猪复合饲料代谢能浓度预测方程的评价。

IF 2 3区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE
Archives of Animal Nutrition Pub Date : 2021-08-01 Epub Date: 2021-07-27 DOI:10.1080/1745039X.2021.1947066
Angelika Grümpel-Schlüter, Andreas Berk, Martin Schäffler, Hubert Spiekers, Sven Dänicke
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引用次数: 0

摘要

以粗营养物质为基础预测代谢能(ME)浓度,可以在实验室规模上进行测定,从而制定基于代谢能浓度的猪配合饲料,并对申报浓度进行控制。2008年,在290个平衡实验的前提下,得出了这样一个方程,该实验表明,由可消化的粗营养物质预测的代谢能与粗营养物质本身之间存在很强的相关性。由于基于回归的预测方程的适用性可能受到观测数的强烈影响,因此本研究旨在1)通过纳入更多的数据集来检验现有预测方程的适用性;2)推导修正的预测方程。利用先前使用的(MES)和新推导的(MESnew)方程计算的粗营养成分能含量,以及可消化营养成分计算的能含量,通过相关分析和回归分析对方程进行评价。MED与MES相关(rs = 0.784;p = 0.802;MES对MED的回归p r2为0.332 MJ/kg DM或0.830,MESnew对MED的回归p r2为0.323 MJ/kg DM或0.839。虽然对ME预测的回归评价结果令人满意,但仍应考虑回归模型无法解释的剩余变异。MES和MESnew在MED上的回归预测区间的最小跨度分别为0.65和0.64 MJ/kg DM,表明基于粗营养物质的ME估计存在可变性。新方程的质量参数较好,MED与MESnew和MES之间的相关系数较强。由于使用新导出的方程估计ME含量也存在不可忽略的不准确性,并且由于质量参数只是稍微好一点,因此此时无需引入新方程。在未来的研究中,应考虑采用其他分析方法来确定配合饲料中代谢能的浓度,以提高估算方程的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

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来源期刊
Archives of Animal Nutrition
Archives of Animal Nutrition 农林科学-奶制品与动物科学
CiteScore
3.90
自引率
5.00%
发文量
31
审稿时长
>24 weeks
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.
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