Unveiling genetic variability and cause-effect relationships of morphological traits of rice (Oryza sativa L.) genotypes in the Terai agro-climatic zone of West Bengal
DOI:
https://doi.org/10.14719/pst.6729Keywords:
genetic variability, grain yield, heritability, Oryza sativa, path analysis, principal component analysisAbstract
Rice (Oryza sativa L.) is an essential staple food crop for billions of people worldwide. Understanding genetic variability is essential for breeding programs targeting yield and resilience. This study assessed 52 rice genotypes across two kharif seasons (2021–23) in West Bengal's Terai zone. Key traits were evaluated using a randomized block design (RBD) with three replications. Key characteristics such as plant height (PH), days to 50 % flowering (DFF), number of effective tillers per plant (NETP), panicle length (PL), number of grains per panicle (NGPP),1000–grain weight (TGW), grain yield per plant (GY_P), and harvest index (HI) were assessed. Statistical analysis revealed significant variability among genotypes. Among the traits, GY_P exhibited the highest genotypic (GCV) and phenotypic coefficients of variation (PCV). Additionally, PH, NETP, NGPP, TGW, HI and GY_P exhibited high heritability and genetic advancement, highlighting their potential for selection. Path coefficient analysis identified HI and NGPP as the most influential traits that directly and positively affected GY_P. Principal Component Analysis (PCA) attributed 78.61 % of the total variation to four principal components, highlighting HI, GY_P, NGPP and PL as major contributors to genetic diversity. Genotypes such as Piolee, Motia Saru, and Dhan Sali exhibited superior performance for specific traits, making them potential candidates for future breeding programs. These findings emphasize the potential of exploiting genetic variability in rice to develop high–yielding, regionally adapted varieties, contributing to sustainable agricultural practices in the Terai region.
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Copyright (c) 2025 S Sadhu, L Hijam, A Roy, R Gupta, A Mondal, S Dey, S K Roy
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