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Record W4225359613 · doi:10.1177/10820132221092378

The effects of packaging type and storage temperature on some of UHT milk quality indexes

2022· article· en· W4225359613 on OpenAlexaff
Atef Fayed, Aly Farag El Sheikha, Ali Ali, Moustafa A. Hassan

Bibliographic record

VenueFood Science and Technology International · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsFood scienceQuality (philosophy)ChemistryPhysics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.250
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueFood Science and Technology InternationalSame topicMilk Quality and Mastitis in Dairy CowsFrench-language works237,207