An Accelerated Postharvest Seed‐Coat Darkening Protocol for Pinto Beans Grown across Different Environments
Bibliographic record
Abstract
ABSTRACT Pinto beans (Phaseolus vulgaris L.) that darken more slowly than conventional pinto beans would be more desirable in the market place and have been identified in the bean breeding program at the University of Saskatchewan. To incorporate the slow‐darkening trait into new cultivars there is a need for a quick, reliable, and inexpensive method to accelerate darkening without affecting seed germination. Three different accelerated darkening protocols were compared. The greenhouse protocol was conducted in the greenhouse by placing the bean seeds in plastic bags with a 1‐cm2 piece of moistened felt. For the ultraviolet C (UVC) light protocol, bean seeds were placed 10 cm below a 254‐nm UVC lamp. For the third protocol, bean seeds were placed in a cabinet set at 30°C, 80% relative humidity, and full fluorescent light. All three protocols examined could be used to distinguish darkening beans from slow‐darkening beans, however the UVC protocol was considered superior as it was quick, consistent over years, and economical and, unlike the greenhouse and the cabinet protocols, had no effect on seed germination. A genotype by environment (g × e) study was conducted to validate the UVC light protocol. After accelerated darkening, line and environment effects were found to be significant (P < 0.0001) but the g × e interaction was not significant (P = 0.29), which indicated that the UVC protocol could be used to distinguish slow‐darkening pinto beans from darkening pinto beans, regardless of where the beans were grown.
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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 | 0.001 |
| 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".