292 Genetic trend for feed efficiency, growth and carcass traits in three Canadian beef cattle populations involved in the Kinsella breeding project.

Journal of Animal Science(2018)

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摘要
Genomic selection for feed efficiency in beef cattle offers an opportunity to reduce feed costs and greenhouse gas (GHG) emissions while increasing profitability and environmental sustainability in beef production. Data from a selection experiment using three beef cattle populations maintained at the University of Alberta Roy Berg Kinsella Research Ranch namely, the Kinsella beef composite (KC - split into efficient and control lines), purebred Angus (AN), and purebred Charolais (CH) were analyzed following three years of selection (2013–2016) to obtain an evaluation of selection responses. Selection was carried out using multiple trait selection indexes based on molecular breeding values (MBVs). For the KC and AN population, a maternal profitability index (MPI) for improved feed efficiency, i.e. low residual feed intake (RFI), higher direct (DWWT) and maternal weaning weights (MWWT) was applied, while for the CH population a feedlot profitability index (FPI) for low RFI, low dry matter intake (DMI), higher average daily gain (ADG), greater carcass marbling (CMAR), greater hot carcass weight (HCW), increased lean meat yield (LMY), and increased average back fat thickness (AFAT) was applied. Across the three populations, average estimated breeding values (EBVs) obtained from a multivariate animal model showed significant differences at P<0.05 between the 2013 and 2016 born calves for some traits in the selection indexes. In the KC population, the 2016 KC-Efficient herd had a significantly lower average EBV for RFI of -0.004 ± 0.015 Kg DMI/d and a higher average MWWT of 0.018 ± 0.003 kg in comparison to 0.121 ± 0.014 kg DMI/d for RFI and 0.011 ± 0.003 kg for MWWT in the 2016 KC-Efficient calves. Average EBVs for DWWT and MWWT increased in the AN population from -2.071 ± 0.987 to 1.949 ± 0.948 kg and -0.76 ± 0.38 to 1.722 ± 0.317 kg respectively across years. In the CH population, LMY increased from -0.448 ± 0.156 to 0.004 ± 0.117% while CMAR decreased from 16.61 ± 3.247 to 1.377 ± 2.153.
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关键词
genomic prediction,multiple trait selection index,genetic trend
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