Evaluation of an equation for predicting metabolisable energy concentration in compound feeds for pigs. Issue 4 (4th July 2021)

• Record Type: Journal Article
• Authors: Grümpel-Schlüter, Angelika; Berk, Andreas; Schäffler, Martin; Spiekers, Hubert; Dänicke, Sven
• Is Part Of: Archives of animal nutrition. Volume 75:Issue 4(2021)
• Page Start: 251
• Page End: 262
• Publication Date: 2021-07-04
• Subjects: Metabolisable energy -- compound feeds -- pigs -- estimation equation -- energy concentration -- feed controlling; Animal nutrition -- Periodicals; Animal Nutrition -- Periodicals; Animal Feed -- Periodicals; 636.085205
• DOI: 10.1080/1745039X.2021.1947066
• Languages: English
• ISSNs: 1745-039X

Abstract

ABSTRACT: It is useful to predict metabolisable energy (ME) concentration based on crude nutrients which can be determined on a laboratory scale to formulate compound feeds for pigs based on ME concentration and to control the declared concentration. In 2008 such an equation was derived premised on 290 balance experiments showing strong associations between ME predicted by digestible crude nutrients and by crude nutrients themselves. Since the suitability of a regression-based prediction equation might be strongly influenced by the number of observations, the current study aimed at 1) checking the suitability of the existing prediction equation by including more datasets and 2) deriving a revised prediction equation. The equations were evaluated by correlation and regression analyses using the energy content calculated on the basis of crude nutrients according to the previously used (MES ) and the newly derived (MESnew ) equations as well as the energy content calculated on the basis of digestible nutrients (MED ). MED was correlated with MES ( r s = 0.784; p < 0.001) and MESnew ( r s = 0.802; p < 0.001). The root mean square error or the adjusted r 2 was 0.332 MJ/kg DM or 0.830 for the regression of MES on MED, and 0.323 MJ/kg DM or 0.839 for the regression of MESnew on MED . Although the regressive evaluation for the prediction of ME revealed satisfying results, the remaining residual variation not explainable by the regression model should be considered. The minimum span of the prediction interval of the regression of MES or MESnew on MED covered a range of 0.65 and 0.64 MJ/kg DM, suggesting the variability of ME estimations to be expected when based on crude nutrients. The quality parameters for the newly derived equation were minimally better and the correlation coefficient between MED and both, MESnew and MES, was strong. Since there is also a non-negligible inaccuracy in the estimation of ME content using the newly derived equation and as the quality parameters were only slightly better, there is at this point no need to introduce the new equation. In future studies, alternative analytical methods for determining the concentration of ME in compound feeds should be considered to improve the accuracy of estimation equations.