动物营养学报 >

2014 , Vol. 26 >Issue 6: 1556 - 1562

DOI: https://doi.org/10.3969/j.issn.1006-267x.2014.06.016

实验方法 Experimental Methods

玉米干酒糟及其可溶物家禽表观代谢能预测模型

  • 李婷婷 ,
  • 蔡辉益 ,
  • 闫海洁 ,
  • 张姝 ,
  • 刘国华 ,
  • 杨禄良 ,
  • 王晓睿
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  • 1. 中国农业科学院饲料研究所, 北京 100081;
    2. 生物饲料开发国家工程研究中心, 北京 100081

收稿日期: 2013-12-05

  网络出版日期: 2014-05-30

基金资助

公益性（农业）科研项目“饲料营养价值与畜禽饲养标准研究与应用”（200903006-03）

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Prediction Model for Apparent Metabolizable Energy of Corn Distillers Dried Grains with Solubles in Poultry

  • LI Tingting ,
  • CAI Huiyi ,
  • YAN Haijie ,
  • ZHANG Shu ,
  • LIU Guohua ,
  • YANG Luliang ,
  • WANG Xiaorui
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  • 1. Feed Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China;
    2. National Engineering Research Center of Biological Feed, Beijing 100081, China

Received date: 2013-12-05

  Online published: 2014-05-30

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摘要

本文旨在对玉米干酒糟及其可溶物（DDGS）进行概略养分分析，建立利用理化指标快速预测玉米DDGS家禽表观代谢能（AME）的最优模型。采集我国有代表性的30种玉米DDGS样品，测定粗蛋白质（CP）、粗脂肪（EE）、粗纤维（CF）、粗灰分、中性洗涤纤维（NDF）、酸性洗涤纤维（ADF）、亮度（L*）、红度（a*）、黄度（b*）、总能（GE）。采用完全随机试验设计，选用体重为（2.5±0.2）kg的18周龄以上的海兰褐壳蛋种公鸡72只，随机分为6组，各组随机接受1种玉米DDGS，每组6个重复，每个重复2只鸡，进行5期代谢试验，测定玉米DDGS的AME。将测得的理化指标值与AME利用SAS 8.0软件进行表型相关分析、通径分析及逐步回归分析，最后获得玉米DDGS的AME最优回归模型。结果表明：1）本试验30种玉米DDGS各概略养分含量均存在一定程度的差异，主要指标含量的平均值分别为CP 27.86％、EE 8.49％、CF 8.52％、NDF 47.76％、ADF 15.55％、GE 19.47 MJ/kg、AME 8.62 MJ/kg，各指标变异系数分别为8.49%、36.77%、18.07%、22.85%、17.04%、4.31%、12.87%。2）利用色差计测得玉米DDGS的L*、a*、b*平均值分别为36.62、7.59、18.52，变异系数分别为8.81%、15.88%、16.34%。本研究得到玉米DDGS的AME最优回归模型为：AME=-3.950（±2.041）-0.533（±0.055 3）CF+0.245（±0.033 3）EE+0.771（±0.115）GE（R2=0.902，P<0.000 1）。

关键词： 玉米DDGS; 家禽; 概略养分; 预测模型; AME

本文引用格式

李婷婷 , 蔡辉益 , 闫海洁 , 张姝 , 刘国华 , 杨禄良 , 王晓睿 . 玉米干酒糟及其可溶物家禽表观代谢能预测模型[J]. 动物营养学报, 2014 , 26(6) : 1556 -1562 . DOI: 10.3969/j.issn.1006-267x.2014.06.016

Abstract

This study was designed to establish the optimal model for predicting poultry apparent metabolizable energy (AME) of corn distillers dried grains with solubles (DDGS) from proximate composition. A total of 30 corn DDGS were sampled from all representative manufacturers in China. All samples were analyzed for crude protein (CP), ether extract (EE), crude fiber (CF), ash, neutral detergent fiber (NDF), acid detergent fiber (ADF), lightness (L*), redness (a*), yellowness (b*) and gross energy (GE). A total of 72 Hy-Line brown roosters with body weight of (2.5±0.2) kg and at more than 18 weeks of age were randomly divided into 6 groups with 6 replicates per group and 2 roosters per replicate in a completely random experiment design, and each group randomly received one of corn DDGS samples for one time to detect the AME of corn DDGS in 5 periods of metabolism trial. The optimal regression model was established by phenotype correlation, path analysis and stepwise regression analysis between physical and chemical indicators and AME. The results showed as follows: 1) all proximate composition content had different levels of variations. Means for each nutrient were CP 27.86%, EE 8.49%, CF 8.52%, NDF 47.76%, ADF 15.55%, GE 19.47 MJ/kg and AME 8.62 MJ/kg, respectively, and the coefficients of variation were 8.49%, 36.77%, 18.07%, 22.85%, 17.04%, 4.31% and 12.87%, respectively. 2) The means of L*, a* and b* of corn DDGS samples were 36.62, 7.59 and 18.52, respectively, and the coefficients of variation were 8.81%, 15.88% and 16.34%, respectively. The optimal regression model for AME of corn DDGS is AME=-3.950(±2.041)-0.533(±0.055 3)CF+0.245(±0.033 3)EE+0.771(±0.115)GE (R2=0.902,P<0.000 1).

Key words： corn DDGS; poultry; proximate composition; prediction model; AME

参考文献

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