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Record W2894215547 · doi:10.3168/jds.2018-15151

Effect of estrous expression on timing and failure of ovulation of Holstein dairy cows using automated activity monitors

2018· article· en· W2894215547 on OpenAlexafffund
T.A. Burnett, Liam Polsky, Manveen Kaur, R.L.A. Cerri

Bibliographic record

VenueJournal of Dairy Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British Columbia
KeywordsEstrous cycleOvulationActivity monitorMedicineAnimal scienceFollicular phaseFollicleInternal medicineEndocrinologyAndrologyBiologyPhysical activityHormone

Abstract

fetched live from OpenAlex

The aim of this study was to determine if estrous expression, as measured by an automated activity monitor (AAM), affects timing and failure of ovulation of lactating Holstein dairy cows. Cows were equipped with 2 AAM, 1 neck-mounted (AAM C ) and 1 leg-mounted (AAM L ), by 10 d postpartum and enrolled into the trial when their activity crossed the alert threshold on the AAM C . A total of 850 episodes of estrus from 293 different cows were used for this study. When cows were enrolled, their ovaries were scanned by transrectal ultrasonography and gait and body condition scored. Ovaries of cows detected in estrus were scanned twice daily for a maximum of 3 d to determine the disappearance of the preovulatory follicle (ovulation) and the interval from estrus to ovulation was calculated. Physical activity data recorded from the AAM were used to determine estrus behavior using 2 traits: (1) peak activity and (2) duration. Peak activity was only available for the AAM L . Peak activity was defined as the maximum activity during an estrus episode. Duration of estrus was defined as the time the activity of the cow exceeded threshold values set by the AAM software. The AAM C correctly identified 87.8% of the estrus alerts, with 12.2% false positives. The average (±standard deviation) intervals from activity alert to ovulation were 25.8 ± 10.2 and 24.7 ± 9.3 h for the AAM C and AAM L , respectively. Changes in estrous expression were associated with differences in the interval from alert to ovulation. Cows with short intervals to ovulation were found to have less intense estrous expression than cows with medium and long length intervals to ovulation using the AAM C , whereas using the AAM L , cows with short intervals to ovulation exhibited less intense estrous expression than cows with medium but the same as those with long intervals to ovulation. Furthermore, irrespective of the AAM, estrus events with less estrous expression had increased odds of having a short interval to ovulation (below the median of 20 h) when compared with those having greater estrous expression (2.6 and 1.9 increased odds for the AAM C and AAM L , respectively). Ovulation failure was affected by estrous expression because estrus events with greater peak activity or longer duration had reduced ovulation failure compared with those with less estrous expression (AAM C peak activity: 1.9 ± 1.4 vs. 9.5 ± 1.7%; AAM L peak activity: 2.3 ± 1.4 vs. 6.2 ± 1.5%; AAM C duration: 2.1 ± 1.4 vs. 8.9 ± 1.7%). In addition, cows with more estrous expression had greater pregnancy per artificial insemination than those with less estrous expression with both the AAM C (42.3 ± 0.4 vs. 31.7 ± 0.4%) and the AAM L (43.1 ± 0.4 vs. 36.3 ± 0.4%). Pregnancy per artificial insemination results were consistent even when removing cows that failed to ovulate. In conclusion, expression of estrus was highly associated with ovulation timing, ovulation failure, and fertility when using 2 different AAM. Cows with greater estrous expression have longer intervals from activity alert to ovulation, experience less ovulation failure, and have greater pregnancy per artificial insemination.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.027
GPT teacher head0.301
Teacher spread0.275 · 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

Citations61
Published2018
Admission routes2
Has abstractyes

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