Genetic diversity of 2142 accessions of rice (Oryza sativa L.) from India based on the multivariate analysis for 10 agro-morphological traits was evaluated using augmented experimental design at CSSRI, Karnal, Haryana, in kharif 2010-11. In all, a total of 8 clusters were obtained based on the estimates of genetic diversity using the UPGMA. On the basis of their greater intercluster distance, high value of cluster mean according to the character to be improved and performance of the individual germplasms for the character, the germplasms could be used in hybridization programme for improvement of different plant characters in the rice germplasms. The results of PCA revealed that the first three principal components explained 40.12% of the total variation thus suggesting that traits such as plant height, days to flowering and maturity, number of effective tillers and grain size (weight, length and width) were the principal discriminatory characteristics. It is suggested that the genetic variation existing in the evaluated germplasm set can be usefully utilized in efforts towards genetic improvement of rice

JOGENDRA SINGH

MAHESH S CHAUHAN

S K SHARMA

S L KRISHNAMURTHY

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Rice (Oryza sativa L.) is one of the most importantcereal crop and a primary energy source for more than onehalf of world’s population. In view of importance of rice asa major food crop, the origin and diversity of Oryza sativahas attracted great interest. The success of breedingprogramme largely depends on the selection of parents forhybridization from diverse base materials with built ingenetic variability. Such materials serve as sources ofdesirable genes needed for relevant breeding programmesto improve yield and productivity and breeders acrosscountries have recycled many traditional varieties as sourcesof genes of interest.For breaking the yield plateau which generally isindicative of a narrow genetic, the widely followed approachinvolves diversification of parents for harnessing of the geneticdiversity present in the germplasm. Genetic diversity analysisusing genetic distance measures, derived from quantitativeand agronomic characters, is an efficient tool to select bestparents for hybridization programme and obtain desirablecombinations in the segregating generations (Whitehouse1969). Considering the above points, the present study wasinitiated to assess the extent of genetic diversity in ricegermplasm using genetic distances calculated on the basis ofmorphological and agronomic traits as the measures.The germplasm used in this study comprised 2142 riceaccessions and six checks (Swarna, Pusa Basmati 1, NDR97, Annada, IR 64 and Jaya) was obtained from the NationalBureau of Plant Genetic Resources (NBPGR), New Delhiunder the Establishment of national rice resource data baseproject. All the accessions along with checks were planted atCSSRI, Karnal experimental fields in kharif 2010-11 usingaugmented randomised complete block design (Federer 1961)in three rows plot having 20 plants spaced at 15 × 30 cm.1Principal Scientist and Head (e mail: sksharma@cssri.ernet.in),2Scientist (e mail: jogendra@cssri.ernet.in), 3Research Associate(e mail: msc3112@gmail.com), 4Scientist (e mail: kmurthy@cssri.ernet.in), Division of Crop Improvement119Recommended cultural practices were followed to grow ahealthy crop and for proper expression of genotypes.Five random but robust plants from inner rows weretagged from each plot for data collection. A total of tenquantitative traits namely; days to flowering, days to maturity,grain length (mm), grain width (mm), 100 seed weight (g),seedling height (cm), plant height (cm), panicle length (cm),number of effective tillers and grain yield/plant (g), weremeasured at particular stages of rice plant following theminimal descriptor of agri-hort crops and standard evaluationsystem of rice provided by NBPGR, New Delhi.Analysis of variance was performed for quantitativecharacters using SAS software (Version 9.2) to estimategenetic variation for the traits. The Pearson’s correlationcoefficient (r) was analyzed to evaluate the relationshipsamong different variables. Cluster analysis was carried outbased on genetic distance matrix of the 2142 accessionsalong with six checks, applying the UPGMA (UnweightedPair-Group Method using Arithmatic average) clusteringmethod (Michener and Sokal 1957).The analysis of variance showed significant block effectsfor all the traits except grain width where block effects werenon-significant implying that blocking had no effect on thegrain width. The accessions however showed significantdifferences