Correlation and Path Coefficient Analysis of Yield Components in NERICA Mutant Rice Lines under Rainfed Conditions
Md. Nuruzzaman, Lutful Hassan, Shamsun Nahar Begum, Md. Monjurul Huda
Journal of Experimental Agriculture International · pp. 1–8 · Published 25 Apr 2017
10.9734/JEAI/2017/32756Abstract
Morphological and yield related traits of 31 genotypes were studied to ascertain the genetic and phenotypic correlations among some morphological traits and contribution of these traits to the yield under rainfed conditions directly and indirectly in NERICA mutant rice lines. Field experiment was conducted during the winter season of 2014 at the experimental field of Biotechnology division in Bangladesh Institute of nuclear agriculture (BINA), Mymensingh. The experiment was lay in a randomized complete block design with three replications. The genotypes differed significantly for all the traits viz., days to flowering (1st, 50%, 80%), days to maturity, plant height, total tillers and effective tillers hill-1, filled and unfilled grains panicle-1, 100-seed weight (g) and yield plant-1 (g). The results indicate that plant height (0.422*and 0.426*), total tillers hill-1(0.663**and 0.669**), effective tillers hill-1 (0.734**) and filled grains panicle-1 (0.525**and 0.530**) showed positive and significant association with yield per plant under rainfed conditions at both phenotypic and genotypic levels; whereas, days to maturity (-0.554** and 0.574**) had significantly negative correlation with yield. Higher phenotypic correlation values for all traits indicated that the environmental effects on traits are high under rainfed conditions. Plant height, total tillers hill-1, effective tillers hill-1, panicle length, filled grains panicle-1 and 100-seed weight showed direct positive effect on yield plant-1 at both genotypic and phenotypic levels. Therefore, these characters would be reliable criteria for improving yield. Higher heritability and genetic advance estimates for all the traits under rainfed condition indicates that these characters can be exploited more efficiently through selection in further generations.
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