Correlation and Path Coefficient Analysis for Grain Yield Components in Maize (Zea mays L.)

Abstract

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.

Studies on Character Association and Path Coefficient Analysis for Grain Yield and Its Contributing Characters in Maize (Zea mays L.)

“…(G-0.6122, P-0.5355), shelling % (G-05789, P-0.4236) also has positive significant association with grain yield. These observations are in agreement with the findings of Kharel et al, [15] and Reddy et al, [16] for plant height, Synrem et al, [17] and Reddy et al, [18] for no. of kernel rows, Jawaharlal et al, (2017) for 100 kernel weight, Kumar et al, (2014) for shelling %.…”

Transgressive Segregant of Tomato F4 Populations Based on Fruit Yield and Lycopene Content

“…Narrow-sense heritability is the proportion of total additive variance of phenotypic variance, and it is also vital in the selection process in plant breeding, particularly in the selection of elite genotypes from the populations (Reddy and Jabeen, 2016). Narrow and broad sense heritability in the supporting production trait showed wider differences in heritability values, where the rate of the broadsense heritability is normal (0%-100%), while the narrow-sense heritability values were lower to very high.…”

“…The path analysis findings helped determine the best selection criteria. The narrow-sense heritability estimates with genetic advance were typically helpful in predicting the gain under selection than heritability estimates alone (Reddy and Jabeen, 2016). Selecting transgressive segregants in F4 populations depended on traits with a high value of narrow-sense heritability.…”

Interactive effects of emitter type, water salinity, and deficit irrigation on of red cabbage (Brassica oleracea L) with evaluating drip irrigation system

“…A difference between the two types of emitters with the quality of water irrigation did not show a marked difference in results. This indicates the efficiency of the emitter on a good distribution of water and a positive effect on the studied qualities [33]. A difference in the manufacture, type of emitter and water salinity lead to a change in the water flow rate [34].…”