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Record W2027680873 · doi:10.3168/jds.2010-4102

Assessment of the application of an automated electronic milk analyzer for the enumeration of total bacteria in raw goat milk

2011· article· en· W2027680873 on OpenAlexafffundabout
L. Ramsahoi, Anli Gao, Martha Fabri, Joseph Odumeru

Bibliographic record

VenueJournal of Dairy Science · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsMinistry of the Environment, Conservation and ParksMinistry of Agriculture, Food and Rural AffairsUniversity of Guelph
FundersOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsRaw milkBulk tankLactoseSomatic cell countFood scienceEnumerationPopulationMathematicsRaw materialAnimal scienceBiologyChemistryMedicineIce calvingHerdLactation

Abstract

fetched live from OpenAlex

Automated electronic milk analyzers for rapid enumeration of total bacteria counts (TBC) are widely used for raw milk testing by many analytical laboratories worldwide. In Ontario, Canada, Bactoscan flow cytometry (BsnFC; Foss Electric, Hillerød, Denmark) is the official anchor method for TBC in raw cow milk. Penalties are levied at the BsnFC equivalent level of 50,000 cfu/mL, the standard plate count (SPC) regulatory limit. This study was conducted to assess the BsnFC for TBC in raw goat milk, to determine the mathematical relationship between the SPC and BsnFC methods, and to identify probable reasons for the difference in the SPC:BsnFC equivalents for goat and cow milks. Test procedures were conducted according to International Dairy Federation Bulletin guidelines. Approximately 115 farm bulk tank milk samples per month were tested for inhibitor residues, SPC, BsnFC, psychrotrophic bacteria count, composition (fat, protein, lactose, lactose and other solids, and freezing point), and somatic cell count from March 2009 to February 2010. Data analysis of the results for the samples tested indicated that the BsnFC method would be a good alternative to the SPC method, providing accurate and more precise results with a faster turnaround time. Although a linear regression model showed good correlation and prediction, tests for linearity indicated that the relationship was linear only beyond log 4.1 SPC. The logistic growth curve best modeled the relationship between the SPC and BsnFC for the entire sample population. The BsnFC equivalent to the SPC 50,000 cfu/mL regulatory limit was estimated to be 321,000 individual bacteria count (ibc)/mL. This estimate differs considerably from the BsnFC equivalent for cow milk (121,000 ibc/mL). Because of the low frequency of bulk tank milk pickups at goat farms, 78.5% of the samples had their oldest milking in the tank to be 6.5 to 9.0 d old when tested, compared with the cow milk samples, which had their oldest milking at 4 d old when tested. This may be one of the major factors contributing to the larger goat milk BsnFC equivalence. Correlations and interactions between various test results were also discussed to further understand differences between the 2 methods for goat and cow milks.

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)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.295
Teacher spread0.269 · 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 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

Citations17
Published2011
Admission routes3
Has abstractyes

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