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Record W6990674043

The effect of body weight during the rearing period on milk production in Québec dairy cattle

2019· dissertation· en· W6990674043 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2019
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsnot available
Fundersnot available
KeywordsDairy cattleMilk productionBody weightPeriod (music)Production (economics)Dairy farming
DOInot available

Abstract

fetched live from OpenAlex

The Canadian dairy industry is composed of around 11,000 farms and approximately 1.4 million head, of which approximately 30 percent are heifers (Canadian Dairy Information Centre, 2018). Heifers are of great importance because they represent the future of dairy farms, and, without them, the herds could not evolve and continue producing over time. Producers select replacement heifers that have the potential to become more profitable than the existing cows that will eventually be replaced. Therefore, they should be raised to reach an adequate size and body weight for breeding, so that they can reproduce successfully, and subsequently become productive. This process of rearing replacement heifers can cost as much as 20 percent of the total production expenses on dairy farms (Delgado et al., 2015). The rearing period of a heifer does not only impact the actual growth rate of the animal early on; some researchers have also discussed longer-lasting effects on the animals' performance as lactating dairy cows (Soberon et al., 2012; Macdonald et al., 2005; Krpálková et al., 2014). The objective of this research was to determine the effects of body weight during rearing on the future milk production of Quebec dairy cattle. This was performed by looking at three periods of growth in a heifer's pre-lactation life – birth to weaning; pre-pubertal; and post-pubertal – and analysing the effect of their respective body weight categories on future milk production. Data were provided by the Quebec Dairy Herd Improvement Agency (Valacta), and included body-weight measurements, breeding records, and information for first, second, and third and plus lactations of Holstein dairy cattle. The study covered the years 2000 to 2015, and analyzed production and economic variables such as milk, protein, and fat yield (lactation and 305-day), gross profit, milk value and feed cost. The analyzed data consisted of a total of 22,312, 16,352 and 7,494 animals for the first, second and the third and plus lactations, respectively.While there was a tendency for heavier body weights up until 90 days of life (birth to weaning period) to have higher yields than lighter weights, the body-weight category of 110 to 124kg (not the heaviest) was found to have a significant effect on future first lactation milk, protein and fat production. Furthermore, pre-pubertal body weight had a significant effect on the first, second, and third and plus lactations where higher weights produced significantly higher first and second milk and milk-component yields. The effect of body weight during the post-pubertal period was significant on the first and second lactation where animals that weighed ≥410kg had higher milk, protein and fat yields.Some of the findings may have been influenced by the substantially lower number of observations in the third and later lactations, pointing to the industry's challenge of longer herd life. In addition, the lack of animals that had weight measurements (both a sufficient number, and a range throughout the complete rearing period) serves to encourage increased recording by producers and advisors, so that the data can be used for better lifetime analyses.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score0.529

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.218
Teacher spread0.209 · 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 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
Published2019
Admission routes1
Has abstractyes

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