Additional effect of coated sodium butyrate 30% in the piglets feeding during the nursery phase

Abstract

In this study, the objective was to assess the growth performance, rectal microbiological profile, serum and immunological standards, and incidence of diarrhoea in piglets in the nursery phase fed diets with and without the addition of coated sodium butyrate 30% (SB). A total of 80 crossbred piglets (40 entire males and 40 females), with an average initial body weight of 9.47 ± 1.03 kg, were distributed in a randomised block design, with four treatments repeated twice in the two blocks and five piglets of the same gender per experimental unit. The treatments comprised a combination of two feeds, formulated based on corn and soybean meal with and without 0.1% SB inclusion as an additional product, and both genders, fed from of the pre-starter I diet. SB did not affect (p > 0.05) the growth performance and rectal microbiological profile of the piglets, but efficiently (p = 0.05) controlled the incidence of diarrhoea. The average values of the characteristics measured in the blood of the piglets were within the normal physiological parameters of the species. The inclusion of SB in commercial feed did not alter the growth performance and rectal microbiological profile of nursery piglets under low sanitary challenge conditions. However, the organic acid efficiently reduced gastrointestinal disorders that cause diarrhoea, with diarrhoea incidence rates of 2.68 and 4.46% for piglets fed with and without the inclusion of the additional organic acid, respectively.

Statistical assessment of feeding corn with higher oil content to piglets in the starter phase

“…Model 4 was nearly the equivalent of Model 3 by this criterion for the analysis of gain and was preferred for the analyses of FCR and FBW. Other assessments of growth performance by pigs included covariates in the statistical models that were used to analyse the data (Oliveira et al, 2018;Genova et al, 2019;Oliveira et al, 2019). Additionally, the use covariates in statistical models to control the experimental error could minimize the number of experimental units required for robust experimentation (Jacobs et al, 2013).…”