Cenchrus purpureus. Key words: qualitative traits. and UPGMA methodsforboththequantitative and formation ofsimilaritygroupsby Tocher’s optimization genetic divergences among the genotypes and allowed the methods. Therefore, themultivariatetechniqueindicated traits, however, the genotypes formed 10 groups for both groups when analyzed byUPGMA.Forthe qualitative according to Tocher’s optimization method and to 13 traits, the 85 genotypes analyzed belonged to 17 groups blocks, withtworeplicates. Based onthequantitative The experimentaldesignwasarrangedasrandomized Minas Gerais,Brazil,wereincludedintheexperiment. Bank ofEmbrapa Dairy Cattle, in Coronel Pacheco, donated bythe Active ElephantGrassGermplasm de Janeiro,Brazil.Eighty-fiveelephantgrassgenotypes Río Goytacazes, dos locatedinCampos at Pesagro-Rio, State CenterforResearchonBioenergy and Waste Use evaluations. The experiment was implemented in the using quantitative and multi-category traits in 2yrof group methodwitharithmeticaverages(UPGMA), Tocher’s clusteringmethodandbytheunweightedpair the diversity among 85 genotypes of elephantgrass by breeding programs. Thus, this study aimed to evaluate the identification ofgenotypes that can be used in the country. The knowledge of genetic diversity allows needs genotypes adapted to different ecosystems of energy. ItiswidelycultivatedinBrazil,howeverit Morrone) hasbeenusedasanalternativesourceof ( Elephant grass ABSTRACT doi:10.4067/S0718-58392017000100006 Accepted: 8February2017. Received: 19July2016. * Rio deJaneiro,Brasil. 2 dos Goytacazes,28035-200RiodeJaneiro,Brasil. 1 quantitative andmulti-category traits for energetic production basedon Maria doS.B.Araujo Avelino dosS.Rocha María L.F. Oliveira ( Genetic diversity ofelephantgrass Corresponding author([email protected]). Universidade FederalRuraldoRiodeJaneiro,23890-000Seropédica, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos Cenchrus purpureus Cenchrus CHILEAN JOURNAL OF AGRICULTURAL RESEARCH 77(1)JANUARY Bioenergy, Cenchrus purpureusCenchrus 1 , Rogério F. Daher 1 1

, Telma N.S.Pereira characterization, , Niraldo J.Ponciano CHILEAN JOURNAL OF AGRICULTURAL RESEARCH 77(1)JANUARY (Schumach.)

1 germplasm, , BrunaR.S.Menezes 1 , andVerônica B.Silva [Schumach.]Morrone) 1 , Antônio T. Amaral Junior -

MARCH 2017 of discretevariation,for2yr. agronomic traits of continuous variation, and 14 qualitative traits clustering method andbyUPGMA, using 10quantitative the diversity among 85 accessions of elephant grass by Tocher’s et al.,2014). optimization, associated withtheMahalanobis distance(Oliveira genotypes is the geneticdiversityamongelephantgrass Tocher’s accessions (Limaetal.,2011). Another methodusedtoquantify be used instudies of genetic diversity among elephant grass Averages (UPGMA)providesconsistentinformationthatcan genotypes insegregatinggenerations(Cruzetal.,2012). on theprogenyandahigher probability ofrecoveringsuperior parents, which, when crossed, generate a greater heterotic effect the of identification for parameters provide can data such because diversity amonggenotypesinthegermplasmbankisimportant, (Paiva et al., 2014). The knowledge of the degree of genetic to estimatethegeneticdiversityanddifferentiate genotypes breeding programs(CavalcanteandLira,2010). to reveal genotypes with the best traits of interest for genetic identification andevaluationingermplasmbanksarenecessary the year (Oliveira et al., 2012). Thus, morein-depthstudiesonthe growth speed and lower seasonality of biomass production over of elephant grass adapted to different ecosystems with a faster renewable energy production(Moraisetal.,2009). productivity. Forthesereasons,itisalsobeingexploitedfor high plantbiomassproduction,rapidgrowth,lowcost,and 2009; Limaetal.,2010),inadditiontobeingaspecieswith researchers forservingasafeedstuff foranimals(Valle etal., et al.,2011). This specieshasarousedtheinterestofmany (Quéno country the of regions geographical five the in cultivated subtropical Africa and arrived inBrazil in 1920.It is currently Elephant grass( INTRODUCTION Agroenergy and Waste Use at Pesagro-Rio,locatedinCampos dos The experimentwascarriedout attheStateCenterforResearchon region Location and climatic characteristics of the MATERIALS AND METHODS Given theseaboveconsiderations, thisstudyaimed to evaluate The UnweightedPair-Group Methodusing Arithmetic Easily detectablequantitativeandqualitativetraitsareused There is a need for producing genetically improved cultivars 2* , Marcelo Vivas 1 - MARCH 2017 1 Cenchrus purpureus , 1 , Schum.) originated inthe

