Revealing quality chemicals of Tetrastigma hemsleyanum roots in different geographical origins using untargeted metabolomics and random-forest based spectrum-effect analysis.

Tetrastigma hemsleyanum root is a popular functional food in China, and the price varies based on the origin of the product. The link between the origin, metabolic profile, and bioactivity of T. hemsleyanum must be investigated. This study compares the metabolic profiles of 254 samples collected from eight different areas with 49 potential key chemical markers using plant metabolomics. The metabolic pathways of the five critical flavonoid metabolites were annotated and enriched using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Moreover, a random forest model aiding the spectrum-effect relationship analysis was developed for the first time indicating catechin and darendoside B as potential quality markers of antioxidant activity. The findings of this study provide a comprehensive understanding of the chemical composition and bioactive compounds of T. hemsleyanum as well as valuable information on the evaluation of the quality of various samples and products in the market.

Cationic Conjugated Polymer Fluorescence Resonance Energy Transfer for DNA Methylation Assessment to Discriminate the Geographical Origins of Lonicerae japonicae flos.

The flavor and taste of Lonicerae japonicae flos (LJF) products are heavily influenced by geographical origin. Tracing the geographical origin is an important aspect of LJF quality assessment. Here, DNA methylation analysis coupled with chemometrics revealed that, in 10 CpG islands upstream of genes in the chlorogenic acid and iridoid biosynthetic pathways, DNA methylation differences appear close association with LJF geographical origin. DNA methylation status in these CpG islands was determined using the cationic conjugated polymer fluorescence resonance energy transfer method. As a result, LJFs from 39 geographical origins were classified into four groups corresponding to Northern China, Central Plain of China, Southeast China, and Western China, according to cluster analysis and principal component analysis. Our findings contribute to an understanding of the modulation of LJF taste and can assist in understanding how DNA methylation in LJF varies with geographical origin.

Discrimination for geographical origin of Panax quinquefolius L. using UPLC Q-Orbitrap MS-based metabolomics approach.

American ginseng, Panax quinquefolius L., is an important medicinal plant with multiple pharmacological effects and high nutritional value. American ginseng from different geographical origins varies in quality and price. However, there was no approach for discriminating American ginseng from different geographical origins to date. In this study, a metabolomic method based on the UPLC-Orbitrap fusion platform was established to comprehensively determine and analyze metabolites of American ginseng from America and Canada, Heilongjiang, Jilin, Liaoning, and Shandong provinces in China. A total of 382 metabolites were detected, including 230 saponins, 30 amino acids and derivatives, 27 organic acids and derivatives, 25 lipids, 17 carbohydrates and derivatives, 10 phenols, 8 nucleotides, and derivatives, as well as 35 other metabolites. Metabolite differences between North America and Asia producing areas were more obvious than within Asia. Twenty metabolites, contributed most to the differentiation of producing areas, were identified as potential markers with prediction accuracy higher than 91%. The results provide new insights into the metabolite composition of American ginseng from different origins, which will help discriminate origins and promote quality control of American ginseng.

Quality analysis and geographical origin identification of Rosa roxburghii Tratt from three regions based on Fourier transform infrared spectroscopy.

The study aimed to provide new information of Rosa roxburghii Tratt (RRT) for the production of functional foods and distinguish the geographical origins of RRT. The nutritional components of RRT from three regions in China, such as vitamin C, polysaccharides, total flavonoids, and total phenolics, and their antioxidant activities were analyzed by one-way ANOVA. The results of Fourier transform infrared spectroscopy (FT-IR) combined with principal component analysis (PCA), stepwise linear discriminant analysis (SLDA), k-nearest neighbor (k-NN), and support vector machine (SVM) were used to establish discriminant models to identify the geographical origin of RRT. The results of one-way ANOVA showed that the contents of some nutrients and antioxidant activity were significantly different among RRT from different regions and their FT-IR spectra also showed significant differences. The characteristic fingerprint bands of FT-IR (1679-1618 cm-1and 1520-900 cm-1) closely related to the geographical origins of RRT were screened out. Based on SLDA, a discriminant model was established to realize the classification and identification of RRT from different regions and the correct discrimination rate of the testing sample set obtained with the established model reached 100 %. Geographical factors caused the obvious differences in nutritional components and antioxidant activity in RRT. The characteristic fingerprint bands of RRT obtained with FT-IR could be used to identify the geographical origins of RRT more quickly and accurately.

