Identification and Evaluation of Novel Estrous-Related Fertility Traits Using Automated Sensor Data from Commercial Holstein Herds

The development and commercial adoption of automated sensor technologies within dairy production systems provide new opportunities to derive accurate and objective phenotypic measures of fertility. This thesis was conducted to identify and evaluate the potential of novel sensor-based fertility traits to be included in the selection criteria for reproductive performance in dairy cattle. Five traits were defined using computed index values linked to estrous expression. Genetic parameters were estimated for the traits, followed by an impact assessment of their direct selection on traditional fertility trait performance. Heritability and repeatability estimates were low and aligned with those of current traits, while genetic correlations between studied traits ranged from moderate to strong. Favourable associations were observed between select combinations of novel traits with existing fertility parameters. Research findings indicate that estrous-related traits based on index values could be suitable predictors of fertility and potentially be considered for future inclusion in genetic evaluations.