for most of the traits, except number of effectivetiller and grain yield/plant.The genetic variability parameters including mean,standard error, coefficient of variation (CV) and minimumand maximum values of the various traits were also estimated.The checks had average days to maturity (129 days), 100-seed weight (2.3 g), grain yield/plant (18.5 g), effectivetillers/plant (6.9) and panicle length (24.63 cm). The largestvariation was observed in the yield/plant (CV = 64.66%)followed by the number of effective tillers, grain width and100 seed weight having CV = 25.73, 19.26, and 15.78%,respectively. Seedling height followed by panicle length anddays to maturity showed the lowest variation (CV = 0.87,7.83 and 7.84%, respectively). Sanni et al. (2012) alsoShort CommunicationIndian Journal of Agricultural Sciences 84 (2): 295–9, February 2014/Short CommunicationMultivariate analysis of phenotypic diversity of rice (Oryza sativa) germplasmin North-West IndiaS K SHARMA1, JOGENDRA SINGH2, MAHESH S CHAUHAN3 and S L KRISHNAMURTHY4Central Soil Salinity Research Institute, Karnal, Haryana 132 001Received: 14 November 2012; Revised accepted: 20 December 2013Key words :  Multivariate analysis, PCA, Phenotypic diversity, Rice, Trait associationhttps://doi.org/10.56093/ijas.v84i2.38054296 [Indian Journal of Agricultural Sciences 84 (2)120SHARMA ET AL.reported variation for quantitative traits in rice germplasm.The accession IC 461817 recorded the longest floweringtime (160 days after sowing), while IC 449551 recorded theearliest flowering time (72 days). Similarly, accession IC330690 recorded the maximum number of effective tillers(17.2), whereas IC 394518 produced the minimum effectivetillers (2.2). IC 392250 was the tallest accession with 221.4cm plant height, whereas the shortest accession IC 385561with 49.0 cm. The accession with least panicle length (12.6cm) was IC 413457, while IC 459773 had the longest panicleof 41.8 cm. The accession that took the longest number ofdays to mature (178 days after sowing) was IC 450100,whereas IC 449656 was the earliest to mature, maturing in106 days after sowing. The accession with the longest grainwas IC 545222 with a grain length of 24.78 mm, whereas IC459798 recorded the shortest grain of 4.2 mm. However, IC114333 with the largest grain width of 11.42 mm had a broadgrain shape, whereas IC 545299 had a width of 1.1 mm.Accession IC 382615 had the highest 100 - seed weight(3.5g) against the lowest (0.4g) width in IC 347612. AccessionIC 333022 produced the maximum yield per plant (43.88g),while the lowest yield (1.2g) was recorded in IC 544956.Seedlings of IC 449774 were the tallest with 50.54 cmheight, whereas IC 316314 had the shortest seedling height(4.38 cm). Thus, from the study of individual characters, it isclear that huge variations in all the characters is present inthe present set of rice accessions in the germplasm set underevaluation and the same could be used for crop improvementprogrammes in rice (Chakravorty et al. 2013, Medhabati etal. 2013 and Wu et al. 2013).Association between traitsAmong the variables studied, the highest correlationcoefficient recorded was between days to flowering and daysto maturity with r = 0.92** (Table 1). The trait presentinghighly significant but negative correlations with these twocharacteristics is the number of effective tillers (r = -0.45**and -0.46**, respectively) showing the number of effectivetillers tends to decrease as the duration of days to floweringand maturity increases. The positive and significantcorrelations among grain weight and grain width (r = 0.44**)and grain length (r = 0.47**) indicated that higher the grainweight, wider and longer the grain becomes. Estimated highervalue of significant and positive correlation between numberof effective tillers and yield/plant (r = 0.59**) revealed thatgrain yield is under direct influence as it tend to increasealong with the increasing number of effective tillers. Thesefindings are in conformity with Medhabati et al. (2013), Wuet al. (2013), Chakravorty et al. (2013), Soharabi et al.