Influence of Storage on Darkening and Hardening of Slow- and Regular-Darkening Carioca Bean (Phaseolus vulgaris L.) Genotypes
Bibliographic record
Abstract
New carioca bean cultivars are being introduced into the market necessitating their evaluation under trade conditions, which often require storage under ambient conditions. We therefore evaluated the darkening and hardening processes of six carioca bean genotypes each representing regular and slow darkening trait during storage under ambient conditions for five months to elucidate their relationship as a breeding strategy. Storage time adversely affected color characteristics (L*, a*, b*, C* and ΔE) depending on bean genotype, whereas hardness and resistance to cooking increased during storage independent of the lignification process. Bean darkening and hardening occurred during storage at different intensities in each genotype and were not always correlated. BRSMG-Madrepérola, a slow darkening genotype, was unaffected (resistant to storage conditions), whereas BRS-Pontal with regular tegument darkening, was highly susceptible to storage conditions reflected in extended cooking time and darkening (low L* values). Principal component and cluster analyses on 8 constituents analyzed in this study demonstrate the difference in color characteristics, cooking time and hardness as major factors in segregating the bean genotypes. Seed coat color is an important but inappropriate single parameter for predicting the resistance to cooking or hardness induced by storage of carioca beans under ambient conditions. Development of carioca bean genotypes resistant to storage conditions is essential in reducing food losses during postharvest.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".