Trait-based model development to support breeding programs. A case study for salt tolerance and rice.

Area of Science:

• Agronomy
• Plant Physiology
• Computational Biology

Background:

• Eco-physiological models aid genotype × environment × management (G×E×M) interactions analysis for breeding.
• Existing models often lack direct links to breeder-selected traits, limiting their utility.
• Salt stress tolerance in rice is a complex trait influenced by multiple physiological processes.

Purpose of the Study:

• To propose a paradigm shift towards ideotyping-specific models tailored for breeding programs.
• To develop and evaluate a novel eco-physiological model explicitly incorporating traits relevant to salt stress tolerance in rice.
• To demonstrate the utility of a trait-based modeling approach for supporting crop breeding.

Main Methods:

• Developed a new eco-physiological model focusing on specific traits for salt stress tolerance.
• Utilized growth chamber experiments to collect data for model evaluation.
• Analyzed model performance using metrics such as R-squared for biomass prediction.

Main Results:

• The new model demonstrated strong performance, with R-squared values ranging from 0.74 to 0.94 for predicting biomass of different plant organs.
• The model successfully illustrated how different physiological mechanisms can lead to enhanced salt tolerance depending on salinity dynamics.
• Model simulations showed the potential for diverse breeding strategies to achieve improved crop tolerance.

Conclusions:

• A trait-based approach significantly enhances the applicability of mathematical models in breeding programs.
• The developed ideotyping-specific model provides a valuable tool for designing targeted breeding strategies for salt stress tolerance.
• This modeling paradigm facilitates the development of climate-resilient crops by linking physiological traits to breeding objectives.