EDITORIAL BOARD Editor-in-Chief : T. Urushadze Agricultural University of Georgia, Tbilisi, Georgia Associate Editor: H. Hidaka Meisei University, Tokyo, Japan Co-editors:
A. Babayev O. Nagorniuk D. Petrosyan Azerbaijan State Agrarian University, Ganja, Institute of Agroecology and Environment National Agrarian University of Armenia, Republic of Azerbaijan Management Kyiv, Ukraine Yerevan, Republic of Armenia J. Dorner A. Ploeger Austral University of Chile, Valdivia, Chile University of Kasel, Kasel, Germany Executive Secretary: I. Pipia Agricultural University of Georgia, Tbilisi, Georgia Editorial Board Members:
V. Abrahamyan M. Gerzabek A. Mohammad National Agrarian University of Armenia, Yerevan, University of Natural Resources and Life Sciences, Aligarh Muslim University, Aligarh, India Republic of Armenia Vienna, Austria L. Montanarella R. Agabeyli T. Gokturk European Commission, Ispra, Italy Institute of Botany, Azerbaijan National Academy Artvin Coruh University, Artvin, Turkey A. Otte of Sciences, Baku, Republic of Azerbaijan R. Gracheva Justus-Liebig-University, Giessen, Germany U. Alekperov Institute of Geography, Moscow, Russia C. Quezada Academy of Public Administration under the I. Ibatullin Universidad de Concepcion-Chile, Chillan, Chile President of the Republic of Azerbaijan, Baku, National University of Life and Environment T. Sadunishvili Republic of Azerbaijan Sciences of Ukraine, Kyiv, Ukraine Agricultural University of Georgia, T. Altan G. Japoshvili Tbilisi, Georgia Cukurova University, Adana, Turkey Agricultural University of Georgia, Tbilisi, Georgia P. Schmidt M. Babayev G. Javakhishvili Dresden University of Technology, Institute of Science and Agrochemistry of ANAS, Georgian Technical University, Tbilisi, Georgia Dresden, Germany Baku, Republic of Azerbaijan N. Karkashadze N. Senesi V. Babayev Academy of Agricultural Sciences, Tbilisi, Georgia University of Bari, Bari, Italy Ganja Agribusiness Association, Ganja, A. Korakhashvili K. Stahr Republic of Azerbaijan Agricultural University of Georgia, Tbilisi, Georgia University of Hohenheim, J. Bech V. Kuznetsov Stuttgart, Germany Universitat de Barcelona, Barcelona, Spain Russian Academy of Sciences, Moscow, Russia W. Stepniewski R. Beglaryan G. Kvesitadze Lublin University of Technology, Lublin, Poland National Agrarian University of Armenia, Yerevan, Georgian National Academy of Sciences, A. Tarverdyan Republic of Armenia Agricultural University of Georgia, National Agrarian University of Armenia, Yerevan, W. Blum Tbilisi, Georgia Republic of Armenia University of Natural Resources and Life Sciences, W. Lawrence L. Vasa Vienna, Austria Organic Research Centre, Hamstead Marshall, UK Institute for Foreign Affairs and Trade, A. Didebulidze N. Makarenko Budapest, Hungary Agricultural University of Georgia, Tbilisi, Georgia National University of Life and Environment Y. Vodyanitskii P. Dlapa Sciences of Ukraine, Kyiv, Ukraine Lomonosov Moscow State University, Comenius University in Bratislava, Slovakia G. Mammadov Moscow, Russia K. H. Erdmann Baku State University, Baku, Republic H. Vogtmann Federal Agency for Nature Conservation of of Azerbaijan University of Kassel, Kassel, Germany Germany, Bonn, Germany Y. Marmaryan A. Voskanyan P. Felix-Henningsen National Agrarian University of Armenia, Yerevan, National Agrarian University of Armenia, Justus-Liebig University, Giessen, Germany Republic of Armenia Yerevan, Republic of Armenia O. Furdychko A. Melikyan V. Yavruyan Institute of Agroecology and Environment National Agrarian University of Armenia, Yerevan, National Agrarian University of Armenia, Yerevan, Management Kyiv, Ukraine Republic of Armenia Republic of Armenia Annals of Agrarian Science
Volume 1, Number , ,WPG Aims and Scope
The aim of “Annals of Agrarian Science” is to overview problems of the following main disciplines and subjects: Agricultural and Biological Sciences, Biochemistry, Genetics and Molecular Biology, Engineering, Environmental Science. The Journal will publish research papers, review articles, book reviews and conference reports for the above mentioned subjects.
ANNALS OF AGRARIAN SCIENCE
Volume 17, Number 2 June 2019
CONTENTS Blue-green Alga Spirulina as a Tool Against Water pollution by 1,1'-(2,2,2-Trichloroethane-1,1-diyl)bis(4-chlorobenzene) (DDT) M. Kurashvili, T. Varazi, G. Khatisashvili, G. Gigolashvili, G. Adamia, M. Pruidze, M. Gordeziani, L. Chokheli, S. Japharashvili, N. Khuskivadze ...... 153
Quality assessment of the aquatic habitat of mountain streams in the period of minimal flow using the ichthyofauna as a bioindicator Z. Štefunková, V. Macura, I. Kondé ...... 158
Spatial and time dynamics of glaciers following the Little Ice Age on the southern slope of the Greater Caucasus D. Svanadze, V. Trapaidze, G. Bregvadze, I. Megrelidze ...... 166
Neonicotinoids against sucking pests on winter wheat stands in the Forest-Steppe Zone of Ukraine F. Melnichuk, L. Melnichuk, S. Alekseeva, M. Retman, O. Hordiienko ...... 175
Determination of the ratio hematite/goethite by soil color Yu.N. Vodyanitskii ...... 180
Ecological Assessment of Pastures of Eastern Georgia (Kakheti) M. Merabishvili ...... 188
Investigation of Simultaneous Occurrence Probabilities of Some Dangerous and Spontaneous Meteorological Phenomena for Various Physical and Geographical Conditions of Georgia Using Multiplication and Addition Theorems of Probabilities E. Elizbarashvili, M. Elizbarashvili, M. Tatishvili, Sh. Elizbarashvili, N. Chelidze ...... 197
Issue of organization of material logistics of work of agricultural machinery in complex mountain-level land conditions B.B. Basilashvili , I.M. Lagvilava, Z.K. Makharoblidze, R.M. Khazhomia ...... 204 Modeling of technological process in rotary tiller D.R. Khazhakyan ...... 208
Introduced Holstein Breed Livestock in Georgia T. Qachashvili, L. Tortladze, A. Chkuaseli ...... 212
Heavy metals specific proteomic responses of a highly resistant rthrobacter globiformis 151B O. Rcheulishvili, L. Tsverava, A. Rcheulishvili, M. Gurielidze, R. Solomonia, N. Metreveli, N. Jojua, H-Y Holman ...... 218
Application of potassium-rich processed dactte tuff as a fertilizer of slow and long-lasting effect S.K. Yeritsyan, M.V. Gevorgyan...... 230
Analysis of the impact of the main factors affecting the pattern of tire depreciation P.A. Tonapetyan, A.G. Avagyan ...... 236
Structural and Magnetic Properties of Silver Oleic Acid Multifunctional Nanohybrids S. Khutsishvili, P. Toidze, M. Donadze, M. Gabrichidze, T. Agladze, N. Makhaldiani ...... 242
Prevalence of Bovine Tuberculosis and Its Risk Factors in Georgia L. Tsitskishvili, T. Kurashvili, L. Makaradze, I. Baratashvili, G. Samadashvili, G. Glunchadze, L. Bartaia, Z. Samadashvili ...... 251
Peculiarities of soils of high mountain (on Khevi example – on the Central Great Caucasus) K. Gogidze ...... 258
Sustaining paddy production through improved agronomic practices in the Gangetic alluvial zone of West Bengal P. Haldar, A. Sarkar, M. Roy, K. Chowdhury ...... 266
On the approach to the complex research into the vibratory technological process and some factors having an influence on the process regularity V. Zviadauri ...... 277
M. Kurashvili et al. Annals of Agrarian Science 17 (2019) 153 – 157
Annals of Agrarian Science
:ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ
Application of Blue-green Alga Spirulina for removing Caesium ions from polluted water
M. Kurashvili*, G. Adamia, T. Varazi, G. Khatisashvili, G. Gigolashvili, M. Pruidze, L. Chokheli, S. Japharashvili
Durmishidze Institute of Biochemistry and Biotechnology of Agricultural University of Georgia, 240, David Agmashenebeli, Alley, Tbilisi, 0159, Georgia;
Received: 23 October 2018; accepted: 12 December 2018
A B S T R A C T
7KHSUHVHQWHGZRUNFRQFHUQVဧXG\LQJDSRVVLELOLW\RIXVLQJEOXHJUHHQDOJD F\DQREDFWHULD 6SLUXOLQD Spirulina platensis) for removal of Caesium ions form polluted waters. For this aim, tolerance of alga to Cs+LRQVLQSDUWLFXODULQÀXHQFHRIGL൵HUHQWFRQFHQWUDWLRQVRI KHDY\PHWDORQXOWUDဧUXFWXUHRI6SLUXOLQDFHOOVDVZHOODVRQELRPDVVSURGXFWLRQE\6SLUXOLQDDQGFKORURSK\OODFFXPXODWLRQLQDOJD FHOOVKDYHEHHQဧXGLHG$FFRUGLQJWRREWDLQHGGDWDWKHKLJKHဧFRQFHQWUDWLRQRI&V+ SSP EORFNHGELRPDVVIRUPDWLRQRQO\E\ DQGWKHFRQWHQWRIFKORURSK\OOGHFUHDVHGE\7KLVFRQFHQWUDWLRQRIKHDY\PHWDOFDXVHGRQO\DQLQFUHDVHRIK\GURFDUERQV containing space between lamella in Spirulina cells, which can be a result of accumulation of Cs+ ions in alga cells. Thus, 100 ppm concentration of Cs+ LRQVKDVEHHQFKRVHQIRUWHဧLQJSRVVLELOLW\RIXVLQJ6SLUXOLQDWRFOHDQDUWL¿FLDOO\SROOXWHGZDWHULQWKHPRGHO ODUJHVFDOHH[SHULPHQW7KHREWDLQHGGDWDKDYHVKRZQWKDW6SLUXOLQDKDVFDSDELOLW\WRDVVLPLODWHXSWR RI&V+ ions from polluted water during 15 days. These results indicate that Spirulina is potentially useful for cleaning waters polluted with nonradioactive Cs+ ions as well as with 137Cs+ ions.
Keywords: Phytoremediation, Spirulina platensis, Water pollution, Heavy metals, Caesium ions, Radioactive and Stable Cesium.
&RUUHVSRQGLQJDXWKRU 0DULWFD.XUDVKYLOL(PDLODGGUHVV [email protected]
1. Introduction SROOXWHG E\ GL൵HUHQW WR[LF FRPSRXQGV6SLUXOLQD has unique chemical content and biological 1RZDGD\V ZDWHU SROOXWLRQ E\ GL൵HUHQW SURSHUWLHV7KLVEOXHJUHHQDOJDLVFKDUDFWHUL]HGE\ chemicals especially by hazardous heavy metals and UHSURGXFWLRQDQGIDဧELRPDVVIRUPDWLRQLQH[WUHPH UDGLRQXFOLGHVLVRQHRIWKHPRဧLPSRUWDQWHFRORJLFDO conditions. Spirulina cells have rich content of 137 problem. Among them Cs is very dangerous. proteins and peptides, and these compounds should Nonradioactive Caesium ions that occur in nature be chelating ions of heavy metals. During the aging, and are released into environment through mining WKH YDFXROHV RI 6SLUXOLQD FHOOV LQÀDWH ZLWK DLU DQGPLOOLQJRIRUHVDUHRQO\PLOGO\WR[LF>@%RWK EXEEOHVDQGDVDUHVXOW6SLUXOLQDFRORQLHVÀRDWRQWR UDGLRDFWLYH DQG ဧDEOH FHVLXP ZKHQ WKH\ RFFXU LQ the water surface. As a result, Spirulina biomass KXPDQ RU DQLPDO ERG\ DFW WKH VDPH ZD\ >@ ZLOOEHHDVLO\ PHFKDQLFDOO\ VHSDUDWHGIURPFOHDUHG Presented work devotes to elaboration of water body after remediation. These factors have + method for cleaning water contaminated with Cs DWWUDFWHG RXU LQWHUHဧ LQ 6SLUXOLQD DV WR SRWHQWLDO LRQVE\XVLQJEOXHJUHHQDOJD6SLUXOLQD Spirulina phytoremediator agent. It is known the information platensis). 6SLUXOLQD Spirulina platensis VKRXOG about using of algae for cleaning the environment have prospects for phytoremediation of waters SROOXWHG ZLWK VXFK WR[LFDQWV DV KHDY\ PHWDOV > M. Kurashvili et al. Annals of Agrarian Science 17 (2019) 153 – 157
@ UDGLRDFWLYH HOHPHQWV > @ ÀXRULGH LRQV >@ ÀDPH HPLVVLRQ DQDO\VLV >13@ Conditions for and others. There is only limited data concerning DQDO\VLVDUHWKHIROORZLQJ ,QဧUXPHQW±3HUNLQ(OPHU using Spirulina as a phytoremediator agent in case HGA900 Graphite Furnace; wavelength – 852.1 of water pollution with Cs+ ions, but for this aim, QP VOLW±QP ÀDPH±DLUDFHW\OHQH ဧRFN Spirulina seems to have prospects, because there ဧDQGDUG VROXWLRQ ± &(6,80 PJ/ OLJKW is a lot of information about heavy metals uptake source – EDL; interfence – ionization controlled by SURFHVVHV E\ 6SLUXOLQD >5@ addition of 0.1% KCl. In presented work, potential of Spirulina 7R ဧXG\ WKH LQÀXHQFH RI &V+ ions on cell to uptake of Cs+ ions from water solutions has XOWUDဧUXFWXUH ELRPDVV RI 6SLUXOLQD ZDV ¿[HG LQ been evaluated. For this aim, tolerance of alga to 2.5% glutaraldehyde and then in 1% OsO4. After Cs+ LRQV LQ SDUWLFXODU WKH LQÀXHQFH RI GL൵HUHQW dehydration in ethanol of increasing concentrations, FRQFHQWUDWLRQVRIKHDY\PHWDORQXOWUDဧUXFWXUHRI the samples were embedded in Epon–Araldite resin Spirulina cells, as well as on biomass formation DQG SRXUHG LQWR JHODWLQ FDSVXOHV >4@ and chlorophyll accumulation by Spirulina have 7KLQVHULDOVHFWLRQV ±QP ZHUHPDGHXVLQJ EHHQ ဧXGLHG$FFRUGLQJ WR WKH REWDLQHG GDWD WKH DQ/.%,,,XOWUDPLFURWRPHဧDLQHGZLWKXUDQ\O phytoremediation technology for cleaning of water acetate, and analyzed by electron microscope Tesla polluted with Caesium based on application of %6 &]HFK5HSXEOLF VSHFL¿FVWUDQVPLVVLRQ 6SLUXOLQDKDYHEHHQHODERUDWHGDQGWHဧHGYLDPRGHO UHVROXWLRQ QP H[SHULPHQWV 2.3 Experimental design 2. Materials and methods 2.1 Materials )RU HဧLPDWLRQ RI LQÀXHQFH RI GL൵HUHQW concentrations of Cs+ on growing parameters of The biomass of Spirulina platensis obtained 6SLUXOLQDDOJDZDVFXOWLYDWHGLQဧDQGDUG=DUURXN¶V YLDFXOWLYDWLRQLQဧDQGDUG=DUURXN¶VPHGLXP S+ PHGLD YROXPH P/ FRQWDLQLQJ GL൵HUHQW + – 8.7; content in g/L: NaHCO3 – 16.8, K2HPO4 concentrations of Cs RUSSP 7KHLQLWLDO . 0.5, NaNO3 – 2.5, K2SO4 – 1.0, NaCl – 1.0, MgSO4 ELRPDVV RI 6SLUXOLQD ZDV J/ 7KH LQFXEDWLRQ . . 7H2O – 0.2, CaCl2 2H2O – 0.04, FeSO4 7H2O – ZDV FDUULHG RXW LQ ÀDVNV GXULQJ K K IRU 0.01, EDTA – 0.08; and microelements kit A5 – 1 XOWUDဧUXFWXUDO LQYHဧLJDWLRQV DW WHPSHUDWXUH qC, P/ ZHUHXVHGLQWKHH[SHULPHQWV,QFXEDWLRQZDV without air barbotage, a photoperiod of lighting FDUULHG RXW ZLWK SHUPDQHQW DLU EDUERWDJH UDWH RI /'33)'§PRO . m . s. After incubation DLUÀRZ/PLQ DWWHPSHUDWXUHqC, and under the biomass productivity by Spirulina and chlorophyll following illumination conditions: a photoperiod of content in cells by above mentioned methods were OLJKWLQJ/' KRXUVRIOLJKW KRXUVRIGDUN GHWHUPLQHG7KH XOWUDဧUXFWXUH DQDO\VLV ZDV FDUULHG DWRWDOSKRWRV\QWKHWLFSKRWRQÀX[GHQVLW\ 33)' out in same samples. RI§PRO. m . s. 7KHPRGHOODUJHVFDOHH[SHULPHQWZDVFDUULHGRXW in following conditions: Spirulina was preliminary 2.2 Methods JURZLQJLQ=DUURXN¶VPHGLXP YROXPH/ DQGDIWHU 7 days 20 L of Cs+ containing solution was added. For measurement of fresh biomass productivity The volume of incubation medium in the beggining and chlorophyll formation by Spirulina, the of incubation of Spirulina with Cs+ was 40 L. At that following method was elaborated: the incubation moment, the biomass of Spirulina was 3.5 g/L and medium was centrifuged at 1000 g during 20 min Cs+ concentration was 100 ppm. The incubation was and obtained pellet was weighted. The obtained fresh FDUULHGRXWLQDJODVVFRQWDLQHUZLWKVL]HV[[ biomass was treated by acetone and the content of LQFPOHQJWK[ZLGWK[KHLJKW ZLWKSHUPDQHQWDLU chlorophyll was determined spectrophotometrically EDUERWDJH UDWHRIDLUÀRZ/PLQ DWWHPSHUDWXUH DWQPDFFRUGLQJWRဧDQGDUGPHWKRG>11@ 25qC, under following illumination conditions: a The biomass of Spirulina in incubation medium KOLJKWLQJ /' 33)'§PRO . m . s. have been measured spectrophotometrically at 750 ,Q WKH FRQWURO YDULDQW LQဧHDG RI &V+ solution 20 L QP>12@ of water was added. The content of Cs+ ions and The content of Cs+ ions in the samples was biomass of Spirulina were determined after 5, 10 and determined by the method of atomic absorption 15 days from addition of heavy metal ions. 154 M. Kurashvili et al. Annals of Agrarian Science 17 (2019) 153 – 157 3. Results and Discussion According to the obtained results, Spirulina revealed + 7KHLQÀXHQFHRI&V+ on Spirulina cells WROHUDQFH WR DOO WHဧHG FRQFHQWUDWLRQV RI &V ions.
7KH LQÀXHQFH RI GL൵HUHQW FRQFHQWUDWLRQV RI &DHVLXPLRQV DQGSSP RQELRPDVVDQG 3.2. Study of penetration and localization of chlorophyll accumulation by Spirulina has been Cs+ in Spirulina ဧXGLHG 7KH REWDLQHG UHVXOWV DUH JLYHQ LQ )LJ 2Q WKH QH[W ဧDJH WKH LQÀXHQFH RI &V+ ions RQ XOWUDဧUXFWXUH RI 6SLUXOLQD FHOOV XVLQJ HOHFWURQ Fresh biomas Chlorophyll PLFURVFRSLFPHWKRGKDVEHHQဧXGLHG )LJ$' 120 $V )LJ VKRZV WKH LQÀXHQFH RI WKH KLJKHဧ + 100 concentration of Cs LRQV SSP FDXVHGRQO\DQ LQFUHDVHRIK\GURFDUERQVFRQWDLQLQJVSDFHEHWZHHQ 80 % from control from % lamella in Spirulina cells, which can be a result of 60 accumulation of heavy metal ions. Thus, 100 ppm + 40 concentration of Cs ions has been chosen for the PRGHO H[SHULPHQWV 20
0 Control 1 ppm Cs 10 ppm Cs 100 ppm Cs 3.3. The results of model experiment
Fig. 1. 7KHLQÀXHQFHRIGLৼHUHQW 7KH PRGHO H[SHULPHQWV IRU HODERUDWLRQ QHZ FRQFHQWUDWLRQVRIFHDVLXPLRQVRQELRPDVV approach of phytoremediation technology for IRUPDWLRQDQGFKORURSK\OODFFXPXODWLRQE\ cleaning water polluted by Cs+ ions have been 6SLUXOLQD,QFXEDWLRQFRQGLWLRQVDUHGHVFULEHG carried out. For this aim, Spirulina cultivated in in part 2.3. ZDWHUDUWL¿FLDOO\SROOXWHGZLWKSSP&V+ ions. The obtained data are given in Fig. 3. According to the obtained results, low As it seen from Fig. 3, Spirulina has capability FRQFHQWUDWLRQVRIKHDY\PHWDOUHYHDOHGLQVLJQL¿FDQW to assimilate up to 90% of heavy metal ions from H൵HFW RQ 6SLUXOLQD YLWDO SURFHVVHV UHGXFWLRQ RI polluted water during 15 days. At the same time ELRPDVV IRUPDWLRQ E\ DQG FKORURSK\OO biomass of alga decreases by 25%. These results FRQWHQW E\ 7KHKLJKFRQFHQWUDWLRQRI&V+ indicate that Spirulina is potentially usable for SSP EORFNHG ELRPDVV SURGXFWLRQ E\ cleaning of waters polluted with nonradioactive Cs+ and the content of chlorophyll decreased by 20%. ions as well as with 137Cs+ ions.
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CD Fig. 2. (OHFWURQPLFURJUDSKVRIFHOOVRI6SLUXOLQDFXOWLYDWHGRQ=DUURXN¶V PHGLXPZLWKRXW&V+LRQV $DQG% DQGZLWKSPRI&V+LRQV,QFXEDWLRQ FRQGLWLRQVDUHGHVFULEHGLQSDUW 155 0.XUDVKYLOL HWDO Annals of Agrarian Science 17 (2019) 153 – 157
Concentration of Cs-ions, ppm Biomass of Spirulina, Control Biomass of Spirulina with Cs-ions 120 12 110 100 10 90 80 8 70 Fresh biomass, g per L per g biomass, Fresh Concentration of Cs+, ppm Cs+,of Concentration 60 6 50 40 4 30 20 2 10 0 0 0246810121416
Time, days
Fig. 3. The results of model experiment for cleaning Cs+ containing water by using Spirulina. The conditions of experiment are described in part 2.3.
5. Conclusions $FXWH WR[LFLW\ RUJDQ FKDQJHV DQG WLVVXH DFFXPXODWLRQ-(QYLURQ6FL+HDOWK3DUW Thus, the work carried out has shown that $ ± 6SLUXOLQDFHOOVKDYHDQDELOLW\WRH൵HFWLYHO\UHPRYH >@ - 5XQGR $ 6XUYH\ RI WKH 0HWDEROLVP RI + Cs LRQV IURP DUWL¿FLDOO\ SROOXWHG ZDWHU 7KHVH &DHVLXP LQ 0DQ%ULWLVK - 5DGLRO UHVXOWVFDQEHFRPHDEDVLVIRUGHYHORSPHQWRIDQHZ ± SK\WRUHPHGLDWLRQ WHFKQRORJ\ IRU FOHDQLQJ ZDWHUV [3] $ $KPDG 5 *KXIUDQ =$ :DKLG &G 137 + SROOXWHG ZLWK UDGLRDFWLYH &DHVLXP LRQV Cs ) $V &X DQG =Q 7UDQVIHU WKURXJK 'U\ WR EDVHG RQ DSSOLFDWLRQ RI 6SLUXOLQD 5HK\GUDWHG %LRPDVV RI 6SLUXOLQD Platensis IURP:DဧHZDWHU3ROLVK-(QYLURQ6WXG 6. Acknowledgment >@ +&KHQ63DQ %LRUHPHGLDWLRQSRWHQWLDORI 7KLV ZRUN ZDV VXSSRUWHG E\ 6KRWD 5XဧDYHOL VSLUXOLQD WR[LFLW\ DQG ELRVRUSWLRQ ဧXGLHV RI 1DWLRQDO 6FLHQFH )RXQGDWLRQ 6516) ZLWK OHDG-=KHMLDQJ8QLY6FL% FRIRXQGLQJ E\ *HRUJLDQ $JULFXOWXUDO 8QLYHUVLW\ $SSOLHG5HVHDUFK*UDQW DQG6516) >@ 20XUDOL60HKDU%LRUHPHGLDWLRQRIKHDY\ &15 PHWDOVXVLQJ6SLUXOLQD,QW-*HRORJ\(DUWK DQG(QYLURQ6FL References >@ .6XUHVK.XPDU+8'DKPV(-:RQ- 6/HH.+6KLQ0LFURDOJDH±$SURPLVLQJ [1] &3LQVN\5%RVH-57D\ORU-0F.HH& WRROIRUKHDY\PHWDOUHPHGLDWLRQ(FRWR[LFRO /DSRLQWH - %LUFKDOO &HVLXP LQ PDPPDOV (QYLURQ6DI ±
156 0.XUDVKYLOL HWDO Annals of Agrarian Science 17 (2019) 153 – 157 [7] $+0DKYL &DGPLXP %LRVRUSWLRQ IURP :DဧHZDWHU E\8OPXV/HDYHVDQG7KHLU$VK(XURS-6FLHQW5HV 23 (2008) 197-203. [8] $0DOHNL$+0DKYL0$=D]RXOL+,]DQORR$+ %DUDWL$TXHRXV&DGPLXP5HPRYDOE\$GVRUSWLRQRQ %DUOH\+XOODQG%DUOH\+XOO$VK$VLDQ-&KHP (2011) 1373-1376. [9] 6)XNXGD./ZDPRWR0$VXPL$
157 =âWHIXQNRYiHWDO Annals of Agrarian Science 17 (2019) 158 – 166
Annals of Agrarian Science
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Quality assessment of the aquatic habitat of mountain streams in the SHULRGRIPLQLPDOÀRZXVLQJWKHLFKWK\RIDXQDDVDELRLQGLFDWRU Zuzana Štefunkováa*, Viliam Macuraa, Igor Kondéb aDepartment of Land and Water Resources Management, Faculty of Civil Engineering, Slovak University of Technology Bratislava, 11, Radlinského, Bratislava, 813 68, Slovak Republic bDepartment of Landscape Engineering, Faculty of Horticulture and Landscape Engineering, Slovak University of Agriculture in Nitra, 7, Tulipánová, Nitra, 949 76, Slovak Republic.
Received: 22 February 2019; accepted: 14 May 2019
A B S T R A C T
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Introduction of climate change on the quality of the aquatic KDELWDW>@&OLPDWHFKDQJHKDVDQHJDWLYHLPSDFW ,Q(XURSHLWLVJUDGXDOO\EHFRPLQJDဧDQGDUG RQWKHELRWDRIWKHÀRZVLPLODUO\DVFRQWDPLQDWLRQ to model the ecological water quality based on the RIÀRZ>@ ,QဧUHDP )ORZ ,QFUHPHQWDO 0HWKRGRORJ\ ,),0 The quality of the aquatic habitats of mountain >@ ,),0 LV DQ LQWHUGLVFLSOLQDU\ GHFLVLRQPDNLQJ DQG SLHGPRQW ဧUHDPV ZDV HYDOXDWHG XVLQJ WKH V\ဧHPWKDWDVVLဧVODQGVFDSHHQJLQHHUVWRFRQVLGHU ,QဧUHDP )ORZ ,QFUHPHQWDO 0HWKRGRORJ\ ,),0 WKH EHQH¿WV DQG FRQVHTXHQFHV RI GL൵HUHQW ZDWHU GHFLVLRQPDNLQJ WRRO ,),0 LV EDVHG RQ WKH PDQDJHPHQWVROXWLRQV>@,),0PHWKRGRORJ\ZDV NQRZOHGJH WKDW PRဧ ¿VK VSHFLHV SUHIHU FHUWDLQ developed in the United States by the U.S. Fish FRPELQDWLRQV RI ZDWHU GHSWKV ÀRZ YHORFLWLHV > DQG :LOGOLIH 6HUYLFH 86):6 WR GHWHUPLQH WKH @ DYDLODELOLW\ RI FRYHU DQG EHG PDWHULDOV >@ H൵HFWRIZDWHUPDQDJHPHQWSURMHFWVRQWKHQDWXUDO ,),0FDQSURYLGHUREXဧDVVHVVPHQWVRIWKHTXDOLW\ environment by quantifying the aquatic environment RI D ULYHU ZKHQ VX൶FLHQW GDWD DUH DYDLODEOH 2QH >@ 7KH EDVLV RI WKH ,),0 PHWKRGRORJ\ LV WKH RIWKHPRဧFRQVLGHUDEOHDGYDQWDJHVRI,),0RYHU 3K\VLFDO +DELWDW 6LPXODWLRQ 6\ဧHP 3+$%6,0 DOWHUQDWLYHPHWKRGV &&$5'$*/0DQGUHODWHG which is used to analyse the relationship between DQDO\VHV LVWKHIDFWWKDWLWLQFRUSRUDWHVDVSDWLDOO\ WKHÀRZDQGELRWLFFRPSRQHQWVRIWKHHQYLURQPHQW GLဧULEXWHG PRGHO LQ DQ\ GHVLUHG GHWDLO 7KLVUHODWLRQVKLSLVDFRQWLQXRXVÀRZIXQFWLRQ>@ In the case of morphological changes, the biotic This method can also be used to predict the impact FRPSRQHQW RI WKH HQYLURQPHQW UHSUHVHQWV ¿VK DV 158 =âWHIXQNRYiHWDO Annals of Agrarian Science 17 (2019) 158 – 166 WKHPRဧFUXFLDOHOHPHQWဧDQGLQJDWWKHWRSRIWKH WKHVDPHSUR¿OH7KHPHDVXUHPHQWVZHUHPDGHE\ food pyramid of aquatic biota. Because of their leveling, which has a higher precision for hydraulic longevity, their mobility and their sensitivity to modeling. KDELWDW PRGL¿FDWLRQ ¿VK DUH JRRG ELRLQGLFDWRUV >@DQGWKH\DUHRIWHQXVHGIRUWKHDVVHVVPHQW 0HDVXUHPHQWRIWKHYHORFLW\¿HOG RI WKH HFRORJLFDO LQWHJULW\ RI ULYHUV > @ In the IFIM methodology, the basic parameters The discharge was measured in a representative RI WKH ÀRZ KDELWDW DUH GLYLGHG LQWR DELRWLF DQG PHDVXULQJ SUR¿OH XVLQJ K\GURPHWULF GHYLFHV 7KH biotic. A more detailed analysis between abiotic and YHORFLW\¿HOGZDVVHWE\SRLQWPHDVXUHPHQWVLQHDFK ELRWLF FKDUDFWHULဧLFV LV JLYHQ LQ WKH EDVLF DELRWLF FURVV VHFWLRQ 7KH GLဧDQFH EHWZHHQ WKH YHUWLFDOV FKDUDFWHULဧLFV DUH GHSWK DQG ÀRZ YHORFLW\ 7KH ranged from 1 to 2 meters. The measurement was UHODWLRQVKLSRIWKHDELRWLFDQGELRWLFFKDUDFWHULဧLFV made in within the ichthyological survey and then of the aquatic area is represented by the suitability VHSDUDWHO\ IRU GL൵HUHQW ZDWHU ဧDJHV WR YHULI\ WKH FXUYHVRILQGLYLGXDO¿VKVSHFLHV$GHWDLOHGDQDO\VLV hydraulic model. of the relation of the suitability curves to the K\GUDXOLFVRIÀRZZDVFRQ¿UPHGPDLQO\LQUHODWLRQ *UDLQVL]HGLဧULEXWLRQRIWKHERWWRP WRWKHÀRZGHSWK>@7KHULYHUUHJXODWLRQFKDQJHV material mainly the morphology of the river bed, which is The grain size was analyzed using a sieve directly UHÀHFWHGLQWKHFKDQJHLQGHSWKDQGÀRZYHORFLW\ LQWKH¿HOG6LHYHVZLWKFLUFXODUPHVKHVZHUHXVHG For this purpose, the Riverine HABitat Simulation The weight of the samples ranged from 120 kg to PRGHO 5+$%6,0 LVXVHGWRJHQHUDWHTXDQWLWDWLYH 240 kg. results representing the quality of the aquatic habitat. Habitat quality is determined by depth Ichthyological survey and velocity parameters, which are derived from suitability curves that represent habitat preference The reference sections of the rivers were blocked IRULQGLYLGXDO¿VKVSHFLHV>@7KHKDELWDWTXDOLW\ DWHDFKHQGE\QHWVZLWKDPHVKVL]HRI[PP LVUHSUHVHQWHGE\WKH:8$:HLJKWHG8VDEOH$UHD Fish were caught using an electric aggregate and put :8$H[SUHVVHVWKHIXQFWLRQDOUHODWLRQVKLSEHWZHHQ DIWHUZDUGLQWRD¿VKWDQNORFDWHGLQWKHULYHUEHORZ WKHÀRZDQGWKHVXUIDFHRIWKHÀRZ WKHORZHUQHWEH\RQGWKHUHDFKRIWKHHOHFWULF¿HOG The following procedure was chosen for the Three catches were made in each of the blocked determination of the quality of the aquatic habitat sections, whereby the second and third catches were IRUUHIHUHQFHVHFWLRQVRIGL൵HUHQWUHSUHVHQWDWLYH made 45 minutes after the previous ones. After each Rivers in Hron River basin: FDWFK HYHU\ ¿VK VSHFLHV ZDV FRXQWHG VHSDUDWHO\ · measurement of topographic parameters of DQG WKH ¿VK ZHUH PHDVXUHG ZHLJKHG DQG OHW RXW the reference sections, LQWR WKH ULYHU EHORZ WKH ODဧ QHW 7KH FDOFXODWHG · PHDVXUHPHQWRIWKHYHORFLW\¿HOG values, combined with the mean weight of the · HYDOXDWLRQRIWKHJUDLQVL]HGLဧULEXWLRQRI respective species, were applied to the calculation the bottom material, of the biomass of the individual species and total · ichthyological research, ichthyomass. At the same time, the mean weight of · evaluation of the results in the IFIM model. each species was calculated, and this weight was The results of the measurements were then FRPSDUHG ZLWK WKH QXPEHU RI ¿VK LQ HDFK RI WKH evaluated for the selected reference sections of the length groups. Teplá River in the town of Sklené Teplice using 7KH DEXQGDQFH H[SUHVVHV WKH QXPEHU RI ¿VK the RHABSIM model and then compared with the of the respective species. The abundance is given model developed by the authors of this paper. LQ ¿VK SHU KHFWDUH WKH LFKWK\RPDVV H[SUHVVHV WKH DJJUHJDWHZHLJKWRIWKHHQWLUH¿VKSRSXODWLRQDQGLV Topographic measurement of the reference given in kg.ha . sections Results and discussion The topography of the reference sections was FKDUDFWHUL]HGE\FURVVVHFWLRQVVHWDW¿[HGSRLQWV :HWULHGWRFRQ¿QHRXUVHOYHVWRDQH[DPLQDWLRQ which permitted the repeating of measurements in RIWKHTXDQWL¿DEOHEDVLFSDUDPHWHUVRIDULYHUZKLFK 159 =âWHIXQNRYiHWDO Annals of Agrarian Science 17 (2019) 158 – 166 would implicitly include ecologically relevant E\WKHVDSURJHQLFLQGH[RIELRVHဧRQHFRUUHVSRQGV information. The width, depth, water level area, WRFODVV,,, PHGLXPFOHDQ YHORFLW\¿HOGZDWHUWHPSHUDWXUHDQGFKDUDFWHULဧLFV of the ichthyic fauna as indicators of the quality Characterization of the riverbed of the of the biological environment in a river may be reference sections of the Teplá River considered as the basic parameters of a river. An analysis of the morphometric, hydraulic and Three reference sections were chosen on ichthyological parameters has been made for all the Teplá River in the town of Sklené Teplice, and selected reference sections in the Hron River basin. these sections follow one another; therefore, they This paper contains the basic results obtained from may be documented in one longitudinal section. the reference sections of the Teplá River in the town The numbering of the sections is identical with the of Sklené Teplice. designation of the cross sections; hence, the sections DUH QXPEHUHG XSဧUHDP %DVLFFKDUDFWHULဧLFVRIWKH7HSOi5LYHU Section No. 1 is in the town of Sklené Teplice. ,WLVPORQJ WKHဧDWLRQLQJRIWKHVHFWLRQLQ Catchment area = 172 km2 ဧDWLRQLQJ ¿JXUH ဧDUWV DW DQG HQGV DW P 7KH km. Water gauge altitude = 287.00 m above sea ULYHUEHGERWWRPLVGLVVHFWHGRQO\WRDVPDOOH[WHQW 3 level, QPD[ = 72 m .s , Qmin = ZLWKXQPDUNHGDOWHUDWLRQVRIWKHGHSWK LWFRQVLဧV 0.17 m3.s. RIJUDYHOVDQG7KLVVHFWLRQUHSUHVHQWVWKHÀRZDUHD The topography of the riverbed bottom in all three Table.1.2YHUUXQRIDYHUDJHGDLO\GLVFKDUJHV sections is partially documented by the longitudinal M-days 30 90 180 270 330 335 364 VHFWLRQLQ¿JXUH 3 -1 Discharge [m .s ] 5.65 2.73 1.52 1.05 0.68 0.53 0.32 6HFWLRQ 1R LV P ORQJ WKH ဧDWLRQLQJ RI WKH VHFWLRQ LQ ¿JXUH ဧDUWV DW DQG HQGV DW Water quality in the Teplá River in the town P 7KHULYHUEHGERWWRPLVGLVVHFWHG WUHHV of Sklené Teplice and shrubs cover the banks. This section represents WKH ÀRZ VKDGRZ DUHD ,Q WKH SUR¿OH VLWXDWHG LQ WKH WRZQ RI 6NOHQp 7HSOLFHWKHH൵HFWRIWKHORFDOPXQLFLSDOSROOXWLRQ 6HFWLRQ1RLVPORQJ WKHဧDWLRQLQJRI ZDVGHPRQဧUDWHGE\WKHXVXDOLQFUHDVHLQWKHQXPEHU WKHVHFWLRQLQ¿JXUHဧDUWVDWDQGHQGV RIFROLIRUP FODVV,9IDLUO\FOHDQ DQGSV\FKURSKLOH DW P 7KHULYHUEHGERWWRPLVGLVVHFWHG EDFWHULD FODVV9ZDWHUVDUHQRWFODVVL¿HGLQFODVV RQO\WRDVPDOOH[WHQW7UHHVDQGVKUXEVFRYHU HVSHFLDOO\ LQ 7KH RUJDQLF SROOXWLRQ the banks. The longitudinal slope of the water H[SUHVVHG E\ %2' DOUHDG\ H[FHHGV WKH FODVV ,, OHYHO LV ODUJH ZKLFK PHDQV JUHDWHU YHU\FOHDQ OLPLWYDOXH&2'0QUHPDLQVLQFODVV ÀRZYHORFLWLHVDQGVPDOOGHSWKV7KLVVHFWLRQ ,,RIWKHFODVVL¿FDWLRQXQGHUဧDQGDUGý61 represents the fording area with small depths 7KHGLVVROYHGR[\JHQFRPSOLHVZLWKFODVV, H[WUD DQGKLJKHUÀRZYHORFLWLHV FOHDQ 7KHELRORJLFDODFWLYLW\RIWKHULYHUH[SUHVVHG
CROSS SECTION 1 2 3 4 5 6 7 8 9 10 11
WATER-LEVEL
BOTTOM
-5.00
0.1 0.2 2.50 7.11 8.07 92.20 7.07 8.07 68.90 7.60 7.96 55.80 7.57 7.81 35.60 7.06 7.65 5.40 6.75 7.63 61.70 80.30 7.01 7.55 7.21 7.56 52.58 7.05 7.54 41.60 7.10 7.52 23.30 7.09 7.47 0.00 1.52 7.13 7.39 7.13 7.40 Fig. 1. /RQJLWXGLQDOVHFWLRQRIUHIHUHQFHVHFWLRQVRIWKH7HSOi 5LYHULQWKHWRZQRI6NOHQp7HSOLFH 160 =âWHIXQNRYiHWDO Annals of Agrarian Science 17 (2019) 158 – 166 Basic abundance and ichthyomass data are the reference sections of the Teplá River is given in JLYHQLQ)LJXUHVDQG WKHOLဧRI¿VKIRXQGLQ Table 2.
Table 2./LVWRI¿VKVSHFLHVIRXQGLQWKHUHIHUHQFHVHFWLRQVRIWKH7HSOi5LYHU
Fish name Scientific name Fish name Scientific name Barbel Barbus barbus Minnow Phoxinus phoxinus Brown trout Salmo labrax m.fario Perch Perca fluviatilis Chub Leuciscus cephalus Picke Exox lucius Eel Anguilla anguilla Roach Rutilus rutilus Grayling Thymallus thymallus Spirling Alburnoides bipunctatus Gudgeon Gobio gobio Stoneloach Barbatula barbatula
Fig. 2. $EXQGDQFH>¿VKKD@LQWKHUHIHUHQFHVHFWLRQVRIWKH7HSOi5LYHU LQWKHWRZQRI6NOHQp7HSOLFH
Fig. 3. ,FKWK\RVHV>NJKD@LQWKHUHIHUHQFHVHFWLRQVRIWKH7HSOi5LYHULQWKHWRZQRI6NOHQp7HSOLFH
Hydraulic and topographic parameters of m3.s and on 7th September 2017, at a discharge of the reference sections in the Teplá River in 0.5 m3.s. Two discharges were modeled: 0.32 m3.s 1 3 the town of Sklené Teplice 4365 = 0.32 m .s DQGPV 4min = 0.17 m3.s 7KHEDVLFK\GUDXOLFFKDUDFWHULဧLFV The hydraulic model of all reference sections ZDWHU GHSWK DQG WKH YHORFLW\ ¿HOG IRU UHIHUHQFH ZDV GHYHORSHG LQ DWZRGLPHQVLRQDO SURJUDP sections 1 to 3 at a discharge of 0.5 m3.s are shown The purpose of the model was to complement in Figure 4. WKH YHORFLW\ ¿HOG DQG ZDWHU OHYHO IRU WKH VHOHFWHG 7KH H[SHFWHG K\GURELRORJLFDO FKDQJHV LQ WKH discharges. river may be simulated by changing the basic 7KH YHORFLW\ ¿HOG RI WKH UHIHUHQFH VHFWLRQV LQ hydraulic parameters using the suitability curve. the Teplá River in the town of Sklené Teplice was measured twice: 20th July 2017, at a discharge of 1.85 161 =âWHIXQNRYiHWDO Annals of Agrarian Science 17 (2019) 158 – 166
Water depth
10.00 0.00 0.00 20.00 40.00 60.00 80.00 100.00 120.00 140.00 160.00 180.00 200.00
Velocity field
10.00 0.00 0.00 20.00 40.00 60.00 80.00 100.00 120.00 140.00 160.00 180.00 200.00
Fig. 4. :DWHUGHSWKV>P@DQGÀRZYHORFLWLHV>PV@LQWKHUHIHUHQFH VHFWLRQV7HSOi5LYHULQWKHWRZQRI6NOHQp7HSOLFH
Habitat Suitability Curves H[SUHVV D SUHIHUHQFH RI HDFK VSHFLHV IRU YDULRXV habitats. The curves are based on the assumption 7KH+DELWDW6XLWDELOLW\&XUYHV +6&V UHSUHVHQW WKDWHYHU\¿VKVSHFLHVSUHIHUVFHUWDLQFRPELQDWLRQV the main abiotic components of the microhabitat RIDELRWLFHQYLURQPHQWDOSDUDPHWHUV> @6XLWDELOLW\ ÀRZ YHORFLW\ ZDWHU GHSWK DQG KLGLQJ SODFHV curves for the Teplá River for water depth are given SUHIHUUHG E\ WKH LQGLYLGXDO ¿VK VSHFLHV +6&V LQ¿JXUH
Fig. 5. 6XLWDELOLW\FXUYHVRIEURZQWURXW VDOPRWUXWWDPIDULR IRUWKHZDWHU GHSWKHYDOXDWHGDWWZRGLVFKDUJHV EOXHDWP3.sDQGJUHHQDWP3.s) ZLWKWKHJHQHUDOL]HGFXUYH UHGGDVKHG 162 =âWHIXQNRYiHWDO Annals of Agrarian Science 17 (2019) 158 – 166 Evaluation of the relation between the RIWKHKDELWDW¶VGHJUHHRIDFFHVVLELOLW\LVEDVHGRQ depth, velocity and water level area the physical essence of the individual phenomena ZLWKRXWVLPSOL¿FDWLRQ,WPD\EHDVVXPHGWKDWWKH The relation between the depth, velocity and results of such a model are of high quality and are ZDWHUOHYHODUHDZDVTXDQWL¿HGXVLQJWZRPHWKRGV VXEဧDQWLDOO\ VXLWDEOH IRU WKH YHUL¿FDWLRQ RI RWKHU )LUဧ PHWKRG ZDV D PHWKRG RI PHDQV RI PRGHOV WKHUHIRUH LQ WKH IXUWKHU WH[W WKH WHUP WKH 5+$%6,0 VRIWZDUH ZKLFK VLPSOL¿HV WKH of the reference model for this methodic will be evaluation of parameters. Depths and velocities used. The measurement and hydraulic modeling are evaluated independently; therefore, the results UHVXOWVDUHQRWHYDOXDWHGWZRGLPHQVLRQDOO\EXWDV UHPDLQ FRQဧDQW IURP RQH ULYHU SUR¿OH WR DQRWKHU DWKUHHGLPHQVLRQDOFRQWRXUSODQZKLFKZDVXVHG WZRGLPHQVLRQDO VROXWLRQ PRGHO 7KH GHSWK IRU WKH HYDOXDWLRQ RI WKH YHORFLW\ ¿HOG DQG ZDWHU and velocity values are multiplied individually GHSWK LQWHUVHFWLRQ DUHDV DW D VSHFL¿F ÀRZ 7KH by parameters from the suitability curves for the intersection areas were corrected by the parameters LQGLYLGXDO ¿VK VSHFLHV ZKLOH ZKHQ DSSO\LQJ WKH of the suitability curves with the same weight. second method, these values are multiplied by one The evaluation of the habitat quality assumes that value, which is the intersection of the depth and D IXQFWLRQ GH¿QHG DV :8$ PD\ FKDUDFWHUL]H WKH ÀRZ YHORFLW\ ZLWK D ဧDQGDUG ZHLJKW degree of accessibility of the physical habitat of the The second method was developed by the WDUJHWHG¿VKVSHFLHV:8$IRUWKHUHIHUHQFHVHFWLRQ authors of this paper, mainly as a reference method of Teplá River in the town of Sklené Teplice is given IRU WKH YHUL¿FDWLRQ RI ဧDQGDUG PRGHOV WKHUHIRUH LQ ¿JXUH accuracy was the primary criterion. The modeling
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163 =âWHIXQNRYiHWDO Annals of Agrarian Science 17 (2019) 158 – 166 Comparison of the results of the evaluation behavior in these habitats, but these are quite of the weighed usable area (WUA) by two H[WHQVLYH DQG GR QRW HQDEOH WKH PDNLQJ RI DQ methods unambiguous decision. This also leads to the conclusion that the parameter of channel should An evaluation of the quality of habitat assumes not be designed in a general manner but has to be that the degree of accessibility of the physical habitat determined individually for each river. RIWDUJHWHG¿VKVSHFLHVPD\EHFKDUDFWHUL]HGE\D The following recommendations for the IXQFWLRQWKDWLVGH¿QHGDVWKHZHLJKWHGXVDEOHDUHD GHWHUPLQDWLRQ RI WKH H൵HFW RI WKH GLVFKDUJH DQG D :8$ 7KHTXDQWL¿FDWLRQRIWKHUHODWLRQEHWZHHQ ULYHUEHG¶VQDWXUHRQWKHELRORJLFDOHQYLURQPHQWRID the depth, velocity and water level area was used river may be formulated from the results obtained: as the basis for an evaluation of the weighed usable • The number of reference sections should be DUHD±:8$IRUWKHLQGLYLGXDO¿VKVSHFLHV UHSUHVHQWDWLYH RI WKH KDELWDWV H[LဧLQJ LQ WKH WUA values obtained by both methods vary. VHFWLRQ LQ TXHဧLRQ :H UHFRPPHQG WKDW It is necessary to remember that the WUA value the reference sections and the percentage of represents the qualitative depiction of the biota represented habitats be selected based on the development in a watercourse depending on WDFKRPHWULF VXUYH\ RI WKH VHFWLRQ RI LQWHUHဧ the discharge, morphology or other parameters; DQG EH VSHFL¿HG LQ WKH ¿HOG WRJHWKHU ZLWK therefore, the WUA development trend which is LFKWK\RORJLဧV maintained is decisive. This is also documented by • The collection of hydraulic and ichthyological ¿JXUHZKLFKGHSLFWVWKHHYDOXDWLRQRIWKH:8$ data should be done simultaneously, and the curve by both methods, whereby the RHABSIM K\GURPHWULF PHDVXUHPHQW RI WKH YHORFLW\ ¿HOG model values are corrected, i.e., reduced by the IRU WKH YHUL¿FDWLRQ RI WKH K\GUDXOLF PRGHO DYHUDJHGL൵HUHQFHEHWZHHQWKHUHVXOWVREWDLQHGE\ should be performed as soon as possible; an both methods. It may be anticipated that in the case ichthyological survey is not necessary for this RIVPDOOZDWHUFRXUVHVZLWKFRQVLGHUDEOHGL൵HUHQFHV measurement. LQYHORFLWLHVDQGGHSWKVPRUHVLJQL¿FDQWGL൵HUHQFHV 7KH5+$%6,0PHWKRGREMHFWLYHO\IHDWXUHVWKH in the trend could occur; in this case, it is useful to WUA development trend; the evaluation based YHULI\RUFRQ¿UPWKHWUHQGHYHQE\WKHUHIHUHQFH on the methodology characterized in second method. method is appropriate only in controversial cases. Results and discussion • We recommend evaluating WUA by the When applying the described method, it is RHABSIM model, especially for the hydraulic QHFHVVDU\WREHDULQPLQGWKDW¿VKDUHFKDUDFWHUL]HG module, which is optimized for modeling in the E\KLJKYDULDELOLW\MXဧDVDUHDOOOLYLQJRUJDQLVPV DUHDRIPLQLPXPGLVFKDUJHVEXWDOVRIRUWURXEOH Some limits determine their habitats and their free communication of the individual modules.
Fig. 7. &RPSDULVRQRI:8$WUHQGVHYDOXDWHGE\ERWKPHWKRGV 164 =âWHIXQNRYiHWDO Annals of Agrarian Science 17 (2019) 158 – 166 %DVHG RQ WKH UHVHDUFK UHVXOWV ZH PD\ ဧDWH Environmental Flow Assessment: Emerging WKDWWKHPHWKRGUHSUHVHQWVDQHZTXDOLWDWLYHဧDJH Trends in the Development abd Application of LQ GHWHUPLQLQJ WKH H൵HFW RI WKH GLVFKDUJH DQG Environmental Flow Methodologies for rivers. ULYHUEHG¶V QDWXUH LQFOXGLQJ WHFKQLFDO ZRUN GRQH 5LYHU 5HVHDUFK DQG $SSOLFDWLRQV ZLWKLQWKHULYHUUHJXODWLRQ RQELRORJLFDODOWHUDWLRQ 397 – 441. in an aquatic area despite the fact, that only a >@ 6WDOQDNHU & /DPE % / +HQULNVHQ - OLPLWHGQXPEHURIHQYLURQPHQWDOIDFWRUV GLVVHFWLRQ %RYHH . %DUWKRORZ - 7KH ,QဧUHDP )ORZ RIWKHULYHUEHGYHORFLW\¿HOGULYHUEHGJUDLQVL]H Incremental Methodology. A primer for IFIM. GLဧULEXWLRQLFKWK\RORJLFDOVXUYH\ ZHUHHYDOXDWHG U. S. National Biological Service. Biological Science Report 29, 1995. Summary >@ 0LNDXWDG]H' .YDE]LULG]H 0 &OLPDWH RI ,PHUHWL LQ DJDLQဧ D %DFNJURXQG RI The measurements made in the reference sections Global Warming. Bulletin of the Georgian RI WKH 7HSOi 5LYHU GHPRQဧUDWHG WKDW WKH UHODWLRQ National Academy of Sciences vol. 9, no. 2 EHWZHHQ WKH ¿VK SRSXODWLRQ DQG FKDUDFWHULဧLFV of the habitat gives a real picture of the changes >@ Surmava, A., Intskirveli, L., Buachidze, N. LQGXFHG E\ WKH WRSRJUDSK\ RI WKH ULYHUEHG IRU Numerical Simulation of Distribution of LQဧDQFH E\ ULYHU UHJXODWLRQV DQG E\ GLVFKDUJH Contaminants Discharged to Kura River. The main advantage of the IFIM methodology is Bulletin of the Georgian National Academy WKDWLWTXDQWL¿HVELRORJLFDOFKDQJHVLQWKHULYHUDV of Sciences, vol. 9, no. 1 (2015) 165-170. DIXQFWLRQRIWKH:8$DQGGLVFKDUJHWKURXJK¿VK >@$\OOyQ ' $OPRGyYDU $ 1LFROD ** which are bioindicators of environmental quality. (OYLUD % ,QWHUDFWLYH H൵HFWV RI FRYHU DQG ,QWKLVZD\TXDQWLWDWLYHGDWDIRUH[SHUWVRQELRWLF hydraulics on brown trout habitat selection and abiotic environments may be obtained. These SDWWHUQV5LYHU5HV$SSO H[SHUWVFDQWKHQHဧDEOLVKDQHFRORJLFDOÀRZRUWKH KWWS G[GRLRUJUUD SDUDPHWHU RI ÀRZ UHဧRUDWLRQ PRUH REMHFWLYHO\ > @,YDQ30DFXUD9âWHIXQNRYi=âNULQiU $ 0DMRURãRYi 0 9RMWNRYi - 8VH RI Acknowledgement Bioindication for Design Parameters of 7KLVဧXG\KDVEHHQMRLQWO\VXSSRUWHGE\WKHE\ River Training in Urbanized Areas. Procedia WKH 6FLHQWL¿F *UDQW $JHQF\ XQGHU &RQWUDFW 1R Engineering: World Multidisciplinary Civil 9(*$ DQG 9(*$ (QJLQHHULQJ$UFKLWHFWXUH8UEDQ 3ODQQLQJ 6\PSRVLXP :0&$86 9RO References (OVHYLHU '2, M SURHQJ ,661 >@ %RYHH.'/DPE%/%DUWKRORZ-0 >@ 3DUDVLHZLF] 3:DONHU -' &RPSDULVRQ RI Stalnaker, C. B., Taylor, J. & Henriksen, J. mesohabsim with two microhabitat models 6WUHDP +DELWDW $QDO\VLV 8VLQJ WKH ,QဧUHDP 3+$%6,0 DQG +$53+$ 5LYHU 5HVHDUFK Flow Incremental Methodology. Information DQG $SSOLFDWLRQV ± DQG 7HFKQRORJ\ 5HSRUW 86*6%5',75 >@ Schiemer, F. Fish as indicators for the )RUW&ROOLQV&2 86*HRORJLFDO assessment of the ecological integrity of large Survey BRD, 1998. rivers. Hydrobiologia, 3 (2000) 271–278; >@ +DZNLQV &3 .HUVKQHU -/ %LVVRQ 3$ 422–423. %U\DQW 0' 'HFNHU /0 *UHJRU\ 69 >@:ROWHU&9LOFLQVNDV$&KDUDFWHUL]DWLRQRI Mcculloch, D.A., Overton, C.K., Reeves, G.H., WKHW\SLFDO¿VKFRPPXQLW\RILQODQGZDWHUZD\V Steedman, R.J., Young, M.K. A hierarchical RI WKH QRUWKHDဧHUQ ORZODQGV LQ *HUPDQ\ DSSURDFKWRFODVVLI\LQJဧUHDPKDELWDWIHDWXUHV. 5HJXO5LYHUV 5HV0JPW )LVKHULHV ± >@6FKPXW]6±-XQJZLUWK0)LVKDVLQGLFDWRUV >@ $QQHDU7&KLVKROP,%HHFKHU+/RFNH for large river connectivity: The Danube andits $ ,QဧUHDP ÀRZV IRU ULYHULQH UHVRXUFHV tributaries. Archiv für Hydrobiologie, 115 ဧHZDUGVKLS 5HYLVHG HGLWLRQ :\RPLQJ ± &KH\HQQH ,QဧUHDP )ORZ &RXQFLO >@ &KRYDQHF$ +RIHU 5 6FKLHPHU ) )LVK >@ 7KDUPH5( $*OREDO3HUVSHFWLYHRQ as bioindicators. Trace metals and other 165 =âWHIXQNRYiHWDO Annals of Agrarian Science 17 (2019) 158 – 166 FRQWDPLQDQWV LQ WKH HQYLURQPHQW 9RO >@ /DVQH ( %HUJHURW % /HN 6 /D൵DLOOH 3 Fish zonation and indicator species for the HYDOXDWLRQ RI WKH HFRORJLFDO ဧDWXV RI ULYHUV H[DPSOH RI WKH /RLUH EDVLQ )UDQFH 5LYHU 5HVHDUFK DQG $SSOLFDWLRQV ± 890. >@9HUQHDX[-/HVSRLVVRQVHWODTXDOLWHGHVFRXUV G¶HDX$QQDOHV6FLHQWL¿TXHVGH/¶8QLYHUVLWH GH)UDQFKH&RPWH´ ± >@0DFXUD9âNULQiU$.DO~].-DOþRYtNRYi 0 âNURYLQRYi 0 ,QÀXHQFH RI WKH PRUSKRORJLFDO DQG K\GUDXOLF FKDUDFWHULဧLFV RIPRXQWDLQဧUHDPVRQ¿VKKDELWDWVXLWDELOLW\ curves. 5LYHU5HVHDUFKDQG$SSOLFDWLRQV9RO 1R ,661 >@ 0DFXUD 9 âNULQiU $ âWHIXQNRYi = 0XFKRYi = 0DMRURãRYi 0'HVLJQ RI 5HဧRUDWLRQ RI 5HJXODWHG 5LYHUV %DVHG RQ Bioindication. In Procedia Engineering: :RUOG 0XOWLGLVFLSOLQDU\ &LYLO (QJLQHHULQJ $UFKLWHFWXUH8UEDQ 3ODQQLQJ 6\PSRVLXP :0&$86 9RO (OVHYLHU V '2, M SURHQJ ,661 > @ 0DFXUD 9 âWHIXQNRYi = 0DMRURãRYi 0 +DODM 3âNULQiU$ ,QÀXHQFH RI GLVFKDUJHRQ¿VKKDELWDWVXLWDELOLW\FXUYHVLQ mountain watercourses in IFIM methodology. J. Hydrol. Hydromech, 9RO1R ,661 ;
166 D. Svanadze et al. Annals of Agrarian Science 17 (2019) 167 – 174
Annals of Agrarian Science
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Spatial and time dynamics of glaciers following the Little Ice Age on the southern slope of the Greater Caucasus Davit Svanadzea,b, Vazha Trapaidzea, Giorgi Bregvadzea, Irakli Megrelidzea,b aIv. Javakhishvili Tbilisi State University, 1, Chavhavadze Ave., Tbilisi, 0179, Georgia bThe Ministry of Environment Protection and Agriculture of Georgia, 50, David Agmashenebeli Ave., Tbilisi, 0012, Georgia
Received: 10 June 2018; accepted: 19 November 2018
A B S T R A C T
The article presents an analysis of the scale in space and time of degradation of some glaciers on the southern slope of Central &DXFDVXV5LGJHIROORZLQJWKH/LWWOH,FH$JHWRPRGHUQWLPHVE\WKHPHWKRGRIUHPRWHVHQVLQJRIVKRUWGLဧDQFHV,WDOVRGHVFULEHV the opportunities and advantages of using this method as compared to the traditional methodology of Orthorectifying and mappingof DHULDOSLFWXUHV,QWKHဧXG\ZHXVHGWKHKLဧRULFDODQGWRSRJUDSKLFPDSVRIGL൵HUHQWSHULRGVDUFKLYHGKLဧRULFDOPDWHULDOVRIDHULDO SKRWRJUDSKLQJUHPRWHVHQVLQJDQGPRGHUQDHULDOLPDJHဧDNHQZLWKDQXQPDQQHGDHULDOYHKLFOH 8$9 3KDQWRPSUR LQ7KH ဧXG\EHVLGHVWKHWUDGLWLRQDODSSURDFKLVEDVHGRQWKHQHZWHFKQLTXHRI8$9SKRWRJUDSK\FUHDWLQJDGLJLWDOWKUHHGLPHQVLRQDOVR FDOOHG³SRLQWFORXG´PRGHODQGLWVXVHLQFDOFXODWLRQVRIYDULRXVJODFLDOJHRPRUSKRORJLFDOSDUDPHWHUVZLWKSKRWRJUDPPHWU\VRIWZDUH DQGJHRLQIRUPDWLRQV\ဧHPV 3L['*OREDO0DSSHU$UF*,6 7KHDUWLFOHJLYHVDGHWDLOHGGHVFULSWLRQRIRSSRUWXQLWLHVRIWKH8$9 VXUYH\LQWHUPVRIKLJKPRXQWDLQRXVUHOLHIDQGKDPSHULQJIDFWRUV,WZDVHဧDEOLVKHGWKDWWKHJODFLHUVZHUHTXDQWLI\IROORZLQJWKH/LWWOH Ice Age and the values of their retreat depend on the concrete types of glaciers and geographical factors. The mentioned glaciers are typical for the soutern slope of the Caucasus Range and are located between mountain Elbrus and 0NLQYDUWVYHULDUUD\VQH[WWRWKHZDWHUVKHGUDQJHV7KHDQDO\VLVRIG\QDPLFVHYLGHQFHVWKDWLQWKHဧXG\SHULRGWKHUHWUHDWYDULHV between 0.8 and 4.2 km.
