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Rare earth element (REE) concentration patterns, while essential in geochemistry for tracing sample histories, have yet to be utilised entirely in food origin authentication. This research analysed 13 heavy metal(oid)s and REEs in Japanese edible seaweed Nori sheet samples (Neopyropia yezoensis), showing that the concentrations mirror the laver cultivation area's geological features (island arc-trench systems vs. continental crust). Thresholds for cadmium (0.5 ppm) and thorium (3.3 ppb) differentiate Japanese products from Korean imports. The slope of REE pattern, gadolinium anomalies, and yttrium/holmium ratios were also examined. However, nori samples significantly conveyed europium (Eu) anomalies, aligning with the mariculture hinterland's geochemistry. Both Japan's major seaweed mariculture areas, the Ariake Sea and the Seto Inland Sea, and Korean imports revealed distinct Eu anomalies (Eu/Eu* = 0.81-0.90, 0.58-0.66, 0.71-0.77), underscoring the potential of Eu anomalies as reliable seafood origin verifiers. This was also confirmed by literature values of Chinese samples., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Geographical traceability plays a crucial role in ensuring quality assurance, brand establishment, and the sustainable development of the crab industry. In this study, we examined the possibility of using gas chromatography-ion mobility spectrometry with multivariate statistical authenticity analysis to identify the origin of crabs from five sites downstream of the Yangtze River. Significant variations were observed in the levels of alcoholic flavor compounds in the hepatopancreas and muscles of crabs from different geographical locations, and a support vector machine exhibited discriminant ability with 100% accuracy. These flavor variations exhibited significant correlations with the types and concentrations of elements within the crabs, as well as with free amino acids. This study offers a practical approach for determining the geographical traceability of Chinese mitten crabs and elucidates the role of elements in flavor modulation, thereby providing innovative strategies to enhance the efficiency of crab farming., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Gentiana lutea rhizomes are known for their bitter tasting properties conferred by its unique biochemical content. They are currently of interest in phytotherapy, animal nutrition, food processing, cosmetic applications and agroecology. In this study, a NIRS, fluorescence and HS-SPME-GCMS dataset of 55 rhizomes from four different French mountains (Alpes, Jura, Massif Central and Pyrénées) was collected with the aim of assessing the variability of Gentiana lutea composition at different scales. The feasibility of data fusion strategies was demonstrated to be effective in distinguishing the geographical origin of Gentiana lutea roots over a wide area. The results suggest that data fusion methods have the potential to be more effective in the quality of separation of studied sites of Gentiana lutea roots than individual decisions obtained from individual analytical tools. However, to guarantee the geographical origin of Gentiana lutea roots within a single massif using these techniques, environmental factors must be considered., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. All authors agreed with the published version of the manuscript., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Metabolomics, the systematic study of metabolites, is dedicated to a comprehensive analysis of all aspects of plant-based food research and plays a pivotal role in the nutritional composition and quality control of plant-based foods. The diverse chemical compositions of plant-based foods lead to variations in sensory characteristics and nutritional value. This review explores the application of the metabolomics method to plant-based food origin tracing, cultivar identification, and processing methods. It also addresses the challenges encountered and outlines future directions. Typically, when combined with other omics or techniques, synergistic and complementary information is uncovered, enhancing the classification and prediction capabilities of models. Future research should aim to evaluate all factors affecting food quality comprehensively, and this necessitates advanced research into influence mechanisms, metabolic pathways, and gene expression., Competing Interests: Declaration of competing interest The authors have no conflicts of interest, either real or potential associated with this work., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Ophiocordyceps sinensis (OS), known as "soft gold", played an important role in local economic development. OS from different producing areas was difficult to be discriminated by the appearance. Nagqu OS, a distinguished and safeguarded geographical indication product, commands a premium price in market. The real claim of OS geographical origins is urgently required. Here, 81 OS samples were collected from Tibetan Plateau in China to explore markers for tracing origins. OS from Xigazê can be distinguished by dark color of head of caterpillar. Then 57 samples, a fully representative training-sample set, were used to set up OPLS-DA models by nontargeted metabolomics from UPLC-QTOF-MS. Certain markers were successfully identified and validation using 21 blind test samples confirmed that the markers can trace the geographical origin of OS, especially Nagqu samples. It was affirmed that UPLC-QTOF-MS-based untargeted metabolomics coupled with OPLS-DA was a reliable strategy to trace the geographical origins of OS., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

