Rapid discrimination of Notoginseng powder adulteration of different grades using FT-MIR spectroscopy combined with chemometrics

Yang, Xiaodong; Li, Guanglin; Song, Jie; Gao, Ming; Zhou, Shuai

doi:10.1016/j.saa.2018.07.056

Cited by 35 publications

(13 citation statements)

References 31 publications

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“…Infrared (IR) spectroscopy, as a detection technology, has some advantages such as rapid, convenience, high efficiency, nondestructive, and low cost (Pereira, Leite, Andrade, Bell, & Anjos, 2019; Sun et al., 2017; Yang, Li, Song, Gao, & Zhou, 2018). IR spectroscopy technology has been widely applied in many fields such as food inspection (Jiang & Chen, 2015; Liu et al., 2019; Sun, Ge, Wu, Dai, & Yang, 2018; Tahir et al., 2017), classification of agricultural products (Chen, Lin, & Tan, 2019; Ferreiro‐González et al., 2018; Wu, Wu, Sun, & Yang, 2017; Wu, Yang, & Wang, 2018), and pharmaceutical analysis(Mazivila, Castro, Leitão, & Esteves da Silva, 2019; Oparin & Kiselev, 2020).…”

Section: Introductionmentioning

confidence: 99%

Discrimination of tea varieties based on FTIR spectroscopy and an adaptive improved possibilistic c‐means clustering

Zhou

et al. 2020

J. Food Process. Preserv.

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Section: Introductionmentioning

confidence: 99%

Discrimination of tea varieties based on FTIR spectroscopy and an adaptive improved possibilistic c‐means clustering

Zhou

et al. 2020

J. Food Process. Preserv.

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“…The performance of SNV processing was tested on raw spectral data of M. micrantha. SNV assumes the reflection values of each wavelength in the raw spectral data to meet a certain distribution (Yang et al, 2018;Liu et al, 2019), thereby eliminating the errors caused by particle size difference between samples, spectral transformation and surface scattering (Asaari et al, 2018).…”

Section: Preprocessingmentioning

confidence: 99%

“…Their model achieved 98.57% accuracy in prediction set. Yang et al (2018) explored the effects of different pretreatment methods on the FT-MIR spectra detection of Panax notoginseng, where the best preprocessing combination for the collected spectra was a mix of baseline correction, SNV and FD with an 11 point smoothing. The above preprocessing methods were optimized based on the full-band raw spectral data set and retained all the information of the raw spectral data.…”

Section: Introductionmentioning

confidence: 99%

Hyperspectral Imaging for Identification of an Invasive Plant Mikania micrantha Kunth

Huang

Yang

et al. 2021

Front. Plant Sci.

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Mile-a-minute weed (Mikania micrantha Kunth) is considered as one of top 100 most dangerous invasive species in the world. A fast and accurate detection technology will be needed to identify M. micrantha. It will help to mitigate the extensive ecologic and economic damage on our ecosystems caused by this alien plant. Hyperspectral technology fulfills the above requirement. However, when working with hyperspectral images, preprocessing, dimension reduction, and classifier are fundamental to achieving reliable recognition accuracy and efficiency. The spectral data of M. micrantha were collected using hyperspectral imaging in the spectral range of 450–998 nm. A different combination of preprocessing methods, principal component analysis (for dimension reduction), and three classifiers were used to analyze the collected hyperspectral images. The results showed that a combination of Savitzky-Golay (SG) smoothing, principal component analysis (PCA), and random forest (RF) achieved an accuracy (A) of 88.71%, an average accuracy (AA) of 88.68%, and a Kappa of 0.7740 with an execution time of 9.647 ms. In contrast, the combination of SG, PCA and a support vector machine (SVM) resulted in a weaker performance in terms of A (84.68%), AA(84.66%), and Kappa (0.6934), but with less execution time (1.318 ms). According to the requirements for specific identification accuracy and time cost, SG-PCA-RF and SG-PCA-SVM might represent two promising methods for recognizing M. micrantha in the wild.

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“…Two supervised pattern recognitions equipped with thin liquid chromatography (TLC) technique effectively distinguish between the authentic saffron and common counterfeit in the international market. In addition, the PLS‐DA combined with modern techniques also have been published in other authenticity discrimination study including Notoginseng Radix et Rhizoma adulterated with low‐quality materials, 82 Rhei Radix et Rhizoma with its counterfeit materials, 83 Gastrodiae Rhizoma with its confused materials, 40 and so on. What is more, there are other supervised pattern recognition such as SVM, 84,85 ANN, 84,86 LDA, 81,82,87,88 SIMCA, 79,87,89 and KNN 84,86 for prediction of the adulteration.…”

Section: Applications Of Chemometrics In Tcmmentioning

confidence: 99%

Pattern recognition: An effective tool for quality assessment of herbal medicine based on chemical information

Wang

Zuo

Wang

2020

Journal of Chemometrics

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Herbal medicine has obtained great attention for its effective efficacy using its crude materials and patent medicines. It is believed that the efficacy is a synergetic action by several chemical components. To present a detailed overview of the usage of multivariate statistical techniques developed for analytical chemistry in quality assessment and origins traceability, we provided an extensive pragmatic and practical overview of these techniques for the quality control of these crude medicines. Two pattern recognition methods, unsupervised and supervised approaches, were interpreted using practical instances. Overall, the review briefly summarized common applications for location, species, harvesting time, processed production, manufacture, botanical part, and authenticity. Besides, we focused on data pretreatment and fusion strategies listing recently published literature to provide a detailed reference to choose the most appropriate statistical method and fusion strategies. Actual applications have proved chemometrics as an effective and rapid tool for the quality control of herbal medicine.

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Rapid discrimination of Notoginseng powder adulteration of different grades using FT-MIR spectroscopy combined with chemometrics

Cited by 35 publications

References 31 publications

Discrimination of tea varieties based on FTIR spectroscopy and an adaptive improved possibilistic c‐means clustering

Discrimination of tea varieties based on FTIR spectroscopy and an adaptive improved possibilistic c‐means clustering

Hyperspectral Imaging for Identification of an Invasive Plant Mikania micrantha Kunth

Pattern recognition: An effective tool for quality assessment of herbal medicine based on chemical information

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