Breeding Common Bean for Resistance to White Mold: A Review
Bibliographic record
Abstract
ABSTRACT Under favorable weather conditions white mold causes 100% loss of yield and quality of susceptible common bean (Phaseolus vulgaris L.) cultivars. The disease is endemic and widespread in North and South American countries including the United States, Canada, Argentina, and Brazil. Our objective was to review progress achieved in identifying sources of resistance in Phaseolus species, genetics, and breeding for resistance to white mold. We also describe an integrated genetic improvement strategy for resistance to the pathogen with germplasm enhancement and cultivar development using multiple‐parent crosses and gamete selection methods of breeding. Substantial progress has been made in understanding pathogenic variation in the white mold fungus, developing screening methods, identifying sources of resistant germplasm, genetics of resistance, and introgressing resistance from the secondary gene pool, and breeding for resistance to white mold. Also, molecular marker‐assisted selection for partial resistance is practiced. However, development of white mold resistant common bean cultivars in most market classes has been slow and localized. Breeding strategies for simultaneous and integrated genetic improvement of qualitatively and quantitatively inherited resistances to white mold and cultivar development are briefly described.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".