Geographic Characterization of Leccinum rugosiceps by Ultraviolet and Infrared Spectral Fusion
Geographic Characterization of Leccinum rugosiceps by Ultraviolet and Infrared Spectral Fusion
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通过紫外和红外光谱融合对 Leccinum rugosiceps 进行地理表征
DOI：
10.1080/00032719.2017.1279172
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发表时间：
2017-09
影响因子：
2
通讯作者：
Wang Yuanzhong
中科院分区：
文献类型：
--
作者：
Yao Sen;Li Tao;Liu Honggao;Li Jieqing;Wang Yuanzhong
摘要皱皮地衣（Leccinumrugosiceps）是牛肝菌科（Boletaceae）地衣属（Leccinumgenus）的一种食用菌。它的子实体比许多蔬菜和水果营养丰富。建立了L. rugosiceps从地区的基础上快速和低成本的紫外和红外光谱。中层数据融合采用支持向量机。与单一光谱技术相比，中级数据融合通过基于偏最小二乘判别分析从数据矩阵中选择最显着的方差来提供更高的准确性。在校准集和测试集的样品的分类的准确性分别为85.00%和94.74%，高于单独测量的紫外或红外光谱。该方法可用于L.皱纹头。
ABSTRACT 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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DOI：
10.1109/icicisys.2010.5658435
发表时间：
2010-12
期刊：
2010 IEEE International Conference on Intelligent Computing and Intelligent Systems
影响因子：
--
作者：
Jing Cui;Ning Ye;Qiaolin Ye;Jie Hu
通讯作者：
Jing Cui;Ning Ye;Qiaolin Ye;Jie Hu
影响因子：
8.8
作者：
Nunes, Karen M.;Andrade, Marcus Vinicius O.;Sena, Marcelo M.
通讯作者：
Sena, Marcelo M.
影响因子：
2.5
作者：
G. Zervakis;G. Bekiaris;P. Tarantilis;C. Pappas
通讯作者：
G. Zervakis;G. Bekiaris;P. Tarantilis;C. Pappas
影响因子：
--
作者：
Xudong Sun;Hailiang Zhang;Zhiyuan Gong;Aiguo Ouyang;Jianmin Zhou;Yande Liu
通讯作者：
Xudong Sun;Hailiang Zhang;Zhiyuan Gong;Aiguo Ouyang;Jianmin Zhou;Yande Liu
影响因子：
8.8
作者：
Borras, Eva;Ferre, Joan;Busto, Olga
通讯作者：
Busto, Olga