Testing the Contribution of Stress Factors to Improve Wheat and Maize Yield Estimations Derived from Remotely-Sensed Dry Matter Productivity

Abstract

According to Monteith’s theory, crop biomass under non-stressed conditions is linearly correlated with the amount of absorbed photosynthetically active radiation (APAR) and the radiation use efficiency (RUE). RUE is set as a constant and subsequently down-regulated by stress factors such as the CO2 fertilisation, temperature and water stress. The relative importance of these stress factors partially determines regional biomass production and yield. The production efficiency model Copernicus Global Land Service - Dry Matter Productivity (CGLS-DMP) was modified and evaluated for common wheat and silage maize in France, Belgium and Morocco using SPOT VEGETATION. For each study site the stress factor which has the highest correlation with crop yield was retained. The correlation between crop yield data and cumulative modified DMP, CGLS-DMP, fAPAR, and NDVI values were analysed for different crop growth stages. A leave-one-year-out cross validation was used to test the robustness of the model. On average, R² values increased from 0.49 for CGLS-DMP to 0.69 for modified DMP, RMSE (t/ha) decreased from 0.84 to 0.59, RRMSE (%) reduced from 13.1 to 8.7 and the index of model performance (E1) increased from 0.08 to 0.29 for the selected sites and crops.