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Both pelleting and reducing particle size of corn increase net energy and digestibility of amino acids and fat in corn-soybean meal diets fed to growing pigs

Pelleting and reducing particle size of grains often improve nutrient digestibility by pigs. Pelleting may also reduce particle size of grains, and it is not known if improvements in nutrient digestibility obtained by reducing the particle size of grain and improvements obtained by pelleting are additive or if there are interactions between particle size reduction and pelleting. Therefore, two experiments were conducted to test the hypothesis that particle size reduction and pelleting, separately or in combination, increase the apparent ileal digestibility (AID) of starch, the standardized ileal digestibility (SID) of amino acids (AA), N balance, apparent total tract digestibility (ATTD) of gross energy (GE), fiber, and fat, and net energy (NE) in corn-soybean meal diets fed to growing pigs.

Experimental design

Six corn-soybean meal based diets were used in a 3 × 2 factorial with three particle sizes of corn (i.e., 700, 500, or 300 μm) and two diet forms (i.e., meal or pelleted). All diets contained 0.40% TiO2 as an index. An N-free diet was also used in Exp. 1 to determine basal endogenous losses of AA. Pigs were allowed ad libitum intake of feed in Exp. 1 and 2.

In Exp. 1, seven pigs (initial weight = 59.30 kg; SD = 2.77) that were equipped with a T-cannula in the distal ileum were allotted to the seven diets using a 7 × 7 Latin square design with seven periods. Each experimental period lasted seven days. The initial five days of each period were considered an adaptation period. Ileal digesta were collected on day 6 and 7 for nine hours using standard procedures. Diets and ileal digesta were analyzed for Ti, starch, and AA to calculate the AID of starch and AA in the diet and the SID of AA was calculated by correcting the AID of AA for the basal endogenous losses of AA.

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In this episode of The Swine it Podcast Show Canada, Swaminathan Jayaraman, Research Assistant and PhD Candidate at Iowa State University College of Veterinary Medicine, explains how integrated data systems can improve disease surveillance in swine production. He discusses combining diagnostics, animal movement data, production records, and spatial analytics to identify risks earlier and support proactive decision-making for PRRS, PED, and swine influenza. Listen now on all major platforms!

"Disease surveillance remains largely reactive because outbreaks are often confirmed only after transmission has already occurred across multiple connected production sites."

Meet the guest: Swaminathan Jayaraman / swamjay is a Graduate Research Assistant at Iowa State University College of Veterinary Medicine. With academic training in management information systems and engineering, he focuses on integrating diagnostic, production, and movement data to improve disease surveillance and decision support in swine production systems. Listen to Swaminathan Jayaraman on The Swine it Podcast Show Canada, available on all major platforms.