Identification of geographical origin and different parts of <i>Wolfiporia cocos</i> from Yunnan in China using PLS‐DA and ResNet based on FT‐NIR

Li, Lian; Zuo, Zhiyan; Wang, Yuanzhong

doi:10.1002/pca.3130

Cited by 5 publications

(4 citation statements)

References 30 publications

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“…Therefore, it can be concluded that the chemical composition of the tested samples remains unchanged and undamaged. With the availability of software integrating databases, pattern recognition, and calibration models, the quality control of medicinal herbs can be rapidly completed [35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

The Dynamic Accumulation Rules of Chemical Components during the Medicine Formation Period of Angelica sinensis and Chemometric Classifying Analysis for Different Bolting Times Using ATR-FTIR

Ma,

Jiang,

et al. 2023

Molecules

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The dried roots of the perennial herb Angelica sinensis (Oliv.) Diels (AS) are commonly used as medicinal and edible resources. In commercial planting, early bolting and flowering (EB) of ca. 60% in the medicine formation period reduces root yield and quality, becoming a significant bottleneck in agricultural production. In the cultivation process, summer bolting (SB) occurs from June to July, and autumn bolting (AB) occurs in September. The AB root is often mistaken for the AS root due to its similar morphological characteristics. Few studies have involved whether the root of AB could be used as herbal medicine. This study explored and compared the accumulation dynamics of primary and secondary metabolites in AS and EB roots during the vegetative growth stage (from May to September) by light microscopy, ultraviolet spectrometry, and HPLC methods. Under a microscope, the amount of free starch granules and oil chamber in the AS root increased. On the contrary, they decreased further from EB-Jul to EB-Sep. By comparison, the wall of the xylem vessel was slightly thickened and stacked, and the cell walls of parenchyma and root cortex tissue were thickened in the EB root. Early underground bolting reduces soluble sugar, soluble protein, free amino acids, total C element, total N element, ferulic acid, and ligustilide accumulation, accompanied by the lignification of the root during the vegetative growth stage. Furthermore, a total of 55 root samples from different bolting types of AS root (29 samples), SB root (14 samples), and AB root (12 samples) were collected from Gansu Province during the harvesting period (October). The later the bolting occurred, the less difference there was between unbolted and bolted roots in terms of morphological appearance and efficacy components. Fourier transform infrared spectroscopy with the attenuated total reflection mode (ATR-FTIR) provides a “holistic” spectroscopic fingerprinting of all compositions in the tested sample. The ATR-FTIR spectrum of the AB root was similar to that of the AS root. However, the number and location of absorption peaks in the spectra of SB were different, and only one strong absorption peak at 1021 cm−1 was regarded as the characteristic peak of C-O stretching vibration in lignin. The ATR-FTIR spectra can be effectively differentiated based on their various characteristics using orthogonal partial least squares discrimination analysis (OPLS-DA). Results were assessed using multiple statistical techniques, including Spearman’s correlation, principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and OPLS-DA. Among these methods, the ATR-FTIR data demonstrated the most effective outcomes in differentiating between viable and non-viable roots for their application in herbal medicine. Essential substances are ferulic acid and flavonoid, which are much more abundant in the AB root. It provides a material basis for the pharmacological action of the AB roots and a theoretical basis for improving their availability.

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Section: Introductionmentioning

confidence: 99%

The Dynamic Accumulation Rules of Chemical Components during the Medicine Formation Period of Angelica sinensis and Chemometric Classifying Analysis for Different Bolting Times Using ATR-FTIR

Ma,

Jiang,

et al. 2023

Molecules

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“…To improve the efficiency of analysis and keep up with the development of the times, the currently hotly discussed artificial intelligence technology should be considered for quality evaluation of TMC. Machine learning is a common research hotspot in the field of artificial intelligence and pattern recognition, which is widely used in different fields of food technology (Sarkar et al, 2022a,b), medicinal plants, and fungi (Li et al, 2022). Common algorithms include deep learning, support vector machines, partial least squares discriminant analysis (PLS-DA), etc.…”

Section: Introductionmentioning

confidence: 99%

Practical Qualitative Evaluation and Screening of Potential Biomarkers for Different Parts of Wolfiporia cocos Using Machine Learning and Network Pharmacology

Zuo

Wang

2022

Front. Microbiol.

