Integrating optimization with thermodynamics and plant physiology for crop ideotype design

TL;DR

This paper presents a computational framework that combines plant physiology modeling with optimization algorithms to design crop ideotypes optimized for specific environmental conditions, aiding climate-resilient crop development.

Contribution

The study introduces a novel integrated framework coupling detailed plant physiological models with genetic algorithms for crop ideotype optimization under varying environmental scenarios.

Findings

Identified maize ideotypes with enhanced photosynthetic yields.

Demonstrated the framework's ability to explore trait configurations for water use efficiency.

Showed potential to inform breeding strategies for climate resilience.

Abstract

A computational framework integrating optimization algorithms, parallel computing and plant physiology was developed to explore crop ideotype design. The backbone of the framework is a plant physiology model that accurately tracks water use (i.e. a plant hydraulic model) coupled with mass transport (CO2 exchange and transport), energy conversion (leaf temperature due to radiation, convection and mass transfer) and photosynthetic biochemistry of an adult maize plant. For a given trait configuration, soil parameters and hourly weather data, the model computes water use and photosynthetic output over the life of an adult maize plant. We coupled this validated model with a parallel, meta-heuristic optimization algorithm, specifically a genetic algorithm (GA), to identify trait sets (ideotypes) that resulted in desired water use behavior of the adult maize plant. We detail features of the model as well as the implementation details of the coupling with the optimization framework and deployment on high performance computing platforms. We illustrate a representative result of this framework by identifying maize ideotypes with optimized photosynthetic yields using weather and soil conditions corresponding to Davis, CA. Finally, we show how the framework can be used to identify broad ideotype trends that can inform breeding efforts. The developed presented tool has the potential to inform the development of future climate-resilient crops.