Budapest, 388. p. Szabó,L . et al., 1994.Heav y metalsi nth e soilan dplants , GATE, Gyöngyös, 419-422.p . Szabó, L., 1995.Environmenta l aspects ofmicr o element content of soils, GATE, Kompolt, 95- 102. p. 708 Book of Abstracts 4th ESA-congress

GROWINGTH EPLANT SO NTH ESOI LPOLLUTE DB YHEAV YMETAL S

N.Kharitonov,M.Bulgacova,V.Pashova,I.Onuphrieva Agroecology Institute, Agrouniversity,Voroshilov st.25,Dnepropetrovsk,320027 ,Ukrain e

Introduction It was established that zone of technogenical contamination of soil in the Dniepropetrovsk region is 10-15 times bigger than area of land disturbed by mining. For example, in the Krivoy Rog iron ore deposition dust post blusting cloud are main source of heavy metals pollution. Thus, it is necessesary to undertake the steps connect with improvement of biological activity contaminated soil, reduction of heavy metals moving in the soil-plant system.

Methods The investigations were conducted in the conditions of laboratory, vegetative,micro- field experiments. The coefficient of quarry dust fitotoxicity (c )wa s determined by the mathematical equation c=m<>-mi/mo.Th e meaning of mathematical symbol for m»i sa bioproductivity of plant on the untread soil, mi is a bioproductivity of plant on the heavy metals contaminated soil. Salts of metals (Fe, Co, Pb and Cd) were brought into the soil in doses which were equivalent to technogenic load. For the soil protection from the toxic action of redundant elements the biohumus and huminate preparation were introduced on the experimental plots of land in barley crops in dose 0,6 and 0,01 kg m-2.The huminate preparations application was made in the several variants(A- introduction in soil,B-treatment of seeds before sowing,C-treatment of sowing).

Results Results arepresente d inth e Table 1-3. Table 1 Maximum meaning of the heavy metals composition in the quarry dust, ppm

Denomination Fe Mn Zn Cu Ni Co Pb Cr Cd

Quarry dust of the primary cloud 15000 800 80 32 25 25 20 8

Quarry dust of the secondary cloud 385 210 259 67 14 63 35 37 Division 6 709

Table 2 Coefficient of fitotoxic action of heavy metals and quarry dust

Plant Dose Substrat

Sand Sand/Clay

Barley 1% 0,1 0,25 Soya 1% 0,07 0,12

Table 3 Influence of the huminate preparations on the barley growth on the soil contaminated by heavy metals,g m -2

Raw material Variant in method B Bioproductivity application, country

Control 315 A 435 A+C 392 A+B Brown coal, 419 Kazakhstan A+B+C 255 A+B Brown coal, 343 Ukraine A+B+ C 331 A+B High-moor 348 peat A+B+ C 300 A+ B lowland 288 peat A+B+ C 275 LSD 46

Conclusions Technoggenic pollution of soils by heavy metals lead to increasing of its migration on trophical chains. Reduction of biological activity of technogenically contaminated soils evoke developing their degradation processes. Improvement of soil condition is possible thanks to realization such rehabilitation steps as using sorbents, vermicompost and huminate preparations. 710 Book of Abstracts 4th ESA-congress

THEACCUMULATIO N AND DISTRIBUTION OF CADMIUM, ZINC AND ARSENIC BY POPPY

D. Pavlikova, V. Vanek, J. Szakova, J.Bali k

Department ofAgrochemistr y andPlan tNutrition , Czech University ofAgricultur e inPrague , 165 21Pragu e 6 - SuchdoL Czech Republic

Introduction Heavy metals can enter intoth e food chainthroug h theiruptak e byplants . One of high Cd accumulators,poppy ,ha slon gbee n cultivated in Czech Republic for popularity ofth e seeds.Th e degree of Cd and otherheav y metalsuptak eb yplant si sinfluence d by factors such assoi lpH , organicmatter , sesquioxide content etc. (Oliver et al., 1994,H e et al., 1994). Therefore poppy hasbee nplante d onth e different polluted soilstreate d with remediated materialst ofind thei r effect onth euptak e ofheav y metalsb y seeds andth emetal sdistributio n withinth eplants .

Methods Poppy (Papaversomniferum L.) was cultivated onthre e soilswit h different contents ofheav y metalsi npo t experiments from 1992t o 1995. Somepropertie s ofthes e soilsar epresente di n Table 1.Lime , farmyard manure andbentonit ewer e appliedi nth efirst yea r ofthi s experiment. Direct and subsequent effect ofuse d materialswa sinvestigated . Fertilizer (NPK) was applied every year. Theyiel d ofpopp y seeds and capsuleswa s determined. Plant tissueswer e analysed for content ofCd , Zn andAs . Heavy metalswer e analysedb yflame an dgraphit e furnace AAS. Certificate materials RM 12-02-03 Lucerne wasuse d for quality tests ofanalyses .

Results Theyield s ofpopp y seedswer eno t effected byth e application of allthre e materials,bu t minor effect oflim e application was observed on acid soil. Our results confirmed that content ofheav y metalsi n soili sth e main factor influencing theiruptak e byplants . Thehighes t content of Cd(4.6 4 mg .kg'1) andA s(0.14 6mg.kg" 1)i n seedswa s determined onth emos tpollute d soilKbely . The effect oflime , farmyard manure andbentonit e application onth euptak e ofmetal s differed with elements andteste d soils(Tabl e 2). Positive effect of applied materials on Cd, Zn andA s concentration wasno t observed on soilwit hth elowes t heavy metal contents (Cerveny Ujezd). Lime application made positive effect atth e cadmium accumulation onth e acid soil(Prestanov) . Cdconcentratio n was decreased by 40 %i n seeds andb y 59 %i n capsules overth e whole experiment. The strong decrease in cadmium after addinglim ei ssignifican t (P <0.05) . Application offarmyar d manure alsoreduce d Cd concentration by 18% i n seeds andb y 25.5 % in capsulesi nmea n oftw o studied soils(Prestano v andKbely) . Zn content in seedswa sno t significantly reduced in seeds,bu t itsconten t in capsuleswa sreduce d by 36 - 59 % atal l treatments on acid soilPrestanov . Seed content of arsenicwa s effected only onth e most polluted soila tlim etreatmen t (by 16% i n seeds and 28 %i n capsules) and atfarmyar d manure (by 14% in seeds and 8% i n capsules).Meta l distribution inpopp y plants differed inelements . Moretha n 50 % ofcadmiu m was accumulated in seeds,bu t 83 % of arsenicwa s accumulated in stemsan d leaves(Tabl e3) .

Conclusions Theuptak e ofcadmium , zinc and arsenicb ypopp y wasmainl y effected bythei r contentsi nsoils . The effect ofuse d materials onth euptak e ofmetal s differed in elements and soils. Application of limeshowe dth ehighes t drop inheav y metal accumulation in seeds and capsules. Cadmium was mostly found in seeds,bu t arsenicwa smor e accumulated instem s andleaves . Division 6 711

Table 1. Selected properties ofth euse d soils

Sou pH/KCl P K Mg Ca Cox Cd Zn As mg.kg"1 % mg.kg"1 Cerveny Ujezd 6.8 137 266 132 2780 1.35 0.33 85.7 19.7 Prestanov 5.1 21 200 244 2380 2.10 0.76 179.9 19.7 Kbely 7.3 95 275 152 6090 2.09 17.50 179.2 16.7

Table 2. Concentration of Cd, Zn andA si npopp y seeds (mg.kg1)

Treatment Sou

C. Ujezd Prestanov Kbely Cd concentration 0 0.432 2.842 4.463 lime 0.520 1.717 5.103 bentonite 0.411 2.340 4.246 farmyard manure 0.521 2.339 3.648 Zn concentration 0 70.69 108.89 80.70 lime 77.04 102.67 89.74 bentonite 75.90 109.77 84.83 farmyard manure 72.14 108.00 75.47 As concentration 0 0.093 0.053 0.146 lime 0.098 0.062 0.122 bentonite 0.083 0.055 0.149 farmyard manure 0.067 0.061 0.126

