Effects of Production Factors and Egg-Bearing Period on the Antioxidant Activity of Enzymatic Hydrolysates from Shrimp (<i>Pandalopsis dispar</i>) Processing Byproducts
Bibliographic record
Abstract
The effects of production factors (protease used, percent enzyme, hydrolysis time, and water-to-substrate ratio) on the antioxidant activity of hydrolysates produced from shrimp processing byproducts (SPB) were assessed using Taguchi's L16 (4(5)) fractional factorial design. SPB hydrolysates showed excellent ABTS radical scavenging activity, metal ion chelating capacity, and inhibition of lipid peroxidation, but weak DPPH radical scavenging activity and ferric ion reducing antioxidant power. The protease used significantly influenced antioxidant activities while hydrolysis time and percent enzyme affected radical scavenging activities and inhibition of lipid peroxidation, respectively. Differences in the lipid and amino acid contents observed between SPB collected early and late in the egg-bearing period may have contributed to the slight variance in antioxidant activities displayed by their hydrolysates. Nevertheless, SPB hydrolysates produced using Alcalase or Protamex had high antioxidant activity regardless of production factors and egg-bearing period.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".