Angelika Grümpel-Schlüter, Andreas Berk, Martin Schäffler, Hubert Spiekers, Sven Dänicke
{"title":"猪复合饲料代谢能浓度预测方程的评价。","authors":"Angelika Grümpel-Schlüter, Andreas Berk, Martin Schäffler, Hubert Spiekers, Sven Dänicke","doi":"10.1080/1745039X.2021.1947066","DOIUrl":null,"url":null,"abstract":"<p><p>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 (ME<sub>S</sub>) and the newly derived (ME<sub>Snew</sub>) equations as well as the energy content calculated on the basis of digestible nutrients (ME<sub>D</sub>). ME<sub>D</sub> was correlated with ME<sub>S</sub> (<i>r</i><sub>s</sub> = 0.784; <i>p</i> < 0.001) and ME<sub>Snew</sub> (<i>r</i><sub>s</sub> = 0.802; <i>p</i> < 0.001). The root mean square error or the adjusted <i>r<sup>2</sup></i>was 0.332 MJ/kg DM or 0.830 for the regression of ME<sub>S</sub> on ME<sub>D</sub>, and 0.323 MJ/kg DM or 0.839 for the regression of ME<sub>Snew</sub> on ME<sub>D</sub>. 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 ME<sub>S</sub> or ME<sub>Snew</sub> on ME<sub>D</sub> 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 ME<sub>D</sub> and both, ME<sub>Snew</sub> and ME<sub>S</sub>, 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.</p>","PeriodicalId":8157,"journal":{"name":"Archives of Animal Nutrition","volume":"75 4","pages":"251-262"},"PeriodicalIF":2.0000,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/1745039X.2021.1947066","citationCount":"0","resultStr":"{\"title\":\"Evaluation of an equation for predicting metabolisable energy concentration in compound feeds for pigs.\",\"authors\":\"Angelika Grümpel-Schlüter, Andreas Berk, Martin Schäffler, Hubert Spiekers, Sven Dänicke\",\"doi\":\"10.1080/1745039X.2021.1947066\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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 (ME<sub>S</sub>) and the newly derived (ME<sub>Snew</sub>) equations as well as the energy content calculated on the basis of digestible nutrients (ME<sub>D</sub>). ME<sub>D</sub> was correlated with ME<sub>S</sub> (<i>r</i><sub>s</sub> = 0.784; <i>p</i> < 0.001) and ME<sub>Snew</sub> (<i>r</i><sub>s</sub> = 0.802; <i>p</i> < 0.001). The root mean square error or the adjusted <i>r<sup>2</sup></i>was 0.332 MJ/kg DM or 0.830 for the regression of ME<sub>S</sub> on ME<sub>D</sub>, and 0.323 MJ/kg DM or 0.839 for the regression of ME<sub>Snew</sub> on ME<sub>D</sub>. 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 ME<sub>S</sub> or ME<sub>Snew</sub> on ME<sub>D</sub> 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 ME<sub>D</sub> and both, ME<sub>Snew</sub> and ME<sub>S</sub>, 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.</p>\",\"PeriodicalId\":8157,\"journal\":{\"name\":\"Archives of Animal Nutrition\",\"volume\":\"75 4\",\"pages\":\"251-262\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2021-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/1745039X.2021.1947066\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Archives of Animal Nutrition\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1080/1745039X.2021.1947066\",\"RegionNum\":3,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/7/27 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURE, DAIRY & ANIMAL SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of Animal Nutrition","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1080/1745039X.2021.1947066","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/7/27 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"AGRICULTURE, DAIRY & ANIMAL SCIENCE","Score":null,"Total":0}
Evaluation of an equation for predicting metabolisable energy concentration in compound feeds for pigs.
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 (rs = 0.784; p < 0.001) and MESnew (rs = 0.802; p < 0.001). The root mean square error or the adjusted r2was 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.
期刊介绍:
Archives of Animal Nutrition is an international journal covering the biochemical and physiological basis of animal nutrition. Emphasis is laid on original papers on protein and amino acid metabolism, energy transformation, mineral metabolism, vitamin metabolism, nutritional effects on intestinal and body functions in combination with performance criteria, respectively. It furthermore deals with recent developments in practical animal feeding, feedstuff theory, mode of action of feed additives, feedstuff preservation and feedstuff processing. The spectrum covers all relevant animal species including food producing and companion animals, but not aquatic species.
Seldom can priority be given to papers covering more descriptive studies, even if they may be interesting and technically sound or of impact for animal production, or for topics of relevance for only particular regional conditions.