Geographical origin discrimination of Ethiopian sesame seeds by elemental analysis and chemometric tools.

Origin discrimination of sesame seeds is becoming one of the important factors for the sesame seed trade in Ethiopia as it influences the market price. This study was undertaken to construct accurate geographical origin discriminant models for Ethiopian sesame seeds using multi-element analysis and statistical tools. The concentration of 12 elements (Na, Mg, Cr, Mn, Fe, Cu, Co, Ni, Zn, Cd, As and Pb) were determined in 93 samples which were collected from three main sesame seed-producing regions in Ethiopia, Gondar, Humera and Wollega. According to a one-way analysis of variance (ANOVA), the concentration of 10 elements showing a significant difference (p < 0.05) was taken for statistical analysis using principal component analysis (PCA) and linear discriminant analysis (LDA). PCA showed some clustering of samples according to their respective origins. Then, the follow-up LDA resulted in a 100 % correct origin classification rate for all 93 sesame seed samples obtained from three regions in Ethiopia.

Headspace GC/MS and fast GC e-nose combined with chemometric analysis to identify the varieties and geographical origins of ginger (Zingiber officinale Roscoe).

Food authenticity regarding different varieties and geographical origins is increasingly becoming a concern for consumers. In this study, headspace gas chromatography-mass spectrometry (HS-GC-MS) and fast gas chromatography electronic nose (fast GC e-nose) were used to successfully distinguish the varieties and geographical origins of dried gingers from seven major production areas in China. By chemometric analysis, a distinct separation between the two varieties of ginger was achieved based on HS-GC-MS. Furthermore, flavor information extracted by fast GC e-nose realized the discrimination of geographical origins, and some potential flavor components were selected as important factors for origin certification. Moreover, several pattern recognition algorithms were compared in varietal and regional identification, and random forest (RF) led to the highest accuracies for discrimination. Overall, a rapid and precise method combining multivariate chemometrics and algorithms was developed to determine varieties and geographical origins of ginger, and it could also be applied to other agricultural products.

ATR-MIR spectroscopy as a tool to assist 'Tempranillo' clonal selection process: Geographical origin and year of harvest discrimination and oenological parameters prediction.

The present study evaluated the ability of Attenuated Total Reflectance - Mid-Infrared (ATR-MIR) spectroscopy combined with Partial Least Squares Discriminant Analysis (PLS-DA) to discriminate the origin and harvest year of 'Tempranillo' grape clones and with Partial Least Squares (PLS) regressions to predict its contents in soluble solids (SS), pH and titratable acidity (TA). Normalized spectra of grape homogenates and normalized plus 1st Derivative spectra of grape skins allowed an overall percentage of correct classifications of 99.6% and 96.7% in validation, according to origin, and 98.3% and 90.0% in validation, according to harvest year, respectively. The normalized spectra of grape homogenates allowed a calibration and validation determination coefficients (R2) of 0.92 and 0.90 for SS, 0.90 and 0.84 for pH, 0.88 and 0.84 for TA, respectively. The ATR-MIR combined with multivariate analysis showed to be an appropriate tool to assist the clonal selection process of 'Tempranillo'.

Differentiating Westlake Longjing tea from the first- and second-grade producing regions using ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry-based untargeted metabolomics in combination with chemometrics.

There are numerous articles published for geographical discrimination of tea. However, few research works focused on the authentication and traceability of Westlake Longjing green tea from the first- and second-grade producing regions because the tea trees are planted in a limited growing zone with identical cultivate condition. In this work, a comprehensive analytical strategy was proposed by ultrahigh performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based untargeted metabolomics coupled with chemometrics. The automatic untargeted data analysis strategy was introduced to screen metabolites that expressed significantly among different regions. Chromatographic features of metabolites can be automatically and efficiently extracted and registered. Meanwhile, those that were valuable for geographical origin discrimination were screened based on statistical analysis and contents in samples. Metabolite identification was performed based on high-resolution mass values and tandem mass spectra of screened peaks. Twenty metabolites were identified, based on which the two-way encoding partial least squares discrimination analysis was built for geographical origin prediction. Monte Caro simulation results indicated that prediction accuracy was up to 99%. Our strategy can be applicable for practical applications in the quality control of Westlake Longjing green tea.

