Crop growth models dynamically simulate processes of C, N and water balance on daily or
hourly time‐steps to predict crop growth and development and at season‐end, final yield …

Accurate predictions of crop yield are critical for developing effective agricultural and food
policies at the regional and global scales. We evaluated a machine-learning method …

Potential consequences of climate change on crop production can be studied using
mechanistic crop simulation models. While a broad variety of maize simulation models exist …

Elevated atmospheric CO 2 concentrations ([CO 2]) cause direct changes in crop
physiological processes (eg photosynthesis and stomatal conductance). To represent these …

Accurate prediction of phenological development in maize (Zea mays L.) is fundamental to
determining crop adaptation and yield potential. A number of thermal functions are used in …

Fast, accurate and inexpensive estimates of crop yields at the field scale are useful for many
applications. Based on the Google Earth Engine (GEE) platform, we recently developed a …

Smallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited
inputs including fertilizer. Climate change may exacerbate current production constraints …

Crop yield can be affected by crop water use and vice versa, so when trying to simulate one
or the other, it can be important that both are simulated well. In a prior inter-comparison …

Crop canopy parameters are critical for environmental remote sensing, describing crop
phenotypes, and ensuring food security. Evaluating the effect of temperature on crop growth …

Temperatures over the next century are expected to rise to levels detrimental to crop growth
and yield. As the atmosphere warms without additional water vapor input, vapor pressure …