Agricultural Innovization: An Optimization-Driven solution for sustainable agricultural intensification in Michigan

Humanity, now increasingly populous and affluent, poses a new challenge for the twentieth-first century farmer: increase food supply while maintaining the earth's underlying ecosystems. This paper proposes a novel systems approach, agricultural innovization, to sustainably increase food production. Innovization applies the knowledge obtained through multi-objective optimization to discover new agricultural management practices which reduce the risk of climate variabilities on crop yields. In agricultural innovization, an optimization platform generated the near-optimal management actions for 30 years using a calibrated crop model for maize. From those near optimal solutions, recommendations for improving management practices were data mined. Then these improved recommended practices were evaluated over 420 validation seasons. The validation results were promising as the recommended practices obtained from the innovization increased yields and generated no negative change in nitrogen leaching. Furthermore, these recommendations can be applied to future seasons of management, which makes them a fully predictive application of multi-objective optimization.

Automated summary

This paper proposes a novel systems approach, called agricultural innovization, to sustainably increase food production. The method applies the knowledge obtained through multi-objective optimization to discover new agricultural management practices that reduce the risk of climate variabilities on crop yields.