Additives in Active Food Packaging Systems
Bibliographic record
Abstract
Food products should be kept fresh and need to be stored for an extended period. Emerging food preservation methods, such as active food packaging, are being investigated because of growing environmental awareness and customer demand for safe food and high-quality products. Moreover, chemical preservatives used in food products exhibit an adverse effect on humans and alter the taste of the products. The utilization of biopolymers in active packaging (AP) also helps in the mitigation of plastic waste and attempts a sustainable approach in food packaging. Plants, mushrooms, microorganisms, and animals are the sources of natural active agents. By incorporating active ingredients obtained from natural sources (such as essential oils [EOs], polyphenols, and antimicrobial peptides) into biopolymer matrices, it will help in the sustainable development of active food packaging films capable of extending the shelf life of packaged food products while maintaining their original quality. The active ingredients perform these functions by inhibiting microbial growth and reducing oxidative stress, which ultimately prevents food spoilage. However, the ecotoxicity of these active compounds must be considered since uncontrolled use of active compounds might be detrimental to other life forms in our ecosystem. In the upcoming years, the availability of AP materials is assumed to increase owing to their different benefits, but precautions should be taken to minimize the potential ecological impacts of these active compounds.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.007 | 0.008 |
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; both teacher heads agree on what is shown here.
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".