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Record W7085866716 · doi:10.1111/ppa.70038

Response of Elite Dry Bean ( <i>Phaseolus vulgaris</i> ) Genotypes to <i>Fusarium oxysporum</i> and <i>Rhizoctonia solani</i> Root Rot

2025· article· en· W7085866716 on OpenAlexaff

Bibliographic record

VenuePlant Pathology · 2025
Typearticle
Languageen
FieldComputer Science
TopicSoftware System Performance and Reliability
Canadian institutionsMcGill University
FundersMichigan Bean CommissionAgBioResearch, Michigan State University
KeywordsRoot rotCultivarGreenhouseShootDry beanResistance (ecology)Trait

Abstract

fetched live from OpenAlex

ABSTRACT Root rot is a major yield‐limiting disease of dry bean ( Phaseolus vulgaris ) production in the United States and worldwide. Specifically, disease symptoms conferred by the soil‐borne fungal pathogens Fusarium oxysporum and Rhizoctonia solani cause significant yield loss in susceptible dry bean cultivars through damage of root biomass, reduced vigour and plant death. This study was conducted in Michigan during 2021 and 2022 to evaluate field resistance to root rot conferred by these pathogens across a diverse set of breeding and diversity panel lines. Secondary objectives were to establish correlations between field and greenhouse trials and non‐destructive traits correlated to root rot resistance to F. oxysporum for ease of future high‐throughput phenotyping. All trials were successful in identifying significant variation for root rot resistance. Significant correlations were found between rankings in field and greenhouse trials (GH; p = 0.03, r = 0.71). Significant trait correlations were also identified between root rating and fresh ( p = 0.01, r = −0.67) and dry root ( p = 0.01, r = −0.64) and dry shoot ( p = 0.04, r = −0.43) biomass in the greenhouse. Ultimately, multiple lines with improved levels of resistance were identified as parents for future root rot resistance breeding efforts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.228
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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