Table 3.Distributio n of Cd, Zn andA si npopp y plants (%)

Seeds Capsules Stem+leaves Cadmium 54.9 12.3 32.8 Zinc 43.8 9.2 47.0 Arsenic 6.5 10.5 83.0

References Oliver, DP. et al., 1994. Journal of Environmental Quality 23: 705-711. He, Q. B. et al., 1994.Water , Air and SouPollutio n 74: 251-265. 712 Book of Abstracts 4th ESA-congress

HEAVY METALS AND DIFFERENTIATION OFPERENNIA L GRASSES IN THE PATHOGEN RESISTANCE CHARACHTER

VA. Pozdnyakov, A.Kudums , A.I. Drizhachenko

Department ofPerennia l Grass Selection, SZNP O"Belogorka" , 188231 Leningrad Gatthina locality, Russia

Introduction In recent 3 decades in Russia processes of a biodiversity elimination were increased. Environment pollutions by industrial outputs icluding heavy metals (HM) is one of basic factors affecting on environment conditions negatively. However nature of plant resistance to HM is not studied. There is not clear differences in the resistance of both plants species and their hybrids. As was shown by Fenic et al. (1995) detoxication of HV by plants carries by participation of organic acids, metalothioneins, phytohelatins and tonoplast transferase emergence.ln addition many metals are necessary to plants as unchangeable microelements for their viable. These are Fe, Co, Mn.Mb, Se, Cu. Enzymes containing HM iones often carry out protection functions (Zarubina et al., 1988).

Methods xFestulolium hybrids have been synthesized by authors due to crosses of tetraploidy cv.Orlinskij plants (Lolium perenne L.) belonging to the Western- European variety-type group (Shutova, 1977) with plants of the cv.Baltica (Festuca arundinacea Schreb.) selected from the VIR collection island Sahalin sample. Female parent plants were emasculated,unripe hybrid embryoos were grown on the Randolf-Kox medium. Methods for an estimation of resistance hybrids to Erysiphe graminis DC.f.festucae Jacz. .Puccinia coronifera Kleb.f.fectucae Eriks. and the local rust population has been described (Pozdnyakov,Drizhachenko,1983;Pozdnyako v et al., 1986). Analysis of the microelement content in the plant green mass was carried out accoding to Sillanpaa (1990). The statistic analysis of evidences in heredity of pathogen resistance plant properties was carried out according to Wolf(1966) and Rokitskij(1974).

Results Our experiments demonstrated German cultivars of Festuca pratensis L. had a few of Fe-contents (58-85+26,3 mg/kg of dry matter)in leaves of the second cutting plants than the Russian cv. Lubava, wich affected by local population of leaf spot plant pathogens. Hybrides of xFestulolium of our selection (1983-3 F5, 1982-52 F3) differencing on resistance to rust fungi and powdery mildew were remarkable for Fe-contents (78-104+26,3 mg/kg). The same hybrides had also high contents of Cu (6.0-9.1+3,6 mg/kg). It may suppose cells and tissues of the plants have more activity of Fe- and Cu-containing ezymes. Differences on Mn-content were not found.

Conclusions Data of our experiments are of interest to studying rules of geographic variability of plants, as according to Petuchov (1995) unusual plant appearence had found in places of the large breakes of continents, ex. at Africa or at the Middle and the Far East. Division6 713

References

Fenic S.J.,Trophymjak T.B.,Blum Ja.B., 1995. Progress in modern biology,pp.261-275. Petuhov l.,1995.S.-Petersburg: Institure of Geochemistry. PozdnjakovV.A.,Drizhachenko A.I.,Kostitsin V.V., 1986. Bul.bot.,gen.and plant breed. 103:67-70. Pozdnjakov V.A.,Drizhachenko A.I.,1983.Improve of the plant defence in the Pribaltic and Belorus.Riga.Thesises,pp.60-61. Rokitskij P.F., 1974.The statistic genetics.Minsk. ShutovaZ.P., 1977. Bul.bot.,gen. and plant breed. 59:70-87. Sillanpaa M.,1990. FAO Soils Bull.48 VolfV.G. 1966. Statistics,Kolos,Moskow. Zarubina M.A. et al.1988. Bull.ofVIZR 70:59-72. 714 Book of Abstracts 4th ESA-congress

THE EFFECT OF SOD. REMEDIATION TREATMENTS ON PLANT UPTAKE OF CADMIUM, ZINCAN D ARSENIC

P. Tlustos,J .Bahk ,J . Szakova,D .Pavlikov a

Department of Agrochemistry andPlan tNutrition , CzechUniversit y ofAgricultur e in Prague, 1652 1Pragu e6 - Suchdo L CzechRepubli c

Introduction Lime,farmyar d manurean dbentonit ear euse d extensively assoi ltreatment st oimprov esoi lstructura l propertiesan ddecreas eth emobilit yo fheav ymetals . Alloway(1990 )summarize dpublishe dresult s andfoun d loweravailabilit y ofC di nsoil swit hhighe rpH ,excep t onesource .Lun e(1985 ) confirmed lowerC duptak eb yplant sa tlime dsoils .Acidificatio n ofthat soilsincrease dC dan dZ nuptak eagain . Highersoi lsorptio nshowe dlowe rC dconten ti noa tbiomas s (Haghiri, 1974).Th ehighe rconten to f organicmatte ran dsorben tmaterial sdecrease d accumulationo fheav ymetal si ncarro troot sbu tdi d noteffec t contenti nryegras san dsprin gwhea t(Hasselbach , 1990).

Methods Theeffect s oflime ,farmyar d manurean dbentonit eapplicatio no ncro pyield san dheav ymeta l accumulationwer einvestigate dusin gpo t experimentsove ra 4 yea rperiod .A loam y soifroml a pollutedare a of NorthernBohemi a(Czec hRepublic )wa suse di nthi sexperiment . Parameters,pH - KC1= 6.80 , amounto favailabl enutrient sP = 195,K = 504 ,an dM g= 26 9mg.kg 1 andtota l concentration ofC d= 0.60 ,Z n= 154.0an dA s= 39. 5mg.kg 'wer edetermine di nmentione dsoil . Bulksoi lwa ssieve dan dfou rtreatment swer eestablished ,phi slime ,dr y choppedmanur ean d bentonite.Remediatio nmaterial swer eapplie donl ybefor efirst plantin gi n 1992.Fertilize r(NPK ) was appliedbefor e eachcrop .Th erate so ffertilizer s differedfrom growin gcrop .Th esam ecro protatio n wasgrow ni neac htreatment . Silageoa twa splante di n 1992,silag emaiz ei n 1993, springbarle yi n 1994,an dpopp yi n 1995.Th eyiel do ffresh an ddr ymatte r andth econcentration so fCd ,Zn ,an dA s weredetermine dfo r eachtreatment ,crop ,an dlocatio nwithi nth eplant .Eac hsoi ltreatmen twa s analyzedever yyea rafte r harwestfo r amounto favailabl emetal sb ythre edifferen t extractants( 2 1 1 1 moll" HNO3 ,0.00 5mol.1" DTPA,an d0.0 1moLl" CaCl2(Tlusto se tal , 1994).Heav ymetal swer e analyzedb yflame an dgraphit efurnac e AAS.Certificat e materialsBC R-14 2 Light Sandy Soilan d RM 12-02-03 Lucerne wereuse dfo r qualitytest so fanalyses .

