Diet mixing time affects nursery pig performance1

Abstract

The objective of this study was to determine the effects of mixing time (mixer efficiency) of diets containing several low-inclusion ingredients (crystalline AA, ZnO, a medication, and vitamin and trace mineral premixes) on growth performance of nursery pigs. In a pilot study, mixing efficiency of a 1,360-kg capacity, horizontal ribbon mixer was evaluated with salt of different particle sizes (440, 730, 2,000, and 3,000 microm). Sample preparation was evaluated by analyzing diet samples as collected (unground) or by grinding the entire sample to approximately 400 microm in particle size (ground). Diets (907 kg) were mixed, and samples were collected after 0, 30, 60, 120, 210, 330, 480, and 630 s of mixing. The coefficient of variation among 10 samples for each mixing time was used to measure mixer efficiency as determined by Cl concentration. A salt particle size x sample preparation x mixing time interaction was observed (P = 0.04). Samples with 2,000- or 3,000-microm salt particle size (unground or ground) never reached the desired mixing efficiency of a 10% CV. Using 440-microm salt (unground or ground) or 730-microm salt particle sizes (ground) was necessary to accurately achieve a mixing efficiency of a <10% CV within 330 and 630 s, respectively. Next, 180 weanling pigs (PIC, 6.31 +/- 0.84 kg of BW, 21 +/- 3 d of age) were fed diets in 2 phases (d 0 to 14 and d 14 to 28). Treatments consisted of mixing diets for 0, 30, 60, 120, or 330 s (440-microm salt particle size). Samples were collected in the mixer, and then each bag of feed (22.5 kg) was labeled (first to last as-manufactured) and sampled to determine the mixing efficiency. An individual bag of feed was fed to a single pen of pigs, and when finished, the next sequential bag was used. As mixing time increased, mixer CV were 178, 38, 26, 21, and 5% for phase 1 and 172, 79, 60, 48, and 26% for phase 2. As mixing time increased, bag CV values were 26, 20, 16, 11, and 7% for phase 1 and 56, 45, 40, 33, and 12% for phase 2. From d 0 to 14, increasing mixing time increased ADG (linear, P < 0.01) and G:F (quadratic, P = 0.03). From d 0 to 28, increasing mixing time increased ADG (quadratic, P < 0.01) and G:F (linear, P = 0.04). These data demonstrate that inadequate diet mixing (CV > 12%) reduces nursery pig performance.

Quantifying the consequences of nutritional strategies aimed at decreasing phosphorus excretion from pig populations: a modeling approach

“…This is again a simplification, as feed composition may vary randomly, due to variation in nutrient composition of the ingredients that compose a feed (Kim et al, 2002) or uncertainty introduced by feed processing or mixing (Groesbeck et al, 2007). Introducing uncertainty in feed composition and environmental features is a long neglected issue in nutrition and metabolism models, and represents our next challenge in model development.…”

The consequences of introducing stochasticity in nutrient utilisation models: the case of phosphorus utilisation by pigs

“…Groesbeck et al (6) and Traylor et al (5) have concluded that a CV of salt of upto 12 and 20 % in pig feeds, respectively, is adequate for maximum growth performance of pigs. This discrepancy may be due to the fact that the model currently overestimates the effect of P deficiency on the reduction of protein growth, as discussed above.…”

“…Feed ingredients may vary substantially in nutrient composition, due to growing conditions, hybrid or variety differences, planting and harvest dates and storage and feed out conditions (4) . In addition variation in feed composition may arise from the feed manufacturing process, such as mixing and processing, including, for example, the drying process in the production of distillers dry grain solubles (DDGS) (5)(6)(7) . Although several authors have identified such uncertainty in feed composition as a significant contributor to variation in performance (8)(9)(10)(11) , it is surprising that none has taken it into account in nutrient utilisation models.…”

Fluorescence method for the assessment of homogeneity of granular mixtures

“…Currently, feeds contain many substances such as: vitamins, minerals, amino acids added in small amounts. This favors the process of segregation and causes that the efficiency of the mixing process becomes even more important (Groesbeck et al, 2007;Rocha, 2015).…”