The following study comprised an evaluation of 21 genotypes, which includes six parental genotypes and 15 half-diallel F1 hybrids, applying the path coefficient analysis. The experiment, carried out in 2022 on upland cotton, used a randomized complete block design (RCBD) with three replications at the Musayyib Technical College of Babylon Governorate, Iraq. Path coefficient analysis enabled researchers to divide the correlation coefficient into direct and indirect effects, determining the relative contribution of each trait to seed cotton yield. The correlation analysis showed the seed cotton yield had a significant positive correlation with traits, such as the boll number, weight, ginning outturn, and seed index. The path coefficient analysis disclosed the seed cotton yield had considerable and direct effects from the ginning outturn and boll number. Correlation coefficient estimates indicated the ginning outturn contribution reached 21.12%, with the said trait becoming useful as a selection criterion to improve seed cotton yield. The coefficient contributions of the seed index and boll number were 11.49% and 8.83%, respectively, and the rest of the effects were 39.92%. The results revealed that the coefficient of determination of traits holds the highest relative importance as a major component of seed cotton yield. Breeders can use these estimates as selection criteria to enhance seed cotton yield in future breeding programs.
Upland cotton (G. hirsutum L.), half-diallel cross, path analysis, yield-related traits, seed cotton yield
Path coefficient analysis revealed the correlation coefficient of various traits holds the highest relative importance in managing seed cotton yield in upland cotton (G. hirsutum L.).