Effects of 1-MCP preservatives with different embedding materials on the physicochemical, textural and aroma properties of ‘Royal Gala’ apples during shelf life
Bibliographic record
Abstract
1-MCP is used in the preservation and storage of postharvest apples. To assess the influence of embedding materials on the release behaviour of 1-MCP. The 1-MCP preservative was embedded separately in two different materials to form two distinct preservative formulations, both of which were commercially acquired and subsequently utilised for treating apples. Preservative A (Yongtai) is an inclusion complex of 1-MCP in α-cyclodextrin, whereas preservative B (SmartFresh) is an inclusion complex of 1-MCP in a combination of α-cyclodextrin and β-cyclodextrin. The harvested ‘Royal Gala’ (Malus × Domestica Borkh.) apples were treated preservative A or B. After ten months of storage, the physicochemical, textural and aroma properties of ‘Royal Gala’ apples were investigated during shelf life. The results showed that 1-MCP could maintain better physicochemical and textural properties than the control group (p < 0.05). Compared with A, B was superior in inhibiting the production of ethylene and maintaining vitamin C content, flesh brittleness and flesh firmness. 1-MCP exhibited higher aroma intensities of ammonia and aromatic compounds. 1-MCP inhibited the aroma intensities of hydrocarbons, alcohols, nitrogen oxides and sulphides. The suppression by B was stronger than A. This study lays a theoretical foundation for the application of 1-MCP to preserve apples.
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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) | 0.001 | 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".