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Machine Processing of Milk in Dairy Production

2019· article· en· W2976603772 on OpenAlexaboutno aff
Юрий Гербер, Yuriy Gerber, Александр Гаврилов, Alexander V. Gavrilov

Bibliographic record

VenueFood Processing Techniques and Technology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Industry and Aquatic Biology
Canadian institutionsnot available
Fundersnot available
KeywordsFood scienceHomogenization (climate)KefirFermentationPasteurizationFermented milk productsMaterials scienceChemistryMathematicsProcess engineeringEngineeringLactic acid

Abstract

fetched live from OpenAlex

For fermented milk products, consistency plays a leading role: it provides a quality product and shapes consumer demand. There have been numerous studies of the effect of the technological process on the properties of sour cream, kefir, etc. However, these studies were performed after the introduction of ferment. Thus, the effect of parameters of thermal and mechanical treatment during the primary stage on the physical and mechanical properties of fermented milk products remains understudied. The research objective was to confirm the following hypothesis: the parameters of homogenization during the primary stage affect the consistency of the fermented milk products. A set of experiments made it possible to expose the dependence of the rheologic properties of sourmilk products from the regime parameters of homogenization. The research featured initial mix for kefir and sour cream production. The milk was preheated to 45C in an Alfa-Laval pasteurizer and separated in an Alfa-Laval separator. The fat-free milk (1% of fat for kefir production) was heated in a pasteurizer to 55–60C and homogenized at 8–16 mPa. The homogenizing device of the manometer was additionally equipped with a phase separator delimiter of the S-homogenizer type. The acidity and viscidity for the sour cream and kefir were measured at different pressure values. The power expenses on homogenization depended on the pressure and the volume of milk. The pressure of homogenization proved to be a meaningful factor and affected the fermentation process. It rendered a substantial influence on the consistency and taste qualities of the fermented milk product. The experiment defined the optimal temperature of fermentation for kefir production. The optimization of pressure decreased the energy consumptions by 4.4 kW/h (24.4%) per ton. Solar thermal collectors were used to preheat the milk before homogenization, which decreased the specific energy consumption by 10.5 kW/h per ton. The new parameters lower the prime cost of the dairy products and raise their competitiveness.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.003

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 head0.017
GPT teacher head0.230
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations7
Published2019
Admission routes1
Has abstractyes

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