Economics of bio-ingredients production from shrimp processing waste in Newfoundland
Bibliographic record
Abstract
This thesis examined the economics of producing high value bio-ingredients such as chitin and carotenoprotein from shrimp processing waste in Newfoundland. The shrimp waste in the province was estimated to be at least 37000 tons annually. A survey of shrimp processing plants in the province revealed that the waste generated was relatively pure with little or no foreign material. The economic engineering approach was employed to estimate the production cost of chitin and carotenoprotein at the laboratory and pilot scale levels. At the laboratory scale where 480 kg/year of raw material (shrimp waste) was processed, the cost of chitin and carotenoprotein was found to be $159/kg and $315/kg, respectively. At the pilot scale level, the cost of chitin and carotenoprotem was estimated to be $125/kg and $244/kg, respectively based on volume of 4800 kg/year. Sensitivity analysis was carried out to establish the cost variations due to changes in the quantity of starting raw material, labor cost and cost of laboratory supplies (chemicals and enzymes). The cost of chitin and caroteinoprotein showed a decreasing trend with increasing scale of production. An expert opinion survey was conducted with a selected panel of 9 experts from the shrimp processing industry, chitin related industry, and the academic/research community to determine the potential market of the high-grade chitin/chitosan in Canada. The results showed that the health and nutraceutical industry is the most promising niche for high-grade chit in/chitosan. The survey also indicated that potential market would be high in Ontario and Quebec due to the presence of large health and nutraceutical companies in the big metropolitan areas of these regions.
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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 | 0.000 |
| 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 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".