A fast and effective way for authentication of Dendrobium species: 2DCOS combined with ResNet based on feature bands extracted by spectrum standard deviation.

Dendrobium Sw., as a traditional herb and function food with over 1500 years of history, shows a significant effect in improving immunity and fatigue resistance. However, due of course the large number of species and the quality fluctuating in different species, a fast and effective discrimination method is in need. Recently, spectroscopic techniques combined with chemometrics have become an effective method for low-cost and fast analysis in food and herb. Nevertheless, chemometrics method which based on one-dimensional spectral dataset still encounter the difficulty that can not effectively extract useful information from the spectra. Different from one-dimensional spectra, the two-dimensional correlation spectroscopy (2DCOS) can reveal more detail information of the spectral dataset. Moreover, the appearance of convolutional neural network makes the application of deep learning in image recognition faster and more accurate. In this study, a novel method 2DCOS combined with residual convolutional neural network (ResNet) was used to discriminate the 20 species of Dendrobium. Five feature bands were selected based on spectrum standard deviation (SDD) method in NIR and MIR spectra. Moreover, the models based on full band, total five feature bands, and their fusion-bands had been compared. The results showed that two feature bands 1800-450 cm-1 and 2400-1900 cm-1 displayed 100% accuracy in both training set and test set. And also, the accurate discrimination of 10% external validation showed that these models have good generalization ability. In conclusion, 2DCOS combined with ResNet could be an effective and accurate method for classify different Dendrobium species.

The traditional uses, phytochemistry, and pharmacological properties of Paris L. (Liliaceae): A review.

ETHNOPHARMACOLOGICAL RELEVANCE: Paris L. (Liliaceae) consisted of 33 species, of which the study focused on Paris polyphylla Smith, P. polyphylla var. chinensis (Franch.) Hara, and P. polyphylla Smith var. yunnanensis (Franch.) Hand. -Mazz. Due of course to the good effects of analgesia and hemostasis, it was traditionally used to treat trauma by folk herbalists. AIM OF THIS REVIEW: This study summarized the traditional uses, distributions, phytochemical components, pharmacological properties, and toxicity evaluation of the genus Paris, and reviewed the economic value of cultivate P. polyphylla. This aim was that of providing a new and comprehensive recognition of these medicinal plants for the further utilization of Paris plants. MATERIALS AND METHODS: The literature about traditional and folk uses of genus Paris was obtained from Duxiu Search, and China National Knowledge Infrastructure (CNKI). The other literature about genus Paris was searched online on Web of Science, PubMed, Google Scholar, Baidu Scholar, Scifinder database, and Springer research. The Scientific Database of China Plant Species (DCP) (http://db.kib.ac.cn/Default.aspx) databases were used to check the scientific names and provide species, varieties, and distribution of genus Paris. The botany studies information of genus Paris was available online from Plant Plus of China (www.iplant.cn). All the molecular structures of chemical compounds displayed in the text were produced by ChemBioDraw Ultra 14.0. RESULTS: The plants of genus Paris, containing about 33 species and 15 varieties, are mainly distributed in Southwest China (Yunnan, Sichuan, and Guizhou provinces). More than 320 chemical components have been isolated from genus Paris since 2020, including steroidal saponins, C-21 steroids, phytosterols, insect hormones, pentacyclic triterpenes, flavonoids, and other compounds. Arrays of pharmacological investigations revealed that compounds and extracts of Paris species possess a wide spectrum of pharmacological effects, such as antitumor, cytotoxic, antimicrobial, antifungal, hemostatic, and anti-inflammatory activities. The studies about toxicity evaluation suggested that Rhizome Paridis had slight liver toxicity. CONCLUSIONS: The dried rhizomes of P. polyphylla, P. polyphylla var. chinensis, and P. polyphylla var. yunnanensis were used to treat wound, bleeding, and stomachache, etc. in folk medicine. Phytochemistry researches showed that different species had pretty similarities especially in terms of chemical constituents. Pharmacological studies witnessed that Rhizome Paridis has various activities. Among these activities, steroidal saponins were the main active ingredients. Furthermore, an important aspect responsible for increasing interest in genus Paris is the use of antifertility-nonhormonal contraceptives by women. Also, the development of TCM (Traditional Chinese medicine) planting industry can improve the income of ethnic minorities and promote economic development.

