Estimating and understanding crop yields with explainable deep learning in the Indian Wheat Belt

Forecasting crop yields is becoming increasingly important under the current context in which food security needs to be ensured despite the challenges brought by climate change, an expanding world population accompanied by rising incomes, increasing soil erosion, and decreasing water resources. Temperature, radiation, water availability and other environmental conditions influence crop growth, development, and final grain yield in a complex non-linear manner. Machine learning (ML) techniques, and deep learning (DL) methods in particular, can account for such non-linear relations between yield and its covariates. However, they typically lack transparency and interpretability, since the way t…