GENETIC VARIABILITY AND CHARACTER ASSOCIATION IN F7 POPULATION OF Brassica napus L

Abstract

The experiment was conducted using 38 promising genotypes of Brassica napus L. during November 2019 to March 2020 at the experimental field of Sher-e Bangla Agricultural University, Dhaka. The study focused on correlation between eleven yield-contributing traits, direct and indirect impacts of several characters on yield per plant, heritability, genetic advance in order to evaluate genotypes. Significant differences were found for all of the variables after doing a variance analysis. Days to first flowering, number of primary branches per plant, number of secondary branches per plant, siliqua length (cm), seeds per siliquae, thousand seeds weight (g), and seeds yield per plant all showed the smallest difference between phenotypic and genotypic variation. The number of primary branches per plant, number of secondary branches per plant, number of siliqua per plant, and yield per plant all showed substantial genotypic and phenotypic coefficient of variation . The number of secondary branches per plant had the highest genotypic co-efficient of variation (42.39) and phenotypic co-efficient of variation (46.93). In number of siliqua per plant, high heritability (68.91) was combined with high genetic advance (55.72), indicating that this quality was under additive gene action and that selection for genetic improvement would be effective. In terms of correlation, the number of secondary branch per plant, siliqua length (cm), seeds per siliqua, and thousand seeds weight (cm) all had positive significant genotypic and phenotypic correlations with yield per plant. Days to 50% flowering (0.236), days to maturity (0.396), plant height (0.552), number of siliquae per plant (0.113), siliqua length (0.474), and seeds per siliquae (2.256) all had a positive and direct effect on yield per plant, indicating that they were the most important contributors to seed yield per plant. The path coefficient analysis was carried out using the correlation coefficient to determine direct and indirect influence. The most promising genotypes for a future research program were chosen after taking into account the genetic parameter, other agronomic characteristics, and the achievement of the objectives. These genotypes were G8, G9, G18, G21, and G14.