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Record W7028276810

The effect of different cluster take-off levels at udder quarter in combination with feeding during milking on milk production in dairy cows : milk yield, milk composition and milking time

2016· other· en· W7028276810 on OpenAlexaboutno aff

Bibliographic record

VenueEpsilon Archive for Student Projects (University of Southampton) · 2016
Typeother
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsnot available
Fundersnot available
KeywordsMilkingUdderLactoseLatin squareMilk productionQuarter (Canadian coin)Automatic milking
DOInot available

Abstract

fetched live from OpenAlex

It was early stated that high take-off level at whole udder level decreases the milking time. There are, however, few studies dealing with take-off level at udder quarter level. It has also been stated that feeding of concentrate during milking can be used as a teaser to motivate the cows to visit the milking unit (MU) and to improve the milk ejection. Furthermore, has it been observed that milk yield can be negatively affected by high take-off levels but positively reinforced by feeding during milking. The aim of the present study was to evaluate different take off levels at udder quarter level in combination with or without feeding of concentrate during milking. The study was conducted at The Swedish Livestock Research Centre, Lövsta, Uppsala, Sweden, during November and December 2015. Thirty cows of the Swedish Holstein (n=9) and Swedish Red breeds (n=21) were used. Three different cluster take-off levels (100, 300 or 500g/min) on udder quarter level in combination with (f) or without feeding (nf) of concentrate during milking were tested in a six week long study in a 6x6 Latin Square model. It was found that milk yield was not affected by neither treatment, take-off level nor feeding of concentrate during milking, while milk composition was affected by both take-off level and feeding of concentrate during milking. Lactose and protein content was higher when concentrate was provided, while there was a tendency for lower fat content. The milking time was shorter with higher take-off level and when no concentrate was provided. Protein and lactose content was highest for take-off level 300 g/min, but also lower when no concentrate was provided during milking. Percent of residual milk was highest in treatment 300f while lowest for 100f and 300nf. The present study therefore suggests that a take-off level at 500 g/min in combination with no concentrate during milking is appropriate to ensure a sufficient udder empting and possible improvement of milking efficiency, with a low effect on milk composition and no effect on milk yield.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.030
GPT teacher head0.283
Teacher spread0.253 · 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.

Study designObservational
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

Citations0
Published2016
Admission routes1
Has abstractyes

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