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Introduction 7KH LPSDFW RI JOREDO ZDUPLQJ LV FRQ¿UPHG E\ QRZ DQG LW LV GHPRQဧUDWHG E\ D UHFHQW LQFUHDVH )RUWKHODဧKDOIDELOOLRQ\HDUVWKHFOLPDWHRQ LQ WKH DYHUDJH WHPSHUDWXUH RQ HDUWK E\ & >@ the earth has been characterized by an alternation 7LPHSHULRGIURP WRZDVGLဧLQJXLVKHG of warm and cold periods. The reasons for such an E\ WKH KLJKHဧ WHPSHUDWXUH EDFNJURXQG IRU WKH alternation have been active volcanism, cyclical ODဧ\HDUVVLQFHWKHRQVHWRIWKHLQဧUXPHQWDO DOWHUQDWLRQRIWKHHDUWK¶VRUELWDOORFDWLRQLQWKH6RODU measurements. The trend in global temperature has V\ဧHP FKDQJLQJ FRPSRVLWLRQ RI WKH DWPRVSKHUH increased sharply in recent years and as compared to shape of continents and ratio between the land DQLQFUHDVHLQWKHDYHUDJHWHPSHUDWXUH and the ocean and a set of many other factors. The RI WKH ODQG UHDFKHG & >@ ;;DQG;;,FHQWXULHVLQWKHKLဧRU\RIWKHHDUWK¶V The ongoing climate change has a decisive climate are marked by a global change, with the LQÀXHQFH RQ VXFK DQ LPSRUWDQW FRPSRQHQW RI DQWKURSRJHQLFDFWLYLWLHVSOD\LQJDVLJQL¿FDQWUROH the geographical layer as cryosphere, which is 167 D. Svanadze et al. Annals of Agrarian Science 17 (2019) 167 – 174 one of the forming elements of the earth climate glaciation transient between the glaciations in the and a good indicator of its changes both, in the FRQWLQHQWDO WKH 3DPLUV 7LDQ 6KDQ DQG KXPLG JOREDO DQG UHJLRQDO DVSHFWV >@7KH EDVLF LPSDFW PDULQHFOLPDWH WKH$OSV ,QDGGLWLRQJODFLHUVH[Lဧ taking place in parallel to the climate change is LQ GL൵HUHQW FOLPDWH FRQGLWLRQV OLNH KXPLG :Hဧ irreversible degradation of the glaciers in the &DXFDVXV PRGHUDWHO\ KXPLG &HQWUDO &DXFDVXV PRXQWDLQRXVV\ဧHPVIRUWKHODဧ\HDUVZKLFK DQG PRGHUDWHO\ GU\ FRQWLQHQWDO (Dဧ &DXFDVXV is associated with the continuous increase ofglobal FOLPDWHV ZLWK WKH GLYHUVLW\ RI WKH FOLPDWLF WHPSHUDWXUH VLQFH WKH /,$ /LWWOH ,FH$JH ,W ZLOO geographical conditions typical to Caucasus lead to the reduction of the freshwater resources and 5LGJH >@ 7KH PDLQ FHQWHU RI JODFLDWLRQ RI WKHP hydropower potential of the rivers and supply of is in Central Caucasus, at 43.200; 42.700. LUULJDWLRQDQGGULQNLQJZDWHUV\ဧHPVDQGLQFUHDVH Between mountains Elbrus and Mkinvartsveri, in the probability of periglacial risks associated ZKHUHWKHUHOLHIUHDFKHVWKHKLJKHဧSRLQWV 0RXQW with glaciers. The southern slope of Great Caucasus Elbrus at 5642 m, Dikhtau at 5025 m, Shkhara 5203 UDQJH DQG LWV DGMDFHQW ULGJHV KDV H[SHULHQFHG D P0NLQYDUWVYHULDWPZLWKRYHUKLJKHဧ ဧURQJ UHGXFWLRQ LQ JODFLDWLRQ DIWHU WKH PD[LPXP SHDNVRYHUPDOWLWXGHDORQJWKHJLYHQVHFWLRQ JODFLHUH[WHQWDWWKHHQGRIWKH/,$ § its average height is 4100 m above sea level. The like other mountainous regions, it have been marked mean annual amount of precipitations is 3000 mm. E\ D VLJQL¿FDQW DEDWHPHQW RI JODFLDWLRQ >@ In this region, while the amount of precipitations 7KH JRDO RI WKH ဧXG\ LV WR SURYLGH D VSDWLR LQWKHHDဧHUQSDUWRIWKH5LGJHLVWLPHVOHVV>@ temporal analysis of the dynamics of the large valley 7KHGL൵HUHQFHEHWZHHQWKHDPRXQWRISUHFLSLWDWLRQV glaciers of the central part of Great Caucasusand on the southern and northern slopes of the Ridge is UHဧRUDWLRQRIWKHLUJHRPHWULFDOFKDQJHVRIEHKDYLRU DOVRODUJH6XFKDGL൵HUHQFHLQFOLPDWLFFRQGLWLRQV from the Little Ice Age to modern times. This problem results from the location of Caucasus Ridge on was solved by using a synthesis of traditional and the border between the moderate and subtropical PRGHUQPHWKRGVDQGGL൵HUHQWWHFKQLTXHVWRREVHUYH FOLPDWLF ]RQHV >@ ,Q DGGLWLRQ &DXFDVXV 5LGJH the process, including an unmanned aerial vehicle, LVXQGHUWKHLQÀXHQFHRIWKHZDUPDQGKXPLGDLU DVZHOODVGL൵HUHQWDSSURDFKHVWRGDWDSURFHVVLQJ masses of the Atlantic Ocean and Mediterranean sea including 3D and Geographical Information on the one hand and of the continental air masses of 6\ဧHPVVRIWZDUHZKHQFRPELQHGZLWKWKHJODFLDO Siberia, Central Asia and Iran mountainous regions. geomorphological method, allows obtaining and 7KH PRဧ LPSRUWDQW UROH LQ WKH IRUPDWLRQ RI WKH swiftly processing much better qualitative and climate of Caucasus ranges played by the Black and quantitative data. This methodology was used &DVSLDQ6HDV,QWHUPVRIVXFKGLYHUVL¿HGFOLPDWLF to calculate the morphometric properties of the conditions, the character of the modern glaciation is JODFLHUV UHဧRUH GRFXPHQW WKH G\QDPLFV RI WKHLU also diverse both, on the northern slope of Caucasus equilibrium line altitude and calculate a number of 5LGJHDQGLQWKHZHဧHUQHDဧHUQDQGFHQWUDOSDUWV glaciological parameters. of it. The principal regularities of the climatic It should be noted, that the method used by us conditions and modern glaciation are as follows: WR ဧXG\ WKH JODFLHUV IXUWKHU SURYLGHV LPSRUWDQW WKHDPRXQWRISUHFLSLWDWLRQVGHFUHDVHVIURPZHဧWR opportunities to calculate many such numerical HDဧDQGWKHLQÀXHQFHRIWKHFRQWLQHQWDODLUPDVVHV values, cannot be calculated by using the traditional LQFUHDVHVDQGWKHHTXLOLEULXPOLQHDOWLWXGH (/$ cartographic and geodetic methods or those of RI WKH JODFLHUV LQFUHDVHV WR P LQ:Hဧ remote sensing. CaucasusWRPLQ&HQWUDO&DXFDVXVDQG P LQ (Dဧ &DXFDVXV Objectives and methods Methods and materials Study Area GIS and Areal Mapping methods 7KH ဧXG\ DUHD FRYHUV WKH VRXWKHUQ VORSH RI Central Caucasus range:LWKLWVGLYHUVL¿HGFOLPDWLF 2QH RI WKH PRဧ FRQYHQLHQW PHDQV WR JDWKHU and relief conditions and compatibility between ဧRUHDQDO\]HDQGYLVXDOL]HWKHJHRVSDWLDOGDWDRI them and in respect of ongoing modern glaciation, GL൵HUHQW WKHPHV DQG VFDOHV LV ± WKH JHRJUDSKLFDO Caucasus is an VSHFL¿F geographical situation on the LQIRUPDWLRQ V\ဧHPV *,6 >@ ,Q FRPELQDWLRQ Eurasian Continent, as a transient hearth of modern with such methods, as remote sensing, unmanned 168 D. Svanadze et al. Annals of Agrarian Science 17 (2019) 167 – 174 Table 1.&RYHUDJHRIWKHDUHDVSKRWRJUDSKHGGXULQJWKH8$9ÀLJKW 6 2 Scale n, cm n, § sq.m. X;Y;Z; sq.m. orthophotom UAV flay date periglacial zone periglacial No.of points,10 No. of aerial photos aerial of No. Coverage area of an an of area Coverage Orthophotoresolutio Glacier and adjacent adjacent and Glacier Density of points per 1. Adishi 25/08/2017 1143 5.86 110.1 38 8.3 1:300 2. Khalde 30/08/2017 989 4.8 98.8 36 9.1 1:350 3. Shkhara 27/08/2017 818 3.9 92.7 36 8.1 1:400 4. Zopkhito 08/09/2017 914 3.31 107.4 40 7.59 1:300
DHULDOYHKLFOHZKLFKKDVEHHQH[WHQVLYHO\XVHGLQ P ZKDWZDVQHFHVVDU\LIFRQVLGHULQJWKHKLJK YDULRXV¿HOGVUHFHQWO\DQGH[SORUDWLRQRIWKHဧXG\ degree of dissection of the relief of the area, short REMHFW8QOLNHWKHWUDGLWLRQDOFDUWRJUDSKLFPHWKRGV ¿HOGVRIYLVLRQDQGSUHVHQFHRIEDUULHUVWRDYRLGD it provides good opportunities to obtain highly collision of the drone with the surrounding slopes accurate and thoroughly informative data, including or other relief forms. The technical parameters of 2D, 3D and 4D cartographic information. Data WKH8$9DUHOLPLWHG WKHPD[LPXPÀLJKWGXUDWLRQ SURFHVVLQJLVIDဧDQGPRဧRISURGXFWLRQSURFHVVHV ZLWKRQHWDNHR൵LVPLQXWHV LQFDVHRIDVOLJKW FDQEHDXWRPDWHG> @$WWKH¿UဧဧDJHDJHR wind, the duration of the battery operation reduces GDWDEDVH RI WKH ဧXG\ JODFLHUV ZDV FUHDWHG DQG WR§PLQXWHV$GURQHDOVRKDVVRPHKHLJKW LQWHJUDWHG LQ D VLQJOH FRRUGLQDWH VSDFH 870 OLPLWDWLRQVDQGLWFDQRSHUDWHDWPD[LPXPP :*6 =RQH 7KHGLJLWDO GDWD REWDLQHG IURP IURPWKHWDNHR൵SRLQW,WVKRXOGDOVREHQRWHGWKDWD the observations of the glaciers and their periglacial GURQHFDQEHXVHGPD[LPXPXSWRPDERYHVHD zones with an aerial vehicle and electronic and paper OHYHO%\FRQVLGHULQJDOOWKHDERYHOLဧHGOLPLWDWLRQV YHUVLRQVRIGL൵HUHQWSHULRGVDQGDYDLODEOHDUFKLYH WKHVXUYH\DUHDZDVGLYLGHGLQWRVHFWLRQVRI§NP2 material of remote sensing and cartography are îP IROORZLQJWKHÀLJKWVDIHW\SDUDPHWHUV LQFOXGHGLQWKLVGDWDEDVHဧUXFWXUH)RUWKHVDNHRI 6)LJ DQGWKHFRRUGLQDWHVRIWDNHR൵SRLQWVDQG thorough data integration, digital elevation models H[WUHPHSRLQWVRIWKHPLVVLRQVZHUHLGHQWL¿HGIRU ZHUHXVHG D WKURXJKWKHPDQXDOGLJLWDOL]DWLRQRI each zone to avoid the collision of the drone with FRQWRXUOLQHVRID VFDOHGWRSRJUDSKLFPDS the relief barriers. RIWKH6RYLHWSHULRGDQGE DGHWDLOHGUHOLHIPRGHO DFTXLUHGZLWKWKH8$90RGHUQLQIRUPDWLRQDERXW WKH ဧXGLHG JODFLHUV DQG RWKHU ¿HOG REVHUYDWLRQV ZHUHFROOHFWHGZLWKDQXQPDQQHGDHULDOYHKLFOH '-, 3KDQWRP3UR E\XVLQJÀLJKWFRQWURODQGSODQQLQJ software (Pix4D) 6HH 7DE The gained data were processed in theGlobal Mapp er and Esri ArcGIS software. The aerial Fig. 1. 3ODQRIDHULDOVXUYH\RIWKHJODFLDO survey of the glacier tongues and periglacial zones JODFLDO]RQHRIWKHJODFLHUVDQGÀLJKWPLVVLRQV UHIHUUHGLQWKHWDEOH VHHWDEOH ZDVGRQHLQ$XJXဧ D $GLVKLE 6KNKDUDF .KDOGHG =RSNKLWR and September of 2017. The aerial survey needs a SUHOLPLQDU\ဧXG\RIWKHဧXG\DUHDDQGHYDOXDWLRQ 7KH ÀLJKW ZDV GRQH DW P ÀLJKW OHYHO RI LWV SDUDPHWHUV $W WKH ¿Uဧ ဧDJH RI WKH ÀLJKW DERYHWDNHR൵DOWLWXGHIURPHDFKWDNHR൵SRLQW,Q planning, the relief of the territory was evaluated, addition, it is important to ensure a continuous radio WKHORQJLWXGLQDODQGODWHUDOSUR¿OHVZHUHGUDIWHGDW communication with the control panel. In order to WKHR൶FHE\XVLQJWRSRJUDSKLFPDSVGLJLWDOUHOLHI JDLQKLJKO\DFFXUDWH; < =FRRUGLQDWHVRIWKHဧXG\ PRGHOVDQGRWKHUDYDLODEOHLQWHUQHWVRXUFHV *RRJOH DUHD /$63RLQW&ORXG'DWD WKHFRYHUDJHRIWKH Earth, SRTM – Shuttle Radar Topography Mission photographs is desirable to vary from 60 to 80%
169 D. Svanadze et al. Annals of Agrarian Science 17 (2019) 167 – 174 GXULQJWKHÀLJKW,WLVWUXHWKDWWKLVZLOOUHGXFHWKH SRLQWV ; < = SHU VTXDUH PHWHU RQ WKH RQH KDQG photographing area to §2,5 km2, but it improves and on the other hand, what is no less important, WKH GDWD DFFXUDF\ LQ D WKUHHGLPHQVLRQDO VSDFH no matter how great the density of the survey of the &RYHUDJHRIHYHQLVVX൶FLHQWWRJHQHUDWHDQ WHUULWRU\DQGH[SORUDWLRQRIWKHWRSRJUDSKLFVXUIDFH orthophotowith the image quality quite satisfactory with the geodetic apparatus is, an aerial photo is for 2D GIS deciphering purposes. impossible to produce. Following the processing of WKHGDWDRI8$9XVHGE\XVGXULQJWKH¿HOGဧXG\ Parametersof the glaciers and their calculation /$6SRLQWFORXGGDWD ; < =DYHUDJHGHQVLW\RI points/m2 ZLWKKLJKDFFXUDF\PDQ\SDUDPHWHUVRI $JRRGLQGLFDWRULQWKHဧXG\RIJODFLHUVYDULDWLRQ a glacier dynamics were made possible to decipher is the location of the glacier tongue above the sea DQG FDOFXODWH )LJ %\ PDQXDO GLJLWDOL]DWLRQ level in altitude, time and space, variation of the DQG VHPLDXWRPDWLF SURFHVVLQJ RI WKH SRLQW FORXG glacier tongue and surface topography, formation LQ*OREDO0DSSHUVRIWZDUHPHGLDZHUHဧRUHGWKH of a moraine cover, its morphometry, etc. In the location of the glacier in the modern period and /LWWOH ,FH $JH SHULRG WKH PRUDLQH H[WHQW RI WKH Little Ice Age period, calculated the location of same period was well preserved in the periglacial the tongue above sea level in the Little Ice Age, zone of some valley glaciers, and they can be used indicators of the tongue retreat both, in length WR UHဧRUH WKH ORFDWLRQ RI D JODFLHU DQG YDULRXV DQG KHLJKW GHVLJQHG D KLJKUHVROXWLRQ DQG KLJKO\ morphometric indicators of the relevant period. The accurate relief model and its lateral and longitudinal advantage of the method lies in the possibility to SUR¿OHV E\ XVLQJ WKH PRGHUQ PHWKRGRORJ\ swiftly obtain and calculate a number of accurate ,Q WKH ဧXG\ RI JODFLHUV DORQJVLGH ZLWK WKH JODFLDOPRUSKRORJLFDO SDUDPHWHUV ZKDW LV RIWHQ *HRJUDSKLFDO,QIRUPDWLRQ6\ဧHPVZHXVHGOLWHUDU\ impossible by using traditional deciphering of VRXUFHV>@>@>@DQGPHWKRGRIRYHUOD\RIWKH FDUWRJUDSKLFDHULDOSKRWRVRULISRVVLEOHLVDODERU FDUWRJUDSKLFPDSV PDSVRIWKH5XVVLDQ FRQVXPLQJSURFHVV$VIRUWKHဧXG\RIWKHWHUULWRU\ (PSLUH DQGUHPRWHVHQVLQJDUFKLYHPDWHULDOV%\ ZLWKWKH¿HOGJHRGHWLFDSSDUDWXVLWVXVHLQWKHKLJK comparing the old and modern data, we obtained PRXQWDLQVLVTXLWHOLPLWHGDQGQHHGVH[WHQVLYHODERU numerical indicators, which thoroughly describe the 7ZRIDFWRUVDUHLPSRUWDQWLQWKLVUHVSHFW D8$9LV JODFLHUG\QDPLFVLQWKHODဧ\HDUV FDSDEOH RI SURGXFLQJ PD[LPXP FRRUGLQDWH
Fig. 2. *ODFLHU=LSNKLWR D /$6[ \ ]SRLQWFORXGGDWD EF JODFLHUWRQJXHG RUWKRSKRWRH HOHYDWLRQFRQWRXUVZLWKDP VSDFLQJI GLJLWDOUHOLHIPRGHO
170 D. Svanadze et al. Annals of Agrarian Science 17 (2019) 167 – 174 Results and analysis thickness at the same time. The variation of the parameters is associated with the process of the The analysis of the gained results evidences JODFLHUG\QDPLFV$VDQH[DPSOHZHFDOFXODWHGWKH that the glaciers on the southern slope of Caucasus FKDUDFWHULဧLF SDUDPHWHUV DQG WKHLU YDULDWLRQ IRURI rangeare in the phase of active diminution JODFLHUVLQWKHဧXG\IURPWKH/LWWOH,FH$JHWR GHPRQဧUDWHG E\ D VLJQL¿FDQW WRQJXH UHWUHDW PRGHUQ WLPHV 7DE increased altitude above sea level and decreased
Table 2.'\QDPLFVRIWKHJODFLHUWRQJXHVIURP/,$WRPRGHUQSHULRG yfggf p Tongue elevationin different Difference in the Average Total Retreat in periods, asl, m periods, m annualelevation elevation in 1820- change, m/yr 1820-2010- 2010-17 ,,,§ 17 ,,§ ,,,§- ,,§ ,,§ ,,,§- Glacier ,§ 1820 2010-
Type of glacier of Type 1960 2017 1960 1960 2017 2017
Shkhara Valley 2310.00 2490.00 2535.00 180.00 45.00 1.29 0.79 225.00 888.00 Guli Valley 2580.00 2800.00 2920.00 220.00 120.00 1.57 2.11 340.00 1081.00 Complex Ushba 2060.00 2380.00 2590.00 320.00 210.00 2.29 3.68 530.00 1243.00 valley Adishi Valley 2270.00 2380.00 2415.00 110.00 35.00 0.79 0.61 145.00 1326.00 Kibisha Cirque 3090.00 3190.00 3225.00 100.00 35.00 0.71 0.61 135.00 1359.00 Khalde Valley 2330.00 2500.00 2525.00 170.00 25.00 1.21 0.44 195.00 1542.00 Boko Valley 2285.00 2440.00 2637.00 155.00 197.00 1.11 3.46 352.00 1592.00 Nageba Valley 2170.00 2413.00 2550.00 243.00 137.00 1.74 2.40 380.00 1600.00 Tbilisa Valley 2540.00 2815.00 3010.00 275.00 195.00 1.96 3.42 470.00 1622.00 Marukhi Valley 2340.00 2400.00 2561.00 60.00 161.00 0.43 2.82 221.00 1734.00 Buba Valley 2400.00 2820.00 2950.00 420.00 130.00 3.00 2.28 550.00 1770.00 Kirtisho Valley 2320.00 2425.00 2618.00 105.00 193.00 0.75 3.39 298.00 2007.00 Suspended Mna 2660.00 2855.00 3050.00 195.00 195.00 1.39 3.42 390.00 2053.00 valley Shdavluri Valley 2320.00 2640.00 2720.00 320.00 80.00 2.29 1.40 400.00 2178.00 Gergeti Valley 2600.00 2930.00 3113.00 330.00 183.00 2.36 3.21 513.00 2187.00 Complex Tsaneri 2060.00 2280.00 2376.00 220.00 96.00 1.57 1.68 316.00 2203.00 valley Koruldashi Valley 2160.00 2480.00 2800.00 320.00 320.00 2.29 5.61 640.00 2249.00 Dolra Valley 2370.00 2540.00 2932.00 170.00 392.00 1.21 6.88 562.00 2338.00 Namkvami Valley 2460.00 2730.00 3023.00 270.00 293.00 1.93 5.14 563.00 2362.00 Complex Laila 2100.00 2220.00 2620.00 120.00 400.00 0.86 7.02 520.00 2467.00 valley Zopkhito Valley 2120.00 2480.00 2560.00 360.00 80.00 2.57 1.40 440.00 2603.00 Complex Chalaati 1620.00 1800.00 1940.00 180.00 140.00 1.29 2.46 320.00 2646.00 valley Complex Lekhziri 1780.00 1970.00 2224.00 190.00 254.00 1.36 4.46 444.00 3698.00 valley Complex Tviberi 2031.00 2140.00 2428.00 109.00 288.00 0.78 5.05 397.00 4096.00 valley Complex Kvishi 2300.00 2415.00 2780.00 115.00 365.00 0.82 6.40 480.00 4224.00 valley
Average 2291.0 2501.3 2684.1 210.3 182.8 1.5 3.2 393.0 2122.7
171 D. Svanadze et al. Annals of Agrarian Science 17 (2019) 167 – 174 2QHRIWKHPRဧLPSRUWDQWIDFWRUVFKDUDFWHUL]LQJ the glaciers elevation has increased from 1.5 to the variability of the glaciers is the variation of the 3.2 m since 1960s caused by the current climate altitude of the glacier tongues above sea level in FKDQJH DQG VXဧDLQDEOH WKHUPDO EDODQFH YDULDWLRQ time and space. We give the data about the tongue HဧDEOLVKHG RQ HDUWK$ ODUJHU UHWUHDW LV VHHQ ZLWK YDULDWLRQVRIJODFLHUVIRUWKUHHSHULRGVဧDUWLQJ WKH FRPSOH[ W\SHV RI YDOOH\ JODFLHUV 0Rဧ RI WKH WKH/,$ § WRWKHPLGGOHRIWKH;;FHQWXU\ JODFLHUV UHWUHDWHGZLWKLQWKHUDQJHRINP § DQGWKHPRဧUHFHQWPRGHUQSHULRG 6HH)LJ 7KHUHVSRQVHRIFRPSOH[YDOOH\JODFLHUV 5*REHMLVKYLOL>@JLYHVWKHDOWLWXGHVRIWKHWRQJXHV and large glaciers to the current climate changes is RI WKH ¿Uဧ DQG VHFRQG SHULRGV DERYH VHD OHYHO particularly worthwhile. The value of their retreat is $HURVSDFHSKRWRVDQGGLJLWDOUHOLHIPRGHO 6570 twice as much as an average value as a result of the RIGL൵HUHQWSHULRGV ZHUHXVHGWRREWDLQ glacier tongues descending to lower altitudes, their the contemporary data about the location of the SK\VLFDO FRQGLWLRQ PHFKDQLFDO GHဧUXFWLRQ ZDWHU glacier tongues and their altitudes. FXUUHQWVH[SRVLWLRQDQGLQÀXHQFHRIRWKHUIDFWRUV The data analysis has made it clear that the Average annual retreat of the considered glaciers is JODFLHUVFRQWLQXHDFWLYHUHWUHDWLQERWKPRဧUHFHQW P\UZKLOHWKLVLQGLFDWRUIRUFRPSOH[YDOOH\ SHULRGV DV FRPSDUHG WR WKH ¿Uဧ /,$ SHULRG ,I and large glaciers varies between 18 and 22 m/yr. during the LIA period, the location of the tongues of There is no doubt that the degradation of the glaciers the considered glaciers above sea level was 2291 m considered in the similar period did not take the RQDYHUDJHWKHVLPLODUGDWDLQWKH,,SHULRG V same pace and included the periods of short pauses, ZHUHPDQGPLQWKH,,,SHULRG 6HH7DEOH EXWLQWKH¿QDOUXQWKHUHWUHDWRIWKHJODFLHUVWRRND 7KHWRWDOGL൵HUHQFHLQHOHYDWLRQRIWKHJODFLHU KLJKSDFH>@>@,WLVWUXHWKDWWKHUHDUHFHUWDLQ tongues above sea level made 400 m. GL൵HUHQFHV¿[HGLQWKHDYHUDJHYDOXHVRIUHWUHDWRI The analysis of the table makes it clear that in JODFLHUVEXWLQWKLVFDVHWRRPRဧRIWKHP the considered period, an average annual value of UHWUHDWHGE\PRQDYHUDJH 6HH)LJ
Fig. 3. 3ODQRIORFDWLRQRIWKHJODFLHUV
Distribition of the density of total retreat of the tongues of glaciers 12 100.00% 90.00% 10 80.00% 70.00% 8 60.00% 6 50.00%
Density 40.00% 4 30.00% 20.00% 2 10.00% 0 0.00% [0-1000] [1001-2000] [2001-3000] [3001-4000] 4000 < Range, m
Fig. 4. 'LVWULEXWLRQRIWKHGHQVLW\RIWRWDOUHWUHDWRIWKHWRQJXHVRIJODFLHUVLQ§ 172 D. Svanadze et al. Annals of Agrarian Science 17 (2019) 167 – 174
Distribition of the density of average annual retreat of the tongues of glaciers 14 100.00% 90.00% 12 80.00% 10 70.00% 8 60.00% 50.00% 6 Density 40.00% 4 30.00% 20.00% 2 10.00% 0 0.00% 8 12162024 Average annual retreat, m
Fig. 5. . 'LVWULEXWLRQRIWKHGHQVLW\RIDYHUDJHDQQXDOUHWUHDWRIWKHWRQJXHV RIJODFLHUVLQ§
Conclusion References
,Q WKH PD[LPDO SKDVH RI WKH /LWWOH ,FH $JH >@ Meladze M., Meladze G., A trend of § WKHJODFLHUVZHUHLQWKHSHULRGRITXLWHDFWLYH increasingly frequent droughts in Kakheti irreversible degradation and melting evidenced by 5HJLRQ $QQDOV RI $JUDULDQ 6FLHQFH their gradual and swift retreat. Dynamics of melting of glaciers at southern slopes of the Greater Caucasus >@ Shahgedanova M., G. Nosenko G., Kutuzov S., is in direct proportion with current climatic cycles, O. Rototaeva O., Khromova T., Deglaciation of the Caucasus Mountains, Russia/Georgia, DWWKDWWKHVHSURFHVVHVDUHPRUHQRWLFHDEOHDWJRUJH LQ WKH ဧ FHQWXU\ REVHUYHG ZLWK $67(5 type glaciers. The reduction of the valley glaciers satellite imagery and aerial photography. The IRUWKHODဧ\HDUVKDVH[FHHGHGRIWKHWRWDO Cryosphere, 2014. DUHDRIWKHPD[LPDOSKDVHDQGဧLOOWDNHVDQDFWLYH >@ Beritashvili B. Climate and its change. course. If such trends continue without any changes, Georgian Technical University, Tbilisi, 2011 presumably the reduction of the large valley glaciers LQ *HRUJLDQ will reach 65% by 2100 what will presumably cause >@ *REHMLVKYLOL 5 6YDQDG]H ' /RPLG]H 1 the disappearance of small karr glaciers. These Dvalashvili G.,Dynamics of valley glacier in processes lead to the increase inequality in the WKH;,;;;,WKFHQWXULHVRQWKHVRXWKHUVORSH ZLWKLQ\HDU GLဧULEXWLRQ RI D K\GURORJLFDO ÀRZ RI RIWKHFHQWUDO&DXFDVXV ,Q*HRUJLDQ 7ELOLVL WKHPDMRUULYHUVLQWKHUHJLRQDQGJUHDWDPSOLWXGHV ,QဧLWXWH RI *HRJUDSK\ 3URFHHGLQJV , LQ GL൵HUHQW VHDVRQV $W WKDW LQFUHDVH LQ PHOWLQJ intensity predetermines the growth of intensity and >@ Maruashvili L. I., Phisical Geography of Georgia, IUHTXHQF\RIJODFLDOPXGÀRZIRUPDWLRQVLQFHWKH Monograph. Publ. house “Metsniereba”, Tbilisi, JODFLHUVZLWKဧDEOHEDODQFHFDUU\OHVVULVNRIJODFLDO LQ*HRUJLDQ PXGÀRZVDQGDEUXSWIUHVKHWV >@ *REHMLVKYLOL5/RPLG]H17LHOLG]H//DWH 3OHLဧRFHQH :XUPLDQ JODFLDWLRQV RI WKH &DXFDVXV LQ 4XDWHUQDU\ *ODFLDWLRQV ([WHQW Acknowledgment and Chronology, edited by: Ehlers, J. Gibbard, 3/ DQG +XJKHV 3'(OVHYLHU$PဧHUGDP The authors would like to thank to the Shota GRL % 5XဧDYHOL 1DWLRQDO 6FLHQFH )RXQGDWLRQ 6516) ; IRU WKH ¿QDQFLDO VXSSRUW JUDQW 3K')B >@ 7LHOLG]H /HYDQ :KHDWH 5RJHU 7KH *UHDWHU &DXFDVXV *ODFLHU ,QYHQWRU\ 5XVVLD *HRUJLD 173 D. Svanadze et al. Annals of Agrarian Science 17 (2019) 167 – 174 DQG$]HUEDLMDQ 7KH &U\RVSKHUH± >@ Eva Savina Malinverni, Claudia Croci and Fabrizio Sgroi laciers monitoring by remote sensing and GIS techniques in open source environment. Ancona: University Politecnica of Marche, Department DARDUS, Ancona, ,WDO\ ($56H/ 3URFHHGLQJV 132. > @ Bernd Resch, Florian Hillen, Andreas Reimer, Wolfgang Spitzer Towards 4D Cartography )RXUGLPHQVLRQDO '\QDPLF 0DSV IRU 8QGHUဧDQGLQJ 6SDWLRWHPSRUDO &RUUHODWLRQV in Lightning Events. Bernd Resch, Florian Hillen, Andreas Reimer, Wolfgang Spitzer. 7KH&DUWRJUDSKLF-RXUQDO >@ Oliver Wigmore, Bryan Mark. Monitoring WURSLFDO GHEULVFRYHUHG JODFLHU G\QDPLFV IURPKLJKUHVROXWLRQXQPDQQHGDHULDOYHKLFOH photogrammetry Cordillera Blanca, Peru., The &U\RVSKHUH >@ Podozerski K., Ledniki Kavkazskovo Khrebta, 7LÀLV =DSLVNL.DYNDVNRYRWGHOD,PSHUDWRUVRYR UXVNRYRJHRJUDSLKFKHVNRYRREVKHဧYR.QLMND ;;,; LQ5XVVLDQ >@ Tielidze L.,Modern and Old Glaciers of Georgia, Samshoblo, Tbilisi, 2016. >@ 5DGLP 6WXFKOtN =GHQČN 6WDFKRĖ 3HWU .XEtþHN8QPDQQHG$HULDO9HKLFOH±(൶FLHQW mapping tool available for recent research in polar regions. Brno : Department of Geography, Faculty of Science, Masaryk 8QLYHUVLW\ SS >@ Lambrecht. A., Mayer C., Hagg. W., 3RSRYQLQ95H]HSNLQ$/RPLG]H1DQG Svanadze. D., .A comparison of glacier melt RQGHEULVFRYHUHGJODFLHUVLQWKHQRUWKHUQDQG VRXWKHUQ&DXFDVXV7KH&U\RVSKHUH
174 F. Melnichuk et al. Annals of Agrarian Science 17 (2019) 175 – 179
Annals of Agrarian Science
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Neonicotinoids against sucking pests on winter wheat stands in the Forest-Steppe Zone of Ukraine Fedir Melnichuka, Larisa Melnichukb, Svetlana Alekseevaa, Michailo Retmanb, Oleksandra Hordiienkoa a,QဧLWXWHRI:DWHUSUREOHPVDQG5HFODPDWLRQ$FDGHP\RI$JULFXOWXUDO6FLHQFH1DXN\ဧU*RUD%RU\VSLOGLဧULFW Kyiv region, 08324, Ukraine b,QဧLWXWHRI:DWHU3UREOHPVDQG0HOLRUDWLRQRIWKH1DWLRQDO$FDGHP\RI6FLHQFHVRI8NUDLQHYXO9DV\ONLYVND Kyiv, 03022, Ukraine
Received: 25 June 2018; accepted: 29 November 2018
A B S T R A C T
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Keywords::KHDW6XFNLQJSHဧV$SKLGV%XJV,QVHFWLFLGHV&URS
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Introduction FHUHDOVLQ8NUDLQH>@6XFNLQJSHဧVDUHHVSHFLDOO\ dangerous. In particular, mass outbreaks of the In recent years, there has been a violation of the VXQQ SHဧ (XU\JDఅHU LQWHJULFHSV , wheat aphids, agricultural crops alternation in the crop rotation of WKULSV FLFDGDV FDXVH VLJQL¿FDQW GDPDJH RI ZLQWHU PRဧIDUPVZKHQRQHFURSLVJURZQLQWKHVDPH¿HOG wheat plants. This leads to a shortage or full loss of IRUWZRRUPRUH\HDUVLQDURZ,QWKH)RUHဧ6WHSSH JUDLQ\LHOG7KXVDFFRUGLQJWRWKH,QဧLWXWHRI3ODQW =RQHRI8NUDLQHDVLWXDWLRQLVFKDUDFWHUL]HGZKHQ Protection of the National Academy of Agrarian FURSV FRUQ VR\EHDQV VXQÀRZHU ZLQWHU UDSH 6FLHQFHVRI8NUDLQHGDPDJLQJWKHဧHPRIFXOWXUH ZLQWHUZKHDW SUHYDLOLQWKHIDUP,QVRPHFDVHVWKH ZLWKDVXQQSHဧFDQUHGXFH\LHOGE\>@ DUHDXQGHUWKHFRUQWDNHVXSRIWKHWRWDODUHD 1HZFKHPLFDOVDJDLQဧSHဧVDSSHDUHYHU\\HDU RIWKHSORZHGODQGRIWKHIDUP'XHWRWKHH[FHVVLYH LQ WKH 6WDWH OLဧ RI SHဧLFLGHV DQG DJURFKHPLFDOV saturation of the crop rotation with one culture, the authorized for use in Ukraine. With the IDYRUDEOH FRQGLWLRQV IRU WKH SHဧ SUROLIHUDWLRQ DQG implementation of modern agricultural technologies, WKHLQIHFWLRQVSUHDGDUHFUHDWHG>@ there is a tendency to increase the use of highly More than 360 species of insects and other animal H൵HFWLYH LQVHFWLFLGHV ZLWK ORZ DSSOLFDWLRQ UDWHV organisms, including nematodes, rodents, birds WKDWPLQLPL]HVWKHLULQÀXHQFHRQWKHHQYLURQPHQW and representatives of other fauna classes damage Preferably, these chemicals are from the group of 175 F. Melnichuk et al. Annals of Agrarian Science 17 (2019) 175 – 179 QHRQLFRWLQRLGVWKDWDUHKLJKO\H൵HFWLYHDJDLQဧSHဧV were used: Actara, 24% SC and Mospilan, 20% DQGDWWKHVDPHWLPHDUHORZWR[LFIRUWKHKXPDQV 63,QDGGLWLRQIRUWKHFRPSDULVRQRIH൶FDF\WKH DQG DQLPDOV >@ FRPSOH[ LQVHFWLFLGHV (QJHR 6& &RQQHFW Neonicotinoids are a relatively new class of 11,25% SC and Proteus 11% OD were used. In the insecticides. One of the success factors of these H[SHULPHQWVWKHZLQWHUZKHDWVRUW0\URQLYVND plant protection products is that their application was grown, the seed planting rate was 4,5 millions LV D൵HFWLQJ SHဧV ZLWK GHYHORSHG UHVLဧDQFH WR SHUKHFWDUH7KHVL]HRIWKHH[SHULPHQWDOSORWVLV insecticides from other chemical groups. The m2 [P UHSOLFDWLRQ±WLPHV$OORFDWLRQ prevalence of neonicotinoids is due to the variety of plots is randomized. RI PHWKRGV RI WKHLU DSSOLFDWLRQ VSUD\LQJ SUH 6FRUHV RI SHဧV VDPSOLQJ DQG DQDO\VLV ZHUH sowing seed treatment, introduction into irrigation carried out in accordance with generally accepted ZDWHULQGULSRULUULJDWHGV\ဧHPV ,QDGGLWLRQWKHVH PHWKRGV>@7KHQXPEHURIODUYDHDQGDGXOWLQVHFWV chemicals have opened new opportunities in the RI WKH VXQQ SHဧ ZDV FRXQWHG IRU P2, while the development of products for protection of seeds and LQVHFWV ZHUH FRXQWHG RQ WHဧ VLWHV RI [ FP VHHGOLQJV > @ P2 VL]H)RUWKHVFRUHVRIWKHWKULSVVSLNHOHWV The mechanism of action of neonicotinoids were selected in 10 places of the plot. Samples were VKRZV LWVHOI LQ GLဧXUEDQFH RI WKH FHQWUDO QHUYRXV placed in paper bags. Then the number of thrips and V\ဧHP RI LQVHFWV $FWLYH LQJUHGLHQWV DFW DV D their average number per spikelet was counted in FRPSHWLWRU WR DFHW\OFKROLQH RI WKH SRဧV\QDSWLF the laboratory. The score of the wheat aphids was PHPEUDQHUHFHSWRU,QWKLVFDVHH[FHVVLYHH[FLWDWLRQ FRXQWHGRQHDFKVLWHIRUဧHPV ဧHPVLQ RI WKH QHUYH FHOOV RFFXUV DQG WKHUHE\ GLဧXUEV WKH SODFHV LPDJRDQGODUYDHZHUHREVHUYHGRQOHDYHV normal conduction of the nerve impulse through the ဧDONVDQGVSLNHOHWV synapses, which is a consequence of a violation of the functional activity of the acetylcholine receptor. Table 1.7KHPDLQDFWLYHLQJUHGLHQWVRI As a result, convulsions and paralysis developed in QHRQLNRWLQRLGVLQ8NUDLQH LQVHFWVZKLFKOHDGVWRWKHLUPRUWDOLW\>@ Active ingredient Name of insecticide Manufacturer Rate of application In the Ukrainian market, insecticides from the Imidacloprid Confidor, 20% SL Bayer Ag, Germany 0,1-0,35 l/hɚ NIPPON SODA CO., Acetamiprid Mospilan, 20% SP 0,05-0,50 kg/hɚ JURXSRIQHRQLFRWLQRLGVDUHPRဧZLGHO\UHSUHVHQWHG LTD, Japan CalypsɨSC 0,15-0,30 l/hɚ Thiacloprid Bayer Ag, Germany Biscaya, 24% OD 0,20-0,40 l/hɚ on the basis of the following active ingredients: Syngenta Crop Protection Thiamethoxam Actara, 24 % SC 0,15-0,16 l/hɚ LPLGDFORSULG WKLDPHWKR[DP WKLDFORSULG DQG Ag, Switzerland DFHWDPLSULG 7DEOH 7KHLU FRPELQDWLRQV ZLWK pyrethroids are also used in order to increase their Research results H൵HFWLYHQHVVDJDLQဧFURSSHဧV (QJHR6& WKLDPHWKR[DP JO ODPEGDF\KDORWKULQ The occupation of winter wheat crops by JO %RUH\ 6& LPLGDFORSULG JO SHဧV ZDV GHWHUPLQHG IURP WKH WLOOHULQJ SKDVH ,Q ODPEGDF\KDORWKULQ JO &RQQHFW 6& the species composition of the aphids, the Grain LPLGDFORSULGJOEHWDF\ÀXWKULQJO DSKLG 6LWRELRQDYHQDH) ZDVPRဧFRPPRQWKH 3URWHXV2' WKLDFORSULGJOGHOWDPHWKULQ 6XQQ SHဧ ZDV GRPLQDWHG DPRQJ WKH VKLHOG EXJV JO ,QDVXPD:* DFHWDPLSULGJNJ 6FXWHOOHULGDH (XU\JDఅHU DXఅULDFD Schrank ODPEGDF\KDORWKULQ JNJ DQG RWKHUV occurs sporadically, $HOLDDFXPLQDWD L. and other 7KHUHIRUHLQWRRSWLPL]HZLQWHUZKHDW species of bugs were found. The number of larvae protection measures, a comparative assessment DQG LPDJR RI ZKHDW DSKLGV UHDFKHG RI WKH H൵HFWLYHQHVV RI QHRQLFRWLQRLGV DJDLQဧ WKH SODQW WKULSV ± VSLNHOHW LPDJR RI WKH 2 JURXS RI VXFNLQJ SHဧV VXQQ SHဧ ZKHDW DSKLGV 6XQQ SHဧ ± P during the observations WKULSV ZDVPDGHRQဧDQGVRIWKLVFURS EHIRUHWKHDSSOLFDWLRQRILQVHFWLFLGHVLQWKHHDUO\ PHGLXP PLON ဧDJH RI ZLQWHU ZKHDW The treatment of crops with insecticides Materials and methods contributed to a decrease of the occupancy of plants E\SHဧV 7DEOH 7KHKLJKHဧH൵HFWLYHQHVVDJDLQဧ )LHOG WULDOV ZHUH FDUULHG RXW LQ LQ 6XQQ SHဧ ZDV SURYLGHG E\ LQVHFWLFLGH (QJHR WKH.\LYUHJLRQFRQGLWLRQV)RULQYHဧLJDWLRQVWKH 24.7% SC. Thus, on average, on the 3rd day after its UHJLဧHUHGFKHPLFDOVIURPWKHQHRQLFRWLQRLGJURXS DSSOLFDWLRQWKHGHDWKRIWKLVSHဧUHDFKHGWR
176 F. Melnichuk et al. Annals of Agrarian Science 17 (2019) 175 – 179 and 100.0% – on the 7th and 14th day. Mospilan, 20% SP this indicator was only 94.4%. 2Q DYHUDJH RYHU WZR \HDUV WKH H൵HFWLYHQHVV During the research period it was found that of the Actara, 24% SC was 88.6% and 95.8% on WKHXVHRILQVHFWLFLGHVSURYLGHGKLJKH൵HFWLYHQHVV the 3rd and 7th day after spraying respectively. DJDLQဧ ZKHDW DSKLGV 7KHLU PRUWDOLW\ UDWH RQ WKH 6RPHZKDWORZHUZDVDQH൶FLHQF\RI3URWHXV 3rd day after application of the Mospilan, 20% SP OD, that on the 3rd day after spraying reached to was 85.4%, on other variants with insecticides it 86.9%, on the 7th – 89.7%. With the application UHDFKHG 2QWKHWKDQGWKGD\VWKH of insecticide Mospilan, 20% SP the mortality rate preparations Actara, 24% SC, Proteus 11% OD, of these phytophages was lower and reached only Connect 11,25% SC and Engeo 24.7% SC were DQG UHVSHFWLYHO\ 7DEOH PRဧH൶FLHQWVXSSO\WKHPRUWDOLW\RIZKHDWDSKLGV Also, on the 3rd day after spraying in the variant DW OHYHO ± with the insecticide Actara, 24% SC the population $W KDUYHဧLQJ LW ZDV IRXQG WKDW SURWHFWLRQ RI of larvae and imago thrips was decreased by 93,8%, winter wheat plants by spraying with insecticides and on the 7th day – by 99.1%. Application of the contributed to the preservation of quality indicators Mospilan, 20% SP ensured the mortality rate of these of the yield. So, the mass of 1000 grains in the phytophages on the 3rd day at the level of 88.2%, variant with Actara, 24% SC, Proteus 11% OD on the 7th – 93.0%. Insecticide Engeo 24.7% SC and Engeo 24.7% SC reached 46.3, 46.4 and 46.5 VKRZHGWKHH൵HFWLYHQHVVDJDLQဧWKHWKULSVVOLJKWO\ J UHVSHFWLYHO\ WKDW ZDV RQ J KLJKHU WKDQ higher, compared with the Actara, 24% SC. Thus, control. Application of the Mospilan, 20% SP and on the 3rd day after application of Engeo 24.7% SC Connect 11,25% SC provided the increasing of the the death of the thrips reached to 98.0%, on the 7th mass of 1000 grains up to 46.0 g, that was on 4.6 g GD\± 6RPHZKDWORZHUZDVDQH൶FLHQF\RI KLJKHU WKDQ WKH FRQWURO LQGLFDWRU 7DEOH Proteus 11% OD, that on the 3rd day after spraying The higher yield of wheat grain was obtained on reached to 96.2%, on the 7th – 98.2%. DOO YDULDQWV RI WKH H[SHULPHQW ZLWK DSSOLFDWLRQ RI At the observations on 14th day after spraying, insecticides, in comparison with the control. So, the WKH LQFUHDVLQJ RI WKH H൵HFWLYHQHVV RI LQVHFWLFLGHV yield on variants with the Actara, 24% SC, Proteus was noted. So, in variants with the use of Actara, 2'DQG(QJHR6&H[FHHGHGWKHFRQWURO 24% SC, Proteus 11% OD and Engeo 24.7% SC E\ DQGPWKDDQGE\PWKDLQ H൶FLHQF\ ZDV DOPRဧ WKH VDPH DQG UHDFKHG WR comparison with the variant with Mospilan, 20% SP ,QWKHYDULDQWZLWKWKHDSSOLFDWLRQRI and Connect 11,25% SC.
Table 2.7KHQXPEHURIZLQWHUZKHDWSHVWVLQWKHHDUO\PHGLXPPLONVWDJHRIZLQWHUZKHDW .\LYUHJLRQ
Number of pests before treatment Number of pests on … day after treatment Applicat 3rd 7th 14th ion rate, thrips wheat thrips wheat thrips wheat thrips wheat Variant Year Sunn pest, Sunn pest, Sunn pest, Sunn pest, kg larvae, aphids, larvae, aphids, larvae, aphids, larvae, aphids, exemplars/ exemplars/ exemplars/ exemplars/ (l)/hɚ exemplars exemplars exemplars exemplars exemplars exemplars exemplars exemplars m2 m2 m2 m2 /spikelet /plant /spikelet /plant /spikelet /plant /spikelet /plant 2016 7,8 27,0 50,0 8,0 32,5 68,0 8,3 44,5 96,5 8,5 51,8 134,3 Control - 2017 5,5 24,5 80,5 6,0 29,3 107,8 6,3 36,5 132,3 6,8 42,0 162,8 average 6,7 25,8 65,3 7,0 30,9 87,9 7,3 40,5 114,4 7,7 46,9 148,6 Actara, 2016 8,3 24,5 53,8 0,5 1,8 8,0 0,3 0,5 4,8 0,0 0,3 2,8 0,15 2017 5,3 23,3 76,5 1,0 2,3 10,0 0,3 0,3 5,3 0,3 0,5 2,3 24% SC average 6,8 23,9 65,2 0,8 2,1 9,0 0,3 0,4 5,1 0,2 0,4 2,6 Mospila 2016 7,5 24,3 52,5 2,0 3,3 13,3 1,0 2,3 11,0 1,0 2,0 6,5 n, 20% 0,12 2017 6,0 24,0 78,5 2,0 4,3 11,3 1,0 3,5 9,0 0,8 3,3 2,0 SP average 6,8 24,2 65,5 2,0 3,8 12,3 1,0 2,9 10,0 0,9 2,7 4,3 Engeo 2016 8,0 26,5 51,5 0,3 0,5 6,8 0,0 0,3 2,8 0,0 0,0 0,5 24.7% 0,18 2017 5,3 23,5 75,0 1,0 0,8 5,3 0,0 0,5 1,5 0,0 0,3 0,5 SC average 6,7 25,0 63,3 0,7 0,7 6,1 0,0 0,4 2,2 0,0 0,2 0,5 2016 8,0 27,0 53,0 0,8 1,5 7,4 0,5 1,2 3,9 0,3 2,0 2,0 Connect 0,5 2017 7,0 24,4 81,0 1,2 1,4 9,0 1,0 1,7 3,5 0,8 2,4 1,5 11,25% SC ɫɟɪɟɞɧɽ 7,5 25,7 67,0 1,0 1,5 8,2 0,8 1,5 3,7 0,6 2,2 1,8 2016 7,0 28,0 54,4 0,5 0,8 7,8 1,0 0,9 3,0 0,5 0,5 1,0 Proteus 1,0 2017 6,8 25,4 79,5 1,0 1,4 6,5 0,5 0,5 2,1 0,0 0,3 0,8 11% OD ɫɟɪɟɞɧɽ 6,9 26,7 67,0 0,8 1,1 7,2 0,8 0,7 2,6 0,3 0,4 0,9
177 F. Melnichuk et al. Annals of Agrarian Science 17 (2019) 175 – 179 Table 3.(৽FLHQF\RILQVHFWLFLGHVDJDLQVWZLQWHUZKHDWSHVWVLQWKHFRQGLWLRQV RIWKH&HQWUDO)RUHVW6WHSSHRI8NUDLQH .\LYUHJLRQ
Efficacy on … day after treatment, % Application Variant Year 3rd 7th 14th rate, kg (l)/hɚ Sunn pest thrips larvae wheat aphids Sunn pest thrips larvae wheat aphids Sunn pest thrips larvae wheat aphids
2016 93,3 95,0 87,3 96,2 99,0 94,6 100,0 99,5 97,8 Actara, 24% SC 0,15 2017 83,9 92,5 91,2 95,4 99,2 96,2 95,7 98,9 98,7 average 88,6 93,8 89,3 95,8 99,1 95,4 97,9 99,2 98,2 2016 76,0 90,9 79,5 88,4 95,3 88,0 88,7 96,5 94,9 Mospilan, 20% SP 0,12 2017 63,6 85,6 89,8 82,7 90,6 93,4 87,2 92,3 98,8 average 69,8 88,2 84,6 85,5 93,0 90,7 87,9 94,4 96,9 2016 96,2 98,5 89,7 100,0 99,3 97,0 100,0 100,0 99,6 Engeo 24.7% SC 0,18 2017 83,9 97,4 95,4 100,0 98,7 98,9 100,0 99,3 99,7 average 90,0 97,9 92,6 100,0 99,0 98,0 100,0 99,7 99,7 2016 89,7 95,4 88,5 93,8 97,3 95,7 96,4 96,1 98,4 Connect 11,25% SC 0,5 2017 74,5 95,2 91,6 79,8 95,4 97,3 85,0 94,3 99,1 average 82,1 95,3 90,0 86,8 96,3 96,5 90,7 95,2 98,7 2016 94,4 97,4 87,5 89,2 97,9 96,6 94,7 99,0 99,2 Proteus 11% OD 1,0 2017 79,4 95,0 94,0 90,2 98,6 98,4 100,0 99,3 99,5 average 86,9 96,2 90,8 89,7 98,2 97,5 97,4 99,1 99,4
SSD05 7,6 3,8 3,5 2,7 1,5 1,4 1,6 1,5 1,1
Table 4. Application rate, Mass of 1000 Variant Year Yield, WKɚ kg (l)/hɚ grains, g 2016 5,08 41,8 Control - 2017 4,46 41,0 average 4,77 41,4 2016 5,65 47,3 Actara, 24% SC 0,15 2017 4,81 45,3 average 5,23 46,3 2016 5,61 47,0 Mospilan, 20% SP 0,12 2017 4,79 45,0 average 5,20 46,0 2016 5,68 47,5 Engeo 24.7% SC 0,18 2017 4,82 45,5 average 5,25 46,5 2016 5,5 46,9 Connect 11,25% SC 0,5 2017 4,7 45,0 average 5,1 46,0 2016 5,6 47,3 Proteus 11% OD 1,0 2017 4,8 45,5 average 5,2 46,4 SSD05 0,38 3,9 178 F. Melnichuk et al. Annals of Agrarian Science 17 (2019) 175 – 179 Conclusions 1. Saturation of crop rotation with grain crops FRUQZLQWHUZKHDWEDUOH\ OHDGVWRWKHFUHDWLRQ of favorable conditions for the development of sucking phytophages and, accordingly, to LQFUHDVHWKHLUGHQVLW\RISRSXODWLRQ ODUYDHDQG LPDJRZKHDWDSKLGV SODQW WULSV VSLNHOHW LPDJR RI WKH 6XQ SHဧ P RQZLQWHUZKHDWဧDQGV 2. Preparations from the neonicotinoids group ZHUH KLJKO\ H൵HFWLYH DJDLQဧ VXFNLQJ ZKHDW SHဧV IRU ZHHNV 7KH PD[LPXP WHFKQLFDO H൶FLHQF\DJDLQဧWKHPZDVQRWHGLQWKHYDULDQW using insecticide Engeo 24.7% SC and reached 6RPHZKDWORZHUH൶FLHQF\ZDV VKRZQ E\$FWDUD &S DQG 3URWHXV 2' 7KH DSSOLFDWLRQ RI LQVHFWLFLGHV VLJQL¿FDQWO\ reduced the occupation of plants by aphids, WKULSV DQG 6XQ SHဧ UHVXOWLQJ LQ LQFUHDVHG wheat yield and a mass of 1000 grains. References [1] Petrukha O.I., Agrotechnics in the pests control, Sugar beets, 2 (1980) 29-31 (in Russian). [2] Strategy and Tactics of Plant Protection, Vol. 2, Tactics, Alfa-Steviya, Kyiv, 2015 (in Ukraine). [3] Sekun M.P. Hazardous sunn pest, Svit, Kyiv, 2002 (in Ukraine). [4] L. V. Ermolova, I. V. Lep'oshkin, I. V. Mudryy, Modern problems of toxicology, food and chemical safety, 4 (2004) 5-7. [5] Bazaka G. Ya., Dukhnytsky V., General characteristics of pesticides of the neonikotinoids group, Naukoviy Visnyk of LNUVMBT named after S. Z. Gzhytsky 15 # 1 (55) (2013) 3-9 (in Ukraine). [6] Sekun M. P., Neonicotinoids in agrarian production, Protection and quarantine of plants, 58 (2012) 180-191 (in Ukraine). [7] Sekun M.P. Zherebko V.M. et al., The Handbook of Pesticides, Kolobir, Kyiv, 2007 (in Ukraine). [8] Methods of Testing and Application of Pesticides, Svit, Kyiv, 2001 (in Ukraine). 179 Annals of Agrarian Science :ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ Determination of the ratio hematite/goethite by soil color Yu.N. Vodyanitskii Lomonosov Moscow State University. Faculty of Soil Science, 1, Leninskie gory, Moscow, 119234, Russia Received: 10 September 2018; accepted: 12 November 2018 A B S T R A C T 7KHFRQWHQWDQGFRPSRVLWLRQRIKHPDWLWHDQGJRHWKLWHFDQVROYHLPSRUWDQWWDVNVRIJHQHVLVDVZHOODVVRLOFODVVL¿FDWLRQ,WLVSURSRVHG DQHZPHWKRGRIGHWHUPLQLQJWKHLQGH[,Lab >+HPDWLWH +HPDWLWH*RHWKLWH @RQFRORUVRLOV\ဧHP&,(/ D E 7KHPHWKRGLVEDVHG RQFDOFXODWLQJVRLOV5HGQHVV 5HG DQGWKHQFDOFXODWLQJWKH,Lab, based on reference Red of hematite and goethite. Replacement of Fe3+ to Al3+LVWDNHQLQWRDFFRXQWWKURXJKDPHQGPHQWVWRWKHFRORURIJRHWKLWHDGPLWWLQJWKDW$OKHPDWLWHFRORUGRHVQRWGL൵HUIURP color pure hematite. The new technique was proven on Northern Italy andosols and was give results similar to results, received for FRQYHUWLQJRSWLFDOVSHFWUXPRQ.XEHOND0XQNWKHRU\%XWWKHQHZWHFKQLTXHKDVWKHDGYDQWDJHRIHDVHRIFDOFXODWLRQDQGWKHDELOLW\ WRXVHWKHROGFRORUGDWDREWDLQHGLQWKH0XQVHOOV\ဧHP9DOLGDWLQJQHZPHWKRGVLQOXYLVROVLVVKRZHGDQDJUHHPHQWLQGH[YDOXHV,Lab ZLWKUHDO>+HPDWLWH +HPDWLWH*RHWKLWH @LQWKRVHSDUWVZKHUHWKHUHDUHSUR¿OHKDYHSXUHKHPDWLWHDQGJRHWKLWH,QOXYLVROVFRQWDLQLQJ $OJRHWKLWHDQG$OKHPDWLWHDGPL[WXUH$OJHQHUDWHVDQHUURULQWKHFDOFXODWLRQ7RGHOHWHWKHHUURULWLVSURSRVHGDQDPHQGPHQWWR WKHGLဧRUWLQJH൵HFWVRIDOXPLQXPLQODWWLFHJRHWKLWHHZLWKKLJKFRQWHQW PROH$O&DPELVROVKDYHDYDOXHLQGH[,Lab also vary depending on the impurities Al in hematite and goethite. From samples with particles of pure goethite Red higher than cambisols FRQWDLQLQJ$OJRHWKLWH$IWHUDGMXဧPHQWIRUWKH$OVKDUHLQJRHWKLWHWKHVKDUHRIKHPDWLWHEHFRPHVFRPSDUDEOHWRLWVVKDUHLQWKH cambisols samples with pure goethite. Keywords:+HPDWLWH*RHWKLWH/XYLVRLOV&DPELVROV*HQHVLV*HRFKHPLဧU\ &RUUHVSRQGLQJDXWKRU Introduction ratio hematite/goethite to determine a soil evolution KLဧRU\+XJHVLJQL¿FDQFHIRUJHRFKHPLဧU\KDV)H +HPDWLWH Į)H O DQG JRHWKLWH Į)H22+ DV WKH 2 3 VXEဧLWXWLRQIRU$OLQWKHODWWLFHRIWKHVHPLQHUDOV PRဧ ဧDEOH )H K\GU R[LGHV IRUPV DUH ZLGHO\ SDUWLFXODUIRUJRHWKLWH)RUH[DPSOHWKHGHJUHHRI GLဧULEXWHGLQVRLOVRIGL൵HUHQWJHQHVLVDQGDJH7R VXEဧLWXWLRQ RI DOXPLQXP DVVRFLDWHG ZLWK DJH RI WKHJUHDWHဧH[WHQW)H K\GU R[LGHVDUHFRQFHQWUDWHG DOOXYLDOVRLOV 9LFWRULD$XဧUDOLD >@,QWKHPRUH LQ WKH R[LVROV DQG FDPELVROV >@ DQG DOVR ± LQ ancient soils with age 760 thousand years Al content PDQ\ ORHVV VRLOV > @ &RQWHQW RI KHPDWLWH DQG ZDVKLJKHU PRO WKDQLQ\RXQJVRLOVZLWKDJH goethite is useful to solve important tasks of genesis ~ 40 thousand years, where the Al contents was only DQG FODVVL¿FDWLRQ IRU H[DPSOH WR GLဧLQJXLVK PRO7KHUHDUHRWKHULPSRUWDQWGL൵HUHQFHV EHWZHHQ R[LVROV DQG FDPELVROV >@ in the content of aluminum in soils with goethite of $W WKH VDPH WLPH JHQHVLV DQG JHRFKHPLဧU\ GL൵HUHQWJHQHVLV&RPSDULVRQRIWKHSURSRUWLRQRI RI WKHVH Į)HPLQHUDOV DUH YDULHV FRQVLGHUDEO\ $O LQ JRHWKLWH RI DOIHVROV ,QGLDQD 8QLWHG 6WDWHV So, goethite is formed in acidic environment and DQG R[LVROV *R\D %UD]LO VKRZHG D ဧDWLဧLFDOO\ in conditions of high humidity and moderate VLJQL¿FDQW GL൵HUHQFH 2[LVROV JRHWKLWH LV FRQWDLQ temperature, whereas hematite is formed in PROH$OZKHUHDVDO¿VROVJRHWKLWH±RQO\ neutral conditions and with low humidity and high PROH$O>@ WHPSHUDWXUH>@7KLVRSHQVXSRSSRUWXQLWLHVWRWKH 180 Į)H2O3 DQG \HOORZ JRHWKLWH Į)H22+ ,W LV DVNHG in soil samples, with modern spectrophotometer a few techniques using optical spectrum of soil to LVVXLQJWKHUHVXOWLPPHGLDWHO\LQWKH&,(/ D E determine the hematite and goethite share. The end 5DWLR>+HPDWLWH +HPDWLWH*RHWKLWH @LVFDOFXODWHG UHVXOW RI WKH DQDO\VLV LV XVXDOO\ H[SUHVVHG DV WKH RQQHZPHWKRGVOHWWKHLQGH[RI,Lab. UDWLR>+HPDWLWH +HPDWLWH*RHWKLWH @/HWXVQDPH 7KH REMHFWLYH RI WKLV ဧXG\ WR SURSRVH D QHZ WKLVUDWLRDVLQGH[, method for determining the ratio hematite/goethite 2SWLFDOPLQHUDORJLFDO PHWKRGV RI DQ LQGH[ E\WKHVRLOFRORULQWKH&,(/ D E V\ဧHP I determination is based on the ratio of red and \HOORZSDUWVRIWKHVRLOVSHFWUXP7KHPRဧFRPPRQ Objects technique is based on converting optical soil VSHFWUXP XVLQJ HTXDWLRQV RI .XEHOND0XQN > :HDUHDQDO\]HG)H K\GU R[LGHVXVLQJGDVKERDUGV @7KHQDQHZVSHFWUXPLVGL൵HUHQWLDWHGWZLFH 6KHLQRဧ DQG 6FKZHUWPDQQ > @ RQ UHIHUHQFH DQGFRPSDUHVWKHDPSOLWXGHVRIWZRUHÀH[HV VDPSOHV K\GU R[LGHV RI LURQ Q $PRQJ WKHP KHPDWLWHĮ)H O PDJKHPLWHȖ)H O , goethite nm for hematite and 413 nm for goethite. Attitude 2 3 2 3 >+HPDWLWH +HPDWLWH*RHWKLWH @FDOFXODWHGE\WKLV Į)H22+ OHSLGRFURFLWH Ȗ)H22+ IHUULK\GULWH . . 2Fe2O3 FeOOH 4H22 DQG IHUR[\KLWH į)H22+ PHWKRG DUH GHQRWHG E\ LQGH[ ,.0. This method can serve as a benchmark in determining the ratio 7KHLUFRORULPHWULFFKDUDFWHULဧLFVLQWKHVRXUFHZHUH of hematite and goethite on optical spectra of H[SUHVVHGLQ0XQVHOOZHFRXQWHGWKHPLQ&,(/DE soil. Disadvantage: the complicated procedure is V\ဧHP requirement to use a computer programs. 