48 RESEARCHRESEARCH CHILEAN JOURNAL OF AGRICULTURAL RESEARCH 77(1)JANUARY plot; b)plantheight(PH,m)measuredwithagraduated per linear meter (NT) was counted in one linear meter per whole-plant samplesinallaccessions:a)numberoftillers experiment after each year of continuous growth, analyzing for aperiodof2yr. and thesecondinNovember2012,i.e.oneharvestperyear The fistharvestforanalysisoccurredinNovember2011, genotypes were cut near the soil level (plot-leveling cut). used measured1m. near theexperimentalarea duringtheexperiment. Table 1.Precipitationcollected dataorganizedintomonths, corresponding to28.6kgNand24K 70 gurea and 40gKCl (potassium chloride) perrow, after planting the cover fertilization was performed using 60 gofsinglesuperphosphatewereapplied,and50d stems, distributed into 10 cm-deep furrows. Inthe planting, were plantedon23and24February2011, usingwhole Pacheco, Minas Gerais, Brazil (Table 2). The genotypes BAGCE) ofEmbrapaDairyCattle,located inCoronel Bank (Banco Ativo de Germoplasma de Capim-Elefante, grass, donated bythe Active Elephant Grass Germplasm The experimentcomprised85genotypesofelephant agronomic traits Experimental conditionsandmorpho- with thefollowingproperties:pH,5.5;18,mgP dm precipitation around1152 mm(Table 1). type, withdrywintersandrainysummersanannual system, theclimatein the regionisan Aw, hothumidtropical de Janeiro,Brazil. According totheKöppenclassification Goytacazes (21°19’23” S, 41°19’40” W; 20-30 m a.s.l.), Rio K dm of a 5.5m rowwith 2m spacing, totaling 11 m blocks with two replicates. The experimental plot consisted oxide) perhectare. dm Bioenergy and Waste UseatPesagro,Rio,Campos dos Goytacazes,Brazil. Source: EvapotranspirationStation ofStateCenterforResearchon Total mm September November December Morpho-agronomic traits were evaluated throughout the After theestablishment phase, on15December2011, all The soil is classified as a as classified is soil The 2006), (Embrapa, Latosol Yellow The experimentaldesignwasarrangedasrandomized -3 February October January August Month March ; H+ Al, 4.5cmol April June May July -3 ; 4.6cmol 2012 Precipitation c Cadm 21.6 14.2 73.6 781.1 10.4 133.7 12.5 5.9 74.0 147.2 59.8 216.5 11.7 c mm dm -3 ; 3.0cmol -3 ; and1.6%C. September November December February October January August Month March April Total June May July c Mgdm 2013 2 -3 O (potassium ; 0.1cmol Precipitation 2 125.7 . The plot . The 45.2 103.2 230.2 44.3 907.8 158.4 26.4 67.1 8.7 41.6 57.0 -3 - MARCH 2017 ; 83 mg ; 83 - c Al of eachgenotypeonthe3 cm) measuredusingagraduatedrulerinthreesamples caliper; d) leaf width andlength (LW andLL, respectively, taking theaverageofthreemeasurements,usingadigital (SD, cm) measured approximately 10 cm above the soil, ruler, takingonemeasurementperplot;c)stemdiameter Y prostrate leaves(60to90°). 1 erectleaves(0to30°),2semi-erect leaves (30 to60°),3 3 highly pilose; e)leaf angle (LA) inrelation to the stem: (hair) ontheleaf sheath(TLS):1glabrous,2lightlypilose, light green, 2dark 3 purple; c) density of trichomes open, 3erect;b)overallcolorofplantsintheplot(PC):1 1open,2semi- values: thefollowing (TF) canassume as described byDaher et al. (1997): a) the tussock form The followingdiscretequalitativetraitswereevaluated growth ageoftheplantswouldnotinterfereinresults. thattheadvanced so at6-mogrowth takeninplots were was measuredintheplotsat12-mogrowth;allothers Of the multi-category traits, only the tussock form (TF) traits Discrete qualitative (multi-category) to the following model: to thefollowing traits ineachvariableand in eachevaluationaccording A simple ANOVA was performed for the quantitative Statistical analysis to 55%),3littleflowering(26%). (75% flowering partial 2 100%), to (81.5% flowering fully at theendofreproductiveperiod(Harvest2:2013): 1 little flowering(9.5%to33%);b.2)percentageof 3 45%), to (60% flowering partial 2 (100%), flowering fully at theendofreproductiveperiod(Harvest1:2012): 1 flowering percentage of 1) b. d); 183 to (168.5 late 4 d), 166 (122 to134d),2early(138152.53regular(156 to appearance of10%flagleaf(Harvest2:2013):1superearly 173.5 d),4late (178 to209d);a.2)numberofdaysforthe (104 to124d),2early(1311453regular(147.5 appearance of10%flagleaf(Harvest1:2012):1superearly were classified asfollows: a.1)number ofdays forthe clustering was performedat 5%, and then all accessions of variance (ANOVA) wasconducted and the Scott-Knott’s analysis an data, these From genotype. each of florescence total the days, flowering the of end the at and, leaf flag 10% was determined how manydayseach accession tooktoemit Subsequently, accession. each in it leaves flag of percentage quantify onceweekly the percentage of flowering and the at theendofreproductiveperiod.Itwasnecessaryto flowering of percentage and leaf flag 10% of appearance the The phenological traits evaluated were number of days for Phenological traits average ofeachparameterwascalculatedseparately. considering thewidest partoftheleaf. Subsequently, the meristem to the root basal meristem; LW was measured ij represents the observation of genotype Y rd ij fullleaffromthestemapical = m +G =m i +B i in block j +e ij , where i ; m ;

