Trait Associations and Path Coefficient Analysis for Yield Improvement in Advanced Breeding Lines of Rice (Oryza sativa L.)
Shivani Vijay Shende *
Department of Genetics and Plant Breeding, College of Agriculture, Indira Gandhi Krishi Vishwavidyalaya, Raipur- 492012 (C.G.), India.
Abhinav Sao
Department of Genetics and Plant Breeding, College of Agriculture, Indira Gandhi Krishi Vishwavidyalaya, Raipur- 492012 (C.G.), India.
S. K. Nair
Department of Genetics and Plant Breeding, College of Agriculture, Indira Gandhi Krishi Vishwavidyalaya, Raipur- 492012 (C.G.), India.
Deepak Gauraha
Department of Genetics and Plant Breeding, College of Agriculture, Indira Gandhi Krishi Vishwavidyalaya, Raipur- 492012 (C.G.), India.
Sanjay Bhariya
Department of Genetics and Plant Breeding, College of Agriculture, Indira Gandhi Krishi Vishwavidyalaya, Raipur- 492012 (C.G.), India.
Yash D Barde
Department of Agricultural Botany, College of Agriculture, Nagpur, Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, Maharashtra, India.
*Author to whom correspondence should be addressed.
Abstract
Rice (Oryza sativa L.) is a staple crop critical for global food security. Enhancing grain yield requires an in-depth understanding of trait associations and their direct and indirect effects. This study evaluates 46 advanced breeding lines including five check varieties of rice to assess correlation and path coefficient analysis for key yield components. The biological yield (1.148) and harvest index (1.08) were identified as the most influential traits with strong direct positive effects on grain yield at both phenotypic and genotypic level in path coefficient analysis. Whereas,100 seed weight (0.287), days to 50% flowering (0.245), panicle length (0.130), and spikelet fertility (0.054) also contributed significantly for grain yield per plant. Therefore, in the process of selecting rice genotypes for further breeding programs of yield improvement characters like biological yield and harvest index that had the highest positive association and high direct influence could be primarily used as selection criteria, since improvement of these traits leads to grain yield enhancement.
Keywords: Rice breeding, correlation, path analysis, yield traits, trait association, selection