With the stagnancy of crop yield improvements, identifying new options to promote crop yields has become a major challenge for plant biologists and breeders. A large number of experimental and theoretical studies showed that improving canopy photosynthesis is one of the few remaining options to dramatically increase crop yields.

Leaf area index, canopy architecture and leaf photosynthetic properties jointly determine canopy photosynthetic rate. Traditional breeding in the past few decades has improved canopy photosynthesis mainly through manipulating canopy architecture. However, little has been done to improve leaf photosynthetic properties mainly due to the lack of effective parameters to select during the breeding programs.

Recently, Prof. ZHU Xinguang and his colleagues at the Shanghai Institute of Plant Physiology and Ecology of Chinese Academy of Sciences developed a natural diversity panel including 215 rice cultivars.

In this study, global linear regression model was applied to compare the relatedness of photosynthetic traits themselves and that to biomass, across single growth condition or combined growth condition from two growing sites. To identify the key photosynthetic traits attributing to phenotypic variation of biomass, researchers used a stepwise feature selection approach based on linear regression model.

During model processing, the 90% dataset was chosen as training model, and remaining 10% was to test model for cross validation. The results demonstrated the employed model was well-performance with R2=0.6~0.8. Taken together, photosynthetic rate under low light (A_low) was pointed out to be key traits correlated to biomass accumulation from 200 times imputation.

Furthermore, 2.3M filtered SNPs from the 215 rice cultivars were employed to determine genomic heritability regarding key photosynthetic traits－A_low. The results revealed that A_low is stably inheritable, and the SNP-based heritability is above 0.3 across two growth conditions, suggesting its great potential as a breeding target in the future rice high-yield breeding programs.

The findings were published online in Plant Physiology. The study was funded by the Strategic leading project of the Chinese Academy of Sciences, Ministry of Science and Technology of China, the National Science Foundation of China, Bill and Melinda Gates Foundation and Shanghai Natural Science Foundation.