7RFRPSDUHWZRPHWKRGV ZLWKWKHFRQYHUVLRQ At present, the color of the soil is characterized RIRSWLFDOVSHFWUXPDFFRUGLQJWRWKH.XEHOND0XQN PDLQO\ E\ WZR RSWLFDO V\ဧHPV HDUOLHU 0XQVHOO IXQFWLRQV DQG QHZ WHFKQLTXHV ZH ZHUH XVHG V\ဧHP DQG PRUH PRGHUQ V\ဧHP RI &,(/ D E the color data of modern andosols and paleosols in >@0XQVHOOFRORUSRLQWLVGH¿QHGE\WKUHH 1RUWKHUQ,WDO\>@ FKDUDFWHULဧLFV +XH + 9DOXH 9 DQG&KURPD & Basic researches are devoted to the analysis Because no equivalent perception of light and dark of luvisols of southern Spain, the source data is FRORUWRQHVDOOF\OLQGULFDOFRORUVSDFHLV¿OOHG SXEOLVKHGLQ>@,QDGGLWLRQUHVHDUFKHVDUHGHYRWHG ,QWKH&,(/ D E V\ဧHP / LVFRRUGLQDWHVHW our data on color of cambisols from Lithuania, and RIOLJKWQHVV YDULHVIURPWRIURPWKHGDUNHဧ $UNKDQJHOVN3HUPDQG9RORJGDUHJLRQV 5XVVLD WR WKH OLJKWHဧ FKURPDWLF FRPSRQHQW LV GH¿QHG E\WZR&DUWHVLDQFRRUGLQDWHVD DQGE 7KH¿Uဧ Methods coordinate is indicated the position of the colors 7KH PHWKRGRORJ\ RI FDOFXODWLQJ WKH UDWLR RI UDQJH IURP JUHHQ D WR WKH UHG D DQG WKH KHPDWLWHJRHWKLWHE\WKHVRLOFRORULQWKH&,(/DE VHFRQGLVUDQJHGIURPEOXH E WR\HOORZ E > 6\అHP)LUဧRIDOOWKHPLQHUDOVFRORULWLVQHFHVVDU\ @&RRUGLQDWHVD DQGE DUHGLဧLQJXLVKHGFOHDUO\ WR H[SUHVV RQH QXPEHU FRQWULEXWLRQRI)HPLQHUDOVWRWKHVRLOFRORU $VFDQEHVHHQIURPWKHWDEOH)HPLQHUDOVLV 6LQFH RUWKRJRQDO &,(/ D E V\ဧHP LV PXFK VKRZQUHGQHVV D DQG\HOORZQHVV E DOWKRXJKLQ EHWWHU WKHQ FRQYHQLHQW F\OLQGULFDO 0XQVHOO V\ဧHP GL൵HUHQWSURSRUWLRQV7KHUDWLREHWZHHQWKHUHGQHVV 181 Table 1. )H K\GU R[LGHVFRORUH[SUHVVHGLQ0XQVHOOV\VWHPDQG&,(/ D E V\VWHP 7KHRULJLQDOGDWDLQWKHSDSHU> @ Ɇɢɧɟɪɚɥ Munsell CIE-L*a*b* L* ɚ b* Red Hematite 1.2 YR 3.6/5.2 36.6 20.9 20.4 0.51 Feroxyhite 4.2 YR 3.8/6.0 38.7 19.1 29.3 0.39 Ferrihydrite 6.6 YR 4.9/6.3 50.0 15.4 34.9 0.31 Maghemite 8.3 YR 3.1/3.2 31.4 7.4 18.0 0.29 Lepidocrocite 6.8 YR 5.5/8.2 56.1 18.5 46.4 0.28 Goethite 0.4 Y 6.0/6.9 61.0 8.2 44.1 0.16 182 0XQNHTXDWLRQV ,.0 DQGEDVHGRQ&,(/ D E V\VWHP7KHRULJLQDOGDWDLVLQWKHSDSHU>@ Sample Munsell CIE-L*a*b* ILab IK-M (depth, cm) L* ɚ b* RedLab RS-A (0-20) 9.6 YR 5.5/3.6 56.7 6.8 25.7 0.21 0.14 0.07 RS-Bw1 (20- 9.6 YR 5.4/3.5 56.7 4.6 18.7 0.20 0.11 0.10 40) RS-C1 (80-100) 9.3 YR 7.0/3.7 71.6 5.8 26.1 0.18 0.06 0.09 I-1 (280-300) 8.9 YR 5.6/4.0 56.7 6.8 24.4 0.22 0.17 0.08 II-1 (460-480) 0.3 Y 6.9/3.8 71.6 4.5 27.1 0.14 0.00 0.00 III-1 (840-860) 9.5 YR 6.5/4.0 66.6 5.4 25.1 0.18 0.06 0.04 III-3 (92-940) 9.8 YR 6.8/4.0 71.6 4.5 25.9 0.15 0.00 0.02 IV-1 (1000- 0.1 Y 6.7/4.1 66.7 4.0 26.1 0.13 0.00 0.01 1020) IV-3 (1040- 9.6 YR 6.6/3.8 66.7 5.4 25.1 0.18 0.05 0.03 1060) IV-4 (1060- 9.4 YR 6.3/3.9 66.7 5.4 25.1 0.18 0.05 0.06 1080) Average 0.06± 0.05± 0.02 0.01 Results and discussion WKH RSWLFDO H൵HFW RI WKH$O SUHVHQFH LQ WKH ODWWLFH of goethite is higher than from its iron replacement Relationship between Hematite and Goethite in hematite. The minerals iron impurities are not in luvisols SUHVHQWDWWKHSUR¿OHERWWRP /HW XV FRPSDUH WKH FDOFXODWHG YDOXH LQGH[ , 7KHPDLQIHDWXUHRIOXYLVROVLVWKHWH[WXUHSUR¿OH Lab GL൵HUHQWLDWLRQ FOD\ DFFXPXODWHV LQ WKH KRUL]RQ ZLWKUHDODWWLWXGH>+HPDWLWH +HPDWLWH*RHWKLWH @ argic, its color ranges from brown to red, depending $VFDQEHVHHQIURPWDEOHDWWKHSUR¿OHVERWWRP RQWKHFRPSRVLWLRQRIWKH)H K\GU /XYLVROVDUH where there are pure hematite and goethite, DOPRဧ IRU DOO VDPSOHV , § >+HPDWLWH +HPDWLWH KROGHG PLOOLRQ +$ LQ WKH ZRUOG PDLQO\ Lab LQ VXE WURSLFDO UHJLRQV >@ :H ZHUH DQDO\]HG *RHWKLWH @7KLVPHDQVWKDWWKHRSWLFDOSURSHUWLHV WZR UHGEURZQ FRORU OXYLVROV SUR¿OHV 5% DQG of goethite and hematite in luvisols are close to 02 LQWKHSURYLQFHRI&RUGREDLQVRXWKHUQ6SDLQ ဧDQGDUG PLQHUDOV RQ 6KHLQRဧ DQG 6FKZHUWPDQQ GHVFULEHGLQ>@,URQPLQHUDOVDUHSUHVHQWHGLQWZR > @$QRWDEOHGHYLDWLRQLVREVHUYHGRQO\VDPSOH RQO\02ZKHUH, ZKHUHDV>+HPDWLWH FRORU UHG KHPDWLWH DQG $O KHPDWLWH DQG \HOORZ Lab JRHWKLWHDQG $O JRHWKLWH,QWKHXSSHUSDUWRIWKH +HPDWLWH *RHWKLWH @ (PSLUH VKDUH ERWKSUR¿OHVLQ)HPLQHUDOVSDUWRI)H3+ is replaced KHPDWLWH ZKHQFDOFXODWLQJE\FRORU REYLRXVO\LV by Al3+5HSODFLQJLVH[WHQWOHVVHU WRPROH$O GXHWRWKHLQFUHDVHGUHGQHVVUHDO)HPLQHUDOVLQWKH LQWKHLURQKHPDWLWH DQGWZLFHဧURQJHU XSWR VDPSOH 02 FRPSDUHG ZLWK UHIHUHQFH PLQHUDOV PROH$OUHSODFHVLQJRHWKLWH ,WLVREYLRXVWKDW 183 Sample Al- Al-he- IMansellL*ɚ b* Red ILab ǻ5HG goe- matite, (depth, cm) thite, % % Profile RB RB-11(22-45) 1.65 2.80 0.63 7.5 YR 61.1 8.4 22.3 0.27 0.33 0.11 6/4 RB-12 (45-70) 2.25 3.10 0.58 8 YR 7/4 70.9 7.2 23.2 0.24 0.23 0.12 RB-13 (70- 2.80 2.80 0.50 7.5 YR 70.9 7.9 22.6 0.26 0.28 0.07 105) 7/4 RB-14(105- 2.20 3.75 0.63 8 YR 7/5 70.9 9.0 29.0 0.24 0.23 0.14 130) RB-15*(130- 4.90 1.65 0.25 8 YR 7/5 70.9 9.0 29.0 0.24 0.23 155) RB-16 (155- 4.95 0.90 0.15 9 YR 8/3 80.5 3.8 18.6 0.17 0.03 170)* RB-17(170- 4.35 - 0.00 1 Y 8/2 80.5 0.8 14.0 0.05 0.00 190)* RB-18(190- 3.60 - 0.00 2 Y 8/1.5 80.5 0.0 10.9 0.00 0.00 230)* RB-19(230- 4.40 - 0.00 2 Y 8/2 80.5 0.0 14.6 0.00 0.00 260)* RB-20(260- 4.15 - 0.00 10 YR 80.5 1.6 13.4 0.11 0.00 300)* 8/2 Profile MO ɆɈ-1 (0-8) 1.95 3.95 0.67 6 YR 6/5 61.0 12.2 26.3 0.32 0.46 0.07 ɆɈ-2 (8-50) 2.10 4.10 0.66 6 YR 7/6 70.9 13.8 32.0 0.30 0.40 0.09 ɆɈ-3 (50-65) 1.50 4.80 0.76 5 YR 6/6 61.0 15.8 30.6 0.34 0.52 0.09 ɆɈ-4 (65-75) 1.50 3.20 0.68 6 YR 7/5 70.9 11.6 26.4 0.31 0.43 0.09 ɆɈ-5 (75- 1.40 3.00 0.68 7 YR 7/4 70.9 8.4 22.1 0.27 0.31 0.13 100) ɆɈ-6 (100- 3.10 - 0.00 7.5 YR 70.9 6.0 16.9 0.26 0.23 145)* 7/3 ɆɈ-7(145- 2.80 - 0.00 10 YR 80.5 1.6 13.4 0.11 0.00 180)* 8/2 * – goethite and hematite without Al. 184 RIWKHFKHPLFDOFRPSRVLWLRQRI)HPLQHUDOVLVOHDG (YHQ ZLGHU UDQJH LQGH[ YDOXHV ,Lab: from 0.07 to WRKHDY\GLဧRUWLRQRIWKHUHVXOWVRIFDOFXODWLRQRI 0.69. Such a large spread of optical indicators is ILabLQGH[,QIDFWLQWKHVDPSOHVSUR¿OH5%VKDUH indicated heterogeneity sampling. $OKHPDWLWH IURP LWV DPRXQW ZLWK $OJRHWKLWH LV $ SRVVLEOH UHDVRQ LV WKH GL൵HUHQFH LQ WKH UHDFKHVZKLOHWKHLQGH[FDOFXODWLRQEDVHG chemical composition of goethite in cambisols. on sheer colors ILAB goethite is show the proportion Indeed, eight samples have pure goethite and four RIKHPDWLWHRQO\,WLVFOHDUWKDWWKHHUURULV samples is composed goethite with part of Fe3+ REOLJHGWRLPSXULWLHV$OLQ)HPLQHUDOVEHFDXVHWKH VXEဧLWXWHGIRU$O3+, these two groups are varying calculation is based on optical reference analysis, in their optical properties. As can be seen from pure particles of hematite and goethite. To correct the table 4, cambisols with pure goethite have DPLဧDNHZLOOPDNHDQDPHQGPHQWWRWKHGLဧRUWLQJ high Red = 0.33 ± 0.02, and the ILabLQGH[ H൵HFWVRIDOXPLQXPRQWKHFRORURIJRHWKLWHZLWK ± 0.05, that is 50% of hematite. The indicators of 0ROH $O 7R D ¿Uဧ DSSUR[LPDWLRQ WKH VRLO FRQWDLQLQJ $OJRHWKLWH VLJQL¿FDQWO\ EHORZ LQÀXHQFHRIDOXPLQXPRQWKHFRORURIKHPDWLWH Red = 0.22 ± 0.02, and the proportion of 17% total PROH$O QHJOLJLEOHOHWXVOLPLWHGWRWKHLQÀXHQFH hematite: ILab 'L൵HUHQFHRIERWKVRLO of Al on the color of the goethite only. groups is authentically P 95. /HW XV FDOFXODWH WKH YDOXH VRLO UHGXFWLRQǻ5HG Make amendments in color of cambisols with GXHWRWKHLQÀXHQFHRI$ORQWKHFRORURIJRHWKLWH $OJRHWKLWH7RGRWKLVZHZLOOXVHWKHGDWDDERXW proceeding from the real relationship between the average reduction Red previously received for $OKHPDWLWH DQG $OJRHWKLWH 7R GR WKLV ZH DUH OXYLVROV ǻ5HG ,Iǻ5HG WR DGG WKH WUDQVIRUPWKHHTXDWLRQ DQGPDNHLWUHDOUHODWLRQ FDPELVROV FRQWDLQLQJ$OJRHWKLWH WKH LQGH[ YDOXH , >+HPDWLWH +HPDWLWH*RHWKLWH @ 5HGXFWLRQ RI ZLOOLQFUHDVHVLJQL¿FDQWO\,Lab WDEOH $VDUHVXOW VRLOǻ5HG ZLOO EH FDOFXODWHG IURP WKH HTXDWLRQ the average value of the ILab team cambisols with $OJRHWKLWHZLOOLQFUHDVHG ,/DE &RUUHFWHG = 0.45 ± 0.06. ǻ5HG ±ɯ^±>+HPDWLWH Now the I/DE &RUUHFWHG LQGH[RIWZRVDPSOHVLVPDWFKHG +HPDWLWH*RHWKLWH @`±5HG XSDQGWKHLUGL൵HUHQFHEHFRPHVXQUHOLDEOHDW3 Thus, the amendment on Al in goethite gives 7KHYDOXHRIǻ5HGIRUOXYLVROVZLWK$OJRHWKLWH more similar picture: 45% of hematite in the same DUH OLဧHG LQ WDEOH 7R 5% SUR¿OH ǻ5HG YDOXHV VHULHVDVWKDWGHVLJQVFDPELVROVZLWKSXUHÀRFNLQJ UDQJLQJIURPWRRQDYHUDJHǻ5HG WR 02 SUR¿OHǻ5HG YDOXHV UDQJLQJ IURP WR DYHUDJH ǻ5HG *HQHUDOL]HG DYHUDJH Conclusion ǻ5HG LV 7KXV$O LQ JRHWKLWH LV XQGHUဧDWHV WKHOXYLVROV5HGRQDYHUDJH7KLVǻ5HGFDQEH ,QGH[ , >+HPDWLWH +HPDWLWH*RHWKLWH @ LV XVHGIRUFRUUHFWLRQRI$OLQÀXHQFHRQJRHWKLWHFRORU ZLGHO\ XVHG LQ WKH ဧXG\ RI WKH JHQHVLV DQG VRLO LQVRLOVFRQWDLQLQJJRHWKLWHZLWKPROH$O FODVVL¿FDWLRQ ,Q DGGLWLRQ WR WKH PLQHUDORJLFDO LW LV NQRZQ WKH RSWLFDO PHWKRG RI REWDLQLQJ , LQGH[ XVLQJ .XEHOND0XQFK HTXDWLRQ :H DUH SURSRVHG The ratio hematite/goethite in cambisols a simpler method of determining ILabLQGH[RQVRLO &KDUDFWHULဧLFV RI FDPELVROV DUH KHDY\ WH[WXUH FRORU XVLQJ WKH RSWLFDO &,(/ D E V\ဧHP 7KH and a reddish tone, with a low content of iron PHWKRGLVEDVHGRQFDOFXODWLQJVRLOV5HGQHVV 5HG FRPSRXQGV >@ 6LQFH XVXDOO\ ɫDPELVROV LV and then calculating the ILab, based on reference Red 185 Horizon Fe-minerals FeTot FeDCB L* ɚ b* Red ILab ILab- corr (depth, cm) % % Pinega district, Arkhangelsk, Russia BM (7-16) Hematite, goethite 2.41 1.29 60.3 14.5 26.3 0.35 0.55 B (16-24) Hematite, goethite 3.65 2.22 57.8 16.8 25.2 0.40 0.69 DCa (44-62) Hematite, goethite 1.00 0.48 71.9 12.0 30.4 0.28 0.35 Perm district, Russia AY (7-12) Hematite, goethite 4.18 1.57 58.9 11.1 24.7 0.31 0.43 B1 (19-36) Hematite, goethite 5.29 2.00 57.6 15.4 25.8 0.37 0.61 B2 (36-56) Hematite, goethite 5.34 2.20 56.6 15.8 24.9 0.39 0.65 Zarasai district, Lithuania PYg (0-10) Hematite, Al- 1.42 66.2 8.0 29.3 0.21 0.16 0.43 goethite B1Ca (40-50) Hematite, goethite 1.09 67.9 11.3 29.0 0.28 0.35 BCCa (80- Hematite, goethite 0.49 68.8 11.9 30.0 0.28 0.35 100) Cherepovez district, Vologda, Russia PY (0-20) Hematite, Al- 0.77 62.7 5.4 21.8 0.20 0.11 0.40 goethite B (31-52) Hematite, Al- 0.48 75.3 6.7 29.8 0.18 0.07 0.34 goethite C (66-85) Hematite, Al- 1.18 63.0 11.3 28.8 0.28 0.35 0.63 goethite FeTot – total content Fe in soil, FeDCB±)HH[WUDFWHGZLWK'&%,/DEFRUU– ILabLQGH[DIWHUFRUUHFWLRQ for Al in goethite. of hematite and goethite. Replacement of Fe3+ to Al3+ SUR¿OHKDYHSXUHKHPDWLWHDQGJRHWKLWH,QOXYLVROV is taken into account through amendments to the FRQWDLQLQJ $OJRHWKLWH DQG $OKHPDWLWH DGPL[WXUH FRORU RI JRHWKLWH DGPLWWLQJ WKDW$OKHPDWLWH FRORU Al generates an error in the calculation. To delete the GRHV QRW GL൵HU IURP FRORU SXUH KHPDWLWH HUURULWLVSURSRVHGDQDPHQGPHQWWRWKHGLဧRUWLQJ Thus, the new technique was proven on Northern H൵HFWV RI DOXPLQXP LQ ODWWLFH JRHWKLWH HZLWK KLJK Italy andosols and was give results similar to FRQWHQW PROH$O &DPELVROV KDYH D YDOXH results, received for converting optical spectrum on LQGH[ ,Lab also vary depending on the impurities .XEHOND0XQNWKHRU\%XWWKHQHZWHFKQLTXHKDVWKH Al in hematite and goethite. From samples with advantage of ease of calculation and the ability to use particles of pure goethite Red higher than cambisols WKHROGFRORUGDWDREWDLQHGLQWKH0XQVHOOV\ဧHP FRQWDLQLQJ $OJRHWKLWH $IWHU DGMXဧPHQW IRU WKH 9DOLGDWLQJ QHZ PHWKRGV LQ OXYLVROV LV VKRZHG $OVKDUHLQJRHWKLWHWKHVKDUHRIKHPDWLWHEHFRPHV DQDJUHHPHQWLQGH[YDOXHV,LabZLWKUHDO>+HPDWLWH comparable to its share in the cambisols samples +HPDWLWH*RHWKLWH @LQWKRVHSDUWVZKHUHWKHUHDUH with pure goethite. 186 Annals of Agrarian Science :ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ (FRORJLFDO$VVHVVPHQWRI3DဧXUHVRI(DဧHUQ*HRUJLD .DNKHWL Mariam Merabishvili Agricultural University of Georgia, Kakha Bendukidze University Campus, 240, David Aghmashenebeli Alley., Tbilisi, 0131, Georgia Received: 12 February 2019; accepted: 9 May 2019 A B S T R A C T 7KHDUWLFOHGLVFXVVHVDFRPSOH[VXUYH\FRQGXFWHGLQ.DNKHWLSDဧXUHV&LQQDPRQLFFDUERQDWHDQGUDZFDUERQDWHVRLOVDUHVSUHDGLQ WKHDUHDRIWKHLQQHU.DNKHWLSDဧXUHV6WXGLHGVRLOVZLWKKHDY\PHWDOV &G&X3E=Q DUHQRWFRQWDPLQDWHGDQGGRQRWH[FHHGWKH PD[LPXPSHUPLVVLEOHFRQFHQWUDWLRQ 03& ,QFDVHRI$UDVKHQGDYLOODJHWKHSURFHVVRIHURVLRQDQGGHJUDGDWLRQLVXQGHUWKHPHGLXP risk level. In Gombori and Shakhvetila villages the risk of degradation and erosion is relatively high. Keywords:3DဧXUH+HDY\0HWDOV(URVLRQ'HJUDGDWLRQ9LVXDO5HVHDUFK2YHUJUD]LQJ &RUUHVSRQGLQJDXWKRU 0DULDP0HUDELVKYLOL (PDLODGGUHVV PPHUD#DJUXQLHGXJH Introduction 6HYHUDO ဧXGLHV KDYH EHHQ FRQGXFWHG LQ $]HUEDLMDQ LQFOXGLQJ IRU WKH SURWHFWLRQ RI WKH 3DဧXUHVDVDUHVRXUFHKDVDJUHDWLPSRUWDQFHIRU JUD]LQJ WHUULWRULHV RI SDဧXUHV WKDW WKUHDWHQ WKH the country, in terms of its use, so it is necessary to HFRORJLFDO EDODQFH ZKLFK LV D FRPSOH[ ဧXG\ RI HQVXUHWKHLUVXဧDLQDEOHFRQGLWLRQ2QHRIWKHPDLQ VRLOHFRORJ\ ဧXG\RISK\VLFDOFKHPLFDOSURSHUWLHV FRQGLWLRQV IRU WKH XVH RI SDဧXUH LV WR GHWHUPLQH >@ WKH FRUUHFW ORDGLQJ ZKLFK LV GH¿QHV WKH DPRXQW Food production and their growth has a positive RI OLYHဧRFN RQ D KHFWDUH RI SDဧXUH GXULQJ WKH LPSDFW RQ SDဧXUH FRQGLWLRQV >@ ,Q *HRUJLD WKH period of grazing without reducing its productivity VLWXDWLRQ RQ WKH SDဧXUHV DQG UHODWHG LVVXHV KDV DQG ZRUVHQ WKH YHJHWDWLRQ FRYHU >@ 5HVXOWV DUH EHHQ ဧXGLHG E\ PDQ\ UHVHDUFKHUV $PRQJ WKHP correlated with environmental factors such as: UHYLHZHGWKHUHGXFWLRQRISDဧXUHSURGXFWLYLW\WKHLU HURVLRQ VRLO WH[WXUH WHPSHUDWXUH HYDSRUDWLRQ LPSURYHPHQW DQG SURSHU PDQDJHPHQW >@ HWF >@7KHUHVHDUFKZDVFRQGXFWHGRQWKHDERYH 'XULQJWKH\HDUVWKHXQV\ဧHPDWLFH[SORLWDWLRQ PHQWLRQHG LVVXHV >@ of natural food plots deterioration of the botanical $QWKURSRJHQLF IDFWRU H൵HFWV RQ SDဧXUH composition of the vegetation cover, to worsen FRQGLWLRQVDORWSDဧXUHVFORVHWRYLOODJHSRSXODWHG feed and hay quality also reduces herbage yield DUHDVDUHPRUHHURGHGDQGGHJUDGHGGXHWRH[FHVVLYH and their productivity, contributing to the spread JUD]LQJ WKDQ GLဧDQW SDဧXUHODQGV >@ RIWXUIGLVHDVHVDQGHURVLRQSURFHVVHVDQG¿QDOO\ 7KHဧXG\RIWKHGHWHULRUDWLRQRISDဧXUHDUHDVKDV HQYLURQPHQWDOSROOXWLRQ,QRUGHUWRLPSURYHH[LဧLQJ EHHQFRQGXFWHGLQWKHVRXWKHUQSDUWRI.D]DNKဧDQ situation, it is necessary to have optimal loading ZKHUHWKHZRUVHQRIVRLOဧUXFWXUHLVGXHWRLPSURSHU RIOLYHဧRFNDQGLPSOHPHQWDWLRQRIHQYLURQPHQWDO JUD]LQJ>@ SURWHFWLRQ PHDVXUHV RQ SDဧXUHV >@ 6LPLODUORQJWHUPVXUYH\VKDYHEHHQFRQGXFWHG The bioproductivity of fodder grasses of LQ$UPHQLDWKDWLWLVHဧLPDWHGWKDWRQWKHSDဧXUH VXEDOSLQHKD\¿HOGVGHSHQGVRQWKHIHUWLOLW\RIVRLO LWLVVLJQL¿FDQWO\UHGXFHGSURGXFWLYLW\DQGPRGL¿HG WKHGHJUHHRIHURGLELOLW\DQGKHUEDJHWKLFNQHVV>@ YHJHWDWLRQFRYHU> @ 188 Mariam Merabishvili Annals of Agrarian Science 17 (2019) 188 – 196 1RZDGD\VVRLOVRISDဧXUHVDUHQRWVX൶FLHQWO\ laboratory analyzes regarding the following heavy enriched with mineral or organic fertilizers, soils PHWDOV &G &X 3E =Q FRQWHQW are contaminated with weed grass, because of the /DERUDWRU\DQDO\]HVRIVRLOVDPSOHVRISDဧXUHV IDLOLQJRIURWDWLRQDOJUD]LQJLWKDVEHHQဧDUWHGWKH have been implemented in Michail Sabashvili HURVLRQSURFHVVRQSDဧXUHV> @ ,QဧLWXWH RI 6RLO 6FLHQFH $JURFKHPLဧU\ DQG ,QWKHVRLOVRI*HRUJLDPDQ\ဧXGLHVKDYHEHHQ Melioration and in the laboratory of ecological carried out regarding heavy metals by various agriculture and nature protection; VFLHQWLဧV >@ Analysis of soil samples were performed by the 6RLO FRQWDPLQDWLRQ E\ KHDY\ PHWDOV &X IROORZLQJ PHWKRGV 6RLO WH[WXUH FRPSRVLWLRQ ZDV =Q 3E LV RQH RI WKH LPSRUWDQW SUREOHPV RQ determined by the pipe method; Reaction of soil SDဧXUHV UHJDUGLQJ WKH UDLVHG LVVXH WKH UHVHDUFK VROXWLRQ S+ ±LQWKHSRWHQWLDOPHWHRULFPHWKRGLQ was conducted in Georgia, in 9 km. radius from ZDWHUVDPSOLQJ K\JURVFRSLFZDWHUGU\LQJPHWKRG village Kazreti, Madneuli mining and processing DW & ([FKDQJHDEOH EDVHV ±WULORQ % YLD WLWUH enterprise, on the milk products of cows. It has >@ 0RELOH 1 DQG 3 FRQWHQW ,6276 been determined that the considerable increasing GHWHUPLQDWLRQRIH[FKDQJHFDOFLXPDWRPLF RI 0D[LPXP 3HUPLVVLEOH &RQFHQWUDWLRQ 03& DEVRUSWLRQ VSHFWURPHWHU >@ has been observed in soil, green grass, also in the 6WXG\ RI FRPPRQ IRUPV RI &G &X 3E EORRGRIFRZVRQWKHVHSDဧXUHVDVZHOODVLQPLON =Q DFFRUGLQJ WR WKH $XဧULDQ ဧDQGDUG ,62 SURGXFWV FKHHVH PDWVRQL >@ DWRPLFDEVRUSWLRQ PHWKRGRORJ\ Erosion process is one of the reasons of 3HUNLQ (OPHU DQG JUDSKLWH WXEH 3HUNLQ degradation of soils of Georgia. Regarding erosion (OPHU $DQDO\ဧ E\ VSHFWURPHWHU >@ SURFHVV PDQ\ ဧXGLHV KDYH EHHQ FRQGXFWHG LQ Soil mapping was created using geoinformation *HRUJLD E\ PDQ\ VFLHQWLဧV >@ V\ဧHPV *,6 For assessing the current situation, it is )RU YLVXDO DVVHVVPHQW RI SDဧXUH GXULQJ WKH recommended to conduct visual assessment of the FROOHFWLQJRISDဧXUHSORWVDPSOHVKDYHEHHQXVHG VRLO FRYHU FRQGLWLRQV HURVLRQ KHDY\ PHWDOV DQG “preferential sampling” and “random sampling” HYDOXDWLRQ RI SDဧXUHV E\ YLVXDO DSSUDLVDO designs. The plots were selected based on the “preferential sampling design” which means, that \RX FDQ FKRRVH WKH SDဧXUH SODFH VXEMHFWLYHO\ Objectives and methods according to certain criteria on the position of your 6WXGLHV ZHUH FRQGXFWHG LQ *HRUJLD VSHFL¿HG plot. Other sampling methods are random designs; LQ .DNKHWL UHJLRQ 7KH UHVHDUFK REMHFWV DUH they are usually developed on the basis of satellite ORFDWHGLQWKUHHYLOODJHVRI*XUMDDQLDQG$NKPHWD images and the selection of plots is done randomly municipalities: Arashenda, Cheremi and Koghoto. E\*HRJUDSKLF,QIRUPDWLRQ6\ဧHPV *,6 >@ 9LOODJH$UDVKHQGDORFDWHGLQWKHXSSHUGUDLQRI 9LVXDO DVVHVVPHQW RI WKH SDဧXUH ¿QGV RXW RQ the river "Lakbe" at 760 m. height altitude from the SDဧXUH SODFHV ; ,Q WRWDO ZKLFK LV WKH VHDOHYHO2Q$UDVKHQGDဧXG\WHUULWRU\KDYHEHHQ VDPSOH RI WKH GHPRQဧUDWLRQ$FFRUGLQJ WR PDQ\ PDGHVRLOSUR¿OHV FULWHULDWKHUHKDYHEHHQFUHDWHGWKHTXHဧLRQQDLUH 9LOODJH&KHUHPLLVORFDWHGRQWKHQRUWKHDဧVORSH EDVHG RQ WKH ZRUOG VFLHQWL¿F H[SHULHQFH LQ WKH of the Gombori Range, altitude from the sea level TXHဧLRQQDLUH LW LV HYDOXDWLQJ H[LဧLQJ SDဧXUH is 1000m. The left side of the river Chermiskhevi condition via percentage, such as: erosion tracks; $OD]DQL ULJKW WULEXWDU\ ,Q ဧXG\ WHUULWRU\ LQ YHJHWDEOH FRYHU DQG HWF >@ &KHUHPL YLOODJH KDYH EHHQ PDGH VRLO SUR¿OHV Based on information which were collected on 9LOODJH.RJKRWRLVORFDWHGRQ$OD]DQLSODLQRQ SDဧXUHVWZRLQGLFDWRUVZHUHFUHDWHGWKH¿UဧLQGH[ the right side of the river Alazani at 460 m. from the FDOOHGVXVFHSWLELOLW\WRHURVLRQ 6(, DQGWKHVHFRQG VHDOHYHO,QWKHဧXG\DUHDRIYLOODJH.RJKRWRKDYH LQGH[LVSDဧXUHGHJUDGDWLRQLQGH[ 3', EHHQPDGHVRLOSUR¿OHV 6XVFHSWLELOLW\WRHURVLRQ 6(, LVFOHDUO\VKRZQ According to the selected methodology and LQWKHFRORXUVRIWKHWUD൶FOLJKWVDFFRUGLQJWRWKH UHVHDUFK FRPSRQHQWV IURP UHVHDUFK REMHFWV DSSURYHGPHWKRGRORJ\>@GXULQJWKHUHVHDUFKDV KDYHEHHQWDNHQ FPGHSWKVRLO needed, we have added orange colour, for observing samples. In the raised article, it has been reviewed medium risk level signs of degradation, taking into WKUHHREMHFWV7KHVRLOVDPSOHVKDYHEHHQFRQGXFWHG consideration colours above, the layout is following: 189 Mariam Merabishvili Annals of Agrarian Science 17 (2019) 188 – 196 Index Risk to Erosion Light Range Level 76-100 Low Risk Green 51-75 Medium Risk Yellow 26-50 Medium Strong Orange Risk 0-25 High Risk Red Based on calculation indices and by easily Results and Analysis H[SUHVVLQJYLVXDODSSUDLVDORISDဧXUHVHYDOXDWLQJ WKH FRQGLWLRQ RI SDဧXUHV DFFRUGLQJO\ On research territories, in the collected soil SUR¿OHVKDYHEHHQPDGHVRLOWH[WXUHDQGFKHPLFDO DQDO\]HV 7DE Table 1. 6RLO7H[WXUH Objects, Fractions, % Horizon, profile_, 0,25- 0,05- 0,01- 0,005- depth (cm) 1-0,25 <0,001 <0,01 N 0,05 0,01 0,005 0,001 A - 0-5 3 32 17 13 2 33 48 Arashenda AB - 5-20 6 24 17 15 6 32 53 2 B - 20-40 6 21 25 4 8 36 48 BC -40-60 8 34 7 8 13 30 51 A -0-20 4 42 19 7 12 16 35 Arashenda B -20-40 1 29 23 10 14 23 47 7 BC -40-60 1 26 21 4 24 24 52 AB -0-35 6 23 9 17 18 27 62 Arashenda B -35-91 2 11 17 11 32 27 70 9 BC1-91-120 0 33 10 4 30 23 57 AB -0-28 0 15 5 17 44 19 80 Cheremi BC1-40 0 16 12 10 24 38 72 3 BC2-40-58 3 27 23 7 18 22 47 CD -58-80 2401013181748 Cheremi AB- 0-20 1311212152056 6 BC-20-70 1 23 23 5 12 36 53 Cheremi AB- 0-30 10 26 23 9 8 24 41 10 BC- 30-60 10 40 6 1 21 22 44 Koghoto A- 0-20 1 16 30 9 15 29 53 2 BC- 20-40 0311013182859 Koghoto A- 0-20 0301218221858 4 BC -20-40 0292018161751 Koghoto A- 0-20 2 35 23 9 16 15 40 5 BC- 20-40 4 38 18 8 22 10 40 190 Mariam Merabishvili Annals of Agrarian Science 17 (2019) 188 – 196 Table 2. 0DLQFKDUDFWHULVWLFV Cation exchange capacity, Sum ,% Objects, Hu- mg/equivalent in 100g. soil Horizon, Hygr. CaCO3 , profile_, pH mus depth (cm) H2O%, % Sum. N % Ca2+ Mg2+ Ca Mg Ca2++Mg2+ A - 0-5 3.52 8.4 8.18 7.4 20.27 6.76 27.03 75 25 Arashenda AB - 5-20 4.38 8.6 10.91 6.3 17.06 5.45 22.51 76 24 2 B - 20-40 4.38 8.4 9.09 5.4 24.56 7.5 32.06 77 23 BC -40-60 4.38 8.5 11.82 2.1 23.87 5.81 29.68 80 20 A -0-20 2.67 8.2 21.36 6.8 22.64 10.47 33.11 75 25 Arashenda B -20-40 3.73 8.3 23.18 4.5 10.42 7.17 25.59 72 28 7 BC -40-60 1.21 8.4 21.36 2.7 16.89 5.64 22.53 75 25 AB -0-35 2.88 8.2 15.91 8.3 20.27 6.42 26.69 76 24 Arashenda B -35-91 5.71 8.4 22.27 6.8 19.12 5.22 24.34 78 22 9 BC-91-120 4.38 8.3 22.73 4.6 17.06 6.14 23.20 73 27 AB -0-28 4.38 7.7 2.27 9.4 30.7 6.82 37.52 82 18 Cheremi BC1-40 3.52 8.0 6.82 8.2 27.97 8.19 36.16 77 23 3 BC2-40-58 2.46 8.3 13.18 7.1 23.08 6.36 29.44 78 22 CD -58-80 2.04 8.4 19.09 6.1 24.09 6.02 30.11 80 20 Cheremi AB- 0-20 3.31 7.9 9.09 9.6 20.95 7.77 28.72 73 27 6 BC-20-70 3.31 8.3 22.73 7.1 19.93 7.1 27.03 74 26 Cheremi AB- 0-30 2.04 7.0 0.91 8.1 25.09 5.02 30.11 83 17 10 BC- 30-60 2.25 8.3 4.09 6.1 19.4 5.69 25.09 77 23 Koghoto A- 0-20 2.04 8.5 30.45 8.7 16.05 5.03 21.08 76 24 2 BC- 20-40 0.81 8.4 29.54 7.4 14.76 4.92 19.68 75 25 Koghoto A- 0-20 5.71 8.4 35.45 7.2 16.34 5.56 21.09 75 25 4 BC -20-40 5.42 8.4 36.36 6.5 17.22 6.2 23.42 73 27 Koghoto A- 0-20 12.1 8.3 36.36 8.2 16.39 5.36 21.75 75 25 5 BC- 20-40 2.50 8.4 42.27 6.4 14.46 5.17 19.63 74 26 ,Q $UDVKHQGD YLOODJH ဧXG\ WHUULWRU\ IRU WKH higroscopic water varies between 1.21 and 5.71%, LOOXဧUDWLRQ KDYH EHHQ FKRVHQ WKUHH VRLO SUR¿OHV LWVKLJKHဧUDWHLVREVHUYHGLQWKHKRUL]RQB. ZKLFKEHORQJVWRFLQQDPRQLFFDUERQDWH SURI DQG 7KH SUR¿OH LV FKDUDFWHUL]HG ZLWK DONDOLQH UDZ FDUERQDWH SURI VRLOV reaction; pH indicator slightly varies between The cinnamonic carbonate soil is characterized &RQWHQW RI &D&23 YDULHV EHWZHHQ E\ WKH SUR¿OH$$%%%& SURI 7KH SUR¿OH 23.18%. The soil is characterized with high and LVKHDY\ORDPZKHUHWKHIUDFWLRQFRQWHQWLV deep content of humus. In horizon A the humus FRQWHQWRI¿QHSDUWLFOHVLVFRQWHQWRI FRQWHQW LQ FRQVLဧV DQG LQ %&KRUL]RQ SK\VLFDOFOD\IUDFWLRQLVEHWZHHQ 7DE 7KHVRLOLVVDWXUDWHGZLWKEDVHV7KHVXP +LJURVFRSLFDO ZDWHU ÀXFWXDWHV 7KH RI WKH H[FKDQJHDEOH FDWLRQV LV PJ SUR¿OH LV FKDUDFWHULVHG DONDOLQH UHDFWLRQV eqv. in 100g. soil. From H[FKDQJHDEOHbases Ca is &DFRQWHQWLVThe humus content in SUHGRPLQDWHV 7DE upper horizons is high and reaches 7,4%, but in the ,Q &KHUHPL YLOODJH ဧXG\ WHUULWRU\ KDYH EHHQ depth in lower horizon 2,1%. The soil is saturated FKRVHQ WKUHH VRLO SUR¿OHV ZKLFK EHORQJV WR H[FKDQJHDEOHEDVLV7KHVXPRIH[FKDQJHDEOHEDVLV FLQQDPRQLFFDUERQDWH SURI DQGUDZFDUERQDWH FRQVLဧV PJHTXLYDOHQW LQ J &D SURI VRLOV SUHGRPLQDWHV 7DE Cinnamonic carbonate soil is characterized by 5DZFDUERQDWHVRLOVKDYHWKHIROORZLQJဧUXFWXUH D SUR¿OH $%%&1%&2&' SURI DQG $%%& $$%%& SURI SURIheavy loam, prof. SURI 3URI LQ XSSHU KRUL]RQV DUH PHGLXP is a light clay, ZKHUHPPIUDFWLRQVFRQWHQW ORDP\DQGLQORZHUKRUL]RQVDUHKHDY\FOD\WH[WXUH WKHSK\VLFDOFOD\IDFWLRQ PP LV SURIPHGLXPORDP\WH[WXUHZKHUHmm FOD\IUDFWLRQ LV Tab 7KH IUDFWLRQFRQWHQWLVFRQWHQWRI¿QHSDUWLFOHVLV 191 Mariam Merabishvili Annals of Agrarian Science 17 (2019) 188 – 196 FRQWHQWRISK\VLFDOFOD\IUDFWLRQLVEHWZHHQ ZLWK WKH 03& LQGH[HV GHYHORSHG E\ ( %DNUDG]H 7DE 7KHFRQWHQWRIKLJURVFRSLFDOZDWHU 9RGLDQLVNL8UXVKDG]H DQG RWKHU DXWKRUV >@ LVEHWZHHQS+ZHDNO\DONDOLQH 2QQDWXUDOSDဧXUHODQGVWKHUHLVQRFRQWDPLQDWLRQ and alkaline. Content of CaCO3 YDULHVEHWZHHQ E\3EDQG&GLQFRPSDULVRQWRPD[LPXPSHUPLVVLEOH 19.09%. The humus content is high and in the upper FRQFHQWUDWLRQ 03& WKH UHVXOW LV EHORZ WKH FULWLFDO KRUL]RQVFRQVLဧV LQORZHUKRUL]RQV edge. The soil is saturated with bases, from H[FKDQJHDEOH ,Q WKH UHVHDUFK VDPSOHV WKH GL൵HUHQFH RI &X bases Ca is SUHGRPLQDWHV 7DE FRQWHQWLQWKHVRLOOD\HUVLVDSSUR[LPDWHO\WR 7KHVRLOSUR¿OHLVUDZFDUERQDWHWKHSUR¿OHLV PJNJ FKDUDFWHUL]HG $%%& the SUR¿OH KDV KHDY\ ORDP Based on literature sources, it is possible to say, WH[WXUH, FRQWHQWRIFOD\, amount of WKDWH[LဧLQJGL൵HUHQFHLVQDWXUDODQGWKHUHIRUHLWLV SK\VLFDOFOD\IUDFWLRQV 7DE 7KHFRQWHQW GH¿QHGE\WKHDFFHSWDEOHFULWHULRQ RIKLJURVFRSLFDOZDWHULVS+ ZHDNO\ ,Q FDVH RI &X DQG =Q WKH GL൵HUHQFH EHWZHHQ WKH alkaline. Content of CaCO3 YDULHV EHWZHHQ GHSWK RI XSSHU DQG ORZHU OD\HUV LV WKHKXPXVFRQWHQWLVKLJKDQGFRQVLဧV LQVLJQL¿FDQW WKDW PHDQV WKDW WKH FRQWHQW RI KHDY\ 9,6%. The soil is saturated with bases, the sum of the metals is DOPRဧ HTXDOO\ GLဧULEXWHG H[FKDQJHDEOHFDWLRQVYDULHV mg.eqv. in Supposedly, there is no source of pollution by heavy 100g. soil. from H[FKDQJHDEOHbases Ca is more than metals in this area. The concentration obtained is mainly 7DE derived from the deep layer of the soil, which can be ,Q .RJKRWR 9LOODJH ဧXG\ WHUULWRU\ KDYH EHHQ conditioned by the biogenic factors and vegetation FKRVHQ WKUHH VRLO SUR¿OHV ZKLFK EHORQJV WR UDZ cover. FDUERQDWHVRLOV3UR¿OHV DQGFKDUDFWHUL]HGZLWK 2Q WKH UHVHDUFK WHUULWRU\ RI SDဧXUHV WKHUH LV SUR¿OHV $%& PHQWLRQHG PJ GL൵HUHQFH RI WKH FRQWHQW RI =Q 3UR¿OHVDQGKDVKHDY\ORDPWH[WXUHSUR¿OH and Cu, which can be due, to the abundance of natural KDVDOLJKWORDPWH[WXUH¿QHSDUWLFOHV¶FRQWHQWLn VXEဧDQFHV WKDW FRPH IURP WKH URFN WKUHHSUR¿OHVYDULHVEHWZHHQ SK\VLFDOFOD\ The survey was carried out to verify the condition SDUWLFOHV ,QWRWDOLQWKUHHVRLOSUR¿OHVWKH RIQDWXUDOSDဧXUHVLQRUGHUWRGHWHUPLQHZKHWKHUWKH FRQWHQWRIKLJURVFRSLFDOZDWHUYDULHVEHWZHHQ place is contaminated by heavy metals concentration on S+ LV DONDOLQH &RQWHQW RI &D&23 LQWHQVLYHJUD]LQJSDဧXUHWHUULWRU\ YDULHVEHWZHHQ 7KHKXPXVFRQWHQWLV Studied soils are not contaminated with heavy metals KLJKDQGLQWKHXSSHUKRUL]RQVFRQVLဧVLQ &G &X 3E =Q WKHLU FRQWHQW LQ VDPSOHV GRHV QRW ORZHUKRUL]RQV7KHVRLOLVVDWXUDWHGZLWK H[FHHGVRFDOOHGPD[LPXPSHUPLVVLEOHFRQFHQWUDWLRQV bases, from H[FKDQJHDEOHbases Ca is predominates 03& DFFRUGLQJO\WRWKLVLWLVLPSRVVLEOHWRPRYHLW . into the food chain and polluted the product. 7KHVH UHVHDUFK REMHFWV DUH QRW FRQWDPLQDWHG E\ Based on visual research, in village Arashenda heavy metals and its contents, as well as the ratio, are IURP ဧXGLHG VDPSOHV LW LV YLVLEOH WKDW HURVLRQ absolutely acceptable for each sample in comparison to and degradation level of the risk is predominates, this WKH OLPLW RI SHUPLVVLEOH FRQFHQWUDWLRQV 03& LV H[SUHVVHG E\ ³\HOORZ´ FRORXU WKLV PHDQV PHGLXP At the same time, in soil samples noted minor risk of erosion. Plots of grazing territory of Arashenda changes in heavy metals content. The result of the survey village, which is located 700 m. above the sea level, LVUHÀHFWHGLQ7DEOH7KHGDWDUHFHLYHGLVFRPSDUDEOH WKH\ DUH PRUH SURQH WR HURVLRQ )LJ Table 3. 7KHFRQWHQWRIKHDY\PHWDOV PJNJ Cu Zn Cd Pb Objects Ssoil depth, cm 0-20 39.48 58.94 <1 <5 Arashenda 20-40 33.33 48.17 <1 <5 0-20 29.52 37.86 <1 <5 Koghoto 20-40 57.09 53.07 <1 <5 0-20 56.45 53.61 <1 <5 Cheremi 20-40 58.17 55.16 <1 <5 192 Mariam Merabishvili Annals of Agrarian Science 17 (2019) 188 – 196 193 Mariam Merabishvili Annals of Agrarian Science 17 (2019) 188 – 196 Conclusion PHWDOV &G&X3E=Q E\WKHH[LဧLQJFRQFHQWUDWLRQ RQWKHSDဧXUHVZLWKKHDY\PHWDOVLWLVLPSRVVLEOH The originality, of this research is that in the to contaminate the food product. framework of the same research, several components ,QWKHREMHFWRI$UDVKHQGDGRPLQDWHVPHGLXP KDYHEHHQဧXGLHGDWWKHVDPHWLPHDVIROORZV VRLO level of erosion and degradation processes, thus, cover condition, erosion, contamination by heavy LQFUHDVLQJ WKH TXDQWLW\ RI OLYHဧRFN DQG SDဧXUH PHWDOVDQGYLVXDODVVHVVPHQWRISDဧXUH XVLQJ SUR¿FLHQWO\ LV YHU\ IUXLWIXO In the inner part of Kakheti region, there are 2QREMHFWVRI*RPERULDQG6KDNKYHWLODYLOODJH GLဧULEXWHGUDZFDUERQDWHDQGFLQQDPRQLFFDUERQDWH SDဧXUHVHURVLRQDQGGHJUDGDWLRQOHYHOLVUHODWLYHO\ VRLOV RQ SDဧXUHV high. $FFRUGLQJWRVRLOWH[WXUHFLQQDPRQLFFDUERQDWH For better coordination of Gombori village soils have a heavy clay content. The reaction is SDဧXUHVLWLVQHFHVVDU\WRGHWHUPLQHWKHTXDQWLW\RI alkaline and weakly alkaline, carbonated, high FDWWOHZKLFKDUHJUD]HGLQGH¿QHGSDဧXUHWHUULWRU\ humus content, soils are saturated with bases; From because of protecting rotational grazing rule, H[FKDQJHDEOH EDVHV &D LV SUHGRPLQDQW according to avoid overgrazing. $FFRUGLQJ WR VRLO WH[WXUH UDZ FDUERQDWH VRLOV ,Q FDVH RI 6KDNKYHWLOD YLOODJH SDဧXUHV WKH DUH PRဧO\ KHDY\ DQG OLJKW FOD\V 7KH UHDFWLRQ LV risk of high degradation maybe caused by climate alkaline, carbonated, the humus content is relatively FRQGLWLRQVဧULFWDQGVQRZ\ZLQWHUDQGDIUHTXHQW high, deeply humifed, soils are saturated with bases, UDLQZKLFKOHDGVWRXQUHDFKDEOHZD\VWRSDဧXUHV IURPH[FKDQJHDEOHEDVHV&DLVSUHGRPLQDQW in addition, it is mentionable, that the process of Studied soils are not contaminated by heavy UHIRUHဧDWLRQ LQ 6KDNKYHWLOD DQG *RPERUL LV D SUHFRQGLWLRQ IRU ORVLQJ SDဧXUHV 194 Mariam Merabishvili Annals of Agrarian Science 17 (2019) 188 – 196 References WKH *UHDW &DXFDVXV RI$]HUEDLMDQ -$QQDOV RI$JUDULDQ6FLHQFH LQ >@ E. Klapp, Wiesen and Weiden, Berlin and 5XVVLDQ Hamburg, 1966. >@ A.F. Gasanova, The comparative evaluation of >@ *6K 0DPPDGRY 6$ +DML\HY 5DWLRQDO ZLQWHU SDဧXUH VRLOV RI$]HUEDLMDQ -$QQDOV use of soils under forage grass condition of RI $JUDULDQ 6FLHQFH LQ Nakhchevan Autonomous Rebuplic, J. Annals 5XVVLDQ RI $JUDULDQ 6FLHQFH LQ >@ *'$JODG]H)RUDJHSURGXFWLRQDVWKHPRဧ 5XVVLDQ important branch of agriculture in Georgia, J. >@ G. Agladze, Food production, Damani, Tbilisi $QQDOVRI$JUDULDQ6FLHQFH LQ *HRUJLDQ LQ5XVVLDQ >@ A.A. Torekhanov, Impact of rangeland use on >@ G.D. Agladze, Animal breeding and fodder OLYHဧRFN SURGXFWLYLW\ -$QQDOV RI$JUDULDQ production in Georgia: analysis of current 6FLHQFH LQ 5XVVLDQ situation and perspectives of its development >@ F.A. Guliyev, K.Y. Babayev, I.J. Karimov, information 1. Animal breeding, J. Annals 5, 7DKLURY 57 .DULPRY 7KH LQÀXHQFH RI $JUDULDQ 6FLHQFH LQ of anthropogenic factors on the soil and 5XVVLDQ YHJHWDWLYH FRYHU LQ WKH VRXWKHDဧ SDUW RI >@ G.D. Agladze, Animal breeding and food $]HUEDLMDQ RQ WKH EDVLV RI VSDFH LPDJHV - production in Georgia: analysis of the current $QQDOVRI$JUDULDQ6FLHQFH situation and perspectives of its development 43. information 2. Food production, J. Annals >@ A.A. Torekhanov, Soil conservation basics for RI $JUDULDQ 6FLHQFH LQ rangeland use, J. Annals of Agrarian Science, 5XVVLDQ LQ5XVVLDQ >@ R.T. Lolishvili, T.M. Subeliani, The >@ %.K 0H]KXQWV 7KH LQÀXHQFH RI PLQHUDO bioproductivity of fodder grasses of subalpine IHUWLOL]HUV DQG XQGHUVRZLQJ RQ \LHOG DQG KD\¿HOGV RI &HQWUDO &DXFDVXV - $QQDOV RI IRGGHUTXDOLW\RIWUDPSOHGSDဧXUHV-$QQDOV $JUDULDQ 6FLHQFH LQ RI $JUDULDQ 6FLHQFH LQ 5XVVLDQ 5XVVLDQ > @ 78UXVKDG]H$%DMHOLG]H6K/RPLQDG]H >@ B.Kh. Mezhunts, M.A. Navasardyan, T.A. Soil science, Batumi, 2011. 6DUJV\DQ7KHဧDWHRISDဧXUHVRIWKHGU\ဧHSSH >@ T. F. Urushadze, G.O. Ghambashidze, W.H. zone of Ararat valley of Armenia and the ways Blum, A. Mentler, Soil contamination with RIWKHLURSWLPL]DWLRQVXဧDLQDEOHGHYHORSPHQW heavy metals in Imereti region *HRUJLD RI PRXQWDLQ WHUULWRULHV 9ODGLNDYND] Bulletin of the Georgian National Academy of LQ 5XVVLDQ 6FLHQFHV > @ %.K0H]KXQWV7KHLQÀXHQFHRIWZR\HDUUHဧ >@ G.O. Ghambashidze, W.H. Blum, T.F. RIKHDYLO\WUDPSOHGSDဧXUHVRQELRSURGXFWLYLW\ Urushadze, A. Mentler, Heavy metals in soils, of grass associations, J. Annals of Agrarian - $QQDOV RI $JUDULDQ 6FLHQFH 6FLHQFH LQ5XVVLDQ >@ I.I. Mardanov, Agroecological pecularities of >@ G. Ghambashidze, T. Urushadze, W. Blum, A. PRXQWDLQPHDGRZ ODQGVFDSHV RI $]HUEDLMDQ Mengler, Heavy metals in some soils of the -$QQDOVRI$JUDULDQ6FLHQFH :Hဧ*HRUJLD3RFKYRYHGHQLH 36 LQ5XVVLDQ LQ 5XVVLDQ >@ *6K 0DPPDGRY 6$ +DML\HY (FRORJLFDO >@ *'$JODG]H*9%DVLODG]H(*.DODQGLD models of fertility management of soils 7KH LQÀXHQFH RI WKH HQYLURQPHQW SROOXWHG XQGHU SDဧXUHV LQ 1DNKLFKHYDQ $XWRQRPRXV from the heavy metals on the quality of milk 5HSXEOLF-$QQDOVRI$JUDULDQ6FLHQFH SURGXFWLRQ-$QQDOVRI$JUDULDQ6FLHQFH LQ 5XVVLDQ LQ 5XVVLDQ >@ * 6K 0DPPDGRY 6= 0DPPDGRYD >@ 3 )HOL[+HQQLQJVHQ 0$+$ 6D\HG ( (FRORJLFDO DVVHVVPHQW RI $]HUEDLMDQ VRLOV 1DULPDQLG]H.LQJ'6WH൵HQV78UXVKDG]H for their rational use, J. Annals of Agrarian Bound forms and plant availability of heavy 6FLHQFH LQ 5XVVLDQ PHWDOVLQLUULJDWHGKLJKO\SROOXWHGNDဧDQR]HPV >@ * 6K 0DPPDGRY 11 6LUDMRY 6RLO in the Mashavera valley, SE Georgia, J. Annals HFRORJLFDO FKDUDFWHULဧLFV RI PRXQWDLQ RI$JUDULDQ6FLHQFH PHDGRZ VRLOV RI WKH QRUWKHDဧHUQ VORSH RI >@ T.T. Urushadze, D. R. Khomasuridze, Practice 195 Mariam Merabishvili Annals of Agrarian Science 17 (2019) 188 – 196 LQDJURHFRORJ\0WVLJQREDUL7ELOLVL LQ *HRUJLDQ >@ *'$JODG]H*9%DVLODG]H(*.DODQGLD 7KH LQÀXHQFH RI WKH HQYLURQPHQW SROOXWHG from The heavy metals on quality of milk SURGXFWV-$QQDOVRI$JUDULDQ6FLHQFH LQ 5XVVLDQ >@ G. P. Gogichaishvili, T. F. Urushadze, T. T. 8UXVKDG]H7KHIRUHFDဧRIWKHLQWHQVLW\RIVRLO erosion for main soils of Georgia, J. Annals of $JUDULDQ6FLHQFH >@ 2 *KRUMRPHODG]H * *RJLFKDLVKYLOL 1 Turmanidze, Evaluating of erosion processes RI VRLO ZLWK GL൵HUHQW IDFWRUV VHGLPHQWV UHOLH൵ VRLOO YHJHWDWLRQ FRYHU - *HRUJLDQ Academy of Agricultural Sciences, Moambe LQ *HRUJLDQ >@ * *RJLFKDLVKYLOL 2 *KRUMRPHODG]H 1 Turmanidze, Evaluating of erosion of soils RI *HRUJLD DQG LWV VXဧDLQDELOLW\ *HRUJLDQ Academy of Agricultural Sciences, Moambe LQ *HRUJLDQ > @ * *RJLFKDLVKYLOL 2 *KRUMRPHODG]H 1 Turmanidze, The dynamic of erosivity during the whole year, J. Georgian Academy of $JULFXOWXUDO 6FLHQFHV LQ *HRUJLDQ >@ G. Talakhadze, L.Nakashidze, R.Kirvalidze, /DE3UDFWLFDO 6WXG\ %RRN RI 6RLO 6FLHQFH *DQDWOHED 7ELOLVL LQ *HRUJLDQ >@ K. Mindeli, L. Guntaishvili, N. Machavariani, D. .LUYDOLG]H.K0LQGHOL/*DPVDNKXUGLD/DE SUDFWLFDOဧXG\ERRNRIVRLOVFLHQFH8QLYHUVDOL Tbilisi, 2011. >@ $-3DUNHU7KHWRSRJUDSKLFUHODWLYHPRLဧXUH LQGH[ DQDSSURDFKWRVRLOPRLဧXUHDVVHVVPHQW in mountain terrain: Physical Geography, 9DULDEOHV XVHG DUH LQFOLQDWLRQ DVSHFW WRSRJUDSKLFSRVLWLRQDQGVORSHFRQ¿JXUDWLRQ >@ J. Etzold & R. Neudert, Monitoring manual IRUVXPPHUSDဧXUHVLQWKH*UHDWHU&DXFDVXV LQ $]HUEDLMDQ VXဧDLQDEOH PDQDJHPHQW RI biodiversity, south Caucasus, working paper, *,= >@ (%DNUDG]H<9RG\DQLWVNLL78UXVKDG]H= Chankseliani, M. Arabidze, About rationing of the heavy metals in soils of Georgia, J. Annals RI$JUDULDQ6FLHQFH 196 Elizbar Elizbarashvili et al. Annals of Agrarian Science 17 (2019) 197 – 203 Annals of Agrarian Science :ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ Investigation of Simultaneous Occurrence Probabilities of Some Dangerous and Spontaneous Meteorological Phenomena for Various Physical and Geographical Conditions of Georgia Using Multiplication and Addition Theorems of Probabilities Elizbar Elizbarashvilia, Mariam Elizbarashvilib*, Marika Tatishvilic, Shalva Elizbarashvilia, Nana Chelidze a a&OLPDWRORJ\DQG$JURPHWHRURORJ\'LYLVLRQ,QဧLWXWHRI+\GURPHWHRURORJ\*HRUJLDQ7HFKQLFDO8QLYHUVLW\ Agmashenebeli Ave., Tbilisi, 0112, Georgia b'HSDUWPHQWRI*HRJUDSK\)DFXOW\RI([DFWDQG1DWXUDO6FLHQFHV,YDQH-DYDNKLVKYLOL Tbilisi State University, 1, Chavchavdze Ave., Tbilisi, 0179, Georgia, Email: c:HDWKHU)RUHFDဧLQJ1DWXUDODQG7HFKQRJHQLF'LVDဧHU0RGHOLQJ'LYLVLRQ,QဧLWXWHRI+\GURPHWHRURORJ\*HRUJLDQ Technical University, 150, Agmashenebeli Ave., Tbilisi, 0112, Georgia Received: 5 November 2018; accepted: 5 January 2019 A B S T R A C T 7KHRFFXUUHQFHSUREDELOLWLHVRIVRPHLQGHSHQGHQWGDQJHURXVDQGVSRQWDQHRXVPHWHRURORJLFDOSKHQRPHQDFRPSOH[HVIRUGL൵HUHQW SK\VLFDODQGJHRJUDSKLFDOFRQGLWLRQVRI*HRUJLDKDYHEHHQHဧLPDWHGXVLQJPXOWLSOLFDWLRQDQGDGGLWLRQSUREDELOLW\WKHRUHPV7KH FRPSOH[RISUHFLSLWDWLRQဧURQJZLQGHYHQWVRFFXUVRQWKH&ROFKLV/RZODQGRQDYHUDJHHYHU\GD\VLQ'HFHPEHUDQG-DQXDU\RQ WKH(DဧHUQ*HRUJLDSODLQVRQFHSHU\HDULQ0D\RQWKH/LNKLULGJHHYHU\GD\VGXULQJZKROH\HDU7KHRFFXUUHQFHRILQWHQVLYH SUHFLSLWDWLRQဧURQJZLQGFRPSOH[LVSRVVLEOHLQ:HဧHUQ*HRUJLDWLPHSHUGHFDGHLQ(DဧHUQ*HRUJLDWLPHLQ\HDUVDQGLQWKH KLJKODQG]RQHRIWKH*UHDWHU&DXFDVXVDSSUR[LPDWHO\ WLPHVLQHYHU\\HDUVDQGRQ/LNKL5LGJHRQFHSHUPRQWK7KHRFFXUUHQFH RIWKHKDLOဧURQJZLQGFRPSOH[LVSRVVLEOHRQDYHUDJHHYHU\DQG\HDUV ZDUPSHULRGRI\HDU LQWKH6RXWK*HRUJLDQ+LJKODQGV DQGLQ(DဧHUQ*HRUJLDUHVSHFWLYHO\7KHIRJဧURQJZLQGFRPSOH[LQ*UHDWHU&DXFDVXVKLJKPRXQWDLQ]RQHLQ0D\FDQEHUHDOL]HGRQ DYHUDJHHYHU\GHFDGHDQGRQWKH/LNKL5LGJHHYHU\GD\V Keywords:3UREDELOLW\0HWHRURORJLFDOSKHQRPHQD&RPSOH[RIHYHQWV&OLPDWLFFRQGLWLRQV'DQJHURXVZHDWKHU3UHFLSLWDWLRQV &RUUHVSRQGLQJDXWKRU 0DULDP(OL]EDUDVKYLOL (PDLODGGUHVV PDULDPHOL]EDUDVKYLOL#WVXJH Introduction and economy of Georgia, as it is evidenced by the impact of global warming on the regional climate, Dangerous and spontaneous meteorological DQG HYHQ RQ WKH ODQGVFDSH ဧUXFWXUH >@ SKHQRPHQDVXFKDVH[WUHPHWHPSHUDWXUHUDLQIDOO ,QYHဧLJDWLRQV RI VRPH GDQJHURXV DQG KDLOEOL]]DUGIRJဧURQJDQGKXUULFDQHZLQGVHWF spontaneous weather phenomena over Georgian create emergency situations, causing damages and territory were initiated by one of the author of this even human victims. article in the late 70th DW WKH EHJLQQLQJ RI th of Natural weather phenomena, as the result ODဧFHQWXU\,QWKHUHVXOWRIWKHVHဧXGLHVWKHPDLQ of modern anthropogenic impact have been IHDWXUHV RI WKH ဧDWLဧLFDO ဧUXFWXUH RI FORXGLQHVV VLJQL¿FDQWO\LQWHQVL¿HGDQGRIWHQKDYHFDWDဧURSKLF WKXQGHUဧRUP SURFHVVHV DEXQGDQW DQG LQWHQVH FKDUDFWHU 7KH LQWHQVL¿FDWLRQ RI QDWXUDO UDLQIDOO ဧURQJ VXUIDFH ZLQGV WKH SUREDELOLဧLF PHWHRURORJLFDOSKHQRPHQDKDVD൵HFWHGHFRV\ဧHPV 197 Elizbar Elizbarashvili et al. Annals of Agrarian Science 17 (2019) 197 – 203 FKDUDFWHULဧLFV RI IRJV LQFOXGLQJ KD]DUGRXV IRJV 3. Data and methods > @ H[WUHPH DQRPDOLHV RI PHDQ PRQWKO\ DLU WHPSHUDWXUH>@IURဧV>@KXUULFDQHZLQGV>@DQG According to the basic provisions of the RWKHUVSRQWDQHRXVPHWHRURORJLFDOSKHQRPHQD> @ SUREDELOLW\WKHRU\>@WKHSUREDELOLW\RIWKHVHWRI ZHUH UHYHDOHG >@ independent events A and B, can be calculated using Thus, for present a rather rich literature has been multiplication theorem of probabilities: FROOHFWHGWKDWFKDUDFWHUL]HJHRJUDSK\ဧUXFWXUHDQG Ɋ Ⱥȼ Ɋ Ⱥ Ɋ ȼ dynamics of individual spontaneous meteorological phenomena on the territory of Georgia. However, and the probability of realization of one of the sometimes some events attack simultaneously, events is determined by the addition theorem of overlapping each other and thereby aggravate probabilities VLWXDWLRQ )RU H[DPSOH LQFUHDVHG ZLQG GXULQJ Ɋ Ⱥȼ Ɋ Ⱥ Ɋ ȼ Ɋ Ⱥȼ shower, fog with snow, hurricane with hail, etc. To ZKHUH 3 $ ±SUREDELOLW\ RI $ HYHQW 3 % ± UHGXFH WKH QHJDWLYH FRQVHTXHQFHV RI FRPSOH[ RI probability of B event, if we consider the complete WKHVHSKHQRPHQDRQHPXဧNQRZWKHLUSUREDELOLဧLF V\ဧHP RI HYHQWV$ , where i = 1,2,3, ... n. FKDUDFWHULဧLFV IRU WKH JLYHQ ORFDOLW\ i If it is known that there has been occurred event These phenomena are independent from each B, then the probability of event A is calculated in RWKHU WKHUHIRUH WKH SUREDELOLWLHV RI WKHLU MRLQW accordance with the Byes theorem: occurrence can be determined using the multiplication DQG DGGLWLRQ WKHRUHPV RI SUREDELOLWLHV >@ Ɋ Ⱥȼ >Ɋ ȺL Ɋ ȼ @Ɋ ȺL Ɋ ȼ In this paper, the occurrence probability of Ɋ Ⱥȼ ±is called conditional probability. some independent dangerous and spontaneous In our case, two opposite events are considered: PHWHRURORJLFDO SKHQRPHQD FRPSOH[HV IRU YDULRXV A1 WKH H[LဧHQFH RI VSHFL¿F PHWHRURORJLFDO physical and geographical conditions of Georgia SKHQRPHQRQ SUHFLSLWDWLRQ KDLO IRJ ဧURQJ DQG KDVEHHQHဧLPDWHGXVLQJPXOWLSOLFDWLRQDQGDGGLWLRQ KXUULFDQHZLQGVHWF DQG$2WKHDEVHQFHRIWKH theorems. same phenomenon. The sum of the probabilities of these phenomena equals to 1, so they form a 2. Study Area FRPSOHWH V\ဧHP RI HYHQWV *HRUJLDLVFKDUDFWHUL]HGE\H[FHSWLRQDOYDULHW\ 7R ဧXG\ SDWWHUQ RI SUHFLSLWDWLRQဧURQJ ZLQG RISK\VLFDOJHRJUDSKLFDODQGFOLPDWLFFRQGLWLRQV> FRPSOH[SUREDELOLWLHVEDVHGRQWKHPHDQDQQXDOGDWD @,WVWHUULWRU\FRPELQHVKLJKPRXQWDLQPLGGOH DQG FRQဧUXFW FRUUHVSRQGLQJ PDS WKH REVHUYDWLRQ PRXQWDLQ KLOO\ ORZÀDW ÀDW DQG SODWHDXOLNH PDWHULDOV RI PHWHRURORJLFDO ဧDWLRQV ZHUH XVHG UHOLHIV7KHORFDWLRQRIVRPHORZODQGVGRQ¶WH[FHHG DQG IRU FRPSOH[ SUREDELOLWLHV RI SKHQRPHQD sea level, and individual mountain peaks ranges FKDUDFWHULဧLF IRU WKH UHJLRQV PRQWKO\ GDWD ZHUH H[FHHGPKHLJKW XVHG$OVR WKH UHVRXUFHV RI VFLHQWL¿F DSSOLFDWLRQ In the northern part of the territory in the KDQGERRN ZHUH XVHG DV LQLWLDO GDWD >@ GLUHFWLRQIURPWKHQRUWKZHဧWRWKHVRXWKHDဧWKHUH ,Q SUHVHQWHG UHVHDUFK SRဧV ZHUH FKRVHQ H[WHQGVWKH0DLQ&DXFDVLDQ5LGJH,QWKHVRXWKHUQ FRQVLGHULQJ *HRUJLDQ SK\VLFDOJHRJUDSKLFDO SDUWDOPRဧSDUDOOHOWRWKH0DLQ&DXFDVXV5LGJH FRQGLWLRQV VHDVLGH UHVRUW %DWXPL P WKHUHH[WHQGVWKH6RXWK*HRUJLDQ+LJKODQGVZKLFK FKDUDFWHUL]LQJ *HRUJLDQ %ODFN 6HD FRDဧOLQH is part of the Lesser Caucasus. The main Caucasian 6DPWUHGLD P ORFDWHG LQ FHQWUDO SDUW RI &ROFKLV ridge is connected to the South Georgian mountain /RZODQG7ELOLVL P W\SLFDOIRUHDဧHUQORZODQG range by the Likhi Ridge, which divides Georgia SDUWRI*HRUJLD7HODYL P ORFDWHGDWQRUWK LQWR WZR FOLPDWLF UHJLRQV WKH :Hဧ ZLWK KXPLG HDဧHUQ VORSH RI *RPERUL 5LGJH FKDUDFWHUL]LQJ VXEWURSLFDO FOLPDWH DQG WKH (Dဧ ZLWK PRGHUDWHO\ IRRWKLOODQGORZPRXQWDLQ]RQHRIHDဧHUQ*HRUJLD dry continental climate. Between the Great Caucasus $NKDONDODNL P FKDUDFWHUL]LQJ WKH FOLPDWLF and the South Georgian upland there is a tectonic conditions of the South Georgian Highland and depression, which is represented by lowlands, river .D]EHJL P FKDUDFWHUL]LQJKLJKPRXQWDLQ]RQH YDOOH\V SODLQV DQG SODWHDXV WKH %ODFN 6HD FRDဧ RI*UHDW&DXFDVXVDQG0WD6DEXHWL P ORFDWHG WKH&ROFKLV/RZODQGWKH,PHUHWLKLJKODQGV(Dဧ on climate separating Likhi Ridge. *HRUJLDSODLQVWKH$OD]DQL9DOOH\ 198 Elizbar Elizbarashvili et al. Annals of Agrarian Science 17 (2019) 197 – 203 Fig. 1. 7KHGLఅULEXWLRQSUREDELOLW\ RISUHFLSLWDWLRQఅURQJZLQGFRPSOH[PHDQ DQQXDOSUREDELOLW\ 4. Discussion WKHLU FRPSOH[HV FKDQJHV VLJQL¿FDQWO\ For example in the Table 1 there are presented 7KH PDS RI SUHFLSLWDWLRQဧURQJZLQG FRPSOH[ values of empirical occurrence probabilities PHDQ DQQXDO GLဧULEXWLRQ SUREDELOLW\ FDOFXODWHG of some typical and dangerous meteorological DFFRUGLQJWRWKHHTXDWLRQ KDVEHHQSUHVHQWHGRQ phenomena for Telavi: hail, fog, strong wind, Fig.1. precipitation and intense precipitation. The wind )URP WKH PDS LW IROORZV WKDW WKH JUHDWHဧ is strong when its speed exceeds 15 m / sec, and SUREDELOLW\ RI WKH FRPSOH[ DV D ZKROH precipitation is considered to be intense when SHU\HDULVUHFRUGHGRQWKH/LNKL5LGJH DERXW their daily amount exceeds 20 mm. GD\VSHU\HDU 2QWKHHDဧHUQSDUWRIWKHVRXWKHUQ )URP7DEOHLWIROORZVWKDWIRU7HODYLWKHPRဧ slope of the Greater Caucasus, the probability of presumable phenomena are fog and precipitation, WKHVDPHFRPSOH[LV GD\V $WWKH including intense precipitation. The probability %ODFN 6HD FRDဧOLQH WKH RFFXUUHQFH SUREDELOLW\ RI RI IRJ LQ ZLQWHU PRQWKV LQFUHDVHV WR WKH FRPSOH[ LV DQG LQ PRဧ RI WKH 6RXWKHUQ ZKLFK DPRXQWV GD\V DQG WKH SUREDELOLW\ RI *HRUJLD+LJKODQGDQGWKHSODLQVRI(DဧHUQ*HRUJLD precipitation month dependence varies between LWGRHVQRWH[FHHGZKLFKFRUUHVSRQGVWRDQG 7KH RFFXUUHQFH SUREDELOLW\ RI RWKHU days. Obviously during year the occurrence of both dangerous meteorological phenomena is low, even individual meteorological phenomena, as well as LI WKH\ FDXVH VLJQL¿FDQW GDPDJHV Table 1. (PSLULFDORFFXUUHQFHSUREDELOLWLHVRIVRPHGDQJHURXVPHWHRURORJLFDO SKHQRPHQD 7HODYL Event Month 1 2 3 4 5 6 7 8 9 10 11 12 Hail 0 0 0.07 1.3 2.7 2 0.3 0.7 0.3 0.3 0.07 0 Fog 20 17 20 10 3 3 2 2 3 10 13 23 Strong wind 3 4 5 3 2 2 0.7 1 2.3 5 2.3 2.7 Precipitation 10 7 10 10 10 10 10 10 7 7 10 7 Intense precipitation 0.3 1.3 1.3 3 7 7 3 3 3 3 3 1.3 199 Elizbar Elizbarashvili et al. Annals of Agrarian Science 17 (2019) 197 – 203 Table 2. 