Results Theapplicatio n ofal lthre ecompound sha da positiv eeffec t onth eyiel do fth efirst tw o crops,th eoa t andmaize .Th eyiel dincreas ewa sapproximatel y 13% i nbentonite , 10% i nmanure ,an d 5% i nlim e treatments.Th efollowin g cropsbarle yan dpoppy , showed aslightl yreduce dyield . Theaccumulatio n ofheav ymetal sdiffere d by cropan dspatia llocatio nwithi nth eplan t( Table 1, 2, 3).C dwa smor e accumulatedi nstalk stha ni ngrain .Arseni cfollowe d similarpattern ,excep tmaiz e withth elowes tA sconcentration . HigherZ ncontent swer efoun d inseed sa scompare dt o stover,agai n withth eexceptio no fmaiz ewit hth ehighes tconcentratio n ofZn . Theeffec t oflime ,bentonit ean dfarmyar d manureapplicatio n onth euptak eo fmetal sdiffere d by elementan dcrop .C duptak ewa sdecrease db y eachtreatmen tprobabl ythroug h reducingth eamoun t ofC di nsolution . Thehighes t effect wasfoun d inth emanur etreatmen t( Table 1).Th emea n concentration ofC di nplant sfel lb y2 5% i nthi streatmen t( mea n ofal lfou r crops).Th econcentratio n ofZ ni nsoi lwa sabou t onehundre dtimes highe rtha nC d( Tabl e2) , theapplicatio n ofremediate d compoundsha dn opositiv eeffec t onZ nuptak eb y crops. Plantuptak eo fA swa sslightl y affected, positivemea neffect s werefoun d inth emanur ean dbentonit etreatments . Division 6 715

Theamoun t ofextractabl eelement sdepende d onth estrengt ho fsolution . Theconcentratio n ofal l threeelement sdecrease di nro wHN0 3> DTP A> CaCl 2 ofuse dextrac t solutions.Differen t element uptakeb yplant sha sno tbee ndetecte d atsoi lremediatio ntreatment sb y chosenthre eextractants .

Table 1. TheC dconten ti nth edr ymatte ro fsubsequentl ygrowin gplant s(mg.kg" 1)

Treatment Oats Maize Barley Poppy Grain Straw Seed Capsule Zero 0.368 0.953 0.162 0.378 0.213 0.259 Lime 0.350 0.819 0.129 0.450 0.130 0.202 Sorbent 0.203 0.803 0.136 0.411 0.305 0.197 Manure 0.213 0.494 0.147 0.450 0.188 0.123

Table2 .Th eZ nconten ti nth edr ymatte ro fsubsequentl ygrowin gplant s(mg.kg J)

Treatment Oats Maize Barley Poppy Grain Straw Seed Capsule Zero 23.20 87.40 31.58 30.40 59.19 10.84 Lime 24.91 159.20 32.52 28.88 57.53 14.01 Sorbent 22.39 99.60 32.30 33.08 71.18 17.99 Manure 22.39 100.89 32.31 25.90 48.69 11.59

Table3 . TheA sconten ti nth edr ymatte ro fsubsequentl ygrowin gplant s(mg.kg' )

Treatment Oats Maize Barley Poppy Grain Straw Seed Capsule Zero 1.883 0.731 0.622 1.740 1.610 5.772 Lime 2.040 0.648 0.731 1.764 1.814 3.821 Sorbent 2.093 0.691 0.698 1.944 1.093 3.418 Manure 2.167 0.718 0.772 1.666 1.336 2.787

Conclusions Theconcentratio n ofheav ymetal si nbiomas swa seffecte d bygrowin gcrop .Highe rconcentratio no f Cdan dA swa smostl yfoun d instalks ,Z nwa smor eaccumulate di ngrain . Applicationo flime ,manure , andbentonit edecrease dth eC daccumulatio ni nth efirs t andsecon d crop,an dslightl ydecrease dA s content overal lfou r crops. Thehighes tdeclin eo fheav ymeta laccumulatio nwa sfoun d at farmyard manuretreatment .

References Alloway,B .J. , 1990.Heav ymetal si nsoils .J .Wille yan dSons. , NewYork ,33 1 p. Haghiri,F. , 1974.Journa lo fEnvironmenta l Quality 3: 180- 183 . Hasselbach,G. , 1990.Verban d DeutscherLandwirtschaftliche r Untersuchungsun d Forschungsanstalten, ReiheKongressbericht e30 :28 1- 286 . Lune,P., 1985.Rapport , Instituutvoo rBodemvruchtbaarheid , No. 13/85,4 5 p. Tlustos,P .e t al., 1994.Rostlinn âvyrob a 40: 1107- 1121. 716 Book ofAbstract s 4th ESA-congress

EVALUATING THE IMPACT OF PESTICIDES ON THE ENVIRONMENT USING AN INDICATOR BASED ON FUZZY CODED VARIABLES H.M.G. vande rWer f andC .Zimme r INRA, Station d'Agronomie, BP507 ,6802 1 Colmar, France. Email [email protected] Introduction Theus eo fpesticide si nagricultur ecause sundesirabl eeffect s onth enatura lenvironment .W e propose anindicato r ofth eenvironmenta l impacto fa pesticid e application (L^,)a sa decisio nai d toolfo rfarmers . Theenvironmenta l impacto fa pesticid elargel y dependson :a )th eamoun t applied,b )it srat e ofdegradation , c)it spartitionin gt oth eair ,th esurfac e water andth e groundwater,d )it stoxicit yt oth especie si nthos eenvironmenta l compartments (Van derWerf , 1996).Severa l methodshav ebee npropose d toestimat epesticid eenvironmenta l impact (Levitane t al., 1995; Vande rWerf , 1996).Non eo fthes emethod s aggregates the four criteria mentioned aboveint oa singl eoutpu tparameter . Toasses spesticid e environmental impactthre etype so finpu tvariable sar e available:a )pesticid e characteristics (e.g.toxicit y towate r organisms),b )characteristic s ofth eenvironmen t (e.g. the runoff risk ofth efield), c )characteristic so fth epesticid eapplicatio n (e.g.th esite :o nth ecrop ,o n thesoil ,i nth esoil) .Fo rsom eo fth einpu tvariable sth evalue savailabl ear e certain andprecis e (e.g.rat eo fapplication) . However, often thevalue sar e imperfect: theirvalidit y mayb e doubtful (e.grunof f risk),o rthe yma yb eimprecis e(e.g .soi lhalf-life) . Theeffec t ofth einpu tvariable so n theris ko fenvironmenta l impact can beexpresse d inevery-da y language (e.g.I f therunof f risko f thefield i slarg ean dth epesticid ei sapplie d onth esoi lan dth epesticid e istoxi ct oaquati c organisms then therisk o fsurfac e watercontaminatio n islarge) .W e havebase d ourindicato ro n anexper t systemusin g acollectio n offuzz y membership functions anddecisio n rules.Thi s techniquei srobus t when uncertain orimprecis edat ai suse dan dallow sth eus eo fknowledg e which isexpresse d inever y daylanguag e (Bouchon-Meunier, 1993).

Methods Thevalu e ofL^ ,depend s onfou r variables:P (presence ,reflectin g amount andpersistence) ,Rgro (risko fgroundwate rcontamination) ,Rsur (risko f surface watercontamination ) andRair (volatilization risk).Th evalu eo feac ho fthes eintermediair yvariable sdepend s ontw o tofou r input variables according tofuzz y decisionrule s which willno tb epresente d here.Fo ral lvariable sth e membershipt oa fuzz y setF (Favorable )an da fuzz y setU (Unfavorable ) has been defined using valuesfro m theliteratur e (Vande rWerf , 1996).Th evalu e ofF dependso nth erat e applied and its soilhalf-life . Thevalu eo fRgro dependso nth emobilit y ofth epesticide ,th esit eo f applicationan d themont h ofapplicatio n andit stoxicit y toman .Th evalu eo fRsur depend s onth erunof f risko f thefield, th esit eo fapplicatio n andit stoxicit yt oaquati c organisms.Th evalu e ofRair depend so n thevolatilit y ofth epesticid e andit ssit eo fapplication .Fo rth eai rth etoxicit y isno ttake n into account because anappropriat e variablei sno tavailable . L^,ca ntak evalue s between 0(n orisk o f environmental impact)an d1 (maximumrisk o fenvironmenta l impact).It svalu ei sdetermine d accordingt oa se to f 16decisio n rules,6 o fwhic h aregive n belowa sa nexample : a) Iff isF an dRgro isF andRsur isF an dRair isF then Ipesti s0. 0 b) IfP isF an dRgro isF andRsur isF an dRair isU the n 1^, is0. 1 c) Iff isF an dRgro isF and Rsur isU an d Rair isU the n Ipesti s0. 3 d) Iff isF an d Rgro isU an d Rsur isU an d Rair isU the n Ipesli s0. 5 e) IfP isU an dRgro isF an dRsur isF andRair isF then IP

Results Resultsar epresente d inth etabl e andth efigure .

