Evidence map›Paper›PMID 40986516›Full record

ArticlePloS one2025

Associations among weed communities, management practices, and environmental factors in U.S. snap bean (Phaseolus vulgaris) production.

Pavle Pavlovic, Jed B Colquhoun, Nicholas E Korres, Christopher A Landau, Rui Liu, Carolyn J Lowry, Nicolas F Martin, Ed Peachey, Barbara Scott, Lynn M Sosnoskie and 2 more

Abstract read
In one paragraph

Article in PloS one, 2025. 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

12 authors.

Pavle PavlovicDepartment of Crop Sciences, University of Illinois Urbana-Champaign, Urbana, Illinois, United States of America.ORCID 0009-0009-5251-2829
Jed B ColquhounDepartment of Plant and Agroecosystem Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Nicholas E KorresUnited States Department of Agriculture, Agricultural Research Service, Global Change and Photosynthesis Research Unit, Urbana, Illinois, United States of America.ORCID 0000-0001-8328-4990
Christopher A LandauUnited States Department of Agriculture, Agricultural Research Service, Global Change and Photosynthesis Research Unit, Urbana, Illinois, United States of America.
Rui LiuDepartment of Crop and Soil Sciences, Washington State University, Pullman, Washington, United States of America.
Carolyn J LowryDepartment of Plant Science, the Pennsylvania State University, University Park, Pennsylvania, United States of America.
Nicolas F MartinDepartment of Crop Sciences, University of Illinois Urbana-Champaign, Urbana, Illinois, United States of America.
Ed PeacheyDepartment of Horticulture, Oregon State University, Corvallis, Oregon, United States of America.
Barbara ScottDepartment of Plant and Soil Sciences, University of Delaware, Georgetown, Delaware, United States of America.
Lynn M SosnoskieSchool of Integrative Plant Science - Horticulture Section, Cornell AgriTech, Cornell University, Geneva, New York, United States of America.
Mark J VanGesselDepartment of Plant and Soil Sciences, University of Delaware, Georgetown, Delaware, United States of America.
Martin M Williams IiUnited States Department of Agriculture, Agricultural Research Service, Global Change and Photosynthesis Research Unit, Urbana, Illinois, United States of America.ORCID 0000-0002-6302-7724

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Weed species that escape control (hereafter called residual weeds) coupled with changing weather patterns are emerging challenges for snap bean processors and growers. Field surveys were conducted to identify associations among crop/weed management practices and environmental factors on snap bean yield and residual weed density. From 2019-2023, a total of 358 snap bean production fields throughout the major U.S. production regions (Northwest, Midwest and Northeast) were surveyed for residual weeds. Field-level information on crop/weed management, soils, and weather also were obtained. To determine associations among management and environmental variables on crop yield and residual weed density, the machine learning algorithm random forest was utilized. The models had 24 and 22 predictor variables for crop yield and residual weed density, respectively, and both were trained on 80% of the data with the remainder used as a test set to determine model accuracy. Both models had pseudo-R2 values of over 0.50 and accuracy over 80%. The models showed that crop yield was higher in the Northwest compared to the Midwest region, while higher average temperatures during early season growth and planting midseason (June-July) predicted greater crop yield compared to other time periods. The use of row cultivation was associated with lower snap bean yield and weed density, suggesting row cultivation had less-than-ideal selectivity between the crop and weed. Moreover, multiple spring tillage operations prior to planting were linked with an increase in weed density, implying that excessive tillage may favor the emergence of residual weeds in snap bean. Over the coming decades, climate change-driven weather variability is likely to influence snap bean production, both directly through crop growth and indirectly through weeds that escape control practices that also are influenced by the weather.

Indexed as

AgriculturePhaseolusPlant WeedsWeed ControlCrops, AgriculturalSeasonsSoilUnited StatesWeatherSoil

Identifiers

PMID40986516
PMCPMC12456788

What OpenQuestion holds

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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 OpenQuestion graph.