A comprehensive study of 603 roasted arabica coffee samples using NMR fingerprinting and multivariate data analysis was performed to differentiate coffee samples according to their geographical origin and cultivation method. Both lipophilic and hydrophilic coffee metabolites were recorded using 1 H NMR spectroscopy, and principal component analysis followed by linear discriminant analysis (PCA-LDA) was applied. Coffee samples were fist differentiated according to their continents of origin followed by discrimination of coffee samples from Brazil, Ethiopia, and Colombia from coffee samples originating from another continent. Discrimination of coffee samples according to their continent of origin and additional assignment to the countries Brazil and Ethiopia were successful. However, an unambiguous separation of Colombian coffee samples from coffee samples of another continent (other than South America) was not possible. Also, differentiation of organically and conventionally produced coffee samples by using 1 H NMR and PCA-LDA was not achieved., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Ginger (Zingiber officinale Roscoe) is a high-value food and herb worldwide. The quality of ginger is often related to its production regions. In this study, stable isotopes, multiple elements, and metabolites were investigated together to realize ginger origin traceability. Chemometrics showed that ginger samples could be preliminarily separated, and 4 isotopes (δ 13 C, δ 2 H, δ 18 O, and δ 34 S), 12 mineral elements (Rb, Mn, V, Na, Sm, K, Ga, Cd, Al, Ti, Mg, and Li), 1 bioelement (%C), and 143 metabolites were the most important variables for discrimination. Furthermore, three algorithms were introduced, and the fused dataset based on VIP features led to the highest accuracies for origin classification, with predictive rates of 98% for K-nearest neighbor and 100% for support vector machine and random forest. The results demonstrated that isotopic, elemental, and metabolic fingerprints were useful indicators for the geographical origins of Chinese ginger., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Kimchi has been designated as one of the world's five healthiest foods, and it is a traditional Korean fermented food. The purpose of this study was to investigate whether the origin of Kimchi can be discriminated against by using inorganic elements to develop a more accurate method. The OPLS-DA showed that the R 2 and Q 2 values were 0.908 and 0.81, a high-quality model. We selected 24 elements ( 133 Cs, 238 U, 88 Sr, K, 157 Gd, Na, Mg, 139 La, P, 141 Pr, 72 Ge, 146 Nd, 147 Sm, 153 Eu, 55 Mn, 165 Ho, 163 Dy, 166 Er, Fe, 172 Yb, 169 Tm, 185 Re, 175 Lu, and 118 Sn) with VIP 1 or higher in the OPLS-DA model. In ROC, the selected elements had an accuracy of 100%. The heatmap confirmed the contents of rare earth elements (REEs) in Korean and Chinese Kimchi, the accuracy of distinguishing classification in CDA is 100%. Such results will help to distinguish the origin of agricultural products through inorganic analysis., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Tea (Camellia sinensis) fraud has been frequently identified and involves tampering with the labelling of inferior products or without geographical origin certification and even mixing them with superior quality teas to mask an adulteration. Consequently, economic losses and health damage to consumers are observed. Thus, a Chemometrics-assisted Color Histogram-based Analytical System (CACHAS) was employed a simple, cost-effective, reliable, and green analytical tool to screen the quality of teas. Data-Driven Soft Independent Modeling of Class Analogy was used to authenticate their geographical origin and category simultaneously, recognizing correctly all Argentinean and Sri Lankan black teas and Argentinean green teas. For the determination of moisture, total polyphenols, and caffeine, Partial Least Squares obtained satisfactory predictive abilities, with values of root mean squared error of prediction (RMSEP) of 0.50, 0.788, and 0.25 mg kg -1 , r pred of 0.81, 0.902, and 0.81, and relative error of prediction (REP) of 6.38, 9.031, and 14.58%., respectively. CACHAS proved to be a good alternative tool for environmentally-friendly non-destructive chemical analysis., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The edible values of P. cocos from different origins vary significantly, therefore, it is important to investigate the traceability of geographical regions and identify the geographical biomarkers of P. cocos. The metabolites of P. cocos of the different geographical origins were assessed using liquid chromatography tandem-mass spectrometry, principal component analysis and orthogonal partial least-squares discriminant analysis (OPLS-DA). The OPLS-DA could clearly discriminate the metabolites of P. cocos from the three cultivation regions (YN, Yunnan; AH, Anhui; JZ, Hunan). Finally, three carbohydrates, four amino acids, and four triterpenoids were selected as biomarkers for P. cocos origin tracing. Correlation matrix analysis revealed that the contents of biomarkers were closely related to geographical origin. Altitude, temperature, and soil fertility were the main factors responsible for the differences in biomarker profiles in P. cocos. The metabolomics approach provides an effective strategy for tracing and identifying the biomarkers of P. cocos from different geographical