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Data fusion of FT-NIR and ATR-FTIR spectra for accurate authentication of geographical indications for Gastrodia elata Blume

文献类型： 外文期刊

作者： Zheng, Chuanmao 1 ; Li, Jieqing 1 ; Liu, Honggao 3 ; Wang, Yuanzhong 2 ;

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

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

3.Zhaotong Univ, Yunnan Key Lab Gastrodia & Fungi Symbiot Biol, Zhaotong 657000, Yunnan, Peoples R China

关键词： Gastrodia elata Blume; Chemometrics; Authentication; Geographical indication; 2DCOS; PLS-DA

期刊名称：FOOD BIOSCIENCE （ 影响因子：5.2； 五年影响因子：5.4 ）

ISSN： 2212-4292

年卷期： 2023 年 56 卷

页码：

收录情况： SCI

摘要： Gastrodia elata Blume (G. elata Bl.), with its excellent nutritional and medicinal value from Zhaotong, has been protected by geographical indication (GI). Accurate certification of its origin is a prerequisite to safeguard consumer interests and maintain the market. Four different regions and three varieties of G. elata Bl. from Zhaotong were used in this study (n = 262). Tri-step infrared spectroscopy was used for ATR-FTIR spectral analysis to filter out fingerprint regions for data fusion with FT-NIR spectra, after which conventional discrim-inant models (PLS-DA and GS-SVM) were built. The second derivative (SD), multiple scattering correction (MSC), and Savitzky-Golay (SG) preprocessing were also performed on the spectra, and it was found that the pre-processing improved the performance of the PLS-DA model. The optimal model results in GS-SVM, based on mid-level data fusion of principal components (PCs) and latent variables (LVs), with sensitivity, specificity, accuracy, and Matthews correlation coefficient (MCC) of 1 for the test set. Furthermore, the residual convolutional neural network (ResNet) models were built, based on FT-NIR full spectra, band 3600-2700 cm-1 (MFA) and band 1750-500 cm-1 (MFB). Their accuracy in both train and test sets exceeds 97%, and the loss function curve is close to 0, which indicates that these three bands can be used as a fingerprint area to verify the GI of Zhaotong G. elata Bl. This study provides a fast, non-invasive method for the authentication of food or medicinal plant GI.

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