{"title":"Bridging Photosynthesis and Crop Yield Formation with a Mechanistic Model of Whole Plant Carbon-Nitrogen Interaction","authors":"Tianxin Chang, Zhongwei Wei, Zai Shi, Yi Xiao, Honglong Zhao, Shuoqi Chang, Mingnan Qu, Qingfeng Song, Faming Chen, Fenfen Miao, Xinguang Zhu","doi":"10.1093/insilicoplants/diad011","DOIUrl":null,"url":null,"abstract":"\n Crop yield is determined by potential harvest organ size, source organ photosynthesis, and carbohydrate partitioning. Filling the harvest organ efficiently remains a challenge. Here, we developed a kinetic model of rice grain filling, which scales from the primary biochemical and biophysical processes of photosynthesis to whole-plant carbon and nitrogen dynamics. The model reproduces the rice yield formation process under different environmental and genetic perturbations. In silico screening identified a range of post-anthesis targets—both established and novel—that can be manipulated to enhance rice yield. Remarkably, we pinpointed the stability of grain filling rate from flowering to harvest as a critical factor for maximizing grain yield. This finding was further validated in two independent super-high yielding rice cultivars, each yielding approximately 21 t ha -1 of rough rice at 14% moisture content. Furthermore, we revealed that stabilizing the grain filling rate could lead to a potential yield increase of around 30-40% in an elite rice cultivar. Notably, the cumulative grain filling rates around 15- and 38-days post-flowering significantly influence grain yield, and we introduced an innovative in situ approach using ear respiratory rates for precise quantification of these rates. We finally derived an equation to predict maximum dried brown rice yield (Y, t ha -1) of a cultivar based on its potential gross photosynthetic accumulation from flowering to harvest (Apc, t CO2 ha -1): Y = 0.74 * Apc + 1.9. Overall, this work establishes a framework for quantitatively dissecting crop physiology and designing high-yielding ideotypes.","PeriodicalId":36138,"journal":{"name":"in silico Plants","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"in silico Plants","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/insilicoplants/diad011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 0
Abstract
Crop yield is determined by potential harvest organ size, source organ photosynthesis, and carbohydrate partitioning. Filling the harvest organ efficiently remains a challenge. Here, we developed a kinetic model of rice grain filling, which scales from the primary biochemical and biophysical processes of photosynthesis to whole-plant carbon and nitrogen dynamics. The model reproduces the rice yield formation process under different environmental and genetic perturbations. In silico screening identified a range of post-anthesis targets—both established and novel—that can be manipulated to enhance rice yield. Remarkably, we pinpointed the stability of grain filling rate from flowering to harvest as a critical factor for maximizing grain yield. This finding was further validated in two independent super-high yielding rice cultivars, each yielding approximately 21 t ha -1 of rough rice at 14% moisture content. Furthermore, we revealed that stabilizing the grain filling rate could lead to a potential yield increase of around 30-40% in an elite rice cultivar. Notably, the cumulative grain filling rates around 15- and 38-days post-flowering significantly influence grain yield, and we introduced an innovative in situ approach using ear respiratory rates for precise quantification of these rates. We finally derived an equation to predict maximum dried brown rice yield (Y, t ha -1) of a cultivar based on its potential gross photosynthetic accumulation from flowering to harvest (Apc, t CO2 ha -1): Y = 0.74 * Apc + 1.9. Overall, this work establishes a framework for quantitatively dissecting crop physiology and designing high-yielding ideotypes.