origins., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Compound-specific stable isotope analysis (CSIA) of food products is a relatively new and novel technique used to authenticate food and detect adulteration. This paper provides a review of recent on-line and off-line CSIA applications of plant and animal origin foods, essential oils and plant extracts. Different food discrimination techniques, applications, scope, and recent studies are discussed. CSIA δ 13 C values are widely used to verify geographical origin, organic production, and adulteration. The δ 15 N values of individual amino acids and nitrate fertilizers have proven effective to authenticate organic foods, while δ 2 H and δ 18 O values are useful to link food products with local precipitation for geographical origin verification. Most CSIA techniques focus on fatty acids, amino acids, monosaccharides, disaccharides, organic acids, and volatile compounds enabling more selective and detailed origin and authentication information than bulk isotope analyses.. In conclusion, CSIA has a stronger analytical advantage for the authentication of food compared to bulk stable isotope analysis, especially for honey, beverages, essential oils, and processed foods., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The identification of geographical origin is an important factor in assessing the quality of aromatic and medicinal seeds such as Black Mahlab (Monechma ciliatum). However, at present, there are no studies concerning Black Mahlab Seeds (BMSs). To identify the geographical origin of BMSs, we have used gas chromatography-mass spectrometry (GC-MS) and Fourier transform infrared spectroscopy (FT-NIR) combined with chemometrics. Chemometrics analysis showed that FT-NIR and GC-MS can be used to discriminate the geographical origin of BMSs. FT-NIR coupled with the partial least squares regression (PLSR) was applied to develop the calibration models. The calibration models had a coefficient of determination (R c 2 ) of 0.82 for coumarin and 0.81 for methyl salicylate. The prediction model (R p 2 ) values ranged from 0.83 for coumarin to 0.77 for methyl salicylate. Overall, the chemometrics presented correct classification, and PLSR accurately predicted the volatiles, with an RMSEP range of 0.9 to 0.16 for the two volatiles targeted., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Ltd.)

Origin verification of high-value saffron is essential for fair trade and to protect consumers' interests and rights. A traceability method using elemental content (% C and % N) and stable isotopes (δ 13 C, δ 2 H, δ 18 O, and δ 15 N) combined with chemometrics was developed to discriminate saffron from Iran and China and classify major domestic production areas in China. Results showed that Iranian samples had lower % C and % N contents but higher δ 13 C values than Chinese origin saffron, with δ 13 C acting as an important variable for origin discrimination. Moreover, δ 2 H and δ 13 C isotopes were found to be important variables to classify Chinese regional saffron origin. Two supervised pattern recognition models (PLS-DA) developed to classify Iranian and Chinese saffron, and regional Chinese saffron had a discrimination accuracy of 85.0 % and 80.2 %, respectively. These models provide the basis for a new regulatory inspection procedure to verify saffron origin and label claims, minimizing fraudulent mislabeling and adding value to saffron from specific regions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Coix seed (CS, Coix lachryma-jobi L. var. ma-yuen (Roman.) Stapf) has rich nutrients, including starch, protein and oil. The geographical origin with a protected geographical indication and high levels of nutrient contents ensures the quality of CS, but non-destructive and rapid methods for predicting these quality indicators remain to be explored. This paper proposed hyperspectral imaging (HSI) assisted with the integrated deep learning models of attention mechanism (AM), convolutional neural networks, and long short-term memory. The method achieved the effective wavelengths selection, the highest prediction accuracy for production region discrimination and the lowest mean absolute error and root mean squared error for nutrient contents prediction. Moreover, the wavelengths selected via the AM model were explicable and reliable for predicting the geographical origins and nutrient contents. The proposed combination of HSI with integrated deep learning models has great potential in the quality evaluation of CS., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Soy sauce is one of the significant seasonings in Asia but is often mislabeled in ingredients or substituted with geographical information. With no adequate methods to distinguish the bean sources and the origins of soy sauce, our study designed a seamless headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME/GC-MS) for analyzing unique volatile components of different soy sauces. Over 400 volatile flavor compounds were identified and the assistance of chemometric analysis successfully discriminated different bean sources (black bean and soybean) and producing regions (Taiwan and Japan). The chemometric models can also perfectly evaluate real samples together with adulterated samples. In brief, these soy sauce volatile signatures can solve the problem of authentication and assist the whole industry in preventing adulteration and producing countries' counterfeit., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Laser-induced breakdown spectroscopy (LIBS) and near-infrared (NIR) spectroscopy were combined to enhance discrimination of soybean paste samples according to geographical origin. Since element and organic component compositions of soybean pastes depend on soybean cultivation areas and fermentation conditions, utilization of two complementary spectroscopic signatures would be synergetic for the discrimination. When the areas of C (A C ) and Ca (A Ca ) peaks in the LIBS spectra were used as the inputs for linear discriminant analysis, the accuracy was 95.4%. The accuracy became 92.1%, when the principal component (PC) scores obtained by principal component analysis of the NIR spectra were employed. To enhance NIR discrimination, two-trace two-dimensional (2T2D) correlation analysis was adopted to recognize minute spectral differences. With using the 1st/2nd PC scores of 2T2D slice spectra, accuracy increased to 95.0%. When the ratios of A Ca /A C and the 2nd PC scores of the samples were combined together, the accuracy improved to 99.6%., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The authentication of geographical origin of food is important using stable isotope analysis. However, the isotopic databank is still short of comprehensive. The isoscapes model based on environmental similarity is used for the first time to predict the geospatial distribution of δ 13 C, δ 2 H and δ 18 O in Chinese rice in 2017 and 2018. 794 rice samples in 2017 were used to build isoscapes model. Independent verification shows that the predicted isotope distribution from this new approach is of high accuracy, with a root mean square error (RMSE) of 0.51 ‰, 7.09 ‰ and 2.06 ‰ for δ 13 C, δ 2 H and δ 18 O values for 2017, respectively. Our results indicate that it is possible to predict the spatial distribution of stable isotopes in rice using an isoscapes model based on environmental similarity. This novel strategy can enrich and complement a stable isotope reference database for rice origin identification at regional scale., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Songjiang CPB rice (cultivated by a 'combination of planting and breeding') and Chongming NCFP rice (cultivated by using 'no chemical fertilizers and pesticides') are two high quality special rice products developed for Shanghai urban agriculture. Protecting these products from geographical origin mislabeling or cultivation method fraud are very important. To verify the origin of Songjiang and Chongming rice and discriminate their cultivation methods (CPB or N (non) CPB, NCFP or chemical fertilizers and pesticides (CFP)), NIR and IRMS methods combined with chemometrics were developed. Results showed complete separation of Songjiang and Chongming rice from other geographic origins using NIR combined with PLSDA and LVQNN; CPB and NCPB Songjiang rice could be completely identified using NIR or IRMS, while the optimal identification accuracy rate of NCFP from CFP in Chongming rice was 87.5%. It provided a rapid and robust method to identify the origin and cultivation methods of Shanghai special rice., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

This study aimed to determine whether Trachinotus ovatus and Pampus argenteus could be differentiated by multi-element composition or stable isotope ratio analysis of δ 13 C and δ 15 N. The multi-element analysis values of a total of 60 Pampus argenteus samples from three sites and 60 Trachinotus ovatus samples from four sites around China were determined, and the other 60 samples of Pampus argenteus and 51 samples of Trachinotus ovatus were tested by principal component analysis (PCA) to estimate the accuracy of origin identification. The results showed that the cross-validation accuracy rate is 92.2% for the Pampus argenteus and 98.3% for the Trachinotus ovatus. Stable isotope analysis of δ 13 C and δ 15 N also can distinguish Trachinotus ovatus from different geographical origins. These results showed that the usefulness of multi-element and stable isotope analysis as indicators for authenticating the geographical origin of two pomfrets in China., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Identifying geographical origins of red wines made in specific regions is of significance since the false claim of geographical origins has been frequently exposed in China's wine industry. In this work, an untargeted metabolomic approach based on UPLC-QTOF-MS was established to discriminate geographical origins of Chinese red wines. The principal component analysis (PCA) showed significant differences between wine samples from three famous geographical origins in China. The metabolites contributing to the differentiation were screened by orthogonal partial least squares-discriminant analysis (OPLS-DA) with pairwise modeling. 