Impacts of pH and Base Substitution during Deaerator Treatments of Herring Milt Hydrolysate on the Odorous Content and the Antioxidant Activity
Bibliographic record
Abstract
Despite the biological interest in herring milt hydrolysate (HMH), its valorization is limited by its unpleasant odor resulting from the presence of mainly amine and carbonyl compounds. Recently, a deaerator was demonstrated as an interesting avenue to reduce the odorous content of HMH. However, the removal rate of amine and carbonyl compounds was highly dependent on the operating conditions, and the impact of such a process on the biological potential of HMH was not considered. Therefore, this study aimed to optimize the deaerator process by assessing the impacts of the combination of deaerator treatments at neutral and basic pH, the increase in pH from 10 to 11, and the substitution of NaOH by KOH on the odorous content and the antioxidant activity of HMH. Results showed that the highest deodorization rate of HMH was obtained when a deaerator treatment at neutral pH was combined with another one at basic pH using KOH for alkalization. This condition resulted in a decrease in the dimethylamine and trimethylamine contents by 70%, while certain compounds such as 2,3-pentanedione, methional, (E,E)-2,4-heptadienal, or (E,Z)-2,6-nonadienal were almost completely removed. Removal mechanisms of the targeted compounds were totally identified, and the performance of the developed process was confirmed by sensory analysis. Lastly, it was shown that the antioxidant potential of HMH was not affected by the deodorization process. These results demonstrated the feasibility of deodorizing a complex matrix without affecting its biological potential.
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 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".