The suitability of rare earth elements for geographical traceability of tea leaves

Identification of lentils (Lens culinaris Medik) from Eglouvi (Lefkada, Greece) based on rare earth elements profile combined with chemometrics

An analytical approach has been developed to verify the authenticity of premium lentils originating from Eglouvi, Lefkada, Greece. The method relies on the digestion of samples followed by the analysis of their rare earth elements (REEs) content. Lentils originating from Eglouvi exhibit higher content in most REEs compared to lentils from other regions as well as distinct Sc/Y and Sc/Yb concentration ratios. Principal component analysis effectively segregates "Eglouvi" lentils into a distinct cluster. Soft Independent Modelling of Class Analogy (SIMCA) successfully models "Eglouvi" lentils. Significant enhancement in model specificity was achieved upon inclusion of Sc/Y and Sc/Yb concentration ratios as additional variables. The model is capable of detecting adulteration in blends of Eglouvi lentils, with a minimum rejection threshold of 4.6% w/w for Greek lentil adulterants and 6.0% w/w for imported lentil adulterants.

Recent advances in the authentication (geographical origins, varieties and aging time) of tangerine peel (Citri reticulatae pericarpium): A review

The consumption of tangerine peel (Citri reticulatae pericarpium, CRP) has been steadily increasing worldwide due to its proven health benefits and sensory characteristics. However, the price of CRP varies widely based on its origin, variety, and aging time, which has led many manufacturers to offer inferior products by exploiting the sensory similarity of CRP, seriously undermining consumers' interests. Therefore, it is essential to identify the authenticity of the CRP. In this study, the research progress on the authenticity of CRP from different origins, years and varieties over the past 10 years and the application and prospects of the main technologies and techniques were reviewed. The advantages and disadvantages of the commonly used methods were also summarized and compared. Mass spectrometry-based and spectroscopy-based techniques are the most commonly used methods for analyzing CRP authenticity. However, designing fast, non-destructive and green methods for identifying CRP authenticity would be the future trend.

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.

Comprehensive applications of metabolomics on tea science and technology: Opportunities, hurdles, and perspectives

With the development of metabolomics analytical techniques, relevant studies have increased in recent decades. The procedures of metabolomics analysis mainly include sample preparation, data acquisition and pre-processing, multivariate statistical analysis, as well as maker compounds' identification. In the present review, we summarized the published articles of tea metabolomics regarding different analytical tools, such as mass spectrometry, nuclear magnetic resonance, ultraviolet-visible spectrometry, and Fourier transform infrared spectrometry. The metabolite variation of fresh tea leaves with different treatments, such as biotic/abiotic stress, horticultural measures, and nutritional supplies was reviewed. Furthermore, the changes of chemical composition of processed tea samples under different processing technologies were also profiled. Since the identification of critical or marker metabolites is a complicated task, we also discussed the procedure of metabolite identification to clarify the importance of omics data analysis. The present review provides a workflow diagram for tea metabolomics research and also the perspectives of related studies in the future.

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.

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.

Traceability of the geographical origin of Siraitia grosvenorii based on multielement contents coupled with chemometric techniques

Siraitia grosvenorii (LHG) is widely used as a medicinal and edible material around the world. The objective of this study was to develop an effective method for the authentication of the geographical origin of LHG in its main producing area Guangxi, China, which is identified as Chinese Protected Designation of Origin product, against other producing regions in China. The content of 14 elements (K, Na, Ca, P, Mg, Al, B, Ba, Cu, Fe, Mn, Ni, Zn, and Sr) of 114 LHG samples was determined by inductively coupled plasma optical emission spectrometry. Multivariate analysis was then performed to classify the geographical origin of LHG samples. The contents of multielement display an obvious trend of clustering according to the geographical origin of LHG samples based on radar plot and principal component analysis. Finally, three supervised statistical techniques, including linear discriminant analysis (LDA), k-nearest neighbours (k-NN), and support vector machine (SVM), were applied to develop classification models. Finally, 40 unknown LHG samples were used to evaluate the predictive ability of model and discrimination rate of 100%, 97.5% and 100% were obtained for LDA, k-NN, and SVM, respectively. This study indicated that it is feasible to attribute unknown LHG samples to its geographical origin based on its multielement content coupled with chemometric techniques.

Conditions Affecting the Release of Heavy and Rare Earth Metals from the Mine Tailings Kola Subarctic

In the Kola Subarctic, a mining industry has developed, which is a source of environmental pollution with heavy metals. The objects of study were the tailings of three large mining enterprises in the region: apatite-nepheline, complex and loparite ores. The geotechnical characteristics were studied, and the granulometric composition of the samples was established. The main minerals that make up the material of ore dressing tailings have been determined. Using inductively coupled plasma mass spectrometry, the content of trace elements, in particular heavy metals and rare earth elements, has been established. The enrichment factor, the geoaccumulation indexes, the potential ecological risk index factor and the potential environmental hazard index have been calculated. Priority pollutants characteristics for specific objects have been identified. It is noted that the finely dispersed material of the tailings of loparite and complex ores is 1.5–3 times enriched in heavy and rare earth metals in comparison with the total material of the tailings. In laboratory conditions, experiments were carried out to simulate the process of interaction of dust particles with soil solutions containing different amounts of dissolved organic matter and at average seasonal temperatures. It was found that a decrease in the pH of the solution and an increase in the amount of organic carbon and temperature lead to the mobilization of heavy and rare earth metals from the tailings.

Origin traceability of peanut kernels based on multi-element fingerprinting combined with multivariate data analysis

BACKGROUND

Multi-elements have been widely used to identify the geographical origins of various agricultural products. The objective of this study was to investigate the feasibility of identifying the geographical origins of peanut kernels at different regional scales by using the multi-element fingerprinting technique. The concentrations of 20 elements [boron (B), magnesium (Mg), phosphorus (P), potassium (K), calcium (Ca), etc.] were determined in 135 peanut samples from Jilin Province, Jiangsu Province, and Shandong Province of China. Data obtained were processed by one-way analysis of variance (ANOVA), principal components analysis (PCA), k nearest neighbors (k-NN), linear discriminant analysis (LDA), and support vector machine (SVM).

RESULTS

Peanut kernels from different regions had their own element fingerprints. The k-NN, LDA, and SVM were all suitable to predict peanut kernels according to their grown provinces with the total correct classification rates of 91.2%, 91.1%, and 91.1%, respectively. While SVM was the best to identify different grown cities of peanut kernels with the prediction accuracy of 91.3%, compared to 72.2% and 78.3% for k-NN and LDA, respectively.

CONCLUSION

It was an effective method to identify producing areas of peanut kernels at different regional scales using multi-element fingerprinting combined with SVM to enhance regional capabilities for quality assurance and control. © 2020 Society of Chemical Industry.

Geographical Origin Authentication of Agri-Food Products: Α Review

This study is a systematic literature review of geographical origin authentication by elemental analytical techniques. Authentication and certification of geographic origin of agri-food products is a useful tool toward the protection of the quality for products. The aim of this work was to map the current state of research in the area of agricultural products and food, identifying emerging fields to the geographical origin of products. The article is divided in three parts. The first part of the article deals with the analytical techniques applied in the food authentication. Special mention is made to elemental analysis and multiple isotope ratio. The second section focuses on statistically published data concerning published research for geographical origin authentication for the period 2015-2019. Specific results are presented inter alia: number of articles according to the type of product, articles according to the type of the analytical techniques, and others. The third part contains characteristic results from articles that were published in the period 2015-2019, on certification of geographical origin on specific agricultural products.