Black Seed Oil Applications for the Preservation of Postharvest Quality of ‘Wonderful’ Pomegranate Under Modified Atmosphere Packaging
Bibliographic record
Abstract
This study was conducted to determine the effects of black seed oil (0.1% and 0.5%) applications with and without modified atmosphere packaging (MAP), on the postharvest quality of pomegranate cv. ‘Wonderful’. Fruit samples were stored at 6.5±1 ºC with 90-95% relative humidity for 150 days and quality analysis done at 30-day intervals. Furthermore, after each storage period, fruits were removed and kept at 20 ºC for 7 days to simulate a period of shelf-life. MAP alone or in combination with black seed oil application found to have a significant influence on the maintaining of fruit weight. Percent reduction in the fruit weight 150 days after storage (DAS) was 4.7% and 8.8% for black seed oil (0.5%)+MAP and control+MAP applications, respectively, where it was 18.9% for the control without MAP. The juice content of pomegranate fruits was 31.4% at harvest and it decreased to 21.9% on the control treatment in 150 days. Furthermore, juice content of the fruits with control+MAP and propolis+MAP were determined as 25.8%, and 28.1%, respectively, at 150 DAS. Applications of 0.5% black seed oil especially when combined with MAP, have found to be effective in preventing weight loss, preventing juice content, controlling gray mould development and decelerate the occurrence of chilling injury.
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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".