Legume Research, 38 (6) 2015 : 758-762

AGRICULTURAL RESEARCH COMMUNICATION CENTRE

Print ISSN:0250-5371 / Online ISSN:0976-0571

www.arccjournals.com/www.legumeresearch.in

Multivariate analysis in green gram [Vigna radiata (L.) Wilczek] Suhel Mehandi, I.P. Singh1, Abhishek Bohra1 and Chandra Mohan Singh2 Department of Genetics and Plant Breeding, Sam Higginbottom Institute of Agriculture, Technology and Sciences (Deemed to -be- University), Allahabad- 211 007, India. Received: 16-07-2014 Accepted: 21-05-2015

DOI: 10.18805/lr.v38i6.6720

ABSTRACT The present study was undertaken to perform the multivariate analysis in green gram using twenty-one green gram genotypes. The extent of genetic divergence revealed that these genotypes could be grouped into ten and five clusters, following Tochers and non-hierarchical Euclidian clustering methods, respectively. Based on the maximum diversity obtained in Tochers method genotype KM 10-1064 of cluster V and genotypes KM 10-1046, KM 10-1059 and KM 10-1070 of cluster VI were found suitable for improving the plant structure, whereas concerning high diversity along with high trait contribution towards total divergence, the clusters KM 10-1064 of cluster V and KM 10-1042 of cluster VIII were found to be appropriate for hybridization. The genotype KM 10-1068, which represents the mono genotypic cluster in case of both the clustering methods signifies that it could be the most diverse from other genotypes and it would be the suitable candidate for hybridization with genotypes present in other clusters to tailor the agriculturally important traits and ultimately, to enhance the seed yield in green gram. Key words: Euclidean clustering, Genetic divergence, Green gram, Principal Component Analysis. INTRODUCTION Mungbean [Vigna radiata (L.) Wilczek], one of the important grain-legume crops ranks third among the pulses grown in India after chickpea and pigeon pea. Being a leguminous crop, it is a good source of proteins in human diets along with providing quality food for livestocks (Karuppanapandian et al., 2006). Like other legumes, it also improves soil health by fixing the atmospheric nitrogen. Despite its high economic importance, the productivity of green gram remains low and the the potential reason may be a lack of determinate and high yielding varieties. It warrants an urgent need for development of high yielding varieties with determinate growth habit. Recombination breeding and trait manipulation are potential alternatives to develop such desirable genotypes which in turn require suitable parents for crossing programme. Assessment of existing genetic diversity following multivariate analysis like D2 statistics and factorial analysis in the primary gene pool still remains the most crucial step in any crop improvement programme (Rahman and Al-Mansur, 2009). In addition, variability estimation helps breeders to understand the genetic relationships among accessions and to select the superior accession in a more systemic and effective way (Lavanya

et al., 2008). Keeping the above points in consideration, the present investigation was carried out to assess the genetic divergence and subsequently, to isolate the suitable parents using multivariate analysis for hybridization and recombination breeding. MATERIALS AND METHODS Twenty-one green gram genotypes were grown following standard cultural practices for evaluation in a randomized block design (RBD) with three replications during Kharif- 2010 at the Field Experimentation Centre, Department of Genetics and Plant Breeding, SHIATS, Allahabad. There were five rows of five meter length at spacing of 30 × 10 cm for each entry in every replication. Five competitive plants were selected to record data on ten quantitative traits viz., plant height (cm), number of primary branches per plant, number of clusters per plant, number of pods per plant, pod length (cm), number of seeds per pod, 100-seed weight (g) and seed yield per plant (g), days to 50% flowering and days to maturity. The latter two traits were computed on plot basis. The recorded data were analysed to assess the genetic divergence using computer software Windostat 8.6 version.

*Corresponding author’s e-mail: [email protected]. 1Crop Improvement Division, Indian Institute of Pulses Research, Kanpur - 208 024 India. 2 Department of Plant Breeding and Genetics, Rajendra Agricultural University, Bihar, Pusa (Samastipur)- 848 125, India.

Volume 38 Issue 6 (2015) RESULTS AND DISCUSSION The analysis of variance (ANOVA) showed significant differences for all the traits studied indicating the existence of adequate genetic variability among the genotypes. Cluster Analysis by Tochers Method: Selection of suitable parents plays an important role in any successful plant breeding program. Parents with more genetic distance are expected to exhibit higher genetic gains from selection. In the present experiment, the cluster analysis conducted in a set of twenty-one genotypes generated a total of ten distinct clusters (Table 1). Among these, clusters I, II and IV comprised four genotypes each, cluster VI consisted of three genotypes and the remaining six mono genotypic clusters indicated to be more distinct from those of the other clusters. The highest intra-cluster distance was found in cluster VI, suggesting possibility of easy trait manipulation between these genotypes for green gram improvement (Arunachalam, 1981). The maximum inter cluster distance was found between cluster IV & V followed by the cluster combinations VI & IX, VI & VIII, IV & VI, VI & X (Table 2). The cluster means of the quantitative traits helps to identify the diverse genotypes for genetic manipulation. Concerning days to 50 per cent flowering and maturity, all TABLE 1: Distribution of 21 green gram genotypes into different clusters following Tochers method Cluster No. No. of genotypes

Name of the Genotypes

I

4

II

4

III IV

1 4

V VI

1 3

VII VIII IX X

1 1 1 1

KM 10-1045, KM 10-1074, KM 10-1063, KM 10-1047 KM 10-1050, KM 10-1057, KM 10-1076, KM 10-1043 KM 10-1053 KM 10-1058, KM 10-1062, KM 10-1051, KM 10-1054 KM 10-1064 KM 10-1046, KM 10-1059, KM 10-1070 KM 10-1041 KM 10-1042 KM 10-1071 KM 10-1068

759

the clusters exhibited similar mean values thus suggesting common crop duration for the genotypes under study |(Table 3). Plant height varied from 53 (cluster IV) to 95 cm (cluster X) suggesting that these clusters could be considered for improvement of plant height of green gram. However, both positive and negative correlations of plant height with seed yield have been reported by various researchers. For example, Singh (1988), Gul et al. (2008) observed the negative association between plant height and seed yield per plant, whereas Rajan et al. (2001), Lavanya and Toms (2009) reported positive association between plant height and seed yield per plant. When, the plant height is used as selection criteria for yield improvement, the average intermodal distance and stem diameter must be taken under consideration but they were not included in the present study. Since improvement in yield is the prime objective in any breeding scheme, cluster means for seed yield per plant and its major components should be considered for selection of genotypes. Accordingly, cluster VII consisting of genotype KM10-1041 and showing the highest cluster mean for yield per plant, number of seeds per pod and moderately early maturing appears a desirable parent. Genotypes belonging to cluster IX and III were found suitable for improvement of number of clusters per plant. The pod length and 100 seed weight appeared non-deviating. Cluster V and VI appeared promising for pods per plant thus the genotypes under these clusters would be useful in breeding. The results obtained with respect to per cent contribution of each character toward total diversity indicated that the characters like days to 50 per cent flowering, pod length and number of primary branches per plant had no contribution towards the total divergence, while seeds per pod, and seed yield exhibited less contribution (