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傅里叶变换衰减全反射红外光谱法(FTIR-ATR)结合偏最小二乘法(PLS)和支持向量机(SVM)化学计量学方法测定生乳中非脂固形物(SNF)。

FTIR-ATR determination of solid non fat (SNF) in raw milk using PLS and SVM chemometric methods.

机构信息

Laboratory of Applied Spectrochemistry and Environmental, Faculty of Sciences and Techniques of Beni Mellal, University Moulay Soulymane, Morocco.

出版信息

Food Chem. 2014 Mar 1;146:250-4. doi: 10.1016/j.foodchem.2013.09.044. Epub 2013 Sep 18.

Abstract

Fourier transform infrared spectroscopy (FTIR) attenuated total reflectance (ATR) spectroscopy, coupled with chemometrics methods have been applied to the fast and non-destructive quantitative determination of solid non fat (SNF) content in raw milk. Partial least squares regression (PLS) and support vector machine (SVM) regression methods were used to model and predict SNF contents in raw milk based on FTIR spectral transmission measurements. Both methods, PLS and SVM, showed good performances in SNF prediction with relative prediction errors in the external validation of between 0.2% and 0.3% depending on the spectral range and regression method. Coefficient of determination of the global fit was always above 0.99. Since, the relative prediction errors were low, it can be concluded that FTIR-ATR with chemometrics can be used for accurate quantitative determinations of SNF contents in raw milk within the investigated calibration range of 79-100g/L. The proposed procedure is fast, non-destructive, simple and easy to implement.

摘要

傅里叶变换红外光谱(FTIR)衰减全反射(ATR)光谱结合化学计量学方法已被应用于快速无损定量测定生乳中的固体非脂(SNF)含量。偏最小二乘回归(PLS)和支持向量机(SVM)回归方法被用于基于 FTIR 光谱透射测量值建立和预测生乳中的 SNF 含量模型。两种方法(PLS 和 SVM)在 SNF 预测方面都表现出良好的性能,外部验证的相对预测误差在 0.2%到 0.3%之间,具体取决于光谱范围和回归方法。全局拟合的决定系数始终高于 0.99。由于相对预测误差较低,可以得出结论,FTIR-ATR 结合化学计量学可用于在 79-100g/L 的研究校准范围内准确定量测定生乳中的 SNF 含量。该方法快速、无损、简单且易于实施。

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