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Application of Near Infrared Spectroscopy Combined with Partial Least Squares in Quantitative Analysis of Polysaccharide in Irpex Lacteus Fr. Mycelia

机译:近红外光谱法与偏最小二乘相结合在乳酸菌的定量分析中的应用。菌丝体

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Near infrared spectroscopy (NIRS) combined with partial least squares (PLS) was applied to establish model for quantitative analysis of the Polysaccharide in Irpex lacteus Fr. mycelia. Savitzky-Golay smoothing, First derivative, second derivative, fast Fourier transform (FFT) and standard normal variate (SNV) transformation methods were applied to preprocess NIRS. The efficacious spectral regions and the modelsȁ9; parameters were chosen by leave-one-out cross-validation method. The root mean square error of cross-validation (RMSECV) of the optimum PLS models was 4.962. Using this model for predicting the polysaccharide contents in prediction set, the root mean square error of prediction set (RMSEP) was 0.450. The coefficient correlation of actual values and predictive values obtained by cross-validation (Rv) was 0.872. It was feasible to apply NIR combined with PLS to non-destructive quantitative analysis of the Polysaccharide in Irpex lacteus Fr. Mycelia.
机译:应用近红外光谱(NIRS)和偏最小二乘(PLS)结合,建立了对Irpex lacteus Fr中多糖进行定量分析的模型。菌丝体。将Savitzky-Golay平滑,一阶导数,二阶导数,快速傅里叶变换(FFT)和标准正态变量(SNV)变换方法应用于NIRS预处理。有效光谱区和模型ȁ9;通过留一法交叉验证方法选择参数。最佳PLS模型的交叉验证均方根误差(RMSECV)为4.962。使用该模型预测预测集中的多糖含量,预测集的均方根误差(RMSEP)为0.450。通过交叉验证(Rv)获得的实际值和预测值的系数相关性是0.872。将NIR与PLS结合用于乳酸艾氏菌(Erpex lacteus Fr)中多糖的无损定量分析是可行的。菌丝体。

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