Sequential Extraction of Valuable Bio-Products from Snow Crab (Chionoecetes opilio) Processing Discards Using Eco-Friendly Methods
Bibliographic record
Abstract
Green extraction methods using a combination of mechanical, enzymatic, and green chemical treatments were evaluated for the sequential extraction of carotenoid pigments, protein, and chitin from crab processing discards. Key objectives included avoiding the use of hazardous chemical solvents, conducting as close to a 100% green extraction as possible, and developing simple processes to facilitate implementation into processing plants without the need for complicated and expensive equipment. Three crab bio-products were obtained: pigmented vegetable oil, pigmented protein powder, and chitin. Carotenoid extractions were performed using vegetable oils (corn, canola, and sunflower oils), giving between 24.85% and 37.93% astaxanthin recovery. Citric acid was used to demineralize the remaining material and afforded a pigmented protein powder. Three different proteases were used to deproteinate and isolate chitin in yields between 17.06% and 19.15%. The chitin was still highly colored and therefore decolorization was attempted using hydrogen peroxide. Characterization studies were conducted on each of the crab bio-products isolated including powder X-ray diffraction analysis on the chitin (80.18% crystallinity index, CI, achieved using green methods). Overall, three valuable bio-products could be obtained but further research is needed to obtain pigment-free chitin in an environmentally friendly manner.
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.
How this classification was reachedexpand
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) | 0.001 | 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 teacher head, 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".