On-site biofouling removal enhances the nutritional and gustatory quality of oysters from suspension aquaculture and the recovery of essential biomolecules for human consumption
Bibliographic record
Abstract
We experimentally tested the effects of on-site biofouling removal (BR) via heat treatment on the biomolecule contents of Pacific oysters and the bay-scale recovery of these biomolecules through the harvest of farmed oysters from suspension aquaculture in a temperate bay. At harvest after an 18-month cultivation period, oysters treated at the 13th month showed 18 % higher soft body weights and increased contents of certain biomolecules compared to untreated (UN) oysters. Specifically, BR oysters had 15 % higher eicosapentaenoic acid (EPA) content and 13 % higher docosahexaenoic acid (DHA) content than UN oysters. The glycogen content of BR oysters was 54 % higher, suggesting enhanced energy storage and potentially improved sweetness. BR likely reduced food competition between oysters and fouling organisms, predominantly mussels, leading to the higher biomolecule contents. If BR were expanded to cover the entire bay (from the current 10–100 %), the recovery of EPA and DHA through the harvest of farmed oysters would increase by 28 %, reaching 869 kg in a 1.5-year production cycle. Biofouling removal (BR) did not significantly affect the content of essential amino acids (AAs), gustatory-related AAs, or taurine in oysters. However, due to improved oyster biomass production, BR is estimated to potentially increase the recovery of these biomolecules by approximately 12 %. In conclusion, on-site BR is a straightforward and effective method for enhancing the levels of certain nutritional and gustatory-related biomolecules in cultivated oysters while simultaneously increasing the recovery of nutritionally important biomolecules for human consumption.
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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 | 0.000 |
| 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 | 0.001 |
| 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 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".