Sustainable intensification has been proposed as a pathway to achieve food security and
reduce environmental impacts of agriculture by focusing on narrowing yield gaps on existing …

Yield prediction models can be divided between data-driven and process-based models
(crop growth models). The first category contains many different types of models with …

With an annual production of∼ 60 Mt, the US accounts for about 8% of the global wheat
(Triticum aestivum L.) production. Still, quantification of the yield gaps (YG) and major …

Context Collection and analysis of large volumes of on-farm production data are widely seen
as key to understanding yield variability among farmers and improving resource-use …

Crop production is at the core of a 'perfect storm'encompassing the grand challenges of
achieving food and nutrition security for all, in the face of climate change, while avoiding …

The increasing availability of complex, geo-referenced on-farm data demands analytical
frameworks that can guide crop management recommendations. Recent developments in …

A large database of individual farmer field data (n= 4,107) for rice production in the
Northwestern Indo-Gangetic Plains of India was used to decompose rice yield gaps and to …

Nitrogen (N) management is important for farmers to balance production, economic and
environmental performance of their farms. This is particularly true in the intensive cropping …

Context Yield gap analyses are useful to assess and benchmark the productivity of cropping
systems. Often such analyses are performed at higher aggregation levels. As a result, these …

Crop yields are determined by the biophysical environment and by farm management
decisions, which in turn depend on socio-economic conditions of the farm (er). The …