3UREDELOLWLHVRIWKHPRVWGDQJHURXVPHWHRURORJLFDOSKHQRPHQD FRPELQDWLRQV 7HODYL Months Precipitation-fog Intense precipitation-strong wind Hail-strong wind Ǹ ǨǪ Ǹ ǨǪ Ǹ ǨǪ Ǹ ǨǪ Ǹ ǨǪ Ǹ ǨǪ Ǹ ǨǪ Ǹ ǨǪ Ǹ ǨǪ 1 2 28 10 0.009 3 0.3 0 3 0 2 1 12 6 0.052 5 1 0 4 0 3 2 28 10 0.065 6 1 0.0035 5 0.12 4 1 19 9 0.09 6 3 0.039 4 2 5 0.3 13 10 0.14 9 7 0.054 5 3 6 0.3 13 10 0.14 9 7 0.04 4 2 7 0.2 12 10 0.021 4 0.3 0.002 4 0.2 8 0.2 12 10 0.04 4 0.4 0.007 1 0.7 9 0.2 9 7 0.069 3 0.3 0.0069 2 0.3 10 0.6 16 6 0.15 8 3 0.015 3 0.3 11 1 22 8 0.069 5 0.3 0.0161 5 0.8 12 2 28 10 0.025 4 1 0 2 0 In Table 2 there are presented the probabilities RI RQH RI WKH HYHQWV RI WKH FRPSOH[HV 3 $ % RI WKH PRဧ GDQJHURXV SKHQRPHQD FRPELQDWLRQV LV LQ WKH ¿Uဧ FDVH DQG LQ WKH VHFRQG SUHFLSLWDWLRQIRJLQWHQVHSUHFLSLWDWLRQဧURQJZLQG RQH'XULQJဧURQJZLQGVSHULRGWKHSUREDELOLW\RI DQG KDLOဧURQJ ZLQG E\ PRQWKV FDOFXODWHG E\ LQWHQVHSUHFLSLWDWLRQDQGKDLO3 $% LQFUHDVHV and HTXDWLRQV EDVHGRQWDEOHGDWD amounts to 0.3% in May. From Table 2 it follows that the occurrence Figure 2 shows the annual course of the SUREDELOLW\RIWKHSUHFLSLWDWLRQIRJHYHQWFRPSOH[3 PRဧ GDQJHURXV SUREDELOLW\ FRPELQDWLRQV RI $% LQZLQWHUPRQWKVDVZHOODVLQWKHEHJLQQLQJ PHWHRURORJLFDO SKHQRPHQD IRU GL൵HUHQW SK\VLFDO RIVSULQJDQGDWWKHHQGRIDXWXPQLVDQGLQ geographical conditions of Georgia. summer months decreases to 0.2%. The occurrence Locations and phenomena combinations: SUREDELOLW\ RI RQH RI WKH HYHQWV 3 $ % 1-Telavi (hail-strong wind); 2-Batumi (heavy SUHFLSLWDWLRQRUIRJ LVPXFKELJJHUDQGDPRXQWV precipitation-strong wind); 3- Samtredia WR WKH PD[LPXP LQ 'HFHPEHU -DQXDU\ (precipitation - strong wind); 4- Tbilisi and March and the minimum in September. While (precipitation - strong wind); 5- Akhalkalaki considering fog, the probability of precipitation P (hail-strong wind); 6- Kazbegi (fog-strong wind); $% LQFUHDVHVPDNLQJLQIDOODQGDWWKHHQG 7-Mta-Sabueti (precipitation-strong wind); RIZLQWHUDQG IRUDOOUHဧPRQWKV 8-Mta-Sabueti (heavy precipitation-strong wind); It also follows from Table 2 that the occurrence 9-Mta-Sabueti (precipitation-fog); 10-Mta- SUREDELOLWLHVRIFRPSOH[SUHFLSLWDWLRQဧURQJZLQG Sabueti (fog-strong wind). On Fig. 1a) curves 1 DQGKDLOဧURQJ3 $% DUHYHU\ORZ7KHSUREDELOLW\ and 5 coincide. a) 50 % 100 % 45 Series1 90 Series1 40 Series2 80 Series2 70 35 Series3 Series3 60 30 Series4 50 Series4 25 Series5 40 Series5 20 30 Series6 Series6 15 20 10 Series7 10 Series7 5 Series8 0 Series8 0 0 5 10 15 Series9 b) -5 0 5 10 15 Fig. 2.7KHDQQXDOFRXUVHRISUREDELOLW\ 90 % Series1 80 FRPELQDWLRQVRIWKHPRVWGDQJHURXV 70 Series2 PHWHRURORJLFDOSKHQRPHQDIRUGLৼHUHQW 60 Series3 50 Series4 SK\VLFDOJHRJUDSKLFDOFRQGLWLRQVRI*HRUJLD 40 Series5 D WKHSUREDELOLW\RIVLPXOWDQHRXVRFFXUUHQFH 30 Series6 20 Series7 RILQGHSHQGHQWHYHQWVE WKHRFFXUUHQFH 10 Series8 SUREDELOLW\RIRQHRIWKHHYHQWVF RFFXUUHQFH 0 Series9 -10 0 5 10 15 SUREDELOLW\RIFRPSOH[LQFDVHLIRQHRIWKH c) HYHQWKDVEHHQRFFXUUHG 200 Elizbar Elizbarashvili et al. Annals of Agrarian Science 17 (2019) 197 – 203 As follows from Fig. 2 the annual course of SKHQRPHQD FRPSOH[ LV RQ WKH %ODFN 6HD occurrence probability of various variants of FRDဧDPLQLPXPLQ-XO\$XJXဧDQGPD[LPXPLQ PHWHRURORJLFDO SKHQRPHQD FRPSOH[HV GHSHQGV 2FWREHU1RYHPEHUDQGWKHRFFXUUHQFHSUREDELOLW\ essentially on the physical and geographical RIWKHFRPSOH[ZLWKWKHRQVHWRIRQHRIWKHHYHQWV FRQGLWLRQV RI WKH ORFDWLRQ )RU H[DPSOH WKH UDQJHV IURP VXPPHU -XO\6HSWHPEHU XS WR SUREDELOLW\ RI VLPXOWDQHRXV RFFXUUHQFH RI ဧURQJ 2FWREHU1RYHPEHU -DQXDU\ )RU WKH /LNKL wind and precipitation on the Colchis Lowland 5LGJHUHVSHFWLYHO\WKHPLQLPXPLQ-XQH 6DPWUHGLD ÀXFWXDWHVRQDYHUDJHIURPWR DQGWKHPD[LPXPLQ$SULO6HSWHPEHU2FWREHUDQG GXULQJWKH\HDUWKHPLQLPXPLQ0D\DQGPD[LPXP WKH PLQLPXP LQ 0DUFK$SULO 6HSWHPEHU LQ 'HFHPEHU DQG -DQXDU\ ZKLOH RQ (Dဧ *HRUJLD DQG WKH PD[LPXP LQ 'HFHPEHU SODLQV 7ELOLVL SUREDELOLW\ RI WKH VDPH FRPSOH[ 9HU\UDUHO\WKHUHLVKDLOဧURQJZLQGVFRPSOH[ LV WKH PLQLPXP LQ$XJXဧ DQG 1RYHPEHU ZKLFK RQ LQ 7HODYL KDV FDWDဧURSKLF DQGPD[LPXPLQ0D\7KHRFFXUUHQFHSUREDELOLW\ QDWXUHDQGFDXVHGVLJQL¿FDQWPDWHULDOGDPDJHV7KH RISUHFLSLWDWLRQဧURQJZLQGFRPSOH[RQWKH/LNKL PD[LPXP SUREDELOLW\ RI WKLV FRPSOH[ DW IRRWKLOO 5LGJH 0WD6DEXHWL PDNHVWKHPLQLPXP DQG ORZODQG ]RQHV RI (Dဧ *HRUJLD 7HODYL LV LQ-XO\DQGWKHPD[LPXPLQ0DUFK&RQVHTXHQWO\ $SULO-XQH DQGDWWKH6RXWK*HRUJLD SUHFLSLWDWLRQဧURQJ ZLQG FRPSOH[ RFFXUV RQ WKH +LJKODQGV $NKDONDODNL 0D\-XQH Colchis Lowland on average every 20 days on 7KLVPHDQVWKDWWKHFRPSOH[KDLOဧURQJZLQGIRU 'HFHPEHU-DQXDU\ RQ (DဧHUQ *HRUJLD SODLQV LQ the indicated months occurs on average 1 time in May per year only once, and on the Likhi Ridge \HDUVDQGIRU\HDUVUHVSHFWLYHO\IRU(DဧHUQ HYHU\GD\V7KHRFFXUUHQFHSUREDELOLW\RIRQH Georgia and the South Georgian Highlands. The RI WKH SKHQRPHQD IURP WKH SUHFLSLWDWLRQ ဧURQJ RFFXUUHQFH SUREDELOLW\ RI RQH RI WKH FRPSOH[ V ZLQG FRPSOH[ LQ WKH &ROFKLV /RZODQG GXULQJ WKH HYHQWVWKURXJKRXWWKH\HDUYDULHVIURPLQ$XJXဧ \HDU ÀXFWXDWHV EHWZHHQ WKH PLQLPXP LQ to 5% in March and May and in the South Georgian $XJXဧ DQG WKH PD[LPXP LQ 'HFHPEHU-DQXDU\ +LJKODQGVIURPLQ'HFHPEHUWR LQ0D\ DQG RQ WKH (DဧHUQ *HRUJLD SODLQV LV WKH -XQH7KHSUREDELOLW\RIWKHFRPSOH[VLJQL¿FDQWO\ PLQLPXPLQ-DQXDU\)HEUXDU\DQGWKHPD[LPXP increases when one of the events has been already LQ0D\DQGDW/LNKL5LGJHUDQJHVEHWZHHQ RFFXUUHGDQGUHDFKHV 0D\-XQH UHVSHFWLYHO\ :KHQ RQH RI WKH HYHQWV IURP WKH SUHFLSLWDWLRQ Unlike the considered meteorological ဧURQJZLQGFRPSOH[RFFXUVWKHSUREDELOLW\RILWV SKHQRPHQDFRPSOH[WKHIRJဧURQJZLQGFRPSOH[ second component occurrence during the year on KDV EHHQ FKDUDFWHUL]HG E\ VLJQL¿FDQW SUREDELOLW\ the Colchis Lowland ranges from 37 to 50%, the in mountains. The occurrence probability of this PLQLPXPLQ1RYHPEHUDQG-XO\DQGWKHPD[LPXP FRPSOH[ RI SKHQRPHQD RQ WKH /LNKL 5LGJH 0WD LQ'HFHPEHU-DQXDU\DQG0DUFKDQGRQWKH(Dဧ 6DEXHWL YDULHVZLWKLQWKHOLPLWVRI -XQH Georgia plains the probability of the corresponding -DQXDU\ 0DUFK DQG RQ WKH &DXFDVXV .D]EHJL HYHQW LV WKH PLQLPXP LQ 'HFHPEHU ZLWKLQ -DQXDU\)HEUXDU\ 0D\ $XJXဧDQG1RYHPEHUDQGWKHPD[LPXPLQ0DUFK 7KXV WKLV FRPSOH[ FDQ EH UHDOL]HG UHVSHFWLYHO\ and May, and on the Likhi Ridge ranges between RQ DYHUDJH GD\V DQG HYHU\ WHQ GD\V 7KH PLQLPXPLQ6HSWHPEHUWKHPD[LPXPLQ likelihood of realizing one of the phenomena of the March. VDPH FRPSOH[ LV DW /LNKL 5LGJH DQG RQ 3UHFLSLWDWLRQဧURQJ ZLQG FRPSOH[ LV &DXFDVXVDQGWKHRFFXUULQJSUREDELOLW\RI characterized by a small probability on the Black WKHFRPSOH[XSRQUHDOL]LQJRQHRIWKHHYHQWVYDULHV 6HD FRDဧ %DWXPL ZKLFK IUHTXHQWO\ LV WKH PRဧ UHVSHFWLYHO\IURP $SULO WR -DQXDU\ GDQJHURXVO\FRLQFLGHGZLWKDဧRUP7KHSUREDELOLW\ DQG IURP -DQXDU\ WR -XQH RI WKLV FRPSOH[ GXULQJ \HDU UDQJHV IURP On the climate separating Likhi Ridge there is -XO\$XJXဧ -DQXDU\ WKHSUREDELOLW\RI DOVRKLJKSUREDELOLW\RISUHFLSLWDWLRQIRJFRPSOH[ WKLVFRPSOH[LQ(DဧHUQ*HRUJLDLVHYHQOHVVDQG WKHPLQLPXPRQ1RYHPEHUDQGPD[LPXP RQ WKH /LNKL 5LGJH LW UDQJHV EHWZHHQ WKH RQ -DQXDU\7KLV FRPSOH[ LV KDSSHQLQJ HYHU\ PD[LPXPLQ2FWREHU7KXVWKLVFRPSOH[FDQEH days. The probability of one of the phenomena UHDOL]HGRQWKH%ODFN6HDFRDဧRQDYHUDJHWLPH RI WKH FRPSOH[ GXULQJ WKH \HDU ÀXFWXDWHV ZLWKLQ SHU GHFDGH DQG RQ WKH /LNKL ULGJH WLPH SHU WKH PLQLPXP DOVR LQ 1RYHPEHU DQG WKH month. The occurrence probability of one of the PD[LPXPLQ-DQXDU\DQGRFFXUUHQFHSUREDELOLW\RI 201 Elizbar Elizbarashvili et al. Annals of Agrarian Science 17 (2019) 197 – 203 WKHFRPSOH[DWWKHRQVHWRIRQHRIWKHHYHQWVYDULHV DQGLQWKH&DXFDVXVDQGWKHSUREDELOLW\RI ZLWKLQ 6HSWHPEHU2FWREHU -DQXDU\ KDSSHQLQJWKHFRPSOH[LQWKHFDVHZKHQRQHRIWKH event has been already occurred varied respectively 5. Conclusion IURP $SULO WR -DQXDU\ DQGIURP -DQXDU\ WR -XQH The simultaneous occurrence probability of ဧURQJ ZLQG DQG SUHFLSLWDWLRQ RQ WKH &ROFKLV Lowland varies from 0.4 to 5% during the year, DQG RQ (DဧHUQ *HRUJLD SODLQV LW LV DQG RQ References WKH /LNKL 5LGJH LW LV 7KH RFFXUUHQFH SUREDELOLW\RIRQHRIWKHVHSKHQRPHQDLV >@ ((OL]EDUDVKYLOL&OLPDWHRI*HRUJLD7ELOLVL LQWKH&ROFKLV/RZODQGDQGLQ(DဧHUQ*HRUJLDLW LQ*HRUJLDQ LVDQGLQWKH/LNKL5LGJHUDQJHVEHWZHHQ >@ ( 6K (OL]EDUDVKYLOL 0 ( (OL]EDUDVKYLOL ,QFDVHRIRQHRIWKHHYHQWVWKHRFFXUUHQFH Possible Transformation of the Caucasus SUREDELOLW\RIWKHVHFRQGFRPSRQHQWRIWKHFRPSOH[ Natural Landscapes in Connection with Global LV LQ WKH &ROFKLV /RZODQG ZKLOH LQ (Dဧ Warming. Meteorology end hydrology, 10 *HRUJLDLWLVDQGLQWKH/LNKL5LGJHUDQJHV LQ 5XVVLDQ EHWZHHQ >@ ( 6K (OL]EDUDVKYLOL 0 ( (OL]EDUDVKYLOL 7KH RFFXUUHQFH SUREDELOLW\ RI WKH FRPSOH[ The Main Problems of Landscape RI LQWHQVH SUHFLSLWDWLRQဧURQJ ZLQG ÀXFWXDWHV &OLPDWRORJ\ 7ELOLVL LQ 5XVVLDQ WKURXJKRXWWKH\HDURQWKH%ODFN6HDFRDဧDQGWKH >@ ( 6K (OL]EDUDVKYLOL 2 6K 9DUD]D &ROFKLV/RZODQGZLWKLQDQGRQWKH nashvili, N. S. Tsereteli, M. E. Elizba rashvili, /LNKL5LGJHLWLV7KHRFFXUUHQFHSUREDELOLW\ and Sh. E. Elizbarashvili. Dangerous RIRQHRIWKHSKHQRPHQDRIWKHFRPSOH[LV Fogs on the Territory of Georgia. Russian RQWKH%ODFN6HDFRDဧDPLQLPXPLQ-XO\$XJXဧ Meteorology and Hydrology, Vol. 37, Issue DQG PD[LPXP LQ 2FWREHU1RYHPEHU DQG WKH 2, February (2012) 106-11. RFFXUUHQFH SUREDELOLW\ RI WKH FRPSOH[ ZLWK WKH >@ (6K(OL]EDUDVKYLOL 7.=XELWDVKYLOL 0LဧV RQVHWRIRQHRIWKHHYHQWVUDQJHVIURP VXPPHU LQ (DဧHUQ *HRUJLD 3URFHHGLQJV RI WKH -XO\6HSWHPEHU XS WR 2FWREHU1RYHPEHU Russian Academy of Sciences, a series of -DQXDU\ )RU WKH /LNKL 5LGJH LW LV UHVSHFWLYHO\ JHRJUDSKLF WKH PLQLPXP LQ -XQH DQG WKH PD[LPXP >@ ( 6K (OL]EDUDVKYLOL 5 6K 0HVNKLD 0 LQ $SULO 6HSWHPEHU2FWREHU DQG WKH E. Elizbarashvili. Dynamics of occurrence PLQLPXP LQ 0DUFK$SULO 6HSWHPEHU DQG WKH IUHTXHQF\RI H[WUHPHDQRPDOLHVRI PRQWKO\ PD[LPXP LQ 'HFHPEHU mean air temperature in Georgia in the 20th 7KHPD[LPXPRFFXUUHQFHSUREDELOLW\RIFRPSOH[ FHQWXU\DQGLWVH൵HFWRQSUHFLSLWDWLRQDQGRQ KDLOဧURQJZLQGLQWKHIRRWKLOODQGORZODQG]RQHRI the river water discharge. Russian Meteorology (DဧHUQ*HRUJLDLV $SULO-XQH DQGLQ DQG+\GURORJ\-DQXDU\9RO,VVXH WKH6RXWK*HRUJLDQ+LJKODQGV 0D\ -XQH 7KH RFFXUUHQFH SUREDELOLW\ RI RQH RI WKH >@ (6K(OL]EDUDVKYLOL 26K9DUD]DQDVKYLOL FRPSOH[ V HYHQWV WKURXJKRXW WKH \HDU YDULHV IURP M. E. Elizbarashvili, N. S. Tsereteli. Light LQ$XJXဧWRLQ0DUFKDQG0D\LQWKH6RXWK IURဧV LQ WKH IUHH]HIUHH SHULRG LQ *HRUJLD *HRUJLDQ+LJKODQGVIURPLQ'HFHPEHUWR 5XVVLDQ0HWHRURORJ\DQG+\GURORJ\9ROXPH LQ 0D\ -XQH 7KH RFFXUUHQFH SUREDELOLW\ RI WKH ,VVXH -XQH VDPH FRPSOH[ ZKHQ RQH RI WKH HYHQWV KDV EHHQ >@ ( 6K (OL]EDUDVKYLOL 2 6K 9DUD]DQDVKYLOL KDSSHQHGUHDFKHV 0D\-XQH N. S. Tsereteli, and M. E. Elizbarashvili. 7KH FRPSOH[ IRJဧURQJ ZLQG LV FKDUDFWHUL]HG Hurricane Winds on the Territory of Georgia. E\ VLJQL¿FDQW SUREDELOLW\ LQ WKH PRXQWDLQV 7KH Russian Meteorology and Hydrology, March, RFFXUUHQFHSUREDELOLW\RIWKLVSKHQRPHQDFRPSOH[ 9ROXPH ,VVXH ± on the Likhi Ridge ranges from 21% to 32%, while > @ ( 6K(OOL]EDUDVKYLOL 0( (OL]EDUDVKYLOL IRUWKH&DXFDVXV .D]EHJL UDQJHVIURPWR ([WUHPH:HDWKHU(YHQWVRYHUWKH7HUULWRU\RI The likelihood of happening one of the phenomena *HRUJLD 7ELOLVL LQ 5XVVLDQ RIWKHVDPHFRPSOH[LV LQWKH/LNKL5LGJH >@-'$OLEHJRYD(6K(OOL]EDUDVKYLOL6WDWLဧLFDO Structure of Atmospheric Precipitation in 202 Elizbar Elizbarashvili et al. Annals of Agrarian Science 17 (2019) 197 – 203 Mountain areas. Gidrometeoizdat, Leningrad, LQ5XVVLDQ >@-'$OLEHJRYD(6K(OL]EDUDVKYLOL2QWKH ဧDWLဧLFDO ဧUXFWXUH RI WKH FORXG ¿HOG RYHU Transcaucasia. Meteorology and hydrology, 4 LQ 5XVVLDQ >@ - ' $OLEHJRYD ( 6K (OOL]EDUDVKYLOL 6WDWLဧLFDO ဧUXFWXUH RI VXUIDFH ZLQG LQ Transcaucasia. Tr. GGO named after A.I 9RHLNRY YRO LQ 5XVVLDQ [13] K.A.Sapitski, E.Sh.Elizbarashvili. On the alignment of the number of days with 20mm rainfall according to Poisson for some points in Georgia. Communications of the Academy RI 6FLHQFHV RI WKH *HRUJLDQ 665 ȹ (1972) 110-118 (in Russian). [14] E.Sh. Elizbarashvili, N.Sh. Gongladze, S.R. Vlasova, B.Galborova, A.A. Popov. About thunderstorm activity in Eastern Georgia. Izvestiya AN SSSR., Series geography, 1 (1983) 130-139 (in Russian). >@7$$JHNLDQ%DVHVRIWKH7KHRU\RI(UURUV 1DXND0RVFRZ LQ5XVVLDQ >@ ( 6K(OOL]EDUDVKYLOL 9HUWLFDO ]RQLQJ RI WKH FOLPDWHV RI 7UDQVFDXFDVLD ,]YHဧL\D RI WKH USSR, Academy of Sciences, a series of JHRJUDSKLFʋ LQ5XVVLDQ >@ 6FLHQWL¿F DQG $SSOLHG +DQGERRN RQ WKH Climate of the USSR. Series 3. Perennial GDWD 3DUWV LVVXH *LGURPHWHRL]GDW /HQLQJUDG LQ 5XVVLDQ 203 B.B. Basilashvili et al. Annals of Agrarian Science 17 (2019) 204 – 207 Annals of Agrarian Science :ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ Issue of organization of material logistics of work of agricultural machinery in complex mountain-level land conditions B.B. Basilashvili , I.M. Lagvilava, Z.K. Makharoblidze, R.M. Khazhomia Agricultural University of Georgia, Kakha Bendukidze University Campus, 240, David Aghmashenebeli All., Tbilisi, 0131, Georgia Received: 19 March 2018; accepted: 09 May 2018 A B S T R A C T $WDQ\ဧDJHRIWKHGHYHORSPHQWRIVRFLHW\VFLHQWL¿FWHFKQLFDOSURJUHVVUHSUHVHQWVWKHPDLQFRQGLWLRQLQJIDFWRUIRUWKLVGHYHORSPHQW $VIDUDVVFLHQWL¿FWHFKQLFDOSURJUHVVUHSUHVHQWVWKHSURFHVVRIJXDUDQWHHGGHYHORSPHQWRIDQ\¿HOGRIHQJLQHHULQJ7KHUHIRUHVRPH XQFRQVFLRXVXQSURIHVVLRQDODQGLQWHUIHULQJGHSHQGHQFHZLWKWKLVSURFHVVLVDFFRPSDQLHGE\VX൶FLHQWO\PXOWLODWHUDOQHJDWLYHUHVXOWV 7KHFRPSOH[QDWXUDODQGLQGXဧULDOFRQGLWLRQVRI*HRUJLDHVSHFLDOO\LQPRXQWDLQRXVDQGFRPSOH[UHOLHIFRQGLWLRQVQHFHVVLWDWHWKH LQWURGXFWLRQDQGGHYHORSPHQWRIVSHFLDOVFLHQWL¿FGLUHFWLRQVLQSDUWLFXODUWKHQHHGWRGHYHORSLVVXHVRIPHFKDQL]DWLRQRIPRXQWDLQ DJULFXOWXUHDWWKHOHYHORIPRGHUQVFLHQWL¿FWHFKQLFDOSURJUHVVLQWKLV¿HOG Keywords:(QHUJ\PHDQV$VVHPEO\XQLWV([FKDQJHIXQG&RQVXPSWLRQRIVSDUHSDUWV)XHOFRQVXPSWLRQ$JURWHFKQLFDO &RUUHVSRQGLQJDXWKRU %HMDQ%DVLODVKYLOL(PDLODGGUHVV EHMDQEDVLODVKYLOL#PDLOUX Introduction It is determined that in Georgia more than 60% RI WKH ODQG DUHD SUR¿WDEOH IRU WKH SURGXFWLRQ RI The natural and climatic as well as production agricultural products, is located on the slopes. It conditions of agriculture in Georgia are quite diverse LVDOVRGHWHUPLQHGWKDWWKHWDဧHOHVVSURSHUWLHVDQG and this diversity is particularly sensitive on the nutritional value of the products produced on the performance of agricultural processes in mountainous VORSHV RI WKH KLJKPRXQWDLQRXV ]RQHV DUH TXLWH DQGKDYLQJFRPSOH[UHOLHIDUHDVZKHQVXFKIDFWRUV KLJKDQGWKH\DUHH[FHHGLQJWKHDQDORJRXVLQGLFHV as the size and contouring of the processed area, the of production produced on plain conditions. At the LQFOLQDWLRQ DQG JHQHUDO ဧDWH RI WKH UHOLHI FOLPDWLF same time, it has been calculated and determined DQG VRLO FRQGLWLRQV HWF VLJQL¿FDQWO\ D൵HFW RQ WKH WKDWGHYHORSPHQWRIWKHVORSHVZLWKဧHHSQHVVXS individual operational indicators of the performed to 8 ... 10°, would additionally produce more than SURFHVVHV DJURWHFKQLFDO HQHUJ\ WHFKQLFDO RI SURGXFWLRQ IUXLW JUDSHV WHD HWF HFRQRPLFDOHWF 7KLVFLUFXPဧDQFHQHFHVVLWDWHVWKH and the development of slopes with value more than development of a special directions of agriculture in 20°, makes additional income in production – it is Georgia, in particular, the development of issues of GRXEOHG >@ mountain agriculture and the corresponding means. -XဧOLNHWKHJHQHUDOGHYHORSPHQWRIDJULFXOWXUH The development of mountain agriculture in the perfect development of slopes and mountain lands Georgia requires the upgrading of relevant research, primarily depends on the level of mechanization GHVLJQWHFKQRORJLFDOHQJLQHHULQJDQGH[SHULPHQWDO of production processes. The issue of the rational ZRUNVDWWKHPRGHUQOHYHOVLQFHWKH\DUHDVLJQL¿FDQW selection of energy means and technological UHVHUYHIRUWKHSHUIHFWGHYHORSPHQWRIWKHFRXQWU\ V PDFKLQHVDVZHOODVWKHLPSOHPHQWDWLRQRIFRPSOH[ DJULFXOWXUH>@ 204 B.B. Basilashvili et al. Annals of Agrarian Science 17 (2019) 204 – 207 mechanization for plain conditions, is relatively 7KH UHTXLUHG QXPEHU RI H[FKDQJH ဧRFN RI easy to solve. Mechanization of agriculture in unit assemblies for the whole economy would be KDYLQJFRPSOH[UHOLHIDQGPRXQWDLQODQGVDVZHOO GHWHUPLQHG IURP WKH VLPSOL¿HG IRUPXOD : as in other similar conditions, is a problematic issue. nm ȡ7 . 7 (1) )LUဧ RI DOO WKH PHFKDQL]DWLRQ RI SURGXFWLRQ ȅĭ % + &3 processes of agriculture depends on the providing where m - is the number of machines on that and proper selection of the corresponding mobile these assembly units are installed; energy means and technological machines. ɏ – is the number of assembly units for one 6LJQL¿FDQW LV DOVR GHWHUPLQHG GXH WKH DFFRUGLQJ machine; calculation of parameters the correct compilation ܶ – is the time of complete restoration of the and completion of the corresponding machine and assembly unit, unit,including includingthe time on trans the- tractor units, based on the theoretic calculations, timeportation; on transportation; determination of their technological parameters ܭு – is the coefficient taking into account and operating modes, the improvement of methods deviations from the established terms of res- RI DSSOLFDWLRQ RI WHFKQRORJ\ WKH ဧUXFWXUDO toration and other normative (ܭு= 1,2 ... 1,8); optimization of all links in engineering service. For ܶ - is the average life of the assembly unit PRGHUQ DJULFXOWXUH WKH XQLQWHUUXSWHG FRQVLဧHQW before replacement. DQG H൵HFWLYH LPSOHPHQWDWLRQ RI UHVHDUFKHV DQG The smaller values of ܭ ு are assumed for large GHYHORSPHQWLQWKLVGLUHFWLRQUHSUHVHQWVDVLJQL¿FDQW farms and vice versa. SUREOHP > @ 7KHYDOXHRIWKHFRH൶FLHQWDWRSHUDWLRQRIܭு 7R HQVXUH D KLJK OHYHO RI PHFKDQL]DWLRQ RI ¿HOG DJULFXOWXUDOPDFKLQHU\LQFRPSOH[PRXQWDLQSODLQ husbandry works in the agricultural enterprise and the conditions undergoes a change in the direction of LPSOHPHQWDWLRQ RI FRPSOH[ PHFKDQL]DWLRQ RI FURS increase that also leads to an increase in the number production, as well as for the full value realization of required assembly units. of the operational properties and capabilities of The number of replaceabl e working bodies of machinery, the available power of work should be machines and recoverable spares would also be in range of 22...25 kW/man, and the energy supply FDOFXODWHGXVLQJWKHIROORZLQJVLPSOL¿HGIRUPXOD of agriculture should be 4...6 kWKD$V VLJQL¿FDQW SDUDPHWHULVDOVRWKHFRPSOH[SDUDPHWHUWKHGHQVLW\RI ªº PHFKDQL]HGZRUNV FRQGLWLRQDOဧDQGDUGKDKD >@ ȍC In order to achieve and maintain of mentioned nmɡɱ ɦȡ ɦ«»$ &73 (2) SDUDPHWHUVLQDVSHFL¿FUHJLRQRULQDQDJULFXOWXUDO «»T1nPpe ɦ ¬¼ enterprise, it is necessary to select and operate agricultural machinery on the basis of proper where mM - is the number of the same type ma- engineering calculation with taking into account the chines; FRUUHVSRQGLQJ QDWXUDOSURGXFWLRQ FRQGLWLRQV ɏM – is the number of parts or work tools per $W WKH SUHVHQW ဧDJH LQ WKH FRQGLWLRQV RI machine; management polymorphism, the selection and ȍC, ܶ - are respectively, the seasonal load per GLဧULEXWLRQRIDJULFXOWXUDOPDFKLQHU\E\UHJLRQLVQRW machine and the average periodicity of parts obey the full value engineering calculations or control replacement, ha,h; FKHFNV DQG WKH QRPHQFODWXUHTXDQWLWDWLYH VHOHFWLRQ ݊ – is the number of parts repairs for the is mainly made by an individual approach. For this period of its service; reason, incomplete application of their capabilities or ܣ் – is the number of insurance fund sets cases of their work with overload is frequent. per machine. In addition, the general organization of material $WH[LဧLQJUHDVRQDEOHQRUPVIRUWKHFRQVXPSWLRQ ORJLဧLFVIRUWKHRSHUDWLRQRIDJULFXOWXUDOPDFKLQHU\ of spares, their required quantity would be WKDWLVWKHPDLQWDVNRIWKHORJLဧLFVDQGRLOSURGXFWV determined by the formula supply, provides a reliable modern supply of agricultural enterprises by the necessary machinery, n m M /100, (3) equipment and spares for them, as well as materials ɡɱ ɦ ɧ for the operation of these machines and equipment, where ܯ – is the rate of consumption of this as well as for all branches of the economy. part for 100 vehicles per year. 205 B.B. Basilashvili et al. Annals of Agrarian Science 17 (2019) 204 – 207 The required amount of materials for the repair, The general principles of the organization of PDLQWHQDQFH DQG ဧRUDJH R I PDFKLQHV ZRXOG the engineering and technical service described be determined in accord a nce with the available are also valid for the newly created machine and regulations according t o the following formula WHFKQRORJLFDOဧDWLRQV 076 WKHQXPEHURIZKLFK is continuously growing throughout all Georgia, Q ɉɆ (4) ɦɊɧɦ and whose main tasks are: rendering services in the production of mechanized works; processing where ܳெ – is the required quantity of materials, of agricultural products; provision of equipment kg, pcs., etc.; IRUUHQWDQGKLUH UHQGHULQJRIVHUYLFHVLQWKH¿HOG ʞ – is an annual program of this type work; of maintenance, including maintenance and repair ܯு.ெ – is the rate of consumption of this type of equipment; manufacture of spares; material of material per machine. ORJLဧLFV RI DJULFXOWXUDO HQWHUSULVHV LQ WKH VHUYLFH The annual requirement of the economy in the DUHD H[HFXWLRQ RI FRQဧUXFWLRQ ZRUNV HWF :LWK HDFK W\SH IXHO LV GHWHU P LQHG IURP WKH ဧDWLဧLFDO FRQVLGHUDWLRQRIWKHVHDUHDVRIDFWLYLW\WKHဧUXFWXUH GDWDRISDဧ\HDUVRUE\DVLPSOL¿HGFDOFXODWLRQE\ of the engineering and technical service of modern formula [3, 6] MTS is formed on the basis of general principles of ɗ VSHFLDOL]DWLRQ DQG GLYLVLRQ RI ODERU > @ ɬɞ ,QWKH¿HOGRIHQJLQHHULQJDQGWHFKQLFDOVHUYLFHV Qɬɝ Ȉ)4 L ɬL 1000 of large farms and MTS, with consent of farmers (5) would also be included the farm enterprises. On the where ்ܳ௰ – is the annual fuel consumption, t; orders of farmers, they can be provided with the ʬ். – is a correction factor that takes into ac- following types of services, either on a permanent count the additional fuel consumption, con- RU WHPSRUDU\ EDVLV RU RQ D RQHWLPH EDVLV nected with the inclination and roughness of implementation of mechanized activities for the the surface of the plots, passages, preparation production and realization of agricultural products; ܨ – is the volume of i work, ha, t, etc.; UHQW RI HTXLSPHQW RQ H൵HFWLYH DSSOLFDWLRQ DQG ்ܳ – is the fuel consumption per unit of per- PDLQWHQDQFHRIHTXLSPHQW VDOHDQGSUHVDOHVHUYLFH formed work, kg/ha, kg/t, etc. of machinery, etc. All these services are possible RQO\RQDYROXQWDU\PXWXDOO\EHQH¿FLDOEDVLVWKDW In the absence of more reliable data, the val- represents the fundamental principle of a market ue ʬ would be approximately accept as ʬ = ். ். economy. 1,05 ... 1,08. The values of ܨ and ்ܳ are ac- cepted accordingly of the flow charts and the Conclusion norms of production and consumption of fuel for mechanized work. 7KH FDOFXODWHG DFFRUGLQJO\ RI HQWHUSULVH¶V According to the ்ܳ is determined required production directions rational supply of its capacity of fuel storage tanks, m³ functioning by material and technical means, in particular the appropriate machinery, replacement VQ ɗȡ (6) x ɬɝ working bodies of machines and spares, materials IRU UHSDLU PDLQWHQDQFH DQG ဧRUDJH RI PDFKLQHV where ʬ – is the coefficient, taking into account DQQXDO IXHO UHTXLUHPHQWV DV ZHOO DV D TXDOL¿HG the necessary production stock of oil products; engineering and technical management of all ɏ – is the density of fuel. production processes, represents the determinative For diesel fuel and petrol, respectively, we can accept the average values ɏ=825 kg/m³ and factor of the whole activity and functioning of the ɏ=700 kg/m³. economy, not depending on its production scale. The numerical value of ʬ depends on the Rational organization and professional conditions for the delivery of oil products to the PDQDJHPHQW RI WKH SURFHVV RI PDWHULDO ORJLဧLFV farm and would vary from 0.1 up to 0.5. Averag- of agricultural technological processes represent a ing for common farms would be accepted as ʬ= QHFHVVDU\FRQGLWLRQIRUDFKLHYLQJRIRSWLPDO¿QDO 0.15 ... 0.20. results. The need for fuel for the month, season, etc. would be calculated by the formula (5). 206 B.B. Basilashvili et al. Annals of Agrarian Science 17 (2019) 204 – 207 References >@ %% %DVLODVKYLOL =6K 0DNKDUREOLG]H ,0 Lagvilava, Calculation of scale factors in WKH PRGHOLQJ RI WKH SURFHVVHV XQGHU ဧXG\ PURFHHGLQJVRI$JUDULDQ6FLHQFH9RO1R >@ 50 0DNKDUREOLG]H 0HWKRGV RI LPSDFW theory and rheology in agricultural mechanics. *DQDWOHED 7ELOLVL LQ 5XVVLDQ >@ %% %DVLODVKYLOL ,0 /DJYLODYD =6K Makharoblidze, R.M. Khazhomia, Criterial PRGHOLQJ RI ¿HOGKXVEDQGU\ WHFKQRORJLFDO processes service baskur. Annals of Agrarian 6FLHQVH 9RO 1R >@ 9$ $OLOXHY HW DO 7HFKQLFDO RSHUDWLRQ RI WKH PDFKLQH DQG WUDFWRU ÀHHW$JURSURPLGDW 0RVFRZ LQ 5XVVLDQ >@ -9 .DWVLWDG]H HW DO 7HFKQLFDO VHUYLFH RI PDFKLQHV*DQDWOHED7ELOLVL LQ5XVVLDQ >@ $$ =DQJLHY $9 6KSLONR $* /HYVKLQ 2SHUDWLRQRIWKHPDFKLQHWUDFWRUÀHHW.RORV 0RVFRZ LQ 5XVVLDQ >@ $3.DUDEDQLWVN\($.RFKNLQ7KHRUHWLFDO EDVLFV RI SURGXFWLRQ RSHUDWLRQ RI PDFKLQH WUDFWRU ÀHHW .RORV 0RVFRZ LQ 5XVVLDQ >@ %% %DVLODVKYLOL ,0 /DJYLODYD 2$ Asatiani, A.B. Kobakhidze, Modeling of running ability indicators of tandem wheeled VHOISURSHOOHG FKDVVLV $QQDOV RI $JUDULDQ 6FLHQVH 9RO 1R > @ $9 .X]QHWVRY )XHO DQG OXEULFDQWV .RORV 0RVFRZ LQ 5XVVLDQ 207 D.R. Khazhakyan Annals of Agrarian Science 17 (2019) 208 – 211 Annals of Agrarian Science :ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ Modeling of Technological Process In Rotary Tiller D.R. Khazhakyan National Agrarian University of Armenia, 74, Teryan Str., Yerevan, 0009, Armenia Received: 15 May 2018; accepted: 5 September 2018 A B S T R A C T 7RLGHQWLI\WKHVSHFL¿FVRIWKHLQWHUDFWLRQRIWKHVRLODQGWKHURWDU\ZRUNLQJHTXLSPHQWWKHLVVXHVRIPRGHOLQJWKHWHFKQRORJLFDOSURFHVV RIWKHURWDU\WLOOHUDQGLWVLQWHUDFWLRQZLWKWKHVRLOKDVEHHQLQYHဧLJDWHG&RPSDULVRQRIVRLOဧUDLQDQGGHIRUPDWLRQYDOXHVWKURXJKWKH DSSOLFDWLRQRIWKH$16<6:25.%(1&+VRIWZDUHHQDEOHGWRFRQFOXGHWKDWWKHKLJKHဧဧUDLQYDOXHLQWKHVRLOLVREVHUYHGGXULQJWKH VRLOFXWWLQJ7KHLVVXHVRIPRGHOLQJWKHWHFKQRORJLFDOSURFHVVHVRIWKHURWDU\WLOOHUDQGLWVLQWHUDFWLRQZLWKWKHVRLOKDVEHHQLQYHဧLJDWHG throughout the research. From this perspective it is important to measure the sizes of the slices cut from the soil and to identify the FXWWLQJIRUP7KHODWWHUDUHUHODWHGWRERWKWKHဧUXFWXUHRIWKHURWDU\WLOOHUDQGWKHPRYLQJYHORFLW\IRUZDUGVSHHGRIWKHVRLOFXOWLYDWLQJ machine, as well as to the rotating numbers of the operating equipment. At the same time during the planning of the working equipment LWLVSRVVLEOHWRJHWIXQFWLRQDOUHODWLRQVEHWZHHQYDULRXVSDUDPHWHUVဧXG\LQJWKHVSHFL¿FVRIWKHVHUHODWLRQVDQGLPSURYLQJWKHဧUXFWXUH of the working equipment. Keywords: Rotary tiller, Rotary hoe, Modeling, Soil, Strain, Deformation. &RUUHVSRQGLQJDXWKRU '.KD]KDN\DQ (PDLODGGUHVV NKD]KDN\DQ#JPDLOFRP Introduction tillers are used in such conditions, where no other alternative is left. When cultivating the soil with Soil cultivating machine with rotating equipment rotary hoes the soil looseness holds well for a long OLNHURWDU\WLOOHU RUURWDU\KRH FXWVWKHVRLOVOLFHV time. Sometimes the depth of rotary tillage amounts WXUQV RYHU WKH VRLO DQG HQDEOHV WR PL[ WKH VRLO WRFPWKHQWKHVRLOGHQVLW\GHFUHDVHVDWWKH SURSRUWLRQDOO\RUWRPL[WKHIHUWLOL]HUZLWKWKHVRLO depth of 30 cm. This is accounted for the vibration >@7KHVRLOFXOWLYDWLRQZLWKURWDU\KRHHQDEOHVWR LPSDFW>@RIWKHURWDU\WLOOHU¶VEODGHV SURYLGHWKHVX൶FLHQWVRLOORRVHQHVVZKLFKFUHDWHV ,QRUGHUWRဧXG\WKHZRUNRIWKHURWDU\WLOOHULWLV favorable conditions for the growth and development recommended to design it through software and to dynamics of the ferments vital for plants growth at model its process. WKH FP GHSWK RI WKH VRLO SORZLQJ KRUL]RQV It is relevant to implement the design works Thus, the soil reclamation with the rotary hoe has of the rotary tiller by means of SOILDWORKS DVLJQL¿FDQWO\SRVLWLYHLQÀXHQFHRQWKHELRORJLFDO software development kit, which has an opportunity conditions of the crops growth and development RI PDNLQJ GLYHUVH JHRPHWULFDO PRGL¿FDWLRQV DQG SURFHVV:LWKWKLVUHJDUGDQXPEHURIUHVHDUFKHUV> WKH ¿QLVKHG GHVLJQ LV SRVVLEOH WR IXUWKHU LQWHJUDWH @KDYHPHQWLRQHGWKDWWKHVRLOFXOWLYDWLRQZLWKWKH in the ANSYS Workbench software package, which URWDU\KRHKDVDSRVLWLYHH൵HFWRQWKHVRLOSK\VLFDO FUHDWHV D YDဧ SODWIRUP IRU DXWRPDWHG GHVLJQ DQG properties and on the improvement of water and DQDO\VHV ZLWK ¿QLWH HOHPHQWV >@>@ nutritional regime conditions in crops. 7KHGHVLJQRIWKHURWDU\WLOOHULVDဧDJHSURFHVV Application of rotary tillers promotes the and it should be implemented through the design of UHGXFWLRQRIWUDFWLRQUHVLဧDQFH7KDWLVZK\WKHVH LWVLQGLYLGXDOSDUWV)LUဧLWLVQHFHVVDU\WRGHVLJQLWV 208 D.R. Khazhakyan Annals of Agrarian Science 17 (2019) 208 – 211 GLVFDQGD[LVSODQQLQJWKHODWWHU¶VVL]HVDFFRUGLQJWR VROLG XQLWV LV REVHUYHG YLD ¿QLWH SDUWLFOHV 'XULQJ WKHIDဧHQLQJGHYLFHRIWKHSRZHUXQLW7ZRW\SHV the analysis of the problem, depending on the tasks RIEODGHVZHUHGHVLJQHG ဧUDLJKWDQGဧDSOHZKLFK and the required precision it is possible to decrease ZHUHLQဧDOOHGRQWKHGLVFRIWKHURWDU\WLOOHUE\WZR RULQFUHDVHWKHGLYLVLELOLW\UDWHRIWKH¿QLWHHOHPHQWV items intermittently. whereupon receiving the needed precision rate of The soil is also designed separately as a solid calculations. VXEဧDQFH VR DV LW ZRXOG EH IXUWKHU SRVVLEOH WR JHW WKH FKDUDFWHULဧLFV RI ZRUNLQJ HTXLSPHQW The aim of research soil interactions/ratio through its modeling and DWWULEXWLQJHODဧLFSURSHUWLHVWRWKHVRLO>@/DWHU The aim of the current research is to simulate the on, in order to model the soil inhomogeneity interaction of the rotary tiller with soil. it will be possible to design several parts of the XQLW PRGHOLQJ WKH VRLO ဧUXFWXUH DQG WR REVHUYH The object of research WKH FKDUDFWHULဧLFV RI WKH URWDU\ WLOOHU DQG VRLO 7KHREMHFWRIWKHFXUUHQWUHVHDUFKLVWKHLQWHUDFWLRQ interaction when the latter passes along the of soil – working equipment in the simulation FRQQHFWLQJ MXQFWXUHV RI WKRVH SDUWV environment. As it is known the rotary tiller implements For this purpose rotary tiller designed through the two types of movements: forward/linear and software of Solidworks has been introduced into the rotating. During the modeling process forward/ software environment of ANSYS Workbench, the sizes linear movement velocity is conveyed to the soil RIZKLFKKDYHJRWDQH[SHULPHQWDOQDWXUH&XWWLQJRI cultivating machine, while the working equipment the soil through rotary tiller is introduced in Fig. 1. is provided with rotational movement velocity. :KHQဧXG\LQJWKHVLPXODWLRQUHVXOWVZHQRWLFH 'XULQJWKHဧXG\RIWKLVဧDJHLWLVSRVVLEOHWRFDUU\ that as a result of cutting with the rotary tiller the out numerous measurements, which can serve as a soil deformation is higher than the geometrical base for the further improvement of the working VL]HV RI WKH EODGH ဧLFNLQJ 7KLV SKHQRPHQRQ equipment. is accounted for soil adhesion/coherence and %\DSSO\LQJWKHPHWKRGRI¿QLWHHOHPHQWVDQDO\VLV the vibratory character of the rotary tiller. The WKH VROLG XQLW FRQYHQWLRQDOO\ LV GLYLGHG LQWR ¿QLWH longitudinal deformation is higher than the sum HOHPHQWV ZKLFK FRPH IRUWK DV ¿QLWHFRQဧLWXHQW of the longitudinal sizes of oppositely arranged particles of the solid unit to which the parameters longitudinal blades, while the vertical deformation of the unit is attributed. Thus, the interaction of the is higher than the length of blade. Fig. 1.6RLOFXWWLQJVFKHPHWKURXJKURWDU\WLOOHU 209 D.R. Khazhakyan Annals of Agrarian Science 17 (2019) 208 – 211 25.24 -250 a P , n i a r t -500 s l i o S -750 -1000 -1079.8 0 2.5e-3 5.e-3 7.5e-3 1.e-2 Simulation period, s ———— Soil strain below the spike wedge ———— Soil strain above the spike wedge Fig. 2.6RLOVWUDLQYDOXHVGXULQJWKHFXWWLQJZLWKURWDU\WLOOHU While considering the soil– working equipment GLVFORVLQJWKHLUQDWXUHWRLPSURYHWKHဧUXFWXUH LQWHUUHODWLRQWKHVRLOဧUDLQZDVLQYHဧLJDWHGDVZHOO of the working equipment. the diagram of which is introduced below Fig. 2 2. 7KHVLPXODWLRQUHVXOWVVKRZWKDWWKHPD[LPXP Strain is the relation/ratio of deformation with ဧUDLQRIWKHVRLOLVPDQLIHဧHGDWWKHဧLFNLQJ the initial length of the unit or it is the relation of the moment of the blade, which should serve as XQLW D൵HFWLQJ SRZHU ZLWK UHJXODU GLUHFWLRQ ZLWK the main indicator for the improvement of the WKHD൵HFWHGVXUIDFH> @ ဧUXFWXUH LQ URWDU\ WLOOHU The diagram shows that at the moment when WKH EODGH RI WKH URWDU\ WLOOHU LV ဧXFN LQWR WKH VRLO References WKH ဧUDLQ LQFUHDVHV DEUXSWO\ ODWHU GXULQJ WKH >@0.HVKXDQ'/LH\XQ)LQLWHHOHPHQWDQDO\VLV cutting it is getting lower. This means that at the RI WXQQHOVRLOEXLOGLQJ LQWHUDFWLRQ XVLQJ accessing moment of the working equipment displacement controlled model, 7 th WSEAS WKH VRLO GHPRQဧUDWHV PD[LPXP UHVLဧDQFH DIWHU Int. Conf. on Applied Computer & Applied ZKLFK WKH UHVLဧDQFH GHFUHDVHV XQWLO WKH DFFHVV RI &RPSXWDWLRQDO 6FLHQFH $&$&26 ¶ WKHQH[WEODGH6RWKHGLDJUDPRIWKHUHJXODUဧUDLQ +DQJ]KRX &KLQD$SULO SS LQGLFDWHVWKDWLQRUGHUWRLPSURYHWKHဧUXFWXUHRI 311. working equipment in the rotary tiller it is vital to >@ 05$]DGL61RUGDO06DGHLQ1RQOLQHDU SD\ DWWHQWLRQ WR VXFK IDFWRUV ZKLFK LQÀXHQFH WKH EHKDYLRURISLOHVRLOVXEMHFWHGWRWRUVLRQGXHWR GHFUHDVHRIUHVLဧDQFHDWWKHFXWWLQJPRPHQW7KH\ HQYLURQPHQWDOORDGVRQMDFNHWW\SHSODWIRUPV DUHIRULQဧDQFHWKHDWWDFNDQJOHEODGHVKDUSQHVV WSEAS Transactions on Fluid Mechanics, sharpening angle, the blade form, etc. LVVXHYROXPH >@ 30 9DVLOHQNR &XOWLYDWRUV &RQဧUXFWLRQ Conclusion 7KHRU\ DQG &DOFXODWLRQ 3XEOLVKLQJ +RXVH of the Academy of Sciences of the Ukrainian 1. During the design of the working equipment 665 .LHY LQ 5XVVLDQ it is possible to obtain functional relations >@ *1 6LQHRNRY 7KHRU\ DQG &DOFXODWLRQ RI between various parameters and through 210 D.R. Khazhakyan Annals of Agrarian Science 17 (2019) 208 – 211 WKH 5RWDU\ 7LOOHUV 0DFKLQHU\ &RQဧUXFWLRQ 0RVFRZ LQ 5XVVLDQ >@ ** 5DP]DQRYD $QDO\VLV RI WKH :RUNLQJ Bodies of Tillage Cutters, Electronic Bulletin 56ȿ$83DUW0RVFRZ LQ5XVVLDQ >@ 0DJG $EGHO :DKDE 7KH 0HFKDQLFV RI Adhesives in Composite and Metal Joints: Finite Element Analysis with ANSYS, 2014. >@ 'DU\O / /RJDQ$ )LUဧ &RXUVH LQ WKH )LQLWH Element Method, Fifth edition, Cengage Learning, 2011. >@ $ +HDWK $ ဧUDLQEDVHG QRQOLQHDU HODဧLF model for geomaterials, WSEAS transactions on applied and theoretical mechanics, issue 6, YROXPH > @-/XEOLQHU3ODVLFLW\7KHRU\5HYLVHG(GLWLRQ University of California at Berkeley, 2006. >@ 6 - 3RXORV 7KH 6WUHVV6WUDLQ &XUYH RI Soils, GEI Internal Report, 1971. 211 T. Qachashvili et al. Annals of Agrarian Science 17 (2019) 212 – 217 Annals of Agrarian Science :ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ Introduced Holstein Breed Livestock in Georgia T. Qachashvilia, L. Tortladze, A. Chkuaseli Agricultural University of Georgia, 240, David Aghmashenebeli Ave., Tbilisi, 0159 Georgia Received: 15 May 2018; accepted: 5 September 2018 A B S T R A C T 7KHFXUUHQWZRUNUHSUHVHQWVWKHDGDSWDWLRQSHUVSHFWLYHRI+ROဧHLQ%UHHG/LYHဧRFNLQWURGXFWLRQLQ.DNKHWLLQWHQVLYHDJULFXOWXUDO ]RQHRI*HRUJLDDQGWKHSKHQRW\SLFDOH[WHULRUDQGLQWHULRUSHFXOLDULWLHVRIWKHPLONFDVKFRZVUHVHDUFKHGE\XV%HVLGHVWKHDERYH ZHFRQGXFWHGWKHDQDO\VLVRIWKHVFLHQWL¿FUHVHDUFKRQLPSRUWDQWIDFWRUVZKLFKZLOOFRQWULEXWHWRVXFFHVVIXOEUHHGLQJRI+ROဧHLQ /LYHဧRFNLQORFDOQDWXUDODQGFOLPDWHFRQGLWLRQV7KHဧXG\RIDFFOLPDWL]DWLRQSURFHVVRI+ROဧHLQ/LYHဧRFNGHPRQဧUDWHGWKDWWKH KHDWUHVLဧHQFHLQGH[LQQHZO\ERUQFRZVLVXQLWVORZHUWKDQLQQRQSDUWXULHQWFRZV)ROORZLQJWKHUHFRPPHQGHGTXDOLW\DQG amount of nutriment ration ensured the normal health condition and maiantained the level of reproductivity ability. As a result we KDYHRIOLYHဧRFNW\SHဧDQGDUGOLYHZHLJKWUHWDUGDWLRQDQGZLWKHUVKHLJKW,WVKRXOGEHPHQWLRQHGWKDWWKHUHFHLYHGGDWDFDQ be considered acceptable dynamic in the conditions of Georgia. As for bringing arterial pulse and breathing rate to norm – it became SRVVLEOHDIWHULQဧDOOLQJUHFLUFXODWLQJIDQVLQFRZဧROOV7KXVWKHFOLQLFDODQDO\VLVDVZHOODVOLYHZHLJKWJURZWKDQGGHYHORSPHQW G\QDPLFRIWKHWHဧHG+ROဧHLQW\SHKHLIHUVGHPRQဧUDWHGWKDWWKHWHဧHGLQGLFHVDUHZLWKLQWKHSK\VLRORJLFDOQRUPV Keywords: +ROဧHLQDGDSWDWLRQKHDWUHVLဧDQFHSURGXFWLYLW\QXWULPHQWUDWLRQJURZWKDQGGHYHORSPHQW &RUUHVSRQGLQJDXWKRU 74DFKDVKYLOL (PDLODGGUHVV WTDFKDVKYLOL#FDXFDVXVJHQHWLFVJH Introduction well as big capacity of milking which is achieved WKURXJKKHDOWK\DQGEDODQFHGIRRG>@ 1DWXUDO PLON SURGXFWLRQ KDV EHHQ WKH PRဧ ,Q WKH 86$ PRUH WKDQ RI OLYHဧRFN LV urgent problem in Georgia for a long time which +ROဧHLQEUHHGDQGWKHPLONLQJFDSDFLW\RIHDFKLV LQ WKH FRQGLWLRQV RI H[LဧLQJ H[WHQVLYH V\ဧHPV LQ PRUHWKDQ NJ7KH+ROဧHLQ$VVRFLDWLRQKDV ဧRFN EUHHGLQJ UHTXLUHV LPPHGLDWH LQWHQVL¿FDWLRQ UHJLဧHUHG PLOOLRQRIFDWWOHLQWKHFRXQWU\>@ implementation of various necessarry activities ,Q *HUPDQ\ WKH +ROဧHLQ VKDUH LQ WKH SRSXODWLRQ in line with breeding and adaptation of intensive LV LQ OLYHဧRFN IDPUV PRUH WKDQ EUHHGV RI OLYHဧRFN million of cattle of high capacity. In Europe the 7RGD\LQPRဧRIWKHFRXQWULHVZKHUHWKHQDWXUDO improvement of the breed is implemented according PLONSURGXFWLRQSUREOHPLVVROYHGWKHUHLV+ROဧHLQ WRWKHSODQDQGWKHSURFHVVLVPDQDJHGE\ȿȺȺɊ ဧRFN EUHG ,W LV QRW RFFDVLRQDO WKDW WKH +ROဧHLQ (XURSHDQ)HGHUDWLRQRI$QLPDO6FLHQFH >@,IZH breed cattle is in the center of attention, it is the UHYLHZ (Dဧ DQG LQ SDUWLFXODU ,VUDHOL H[SHULHQFH PRဧSRSXODUEUHHGLQPLONSURGXFWLRQVHFWRUZKLFK WRGD\WKHUHLVDSSUR[LPDWHO\RQHKXQGUHGWKRXVDQG LV DOVR GLဧLQJXLVKHG IRU LWV OLYH ZHLJKW GLဧLQFW cattle which produces around 1 billion kg of milk milking forms, with the special form and location of annually which fully meets the needs of local udders which despite the capacity is located higher population on milk and milk products and a part of DQGVSUHDGVLQZLGWKZKHQ¿OOHGXS%HVLGHVWKH WKH SURGXFWV LV H[SRUWHG >@ DERYH WKH +ROဧHLQ EUHHG RI FDWWOH KDV SHFXOLDU 2YHU WKH ODဧ \HDUV IDUPHUV LPSRUW (XURSHDQ quality of its intensive growth and development as breed cattle in Georgia. Due to the peculiarities 212 T. Qachashvili et al. Annals of Agrarian Science 17 (2019) 212 – 217 RI KRPHRဧDWLF FDSDFLWLHV WKH VHW RI SK\VLRORJLFDO • 5HJLဧHURIWKHUHFHLYHGQXWULPHQWV disorders causing negative results is revealed. • Study of the nutritiousness of the nutriments; ,W LV LGHQWL¿HG WKDW DSDUW IURP RWKHU EUHHGV WKH • Dynamics and calculation of average daily +ROဧHLQEUHHGPRUHHDVLO\DGRSWVWRHQYLURQPHQWDO weight gain of heifers; FRQGLWLRQVDQGWRDFKLHYHWKHPD[LPXPRILWVJHQHWLF capacity it is necessary to create conditions which EHဧFRUUHVSRQGWRLWVJHQRW\SH&RQVHTXHQWIURP Results and Analysis WKHDERYHEUHHGLQJRI+ROဧHLQFDWWOHLQXQW\SLFDO natural environment is very important. In general Development of peculiarities of an organism the genetically predetermined norm of reaction of GHSHQGVRQKHUHGLW\ JHQRW\SH DQGHQYLURQPHQWDO DQLPDOVGH¿QHVLWVHQYLURQPHQWDGDSWDWLRQFDSDFLW\ conditions. When we are talking about the limits. It is noteworthy that in some cases the DGDSWDWLRQ RI DQLPDOV WR WKHVH RU WKRVH H[WUHPH ignorance of adaptation peculiarities impeded the conditions we agree to take into consideration the DGMXဧPHQWWRH[WUHPHHQYLURQPHQWDOFRQGLWLRQV> fact that any dislocation of animals is accompanied @ by negative results. Environment is the basic 7RGD\ WKHUH DUH FRZV LQGXဧULDO EUHHGV limiting factor of revealing genetic capacities of imported in our country. Out of this number 2170 DQRUJDQLVP,QWKHFRQGLWLRQRIH[WUHPHO\KLJKDLU LV+RVOWHLQEUHHGDQGWKHPRဧRIWKHP DUH WHPSHUDWXUH LQÀXHQFH (XURSHDQ PLON FRZ EUHHGV in Kakheti region. It should be mentioned that the DUH FKDUDFWHUL]HG E\ OLPLWHG KRPHRဧDWLF FDSDFLW\ breeding of Hosltein cattle in Kakheti intensive which results in the whole set of physiological DJUDULDQ ]RQH KDV QRW EHHQ VFLHQWL¿FDOO\ ဧXGLHG disorders causing decrease in reproductivity, and there are no corresponding recommendations growth intensity, milking productivity, period of GHYHORSHG ,W LV XUJHQW WR ဧXG\ WKH SHFXOLDULWLHV DJULFXOWXUDO H[SORLWDWLRQ DQG RWKHU XQGHVLUDEOH RI +ROဧHLQ FRZ SURGXFWLYLW\ SRWHQWLDO UHDOL]DWLRQ UHVXOWV,WLVREYLRXVWKDWFRQVLGHULQJWKHH[LဧLQJ DV ZHOO DV WR ဧXG\ WKH HFRQRPLF DQG ELRORJLFDO natural and economic conditions and biological peculiarities of it in the new environmental SHFXOLDULWLHV RI FDWWOH SUHGH¿QHV WKH VHOHFWLRQ RI FRQGLWLRQVZKLFKLVRIVLJQL¿FDQWQDWLRQDOHFRQRPLF relevant technological methods in cattle farming LPSRUWDQFH GHYHORSPHQWRILQWHQVLYHIDUPLQJDQG >@ LQFUHDVHRIUDZPLONSURGXFWLRQ ZKLOHRQWKHRWKHU 2Q WKH ¿Uဧ ဧDJH RI FDWWOH IDUPLQJ RI WKH hand, in order to reveal the high genetic qualities of nulliparous and primaparous cows the whole set this breed, it is necessary to create such conditions of problems related to feeding and breeding arose. which fully correspond to its genotype. 