Development and characterization of food packaging bioplastic film from cocoa pod husk cellulose incorporated with sugarcane bagasse fibre
Bibliographic record
Abstract
Agricultural wastes, including cocoa pod husk (waste from the chocolate industry) and sugarcane bagasse (waste from the sugar industry), are increasing day by day. The development of food packaging biofilms from these two wastes could be beneficial to the environment and human. Therefore, this study was conducted to develop biodegradable plastic films by using cocoa pod husk and sugarcane bagasse. Cellulose and fibre were extracted from cocoa pod husk and sugarcane bagasse, respectively. The developed bioplastic films were divided into several concentration ratios of cellulose and fibre which are 100꞉0 (100% cellulose), 75꞉25 (cellulose꞉fibre), 50꞉50 (cellulose꞉fibre), 25꞉75 (cellulose꞉fibre), and 0꞉100 (100% fibre). The physicochemical properties for all bioplastic concentration ratios were determined in terms of sensory evaluation, drying time, moisture content, water absorption and water vapor permeability. From the observation and analysis of the physicochemical properties of bioplastic, we found that the most suitable bioplastic film for food packaging goes to the combination of 75% cellulose and 25% fibre bioplastic, as it demonstrated the lowest water absorption percentage and water vapor permeability.
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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) | 0.000 | 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 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".