Challenge Rising global temperatures and frequent heatwaves are threatening crop productivity by impairing Photosystem II (PSII), a critical component of photosynthesis. The PSII heat tolerance threshold (Tcrit) indicates the temperature at which photosynthetic function begins to fail. However, current methods to measure Tcrit are slow, invasive, and unsuitable for large-scale breeding programs, creating a bottleneck in developing heat-resilient crop varieties. Although Tcrit can acclimate to heat, the molecular mechanisms behind this acclimation are not yet understood, limiting genetic improvement strategies.
Solution This project integrates high-throughput phenotyping, machine learning, and molecular biology to develop a non-invasive method for predicting Tcrit and investigating the regulatory mechanisms underlying its acclimation. The goal is to identify genotypic variation and physiological traits linked to PSII resilience and to enable rapid, scalable selection of heat-tolerant genotypes across both horticultural and broad-acre crops.
Impact The project will deliver a powerful, data-driven tool for breeders to accelerate the development of heat-tolerant crops, improving yield and quality under heat stress conditions. By providing a practical, scalable solution for predicting photosynthetic heat tolerance, the research contributes to enhanced breeding efficiency, climate adaptation strategies, and long-term global food security in an increasingly warm climate.