7KRXJKWKHUHYHDOHGPLဧDNHVZHUHHOLPLQDWHGDQG the technological process was improved. ,W LV SDUWLFXODUO\ LPSRUWDQW WR GH¿QH FOLQLFDO Goal and Methodology of the Research LQGLFDWRUV FKDQJHV LQ WKH LQGLFDWRUV DFFRUGLQJ 7KH JRDO RI RXU UHVHDUFK ZDV VFLHQWL¿F WR YDULRXV IDFWRUV RI FDWWOH LQ WKH SURFHVV RI MXဧL¿FDWLRQ RI +ROဧHLQ FDWWOH EUHHGLQJ LQ WKH adaptation to new environmental conditions which conditions of Kakheti region. To accomplish the HQDEOHVWRGH¿QHLWVKHDOWKFRQGLWLRQ7KHUHZLWKDO UHVHDUFK ZH REVHUYHG EUHHGV RI PRQWKV the important criteria which characterize the SUHJQDQW QRQSDURXV +ROဧHLQ FDWWOH LPSRUWHG quality of adaptation and its maintenance in the IURP (ဧRQLD E\ 1RUVKL /WG RQ 0DUFK given environment are growth and development, Consequent from the research goal the observation SURGXFWLYLW\ DQG UHSURGXFWLYLW\ >@ was conducted over the whole herd as well as over 9LVXDOREVHUYDWLRQRIWKHDQLPDOVGHPRQဧUDWHG the breeding and development of locally reproducted that the imported animals are less adapted to FDOYHV ဧXGLHG KHLIHUV IURP WKHLU ELUWK WLOO WKH WKH VXPPHU KHDW :H ဧXGLHG WKH UHVLဧHQFH WR DJHRIFRSXODWLRQ ,QSDUDOOHOZLWKWKHDERYHZH the high temperatures by nonporous speices by accomplished zoo technical analysis of the food. FDOFXODWLQJ WKH KHDWUHVLဧHQFH LQGH[ DFFRUGLQJ WR Consequent from the mentioned goals the ,$5DXVFKHQEDFK>@7KH¿UဧWHဧZDVGRQHLQ following results were obtained in the period of the WKH PRUQLQJ R¶FORFN ZKHQ DLU WHPSHUDWXUH research: ZDV ɨɋ WKH VHFRQG WHဧ ZDV GRQH GXULQJ • 'HVFULSWLRQRIWKHFOLQLFDOဧDWXVLQGLFDWRURI WKHKRWGD\WLPHSHULRGDWR¶FORFNZKHQWKH WKHFDWWOHLQGL൵HUHQWSHULRGVRISURFUHDWLRQ WHPSHUDWXUH ZDV ɨɋ 7KH KHDW UHVLဧDQFH 213 T. Qachashvili et al. Annals of Agrarian Science 17 (2019) 212 – 217 LQGH[RIQRQSRURXVFRZVZDVORZHUWKDQRISULP a result of it the ethanoic acid decreases to 40%, parous cows. The body temperature of nonporous propionic acid is increased by 40%. The decrease cows in the morning under the condition of 200ɋDLU of ethanoic acid in its turn causes the following: temperature was 38,80ɋZKLOHWKHERG\WHPSHUDWXUH decrease of milk and fat formation, toughening of prim parous cows varied from 38,2 to 38,40ɋ of active champing, decrease in saliva formation. under the condition of 300ɋDLUWHPSHUDWXUHWKHERG\ ,QVX൶FLHQF\ RI EX൵HU VXEဧDQFH QHXWUDOL]HU temperature of nonporous cows increased by 0,80ɋ results in increase of acidity which, in its turn, is DQGLQSULPSDURXVFRZVLWLQFUHDVHGE\0ɋ D SUHFRQGLWLRQ RI GHFUHDVH RI FHOOXORVH GLJHဧLRQ &RUUHVSRQGLQJO\ WKH LQGH[ RI KHDWUHVLဧDQFH RI > @$VLWZDVDOUHDG\PHQWLRQHGLQFDVHWKDWVXFK SULPSDURXVFRZVZDVXQLWVOHVVWKDQWKDWLQ SURFHVV ODဧV LW PD\ FDXVH IDW UHGXFWLRQ LQ PLON nonporous cows. LQÀDPPDWLRQRIMRLQWVDQGFORYHQKRRIVOLTXLGဧRRO In line with it we revealed the number of visually $OOWKHDERYHFDXVHGGLVSURSRUWLRQRIVXJDUSURWHLQ observed problems such as saliva foam formation FRUUHODWLRQ WKHQRUPLV ZKLFKPHDQVWKDW GXULQJWKHFKHZLQJSURFHVVLQÀDPPDWLRQRIMRLQWV JUPSURWHLQPXဧFRQWDLQJURIVXJDU ,W DQGFORYHQKRRIVOLTXLGဧRRODQGLQVRPHFDVHV is known that the quality and volume of the feed loss of the cattle The conducted zoological analysis FRPSRQHQW VXEဧDQFHV DV ZHOO DV WKHLU FRUUHODWLRQ of the feed and its ingredients revealed: GH¿QHVWKHH൵HFWLYHQHVVRIWKHIHHGZKLFKHQVXUHV • The protein content is low; the productivity, health and reproductive capacity of • 7KHSRUWLRQRIQXWULWLRXVQHVVLQWKHIHHGLV DQLPDOV >@ 40% In parallel we observed the breeding of the • 7KH FRQFHQWUDWHG IHHG FRQWHQW LQ FRUQ VLOɚJH calves. We selected 12 units of the same age based LVFRQVHTXHQWIURPLWVQXWULWLRXVQHVV on the analogy. It is known that the correct breeding WKRXJKLWVKRXOGQRWH[FHHG RIWKHFDOYHVGH¿QHVWKHKHDOWKDQGUHSURGXFWLYLW\RI • The ration contains big number of the mature cows at the same time the live weight of FDUERK\GUDWHV VXJDUဧDUFK ZKLOHDFFRUGLQJ DQDQLPDODWFHUWDLQDJHDQGLWVH[WHULRUUHSUHVHQWV WRWKHQRUPWKHUDWLRQRIDPLONLQJFRZPXဧ the indicator of the growth quality. FRQWDLQJURIVXJDUSHU)8 JU :HXVHGWKHEUHHGဧDQGDUGIRUFRPSDULVRQ>@ '0 SHU NLOR DQG JU RI ဧDUFK Based on the capacity of the farm we tried to use • 7KHXVHRINJRIVRGDDVDEX൵HUUHGXFHV WKH UDWLRQDO V\ဧHP RI EUHHGLQJ ZKLFK VXSSRUWV the energy content in the ration which in turn the normal growth and development, and ensures causes the reduction of the milking; IRUPDWLRQRIKLJKFDSDFLW\DQGဧURQJFRQဧLWXWLRQ • The corn grains in silage is not powdered The feed ration was composed of the available feed ZKLFK KLQGHUV LWV GLJHဧLRQ components with the consideration of feeding norms • 7KHQXWULHQWPL[WXUHLVRYHUJULQGHG )LJ which gave us the guarantee that we receive such Unbalanced feed of cows, the use of concentrates desirable weight of the animals which will meet the LQFOXGLQJFDUERK\GUDWHVLQELJDPRXQWGHPRQဧUDWHG UHTXLUHPHQWVRIWKH¿UဧFODVVDQGKLJKHUဧDQGDUGV QHJDWLYHH൵HFWRQ3+RI¿UဧဧRPDFKRQJHQHUDWLRQ GXULQJWKH¿UဧPDWLQJ$OOWKHDERYHHQVXUHVWKDW of evaporating fatty acids and their correlation. As we get desirable live weight of cows in future. Average Indicators of the Cattle 84.4 69.2 56.3 65 39.4 38.2 38.5 26.5 18.5 Breathing sec. Puls sec Temperature C August 69.2 84.4 39.4 October 26.5 56.3 38.2 Norm 18.5 65 38.5 August October Norm Fig. 7KH$YHUDJH&OLQLFDO,QGLFDWRUVRIWKH&RZV 214 T. Qachashvili et al. Annals of Agrarian Science 17 (2019) 212 – 217 Table 1.)HHGFRQVXPSWLRQIURPELUWKWRWKHDJHRIPRQWKVSHURQHDQLPDO Feed kg Dry substance. kg mgj Feed unit Digestable pro- tein, kg milk 410 32,0 1,11 123 13,5 concentrate 650 578,5 7,67 650 72,15 hay 720 597,6 5,04 324 36,7 Oat straw 430 356,9 2,45 94,6 5,59 Silage 2070 517,5 4,76 476,1 28,98 Green mass 3400 697,0 88,4 680 88,4 Total 7750 2779,5 109,4 2347,7 245,32 Table 2.*URZWKDQGGHYHORSPHQWG\QDPLFRIKHLIHUVQ Result in correlation Result in correlation Stand- Age/months Standard/mass/kg with the standard, with the standard, ard/height, cm kg cm 2 75 71 83 82 8 235- 237 112 110 15 390- 395) 386 128 125 22 550- 555) 520 137 134 Holsteiner breed standard considers: live mass standard – live mass and whithers height. Despite of 75 kg in 2 months of age, by the end of milk the above these indicators may be considered feed period [23]. The indicators of the tested applicable in local conditions. heifers was 5% less than the standard. At the age Breathing is an unintegrated sign of life. of 8 months the standard is 237 kg [23], which The volume of oxygen in the organism of cattle is 3% more than the tested heifer mass; and at is limited thus it requires to get oxygen from the age of 15 months the standard is 395 kg while the environment. The dynamic of respiratory the locally bred heifers achieved 386 kg. This movements demonstrated that the respiration indicator is considered a good result in Georgian frequency is directly related to the age. It is reality but it lagged behind compared to the similar to puls frequency variability – the highest European standard. The tested heifer also showed indicator is registered at birth and it dicreases retardation by 3-4% in height growth compared with the age which varies within the norm. to standard. The listed disadvantages need to According to the literature data the body be taken into consideration when planning temperature of animals is almost permanent and the growth of heifers though usually these are GRHV QRW VXIIHU VLJQL¿FDQW FKDQJHV H[FHSW VLFN ignored. animals). Apart to the temperature the puls of The observation over the dunamic of animals and especially the breathing frequency the growth and development of the animals VLJQL¿FDQWO\ FKDQJHV demonstrated 2-3% of retardation from the breed 215 T. Qachashvili et al. Annals of Agrarian Science 17 (2019) 212 – 217 Table 3.&OLQLFDO6WDWXVRIWKH+HLIHUV Age, month Temperatureɋ Pulse PLQXWH Respiration frequency At birth months months months months Table 4.&OLQLFDO6WDWXVRI$QLPDOV Test period Frequency of Arterial Breathing Frequency Pulse Pregnancymonths Pregnancy months First parturition The puls frequency of the tested six to nine sign of pathology. The body temperature during months pregnant nulliparous cows showed the the parturition is particularly worthy attention. puls frequency increase by 13 beats (11.9%). The +LJKWHPSHUDWXUHPD\EHFDXVHGE\WKHLQÀXHQFH puls increase to 85 beats per minute during the of thte environment on the body of a newborn calf, ¿UVWSDUWXUȈWLRQ+HQFHWKHSXOVHIUHTXHQF\ZDV later the temperature may slightly change though VHYHUDOWLPHVOHVVLQWKH¿UVWKDOIRIWKHSUHJQDQF\ it varies within the physiological norm limits. As period than in the second half and especially for the heart contraction frequency, i.e. puls – it is compared to the parturition. The results of the periodic rythmal blood vessels widening which is respiration frequency data analysis are similar FRQQHFWHGWRWKHG\QDPLFRIYHVVHOV¿OOLQJGXULQJ ZKLFKFDQEHMXVWL¿HGE\WKHKRWVXPPHUGD\V the one cycle of the heart. Particularly high puls 7KHVXPPHUKHDWEHFDPHLQMXULRXVIRUWKHQHZO\ was detected in claves during the parturition which imported animals. Due to the bad ventilation of ODWHU ZDV GHFUHDVHG DQG LQ WKH DJH RI VL[ PRQWKV WKH EXLOGLQJ WKH ¿Uဧ V\PSWRPV RI WKHUPDO ဧUHVV it reaches 70, 20 beats a minute. Later it decreases ZHUH UHYHDOHG IUHTXHQW EUHDWKLQJ FRQFHWUDWLRQ PRUHWREHDWVDQGFKDQJHVVLJQL¿FDQWO\XQWLOWKH of animals at water places, saliva formation, foam copulation. At the same time all variations of the DWWKHPRXWKDQGHWF ,QLQဧDQWUHVSRQVHWRWKH indicators were within the physiological limits of mentioned the recirculation fans were montaged the breed. LQWKHULJKWDQGOHIWVLGHVRIWKHIDUPLQP GLဧDQFH IURP WKH IHHG WDEOH Conclusion The body temperature of an animal is the - ,QGH[RIKHDWUHVLဧHQFHRISULPDSDURXVFRZV FRPSOH[LQGLFDWRUVRILWVWKHUPDOFRQGLWLRQZKLFK ZDVXQLWVOHVVWKDQWKDWLQQRQSRURXV gives clear picture of its organism condition. In cows. hot weather the evening temperature of the cattle - The quality and volume as well as the LV & KLJKHU FRPSDUHG WR WKH QRUP ZKLFK correlation of nutriments in the animal feed PXဧ QRW EH FRQVLGHUHG D SDWKRORJ\ >@ GDLO\UDWLRQGH¿QHGWKHဧDELOL]DWLRQRIWKHIHHG degrees increase of the body temperature is the consumption ration for animals to maintain 216 T. Qachashvili et al. Annals of Agrarian Science 17 (2019) 212 – 217 production and normal health and reproduction +ROဧHLQ &RZV LQ Annals of Agrarian Science :ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ +HDY\PHWDOVVSHFL¿FSURWHRPLFUHVSRQVHVRIDKLJKO\UHVLVWDQW Arthrobacter globiformis 151B O. Rcheulishvilia,c,f*, L. Tsveravab, A. Rcheulishvilia, M. Gurielidzed, R. Solomoniab, N. Metrevelic, N. Jojuaf, H-Y Holmane aDepartment of Physics of Biological Systems of Andronikashvili Institute of Physics of Iv. Javakhishvili Tbilisi State University, 6, Tamarashvili Str., Tbilisi, 0177, Georgia bCentre for Pathogen Research, Ilia State University, 3/5 Kakutsa Cholokashvili Ave., Tbilisi, 0162, Georgia cInstitute of Biophysics, Ilia State University, 3/5 Kakutsa Cholokashvili Ave., Tbilisi, 0162, Georgia dS.Durmishidze Institute of Biochemistry and Biotechnology of the Agricultural University of Georgia, 240, David Aghmashenebeli All., Tbilisi 0159, Georgia eLawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA f(XURSHDQ8QLYHUVLW\6DUDMLVKYLOL$YH7ELOLVL *HRUJLD Received: 21 September 2018; accepted: 12 December 2018 A B S T R A C T 7KHJUDPSRVLWLYHDHURELFEDFWHULD$UWKUREDFWHUJORELIRUPLV%LVDSURPLVLQJFDQGLGDWHIRUELRUHPHGLDWLRQRI&U 9, DQGRWKHU PHWDOVLRQVEHFDXVHLWH[KLELWVUHVLဧDQFHDJDLQဧKLJKFRQFHQWUDWLRQVRI&U 9, DQGRWKHUPHWDOOLFLRQV7KLVEDFWHULDOVSHFLHVFRXOG UHGXFHKLJKO\WR[LFDQGFDUFLQRJHQLF&U 9, LQWR&U ,,, ,QWKLVဧXG\ZHLQYHဧLJDWHGWROHUDQFHDQGDFFXPXODWLRQRI&U 9, DQG=Q ,, RQSURWHLQOHYHOE\SURWHRPLFDSSURDFK$UWKUREDFWHUJORELIRUPLV%ZDVJURZQDWIROORZLQJFRQGLWLRQV ZLWK&U 9, ZLWK =Q ,, ZLWKRXW&U 9, DQG=Q ,, %DFWHULDOFHOOVZHUHKDUYHဧHGLQDWLPHGHSHQGHQWIDVKLRQ DQGKDIWHUWKHဧDUWLQJRI FXOWLYDWLRQ DQGFKDQJHVLQSURWHRPHH[SUHVVLRQZDVDQDO\]HGXVLQJWZRGLPHQVLRQDOJHOHOHFWURSKRUHVLVDQGliquid chromatography DQG PDVV VSHFWURPHWU\ /&0606 FRXSOHG ZLWK ELRLQIRUPDWLFV WR LGHQWLI\ SURWHLQV 6LJQL¿FDQW FKDQJHV LQ SURWHLQ H[SUHVVLRQ LQFOXGHGERWKXSDQGGRZQUHJXODWLRQRIGL൵HUHQWJURXSVRISURWHLQV0RဧUHPDUNDEOHFKDQJHVZHUHDVVRFLDWHGZLWKPHWDOELQGLQJ SURWHLQVDQGSURWHLQVLQYROYHGLQDFWLYHWUDQVSRUW3DUDOOHOH[SHULPHQWVZLWKAtomic Absorption Spectroscopy revealed that reduced FKURPLXPDSSHDUVPRဧO\VROXEOHDQGPDLQO\DVVRFLDWHGZLWKRUJDQLFV HVSHFLDOO\ZLWKEDFWHULDOSURWHLQV2XUUHVXOWVVLJQLI\WKDW $UWKUREDFWHUJORELIRUPLV%LVQDWXUDOO\HTXLSSHGDWWKHSURWHRPLFOHYHOFRUUHVSRQGLQJO\ZLWKWKHUHOHYDQWJHQHVWRVXUYLYHH[WUHPH WR[LFFRQGLWLRQVWKXVKDVJUHDWSRWHQWLDOIRUELRUHPHGLDWLRQ Keywords:+HDY\PHWDOV3DUDOOHOH[SHULPHQWV%LRLQIRUPDWLFV%DFWHULDOSURWHLQ%DFWHULDOFHOOV$UWKUREDFWHU &RUUHVSRQGLQJDXWKRU 2OLD5FKHXOLVKYLOL (PDLODGGUHVV ROLDUFKHXOLVKYLOL#LOLDXQLHGXJH Introduction %LV*UDPSRVLWLYHDHURELFEDFWHULDZKLFKFDQ VXUYLYHLQKHDY\PHWDOFRQWDPLQDWHGWHUULWRU\DQG Arthrobacter and many other members of the KDVKLJKSRWHQWLDOIRUHQYLURQPHQWUHPHGLDWLRQ>@ actinobacteria group are common residents of soil 7KLVဧUDLQZDVLVRODWHGRXWRIEDVDOWVDPSOHVIURP DQG KDYH KLJK WROHUDQFH WR ဧUHVVIXO FRQGLWLRQV heavy metal contaminated site of Georgia –Kazreti encountered in the soil environment, including >@2XUSUHYLRXVဧXGLHVE\(65VSHFWURVFRS\KDV WKH DELOLW\ WR GHJUDGH SDUDVXEဧLWXWHG SKHQROLF shown that bacteria posses the ability to reduce compoundsDQGKXPLFVXEဧDQFHV>@7KHSDUWLFXODU &U 9, LQWR &U ,,, ZKLFK LV OHVV VROXEOH DQG OHVV ဧUDLQ RI WKLV IDPLO\ $UWKUREDFWHU JORELIRUPLV 218 O. Rcheulishvili et al. Annals of Agrarian Science 17 (2019) 218 – 229 WR[LFFRPSRXQG>@FTIR absorption spectroscopy ZLWKRXW RU ZLWK &U 9, DQG =Q ,, SURFHHGHG VKRZHG WKDW $UWKUREDFWHU R[\GDQV LV FDSDEOH WR without medium renewal. UHGXFH &U 9, DQG FRPSOHWH XSWDNH RI ȝJP/ RI &U 9, FRQFHQWUDWLRQ ZDV DFKLHYHG LQ DERXW GD\VDIWHU&KURPLXPDGGLWLRQLQWRWKHPHGLXP>@ We have also shown that &U 9, UHGXFWLRQ SURFHVV LV YHU\ IDဧ DQG RFFXUV RQ EDFWHULDO FHOO ZDOO >@ 7KLVUHGXFWLRQLVQRWLQÀXHQFHGE\WKHSUHVHQFHRI =Q ,, DW FRQFHQWUDWLRQ RI PJ/ EXW WKH KLJKHU FRQFHQWUDWLRQV PJ/ LQKLELWV WKH UHGXFWLRQ RI &U 9, E\ SUHYHQWLQJ WKH FRQWDFW RI &U 9, ZLWK EDFWHULDO FHOO ZDOO >@ 7KH &U 9, UHGXFWLRQ PHFKDQLVPVDQGWKHIDWHRIUHGXFHG&U ,,, DUHXQGHU ဧXG\6RPHRIဧXGLHVSURYLGHHYLGHQFHWKDW&U 9, reduction is an enzymatically catalyzed reaction DWWULEXWHG WR VROXEOH SURWHLQV IRU VRPH EDFWHULD >@ DQG FHOO PHPEUDQHV IRU RWKHUV > @ )XUWKHU ဧXG\ RI WKH PHFKDQLVPV &U 9, reduction by $UWKUREDFWHUJORELIRUPLV 151B is an important topic, because such bacteria could be Fig. 1. 7KHVFKHPHRIH[SHULPHQWDOGHVLJQ H൵HFWLYHO\ XVHG IRU ELRUHPHGLDWLRQ SURFHVVHV ,Q WKH SUHVHQW ဧXG\ ZH KDYH LQTXLUHG LI KHDY\ PHWDO H[SRVXUH &U 9, =Q ,, LQGXFHV FKDQJHV LQ (YDOXDWLRQRI&U 9, DQG=Q ,, UHVLဧDQFH the proteome of $UWKUREDFWHUJORELIRUPLV 151B and ZKDWLVWKHIDWHRIUHGXFHG&U ,,, ([SHULPHQWV Culture growth was monitored by measuring were conducted in a time dependent fashion and optical density at 490 and 590nm. The viability was ' HOHFWURSKRUHVLV06 DQG $WRPLF $EVRUSWLRQ detected by cell growth on agar plates with a cell 6SHFWURVFRS\ $$6 DSSURDFKHVZHUHXVHG$VIDU VXVSHQVLRQ GLOXWLRQ %DFWHULDO UHVLဧDQFH DJDLQဧ DVZHNQRZQRVXFKဧXGLHVZHUHFRQGXFWHGEHIRUH =Q ,, DQG&U 9, ZDVGHWHFWHGE\FRXQWLQJRIWKH Colony Forming Units on metal containing agar SODWHV&HOOYLDELOLW\ZDVREVHUYHGRQKLJK ! Materials and methods PJO PHWDO FRQFHQWUDWLRQ FRQGLWLRQV Bacterial Growth Conditions $IWHU JURZLQJ EDFWHULDO FHOOV ZHUH KDUYHဧHG from the nutrient medium by centrifugation Bacterial cells of $UWKUREDFWHUJORELIRUPLV 151B JPLQÛ& ULQVHGWZLFHin a Phosphate ZHUH JURZQ DHURELFDOO\ LQ P/ (UOHQPH\HU EX൵HUHGVDOLQH 3%6 DQGVDPSOHVSUHSDUHGHLWKHU ÀDVNVDVDPOVXVSHQVLRQLQ76%EURWK 6LJPD IRU'HOHFWURSKRUHVLV06RU$WRPLFDEVRUSWLRQ DW Û& 7KH FHOOV ZHUH JURZQ ZLWK D FRQဧDQW spectroscopy analysis. VKDNLQJ DW D VSHHG RI USP 7KH H[SHULPHQWV For determination the metal accumulation were carried out on the following groups of capacity by bacteria itself, wet biomass of bacterial bacteria: 1. Cells without any salt addition; 2. SHOOHW DIWHUFHQWULIXJDWLRQDQGZDVKLQJSURFHGXUHV &HOOV ZLWK DGGLWLRQ RI RQO\ &U 9, &HOOV ZLWK ZDVSODFHGLQDQDGVRUSWLRQFRQGHQVDWLRQO\RSKLOL]HU DGGLWLRQRIRQO\=Q ,, ([SHULPHQWVZHUHဧDUWHGDW DQGGULHGIROORZLQJWKHSURFHGXUHUHSRUWHGLQ> @ WKHHDUO\ဧDWLRQHU\SKDVHRIEDFWHULDOFHOOJURZWK dried cells were ashed in nitric acid, diluted with &U 9, DQG=Q ,, ZHUHDGGHGVLPXOWDQHRXVO\WRWKH ELGLဧLOOHGZDWHUDQGDQDO\]HGE\DWRPLFDEVRUSWLRQ EDFWHULDO FHOO FXOWXUHV DW WKLV ဧDJH DV . CrO and 2 4 VSHFWURPHWU\ DDV $QDO\ဧZDVXVHG =Q624 UHVSHFWLYHO\ 7KHLU PHWDOV FRQFHQWUDWLRQ made up 40 mg/l in a nutrient liquid medium. The H[SHULPHQWDOVDPSOHVIURPWKHVHJURXSVZHUHWDNHQ 2-D electrophoresis and MS in a time dependent fashion: 36, 60 and 120 hours Sample preparation DIWHU WKH ဧDUW RI FXOWLYDWLRQ ([SHULPHQWDO GHVLJQ LV SURYLGHG LQ ¿JXUH %DFWHULDO FXOWXUH JURZWK %DFWHULDO FHOO ZDOO O\VHV DQG SURWHLQ H[WUDFWLRQ The VDPSOHVIRU'HOHFWURSKRUHVLVDQG06DQDO\VLV 219 O. Rcheulishvili et al. Annals of Agrarian Science 17 (2019) 218 – 229 ZHUH FDUULHG RXW HVVHQWLDOO\ DV GHVFULEHG LQ >@ RI H[SHULPHQWV WKH WKUHH W\SH RI $ JORELIRUPLV %DFWHULDOSHOOHWVZHUHUHVXVSHQGHGLQEX൵HU P0 151B samples were analyzed concurrently for each 7ULVDFHWDWH S+ P0 1D&O P0 ('7$ WLPHSRLQW3URWHLQVWKDWH[KLELWHGDWOHDဧIROG ȝJP/ O\VR]\PH 6DPSOHV ZHUH LQFXEDWHG GL൵HUHQFH EHWZHHQ WKH FRQGLWLRQV ZHUH VHOHFWHG IRU PLQ DW & ZLWK LQWHUPLWWHQW YRUWH[LQJ The relative intensities of protein spots coinciding 9M Urea, 4% Tween 40, 2% Pharmalyte, 2% E\ORFDWLRQ LVRHOHFWULFSRLQWDQGPROHFXODUZHLJKW 0HUFDSWRHWKDQROSURWHDVHLQKLELWRU EDFWHULDO IURPGL൵HUHQWH[SHULPHQWVZHUHFRPSDUHGE\tWHဧ were added and lysates were centrifuged at 15,000 7KH VLJQL¿FDQWO\ GL൵HUHQWLDOO\ H[SUHVVHG SURWHLQ îJfor 30 min at 4°C. VSRWV p ZHUHH[FLVHGGHဧDLQHGDQGဧRUHG Metal accumulation ability by bacterial proteins DW í& XQWLO 06 DQDO\VLV was determined by atomic absorption spectroscopy, RQWKHSRUWLRQRIH[WUDFWHGSURWHLQV ,QJHO'LJHဧLRQ 3URWHLQ 4XDQWL¿FDWLRQ Protein concentration LV VXSHUQDWDQWV ZDV TXDQWL¿HG E\ a PLFUR%&$ ([FLVHGSURWHLQVZHUHUHGXFHGZLWK7&(3DQG NLW 3LHUFH 7KHUPR 6FLHQWL¿F LQ TXDGUXSOLFDWH alkylated with iodoacetamide. Samples were then $SSURSULDWH EX൵HU FRQWUROV ZHUH XVHG treated with acetonitrile, dried, and rehydrated in DFWLYDWHGWU\SVLQ 7KHUPR6FLHQWL¿F3LHUFH WREHJLQ Isoelectric focusing GLJHဧLRQ SURWHLQVZHUHGLJHဧHGDW&RYHUQLJKW $IWHU GLJHဧLRQ WKH VXSHUQDWDQW ZDV SLSHWWHG LQWR ,VRHOHFWULFIRFXVLQJ ,() ဧULSV OLQHDUS+± a sample vial and loaded into an autosampler for DQG S+ ZHUH UHK\GUDWHG LQ 0 XUHD DXWRPDWHG /&0606 DQDO\VLV 7ULWRQ;3KDUPDO\WH±DQGP0 'HဧUHDFN UHDJHQW RYHUQLJKW 3URWHLQ VDPSOHV MS analysis J ZHUH ORDGHG RQWR UHK\GUDWHG ဧULSV LQ EX൵HU FRQWDLQLQJ0XUHD0WKLRXUHD7ULWRQ; 0DVVVSHFWURPHWU\H[SHULPHQWVZHUHSHUIRUPHG $6%PHUFDSWRHWKDQRO3KDUPDO\WH XVLQJ/74)OHHWLRQWUDS¿WWHGZLWKQDQRVSUD\LRQ 3–10, bromophenol blue and 2% protease inhibitor. VRXUFHV 7KHUPR)LVKHU 7KHVHSDUDWLRQRISHSWLGHV ,()ZDVFDUULHGRXWDW9IRUKDQG9 ZDV SHUIRUPHG E\ UHYHUVHSKDVH FKURPDWRJUDSK\ DSSUR[LPDWHO\IRUK XVLQJ ($6<Q/& ,QWHJUDWHG 8OWUD +LJK 3UHVVXUH1DQR+3/&V\ဧHPDWDÀRZUDWHRIQ/ Equilibration PLQDQGDQ/&3DFNLQJV 'LRQH[6XQQ\YDOH&$ 3HS0DS FROXPQ & 0 LG î PP ,()ဧULSVZHUHHTXLOLEUDWHGIRUPLQLQDEX൵HU 0 SDUWLFOH VL]H 3HSWLGHV ZHUH ORDGHG RQWR DQ FRQWDLQLQJ 0 7ULV+&O S+ 0 XUHD /&3DFNLQJV SUHFROXPQ $FFODLP 3HS0DS 30% glycerol, 3% SDS, and 1% DTT, followed by &0SDUWLFOHVL]H$0LGîPP HTXLOLEUDWLRQ LQ WKH VDPH EX൵HU ZLWK '77 from the autosampler using 0.1% formic acid for LRGRDFHWDPLGHLQဧHDGRI'77IRUPLQ PLQ DW D ÀRZ UDWH RI /PLQ WR GHVDOW VDPSOHV and focus peptides prior to analytical separation. SDS Electrophoresis $IWHUWKLVSHULRGWKHVL[SRUWYDOYHZDVVZLWFKHG to allow elution of peptides from the precolumn 6'6HOHFWURSKRUHVLVZDVUXQRQDPPWKLFN onto the analytical column. Solvent A was water + SRO\DFU\ODPLGHJHODW&)RUWKH¿Uဧ 0.1% formic acid in water and solvent B was 100% KRXUP$SHUJHODW9ZDVDSSOLHGDQGWKHQIRU DFHWRQLWULOHIRUPLFDFLG7KH/74LQဧUXPHQW KP$SHUJHODW9 ZDVRSHUDWHGLQDGDWDGHSHQGHQWPDQQHULQZKLFK a survey scan was performed to analyse the m/z Staining, Scanning, and Analysis YDOXHV RI LRQV ZKLFK ZHUH HOXWHG IURP D UHYHUVH 7KH JHOV ZHUH ဧDLQHG ZLWK D VLOYHU ဧDLQ NLW phase HPLC column. MS/MS spectra data were *(+HDOWKFDUH RPLWWLQJ WKH JOXWDUDOGHK\GH DQDO\]HG XVLQJ 6(48(67 3URWHRPH 'LVFRYHUHU ဧHS 6LOYHUဧDLQHG JHOV ZHUH VFDQQHG ZLWK DQ VHDUFKLQJ DJDLQဧ 8QL3URW 8QL5HI LPDJH VFDQQHU /DEVFDQ *( +HDOWKFDUH Arthrobacter species protein databases. Images were digitalized and processed using Image 0DဧHU ' SODWLQXP VRIWZDUH ,Q HDFK VHULHV 220 O. Rcheulishvili et al. Annals of Agrarian Science 17 (2019) 218 – 229 AAS measurements gel electrophoresis and mass spectrometry analyses. MS analysis was used to determine The total chromium and total zinc contents in WKH LGHQWLW\ RI WKH H[FLVHG SURWHLQV bacterial proteome were measured using an atomic 7KH'JHOHOHFWURSKRUHVLVRI$UWKUREDFWHU DEVRUSWLRQ VSHFWURPHWHU $QDO\ဧ ZLWK DQ JORELIRUPLV%SURWHLQH[WUDFWVZDVFDUULHG DFHW\OHQHDLUÀDPH7KHGHWHFWLRQZDVFDUULHGRXW out initially with two pH gradients: 3.0 – 11.0 DW QP IRUFKURPLXP DQGDWQP IRU DQG±7KHPDMRULW\RIWKHSURWHLQVRQWKH ]LQF 7KH LQဧUXPHQWDWLRQ GHWHFWLRQ OLPLW IRU &U 3.0 – 11.0 pH gradient gels were concentrated PHDVXUHPHQWZDVJPODQGIRU=QZDV EHWZHHQ S+ DQG )LJXUH $ 7KXV JPO IRU WKH EHWWHU UHVROXWLRQ DQG LGHQWL¿FDWLRQ RI GL൵HUHQWLDOO\ H[SUHVVHG EDQGV ' JHO Results and discussion HOHFWURSKRUHVLVZDVFRQWLQXHGXVLQJဧULSVZLWK DS+JUDGLHQWIURPWR )LJXUH B. 2-D gel electrophoresis C. D)0RဧVLJQL¿FDQWဧDEOHGL൵HUHQFHVZHUH :H H[DPLQHG WKH EHKDYLRU RI EDFWHULDO observed at 60h of cultivation and all results SURWHRPH XQGHU WKH LQÀXHQFH RI =LQF ,, DQG SURYLGHGEHORZUHSUHVHQWWKHGL൵HUHQFHVDWWKLV &U 9, WRFRPSDUHWRFRQWUROFHOOVXVLQJ' time point. Fig. 2. 5HSUHVDQWLWLYHLPDJHVRIVLOYHUVWDLQHG'JHOHOHFWURSKRUHVLVJHOVRI$UWKUREDFWHU JORELIRUPLV%SURWHLQH[WUDFWVKRXURIJURZWK$ SURWHLQH[WUDFWIURPFRQWUROFHOOVIURP 'VWULSVZLWKS+OLQHDUJUDGLHQW %&'UHSUHVHQWDWLYHLPDJHVRI'HOHFWURSKRUHVLV JHOVRQVWULSVZLWKS+OLQHDUJUDGLHQW %SURWHLQH[WUDFWIURPFRQWUROFHOOV &SURWHLQ H[WUDFWIURP=Q ,, WUHDWHGFHOOV 'SURWHLQH[WUDFWIURP&U 9, WUHDWHGFHOOV 221 O. Rcheulishvili et al. Annals of Agrarian Science 17 (2019) 218 – 229 The cultivation of $UWKUREDFWHU JORELIRUPLV cellular active transport. Functions of proteins %ZLWK&U 9, UHVXOWVLQဧDWLဧLFDOO\VLJQL¿FDQW from 2nd group mostly relate to the trans- GL൵HUHQWLDO H[SUHVVLRQ RI SURWHLQV DV FRPSDUHG membrane transport activity, ATP binding WR XQWUHDWHG FRQWURO FHOOV ZKHUHDV DGGLWLRQ RI =Q and ATP-ase activity, GTP-ase activity, NADP ,, LQGXFHVWKHGL൵HUHQWLDOH[SUHVVLRQRISURWHLQV binding activities. (Table 1. A-B). Availability 7DEOH $% of Zn to biomolecules is tightly regulated by Differently expressed proteins are involved binding proteins, metallothioneins (MTs) in a variety of activities and functions. and Zn transporters [19]. Cysteine synthase Function of 1st group proteins, expression of is increasing in Zn treated cells (see table 1B which is increased with metal treated cells, second row). It is interesting to note that, MTs mostly relate to stress response reactions and are cysteine rich proteins that bind up to seven maintenance of the cellular ion homeostasis. =QLRQVZLWKSLFRPRODUDI¿QLW\DQGFDUU\WKH It is widely accepted that, these proteins labile Zn fraction to cellular compartments. also participate in protein translation MTs are induced during oxidative stress, processes, activate transcriptional factors scavenge reactive oxygen species (ROS) and and phosphorylate components of signal reduce heavy metal intoxication [12, 11]. Thus transduction systems. They can also participate the increase in Cystein synthase could stabilize in Zinc and Ferric ion binding processes and the necessary conditions for MTs homeostasis. act as chaperones. (Table 1 A, B). Function Chromium and Zinc concomitant action of 2nd group proteins, expression of which causes the strongest oxidative stress in the decrease in Zn(II) and Cr(VI) treated cells, are case of A. globiformis that is demonstrated by mostly related to cellular energetic processes. the increased activity of superoxide dismutase These energetic processes are associated with (SOD) and catalase [13]. Table 1 A.7KHOLVWRIVWDWLVWLFDOO\VLJQL¿FDQWO\GLৼHUHQWLDOO\H[SUHVVHGSURWHLQVEHWZHHQ&U 9, WUHDWHGEDFWHULDDQGFRQWUROJURXSV DOOFKDQJHVDUHPRUHWKDQIROG 3URWHLQVDUH YLUWXDOO\DEVHQWLQ&U 9, WUHDWHGFHOOV LQGLFDWHVIRUWKRVHSURWHLQVZKLFKDUHDOVRVLJQL¿FDQWO\ GLৼHUHQWLDOO\H[SUHVVHGLQ=Q ,, YV&RQWUROFRPSDULVRQV VHHDOVR7DEOH% ## Proteins Direction Molecular/biological functions of changes 1 Succinate--CoA ligase ATP binding, metal ion binding, succinate- CoA ligase (ADP-forming) activity 2 Peptidyl-prolyl cis- peptide binding, peptidyl-prolyl cis-trans trans isomerase isomerase activity, unfolded protein binding (chaperone function) 3 2'-5' RNA ligase Ligase activity 4 Phage shock protein A Not given (PspA) family protein 5 Alanine alanine dehydrogenase activity dehydrogenase 6 Probable xylitol D-arabinono-1,4-lactone oxidase activity, oxidase flavin adenine dinucleotide binding 7 UncharacterizedN- Proton donor and acceptor acetyltransferase BWQ92_22005 8 50S ribosomal protein Structural constituent of ribosome, 5s rna * L25- binding-participates In translation 222 O. Rcheulishvili et al. Annals of Agrarian Science 17 (2019) 218 – 229 9 Cysteine synthase Cysteine synthase activity * 10 DNAstarvation/station Ferric ion binding, oxidoreductase activity, * ary phase protection oxidizing metal ions, cellular ion homeosta- protein sis, response to stress 11 Chorismate mutase Prephenate dehydratase (pheA) L-phenylal- * OS=Arthrobacter sp anine biosynthetic process 12 GntR family catalytic activity, DNA binding, DNA bind- * transcriptional ing transcription factor activity, pyridoxal regulator phosphate binding 13 Response regulator phosphorelay signal transduction system, * receiver protein regulation of transcription, DNA-templated, protein-glutamate methylesterase activity, chemotaxis 14 Putative periplasmic metalloendopeptidase activity, zinc ion * membrane protein binding, chaperone-mediated protein fold- ing 15 LSU ribosomal protein Ribonucleoprotein, Ribosomal protein * L25P 16 Uncharacterized ATP-ase activity, transmembrane transport, * protein Lipase activity, lipid metabolic process, outer membrane component, 17 Avirulence D protein Non predicted * (AvrD) 18 Chlorite dismutase Non predicted 19 Oxidoreductase(electro choline: oxygen 1-oxidoreductase activity ns transfer from donors to acceptors) 20 ABC transporter ATP-ase activity, ATP binding, trans-membrane substrate-binding protein transporter activity 21 Ketol-acid Ketol-acid reductoisomerase activity, metal reductoisomerase ion binding, NADP binding, isoleucine bio- (NADP(+)) synthetic process, valine biosynthetic pro- cess, Branched-Chain Amino acid biosyn- thesis, Mg-binding 22 Sugar ABC transporter ATP-binding cassette (ABC) transporter substrate-binding complex protein 23 Amino acid ABC Ionotropic glutamate receptor activity, ni- transporter substrate- trogen compound transport, binding protein, PAAT family 24 Nicotinate Transferase activity, transferring glycosyl phosphoribosyltransfer groups, nucleoside metabolic process ase 223 O. Rcheulishvili et al. Annals of Agrarian Science 17 (2019) 218 – 229 23 Amino acid ABC Ionotropic glutamate receptor activity, ni- transporter substrate- trogen compound transport, binding protein, PAAT family 24 Nicotinate Transferase activity, transferring glycosyl phosphoribosyltransfer groups, nucleoside metabolic process ase 25 MarR family DNA-binding, DNA- binding transcription transcriptional factor activity, transcription DNA templated regulator 26 Elongation factor G GTP-ase activity, GTP binding 27 Putative tricarboxylic Integral component of membrane, outer transport membrane membrane- bounded periplasmic space protein 28 SPG23_c14, whole DNA binding, phosphoreley signal transduc- genome shotgun tion system, regulation of transcription, sequence DNA-templated, 29 tRNA pseudouridine tRNA processing, Isomerase, RNA binding, synthase A tRNA pseudouridine synthase activity, 30 Putative tricarboxylic Integral component of membrane, outer transport membrane membrane-bounded periplasmic space protein 31 C4-dicarboxylate ABC ATP-binding, sequence specific DNA bind- transporter substrate- ing, transcription factor binding, phosphore- binding protein ley signal transduction system, regulation of transcription, DNA-templated, 32 Citrate synthase Citrate (Si)-synthase activity, tricarboxilic acid cycle 33 Carbohydrate ABC Integral component of membrane transporter substrate- binding protein, CUT1 family 34 Transaldolase Sedoheptulose-7-phosphate: D-glyceralde- hyde-3-phosphate glyceronetransferaze ac- tivity, carbohydrate metabolic process, pen- those phosphate shunt 35 ATP synthase subunit ATP binding, proton-transporting ATP syn- beta thase activity, rotational mechanism, ATP synthesis coupled proton transport 36 ATP-binding transport ATP ase activity, ATP binding protein NatA 37 Type I restriction- Not given modification enzyme subunit S 224 O. Rcheulishvili et al. Annals of Agrarian Science 17 (2019) 218 – 229 38 Methionine DNA binding, metal ion (divalent metal cat- aminopeptidase ions) binding, metalloaminopeptidase activ- ity, positive regulation of transcription, DNA template, protein initiator methionine re- moval, regulation of DNA replication, 39 ATP synthase gamma ATP binding, proton transporting ATP syn- chain thase activity, 40 Signal transduction ATP binding, hydrolase activity, phosphore- protein ley sensor kinase activity, integral compo- nent of plasma membrane 41 Nitroimidazol cofactor binding reductase NimA, Table 1 B.7KHOLVWRIVWDWLVWLFDOO\VLJQL¿FDQWO\H[SUHVVHGSURWHLQVEHWZHHQ=Q ,, WUHDWHG EDFWHULDDQGFRQWUROJURXS DOOFKDQJHVDUHPRUHWKDQIROG ## Proteins Direc- Molecular/biological functions tion of changes 1 50S ribosomal protein Structural constituent of ribosome, 5s rna * L25- binding-participates In translation 2 Cysteine synthase Cysteine synthase activity * 3 DNAstarvation/stationary Ferric ion binding, oxidoreductase activity, * phase protection protein oxidizing metal ions, cellular ion homeosta- sis, response to stress 4 Chorismate mutase Prephenate dehydratase (pheA) L-phenylal- * OS=Arthrobacter sp anine biosynthetic process 5 GntR family catalytic activity, DNA binding, DNA bind- * transcriptional regulator ing transcription factor activity, pyridoxal phosphate binding 6 Response regulator phosphorelay signal transduction system, * receiver protein regulation of transcription, DNA-templated, protein-glutamate methylesterase activity, chemotaxis 7 Putative periplasmic metalloendopeptidase activity, zinc ion * membrane protein binding, chaperone-mediated protein fold- ing 8 LSU ribosomal protein Ribonucleoprotein, Ribosomal protein * L25P 9 Uncharacterized protein ATP-ase activity, transmembrane * tranbsport, Lipase activity, lipid metabolic process, outer membrane component, 10 Avirulence D protein Non predicted * (AvrD) 225 O. Rcheulishvili et al. Annals of Agrarian Science 17 (2019) 218 – 229 11 Ribonucleoside- metal ion binding, ribonucleoside-diphos- diphosphate reductase phate reductase activity, thioredoxin disul- subunit beta fide as acceptor, Binds 2 iron ions per subunit 12 Acylpyruvate hydrolase hydrolase activity 13 Zn-dependent hydrolase metal ion binding, metalloendopeptidase ac- tivity, ribonuclease P activity 14 Succinyl-CoA ligase ATP binding,metal ion binding, succinate- [ADP-forming] subunit CoA ligase (ADP-forming) activity, ATP + alpha succinate + CoA = ADP + phosphate + suc- cinyl-CoA. Binds 1 Mg2+ ion per subunit 15 Short-chain oxidoreductase activity dehydrogenase/reductase aspartic-type endopeptidase activity SDR 16 Superoxide dismutase metal ion binding, superoxide dismutase ac- tivity,Binds 1 Fe cation per subunit, 2 super- oxide + 2 H+ = O2 + H2O2 17 ABC transporter antibiotic transmembrane transporter activ- permease ity, ATPase activity,ATP binding, efflux transmembrane transporter activity, Con- fers resistance against macrolides 18 Ribosome-recycling translation, translational termination, Re- factor sponsible for the release of ribosomes from messenger RNA at the termination of pro- tein biosynthesis 19 LacI family alanine racemase activity, DNA binding, transcriptional regulator regulation of transcription, DNA-templated, transcription, DNA-template 20 ATP-dependent DNA ATP binding, ATP-dependent DNA helicase helicase RecG activity, nucleic acid binding, DNA recom- bination, DNA repair 21 D-isomer specific 2- 4-phosphoerythronate dehydrogenase activ- hydroxyacid ity, NAD binding, protein dimerization ac- dehydrogenase, NAD- tivity binding protein 22 LysR family DNA binding, DNA binding transcription transcriptional regulator factor activity 23 Alpha-hydroxy-acid (R-pantolactone dehydrogenase (flavin) ac- oxidizing enzyme tivity, FMN binding, oxydoreductase, Flavo- protein, FMN, 24 Uncharacterized Component of cellular membrane, lipoprotein YufN 226 O. Rcheulishvili et al. Annals of Agrarian Science 17 (2019) 218 – 229 %DFWHULDO GHIHQVLYH PHFKDQLVPV DJDLQဧ KLJK IXQFWLRQ>@=LQFÀX[HVDUHLQYROYHGLQUHJXODWLQJ &U 9, FRQFHQWUDWLRQV DUH VKRZQ LQ GL൵HUHQW ZD\V DZLGHYDULHW\RIFHOOXODUIXQFWLRQVLQFOXGLQJKRဧ D &KURPDWH H൷X[ E\ WKH &KU$ WUDQVSRUWHU ZKLFK LPPXQHDFWLYDWLRQ>@,QPRဧEDFWHULDWKH]LQF LV WKH PHPEUDQH SRWHQWLDO GULYHQ HQHUJ\GHSHQGHQW XSWDNH UHSUHVVRU =XU FRQWUROV WKH H[SUHVVLRQ SURFHVV E &KURPDWH UHGXFWLRQ WR &U ,,, FDUULHG of a small number of genes required to adapt to out by chromate reductases, enzymes belonging to FRQGLWLRQVRIVHYHUH]LQFGHSOHWLRQ>@:KHQWKH WKH ZLGHVSUHDG 1$' 3 +GHSHQGHQW ÀDYRSURWHLQ LQWUDFHOOXODU=LQFFRQFHQWUDWLRQLVIDUEHORZDFULWLFDO IDPLO\ F 2WKHU PHFKDQLVPV RI EDFWHULDO UHVLဧDQFH WKUHVKROG>PHWDO@free .metalWKH]LQFIUHHIRUPRI WRFKURPDWHLQYROYHWKHH[SUHVVLRQRIFRPSRQHQWVRI =XUKDVORZD൶QLW\IRUWKH'1$RSHUDWRUZKLFK WKHPDFKLQHU\IRUUHSDLURI'1$GDPDJHDQGV\ဧHPV overlaps the promoter, thus allowing unfettered UHODWHG WR WKH KRPHRဧDVLV RI LURQ DQG VXOIXU >@ access by RNA polymerase to transcribe the genes =LQF LV DQ HVVHQWLDO WUDFH HOHPHQW IRU PRဧ HQFRGLQJDKLJKD൶QLW\=QXSWDNHV\ဧHP V >@ RUJDQLVPV =Q2+LRQSHUIRUPVQXPHURXVဧUXFWXUDO ,Q DGGLWLRQ JHQHV HQFRGLQJ WKH H൷X[ V\ဧHP DUH regulatory, and catalytic roles in a range of proteins. transcriptionally repressed by the apo form of the However, this nutrient can neither be synthesized =QH൷X[UHSUHVVRU=QW5LQ(VFKHULFKLDFROLXQGHU nor degraded and individual cells need to be WKHVHFRQGLWLRQV$VOHYHOVRIELRDYDLODEOH=QULVH DEOH WR PDLQWDLQ ဧHDG\ OHYHOV RI =LQF LQ WKH IDFH WR>PHWDO@free!.metal =LQFUHSOHWHFRQGLWLRQV WKH RI QHDU]HUR RU H[FHVVLYHO\ KLJK HQYLURQPHQWDO =LQFERXQGIRUPRI=XUELQGVWLJKWO\WRWKHRSHUDWRU FRQFHQWUDWLRQV >@ ,W LV EHFRPLQJ LQFUHDVLQJO\ VLWH SUHYHQWLQJ WUDQVFULSWLRQ >@ apparent that the ability of commensal organisms WRDGDSWWRWKHKRဧHQYLURQPHQWGHSHQGVXSRQWKH AAS Analyses DELOLW\WRZLWKဧDQGODUJHÀX[HVLQ=LQFDYDLODELOLW\ WKDWDUHSURGXFHGE\WKHKRဧ>@=QLQEDFWHULD AAS measurements have revealed that portion is primarily used as a metalloenzyme cofactor with RI=LQFDQG&KURPLXPZKLFKDUHDFFXPXODWHGE\ a total concentration in the 0.1–1.0 mආUDQJH> $.JORELIRUPLV 151B cells, are bound to bacterial @ =Q LV LQFRUSRUDWHG LQWR DERXW RI DOO SURWHLQV7KHVHH[SHULPHQWVLQGLFDWHGWZRGL൵HUHQW human proteins, and well over 300 enzymes are EHKDYLRU WHQGHQF\ EHWZHHQ &KURPLXP DQG =LQF NQRZQ WR UHTXLUH =Q ,, IRU FDWDO\WLF RU ဧUXFWXUDO in the proteome of $UWKUREDFWHU JORELIRUPLV IXQFWLRQV> @0HWDOOLFKRPHRဧDVLVRIWKHFHOO % &RQFHQWUDWLRQ RI =LQF LQ EDFWHULDO SURWHLQV LV should be defended according the special metal LQFUHDVLQJ DIWHU WLPH DQG UHDFKHV PD[LPDO OHYHO sensors, which should FRUUHFWO\GLဧLQJXLVKEHWZHHQ after 120 hour growth, when bacterial medium WKH LQRUJDQLF HOHPHQWV >@ 7KHVH PHWDO VHQVRU FRQWDLQVPJO=Q ,, )LJ$ %XWEHKDYLRU proteins WUDQVFULSWLRQDOO\ UHJXODWH WKH H[SUHVVLRQ RI&KURPLXPLQSURWHRPHTXLWHGL൵HUVIURP=LQF¶V of genes that encode metal transporters and other Chromium content in proteins is decreasing after UHVLဧDQFHSURWHLQV>@$OPRဧKDOIRIDOO WLPH ,I LW ZDV PD[LPDO DW KRXU RI EDFWHULDO HQ]\PHVPXဧDVVRFLDWHZLWKDSDUWLFXODUPHWDOWR growth phase, after 120 hour, Chromium content in SURWHRPH LV GHFUHDVHG VLJQL¿FDQWO\ )LJ % Fig. 3.7KHGHSHQGHQFHRIWKHFRQFHQWUDWLRQRI=Q ,, DQG&U PJJ LQSURWHLQVIURPWKHWLPH7 K RIFXOWLYDWLRQRIEDFWHULD$UWKUREDFWHUJORELIRUPLV% 227 O. Rcheulishvili et al. Annals of Agrarian Science 17 (2019) 218 – 229 Fig. 4.&KURPLXPDFFXPXODWLRQFDSDFLW\LQSURWHLQV $ DQGLQWKHZKROHEDFWHULDLWVHOI % ,QÀXHQFHRI=LQF ,, LRQVRQ&KURPLXPDFFXPXODWLRQFDSDFLW\LQEDFWHULDOSURWHLQV $ DQGLQ EDFWHULD % ,QWKLVH[SHULPHQWZHH[DPLQHG=Q ,, DQG&U 9, &RQÀLFWVRI,QWHUHဧ MRLQWDFWLRQRQWKHFKURPLXPDFFXPXODWLRQFDSDFLW\ on both: protein or bacterial levels. Samples were None declared. made according to abovementioned design: same FRQFHQWUDWLRQRI&U 9, DQG=Q ,, ZHUHDGGHGEXW References WRJHWKHU MRLQW ([SHULPHQW UHYHDO WKDW =LQF ,, >@08QHOO3($EUDKDP06KDK%=KDQJ& LRQV RQ JLYHQ FRQFHQWUDWLRQ PJO HQKDQFHV 5FNHUW1&9HU%HUNPRHV.-DQVVRQ,PSDFW bacterial ability for Chromium accumulation Fig. 4 RI3KHQRORF6XEဧUDWHDQG*URZWK7HPSHUDWXUH %=LQFDOVRLQFUHDVHV&KURPLXPFRQWHQWLQEDFWHULDO on the Arthrobacter chlorophenolicus Proteome, SURWHLQV UHGXFHG&KURPLXPSURWHLQELQGLQJ )LJ Journal of Proteome research. 3A. and the concentration of proteins with bound 1953–1964 DOI: 10.1021/pr800897c. FKURPLXPLQFUHDVHGDIWHUWLPH IRUKRXU =LQF >@ 1< 7VLEDNKDVKYLOL 7/ .DODEHJLVKYLOL action enhances Chromium accumulation in bacteria A.N. Rcheulishvili, I.G. Murusidze, S.M. E\WZRPHWDOVVLPXOWDQHRXVSUHVHQFH:LWKRXW=LQF .HUNHQMLD 2$ 5FKHXOLVKYLOL +<+ROPDQ chromium content in proteome tends to decrease 'HFRPSRVLWLRQ RI &U 9 GLROV WR &U ,,, DIWHU WLPH $QG PD[LPDO FRQWHQW LV REVHUYHG DW FRPSOH[HV E\ $UWKUREDFWHU R[\GDQV Microb HDUO\ဧDJHRIFXOWLYDWLRQKRXU)RUKRXU&U (FRO FRQWHQWLQSURWHLQVLVVLJQL¿FDQWO\GHFUHDVHG >@ 1<7VLEDNKDVKYLOL7/.DODEHJLVKYLOL$1 Rcheulishvili, E.N. Ginturi, L.G. Lomidze, Conclusion 2$ 5FKHXOLVKYLOL '1 *YDUMDODG]H +< +ROPDQ (൵HFW RI =Q ,, RQ WKH UHGXFWLRQ Remarkable changes in bacterial proteome DQG DFFXPXODWLRQ RI &U 9, E\ $UWKUREDFWHU were associated with metal-binding proteins and VSHFLHV-,QG0LFURELRO%LRWHFKQRO proteins involved in active transport. Experiments with atomic absorption spectroscopy revealed >@ 1< 7VLEDNKDVKYLOL /0 0RVXOLVKYLOL 7/ that reduced chromium appears mostly associated Kalabegishvili, E.I. Kirkesali, I.G. Murusidze, with organics: especially with bacterial proteins. 