Measuring and comparing reproductive performance in dairy herds: strengths and weaknesses of frequently used parameters

Wapenaar, Wendela; Green, Martin A.; Huxley, J.N.; Reader, Jon; Biggs, Andrew G.; Burnell, Mark; Breen, James; Husband, James; Statham, Jon; Thorne, M C; May, Bill

doi:10.1111/j.2044-3870.2009.tb00236.x

Cited by 2 publications

(3 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Reproductive performance in dairy cows is estimated and monitored by various measurements, such as the calving interval, conception rate, and number of inseminations. When monitoring and benchmarking reproductive performance, herd-specific factors such as delaying first service (Wapenaar et al, 2009) by designating a longer VWP may affect, for example, the calving interval. Comparing the calving interval between 2 cows (or the median between 2 herds) that have different VWP would lead to the conclusion that one cow (or herd) performs better than the other if this difference is not accounted for.…”

Section: Introductionmentioning

confidence: 99%

Factors influencing the chance of cows being pregnant 30 days after the herd voluntary waiting period

Löf

Gustafsson

Emanuelson

2014

Journal of Dairy Science

View full text Add to dashboard Cite

The objective of this study was to study factors affecting a reproductive performance indicator at the cow level adjusted for herd management strategy. Associations between the outcome variable, pregnant or not at the herd voluntary waiting period (VWP) plus 30d (pregnant at VWP+30), and the predictor variables were analyzed using a multivariable, generalized estimation equations model that adjusted for clustering of the data at the herd level. The statistical analysis was stratified on parity. In total, 132,721 cows were retained for analyses, of which 29,113 (22%) were pregnant at VWP+30d. Of the nonpregnant cows, 81,483 cows had records of artificial inseminations (AI) and 22,125 cows had no records of AI. The chance of pregnancy was higher for cows of the Swedish Red and for other/crossbreeds compared with Swedish Holstein, for cows from herds with high heat detection efficiency compared with cows from herds with medium and low heat detection efficiency, for cows from herds with long VWP (i.e., >51d) compared with cows from herds with short VWP (<51d), and for cows in freestalls compared with cows in tiestalls. The chance for pregnancy was lower for cows with severe problems at claw trimming compared with cows with no problems at trimming (only for second- and higher-parity cows), for cows that had a record of reproduction-related disease, for cows that had a record of any other disease compared with cows without record, for second- and higher-parity cows with records of dystocia compared with cows with no record of dystocia, for first-parity cows in the group with the highest milk yield compared with first-parity cows in the group with the lowest milk yield, for cows of third and higher parity in the group with the lowest milk yield compared with cows in higher yielding groups, for cows bred in summer compared with those bred in winter-spring (not significant for first-parity cows), and for cows with a twin birth had compared with cows with a single birth. We observed associations of the dose-response type, such that when the milk fat-to-protein ratio increased, the chance for pregnancy decreased, and as the somatic cell count increased, the chance for pregnancy decreased. In conclusion, factors that are known to affect reproductive efficiency also affect the chance of cows being pregnant at the herd VWP plus 30d.

show abstract

Section: Introductionmentioning

confidence: 99%

Factors influencing the chance of cows being pregnant 30 days after the herd voluntary waiting period

Löf

Gustafsson

Emanuelson

2014

Journal of Dairy Science

View full text Add to dashboard Cite

show abstract

“…Most data analysis software provides visualisation of the eligible population size or confidence intervals around rates to assist with this. *Adapted from Wapenaar and others (2009)…”

Section: Box Continued: Summary Of Fertility Key Performance Indicators*mentioning

confidence: 99%

“…Regular and early pregnancy diagnosis (PD) enables minimal time lag when assessing this metric, although lack of PD data results in use of either non-return to service after a specific time or next calving event as outcome measures for this rate, making analysis more retrospective. *Adapted fromWapenaar and others (2009),Hudson and others (2012)…”

mentioning

confidence: 99%

Herd health: approach to assessing fertility data quality

Reynolds¹,

Hudson²

2023

In Practice

View full text Add to dashboard Cite

Background: Farm animal veterinarians are increasingly using routinely collected farm data to assess performance and enable implementation of preventive management changes on farm. Furthermore, the significance of data collection and data management to the farming industry and the farmer‐vet relationship has been identified as a key component of the future cattle veterinary practitioner role in the UK. Aim of the article: This article provides an overview of commonly recorded key performance indicators of herd fertility, and guides practitioners on how to assess the quality of such recorded data so that they can undertake meaningful data analyses.

show abstract

Measuring and comparing reproductive performance in dairy herds: strengths and weaknesses of frequently used parameters

Cited by 2 publications

References 1 publication

Factors influencing the chance of cows being pregnant 30 days after the herd voluntary waiting period

Factors influencing the chance of cows being pregnant 30 days after the herd voluntary waiting period

Herd health: approach to assessing fertility data quality

Contact Info

Product

Resources

About