不同饲料原料日粮纤维水平的近红外测定方法
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“十二五”国家科技支撑计划项目(2014BAD08B06)


Measurement of Fiber Content in Different Feed Ingredients Using Near-infrared Spectroscopy Method
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    摘要:

    分别针对中性洗涤纤维(NDF)和酸性洗涤纤维(ADF)2个日粮纤维水平评价指标,开展适用于不同饲料原料的NDF和ADF近红外综合预测方法研究。收集包括玉米干酒糟及其可溶物、大豆皮、小麦麸、苜蓿草颗粒、喷浆玉米皮和甜菜粕共6种饲料原料,共计327个样品。按照Van Soest滤袋法测定每个样品的NDF和ADF,获取参考值,并进行统计学分析。利用傅里叶变换近红外光谱仪采集样品的近红外漫反射光谱。选择偏最小二乘法,结合导数处理、多元散射校正和变量标准化等不同的光谱预处理方法,构建定标模型。结果表明:6种饲料原料的NDF和ADF分布范围分别在21.20%~65.28%和6.40%~48.31%,洗涤纤维含量覆盖范围广。NDF近红外快速预测模型:最优预处理方法为二阶导数,模型验证集决定系数为0.963,预测标准误差为1.82,相对分析误差为5.2。ADF近红外快速预测模型:最优预处理方法为一阶导数结合变量标准化,验证集决定系数为0.985,预测标准误差为1. 63,相对分析误差为8.23。本研究表明基于近红外光谱这种无损分析技术,可构建适用于多种纤维类饲料原料的日粮纤维水平快速预测模型,该方法可为饲料工厂快速检测洗涤纤维、精细调控饲料中纤维水平提供有效的技术保障。

    Abstract:

    Feed ingredients with high-fiber are widely available and a price competitive source of energy and nutrients for nonruminants. Rapid analysis of detergent fiber content in highfiber feed ingredients, including neutral detergent fiber (NDF) and acid detergent fiber (ADF), contributes to a fine regulation of dietary fiber levels in feed, and the exercise of its nutritional value. Classical Van Soest method for detergent fiber determination is tedious and sensitive to particle size and high cost in the consumption of filter-bag. It is not suitable for feed plant regular detection. The nearinfrared spectroscopy (NIRS) technique is nondestructive, non-pollutive, fast and relatively inexpensive. NIRS methods have been widely adapted in conventional composition analysis of feed. Feed ingredients with highfiber normally derives from a wealth of sources, like byproducts of grain plant. Single species NIRS model is hardly satisfied the demand of various ingredients in one feed plant. Researchers devoted to developing a unified NIRS model to determination of NDF and ANF for different feed ingredients with highfiber. A NIRS model for NDF and a NIRS model for ADF were built for analyzing six kinds of feed ingredients, including maize DDGS, soybean hull, wheat bran, alfalfa pellet, shotcrete corn bran, and beet pulp particles. Totally 327 samples were collected from China, including 75 maize DDGS, 48 soybean hull, 48 wheat bran, 48 alfalfa pellet, 59 shotcrete corn bran, and 49 beet pulp particles. NDF and ADF were obtained by using Van Soest methods. Fouriertransform nearinfrared spectrometer collected nearinfrared diffuse reflectance spectroscopy with spectral range of 4000~10000cm-1, at the resolution of 16cm-1 and 64 times scanning per scan. Calibration models were constructed by using partial least squares method, combined with derivative processing, multiplicative scatter correction and so on. Results showed that NDF and ADF distribution of six kinds of feed ingredients were respectively 21.20% ~ 65.28%, 6.40%~48.31%. For NDF model: determination coefficients of calibration and verification were 0.971 and 0.963 respectively; RMSEs of calibration and verification were 1.68 and 1.82 respectively; the relative percent deviation was 5.2, and optimal pretreatment method was the second derivative. For ADF model: determination coefficients of calibration and verification were 0.990 and 0.985 respectively; RMSEs of calibration and verification were 1.32 and 1.63 respectively; the relative percent deviation was 8.2 and the optimal pretreatment method was the first derivative with multiplicative scatter correction. These models are appropriate to a variety of high-fiber feed ingredients for the determination of NDF and ADF in feed plant.

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姜训鹏,雷恒,李海涛,焦鹏,张宏宇,王博.不同饲料原料日粮纤维水平的近红外测定方法[J].农业机械学报,2016,47(s1):353-358. Jiang Xunpeng, Lei Heng, Li Haitao, Jiao Peng, Zhang Hongyu, Wang Bo. Measurement of Fiber Content in Different Feed Ingredients Using Near-infrared Spectroscopy Method[J]. Transactions of the Chinese Society for Agricultural Machinery,2016,47(s1):353-358.

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  • 收稿日期:2016-07-20
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  • 在线发布日期: 2016-10-15
  • 出版日期: 2016-10-15
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