60.HUNHQMLD09)URQWDVLHYD+<+ROPDQ Zinc(II) ions enhances bacterial ability for %LRWHFKQRORJ\ RI &U 9, WUDQVIRUPDWLRQ LQWR Chromium accumulation. Zinc(II) also increases &U ,,, FRPSOH[HV-UDGLRDQDO1XFO&KHP reduced Chromium-protein connections and their content increases after time (for 120 hour). >@ 1$VDWLDQL0DEXODG]H7.DUWYHOLVKYLOL1 %DNUDG]H 1 6DSRMQLNRYD 1 7VLEDNKDVKYLOL Acknowledgements / 7DEDWDG]H / /HMDYD /$VDQLVKYLOL +< +ROPDQ(൵HFWRI&U 9, DFWLRQRQ$UWKUREDFWHU 7KLVZRUNZDVIXQGHGE\*UDQWFR/218 018/16 R[\GDQV &XUU 0LFURELRO IURP6KRWD5XဧDYHOL1DWLRQDO6FLHQFH)RXQGDWLRQ >@ <,VKLEDVKL&&HUYDQWHV66LOYHU&KURPLXP 6516) 228 O. Rcheulishvili et al. Annals of Agrarian Science 17 (2019) 218 – 229 reduction in Pseudomonas putida. App 0RQGUDJyQ 79 2 +DOORUDQ 6WUXFWXUDO DQG (QYLURQ 0LFURELRO ± PHFKDQLဧLF EDVLV RI ]LQF UHJXODWLRQ DFURVV >@ 7/ 'DXOWRQ %- /LWWOH -- 0HHKDQ '$ WKH(FROL=XUUHJXORQ3/R6%LRO Blom, L.F. Allard, Microbial reduction of e1001987. FKURPLXP IURP WKH KH[DYDOHQW WR GLYDOHQW >@ 6/ %HJJ %$ (LMNHONDPS = /XR 50 ဧDWH *HRFKLP &RVPRFKLP $FWD Couñago, J.R. Morey, M.J. Maher, C.L. Ong, 556–565. $* 0F(ZDQ % .REH 0/ 2 0DUD -& >@ &5 0\HUV %3 &DUဧHQV :( $QWKROLQH Paton, C.A. McDevitt, Dysregulation of - 0 0\HUV &KURPLXP 9, UHGXFWDVH WUDQVLWLRQPHWDOLRQKRPHRဧDVLVLVWKHPROHFXODU activity is associated with the cytoplasmic EDVLV IRU FDGPLXP WR[LFLW\ LQ6WUHSWRFRFFXV membrane of anaerobically grown Shewanella SQHXPRQLDH1DW &RPPXQ SXWUHIDFLHQV05 - $SSO 0LFURELRO >@)(-DFREVHQ.0.D]PLHUF]DN-3/LVKHU ± M.E. Winkler, D.P. Giedroc, Interplay between > @ /0 0RVXOLVKYLOL (, .LUNHVDOL $/ PDQJDQHVH DQG ]LQF KRPHRဧDVLV LQ WKH %HORNRELOVN\ $/ .KL]DQLVKYLOL 09 human pathogen Streptococcus pneumoniae. Frontasyeva, S.F. Gundorina, C.D. Oprea, 0HWDOORPLFV ± Epithermal neutron activation analysis of >@ &( 2XWWHQ 79 2 +DOORUDQ)HPWRPRODU EOXHJUHHQ DOJDH 6S 3ODWHQVLV DV D PDWUL[ sensitivity of metalloregulatory proteins IRU VHOHQLXPFRQWDLQLQJ SKDUPDFHXWLFDOV - FRQWUROOLQJ ]LQF KRPHRဧDVLV6FLHQFH 5DGLRDQDO 1XFO &KHP ± >@ 0 1R]DG]H ( =KJHQWL 0 0HSDULVKYLOL > @ & $QGUHLQL / %DQFL , %HUWLQL $ L. Tsverava, T. Kiguradze, G. Chanturia, G. 5RVDWR&RXQWLQJWKH]LQFSURWHLQVHQFRGHGLQ Babuadze, M. Kekelidze, L. Bakanidze, T. WKHKXPDQJHQRPH-3URWHRPH5HV Shutkova, P. Imnadze, S.C. Francesconi, R. 196–2011. Obiso, R. Solomonia, Comparative proteomic >@'$&DSGHYLOD J. Wang , D.P. Giedroc, Bacterial ဧXGLHVRI Annals of Agrarian Science :ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ $SSOLFDWLRQRISRWDVVLXPULFKSURFHVVHGGDFWWHWX൵DVDIHUWLOL]HURI VORZDQGORQJODVWLQJH൵HFW S.K. Yeritsyan, M.V. Gevorgyan National Agrarian University of Armenia, 74, Teryan Str., Yerevan, 0009, Republic of Armenia Received: 22 December 2018; accepted: 12 February 2019 A B S T R A C T 7RJHWKHUZLWKWKH,QဧLWXWHRI*HQHUDODQG,QRUJDQLF&KHPLဧU\RI1$65$WKHUHVHDUFKHUVRI1DWLRQDO$JUDULDQ8QLYHUVLW\RI$UPHQLD KDYHGHYHORSHGWKHPHWKRGRIGHULYLQJDFRPSOH[IHUWLOL]HURIVORZDQGORQJODဧLQJH൵HFWIURPSRWDVVLXPULFKDOXPLQRVLOLFDWHV SURFHVVHGGDFLWHWX൵3'7 FRQWDLQLQJSRWDVVLXPFDOFLXPPDJQHVLXPSKRVSKRUXVDQGVLOLFLXPIURPZKLFKWKHQXWULHQWVSDVVLQWR WKHVRLOVROXWLRQJUDGXDOO\8SRQWKH¿HOGDQGYHJHWDWLRQH[SHULPHQWVLWKDVEHHQဧDWHGWKDWLQFDVHRIXVLQJ3'7ZLWKWKHDPRXQW HTXLYDOHQWWRSRWDVVLXPLWSURYLGHVKLJKHU\LHOGLQWKDQLWLVLQFDVHRIXVLQJSRWDVVLXPFKORULGH It has been proved that PDT prevents the leaching of ammonium and nitrate ions from the soil, which is very important for the reduction of the nitrogen loss from the nitrogenous fertilizers and for the environmental protection; it also promotes the increase of phosphorus DQGSRWDVVLXPLQWKH\LHOGDQGHQKDQFHVWKHFURSVGURXJKWUHVLဧDQFH Keywords:'DFLWHWX൵(൶FLHQF\1LWURJHQORVV$FWLYHSKRVSKRUXV3RWDVVLXP &RUUHVSRQGLQJDXWKRU 6 Introduction LQSRWDVVLXPVXFKDVIRUH[DPSOHWKHGDFLWHWX൵ moreover, they have revealed that it is possible Among the mineral fertilizers used in the to realize this process through ecologically safe agricultural production the potassium fertilizers methods. The derived fertilizer is allowed to be used also make a certain amount. Potassium chloride is in organic agriculture as well. The fertilizer contains mainly used which is derived from Sylvinite. But plants available potassium, as well as calcium, the mentioned mineral variety is not found in many magnesium, phosphorus, silicium, which penetrate countries, also in the republic of Armenia. into the soil solution gradually and that is why they Potassium chloride also contains 47 % chlorine, DUH FRQVLGHUHG WR EH IHUWLOL]HUV RI VORZ DQG ORQJ ZKLFKKDVDQDGYHUVHH൵HFWRQWKHVRLOSURSHUWLHV ODဧLQJH൵HFW>@,WLVDOVRHQGRZHGZLWKLQGLUHFW DQGDOVRRQWKH\LHOGTXDOLW\RIVRPHFURSV SRWDWR SRVLWLYHLQÀXHQFHVIRUH[DPSOHLWFDQDEVRUEXSWR WREDFFRJUDSHYLQHHWF >@ 500 %water and due to this property it temporarily $OXPLQRVLOLFDWHV ULFK LQ SRWDVVLXP >@ DV absorbs the humidity from the environment, which ZHOO DV QDQRPRGL¿HG QDWXUDO ]HROLWHV >@ DUH the plants use gradually. It is obvious that it is RI LQGXဧULDO LPSRUWDQFH IRU WKH HQODUJHPHQW RI particularly prioritized for the agriculture in dry the varieties of potash fertilizers and the base of FRQGLWLRQV> @7KHIHUWLOL]HULVDOVRDEOHWRDEVRUE SURGXFWLRQ UDZ PDWHULDO >@ ା ି ܰܪସ DQGܱܰ ଷ LRQV XS WR PJHT GXH WR 7KH UHVHDUFKHUV RI WKH LQဧLWXWH RI JHQHUDO DQG which the loss of nitrogen and other nutrients LQRUJDQLFFKHPLဧU\DW1$65$DQGWKRVHRI$1$8 LQWURGXFHG LQWR WKH VRLO LV SUHYHQWHG >@ %HLQJ have disclosed that it is possible to obtain potassium endowed with the ability of absorbing the heavy IHUWLOL]HURXWRIWKHDOXPLQRVLOLFDWHVZKLFKDUHULFK PHWDOV LQ QRQH[FKDQJHDEOH ZD\ WKH PHQWLRQHG 230 S.K. Yeritsyan et al. Annals of Agrarian Science 17 (2019) 230 – 235 IHUWLOL]HU FDQ EH XVHG IRU WKH UHFXOWLYDWLRQ RI WKH in the ANAU greenhouse in four repetitions by the VRLOV FRQWDPLQDWHG ZLWK KHDY\ PHWDOV >@7KH following scheme /the holding capacity of a vessel IHUWLOL]HU SURPRWHV WKH ဧUHQJWKHQLQJ RI WKH SODQWV ZDVNJDLUGU\VRLO URRW V\ဧHP UHVXOWLQJ LQ WKH EHWWHUPRUH H൶FLHQW use of soil humidity and nutrients by the plants, it 1. Without fertilization (control) 4. background+K1(PDT) also contributes to the increase of plants available 2. N2P2 (background) 5. background+K2(PDT) 3. background+K2(KCl) phosphorus and potassium, which takes place at WKH H[SHQVH RI WKH VROXELOLW\ LQFUHDVH RI KDUGO\ ,QWKHH[SHULPHQWV12 is equal to 0,2 g N per 1 soluble compounds and the opportunity to reduce kg soil, P2 –is equal to 0,2 g P2O5, K1LVJ.2O,K2 WKH DSSOLFDWLRQ GRVDJHV>@RI SKRVSKRURXV DQG is 0,2 g K2Oper 1 kg soil. Ammonium saltpeter, double potassium fertilizers or to improve the plants VXSHUSKRVSKDWH SURFHVVHG GDFLWH WX൵ 3'7 DQG nutrition with phosphorus, particularly in the soils potassium chloride have been used. The processed SRRUO\SURYLGHGZLWKSKRVSKRUXV>@DSSHDUV GDFLWHWX൵KDVWKHIROORZLQJFRPSRVLWLRQ .22 The impact of the fertilizer maintains in the soil &D20J232O5$O2O3 for several years, thus it is possible to apply it in the SiO2 +22 VDPHSODFHRQFHLQ\HDUV>@ Results and analyses Objectives and methods 7KH¿HOGH[SHULPHQWVZHUHFRQGXFWHGLQ$U]DNDQ The REMHFWLYH of the research is to ¿QG out the FRPPXQLW\ RI .RWD\N UHJLRQ LQ WKH IRUHဧ EURZQ agrochemical FKDUDFWHULဧLFV of the fertilizer dacite DQG FDUERQDWHG VRLOV ZLWK DOPRဧ QHXWUDO UHDFWLRQ WX൵ of slow and longlasing LQÀXHQFH containing and low humus content, which is weakly provided potassium, calcium, magnesium, Silicium and with nitrogen and phosphorus and well provided phosphorus H[WUDFWHG from the potassiumrich ZLWK SRWDVVLXP WDEOH 7KH ¿HOG H[SHULPHQWV LQ aluminosilicates and its H൶FLHQF\ on the H[DPSOH Hatsashen community of Aragatsotn region were of spring barley H[SHULPHQWV comparing it with carried out in the brown carbonated soils which are potassium chloride. poor in humus and poorly provided with nitrogen and The ¿HOG H[SHULPHQWV have been conducted in averagely provided with phosphorus and potassium dry ဧHSSH and ဧHSSH zones nonirrigated of RA DQG LQ $UWLN SURYLQFH WKH H[SHULPHQWV ZHUH in three repetitions, the size of an H[SHULPHQWDO bed implemented in the carbonated black soils, where the is 50 m2 , they were implemented by the following KXPXVFRQWHQWPDNHVS+DQGWKHVHVRLOV scheme: are weakly provided with plants available nitrogen, 1. :LWKRXWIHUWLOL]DWLRQ FRQWURO SKRVSKRUXV DQG SRWDVVLXP 7DEOH 2. N90P90 EDFNJURXQG ,Q WKH ¿HOG H[SHULPHQWV WKH LPSDFW RI WKH 3. background+K .&O 90 application of KCl and PDT on N90P90background is 4. background +K90 3'7 remarkable on the growth, yield capacity and chemical composition of the grain of the spring barley in all NH NO &D + 3Ɉ .H O, KCl and the 4 3 2 4 2 2 WKUHHVLWHV DQ\KRZWKHLQÀXHQFHUDWHGHSHQGVRQWKH SURFHVVHG GDFLWH WX൵ KDYH EHHQ XVHG variant of the fertilization. 7KHYHJHWDWLRQH[SHULPHQWVKDYHEHHQFRQGXFWHG Table 1.$JURFKHPLFDOLQGLFDWRUVRIWKHH[SHULPHQWDOSORWV SORZLQJOD\HU Sampling site Available nutrients, pH EC CaCO3 mgin100 g soil % Humus, % % N P2O5 K20 Physical clay, Kotayk region 3,11 7,1 0,12 3,5 52,1 3,5 1,5 40,7 Arzakan community Aragatsotn re- 2,85 7,3 0,20 8,6 54,8 2,6 3,1 33,1 gionHatsashen commu- nity Shirak region 4,45 7,1 0,29 1,4 63,6 4,1 1,6 17,5 Artik province 231 S.K. Yeritsyan et al. Annals of Agrarian Science 17 (2019) 230 – 235 Table 2.7KHLPSDFWRI3'7DQG.&ORQ13.FRQWHQWLQWKHVSULQJEDUOH\JUDLQ Arzakan community Hatsashen community Artik community Variants N P2O5 K2O N P2O5 K2O N P2O5 K2O 1. 1,42 0,56 0,44 1,53 0,47 0,43 1,38 0,39 0,41 2. 1,73 0,72 0,40 1,79 0,58 0,41 1,80 0,59 0,37 3. 1,75 0,70 0,55 1,76 0,53 0,54 1,85 0,74 0,48 4. 1,81 0,87 0,67 1,79 0,87 0,70 1,87 0,90 0,67 9DULDQWVZLWKRXWIHUWLOL]DWLRQ FRQWURO 1 3 EDFNJURXQG EDFNJURXQG. .&O EDFNJURXQG. 3'7 So, we can see that the plants growth, weight of ofN90P90 EDFNJURXQG KDV PDGH FKD DQG the grains in an ear and the yield capacity is lower DJDLQဧ WKH YDULDQW RI EDFNJURXQG .90 .&O LW in control variant. Only in case of nitrogen and LVFKD:HWKLQNWKDWWKLVUHJXODULW\LVUHODWHG phosphorus application the yield has increased by WRWKHSRVLWLYHVLGHH൵HFWVRI3'7 LWSURPRWHVWKH FKDDVFRPSDUHGWRWKDWRIFRQWUROYDULDQW ဧUHQJWKHQLQJ RI WKH SODQWV URRW V\ဧHP UHGXFWLRQ which is rather high in Artik province making10,9 of the water amount spent for getting a yield unit, FKD WDEOH ZKLFK LV UHODWHG WR WKH UHODWLYHO\ PRUHH൶FLHQWDFFXPXODWLRQRIWKHPRLဧXUHUHVXOWHG high precipitation rate and low soil fertility in the from the precipitations, as well as it promotes the ဧHSSH]RQHVLQFRQGLWLRQVRIZKLFKWKHIHUWLOL]HUV increase of the available phosphorus and potassium GHPRQဧUDWHG UDWKHU KLJK H൶FLHQF\ TXDQWLWLHVLQWKHVRLO>@ In case of using potassium chloride or PDT on The use of the fertilizer has also promoted WKH QLWURJHQSKRVSKRUXV EDFNJURXQG WKH KLJKHဧ the increase of the amounts of the main nutrients JUDLQ \LHOG FKD ZDV REWDLQHG LQ WKH 13. ZKLFKLVPRUHQRWLFHDEOHLQFDVHRIXVLQJ variant of N90P90K90 3'7 PRUHRYHUWKLVUHJXODULW\ 3'7 WDEOH :HWKLQNWKDWLWLVFRQQHFWHGZLWKWKH ဧD\VဧDEOHLQGHSHQGHQWRIWKHVRLOSURYLVLRQZLWK improvement of plants nutrition particularly with SRWDVVLXP 7KXV LQ WKH H[SHULPHQWDO YDULDQW RI phosphorus and potassium. N90P90K90 3'7 WKH\LHOGVXUSOXVDJDLQဧWKHYDULDQW Table 3.7KHLPSDFWRI3'7DQG.&ORQWKHJURZWKDQG\LHOGFDSDFLW\RIVSULQJEDUOH\ DYHUDJHGDWDIRU Arzakan community Hatsashen community Artik community Variants in an ear, g. in an ear, g. in an ear, g. in an ear, g. Grain yield, c/ha c/ha Grain yield, c/ha Grain yield, c/ha Grain yield, Weight of grains grains Weight of grains Weight of grains Weight of Plants height, cm cm Plants height, cm Plants height, cm Plants height, 1. 43 0,65 15,2 37 0,51 14,5 49 0,81 22,6 2. 48 0,81 23,1 44 0,66 20,2 56 1,10 33,5 3. 49 0,83 24,0 43 0,70 21,6 58 1,18 37,2 4. 51 0,92 27,6 45 0,78 24,9 61 1,27 41,3 9DULDQWV :LWKRXWIHUWLOL]DWLRQ FRQWURO 1 3 EDFNJURXQG EDFNJURXQG. .&O EDFNJURXQG. 3'7 232 S.K. Yeritsyan et al. Annals of Agrarian Science 17 (2019) 230 – 235 7KH FRPSDUDWLYH H൶FLHQF\ RI WKH SURFHVVHG DPRXQWVVRDVWKHRXWÀRZLQWKH¿OWUDWHRFFXUUHG ା ି GDFLWHWX൵ 3'7 DQGSRWDVVLXPFKORULGHKDVEHHQ DQGZKHUHWKHFRQWHQWRIDQG WDEOH ܰܪସ ܱܰଷ ဧXGLHGDOVRLQWKHYHJHWDWLRQH[SHULPHQWV7KHVRLO was determined. The results show, that up on the ା ି EURZQ ZDV VHOHFWHG IURP +DWVDVKHQ FRPPXQLW\ application of PDT, the loss of ܰܪ ସ and ܱܰ ଷ ions of Talin region. The mechanical composition of from the soil is considerably mitigated. So, in the WKH VRLO ZDV FOD\ DQG VDQG\ KHDY\ S+ZDV QRQIHUWLOL]HGYDULDQW FRQWURO WKHORVVRIQLWURJHQ carbonates made 8,6 %, the plants available nitrogen is minimal and this is related to the low content ା ି made 2,6 mg N, phosphorus content was 3,1 mg RI྆ܰܪସ ܱܰଷ LRQVLQWKHVRLO:KLOHLQ12P2variant, P2O5, potassium was 33,1 mg K2O, in 100 g soil. where NH4NO3was used as a nitrogenous fertilizer According to these data the soil is poor in nitrogen WKH QLWURJHQ ORVV ZDV UDWKHU KLJK$OPRဧ VLPLODU and is averagely provided with phosphorus and loss rate was observed when potassium chloride on SRWDVVLXP7KHJRDORIWKHYHJHWDWLRQH[SHULPHQWV the background of N2P2ZDV XVHG >YDULDQW 12P2K2 KDV EHHQ WR LQYHဧLJDWH WKH FRPSDUDWLYH LPSDFW .&O @ :KLOH LQ FDVH RI WKH XVH RI 3'7 RQ WKH RI WKH SURFHVVHG GDFLWH WX൵ 3'7 DQG SRWDVVLXP background of N2P2the nitrogen loss considerably chloride on the mitigation of the loss of nitrogen GHFUHDVHG LQ DOO FDOFXODWLQJ SHULRGV 7DEOH $V ା ି IRUPV ܰܪ ସ DQGܱܰ ଷ IURP WKH VRLO DQG IURP a result the plants growth and yield capacity have the nitrogenous fertilizers inserted into the soil, DOVRFKDQJHG 7DEOH $FFRUGLQJWRWKHGDWDRIWKDW as well as the comparative impact on the growth table in the variant of N2P2K2 3'7 WKHJUDLQ\LHOG DQG\LHOGFDSDFLW\RIVSULQJEDUOH\ 7DEOH ,W has made 16,5 g, which is higher than the control should be mentioned that in the production due to RQHE\J DJDLQဧWKH12P2 variant it is the reduction of nitrogen loss from nitrogenous KLJKHUE\J DQGFRPSDULQJWR12P2K2 IHUWLOL]HUV WKHLU DSSOLFDWLRQ GDWHV JHW UHဧULFWHG RU .&O YDULDQW E\ J 7KXV WKH KLJKHဧ QLWURJHQRXVIHUWLOL]HUVRIORQJODဧLQJH൵HFWDUHXVHG yield was resulted in the variant where PDT was >@,QRUGHUWRဧXG\WKHLVVXHWKHYHJHWDWLRQYHVVHOV used on the background of N2P2 . ZHUH SHULRGLFDOO\ SURYLGHG ZLWK H[FHVVLYH ZDWHU Table 4. 7KHLPSDFWRIWKHSURFHVVHGGDFLWHWXৼ 3'7 DQG.&ORQWKHOHDFKLQJ ା ି PLWLJDWLRQRI QXPHUDWRU DQG GHQRPLQDWRU Iܰܪସ ܱܰଷ URPWKHVRLOPJO YHJHWDWLRQ H[SHULPHQWWKHFURSLVVSULQJEDUOH\ Periods of Analyses 3-leaves- Ear-formation 5-6-leaves Milk maturation The total during growth stage of the Variant Variant growth stage stage vegetation stage growth 0,11 0,07 0,02 n/a 0,20 1. 0,17 0,04 0,01 n/a 0,22 2,45 1,02 0,13 0,07 3,67 2. 5,76 2,84 0,31 n/a 8,91 2,40 1,16 0,10 0,08 3,74 3. 5,79 2,67 0,28 n/a 8,74 0,35 0,13 0,02 n/a 0,50 4. 2,13 0,76 0,18 n/a 3,07 0,21 0,07 0,02 n/a 0,30 5. 0,76 0,58 0,10 n/a 1,44 9DULDQWV :LWKRXWIHUWLOL]DWLRQ FRQWURO 12P2 EDFNJURXQG EDFNJURXQG.2 .&O EDFNJURXQG. 3'7 EDFNJURXQG.2 3'7 233 S.K. Yeritsyan et al. Annals of Agrarian Science 17 (2019) 230 – 235 Table 5.7KHLPSDFWRIWKHSURFHVVHGGDFLWHWXৼ 3'7 DQG.&ORQWKHSODQWV JURZWKDQGJUDLQ\LHOGRIVSULQJEDUOH\ YHJHWDWLRQH[SHULPHQWV The number of The weight of The weight Plants height yield, g./ grains in an ear, grains in an of thousand vessel cm ear, g grains, g. Variants n 1. 39 15,0 0,60 8,9 39,6 2. 47 21,4 0,90 13,5 42,0 3. 47 23,1 0,97 14,6 42,1 4. 48 22,9 0,97 14,5 42,3 5. 48 25,9 1,10 16,5 42,4 9DULDQWV :LWKRXWIHUWLOL]DWLRQ FRQWURO 13 EDFNJURXQG EDFNJURXQG . .&O EDFNJURXQG. 3'7 EDFNJURXQG. 3'7 Conclusion References 1. 7KHIHUWLOL]HURIVORZDQGORQJODဧLQJH൵HFW >@ $ DJDLQဧWKH12P2K2 .&O YDULDQW %.RဧDQ\DQ$.%DUWLN\DQ300HWKRGV 234 S.K. Yeritsyan et al. Annals of Agrarian Science 17 (2019) 230 – 235 of obtaining hardly soluble fertilizers. Patent DEဧUDFWGLVV&DQG%LRO6FLHQFHV0 ʋ 5$ XSRQ WKH UHTXHဧ ʋ RI LQ 5XVVLDQ $UPLQGSURSHUW\ʋ LQ$UPHQLDQ >@( *XJDYD $ .RURNKDVKYLOL 7HFKQRORJLHV > @ +* *KD]DU\DQ $/ 0NUWFK\DQ ** for obtaining nitrogen fertilizers prolonged Petrosyan, Climate changes and soil H൵HFWLQZKHDW-$QQDOVRI$JUDULDQ6FLHQFH degradation process in Armenia, J. Annals of 9RO 1R $JUDULDQ 6FLHQFH 9RO1R LQ 5XVVLDQ >@6. Annals of Agrarian Science :ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ $QDO\VLVRIWKHLPSDFWRIWKHPDLQIDFWRUVD൵HFWLQJWKHSDWWHUQRIWLUH depreciation P.A. Tonapetyan, A.G. Avagyan 1DWLRQDO$JUDULDQ8QLYHUVLW\RI$UPHQLD7HU\DQဧU Received: 15 August 2018; accepted: 04 October. 2018 A B S T R A C T 7KLV ဧXG\ LQYHဧLJDWHV WKH RSWLPDO LQWHUQDO WLUH SUHVVXUH D൵HFWLQJ WKH PD[LPXP WLUH usageof a particular minibus operating on a particular route in Armenia.Regression equations were developed that show the dependence of the tire usage on the internal tire pressure and wear.7KHUHVXOWVRIRSHUDWLRQDODQGဧDQGWHဧVUHYHDOWKHQDWXUHRIWKHLPSDFWRIWKHWUHDGVLSHGHQVLW\RQWLUHusage. The DQDO\VLVRIWKHဧXG\VKRZVWKDWDPRQJWKHPRဧLQÀXHQWLDOIDFWRUVD൵HFWLQJDXWRPRELOHWLUHusage are the density of tire tread sipes and WKHLQWHUQDOWLUHSUHVVXUH Keywords: Tires, Mileage, Weight, Internal tire pressure, Depreciation pattern, Tread height. &RUUHVSRQGLQJDXWKRU 3DUJHY7RQDSHW\DQ (PDLODGGUHVV WRQDSHW\DQSDUJHY#PDLOUX Introduction Objectives and Methods ,WLVLPSRUWDQWWRXQGHUဧDQGWKDWWKHWLUHVXVHGLQ 'XULQJဧDQGWHဧLQJWLUHZHLJKWDQGWUHDGKHLJKW Armenia are imported from Russian manufacturers ZHUHPHDVXUHGIRUGL൵HUHQWPLOHDJHYDOXHV ZKLOH in Russia and the recommended maintenance during actual operation, the weight of the front YDOXHVIRURSWLPDOXVDJHPD\EHGL൵HUHQWIRUURDG and rear tires were measured for the same mileage climate, and usage conditions in Armenia. Our values.The ဧDQG WHဧV ZHUH FDUULHG RXW XVLQJ ဧXG\SURYLGHVUHFRPPHQGDWLRQVDVWRWKHRSWLPDO ³&7:,67´ဧDQGV7KHUHVXOWVRIWKHဧDQGWHဧVDUH tire pressure and usage conditions required for VXPPDULVHG 7DEOHV DQG PD[LPXPXVDJHRIWLUHVLQ$UPHQLDIRULPSRUWDQW ORQJDUWHULDOURXWHVEHWZHHQPDMRUFLWLHV7KLVဧXG\ VKRZVPRဧLQÀXHQWLDOIDFWRUVD൵HFWLQJDXWRPRELOH tire usagewere the density of tire tread sipes and the LQWHUQDO WLUHSUHVVXUH > @ ([SHULPHQWV ZHUH FDUULHG RXW IRU 5& radial model tires include tire tread pattern wear, ERWKZLWKWKHDSSOLFDWLRQRIUHOHYDQWဧDQGVDQGLQ real operating conditions. 236 P.A. Tonapetyan et al. Annals of Agrarian Science 17 (2019) 236 – 241 Table 1.7KHWUHDGKHLJKWRI5&5DGLDOPRGHOWLUHVGHSHQGLQJRQ WKHPLOHDJHIRUGLৼHUHQWDLUSUHVVXUHYDOXHV Number of Tread height, h,mm Mileage, L tests P=2͎8P=3͎0P=3͎2 1 8.984 8.671 8.898 2 8.880 8.800 8.740 12000 3 8.778 8.930 8.584 average 8.881 8.800 8.741 1 5.997 5.003 4.998 2 5.212 5.477 4.864 36000 3 5.600 5.200 4.930 average 5.603 5.227 4.931 1 2.263 1.739 1.693 2 2.090 1.870 1.810 60000 3 1.920 1.999 1.925 average 2.091 1.869 1.809 Table 2.7KHZHLJKWRI5&5DGLDOPRGHOWLUHVGHSHQGLQJRQWKH PLOHDJHIRUGLৼHUHQWDLUSUHVVXUHYDOXHV Number of Weight, m,kg Mileage, L tests P=2͎8P=3͎0P=3͎2 1 23.420 23.352 23.062 2 23.324 23.241 23.159 12000 3 23.230 23.130 23.258 average 23.325 23.241 23.160 1 21.842 21.368 21.430 2 21.550 21.611 21.210 36000 3 21.700 21.486 21.322 average 21.697 21.488 21.321 1 20.401 20.121 20.168 2 20.280 20.170 20.088 60000 3 20.155 20.220 20.006 average 20.279 20.170 20.087 237 P.A. Tonapetyan et al. Annals of Agrarian Science 17 (2019) 236 – 241 7KHWHဧVZHUHFDUULHGRXWXVLQJWKHH[SHULPHQWDO b LV WKH FRH൶FLHQW RI WKH VTXDUH WHUP k is the SODQQLQJ PHWKRG ȼɤW\SH FRPSRVLWH SODQV ZHUH ij number of factors. XVHGWRSURFHVVH[SHULPHQWDOGDWD 7KH YHKLFOH PLOHDJH / DQG DLU SUHVVXUH LQ ,QဧDWLဧLFDODSSURDFKWKHPDWKHPDWLFDOPRGHO WLUHV 3 ZHUHFKRVHQDVIUHHIDFWRUV x 7LUHWUHDG RIDQREMHFWRUDSURFHVVLVSUHVHQWHGLQWKHIRUPRID KHLJKW h DQGZHLJKW P ZHUHFKRVHQDVRSWLPL]LQJ WZRGLPHQVLRQDOVHFRQGRUGHUSRO\QRPLDOHTXDWLRQ IDFWRUV < ZKLFKKDVWKHIROORZLQJDSSHDUDQFH>@ Factor levels and transformationintervals are given in Table 3. k k k 2 ([SHULPHQW SODQQLQJ PDWUL[ ZDV GHYHORSHG Y b0 ¦bi xi ¦bij xi x j ¦bii xi , i 1 i, j 1 i 1 to determine actual tread height and weight of215/75R16C Radial model tiredepending on YHKLFOH PLOHDJH / DQG DLU SUHVVXUH LQ WLUHV 3 where` b is the free term, b is the linear impact 0 i 7DEOHV DQG FRH൶FLHQWLVbGRXEOH SDLU LQWHUDFWLRQFRH൶FLHQWij Table 3.)DFWRUOHYHOVDQGWUDQVIRUPDWLRQLQWHUYDOV Factors studied Factor level and transformationinterval Pressure, P Mileage, L Code naming X1 X2 Zero level, xi 0 3 36000 Transformation interval, 'xi 0.2 24000 Lower level, xmin 1 2.8 12000 Upper level, xmax 1 3.2 60000 Table 4. ([SHULPHQWSODQQLQJPDWUL[GHWHUPLQLQJDFWXDOWUHDGKHLJKWRI5& 5DGLDOPRGHOWLUHVGHSHQGLQJRQYHKLFOHPLOHDJH / DQGDLUSUHVVXUHLQWLUHV Tread height, h, True value of factors Coded value of factors mm N° PL,kmX1 X2 hi 12 3 4 5 6 1 3.2 60000 1 1 1.809 2 2.8 60000 -1 1 2.091 3 3.2 12000 1 -1 8.741 4 2.8 12000 -1 -1 8.881 5 3.2 36000 1 0 4.931 6 2.8 36000 -1 0 5.603 7 3 60000 0 1 1.869 8 3 12000 0 -1 8.800 9 3 36000 0 0 5.227 238 P.A. Tonapetyan et al. Annals of Agrarian Science 17 (2019) 236 – 241 Table 5. ([SHULPHQWSODQQLQJPDWUL[GHWHUPLQLQJDFWXDOZHLJKWRI5& 5DGLDOPRGHOWLUHVGHSHQGLQJRQYHKLFOHPLOHDJH / DQGDLUSUHVVXUHLQWLUHV True value of factors Coded value of factors Weight, kg N° PLX1 X2 m 12 3 4 5 6 1 3.2 60000 1 1 20.087 2 2.8 60000 -1 1 20.279 3 3.2 12000 1 -1 23.160 4 2.8 12000 -1 -1 23.325 5 3.2 36000 1 0 21.321 6 2.8 36000 -1 0 21.697 7 3 60000 0 1 20.170 8 3 12000 0 -1 23.241 9 3 36000 0 0 21.488 Results and analysis PD\H[FHHGWKHSHUPLVVLEOHOLPLWGXULQJURDGWHဧV %\WDNLQJWKHFLUFXPဧDQFHLQWRDFFRXQWLQဧHDGRI As a result of mathematical processing of using the tread height, it is advisable to weigh the H[SHULPHQWDO GDWD UHVXOWV UHJUHVVLRQ HTXDWLRQ tire and determine the weight loss caused by tire FRH൶FLHQWV ZHUH GHWHUPLQHG DQG WKH IROORZLQJ wear. Internal tire air pressure was measured on a equations were developed: GDLO\EDVLVPDLQWDLQWKHဧDELOLW\RIWKHLQWHUQDODLU - for determining tread height of pressure. Tire pressures were measured and it was 215/75R16C Radial model tire measured on a daily basis after the minibus was 2 retired at the end of the day and was brought to m(X) 21.641 0.122X1 1.532X 2 0.208X 2 the recommended pressure less 4%.In addition, the (2) impact of the temperature increase on the internal - for determining weight of 215/75R16C pressure due to tire operation was not considered Radial model tire GXULQJ WKH WHဧV (60.0) +1.0 2.224 h(X) 5.328 0.182X 3.442X 0.112X 2 2.224 1 2 2 3.0 3.0 3.0 (3) (48.0) +0.5 3.881 3.881 3.881 ) 4.5 7KHDGHTXDF\RIUHJUHVVLRQHTXDWLRQZDVYHUL¿HG m 4.5 k 4.5 0 E\)LVFKHUFULWHULD>@ 0 5.328 0 5.328 1 (36.0) 0 8VLQJWKHHTXDWLRQV DQG DJURXSRIJUDSKV , 5.328 L ( e 6.5 showing the change of tread height and weight g 6.5 a 6.5 l of 215/75R16C Radial model tires weremade i M (24.0) -0.5 7.303 depending on vehicle mileage and air pressure in 7.303 7.303 8.0 WLUHV )LJXUH DQG 8.0 8.0 8.882 Under real operating conditions the vehicle tire 8.882 (12.0) -1.0 LQWHUDFWVZLWKWKHURDGSDYHPHQWDQGLVVXEMHFWHG -1 -0.5 0 +0.5 +1 (2.8) (2.9) (3.0) (3.1) (3.2) to surface irregularities including cutting and 5 Pressure (P, 10 Pa) VKDUSREMHFWVIRXQGRQWKHURDGAs a result of this Fig. 1.$JURXSRIJUDSKVVKRZLQJWKHFKDQJH interaction, as well as tire gyration, braking and RIWUHDGKHLJKWRI5&5DGLDOPRGHO acceleration; the tire tread sipes are worn unevenly. WLUHGHSHQGLQJRQYHKLFOHPLOHDJH X DQGDLU Therefore, the measurement error of the sipe height 1 SUHVVXUHLQWLUHV X 2 ) 239 P.A. Tonapetyan et al. Annals of Agrarian Science 17 (2019) 236 – 241 (60.0) +1.0 (60.0) +1.0 20.4 20.7 32 2 0.61 2 8 0.8 20.732 20.8 ) 20.8 85 20.73 20.8 2 m (48.0) +0.5 20. k 21.05 885 0 (48.0) +0.5 0 21.05 2 21.3 1.0 20 0 .885 ) 21.0 1 21.3 m , 21.3 21.0 k L 21.04 0 ( 0 e (36.0) 0 0 1 g 21.04 21.448 , a 21.04 21.4 l 48 23.0 L i 23.0 ( (36.0) 0 e M 23.0 g 21.448 22.33 a l 22.33 i 22.33 (24.0) -0.5 M 22.0 22.0 22.302 22.0 22.302 (24.0) -0.5 23.3 22. 23.3 302 23.3 (12.0) -1.0 23.0 -0.5 +0.5 +1 23.0 -1 0 23.0 (2.8) (2.9) (3.0) (3.1) (3.2) 23.4 5 53 23.453 Pressure (P, 10 Pa) (12.0) -1.0 -1 -0.5 0 +0.5 +1 (2.8) (2.9) (3.0) (3.1) (3.2) 5 Fig. 2.$JURXSRIJUDSKVVKRZLQJWKH Pressure (P, 10 Pa) ZHLJKWFKDQJHRI5&5DGLDOPRGHO WLUHGHSHQGLQJRQYHKLFOHPLOHDJH X1 DQGDLU Fig. 3.$JURXSRIJUDSKVVKRZLQJWKHZHLJKW SUHVVXUHLQWLUHV X 2 ) FKDQJHRIUHDUWLUHGHSHQGLQJRQYHKLFOH 7KHIROORZLQJUHJUHVVLRQHTXDWLRQV DQG ZHUH PLOHDJH X1 DQGDLUSUHVVXUHLQWLUHV X 2 ) developed as a result of the mathematical processing of the results obtained from measurements taken (60.0) +1.0 20.1 20 20 25 during mini bus operation: .515 .23 20.3 20 - For measuring weight of rear tire .515 20.3 2 0.03 20.515 2 (48.0) +0.5 (4) 21 m(x) 21.446 0.114X1 1.418X2 0.589X 2 .872 20.03 ) 21.872 m k 21.872 - For measuring weight of front tire 0 2 0 1.286 0 21.286 1 , (36.0) 0 2 L ( 21.286 m(x) 21.286 0.168X 1.579X 0.529X e 1 2 2 2 g 1.8 a 21 l .8 i 21.8 (5) M 22.207 22.207 22.207 8VLQJHTXDWLRQV DQG D JURXS RI JUDSKV 23.0 (24.0) -0.5 23.0 showing the weight change of front and rear tireswas 23.0 23.394 made depending on vehicle mileage and air pressure (12.0) -1.0 -1 -0.5 0 +0.5 +1 (2.8) (2.9) (3.0) (3.1) (3.2) LQWLUHV )LJDQG 5 Pressure (P, 10 Pa) Conclusion Fig. 4.$JURXSRIJUDSKVVKRZLQJWKHZHLJKW 2SHUDWLRQDOWHဧLQJRIPLQLEXVWLUHVVKRZVWKDW FKDQJHRIIURQWWLUHGHSHQGLQJRQYHKLFOH WKH YHKLFOHVZLOO KDYH PD[LPXP PLOHDJH XQGHU PLOHDJH X1 DQGDLUSUHVVXUHLQWLUHV X 2 ) optimal pressure conditions.)RU H[DPSOH ZKHQ the tire inner pressure is within recommended The analysis of regression equations, developed limits, the weight of rear tire is 21.872 kg in case of E\ WKLV ဧXG\ LQ ERWK ဧDQG DFFHOHUDWHG DQG UHDO 36000 km, while in case of 48000 km, the weight operating conditions visualised with the graphs LV NJ WKHKHLJKWRIWKHWUHDGLVZLWKLQOLPLWV indicates that the tire tread wear is more intense RIPPKHQFHWKHWLUHWUHDGZHDULVPP VR in the middle of the tire compared to the rims, and tire tread wear tends to be minimal under optimal more pronounced when measuring between 24000 SUHVVXUH FRQGLWLRQV7KH FRPSDULVRQ RI ဧDQG DQG to 36000km of travel. The maintenance internal RSHUDWLRQDOWHဧLQJUHVXOWVVKRZVWKDWWKHGL൵HUHQFH SUHVVXUHRIWKHWLUH RSWLPDOYDOXH PD[LPL]HVWKH in tire weight loss is 3 to 7%, while the average tire tire usage. tread wear in comparison is within 5%. 240 P.A. Tonapetyan et al. Annals of Agrarian Science 17 (2019) 236 – 241 References Yu.I., Methods of Planning and Processing the 5HVXOWVRID3K\VLFDO([SHULPHQW$WRPL]GD [1] $YDJ\DQ$* )DFWRUV D൵DFWLQJ DXWRPRELOH 0RVFRZ LQ 5XVVLDQ tire resource and the evaluation of their >@ 0RQWJRPHU\ '. ([SHULPHQW 3ODQQLQJ DQG ,PSDFW 18$&$&ROOHFWLRQ RI 6FLHQWL¿F Data Analysis, Shipbuilding, Lion, 1980. :RUNV9RO,,, 241 S. Khutsishvili et al. Annals of Agrarian Science 17 (2019) 242 – 250 Annals of Agrarian Science :ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ Structural and Magnetic Properties of Silver Oleic Acid Multifunctional Nanohybrids S. Khutsishvilia, P. Toidzeb, M. Donadzeb, M. Gabrichidzeb*, T. Agladzeb, N. Makhaldianib a$()DYRUVN\,UNXWVN,QဧLWXWHRI&KHPLဧU\RIWKH6LEHULDQ%UDQFKRIWKH5XVVLDQ$FDGHP\RI6FLHQFHV Favorskogo Str., Irkutsk, 664033, Russia bTechnical University of Georgia, Department of Chemical and Biological Technologies 0.RဧDYD6WU7ELOLVL*HRUJLD Received: 15 May 2018; accepted: 19 September 2018 A B S T R A C T 6ROVRIFRUHVKHOOVLOYHU13VDUHV\QWKHVL]HGE\HOHFWURFKHPLFDOPHWKRG7KHPHWKRGSURYLGHVWKHDELOLW\WRDGMXဧWKHSDUWLFOHVL]H by changing both the concentration of oleic acid and the residence time W 0 in the organic phase. We synthesized silver nanoparticles ZLWKROHLFDFLGFRQFHQWUDWLRQRI $J 2$ DQG $J 2$ 7KHVHVLOYHUQDQRSDUWLFOHVKDYHEHHQဧXGLHG XVLQJPRGHUQSK\VLFDO±FKHPLFDOPHWKRGV 7UDQVPLVVLRQ(OHFWURQ0LFURVFRS\ 7(0 )RXULHU7UDQVIRUP,QIUDUHG6SHFWURVFRS\ )7 ,5 '\QDPLF/LJKW6FDWWHULQJ '/6 7KHUPRJUDYLPHWULFDQG'L൵HUHQWLDO7KHUPDO$QDO\VLV 7*$DQG'7$ (OHFWURQ3DUDPDJQHWLF 5HVRQDQFH (35 DTA curves indicate the chemical nature of bond ligand in the secondary shell.This conclusion supported by quantum FKHPLFDOVLPXODWLRQE\XVLQJTXDQWXPFKHPLFDOVRIWZDUH+\SHU&KHPDQGVHPLHPSLULFDOFDOFXODWLRQPHWKRG=,1'2In the EPR VSHFWUDRIVLOYHUFRQWDLQLQJVROV$J 2$DQG$J 2$DFRPSOH[ZLGHDV\PPHWULFVLJQDOZLWKVHYHUDOUHVRQDQWOLQHVLV UHFRUGHGZKLFKLVFRQVLဧHQWZLWKDZLGHVL]HGLဧULEXWLRQRIQDQRSDUWLFOHV,WLVLPSRUWDQWWRQRWHWKDWDFKDQJHLQWKHROHLFDFLGOD\HUV RIWKHQDQRSDUWLFOHVVHHPVWRD൵HFWWKHGLPHQVLRQRIWKHQDQRFU\ဧDOOLWHVWKDWDUHEHLQJIRUPHG7KHSUHVHQFHRIWKH)05UHVRQDQFH OLQHLQ$J 2$PD\LQGLFDWHVWKHSUHVHQFHRI$JFXELFFHOOVLQQDQRSDUWLFOHVZLWKLQWHUQDOPDJQHWLF¿HOGVVLJQL¿FDQWO\ODUJHU WKDQWKH=HHPDQ¿HOGWKHDYDLODEOH(35LQWKH;EDQGUDQJH Keywords:&RUHVKHOO1DQRSDUWLFOHV2OHLFDFLG/LJDQG&KDUJH$FWLYDWLRQHQHUJ\ &RUUHVSRQGLQJDXWKRU 0DLD*DEULFKLG]H (PDLODGGUHVV JDEULFKLG]HPDLD#JPDLOFRP Introduction area to volume. In this regard, it is necessary to determine the physicochemical properties of Silver nanoparticles is one of the important QDQRSDUWLFOHV LQ RUGHU WR HဧDEOLVK WKH H[SHFWHG DQG LQWHUHဧLQJ QDQRPDWHULDOV WKH XVH RI ZKLFK chemical, physical and catalytic activity. LV SURPLVLQJ LQ WKH HQYLURQPHQW ZDWHU DQG DLU (൵HFWLYHDSSOLFDWLRQRIQDQRSDUWLFOHVDVEXLOGLQJ SXUL¿FDWLRQFDWDO\VLV LQWKH¿HOGRIELRPHGLFLQH EORFNV LQ ERWWRPXS GHVLJQ RI PXOWLFRPSRQHQW GLDJQRVLVDQGWUHDWPHQWRIFDQFHU IRRGLQGXဧU\ QDQRFRPSRVLWHV UHTXLUHV PRQLWRULQJ RI SDFNDJLQJ PDWHULDOV LQ WKH PDQXIDFWXUH RI fundamental properties, such as size, charge, PHGLFDO LQဧUXPHQWV DQWLEDFWHULDO FRDWLQJV LQ chemical reactivity and ability of nanoparticles to optical devices, cosmetics, in the pharmaceutical disperse in various media. Owing to high aspect LQGXဧU\ ratio, metal nanoparticles tend to agglomeration, 'XHWRWKHLUQDQRVL]HPHWDOOLFVLOYHUSDUWLFOHV DJJUHJDWLRQDQGFRUURVLRQSURFHVVHV¿QDOO\OHDGLQJ have unique physicochemical, biological properties to loss of valuable properties inherent to building that are associated with an increased ratio of surface of blocks. Chemisorption of organic ligand shell 242 S. Khutsishvili et al. Annals of Agrarian Science 17 (2019) 242 – 250 SURYLGHV ဧHULF ဧDELOL]DWLRQ RI QDQRSDUWLFOH FRUH following conditions: amplitude modulation 10.0 SUHYHQWLQJ LWV GHJUDGDWLRQ 7KH SUHVHQW ဧXG\ LV G, modulation frequency 100 kHz, averaged scans IRFXVHG RQ FKDUDFWHUL]DWLRQ RI PHWDO FRUHOLJDQG ¿HOGUDQJH*FHQWUH¿HOG*WLPH shell interactions as well as on ligands molecules FRQဧDQWVFRQYHUVLRQWLPHVPLFURZDYH interaction in primary and secondary layers of the SRZHU P: &: (35VSHFWUD ZHUH VKHOO SKHQRPHQD ODUJHO\ GHWHUPLQLQJ ERWWRPXS UHFRUGHG RI WKH DQG VDPSOHV J DW WKH ဧUDWHJ\ IRU V\QWKHVLV RI PXOWLIXQFWLRQDO K\EULG following conditions: amplitude modulation 10.0 QDQRSDUWLFOHV >@ G, modulation frequency 100 kHz, averaged scans ¿HOG UDQJH * FHQWUH ¿HOG * WLPH Experimental FRQဧDQWVFRQYHUVLRQWLPHVPLFURZDYH power 0.6325 mW. &KHPLFDOV DQG LQဧUXPHQWV The reagents 7KH PHWDOV SHUFHQWDJH RI WKH ဧXGLHG XVHG LQ WKLV ဧXG\ DUH SXUFKDVHG IURP 6LJPD nanocomposites was evaluated by atomic absorption $OGULFKXQOHVVRWKHUZLVHVSHFL¿HGDQGXVHGZLWKRXW analysis using a HITACHI TM 3000, detector SDD SXUL¿FDWLRQ &KHPLFDO LQWHUDFWLRQV RI VXUIDFWDQW ;)ODVK + 7DEOH ZLWK 13V ဧXGLHG E\ )7,5 VSHFWURVFRS\ LQ D range of 400–4000 cmí with the resolution of 0.5 Preparation of sols of AgNPs. Sols of silver cmí 7KHUPR 1LFROHW $YDWDU XVH WKH .%U 13VLQDKH[DQHDUHV\QWKHVL]HGE\HOHFWURFKHPLFDO technique. Size, shape and chemical composition PHWKRGLQDUHDFWRUFRQVLဧLQJRIVDFUL¿FLDOVLOYHU RI LVRODWHG 13V DUH HဧLPDWHG IURP 7(0 7HVOD DQRGH SXULW\ DQG DOXPLQXP %6 DQG 6(0 -60/9 LPDJHV 7KH cathode, which upon rotation crosses immiscible samples are prepared by placing small drops of a OD\HUVRIDTXHRXV 0$J123GRXEOHGGLဧLOOHG VRO RQWR WKH FDUERQFRDWHG FRSSHU JULG 7KH VL]H ZDWHU DQGRUJDQLF KH[DQHDQG2$ GLဧULEXWLRQRI13VLQDVROHLVHYDOXDWHGIURPODVHU VROYHQWV>@7KHH[SHULPHQWDOVHWXSDOORZVVLOYHU EHDP G\QDPLF OLJKW VFDWWHULQJ GDWD =HWDVL]HU ions formed at the anode to discharge at the cathode 1DQR 0DOYHUQ 3ULRU WR VDPSOH SODFLQJ LQWR D VXUIDFHSRLVRQHGE\VXUIDFWDQW 2$ ZKLFKDGVRUEV FXYHWWHWKHDVSUHSDUHGVROVDUHGLOXWHGZLWKKH[DQH at sites favorable for silver adatoms and inhibits the 7KHဧUXFWXUDODQGWKHUPDOဧDELOLW\SURSHUWLHV JURZWKRIVLOYHUQDQRFOXဧHUV7KHODWWHULVZHDNO\ RI QDQRSDUWLFOHV DUH FKDUDFWHUL]HG E\ WKHUPR DGVRUEHG DW WKH VXUIDFH DQG ဧURQJO\ ERQGHG WR JUDYLPHWULFDQDO\VLV 7*$ DQGGL൵HUHQWLDO thermal amphiphile OA molecules which are easily washed DQDO\VLV '7$ WHFKQLTXH 1(7=6&+67$ RXWIURPFDWKRGHXSRQURWDWLRQIRUPLQJဧDEOHVROV 5HJXOXV ,QERWKFDVHVFKDUDFWHUL]HGE\DFWLYDWLRQ RI$J±2$FRUH±VKHOO13VLQKH[DQH7KHPHWKRG energies calculated from OA transformation SURYLGHV WKH DELOLW\ WR DGMXဧ WKH SDUWLFOH VL]H E\ during the thermal decomposition, using Ozawa changing both the concentration of oleic acid and )O\QQ:DOOPHWKRGGHULYHGIURPWKHLQWHJUDOLVR the residence time W 0 GXULQJZKLFKWKHPHWDOFOXဧHU FRQYHUVLRQDO PHWKRG > @ IRUPHGDWWKHERUGHURIWKHFDWKRGHZDWHUHOHFWURO\WH (35 VSHFWUD ZHUH UHFRUGHG RQ D )7 ;EDQG allows the amphiphile surfactants to adsorb from %UNHU (/(;6<6 ( VSHFWURPHWHU ;ZDYH the organic phase. The results of measuring the size UDQJH *+] 3UHFLVLRQ RI WKH PHDVXUHPHQW RI of silver nanoparticles using the DLS method are JIDFWRU ZDV &: (35VSHFWUD ZHUH VKRZQ 7DEOH UHFRUGHG RI WKH DQG VDPSOHV J DW WKH Table 1.7KHHOHPHQWDODQDO\VLVRIWKHVDPSOHV Mass content, % Sample COAg $J 2Ⱥ 11.8 3.6 84.6 $J 2Ⱥ 12.8 3.9 83.3 243 S. Khutsishvili et al. Annals of Agrarian Science 17 (2019) 242 – 250 Table.2.6L]HRIVLOYHUQDQRSDUWLFOHVFRYHUDJHE\ROHLFDFLG Concentration OA(%) Z-Average (d.nm) PdI Wo (sec) 0.25 15.62 0.15 45 0.50 14.95 0.14 42 0.75 15.74 0.14 39 1.00 16.96 0.24 36 ,Q WKH SUHVHQW ဧXG\ HOHFWURV\QWKHVLV KDV EHHQ OA solutions are characterized by appearance of FDUULHG RXW DW H[SHULPHQWDO FRQGLWLRQV \LHOGLQJ two new bounds at 1639 and 1509 cm )LJ D assembles of spherical silver NPs Ag&0.25%OA by which are typical for the asymmetric and symmetric 7(0 )LJD 7KHKLဧRJUDP )LJE RIWKHVL]H FDUER[\ODWHဧUHWFK7KHVHH൵HFWVDUHLQWHUSUHWHGDV GLဧULEXWLRQVKRZVWKHDYHUDJHGLDPHWHURIWKH13V the evidence of OA bidentate bonding to silver via LVQPǻ4±QXPEHURISDUWLFOHVLQ6L]H WZRV\PPHWULFDOO\FRRUGLQDWHR[\JHQDWRPVRIWKH GLဧULEXWLRQRI$J 2$DQG$J 2$ FDUER[\ODWHKHDG>@7KHH൵HFWRILQFUHDVHLQROHLF determined from DLS method is Z ave =15.62 nm, DFLGFRQFHQWUDWLRQRQ)7,5VSHFWUDFKDUDFWHULဧLFV PdI= 0.15 and Z ave QP3G, 7DEOH )LJE $FFRUGLQJ WR WKHVH GDWD WKH PDMRU H൵HFW is appearance of a new peak at 1708.6cm that is FT-IR spectroscopy. The chemical bonding FKDUDFWHULဧLFIRU& 2ERQGဧUHWFK RI 2$ PROHFXOHV WR VLOYHU QDQRFOXဧHUV LQ GLOXWHG a b Fig. 1.7(0LPDJH D DQGKLVWRJUDPRIWKHVL]HGLVWULEXWLRQ E RIVLOYHU13VFDSSHGRI2$ a b Fig. 2.)7,5VSHFWUDVLOYHUQDQRSDUWLFOHVFDSSHGE\PRQROD\HU D DQGELOD\HU E 244 S. Khutsishvili et al. Annals of Agrarian Science 17 (2019) 242 – 250 TGA and DTA measurements data. The According to this method: application of dynamic TG methods holds great AE E promise as a tool for unraveling the mechanisms of ln E ln a 5.3311.052 a (2) physical and chemical processes occurred during Rg x RT WKH GHFRPSRVLWLRQ RI VROLGV ,Q WKLV LQYHဧLJDWLRQ 2]DZ)O\QQ:DOO 2): PHWKRGVKDYHEHHQXVHG ZKHUH $ LV IUHTXHQF\ IDFWRU DQG J [ LV WR DQDO\]H WKH QRQLVRWKHUPDO GHVRUSWLRQ NLQHWLFV IXQFWLRQGHSHQGVRQWKHUDWHRIFRQYHUVLRQȕ± of silver nanoparticles capped with oleic acid heating rate, T – temperature, R = 8.31J/mol·K. ligand. TGA and DTA curves of Ag&0.25%OA and Thermodesorption activation energies Ag&0.75%OA samples are measured at heating rate calculated by OFW method (Equation 1) as ȕ .PLQ )LJDE a function of the conversion degree (Fig. 4). E Sharp increase in a observed at low mass losses in concentrated solution indicates the change of desorption mechanism in bilayer system. Ag&0.75%OA a Ea (kJ/mol) Ag&0.25%OA Fig. 4.7KHUPRGHVRUSWLRQDFWLYDWLRQHQHUJLHV FDOFXODWHGE\2):PHWKRGDVDIXQFWLRQRIWKH b FRQYHUVLRQGHJUHH Fig. 3.7*$DQG'7$FXUYHVRI$J 2$ The calculation of the coating of nanoparticles D DQG$J 2$ E VDPSOHV with OA was calculated according to equation 3. 3 TGA patterns in diluted OA solutions are 4Ur SZN N A (3) characterized by one step mass loss (3.81%) curve. 3 100 Z M OA DTA curve measured under the same conditions where N is the number of oleic acid ligands per 0 displays exothermic peak at 287.9 C. Corresponding SDUWLFOHȡ JFP3 is the density of the silver, enthalpy is 96.4 J/g. Contrary to these data, TGA r= 7.2nm is the average radius of the Ag&0.25%OA curves measured in OA rich solutions display two EDVHGRQWKH7(0UHVXOWV)LJ Ȧ LVWKH 0 step mass loss 9.35 % (50 – 340 C) and 21.89 % ZHLJKW ORVV LQ N î 23 mol, is 0 A (340-600 C). Corresponding DTA curve displays $YRJDGUR¶VFRQဧDQWDQGM JPROLV 0 OA two exothermic peaks at 276.3 and 376.5 ǹ. the molecular weight of oleic acid. Calculated enthalpies are 44.22 J/g and 43.77 J/g. The number of ligands was calculated for Thermodesorption E values have been calculated a Ag&0.25%OA N=1385. Assuming that the surface E\2]DZD)O\QQ:DOO 2): PHWKRGGHULYHGIURP of the NPs is covered with a close packed monolayer WKH LQWHJUDO LVRFRQYHUVLRQDO PHWKRG XVLQJ 'R\OH¶V of the surfactant, the surface area S occupied by the DSSUR[LPDWLRQ (TXDWLRQ >@ oleic acid ligand A indicates the ratio of the total surface area of the particle to the number of oleic AE acid ligands A=0.46nm2. Considering the fact that f a | 7.03103 a exp(1.052E / RT) ER a the area of one molecule of oleic acid S=0.21nm2, (1) percentage of silver nanoparticle surface coating 245 S. Khutsishvili et al. Annals of Agrarian Science 17 (2019) 242 – 250 with oleic acid molecules is 45%. Discussion Quantum-chemical simulation. Molecular models of free and adsorbed oleic acid at silver NPs $Q LQFUHDVLQJ YROXPH RI ဧXGLHV DLPHG DW DUH FUHDWHG E\ XVLQJ TXDQWXPFKHPLFDO VRIWZDUH H[DPLQDWLRQRIWKHPHFKDQLVPRIXQVDWXUDWHGIDWW\ +\SHU&KHP DQG VHPLHPSLULFDO FDOFXODWLRQ DFLGOLJDQGVLQWHUDFWLRQZLWKPHWDOVDQGPHWDOR[LGH PHWKRG =,1'2>@ (OHFWURဧDWLF SRWHQWLDOV cores have been conducted by means of TEM, DLS, VLJQL¿FDQWO\YDU\IURPFKHPLVRUEHG2$PROHFXOHV )7,57*$ '7$ DQG (35 PHWKRGV >@ 7KH )LJDE /LJDQGLQWHUDFWLRQZLWK$J13VUHVXOWV ELGHQWDWHFRYDOHQWERQGLQJRIR[\JHQDWRPVRISRODU LQ LQFUHDVH RI H൵HFWLYH FKDUJH DQG HOHFWURဧDWLF FDUER[\OLF JURXSV ZLWK FRUH 13V DVVXPHG WR EH potential at silver surface indicating charge transfer the driving force formation of chemisorbed ligand IURPOLJDQGFDUER[\OJURXSWRQDQRSDUWLFOHDWRPV PRQROD\HU $SSHDUDQFH RI D QHZ )7,5 SHDN DW Formation of a secondary layer in solutions 1708cm FKDUDFWHULဧLFIRU& 2ERQGဧUHWFK )LJ ULFKLQ2$LVDFFRPSDQLHGE\LQFUHDVHHOHFWURဧDWLF E DVZHOODVWZRဧHSPDVVORVV7*$FXUYHVDQG potential at silver. DSSHDUDQFH WZR H[RWKHUPLF SHDNV DW '7$ FXUYHV According to quantum, chemical calculations of )LJE VKRZQLQSUHVHQWဧXG\FOHDUO\GHPRQဧUDWH chemisorbed OA silver ligand interaction resulted that at high OA concentration Ag NPs are capped LQUHGLဧULEXWLRQRIHOHFWURQGHQVLW\DW2$PROHFXOH by adsorbed ligand bilayers. Contrary to widely 7KH HOHFWURဧDWLF SRWHQWLDO DW FDUER[\O JURXS RI accepted concept on physical nature of ligands, ERQGLQJLQWKHVHFRQGDU\VKHOO> @VLJQL¿FDQW monolayer and bilayer OA are U1 Hc DQG U Hc FRUUHVSRQGLQJO\ )LJDE enthalpies calculated from DTA curves indicates 2 the chemical nature of bonding. This conclusion supported by quantum chemical simulation leads to the model of formation C=C double bonds as D UHVXOW RI FRXSOLQJ RI GHORFDOL]HG SHOHFWURQV RI primary and secondary layers. Inversion of the secondary OA layer apparently originated from UHSXOVLRQRISRODUFDUER[\OLFJURXSVLQDVHFRQGDU\ VKHOORZHVWRLQFUHDVHLQQHJDWLYHFKDUJHDWR[\JHQ atoms. Finally, this leads to formation of branching ligand network. The other important conclusion on the mechanism of ligand chemisorption is followed from variation of thermodesorption activation HQHUJLHV ZLWK FRQYHUVLRQ GHJUHH )LJ ,W LV widely accepted that formation of ligand primary adsorbed layer follows Langmuir low, which DVVXPHV DGVRUSWLRQ DW KRPRJHQRXV VXEဧUDWH DQG predicts independence of adsorption energy from VXUIDFH FRYHUDJH 2XU H[SHULPHQWDO GDWD DUH LQ sharp disagreement with these assumptions. In contradiction to Langmuir adsorption model the GDWD VKRZQ DW )LJ WHဧLI\ D VLJQL¿FDQW FKDQJH LQ thermodesorption activation energy with variation in a number of adsorbed OA molecules in a primary shell. To interpret activation energy patterns we have to account for the fact that nanoparticles surface formed under highly nonequilibrium conditions due WRDUWL¿FLDOWHUPLQDWLRQRIFU\ဧDOJURZDQGIUHH]LQJ LUUHJXODUဧUXFWXUHE\FDSSLQJDJHQW7KHVHOHDGVWR PRUHUHDOLဧLFPRGHODFFRXQWLQJIRUH൵HFWRIVXUIDFH Fig. 5.(OHFWURVWDWLFSRWHQWLDOVPDSVIRU inhomogeneity resulting in increase of adsorption FKHPLVRUEHGPRQR D DQGELOD\HU E HQHUJ\ZLWKVXUIDFHFRYHUDJH&RPSOH[YDULDWLRQRI 2$PROHFXOHV Ea.ZLWKPDVVORVVLQSUHVHQFHRI2$H[FHVVDSSDUHQWO\ 246 S. Khutsishvili et al. Annals of Agrarian Science 17 (2019) 242 – 250 UHÀHFWVFRQWULEXWLRQRIVHYHUDOIDFWRUV LQFUHDVHLQ(a (35DFWLYH SDUDPDJQHWLF VXUIDFHဧDWHV1RWHLQWKH as OA molecules desorbed from sites with higher case Ag&0.25%OA sols with the one layer of oleic adsorption energy and simultaneous variation in DFLG )LJ D LQ FRPSDULVRQ ZLWK $J 2$ FKHPLFDO ERQG ဧUHQJWK LQ D VHFRQGDU\ OD\HU the broad line becomes more intense with a changing EPR. ,Q WKH (35 VSHFWUD RI VLOYHUFRQWDLQLQJ environment due to decrease in the “shielding” of VROV$J 2$DQG$* 2$DFRPSOH[ the nanoparticles between themselves. In addition, wide asymmetric signal with several resonant lines the nanoscale particles are closely located to each LV UHFRUGHG )LJ ZKLFK LV FRQVLဧHQW ZLWK D RWKHUDVDUHVXOWRIZKLFKGLSROHGLSROHLQWHUDFWLRQV ZLGHVL]HGLဧULEXWLRQRIQDQRSDUWLFOHV>@,Q between them intensify, which also could be leads VLPLODU PHWDOFRQWDLQLQJ QDQRV\ဧHPV OLNH RWKHU to an additional line broadening. GLVRUGHUHG RU SDUWLDOO\ RUGHUHG V\ဧHPV KDYH D ,QWKH(35VSHFWUDRIVLOYHUFRQWDLQLQJVROVWKH VSUHDGLQWKHV\PPHWULHVRIWKHQHDUHဧHQYLURQPHQW DQLVRWURSLF VLJQDO ZKLFK EHORQJV WR GLYDOHQW of individual paramagnetic centers, so in the EPR VLOYHU7KHDSSHDUDQFHRIVXFKKLJKO\R[LGL]HGVLOYHU spectra we observe not one line, but the envelope ဧDWHVRQWKHVXUIDFHRIQDQRSDUWLFOHVRFFXUVWKURXJK RIDVHWRIOLQHVZLWKFORVHEXWGL൵HUHQWIURPHDFK WKHGLVSURSRUWLRQDWLRQRI$J , ZKLFKOHDGVWRWKH other parameters. The presence of nanoparticles of IRUPDWLRQRI$J ,, LRQVDQGPHWDO$J0VLOYHU> GL൵HUHQW GLDPHWHUV DQG GL൵HUHQW VXSUDPROHFXODU @ (35 FKDUDFWHULဧLFV RI WKH FRPSOH[HV DFFRUG RUJDQL]DWLRQRI WKH V\ဧHP DV D ZKROH LQFOXGLQJ ZLWKWKHDYDLODEOHOLWHUDWXUHGDWDIRUDQDORJRXVWZR The inevitable absence of a regular periodic YDOHQFHVLOYHU>@ ဧUXFWXUHDQGWKHXQHYHQGLဧULEXWLRQRIQDQRSDUWLFOHV It is important to note that a change in the oleic LQDဧDELOL]LQJPHGLXPD൵HFWVWKHV\PPHWU\RIWKH DFLG OD\HUV RI WKH QDQRSDUWLFOHV VHHPV WR D൵HFW WKH VLJQDO 7KH OLQHV ZLWK D SHDNWRSHDN ZLGWKǻ+pp GLPHQVLRQRIWKHQDQRFU\ဧDOOLWHVWKDWDUHEHLQJIRUPHG of several hundred Gauss are caused by collective 7KXVLQWKHVROVZKHQSDVVLQJIURPWKHPRQRWRWKH HOHFWURQLF VSLQ SKHQRPHQD IRU D PHWDOFRQWDLQLQJ bilayer of oleic acid, both small particles and larger QDQRPDWHULDO>@ZKLFKDUHH[SODLQHGDV5..< multidomain agglomerates are found. So, the narrow LQWHUDFWLRQVH[FKDQJHLQWHUDFWLRQVRIPDJQHWLFLRQV ZHDNVLJQDO LQWKHUHJLRQRIWKHJIDFWRUDOVR ZLWKFRQGXFWLRQHOHFWURQV>@VLJQL¿FDQWOLQH refers to the spin resonance of conduction electrons broadening can be attributed to Korringa interaction IURP]HURYDOHQWVLOYHU>@7KLVOLQHLVXVXDOO\ >@IHUURPDJQHWLVP>@DQGRWKHUH[FKDQJH FKDUDFWHULဧLFRIVPDOOQDQRSDUWLFOHVXVXDOO\DURXQG LQWHUDFWLRQV >@ QP> @7KHSUHVHQFHRIWKH)05UHVRQDQFHOLQH 7KH (35 VLJQDO WKH VRFDOOHG VXSHUSDUD LQ$J 2$ PD\ LQGLFDWHV WKH SUHVHQFH RI PDJQHWLFFRQVLဧVRIVHYHUDORYHUODSSLQJFRPSRQHQWV $JFXELFFHOOVLQQDQRSDUWLFOHVZLWKLQWHUQDOPDJQHWLF with an average JIDFWRURI DQGDOLQHZLGWK ¿HOGV VLJQL¿FDQWO\ ODUJHU WKDQ WKH =HHPDQ ¿HOG WKH ǻ+ RI DERXW * 7KLV OLQH LV GXH WR WKH DYDLODEOH(35LQWKH;EDQGUDQJH )LJE > FRQGXFWLRQ HOHFWURQV RI &(65 QDQRSDUWLFOHV > @$W ORZ WHPSHUDWXUH RI . WKH )05 VLJQDO LV @ZKLOHWKHVSLQRUELWLQWHUDFWLRQIRUEXON$JLV broadened several times. This resonance line arises VRVLJQL¿FDQWWKDWWKHUHVRQDQWVLJQDOFDQEHREVHUYHG IURP VLOYHU QDQRFU\ဧDOOLWHV ZLWK WKH SURSHUWLHV RI D RQO\ DW YHU\ ORZ WHPSHUDWXUHV >@ 6XFK D EURDG EXON PDWHULDO UHSUHVHQWLQJ D PXOWLGRPDLQ V\ဧHP signal can also be associated with some localized ZKHUHVSLQVDUHRULHQWHGDORQJWKHGLUHFWLRQRIWKH¿HOG a b Fig. 6.$J 2$ D DQG$J 2$ E 247 S. Khutsishvili et al. Annals of Agrarian Science 17 (2019) 242 – 250 The inevitable absence of a regular periodic $J 2$ PD\ LQGLFDWHV WKH SUHVHQFH RI$J ဧUXFWXUHDQGWKHXQHYHQGLဧULEXWLRQRIQDQRSDUWLFOHV cubic cells in nanoparticles with internal magnetic LQDဧDELOL]LQJPHGLXPD൵HFWVWKHV\PPHWU\RIWKH ¿HOGVVLJQL¿FDQWO\ODUJHUWKDQWKH=HHPDQ¿HOGWKH VLJQDO 7KH OLQHV ZLWK D SHDNWRSHDN ZLGWKǻ+pp DYDLODEOH(35LQWKH;EDQGUDQJH )LJE > of several hundred Gauss are caused by collective @$WORZWHPSHUDWXUHRI.WKH)05VLJQDOLV HOHFWURQLF VSLQ SKHQRPHQD IRU D PHWDOFRQWDLQLQJ broadened several times. This resonance line arises QDQRPDWHULDO>@ZKLFKDUHH[SODLQHGDV5..