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Science, Technology, Engineering, Management and Medicine
Detection of Moldy Gastrodia Elata Based on Mid Infrared Spectroscopy
DOI: https://doi.org/10.62517/jlsa.202507401
Author(s)
Yan Cai1, Peisheng Yan2, Yuqiong Shan1, Ningyun Dan1, Kaize Shen3, Dianxu Ma1,*
Affiliation(s)
1School of physics and information engineering, Zhaotong University, Zhaotong, Yunnan, China 2School of Geographic Science and tourism, Zhaotong University, Zhaotong, Yunnan, China 3Yunnan Provincial Key Laboratory of Gastrodia and Fungi Symbiotic Biology, Zhaotong University, Zhaotong, Yunnan, China *Corresponding Author
Abstract
In order to solve the problem that Gastrodia elata is easy to mildew and produce mycotoxins during storage, and overcome the limitations of traditional detection methods, such as strong subjectivity and low efficiency, the spectral characteristics of normal and laboratory mildew samples were systematically analyzed by Fourier transform infrared spectroscopy combined with potassium bromide compression method. The results showed that although there were differences in the background spectra of Gastrodia elata in different production areas, the mildew samples showed consistent changes in the three key spectral areas of 3400 cm-1, 1630 cm-1 and 1050 cm-1, which revealed the chemical nature of microbial biomass and water increase, protein degradation and transformation, and polysaccharide system reconstruction, respectively, providing a reliable spectral basis for mildew identification. This study confirmed that mid infrared spectroscopy technology can surpass the differences of production areas, and achieve rapid and nondestructive identification of moldy Gastrodia elata by capturing common chemical changes, which provides an effective means for quality and safety control.
Keywords
Mid Infrared Spectroscopy; Gastrodia Elata; Mildew Detection; Rapid Identification; Changes in Chemical Composition; Cross Region Analysis
References
[1] Feng Xiaozhang, Chen Yuwu, Yang Junshan Research on the Chemical Components of Gastrodia elata. Chinese Journal of Chemistry, 1979, (03):175-182. [2] Zhou Jun, Yang Yanbin, Yang Chongren Chemical Research on Tianma -- Ⅰ Isolation and Identification of Chemical Components in Gastrodia elata. Chinese Journal of Chemistry, 1979, (03):183-189. [3] Liu Gang, Dong Qin, Yu Fan, etc Study on Fourier Transform Infrared Spectroscopy Identification of Tianma. Spectroscopy and Spectral Analysis, 2004, (03):308-310. [4] Cheng Zefeng, Xu Rui, Cheng Cungui The application of Fourier transform deconvolution infrared spectroscopy analysis method in the identification of traditional Chinese medicine Tianma. Spectroscopy and Spectral Analysis, 2007, (09):1719-1722. [5] Ji Xiaohui, Li Na, Wang Junru, etc Identification of Tianma and its 5 counterfeit products by infrared fingerprint spectra. Northwest Botanical Journal, 2008, (04):4831-4835. [6] Du Weifeng, Chen Lin, Cong Xiaodong, etc Research progress on chemical constituents and quality control of Gastrodia elata. traditional Chinese patent medicines and simple preparations, 2011, 33 (10): 1785-1787. [7] Hou Ying, Yuan Tianjun, Xu Juan, etc Research on Multivariate Selection of Near Infrared Spectroscopy and Two Dimensional Correlation Spectral Identification of Gastrodia elata from Different Production Areas. Chinese Journal of Traditional Chinese Medicine, 2019, 44 (04): 740-749. [8] Bai Qingxu, Hou Ying, Yang Panpan, etc Identification method of Tianma production area based on near-infrared spectroscopy technology. Western Forestry Science, 2021, 50 (03): 124-130. [9] Peng Lu, Zhong Shumei, Liao Pengcheng, etc Rapid quantitative analysis of active ingredients in Tianma based on near-infrared spectroscopy technology. Medical Review, 2022, 41 (06): 858-862. [10] Hu Shuang, Wang Hairui, Bai Xueyuan, etc Research Status and New Technology Exploration of Tianma Analysis and Identification Methods. Specialty Research, 2024, 46 (05): 157-164. [11] Pei Zhengyang, Lu Tongsuo Infrared Spectral Analysis and Feature Recognition of Tianma. Traditional Chinese Medicine Information, 2025, 42 (03): 1-5+10. [12] Zhang Cuiping, Zhang Junxing, Liu Yewei, etc Rapid identification of adulteration behavior of Tianma using MDS-SVM algorithm and Raman fluorescence spectroscopy technology. Journal of Light Scattering, 2025, 37 (01): 86-93.
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