49 CHILEAN JOURNAL OF AGRICULTURAL RESEARCH 77(1)JANUARY the effect of block generate thedendrograms. (Cruz et al., 2012), and UPGMA were carried out to distance, the clustering by Tocher’s optimization method the clusteringtechniquebasedonmeanEuclidean quantify thegeneticdivergence amongindividuals, were performedonGENESsoftware(Cruz,2013). To qualitative (multi-category) traits. All ofthese analyses Mantel testwereusedforbothquantitativeanddiscrete correlation of quantitative and qualitative matrices by the Euclidean distance, Tocher’s method, UPGMA, and the error associatedwithobservation variable; represents anoverallconstantassociatedwiththisrandom BAGCE), CamposdosGoytacazes,RiodeJaneiro, 2012-2013. Table 2.Genotypespresent inthe (Banco Active ElephantGrassGermplasmBank Ativo deGermoplasmaCapim-Elefante 43 42 IAC-Campinas 41 40 Vrukwona 39 38 37 36 Turrialba 35 34 33 32 Teresopólis 31 30 Napier 29 28 27 Mineiro 26 25 24 23 22 21 20 19 18 17 16 15 14 13 Albano 12 11 10 9 8 7 6 5 4 3 2 1 Nº Elefante CachoeiraItapemirim P241 Piracicaba Taiwan A-121 Cameroon -Piracicaba Taiwan A-146 Mercker ComumPinda Duro de Volta Grande Taiwan A-46 Mercker Comum Porto Rico Mole de Volta Grande Elefante dePinda Pusa NapierN1 Taiwan A-143 Napier S.E.A. Taiwan A-144 Mercker 86México Mercker PindaMéxico Mercker Pinda Cubano Pinda Costa Rica Elefante Híbrido534-A Pusa GiganteNapier Hib. GiganteColômbia Taiwan A-25 Porto Rico534-B Taiwan A-148 Mercker S.E. A Napier N2 Gigante dePinda Pusa NapierN2 Mercker SantaRita Napier Volta Grande Três Rios Mercker Elefante daColômbia G i representstheeffect ofgenotype Genotype

j ; and

e ij represents the experimental Y . Subsequently, themean i ; B Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Colombia India Brazil Brazil Brazil Colombia Brazil Brazil Brazil Costa Rica Brazil India Colombia Colombia Brazil Brazil Brazil Brazil Brazil Brazil India Brazil Brazil Brazil Brazil Colombia j Origin represents - MARCH 2017 Nº 85 84 União 83 82 81 80 79 78 77 76 75 74 73 72 71 70 69 68 67 Ibitinema 66 CAC-262 65 Goiano 64 63 62 61 60 59 58 Napierzinho 57 Guacu 56 CPAC 55 Cameroon 54 53 52 51 50 Cuba-169 49 Cuba-116 48 Cuba-115 47 Guaco/I.Z.2 46 Roxo 45 Gramafante 44 Pinda) and69 (13 AD). 18(Cubano were (2.8425) accessions distant and themost A-144 (accession22)andNapier S.E.A (accession 23), most geneticallysimilaraccessions (0.2521)were Taiwan Napierzinho (58),and IJ7136cv. EMPASC 307(62). The follows: Cubano Pinda (18), Teresópolis (32),CPAC (56), (13, 14,15,16,and17),containingonlyonegenotype, as as the second largest. Another five groups were formed was represented by 16 genotypes (18.82%), and was ranked its composition: 29;i.e.34.12%oftheaccessions.Group2 (Table 3). Group1hadthe largest number of accessions in 16 groupswereformedforthe85elephant grass genotypes in variables thecontinuous Using Tocher’s optimization, morpho-agronomic traits Cluster analyses basedon quantitative RESULTS ANDDISCUSSION Pesagro Bord IRI 08 AD IRI 02 AD IRI 03 AD IRI 13 AD IRI 04 AD IRI 01 AD IRI 06 AD IRI 05 AD IRI 11 AD IRI 09 AD BAG -92 Pasto Panamá IRI 07 AD IRI 10 AD 13 AD ou Australiano 903-77 IJ 7141cv. EMPASC 306 IJ 7139 IJ 7136cv. EMPASC 307 IJ 7127cv. EMPASC 309 IJ 7126cv. EMPASC 310 IJ 7125cv. EMPASC 308 Vruckwona Africano Mineirão IPEACO Roxo Botucatu King Grass Capim CanaD’África Genotype Origin Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Panamá Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Cuba Cuba Cuba Cuba Brazil Brazil Brazil Brazil Origin