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Wolfiporia cocos is a widely used traditional Chinese medicine and dietary supplement. Artificial intelligence algorithms use different types of data based on the different strategies to complete multiple tasks such as search and discrimination, which has become a trend to be suitable for solving massive data analysis problems faced in network pharmacology research. In this study, we attempted to screen the potential biomarkers in different parts of W. cocos from the perspective of measurability and effectiveness based on fingerprint, machine learning, and network pharmacology. Based on the conclusions drawn from the results, we noted the following: (1) exploratory analysis results showed that differences between different parts were greater than those between different regions, and the partial least squares discriminant analysis and residual network models were excellent to identify Poria and Poriae cutis based on Fourier transform near-infrared spectroscopy spectra; (2) from the perspective of effectiveness, the results of network pharmacology showed that 11 components such as dehydropachymic acid and 16α-hydroxydehydrotrametenolic acid, and so on had high connectivity in the “component-target-pathway” network and were the main active components. (3) From a measurability perspective, through orthogonal partial least squares discriminant analysis and the variable importance projection > 1, it was confirmed that three components, namely, dehydrotrametenolic acid, poricoic acid A, and pachymic acid, were the main potential biomarkers based on high-performance liquid chromatography. (4) The content of the three components in Poria was significantly higher than that in Poriae cutis. (5) The integrated analysis showed that dehydrotrametenolic acid, poricoic acid A, and pachymic acid were the potential biomarkers for Poria and Poriae cutis. Overall, this approach provided a novel strategy to explore potential biomarkers with an explanation for the clinical application and reasonable development and utilization in Poria and Poriae cutis.

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“…In addition, ResNet combined with 2DCOS images has achieved remarkable results in the classification of Eucommia ulmoides (Li et al, 2022a), bolete mushrooms (Dong et al, 2021a) and other species. It has been reported that different parts of W. cocos could be authenticated successfully by 2DCOS combined with Resnet, but this study did not explore the effects of wild and cultivated on the quality of W. cocos (Li et al, 2022b). Using ResNet combined with 2DCOS to comprehensively evaluate the quality of wild and cultivated W. cocos in different parts is one of the focuses of this study.…”

Section: Introductionmentioning

confidence: 99%

“…Near-infrared (NIR) spectroscopy pertains to a common vibrational spectroscopy technology. Fourier transform near-infrared (FT-NIR) spectroscopy has an edge in terms of non-destructive and high sensitivity, and has been widely applied to the research of quality control ( Li et al., 2022b ). Its detection range is 12500-4000 cm -1 , and this region can present the information of O-H, N-H and C-H bonds vibration, chemical structure, and intermolecular or intramolecular interactions ( Bec et al., 2021 ).…”

Section: Introductionmentioning

confidence: 99%

ResNet and MaxEnt modeling for quality assessment of Wolfiporia cocos based on FT-NIR fingerprints

et al. 2022

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As a fungus with both medicinal and edible value, Wolfiporia cocos (F. A. Wolf) Ryvarden & Gilb. has drawn more public attention. Chemical components’ content fluctuates in wild and cultivated W. cocos, whereas the accumulation ability of chemical components in different parts is different. In order to perform a quality assessment of W. cocos, we proposed a comprehensive method which was mainly realized by Fourier transform near-infrared (FT-NIR) spectroscopy and ultra-fast liquid chromatography (UFLC). A qualitative analysis means was built a residual convolutional neural network (ResNet) to recognize synchronous two-dimensional correlation spectroscopy (2DCOS) images. It can rapidly identify samples from wild and cultivated W. cocos in different parts. As a quantitative analysis method, UFLC was used to determine the contents of three triterpene acids in 547 samples. The results showed that a simultaneous qualitative and quantitative strategy could accurately evaluate the quality of W. cocos. The accuracy of ResNet models combined synchronous FT-NIR 2DCOS in identifying wild and cultivated W. cocos in different parts was as high as 100%. The contents of three triterpene acids in Poriae Cutis were higher than that in Poria, and the one with wild Poriae Cutis was the highest. In addition, the suitable habitat plays a crucial role in the quality of W. cocos. The maximum entropy (MaxEnt) model is a common method to predict the suitable habitat area for W. cocos under the current climate. Through the results, we found that suitable habitats were mostly situated in Yunnan Province of China, which accounted for approximately 49% of the total suitable habitat area of China. The research results not only pave the way for the rational planting in Yunnan Province of China and resource utilization of W. cocos, but also provide a basis for quality assessment of medicinal fungi.

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Identification of geographical origin and different parts of Wolfiporia cocos from Yunnan in China using PLS‐DA and ResNet based on FT‐NIR

Cited by 5 publications

References 30 publications

The Dynamic Accumulation Rules of Chemical Components during the Medicine Formation Period of Angelica sinensis and Chemometric Classifying Analysis for Different Bolting Times Using ATR-FTIR

The Dynamic Accumulation Rules of Chemical Components during the Medicine Formation Period of Angelica sinensis and Chemometric Classifying Analysis for Different Bolting Times Using ATR-FTIR

Practical Qualitative Evaluation and Screening of Potential Biomarkers for Different Parts of Wolfiporia cocos Using Machine Learning and Network Pharmacology

ResNet and MaxEnt modeling for quality assessment of Wolfiporia cocos based on FT-NIR fingerprints

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