A Comprehensive Review on Recent Advances in Plant Flour–Based Edible Tableware
Bibliographic record
Abstract
Nowadays, plastic has become an integral part of our daily used products. Packaging is the sector where a significant portion of plastics are being used, and it has increased many folds after the recent pandemic. The plastic-based cutlery, cups, bowls, and plates have been commonly used in ready-to-eat packaged food, and they include mostly single-use plastic; thus, there is an urgent need for substitution with eco-friendly alternatives. The edible cups, bowls, and cutlery could be a promising alternative to the plastic counterparts. This review debated the current scenario in edible cutlery fabrication and characterization. The plant-based, eco-friendly edible flour materials are commonly used for fabricating edible cutlery such as bowls, cups, and spoons. The fortification and enrichment of additives into the edible cutlery and tableware were promising to improve the physical and functional performance. To develop edible cutlery, various flours such as millet, wheat, and rice have already been explored, and the results are promising for attaining sustainable development. The edible spoons prepared by using various flours such as finger millet and wheat flour with ashwagandha powder showed high proximate composition, including protein 5.96% and carbohydrates 85.73%. Similarly, the edible cutlery prepared using rice flour, wheat flour, and banana blossom powder resulted in a high water absorption capacity of 31.59% and showed high biodegradable capacity and decayed in 5 days. The use of this edible tableware not only reduces plastic waste issues but also makes our food healthier and nutrition-rich. Hence, this review aims to provide an overview of edible cutlery's needs and current status.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".