Optimum Solutions for Grower-Finisher Pigs

At the best of times, it is not easy to identify the most economical feeding and production strategy for a grower-finisher barn. Which alternative ingredients should I consider? Should I buy distillers and which supplier offers the product with the most value and the least variation? What nutrient specifications are the most profitable with the current economics for my genotype and my barn environment? At what weight should I ship my pigs? These are just a few of the questions that producers have to find answers for in an increasingly complex and fast changing market environment.

Dynamic, integrated models, such as Shur-Gain's Watson^TM or Purina's OptiPork^TM, are being used to improve performance and profitability of finishing pigs by simplifying the decision making process. One of the main purposes of a modelling approach is to bring together the complex interactions between the animal, its environment and its diet, into a system that will accurately predict the animal's performance under commercial conditions.

The ability of a model to predict or simulate the optimum solution depends on:

     1. the reliability of the input data used to define the problem,

     2. the accuracy of the system used to measure the biological responses, and

     3. the expected outcome to be reported.

These components form the foundation of any model used to predict animal growth.

Solutions generated by a model can examine a problem from multiple facets to determine an appropriate nutrition, feeding management or financial strategy. Because of the integrated nature of the data, "what if" scenarios can be explored and the results measured immediately in terms (economic or production) that meet the producers objectives. This can significantly enhance the management decision making process and allows for the prediction of optimum solutions in grower-finisher production. It is important to note that optimum solutions are farm specific and no one solution fits all because of the differences in production systems on each farm (e.g. health status, genetics, housing, ingredient/feed costs, etc.).

With a modelling approach, there are many different nutrition strategies that can be optimized. Some of these include:

     1. Determining nutrient requirements based on:

     2. Minimizing under and over feeding nutrients

     3. Incorporation of alternative ingredients into diets

     4. Identifying the feeding value of a particular ingredient

     5. Use of ractopamine (Paylean^TM)

It is possible to predict the optimum feed program by comparing the performance and financial responses to different diets within a model. This allows the design and implementation of a feeding budget that best meets the producer's objectives whether that is higher profits per pig or space, lowest feed cost/kg gain, faster growth, or best feed efficiency.

Key to any solution for finishing hogs is the incorporation of a grading grid and the variation of the carcass components associated with a group of pigs shipped to market. A model makes it possible to simulate market performance for any grading grid and determine the financial consequences of any production change such as feed costs, health, stocking density and housing, genetics and marketing or optimum marketing weight.

While both Watson^TM and OptiPork^TM will predict some of the inputs, to generate accurate and reliable results, a baseline of on-farm data is generally required.

Producers will need to gather feed intake, growth rate and carcass data on a representative group of approximately 50 pigs. Feed intake and growth rate should, ideally, be measured every two weeks during the grow-out period; however, in practise it is often easier to gather this data when switching to the next phase. Carcass data and accurate estimates of the variation in carcass weights, loin depth, backfat depth and lean yield are easily obtained through Ontario Pork's OINK system or from grading sheets. Your nutrition consultant should be able to help determine the best approach to gathering this data on your farm.

In an increasingly volatile market environment, use of an integrated model will assist producers in determining the optimum nutrition, management and financial strategies to simplify a complex decision making process. With accurate and reliable on-farm data "what if" scenarios can be simulated within a model to determine the best solution for individual farms based on your goals.


Presented by Dr. Neil S. Ferguson, Nutreco Canada Agresearch; and Dr. Bruno Marty, Agribrands Purina Canada Inc.
Summarized by Greg Simpson - Swine Nutritionist/OMAFRA
Pork News & Views (June 2008) newsletter
Government of Ontario Ministry of Agriculture, Food and Rural Affairs