A meta-analysis to predict the concentration of standardized ileal digestible amino acids in distillers dried grains with solubles for poultry. (1st August 2018)

• Record Type: Journal Article
• Authors: Zhu, J L; Zeng, Z K; Shurson, G C; Urriola, P E
• Is Part Of: Poultry science. Volume 97:Number 12(2018:Dec.)
• Page Start: 4359
• Page End: 4366
• Publication Date: 2018-08-01
• Subjects: amino acid -- distillers dried grains with solubles -- meta-analysis -- prediction equation -- standardized ileal digestibility; Poultry -- Periodicals; Poultry -- Periodicals; Poultry Diseases -- Periodicals; Electronic journals; 636.5005
• DOI: 10.3382/ps/pey340
• Languages: English
• ISSNs: 0032-5791

Abstract

ABSTRACT: High variability in amino acid (AA) content and digestibility among sources of distillers dried grains with solubles (DDGS) create challenges for nutritionists when using it in precision nutrition feeding programs. The objective of this meta-analysis was to develop prediction equations for standardized ileal digestible content (SIDC) of AA in DDGS for poultry. A meta-analysis based on 86 observations from 19 publications was conducted to develop equations for predicting SIDC of AA based on chemical composition in DDGS. A mixed model was used to develop prediction equations for SIDC of AA, and a backward selection of variables was conducted based on chemical composition of DDGS. Each total AA content was the best predictor of SIDC for all indispensable AA. The prediction equations for SIDC of Met and Lys were y = –0.12 + 1.05 × Met (R 2 = 0.899) and y = –0.22 + 0.91 × Lys (R 2 = 0.870), respectively. The prediction equations for SIDC of Met and Lys using data from broiler chick assays were y = –0.16 + 1.12 × Met (R 2 = 0.809) and y = –0.24 + 0.90 × Lys (R 2 = 0.731), respectively, and equations derived from rooster assay data for Met and Lys were y = –0.05 + 0.97 × Met (R 2 = 0.996) and y = –0.20 + 0.97 × Lys (R 2 = 0.982), respectively. For all the prediction equations, the intercept (=0) and slope (=1) were not different ( P > 0.10) between predicted and observed SID AA values, indicating high accuracy of the models. In conclusion, equations for predicting SIDC of AA in DDGS were developed and showed that total concentration of each AA was the best predictor of SDIC. These prediction equations can be used by animal nutritionists to more accurately estimate SIDC of AA among DDGS sources in diet formulations for precision poultry nutrition feeding programs.