Sensitivity of !„«, to variation of input variables

-Cro pcove r -A Toxicity -huma n • Month S Soilmobilit y -O Soilhalf-lif e •—Amount applied H Volatility -A Toxicity -aquati c +— Runoffris k 0.25 -H— 20 40 60 80 100 % ofth e transition interval

Analysis of the sensitivity of 1,^, tovariatio n ofinpu tvariables .Eac hinpu tvariabl e isvarie d over itstransitio n intervalfro m favorable (0%)t ounfavorabl e (100%),whil eth eothe rinpu tvariable s arekep t atthei r median value,or ,fo r crop cover, at unfavorable. The values ofP, Rgro, Rsur, Rair andIp, , for anumbe r of pesticides applied atthei r recommended ratei na fiel d with mediumrunof f risk. Pesticide Siteo f application Month P Rgro Rsur Rair Ipest Rimsulfuron plant/soil,cro pcove r50 % June 0.00 0.00 0.46 0.00 0.09 Parathion plant/soil,cro pcove r 100% Aug. 0.07 0.00 0.20 1.00 0.13 Cyfluthrin plant/soil,cro pcove r 100% July 0.07 0.00 0.20 0.95 0.14 2,4-D plant/soil,cro pcove r50 % April 0.12 0.32 0.38 0.00 0.19 EPTC inth esoi l April 0.50 0.00 0.19 0.00 0.28 Carbofuran inth esoi l April 0.35 0.69 0.20 0.00 0.36 Glyphosate plant/soil,cro pcove r 100% April 0.66 0.00 0.10 0.00 0.38 Alachlor plant/soil,cro p cover0 % April 0.52 0.45 0.69 0.00 0.49 Atrazine plant/soil,cro p cover0 % April 0.56 0.84 0.69 0.00 0.58 Isoproturon plant/soil, crop cover10 % Jan. 0.55 0.89 0.67 0.18 0.59 Lindane inth esoi l April 0.88 0.60 0.20 0.00 0.61 Conclusions TheIpe Sl indicator can beuse da sa decisio n aidtoo lb yfarmer s orextensio n officers tocompar e the environmental impactrisk o fpesticid etreatments . References Bouchon-Meunier. B., 1993.L a logique floue. Presses Univ. de France, Paris, France, 128 p. Levitan, L. et al., 1995.Agriculture ,Ecosystem s andEnvironmen t 55: 153-168. Van derWerf , H.M.G., 1996. Agriculture, Ecosystems and Environment, submitted. Author index 720 Book of Abstracts 4th ESA-congress

Author index

Abad, A 514 Blount, J.W 700 Acutis, M 86 Bobyleva, N.I 212 Agüera, F 130, 132, 134, 172 Bockstaller, C 228,414 Agarwal, A 496 Bogdanovic, D 230,696 Alavoine, G 222, 276 Boixadera, J 322 Aleton, B 434 Boixadera Llobet, J 340 Alexandrescu, A 298 Boizard, H 488 Alexieva, A.S 640,674 Bolanos, J 164 Altimirska, R.A 320 Bonari, E 226,684 Amaducci, M.T 198 Bonciarelli, F 444 Amigues, J.P 112 Bondarenko, N.Ph 114 Angelini, L.G 516 Bonet-Torrens, M 78 Angonin, C 528 Bonhomme, R 190 Annerose, D.J.M 74, 106, 118 Bonnet, A.-C 92 Antûnez, M 322 Booth, E.J 144,540 Appel, T 324 Borin, M 348 Àrendâs, T 236 Borowiec, F 692 Arsène, G.G 362 Bos, H.J 146 Asanome, N 174 Bosch-Serra, A.D 78,340 Auclair, D 618 Bouthier, A 526 Aufhammer, W 564 Braga, R.P 148, 196 Aveline, A 326 Breman, H 620 Aydin, M 518 Brink, M 150 Babich, N 412 Brownlow, M.J.C 424 Baier, J 252 Bruckler, L 356 Baker, J.M 504 Bryson, R.J 522 Balashov, E.V. 224 Buchkina, N.P 676 Balîk, J 704, 710, 714 Bujân, M 524 Balko, Ch 76 Bujak, K 470 Ballesta, A 328 Bulgakova, M 708 Bannayan Awal, M 20 Bullock, P 14 Bänziger, M 164 Burda, V 302 Bara-Herczegh, 0 332 Bürgi, H 410 Barben, P 136, 520 Butcher, CS 416 Bartosova, M.L 446 Bzowska-Bakalarz, M 678 Baudet, D 530 Cabelguenne, M 112, 498 Bavec, F 138, 330 Cabrera, F 544 Bavec, M 138, 330 Canarache, A 448 Beblik, A.J 490 Carrai, E 658 Bellocchi, G 226 Castelao, A 658 Benincasa, P 554 Castelao, A.M 524 Berecz, K 332 Castellvi, F 80, 116 Bernardes, M.S 24, 160 Castillon, P 526 Berti, A 348 Castrignanô, A 450, 452 Berzsenyi, Z 140 Cazanga Solar, R 186 Bezdushny, M 572 Ceccarini, L 516 Bindi, M 54 Ceotto, E 258, 454, 492 Black, CR 632 Chapman, P.J 310 Blâha, L 142 Chapot,J.Y 334 Blâzquez, R 386 Chassin, P 238 Blouet, A 666 Chaussod, R 372 Author index 721

Chauvel, B 528 Dobrescu, A 680 Chiang, C 372 Domingo-Olivé, F 78, 340 Clark, W.S 522 Dominguez Giménez, J 172 Cleyet-Marel, J.C 326 Donatelli, M 86, 342, 454 Colbach, N 456, 458, 528 Doneva, E.V 88 Colnenne, C 336, 588 Doughty, K.J 540 Colomb, B 530 Dourado-Neto, D 24, 90, 160 Colucci, R 576 Dragovic, S 110 Conde, J.R 200 Drizhachenko, 1 712 Conijn, J.G 622 Dubrulle, P 530 Connor, D 72 Dumanovic, Z 26 Convertini, G 232, 234, 450, 452 Durand, J.-L 92 Copchyk,Z.M 532 Durkic.M 542,558 Cosentino, V 46, 56 Eason,W.R 630 Costea, M 298 Edmeades, G.0 164, 166 Coutinho, J.F 288, 294, 368 Edwards, A.C 310 Couture, S 112 Eiland, F 390 Crafts-Brandner, S.J 642 Elgersma, A 188,242 Crnobarac, J 694 Elings, A 164, 166 Crout, N.M.J 20 Ercoli, L 136, 182, 244, 246, 262, 344, Crozat, Y 326 Eric, P 152 Csajbók, J 82 Eroy, M 624 Csathó, P 236 Etchebest, S 92 Cupina, B 152 Ewert, F 168 Cyran, A 62, 64 Fabre, B 418 Czerednik, A 154 Falcimagme, R 68 Daamen, C.C 598 Fancelli, A.L 24 Dal Rio, MP 358 Fardeau, J.C 312 Dauzat, J 624 Fayet, G 530 David, C 418, 430, 586 Fedeli, A.M 100 de Barros, J.M.C 156 Feil, B 464 De Cock, L 158 Feller, U 642, 664 De Giorgio, D 234 Fereres, E 72 De Jaeger, 1 158 Fernandes, M.L.V 288, 294 DeLorenzi, F 84,670 Fernandez, J.E 544 De Ruijter, F.J 534 Fernândez-Boy, E 544 de S. Câmara, G.M 24, 90, 160 Ferri, D 232, 234, 450, 452 de Toledo, V.C 240 Filcheva, E 266 Debaeke, P 498,600 Fischer, A 256 Debreczeni, K 338, 460 Fismes, J 546 Deflune, G 536 Flotats, F.X 322 Dekkers, Th.B.M 290 Flotats Ripoll, F.X 340 Delmas, R 32 Fodor, L 706 Delphin, J.-E 462 Fornaro, F 506 Delprat, L 32, 238 Fotyma, E 548, 550 Demotes-Mainard, S 538 Fotyma, M 548,550 Denys, D 276 Fraser, AR 310 Dietrych-Szóstak, D 662 Frenda, A.S 350 Dijkstra, P 22, 60, 62, 64 Friesen, D.K 304 Dines, L.J 162 Frossard, E 304, 308, 312 Dirks, B.O.M 40 Fuhrer, J 58 Dixon, R.A 700 Füleky, Gy 292 Djukic, D 152 Furgal, K 692 722 Book of Abstracts4t h ESA-congress

