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Researchers find better ways to predict energy value in feed ingredients

A team of researchers set out to test the hypothesis that if all chemical components in the ingredient were accounted for, gross energy would equal analyzed gross energy.

Source: University of Illinois College of Agricultural, Consumer & Environmental Sciences
To formulate cost-effective livestock diets based on energy, it’s vital that the energy content of feed ingredients is known as accurately as possible. Researchers at the University of Illinois are working on more accurate ways to predict the energy value of ingredients.

Hans Stein, professor in the Department of Animal Sciences at the University of Illinois, says that the feed components presented in composition tables usually don’t add up to 100%, which indicates that not all energy-contributing components are accounted for.

“Analyzing all chemical components in feed ingredients is challenging,” Stein says. “However, we believe that being able to analyze all energy-contributing components in a feed ingredient is likely to yield more accurate estimates for the energy value in that ingredient.”

A team of researchers led by Stein set out to test the hypothesis that if all chemical components in the ingredient were accounted for, gross energy — calculated by adding values from all energy-containing components in feed ingredients — would equal analyzed gross energy.

They studied 10 ingredients that varied in fiber concentration and composition: corn, wheat, soybean meal, canola meal, distillers dried grains with solubles, corn germ meal, copra expellers, sugar beet pulp, synthetic cellulose and pectin.

In addition to the traditional analyses for components such as crude protein, starch, fiber and fat, Stein’s team also analyzed the 10 ingredients for tannins, sinapine, glucosinolates, glycerol, fructo-oligosaccharides and a number of soluble carbohydrates.

Their hypothesis didn’t hold true for all ingredients. The calculated gross energy was 8% greater than the analyzed value for corn, 12% greater for pectin and 12% less for DDGS and sugar beet pulp. Stein says this is likely due to inaccuracies in measurement, as well as insufficient knowledge about the energy value of components that are analyzed less frequently.

“Some energy-contributing components may be analyzed as a different component of the feed ingredient. It’s also possible that the gross energy values we use for lignin, tannins, sinapine and other components in the ingredient are inaccurate.”

However, the calculated gross energy values for wheat, soybean meal, canola meal, corn germ meal, copra expellers and synthetic cellulose were within 4% of analyzed gross energy for these ingredients, indicating that the analyzed components appear to be accurate.

“You don’t get the complete picture on energy content without analyzing all energy-contributing components, in particular low-molecular-weight carbohydrates,” Stein says.

“Our data indicate that at least for some ingredients, it’s possible to predict gross energy accurately if traditional analyses are complemented by additional analyses, primarily of soluble carbohydrates and lignin.”

In another phase of the experiment, the team simulated apparent ileal digestibility and apparent total tract digestibility of the ingredients using an in vitro procedure. They found that the fiber components that are traditionally analyzed, acid detergent fiber and neutral detergent fiber, may not be the best predictors of the fiber value in ingredients.

“Instead of ADF and NDF, we recommend analyzing insoluble fiber and total dietary fiber to estimate digestibility, because these values are better correlated with digestibility of dry matter and organic matter,” Stein says.

The paper, “Analysis for low-molecular-weight carbohydrates is needed to account for all energy-contributing nutrients in some feed ingredients, but physical characteristics do not predict in vitro digestibility of dry matter,” is published in the Journal of Animal Science. Co-authors were Diego Navarro of Illinois and Erik Bruininx and Lineke de Jong of Agrifirm Innovation Center. Agrifirm Innovation Center of Apeldoorn, The Netherlands, provided funding for the study.

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