Conventional use and sustainable valorization of spent egg-laying hens as functional foods and biomaterials: A review
Bibliographic record
Abstract
Spent hen are egg-laying hens reaching the end of their laying cycles; billions of spent hens are produced globally each year. Differences in people's attitudes towards spent hen as foods lead to their different fates among countries. While spent hens are consumed as raw or processed meat products in Asian countries such as China, India, Korea, and Thailand, they are treated as a byproduct or waste, not a food product, in the western society; they are instead disposed by burial, incineration, composting (as fertilizers), or rendering into animal feed and pet food, which either create little market value or cause animal welfare and environmental concerns. Despite being a waste, spent hen is a rich source of animal proteins and lipids, which are suitable starting materials for developing valorized products. This review discussed the conventional uses of spent hens, including food, animal feed, pet food, and compost, and the emerging uses, including biomaterials and functional food ingredients. These recent advances enable more sustainable utilization of spent hen, contributing to alternative solutions to its disposal while yielding residual value to the egg industry. Future research will continue to focus on the conversion of spent hen biomass into value-added products.
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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 | 0.002 |
| 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".