Evaluation of feed processing and analytical methods to improve nutrient utilization of swine diets

Abstract

A total of 7 experiments were conducted to evaluate the effects of particle size and thermal processing on swine growth performance or to develop improved analytical methods for particle size prediction. First, 5 experiments utilized 596 nursery pigs to assess how corn particle size and pelleting affected nursery pig growth performance and feed preference. The improvements from reducing particle size were mixed among experiments, potentially because pigs preferred to consume more coarsely ground corn in both mash (P < 0.05; 79.3 vs. 20.7%) and pelleted diets (P < 0.05; 58.2 vs. 31.8%) diets. Pelleting diets led to a reduction in feed disappearance, which tended to improve feed efficiency in nursery pigs (P < 0.05; 0.61 vs. 0.64 for pigs fed mash vs. pelleted diets in Exp. 1). Next, a total of 270 finishing pigs were utilized to determine the effects of long-term conditioning or extrusion of low energy feedstuffs on finishing pig nutrient digestibility, growth performance and carcass characteristics. Treatments included the same basal diet processed as: 1) non-processed mash, 2) pelleted with 45 s conditioner retention time, 3) pelleted with 90 s conditioner retention time, or 4) extruded. Thermal processing, regardless of type, improved daily gain and feed efficiency (P < 0.05), but did not affect feed intake (P > 0.10). Extruded diets tended to improve feed efficiency compared to pelleted diets (P < 0.10). However, pigs fed thermally-processed diets had greater jowl iodine value compared to those fed mash diets (P < 0.05). Finally, 420 samples were used to determine the impact of top sieve size, grain type, technician, and flow agent on the ability of a 3-sieve analytical method to accurately predict the mean particle size determined by a standardized 12-sieve method. The experiment was a 3 × 2 × 2 × 3 factorial with 3 technicians, 2 sieve sizes (U.S. No. 12 vs. 16 sieve as the top sieve), 2 flow agent levels (0 vs. 0.5 g), and 3 grain types (corn, sorghum, or wheat). Linear regression was used to develop individual equations to predict the mean particle size for each of the 3-sieve methods compared to the standard 12-sieve method recognized as ASAE S319.4, and the GLIMMIX procedure of SAS was used to evaluate the impact of main effects and interactions on predication accuracy. All interactions were removed from the model due to insignificance (P > 0.10). Technician, screen size and flow agent did not affect (P > 0.10) the accuracy of the prediction equations. Grain was the only main effect of significance (P < 0.05), where the prediction equation overestimated the particle size of wheat by approximately 15 µm and underestimated the particle size of corn by approximately 12 µm. While statistically significant, these variations were deemed to be sufficiently accurate for the 3-sieve method, and that separate equations for each grain type were not warranted to retain the simplicity of the method. In summary, technician, sieve size, grain type, and the use of flow agent did not greatly affect the accuracy of the 3-sieve particle size analytical method, so the original method was concluded to be accurate and the preferred method.