(2012), Sanni et al. (2012) and Lasalita-Zapico et al. (2010).Cluster analysisAnalyses performed by the UPGMA grouped 2142accessions into total eight clusters (Fig 1) with 1569accessions in cluster I, 159 in cluster II, 155 accessions incluster III, 370 accessions in the cluster IV, 69 accessions incluster V, 8 accessions in cluster VI whereas cluster VII andVIII had only two accessions each (Table 2). The accessionsin cluster VIII were primarily early flowering types with amean of 77 days flowering duration. Number of effectivetillers per plant was higher in clusters II, IV, V and VIII (7 to8). Accessions in clusters VIII were taller (plant height 205.80cm), whereas shorter accession were grouped in clusters II,V and VII having plant height between 87.33 to 91.0 cm.Cluster III had accession with the longest panicle (24.55cm), the highest 100-seed weight (2.11 g), higher grain yieldper plant (18.09 g) and the shortest seedling (17.88 cm).Early maturing accessions were grouped in cluster V and VIhaving mean maturity duration from 110 to 113 days. ClusterI, III, IV and VIII had the accession with the longest grainTable 1 Correlation coefficient among ten quantitative traits in rice germplasm accessionsTraits Correlation coefficientsDays to No. of Plant Panicle Days Grain Grain 100 seed Yield/ Seedlingflowering effective height length to length width weight plant heighttillers  (cm)   (cm) maturity (mm) (mm) (g) (g)  (cm)Days to flowering 1.00 -0.45** 0.27** -0.16** 0.92** -0.09* -0.06 -0.19** -0.10** 0.10**No. of effective tillers 1.00 -0.23** -0.02 -0.46** -0.01 -0.05 -0.04 0.59** -0.05Plant height (cm) 1.00 0.18** 0.27** 0.08 0.07 0.10** 0.13** 0.01Panicle length (cm) 1.00 -0.16** 0.12** 0.07 0.11** 0.31** -0.01Days to maturity 1.00 -0.09* -0.06 -0.18** -0.10** 0.11**Grain length (mm) 1.00 -0.08 0.47* 0.12** -0.02Grain width (mm) 1.00 0.44* 0.09* -0.02100 seed weight (g) 1.00 0.14** -0.01Yield/plant (g) 1.00 -0.12**Seedling height (cm) 1.00*, **Significant at 5% and 1% level of significance, respectively297February 2014]121MULTIVARIATE ANALYSIS IN RICE(8.00 - 8.38 mm). Longer seedling accessions were groupedin cluster VI and VII with 22.15 to 23.59 cm height,respectively. Similarly, fine grain accessions were largelygrouped in cluster VI with average grain size of 2.33 mm,whereas cluster VIII had accession with bolder grain havingmean grain width of 2.73 mm (Table 2). Accessions fallingunder distant clusters could be hybridized to get the higherheterotic responses. Medhabati et al. (2013), Wu et al. (2013),Chakravorty et al. (2013), Sanni et al. (2012), Soharabi et al.(2012) and Latif et al. (2011) also reported similar findingsfrom cluster analysis of the rice germplasm for agro-morphological traits diversity.Table 2 Rice accessions grouped into eight different clusters using unweighted pair group method of the average linkage (UPGMA) basedmorphological dendrogramNo. of Correlation mean values of charactercluster No. of Days to No. of Plant Panicle Days Grain Grain 100 seed Yield/ Seedlingmember flowering effective height length to length width weight plant heightaccessions tillers  (cm)   (cm) maturity (mm) (mm) (g) (g)  (cm)CL I 1569 133.00 6.22 140.68 23.09 164.00 8.00 2.36 1.94 11.14 20.02CL II 159 132.00 6.68 87.37 19.88 164.00 7.77 2.34 1.80 8.01 19.61CL III 155 97.00 7.35 144.34 24.55 126.00 8.24 2.48 2.11 18.01 17.88CL IV 370 110.00 7.04 105.64 22.62 139.00 8.12 2.34 2.00 12.39 19.29CL V 69 77.00 8.26 88.11 22.46 110.00 7.97 2.35 2.03 14.59 19.17CL VI 8 134.00 6.23 130.33 23.38 113.00 7.75 2.33 2.04 10.12 22.15CL VII 2 90.00 5.2 91 20.9 164.00 7.85 2.44 1.55 10.1 23.59CL VIII 2 99.00 7.4 205.8 22.5 140.00 8.38 2.73 1.9 9.4 20.52Fig. 1 Dendrogram of similarity patterns by the UPGMA method based on the average Euclidean Distance estimated from 10 agro-morphological traits analysed in 2142 accessions of Indian rice accessions used in the experiment.Average Distance Between Clusters2.0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0298 [Indian Journal of Agricultural Sciences 84 (2)122SHARMA ET AL.Principal Component Analysis (PCA)The first three principal components are often the mostimportant in reflecting the variation patterns among accessionsand the traits associated with these are more useful indifferentiating accessions. In the present study, first threecomponents account for about 44.12% of total variation(Table 3), giving a clear idea of the structure underlying thevariables analyzed..However, the criterion of cut-off limitfor the coefficients of the proper vectors greater than 0.3having a large enough effect to be considered importantwhile the traits having coefficient value lower than 0.3 werenot considered to have important effects on the overallvariation observed in the present study.The first principal component accounted for 20.32% oftotal variance indicating that number of days to flowering,plant height, days to maturity and seedling height were thevariables that contributed most negatively and also registeredthose with high yield component values (Table 3). The secondcomponent accounted for 10.0 percent of total variance whichidentified yield component variables (number of effectivetillers, panicle length, weight of 100 grains and grain yield/plant) presenting positive contributions and the maincharacters responsible for classification. The third principalcomponent accounted for 13.80% and was positivelyassociated with grain length and grain width. This componentwas negatively associated with yield per plant, plant heightand panicle length, thereby differentiating those accessionswith their grain characteristics (Table 3). These results arecorroborated by Medhabati et al. (2013), Wu et al. (2013),Chakravorty et al. (2013), Sanni et al. (2012), Soharabi et al.