October 19, 2017

3 Min Read
Optimizing dietary net energy that maximizes profitability in growing-finishing pigs
National Pork Producers Council

By Jose Soto, Mike Tokach, Steve Dritz, Jason Woodworth, Joel DeRouchey and Robert Goodband, Kansas State University; Marcio Goncalves and Uislei Orlando, Genus PIC-USA
With energy representing the most expensive component of the diet, the first and most important step in diet formulation is to set the energy concentration. Selected energy levels are often based on history or impact on diet cost rather than an in-depth economic analysis. To assist in determining the most economic dietary energy levels for growing-finishing pigs, a Microsoft Excel-based model was developed to contrast dietary net energy defined by the user with recommended concentrations intended to maximize profitability.

The model is divided into three sections: 1) model inputs (including economics, production, and dietary information; 2) model calculations and optimization, and 3) model outputs with recommended dietary NE concentrations. To calculate pig performance, the model uses prediction equations for average daily gain. Where ADG, g = 0.1135 x NE, kcal/kg + 8.8142 x Avg BW, kg - 0.05068 x (Avg BW, kg)2 + 275.99, when lysine or other amino acids are not limiting. To calculate G:F, the assumption is that feed efficiency has a linear relationship with net energy in the diet. Therefore, a 1% change in net energy will result in a 1% change in feed efficiency. To account for the negative impact of fiber on carcass yield, this model utilizes prediction equations developed by Soto et al. (2017), reviewed in a previous edition. For profitability calculations, a non-linear mathematical programming model was designed to select the dietary NE content that yields the greatest income over total cost per pig on a live or carcass basis.

An example using this model is presented in Tables 1, 2, and 3. The example uses a six-phase feeding program based on the corn-soybean meal and dried distillers grains with solubles (DDGS). To generate the NE range, five diets in each phase were formulated to include 0, 10, 20, 30, and 40% DDGS. Results were compared to a base feeding program with 20% DDGS in all diet phases. Assumptions for the base feeding program included: 1) overall ADG of 2.15 lb; 2) overall F/G of 2.90; 3) carcass yield of 73.4%; 4) feeder pig cost of $55.00/pig; 5) facility cost of $0.11/pig/d; 6) other cost (veterinary supplies, trucking, etc.) of $8.00/pig; 7) carcass price $0.65/lb. To further evaluate the model performance, DDGS pricing was modified from low-cost ($90/ton) to high-priced ($150/ton). Main ingredients prices used were: corn $3.48/bu, soybean meal $290.60/ton, L-Lys $0.69/lb.

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With low-priced DDGS, the model solution suggested that NE should be decreased in phases 1 to 5, forcing in 40% DDGS. In phase 6, the model yielded no modification from the current energy value. The recommended NE values projected worse ADG, feed efficiency, and carcass yield than the current 20% DDGS diets; however, income over total costs was projected to increase by $3.75/pig. With high-priced DDGS, the model solution still suggested that NE should be decreased and more DDGS fed; however, the extent of this decrease is lower compared to the low priced DDGS scenario. For phases 5 and 6, the recommended NE values are increased, particularly for phase 6. In this scenario, the recommended NE values project to slightly worsen feed efficiency but improve carcass yield. With the use of the recommend NE values under the conditions of this scenario, income improved by $1.26/pig.

The model described can be used to predict the value of dietary NE that yields the greatest economic return to the production system. The model can be downloaded at KSUSwine.org.

 The model will be discussed in more depth at KSU Swine Day, Nov. 16. Click here for more information.

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