Impact of sterilization and storage on the properties of concentrated skim milk by cryoconcentration in comparison with vacuum evaporation and reverse osmosis concentration
Bibliographic record
Abstract
Abstract The aim of this study was to compare the impact of sterilized skim milk after being concentrated by three concentration techniques; namely cryoconcentration, vacuum evaporation, and reverse osmosis. To achieve this objective, skim milk was concentrated up to 18% total dry matter by cryoconcentration, vacuum‐evaporation and reverse osmosis, heat sterilized, and stored during 3 months. The obtained results showed that the surface net charge of the proteins in milk concentrated by vacuum evaporation decreased during storage, while that of the other milks remained stable. The levels of free amino acids decreased as a function of the storage time for the three skim milk samples with a higher rate for the vacuum evaporated milk. Thiol groups were affected by sterilization, but remained stable during storage. After sterilization, the consistency coefficient of milk increased by 8.6, 2.25, and 2.35 times for evaporated milk, concentrated by reverse osmosis, and cryoconcentrated, respectively. This result indicated a more stability of sterilized cryoconcentrated skim milk in comparison with the other skim milk samples which showed a tendency to age thickening. Practical Applications The findings of this research work can be applied by the dairy industry to produce concentrated skim milk following a cryoconcentration procedure. This subzero concentrating technique can substitute vacuum evaporation and reverse osmosis. The advantage of cryoconcentration, as used in this work, is its low energy consumption and high product quality. Indeed, because of the low latent heat of freezing of water in comparison with its latent heat of vaporization (seven times lower), cryoconcentration is an effective energy saving technology. Thus, the dairy processing industry can exploit the advantages of cryoconcentration to develop novel dairy foods and to save energy.
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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 | 0.001 |
| 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 | 0.000 | 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".