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Analyzing the genetic potential and health status of your herd

Tracing the next steps in evidence-based pig production

Fredrik Sandberg, PhD, vice-president of health and nutrition, Furst-McNess Company

Last week, I introduced the system of “evidence-based pig production” and discussed the importance of disseminating information to stakeholders in a timely manner. The key paradigm of this system is organized data and information, which is then reviewed by an expert, before the producer uses any of that information to make management decisions.

This week, I’ll discuss the genetic potential and health status of your herd. Draw on the expertise of others in the field to make successful and fast management decisions.

Knowing and maximizing the genetic potential of your herd

Regardless of the phase of production, your production data is always constrained by the maximum genetic potential of the animal you are producing. This limitation is the case for ALL physiological traits that you are monitoring: e.g. total born, birth weight, weaning weight, average daily gain, feed intake, feed efficiency or carcass traits.

Do not confuse “production potential” with “genetic potential.” The concept of “production potential” can be misleading as it refers to the “typical performance of an animal in a particular type of environment” – it does not refer to genetic potential.

The genetic potential means that the maximum growth rate is, for example, 2.0 lbs/day (or 0.9 kg/day) from weaning to market – and it cannot be exceeded. If a sow has a maximum genetic potential to have a total of 15 piglets, she will not lay down and give 16 or 17 pigs, regardless what we do.

It is critical to strive to know the genetic potential of your animals. Genetic and nutritional suppliers, as well as external resources such as universities, are key sources for this information.

Once you know the maximum potential of your animal, then you can decide how close to that genetic potential it is economically feasible to attain at any given time. For example, you can decide if you should feed low or higher energy diets, if you should invest in state of the art ventilation, or if you should increase space per pig. As we look to long-term performance data, genetic improvements have very large and long-term consequences.  

Knowing, understanding and communicating your health status

Health status is critical to animal production. Our challenge is how do we effectively report that health status in a numerical and reliable way to our veterinary staff and other support staff (e.g. production managers or nutritionists) in as close to real time as is possible? These stakeholders can use this information to help us make any necessary interventions.

The use of cellphone applications, as well as cloud-based information sharing, has moved our ability for such communication forward extensively. Whether large or small, producers can easily afford to use these technologies with significant benefits.

Mortality and medical treatments occurs on daily basis, across multiple stages of production – but how often do you review and communicate that information? As we look to track health, we need to look beyond simply death loss on a daily basis. We also need to begin recording and monitoring medical treatments, amount and level of medications we administer, as well as water consumption.

Effectively communicating and analyzing these key indicators of health information will arm you with the greatest level of management control. The fluctuations in health is undoubtedly the greatest internal financial risk factor of any livestock farm.

Next week, I will discuss the importance of knowing and communicating the limits of your production capability.

Dr. Fredrik Sandberg is the vice-president of health and nutrition for the Furst-McNess Company. He has primary oversight of the company’s swine feeding program, as well as its research and development program, with a heavy focus on antibiotic-free and ractopamine-free feeding programs for swine, poultry and ruminants. Sandberg completed his PhD at the University of Edinburgh in Scotland, with a focus on computational modeling of growth and nutrient requirements in swine during periods of health and disease.