Geographical traceability of Chinese green tea using stable isotope and multi-element chemometrics

Unlocking the elemental signature of European tea gardens: Implications for tea traceability

This study presents a comprehensive analysis of the elemental profiles of tea leaves coming from plants grown in several European gardens, with a focus on the bioaccumulation of essential and potentially toxic trace elements in relation to processing and location of tea garden. Samples were collected from various gardens across Europe, including Portugal, the Azores, Germany, the Netherlands, and Switzerland. Elemental analysis was conducted on fresh tea leaves, dried leaves, and leaves processed for the production of green and black tea, along with soil samples from the root zones of tea plants. The results reveal no significant differences in elemental content based on the processing of tea leaves. However, distinct elemental profiles were observed among tea leaves of plants grown in gardens from different European regions. Utilizing chemometric and machine learning tools, the study highlights the potential of these elemental profiles for enhancing the traceability of tea products.

Effects of Geographical Origin and Tree Age on the Stable Isotopes and Multi-Elements of Pu-erh Tea

Pu-erh tea is a famous tea worldwide, and identification of the geographical origin of Pu-erh tea can not only protect manufacture's interests, but also boost consumers' confidence. However, tree age may also influence the fingerprints of Pu-erh tea. In order to study the effects of the geographical origin and tree age on the interactions of stable isotopes and multi-elements of Pu-erh tea, 53 Pu-erh tea leaves with three different age stages from three different areas in Yunnan were collected in 2023. The δ13C, δ15N values and 25 elements were determined and analyzed. The results showed that δ13C, δ15N, Mg, Mn, Fe, Cu, Zn, Rb, Sr, Y, La, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu had significant differences among different geographical origins (p < 0.05). Mn content was significantly influenced by region and tree age interaction. Based on multi-way analysis of variance, principal component analysis and step-wised discriminant analysis, 24 parameters were found to be closely related to the geographical origin rather than tree age, and the geographical origin of Pu-erh tea can be 100.0% discriminated in cross-validation with six parameters (δ13C, δ15N, Mn, Mg, La, and Tb). The study could provide references for the establishment of a database for the traceability of Pu-erh tea, and even the identification of tea sample regions with different tree ages.

Determination of adulteration, geographical origins, and species of food by mass spectrometry

Food adulteration, mislabeling, and fraud, are rising global issues. Therefore, a number of precise and reliable analytical instruments and approaches have been proposed to ensure the authenticity and accurate labeling of food and food products by confirming that the constituents of foodstuffs are of the kind and quality claimed by the seller and manufacturer. Traditional techniques (e.g., genomics-based methods) are still in use; however, emerging approaches like mass spectrometry (MS)-based technologies are being actively developed to supplement or supersede current methods for authentication of a variety of food commodities and products. This review provides a critical assessment of recent advances in food authentication, including MS-based metabolomics, proteomics and other approaches.

Essential and Potentially Toxic Elements (PTEs) Content in European Tea (Camellia sinensis) Leaves: Risk Assessment for Consumers

Tea (Camellia sinensis) is the second most consumed beverage worldwide, playing a key role in the human diet. Tea is considered a healthy drink, as its consumption has been linked to a lower risk of cardiovascular disease-related events and death, stroke, metabolic syndrome and obesity. However, several studies have shown that C. sinensis is a hyperaccumulator of Al and other elements that are considered potentially toxic. In the present study, the contents of 15 elements (both essential and toxic) were determined for the first time in tea leaves collected in tea gardens located in six different European countries and processed to provide black and green tea. The results showed that Al was the major toxic element detected, followed by Ni, Cr, Pb, As, Cd, Ag, and Hg. Essential elements were detected in the order of Mn, Fe, Zn, Cu, Co, and Se. Statistically significant correlations (p < 0.05) were found in the distribution of some elements, highlighting mechanisms of synergic or antagonist interaction. Multivariate analysis revealed that geographical origin was the main driver in clustering the samples, while the different treatment processes (black or green) did not significantly affect the contents of elements in the leaves. The estimation of potential non-carcinogenic risk revealed no risk for the consumption of European teas for consumers in terms of potentially toxic elements.