Gaetani, M 610 Hristov,N 656 Gahoonia, T.S 296 Hütsch, B.W 30 Gak,E.Z 28 Huzsvai, L 108, 580 Gak,M.Z 28 Ibanez, M 80, 116 Galan, M 552,572 Ikeda, T 174 Garcia Ruiz, R 172 Iwama, K 94 Garibay, S.V 464 Jambert, C 32, 238 Gastal, F 92, 654 Janâcek, J 142, 302 Gaunt, J.L 318 Jansen, D.M 468 Gautronneau, Y 430 Jansen, M 62, 64 Gebbing, T 644,646 Jansen, M.J.H 22 Ghesquière, M 92 Janssen, B.H 282 Giardini, L 348 Jarvis, S.C 496 Gigout, M 530 Jedruszczak, M 470, 612 Ginanni, M 520, 684 Jeuffroy, M.-H 352, 538 Giorio, P 84 Jolânkai, M 556 Girard, M.L 346, 624 Jones, P 176 Girardin, P 228,414 Jouan, B 570 Giupponi, C 348 Jovanovic, 0 34, 178, 280 Glaude, E 222 Jovic,M 194 Gómez-Macpherson, H 170 Juric, 1 542,558 Gonzalez, M.A 248, 274 Justes, E 276 Gonzalez-Rodriguez, A 660 Käding,H 256 Goudriaan, J 184, 306 Kalinowska-Zdun, M 392,592 Goulding, K.WT 496 Kaneko, T 94 Grandi,S 358 Karvonen, T 96 Greco, P 450,466,482 Kaul, H.-P 354 Grevsen, K 48 Kawashima, H 94 Grichanov, 1 412 Keane, E.M 176 Gristina, L 350, 370 Keating, B.A 44, 104, 184 Groenwold, J 22,60 Kessler, J.J 620 Grossi, N 610 Kharitonov, N 708 Grub, A 58 Kilifarska, M 640 Guckert, A 546, 666 King, J.A 250 Guiducci, M 554,602 Kiniry, J.R 584 Guiking, F.C.T 468 Kiriyama, H 254 Guinchard, M.P 648 Kirkham, M.B 126 Halmajan, H.V 298, 494, 680 Kleemola, J 96 Hammer, GL 44, 104, 184 Kieps, C 98 Hansen, S 390 Klir, J 252 Harrison, R 250 Knezevic, M 542, 558 Hassink, J 220,242 Koeijer, T.J 426 Haverkort, A.J 512, 534 Kolodziej, J 472 Hay, M.J.M 300 Kosovan, S 446 Heineman, A.M 626, 628 Kovâcs, G.J 580 Heiander, CA 420 Kozmiüski, C 36 Hellebrand, H.J 256 Kren, J 560, 562, 582 Hengsdijk, H 422 Kresovic, B 208 Hensen, A 40 Kruse, M 564 Herzog, F 424 Kubât, J 220, 252 Hislop, M 630 Kudums, A 712 Hölzner, R 642 Kuida, C 254 Hoppe, G.M 630 Kujira, Y 254 Authorinde x 723

Kulig, B 566, 614 Marinova Garvanska, S 260 Kühbauch, W 646 Mariotti, M 136, 182, 244, 246, 262, 344 Kurtener, D 38 Mariscal, M.J 180 Kyriakopoulus, K 10 Marras, G 100 La Loggia, F 84 Martelo, J.M 202 Lafolie, F 356 Martignac, M 68 Lamascese, N 574 Martinez-Cob, A 80 Lange, A 568 Martorana, F 136, 182, 226 Langeveld, CA 40 Maruhnyak, A.Y 532 Langeveld, J.W.A 474 Mary, B 216, 222, 362 Lantinga, E.A 188, 428, 502 Masoni, A 246,344 Lap, D.Q 140 Matin, M.A 264 Laruccia, N 86 Matthews, K.B 416 Lascano, CE 304 Matula, J 682 Lasserre, F 570 Maurice, 1 654 Laureti, D 100 Mazurek, J 50 Leakey, R.R.B 2 Mazzoncini, M 226, 516, 520, 684 Ledent, J.F 186 McAdam, J.H 630 Lee, H.C 240, 536, 270 McCartney, H.A 540 Leenhardt, D 356 Meinke, H 44, 104, 184 Leffelaar, P.A 502 Menconi, M 46, 54, 56 Leipnitz, W 256 Mengel, K 286 Lemeur, R 158 Menini, S 520,684 Leterme, Ph 362 Mészâros, 1 580 Lewis, C 540 Meynard, J.M 336, 408, 458 Linères, M 238 Michalska, B 36 Liniewicz, K 42, 472 Michelena, A 514 Lipavskâ, H 650 Miele, S 610 Lipavsky, J 302 Miglietta, F 54 Lisova, N 552, 572 Migni, M 554 Lloveras, J 328,514 Mihailovic, V 152 Lombardo, V 370 Mikkelsen, G 478 Longobucco, A 54 Millard, P 382 Lopez, A 386 Minguez, M.I 200,512 López, E 658 Misa, P 476 Lopez-Real, J.M 270, 536 Mitchell, D.T 604 Losavio, N 574 Mitchell, R.D.J 250, 360 Lötscher, M 300 Mitova, T 266 Lott, J.E 632 Mladenov,N 110,656 Ludva, L 302 Mladenovic, G 194 Lustrini, L 670 Moirón, C 658 MacGillivray, C.W 18 Moreno, F 544 Maciorowski, R 652 Moriondo, M 54 Madry, W 392, 592 Morvan, T 362 Magliulo, V 84, 670 Mosquera-Losada, R 660 Maiorana, M 576 Mouraux, D 186 Maja, C 230 Muhr, L 500 Malesevic, M 110, 230, 696 Mulholland, B.J 168 Mallo, F 386 Murillo, J.M 544 Mambelli, S 358 Nâdasy, E 578 Manzi, G 466 Nagy, J 122, 580 Marchetti, R 102, 258, 342, 454, 492 Najmanova, J 384 Marinkovic, B 694 Nakeseko, K 94 724 Book of Abstracts4t h ESA-congress