< IURPVLOYHUQDQRFU\ဧDOOLWHVZLWKWKHSURSHUWLHVRID LQWHUDFWLRQVH[FKDQJHLQWHUDFWLRQVRIPDJQHWLFLRQV EXONPDWHULDOUHSUHVHQWLQJDPXOWLGRPDLQV\ဧHP ZLWKFRQGXFWLRQHOHFWURQV>@VLJQL¿FDQWOLQH where spins are oriented along the direction of the broadening can be attributed to Korringa interaction ¿HOG >@IHUURPDJQHWLVP>@DQGRWKHUH[FKDQJH LQWHUDFWLRQV >@ 7KH (35 VLJQDO WKH VRFDOOHG VXSHUSDUD Conclusion PDJQHWLFFRQVLဧVRIVHYHUDORYHUODSSLQJFRPSRQHQWV ,QWKHSUHVHQWဧXG\ZHFODLPHGWKDWVHFRQGDU\ with an average JIDFWRURI DQGDOLQHZLGWK OLJDQGOD\HURIWKHVKHOOIRUPVEUDQFKLQJဧUXFWXUH ǻ+ RI DERXW * 7KLV OLQH LV GXH WR WKH of chemically bonded ligand molecules. This FRQGXFWLRQHOHFWURQVRI&(65QDQRSDUWLFOHV> conclusion supported by quantum chemical @ZKLOHWKHVSLQRUELWLQWHUDFWLRQIRUEXON$JLV simulation which leads to the model of formation VRVLJQL¿FDQWWKDWWKHUHVRQDQWVLJQDOFDQEHREVHUYHG C=C double bonds resulting from coupling of RQO\DWYHU\ORZWHPSHUDWXUHV >@6XFKDEURDG GHORFDOL]HGSHOHFWURQVRISULPDU\DQGVHFRQGDU\ signal can also be associated with some localized layers. Desorption activation energy patterns (35DFWLYH SDUDPDJQHWLF VXUIDFHဧDWHV1RWHLQWKH GLVSOD\HGVLJQL¿FDQWYDULDWLRQLQDFWLYDWLRQHQHUJLHV case Ag&0.25%OA sols with the one layer of oleic ZLWKOLJDQGVXUIDFHFRYHUDJHWHဧLI\LQJLQFRQVLဧHQFH DFLG )LJ D LQ FRPSDULVRQ ZLWK$J 2$ with widely accepted Langmuir adsorption model. the broad line becomes more intense with a changing 0RUH UHDOLဧLF PRGHO RI OLJDQG FKHPLVRUSWLRQ environment due to decrease in the “shielding” of accounting for energetic inhomogeneity of metal the nanoparticles between themselves. In addition, nanoparticle surface is proposed. In the EPR the nanoscale particles are closely located to each VSHFWUD RI VLOYHUFRQWDLQLQJ VROV $J 2$ RWKHUDVDUHVXOWRIZKLFKGLSROHGLSROHLQWHUDFWLRQV DQG $J 2$ D FRPSOH[ ZLGH DV\PPHWULF between them intensify, which also could be leads signal with several resonant lines is recorded, to an additional line broadening. ZKLFKLVFRQVLဧHQWZLWKDZLGHVL]HGLဧULEXWLRQRI ,QWKH(35VSHFWUDRIVLOYHUFRQWDLQLQJVROVWKH nanoparticles. It is important to note that a change DQLVRWURSLF VLJQDO ZKLFK EHORQJV WR GLYDOHQW in the oleic acid layers of the nanoparticles seems to VLOYHU7KHDSSHDUDQFHRIVXFKKLJKO\R[LGL]HGVLOYHU D൵HFWWKHGLPHQVLRQRIWKHQDQRFU\ဧDOOLWHVWKDWDUH ဧDWHVRQWKHVXUIDFHRIQDQRSDUWLFOHVRFFXUVWKURXJK being formed. The presence of the FMR resonance WKHGLVSURSRUWLRQDWLRQRI$J , ZKLFKOHDGVWRWKH line in Ag&0.75%OA may indicates the presence 0 IRUPDWLRQRI$J ,, LRQVDQGPHWDO$J VLOYHU> RI $JFXELF FHOOV LQ QDQRSDUWLFOHV ZLWK LQWHUQDO @ (35 FKDUDFWHULဧLFV RI WKH FRPSOH[HV DFFRUG PDJQHWLF¿HOGVVLJQL¿FDQWO\ODUJHUWKDQWKH=HHPDQ ZLWKWKHDYDLODEOHOLWHUDWXUHGDWDIRUDQDORJRXVWZR ¿HOG WKH DYDLODEOH (35 LQ WKH ;EDQG UDQJH YDOHQFHVLOYHU>@ It is important to note that a change in the oleic DFLGOD\HUVRIWKHQDQRSDUWLFOHVVHHPVWRD൵HFWWKH Acknowledgments GLPHQVLRQ RI WKH QDQRFU\ဧDOOLWHV WKDW DUH EHLQJ 7KH DERYH SURMHFW KDV EHHQ IXO¿OOHG ZLWK formed. Thus, in the sols, when passing from ¿QDQFLDO VXSSRUW RI 6KRWD 5XဧDYHOL 1DWLRQDO WKHPRQRWRWKHELOD\HURIROHLFDFLGERWKVPDOO 6FLHQFH)RXQGDWLRQRI*HRUJLD *UDQW1R particles and larger multidomain agglomerates Any idea in this publication is possessed by the DUH IRXQG 6R WKH QDUURZ ZHDN VLJQDO LQ WKH author and may not represent the opinion of Shota region of the JIDFWRUDOVRUHIHUVWRWKHVSLQ 5XဧDYHOL1DWLRQDO6FLHQFH)RXQGDWLRQRI*HRUJLD UHVRQDQFHRIFRQGXFWLRQHOHFWURQVIURP]HURYDOHQW The authors are grateful to the Baikal Analytical VLOYHU>@7KLVOLQHLVXVXDOO\FKDUDFWHULဧLF Center for the special measurements. Research RI VPDOO QDQRSDUWLFOHV XVXDOO\ DURXQG QP > completed by Khutsishvili Spartak in the framework @7KHSUHVHQFHRIWKH)05UHVRQDQFHOLQH LQ 248 S. Khutsishvili et al. Annals of Agrarian Science 17 (2019) 242 – 250 RIWKHVFLHQWL¿FSURMHFW9RIWKHSURJUDPRI >@09/HVQLFKD\D%*6XNKRY(*DVLORYD* fundamental research of SB RAS. $OHNVDQGURYD79DNXO¶VND\D6.KXWVLVKYLOL $6DSR]KQLNRY,.OLPHQNRY%7UR¿PRY References Chiroplasmonic magnetic gold nanocomposites SURGXFHG E\ RQHဧHS DTXHRXVPHWKRG XVLQJ >@ 0 'RQDG]H 0 *DEULFKLG]H 6 &DOYDFKH țFDUUDJHHQDQ &DUERK\GUDWH 3RO\PHUV T. Agladze, Novel method of preparation RI WKH K\EULG PHWDO , ± PHWDO ,, R[LGH >@$6PLUQRY(35ဧXGLHVRIQDQRPDWHULDOV,Q nanoparticles, Int. J. Transactions of the IMF (G 6 0LVUD 0XOWLIUHTXHQF\:LOOH\9&+ 9HUODJ >@ -+ )O\QQ 7KH ,VRFRQYHUVLRQDO PHWKRG IRU >@0 6FKORWW + 6FKDH൵HU % (OVFKQHU GHWHUPLQDWLRQHQHUJ\RIDFWLYDWLRQDWFRQဧDQW Gd3+(65 LQ WKH LQWHUPHGLDWH YDOHQW FHULXP KHDWLQJUDWH-7KHUP$QDO compounds Ce[La[Os2=HLWVFKULIWIU3K\VLN 102. % &RQGHQVHG 0DWWHU >@ Ɍ$2]DZD1HZPHWKRGRIDQDO\]LQJWKHUPR >@ - 6W|KU + 6LHJPDQQ 0DJQHWLVP )URP gravimetric data, Bull. Chem. Soc. Japan 38 )XQGDPHQWDOVWR1DQRVFDOH'\QDPLFV6SULQJHU 9HUODJ %HUOLQ +HLGHOEHUJ >@ 7$JODG]H0'RQDG]H37RLG]HHWDO6\QWKHVLV >@ 3 9HQHJDV 3 1HWWR ([FKDQJH QDUURZLQJ DQG6L]H7XQLQJRI0HWDO1DQRSDUWLFOHV=3K\V H൵HFWVLQWKH(35OLQHZLGWKRI*GGLOXWHGLQ &KHP &HFRPSRXQGV-$SSO3K\V >@ '+/HH)7,5VSHFWUDOFKDUDFWHUL]DWLRQRIWKLQ ¿OPFRDWLQJVRIROHLFDFLGRQJODVVHV-0DW >@36KLQ6:X0DJQHWLFDQLVRWURSLFHQHUJ\JDS 6FL DQGဧUDLQH൵HFWLQ$XQDQRSDUWLFOHV1DQRVFDOH >@ &'R\OH.LQHWLFDQDO\VLVRIWKHUPRJUDYLPHWULF 5HVHDUFK/HWWHUV GDWD-$SSO3RO\P6FL ± >@0 .DND]H\ 1 ,YDQRYD * 6RNROVN\ - 292. *RQ]DOH]5RGULJXH] (OHFWURQ SDUDPDJQHWLF >@ . OD\HU LQ ELOD\HU ROHLF DFLGFRDWHG )H3O4 > @)%ODWWHU.%OD]H\&RQGXFWLRQHOHFWURQVSLQ QDQRSDUWLFOHV $SSO 6XUI 6FL UHVRQDQFHRIVLOYHULQ]HROLWH$J<=3K\V' 3093–3097. $WRPV0ROHFXOHVDQG&OXဧHUV >@ 4 /DQ & /LX ) ELOD\HUROHLFDFLGFRDWHG)H3O4 and interface >@66DNR.LPXUD.6L]H(൵HFWLQ&(65RI QDQRSDUWLFOHV DQG WKHLU DSSOLFDWLRQ LQ S+ magnesium and calcium small particles, responsive Pickering emulsions, J. Coll. Sci. 6XUIDFH 6FL ± >@;/L$9DQQLFH(65ဧXGLHVRIZHOOGLVSHUVHG > @ /6KHQ3(/DLELQLVDQG7$+DWWRQ%LOD\HU $JFU\ဧDOOLWHVRQ6L22-&DWDO\VLV VXUIDFWDQWဧDELOL]HGPDJQHWLFÀXLGV V\QWKHVLV and interactions at interfaces, Langmuir 15 >@0 $OL $ 6KDPHV 6 *DQJRSDGK\D\ % 6DKD ' 0H\HUဧHLQ 6LOYHU ,, FRPSOH[HV >@ 6 1HOOXWOD 6 1RUL 65 6LQJDPDQHQL -7 RI WHWUD]DPDFURF\FOHV ဧXGLHV RQ HSU DQG 3UDWHU-1DUD\DQ$,6PLUQRY0XOWLIUHTXHQF\ electron transfer kinetics with thiosulfate ion, IHUURPDJQHWLF UHVRQDQFH LQYHဧLJDWLRQ RI 7UDQVLWLRQ0HWDO&KHPLဧU\ 'RUGUHFKW1HWK nickel nanocubes encapsulated in diamagnetic PDJQHVLXPR[LGHPDWUL[-$SSO3K\V [23] M. Kester, A. Allred, Ligand-induced disproportionation of silver (I), J. American >@9 $QJHORY + 9HOLFKNRYD ( ,YDQRY 5 Chemical Society 94 (1972) 7189-7189. Kotsilkova, M.H. Delville, M. Cangiotti, A. [24] S. Khutsishvili, T. Vakul’skaya, N. Kuznetsova, Fattori, M.F. Ottaviani, EPR and rheological T. Ermakova, A. Pozdnyakov, G. Prozorova, ဧXG\RIK\EULGLQWHUIDFHVLQJROGFOD\HSR[\ Formation of stable paramagnetic nano- QDQRFRPSRVLWHV /DQJPXLU compositescontaining zero-valence silver and copper in a polymeric matrix, J. Phys. Chem. C 249 S. Khutsishvili et al. Annals of Agrarian Science 17 (2019) 242 – 250 118 (33) (2014) 19338–19344. [25] J. McMilan, B. Smaler, Paramagnetic resonance of some silver(II) compounds. J. Chem. Phys. 35 (1961) 1698-1701. [26] H. Moon, J. Kim, M. Suh, Redox-active porousorganic framework Chemie producing silver nanoparticles from AgI ions at room temperature, Angew.Chem. Int. Ed. 44 (2005) 1261-1265. [27] G. Deligiannakis, Y. Trapalis, C. Boukos, N. Kordas, CW and pulsed EPR study of silver nanoparticles in SiO2 matrix, J. Sol-Gel Science 7HFKQRORJ\ í [28] S. Khutsishvili, T. Vakul’skaya, G. Aleksandrova, B. Sukhov, Stabilized silver nanoparticles and clusters Agn of humic-based bioactive nanocomposites, J. Cluster Sci. 28 (2017) 3067- 3074. [29] V. Timoshenko, T. Shabatina, Yu. 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Annals of Agrarian Science 17 (2019) 251 – 257 Annals of Agrarian Science :ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ Prevalence of Bovine Tuberculosis and Its Risk Factors in Georgia Levan Tsitskishviliab*, Tengiz Kurashvilic, Levan Makaradzec, Iuri Baratashvilic, Guram Samadashviliab, Gabriel Glunchadzeab, Laura Bartaiaab, Zaza Samadashviliab a,YDQH%HULWDVKYLOL&HQWHURI([SHULPHQWDO%LRPHGLFLQH/HYDQ*RWXD6WU7ELOLVL*HRUJLD b,QWHUQDWLRQDO$VVRFLDWLRQ³9HWHULQDULDQV6DQV)URQWLHUV±&DXFDVXV´,YDQH-DYDNKLVKYLOL6WU7ELOLVL*HRUJLD cAgricultural University of Georgia, 240, David Agmashenebeli Ave., Tbilisi, 0159, Georgia Received: 14 September 2018; accepted: 12 November 2018 A B S T R A C T 7KHPDLQJRDORIWKLVဧXG\ZDVWZRIROG WRDVVHVVUHJLRQDOGLဧULEXWLRQRIERYLQHWXEHUFXORVLV E7% LQGRPHဧLFFDWWOHLQ*HRUJLD DQG WRGHVFULEHWKHGLVHDVHULVNIDFWRUVLQWKHFRXQWU\6WXG\VDPSOHDQGPHWKRGV 5DQGRPO\VHOHFWHGFDWWOHFDUFDVVHVZHUHH[DPLQHG LQDOORSHUDWLRQDOVODXJKWHUKRXVHV7KHLQIRUPDWLRQRQFDWWOHDJHVH[EUHHGDQGRULJLQZHUHREWDLQHGIURPWKHQDWLRQDOUHJLဧU\ 3RဧPRUWHPVDQLWDU\LQVSHFWLRQRIFDUFDVVHVZDVGRQHIRUDOOUDQGRPO\VHOHFWHGFDVHV,QFDVHRIPDFURVFRSLFFKDQJHVVDPSOHV IURPLQWHUQDORUJDQVDQGO\PSKDWLFQRGHVZHUHFROOHFWHGIRUIXUWKHUKLဧRSDWKRORJLFDODQGPLFURELRORJLFDOH[DPLQDWLRQ*HRJUDSKLFDO FRRUGLQDWHV IRU DOO SDUWLFLSDWLQJ VODXJKWHUKRXVHV DQG IDUPV ZHUH PHDVXUHG DQG LQWHJUDWHG LQWR *,6 V\ဧHP 'HVFULSWLYH ဧDWLဧLFDO DQDO\VLVZDVSHUIRUPHGWRGHVFULEHE7%UHJLRQDOGLဧULEXWLRQLQ*HRUJLDDQGဧUDWL¿HGULVNDQDO\VLVZDVGRQHWRLGHQWLI\KLJKULVNဧUDWD IRUE7%LQWKHFRXQWU\,QWRWDOFDUFDVVHVZHUHH[DPLQHGLQVODXJKWHUKRXVHVQDWLRQZLGH2XWRIWKHVHFDVHVZHUHIXUWKHU LQYHဧLJDWHGE\KLဧRSDWKRORJLFDODQGPLFURELRORJLFDOPHWKRGV8VLQJWKLVK\EULGDSSURDFK KLဧRSDWKRORJLFDODQGPLFURELRORJLFDO WHဧLQJ DQHဧLPDWHGERYLQH7%UDWHLV LQVODXJKWHUHGFDWWOHLQ*HRUJLD2XWRIWHQUHJLRQVRQO\WKUHHKDGE7% FDVHV7KHHဧLPDWHGUDWHVZHUH DQG IRU.YHPR.DUWOL6KLGD.DUWOL DQG6DPဧNKH-DYDNKHWLUHJLRQVUHVSHFWLYHO\7KHဧXG\UHYHDOHGWKDWWKHGLVHDVHDQWHFHGHQWVLQWKHUHJLRQFDWWOHIHPDOHJHQGHUDQG ROGHUDJH !\HDUVROG DUHE7%ULVNIDFWRUVLQ*HRUJLD6WUDWL¿HGDQDO\VLVVKRZVWKDWWKHဧUDWXPZLWKWKHKLJKHဧFRPSRVLWHULVN ! \HDUVROGIHPDOHFDWWOHVODXJKWHUHGLQWKHUHJLRQZLWKE7%DQWHFHGHQWV KDVHဧLPDWHGE7%SUHYDOHQFH Keywords: &DWWOH=RRQRVLV%RYLQH7XEHUFXORVLV5LVNIDFWRUV3DWKRORJ\$VVHVVPHQW&URVVVHFWLRQDOဧXG\ *Corresponding author: /HYDQ7VLWVNLVKYLOL (PDLODGGUHVV WVLWVNLVKYLOLO#JPDLOFRP Introduction ,W LV HဧLPDWHG WKDW DERXW RI DOO7% FDVHV DQGRIDOOQRQUHVSLUDWRU\7%FDVHVLQKXPDQV 1DWXUDO PLON SURGXFWLRQ KDV EHHQ WKH PRဧ have bTB origin in developing countries. The XU*HRUJLD KDV RQH RI WKH KLJKHဧ UDWHV RI KXPDQ routes of bovine TB transmission from cattle to WXEHUFXORVLV 7% SHU :+2 LQ KXPDQVLQFOXGHGLUHFWH[SRVXUHWRLQIHFWHGFDWWOHRU (DဧHUQ (XURSH 7KLV UDWH LV QHDUO\ WKUHH WLPHV consumption of contaminated animal products. higher than the regional average. Although TB is )LUဧFDVHVRIE7%KDYHEHHQUHFRUGHGR൶FLDOO\ RQHRIWKHPDMRUKHDOWKSULRULWLHVLQ*HRUJLDDUDWH LQ WZR UHJLRQV RI *HRUJLD 6DPဧNKH-DYDNKHWL RI QHZO\ LGHQWL¿HG FDVHV D \HDU SHU DQG .YHPR .DUWOL DURXQG WKH PLGWZHQWLHWK remains unacceptably high. For comparison, the century. The following nationwide epidemiological UDWHRIDOO7%FDVHVLQLQGXဧULDOL]HGFRXQWULHVLV DVVHVVPHQW ZDV FRQGXFWHG LQ DQG per 100,000. revealed bTB cases in 73 farms of the country. As 251 L. Tsitskishvili et al. Annals of Agrarian Science 17 (2019) 251 – 257 a result of bTB eradication measures by 1972, the EHSUHVHQW6WDJH,,,JUDQXORPDVH[KLELWFRPSOHWH QXPEHU ZDV UHGXFHG WR IDUPV LQ ¿YH GLဧULFWV ¿EURXV HQFDSVXODWLRQ DQG VLJQL¿FDQW QHFURVLV DQG RIWKHFRXQWU\7KHQWKHQXPEHURID൵HFWHGDUHDV PLQHUDOL]DWLRQFDQEHSUHVHQW 6WDJH,9JUDQXORPDV increased again, and bTB cases were recorded in 19 DUH FKDUDFWHUL]HG E\ PXOWLSOH FRDOHVFLQJ FDVHR GLဧULFWV RI WKH FRXQWU\ LQ 6HH )LJXUH QHFURWLF JUDQXORPDV ZLWK PXOWLFHQWULF QHFURVLV 7KHODဧNQRZQE7%ဧXG\LQ*HRUJLDVKRZHG DQG PLQHUDOL]DWLRQ 7KH KLဧRSDWKRORJLFDO VFRUH PXOWLGUXJUHVLဧDQFHRIERYLQHP\FREDFWHULDဧUDLQV ZDV EDVHG RQ WKH PRဧ VHYHUH OHVLRQ REVHUYHG LQ LVRODWHG IURP FDUFDVVHV RI LQIHFWHG DQLPDOV >@ each pulmonary lymph node section with scores ranging from 0 to 4, corresponding to Stages 0 to Materials and Methods ,9 UHVSHFWLYHO\ $ WRWDO KLဧRSDWKRORJLFDO VFRUH was compiled by pooling scores for each of the Study Design: 7KLV ZDV H[SORUDWRU\ FURVV four pulmonary lymph nodes. Scoring of gross VHFWLRQDO ဧXG\ LQ ZKLFK UDQGRPO\ VHOHFWHG FDWWOH DQGKLဧRSDWKRORJLFDOOHVLRQVZDVDVVLJQHGZLWKRXW FDUFDVVHV ZHUH H[DPLQHG LQ DOO FRQFXUUHQWO\ NQRZOHGJH RI WKH VODXJKWHUKRXVH VRXUFH >@ operational slaughterhouses. The information on 7LVVXHDQGO\PSKQRGHVDPSOHV PRဧO\KHDGDQG FDWWOH DJH VH[ EUHHG DQG RULJLQ ZHUH REWDLQHG FHUYLFDO O\PSK QRGHV IURP HYHU\ E7% VXVSHFWHG IURP WKH QDWLRQDO UHJLဧU\ 3RဧPRUWHP VDQLWDU\ DQLPDOZDVVXEMHFWHGWREDFWHULDOLVRODWLRQ6DPSOHV inspection of carcasses was performed for all from all tissues were pooled, homogenized with randomly selected cases. In case of macroscopic ဧHULOHGLဧLOOHGZDWHUDQGGHFRQWDPLQDWHGZLWK changes, samples of select internal organs and KH[DGHF\OS\ULGLQLXP FKORULGH IRU PLQXWHV >@ lymphatic nodes were collected for further FHQWULIXJHGDW;JIRUPLQXWHVDQGFXOWXUHG KLဧRSDWKRORJLFDODQGPLFURELRORJLFDOH[DPLQDWLRQ RQWR &ROHWVRV DQG ZY S\UXYDWHHQULFKHG Geographical coordinates of all participating /RZHQဧHLQ-HQVHQ PHGLD %LR5DG &DUOVEDG &$ slaughterhouses and farms were measured and 86$ DW0&>@,VRODWHVZDVDVVHVVHGE\GHWHUPLQLQJ LQWHJUDWHG LQWR *,6 V\ဧHP traditional cultural and biochemical properties for Bovine TB Diagnosis: Pathology Assessment Bovine Mycobacteria. ZDVGRQHLQDFFRUGDQFHRI3DUODQHHWDO , The primary outcome measure – positive bTB lung lesion score was calculated by counting the FDVHZDVGH¿QHGDVERYLQH7%FKDUDFWHULဧLFFKDQJHV WRWDOQXPEHURIOHVLRQVDVIROORZV QROHVLRQV E\ ERWK KLဧRSDWKRORJLFDO DQG PLFURELRORJLFDO ± OHVLRQV± OHVLRQV± OHVLRQV assessments. ± OHVLRQV ! OHVLRQV ,, $ WRWDO 6WDWLဧLFDO $QDO\VLV 3URSRUWLRQV RI WKH lymph node lesion score per animal was calculated randomly selected carcasses and of cases that by pooling scores for four pulmonary lymph nodes ZHUH VHOHFWHG IRU IXUWKHU KLဧRSDWKRORJLFDO DQG OHIWDQGULJKWEURQFKLDODQGDQWHULRUDQGSRဧHULRU EDFWHULRORJLFDO H[DPLQDWLRQ ZHUH FRPSXWHG IRU PHGLDဧLQDO 6FRUHV IRU LQGLYLGXDO O\PSK QRGHV each region. Bovine TB mean rates and its 90% ZDVHဧLPDWHGDVIROORZV QROHVLRQV± FRQ¿GHQFHLQWHUYDOVZHUHHဧLPDWHGIRUHDFKUHJLRQ VPDOO OHVLRQV ± PP GLDPHWHU ! VPDOO E\XVLQJ&ORSSHU3HDUVRQ H[DFW DQG:LOVRQWHဧV OHVLRQV ±PPGLDPHWHU RUPHGLXPVL]HOHVLRQ V Bivariate relationship between bovine TB and ± PP GLDPHWHU ODUJH OHVLRQ V ! PP VHOHFWULVNIDFWRUV DJHJHQGHUEUHHGDQGRULJLQ GLDPHWHU >@ as well as variation of the disease rates across )RU KLဧRORJLFDO H[DPLQDWLRQ VHFWLRQV ZHUH UHJLRQVIRUHDFKULVNIDFWRUZHUHH[DPLQHGE\FKL KHPDWR[\OLQ DQG HRVLQ ဧDLQHG 6FRULQJ RI VTXLUH WHဧV$OO ULVN IDFWRUV WKDW ZHUH SRWHQWLDOO\ KLဧRSDWKRORJLFDO OHVLRQV LQ WKH O\PSK QRGHV ZDV DVVRFLDWHG S ZLWK SULPDU\ RXWFRPH ZHUH based on the scale described by Wangoo, et. al., XVHGLQဧUDWL¿HGDQDO\VLV7KHODWHUZDVSHUIRUPHG 6WDJHQRJUDQXORPDVDUHREVHUYHG 6WDJH WR GHWHUPLQH KLJK ULVN ဧUDWD RI E7% LQ *HRUJLD , JUDQXORPDV DUH FRPSRVHG RI DFFXPXODWLRQV 6WDWLဧLFDO DQDO\VHV ZHUH GRQH LQ 6$6 DQG of epithelioid macrophages with low numbers DOOUHSRUWHGUHVXOWVDUHWZRVLGHGDWVLJQL¿FDQFH of lymphocytes,neutrophils and Langerhans level. multinucleated giant cells and an absence of QHFURVLV 6WDJH,,JUDQXORPDVDUHVLPLODUWR6WDJH , JUDQXORPDV EXW DOVR KDYH FHQWUDO LQ¿OWUDWHV RI neutrophils and lymphocytes and necrosis could 252 L. Tsitskishvili et al. Annals of Agrarian Science 17 (2019) 251 – 257 Results in DOO WHQ UHJLRQV RI WKH FRXQWU\ GXULQJ WKH ဧXG\ period. Animal ID number, age, gender, breed, and During WKH ဧXG\ SHULRG FDWWOH ZHUH geographic origin information were obtained from slaughtered in ten regions RI *HRUJLD PRUH WKH1DWLRQDO5HJLဧU\7KHFDUFDVVHVRIDOO randomly than 70% of these in four regions of the country: selected animals were then inspected by a trained Imereti, Kakheti, Kvemo Kartli, and Shida Kartli veterinarian and in the case of macromorphological Although the rates were proportional to overall FKDQJHV HYHU\th or 5th FDVH LQWHUQDORUJDQDQG GRPHဧLF FDWWOH SRSXODWLRQ in the regions, the lymph node samples were IXUWKHU H[DPLQHG E\ numbers of the slaughtered animals varied from KLဧRSDWKRORJLF DQG PLFURELRORJLF PHWKRGV 7KH 5DFKD WR ,PHUHWL DFURVVWKHUHJLRQV number ofWKHFDUFDVVHVLQYHဧLJDWHGYDULHGIURP VHH 7DEOH DQLPDO FDUFDVVHV RI 5DFKD WR ,PHUHWL DQGH[FHHGHGFDVHVIRU all slaughtered cattle ZHUH UDQGRPO\ VHOHFWHG VHYHQ UHJLRQV 7DEOH from all slaughterhouses that were operational Table 1. )UHTXHQFLHV DQG SURSRUWLRQV RI LQYHVWLJDWHG DQLPDOV E\ UHJLRQ GXULQJ VWXG\ SHULRG ) Region Total Proportion of Cases Number of Proportion of number of (Percent of total randomly inspected carcasses slaughtered number of animals selected (Percent of animals animals slaughtered in the carcasses slaughtered in the country) region) Achara 12574 3.9 141 1.1 Guria 7766 2.4 80 1.0 Imereti 70494 21.9 467 0.7 Kakheti 46643 14.5 381 0.8 KvemoKartli 52001 16.1 408 0.8 Mtskheta-Mtianeti 28489 8.8 102 0.4 Racha-Lechkhumi 1873 0.6 41 2.2 Samtskhe- Javakheti 6413 2.0 217 3.4 Samegrelo- ZemoSvaneti 29074 9.0 228 0.8 ShidaKartli 66747 20.7 221 0.3 Total 322074 100.0 2286 0.7 253 L. Tsitskishvili et al. Annals of Agrarian Science 17 (2019) 251 – 257 %\ DSSO\LQJ K\EULG KLဧRSDWKRORJLF DQG 6DPWVNKH-DYDNKHWL UHVSHFWLYHO\ 7DEOH PLFURELRORJLFDO GLDJQRဧLF DSSURDFK RXW RI WKH 7KHGLဧULEXWLRQRIE7%ULVNIDFWRUVE\UHJLRQLV H[DPLQHGFDVHVFDVHVZHUHLGHQWL¿HGWREH VKRZQLQ7DEOH$OWKRXJKPRဧRIWKHVODXJKWHUHG E7%SRVLWLYH7KHUHIRUHWKHHဧLPDWHGSUHYDOHQFH FDWWOH ZHUH IHPDOH DQLPDOV WKH UDWH YDULHG DQG LWV FRQ¿GHQFH LQWHUYDO IRU ERYLQH 7% VXEဧDQWLDOO\ DFURVV WKH UHJLRQV 7KH ORZHဧ UDWH prevalence in cattle slaughtered in Georgia is 0.44% ZDV UHFRUGHG LQ ,PHUHWL DQG KLJKHဧ UDWH 7KH UDWHV YDU\ DFURVV WKH UHJLRQV LQ6DPHJUHOR7KHJHQGHUGL൵HUHQFHDPRQJ no bovine TB case was detected in seven regions UHJLRQVZDVဧDWLဧLFDOO\VLJQL¿FDQW 3 2QH of the country and bTB prevalences are 0.98% H[SODQDWLRQRIWKHSUHYLRXVIDFWPLJKWEHWKHLPSRUW DQG of male cattle from some regions of Georgia to the IRU .YHPR .DUWOL 6KLGD .DUWOL DQG neighboring countries. Table 2. %RYLQH 7% SUHYDOHQFH in VODXJKWHUHG DQLPDOV E\ UHJLRQ Region Number of Positive 95% CI* researched cases (%) animals Achara 141 0.00 0.00 -2.58 Guria 80 0.00 0.00 -4.51 Imereti 467 0.00 0.00 -0.79 Kakheti 381 0.00 0.00 -0.96 KvemoKartli 408 0.98 0.27 -2.49 Mtskheta- Tianeti 102 0.00 0.00 -3.55 Racha- Lechkhumi 41 0.00 0.00 -8.60 Samtskhe- Javakheti 217 1.84 0.50 -4.65 Samegrelo- ZemoSvaneti 228 0.00 0.00 -1.60 ShidaKartli 221 1.36 0.28 -3.92 Total 2286 0.44 0.36-0.54** &ORSSHU3HDUVRQ ([DFW WHఅZDVXVHGWRFRPSXWH FRQ¿GHQFHLQWHUYDOV :LOVRQWHఅZLWKZHLJKWఅDWHPHQWZDVXVHGWRFRPSXWH FRQ¿GHQFHLQWHUYDOV ZHLJKWV ZHUHDVVLJQHGEDVHGRQUDWLRRIWKHQXPEHURILQYHఅLJDWHGFDVHVLQDUHJLRQWRWKHWRWDOQXPEHU RIVODXJKWHUHGDQLPDOVQDWLRQZLGHGXULQJWKHఅXG\SHULRG 254 L. Tsitskishvili et al. Annals of Agrarian Science 17 (2019) 251 – 257 Table 3. %RYLQH 7% SUHYDOHQFH in VODXJKWHUHG DQLPDOV E\ UHJLRQ Guria Racha Achara Imereti P-value Kakheti Mtianeti Javakheti Mtskheta- Samtskhe- Risk factor Samegrelo- ShidaKartli ZemoSvaneti Kvemo-Kartli For all regions 2286 141 80 467 228 41 102 221 381 408 217 Total (100) (6.2 ) (3.5 ) (20.4) (10.0) (1.8 ) (4.5 ) (9.7 ) (16.7) (17.8) (9.5 ) Sex <0.001 480 43 11 203 19 9 4 77 33 62 19 Male (21.0) (30.5) (13.8) (43.5) (8.3 ) (22.0) (3.9 ) (34.8) (8.7 ) (15.2) (8.8 ) 1806 98 69 264 209 32 98 144 348 346 198 Female (79.0) (69.5) (86.3) (56.5) (91.7) (78.0) (96.1) (65.2) (91.3) (84.8) (91.2) Age <0.001* <2 years 332 57 16 83 4 5 11 50 35 48 23 (14.5) (40.4) (20.0) (17.8) (1.8 ) (12.2) (10.8) (22.6) (9.2 ) (11.8) (10.6) 2-4 years 1145 68 17 287 98 18 55 146 68 242 146 (50.1) (48.2) (21.3) (61.5) (43.0) (43.9) (53.9) (66.1) (17.8) (59.3) (67.3) >4 years 419 13 4 97 36 18 36 25 51 91 48 (18.3) (9.2 ) (5.0 ) (20.8) (15.8) (43.9) (35.3) (11.3) (13.4) (22.3) (22.1) Unknown 390 3 43 0 90 0 0 0 227 27 0 (17.1) (2.1 ) (53.8) (0.0 ) (39.5) (0.0 ) (0.0 ) (0.0 ) (59.6) (6.6 ) (0.0 ) Breed 1378 85 54 394 82 41 91 188 131 162 150 <0.001* Local (60.3) (60.3) (67.5) (84.4) (36.0) (100 ) (89.2) (85.1) (34.4) (39.7) (69.1) 86 22 0 0 0 0 11 24 11 9 9 Other (3.8 ) (15.6) (0.0 ) (0.0 ) (0.0 ) (0.0 ) (10.8) (10.9) (2.9 ) (2.2 ) (4.1 ) 822 34 26 73 146 0 0 9 239 237 58 Unknown (36.0) (24.1) (32.5) (15.6) (64.0) (0.0 ) (0.0 ) (4.1 ) (62.7) (58.1) (26.7) 2QO\ the FDVHV ZLWKRXW 0LVV8QNQRZQ LQIRUPDWLRQ ZDV XVHG in WHఅLQJ అDWLఅLFDO VLJQL¿FDQFH In seventeen percent of randomly selected H[FOXVLRQRIFDVHVZLWKPLVVLQJEUHHGLQIRUPDWLRQ animals, information of the animal age was missing. PLJKWUHGXFHWKHDQDO\WLFVDPSOHVLJQL¿FDQWO\WKH ,QWKHJURXSZLWKQRPLVVLQJDJHLQIRUPDWLRQYDဧ risk factor was used only in univariate and bivariate PDMRULW\ ZHUHDGXOWDQLPDOV ! Table 4. %RYLQH 7% SUHYDOHQFH in VODXJKWHUHG DQLPDOV E\ UHJLRQ Number of researched P-value Risk Factor animals positive cases % Total 2286 11 (0.48 ) Sex 0.09 Male 480 0 (0.0 ) Female 1806 11 (0.61) Age 0.17** <2 years 332 0 (0.0) 2-4 years 1145 9 (0.79) >4 years 419 2 (0.48) Breed Local 1378 10 (0.73) 0.65* Other 86 1 (1.16 ) bTB (Region) 0.002 Yes 1059 11 (0.90) No 1227 0 (0.0) 2QO\ the FDVHV ZLWKRXW PLVVLQJ8QNQRZQ LQIRUPDWLRQ ZDV XVHG IRU WHఅLQJ అDWLఅLFDO VLJQL¿FDQFH PYDOXH GHULYHG IURP WHఅ that FRPSDUHV <2 DQG2 \HDUV ROG DQLPDOV 255 L. Tsitskishvili et al. Annals of Agrarian Science 17 (2019) 251 – 257 As the low number of the primary outcome UHJLRQVZLWKE7%KLဧRU\KDVDVLJQL¿FDQWO\KLJKHU GLGQRWDOORZWRGRDPXOWLYDULDWHH[DPLQDWLRQRI ULVN RI WKH GLVHDVH RXWEUHDN >@ LQGHSHQGHQWULVNIDFWRUVဧUDWL¿HGULVNDQDO\VLVZDV %DVHGRQ6WUDWL¿HGDQDO\VLVWKLVဧXG\VKRZHG SHUIRUPHG WR LGHQWLI\ KLJK ULVN ဧUDWD IRU E7% LQ WKDWE7%ULVNLQWKHKLJKHဧULVNဧUDWXP !\HDUV WKHFRXQWU\$QLPDOJHQGHUDJHDQGE7%KLဧRU\RI old female cattle slaughtered in the region with bTB WKHUHJLRQZHUHXVHGLQWKHဧUDWL¿HGDQDO\VLV7KH DQWHFHGHQWV LVDERXWWLPHVKLJKHUWKDQQDWLRQZLGH reason behind not using animal breed information rate of the disease. LV H[SODLQHG LQ D SUHYLRXV SDUDJUDSK 7KH ဧXG\ VKRZHGWKDWWKHဧUDWXPZLWKWKHKLJKHဧFRPSRVLWH Future Studies ULVN !\HDUVROGIHPDOHFDWWOHVODXJKWHUHGLQWKH UHJLRQ ZLWK E7% DQWHFHGHQWV KDV HဧLPDWHG E7% 2QH RI WKH PDLQ OLPLWDWLRQV RI RXU ဧXG\ ZDV SUHYDOHQFH WKDWZHZHUHQRWDEOHWRFRQ¿UPEDFWHULDOLVRODWHV by using molecular methods. Additionally, limited Discussion number of positive bTB cases did not allowed WR SHUIRUP PXOWLYDULDWH DQDO\VLV WR H[DPLQH 7KLVဧXG\H[DPLQHGE7%UHJLRQDOGLဧULEXWLRQ independent relationship between the disease and DORQJZLWKLWVDQLPDO DJHJHQGHUEUHHG DQGUHJLRQ its risk factors. This emphasizes the need of using E7%KLဧRU\ OHYHOULVNIDFWRUVLQ*HRUJLD PRUH VHQVLWLYH DQG DFFXUDWH HJ 3&5 PROHFXODU ,Q WKLV ဧXG\ ZH IRXQG WKDW DOO E7% FDVHV PHWKRGV LQ IXWXUH ဧXGLHV were diagnosed in adult animals. This agrees to WKHH[LဧLQJHYLGHQFHWKDWROGHUDQLPDODJHLVRQH Recommendation of the important risk factors of bTB. Studies that were conducted in both developing and developed Bovine TB remains a public health problem in FRXQWULHVVKRZHGWKDWWKHGLVHDVHUDWHLVVLJQL¿FDQWO\ Georgia and requires measures to minimize the risk higher in adult animals compared to young ones of the disease transmission to humans. >@7KHUH DUH WZR SRVVLEOH H[SODQDWLRQV RI WKLV DVVRFLDWLRQ ROGHUDQLPDOVKDYHKLJKSUREDELOLW\ Funding: This work was supported by Shota to get in contact with the infectious agent source; 5XဧDYHOL1DWLRQDO6FLHQFH)RXQGDWLRQRI*HRUJLD DQG ERYLQH7%KDVORQJODWHQWSHULRG>@ 6516)* >JUDQW QXPEHU )5217822@ There is contradictory information of animal JHQGHU UROH LQ ERYLQH 7% LQIHFWLRQ :KLOH D ဧXG\ References IRXQGWKDWPDOHJHQGHULVDVLJQL¿FDQWULVNIDFWRURI >@ ,)UDQJLVKYLOL'RFWRUDO7KHVLV³0\FREDFWHULDO E7% > @ DQRWKHU ဧXG\ VKRZHG WKDW IHPDOH JHQGHU WHဧLQJ RI LQWHဧLQDO O\PSK QRGHV IRU E7% ZDVDVVRFLDWHGZLWKWKHGLVHDVHGHYHORSPHQW>@2XU HUDGLFDWLRQLQ*HRUJLD³7ELOLVL6WDWH9HWHULQDU\ ဧXG\VKRZHGWKDWDOOGLVHDVHGFDVHVZHUHGLDJQRVHG 8QLYHUVLW\ LQ *HRUJLDQ LQIHPDOHFDWWOH7KLVPLJKWEHH[SODLQHGE\WKHIDFW >@ &RUQHU /$ 7UDMဧPDQ $& $Q HYDOXDWLRQ that, in Georgia, female cattle are kept for longer time RI KH[DGHF\OS\ULGLQLXP chloride as a because of milk production and reproductive purposes. decontaminant in the primary isolation of 7KHUHIRUHWKHUHODWLRQVKLSIRXQGLQRXUဧXG\PLJKWEH Mycobacterium ERYLV IURP ERYLQH OHVLRQV9HW confounded by animal age. 0LFURELRO ±. 7KHUHLVHYLGHQFHWKDWQRQORFDOEUHHGFDWWOHKDYH >@ 6DQWRV1*HUDOGHV0$IRQVR$$OPHLGD9 KLJKE7%ULVNFRPSDUHGWRORFDORQHV>@'XHWR &RUUHLD1HYHV M, Diagnosis of tuberculosis a high rate of missing breed information and a very LQWKHZLOGERDU 6XVVFURID $ comparison of ORZ QXPEHU RI DQLPDOV FDWHJRUL]HG DV QRQORFDO PHWKRGVDSSOLFDEOHWRKXQWHUKDUYHဧHGDQLPDOV EUHHGZHZHUHQRWDEOHWRH[DPLQHWKHUHODWLRQVKLS PLoS One MRXUQDOSRQH0012663, between cattle breed and bTB infection. However, 2010. WKLVVKRXOGQRWVLJQL¿FDQWO\D൵HFWWKHဧXG\¿QGLQJV >@ 3DUODQH 1$ 6KX ' 6XEKDUDW 6 :HGORFN DVWKHYDဧPDMRULW\RIWKHFDWWOHLQ*HRUJLDEHORQJ DN, Rehm BH, de Lisle GW, Buddle to the local breed. BM,Revaccination of cattle with bacilli 7KLV ဧXG\ IRXQG WKDW E7% DQWHFHGHQWV LQ WKH &DOPHWWH*XpULQWZR\HDUVDIWHU¿UဧYDFFLQDWLRQ UHJLRQ LV WKH PRဧ LPSRUWDQW ULVN IDFWRU RI WKH ZKHQLPPXQLW\KDVZDQHGERRဧHGSURWHFWLRQ LQIHFWLRQ 3UHYLRXV ဧXGLHV DOVR VKRZHG WKDW WKH DJDLQဧFKDOOHQJHZLWK0\FREDFWHULXPERYLV. 256 L. Tsitskishvili et al. Annals of Agrarian Science 17 (2019) 251 – 257 3/R6 2QH H GRL MRXUQDOSRQH >@ :DQJRR$ -RKQVRQ L, Gough J, Ackbar R, Inglut S, et al., Advanced granulomatous lesions in 0\FREDFWHULXP ERYLV LQIHFWHG cattle are associated ZLWKLQFUHDVHGH[SUHVVLRQ RI W\SH , SURFROODJHQ JDPPD GHOWD :& T cells and CD68+cells. J Comp Pathol 133 223–234. >@ Cleaveland C et al. 0\FREDFWHULXP ERYLV in rural Tanzania: Risk factors for infection in KXPDQ >@ *UL൶Q -0 HW DO $ FDVHFRQWURO ဧXG\ RQ the association of selected risk factors with the occurrence of bovine tuberculosis in the 5HSXEOLF RI ,UHODQG 3UHYHQWLYH 9HWHULQDU\ Medicine >@ 3ROORFN -0 HW DO 0\FREDFWHULXP ERYLV LQIHFWLRQDQGWXEHUFXORVLVLQFDWWOH9HWHULQDU\ MRXUQDO > @ .D]ZDOD 55 HW DO 5LVN IDFWRUV DVVRFLDWHG with the occurrence of bovine tuberculosis in cattle in the Southern Highlands of Tanzania. 9HWHULQDU\ UHVHDUFK FRPPXQLFDWLRQV >@,QDQJROHW)2HWDO$FURVVVHFWLRQDOဧXG\RI bovine tuberculosis in the transhumant and DJURSDဧRUDO FDWWOH KHUGV in the border areas RI .DWDNZL DQG 0RURWR GLဧULFWV 8JDQGD 7URSLFDODQLPDOKHDOWKDQGSURGXFWLRQ >@OmeU0.HWDOFURVVVHFWLRQDOဧXG\RIERYLQH tuberculosis in dairy farms in Asmara, Eritrea. 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Gogidze Annals of Agrarian Science 17 (2019) 258 – 265 Annals of Agrarian Science :ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ 3HFXOLDULWLHVRIVRLOVRIKLJKPRXQWDLQ RQ.KHYLH[DPSOH±RQWKH Central Great Caucasus) Ketevan Gogidze $JULFXOWXUDO8QLYHUVLW\RI*HRUJLD0LNKHLO6DEDVKYLOL,QဧLWXWHRI6RLO6FLHQFH$JULFKHPLဧU\DQG0HOLRUDWLRQ David Aghmashenebeli Alley, Tbilisi, 0159, Georgia Received: 21 January 2019; accepted 12 March 2019 A B S T R A C T 7KH DUWLFOH LQFOXGHV WKH UHVHDUFK LQ .KHYL UHJLRQ RI &HQWUDO &DXFDVXV 6WXG\ DUHD ZDV GLYLGHG E\ H[SRVLWLRQV QRUWK DQG VRXWK LQFOLQDWLRQ 00!0 DQGDOWLWXGH P±VXEDOSLQHIRUHဧVP±VXEDOSLQHPHDGRZVP± DOSLQHPHDGRZV 7KHQXPEHURIVRLOSUR¿OHVDVDUHVXOWRIGLYLVLRQZDVFRQVLဧHGRI%\FRPSDULQJWKHSUR¿OHVRIKLJKPRXQWDLQ VRLOVWRHDFKRWKHUWKH\GRQRWဧDQGRXWE\JHQHWLFLQGLYLGXDOLW\ Keywords:6RLO3DဧXUH0HDGRZIRUHဧPRXQWDLQVRLOV0HDGRZPRXQWDLQVRLOV6XEDOSLQH$OSLQH &RUUHVSRQGLQJDXWKRU .HWHYDQ*RJLG]H (PDLODGGUHVV THWXVL#JPDLOFRP Introduction >@ DQG RWKHUV 7KH KLJK PRXQWDLQ VRLOV ZHUH ဧXGLHGTXLWHZHOOEXWLQWKHLULQYHဧLJDWLRQVWKHUH 7KH ဧXG\LQJ RI WKH VRLOV RI +LJK 0RXQWDLQ are given less about comparative characterization of RI WKH &DXFDVXV ZDV ဧDUWHG ZLWK JUHDW LQWHQVLW\ soils in subalpine and alpine belts. 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Sum % (cm) ɪɇ mg/equivalent in 100g. soil Profile % H2O % ʋ Ca++ Mg++ H+ ˇʨʳʰ Ca Mg H Subalpine forests zone 1700-2000 m a. s. l. $ƍ0-10 6,5 9,22 1,02 10,02 3,67 1 14,69 68 25 7 15 $ƍƍ10-40 6,5 5,32 1,02 10,68 6,68 0,6 15,96 67 29 4 Tsdo AB 40-55 7,0 3,62 1,03 9,46 4,05 0 13,48 70 30 0 S B 55-95 7,1 2,79 1,02 11,35 5,35 0 16,7 68 32 0 BC 95-150 7,3 2,02 1,02 10,11 4,04 0 14,15 71 29 0 A 0 - 15 5,5 10,63 1,06 14,15 8,09 0 22,24 64 36 0 5I AB 15 –30 5,5 3,37 1,02 12,13 7,41 1,8 21,34 57 35 8 Gergeti B1 30 – 50 5,8 0,75 1,04 11,69 5,01 1,8 18,5 64 27 9 S B2 50-70 5,9 0,75 1,02 13,15 6,74 1,8 21,69 49 43 8 BC 70-90 6,1 0,55 1,02 12,45 6,36 1,8 20,61 50 41 9 A 0-10 5,0 4,96 1,02 14,32 4,1 1 19,42 74 21 5 6 AB 10-25 5,2 1,86 1,06 7,69 4,35 5 14,04 55 31 14 Gergeti B1 25-40 5,7 1 1,04 4,01 2,68 1,2 7,89 51 34 15 S B2 40-60 6,5 0,75 1,02 4,01 3,35 1,4 8,76 46 38 16 BC 60-80 6,5 0,75 1,02 4,34 1,01 1,8 7,15 61 14 25 A 0—10 7,1 7,88 1,02 8,18 2,15 1 11,33 73 19 8 5 AB 10—22 5,8 5,42 1,04 4,43 2,73 2,6 9,76 45 28 27 Stepantsminda N BC1 22—40 5,0 5,42 1,04 6,35 2,01 1 9,36 68 21 11 BC2 40—60 5,8 3,93 1,06 10,03 5,02 2 17,05 59 29 12 261 K. Gogidze Annals of Agrarian Science 17 (2019) 258 – 265 42 A 0--12 6,4 10,91 1,04 17,05 7,85 0,4 25,3 67 31 2 Akhaltsikhe B 12--30 5,0 9,43 1,02 6,02 4,01 1,4 11,43 53 35 12 N BC 30--65 5,2 3,37 1,02 6,69 3,68 1,8 12,17 55 30 15 $ƍ-10 6,2 7,9 1,02 10,01 4,35 0,4 14,78 66 33 1 4 $ƍƍ-20 5,7 8,9 1,04 9,21 5,11 0,8 15,12 61 34 5 Stepantsminda N BC 20-40 5,5 1,73 1,02 10,57 6,82 1,2 18,59 57 37 6 CD >40 ------Subalpine meadows zone 2000-2200 m a. s. l. 4I A 0-14 5,6 8,43 1,06 4,01 5,35 0,8 10,16 39 53 8 Gergeti AB 14-35 6,0 2,85 1,02 5,25 7,68 0,7 13,63 53 29 18 S BC 35-50 6,3 0,85 1,02 8,23 4,05 0,8 13,08 49 48 3 3I A 0-13 5,8 9,17 1,02 9,36 5,32 0,4 15,08 58 35 7 Gergeti AB 13-30 5,4 5,94 1,04 11,86 4,45 2 18,31 47 35 18 S BC 30-55 6,0 1,77 1,04 9,35 5,04 2 16,39 65 25 10 A 0-20 5,9 8,39 1,02 11,56 8,32 0,4 20,28 48 34 18 2I AB 20-35 5,8 3,78 1,02 15,26 8,27 2,3 25,83 65 20 15 Gergeti B 35-50 6,2 0,75 1,04 12,35 9,03 0,6 21,98 47 45 8 S BC 50-80 5,7 0,55 1,02 10,68 6,68 0,6 15,96 50 38 12 29 A 0--10 5,8 9,91 1,02 8,02 3,68 0,4 12,1 66 33 1 Pansheti N BC 10--30 6,3 2,47 1,02 9,36 3,35 0 12,71 74 26 0 2 $ƍ-20 4,7 8,6 1,02 27,27 6,38 1,8 35,45 65 20 15 Stepantsminda $ƍƍ-35 5,1 4,5 1,02 6,48 3,75 8,8 19,03 53 42 5 N BC 35-50 5,3 4,6 1,04 3,41 1,7 5,6 10,71 45 52 3 $ƍ-20 5,5 9,4 1,02 14,32 4,1 1 19,42 74 21 5 3 $ƍƍ-40 5,7 6,5 1,04 4,01 2,68 1,2 7,89 51 34 15 Stepantsminda N AB 40-60 5,9 3,13 1,06 4,34 1,01 1,8 7,15 61 14 25 BC 60-80 5,9 1,06 1,02 4,01 5,35 0,8 10,16 39 53 8 Alpine meadows zone 2200-2500 m a. s. l. 37 $ƍ--25 4,5 11,18 1,04 5,45 4,78 2,8 13,03 42 37 21 Sno $ƍƍ--65 5,4 8,27 1,02 6,69 4,65 5,35 16,69 44 36 20 S BC 65--100 5,6 0,94 1,02 4,01 2,68 0,6 7,29 55 37 8 A 0--12 5,9 8,85 1,02 12,69 5,34 1,2 19,23 66 28 6 9 AB 12--30 5,5 5,11 1,03 10,11 5,39 1,6 17,1 59 31 10 Pkhelshe S B 30--58 6,0 1,21 1,03 8,76 4,38 1,4 14,54 60 30 10 BC 58--100 6,1 0,95 1,03 10,11 4,71 1,4 16,22 62 29 9 $ƍ-5 5,6 8,90 1,02 17,05 7,85 0,4 25,3 67 31 2 I 1 $ƍƍ-20 5,5 8,03 1,04 8,86 4,78 0,2 13,84 45 21 34 Gergeti S AB 20-30 5,7 6,46 1,04 9,03 2,34 0,6 11,97 75 20 5 BC 30-55 6,4 1,77 1,04 6,02 4,01 1,4 11,43 53 35 12 1 A 0-18 5,1 8,12 1,02 8,02 3,68 0,4 12,1 66 33 1 Stepantsminda N BC 18-40 5,4 3,12 1,06 9,36 3,35 0 12,71 74 26 0 $ƍ--10 5,5 10,77 1,08 27,27 6,38 1,8 35,45 80 18 2 33 $ƍƍ--25 4,6 8,97 1,04 6,48 3,75 8,8 19,03 34 20 46 Achkhoti N AB 25--40 4,8 5,32 1,04 3,41 1,7 5,6 10,71 32 16 52 BC 40--60 5,2 3,11 1,04 6,14 2,44 4,4 12,98 47 19 34 32 A 0--15 5,4 11,23 1,04 15,69 5,8 2,2 23,69 66 24 10 Achkhoti N BC 15--30 4,7 3,37 1,02 14,05 6,02 6,6 26,67 53 23 24 262 K. Gogidze Annals of Agrarian Science 17 (2019) 258 – 265 Table 2.6RLO7H[WXUH Location, exposition, Fractions , % Horizon, depth 3URILOHʋ altitude 0,25- 0,05- 0,01- 0,005- (cm) 1-0,25 <0,001 <0,01 0,05 0,01 0,005 0,001 Subalpine forest zone 1700-2000 m a. s. l. $ƍ0-10 9 47 19 5 8 12 25 $ƍƍ10-40 17 39 15 11 8 10 29 Tsdo, 15 AB 40-55 12 37 29 5 12 5 22 S B 55-95 15 47 13 9 7 9 25 BC 95-150 10 44 25 2 14 5 21 A 0--12 18 24 13 18 24 3 45 42 Akhaltsikhe, B 12--30 10 23 22 14 28 3 45 N BC 30--65 12 26 25 10 10 17 37 Subalpine meadows zone 2000-2200 m a. s. l. A 0-14 4 45 18 9 15 9 33 Gergeti, 4I AB 14-35 8 29 29 13 13 8 34 S BC 35-50 5 46 4 11 20 14 45 Pansheti, A 0--10 34 43 4 6 6 7 19 29 N BC 10--30 61 20 2 7 7 3 17 Alpine meadows zone 2200-2500 m a. s. l. $ƍ--25 5 38 13 20 13 11 44 Sno, 37 $ƍƍ--65 0.6 53.4 26 7 5 8 20 S BC 65--100 29 45 4 6 2 14 22 $ƍ--10 17 33 1 36 9 4 49 Achkhoti, $ƍƍ--25 5 17 22 16 34 6 56 33 N AB 25--40 4 26 18 3 11 38 52 BC 40--60 4 27 31 13 18 7 38 Conclusion HFRORJLFDO FRQGLWLRQV VRLOV GR QRW GL൵HU E\ nature of genesis. 1. 6XEDOSLQHIRUHဧV]RQHRQGL൵HUHQWH[SRVLWLRQ $OSLQH PHDGRZV ]RQH RQ GL൵HUHQW H[SRVLWLRQ DQG LQFOLQDWLRQ DUH FKDUDFWHUL]HG E\ ZHOO DQG LQFOLQDWLRQ DUH FKDUDFWHUL]HG E\ ZHOO H[SUHVVHGKXPXVKRUL]RQ $ƍ$ƍƍ$%RU$$% H[SUHVVHG KXPXV KRUL]RQ $$% RU $ƍ $ƍƍ These soils are characterized by acid and These soils are characterized by weak acid QHXWUDO UHDFWLRQ S+ KLJK FRQWHQW RI UHDFWLRQ S+ YHU\ KLJK FRQWHQW RI KXPXV ORDPWH[WXUH,QYDULRXV KXPXV ORDPWH[WXUH,QYDULRXV HFRORJLFDO FRQGLWLRQV VRLOV GR QRW GL൵HU E\ HFRORJLFDO FRQGLWLRQV VRLOV GR QRW GL൵HU E\ nature of genesis. nature of genesis. 2. 6XEDOSLQHPHDGRZV]RQHRQGL൵HUHQWH[SRVLWLRQ 4. Thus, comparing the high mountain soils to DQG LQFOLQDWLRQ DUH FKDUDFWHUL]HG E\ ZHOO HDFK RWKHU WKH\ GR QRW ဧDQG RXW E\ JHQHWLF H[SUHVVHG KXPXV KRUL]RQ $$% RU $ƍ $ƍƍ LQGLYLGXDOLW\ ZKLFK FDQ EH H[SODLQHG E\ These soils are characterized by acid and general similarities of ecological conditions, QHXWUDO UHDFWLRQ S+ KLJK FRQWHQW RI ZKLFKLVQRWH[SUHVVHGLQWKHJHQHWLFLGHQWLW\RI KXPXV ORDPWH[WXUH,QYDULRXV LQGLYLGXDO REMHFWV 263 K. Gogidze Annals of Agrarian Science 17 (2019) 258 – 265 Acknowledgments >@ 0 1 6DEDVKYLOL 0$ -LNDHYD$ERXW RI PRXQWDLQPHDGRZ VRLOV RI .D]EHJL 7KLV ZRUN ZDV VXSSRUWHG E\ 6KRWD 5XဧDYHOL GLဧULFW$FDGHP\RI6FLHQFHRI*665 1DWLRQDO 6FLHQFH )RXQGDWLRQ 6516) >JUDQW LQ 5XVVLDQ 3K'B)BB 6WXG\LQJ RI JHQHWLF SHFXOLDULWLHV >@6K.6KXEODG]H7KH*HQHWLF&KDUDFWHULဧLFV RI VRLO LQ .D]EHJL 0XQLFLSDOLW\@ of the Soil of highmountains of the Central Caucasus, The Thesis of Agriculture, References Tbilisi, 1987 (in Russian). [15] T. Urushadze, T. Kvrivishvili, The Guideline >@ 6$=DNKDURY7RWKH&KDUDFWHULဧLFVRIWKH of Soils of Georgia, “Mtsignobari”, Tbilisi, 6RLOV RI 0RXQWDLQRXV &RXQWULHV ¿IWK HG 2014 (in Georgian). ,QဧLWXWH RI 6HSDUDWLRQ RI .RQဧDQWLQRYVN\ [16] T. F. Urushadze, W. E. H. Blum, Soils of 0RVFRZ LQ 5XVVLDQ Georgia, Nova Publishers, New York, >@ $9R]QHVHQVN\7KHVRLOVRIDQGGLYLVLRQV 2014. RI ဧHSSH RI .DUD\VN\ 6FLHQWL¿F 5HVHDUFK [17] T. Urushadze, A. Korakhashvili, O. ,QဧLWXWHRI:DWHU0DQDJHPHQW Kvirikashvili, L. Ninua, Some Aspects LQ5XVVLDQ of Interdependence Between Soils and >@ 210LNKDLORYVND\2QWKH4XHဧLRQRIWKH Pastures in the Central Caucasus, M. Genesis of Soils of Highmountains, Academy Sabashvili Institute of Soil Science, RI 6FLHQFHV RI WKH 8665 0RVFRZ LQ Aagrochemistry and Reclamation, Tbilisi, 5XVVLDQ 1984 (in Georgian). >@ *'$NKYOHGLDQL6,7VLQWVDG]H7KH6RLOV [18] L. I. Maruashvili, The Geomorphology RI.OXNKRUL'LဧULFW:RUNVRI,QဧLWXWHRI6RLO of Georgia, Academy of Science of GSSR, 6FLHQFH DQG $JURFKHPLဧU\ *665 7ELOLVL Tbilisi, 1971 (in Russian). LQ 5XVVLDQ [19] B. Goishvili, Khevi, National Academy >@ *07DUDVDVKYLOL7KH6RLOVRI0RXQWDLQ of Science of Georgia, Tbilisi, 1981 (in )RUHဧ DQG 0RXQWDLQ0HDGRZV RI (Dဧ Georgian) Georgia, Academy of Science of Georgia, [20] T. Hanauer, C. Pohlenz, B. Kalandadze, 7ELOLVL LQ *HRUJLDQ T. Urushadze, P. Felix-Henningsen, Soil >@ $ ' *RJDWLVKYLOL 7R WKH TXHဧLRQ RI distribution and soil properties in the ဧXG\LQJ RI FHQRVLV RI VRLOV RI WUDQVLWLYH subalpine region of Kazbegi; Greater VXEDOSLQH]RQH,QဧLWXWHRI6RLO6FLHQFH Caucasus; Georgia: Soil quality rating LQ 5XVVLDQ of agricultural soils, Annals of Agrarian >@ *57DODNKDG]H7KH0DLQ7\SHVRI6RLOV Science. 15 (2017) 1-10. RI *HRUJLD ³7VRGQD´ 7ELOLVL LQ [21] I. V. Bondyrev, Geodynamical processes, *HRUJLDQ in: I. V. Bondyrev, Z. V. Davitashvili, >@ 7 8UXVKDG]H 7KH 6RLOV RI )RUHဧ RI V. P. Sinngh (Eds.), The Geography of Georgia, “Soviet Georgia”, Tbilisi, 1972 Georgia, World Regional Geography LQ *HRUJLDQ Book Series, Springer International > @ 7)8UXVKDG]H7KH6RLOVRI6RPH3LQH Publishing, Switzerland, 2015, pp. 67-80. )RUHဧVRI*HRUJLD³/HVRYHGHQLH´7ELOLVL [22] I. V. Bondyrev, Geodynamical processes, LQ5XVVLDQ in: I. V. Bondyrev, Z. V. Davitashvili, >@ 7 ) 8UXVKDG]H 7KH 0RXQWDLQRXV 6RLOV V. P. Sinngh (Eds.), The Geography of of the USSR, “Agropromizdat”, Moscow, Georgia, World Regional Geography LQ5XVVLDQ Book Series, Springer International >@ 0 1 6DEDVKYLOL 7KH 6RLOV RI *HRUJLD Publishing, Switzerland, 2015, pp. 87-95 ,QဧLWXWHRI6RLO6FLHQFHRI*6657ELOLVL [23] R. Khazaradze, K. Kharadze, Geographical LQ 5XVVLDQ Environment and Ongoing Geodynamic >@ 0 1 6DEDVKYLOL 0$ -LNDHYD$ERXW Processes in Kazbegi Municipality, RI PRXQWDLQPHDGRZ VRLOV RI .D]EHJL National Academy of Science of Georgia, GLဧULFW$FDGHP\RI6FLHQFHRI*665 Tbilisi, 2012 (in Georgian). LQ 5XVVLDQ [24] L. B. Makhatadze, T. F. Urushadze, The 264 K. Gogidze Annals of Agrarian Science 17 (2019) 2258 – 265 Subalpine Forests of Caucasus, Academy of Sciences of the USSR, Moscow, 1972 (in Russian). [25] M. Kordzakhia, Climate of Georgia, Geography Institute of Vakhushti, Tbilisi, 1961 (in Georgian). [26] G. Agladze, P. Chkheidze, Natural Mowing and Pastures of Mtkheta-Mtianeti Region, Their Meaning in Resolve Problems of Livestock, National Academy of Science of Georgia, Tbilisi, 2012 (in Georgian). [27] K38-54-A, Ministry of Geology of USSR, Geological Map M 1:50 000, 1983 (in Russian). [28] K38-54-B, Ministry of Geology of USSR, Geological Map M 1:50 000, 1983 (in Russian). [29] K38-54-G, Ministry of Geology of USSR, Geological Map M 1:50 000, 1962 (in Russian). [30] K38-54-V, Ministry of Geology of USSR, Geological Map M 1:50 000, 1983 (in Russian). [31] K. Mindeli, L. Guntaishvili, N. Macha- variani, D. Kirvalidze, Kh. Mindeli, L. Gamsakhurdia, Practical-Laboratory Manual of Soil Science, Tbilisi, 2011 (in Georgian). 265 P. Haldar et al. Annals of Agrarian Science 17 (2019) 266 – 276 Annals of Agrarian Science :ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ Sustaining paddy production through improved agronomic practices in the Gangetic alluvial zone of West Bengal Pallabendu Haldara, Arindam Sarkar*b, Manabendra Roya, Kabita Chowdhuryc a $,&53RQ,QWHJUDWHG)DUPLQJ6\ဧHP'LUHFWRUDWHRI5HVHDUFK%LGKDQ&KDQGUD.ULVKL9LVZDYLG\DOD\D.DO\DQL 1DGLD:Hဧ%HQJDO b 5HJLRQDO5HVHDUFK6WDWLRQ 5 /=RQH %LGKDQ&KDQGUD.ULVKL9LVZDYLG\DOD\D-KDUJUDP:Hဧ%HQJDO c 'HSDUWPHQWRI$JULFXOWXUDO&KHPLဧU\DQG6RLO6FLHQFH%LGKDQ&KDQGUD.ULVKL9LVZDYLG\DOD\D0RKDQSXU1DGLD :Hဧ%HQJDO Received: 26 March 2019; accepted 1 May 2019 A B S T R A C T 7KHDUWLFOHLQFOXGHVWKHUHVHDUFKLQ.KHYLUHJLRQRI&HQWUDO*UHDW&DXFDVXV6WXG\DUHDZDVGLYLGHGE\H[SRVLWLRQV QRUWKDQGVRXWK ([FHVVLYHDQGLPEDODQFHGXVHRIFKHPLFDOIHUWLOL]HULQPRGHUQDJULFXOWXUHKDVGRZQJUDGHGVRLOKHDOWK)DUPHUVYHU\RIWHQDYRLG RUJDQLF IHUWLOL]HU LQ FURS SURGXFWLRQ GXH WR LWV XQDYDLODELOLW\ 6WXEEOH UHPRYDO DQG RWKHU XQVFLHQWL¿F FXOWXUDO SUDFWLFHV DUH PRUH OLNHO\WRHQKDQFHVRLOGHJUDGDWLRQSURFHVVDQGFURSSURGXFWLRQLQORQJHUWHUP+HUHZHXQGHUWRRNDQH[SHULPHQWWRLGHQWLI\VXLWDEOH DJURQRPLFPDQDJHPHQWSUDFWLFHVIRUSDGG\FXOWLYDWLRQLQWKH*DQJHWLFDOOXYLDO]RQHRI:Hဧ%HQJDO,QGLD,QWHUDFWLRQVEHWZHHQ GL൵HUHQWFURSSLQJV\ဧHPV 5LFH5DSHVHHG)RGGHUFRZSHD5LFH)LHOGSHD)RGGHUFRZSHDDQG5LFH:KHDW)RGGHUFRZSHD DQGDYDLODEOHQXWULHQWVRXUFHVWKURXJKFKHPLFDOIHUWLOL]HUDORQHRULQFRPELQDWLRQZLWKRUJDQLFIHUWLOL]HUVZHUHဧXGLHG&URSXSWDNH RIQLWURJHQSKRVSKRURXVDQGSRWDVVLXPYLVDYLVGL൵HUHQW\LHOGFRPSRQHQWVDVD൵HFWHGE\PDQDJHPHQWSUDFWLFHVZHUHLQYHဧLJDWHG ,QFRUSRUDWLRQRIOHJXPLQRXVFURS ¿HOGSHD LQWKHFURSSLQJVHTXHQFHUHVXOWHGLQHQKDQFHGQXWULHQWXSWDNHDQGSDGG\SURGXFWLRQWKDQ RWKHUFURSSLQJV\ဧHPV$SSOLFDWLRQRIRUJDQLFPDQXUHVPL[HGZLWKFKHPLFDOIHUWLOL]HUKDVUHVXOWHGLQWRKLJKHUQXWULHQWXSWDNHDQG FURS\LHOGWKDQFKHPLFDOIHUWLOL]HUVDORQH+RZHYHUWKHUHZDVDVLJQL¿FDQWGL൵HUHQFHZLWKW\SHRIRUJDQLFPDQXUHXVHG$SSOLFDWLRQRI IDUP\DUGPDQXUHDQGELRJDVVOXUU\KDVUHVXOWHGLQPD[LPXPQXWULHQWXSWDNHDQG\LHOG)DUP\DUGPDQXUHDQGELRJDVVOXUU\EHLQJ QLWURJHQSRRUKDYHWKHDELOLW\WRVXSSO\QXWULHQWIRUDORQJHUWLPHEHIRUHH[KDXဧLRQWKDQQLWURJHQULFKYHUPLFRPSRဧDQGD]ROOD2XU ¿QGLQJVZLOOEHKHOSIXOWRIDUPHUVIRUEHWWHUXVHRIWKHLUUHVRXUFHVLQDJULFXOWXUDOPDQDJHPHQW Keywords: Integrated nutrient management, Paddy cultivation, Cropping sequence, Crop nutrient uptake, Organic manure, Chemical fertilizer. &RUUHVSRQGLQJDXWKRU $6DUNDU(PDLODGGUHVV DULQSVE#JPDLOFRP Introduction progressively since its introduction to agriculture. It KDV UHDFKHG WR DERXW PLOOLRQ WRQV LQ 3DGG\ LV WKH PRဧ LPSRUWDQW ဧDSOH FURS DPRQJ IURP RQO\ WKRXVDQG WRQV GXULQJ >@ FHUHDOV LQ VRXWKZHဧ $VLD ,Q ,QGLD SDGG\ LV )RUDSUR¿WDEOHUHWXUQIDUPHUVDUHDSSO\LQJFKHPLFDO FXOWLYDWHG WKURXJKRXW WKH FRXQWU\ H[FHSW IHZ fertilizers at the rate higher than recommended dose GU\ DUHDV WKH ,QGR*DQJHWLF SODLQ EHLQJ PRဧ causing soil health deterioration. Decreasing soil important among them. Muddy soils, which are health and crop production in long run resulting from capable of holding enough water, have advantage H[FHVVLYHXVHRILPEDODQFHGLQRUJDQLFIHUWLOL]HUKDV of cultivating paddy here over other areas. The use EHHQUHSRUWHGHOVHZKHUH>DQGUHIHUHQFHVWKHUHLQ@ of chemical fertilizer for nitrogen, phosphorous and /HDFKLQJDQGUXQR൵ORVVRILQRUJDQLFQXWULHQWVSRVH SRWDVVLXP 13. LQ,QGLDQDJULFXOWXUHLVLQFUHDVLQJ DFXWH SUREOHP RI ZDWHUERG\ HXWURSKLFDWLRQ > @ 266 P . Haldar et al. Annals of Agrarian Science 17 (2019) 266 – 276 Thus society faces both environmental and economic LQ RXU ဧXG\ DUHD :H WULHG WR FRPELQH YDULRXV WKUHDW+RZHYHUWKHIDUPHUVDUHXQDEOHWRXQGHUဧDQG possible nutrient sources and prevalent cropping the negative impact these type of malpractice. SDWWHUQRIWKHDUHDDQGLQYHဧLJDWHGLQWHUDFWLRQH൵HFW 7KHLQWHJUDWHGQXWULHQWPDQDJHPHQW ,10 DLPV H[LဧHGZLWKLQWKHP7KLVဧXG\ZLOOLGHQWLI\WKHEHဧ WR¿QGDVXLWDEOHPDQDJHPHQWSUDFWLFHZKLFKVKRXOG possible combination of nutrient source and cropping EHSUR¿WDEOHDVZHOODVVXဧDLQDEOHIRUWKHHQYLURQPHQW VHTXHQFH IRU WKH ZKROH ,QGR*DQJHWLF SODLQ >@,WFRPELQHVDOOSRVVLEOHVRXUFHVRIQXWULHQW :HK\SRWKHVL]HGWKDWDJURQRPLFFURSSLQJV\ဧHP YL] RUJDQLF LQRUJDQLF DQG ELRIHUWLOL]HU DQG KHOSV DQGWKHVRXUFHRIQXWULHQWDSSOLHGZRXOGD൵HFWWKH us to achieve our goal without environmental nutrient supplying capacity of soil, hence crop yield. GHJUDGDWLRQ>@2UJDQLFVRXUFHRIQXWULHQWV We considered Rice–Rapeseed–Fodder cowpea, VXFKDVIDUP\DUGPDQXUHV )<0 YHUPLFRPSRဧV Rice–Field pea–Fodder cowpea and Rice–Wheat– azolla etc. are rich in carbon, nitrogen and other Fodder cowpea cropping sequence for alternative HVVHQWLDO FRPSRXQGV >@ 7KH\ QRW RQO\ SURYLGH FURSSLQJ V\ဧHP DQG )<0 YHUPLFRPSRဧ ELRJDV the crop nutrient, but also help in improving soil slurry and azolla as possible organic nutrient source KHDOWK > @ +RZHYHU WKHLU ¿HOG UHTXLUHPHQW LV besides chemical fertilizer suitable for this region. quite high due to lesser concentration of nutrients as 2XUREMHFWLYHZDVWR¿QGRXWWKHH൵HFWRIRUJDQLFDQG FRPSDUHGWRLQRUJDQLFIHUWLOL]HUV>@7KHDELOLW\ inorganic sources of nutrients on crop nutrient uptake of organic fertilizers to supply nutrient is dependent DQGSURGXFWLYLW\RISDGG\:HDOVRWULHGWR¿QGRXW on nature and composition of material, soil microbial the suitability of organic fertilizers in rice cultivation diversity and climatic condition. Sources such as DQGIDUPLQJV\ဧHPZKLFKDLPVIRUVXဧDLQDEOHSDGG\ )<0 YHUPLFRPSRဧ JUHHQ PDQXUH ELRJDV VOXUU\ cultivation in the area. DUH DOO PDGH XS RI GL൵HUHQW FKHPLFDO FRPSRVLWLRQ > @7KXVGHJUDGDELOLW\DQGFURSVXLWDELOLW\RIWKHVH 2. Materials and methods PDWHULDOVDUHGL൵HUHQW7KHLQRUJDQLFIHUWLOL]HUVRQ the other hand being very concentrated in nutrients 6LWHGHVFULSWLRQDQGH[SHULPHQWDOGHVLJQ DUH UHTXLUHG LQ OHVVHU TXDQWLW\ >@ 7KRXJK WKHLU 7KH¿HOGH[SHULPHQWZDVFRQGXFWHGGXULQJWKH requirement is less, they are found to aggravate soil period of July 2013 to June 2015 at Central Research KHDOWK GHJUDGDWLRQ >@ 1HYHU WKH OHVV IHUWLOH )DUP*D\HVKSXU1DGLD:Hဧ%HQJDO ¶1DQG soils are prerequisite for higher crop yield. Thus we (06/ XQGHUQHZDOOXYLDO=RQH7KH¿HOG KDYHWR¿QGDSRVVLEOHSURSRUWLRQRIRUJDQLFDVZHOO was medium in slope having well irrigation facility. DVLQRUJDQLFIHUWLOL]HUVZKLFKQRWRQO\JLYHVSUR¿WDEOH The site receives an average annual rainfall of return, but protects our soil form further degradation. 