The perfect knowledge of yield before harvest has been a wish puzzling human being since
the beginning of agriculture because seasonal forecast of crop yield plays a critical role in …

Assessments of the relationships between crop productivity and climate change rely upon a
combination of modelling and measurement. As part of this review, this relationship is …

This study investigates whether coupling crop modeling and machine learning (ML)
improves corn yield predictions in the US Corn Belt. The main objectives are to explore …

The emergence of new technologies to synthesize and analyze big data with high-
performance computing has increased our capacity to more accurately predict crop yields …

Abstract The Crop Environment Resource Synthesis (CERES) models have been developed
and utilized for the last 30 years to simulate crop growth in response to climate, soil …

The application of machine learning in crop yield prediction has gained considerable
traction, yet uncertainties persist regarding the impact of the yield trends on these …

China is one of the top maize exporting countries in the world. In China, maize is the most
important staple food crop, and Northeast China is one of the main maize-growing regions …

This study underscores the critical importance of accurate crop yield information for national
food security and export considerations, with a specific focus on wheat yield estimation at …

Coupling remote sensing data with a crop growth model has become an effective tool for
estimating grain yields and assessing grain quality. In this study, a data assimilation …

Worldwide, cereals are of great interest for national food security. The recently released free
Sentinel 2 imagery is promising for cereal production systems management, both at field …