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Discrimination of Boletus Tomentipes from Different Regions Based on Infrared Spectrum Combined with Principal Component Analysis and Cluster Analysis

文献类型： 外文期刊

作者： Yang Tian-wei 1 ; Zhang Ji 2 ; Li Tao 3 ; Wang Yuan-zhong 2 ; Liu Hong-gao 1 ;

作者机构： 1.Yunnan Agr Univ, Coll Agron & Biotechnol, Kunming 650201, Peoples R China

2.Yunnan Acad Agr Sci, Inst Med Plants, Kunming 650200, Peoples R China

3.Yuxi Normal Univ, Coll Resources & Environm, Yuxi 653100, Peoples R China

关键词： Infrared spectroscopy;Principal component loadings analysis;Boletus tomentipes;Discrimination

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 影响因子：0.589； 五年影响因子：0.504 ）

ISSN： 1000-0593

年卷期： 2016 年 36 卷 6 期

页码：

收录情况： SCI

摘要： With the aim of establishing a rapid method to discriminate Boletus tomentipes samples from different regions, FTIR spectroscopy with the aid of principal component analysis and clustering analysis were used in the present study. The information of infrared spectra of B. tomentipes samples originated from 15 regions has been collected. The original infrared spectra was pre-treated by multiplicative signal correction (MSC) in combination with second derivative and Norris smooth. The spectral data were analyzed by principal component analysis and cluster analysis after the optimal pretreatment of MSCH-SDH-ND (15, 5), and the reasons for the differences of B. tomentipes samples from different regions could be explained through the principal component loading plot. The results showed that, the RSDs of repeatability, accuracy and stability of the method were 0. 17%, 0. 08% and 0. 27%, respectively, which indicated the method was stable and reliable. The cumulative contribution of first three principal components of PCA was 87. 24% which could reflect the most information of the samples. Principal component scores scatter plot displaying the samples from same origin could clustered together and samples from different areas distributed in a relatively independent space. Which can distinguish samples collected from different origins, effectively. The loading plot of principal component showed that with the principal component contribution rate decreasing, the captured sample information of principal component was also reducing. In the wave number of 3 571, 2 958, 1 625, 1 456, 1 405, 1 340, 1 191, 1 143, 1 084, 935, 840, 727 cm(-1), the first principal component captured a large amount of sample information which attributed to carbohydrates, proteins, amino acids, fat, fiber and other chemical substances. Which showed that the different contents of these chemical substances may be the basis of discrimination of B. tomentipes samples from different origins. Cluster analysis based on ward method and Euclidean distance has shown the classification and correlation among samples. Samples originated from 15 regions could be clustered correctly in accordance with the basic origins and the correct rate was 93. 33%. Which can be used to identify and analyze B. tomentipes collected from different sites. Fourier transform infrared spectroscopy combined with principal component analysis and cluster analysis can be effectively used to discriminate origins of B. tomentipes mushrooms and the reasons for the differences of B. tomentipes samples from different regions could be explained. This method could provide a reliable basis for discrimination and application of wild edible mushrooms.

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