In the present study, "Correlation and path coefficient analysis for grain yield components in maize (Zea mays L.)," the aim was to estimate genetic variability, genetic advance, correlation, and direct and indirect effects of yield contributing traits on yield. According to the analysis of variance, all traits exist. Hence, the data on all the 16 traits which showed significant differences among the entries were subjected to further statistical analysis. GP-184 had the shortest grain yield per plant in comparison to other genotypes, whereas GP-87 had the highest grain yield. Grain yield per plant, ear height, plant height, and cob weight exhibited the highest genotypic coefficient of variation. Cob weight. Among the traits, grain yield per plant, ear height, plant height, cob weight, and cob length showed a higher phenotypic coefficient of variation. The traits ear height, grain yield per plant, plant height, number of cobs per plant, cob length, number of kernels per row, cob weight, number of kernels per row per cob, anthesis to silking interval, shank weight, and days to 50% silking exhibited the highest heritability. Plant height, grain yield per plant, ear height, and cob weight were traits that showed higher genetic advances. These traits included grain yield per plant, ear height, plant height, cob weight, cob length, number of cobs per plant, tassel length, number of kernels per row, number of kernel rows per cob, 100-kernel weight, anthesis to silking interval, cob girth, and shank weight that showed higher genetic advance as a percent mean. The correlation coefficient indicates there is a significant positive correlation between grain yield and cob weight, number of cobs per plant, number of kernels per row, number of kernel rows per cob, 100 kernel weight, cob length, cob girth, plant height, ear height, shank weight, and tassel length at the phenotypic level. Grain yield per plant significantly positive correlation with cob weight, number of cobs per plant, number of kernels per row, number of kernel row per cob, 100 kernel weight, cob length, cob girth, plant height, shank weight, ear height, tassel length at the genotypic level the phenotypic level, the traits cob weight, 100 kernel weight, and plant height had the greatest direct impact on grain yield per plant. The traits were cob weight, number of kernel row per cob, 100 kernel weight showed higher direct effect on grain yield per plant at genotypic level.
The present investigation was carried out to assess the genetic variability parameters, correlation and path analysis in twenty-one maize genotypes for sixteen quantitative traits Kharif seasons at Field Experimentation Centre, Department of Genetics and Plant Breeding, Naini Agricultural Institute, Sam Higginbottom University of Agriculture Technology and Sciences, Uttar Pradesh in Randomized Block Design replicated thrice. Analysis of variance for all sixteen quantitative characters revealed that treatment differences were highly significant under study at 1% level in Kharif season. The present investigation objective was oriented to calculate and estimate yield traits through analyzing the mean performance, variability, expected genetic advance, correlation coefficient and path analysis involving the yield attributing characters. Among 21 genotypes, BML-13 (109.67), MGW-376 (108.93) genotypes were found to be superior for grain yield per plant over the check (Shaktiman-5). GCV for all the characters were less than PCV, indicating the influence of environmental component on the expression of the character. High heritability coupled with high genetic advance as percent mean in the present genotypes was recorded for traits plant height, ear height, grain rows per cob, cob weight, biological yield per plant, 100 grain weight, grain yield per plant. Path coefficient and Correlation analysis revealed that ear height, cob length, cob girth, grain rows per cob, grains per row, number of cobs per plant, cob weight and biological yield per plant had positive correlation and direct effects with grain yield per plant. Therefore, it is concluded that effective selection must be attempted for these traits which would help in improvement of grain yield in maize genotypes.
The present investigation was carried out to assess the genetic variability parameters, correlation and path analysis in the 23 genotypes of Blackgram during Zaid-2021 at the research field, Department of Genetics and Plant Breeding, Naini Agricultural Institute, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj. LBG-645 is identified as high seed yielding per plant at Prayagraj agro-climatic condition. The analysis of variance for all the characters revealed that genotypes were highly significant except harvest index (%). Genotypes were highly significant at 5%, 1% level for all the characters, indicating presence of considerable amount of genetic variability in the parental material tested. The characters with high range estimates of GCV and PCV number of clusters per plant, number of pods per plant. Heritability and genetic advance as % of mean values were high for number of pods per plant. The seed yield per plant exhibited positive significant and correlation with number of pods per plant at genotypic and phenotypic level. At genotypic and phenotypic path coefficient analysis revealed that number of pods per plant had greatest positive direct effect on seed yield per plant. Principal component (PC1) contributed maximum towards variability 22.808% was correlated with Seed Index followed by, plant height and number of seeds per pod. The second principal component (PC2) accounted 21.410% per cent of total variance and it reflected positive loading of days to 50% pod initiation, days to 50% flowering, and pod length whereas; the third principal component (PC3) accounted 15.642% per cent of total variance and positive loading of harvest Index followed by seed Index. Fourth principal component (PC4) contributed 11.325% of variability reflected loadings of days to maturity followed by seed yield per plant. The fifth principal component (PC5) contributed 9.489% variability of seed yield per plant, followed by days to 50% flowering.
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