Data Fusion of Fourier Transform Mid-Infrared (MIR) and Near-Infrared (NIR) Spectroscopies to Identify Geographical Origin of Wild Paris polyphylla var. yunnanensis.

Origin traceability is important for controlling the effect of Chinese medicinal materials and Chinese patent medicines. Paris polyphylla var. yunnanensis is widely distributed and well-known all over the world. In our study, two spectroscopic techniques (Fourier transform mid-infrared (FT-MIR) and near-infrared (NIR)) were applied for the geographical origin traceability of 196 wild P. yunnanensis samples combined with low-, mid-, and high-level data fusion strategies. Partial least squares discriminant analysis (PLS-DA) and random forest (RF) were used to establish classification models. Feature variables extraction (principal component analysis-PCA) and important variables selection models (recursive feature elimination and Boruta) were applied for geographical origin traceability, while the classification ability of models with the former model is better than with the latter. FT-MIR spectra are considered to contribute more than NIR spectra. Besides, the result of high-level data fusion based on principal components (PCs) feature variables extraction is satisfactory with an accuracy of 100%. Hence, data fusion of FT-MIR and NIR signals can effectively identify the geographical origin of wild P. yunnanensis.

Traceability the provenience of cultivated Paris polyphylla Smith var. yunnanensis using ATR-FTIR spectroscopy combined with chemometrics.

The conventional procedures, based on attenuated total reflectance-Fourier transform infrared spectrometry (ATR-FTIR), have been developed for the origins traceability of cultivated Paris polyphylla Smith var. yunnanensis (PPY) samples with the help of partial least square discriminant analysis (PLS-DA) and random forest. In this study, a set of 219 batch cultivated PPY samples, containing the cultivation years of 5, 6 and 7, and covering the municipal districts of Chuxiong, Dali, Honghe, Lijiang and Yuxi in Yunnan Province, China, were used to build the discrimination models. Firstly, a visualized analysis was carried out by t-distributed stochastic neighbor embedding (t-SNE) to reduce each data point in a two-dimensional map and make a knowledge of the sample distribution tendency. Secondly, the single spectra data sets of Paridis rhizome and leaf tissues, and the combination of these two data sets with variable selection (mid-level data fusion strategy), were used to establish PLS-DA and random forest models, and parallelly compared the model performance. Results demonstrated that the discrimination ability of PLS-DA preceded the random forest model, and the classification performance was remarkably improved after mid-level data fusion. These results verified each other by 5-, 6- and 7-year old Paridis samples and indicated that the model performance established in the present study was reliable. Besides, five agronomic characters, including the plant height, dry weight of rhizome and leaf tissues, and the allocation of rhizome and leaf were determined and analyzed, results of which indicated that the dry weight and their allocation was significantly different among various origins and fluctuated with the cultivation years. This study was using a comprehensive and green analytical method to discriminate the cultivated Paridis according to their provenances, which was simultaneously benefited for the appropriate cultivation areas selection based on the dry weight of rhizome tissues.

Comparison and Identification for Rhizomes and Leaves of Paris yunnanensis Based on Fourier Transform Mid-Infrared Spectroscopy Combined with Chemometrics.

