The potential of considering photosynthesis parameters in crop yield breeding by genomic prediction.

To meet the growing demand for agricultural products, optimizing photosynthesis is a promising strategy to improve crop yields. Phenotypic variance in photosynthesis has been observed within or between species. To explore the potential of integrating photosynthetic parameters into crop breeding programs, we explored the genetic variation in photosynthesis by assessing photosynthesis-related parameters across plant development in 631 barley recombinant inbred lines (RILs) from eight HvDRR subpopulations under field conditions. The genetic complexity of these parameters was resolved by analyses of bi-parental and multi-parental quantitative trait loci (QTLs). Finally, we examined the merit of integrating photosynthesis-related parameters in genomic prediction of yield and its components. Significant genotypic variations of the photosynthesis-related parameters were found among the RILs, with their heritability ranging from 0.38 to 0.54. The multiple QTLs and dynamic QTLs for photosynthesis observed across different developmental stages underlined the complexity of the genetics of photosynthesis in barley. The considerably higher percentage of phenotypic variance explained for genomic prediction than multi-parental QTL analysis illustrates that the photosynthesis-related parameters are inherited in a more complex way than classical agronomic traits. Notably, the prediction ability for yield was increased by integrating the photosynthesis-related parameters of some developmental stages into genomic prediction models. Thus, our results suggest a novel perspective on increasing the efficiency of crop breeding programs by integrating photosynthesis-related parameters into prediction models.