ATR-FTIR combined with chemometrics to distinguish geographical indications from non-geographical indications Gastrodia elata Bl
文献类型: 外文期刊
第一作者: He, Qiong
作者: He, Qiong;Huang, Hengyu;Huang, Hengyu;Wang, Yuanzhong
作者机构:
关键词: Attenuated fourier transform infrared spectrum; Chemometrics; Gastrodia elata Bl; Geographical indications and non-geographical indications
期刊名称:ARABIAN JOURNAL OF CHEMISTRY ( 影响因子:5.2; 五年影响因子:5.6 )
ISSN: 1878-5352
年卷期: 2025 年 18 卷 4 期
页码:
收录情况: SCI
摘要: Gastrodia elata Bl (G. elata), a medicinal and edible homologous variety, has been artificially cultivated in different regions of China to meet the growing demands of human beings. In this study, attenuated total reflection/Fourier transform infrared spectroscopy (ATR/FTIR) combined with chemometrics [Principal component analysis (PCA), Partial least squares discrimination (PLS-DA), Support vector machines (SVM), and Data-driven soft independent modeling of class analogy (DD-SIMCA)] was used to differentiate between geographical indications and non-geographical indications of G. elata. PLS-DA, after the application of SNV+SD spectral preprocessing, achieved 100% accuracy on the training set and 88.89% on the test set, respectively. Under SG+SD conditions, SVM outperformed PLS-DA with 100% training set accuracy and 94.74% for the test set. A ResNet model that used synchronous 2DCOS data successfully distinguished G. elata from Yunnan and Guizhou, achieving 100% accuracy across training, test, and external validation sets. These findings support that ATR-FTIR and chemometrics can be utilized to effectively identify the geographical origin of G. elata, with potential applications for other medicinal and edible plants.
分类号:
- 相关文献
作者其他论文 更多>>
-
Rapid determination of geographical authenticity of Gastrodia elata f. glauca using Fourier transform infrared spectroscopy and deep learning
作者:Deng, Guangmei;Li, Jieqing;Deng, Guangmei;Wang, Yuanzhong;Liu, Honggao
关键词:Gastrodia elata f. glauca; Fourier transform infrared spectroscopy; Deep learning; Data driven version of soft independent; modeling of class analogy
-
Rapid prediction of nucleosides content and origin traceability of Boletus bainiugan using Fourier transform near-infrared spectroscopy combined with chemometrics
作者:Deng, Guangmei;Li, Jieqing;Deng, Guangmei;Wang, Yuanzhong;Liu, Honggao
关键词:Fourier transform near-infrared spectroscopy; Nucleoside compounds; Climatic factors; Two-dimensional correlation spectroscopy; Residual neural networks
-
Predicting the suitable habitat distribution of Polygonatum kingianum under current and future climate scenarios in southwestern Yunnan, China
作者:Hu, Xiaoyan;Yang, Shaobing;Li, Zhimin;Wang, Yuanzhong;Hu, Xiaoyan
关键词:Polygonatum kingianum; Maximum entropy model; Species distribution; Suitable habitat; Geographical traceability
-
Geographical origin identification of Dendrobium Officinale based on FT-NIR and ATR-FTIR spectroscopy
作者:Han, Jiaqi;Hu, Qiang;Wang, Yuanzhong
关键词:Spectral analysis; Data fusion; Two-dimensional correlation spectroscopy; The residual convolutional neural network; Dendrobium officinale Kimura & Migo
-
Classification of bolete species and drying temperature using LC-MS and infrared spectroscopy and simultaneous prediction of their major compounds using chemometrics
作者:Zheng, Chuanmao;Li, Jieqing;Zheng, Chuanmao;Wang, Yuanzhong;Liu, Honggao
关键词:Boletes; Organic acids; Postharvest drying; Species identification; Quality assessment
-
Infrared spectroscopy combined with machine learning: A fast method for origin tracing and dry matter content prediction of Dendrobium officinale Kimura et Migo
作者:Feng, Yangna;Feng, Yangna;Yang, Shaobing;Wang, Yuanzhong
关键词:FT-NIR; ATR-FTIR; Dendrobium officinal; Prediction; Origin tracing
-
Prediction of pyrazines and identification of flavor intensity in boletus bainiugan at different drying temperatures based on feature variables
作者:Deng, Guangmei;Li, Jieqing;Deng, Guangmei;Wang, Yuanzhong;Liu, Honggao
关键词:Boletus bainiugan; Fourier transform near infrared spectroscopy; Attenuated total reflectance Fourier transform; infrared spectroscopy; Data fusion; Volatile compounds