Automatically tracking down dynamic physiological traits in Millet plants as a possible physiological pre-breeding system

Agriculture is a cornerstone of national security, underpinning human survival and economic stability. However, the combined pressures of climate change, population growth, and recent global disruptions—most notably the COVID-19 pandemic—have intensified vulnerabilities within agricultural systems and food supply chains. These compounded challenges have led to socio-economic insecurities and health disparities, particularly among marginalized communities. Farmers now face the dual crises of climatic variability and pandemic-induced uncertainties, underscoring the urgent need for a transition from incremental adaptation to transformative agricultural strategies that emphasize human health, nutrition, and environmental sustainability.

Developing climate-resilient agricultural systems requires the cultivation of crops that can withstand diverse and extreme environmental conditions. Millets, often referred to as “climate-smart crops,” offer a promising solution due to their inherent resilience to biotic and abiotic stresses, ability to thrive on marginal lands, and superior nutritional profile compared to major cereals. To advance millet improvement and identify stress-resilient genotypes, high-throughput phenotyping (HTP) technologies provide a powerful approach for rapid, quantitative, and automated evaluation of physiological performance under controlled and field conditions.

In this study, we applied HTP to assess water-use traits in two pearl millet hybrid lines (COH9 and COH10) grown under well-watered (WW) and water-stress (WS) regimes. Environmental monitoring revealed characteristic diurnal variations in vapor pressure deficit (VPD) and photosynthetically active radiation (PAR), both peaking around midday. The two hybrids exhibited distinct transpiration dynamics in response to stress. COH9 maintained higher transpiration rates during midday hours under WW conditions and demonstrated faster transpiration recovery in the mornings following water stress, indicating superior water-use efficiency and regulatory capacity. Over the entire experimental period, COH9 showed greater cumulative transpiration and soil water extraction efficiency relative to COH10. These physiological advantages were reflected in significantly higher field yields for COH9 under both irrigated and rain-fed conditions.

Our findings confirm the effectiveness of HTP for identifying genotypic variation in water utilization and stress adaptation. The integration of HTP with genomic sequencing and bioinformatic analysis presents a promising pathway to accelerate millet breeding programs. This combined approach enables precise, data-driven selection of drought-tolerant and water-efficient genotypes, reducing both time and cost associated with conventional breeding methods.

Overall, this study highlights the critical role of climate-resilient crops such as millets and the transformative potential of advanced phenotyping technologies in ensuring sustainable food production under changing global conditions.