50 CHILEAN JOURNAL OF AGRICULTURAL RESEARCH 77(1)JANUARY accessions, wasusedasacriterion for formation of groups amongthegenerated bythemeanEuclideandistance (Leão etal.,2011). belongingtodifferent parents with groups dissimilarity on thesegregatinggenerations,soitshouldbeperformed (crossing), one expects to obtain maximal heterotic effect (Campos etal.,2010; Silva et al., 2013).In interbreeding be agreataccumulationofgenotypesinsinglegroup always a synonym of high variability, because there may have demonstratedthatthenumberofgroupsformedisnot division ofthe accessions among groups.Other studies of theaccessions,indicating genetic variabilityand good 30 groups, with the largest concentrating only 30.14% by quantitativemorpho-agronomictraitsandobtained evaluated thegeneticdiversityof136accessionsgrape Similar results were found by Leão et al. (2011), who the satisfactorydistributionofaccessionsamonggroups. revealed bythelarge numberofgroupsformedandby among theaccessionsofthiscollection,whichwas grass, inCamposdosGoytacazes,RiodeJaneiro, Brazil,2012-2013. Table 3.Cluster analysisby Tocher’son themeanEuclidiandistancefor optimizationmethodobtainedbased 85genotypesofelephant genotypes ofelephantgrass,inCamposdosGoytacazes,Rio de Janeiro, Brazil,2012-2013. Figure 1.Dissimilarity dendrogram basedonthequantitativetraitsdissimilarity matrixobtainedbytheUPGMA methodfor 85 Group

17 12 11 10 9 8 7 6 5 4 2 3 1 16 15 14 13 The UPGMA method,basedonthedissimilaritymatrix It canbestatedthatthereisawidegeneticdiversity 56 47 79 43 31 67 50 20 44 13 22 58 62 32 18 3 1 49 80 68 73 70 84 60 55 17 23 15 4 83 69 85 19 42 81 24 61 57 25 63 82 5272 34 1012 77 21 38 40 7 28 46 4836 71 11 14 37 74 65 165164 75 547653 - MARCH 2017 Genotype 41 66 27 A studyevaluating53accessionsofthisplantshowedthe has already been applied in several crops, such as cassava. EMPASC 307(62)and Teresópolis (32),respectively. (9 and10)comprisingonlyoneaccession:IJ7136cv. Filho etal.,2010). The dendrogramalsoshowedtwogroups usually composedofalarge numberofaccessions(Gomes The groupsthatgatheredpairswithshorterdistancesare of thetotal,followedbygroup2,with17genotypes(20%). the largest 28,representing32.95% numberofaccessions 2010; Monteiroetal.,2010). different cutoff point(Rochaetal.,2009;Campos point is thus subjective, and each analysis can indicate a should occuratapointofsuddenchangelevel;thecutoff the number of genotypes for each group in the dendrogram Cruz etal.(2012)argued that the cutoff pointthat delimits on axis yat 58%relative distance among the accessions. the formation of 13distinct groups, considering the harvest genetic diversity amongthe85accessionsstudieddue to in the dendrogram (Figure 1),which shows that there is The UPGMA analysisbasedoncontinuousvariables From left to rightin the dendrogram, group 6 contained 2 45 30 26 39 33 59 5 29 9 6 8 78 35

51 CHILEAN JOURNAL OF AGRICULTURAL RESEARCH 77(1)JANUARY leaf lengthin both harvests,mediumvalues forleafwidth both harvestsandforplantheight inharvest2. elevated value onlyfornumberoftillers per linear meter in of tillersinharvest2,whereas thesecondshowedan genotype showed ahighvalue only forthe variable number cv. EMPASC 307and Teresópolis, respectively. The first and leafwidthinharvests12. number oftillersperlinearmeterandleaflengthinharvest 2, in harvest 1,stem diameter and plant height in harvest 1, forstemdiameter values thelowest with of accessions lengths, bothinthetwoharvests.Group8wascomposed leafwidths and 1),andthelowest diameters (bothinharvest tillers inharvest2,thegreatestplantheightsandstem numbers oftillersinharvest1,thelowest of harvests 1and2. height andstemdiameterinharvest1leaflength genotypes from group 6 had the lowest values for plant and lowestleafwidthslengthsinbothharvests. The lowest plantheightsandstemdiametersinharvest1, numbers oftillersperlinearmeterinharvests1and2, and lowerleafwidthsinharvest2. lengths inharvest1,loweststemdiameter in bothharvests, plant heightsinharvest2,lowestandleaf with thehighestnumbersoftillersinharvest1, and leaf blade in harvest 1. Group 4comprised genotypes tillers perlinearmeter, leafwidth(bothinharvests1and2), height and stem diameter in harvest 2 and lowest number of in harvest2. in harvests1and2,lowestleafwidthslengths,both harvests 1and2,lowestnumbersoftillers per linear meter in group 2, however, had the greatest plant heights in of tillers per linear meter in harvests1and2. The genotypes and 2,lowestleaflengths in harvest2,andlowestnumbers plant heightsinharvest2,lowestleafwidthsharvests1 group 1 comprised the genotypes that displayed the greatest Gonçalves etal.,2008;Neitzke2010). formation oflessthanfivegroups(Bentoetal.,2007; evaluations withmorethan15accessionsshowedthe formed in demonstrated bythelownumberofdissimilaritygroups not welldistributed. is diversity genetic that demonstrating 2012), al., et Quintal were concentrated2010; in only one group (Campos et al., two above-mentioned studies more than 50% of the accessions distribution of the genotypes into the groups, given that in the the number of groups formed; however, it differs as by the are proportionally similar tothe currentstudyregarding Theseresults2012). al., et (Quintal