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中国精品科技期刊2020
王旭峰, 马冰峰, 石磊, 邓丹雯, 耿响. 利用近红外光纤分析技术检测饲料中粗纤维含量[J]. 食品工业科技, 2013, (02): 75-77. DOI: 10.13386/j.issn1002-0306.2013.02.004
引用本文: 王旭峰, 马冰峰, 石磊, 邓丹雯, 耿响. 利用近红外光纤分析技术检测饲料中粗纤维含量[J]. 食品工业科技, 2013, (02): 75-77. DOI: 10.13386/j.issn1002-0306.2013.02.004
Detection of crude fiber in forage with the Near Infrared Spectroscopy (NIRS) analysis technology[J]. Science and Technology of Food Industry, 2013, (02): 75-77. DOI: 10.13386/j.issn1002-0306.2013.02.004
Citation: Detection of crude fiber in forage with the Near Infrared Spectroscopy (NIRS) analysis technology[J]. Science and Technology of Food Industry, 2013, (02): 75-77. DOI: 10.13386/j.issn1002-0306.2013.02.004

利用近红外光纤分析技术检测饲料中粗纤维含量

Detection of crude fiber in forage with the Near Infrared Spectroscopy (NIRS) analysis technology

  • 摘要: 利用近红外光纤分析技术检测饲料中粗纤维的含量,采用偏最小二乘回归(PLS)方法,分别对光谱进行附加散射校正、变量标准化、一阶导数和平滑处理,建立了饲料中粗纤维含量的预测模型。其中附加散射校正、一阶导数和9点平滑处理定标效果最优。定标集化学分析值与预测值之间的决定系数(Rc2)和标准分析误差(SEC)分别为0.9698和0.1131%,相对分析误差为6.01;验证集化学分析值与预测值之间的决定系数(Rv2)和标准分析误差(SEP)分别为0.9402和0.1536%,相对分析误差为4.04。结果表明,利用近红外光纤分析技术可以比较准确地定量检测饲料中粗纤维的含量。 

     

    Abstract: A prediction model was built using the technology of Near Infrared Spectroscopy (NIRS) with fiber optic probe and method of partial least squares regression (PLS ) . Multiplicative Signal Correction (MSC ) , Standard Normal Variate, First Derivative and Smoothing were used to pretreat the spectra. The best effect, with a correlation coefficient of 0.9698 were achieved by the petreatments of MSC full, First Derivative BCAP and smooth average 9 points, a standard analytical error of calibration (SEC) of 0.1131% and a RPD of 6.01 for the calibration sample set and a correlation coefficient of 0.9402, a standard analytical error of prediction (SEP) of 0.1536% and a RPD of 4.04 for the validation sample set. The result showed that the technology of Near Infrared Spectroscopy (NIRS) with fiber optic probe could be used to protect crud fiber content in forage.

     

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