Aim: Assessment of genetic diversity studies using D2 statistics in Brinjal of North Bengal. Study Design: Diversity D2 analysis. Methodology: This study was undertaken to understand the genetic divergence of the 32 brinjal genotypes collected from different locations of North Bengal region. Through diversity D2 analysis whole genotypes were categorized under seven groups with no evidence for geographical diversity as necessarily cause of genetic diversity. Results and Conclusion: Highest genetic diversity was recorded in cluster I and V argued for their utilization to develop transgressive segregate lines. Genotypes under cluster VI and VII found to be effective for the improvement of yield related attributes. The cross combinations between cluster VI and V, cluster VI and II, cluster VI and VI, cluster VI and I, cluster VI and III, cluster VI and cluster VII could be effectively utilized to improve heterotic population or recombinant.
Two F2 populations of brinjal (Solanum melongena L) from intra-specific hybridizations MLC-1 x Longai (oblong) and MLC-3 x Longai (oblong) attempted in 2015-16 were evaluated for eight quantitative traits using genetic variability parameters, heritability, genetic advance, genetic advance as per cent of mean, correlation and selection indices in the year 2017-18. The characters viz., number of fruits per plant (0.794) and number of branches per plant (0.633) recorded positive and highly significant correlations with yield per plant in F2 plants of MLC-1 x Longai (oblong), whereas the characters viz., number of fruits per plant (0.819), average fruit weight (0.700) and fruit volume (0.593) recorded positive and highly significant correlations with yield per plant in F2 plants of MLC-3 x Longai (oblong). Selection indices for yield selection were constructed in both the F2 populations using the characters with highly significant yield correlations. Based on the efficient selection index, the genotypes were given scores or ranks and the best 5% plants were selected in both F2 populations i.e., plant number 2, 12, 10, 3, 11 and 19 in F2 plants of MLC-1 x Longai (oblong) and plant number 105, 28, 107, 26, 22 and 109 in F2 plants of MLC-3 x Longai (oblong) for constituting the third generation, evaluated in the year 2018-19. A comparative evaluation of the performance of the two populations arising from one common parent i.e. Longai showed that population generated from cross MLC-1 x Longai (oblong)was more promising than MLC-3 x Longai (oblong).
Total 21 high zinc rice genotypes were evaluated under five different locations for 14 different yield attributing traits, including grain yield/plant (gm) to determine the pattern of variation, the relationship among the individuals and their characteristics through Principal Component Analysis (PCA) during the Kharif-2017. PCA was done for all the locations individually as well as pooled analysis for all locations using R software. Out of the 14 PCs, the initial four PCs contributed more to the total variability. The highest cumulative variability of the first four PCs found at Bhikaripur (81.11%) followed by BHU Agriculture research farm-II (79.23%) etc. and Pooled variability was 76.61%. Pooled data analysis indicates PCA biplot or loading plot of first two principal components revealed that days to maturity, days to 1st flowering date and days to 50% flowering loaded more on the first component and number of spikelets per panicles, number of grains/panicles, grain weight per panicle, grain yield/plant accounted more variation in the second component compared to the other parameters. Thus, the pooled analysis of principal component analysis revealed the characters contributing to the variation and genetic variability that exists in these rice genotypes. This is because the genotypes BRRIdhan 72, Sambamahsuri and Swarna were identified in different principle components related to grain yield and grain quality, and were also located farthest away from biplot origin in individual PCA based biplot. So they may be employed to improve yield attributing factors like total effective tiller number. PC1, PC2 and PC3 have days to first flowering and days to 50% flowering, hence their genotypes may be valuable in producing early maturing cultivars. Thus, the results revealed that wide range of variability was shown by different traits of the genotypes which can be utilized in rice improvement programmes.
In the present experiment the selected progenies of F2 population [MLC-1 x Longai (oblong)] i.e. plant number 2, 12, 10, 3, 11, 19 and progenies of F2 population [MLC-3 x Longai (oblong)] i.e. plant number 22, 26, 28, 105, 107, 109 along with their respective bulk populations evaluated based on eight quantitative traits. There was a significant difference among the genotypes for all the characters studied at 1% level of significance. The phenotypic variance, phenotypic coefficients of variation were higher than the genotypic variance, genotypic coefficient of variation respectively in all the traits studied. Among all the genotypes high heritability coupled with high genetic advance as percent of mean except fruit length which indicating that all the traits were governed by additive gene action except fruit length. Characters viz., number of fruits per plant, plant height, fruit weight, number of branches per plant recorded positive and significant association with yield per plant in the genotypes. Path coefficient analysis revealed that number of fruits per plant is important yield attributing trait because of their high direct effect and indirectly influencing number of branches per plant is another most important yield attributing trait.
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