Multi‐Functional Properties of Halloysite Nano‐Clays in Food Safety and Security
Bibliographic record
Abstract
The expected rise in human population by 2050 demands an additional 60% increase in food production. The objective seems tough to achieve considering a significant global upsurge in food spoilage due to physicochemical and microbial factors posing major threats to food security and safety. Innovative nanotechnology solutions addressing field-deployable antimicrobials, functional food packaging, storage container materials, and preservatives along with efficient supply chain management hold promise for reducing food wastage. For instance, the use of halloysite nanotubes (HNTs) in packaging films not only improves the mechanical strength, and barrier properties but also enables encapsulation and controlled release of bioactive agents. Further, the unique and desirable properties of HNTs for biomedical, agri-food, industrial, and environmental applications along with their natural origins in abundance make it a promising platform for developing sustainable nanotechnology applications. As the third chapter of Section III, we will focus our discussion on the multifunctional roles of HNTs in active/intelligent food-packaging systems as nanofillers, nano-carriers, food-quality indicators, coatings, fibers, and capsules. Moreover, HNTs in therapeutic development and delivery for application in animal and plant agriculture will be addressed. Current limitations and future perspectives concerning health risk assessment, material transformation, migration, and regulatory issues will be systematically discussed.
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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) | 0.003 | 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".