1460 mm and the annual temperature varies from /HJXPH FURSV DUH HVVHQWLDOO\ EHQH¿FLDO WR & LQ -DQXDU\ WR & LQ $SULO 7KH LQLWLDO DJULFXOWXUH7KH\ ¿[ DWPRVSKHULF LQRUJDQLF QLWURJHQ VRLO FKDUDFWHULဧLFV ZHUH UHSRUWHG LQ 7DEOH 7KH DQGUHOHDVHWKHPLQVRLOFXWWLQJDVLJQL¿FDQWSURSRUWLRQ H[SHULPHQWZDVODLGRXWLQဧULSSORWGHVLJQ$OOWKH RILQRUJDQLFQLWURJHQRXVIHUWLOL]HUUHTXLUHPHQW>@ nutritional management treatments were applied to However their cultivation in Gangetic alluvium belt ULFHUDSHVHHG¿HOGSHDDQGZKHDWZKHUHDVIRGGHU KDV GHFOLQHG FRQVLGHUDEO\ >@ )DUPHUV SUHIHU cowpea was grown in the residual fertility of the soil. cereals and oil seeds over legumes for their daily 7KH GHWDLOV RI WKH WUHDWPHQWV ZHUH OLဧHG LQ7DEOH requirement. Legumes, if incorporated in the cropping 2. Recommended cultural practices were followed sequence increases the chance of further cut down IRUDOOWKHFURSV7KHULFHFURSZDVKDUYHဧHGDW RQFRဧRIFXOWLYDWLRQZKLFKLVDOVRHQYLURQPHQWDOO\ % physiological maturity and air dried for 3 days. VRXQG DQG YLDEOH > @ After drying, the total plant was weighed, threshed 7KHUH DUH VHYHUDO UHSRUWV DYDLODEOH RQ LQÀXHQFH DQGWKHJUDLQ\LHOGZDVFDOFXODWHG7KHဧUDZ\LHOG of organic fertilizer on plant nutrition and crop yield. was calculated by deducting grain yield from the $SSOLFDWLRQV RI IDUP \DUG PDQXUH YHUPLFRPSRဧ total yield. The yield determining parameters of rice D]ROOD ELRJDV VOXUU\ ZHUH IRXQG WR KDYH SRVLWLYH viz. number of panicle mQXPEHURI¿OOHGJUDLQ H൵HFWRQQXWULHQWXSWDNHDVZHOODVVRLOKHDOWK> SDQLFOH1 SDQLFOH ZHLJKW J SDQLFOH OHQJWK FP @ +RZHYHU RQO\ IHZ UHSRUWV DQGWHဧZHLJKW J ZHUHUHFRUGHGDIWHUKDUYHဧLQJ >@DUHDYDLODEOHRQFRPELQHGLQÀXHQFHRI of the crop. YDULRXV VRXUFHV RI QXWULHQWV YDULRXV FKHPLFDO DQG RUJDQLF IHUWLOL]HUV DQG GL൵HUHQW FURSSLQJ VHTXHQFH 267 P . Haldar et al. Annals of Agrarian Science 17 (2019) 266 – 276 2.2 Nutrient analysis of soil and plant of inorganic and organic fertilizer was reported HOVHZKHUH > @ +LJKHU JUDLQ DQG 7KH FRPSRVLWH VXUIDFH VRLO VDPSOHV WRS ဧUDZ \LHOG ZDV REWDLQHG IURP WKRVH SORWV ZKHUH FP ZHUH FROOHFWHG IURP GL൵HUHQW UDQGRP higher nutrient uptake was found, since minerals ORFDWLRQVRIWKHH[SHULPHQWDO¿HOGDQGZHUHPL[HG uptake by rice is associated with biomass production WKRURXJKO\ 7RWDO QLWURJHQ 1 FRQFHQWUDWLRQ ZDV >@ GHWHUPLQHG E\ PRGL¿HG .MHOGDKO PHWKRG >@ 7KH YDULDWLRQ LQ 1 XSWDNH ZLWK GL൵HUHQW whereas hot alkaline KMnO4 PHWKRG >@ ZDV treatments is reported in Table 3. The pooled data followed for available N determination. Soil and VKRZHGWRWDO1XSWDNH JUDLQဧUDZ YDULHGIURP SODQWSKRVSKRUXV 3 FRQFHQWUDWLRQZDVGHWHUPLQHG 121.95 to 205.21 kg ha among treatments. The E\ 2OVHQ¶V PHWKRG >@ DQG YDQDGRPOR\EGR JUDLQ QLWURJHQ XSWDNH DYJ NJ KD ZDV SKRVSKRULF DFLG \HOORZ FRORU PHWKRG E\ >@ PRUHWKDQဧUDZ DYJNJKD +LJKHUJUDLQ UHVSHFWLYHO\3RWDVVLXP . ZDVGHWHUPLQHGÀDPH DQGဧUDZ1XSWDNH DYJ DQGNJKD SKRWRPHWU\ >@ &URS QXWULHQW XSWDNH NJ KD UHVSHFWLYHO\ ZDV IRXQG ZKHQ OHJXPH FURS ¿HOG was calculated by multiplying the concentration SHDZDVLQWURGXFHGLQWKHFURSSLQJVHTXHQFH &2 DV RIQXWULHQWVWRWKHFURS\LHOG NJKD XVLQJWKH FRPSDUHGWRFRQYHQWLRQDOUDSHVHHG &1; avg. 90.16 following formula, and 79.98 kg ha DQGZKHDW &3; 84.52 and 79.98 O 1XWULHQWXSWDNH NJKD 1XWULHQWFRQFHQWUDWLRQ kg ha FXOWLYDWLRQSUDFWLFH+RZHYHUH൵HFWRI&1 î\LHOG NJKD and C2 FURSSLQJ VHTXHQFH ZDV ဧDWLဧLFDOO\ DW SDU Nitrogen uptake in terms of nutrient management 6WDWLဧLFDODQDO\VLV SUDFWLFH 0 ZDV GL൵HUHQW ZKHQ RUJDQLF DQG FKHPLFDO IHUWLOL]HU ZDV DSSOLHG LQ GL൵HUHQW $OO WKH YDULDEOHV ZHUH VXEMHFWHG WR $129$ FRPELQDWLRQ +LJKHU JUDLQ DQG ဧUDZ XSWDNH ZDV DQDO\VLV PHDQW IRU ဧULS SORW GHVLJQ >@ XVLQJ found in case of M DYJ DQGNJKD 6366 Y VRIWZDUH7KHဧDQGDUGHUURURIPHDQ 1 UHVSHFWLYHO\ 0 DYJ DQG NJ KD 6(P DQG WKH YDOXH RI FULWLFDO GL൵HUHQFH &' 2 UHVSHFWLYHO\ DQG0 DYJ DQGNJKD DW OHYHO RI VLJQL¿FDQFH ZHUH LQGLFDWHG LQ WKH 3 UHVSHFWLYHO\ IROORZHGE\0 DYJDQG WDEOHVWRFRPSDUHWKHGL൵HUHQFHEHWZHHQWKHPHDQ 4 kg haUHVSHFWLYHO\ DQG0 DYJ DQG values. Pearson correlations were calculated in 5 kg ha UHVSHFWLYHO\ )DUP \DUG PDQXUH )<0 0LFURVRIW ([FHO Y )LJXUHV ZHUH SUHSDUHG LQFRUSRUDWLRQ 0 KDG UHVXOWHG KLJKHဧ JUDLQ XVLQJ 6LJPDSORW Y 2 XSWDNH DYJ NJKD ZKHUHDVဧUDZXSWDNH ZDVKLJKHဧZKHQELRJDVVOXUU\ 03; avg. 88.13 kg 3. Results and discussion ha ZDVDSSOLHG+RZHYHUWKHGL൵HUHQFHEHWZHHQ M1, M2 and M3 ZDV ဧDWLဧLFDOO\ LQVLJQL¿FDQW &URS QXWULHQW XSWDNH DV LQÀXHQFHG E\ 6LJQL¿FDQW YDULDWLRQ LQ 3 XSWDNH ZDV REVHUYHG management practices: 7DEOH LQULFHJUDLQDQGဧUDZGXHWRWKHYDULDWLRQ :HဧXGLHGWKHFKDQJHVLQFURSXSWDNHRIQLWURJHQ in nutritional management treatments during both SKRVSKRURXV DQG SRWDVVLXP 1 3 DQG . ZLWK WKH \HDUV RI LQYHဧLJDWLRQ 3KRVSKRURXV XSWDNH GL൵HUHQWQXWULHQWVRXUFHVDQGPDQDJHPHQWSUDFWLFH FORVHO\ IROORZHG 1 XSWDNH WUHQG +LJKHဧ JUDLQ 3 7KHUHZDVVLJQL¿FDQWYDULDWLRQLQQXWULHQWXSWDNHE\ uptake was recorded in C2FURSSLQJVHTXHQFH ULFHFURSZLWKLQGL൵HUHQWFURSSLQJVHTXHQFH & DQG kg ha IROORZHGE\&1 NJKD DQG&3 kg ha 7KRXJK&1 and C2SURGXFHGVLPLODUH൵HFW QXWULHQW PDQDJHPHQW 0 *HQHUDOO\ &2 cropping sequence reported higher nutrient uptake for N, P LWZDVVLJQL¿FDQWO\ORZLQ&1. Similar variation was and K followed by C and C . Though lesser amount IRXQG IRU ဧUDZ 3 XSWDNH +LJKHဧ FRQFHQWUDWLRQ 1 3 of nutrient uptake was found for C cropping was found in C2 NJKD IROORZHGE\&3 1 kg ha DQG &1 NJ KD $PRQJ GL൵HUHQW VHTXHQFHWKHH൵HFWZDVဧDWLဧLFDOO\DWSDUZLWK&2. The nutrient uptake in C VHTXHQFHZDVORZHဧDQG PDQDJHPHQW SUDFWLFHV KLJKHU JUDLQ DQG ဧUDZ 3 3 VLJQL¿FDQWO\GL൵HUVIURPWKHUHဧ3DGG\JUDLQZDV uptake was found in M2 DQG NJ KD HQULFKHGLQ1DQG3 DQGUHVSHFWLYHO\ WKDQ UHVSHFWLYHO\ IROORZHG E\ 03 DQG ဧUDZ DQGUHVSHFWLYHO\ H[FHSW.ZKHUH kg ha DQG 01 DQG NJ KD /RZHဧ ဧUDZUHWDLQHGKLJKHU. DJDLQဧJUDLQ DPRXQWRIJUDLQDQGဧUDZ3XSWDNHZDVIRXQGLQ Better nutrient uptake with combined application M4 DQGNJKD DQG05 DQG 268 P . Haldar et al. Annals of Agrarian Science 17 (2019) 266 – 276 kg ha 6WDWLဧLFDODQDO\VLVUHYHDOHG01, M2 and M3 during entire crop duration or would have to apply in \LHOGHG ဧDWLဧLFDOO\ VLPLODU 3 XSWDNH ZKHUHDV 04 higher amount to achieve desired crop production. and M5 produced poor results. +LJKHဧJUDLQ.XSWDNHZDVIRXQGLQ&2 NJ ha IROORZHGE\&1 NJKD KRZHYHUWKHUH ,QÀXHQFH RI FXOWXUDO PDQDJHPHQW RQ ZDVQRVLJQL¿FDQWYDULDWLRQ 7DEOH /HDဧXSWDNH paddy yield and yield components: was recorded in C3 NJ KD ZKHUH 5LFH :KHDW )RGGHU FRZSHD VHTXHQFH ZDV IROORZHG 2XUGDWDUHYHDOHGVLJQL¿FDQWYDULDWLRQLQSDQLFOH +LJKHUဧUDZXSWDNHZDVIRXQGLQ& NJKD no m ZLWK GL൵HUHQW WUHDWPHQWV +LJKHဧ QR 2 1 panicle m ZDV IRXQG XQGHU OHJXPH FURSSLQJ IROORZHGE\&3 NJKD DQG&1 NJ ha +RZHYHUWKHLUH൵HFWZDVဧDWLဧLFDOO\DWSHU sequence, where as other cropping sequence When it comes to nutrient management, grain K UHVXOWHGVLPLODUSDQLFOHLQLWLDWLRQ SDQLFOHP +RZHYHUZKHQFRPSDUHGZLWKLQGL൵HUHQWQXWULHQW uptake in M2 NJKD DQG03 NJKD ZDVKLJKHUWKDQWKHUHဧ0 , M and M VRXUFHVQRVLJQL¿FDQWGL൵HUHQFHZDVIRXQGZLWKLQ 1 4 5 M , M and M DQGUHVSHFWLYHO\ VHH and 18.62 kg haUHVSHFWLYHO\ 6WUDZ.XSWDNHZDV 1 2 3 7DEOH +RZHYHU0 and M UHSRUWHGORZHဧQR found to be higher in M NJKD IROORZHG 4 5 3 of panicle m DQGUHVSHFWLYHO\ 7KH)LJ by M2 NJKD DQG01 NJKD 6WUDZ D VKRZV WKH LQWHUDFWLRQ H൵HFW EHWZHHQ FURSSLQJ K uptake in M4 and M5 DQG NJ KD UHVSHFWLYHO\ ZDVVLJQL¿FDQWO\ORZHUWKDQRWKHUV VHTXHQFH DQG QXWULHQW VRXUFHV %Hဧ UHVXOW ZDV found in C M , followed by C M and C M )LJXUH VKRZV WKH LQWHUDFWLRQ H൵HFW EHWZHHQ 2 2 2 3 2 1 FURSSLQJ VHTXHQFH & DQG QXWULHQW PDQDJHPHQW 278 and 275 panicle m UHVSHFWLYHO\ $GHTXDWH 0 IRU13DQG.XSWDNH7KHUHZDVVLJQL¿FDQW DQG VXဧDLQHG QXWULHQW VXSSO\ GXULQJ YHJHWDWLYH variation between treatments. Cropping sequence JURZWKဧDJHPLJKWKDYHUHVXOWHGKLJKHUSDQLFOHQR C along with M QXWULHQWPDQDJHPHQW\LHOGHGEHဧ m LQWKHVHWUHDWPHQWV>@$PRQJWKHQXWULHQW 2 2 sources M and M yielded poor result with cropping UHVXOWLQQXWULHQWXSWDNH DQG 4 5 kg ha UHVSHFWLYHO\ IRU 1 3 DQG . )LHOG SHD VHTXHQFH & and cowpea being a leguminous crop in cropping 7KHQRRI¿OOHGJUDLQSDQLFOH YDULHGVLJQL¿FDQWO\ DPRQJWUHDWPHQWV%HဧUHVXOWZDVIRXQGLQ& VHTXHQFHKHOSVLQ¿[LQJDWPRVSKHULF1LPSURYLQJ 2 VRLOQXWULHQWဧDWXV7KHH൵HFWZDVIXUWKHUDPSOL¿HG grain panicle 7DEOH LH ZKHQ OHJXPH FURS when FYM was incorporated in the nutrient was incorporated in the cropping sequence. This ZDV VLJQL¿FDQWO\ KLJKHU WKDQ & and C DQG PDQDJHPHQWV\ဧHP 0 )DUP\DUGPDQXUHEHLQJ 1 3 2 rich in carbonaceous and lignin compound helps 147 grain panicle UHVSHFWLYHO\ 6LPLODU UDQJH RI LQ UHဧRULQJ VRLO KHDOWK DQG EHWWHU QXWULHQW XSWDNH UHVXOWZDVIRXQGZKHQGL൵HUHQWVRXUFHVRIQXWULHQWV DQG JUDLQ SDQLFOH for M , M and > DQG UHIHUHQFHV WKHUHLQ@ $SSOLFDWLRQ RI ERWK 1 2 M UHVSHFWLYHO\ ZHUHFRQVLGHUHG+RZHYHU0 and organic and inorganic fertilizer together helps in 3 4 M \LHOGHG VLJQL¿FDQWO\ ORZHU QR RI ¿OOHG JUDLQ slow release of nutrient, thus enhanced nutrient use 5 H൶FLHQF\>@7KH\DOVRဧLPXODWHVRLOPLFURELDO panicle DQGJUDLQSDQLFOH UHVSHFWLYHO\ activity, crop root growth and reduced nutrient loss )LJXUH E VKRZV WKH LQWHUDFWLRQ H൵HFW EHWZHHQ cropping sequence and nutrient sources. The C M , UHVXOWLQJEHWWHUXSWDNHRIZDWHUDQGQXWULHQW>@ 2 2 +RZHYHU WKH H൵HFW ZDV ဧDWLဧLFDOO\ LQVLJQL¿FDQW OLNHRWKHUSDUDPHWHUSURGXFHGEHဧUHVXOW JUDLQ panicle IROORZHGE\& M JUDLQSDQLFOH when compared to other nutrient management 2 3 Legume crop incorporation and addition of organic OLQH H[FHSW 04 and M5 DJDLQဧ &2 6LPLODUO\ &1 and C yielded comparable results with M , M IHUWLOL]HU HQVXUHG VX൶FLHQW QXWULHQW VXSSO\ GXULQJ 3 1 2 ÀRZHULQJ WR SK\VLRORJLFDO PDWXULW\ ဧDJH >@ and M3 6HYHUDO UHSRUWV >@ ZHUH DYDLODEOH Reduced amount of N supply in M4 and M5 during VKRZLQJ SRVLWLYH LQÀXHQFH RI YHUPLFRPSRဧ 04 DQGD]ROOD 0 RQFURSQXWULHQWXSWDNHDQG\LHOG WKLV ဧDJH PLJKW KDYH UHGXFHG QR RI ¿OOHG JUDLQ 5 +RZHYHUZHGLGQ¶W¿QGDQ\VLJQL¿FDQWLPSDFWRI panicle . WKHPRQQXWULHQWXSWDNH$]ROODDQGYHUPLFRPSRဧ Table 4 shows the variation in Panicle weight being N rich is preferentially decomposed and have J SDQLFOH OHQJWK FP DQG WHဧ ZHLJKW +LJKHဧ TXLFNHUWXUQRYHUUDWHUHODWLYHWR)<0>@7KXV SDQLFOH ZHLJKW SDQLFOH OHQJWK DQG WHဧ ZHLJKW was found in C J FP DQG J YHUPLFRPSRဧ DQG D]ROOD PD\ DFW DV VRXUFH RI 2 UHVSHFWLYHO\ IROORZHGE\& JFPDQG nutrients, but it might not be able to supply nutrients 1 269 P . Haldar et al. Annals of Agrarian Science 17 (2019) 266 – 276 JUHVSHFWLYHO\ DQG&3 J FPDQG QXWULHQWV E\ SODQWV 7KRXJK DOO WKH QXWULHQWV 1 3 JUHVSHFWLYHO\ 7KRXJKWKHH൵HFWRI&1 was DQG . ZHUH ဧURQJO\ FRUUHODWHG ZLWK RWKHU \LHOG ဧDWLဧLFDOO\ DW SHU &2; C3 SURGXFHG VLJQL¿FDQWO\ SDUDPHWHUV WKH DVVRFLDWLRQ RI 1 ZDV ဧURQJHဧ lower values. Among nutrient management, M2 U S 7KLVVXJJHဧVSULPDU\UROHRI1RQ JFPDQGJPUHVSHFWLYHO\ SURYHG growth and yield of crops. Researchers have found N to be superior to others. However there were no in adequate account accounted 75 to 90% variation VLJQL¿FDQW GL൵HUHQFH LQ WHUPV RI SDQLFOH ZHLJKW LQ \LHOG FRPSRQHQW >@ $VVRFLDWLRQ RI QXPEHU SDQLFOH OHQJWK DQG WHဧ ZHLJKW DPRQJ YDULRXV of panicle m QXPEHU RI ¿OOHG JUDLQ SDQLFOH and QXWULHQW VRXUFHV 7KH LQWHUDFWLRQ H൵HFW EHWZHHQ SDQLFOHZWZLWK13DQG.ZHUHPRဧO\YHU\ဧURQJ the cropping sequence and nutrient sources were U!S 7KRXJKSDQLFOHOHQJWKLVNQRZQ SUHVHQWHGLQ)LJ([FHSWIRUSDQLFOHZHLJKW&2M2 WREHLQÀXHQFHGE\QXWULHQWXSWDNH>@ZHIRXQG UHSRUWHG PD[LPXP YDOXHV +RZHYHU ZH GLGQ¶W RQO\PRGHUDWHFRUUHODWLRQ U WRS ¿QG DQ\ VLJQL¿FDQW GL൵HUHQFH EHWZHHQ WUHDWPHQW 9HU\ ဧURQJ FRUUHODWLRQ U ! S EHWZHHQ combinations for these components. JUDLQ DQG ဧUDZ \LHOG DQG 13. LQGLFDWHV LQÀXHQFH 7KH JUDLQ \LHOG ဧUDZ \LHOG DQG KDUYHဧ LQGH[ of nutrient uptake on dry matter accumulation and ZHUHSUHVHQWHGLQ7DEOH +LJKHဧJUDLQ\LHOGRI VXEVHTXHQWFURS\LHOG> @5HVHDUFKHUVKDYH t ha was obtained in cropping sequence C2 to which IRXQGSRVLWLYHDVVRFLDWLRQVRIKDUYHဧLQGH[ZLWKJUDLQ leguminous crop was incorporated, followed by C1 yield and nutrient uptake. However, we found weak WKD 7KH\LHOGZDVVLJQL¿FDQWO\ORZHUZKHQ correlation between them. Climatology, location, ZKHDW FURS ZDV JURZQ DIWHU ULFH &3; 4.42 t ha DQGHFRORJ\RIWKHဧXG\DUHDPLJKWEHUHVSRQVLEOH Similarly higher yield was obtained from M2 W for rendering their association. The plots where ha ZKHUH)<0ZDVDVLJQL¿FDQWVRXUFHFRPSRQHQW nutrient uptake was higher were found to produce followed by M3 and M1 DQG W KD higher yield. Improved soil health from balanced UHVSHFWLYHO\ +RZHYHU WKH \LHOG ZDV VLJQL¿FDQWO\ use of organic and inorganic fertilizers has resulted ORZHUZKHQHLWKHUYHUPLFRPSRဧ 04; 4.18 t ha RU LQHQKDQFHGDQGVXဧDLQHGQXWULHQWXSWDNHIURPVRLOV D]ROOD 05; 3.91 t ha ZDVXVHGDVRUJDQLFVRXUFH during entire crop growth period, increased biomass of nutrient besides inorganic sources. Similar results SURGXFWLRQ DQG FURS \LHOG >@ ZHUH UHFRUGHG IRU ဧUDZ \LHOG &URSSLQJ VHTXHQFH C UHVXOWHG EHWWHU ဧUDZ \LHOG IROORZHG E\ & and 2 1 4. Conclusion C3. Though M2 was better in case of grain yield than M ODWWHU SHUIRUPHG EHWWHU ZKHQ ဧUDZ \LHOG ZDV 3 :HဧXGLHGWKHLQÀXHQFHRIFURSSLQJV\ဧHPDQG FRQVLGHUHG +RZHYHU WKH H൵HFW RI 0 , M and M 3 2 1 nutrient sources on crop nutrient uptake and paddy ZDV ဧDWLဧLFDOO\ LQVLJQL¿FDQW 6WUDZ \LHOG IURP 0 4 yield. Few treatment combination produced better and M ZDVVLJQL¿FDQWO\ORZHUWKDQWKHRWKHUV*UDLQ 5 results in terms of nutrient uptake and yield and KDUYHဧ LQGH[ RI ULFH GLG QRW FKDQJH VLJQL¿FDQWO\ ZHUHဧDWLဧLFDOO\VLJQL¿FDQWWKDQRWKHUV1XWULHQWV LQ GL൵HUHQW WUHDWPHQWV +RZHYHU LQFRUSRUDWLRQ RI XSWDNHDQG\LHOGZDVKLJKHဧZKHQOHJXPLQRXVFURS OHJXPLQRXV FURS & DQG XVH RI )<0 DV QXWULHQW 2 ¿HOGSHDZDVLQFRUSRUDWHGLQWKHFURSSLQJV\ဧHP VRXUFH 02 \LHOGHG EHWWHU UHVXOWV WKDQ RWKHUV &2 /HJXPLQRXVFURSV¿[HGDWPRVSKHULFQLWURJHQ )LJXUHVKRZVWKHLQWHUDFWLRQH൵HFWRIFURSSLQJ to soil as plant available form, which in turn helped sequence and nutrient sources on paddy yield in better nutrient uptake and therefore crop yield. parameters. The treatment combination of C M 1 3 However, C and C SURGXFHG ဧDWLဧLFDOO\ VLPLODU \LHOGHGKLJKHဧJUDLQDQGဧUDZIROORZHGE\& M and 1 3 2 2 result to C +RZHYHUWKHLU &OLQH LQWHUDFWLRQZLWK C M . Though C N ZDVIRXQGEHဧLQWHUDFWLRQH൵HFW 2 2 3 1 3 H[WHUQDOQXWULHQWVRXUFH 0OLQH YDULHGVLJQL¿FDQWO\ between line C , C and M , M , M ZDVဧDWLဧLFDOO\ 1 2 1 2 3 in terms of nutrient uptake and crop yield. Though similar. However, the treatment combination between WKHLUH൵HFWZDVVLPLODURQQXWULHQWXSWDNHDQG\LHOG line M , M and C , C , C SURGXFHGORZHဧJUDLQDQG 4 5 1 2 3 WKHLUH൵HFWRQVRLOHQYLURQPHQWPLJKWEHGL൵HUHQW ဧUDZ\LHOGDQGZDVဧDWLဧLFDOO\VLJQL¿FDQWFRPSDUHG $PRQJ GL൵HUHQW H[WHUQDO QXWULHQW VRXUFHV XVH to others. RI IDUP \DUG PDQXUH )<0 DORQJVLGH FKHPLFDO :H IRXQG ဧURQJ WR YHU\ ဧURQJ FRUUHODWLRQ fertilizer was found to be superior. Organic carbon S EHWZHHQ WKH QXWULHQW XSWDNH DQG SDGG\ ULFK )<0 ZDV DEOH WR VXဧDLQ WKH FURS QXWULHQW \LHOG SDUDPHWHUV 7DEOH 9HU\ ဧURQJ FRUUHODWLRQ supply during the entire crop duration. Higher EHWZHHQ 1 3 DQG . LQGLFDWHV FRDGVRUSWLRQ RI QXWULHQW XSWDNH GXH WR )<0 DSSOLFDWLRQ LQ 02 270 P . Haldar et al. Annals of Agrarian Science 17 (2019) 266 – 276 ZDVDEOHWRSURGXFHKLJKHဧJUDLQDQGဧUDZ\LHOG consumption in India: determinants and LQRXUဧXG\DUHD+RZHYHULQÀXHQFHRIFKHPLFDO RXWORRNIRUDUHYLHZ,QWHUQDWLRQDO-. of IHUWLOL]HU DORQH RU ZLWK ELRJDV VOXUU\ WUHDWPHQW 6FLHQWL¿F (QJLQHHULQJ DQG 7HFKQRORJ\ M1 and M3 UHVSHFWLYHO\ ZHUH ဧDWLဧLFDOO\ DW SDU with M2 in respect of nutrient uptake and yield. >@ )HUWLOLVHU $VVRFLDWLRQ RI ,QGLD )HUWLOLVHU 7KRXJKUHSRUWVDUHDYDLODEOHRQSRVLWLYHLQÀXHQFH 6WDWLဧLFV DQG (DUOLHU ,VVXHV 7KH RIYHUPLFRPSRဧDQGD]ROOD WUHDWPHQW04 and M5 Fertiliser Association of India, New Delhi, UHVSHFWLYHO\ ZH IRXQG VLJQL¿FDQWO\ OHVV QXWULHQW 2010. uptake and crop yield with their application. >@ 6 6DYFL ,QYHဧLJDWLRQ RI H൵HFW RI FKHPLFDO $]ROOD DQG YHUPLFRPSRဧ DUH QLWURJHQ ULFK DUH fertilizers on environment. APCBEE Procedia, preferentially degraded over carbon rich organic fertilizer such as FYM. Slow release of nutrient >@ '2 +HVVHQ $ +LQGDU * +ROWDQ for longer time with FYM application might have 7KH VLJQL¿FDQFH RI QLWURJHQ UXQR൵ IRU RXWSHUIRUPHG QLWURJHQ ULFK PDWHULDOV ,QWHJUDWLRQ eutrophication of freshwater and marine of these locally available fertilizer sources with UHFLSLHQWV $PELR GRPLQDQWFURSSLQJV\ဧHPKHOSHGXVWRLGHQWLI\WKH >@ 5%KDWHULD'-DLQ:DWHUTXDOLW\DVVHVVPHQW EHဧVXLWDEOHFURSSLQJSDWWHUQDQGIHUWLOL]HUVWREH RI ODNH ZDWHU D UHYLHZ 6XဧDLQDEOH :DWHU DSSOLHG IRU VXဧDLQDEOH DJULFXOWXUH DQG QHW UHWXUQ 5HVRXUFHV0DQDJHPHQW 7KLV ဧXG\ ZLOO DOVR KHOS SROLF\ PDNHUV WR PDNH >@ % 0RVV :DWHU SROOXWLRQ E\ DJULFXOWXUH FHUWDLQWRVXဧDLQDJULFXOWXUDOSURGXFWLRQRI,QGLD Philosophical Transactions of the Royal +RZHYHUIXUWKHUဧXG\LVUHTXLUHGWRXQGHUဧDQG 6RFLHW\ % %LRORJLFDO 6FLHQFHV possible nutrient dynamics and their uptake. 0LFURELDO GLYHUVLW\ ဧXG\ DQG LVRWRSH WUDFLQJ > @ *' $JUDZDO 'L൵XVH DJULFXOWXUDO ZDWHU WHFKQLTXH FDQ KHOS XV WR XQGHUဧDQG WKH FKDQJHV pollution in India. Water science and going on in soil upon application of these fertilizers. WHFKQRORJ\ 7KHVHဧXGLHVDOVRPDNHXQGHUဧDQGZK\VRPHDUH >@6.=DPDQ0-DKLUXGGLQ*03DQDXOODKL RXWSHUIRUPLQJ RWKHUV LQ WHUPV RI QXWULHQW XSWDNH M.H. Mian, M.R. Islam, Integrated nutrient and crop production. Studies may also be conducted PDQDJHPHQWIRUVXဧDLQDEOH\LHOGLQULFHULFH with other available nutrient sources, such as FURSSLQJ V\ဧHP ,Q th World Congress of VHZDJHVOXGJH À\ DVK IURP WKHUPDO SRZHU SODQW 6RLO6FLHQFH%DQJNRN 7KDLODQG DQG WKHLU LQÀXHQFH RQ FURS SURGXFWLRQ 21 Aug. >@0 $ULI 0 7DVQHHP ) %DVKLU * Table 1.,QLWLDOSK\VLFRFKHPLFDOSURSHUWLHVRIWKHH[SHULPHQWDOVRLO Particulars Sand (%) 36.8 Silt (%) 28.0 Clay (%) 35.2 Textural class Clay-loam Bulk density (g cm-3) 1.53 Soil pH 6.84 EC 0.24 Organic carbon (%) 0.66 Available N (kg ha-1) 147.84 -1 Available P2O5 (kg ha ) 18.24 -1 Available K2O (kg ha ) 125.25 273 P. Haldar et al. Annals of Agrarian Science 17 (2019) 266 – 276 Table 2.'HWDLOVRIWKHWUHDWPHQWVHPSOR\HGLQWKHH[SHULPHQW Vertical strips (Cropping system; C): C1 Rice –Rapeseed – Fodder cowpea C2 Rice – Field pea – Fodder cowpea C3 Rice – Wheat – Fodder cowpea Horizontal strips (Nutrient management; M): M1 100% Recommended dose of Fertilizers (RDF) through chemical fertilizer (CF) M2 75% RDN through CF +25% N through FYM+ 100% RD of PK through CF M3 75% RDN through CF +25% N through Biogas Slurry + 100% RD of PK through CF M4 75% RDN through CF +25% N through Vermicompost + 100% RD of PK through CF M5 75% RDN through CF +25% N through Azolla+ 100% RD of PK through CF Table 3.&KDQJHVLQQLWURJHQ 1 SKRVSKRUXV 3 DQGSRWDVVLXP . XSWDNH ZLWKGLৼHUHQWDJURQRPLFSUDFWLFHV WZR\HDUVSRROHGGDWD Treatments N uptake P uptake K uptake Grain N (kg ha-1) Straw N (kg ha-1) Grain P (kg ha-1) Straw P (kg ha-1) Grain K (kg ha-1) Straw K (kg ha-1) Cropping system C1 90.16 79.98 18.11 7.95 24.32 67.13 C2 93.86 82.75 19.78 9.81 25.59 72.22 C3 84.52 73.45 16.72 8.02 23.03 67.58 SEm ± 1.51 1.89 0.34 0.20 0.50 1.80 CD (p=0.05) 4.93 6.18 1.12 0.64 1.64 5.86 Nutrient management M1 96.21 85.11 19.62 9.83 25.33 74.05 M2 99.05 86.33 22.72 11.20 29.12 76.93 M3 98.72 88.13 21.09 10.52 28.08 76.81 M4 80.00 68.99 14.70 6.61 20.41 62.39 M5 73.59 65.05 12.89 4.80 18.62 54.69 SEm ± 3.69 2.14 0.83 0.35 0.94 2.47 CD (p=0.05) 11.07 6.41 2.48 1.06 2.83 7.39 274 P. Haldar et al. Annals of Agrarian Science 17 (2019) 266 – 276 Table.4.9DULDWLRQLQSDGG\\LHOGSDUDPHWHUDVLQÀXHQFHGE\YDULRXV DJURQRPLFSUDFWLFHV WZR\HDUVSRROHGGDWD Treatments Number Number of Panicle Panicle Grain Straw Harvest of panicle filled grain weight length yield (t yield (t index (%) m-2 panicle-1 (g) (cm) ha-1) ha-1) Cropping system C1 249 155 2.55 26.8 4.66 6.64 41.08 C2 267 163 2.65 27.2 4.74 6.77 41.10 C3 249 147 2.47 26.9 4.42 6.37 40.82 SEm ± 3.1 1.3 0.03 0.07 0.05 0.07 0.28 CD 10.2 4.3 0.11 0.24 0.15 0.24 NS (p=0.05) Nutrient management M1 264 168 2.63 27.2 4.84 6.96 40.89 M2 265 163 2.66 27.4 5.08 7.07 41.69 M3 267 163 2.66 27.2 5.01 7.15 41.08 M4 247 145 2.52 26.8 4.18 6.01 41.02 M5 231 134 2.33 26.3 3.91 5.77 40.33 SEm ± 4.9 3.4 0.05 0.17 0.17 0.12 0.53 CD 14.7 8.6 0.16 0.50 0.50 0.37 NS (p=0.05) Table.5.&RUUHODWLRQEHWZHHQ13.XSWDNHDQG\LHOGSDUDPHWHUV Filled Panicle Test Grain Straw N P K Panicle grain Panicle length Weight yield yield Harvest Uptake Uptake Uptake m-2 panicle-1 wt (g) (cm) (g) (t ha-1) (t ha-1) Index N Uptake 1.00 PUptake 0.94a 1.00 K Uptake 0.95a 0.93a 1.00 Panicle m-2 0.85a 0.86a 0.82a 1.00 Filled grain panicle-1 0.83a 0.85a 0.73a 0.84a 1.00 Panicle wt (g) 0.75a 0.76a 0.64a 0.80a 0.80a 1.00 Panicle length (cm) 0.63a 0.69a 0.70a 0.80a 0.54b 0.42 1.00 Test Weight (g) 0.76a 0.86a 0.75a 0.69a 0.71a 0.71a 0.53b 1.00 Grain yield (t ha-1) 0.98a 0.93a 0.96a 0.79a 0.77a 0.71a 0.62a 0.74a 1.00 Straw yield (t ha-1) 0.98a 0.93a 0.95a 0.80a 0.77a 0.72a 0.57a 0.74a 0.98a 1.00 Harvest Index 0.48b 0.49b 0.49b 0.42 0.40 0.32 0.58a 0.38 0.57a 0.39 1.00 µD¶DQGµE¶LQGLFDWHVVLJQL¿FDQFHOHYHODWS DQGUHVSHFWLYHO\ Q 275 P. Haldar et al. Annals of Agrarian Science 17 (2019) 266 – 276 Fig. 1a, b, c. Interaction effect between cropping sequence (C) and nutrient management (M) for N, P and K uptake respectively Fig. 2a, b. Interaction effect between cropping sequence (C) and nutrient management (M) for number of panicle m-2 and number of filled grain panicle-1 respectively Fig. 3a, b. Interaction effect between cropping sequence (C) and nutrient management (M) for panicle weight (g) and panicle length (cm) respectively Fig. 4a, b. Interaction effect between cropping sequence (C) and nutrient management (M) for grain yield and straw yield respectively 276 9=YLDGDXUL Annals of Agrarian Science 17 (2019) 277 – 285 Annals of Agrarian Science :ŽƵƌŶĂůŚŽŵĞƉĂŐĞ͗ŚƩƉ͗ͬͬũŽƵƌŶĂůƐ͘ŽƌŐ͘ŐĞͬŝŶĚĞdž͘ƉŚƉ On the approach to the complex research into the vibratory WHFKQRORJLFDOSURFHVVDQGVRPHIDFWRUVKDYLQJDQLQÀXHQFHRQWKH process regularity Viktor Zviadauri Dvali Institute of Machine Mechanics, 10, Mindeli Str., Tbilisi, 0187, Georgia Received: 15 June 2018; accepted: 12 September 2018 A B S T R A C T 9LEUDWRU\WUDQVSRUWDWLRQDQGWHFKQRORJLFPDFKLQHVDUHZLGHO\XVHGIRUWUDQVSRUWDWLRQDQGSURFHVVLQJRIWKHIULDEOHPDWHULDOVLQPDQ\ VSKHUHVRILQGXဧU\ DJULFXOWXUHPLQLQJLQGXဧU\FRQဧUXFWLRQHWF $WWKHVDPHWLPHPDQ\IDFWRUVLQÀXHQFLQJWKHSURFHVVDUHQRW WKRURXJKO\UHYHDOHG DPRQJWKHPLQÀXHQFHRIVRFDOOHGSDUDVLWLFYLEUDWLRQVRIWKHZRUNLQJPHPEHULVQRWဧXGLHGVX൶FLHQWO\$WKUHH PDVVYLEUDWRU\V\ဧHPDQDQDORJXHRIWKHYLEUDWRU\WUDQVSRUWDWLRQDQGWHFKQRORJLFV\ဧHP³YLEURGULYH±ZRUNLQJPHPEHU±WHFKQRORJLF ORDG´ZDVဧXGLHGKROLဧLFDOO\$UHOHYDQWPDWKHPDWLFDOPRGHORIWKHVSDWLDOLQWHUFRQQHFWHGYLEUDWRU\PRYHPHQWLVGUDZQXSLQWKHIRUP RIWKHGL൵HUHQWLDOHTXDWLRQV7KHUHDOSRVVLEOHUHDVRQVRIJHQHUDWLRQRIWKHVSDWLDOYLEUDWLRQVLQWKHPHQWLRQHGV\ဧHPVDQGSRVVLELOLW\RI WKHLULQÀXHQFHRQWKHWHFKQRORJLFSURFHVVDUHFRQVLGHUHG7KHLQÀXHQFHRIWKHFRQဧUXFWLRQDOHUURUVDQGUHVXOWLQJVSDWLDO QRQZRUNLQJ YLEUDWLRQVRIWKHZRUNLQJPHPEHURQWKHUHJXODULW\RIWKHIULDEOHPDWHULDOYLEUDWRU\PRYHPHQWLVဧXGLHGE\PDWKHPDWLFDOPRGHOLQJ 7KHUHVHDUFKHVKDYHVKRZQWKDWVRPHQRQZRUNLQJ VRFDOOHGSDUDVLWLF YLEUDWLRQVLQFRPELQDWLRQZLWKWKHEDVLFYLEUDWLRQVFDQLPSURYH WKHWHFKQRORJLFDOSURFHVVLQFUHDVHLQWHQVLW\RIPRYHPHQWRIWKHIULDEOHPDWHULDO7KHJUDSKLFDOLOOXဧUDWLRQVDUHSUHVHQWHG Keywords: 9LEUDWRU\ V\ဧHP 6SDWLDO YLEUDWLRQV 9LEUDWRU\ GLVSODFHPHQW 0DWKHPDWLFDO PRGHOLQJ )ULDEOH PDWHULDO 9LEUDWRU\ technology. &RUUHVSRQGLQJDXWKRU 9LNWRU=YLDGDXUL (PDLODGGHVV YB]YLDGDXUL#\DKRRFRP 1. INTRODUCTION The vibratory technologic processes are in fact the useful movements of the friable materials and single small parts under influence of vibrations: transportation, metered feeding, sorting, mixing and etc.[1-4]. The vibratory technologic machines and processes are widely used in metallurgy, construction, mining industry, agriculture, chemical industry and confectionaries [5-7]. A vibratory technologic process is a dynamically sensitive process in which participate many physically different components: vibro-drive, elastic system, working member (absolutely rigid or of finite rigidity), diverse friable loads. Dynamical interaction of these components stipulates behavior of the friable material on the working member surface. The mathematical models of vibratory transportation and technological processes presented in the existent researches [1, 2, 5] are mostly simplified. For example, non-linear excitation is replaced by harmonic vibrations; reaction of the material on the working member is provided by 277 9 =YLDGDXUL Annals of Agrarian Science 17 (2019) 277 – 285 so called coefficient of connection that is 1/3 of the whole mass; non-working vibrations that accompany vibratory technologic processes and have influence on them, are not often taken into account neither etc. Because of such approaches many nuances that could be important from the standpoint of influence on the process, are ignored. Consequently, the attempt is made in the work to create a more or less universal model, where more perfect mathematical description of the vibratory transportation and technologic processes of the friable materials and study of influence of various parameters on the process would be possible. 2. A DYNAMICAL MODEL Since a vibratory technologic process is in fact a vibratory movement of the system “vibro- drive – working member – technologic load” in space then it is evident that besides pre- determined working vibrations the working member and consequently technologic load can be subjected to non-working (spatial) vibrations [ 4, 8 ] not envisaged by the calculation. This in the first place concerns the spatial, so called parasitic vibrations of the working member that can be caused by various factors such as inaccuracy of transmission of the exciting force, errors of relative disposition of the vibratory machine units, elastic specificity and etc. In Fig.1 is presented a two-mass system “vibro-drive – working member” and are shown deviations of the working member caused by various possible errors: I – nominal (designed) position of the working member; II – position of the working member considering the errors including the eccentricities ex, ey, ez of displacement of the center of gravity from position O1 to ' pointO1 ;T 0 ,\ 0 , M0 - turnings of the coordinate axes caused by the assembly errors of the ' ' ' ' vibratory machine and transition from position O1 x1 y1 z1 to position O1 x1 y1 z1 (Fig.1 a, b); III – dynamical (working) position of the working member. System of coordinates Ov xv yv zv is connected to the vibro-drive; 1 – basic elastic system of the vibro-machine; 2 – suspensions of the vibro-machine; Q – exciting force; mv, m1 – masses of the vibro-drive and working member. Fig. 1. 7KH$YHUDJH&OLQLFDO,QGLFDWRUVRIWKH&RZV 278 9 =YLDGDXUL Annals of Agrarian Science 17 (2019) 277 – 285 In the Fig.2 are shown spatial schemes of the three-mass spatial vibratory system, a generalized dynamical model of the vibratory technologic system “vibro-drive – working member – technologic load” (Fig.2a), elastic system of the vibro-drive – working member (Fig.2c) and conventional elastic system of the technologic load (Fig.2b). At that, the latter imitating phenomenological properties of the friable material is restricted unilaterally by the working member surface. For full description of the spatial vibratory movement of the presented system it is expedient to use classical methods of relative movement of rigid bodies [8]. For this purpose a friction material (load) is presented as a rigid body in the form of cube where total mass of the load is located and which is provided with conventional elastic elements describing phenomenological properties and elastic and damping connections between layers as well as with surfaces of the working member [ 4, 9]. For obtaining general vector expressions of the kinetic energy of a body it is necessary to determine absolute movement of a free point of this body. Such points in Fig.2 are Ai (M1), Bi (M2), Ci (M3) that are connected to the origins of the own coordinate axes as well as to the origins of coordinate axes inertial relative to them. Besides, mass M3 is connected to mass M2 at the center of gravity (at the origin of coordinate system). Consider expressions of each component part of the three-mass system (Fig, 2a). Vector equations of absolute velocities of free points Ai, Bi, Ci of masses M1, M2 and M3 have the form: VAi V01 Z01 u r1i ; VCi V02 Z02 u r2i ; VVBi 01uuZZ 01 RV 3 i 03 03 r 3 i,( RRr 3 i 3 3 i )(1) Fig. 2. 7KUHHPDVVVSDWLDOYLEUDWRU\V\VWHP±DQDQDORJXHRIWKHYLEUDWRU\ WHFKQRORJLFV\VWHP³YLEURGULYH±ZRUNLQJPHPEHU±WHFKQRORJLFORDG´ 279 9 =YLDGDXUL Annals of Agrarian Science 17 (2019) 277 – 285 where V01, V02 are translatory velocities of the particles Ai and Ci ; r1i , r2i , r3i – position vectors of the particles Ai, Bi, Ci ; ZO1, ZO2, ZO3 – velocities of rotary movement of masses M1, M2 and M3; V03 – velocity of relative movement of mass M3; r1i , r2i , r3i - position vectors of points Ai, Bi, Ci relative to the origins of the proper coordinate axes. Consequently, the vector expressions of kinetic energies of masses M1, M2 and M3 will have the form (is shown kinetic energy of mass M1 only): n1 1 2 2 T1 ¦ M 1i [V01 (Z01 u r1i ) V01 (Z01 u r1i )] , (2) 2 i 1 where M1i, M2i, M3i are masses of the particles Ai, Bi, Ci . The vector expressions are converted into the analytical form with the help of the direction cosines and Euler’s angles [8]. Then they (T1, T2, T3) are reduced on the coordinate axes of the working member (M1). " " " " Kinetic energy of mass M1 relative to the coordinate system O1 x1 y1 z1 has the following form: . 2 . 2 . 2 . 2 . 2 1 1 2 2 2 2 T M (x1 y z1 ) [(J cos D J sin D )T 1 (J sin D J cos D )M 1 2 1 1 2 x1 1 z1 1 x1 1 z1 1 1 . 2 . . . . 2 2 J y1\ 1 ] (J x1 J z1 )sinD1 cos D1 T 1 M 1 (J x1 cos D1 J z1 sin D1 J y1 )T 1 \ 1 M1 . . . . (J J )cosD sinD T 1 \ T (J J )cosD sinD M \ M z1 x1 1 1 1 1 x1 z1 1 1 1 1 1 (3) . . 2 2 (J x1 sin D1 J z1 cos D1 )M 1 \ 1 T1; where x1, y1, z1,T1,\ 1,M1 are linear and angular displacements of the center O2 of mass M2; J x1, J y1, J z1 - moments of inertia of mass M2 about axes O1 x1 y1 z1 . Similar forms will have kinetic energies of masses M2 and M3. 3. EQUATIONS OF SPATIAL MOVEMENT OF THE WORKING MEMBER AND TECHNOLOGIC LOAD The main difference between the system under research – vibratory technologic machine and classical n-mass system is stipulated by the following aspects: 1) Specificity of mass M3 (load) performing relative movement with respect to mass M1; 2) Predetermined location relative to each other of masses M1, M2, M3 (vibro-drive, working member, load); 3) Pecularity of interaction of masses M1 and M3. On the base of method of Lagrange we obtain the following differential equations of spatial movement of the system d wT wT ' ( . ) Qq Qq ,(4) dt w q wq where T is the system kinetic energy; q – generalized coordinate that takes the values x1 , y1 , z1 ,T1 ,\ 1 ,M1; x2 , y2 , z2 ,T 2 ,\ 2 ,M 2 ; x3 , y3 , z3 ,T3 ,\ 3 ,M3 ; Qq - elastic and resistant forces ' stipulated by the machine elastic and damping system; Qq - forces that are not related with deformations of the elastic system or inertness of masses of the vibratory system under consideration (external exciting forces, forces of gravity, external forces resistant forces of the friction type and etc). 280 9 =YLDGDXUL Annals of Agrarian Science 17 (2019) 277 – 285 For illustration of the proposed approach consider a vibratory feeder with electromagnetic vibro- exciter (Fig.3) and its mathematical model with some assumptions. Namely, influence of the material on the working member dynamics will not be taken into account (kinetic and potential terms in the working member equations are presented in the linear form in contrast to the equations of the load, where kinetic terms are presented by the products of second order of the working member coordinates, their velocities and accelerations). The research considers influence of the machine design errors and non-working spatial vibrations on the friable material vibratory movement. Fig. 3. The errors of the force transmitted to the working member The equations of the working member will have the form .. . ' M 1 x1 cx x1 k x x1 k xT1 Qf (\ 0 ,\ 1 ,D1 ); .. . ' M 1 y1 c y y1 k y y1 k y\ 1 Qf (M0 ,M1 ,T 0 ,T1 ,D1 ) .. . ' M 1 z1 cz z1 k z z1 k zM1 Qf (\ 0 ,\ 1 ,D1 ) 5 .. . ' JT T 1 cT T 1 kTT1 kT x1 Qf (ey ,ez ,T 0 ,\ 0 ,M0 ,D1 ) .. . ' J\ \ 1 c\ \ 1 k[T1 kT y1 Qf (ex ,ez ,\ 0 ,D1 ) .. . J M c M k M k ' z Qf (e ,e ,T ,\ ,M ,D ) M 1 M 1 M 1 M 1 x y 0 0 0 1 where ccccccxyz,,,,,T\M, Qq are coefficients of damping of the elastic system; ' ' ' ' ' ' k x , k y , k z , kT , k\ , kM - coefficients of rigidity; k x ,k y ,k z ,kT ,k\ ,kM - coefficients relating lateral-rotary and longitudinal-torsional vibrations; Q = Q0 f (t), Q0 – coefficient of the exciting forcr; f (t) – regularity of variation of the exciting force. Spatial vibratory movement along the coordinate axes will have the following form ...... M 3[y 3 y1 (z1 T1 x1 M1 )cos a1 (x1 T1 z1 M1 )sin a1 T1 z3 2T 1 z 3 ...... ' 2M 1 x 3 x1 (M cos a1 T 0 sin a1 ) z1 (T 0 cos a1 M0 sin a1 )] B y 3 C y3 6 . fN z sign(y 3 ); ...... M 3[z 3 (z1 x1 \ 1 )cos a1 (x1 z1 \ 1 )sin a1 T1 y1 y3 T 1 2 y 3 T1 ...... ' 2 x 3 \ 1 z1 \ 0 sin a1 x1 \ 0 cos a1 y1 T 0 ] D1 Z 1 E x1 E z 3 Cz3 . fN y sign(z 3 ) M 3 g cos a1 , 281 9 =YLDGDXUL Annals of Agrarian Science 17 (2019) 277 – 285 where coefficients A, B, B1, C”, D, E, E1, C characterize state of the load relative to the working member surface (movement together with the surface or separately from it) and vary properly; . . . . N z f (z3 , z 3 , z1 ) , N y f (y3 , y 3 , y1 ) - forces of the material normal reaction whose coefficients vary similarly to the above mentioned. Equations (6) differ from generalized equations of the material spatial movement [4] by the terms generated from the errors of T\000,, M. ' Qx1 Q(x,t); (7) where Q(x,t) is a nonlinear exciting force; . 2 Q A) ; ) BF1 (t) C(G x1 )) ; Ɏ– electromagnetic flow; A, B, C - coefficients depending on parameters of the electromagnetic vibro-exciter; į – clearence of the electromagnet. The system of equations was solved by the method of Runge-Kutta in the following limits of errors: for angular deviations T 0 ,\ 0 ,M 0 = ( 0 - 0,15) rad; for deviations of the force direction ex , ey ,ez = (0 – 0,015) m. For greater visualization of influence of the mentioned deviations on the process the vibrations were enhanced in one concrete direction or another by resonating with the exciting force (in combination of variation of the errors). Below are given some results of the modeling (Fig. 4-7), where are shown dependences of the material velocity V and other dynamical characteristics (z3, y3, Nz , Ny) on the non-working vibrations (y1, M1, z1, \ caused by the working member design errors (T 0 ,\ 0 ,M 0 , e0 , e0 ,e0 ). Fig. 4. 'HSHQGHQFHVRI9DQG]3RQT 0 ,\ 0 ,M 0 DQG\. 282 9 =YLDGDXUL Annals of Agrarian Science 17 (2019) 277 – 285 Fig. 5. 'HSHQGHQFHVRI9]3 N]DQG1\RQT 0 ,\ 0 ,M 0 DQG e , e ,e Fig. 6.'HSHQGHQFHVRI9DQG]3RQ x y z DQG] Fig. 7. 'HSHQGHQFHVRI9\3DQG]3RQ ex , ey ,ez DQGȥ 283 9 =YLDGDXUL Annals of Agrarian Science 17 (2019) 277 – 285 4. DISSCUSION The design and assemblage errors in the vibratory transport and technologic machines (especially in the resonant ones) can cause a significant distortion of conformity with a law of the technologic process. Development of the spatial dynamical and corresponding mathematical models of the vibratory technologic system (vibrator – working member – load) was considered expedient for complex study of this problem. The obtained mathematical model is universal and it ensures complex research into the technologic process. The results of influence of the spatial (non-working) vibrations (Fig.2) and eccentricity caused by the improper transfer of the force (Fig.3) on the process of vibratory displacement of the friable material are presented in the work. The approach to the research envisaged enhancing of each non-working (“parasitic”) spatial vibration at retaining other vibrations in the admissible limits. As the results of modeling have shown, in most cases, the non-working vibrations have a negative influence on the velocity of the material displacement (Fig. 4, 6, 7) but in some cases, increase of velocity takes place (Fig 5). It should also be noted that non-working spatial vibrations have a significant influence on the material displacement in the vertical direction (z3) (Fig.4, 5, 6, 7) or on the intensity of displacement. The analysis of the research results have shown that improvement of the vibratory technologic process is mainly possible by combination of the basic working vibrations and some non-working, so called parasitic vibrations that implies design changes of the vibratory machine and will present the subject of the author’s further research. 4.1. CONCLUSION 1. The considered approach and a mathematical model of spatial movement of the system “vibro-drive – working member – friable load” allows to realize complex research into the vibratory technologic process by the mathematical modeling; 2. Design errors of the vibratory transportation technologic machine have an influence on the process that is more expressed in the resonant machines; 3. The errors at their certain combination can promote improvement of the process indices (velocity for example, Fig.5) that may be realized in the machine. Acknowledgements This work was supported by Shota Rustaveli National Science Foundation of Georgia (SRNSFG) [ N FR17_292, “Mathematical modeling of the vibratory technologic processes and design of the new, highly effective machines” REFERENCES [1].I.I. Blekhman, Theory of Vibration Processes and Devices. Vibration mechanics and vibration technology, Ore and metals, SPB, 2013 (in Russian). [2]. I. Goncharevich. Theory of Vibratory Technology. Hemisphere Publisher, 1990 (in Russian). [3].I. I. Fedorenko, Vibration processes and devices in the agroindustrial complex: monograph. RIO of the Altai State University, Barnaul, 2016 (in Russian). http://www.asau.ru/ru/mekhanizatsii-zhivotnovodstva?task=getfile&fileid=15612. [4].V. Zviadauri. Dynamics of the vibratory transportation and technological machines; “Mecniereba”, 2001(in Russian). [5].L.Vaisberg, I. Demidov, K. Ivanov, Mechanics of granular materials under vibration action: Methods of description and mathematical modeling. Enrichment of ores. ʋ 4 (2015) 21-31. 284 9 =YLDGDXUL Annals of Agrarian Science 17 (2019) 277 – 285 http://rudmet.net/media/articles/Article_OR_04_15_pp.21-31_1.pdf (in Russian). [6].V. S. Zviadauri, T. M. Natriashvili, G. I Tumanishvili, T. N. Nadiradze, The features of modeling of the friable material movement along the spatially vibrating surface of the vibratory machine working member. Mechanics of machines, mechanisms and materials, 1 (38), (2017) 21-26 (in Georgian). [7].V. S. Zviadauri, M. A. Chelidze, G. I. Tumanishvili, On the spatial dynamical model of vibratory displacement, Proceedings of the International Conference of Mechanical Engineering; London, U.K., 30 June - 2 July, (2010) 1567 – 1570. [8].R. Ganiev, V. Kononenko, Oscillations of solids. M. Nauka, 1976 (in Russian). http://stu.scask.ru/book_cst.php. [9].O. G. Loktionova, Dynamics of vibratory technological processes and machines for the processing of granular materials, Dissertation, 2008 (in Russian). http://www.dissercat.com/content/dinamika-vibratsionnykh-tekhnologicheskikh-protsessov- i-mashin-dlya-pererabotki-neodnorodnyk. 285 GUIDE FOR AUTHORS Papers to be published in “Annals of Agrarian WH[W 7DEOHV PXဧ EH WLWOHG 6FLHQFH´PXဧPHHWWKHIROORZLQJUHTXLUHPHQWV $OOWKH)LJXUHVDQG7DEOHVPXဧEHWLWOHGDQG lined vertically. 1 . $SDSHUPXဧGHDOZLWKDWHPSRUDU\SUREOHP :RUGVLQ7DEOHVPXဧQRWEHDEEUHYLDWHG PHWKRGV RI LQYHဧLJDWLRQ DQG DQDO\VLV RI $UUDQJHPHQW RI ¿JXUHV LQ OLQHV PXဧ EH WKHUHFHLYHGGDWD7KHWLWOHRIDSDSHUPXဧ GLဧLQFW FRPSOHWHO\UHÀHFWLWVFRQWHQW7KHဧUXFWXUH 7KH VDPH GDWD PXဧ QRW EH UHSHDWHG LQ RI D SDSHU PXဧ EH ဧDQGDUGL]HG E\ WKH WDEOHV JUDSKV DQG D WH[W IROORZLQJVXEWLWOHV ,QWURGXFWLRQ2EMHFWLYHV $UUDQJHPHQWRILOOXဧUDWLRQV DQG0HWKRGV([SHULPHQWDO6HFWLRQ5HVXOWV 3LFWXUHVDQGSKRWRVPXဧQRWEHJOXHGWKH\ and Analysis, Conclusion, References. 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