Genotypic variation for phenolic compounds in developing and whole seeds, and storage conditions influence visual seed quality of yellow dry bean genotypes
Bibliographic record
Abstract
Seed coat colour is an important determinant of the visual quality of dry beans, as seeds are sold as a dry commodity. Phenolic compounds have a major effect on the colour of bean seeds. The objectives of the study were to determine the changes in phenolic compounds during seed development and in whole seeds of yellow bean genotypes with contrasting seed coat colour, and the effects of storage temperature and duration on seed phenolics and colour. Condensed tannin, phenolic acid, flavonoids, and antioxidant activity were observed as early as 10 d after flowering in the developing seeds of Arikara Yellow, which darken at harvest and during postharvest storage. In contrast, for CDC Sol and AAC Y073 seeds which remain yellow, phenolic compounds and antioxidant activity were consistently low. Seed brightness (L*) and yellow colour (b*) were negatively correlated with phenolic compounds and antioxidant activity, and conversely seed redness (a*) was positively correlated with phenolic compounds, confirming a negative influence of phenolic compounds on seed coat colour. Yellow bean genotypes had low anthocyanin but were high in β-carotene. Storage temperature influenced condensed tannin and seed coat colour, whereas the duration of storage influenced phenolic compounds, antioxidant activity, and seed coat colour. Higher temperatures (20 or 30 °C) and longer storage duration (120 or 180 d) generally resulted in darker seeds with increasing redness compared with seeds stored at 6 °C or for 60 d. AAC Y073 and CDC Sol with improved seed coat colour may increase consumer preference, value, and marketability of yellow beans.
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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 | 0.000 |
| 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".