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Drought tolerance in soybean: genetics, metabolomics, remote sensing, and breeding for enhanced drought tolerance

Title: Drought tolerance in soybean: genetics, metabolomics, remote sensing, and breeding for enhanced drought tolerance
Authors: Burner, Nathaniel; Harris, Donna K.; Nyam, Clement Kwarteng; Ahmad, Ilyas; Lee, Namhee; Suh, Joon Hyuk; Fallen, Benjamin; Li, Zenglu
Source: Frontiers in Plant Science ; volume 17 ; ISSN 1664-462X
Publisher Information: Frontiers Media SA
Publication Year: 2026
Collection: Frontiers (Publisher - via CrossRef)
Description: Drought is the most damaging abiotic stress affecting soybean production, with variable rainfall contributing significantly to year-to-year yield variability. Breeding efforts aim to develop cultivars with stable and competitive yields under both drought and non-drought stressed conditions. However, drought tolerance in soybean is a highly complex trait, influenced by diverse physiological, morphological, genetic factors and environments. Identifying genotypes with improved drought tolerance is challenging because traditional phenotyping methods for drought tolerance are subjective and time-consuming. Furthermore, quantitative trait loci (QTLs) associated with drought tolerance typically exhibit small effects and limited consistency across environments and populations. These challenges highlight the need for improved methodologies to identify and evaluate promising sources of genetic variation. This review summarizes the current state of drought tolerance breeding in soybean and discusses recent advances in remote sensing, transcriptomics, proteomics, and metabolomics aimed at enhancing drought tolerance research and cultivar development in soybean.
Document Type: article in journal/newspaper
Language: unknown
DOI: 10.3389/fpls.2026.1733525
DOI: 10.3389/fpls.2026.1733525/full
Availability: https://doi.org/10.3389/fpls.2026.1733525; https://www.frontiersin.org/articles/10.3389/fpls.2026.1733525/full
Rights: https://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.EBE72978
Database: BASE