title: Geographical traceability of wild Boletus edulis based on data fusion of FT-MIR and ICP-AES coupled with data mining methods (SVM).
abstract: In this work, the data fusion strategy of Fourier transform mid infrared (FT-MIR) spectroscopy and inductively coupled plasma-atomic emission spectrometry (ICP-AES) was used in combination with Support Vector Machine (SVM) to determine the geographic origin of Boletus edulis collected from nine regions of Yunnan Province in China. Firstly, competitive adaptive reweighted sampling (CARS) was used for selecting an optimal combination of key wavenumbers of second derivative FT-MIR spectra, and thirteen elements were sorted with variable importance in projection (VIP) scores. Secondly, thirteen subsets of multi-elements with the best VIP score were generated and each subset was used to fuse with FT-MIR. Finally, the classification models were established by SVM, and the combination of parameter C and γ (gamma) of SVM models was calculated by the approaches of grid search (GS) and genetic algorithm (GA). The results showed that both GS-SVM and GA-SVM models achieved good performances based on the #9 subset and the prediction accuracy in calibration and validation sets of the two models were 81.40% and 90.91%, correspondingly. In conclusion, it indicated that the data fusion strategy of FT-MIR and ICP-AES coupled with the algorithm of SVM can be used as a reliable tool for accurate identification of B. edulis, and it can provide a useful way of thinking for the quality control of edible mushrooms.
authors.affiliation: Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming 650200, PR China; Yunnan Technical Center for Quality of Chinese Materia Medica, Kunming 650200, PR China; College of Traditional Chinese Medicine, Yunnan University of Traditional Chinese Medicine, Kunming 650500, PR China.
authors.forename: Yun
authors.initials: Y
authors.lastname: Li
authors.affiliation: Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming 650200, PR China; Yunnan Technical Center for Quality of Chinese Materia Medica, Kunming 650200, PR China.
authors.forename: Ji
authors.initials: J
authors.lastname: Zhang
authors.affiliation: College of Resources and Environment, Yuxi Normal University, Yuxi 653100, PR China.
authors.forename: Tao
authors.initials: T
authors.lastname: Li
authors.affiliation: College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming 650201, PR China.
authors.forename: Honggao
authors.initials: H
authors.lastname: Liu
authors.affiliation: College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming 650201, PR China. Electronic address: lijieqing2008@126.com.
authors.forename: Jieqing
authors.initials: J
authors.lastname: Li
authors.affiliation: Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming 650200, PR China; Yunnan Technical Center for Quality of Chinese Materia Medica, Kunming 650200, PR China. Electronic address: boletus@126.com.
authors.forename: Yuanzhong
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000363:Agaricales / Q000502:physiology*; D002138:Calibration; D002681:China; D057225:Data Mining; D005843:Geography; D015203:Reproducibility of Results; D013054:Spectrophotometry, Atomic; D017550:Spectroscopy, Fourier Transform Infrared; D013059:Spectrum Analysis, Raman; D060388:Support Vector Machine
keywords: Boletus edulis; Data fusion; Fourier transform mid infrared (FT-MIR) spectroscopy; Geographical traceability; Inductively coupled plasma-atomic emission spectrometry (ICP-AES); Quality control; Support vector machine (SVM)