Determinants of Reproductive Performance in Dairy Herds using Activity Monitors

The objective of this thesis was to identify cow- and herd-level risk factors associated with reproductive performance in dairy herds that prioritize artificial insemination (AI) at detected estrus by automated activity monitors. We comprehensively assessed reproductive and non-reproductive diseases as well as markers of adaptation to the initiation of the lactation and predictors of subsequent fertility such as early estrus expression during the pre-breeding period. Doing so in a large number of commercial herds allowed us to quantify variability and augment the external validity of determinants of variability among herds. At the cow level, postpartum uterine diseases, excessive loss of body condition, and milk yield in the top third of the herd were associated with decreased odds of detection in estrus during the breeding period. We found substantial variability among herds in the proportion of cows bred in estrus. Early postpartum estrus detection is a promising trait to predict subsequent fertility, but its determinants have not been assessed comprehensively. It is unclear whether it has an independent association with fertility after controlling for health variables known to impair fertility. Cows diagnosed with reproductive or non-reproductive diseases, ranked as medium or high milk producers within the herd in early lactation, or with low body condition at calving had lower odds of being detected in estrus before breeding. Accounting for health variables associated with lower odds of being bred at detected estrus, pregnant at first AI, or pregnant by 120 days, early postpartum estrus detection remained associated with those outcomes, with cows having at least one early estrus having better reproductive performance. At the herd level, the prevalence of reproductive and non-reproductive disorders was linearly negatively associated with the proportions of cows bred at detected estrus, pregnant at first AI, and pregnant by 120 days. It seems that measured management practices and infrastructure characteristics initially associated with the outcomes exert their effects through health variables. This thesis demonstrates that postpartum health disorders are associated with reproductive performance in herds using automated activity monitors as the primarily tool to submit cows to first AI.

Grantor dc:publisher

University of Guelph

Author dc:creator

• Campora, Lucio

Advisor dc:contributor.advisor

• LeBlanc, Stephen

• targeted reproductive management
• estrus detection
• transition health
• uterine disorders

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10214/29627

OAI record oai:identifier

https://atrium.lib.uoguelph.ca/server/oai/request?verb=GetRecord&metadataPrefix=dim&identifier=oai%3Aatrium.lib.uoguelph.ca%3A10214%2F29627