Eco-friendly innovations for enhancing value from farm to function using poultry feathers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The poultry industry has seen significant growth in response to the expanding global population, resulting in an increased demand for white meat. Recently, agricultural by-products derived from poultry have gained attention for their potential use in various applications. However, the large-scale utilization of by-products like keratin faces challenges such as low thermoplasticity and difficulty in dissolving keratin, as well as limited knowledge about the properties and processability of the resulting products. To address these issues, both chemical and biological methods are employed to extract keratin and produce different products. One promising strategy is the bioconversion of these by-products into valuable materials using enzymes. A small peptide product obtained through enzymatic biodegradation can be used in green biotechnology for industrial applications as a feed additive or a significant protein source. This review aims to discuss the eco-friendly fermentation process for feather by-products and their multifunctional applications in areas such as water purification, cosmetics, and biomedical uses. Additionally, it addresses the challenges associated with the utilization of chicken feathers and proposes possible solutions to overcome them. • Adding value to agro-industrial waste can be accomplished through bioconversion. • Byproduct utilization is hindered by nutritional, technological, and economic obstacles. • Chicken feathers are a huge bioresource for developing multifunctional materials. • Keratin-derived materials hold promise to replace petro-based materials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 it