formed were groups and in another study with 46 accessions of papaya, seven formation ofeightdissimilargroups(Camposetal.,2010), The genotypes fromgroup11 displayed a highvalue for Groups 9 and 10 comprised only one genotype: IJ7136 fromgroup7containedthehighestThe accessions Group 5wasrepresented bygenotypes with the highest Group 3wasformedbythegenotypesofgreatestplant Of the13groupsformedindendrogram(Figure1), However, was thelowdiversity inotherstudies, Capsicum ssp. andtomato,inwhichthe - MARCH 2017 to theothers,such asplantheightinharvests 1and2,leaf with lessthan0.70%showed littlecontributioninrelation respectively) (Table 4). However, variables that contributed together, contributed with over80%(33.50% and54.55%, of tillersperlinearmeterin 2012andin2013,which, (Singh, 1981),fortheformation ofgroups,werenumber most in the division ofgenotypes, bySingh’s approach thatcontributedmethod andthedendrogram,variables (Campos etal.,2010). the visualizationofmoresimilaraccessionswithingroups UPGMA featuresamorecomplexformation,allowing UPGMA inotherwords, eachaccession; discriminating with Tocher’s techniquediscriminatingeachgroupand provides amoreefficient supportforthedivergence, 2010). Thus, coupledwith Tocher’s method,UPGMA (Bento et al., 2007; Campos et al., 2010; Monteiro et al., of accessions between Tocher’s optimization and UPGMA of groups formed (Sobral et al., 2012) and in the clustering Tocher’s optimizationandUPGMA methods. a certainagreementinthe formation ofgroupsbetween Tocher’s optimization method. Overall, this demonstrates in onlyappearedisolated 18,58,and56,which genotypes both Tocher’s optimization and thedendrogram,exceptfor other groups,belongingtosinglewerethesameby that did not have enough similarity to form groups with two accessions belonged to other groups. The genotypes groups 1and2by Tocher’s optimization method; however, group, comprisedmainlythe accessions belongingto groups. Group 2, in the dendrogram, the second largest optimization; onlyfiveaccessionsbelongedtotheother group 6,belongedtogroups1and6by UPGMA, Tocher’s Most accessions that were part of the largest group of formed and the number of groupswith only one accession. was someagreementregardingthenumberofgroups with thoseformedby Tocher’s optimizationmethod,there diameter andnumberoftillers. yield in oneofthe harvests forevaluation, followed by stem height wasthevariablethatmostinfluencedtraitDM elephant-grass genotypes,theauthorsobservedthatplant a studyconductedevaluated byMenezesetal.(2014),who In grass forenergy2014). biomass production (Rossi et al., the percentageorashincreases,whichisdesirableinelephant correlated withtheashcontent;i.e.,asdiameterisreduced (Oliveira etal.,2013). The stemdiameterisalsonegatively influenced bytheclimateandmanagementconditions production. The variable plant height, in turn, may be 2. perlinearmeterinharvest valuesfornumberoftillers low in harvest2,medium values forleaf width inharvest1,and included accessionswiththehighestvaluesforleaflength low valuesfornumber of tillers in harvest 1. The last group stem diameter in harvest 1 andleaf width inharvest 2, and 1 and2.Group11 containedaccessionswithhighvaluesfor in harvest2,andlowvaluesfornumberoftillers in harvests In groupingthegenotypes by both Tocher’s optimization Many studiesalso demonstrated similarity in the number When comparing the groupsformed based on UPGMA The stem diameter is directly related to biomass

52 CHILEAN JOURNAL OF AGRICULTURAL RESEARCH 77(1)JANUARY the accessions be welldistributedwithineach group. addition tothenumberofgroups formed,itisimportantthat only. Itisnotablethatinorderto obtaingoodvariability, in of 59 accessions of pepper and bell pepper into one group only onegroup.Likewise,Sudré etal.(2006)obtained94% also reportedlowvariability, with 54.5%oftheaccessionsin ofcoffee, evaluating88accessions obtained 12groups, but indicating greatvariability. Silvaetal.(2013),however, group withthemostaccessionshad35.3%oftotal136, dispersion ofthegenotypesineachgroup,giventhat descriptors andobtainedninegroupsformed,withgood who evaluated136accessionsofgrapebymulti-category group, 10groupswereformed. since although 40% of genotypes are gathered in only one These resultsindicatevariabilityinthegermplasmbank, defined asmoredivergent, todistinctgroupsseparately. ofcommonbean,previously allocated traditionalaccessions Gonçalves et al. (2014), Tocher’s optimization method (28), andRoxoBotucatu (52),respectively. According to to begrouped:P241Piracicaba (41), Molede Volta Grande in their composition, genotypes that were not similar enough groups wereformed(8,9,and10)withonlyoneaccession containing 21accessions(24.71%). Additionally, three 40% ofthetotal. The secondlargest group was group2, of genotypeswasgroup1,comprising34accessions,or method (Table 3). The groupthatshowedthelargest number clustered into 10distinct groupsby Tocher’s optimization With themulti-categorytraits,85genotypeswere qualitative (multi-category) traits Cluster analyses basedonthediscrete in Tocher’s andUPGMA methods. by discardingittheyhadchangedtheformationofgroups trait withapercentcontributionof0.01%andnoticedthat can bediscarded,sinceBentoetal.