ORIGINAL RESEARCH article
Front. Plant Physiol.
Sec. Photosynthesis and Metabolism
Volume 3 - 2025 | doi: 10.3389/fphgy.2025.1591146
This article is part of the Research TopicEnhancing Crop Resilience Through Photosynthetic Trait OptimizationView all articles
Harnessing Photosynthetic and Morpho-Physiological Traits for Drought-Resilient Soybean: Integrating Field Phenotyping and Predictive Approaches
Provisionally accepted
Harmeet Singh-Bakala1,2
Francia Ravelombola2
Cheryl Adeva2
Maiara Oliveira2
Ru Zhang3Jessica Argenta2Grover Shannon2
Feng Lin2*- 1University of Missouri, Columbia, United States
- 2Fisher Delta Research Center, College of Agriculture, Food and Natural Resources, University of Missouri, Columbia, Missouri, United States
- 3Donald Danforth Plant Science Center, St Louis, Missouri, United States
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Drought stress is a major constraint for Soybean (Glycine max (L.) Merr.) productivity, exacerbating yield instability under current and predicted environments. Breeding drought resilient soybean varieties requires more robust selection markers for improved accuracy. To identify the traits associated with field drought tolerance, we evaluated photosynthetic and other morphophysiological traits in elite soybean lines at drought sensitive reproductive stage (R2-R3). Using chlorophyll fluorescence phenotyping and mixed model analysis, we assessed genotypic variability in various photosynthetic and other morpho-physiological traits under irrigated and rainfed field conditions. Tolerant genotypes (higher yield stability) exhibited significantly higher SPAD, NPQt, and FvP/FmP under drought, along with reduced leaf thickness. Multivariate analyses suggested these photosynthetic and morpho-physiological traits as key driverskey indicators of yield stability under drought. By coupling with soil parameters, these traits were able to explain 74-79% of yield variance predictive models. These findings suggest that SPAD, NPQt, FvP/FmP, and leaf thickness are valuable physiological markers for identifying drought-tolerant genotypes. Integrating these traits into selection criteria could improve the accuracy of breeding programs aimed at developing drought-resilient soybean varieties. Future efforts should validate these markers across diverse environments and leverage genomic tools to accelerate allele discovery, offering a pathway to climate-resilient soybean production.
Keywords: Chlorophyll Fluorescence, Drought Tolerance, Multivariate analysis, Photosynthesis, Physiological Markers, Predictive Modeling, Yield Stability cB: Centibar, CWS: canopy wilting score, CV: Cross Validation, DPI: Drought Performance Index, RF: Rainfed : RCBD: Randomized Complete Block Design, Predictive Modeling
Received: 10 Mar 2025; Accepted: 08 Jul 2025.
Copyright: © 2025 Singh-Bakala, Ravelombola, Adeva, Oliveira, Zhang, Argenta, Shannon and Lin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Feng Lin, Fisher Delta Research Center, College of Agriculture, Food and Natural Resources, University of Missouri, Columbia, 63873, Missouri, United States
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