Environmental concerns of the general public, droughts, and climate change effects require continual adaptation and optimization of agricultural systems through changes in cropping and management. Advancement of science and technology to achieve these changes requires cutting-edge field research, using a quantitative whole-system approach. Process-based models of agricultural systems integrated with field research provide such a systems approach. The models help: 1) quantify field research results in terms of the fundamental theory and concepts that are broadly applicable beyond the site-specific empirical relationships, 2) predict experimental results from knowledge of the fundamental factors that determine the environment and plant growth under different climates, 3) extend the experimental results to longer term weather conditions beyond the limited duration of the field experiments and to other soil types and climates in the area outside the experimental plots, and 4) use extended results to develop broad-based precision management decision support tools or simple management guidelines for producers and other users, which may include linkage to economic and social considerations. As a result, the models are also continually improved and serve as an evolving theoretical backbone of complex agricultural system research and information transfer. In the last three decades, considerable progress has been made on the applications of models for evaluating and improving current agricultural systems for optimal management of water, nutrients, and cultivar resources under varying climates, especially in developed countries. Importantly, these applications were made in collaboration with field research scientists at several locations. Key areas of further trans-disciplinary research, synthesis, and improvement of the modeling backbone have also been identified.

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