Integrating Non-photochemical Quenching (NPQ) Measurements for Identifying Flood-Tolerant Soybean Genotypes in the Era of Climate Change

Abstract

Climate change has negatively affected agriculture worldwide, including soybean production. Studies have shown that rising temperatures and extreme weather events like droughts and floods significantly reduce soybean yields. Developing flood-tolerant soybean genotypes is crucial for ensuring food security. Conventional breeding programs are limited by laborious and imprecise visual rating methods for flooding tolerance identification. High-throughput platforms for plant phenotyping using imaging techniques offer potential solutions, but they lack information on underlying physiological mechanisms. Non-photochemical quenching (NPQ) is a molecular adaptation in photosynthesis that dissipates excess light energy, protecting plants from damage. This study aimed to integrate NPQ measurements into high-throughput phenotyping procedures to identify flooding-tolerant soybean genotypes. The study evaluated 160 soybean genotypes for flooding tolerance, identifying those with higher grain yield potential. Subsequently, ten genotypes were selected for monitoring NPQ responses under flooded conditions. Results showed that genotypes with higher grain yields also exhibited superior NPQ performance, suggesting a positive correlation between flooding tolerance and energy dissipation capacity. Among these genotypes, 58I60 RSF IPRO, 64HO130 I2X and BRS 525 displayed superior potential and could be further exploited in breeding efforts, considering their grain yield capacity, plant leaf area, and photoprotective capacity under flooding conditions. These findings suggest that integrating NPQ measurements into high-throughput phenotyping platforms can aid in identifying flood-tolerant soybean genotypes for breeding programs, leading to more resilient crops in the face of climate change. Further field studies are warranted to validate these hypotheses and improve crop models for future climate scenarios.