Studies of Path-Coefficient Analysis of Yield Components in Pearl Millet [Pennisetum glaucum (L.) R. Br.]
Rajesh Yadav *
Department of Plant Breeding and Genetics, Institute of Agriculture Science, Bundelkhand University, Jhansi, UP, India.
Mahipat Singh Yadav
Department of Plant Breeding and Genetics, Institute of Agriculture Science, Bundelkhand University, Jhansi, UP, India.
Rajesh Yadav
Department of Plant Breeding and Genetics, Institute of Agriculture Science, Bundelkhand University, Jhansi, UP, India.
Lokesh Choudhary
Department of Plant Breeding and Genetics, Institute of Agriculture Science, Bundelkhand University, Jhansi, UP, India.
Jitu Choudhary
Department of Plant Breeding and Genetics, Institute of Agriculture Science, Bundelkhand University, Jhansi, UP, India.
Shankar Lal Yadav
Department of Soil Science, College of Agriculture, RVSKVV, Gwalior, MP, India.
*Author to whom correspondence should be addressed.
Abstract
Path-coefficient analysis was employed to investigate the direct and indirect effects of various yield components on grain yield in pearl millet [Pennisetum glaucum (L.) R. Br.] during the Kharif season of 2023. Path-coefficient analysis was utilized to examine the direct and indirect effects of various yield components on grain yield in pearl millet [Pennisetum glaucum (L.) R. Br.]. The study included 15 genotypes and 11 traits, namely days to 50% flowering, days to maturity, plant height, number of effective tillers per plant, ear head length, ear head diameter, test weight, harvest index, dry fodder yield per plant, biological yield per plant, and grain yield per plant. The results indicated that biological yield per plant (3.09273) showed the highest direct positive effect on grain yield at the phenotypic level, followed by harvest index (0.00070) and ear head length (0.00022). On the other hand, dry fodder yield per plant exhibited the highest negative direct effect (-2.63120). At the genotypic level, harvest index (3.01206) exhibited the highest direct positive effect on grain yield, followed by biological yield per plant (3.01206) and plant height (0.00035). Dry fodder yield per plant showed the highest negative direct effect (-2.70743). The low residual effects (phenotypic = 0.00153; genotypic = 0.00012) indicated that the model effectively explained most of the variability in grain yield, emphasizing the importance of these traits in pearl millet breeding programs aimed at enhancing grain yield of pearl millet.
Keywords: Pearl millet, grain yield, path analysis