Geographic Characterization of Leccinum rugosiceps by Ultraviolet and Infrared Spectral Fusion
文献类型： 外文期刊
作者： Yao, Sen 1 ; Li, Tao 3 ; Liu, Hong-Gao 1 ; Li, Jie-Qing 1 ; Wang, Yuan-Zhong 2 ;
作者机构： 1.Yunnan Agr Univ, Coll Agron & Biotechnol, Kunming, Yunnan, Peoples R China
2.Yunnan Acad Agr Sci, Inst Med Plants, Kunming 650200, Yunnan, Peoples R China
3.Yuxi Normal Univ, Coll Resources & Environm, Yuxi, Peoples R China
4.Yunnan Tech Ctr Qual Chinese Mat Medica, Kunming, Yunnan, Peoples R China
关键词： Data fusion;infrared spectroscopy;Leccinum rugosiceps;support vector machine;ultraviolet spectroscopy
期刊名称：ANALYTICAL LETTERS （ 影响因子：2.329； 五年影响因子：1.738 ）
ISSN： 0003-2719
年卷期： 2017 年 50 卷 14 期
页码：
收录情况： SCI
摘要： Leccinum rugosiceps is an edible mushroom belonging to genus Leccinum of Boletaceae. Its fruiting bodies are richer in nutrients than many vegetables and fruit. The model of support vector machine was established for the discrimination of L. rugosiceps from regions based on rapid and low-cost ultraviolet and infrared spectroscopies. The mid-level data fusion was performed by support vector machine. Compared to a single spectroscopic technique, mid-level data fusion provided higher accuracy by selecting the most significant variance from data matrixes based on partial least squares discriminant analysis. The accuracy of the classification of samples in the calibration and test sets were 85.00 and 94.74%, higher than separate measurements by ultraviolet or infrared spectroscopy. This approach has applications for authentication and quality assessment of L. rugosiceps.
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