Paris polyphylla, as a traditional herb with long history, has been widely used to treat diseases in multiple nationalities of China. Nevertheless, the quality of P. yunnanensis fluctuates among from different geographical origins, so that a fast and accurate classification method was necessary for establishment. In our study, the geographical origin identification of 462 P. yunnanensis rhizome and leaf samples from Kunming, Yuxi, Chuxiong, Dali, Lijiang, and Honghe were analyzed by Fourier transform mid infrared (FT-MIR) spectra, combined with partial least squares discriminant analysis (PLS-DA), random forest (RF), and hierarchical cluster analysis (HCA) methods. The obvious cluster tendency of rhizomes and leaves FT-MIR spectra was displayed by principal component analysis (PCA). The distribution of the variable importance for the projection (VIP) was more uniform than the important variables obtained by RF, while PLS-DA models obtained higher classification abilities. Hence, a PLS-DA model was more suitably used to classify the different geographical origins of P. yunnanensis than the RF model. Additionally, the clustering results of different geographical origins obtained by HCA dendrograms also proved the chemical information difference between rhizomes and leaves. The identification performances of PLS-DA and the RF models of leaves FT-MIR matrixes were better than those of rhizomes datasets. In addition, the model classification abilities of combination datasets were higher than the individual matrixes of rhizomes and leaves spectra. Our study provides a reference to the rational utilization of resources, as well as a fast and accurate identification research for P. yunnanensis samples.

Traceability of wild Paris polyphylla Smith var. yunnanensis based on data fusion strategy of FT-MIR and UV-Vis combined with SVM and random forest.

Paris polyphylla Smith var. yunnanensis (Franch.) Hand.-Mazz (PPY) was a frequently used herbal medicine in pharmaceutical field and different provenances might affect the clinical efficacy. Tracing the geographical origin was an important portion for PPY authentication and quality assessment. Present study was compared low-, mid- and high-level data fusion methodology for geographical traceability of PPY samples (161 batches) combined with multivariate classification methods such as support vector machine gird search (SVM-GS) and random forest (RF) on the basis of Fourier transform mid-infrared (FT-MIR) and ultraviolet-visible (UV-Vis) spectra. Compared with the low- and mid-level data fusion strategy results basing on SVM-GS algorithm, result of high-level data fusion method (calculated by RF) was more satisfying. Result of RF basing on high-level data fusion strategy showed that merely two samples were misclassified and one sample was multiple assigned after voting with fuzzy set theory. Values of specificity, sensitivity, and accuracy rates were exceeded 0.91, 0.99 and 90.91%, for each class respectively, satisfying results of these were shown in training and test sets for high-level data fusion method. This feasible result indicated that the RF algorithm could establish a reliable and good performance model in geographical traceability on the basis of high-level data fusion strategy. Combination of high-level data fusion and RF algorithm could consider as a good choice for establishing a discrimination multivariate model for origins identification of PPY samples.

[Study on Different Parts of Wild and Cultivated Gentiana Rigescens with Fourier Transform Infrared Spectroscopy].

The application of traditional Chinese medicine (TCM) and their preparations have a long history. With the deepening of the research, the market demand is increasing. However, wild resources are so limited that it can not meet the needs of the market. The development of wild and cultivated samples and research on accumulation dynamics of chemical component are of great significance. In order to compare composition difference of different parts (root, stem, and leaf) of wild and cultivated G. rigescens, Fourier infrared spectroscopy (FTIR) and second derivative spectra were used to analyze and evaluate. The second derivative spectra of 60 samples and the rate of affinity (the match values) were measured automatically using the appropriate software (Omnic 8.0). The results showed that the various parts of wild and cultivated G. rigescens. were high similar the peaks at 1732, 1 643, 1 613, 1 510, 1 417, 1 366, 1 322, 1 070 cm(-1) were the characteristic peak of esters, terpenoids and saccharides, respectively. Moreover, the shape and peak intensity were more distinct in the second derivative spectrum of samples. In the second derivative spectrum range of 1 800-600 cm(-1), the fingerprint characteristic peak of samples and gentiopicroside standards were 1 679, 1 613, 1 466, 1 272, 1 204, 1 103, 1 074, 985, 935 cm(-1). The characteristic peak intensity of gentiopicroside of roots of wild and cultivated samples at 1 613 cm(-1) (C-C) was higher than stems and leaves which indicated the higher content of gentiopicroside in root than in stem and leaves. Stems of wild samples at 1 521, 1 462 and 1 452 cm(-1) are the skeletal vibration peak of benzene ring of lignin, and the stem of cultivated sample have stronger peak than other samples which showed that rich lignin in stems. The iInfrared spectrum of samples were similar with the average spectral of root of wild samples, and significant difference was found for the correlation between second derivative spectrum of samples and average spectral of wild samples root, and the sequence of similarity was root > stem > leaf. Therefore, FTIR combined with second derivative spectra was an express and comprehensive approach to analyze and evaluate in the imperceptible differences among different parts of wild and cultivated of G. rigescens.