Metabolomics integrated with machine learning to discriminate the geographic origin of Rougui Wuyi rock tea

The geographic origin of agri-food products contributes greatly to their quality and market value. Here, we developed a robust method combining metabolomics and machine learning (ML) to authenticate the geographic origin of Wuyi rock tea, a premium oolong tea. The volatiles of 333 tea samples (174 from the core region and 159 from the non-core region) were profiled using gas chromatography time-of-flight mass spectrometry and a series of ML algorithms were tested. Wuyi rock tea from the two regions featured distinct aroma profiles. Multilayer Perceptron achieved the best performance with an average accuracy of 92.7% on the training data using 176 volatile features. The model was benchmarked with two independent test sets, showing over 90% accuracy. Gradient Boosting algorithm yielded the best accuracy (89.6%) when using only 30 volatile features. The proposed methodology holds great promise for its broader applications in identifying the geographic origins of other valuable agri-food products.

Production regions discrimination of Huangguanyin oolong tea by using the content of chemical components and rare earth elements

Oolong tea is one of the most popular tea beverages in China. Tea cultivars, processing technology and origin of production affect the quality and price of oolong teas. To investigate the differences in Huangguanyin oolong tea from different production regions, the chemical components, mineral elements and rare earth elements of Huangguanyin oolong tea produced in Yunxiao (YX) and Wuyishan (WY) were analyzed by using spectrophotometry methods, targeted metabolomics and inductive plasma coupled mass spectrometry (ICP-MS). The results of spectrophotometry methods revealed that there were significant differences in thearubigin, tea polyphenols and water extract between Huangguanyin oolong teas from different production regions. Targeted metabolomics identified a total of 31 chemical components in Huangguanyin oolong teas from the two production regions, of which 14 chemical components were significantly different and contributed to the regional differentiation of Huangguanyin oolong tea. Yunxiao Huangguanyin had relatively higher contents of (-)-Epigallocatechin-3-O-(3-O-methylgallate) (EGCG3″Me), ornithine (Orn) and histidine (His), while Wuyishan Huangguanyin had relatively higher contents of glutamic acid (Glu), γ-aminobutyric acid (GABA), β-aminobutyric acid (β-ABA) and other components. Moreover, ICP-MS identified a total of 15 mineral elements and 15 rare earth elements in Huangguanyin oolong tea from the two production regions, of which 15 elements were significantly different between YX and WY, and contributed to the regional differentiation of Huangguanyin oolong tea. K had a relatively higher content in Yunxiao Huangguanyin, while rare earth elements had relatively higher contents in Wuyishan Huangguanyin. The classification results by the production region showed that the discrimination rate of the support vector machine (SVM) model based on the 14 different chemical components reached 88.89%, while the SVM model based on the 15 elements reached 100%. Therefore, we used targeted metabolomics and ICP-MS techniques to screen and explore the chemical components, mineral elements and rare earth elements differences among two production regions, which indicated the feasibility of Huangguanyin oolong tea classification by production regions in the study. The results will provide some reference for the distinction between the two production regions of Huangguanyin oolong tea.

Stable isotope characterization of tobacco products: A determination of synthetic or natural nicotine authenticity

RATIONALE

"Tobacco-free" or synthetic nicotine products have appeared in some markets, increasing potential health risks and regulatory compliance challenges. Currently, there are few reliable methods for the determination of authenticity of natural and synthetic nicotine. Analytical techniques based on stable isotopes have broad application prospects in the traceability and identification of agricultural products.

METHODS

Tobacco leaves from four main tobacco production regions in China and different types of tobacco products were extracted with n-hexane and 5% sodium hydroxide to obtain nicotine extracts. Subsequent stable isotope mass spectrometry was performed by analyzing δ² H, δ¹³ C, and δ¹⁵ N values of nicotine.

RESULTS

Firstly, results from a batch of 233 samples indicated stable isotopes were closely related to climate and geographical locations and provide a basis for a determination of the origin of tobacco leaves. In addition, the δ² H values had significant differences between natural and synthetic nicotine and the results indicate a δ² H value of -163.0‰ could be the threshold for assessing synthetic and natural nicotine. Finally, a total of 239 results further validated the δ² H value as a metric for source authentication of commercial tobacco products.