Nalborczyk, E 154 Pitacco, A 670 Nassiri, M 188 Podolska, G 50, 652 Nâtr, L 650 Pogorecky, A 572 Navari-Izzo, F 46 Poma, 1 350,370 Neeteson, J.J 216 Popa, G 190 Neudert, L 582 Popovic, T 34 Neumann, R 8 Porceddu, E 6 Newman, S.H 634 Porta, J 322 Nicolardot, B 222, 276 Porter, J.R 18, 168 Nielsen, N.E 296 Posca, G 608 Nijland, G.0 596 Poulik, Z 590 Nocquet, J 430 Pozdnyakov, V.A 712 Norton, G 540 Pritoni, G 198 Nwalozie, M.C 74, 106, 118 Prodanovic, S 194, 656 Oberson, A 304 Promayon, F 586 Odinga, J.J 268 Przulj.N 110,656,696 Olesen, J.E 48 Pucaric, A 486 Ong, CK 632 Puech, J 112 Onofri, A 602 Putaric, V 52 Onuphrieva, 1 708 Rabbinge, R 6, 44, 104, 428, 436 Orgaz, F 130, 132, 134, 180 Ragab, A.Y.R 140 Osborne, B.A 176, 604 Ragasits, 1 332 Otegui, M.E 190 Rapini, R 492 Overbosch, G.B 474 Raschi, A 46, 54, 56 Paasonen-Kivekäs, M 96 Reau, R 336,588 Pâlinkâs, 1 698 Recous, S 352 Pantone, D.J 584 Richard, G 488 Papini, R 342 Richner, W 410 Pardini, G 610 Richter, G.M 366, 490 Park, J 634 Richter, J 490 Pashova, V 708 Richter, 0 366 Patyka,V. 572 Richter, R 590 Paveley, N.D 522 Ridao, E 200 Pavlikova, D 384, 710, 714 Riedo, M 58 Pavlyshyn, M.M 212 Rigueiro, A 658 Pawlowska, J 662 Rikanovâ, J 590 Paz, A 248,274 Rinaldi, M 452, 506 Pechovâ, M 142 Rivoal, R 570 Pecio, A 192,652 , 662 Rizzo, V 232, 234, 452, 506 Perez, P 116 Robin, Ch 648 Perez, P.J 80 Rodriguez, D 306 Perovic, D 194 Rodrigues, M.A.R 368 Peters, M 500 Rodrigues, M.S 270 Petö, K 108,480 Rokhinson, E.E 114 Pfarrer, R 664 Roostalu, H 66 Pietkiewicz, S 154 Rosell, J.1 80, 116 Pilbeam, C.J 364,598 Rosset, M 58 Pinochet, X 326 Rossing, W.A.H 408 Pinto, P.A 148, 196 Roy-Macauley, H 74, 106, 118 Pinxterhuis, J.B 268 Rozbicki, J 392,592 Piro, F 482 Rubaek, G.H 308 Pisulewska, E 692 Ruiz-Nogueira, B 202, 204 Pisulewska, E.K 484 Ruzicka, M 302 Author index 725

Ryan, J 364 Stamp, P 410 Sâinz, M.J 524 Stankowski, S 62, 64, 652 Sail, M 118 Starcevic, Lj 230, 696 Sancarlo, F 684 Stefan, V 494, 680 Sanchez, P 2 Stefanescu, D 298 Santoalla, M.C 386 Stockdale, E.A 496,318 Sârdi,K 272 Stockle, C.0 388, 498, 600 Sarno, R 350,370 Stojsic, M 120 Sau, F 202, 204 Streiff, K 666 Savulescu, I 494,680 Struik, P.C 444 Sayre, K.D 510, 594 Svendsen, H 390 Sbaï, A 372 Sylvester-Bradley, R 162 Scalabrelli, G 610 Szabó, L 686, 688 Scarpa, G.M 100 Szakova, J 704, 710, 714 Schapendonk, A.H.C.M 22, 60 Szalai, T 556 Scherer, H.W 374, 568 Szentpétery, Z 556 Schjönnig, P 390 Szundy, T 314 Schneiders, M 374 Taboada, M.T 248, 274 Schnyder, H 644, 646 Tabourel-Tayot, F 206 Schouls, J 596 Tamâs, J 122, 580 Schultze-Kraft, R 500 Tamm, T 66 Schvartz, Ch 372 Tarawali, G 500 Sciazko, D 62,64 Tarawali, S.A 500 Scofield, A.M 536 Tei, F 602 Scott, R.K 162 Teira,M.R 322 Seddig, S 76 Teittinen, M 96 Segers, R 40 Teklehaimanot, Z 630 Serça, D 32 Thornton, B 382 Serio, F 574 Thorup-Kristensen, K 606 Setatou, H.B 376, 378, 380 Tiessen, H 304 Sewalt, VJ.H 700 Tischner, T 314 Sgherri, C.L.M 46 Tlustos, P 384, 704, 714 Shand, CA 310 Tolimir, M 208 Shopski, N 88 Triboi, A.M 68, 434 Sibbald, A.R 416,630 Triboi, E 68,434 Sibbesen, E 308 Trinsoutrot, 1 276 Silvestri, N 226,520 Tsadilas, CD 124 Simünek, P 536 Ulasik, S 62, 64 Simmonds, L.P 598 Ungurean, L 680 Simonis, A.D 376, 378, 380 Vago, D 298 Sinaj, S 308, 312 Valentine, A.J 604 Sisak, 1 272 Valgus, T 66 Skoric, M 120 van Dam, A.M 502 Smith, J.W 500 van de Geijn, S.C 18,22 , 60, 62, 64 Smith, S 310 van den Boogaard, R 606 Smolyar, E.1 28 van den Pol-van Dasselaar, A 40 Solcan, E 298 van der Putten, P.E.L 608 Soldati, A 410 van der Werf, H.M.G 716 Somers, B.M 432 van der Werff, P.A 290 Sousa, J.R 288 vanderWilk, C 594 Sovero, M 144 van Dijk, G 10 Spallacci, P 102, 258, 342, 454, 492 van Evert, F.K 504 Spasova, D 34 van Ittersum, M.K 422, 436 726 Book of Abstracts 4th ESA-congress van Keulen, H 44, 104, 278 Zimmer, C 716 van Noordwijk, M 636 Zugec, 1 558 Vandiepenbeeck, M 186 Zvereva, T.S 676 Vanek, V 384, 704, 710 Vanhoutvin, S 168 Varga, B 486 Vasic, G 26,208 Veerman, C 10 Végh, K.R 236,314 Veithof, G.L 40 Ventrella, D 506, 576 Venturi, G 198, 358 Vereijken, P 404 Veskovic, M 178, 280 Vidal, M 386 Videnovic, Z 26 Villalobos, F.J 130, 132, 134, 170, 172, 180, 210 Villar, J.M 80, 116, 388 Villar, P 116, 388 Villarino, J 658 Villette, C 530 Vintner, F.P 390 Voijslava, M 110 Volterrani, M 610 von Fragstein, P 438 Vonella, A.V 574 Vong, P.C 546 Vos, J 318, 502, 608 Vuckovic, S 194, 656 Wagner, D 588 Walker, K 540 Walker, K.C 144 Watt, T.A 240 Webb, J 250,360 Werner, A 256 Wesolowski, M 470, 612 White, J 166 Whytock, G.P 144 Wijnands, F.G 440 Witkowicz, R 484 Wolfert, J 502 Wood, M 364 Wossink, G.A.A 426 Wozniak, A 508 Wyszynski, Z 392, 592 Yan, Y 656 Yang, H.S 282 Zajac, T 484 Zayats, O.M 212 Zebrowski, J 154 Zelinschi, B 298 Zhang, J 126 Ziólek, W 566,614 Subject index 728 Book of Abstracts 4th ESA-congress