[Study on the Discrimination of Gentiana Rigescens with Different Processing Methods by Using FTIR Spectroscopy].

The Processing of traditional Chinese medicine (TCM) is the key to clinical application of TCM, and processing has functions such as enhancing the efficacy, attenuating the toxicity andmoderating medicine property. In order to the realizing safe, reasonable and effective use of medicine in clinical, research on identification of TCM processed products is of great significance. The Gentiana rigescens samples which processed with five different methods were discriminated by Fourier transform infrared spectroscopy (FTIR). Baseline correction and normalization were used to pretreat all original spectra and the noise was cut off. The spectra range was from 3 400 to 600 cm-1. The effect of multiple scattering correction and standard normal variable on the model were observed and compared. Samples were divided into calibration set and prediction set at the ratio of 3∶1. The principal component analysis (PCA) was applied to reduce data dimensionality and discriminant analysis model was established. The result indicated that the main absorption peaks of samples were 3 378, 2 922, 1 732, 1 610, 1 417, 1 366, 1 316, 1 271, 1 068, 1 048 cm- 1 which 1 738, 1 643, 1 613, 1 420, 1 051 cm-1 as to gentiopicrin; 1 068, 1 048, 935 cm-1 as to carbohydrate. The accumulation contribution rate of first three principal components is 94.05%. Most of the information reflected the original data. There were differences among different samples. The result of discriminant analysis showed that the recognition rate of G. rigescens samples could achieve to 100% based on baseline correction and normalization treatment combined with MSC with the precondition of principal component scores being 10. In conclusion, FTIR is a feasible, rapid and non-destructive method to discriminate G. rigescens samples wtih different processing methods. It also provided reference for discrimination of processed products of medicine materials.

[Application of the vanillin sulfuric acid colorimetry-ultraviolet spectrometry on quality evaluation of Panax notoginseng].

In this study, Panax notoginseng samples were extracted by chloroform, ethanol and water, or by those extracted solution with 5% vanillin sulfuric acid to establish two kinds of UV fingerprint of P. notoginseng which were compared by applying the common and variation peak ratio dual index sequence analysis method and SIMCA software qualitative analysis. The results indicated that the optimization extraction time of P. notoginseng samples was 20 min with chloroform, ethanol and water extraction, but the fingerprint differed significantly after add vanillin sulfuric acid. The common peak ratios of UV fingerprint of P. notoginseng were scattered. The minimum was 25% (Y5-Y8), while the maximum was 84.38% (Y11-Y13, Y20-Y21). The maximum variation peak ratio was 177.78% (Y8-Y5), meanwhile, the variation peak ratios of several samples were more than 100%. However, the common peak ratios of UV fingerprint of P. notoginseng with vanillin sulfuric acid were concentrated (distributed in the range of 50%-70%): the minimum was 42.86%(Y1-Y19), whereas the maximum was 79.55% (Y22-Y23); the range of the variation peak ratios was also smaller with the ranges of 20%-50% in general. The result of the dual index sequence analysis was agreement with the fingerprint implied. The similarity of the UV fingerprint of the extracts of P. notoginseng after adding vanillin sulfuric acid was greater than before. Both the ages and origin was related with the difference of UV fingerprint. The similarity of the two samples with same age was more significant than those with different ages. The similarity and difference between samples was no correlation with the distance of geographic space, the near origin samples maybe have a significant similarity or difference. This method appears as good alternative for evaluate quality of the P. notoginseng and can distinguish at least two samples quantitatively, duo to it reaches the limitation of the multiple methods which only could be used to indistinctly distinguish herbs.