CONCLUSIONS

Synthetic (S)-(-)-nicotine could be accurately and quickly identified using the method developed by measuring δ² H values in a qualitative manner. To our knowledge, this is the first time a stable isotope mass spectrometry technique has been used for distinguishing the source of nicotine. This technique will aid in the accurate identification, labelling, and regulation of synthetic nicotine-based tobacco products.

Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), a Useful Tool in Authenticity of Agricultural Products' and Foods' Origin

Fraudulent practices are the first and foremost concern of food industry, with significant consequences in economy and human's health. The increasing demand for food has led to food fraud by replacing, mixing, blending, and mislabeling products attempting to increase the profits of producers and companies. Consequently, there was the rise of a multidisciplinary field which encompasses a large number of analytical techniques aiming to trace and authenticate the origins of agricultural products, food and beverages. Among the analytical strategies have been developed for the authentication of geographical origin of foodstuff, Inductively Coupled Plasma Mass Spectrometry (ICP-MS) increasingly dominates the field as a robust, accurate, and highly sensitive technique for determining the inorganic elements in food substances. Inorganic elements are well known for evaluating the nutritional composition of food products while it has been shown that they are considered as possible tracers for authenticating the geographical origin. This is based on the fact that the inorganic component of identical food type originating from different territories varies due to the diversity of matrix composition. The present systematic literature review focusing on gathering the research has been done up-to-date on authenticating the geographical origin of agricultural products and foods by utilizing the ICP-MS technique. The first part of the article is a tutorial about food safety/control and the fundaments of ICP-MS technique, while in the second part the total research review is discussed.

An overview on multi-elemental profile integrated with chemometrics for food quality assessment: toward new challenges

Food products, especially those with high value-added, are commonly subjected to strict quality controls, which are of paramount importance, especially for attesting to some peculiar features related, for instance, to their geographical origin and/or the know-how of their producers. However, the sophistication of fraudulent practices requires a continuous update of analytical platforms. Different analytical techniques have become extremely appealing since the instrumental analysis tools evolution has substantially improved the capability to reveal and understand the complexity of food. In light of this, multi-elemental composition has been successful implemented solving a plethora of food authentication and traceability issues. In the last decades, it has existed an ever-increasing trend in analysis based on spectrometry analytical platforms in order to obtain a multi-elemental profile that combined with chemometrics have been noteworthy analytical methodologies able to solve these problems. This review provides an overview of published reports in the last decade (from 2011 to 2021) on food authentication and quality control from their multi-element composition in order to evaluate the state-of-the-art of this field and to identify the main characteristics of applied analytical techniques and chemometric data treatments that have permit achieve accurate discrimination/classification models, highlighting the strengths and the weaknesses of these methodologies.

Identification of the age of white tea using proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) coupled with multivariate analysis

RATIONALE

In recent years, white tea has become increasingly popular. Some merchants confuse the age of white tea and sell poor-quality products for profit. Therefore, it is necessary to provide technical support for product authentication and valorization in white tea of different marked ages.

METHODS

Volatile organic compounds (VOCs) were detected by proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) and identified as volatile fingerprints. PTR-TOF-MS combined with multivariate analysis was found to identify white tea of four different marked ages (1, 3, 5, and 8 years) for authentication. Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) were used as classification models to identify key volatile metabolites.

RESULTS

The OPLS-DA model achieved the best results (96.67%, 96.67%, 96.67%, and 96.67% in the training set and 96.00%, 96.00%, 100%, and 100% in the prediction set for 1-year, 3-year, 5-year, and 8-year tea samples, respectively), showing that PTR-TOF-MS with the OPLS-DA model could successfully be used in the identification of white tea with different marked ages. Out of the 60 identified VOCs, 26 volatile materials were closely correlated with tea age and were used as markers to discriminate white tea of different ages.

CONCLUSIONS

PTR-TOF-MS coupled with multivariate analysis could be applied for quality evaluation of tea products of different ages and provided a feasible technical support for product authentication and valorization in white tea of different marked ages.