Subject index abiotic stress 142 carbon dioxide 22, 40, 46, 54, 56 absorption 362 60,64,222 acid savannas 304 carbon-partitioning 206 advection 80 castor 100 agricultural development 6 catch crop 334, 466, 502, 482 agricultural production systems 436, 620 cauliflower 48, 606 agricultural soils 248, 274, 366, 688 cereals 296, 562, 590, 692 agro-ecosystems 220 CERES-barley model 66 agro-ecological indicator 228, 414 CERES-rice model 148, 196 agro-ecological zones 14 CERES-sorghum model 452 agroforestry 424, 618, 620, 622, 630 CERES-wheat model 450 632, 634, 636 chilling 648 air humidity 640 chlorophyll 642 air temperature 42 Cinderella trees 2 alternative crops 574 climate 18,52,356 alfalfa 46 climate change 18, 22, 58 alien cytoplasm 176 cocklebur 584 allelopathy 536 coconut based farming system 624 alley cropping 626, 628 coenosys 556 Alopecurus myusuroides 528 composting 256, 270 alternative land use 424 computer modelling 122, 624 amaranth 564 conductometric transducer 674 ammonia volatization 474 continuous cropping 178 anatomy 654 copper deficiencies 526 arable farming 512 cotton 124,518 arbuscular mycorrhizal fungi 290 cover crop 334, 370, 464 aridity index 52 cowpea 74, 106 aspargus 524 crop growth 18,336,490 associative diazotrophs 572 crop growth analysis 140, 606 atmospheric precipitation 42 crop growth chamber 68 atrazine 462 crop growth enhancement 22 crop growth model 14, 108, 156, 186, 206 bambara groundnut 150 388,480,502 barley 66, 386, 714 cropjuvenilit y 160 bio-dynamic 536 crop management 582 biological recultivation 260 crop modelling 96, 202 Bradyrhizobium japonicum 326 crop protection 8 Brassica napus 276 crop residues 216, 250, 360 bread wheat 514, 594 crop rotations 82, 178, 232, 266, 428 breeding 166 434, 444, 466, 470, 482 broom-rape 172 crop species 136 buckwheat 192, 564, 652, 662 crop water consumption 98 bulk density 264 crop-livestock systems 500 buried seed 144 cropping system 444, 454, 458, 476, 486 504,506 cadmium 710, 714 CropSyst 342,498 calcium sulfate 254 cultivar mixture 494 canopy model 50 cumulative ryegrass Puptak e 292 canopy resistance 84 cytoplasm 176 canopy structure 146, 154, 188 carbohydrate 648 dairy manure compost 240 Subject index 729 dairy rotational systems 660 food quality 536 decision aid tool 228, 414 forage 692 decision rules 112 forage systems 500 decision support system 416 forecasting 20 decomposition 222, 276 forest soil 248 defoliation 382,606 fungicides 522 denitrification 238, 390 furrow-irrigated 510 detoxication 708 fuzzy logic 716 development 6, 150, 170 dimetipin 662 gas exchange 68 disease resistance 594 gaseous nitrogen losses 338 drainage 96 gene flow 458 drainage system 88 genetic engineering 700 drought 120, 164, 524 genetic inputs 148 drought adaption mechanism 74 genotypicvariatio n 300 drought duration 34 germination 118, 686, 694 drought resistance 118 gliadin 656 drought stress 76 global warming 38 drought tolerance 94 grain development 656 dry matter 392,574 grain filling 644, 646 drymatte r partitioning 156 grain nitrogen content 346 dryland 632 grain protein 696 durum wheat 350,450,466,514 grain quality 62, 64, 110 dynamic optimization 318 grain yield 194 grapevine 54 early vigour 132, 134 grass cover 610 earthworms 684 grassland 268,658 ecological 144, 420 grassland ecosystem 58 ecological cultivation 524, 562 greenbul k 212 ecological systems 478 green leaf area 522 ecophysiology 130 green pea 578 ecosystem 28 greenhouse effect 30 efficiency 426 ground cover 472 electrothermal device 640 ground water reserve 472 emission 32 groundnut 118 emission of gasses 256 groundwater 348 energy balance 84,476,562, 582 environmental impact 14,430 , 716 Henin-Dupuis model 226 EPIC 446 halophytes 158 eternal frozen soil 38 heat flux density in soil 674 Europe 6 heating 380 évapotranspiration 80 heavy metals 686, 706, 708, 710, 712, 714 extractable organic N 324 herbicides 556 eyespot 456 Heterodera avenae 570 horse bean 566 farming systems 228, 404, 408, 414, 420 humic substances 224 farmyard manure 384, 710 humus 230 fatty acids 540 hypocotyl 134 fertilization 82, 280, 352, 372, 434 532, 580, 614 I-WHEAT 44 fertilizers application technologies 590 immobilization 362 Festuca rubra 382 improved pastures 304 finite elements method 116 invitr o cultures 650 730 Book of Abstracts 4th ESA-congress inbred maize lines 542 26, 544, 580, 698, 704 »identification index 182 maize genotypes 314 indirect selection criteria 76 malting barley 110, 696 infiltration 264 malting quality 110 informatie programme 98 manure 386 infrared spectroscopy 310 manuring methods 612 inoculation 320 maturity 694 inorganic fertilisers 628 meiosis 666 input-output combinations 426, 436 methane 32, 40 integrated crop protection 440 methane evolution 254 integrated farming 440 methane oxidation 30 integrated management 570 methods 86,658 integrated systems 478 micro-elements 614 intensive and low input management 592 microbial activity indexes 258 interactive development of sustainable farming microbial biomass 372 systems 432 micrometeorology 670 intercropping 484 mineral nitrogen 384 intraplant competition 560 mineralizable nitrogen 384 irrigated maize 328 mineralization 250, 318, 350, 354, 360 irrigation 100, 122, 356, 518, 580 364,370,380 irrigation water 114 minirhizotron 410 Mitscherlich equation 236 Kenya 626 mixed fanning 428 kernel number 538 modelling 44, 48, 58, 72, 166, 192, 226 kernel set 190 278, 282, 346, 338, 390, 408 456, 458, 446, 490, 600 land use 618,630 modular growth 560 land use allocation 416 mole drainage 88 land use technology 422 molecular mass distribution 332 leaching 114,344,496,544 morphogenesis 648 leaf 654 mRNA 642 leaf area index 542 mulch 468 leaf emergence 168 mutants 212 leaf expansion 608 mycorrhizal infection 604 leaf growth 92 leaf photosynthesis 554 NAR 152 learning processes 432 new modes of action 8 legumes 484, 568 nintrification inhibitor 546 light absorption 554 nitrate 340, 348, 370, 462, 544, 578 light interception 162, 184 nitrate leaching 322, 356 lignin 700 nitrate reductase activity 358 linear programming 408 nitrate-N 696 Lolium multiflorum L 410 nitrification rate 378 Lolium perenne L 60, 382 nitrogen 104, 164, 182, 244, 246 long-term experiments 196, 230, 278, 308 250, 262, 270, 318, 340 long-term fertilization 460 344, 352, 354, 360, 380 lucerne 492 428, 486, 496, 502, 538 572,578,664 magnetic field 114 nitrogen availability 372 maize 26, 84, 122, 124, 140, 164 nitrogen balance 386, 492 178, 186, 208, 236, 238 nitrogen compounds 32 240, 246, 280, 330, 376 nitrogen critical concentration 602 460, 464, 486, 516, 520 nitrogen deficiency 336, 528 Subject index 731 nitrogen dynamics 252 phenology 198,202 nitrogen economy 564 phenylpropanoid biosynthesis 700 nitrogen fertilization 30, 332, 338, 368, 514 phosphate 286,290 518, 548, 550, 566, 588, 704 phosphate availability 292, 308, 312 nitrogen fixation 568 phosphorus 244, 262, 296, 306, 310, 530 nitrogen fixing bacteria 320 phosphorus distribution 300 nitrogen losses 474 phosphorus test 288,294 nitrogen mineralization 216, 240, 324 photoperiod 150 nitrogen nutrition 298, 586, 650 photoperiodism 160 nitrogen recovery 334, 376 photosynthesis 126, 158, 176, 516, 604, 608 nitrogen requirements 490, 600 photosynthetically active radiation 190, 210 nitrogen supply 468 phyllotaxis 174 nitrogen uptake 392 phytic acid 298 nitrogen use efficiency 368, 512 phytotoxic 706 nitrous oxide 40 pig slurry 322,340,342 nodulation 326, 470, 680 Piracicaba 24 nodule structure 680 plant ecosystem 28 nonexchangeable NHt+ 374 plant canopy analyzer 210 nutrient accumulation 272 plant community composition 676 nutrient availability 288, 294, 302 plant densities 138 nutrient balance 444, 454 plant growth analysis 652 nutrient contents 274 plant morphology 146 nutrient dynamics 242 plant nitrate test 330 nutrient use efficiency 314, 474, 626, 628 plant pathogen 712 nutrient utilisation 142 plant protection 508 nutrients 248, 534, 596 plant residues 222,276 nutrients dynamics 322 planting date 204 planting systems 138 object-orientation 504 pod yield 106 oilseed rape 336, 540 policy 2 olive orchard 180 poplar 634 on-farm research 418 population dynamics 570 onion 78 potassium 530,682 open top chamber 62 potato 76,94,534,608 optimal input 596 potato cyst nematodes 534 organic amendments 246 potential yield 186, 196 organic carbon 238 precipitation 26, 42, 120 organic farming 418, 430, 438, 586 production estimation 658, 660 organic farming system 290 protein content 484 organic fertilization 350, 368 prototyping farming systems 404 organic manuring 282 organic matter 220, 224, 266, 310 radiation interception 200, 210 organic soilP 304 radiation model 180, 624 oriental tobacco 482 radiation use efficiency 48, 306, 574 osmotic potential 126 rain intensity 102 rainfall 24 particle-size fractions 312 rape 56, 546 peanut 74 ratio N/S 546 peas 152,614 redox potential 374 perennial grass 206 reduced tillage 510 permanent fallow 366 relative growth rate 602 pesticides 440, 716 residual nitrate 328 pH 704 residue 596 732 Book of Abstracts 4th ESA-congress resource capture 636 soil volume 262 resource use 560 soil water 390 Rhizobium strains 552 soil water content 82 rice 254 soil water deficit 516 riskbenefi t 8 soil water depletion 106 root density 264 soil water potential 94 root distribution 78, 410 soils 258, 260, 288, 302, 308 root growth model 78 312, 364, 448, 634, 682 root mass 256 686,688 root system 142 solar radiation 154 rotational fallow 366 sorghum 126,452 roughness parameter 670 sowing rates 532 row orientation 208 sowing term 50 runoff 102 soybean 174, 202, 204, 298, 326 ryegrass 188, 242 470,584,680 spatial distribution 36 Sahel 620 spectral component analysis 200 salinity 158 spectral properties 136, 182 saturated conductivity 102 spring barley 532, 548 seed quality 540 spring wheat 168, 194 seedyiel d 192,662 stability 194,676 senescence 642, 664 stochastic simulation 24 sensitivity analysis 148 stockless systems 438 silage 692 stored soil water 90 silvopastoral system 618, 630 subsurface irrigation 96, 244 simulation 28, 108, 354, 388, 480 SUCROS 20 504, 584, 622 sugarbeet 358,392,612 simulation model 130, 132, 172 sugarbeet roots 678 Slovakia 446 sulphur 568 sludge 260 sunflower 130, 132, 134, 156, 172 slurry 362 670,694 soil analysis 530 sustainability 278, 422, 434 soil C and N 232,234 sustainable farming system 448 soil conservation 464 sustainable pest management 412 soil drying-rewetting 324 sustainable production techniques 426 soil evaporation 598 sweet pepper 138, 602 soil fertility 230, 232, 252 synchronization 468 soil fertility replenishment 2 soil management 348 tall fescue 654 soil microclimate 38 technogenic influence 52 soil moisture 36, 488, 576 temperature 378 soil nitrate 328, 342, 492 thermal conductivities 640 soil nitrogen 330 thermoelectric transducer 674 soil organic matter 216, 226, 280, 282, 622 thermoperiodism 160 soil parameters estimate 86 tillage 520,684 soil phosphate 268, 286 tobacco 554 soil physical properties 224 toxic elements 706 soil properties 272 trace element 688 soil solution 462 transgenic rapeseed 144 soil strength 576 transpiration 598 soil temperature 168 trend analysis 302 soil testing 268 tropical maize 166 soiltillag e 234, 488, 558 tundra soils 676 Subject index 733

