Genetic variability, correlation and principal component analysis for agronomic traits in lentil genotypes
1 Balochistan Agricultural Research and development center Quetta (BARDC).
2 SBK Women’s University, Quetta, Balochistan.
Research Article
International Journal of Frontiers in Science and Technology Research, 2021, 01(01), 029–035.
Article DOI: 10.53294/ijfstr.2021.1.1.0067
Publication history:
Received on 06 April 2021; revised on 10 May 2021; accepted on 14 May 2021
Abstract:
The investigation was carried out in a RCBD with 3 repeats on 15 lentil genotypes for 7 agro morphological characteristics. A wide range of divergence of plant characteristics were recorded for the lentil genotypes. The parameters (Days to fifty percent flowering, Days to fifty percent maturity, plant height, Biological yield, Grain yield, H.I and Hundred Seed Weight) showed weighty differences (P ≤ 0.05). The promising genotype ILL11 (918.9 Kilo gram per hectare) and ILL8081 (847.4 Kilo gram per hectare) fashioned the highest yield than the other genotypes tested. Correlation and PCA was also conducted on 15 lentil genotypes over one year for 7 characters. Harvest Index (0.807) and biological yield (0.389) showed a helpful significant correlation with seed yield while a analogous positive correlation with seed yield was recorded for plant height (0.062). An adverse non-significant connection was logged for days to flowering (-0.248) and days to maturity (-0.312). These 3 principal components (PC) accounted for 82 % of the total dissimilarity. PC1 was positive correlate with the flowering interval, days to maturity, plant height and hundred seed weight while it was negatively correlated with biological yield, seed yield and H.I. PC2 was positively correlated with grain yield and harvest index. PC3 was positively correlated with days to flowering, H.I. and hundred seed weight. With the analysis of the agronomic features over the 1st and 2nd principal modules, the lentil genotypes were designated into 4 different groups.
Keywords:
Genetic correlation; Lens culinaris; Principal component analysis (PCA); Yield components
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