Optimizing decolorization and deodorization to remove pigments and fishy odors while preserving antioxidant activity in Asian swamp eel (Monopterus albus) hydrolysate
Bibliographic record
Abstract
The objective of this study was to develop an efficient method for decolorizing and deodorizing Asian swamp eel (ASE) hydrolysate. At an activated carbon (AC) dosage of 0.5 % and pH 4.0, insoluble peptides from trichloroacetic acid (TCA), which have poor antioxidant activity, were effectively removed. Meanwhile, other nitrogenous fractions with better antioxidant activity were retained, achieving a decolorization rate of 74.02 ± 0.38 %. Orthogonal partial least squares discriminant analysis (OPLS-DA) successfully distinguished the solid phase microextraction gas chromatograph-mass spectrometery (SPME-GC-MS) results of samples treated with different deodorization methods (ASE stock hydrolysate, AC treatment, AC + complex bacteria, AC + yeast, and AC + cyclodextrin). A total of 22 differential volatile compounds with variable importance projection (VIP) values greater than 1 were identified. The combination of AC treatment and cyclodextrin encapsulation effectively removed undesirable odors, enhancing the sensory quality and market competitiveness of the final product.
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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 | 0.000 |
| 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 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".