Many studies have applied machine learning to crop yield prediction with a focus on specific
case studies. The data and methods they used may not be transferable to other crops and …

Mycotoxins in small grains are a significant and long-standing problem. These contaminants
may be produced by members of several fungal genera, including Alternaria, Aspergillus …

Grass pollen is a leading cause of allergy in many countries, particularly Europe. Although
many elements of grass pollen production and dispersal are quite well researched, gaps still …

Abstract Machine learning models for crop yield forecasting often rely on expert-designed
features or predictors. The effectiveness and interpretability of these handcrafted features …

Crop yield forecasting at national level relies on predictors aggregated from smaller spatial
units to larger ones according to harvested crop areas. Such crop areas come from land …

Timely and reliable in-season forecasting of crop yield is crucial for regional and national
agricultural management. To improve the winter wheat yield prediction accuracy at the …

This study focuses on the northward shift of homogeneous agro‐climate zones in Europe
analyzed for the observed past and projected climate conditions for the next decades …

Accurate and timely crop yield forecasts can provide essential information to make
conclusive agricultural policies and to conduct investments. Recent studies have used …

Developing an accurate crop yield predicting system at a large scale is of paramount
importance for agricultural resource management and global food security. Earth …

It is important to investigate the potential impacts of global climate change on crop yield
especially there have been limited relevant studies conducted in the cold regions such as …