Proanthocyanidin biosynthesis and postharvest seed coat darkening in pinto bean
Bibliographic record
Abstract
Abstract Proanthocyanidins (PAs) are polyphenolic compounds present widely in the plant kingdom. These specialized metabolites are derived from the phenylpropanoid pathway and are known for producing brown pigments in different plant organs. PAs accumulate in the seed coat tissues of flowering plants and play a determinant role in seed germination and viability, protect seeds from biotic and abiotic stresses, and thus ensure the long-term storage potential of seeds. In addition, PAs are a rich source of antioxidants for the health of both human and livestock. Many of the commercially relevant dry beans ( Phaseolus vulgaris ) contain high levels of PAs, which when oxidized cause the beans to overdarken, a phenomenon known as postharvest darkening. These darker beans give the impression of oldness, and consumers tend to avoid buying them which, in turn, affects their market value. Pinto beans, one of the leading market classes of dry beans, are affected the most by the postharvest darkening. Therefore, exploring the regulation of PA biosynthesis and accumulation in bean seed coat tissues will help to develop strategy to manage the postharvest darkening effect in pintos. In this review, we discuss the PA biosynthesis and its regulation, connecting it to seed coat color genetics for a better understanding of the mechanism of seed coat darkening.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".