Effects of Post-Harvest Ozone Treatment on Some Molecular Stability Markers of Amelanchier alnifolia Nutt. Fruit during Cold Storage
Bibliographic record
Abstract
Nutt. ex M. Roem. (Nutt.) are a good source of bioactive compounds and vitamins. Due to the fact that the berries are a soft fruit, they require special procedures to increase their molecular and mechanical stability during cold storage. The study investigated the effects of ozone treatment applied cyclically (every 24 h) on selected chemical and mechanical parameters of saskatoon berries kept in storage. For this purpose, measurements were performed to assess changes in some molecular markers such as antioxidant potential, content of vitamin C, and total polyphenols, as well as microbial stress and maximum destructive force under uniaxial compression of samples. The effectiveness of the storage process was also assessed in relation to the conditions used by determining the proportion of fruit affected by diseases occurring in storage. The findings show that ozone treatment led to increased content of bioactive compounds at the initial stages of storage and resulted in decreased loss of water and bioactive compounds at the later stages. Ultimately, irrespective of the conditions applied during ozone treatment, it was observed that the growth of micro-organisms on the fruit surface was inhibited, and as a result, storage losses during the relevant period were significantly reduced.
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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".