(2012), Lasalita-Zapico et al. (2010) and Rajiv et al. (2010).The genotypes superior in some clusters might be usefullyinvolved in multiple crossing programmes to recovertransgressive segregants with high genetic yield potentialand early maturity. The generated information can be helpfulin reducing the overall time required to screen largepopulations for potential breeding stock. Accessions showingtall plant types for plant height may be useful as potentialdonors for increasing total plant biomass. The genotypeswith early maturity, higher 100-seed weight, grain yield perplant, effective tillers per plant and panicle length mightserve as potential donors for increasing grain yield ofpredominant rice varieties.ACKNOWLEDGMENTSAuthors convey sincere thanks to the Department ofBiotechnology, New Delhi for providing the financial supportto the Establishment of National Rice Resource Databaseproject and Director, NBPGR, New Delhi for providing thegermplasm. Thanks are due to Director, CSSRI Karnal forproviding the facilities.SUMMARYGenetic diversity of 2142 accessions of rice (Oryzasativa L.) from India based on the multivariate analysis for10 agro-morphological traits was evaluated using augmentedexperimental design at CSSRI, Karnal, Haryana, in kharif2010-11. In all, a total of 8 clusters were obtained based onthe estimates of genetic diversity using the UPGMA. On thebasis of their greater intercluster distance, high value ofcluster mean according to the character to be improved andperformance of the individual germplasms for the character,the germplasms could be used in hybridization programmefor improvement of different plant characters in the ricegermplasms. The results of PCA revealed that the first threeprincipal components explained 40.12% of the total variationthus suggesting that traits such as plant height, days toflowering and maturity, number of effective tillers and grainsize (weight, length and width) were the principaldiscriminatory characteristics. It is suggested that the geneticvariation existing in the evaluated germplasm set can beusefully utilized in efforts towards genetic improvement ofrice.REFERENCESChakravorty A, Ghosh P D and Sahu P K. 2013. Multivariateanalysis of phenotypic diversity of landraces of rice of WestBengal. American Journal of Experimental Agriculture 3(1):110–23.Federer W T. 1961. Augmented designs with one-way eliminationof heterogeneity. Biometrics 20: 540–52.Lasalita-Zapico F C, Namocatcat J A and Carino-Turner J L. 2010.Genetic diversity analysis of traditional upland rice cultivars inKihan, Malapatan, Sarangani Province, Philippines usingmorphometric markers. 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Genetic diversity analyzed by quantitative traitsTable 3 Coefficients and vectors associated with the first threeprincipal componentsParticulars First Second Thirdcomponent  component componentEigen value 2.03 1.00 1.38Variance (%) 20.32 10.00 13.80Cumulative variance (%) 20.32 30.32 44.13Coefficient VectorDays to flowering –0.61 –0.13 0.24No. of effective tillers –0.14 0.55 0.23Plant height (cm) –0.35 0.24 –0.37Panicle length (cm) 0.23 0.41 –0.49Days to maturity –0.69 0.08 –0.12Grain length (mm) –0.11 0.17 0.35Grain width (mm) –0.21 0.16 0.33100 seed weight (g) –0.23 0.37 0. 09Yield/plant (g) 0.15 0.43 –0.55Seedling height (cm) –0.62 –0.27 0.25299February 2014] MULTIVARIATE ANALYSIS IN RICE123among rice (Oryza sativa L.) genotypes resistant to blast disease,African Journal of Microbiology Research 5 (25): 4 383–91.Medhabati K,  Rajiv D K,  Rohinikumar M,  Sunitibala H and SinghT D. 2013. Genetic divergence in indigenous wild and cultivatedrice species of Manipur Valley. 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Multivariate analysis of phenotypic diversity of rice (Oryza sativa) germplasm in North-West India

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Multivariate analysis of phenotypic diversity of rice (Oryza sativa) germplasm in North-West India

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