Tracking paddy rice yield using solar-induced chlorophyll fluorescence and a mechanistic light-response model in the middle and lower reaches of the Yangtze River

Abstract Crop yield estimations facilitate effective crop management, contributing to global food security and cropland sustainability. Solar-induced chlorophyll fluorescence (SIF), consisting of actual photosynthetic activity, is closely related to gross primary productivity. However, it is unclear whether paddy rice yield can be effectively estimated by SIF. Here, we used a mechanistic light reaction (MLR) model and SIF data coupled with rice phenology and climate information to estimate net primary productivity (NPP). Subsequently, we used a harvest index (HI) based on absorbed photosynthetically active radiation data in combination with NPP to estimate paddy rice yield in the middle and lower reaches of the Yangtze River from 2001 to 2019. The results showed that the MLR model coupled with SIF was excellent in estimating crop yield, showing a high correlation between simulated and actual yield ( R 2 = 0.71 on average, P < 0.01). NPP rather than HI was the predominant factor influencing paddy rice yield. Photosynthetically active radiation presents a more pronounced effect on paddy rice yield (early and single rice) than that of air temperature and precipitation. These findings emphasize the crucial role of SIF in estimating large-scale crop yields.