(2007)discardedone from the above-mentioned traits, it cannot be said that they (Sobral etal.,2012).However, evenwithlittle contribution contribute with0.1%),andstemdiameterinbothharvests width inharvests 1and2(which, summed, did not even NP2 NP1 Campos dosGoytacazes,RiodeJaneiro, Brazil,2012-2013. (1981), in on Singh of 85accessionselephantgrass,based Table 4.Relativecontributionofthetraitsfor geneticdiversity harvests 1and2. 1 and2;LW1, LW: leafwidthinharvests1and2;LL1,LL2:length SD2: stemdiameter PH2: plantheightinharvests1and2;SD1, NT1, NT2:numberoftillersperlinearmeterinharvests1and2;PH1, Similar resultswereobtainedby Leão et al.(2011), Variable CL2 CL1 LL2 LL1 DC2 DC1 ALT2 ALT1 Value (%) 5.88 5.35 0.02 0.03 0.38 0.28 0.01 0.01 54.55 33.50 - MARCH 2017 plant colorin theplotvaryingfromlight todarkgreen, the endofreproductive period, displayinganoverall at flowered completely were and early all were accessions with leafangleandtussockform mostlyerect. complete floweringattheend ofthereproductiveperiod, prostrate leaves. Group 3 gathered plants that showed flowered at the end ofthe reproductive period, and with 7127 cv. EMPASC 309(61),considered super early, fully angle oftheleavesvariedlargely, featuringallvarieties. green anddarkgenotypes;however, thehairinessand color oftheplantsinplot,thisgroupcontained the light ranged betweensemi-openanderect,forthegeneral in harvests1and2. As regardsthetussockform,group1 was consideredpartiallyfloweredinharvest1andlate except forgenotypeIJ7141cv. EMPASC 306(64), which end ofthereproductivecycleinbothharvests1and2, considered superearlyandcompletelyfloweredatthe 309) and18(CubanoPinda). 7127cv. 61(IJ formed, containingaccessions EMPASC (24.71%). Two groupswith only one accession were of allaccessions,followedbygroup4,with21accessions was group1,with33accessions,accountingfor38.82% distinct groups. The largest groupformed, from left to right, among the85accessionsstudied,duetoformation of 10 geneticdivergence itcanbeinferredthatthereis accessions, the harvestonaxisyata70%relativedistanceamong groups (Arrieletal.,2006;Cruz2012). in levels occur, thereby allowing the visualization ofthe a visual examination of points atwhich dramatic changes patterns. Forthisreason, it isrecommended to establish groups formed,whichmaygeneratedifferent clustering regarding thecutoff pointandconsequentlythenumberof and may end upgenerating difficulty in decision-making not beenlargely exploitedinelephantgrass. Nevertheless, itshouldbestressedthatthisevaluationhas of pepper(Monteiroetal.,2010;Neitzke2010). coconut (Sobraletal.,2012),and2617accessions of melon (Neitzke et al., 2009),six accessions ofdwarf accessions ofcorn (Coimbra et al., 2010),14accessions and different numbers of accessions; for instance, in 16 variability and becauseitcanbeusedwithdifferent species widely adopted, because it demonstrates whether there is programs forenergy production. six hybridswithpotential for useinelephant grass breeding genetically divergent elephant grass genotypes and obtained effect (Cruzetal.,2012).Menezesal.(2015)crossed of parents that, when crossed, generate agreater heterotic theidentification withinagermplasmbankallows genotypes The knowledge of variability and genetic diversity among superior genotypesinelephantgrass(Daheretal.,2014). In thesecondlargest group,4inthedendrogram, Group 2inthedendrogramincludedonlygenotypeIJ Group 1 in the dendrogram gathered all plants Thus, by the UPGMA method(Figure 2), considering The interpretationofthedendrogramissubjective This type of analysis with multi-category variables is forobtaining animportantstrategy Hybridization is