40 and 46 differential metabolites in positive and negative ionization modes were putatively identified as chemical markers. Furthermore, heatmap visualization and OPLS-DA models were constructed based on these identified markers and external verification wine samples from different regions were successfully discriminated, with recognition rate up to 96.7%. This study indicated that UPLC-QTOF-MS-based untargeted metabolomics has great potential for the geographical origin traceability of Chinese red wines., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Geographical origin discrimination of agro-products is essential to guarantee food safety and fair trade. Garlic samples cultivated in six provinces or major production regions in China were characterized for stable isotopes (δ 13 C, δ 2 H, δ 18 O, δ 15 N, and δ 34 S), bioelemental contents (% C, % N and % S), and sulfur-containing compounds (8 organosulfur components and 2 amino acids). Results showed that many of the 18 analyzed garlic variables had significant differences among production regions. Some sulfur-containing compounds found in garlic from different provinces had a strong correlation with sulfur isotopes, suggesting garlic sulfur isotopes were also affected by geographical origin. Two supervised pattern recognition models (PLS-DA and k-NN) were developed using stable isotopes, elemental contents, and sulfur-containing compounds, and had a discrimination accuracy of 93.4 % and 87.8 %, respectively. Chemometric classification models using multi-isotopes, elements and sulfur-containing compounds provides a useful method to authenticate Chinese garlic origins., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The aim of this work was to address whether the growing location of tomato could generate a different (poly)phenol profile able to affect both in vivo absorption and (poly)phenol metabolite pattern upon tomato consumption. uHPLC-MS n analyses allowed to obtain a detailed (poly)phenol profile of tomatoes from two locations in Spain, quantifying 57 (poly)phenolic compounds. However, local and non-local tomatoes showed a different concentration of their native (poly)phenols, which could be attributed to diverse cultivation origin. Rat serum was analysed after an acute tomato feeding. Seven phenolic metabolites were quantified through uHPLC-MS n . Pharmacokinetic parameters were further evaluated, revealing different serum concentrations of (poly)phenolic metabolites between tomatoes. The maximum peak serum concentrations, reached mainly after 2 h after ingestion, led to suppose that serum metabolites were mostly derived from absorption in the upper gastrointestinal tract. The growing location of tomatoes affected both the content of native (poly)phenols and their in vivo absorption., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The complete medium used for mushroom cultivation is important for reliable crop production. We aimed to identify how the origin of Agaricus bisporus grown in Korea was affected by complete media produced in different geographical regions using stable isotope ratios (SIRs). We found that the SIR features of A. bisporus significantly depended on the complete media origin used; in particular, it appeared the high δ 34 S in the Chinese complete medium, low δ 34 S in the Dutch complete medium, and high δ 15 N in the Korean complete medium (P < 0.05). The support vector machine method appeared better geo-origin classification of A. bisporus by the complete media compared to a linear discriminant analysis. A large-scale study should be conducted to establish a reliable origin identification model for A. bisporus grown in complete media to improve the global mushroom marketplace., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Japonica rice is widely planted in different regions of China. Rice of different geographical origins may have substantially different economic values. In this study, An untargeted metabolomics based approach using headspace solid-phase microextraction coupled to gas chromatography-mass spectrometry (HS-SPME/GC-MS) was applied to distinguish 27 japonica rice varieties originated from South, Northern and Northeastern China in raw and cooked form, respectively. Orthogonal partial least-squares discriminant analysis (OPLS-DA) models exhibited good geographic discrimination. Sixteen and twenty-two volatiles were selected as the discriminant markers in raw and cooked rice, respectively. However, only hexanal, 3,5-octadien-2-one and 2-butyl-2-octenal were selected both in raw and cooked rice. Markers in raw rice mainly involved in terpenes, lipoxygenases, indole, and shikimate and benzoic acid pathways. Markers in cooked rice were mainly derived from lipid oxidation. The results provided a deeper understanding of volatiles variation of rice in China from different geographic origins., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Headspace solid-phase microextraction (HS-SPME) coupled with mass spectrometry-based electronic nose (MS-eNose), in combination with multivariate statistical analysis was used as untargeted method for the rapid authentication of 100% Italian durum wheat pasta. Among the tested classification models, i.e. PCA-LDA, PLS-DA and SVMc, SVMc provided the highest accuracy results in both calibration (90%) and validation (92%) processes. Potential markers discriminating pasta samples were identified by HS-SPME/GC-MS analysis. Specifically, the content of a pattern of 8 out of 59 volatile organic compounds (VOCs) was significantly different between samples of 100% Italian durum wheat pasta and pasta produced with durum wheat of different origins, most of which were related to different lipidic oxidation in the two classes of pasta. The proposed MS-eNose method is a rapid and reliable tool to be used for authenticating Italian pasta useful to promote its typicity and preserving consumers from fraudulent practices., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Geographical traceability of marine bivalves is becoming increasingly important to assure their quality and to defend the interest of consumers and producers. This study verifies the neodymium isotopic ratio ( 143 Nd/ 144 Nd) in Ruditapes philippinarum shells as a tracer of the geographic origin, based on the geochemical aspect that 143 Nd/ 144 Nd of their habitats strongly depends on the geology of its catchment