Recent Advances in Functional Cellulose-based Films with Antimicrobial and Antioxidant Properties for Food Packaging
Bibliographic record
Abstract
The packaging of food plays a crucial role in food preservation worldwide. However, traditional packaging systems are passive layers with weak efficiency in protecting the food quality. Therefore, packaged foods are gradually spoiled due to the oxidation and growth of microorganisms. Additionally, most of the commercial packaging films are made of petroleum-based materials which raise environmental concerns. Accordingly, the development of eco-friendly natural-derived active packaging systems has increased the attention of scientists. Cellulose as the most abundant polysaccharide on earth with high biocompatibility, no toxicity, and high biodegradability has extensively been applied for the fabrication of packaging films. However, neat cellulose-based films lack antioxidant and antimicrobial activities. Therefore, neat cellulose-based films are passive films with weak food preservation performance. Active films have been developed by incorporating antioxidants and antimicrobial agents into the films. In this review, we have explored the latest research on the fabrication of antimicrobial/antioxidant cellulose-based active packaging films by incorporating natural extracts, natural polyphenols, nanoparticles, and microparticles into the cellulose-based film formulations. We categorized these types of packaging films into two main groups: (i) blend films which are obtained by mixing solutions of cellulose with other soluble antimicrobial/antioxidant agents such as natural extracts and polyphenols; and (ii) composite films which are fabricated by dispersing antimicrobial/antioxidant nano- or microfillers into the cellulose solution. The effect of these additives on the antioxidant and antimicrobial properties of the films has been explained. Additionally, the changes in the other properties of the films such as hydrophilicity, water evaporation rate, and mechanical properties have also been briefly addressed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".