Evaluation and genetic analysis of backcross nested Association mapping (bcnam) population in sorghom (sorghum bicolor (l.) Moench) under moisture stress Conditions at meiso, eastern Ethiopia

Abstract

Drought is the major constraint for sorghum production in Ethiopia causing high yield loses every year. Developing and using drought tolerant sorghum varieties is one of the available solutions to cope with the effects of drought. The objectives of this study was to evaluate BCNAM population for drought tolerance and other agronomic traits and estimate components of variance, heritability and genetic advance of traits. The experiment was conducted at Meiso (Western Harerge) under rainfed condition. A total of 1464 BCNAM progenies (BC1F4 genotypes), 14 parents and two checks (local and standard) were evaluated using an alpha lattice design with two replications. The analysis of variance showed highly significant difference (P<0.01) among the genotypes for all the studied traits. With regard to grain yield per panicle, genotypes 660,10, 141, 494 and 970 were found to be the top performing genotypes while 552 followed by 1358, 1464, 636 and 1308 were the poor ones. The variability estimate indicated that phenotypic coefficient of variation (PCV) ranged from 3.42% for days to flowering to 41.74% for panicle excertion while genotypic coefficient of variance (GCV) ranged from 1.24% f or days to maturity to 25.15% for panicle excertion. Heritability (Hb 2 ) estimates ranged from 8.39% for number of tiller to 36.32% for panicle excertion. Panicle excertion and number of leaf showed moderate heritability values of 34.55%, 31.46% and 36.32%, respectively. Moderate heritability coupled with high genetic advance was observed in panicle excertion. Number of leaf, panicle weight, 1000 seed weight and panicle harvest index had higher magnitude of phenotypic and genotypic correlation with grain yield per panicle. The path coefficient analysis indicated that panicle weight and panicle harvest index contributed high positive direct effect to grain yield per panicle followed by number of leaf. The principal component analysis indicated that the first three principal components (PCs) explain 64.85 % of the total variation. The presents study indicate the presence of genetic variability among the genotypes. However, there is a need to repeat the experiment so as to get reliable phenotypic data for QTL mapping