Quantitative Genetic Analysis of Cotton Traits: GCA, Gene Action and Proportion of Variance via Line × Tester Design

Background Cotton plant faces various biotic and abiotic stresses from its environment and among these stresses, high temperature is a limiting factor to cotton productivity. The temperature has increased gradually worldwide due to climate change. Therefore, there is a dire need to identify genotypes against high temperature stress. For this purpose, an experiment was designed to identify high temperature resilient genotypes. The hybrids were made on already identified parents under line × tester pattern and then F ₀ seeds were sown in two planting dates, early sowing for high temperature stress and late sowing for control. Hybrid population was assessed on the basis of general combining ability. The physiological parameters namely pollen germination, pollen viability, CMT, biochemical assays namely proline, POD were estimated according to recommended protocol at the onset of flowering in both conditions. Additionally, various yield parameters were also observed at harvesting. The collected data were analyzed by using various biometrical approaches to determine the presence of genetic diversity and response of genotypes under both treatments. Results The results showed that high temperature significantly effect on cotton and it also showed a critical role of non-additive genetic effects in various traits. The interaction between L × T is vital for achieving yield, especially under high-temperature conditions. Combining ability assessment revealed that three lines namely FH-Lalazar, AGC-999 and VH-329 were considered superior parental lines particularly under high temperature stress. These parents can be used to make synthetic cultivar to combat temperature stress problem. Conclusion The findings emphasized the importance of additive and non-additive genetic effects in breeding programs, especially for improving traits under stress, and it suggest that hybrid breeding might be the most effective strategy for enhancing yield parameters under various environmental challenges.