Response of Elite Dry Bean ( <i>Phaseolus vulgaris</i> ) Genotypes to <i>Fusarium oxysporum</i> and <i>Rhizoctonia solani</i> Root Rot
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".