112 Effects of Edible Plant Oil Emulsions on Storage Disorders in `Elegant Lady' Peaches
Bibliographic record
Abstract
Effects of different plant oils (soybean, corn, peanut, cottonseed, conola, sunflower, safflower, rape seed, and linseed) on mealiness, leatheriness, and flesh browning (FB) in `Elegant Lady' peaches ( Prunus persica Batsch) were studied. Fruit were harvested at three dates (10 days apart) with the second harvest concomitant to commercial harvest, dipped in a 5% or 10% oil emulsion for 3 min, and stored at 0 or 5 °C, respectively. After 6 weeks at 0 °C, fruit developed more leatheriness and FB but less mealiness in early harvested compared to late-harvested fruit. When stored at 5 °C, fruit did not develop any leatheriness regardless of harvest dates, but fruit from the last harvest developed high levels of mealiness and FB compare with fruit from the other two harvests. FB was found only, but not in all, leathery or mealy fruit. None of the oils affected leatheriness, but all reduced mealiness to the same extent at the same concentration. Oil treatments controlled FB completely in both leathery and mealy fruit. Oil at 10 % was more effective in controlling mealiness and FB than at 5%. Oil-treated fruit had higher flesh firmness and titratable acidity and developed less decay than the controls at removal from storage.
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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".