偏最小二乘回归
傅里叶变换红外光谱
波数
数学
绿茶
分析化学(期刊)
傅里叶变换
红外线的
线性判别分析
支持向量机
化学
材料科学
统计
物理
人工智能
色谱法
计算机科学
光学
数学分析
食品科学
作者
Xiaoli Li,Kaiwen Xu,Yuying Zhang,Chanjun Sun,Yong He
出处
期刊:PLOS ONE
[Public Library of Science]
日期:2017-01-09
卷期号:12 (1): e0169430-e0169430
被引量:22
标识
DOI:10.1371/journal.pone.0169430
摘要
The potential of Fourier transform infrared (FT-IR) transmission spectroscopy for determination of lead chrome green in green tea was investigated based on chemometric methods. Firstly, the qualitative analysis of lead chrome green in tea was performed based on partial least squares discriminant analysis (PLS-DA), and the correct rate of classification was 100%. And then, a hybrid method of interval partial least squares (iPLS) regression and successive projections algorithm (SPA) was proposed to select characteristic wavenumbers for the quantitative analysis of lead chrome green in green tea, and 19 wavenumbers were obtained finally. Among these wavenumbers, 1384 (C = C), 1456, 1438, 1419(C = N), and 1506 (CNH) cm-1 were the characteristic wavenumbers of lead chrome green. Then, these 19 wavenumbers were used to build determination models. The best model was achieved by least squares support vector machine (LS-SVM)algorithm with high coefficient of determination and low root-mean square error of prediction set (R2p = 0.864 and RMSEP = 0.291). All these results indicated the feasibility of IR spectra for detecting lead chrome green in green tea.
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