53 CHILEAN JOURNAL OF AGRICULTURAL RESEARCH 77(1)JANUARY genetic diversity amonggenotypesof by someauthors;e.g.Sudré et al. (2006),whoevaluated the discriminationofgenotypes hasbeendemonstrated 2007; Büttowetal.,2010)variables. (Coimbra etal.,2010)and multi-category (Bentoetal., Sobral et al., 2012). It is sufficient for both continuous etal.,2010;Scheffer-Basso (Campos species etal.,2012; used inthestudyofvariabilitygermplasmsseveral simple for the construction of phylogenetic trees, frequently levels ofNfertilization,whichisnotdesirable. genotype displayedthehighestdrymatteryieldathigher However, etal.(2015)observed thatthissame Oliveira elephant grassgenotypesintendedforenergy production. of 10%flagleaf.Latefloweringisadesirablefeature in (18), whichshowedanerect leaf angleandlate appearance Group 1wasformed by only one accession, Cubano Pinda of theplotandtussockvaryingfromopentosemi-open. Group 9,in turn, had late accessions with light green color 8. group in gathered were leaf flag 10% of appearance the color, lightlypilose,andwithamedium number ofdaysfor flowered attheendofreproductiveperiod. light green, with an erect leaf angle, early, and completely pilose. Group 7was characterized by all genotypes being the majorityofleafsheathsingroupwaslightly angle foundinthisgroupwaserectandsemi-erect, flowered attheend of thereproductiveperiod. The leaf completely leaf, flag 10% of appearance for days of number Grande (34)tolightlypiloseintheothers. in genotypes Mole de Volta Grande (28) and Duro de Volta period, withthehairinessvaryingfromglabrous(nohair) were completely flowered at the end of the reproductive All genotypesfrom group 5showederectflowers,and open orsemi-opentussock,anderectsemi-erectleaf. genotypes ofelephantgrass,inCamposdosGoytacazes,RiodeJaneiro, Brazil,2012-2013. Figure dendrogram 2.Dissimilarity UPGMA matrixobtainedby dissimilarity traits themulti-category on based for method 85 The efficiency of useofmulti-categoryvariablesin The UPGMA themost considered methodis clustering Accessions with erect leaves,opentussock, lightgreen Group 6 was composed ofaccessionswith a medium Capsicum ssp.,and - MARCH 2017 for the formation of groups; i.e., each method utilizes by thefact that different methods utilize distinct procedures a certainsimilaritybetweenthe twoanalyses. 7136 cv. EMPASC 307), and36(Turrialba), demonstrating in theoptimization:71(07 AD IRI),45 (Gramafante),62(IJ dendrogram, onlyfouraccessions didnot belongtogroup2 6 by Tocher’s ingroup4the allgenotypes method.Of method: genotype 13 AD IRI(80),whichbelonged to group one wasnotrepresentedingroup1by Tocher’s optimization accessions that were part of group 1 in the dendrogram, only were identifiedashavingoneaccession.Curiously, ofall composition, whereas in the dendrogram, two groups Tocher’s method,threegroupshadoneaccessionintheir similarity inthenumberofgroupsformed;however, by optimization ofthemulti-categoryvariables,therewas a as inthisstudy. Neitzke etal.,2009;Campos2010;Silva2013), studies also analyze them quantitatively (Bento et al., 2007; when analyzing the diversitybyqualitative variables, many Bento etal.,2007;Neitzke2009).Forthisreason, greater supporttobreedingprograms(Sudréetal.,2006; that a collection be studied in depth sothat it can provide preferred itsuniqueimportance,anditis each methodhas resource isavailable.However, itshouldbestressedthat for banksandcollectionswhenlittlehumanfinancial compared withquantitativedata,whichrenderitideal practicality, andforrequiringlesslabortimeas was alsoaneasytechniqueduetoitsobservation, efficient indemonstrating thegeneticvariability, and characterization andmanagementofgermplasmbanks. of genotypes,demonstratingthegreatpotentialusein of usemulti-categoryvariablesinthediscrimination efficiency the determined and cassava of accessions among Campos etal.(2010),whoevaluatedgeneticdiversity The few disagreements that occurred can be explained In thecomparison betweenthedendrogram and Tocher’s The useofmulti-categoryvariablesshowedtobe

54 CHILEAN JOURNAL OF AGRICULTURAL RESEARCH 77(1)JANUARY variables andmulti-category variables Correlation betweencontinuousdiscrete the distinctgroups(Camposetal.,2010). complementing Tocher’s method, which already provided the visualization ofthe distances within agiven group, UPGMA providedamoredetailed demonstration, allowing Campos etal.,2010). Another factworthmentioningisthat agreeing result (Neitzke et al., 2009; Büttow et al., 2010; most studiescomparing these twomethodsyieldapartially et al., 2009; Büttow et al., 2010). Thus, it is normal that different calculations todetermine genetic distance (Neitzke presented similar numbers of groups, meaning thatboth ofgroups, similar numbers presented category traitsseparately. among accessionswhenconsidering quantitative and multi- assertion, Silvaetal.(2013) obtained low genetic diversity on similarityshouldbeused together. Corroboratingthis Coimbra etal.