Incorporating genetics into crop models to identify new phenotypes adapted to climate change

Code: 9781801469050
Publication date: 25/07/2023
Extent: 30 pages

Contributions by: Carlos D. Messina, Institute of Food and Agricultural Sciences (IFAS), University of Florida, USA and The ARC Centre of Excellence for Plant Success in Nature and Agriculture, Australia; and Mark Cooper, The Queensland Alliance for Agriculture and Food Innovation (QAAFI) and The ARC Centre of Excellence for Plant Success in Nature and Agriculture, Australia

Chapter synopsis:

This chapter proposes a framework to develop new genotype (G) x management (M) technologies (G x M) to adapt to climate change, and to transition from current to future G x M technologies in a way that future food security does not come at the expense of current food security. The framework integrate genomic, agronomic, and environmental (E) predictors to accomplish two critical goals: 1-predict emergent phenotypes that stems from the dynamic interplay between G, E and M, and thus enable the breeder to consider the behavior of new genetic and trait combinations in environments that plants have not been exposed or tested before, and 2-identify G x M technologies that could increase food and nutritional security while regenerating natural and production resources.



DOI: 10.19103/AS.2022.0115.04
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Table of contents
  • 1 Introduction
  • 2 Systems analyses and models of crop growth
  • 3 Linking genetics and physiology for phenotypic prediction
  • 4 Models that predict emergent phenotypes
  • 5 Integrating environmental and genomic predictions using crop models
  • 6 Assessing impacts of traits and their underpinning genetics on crop performance
  • 7 Managing genotype environment interactions to optimize rather than hamper genetic gain in current and future climates
  • 8 Predictive breeding enables iterative impact assessment and adaptation to climate change
  • 9 Crop growth models can enable a rethinking of breeding objectives to adapt to and combat climate change
  • 10 Conclusion and future trends
  • 11 References

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