Abstract
The objective of this study was to estimate the breed, heterosis, and recombination effects on different components of the lactation curve of Girolando cattle. The dataset used consisted of 12,121 purebred cows of Holstein (H) and Gyr (G) breeds, and six H×G crossbred cows (Girolando). The model used presents random effects of herd and cow, regression coefficient associated with linear effect of proportion of H breed, regression coefficient associated with the linear effect of heterosis between H and G [...]
Highlights
Girolando is a dairy cattle breed created in Brazil by crossing the Gyr and Holstein breeds for milk production systems in tropical pastures (Canaza-Cayo et al, 2017)
The model used presents random effects of herd and cow, regression coefficient associated with linear effect of proportion of H breed, regression coefficient associated with the linear effect of heterosis between H and G breeds, regression coefficient associated with the linear effect of recombination between H and G breeds, and random effect of residual
Dijkstra’s (DJ), Nelder’s (ND), Wilmink’s (WL), and Wood’s (WD) models were tested to fit production records of these different genetic groups. These models were tested according to evaluation criteria of quality of fit (AIC, Bayesian information criterion (BIC), and root mean square error (RMSE)), and the two best models (WD and WL) were chosen for estimation of 305-day milk yield (MY305), peak yield, time to peak, and persistency of milk yield
Summary
Girolando is a dairy cattle breed created in Brazil by crossing the Gyr and Holstein breeds for milk production systems in tropical pastures (Canaza-Cayo et al, 2017). This crossing aimed to obtain heterosis and complementarity between these breeds (Canaza-Cayo et al, 2014). The use of crossbred animals for milk production requires analysis of performance of individual cows, and the lactation curve is one of the main tools used to predict such performance (Pereira et al, 2016). The main components of the lactation curve are peak yield, time to peak, and persistency of milk yield (Wasike et al, 2014). Animals with a less pronounced peak of lactation are less prone to physiological stress because they have lower production at peak and do not have as high of an
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
