The Phaseolus vulgaris L. Yellow Bean Collection: genetic diversity and characterization for cooking time
Bibliographic record
Abstract
Abstract Common bean ( Phaseolus vulgaris L.) is a nutrient-rich food, but its long cooking times hinder its wider utilization. The Yellow Bean Collection (YBC) was assembled with 295 genotypes from global sources to assess the genetic and phenotypic diversity for end-use quality traits in yellow beans. The panel was genotyped with over 2,000 SNPs identified via Genotyping-By-Sequencing (GBS). Through population structure analyses with the GBS markers, the YBC was determined to be 69% Andean, 26% Middle American, and 5% admixture. The YBC was grown in two major bean production regions in the U.S., Michigan (MI) and Nebraska (NE) over two years. The genotypes exhibited a wide diversity in days to flower, seed weight, water uptake, and cooking time. The cooking times of the YBC ranged from 17–123 min. The cooking time were longer and varied more widely in NE with many more genotypes exhibiting hardshell than in MI. Fast-cooking genotypes were identified with various yellow colors; 20 genotypes cooked within 20 min in MI, and eight genotypes cooked within 31 min in NE. Water uptake and cooking time were significantly affected by the environment, which included both the growing and cooking environment, and notably in relation to cooking, NE is higher elevation than MI. SNPs associated with cooking time were identified with genome-wide association analyses and a polygalacturonase gene on Pv04 was considered to be a candidate gene. The genotypic and phenotypic variability, fast-cooking genotypes, and the associated SNPs of the YBC will lay the foundation for utilizing yellow beans for breeding and genetic analyses.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".