FT-MIR and NIR spectral data fusion: a synergetic strategy for the geographical traceability of Panax notoginseng
文献类型： 外文期刊
作者： Li, Yun 1 ; Zhang, Jin-Yu 1 ; Wang, Yuan-Zhong 1 ;
作者机构： 1.Yunnan Acad Agr Sci, Inst Med Plants, Kunming 650200, Yunnan, Peoples R China
关键词： Panax notoginseng;Geographical traceability;Data fusion;Fourier transform mid-infrared spectroscopy;Near-infrared spectroscopy
期刊名称：ANALYTICAL AND BIOANALYTICAL CHEMISTRY （ 影响因子：4.142； 五年影响因子：3.863 ）
ISSN： 1618-2642
年卷期： 2018 年 410 卷 1 期
页码：
收录情况： SCI
摘要： Three data fusion strategies (low-llevel, mid-llevel, and high-llevel) combined with a multivariate classification algorithm (random forest, RF) were applied to authenticate the geographical origins of Panax notoginseng collected from five regions of Yunnan province in China. In low-level fusion, the original data from two spectra (Fourier transform mid-IR spectrum and near-IR spectrum) were directly concatenated into a new matrix, which then was applied for the classification. Mid-level fusion was the strategy that inputted variables extracted from the spectral data into an RF classification model. The extracted variables were processed by iterate variable selection of the RF model and principal component analysis. The use of high-level fusion combined the decision making of each spectroscopic technique and resulted in an ensemble decision. The results showed that the mid-level and high-level data fusion take advantage of the information synergy from two spectroscopic techniques and had better classification performance than that of independent decision making. High-level data fusion is the most effective strategy since the classification results are better than those of the other fusion strategies: accuracy rates ranged between 93% and 96% for the low-level data fusion, between 95% and 98% for the mid-level data fusion, and between 98% and 100% for the high-level data fusion. In conclusion, the high-level data fusion strategy for Fourier transform mid-IR and near-IR spectra can be used as a reliable tool for correct geographical identification of P. notoginseng.
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