Computational design for more engaged, impactful, and dynamic agricultural research

Abstract Computational design in agriculture is the use of data‐driven systems and tools to propose and evaluate alternative configurations of agricultural systems. It is unique from digital agriculture in that it integrates computational and crop science approaches to formulate problems rather than mitigating problems by applying digital technologies. In this special issue, we highlight how computational design could be used to adapt agricultural systems to better meet societal goals more rapidly and at lower cost. Many disciplines within crop sciences are represented, from breeding to cropping systems agronomy. Using a symposium at a major scientific conference as a case study, we also demonstrate how this framing of computational design can facilitate transdisciplinary research. Critically, all participants highlighted the potential of computational design to facilitate stakeholder engagement through eliciting, formalizing, and evaluating their values and experiences. This is especially important within the grand challenge contexts of changing climates and market demands, where intuition developed in the past may break down. By leveraging the power of computational design, we can make informed decisions to create agricultural systems that maximize productivity while minimizing environmental impact under current and future environments.

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Institutions

Publication Details

Journal
Crop Science
Published
2025-03-01
DOI
https://doi.org/10.1002/csc2.70034
Citations
1
Primary Topic
Greenhouse Technology and Climate Control
Type
article
Field-Weighted Citation Impact
1.75

Funders

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article

Computational design for more engaged, impactful, and dynamic agricultural research

Jacob M. Jungers, Barath Raghavan, Jasdeep Singh, Nathan Fumia et al.
1 citations
Crop Science
Greenhouse Technology and Climate Control
1.75
article

Computational design for more engaged, impactful, and dynamic agricultural research

Jacob M. Jungers, Barath Raghavan, Jasdeep Singh, Nathan Fumia, Ismail Ibrahim Garba, Harsh Pathak, Diane Wang, Bryan C. Runck, Jean‐Luc Jannink, Siddhartho Shekhar Paul, Sajad Jamshidi, V.R. Joshi, Jon Bančič, Samikshya Subedi, Michael Benjamin Kantar, Patrick M. Ewing, Prakash Jha
article en
1 citations

Abstract

Abstract Computational design in agriculture is the use of data‐driven systems and tools to propose and evaluate alternative configurations of agricultural systems. It is unique from digital agriculture in that it integrates computational and crop science approaches to formulate problems rather than mitigating problems by applying digital technologies. In this special issue, we highlight how computational design could be used to adapt agricultural systems to better meet societal goals more rapidly and at lower cost. Many disciplines within crop sciences are represented, from breeding to cropping systems agronomy. Using a symposium at a major scientific conference as a case study, we also demonstrate how this framing of computational design can facilitate transdisciplinary research. Critically, all participants highlighted the potential of computational design to facilitate stakeholder engagement through eliciting, formalizing, and evaluating their values and experiences. This is especially important within the grand challenge contexts of changing climates and market demands, where intuition developed in the past may break down. By leveraging the power of computational design, we can make informed decisions to create agricultural systems that maximize productivity while minimizing environmental impact under current and future environments.

Crop ScienceVol. 65(2)
University of Southern California (US), University of Hawaiʻi at Mānoa (US), University of Minnesota (US), Agricultural Research Service (US), Roslin Institute (GB), The University of Queensland (AU), Purdue University West Lafayette (US), University of Florida (US), Hawaii Agriculture Research Center (US), Agriculture and Food (AU), University of California Division of Agriculture and Natural Resources (US), Robert W. Holley Center for Agriculture & Health (US), University of California, Davis (US), University of Edinburgh (GB)
National Institute of Food and Agriculture
Openalex Percentile: Top 17%
Greenhouse Technology and Climate Control
1.75
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