Breeding for Profitability

by 5m Editor
22 May 2009, at 10:41am

EU - Following on from the article on PIC Profit Equations (4 March 2009), which explained the importance of considering the economic contribution of all traits to farm performance and profitability, this article focuses on how some of those traits and novel technologies are utilised in PIC’s breeding program (Genetic Improvement program).

The objective of PIC’s breeding programme is to maximise the rate of genetic improvement of the breeding stock (delta G) so that the performance and profitability of the breeding animals and their commercial offspring increases generation after generation. Or in other words: to make your business a more profitable one.

This is done by selecting animals with the highest genetic merit from the population and mating them to produce the next generation. However, Genetic Improvement/genetic merit is meaningless unless is it defined in such a way that it is relevant to commercial production. Defining the breeding goal i.e. which performance traits to improve is, therefore, a critically important part of the process of PIC Genetic Improvement.

Using the Profit Equations, PIC is able to calculate profit per sow or per finishing pig and the marginal economic value (MEV) of the different traits involved. In this way PIC is able to understand the value and profitable contribution of all traits and ensure that these are combined into a selection index in an optimised way. This ensures that all the beneficial traits are captured and improved, so that increasing delta G directly improves profitability of commercial producers.

PIC now routinely measures 49 traits that affect the profitability of pig production. These can be grouped into the following areas:

  • Robustness and mortality of both the sow and her offspring at different phases of life
  • Female reproductive performance
  • Grower-finisher pig performance
  • Meat quality
  • Carcass composition

Although the basic principles of Genetic Improvement have been applied by many pig breeders for a number of years, the difference here is the sheer breadth and depth of traits that are selected, plus the many novel and proprietary technologies that PIC has developed and implemented to drive Genetic Improvement faster.

PIC is now utilizing many cutting edge and proprietary technologies in its breeding program to ensure that Breeding Values (EBVs) are more accurate than ever; that Genetic Improvement is faster than ever; and that pigs are selected for improved profitability in a commercial environment i.e. in our customer farms:

  • PopSim: Software developed to optimize population sizes and structure required to most efficiently drive Genetic Improvement.
  • GNXbred: A breeding program implemented to produce and record performance of crossbred progeny of nucleus sires in commercial farms. This data is used in calculating Cross-bred Breeding Values (CBVs) for performance of commercial sows and finishing pigs, rather than traditional Estimated Breeding Values (EBVs) focused on pure line performance.
  • DNA Markers: PIC now routinely uses 159 DNA markers in the breeding program to increase the accuracy of breeding values.
  • PICblup: Customised software used to perform MA-BLUP (Marker Assisted, Best Linear Unbiased Prediction) which optimally combines DNA marker information with commercial cross-bred performance, pure line performance, and pedigree information to ensure the most accurate breeding values available today.
  • PICmate: Software developed to enhance selection and mating in order to optimize Genetic Improvement at chosen rates of inbreeding.
  • APEX: A brand new genetic nucleus farm which increases global nucleus capacity with pen sow housing, increased performance test capacity and expanded AI-centre capacity. This new nucleus increases the quantity and quality of the data recorded and maximizes availability of highest genetic potential boars and gilts for global dissemination. All of this contributes to increased delta G.

So, in summary, rather than focusing on selecting for single traits (which may rapidly improve performance of specific, individual phenotypes), PIC measures and collects a vast range of traits and information but with only one goal in mind – improving your profitability.