Selection Indices for Heat Tolerance Improvement in Bread Wheat

Aims: To establish a screening method for evaluating the contribution of key heat tolerance traits in the selection of heat-tolerant bread wheat genotypes Study Design: Randomized block design with three replicates. Place and Duration of Study: The field trial was conducted at the College Farm of N. M. College of Agriculture, Navsari Agricultural University, located at 20°37' N latitude and 72°54' E longitude. The farm is situated at an altitude of 11.98 meters above mean sea level, representing the South Gujarat agro-climatic zone known for heavy rainfall. Methodology: Heat stress poses a significant challenge in wheat cultivation, particularly during the flowering stage, severely impacting crop productivity. Developing wheat genotypes with enhanced performance under current and future high-temperature conditions remains a crucial objective for breeders. To achieve this, breeders prioritize specific traits by assigning relative weights to optimize the selection process for heat-tolerant genotypes, underscoring the relevance of selection indices. This study, we analyzed 48 bread wheat genotypes under heat stress conditions, utilizing 21 agro-physiological and quality traits. Through path analysis, five key traits, grain yield per plant (GYP), biological yield per plant (BYP), harvest index (HI), normalized difference vegetative index (NDVI) and chlorophyll content index (CCI) were identified as critical determinants of heat tolerance. Results: Using discriminant function analysis, we developed 31 selection indices to identify the most effective trait combinations for selection.  The index incorporating these five traits exhibited the highest relative and selection efficiency, offering breeders a practical approach to achieving substantial genetic gains with a minimal number of traits.  Notably, the selection indices involving chlorophyll content index and harvest index (X3 +X5) followed by grain yield/plant and harvest index (X1+X5), showed the highest relative efficiency per character, emphasizing their potential utility in heat-tolerance breeding programs. Conclusion: Overall, the findings indicate that the discriminant function method is more effective than direct selection based solely on grain yield, particularly under heat stress conditions. Importantly, the selection indices combining chlorophyll content index with harvest index (X₃ + X₅), and grain yield per plant with harvest index (X₁ + X₅), demonstrated the highest relative efficiency per trait. This underscores their relevance in identifying heat-tolerant genotypes. Therefore, prioritizing these key selection indices can significantly enhance the effectiveness of wheat breeding programs targeting improved grain yield and resilience under high-temperature environments.