Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security

Christensen, A. J.; Srinivasan, V.; Hart, J. C.; Marshall-Colon, A.

doi:10.1093/nutrit/nux076

Title: Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security

Journal Article · Sat Mar 17 00:00:00 EDT 2018 · Nutrition Reviews

DOI:https://doi.org/10.1093/nutrit/nux076· OSTI ID:1438248

Christensen, A. J. ^[1]; Srinivasan, V. ^[2]; Hart, J. C. ^[3]; Marshall-Colon, A. ^[4]

Univ. of Illinois, Urbana-Champaign, IL (United States). National Center for Supercomputing Applications (NCSA)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Univ. of Illinois, Urbana-Champaign, IL (United States). Dept. of Computer Science
Univ. of Illinois, Urbana-Champaign, IL (United States). Dept. of Plant Biology

Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have led to discoveries in “big data” analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. Lastly, this survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.

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Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE; National Science Foundation (NSF); Bill and Melinda Gates Foundation; Foundation for Food and Agriculture Research (FFAR)

Grant/Contract Number:: AC05-76RL01830; 515760

OSTI ID:: 1438248

Journal Information:: Nutrition Reviews, Vol. 76, Issue 5; ISSN 0029-6643

Country of Publication:: United States

Language:: English

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Cited by: 13 works

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