Improving Shelf‐life and Quality of Sweet Cherry ( <i>Prunus avium</i> L.) by Preharvest Application of Hexanal Compositions
Bibliographic record
Abstract
Sweet cherry is highly appreciated by consumers for its red color, sweetness, size, flavor, and health benefits. Skin color, fruit size, firmness, flavor, sweetness, and sourness are some of the major quality determinants of sweet cherries. Storage temperature can affect the postharvest deterioration of quality in cherries. Proper storage temperature and humidity can greatly reduce water loss, dehydration, and metabolic activity. Fruit firmness is an important quality attribute in cherry. No major changes in fruit firmness were detected in cherries subjected to preharvest spray with hexanal formulations. Total polyphenolic contents were analyzed in cherry fruit subjected to preharvest and postharvest treatments. Phenolic compounds including anthocyanins account for the antioxidant activity and the health benefits of sweet cherries. Preharvest spray treatment of cherry fruit did not induce major changes in ascorbate peroxidase (APX) activities. Enzyme activity declined during postharvest storage in both control and spray-treated cherries.
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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".