(2010)statedthat thesepiecesofinformation reason, that and 136 accessions of grape, respectively.For with 88accessionsof the cluster formedby quantitative and multi-category traits distribution oftheaccessionsintogroupswhencomparing also found a different number of groups and differentiated similarity withtheothergenotypes. that were isolated making single groups formed groups of genotypes whereas groupedbymulti-categorytraits, when same groupweredispersed,composingdifferent groups pattern; i.e.,thegenotypesgroupedquantitativelyina diversity. distributing theaccessionsmoreaccording totheirgenetic bank better, as it formed more groups than the latter, traits, the former demonstrated variability ofgermplasm variables with Tocher’s optimization for the multi-category category one,in Tocher’s optimizationforthecontinuous nonsignificant magnitudeof0.25forpapaya. also an obtained who (2012), al. et Quintal by and coffee, in 0.02 of correlation nonsignificant a reported who (2013), et al.,2013). This wasthecasepresentedbySilvaetal. not explain thediversity ofthe multi-category traits (Silva diversity obtainedbasedonthequantitativetraitsdoes utilized addresseddifferent regionsinthegenome. magnitude (0.40)intomato,explainingthatthetechniques corroborated Gonçalvesetal.(2008),whofoundasimilar dataset of adifferent nature(Silvaetal.,2013). This result diversity fromadatasetcanbeextrapolatedintoanother (0.41) thatwassignificantat1%,demonstratingthe et al., 2013). The correlation estimate had a high magnitude each set oftraits, both quantitative or multi-category (Silva to determine the discordance among the clusters formed for based onthecontinuousormulti-categoryvariableshelps Mantel test between the dissimilarity matrices obtained The estimateofthecorrelationcoefficient tested bythe Dendrograms ofcontinuous and discrete variables Silva etal.(2013),Neitzke(2010),andLeãoal Tocher’s optimizationmethodalsodidnotshowa In comparingthequantitativematriceswithmulti- A correlation lowerthan0.10suggeststhatthegenetic Coffea ssp., 17accessionsofpepper, - MARCH 2017 . (2011) corroborates thestudyofGonçalvesetal. same thatformedgroupsinthediscretevariables. This result that formedgroupsinthecontinuousvariableswerenot other genotypes in the quantitative analysis; i.e., genotypes the groupinquantitativeanalysisweregroupedwith in the germplasm bank. However, genotypes that formed UPGMA, showedtheexistenceofabroadgeneticdiversity the quantitative and the multi-category descriptors, in crosses inbreedingprograms. dissimilarity andbetter direction forthe elephant grass provide datathatallowabetterinterpretation of thegenetic and characterizationbasedonqualitativedescriptors could beobserved. of genotypes.Comparingallgroups,noclusteringpattern should notbeexcluded,asitalsoallowedtheclustering qualitative analysis did; however, the qualitative analysis more, forming a larger number of groups than the energy production. biomass of case the is as purposes, diversified most the with in breeding programs aimed at the development of cultivars dissimilarity can be exploited forforming crossing blocks ofquantitativeandqualitativetraits. the analysis This support forthis study. Janeiro To Fundaçãode Amparo aPesquisadoEstado Riode ACKNOWLEDGEMENTS of There is genetic dissimilarity among studied accessions CONCLUSION grass crossesinbreedingprograms(Neitzkeetal.,2010). interpretation and allows for better directions for elephant and multi-category data provides a reliable genetic et al.,2010). Therefore, thecombinedanalysisofquantitative diversity (Gonçalves et al., 2008; Campos et al., 2010; Moura more efficient breedingresearch,facilitatingthestudyof genotypes andgeneticdiversity patterns serves asbasis for of thebank;i.e.,amorecompletecharacterization data canprovidebetterunderstandingofthegeneticdiversity breeding programs(Mouraetal.,2010). of genetic diversity, as they possess great relevance to Hence, quantitativedescriptorsmustbeusedinthestudy et al.,2010;MouraNeitzke2010). majority ofdescriptorsutilizedwasquantitative(Monteiro formed. This mighthaveoccurredhere,though,sincethe of qualitativevariablesintheexplanationclusters separation of genotypes, indicating a greater participation inthe haveagreaterefficiency method, qualitativevariables difference inthedistributionofaccessionsinto thegroups. the samenumberofgroupswasformedbutthereagreat The characterization based onquantitativedescriptorsThe characterizationbased The analysisofquantitativedataseparatedtheaccessions The combinedanalysisofquantitative andqualitative Most studies demonstrate that, by the UPGMA clustering Cenchrus purpureus

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