Breeding Common Bean for Resistance to White Mold: A Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it