Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS
Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS
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DOI：
10.1016/j.saa.2015.04.024
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发表时间：
2015-10-05
影响因子：
4.4
通讯作者：
Liu, Guohai
中科院分区：
文献类型：
--
作者：
Jiang, Hui;Zhang, Hang;Liu, Guohai
采用傅立叶变换近红外光谱技术，研究了偏最小二乘判别分析（PLS-DA）前波长变量选择在固态发酵程度定性鉴别中的应用。采用竞争性自适应加权采样（汽车）和稳定性竞争性自适应加权采样（SCARS）两种波长变量选择方法选择重要波长。利用汽车和SCARS方法选择波长变量，应用PLS-DA方法对固态发酵度的辨识模型进行校正。实验结果表明，汽车和SCARS从1557个原始波长变量中分别选择了58个和47个波长变量。与全谱PLS-DA的结果相比，两种波长变量选择方法均能提高模型的辨识性能。同时，与CARS-PLS-DA模型相比，SCARS-PLS-DA模型在验证过程中取得了更好的识别效果，识别率达到91.43%.结果表明，采用适当的波长变量法，选取合适的波长变量，构建的PLS-DA模型能够更准确地识别固态发酵程度。(C)2015爱思唯尔B. V.保留所有权利。
The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree. (C) 2015 Elsevier B.V. All rights reserved.