Evidence map›Paper›PMID 42312078›Full record

ArticleFrontiers in plant science2026

UAV-based phenotyping outperforms visual canopy wilting for evaluating soybean drought tolerance and yield retention under rainfed conditions.

Popat Shivaji Pawar, Chengjun Wu, Derrick Harrison, Daniel Rogers, Ben Fallen, Caio Canella Vieira

Abstract read
In one paragraph

Article in Frontiers in plant science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Popat Shivaji Pawar *Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR, United States.
Chengjun Wu *Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR, United States.
Derrick HarrisonDepartment of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR, United States.
Daniel RogersDepartment of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR, United States.
Ben FallenNitrogen Fixation Unit, United States Department of Agriculture (USDA)-Agriculture Research Service, Raleigh, NC, United States.
Caio Canella VieiraDepartment of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drought is the major abiotic stress limiting soybean growth and yield, yet accurately identifying genotypes that sustain yield under rainfed conditions remains a major bottleneck in soybean breeding. Canopy wilting scores are widely used as a proxy for evaluating plant responses to drought stress. However, most assessments rely on leaf-level visual observations that are inherently subjective and typically based on single time-point scores, providing only a snapshot of stress expression and failing to capture their relationship with yield retention under rainfed conditions. To address these limitations, this study used Unmanned Aerial Vehicle (UAV)-based high-throughput phenotyping at a single growth stage (R4/R5) as a more quantitative and objective alternative to visual scoring, with closer relevance to yield performance under drought conditions. From 2023 to 2025, a total of 85 soybean genotypes developed by soybean breeding programs in Arkansas, Missouri, Kansas, and North Carolina, along with commercial checks, were evaluated under irrigated and rainfed conditions in Stuttgart, Arkansas. Visual canopy wilting scores were recorded at R4/R5, along with vegetation indices captured using UAV-based multispectral imagery. UAV-derived indices showed significant correlations with yield (

Indexed as

canopy stressdrought tolerancesoybean breedingUAV phenotypingvegetation indicesyield retention

Identifiers

PMID42312078
PMCPMC13269238

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.