underplant crops 508 zinc deficiencies 526 upland farming systems 416 validation 196 variability 274 variety 152 vineyard 610 volcanic soils 294 wastewater 124 water balance 68,90, 116,548,550 water deficit 34, 92, 666 water infiltration model 116 water infiltration rate 576 water limitation 72 water management 112, 498 water potential 92 water relations 46, 54, 56 water soluble carbon 258 water use 506 water use efficiency 314,506,512, 598 water-soluble carbohydrates 644, 646 waterlogged soils 88 waterlogging 664 weed control 542 weed level 558 weed species 136 weed tolerance 556 weeds 520 West Africa 500 Western Europe 424 wetland rice 374 wheat 20,44, 104, 146, 170 176, 184, 270, 306, 346 352,364,494,510,538 644, 646, 656, 666, 684 wheat competition 528 wheat flour proteins 332 white clover 188, 242, 300 winter barley 212 winter hairy vetch 552 winter oilseed rape 198, 588 winter triticale 154,508, 592 winter wheat 50, 62, 64, 162, 236 344, 456, 460, 550, 558 582,586 workability 488 xFestulolium 712 yield 26, 174, 198,204,208,522 552, 566, 572, 594, 612 734 Book of Abstracts 4th ESA-congress

List of national representatives

Albania Sulejman Sulce Tel: +355 42 25500 Fax: not known

Belgium J.-F. Ledent Tel: +32 10 473458 Fax: +32 10 473455

Cyprus I. Papastylianou Tel: +357 2 305101 Fax: +357 2 316770

Czech Republic J. Kubat Tel: +42 2 360851 Fax: 42 2 365228

Denmark N.E. Nielsen Tel: +45 32283496 Fax: +45 35283460

Finland Païvi Nykänen-Kurki Tel: +358 55 230028 Fax: +358 55 178628

France A. Guckert Tel: +33 83 595837 Fax: +33 83 595804

Germany W. Aufhammer Tel: +49 7114592386 Fax: +49 7114592297

Greece A. Simonis Tel: +30 31471280 Fax: +30 31471280

Hungary G. Fuleky Tel: +36 28 330737 Fax: +36 28 310804

Ireland T. Storey Tel: +353 1 2693244 Fax: +353 1 2837328

Italy G. Zerbi Tel: +39 432 558618 Fax: +39 432 558603 National Representatives 735

The Netherlands S.C. van de Geijn Tel: +31317 475850 Fax: +31317 423110

Poland M. Fotyma Tel: +48 81 863421 Fax: +48 81864547

Portugal P.J.C. AguiarPint o Tel: +351 1 3637970 Fax: +351 1 3637970

Slovak Republic J. Vidovic Tel: +42 838 22311 Fax: +42 838 26306

Slovenia F.Bave c Tel: +386 6222661 1 Fax: +386 622336 3

Spain M. InesMingue z Tel: +34 15491122 Fax: +34 1544998 3

Switzerland A. Soldati Tel: +4152 339120 Fax: +41 5233270 6

U.K. G.Rüsse l Tel: +44 316671041 Fax: +44 316672601

North America M.J.Gos s Tel: +1519824412 0 Fax: +1519824573 0 736 Booko fAbstract s4t h ESA-congress

ESA Executive Committee

President: Dr. Hubert Spiertz Research Institute forAgrobiolog y andSoi lFertilit y (AB-DLO) P.O. Box 14 NL-6700 AAWageninge n THE NETHERLANDS Fax: +31 31742311 0

Secretary: Dr.Philipp e Girardin INRA,Laboratoir ed'Agronomi e P.O.Bo x 52 68001Colma rCede x FRANCE Fax:+3 3 897 24 9 33

President Elect: Prof. MiroslavZim a Department ofPlan t Physiology Faculty ofAgronom y University ofAgricultur e Nitra SLOVAK REPUBLIC Fax: +42 8751159 3

Past president: Prof. L.Giardin i Istituto diAgronomi a generale ecoltivazion i erbacee Universistà diPadova , viaGradenig o6 35131 Padova ITALY Fax: +9 49807085 0