Stable isotope and photosynthetic response of tea grown under different temperature and light conditions

The stable isotope and photosynthesis response of tea (Camellia sinensis) is determined under different light and temperature conditions. The results showed that isotopes of young tea leaves were more enriched with increasing light intensity (31 ~ 411 µmol m^-2∙s^-1). However, the value of δ¹³C and δ¹⁵N seemed depleted, while δ²H and δ¹⁸O became enriched as temperature increasing from 15 to 35 °C. Significant isotope differences were found in tea leaves harvested between early growth (0 ~ 10 days) and later growth (10 ~ 21 days) periods (p < 0.05). Pearson's correlation showed a negative correlation between isotopes (δ¹³C, δ¹⁵N and δ²H) and photosynthetic parameters (EVAP and CI) ranging from 0.497 to 0.872, under 25 °C/203 µmol m^-2∙s^-1. But δ¹⁸O had a weak correlation with all photosynthetic parameters under the same conditions. These distinctive correlations between isotopes and photosynthetic parameters provide new insights which could be used to predict tea isotope responses arising from subtle seasonal or climate change conditions.

Recent techniques for the authentication of the geographical origin of tea leaves from camellia sinensis: A review

Tea is one of the most important beverages worldwide, is produced in several distinct geographical regions, and is traded on the global market. The ability to determine the geographical origin of tea products helps to ensure authenticity and traceability. This paper reviews the recent research on authentication of tea using a combination of instrumental and chemometric methods. To determine the production region of a tea sample, instrumental methods based on analyzing isotope and mineral element contents are suitable because they are less affected by tea variety and processing methods. Chemometric analysis has proven to be a valuable method to identify tea. Principal component analysis (PCA) and linear discriminant analysis (LDA) are the most preferred methods for processing large amounts of data obtained through instrumental component analysis.

Tea and Chicory Extract Characterization, Classification and Authentication by Non-Targeted HPLC-UV-FLD Fingerprinting and Chemometrics

Tea is a widely consumed drink in the world which is susceptible to undergoing adulterations to reduce manufacturing costs and rise financial benefits. The development of simple analytical methodologies to assess tea authenticity, as well as to detect and quantify frauds, is an important matter considering the rise of adulteration issues in recent years. In the present study, untargeted HPLC-UV and HPLC-FLD fingerprinting methods were employed to characterize, classify, and authenticate tea extracts belonging to different varieties (red, green, black, oolong, and white teas) by partial least squares-discriminant analysis (PLS-DA), as well as to detect and quantify adulteration frauds when chicory was used as the adulterant by partial least squares (PLS) regression, to ensure the authenticity and integrity of foodstuffs. Overall, PLS-DA showed a good classification and grouping of the tea samples according to the tea variety and, except for some white tea extracts, perfectly discriminated from the chicory ones. One hundred percent classification rates for the PLS-DA calibration models were achieved, except for green and oolong tea when HPLC-FLD fingerprints were employed, which showed classification rates of 96.43% and 95.45%, respectively. Good predictions were also accomplished, also showing, in almost all the cases, a 100% classification rate for prediction, with the exception of white tea and oolong tea when HPLC-UV fingerprints were employed that exhibited a classification rate of 77.78% and 88.89%, respectively. Good PLS results for chicory adulteration detection and quantitation were also accomplished, with calibration, cross-validation, and external validation errors beneath 1.4%, 6.4%, and 3.7%, respectively. Acceptable prediction errors (below 21.7%) were also observed, except for white tea extracts that showed higher errors which were attributed to the low sample variability available.

