Changes in Microbial Safety and Quality of High-Pressure Processed Camel Milk
Bibliographic record
Abstract
High-pressure processing (HPP) is used as a non-thermal approach for controlling microbial viability. The purposes of this study were to (i) establish the decimal reduction times (D-values) for pathogenic bacteria during 350 MPa HPP treatment,; (ii) evaluate the impact of 350 MPa HPP on total plate count (TPC), yeasts and molds (YM), and lactic acid bacteria (LAB) in camel milk; (iii) investigate the behavior of several spoilage-causing bacteria during storage at 4 °C and 10 °C for up to 10 d post-HPP treatment; and (iv) assess the effect of HPP on the protein degradation of camel milk. The D-values for L. monocytogenes, E. coli O157:H7, and Salmonella spp. were 3.77 ± 0.36 min, 1.48 ± 0.08 min, and 2.10 ± 0.13 min, respectively. The HPP treatment decreased pathogenic microorganisms by up to 2 to 3 log cfu/mL (depending on treatment conditions). However, HPP reduced TPC, YM, and LAB by <1 log cfu/mL, regardless of the length of pressure exposure. HPP treatment, even at extended holding times, did not significantly alter either the proteolytic activity or casein micelle structure in camel milk. This study highlights HPP as a promising non-thermal technique for enhancing the microbiological safety of camel milk.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".