Natural Antioxidant and Antimicrobial Agents and Processing Technologies for the Design of Active Food Packaging Polymers
Bibliographic record
Abstract
Over the last decades, food packaging has advanced significantly, which is crucial in maintaining food safety and minimizing waste. However, most traditional food packaging materials in the market are typically made of inexpensive synthetic plastics with a limited scope of providing physical containment and an effective barrier against moisture and gases. In contrast, sustainable active packaging offers a promising solution to extend the shelf-life of food by effectively decreasing the rate of oxidative deterioration and microbial growth while reducing the environmental impact of petrochemical-derived plastics. As a result, there is a significant interest in developing sustainable and active food packaging materials with a low carbon footprint. Natural resource-derived antioxidant and antimicrobial agents are better alternatives to traditional synthetic agents when combined with any biodegradable polymer as it enhances the sustainability portfolio. This review critically evaluates recent trends in developing natural resource-derived antioxidant and antimicrobial agents for active food packaging applications. Various active biobased antioxidant and antimicrobial agents are critically reviewed and discussed, including their structure, physico-chemical properties, and various attributes in food packaging applications. Finally, this review presents an outlook on the future of sustainable and active food packaging materials and highlights the potential challenges in their development and implementation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".