Chemometrics-assisted isotope ratio fingerprinting based on gas chromatography/combustion/isotope ratio mass spectrometry for saffron authentication

In the present contribution, the capability of isotopic ratio mass spectrometry (IRMS) for saffron authentication and detection of four common plant-derived adulterants (marigold flower, safflower, rubia, and saffron style) was investigated. For this purpose, 62 authentic saffron samples were analyzed by elemental analyzer-IRMS (EA-IRMS) and gas chromatography-combustion-IRMS (GC-C-IRMS). In this regard, EA-IRMS and GC-C-IRMS isotope fingerprints of carbon-13 and nitrogen-15 isotopes of saffron components were provided and then analyzed by chemometric methods. Principal component analysis (PCA) showed two different behaviors regarding two main regions. Then, a representative saffron sample was provided to study adulteration. On this matter, binary mixtures of saffron and adulterants were prepared at five different weight percentages (5%, 10%, 15%, 25%, and 35%) and analyzed by EA-IRMS and GC-C-IRMS. Data-driven soft independent modeling of class analogy (DD-SIMCA) was used to model authentic saffron samples and find a boundary between authentic and adulterated samples with a sensitivity of 100% by GC-C-IRMS. After that, discriminant models of linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and partial least squares-discriminant analysis (PLS-DA) were tested to find the best discrimination line and also detection of the lowest level of adulterants. Among different models, the QDA model outperformed other methods and showed the ability to predict adulterants at 5% w/w level with 100% accuracy and precision. Finally, the developed QDA model was successfully used to discriminate a set of mixed samples of saffron and four adulterants as well as some commercial samples.

Authentication of Geographical Origin in Hainan Partridge Tea (Mallotus obongifolius) by Stable Isotope and Targeted Metabolomics Combined with Chemometrics

Partridge tea (Mallotus oblongifolius (Miq.) Müll.Arg.) is a local characteristic tea in Hainan, the southernmost province of China, and the quality of partridge tea may be affected by the producing areas. In this study, stable isotope and targeted metabolomics combined chemometrics were used as potential tools for analyzing and identifying partridge tea from different origins. Elemental analysis-stable isotope ratio mass spectrometer and liquid chromatography-tandem mass spectrometrywas used to analyze the characteristics of C/N/O/H stable isotopes and 54 chemical components, including polyphenols and alkaloids in partridge tea samples from four regions in Hainan (Wanning, Wenchang, Sanya and Baoting). The results showed that there were significant differences in the stable isotope ratios and polyphenol and alkaloid contents of partridge tea from different origins, and both could accurately classify partridge tea from different origins. The correct separation and clustering of the samples were observed by principal component analysis and the cross-validated Q² values by orthogonal partial least squares discriminant analysis (OPLS-DA) were 0.949 (based on stable isotope) and 0.974 (based on polyphenol and alkaloid), respectively. Potential significance indicators for origin identification were screened out by OPLS-DA and random forest algorithm, including three stable isotopes (δ¹³C, δ D, and δ¹⁸O) and four polyphenols (luteolin, protocatechuic acid, astragalin, and naringenin). This study can provide a preliminary guide for the origin identification of Hainan partridge tea.

Rapid and direct identification of the origin of white tea with proton transfer reaction time-of-flight mass spectrometry

RATIONALE

White tea has become very popular in recent years, but there has been no scientific identification of white tea from different origins. For product authentication and valorization, every kind of white tea must be marked with an indication of its origin.

METHODS

Volatile profiles of white tea leaf samples from their main origins in China (Fuding City, Zhenghe City and Jianyang City) were analyzed using proton transfer reaction time-of-flight mass spectrometry (PTR-TOFMS). Tentative identifications of the volatile organic compounds (VOCs) were obtained by PTR-TOFMS of the headspace. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed to evaluate the differences among the various origins.

RESULTS

Teas from different origins were shown to have characteristic VOCs and profiles. Thus, white teas from different origins could be separated by characterizing the volatile emissions from the dry tea leaves. The ability of the two classification models to use the volatile fingerprints in origin discrimination was investigated.

CONCLUSIONS

Two classification models (PCA and OPLS-DA) were applied to the PTR-TOFMS data obtained from the VOCs of various white teas. The classification models were shown to be useful in identifying the origin of white tea samples, providing a reference for white tea identification.