areas. The 143 Nd/ 144 Nd ratios of clam shells from the Japanese and Chinese coastal areas displayed a heterogeneous pattern from local to international scales, reflecting the geological age of the catchment area. The blind test suggested that a part of Manila clam was sold with mislabeling in the Japanese market, demonstrating the high potential of 143 Nd/ 144 Nd to unmask the fraud labeling in a food market. Our findings emphasize the potential of 143 Nd/ 144 Nd as a tracer for the geographical origin of marine bivalves, and also as a strong deterrent against mislabeling., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The geographical classification and authentication of strawberries were attempted using discriminant and class-modelling methods applied to stable isotopes of light elements and elemental composition. The work involved creating a database of 92 authentic Slovenian strawberry samples and 32 imported samples. All samples were harvested between 2018 and 2020. A good geographical classification of Slovenian and non-Slovenian strawberries was obtained despite different production years using discriminant approaches. However, for verifying compliance with a given specification (geographical indications), a class-modelling approach was used to build an unbiased verification model. Class models generated by data-driven soft independent modelling of class analogy (DD-SIMCA) had high sensitivity (96% to 97%) and good specificity (81% to 91%) on a yearly basis, while a more generalised model combining total yearly data gave a lower specificity (63%). Of the 33 commercially available samples (test samples) with declared Slovenian origin, 39% were from outside of Slovenia., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

According to the last report from the European Union (EU) Food Fraud Network, olive oil tops the list of the most notified products. Current EU regulation states geographical origin as mandatory for virgin olive oils, even though an official analytical method is still lacking. Verifying the compliance of label-declared EU oils should be addressed with the highest priority level. Hence, the present work tackles this issue by developing a classification model (PLS-DA) based on the sesquiterpene hydrocarbon fingerprint of 400 samples obtained by HS-SPME-GC-MS to discriminate between EU and non-EU olive oils, obtaining an 89.6% of correct classification for the external validation (three iterations), with a sensitivity of 0.81 and a specificity of 0.95. Subsequently, multi-class discrimination models for EU and non-EU countries were developed and externally validated (with three different validation sets) with successful results (average of 92.2% of correct classification for EU and 96.0% for non-EU countries)., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In this study, we investigated the possibility of the geographical origin discrimination between Japanese and Mexican kabocha pumpkin using δ 13 C and δ 18 O in lyophilized raw flesh. Kabocha harvested in Hokkaido, the major kabocha production area in Japan, could be discriminated against not only that grown in Mexico but also that in New Zealand. However, seasoning after cooking or processing affected the δ 13 C and the δ 18 O values. Crude fiber extraction eliminated the effect of seasonings and enabled the adoption of the δ 13 C and δ 18 O values in crude fiber for the geographical origin verification of kabocha even after cooking and processing. The usage of δ 13 C and the δ 18 O in crude fiber would extend the application possibilities of stable isotope analysis in the geographical origin determination of various cooked and processed vegetables and fruits as well as raw materials., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Determining the geographical origin of wines is a major challenge in wine authentication, but little information is available regarding non-parametric statistical approaches for wines. In this study, we collected 33 domestic Chardonnay wines vinified on a small scale from grapes cultivated in Japan, and 42 Chardonnay wines imported from 8 countries, for oxygen stable isotope and multi-element analyses. Non-metric multidimensional scaling (NMDS), kernel principal component analysis (KPCA) and principal component analysis (PCA) were applied to the oxygen stable isotopic compositions (δ 18 O) and the concentrations of 18 elements in the wines to compare the extractions by parametric and non-parametric methods. The non-parametric methods, NMDS and KPCA, separated domestic from imported Chardonnay wines better than the parametric method, PCA. Of 19 variables, 18 were important for geographical discrimination, with the δ 18 O value being the most significant in all statistic methods. Non-parametric multivariate analyses will help discriminate domestic from imported Chardonnay wines., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Octopus play an increasingly important role in ocean ecosystems and global fisheries, yet techniques for authenticating provenance are sorely lacking. For the first time, we investigate whether chemical profiling can distinguish geographical origins of octopus on international and domestic scales. Our samples consisted of wild-caught octopus from south-east Asia and southern Australia, regions with high seafood trade. We used a novel combination of stable carbon (δ 13 C) and oxygen (δ 18 O) isotope analyses (Isotope-Ratio Mass Spectrometry) of internal calcified structures called statoliths, with elemental analyses (X-Ray Fluorescence using Itrax) of