Biodegradable Carbohydrate-Based Films for Packaging Agricultural Products—A Review
Bibliographic record
Abstract
Carbohydrate-based biodegradable films offer an eco-friendly alternative to conventional petroleum-derived packaging for agricultural commodities. Derived from renewable polysaccharides such as starch, cellulose, chitosan, pectin, alginate, pullulan, and xanthan gum, these films exhibit favorable biodegradability, film-forming ability, and compatibility with food systems. This review presents a comprehensive analysis of recent developments in the preparation, functionalization, and application of these polysaccharide-based films for agricultural packaging. Emphasis is placed on emerging fabrication techniques, including electrospinning, extrusion, and layer-by-layer assembly, which have significantly enhanced the mechanical, barrier, and antimicrobial properties of these materials. Furthermore, the incorporation of active compounds such as antioxidants and antimicrobials has improved the performance and shelf-life of packaged goods. Despite notable advancements, key limitations such as moisture sensitivity, poor mechanical durability, and high production costs persist. Strategies including polymer blending, nanofiller incorporation, and surface modification are explored as potential solutions. The applicability of these films in packaging fruits, vegetables, dairy, grains, and meat products is also discussed. By assessing current progress and future prospects, this review underscores the importance of carbohydrate-based films in promoting sustainable agricultural packaging systems, reducing environmental impact through the advancement of circular bioeconomy principles and sustainable development.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".