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DOI:10.31220/agriRxiv.2022.00158
声明:预印本系统所发表的论文仅用于最新科研成果的交流与共享,未经同行评议,因此不建议直接应用于指导生产实验。

State spaces for agriculture: a metasystematic design automation framework.

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    Abstract: Abstract 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.

    Key words: agriculture; designs; approach; agricultural; system design; evaluatin

    提交时间:2022-01-01

    版权声明:作者本人独立拥有该论文的版权,预印本系统仅拥有论文的永久保存权利。任何人未经允许不得重复使用。
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引用格式

Bryan C. Runck, Adam Streed, Diane Wang, Patrick M. Ewing, Michael B. Kantar, Barath Raghava. State spaces for agriculture: a metasystematic design automation framework.. 2022. agriXiv.2022.00158

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