Spray-drying and ultrasonication processing of camel whey protein concentrate: Characterization and impact on bioactive properties
Bibliographic record
Abstract
The production of whey protein concentrates (WPCs) from camel milk whey represents an effective approach to valorize this processing by-product. These concentrates harbor active ingredients with significant bioactive properties. Camel WPCs were spray-dried (SD) at inlet temperature of 170, 185 and 200°C, or Ultrasonicated (US) for 5, 10 and 15 min, then freeze-dried to obtain fine powder. The impact of both treatments on protein degradation was studied by sodium dodecyl sulfate-PAGE and reverse-phase ultraperformance liquid chromatography (RP-UPLC) techniques. Significantly enhanced protein degradation was observed after US treatment when compared with SD. Both SD and US treatments slightly enhanced the WPCs samples' antioxidant activities. The US exposure for 15 min exhibited highest 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) scavenging activity (12.12 mmol TE/g). Moreover, US treatment for 10 min exhibited the highest in vitro anti-diabetic properties (α-amylase and α-glucosidase inhibition), and dipeptidyl-peptidase-IV inhibitory activity among all samples. In addition, the ultrasonication for 10 min and SD at 170°C showed the lowest IC 50 values for in vitro anti-hypercholesterolemic activities in terms of pancreatic lipase and cholesteryl esterase inhibition. Conclusively, these green techniques can be adapted in the preservation and processing of camel milk whey into active ingredients with high bioactive properties.
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 | 0.000 | 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".