Sr isotope discrimination of multi species aquaculture productions at a worldwide scale and contribution of the water reservoir in Sr plant input.

Aquatic plants commonly used in landscaping or as ornaments are subject to a growing worldwide market that is source of trade between countries which can induce the transfer of unwanted invasive alien plant species. To protect national biodiversity and economy, authorities promote the use of local markets without however providing the method to do so. This study deals with the feasibility of using Sr stable isotopes for discriminating the origin of aquatic plants at a worldwide scale. More than 15 aquatic plant species were collected from main producers in four countries (China, Hungary, Germany, France). Each plant was analysed for its 87Sr/86Sr ratio and the results are compared within samples from each producer and between countries. For a given produce, significant 87Sr/86Sr can be measured as a function of the plant species. However, at the scale of Europe, plants from different producers are almost isotopically identical with 87Sr/86Sr ratios of 0.71228 ± 218.10-5, 0.71116 ± 178.10-5 and 0.71066 ± 156.10-5 for France, Hungary and Germany, respectively. These values are clearly distinguishable from those measured in Chinese aquatic plants, which yield a mean 87Sr/86Sr ratio of 0.70591 ± 168.10-5. This Sr isotopic discrimination between European and Chinese aquatic plants is explained by the specific agricultural and hydrogeological environments of the producing countries. Indeed, the cycle of Sr in aquatic plants is studied here for the first time. Natural and anthropic materials of French origin were collected and characterized in terms of 87Sr/86Sr. Mixing models reveal that irrigation water is the main source of Sr for plants (35-85%). Clays from the substrate (4-38%) and fertilizers (5-19%) can also contribute, in proportions depending on the plant species. This model accounts for the small variations in 87Sr/86Sr ratios of species from the same producer and allows a discrimination between producers using different agricultural practices.

Recent advances in untargeted and targeted approaches applied in herbal-extracts and essential-oils fingerprinting - A review.

Herbal extracts and essential oils have been used over the centuries for their dietary, cosmetic and therapeutic properties. Quality control is needed to guarantee the safety and quality of these consumables. In this regard, fingerprinting techniques are important for inspection of the authenticity and for quality control. Analytical fingerprinting techniques provide signals related to the composition of a matrix (oil, plant extract, food…). The resulting fingerprint (spectrum or chromatogram) obtained for an untargeted or targeted approach is coupled to chemometric data processing, which may allow, for instance, the desired identification or discrimination of the sample considered. In this context, recent advances in untargeted/targeted fingerprinting approaches (especially chromatographic and spectroscopic) were described and their application in the taxonomic identification, classification and authentication of plants (medicinal) and essential oils discussed. An overview of the applications of untargeted/targeted fingerprinting techniques on herbal-extracts and essential-oils analysis, using different chemometric tools, has been included.

Discriminating geographical origins of green tea based on amino acid, polyphenol, and caffeine content through high-performance liquid chromatography: Taking Lu'an guapian tea as an example.

Seventy-three Lu'an guapian tea (LAGP) samples were collected from 11 growing locations in the city of Lu'an, Anhui Province, China. Through high-performance liquid chromatography, 18 amino acids, along with gallic acid, caffeine, and five catechins, were quantitatively detected. Hierarchical cluster, correlation and principal component analysis, and a support vector machine were used for geographical discrimination. The findings suggested that the differences in tea quality between the inner and outer mountain regions are related to isoleucine, leucine, phenylalanine, and valine contents, with a correlation coefficient of more than 0.85. Principal component analysis combining with support vector machine was a feasible method. The identification rates for the inner and outer mountains were 97.96% in the training set and 95.83% in the prediction set. Furthermore, the identification rates for the three counties were 91.84% and 95.83% in the training and prediction sets, respectively.

Multielemental Analysis Associated with Chemometric Techniques for Geographical Origin Discrimination of Tea Leaves (Camelia sinensis) in Guizhou Province, SW China.

