Effects of Five Oxidative Decontaminating Agents on the Quality and Proteins of Tilapia Fillets
Bibliographic record
Abstract
In this study, the effects of five common oxidative decontaminating agents (H2O2 solution, ClO2 solution, NaClO solution, ozonated water and slightly acidic electrolytic water) on the bacterial decontamination of tilapia fillets and their influence on the texture, color and myofibrillar protein (MP) oxidation in tilapia fillets were investigated. The results showed that a decontamination rate of 80% was attained by immersion in 1 500 mg/L H2O2 solution for 8 min, 200 mg/L ClO2 solution for 10 min, 200 mg/L NaClO solution for 10 min, 9 mg/L ozonated water for 10 min, or 30 mg/L slightly acidic electrolytic water for 20 min. Compared with the control group, treatment with decontaminating agents increased the hardness and L* value of tilapia fillets, decreased the a* value, MP content, total sulfhydryl group content, and raised the content of carbonyl groups and the amount of surface hydrophobic groups. The degree of protein denaturation in the slightly acidic electrolytic water and NaClO solution groups was the highest; the fluorescence intensity of MP was decreased after decontamination treatments, with the greatest decrease being found in the slightly acidic electrolytic water-treated group; the relative contents of α-helix and β-turn in MP were decreased, while the relative contents of β-fold and random coil were increased, with the most significant changes in the secondary structure of MP being observed in the slightly acidic electrolytic water-treated group (P < 0.05). MP underwent degradation to different extents, and the degradation degree of the slightly acidic electrolytic water group was higher than that of the other treatment groups. In summary, the oxidation of fish MP occurred to varying degrees after oxidative decontamination treatments, with slightly acidic electrolytic water treatment having the strongest oxidative effect.
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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) | 0.001 | 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) | 0.001 | 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".