State spaces for agriculture: a metasystematic design automation framework.

Agriculture is a designed system with the largest areal footprint of any human activity. In some cases, the designs within agriculture emerged over thousands of years, such as the use of rows for the spatial organization of crops. In others, designs were deliberately chosen and implemented over decades as occurred during the Green Revolution. Currently, much work in agricultural science is focused on evaluating designs that could improve agriculture's sustainability. However, approaches to agricultural system design are diverse and fragmented, relying on individual intuition and discipline-specific methods for how to meet stakeholders' often semi-incompatible goals. This presents a risk that agricultural science will overlook non-obvious designs with large societal benefits. Here, we introduce a state space framework, a common approach from computer science, for agriculture to address the problem of proposing and evaluating designs computationally. This approach overcomes current limitations of agricultural system design by enabling a general set of computational abstractions to explore, and then select from, a much larger agricultural design set, which can then be empirically tested.