Evidence map›Paper›PMID 41907757›Full record

ReviewFrontiers in plant science2026

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

Nathaniel Burner, Donna K Harris, Clement Kwarteng Nyam, Ilyas Ahmad, Namhee Lee, Joon Hyuk Suh, Benjamin Fallen, Zenglu Li

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in plant science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Nathaniel BurnerDepartment of Crop and Soil Sciences, and Institute of Plant Breeding, Genetics, and Genomics, University of Georgia, Athens, GA, United States.
Donna K HarrisDepartment of Plant Sciences, Sheridan Research & Extension Center, University of Wyoming, Sheridan, WY, United States.
Clement Kwarteng NyamDepartment of Plant Sciences, Sheridan Research & Extension Center, University of Wyoming, Sheridan, WY, United States.
Ilyas AhmadDepartment of Plant Sciences, Sheridan Research & Extension Center, University of Wyoming, Sheridan, WY, United States.
Namhee LeeDepartment of Food Science and Technology, University of Georgia, Athens, GA, United States.
Joon Hyuk SuhDepartment of Food Science and Technology, University of Georgia, Athens, GA, United States.
Benjamin FallenSoybean & Nitrogen Fixation Research Unit, United States Department of Agriculture, Agricultural Research Service (USDA-ARS), Raleigh, NC, United States.
Zenglu LiDepartment of Crop and Soil Sciences, and Institute of Plant Breeding, Genetics, and Genomics, University of Georgia, Athens, GA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

artificial intelligencecanopy wiltingdrought tolerancegenomic predictionhigh-throughput phenotypingmetabolomicsproteomicsQTL mapping

Identifiers

PMID41907757
PMCPMC13021458

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.