Growth Simulation Outputs for Detection of Differential Cultivar Response to Environmental Factors

Abstract

Despite considerable research on genotype‐environment (GE) interactions, breeders still need a simple way to describe the specificity of each genotype's response to environmental factors. A new approach is suggested based on (i) use of growth simulation outputs (simulated water deficit, anthesis date, maximum leaf area) as environmental indices, (ii) use of simulated yield as a check, and (iii) use of simple correlation coefficients to describe the association between environmental indices and deviations from the average difference computed for each pair entry‐check. Simulated grain yield can be considered a better indicator of environmental adaptability, unaffected by factors like diseases, lodging, or winter‐kill that can reduce the average yield in the best environments. Other outputs of simulation models, which integrate weather and soil factors with proper timing according to plant development, can provide a better description of environments than the raw weather data. Yield data of sixteen wheat (Triticum aestivum L.) genotypes, grown at three locations in Oregon for a 5‐yr period (1988‐1992) were analyzed. Correlation with water availability indices clearly differentiated the cultivars that were unable to adapt to improved environments, because of lodging and/or disease susceptibility. Correlation with other environmental indices identified genotypes that responded more to low winter temperatures, to high temperatures after anthesis, or to delayed anthesis following cooler springs. The results indicated that the use of outputs from growth simulation models as covariates in analysis of GE interaction could be a useful tool in characterizing differential responses of genotypes to environmental factors.