Crop susceptible to drought and heat stress is increasing due to climate change. Consequently, new analytical strategies are urgently required to determine sources of adaptation, and pyramid them into new sustainable cultivars for food security. Here we offer an overview on how modeling analytical tools serve to predict crop adaptive responses to ongoing climate change. First, we will describe how climate data meets ecophysiology modeling in order to forecast in situ stresses. Second, we will encourage coupling these climate-based ecophysiological inferences with genomics, as proxy to model standing natural adaptation already contained within current crop landraces, and their wild relatives. Third, we will discuss genomic-enabled modeling alternatives to optimize the introgression of such adaptive genetic variation into elite customized cultivars. Finally, we will prospect alternative models that could boost de novo adaptive variation, such as in silico breeding models, speed breeding, and genome editing. Throughout this compilation of case studies and reflections, readers will be able to identify the need for more robust high-resolution ecological data, combined with explicit empirical summary statistics of the genomic diversity within crop genepools. Only then, ecophysiological-based models would meet genomic-enabled predictions of the adaptive potential in current crops, empowering sustainable food security in the face of climate change.
What will audience learn from your presentation?
- Predict crop adaptive responses to ongoing climate change
- Determine sources of adaptation, and pyramid them into new sustainable cultivars
- Empowering sustainable food security in the face of climate change