Optimising the specific adaptation of sorghum in variable water-limited environments in Australia

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ID: 330062
2026
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Abstract
Abstract Crop productivity outcomes emerge from complex interactions among genotype (G), management (M), and environment (E). These G×M×E interactions complicate crop improvement and the identification of strategies that maximise yield while minimising production risk. Conventional crop improvement largely focuses on broad adaptation, seeking crop design solutions that perform well across the target population of environments (TPE). However, this approach can be constrained by substantial yield-risk trade-offs. This study quantified opportunities associated with broad adaptation and water-limitation environment type (ET)-specific adaptation to support crop design optimisation. Resource capture factors (planting density, leaf number, leaf size, fertile tiller number) were evaluated alone and in combination with resource use efficiency traits related to photosynthesis and stomatal conductance. Optimal trait combinations were identified for the Australian sorghum TPE and ET-specific scenarios. Results showed that ETs provided an effective framework for dissecting G×M×E interactions and identifying ET-specific crop designs that substantially reduced yield-risk trade-offs. Optimisation of resource capture factors alone produced modest gains (∼5%) in average yield in the dominant ETs within the TPE, but larger gains (∼15-20%) in niche ETs. In contrast, incorporating resource use efficiency traits was predicted to generate consistent ∼15% gains in average yield and ∼12% improvements under risky conditions across all ETs. The value of individual resource use efficiency traits differed among ETs, with enhanced photosynthetic capacity contributing most in low water-stress ETs and reduced conductance being most beneficial in high water-stress ETs. These findings highlight opportunities for improving Australian sorghum production and demonstrate the value of combining crop design optimisation with environment characterisation to guide improvement in water-limited environments.
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openalex_W7214575926 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors
Journal in silico Plants
Year 2026
DOI
10.1093/insilicoplants/diag027
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