Isotope chemometrics determines farming methods and geographical origin of vegetables from Yangtze River Delta Region, China

Shanghai city has encountered possible food fraud regarding the geographical mislabeling of vegetables for economic gain. A combination of δ¹³C, δ¹⁵N, δ²H and δ¹⁸O values and partial least squares discrimination analysis and support vector machine (SVM) methods were used for the first time to assess farming methods and determine the origin of vegetables from Shanghai city, Anhui and Zhejiang provinces. The results showed that 65.8% of Shanghai vegetables, 38.2% of Anhui vegetables and 23.6% of Zhejiang vegetables appeared to be grown using green or organic farming methods. The optimal discriminant model was obtained using SVM with a predictive accuracy of 100% for Shanghai vegetables. Zhejiang vegetables had a predictive accuracy of 91.7%, while it was difficult to distinguish Anhui vegetables from Shanghai or Zhejiang vegetables. Therefore, this study provided a useful method to identify vegetable farming methods and discriminate vegetables from Shanghai and Zhejiang.

Use of mineral multi-elemental analysis to authenticate geographical origin of different cultivars of tea in Guizhou, China

BACKGROUND

The geographical origin of tea (Camellia sinensis) can be traced using mineral elements in its leaves as fingerprints. However, the role that could be played by soil mineral elements in the geographical authentication of tea leaves has been unclear. In this study, 22 mineral elements in 73 pairs of tea leaves and soils from three regions (Pu'an, Duyun, and Liping) in Guizhou, China, were determined using inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma atomic emission spectrometry (ICP-AES). The mineral element concentrations were processed by multivariate statistical analysis, including one-way analysis of variance (ANOVA), correlation analysis, principal component analysis (PCA), and stepwise linear discriminant analysis (S-LDA).

RESULTS

Based on a one-way ANOVA, tea leaves and soils with different origins possessed unique mineral element fingerprints. Sixteen mineral element concentrations in tea leaves were significantly correlated with those in soils (P < 0.05). The geographical origins of tea leaves were effectively differentiated using the 16 correlated mineral elements combined with PCA. The S-LDA model offered a 100% differentiation rate, and six indicative elements (phosphorus, Sr, U, Pb, Cd, and Cr) were selected as important fingerprinting markers for the geographic traceability of tea leaves. The accurate discrimination rate of geographical origin was unaffected by the cultivars of tea in the S-LDA model.

CONCLUSIONS

Mineral elements in soils played an important role in the geographical authentication of tea leaves. Mineral elemental concentrations with significant correlations between tea leaves and soils could be robust, and could be used to trace the geographical origins of tea leaves. © 2020 Society of Chemical Industry.

Influence of leaf age, species and soil depth on the authenticity and geographical origin assignment of green tea

RATIONALE

Stable isotope fractionation occurring during leaf growth provides internal characteristics for identifying the geographical origin, traceability and authentication of tea. Studying the influence of leaf age, species and the relationship with the cultivated soil may reveal previously undocumented stable isotope fractionation mechanisms, and provide a deeper understanding of the physiological isotopic effects on the tractability and authentication accuracy of green tea to combat mislabeling and fraudulent conduct.

METHODS

A total of 36 pairs of young (one bud with one leaf) and mature growth (older leaf) samples from two species of Longjing tea (Longjing #43 and Colonial cultivar) and corresponding cultivation soil samples from two different depth layers (0-20 cm and 20-40 cm) were collected in Westlake district, Hangzhou, Zhejiang province, China. Four stable isotope ratios (δ¹³ C, δ¹⁵ N, δ² H, and δ¹⁸ O values) were measured using an elemental analyzer coupled with an isotope ratio spectrometer. Linear correlation and one-way analysis of variance (ANOVA) statistical analyses were performed to investigate isotopic fractionation mechanisms during plant growth, and reflect the dynamic physiological processes from soil to leaf.

RESULTS

The carbon and nitrogen isotope ratios (δ¹³ C and δ¹⁵ N values) reflected the absorption, migration and fractionation of carbon dioxide and nitrogenous nutrients during photosynthesis, nutrient uptake, nitrogen fixation and leaf respiration. The water isotope ratios (δ² H and δ¹⁸ O values) reflected the use and fractionation of water by tea plants at different growth stages.

CONCLUSIONS

Considerable differences were found for hydrogen and oxygen isotope ratios according to leaf age, revealing complex isotopic fractionation mechanisms and possible interference factors. Leaf maturity effects should be considered, as they will influence the precision and accuracy of models when assigning the geographical origin, traceability and authentication of tea.