This study aimed to construct objective and accurate geographical discriminant models for tea leaves based on multielement concentrations in combination with chemometrics tools. Forty mineral elements in 87 tea samples from three growing regions in Guizhou Province (China), namely Meitan and Fenggang (MTFG), Anshun (AS) and Leishan (LS) were analyzed. Chemometrics evaluations were conducted using a one-way analysis of variance (ANOVA), principal component analysis (PCA), linear discriminant analysis (LDA), and orthogonal partial least squares discriminant analysis (OPLS-DA). The results showed that the concentrations of the 28 elements were significantly different among the three regions (p < 0.05). The correct classification rates for the 87 tea samples were 98.9% for LDA and 100% for OPLS-DA. The variable importance in the projection (VIP) values ranged between 1.01⁻1.73 for 11 elements (Sb, Pb, K, As, S, Bi, U, P, Ca, Na, and Cr), which can be used as important indicators for geographical origin identification of tea samples. In conclusion, multielement analysis coupled with chemometrics can be useful for geographical origin identification of tea leaves.

Automatic untargeted metabolic profiling analysis coupled with Chemometrics for improving metabolite identification quality to enhance geographical origin discrimination capability.

Untargeted metabolic profiling analysis is employed to screen metabolites for specific purposes, such as geographical origin discrimination. However, the data analysis remains a challenging task. In this work, a new automatic untargeted metabolic profiling analysis coupled with a chemometric strategy was developed to improve the metabolite identification results and to enhance the geographical origin discrimination capability. Automatic untargeted metabolic profiling analysis with chemometrics (AuMPAC) was used to screen the total ion chromatographic (TIC) peaks that showed significant differences among the various geographical regions. Then, a chemometric peak resolution strategy is employed for the screened TIC peaks. The retrieved components were further analyzed using ANOVA, and those that showed significant differences were used to build a geographical origin discrimination model by using two-way encoding partial least squares. To demonstrate its performance, a geographical origin discrimination of flaxseed samples from six geographical regions in China was conducted, and 18 TIC peaks were screened. A total of 19 significant different metabolites were obtained after the peak resolution. The accuracy of the geographical origin discrimination was up to 98%. A comparison of the AuMPAC, AMDIS, and XCMS indicated that AuMPACobtained the best geographical origin discrimination results. In conclusion, AuMPAC provided another method for data analysis.

Species authentication and geographical origin discrimination of herbal medicines by near infrared spectroscopy: A review.

Near infrared (NIR) spectroscopy as a rapid and nondestructive analytical technique, integrated with chemometrics, is a powerful process analytical tool for the pharmaceutical industry and is becoming an attractive complementary technique for herbal medicine analysis. This review mainly focuses on the recent applications of NIR spectroscopy in species authentication of herbal medicines and their geographical origin discrimination.

Rapid geographical differentiation of the European spread brown macroalga Sargassum muticum using HRMAS NMR and Fourier-Transform Infrared spectroscopy.

Two recent techniques based on chemical footprinting analysis, HRMAS NMR and FTIR spectroscopy, were tested on a brown macroalgal model. These powerful and easily-to-use techniques allowed us to discriminate Sargassum muticum specimens collected in five different countries along Atlantic coasts, from Portugal to Norway. HRMAS NMR and FTIR permitted the obtaining of an overview of metabolites produced by the alga. Based on spectra analysis, results allowed us to successfully group the samples according to their geographical origin. HRMAS NMR and FTIR spectroscopy respectively point out the relation between the geographical localization and the chemical composition and demonstrated macromolecules variations regarding to environmental stress. Then, our results are discussed in regard of the powerful of these techniques together with the variability of the main molecules produced by Sargassum muticum along the Atlantic coasts.

Species authentication and geographical origin discrimination of herbal medicines by near infrared spectroscopy:A review / 药物分析学报

Near infrared (NIR) spectroscopy as a rapid and nondestructive analytical technique, integrated with chemometrics, is a powerful process analytical tool for the pharmaceutical industry and is becoming an attractive complementary technique for herbal medicine analysis. This review mainly focuses on the recent applications of NIR spectroscopy in species authentication of herbal medicines and their geo-graphical origin discrimination.