GENETIC DIVERSITY AND CHARACTER ASSOCIATION IN GREENGRAM [Vigna radiata (L.) Wilczek]
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Date
2023-12-04
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Acharya N G Ranga Agricultural University
Abstract
The present investigation was undertaken with the objectives to study the genetic variability present in the experimental material, to assess the extent of association between yield, yield components, protein, zinc and iron content; to estimate the direct and indirect effects of yield components and three qualitative traits on seed yield; and to study the genetic diversity in greengram for 11 quantitative and three qualitative traits.
The analysis of variance indicated significant differences among 60 genotypes for all of the traits viz., days to 50% flowering, days to maturity, plant height, branches per plant, clusters per plant, pods per plant, pods per cluster, pod length, seeds per pod, test weight, protein content, zinc content, iron content and seed yield per plant. High PCV and GCV were recorded for pods per plant and iron content, moderate PCV and GCV recorded for pods per cluster, clusters per plant and test weight. Low PCV and GCV were observed for days to 50% flowering, days to maturity and seeds per pod. However, the trait seed yield per plant had high PCV and moderate GCV.
The estimates of heritability and genetic advance as per cent of mean were high for the characters viz., pods per plant, test weight, zinc content, iron content and seed yield per plant indicating the probable operation of additive gene action in inheritance of these traits and simple selection is sufficient to improve these traits. High heritability coupled with moderate genetic advance as per cent of mean was observed for seeds per pod and protein content. Moderate heritability and moderate genetic advance was observed for pods per cluster, plant height and clusters per plant.
The results on character associations revealed positive and highly significant association of seed yield per plant with seeds per pod, pods per plant, pods per cluster clusters per plant, test weight and pod length at both genotypic and phenotypic levels,
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respectively. So, it can be inferred that the above traits which were positively and significantly correlated with yield were important during selection for improvement of dependent variable i.e., seed yield per plant for the studied genotypes. Path analysis revealed that pods per plant, pods per cluster, pod length, seeds per pod and branches per plant had recorded high and positive direct effects on seed yield per plant indicating the effectiveness of these traits as effective selection criteria in improvement of seed yield per plant towards development of high yielding greengram varieties. Further, the lower magnitude of residual effect at genotypic level (0.32) indicated the precision of path analysis showing that the traits included in present investigation are contributing up to 68 per cent of total variability pertaining to the dependent variable.
The D2 analysis grouped the 60 greengram genotypes into eleven clusters. Divergence analysis using Mahalanobis’ D2 revealed maximum divergence between clusters VIII and XI, IV and XI, and VII and XI suggesting the genotypes from these clusters which are having better per se performance may result in superior hybrids or transgressive segregants as there was wide genetic diversity between these clusters. The genotypes taken from same geographical area were grouped into different clusters. This indicated that geographical divergence and genetic diversity were not related.
In D2 analysis, based on inter and intra-cluster distances it was observed that hybridization between the genotypes belonging to cluster VIII (LGG 460) and cluster XI (COGG 18-17), followed by cluster IV (IPM 1603-3) and cluster XI (COGG 18-17) may be utilized under inter-varietal hybridization programme (transgressive breeding) for obtaining superior segregants after conforming their general combining ability. It would be always desirable to attempt hybridisation between genotypes belonging to distant clusters to obtain highly heterotic crosses.
The PCA analysis thus identified that the maximum contributing traits towards the existing variability are seeds per pod, pods per plant, pods per cluster, seed yield per plant, test weight, clusters per plant, pod length and branches per plant. It is important to study the variance as the relative contribution than the signs (indicative of direction) in principal component analysis. It also revealed that the first five principal components contributed 70% per cent towards the total variability. Further, the hybrid combination with the diverse genotypes numbered as COGG 18-17, LGG 625, RMG 1166, LGG 604, PM 1711 and VGG 17-106 which are far apart from each other in the two dimension and three dimension diagrams may result in good F1 combinations to explore the heterosis or to produce transgressive segregants in their respective F2 and subsequent segregation generation.