soft-tissue. We found that multivariate profiles exhibited distinctive regional signatures, even across species, with high classification success (∼95%) back to region of origin. This study validates isotopic and multi-elemental profiling as an effective provenance tool for octopus, which could be used to support transparency and accountability of seafood supply chains and thus encourage sustainable use of ocean resources., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Crude palm oil (CPO) is extracted from the mesocarp of oil palm (Elaeis guineensis) fruits. CPO is widely consumed in many African countries. Due to its high provitamin A carotenoid content, it is also widely used in programmes designed to prevent vitamin A deficiency. Elaeis guineensis occurs naturally across a wide geographical range in Africa. We investigated the carotene, tocochromanol (vitamin E) and fatty acid composition of a large set of genotypes representative of this genetic and geographic diversity. We found considerable intraspecific diversity in most lipid traits. Populations from Côte d'Ivoire were distinguished from other origins by their very low palmitate content and high tocochromanol content. Genotypes from Benin, Côte d'Ivoire and Nigeria were characterized by high carotene contents. Finally, hybrids of crosses between genotypes from Côte d'Ivoire and Nigeria produce CPO with exceptionally high provitamin A and vitamin E contents together with low palmitate content., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Quadrupole inductively coupled plasma mass spectrometry (Q-ICP-MS) and direct mercury analysis were used to determine the elemental composition of 180 transformed (salt-ripened) anchovies from three different fishing areas before and after packaging. To this purpose, four decision trees-based algorithms, corresponding to C5.0, classification and regression trees (CART), chi-squareautomatic interaction detection (CHAID), and quick unbiased efficient statistical tree (QUEST) were applied to the elemental datasets to find the most accurate data mining procedure to achieve the ultimate goal of fish origin prediction. Classification rules generated by the trained CHAID model optimally identified unlabelled testing bulk anchovies (93.9% F-score) by using just 6 out of 52 elements (As, K, P, Cd, Li, and Sr). The finished packaged product was better modelled by the QUEST algorithm which recognised the origin of anchovies with F-score of 97.7%, considering the information carried out by 5 elements (B, As, K. Cd, and Pd). Results obtained suggested that the traceability system in the fishery sector may be supported by simplified machine learning techniques applied to a limited but effective number of inorganic predictors of origin., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

The measurement and analysis of fifty-two elements by quadrupole inductively coupled plasma mass spectrometry (Q-ICP-MS) and direct mercury analysis were applied to origin discrimination of Italian traditional cuttlefish (Chioggia, Venice lagoon) from Mediterranean and Atlantic samples. A total 68 specimens were analyzed in triplicates to generate 204 mass spectra profiles which were statistically processed by different chemometric techniques. Loading weights from principal component analysis as input for linear discriminant analysis (LW-LDA), stepwise-LDA (S-LDA) and variable influence of projection-partial least square discriminant analysis (VIP-PLS-DA) were used to classify samples while retaining the lowest possible number of key variables. VIP-PLS-DA was found to be the best variable selection-discriminant tool combo since the selected Na-Co-B-K-Cd-V-U-Rb-Ni-Ba-Cu-As-Sr-Mn-Mo-Li-Ca-Mg-Se-Bi-Cs-P-Y elemental pattern allowed the samples to be classified with 100% sensitivity, specificity and accuracy., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Consumers have an increasing concern in the provenance of the foods they consume. Methods for discriminating geographical origins and species of cattle bone product are essential to provide veracious information for consumers and avoid the adulteration and inferior problems. In this study, 50 element contents of a total of 143 cattle bone samples from eight producing regions in China, were determined by inductively coupled plasma mass spectrometry (ICP-MS). Element contents were used as chemical indicators to discriminate species and geographical origins of cattle bone samples by multivariate data analysis, including hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). The K-fold cross validation accuracy for species and geographical origin discrimination was 99.3% and 94.5%, respectively. This study reveals that multi-element analysis accompanied by LDA is an effective technique to ensure the information reliability of cattle bone samples, and this strategy may be a potential tool for standardizing market., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

