Screening and Characterization of Antioxidant Film Applicable to Walnut Kernels from Juglans sigillata
Bibliographic record
Abstract
Walnuts play a positive role in human health due to their large amounts of unsaturated fatty acids, whereas lipid oxidation can easily occur during storage. Herein, three natural antioxidants (epicatechin, sesamol, and myricetin) were added to the composite film cross-linked with chitosan and soy protein peptide, and the antioxidant film appropriate for the preservation of walnut kernels from Juglans sigillata was screened to improve the storage quality of walnuts. The results showed that three antioxidant films could all enhance the storage performance of walnut kernels, with sesamol being the best. The characterization of antioxidant film cross-linked with chitosan and soy protein peptide containing sesamol (C/S-ses film) revealed that the composite film improved the slow release and stability of sesamol; in addition, the presence of sesamol could effectively reduce the light transmittance and water vapor permeability of the composite film, together with significantly enhancing the antioxidant and antimicrobial activities, resulting in an effective prolongation of the storage period of walnut kernels. These findings indicated that C/S-ses possess excellent potential for retarding the oxidative rancidity of unsaturated fatty acids and will provide an effective strategy for the preservation of walnut kernels.
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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) | 0.000 | 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".