Genetic improvement and dissemination for the global commercial swine industry
M. S. Culbertson A B , W. O. Herring A , J. W. Holl A and D. Casey AA Genus PIC, Hendersonville, Tennessee 37075, USA.
B Corresponding author. Email: matt.culbertson@genusplc.com
Animal Production Science 57(12) 2366-2369 https://doi.org/10.1071/AN17317
Submitted: 5 June 2017 Accepted: 19 September 2017 Published: 20 November 2017
Abstract
Commercial swine production has become an increasingly globalised industry, with global meat trade demanding that all regions compete on cost and differentiation of pork products. The utilisation of continually improving genetic populations can be one input that helps maintain, or increases, the competitiveness of an individual producer or regional industry. So as to deliver these improving genetic populations, genetic providers of today must focus on developing and implementing best science that delivers improvement on traits affecting commercial profitability. Providers must also efficiently multiply and disseminate the improved merit to the commercial hog production level. The swine-genetics industry has made considerable progress in driving a faster genetic gain over the past 30 years by systematically combining ever-changing computing power, accurate data capture and emerging genomics information. The combination of these technologies today has resulted in hundreds of thousands of animals being genotyped for tens of thousands of markers, and this information is being combined with extensive phenotypic data to deliver rates of genetic gain nearly double what we were able to achieve 20 years ago. As importantly, this scientific advancement can then be combined with the ability to continue to understand and evaluate emerging traits related to animal robustness, well-being and consumer demand, resulting in the most comprehensive definition of selection targets in the history of modern animal improvement. Finally, managing the dissemination of these genes through boar stud and multiplication systems helps ensure that the commercial level minimises lag and utilises the highest-merit genetics available.
Additional keywords: genetic lag, performance testing, selection objectives.
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