Modelling plants across scales of biological organisation for guiding crop improvement
Alex Wu
A *
+ Author Affiliations
- Author Affiliations
A Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, Qld, Australia.
Functional Plant Biology 50(6) 435-454 https://doi.org/10.1071/FP23010
Submitted: 10 January 2023 Accepted: 6 April 2023 Published: 28 April 2023
© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution 4.0 International License (CC BY)
Abstract
Grain yield improvement in globally important staple crops is critical in the coming decades if production is to keep pace with growing demand; so there is increasing interest in understanding and manipulating plant growth and developmental traits for better crop productivity. However, this is confounded by complex cross-scale feedback regulations and a limited ability to evaluate the consequences of manipulation on crop production. Plant/crop modelling could hold the key to deepening our understanding of dynamic trait–crop–environment interactions and predictive capabilities for supporting genetic manipulation. Using photosynthesis and crop growth as an example, this review summarises past and present experimental and modelling work, bringing about a model-guided crop improvement thrust, encompassing research into: (1) advancing cross-scale plant/crop modelling that connects across biological scales of organisation using a trait dissection–integration modelling principle; (2) improving the reliability of predicted molecular–trait–crop–environment system dynamics with experimental validation; and (3) innovative model application in synergy with cross-scale experimentation to evaluate G × M × E and predict yield outcomes of genetic intervention (or lack of it) for strategising further molecular and breeding efforts. The possible future roles of cross-scale plant/crop modelling in maximising crop improvement are discussed.
Keywords: APSIM, crop dynamics, cross-scale modelling, G × M × E, genetic engineering, photosynthesis, plant/crop physiology, trait dissection, yield improvement.
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