Prediction of digestible and metabolizable energy of corn distillers dried grains with solubles for growing pigs using in vitro digestible nutrients. (20th March 2018)

• Record Type: Journal Article
• Authors: Huang, Z; Urriola, P E; Shurson, G C
• Is Part Of: Journal of animal science. Volume 96:Number 5(2018)
• Page Start: 1818
• Page End: 1824
• Publication Date: 2018-03-20
• Subjects: corn distillers dried grains with solubles -- digestible energy -- in vitro nutrient digestibility -- in vivo nutrient digestibility -- metabolizable energy -- prediction equations; Livestock -- Periodicals; Livestock; Electronic journals; Periodicals; 636.005
• DOI: 10.1093/jas/sky102
• Languages: English
• ISSNs: 0021-8812

Abstract

Abstract: The objective of this study was to develop prediction equations (EQS ) that estimate DE and ME content of corn distillers dried grains with solubles (DDGS ) using digestible (DIG ) nutrients from in vitro or in vivo assays. Chemical composition data from 12 sources of corn DDGS were obtained using laboratory chemical analysis (LCA ) and near infrared spectroscopy (NIRS ). In vitro DM disappearance (IVDMD ) from gastric and small intestine hydrolysis (IVDMD h ), large intestine fermentation (IVDMD f ), and total tract digestion (IVDMD t ) were also determined along with in vivo apparent total tract digestibility (ATTD ) of DM, CP, ether extract (EE ), NDF, and ADF, and energy values (GE, DE, and ME). Correlation analysis was used to compare chemical composition from LCA with NIRS, and a stepwise selection of variables was performed using linear regression to establish DE and ME prediction EQS. Composition determined by NIRS did not correlate with values from LCA. Consequently, significance and R 2 were poorer when using NIRS data as inputs to predict DE ( P = 0.11; R 2 = 0.23) and ME ( P = 0.11; R 2 = 0.24). However, when using LCA data, DE ( P = 0.04; R 2 = 0.35) and ME ( P = 0.04; R 2 = 0.52) estimates of corn DDGS obtained from prediction EQS had significant P values, but low R 2 . Better prediction of DE ( P < 0.01; R 2 = 0.83) and ME ( P < 0.01; R 2 = 0.76) was observed when using in vivo DIG nutrients as inputs (DM basis) for DE, kcal/kg = 854.5 + (3.6 × DIG DM, g/kg) + (3.7 × DIG EE, g/kg) + (2.0 × DIG NDF, g/kg) and ME, kcal/kg = 704.5 + (3.3 × DIG DM, g/kg) + (4.8 × DIG EE, g/kg) + (2.6 × DIG NDF, g/kg). In vitro DIG DM, but not in vitro DIG NDF, was selected for use in EQS (7) DE, kcal/kg = 6, 383.6 − (42.5 × in vitro DIG DM, g/kg) + (35.4 × DIG EE, g/kg) and (8) ME, kcal/kg = 6, 635.1 − (49.8 × in vitro DIG DM, g/kg) + (41.3 × DIG EE, g/kg), but the significance and accuracy for both DE ( P = 0.07; R 2 = 0.45) and ME ( P = 0.05; R 2 = 0.49) predictions was less using in vitro DIG nutrient values than using in vivo DIG nutrient values. If chemical composition was used to replace in vivo EE, along with in vitro DIG NDF and DM, the prediction EQS only used the concentration of ADF and EE as predictors instead of in vitro DIG NDF and DM. In conclusion, in vivo DIG NDF, DM, and EE are the best predictors for DE and ME content of corn DDGS for swine. Using NIRS to determine chemical composition, in vitro DIG NDF, and in vitro DIG DM did not result in accurate predictions of DE and ME.