The effects of packaging type and storage temperature on some of UHT milk quality indexes
Bibliographic record
Abstract
The objective of the present study was to illustrate the changes in physicochemical properties in ultra-high temperature (UHT) milk packed into a pouch and Tetra Brik during storage. UHT milk samples were kept at 5 and 25 °C for 3 months and regularly analyzed monthly. During storage, significant increases ( p < 0.05) in titratable acidity (TA), water-soluble nitrogen (WSN), and non-protein nitrogen (NPN) when UHT milk was packed into pouch versus Tetra Brik and stored at 25 versus 5 °C. Neither type of packaging nor storage temperature affect pH values during storage. Spore-forming bacterial (SFB) count was always higher in UHT milk packed into pouch versus Tetra Brik. Refrigerated storage kept UHT milk without detectable SFB compared to UHT milk held at 25 °C. Pouch packages were responsible for the migration of phthalate derivatives [dimethyl phthalate “DMP”, diethyl phthalate “DEP”, dibutyl phthalate “DBP”, and di-(2-Ethylhexyl) phthalate “DEHP”] into milk with significantly greater levels than milk filled into Tetra Brik. The total sensory scores were decreased significantly during storage, which was more pronounced in UHT milk filled into pouch versus Tetra Brik or stored at 25 °C versus 5 °C. It is concluded that UHT milk filled into Tetra Brik stored at 5 and 25 °C is better in terms of quality and safety indexes than such filled into a pouch.
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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".