The identification of geographical origin is an important factor in evaluating the authenticity of honey. However, at present, there are few studies concerning the honey of Apis cerana Fabricius (A. cerana, Asiatic honeybee). To identify geographical origin, we used two common methods (multi-physicochemical parameters and phenolic chromatographic fingerprints) but achieved only poor identification. To compensate for this shortcoming, we established an ICP-MS-based ionomics method using 18 elements in 27 A. cerana honey samples from three different areas in Shaanxi Province, China. Multivariate analysis showed that significant differences in contents can be used to discriminate the geographical origin of A. cerana honey. The method was further validated using an independent test set of 11 samples with 90.91% accuracy, demonstrating its potential for the identification and prediction of the geographical origin of honey., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Honey is widely consumed by humans, due to its multiple applications as a food constituent and its therapeutic effects. This study reports on the discrimination of honey products from different geographical and botanical sources, as well as honey products containing distinct forms of syrup used in honey adulteration. Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS)-based proteomic analysis combined with chemometrics was successfully applied in identifying characteristic proteins that can be used as biomarkers of the original source of honey. Honey samples from different producing regions (Tainan, Changhua, and Taichung), countries (Taiwan and Thailand), and distinct botanical sources (longan and litchi) were clearly distinguished by the developed orthogonal projections to latent structures discriminant analysis (OPLS-DA) model with good fitness and prediction ability. Furthermore, we successfully discriminated the adulteration of honey with syrup in different proportions (even with honey content as low as 20%) with this proteomic SWATH-MS platform., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Authentication of geographical origin is essential to the food safety of refined sugar. This study aimed to determine the geographical origin traceability and authenticity of refined sugar in China. Ultra performance liquid chromatography-quadrupole time-of-flight Mass Spectrometry (UPLC-QTof-MS), instead of conventional stable isotope ratio mass spectrometer (IRMS), was used to detect the mass fragment ratios (Rδ-sucrose and Rδ-glucose) of refined sugar. These ratios could reflect the cultivation practice and environmental conditions. A total of 108 batches of samples were collected from six regions in China, and additional 72 samples were verified with support vector machines (SVM) model, in order to evaluate the accuracy of origin identification and composition prediction. Our results showed that 83.3% of the refined sugar was correctly classified based on the geographical region of origin under different environmental conditions. These findings indicate that the specified mass fragment ratio may be a promising approach for assessing the traceability and authenticity of refined sugar., (Copyright © 2020. Published by Elsevier Ltd.)

Shanghai city has encountered possible food fraud regarding the geographical mislabeling of vegetables for economic gain. A combination of δ 13 C, δ 15 N, δ 2 H and δ 18 O 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., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

A green ASE (accelerated solvent extraction) with a shorter UHPLC (ultra-high performance liquid chromatography) method was developed for simultaneous determination of phenolics. High extract yield (130 mg/g) was observed for water at 100 °C in a short time of 19.5 min using 33.5 mL solvent whereas, UHPLC showed more phenolics of GA (gallic acid), QT (quercetin), LT (luteolin) in ACE (acetone) and RT (rutin) in EtOH (ethanol) solvent at 60 °C. The binary solvent system of ACE: EtOH (1:1) at 60 °C was optimized as extraction set. UHPLC runtime was 3 min with retention times of (min); 0.63 (GA), 0.97 (RT), 2.00 (QT) and 2.41 (LT). Average for phenolics (ppm) was, QT (10.91) > GA (7.33) > LT (4.10) > RT (3.90) whereas, Spanish whole green olive (SP2) showed more phenolics (20.72). Individual phenolic was, GA (47.06) > RT (26.21) > QT (19.34) > LT (6.18). Multivariate, K-mean and PCA (principal component analysis) for solvent*extract yield showed significant correlation and temperature showed no significant correlation for phenolics., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Jackfruits are nutritionally rich fruit crop indigenous to the humid tropics, known by their place of origin. In the present study, using multielemental profiling of fruit samples, we demonstrated the discrimination of different jack fruit germplasm based on their geographical origin in India. The concentration of 24 elements in soil and fruit were determined by inductively coupled plasma mass spectrometry (ICP-MS). ANOVA revealed the significant difference of these 24 elements amongst the geographical locations both in soils and fruits. The correlation between soil and fruit ionome indicated the major influence of germplasm and other locational factors on the acquisition and accumulation of fruit multi elemental characteristics with minimal contribution of soil elements. Among the multivariate analysis tools, linear discriminant analysis (LDA) of fruit multi elemental fingerprint was found to be an efficient tool for discrimination of geographical origin of Indian jackfruits., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Origin verification of 240 French wines from four regions of France was undertaken using isotope and elemental analyses. Our aim was to identify and differentiate the geographical origin of these red wines, and more importantly, to build a classification tool that can be used to verify geographic origin of French red wines using machine learning models. Multivariate analyses of the isotopic and elemental data revealed that it is possible to determine the geographical origin of French wines with a high level of confidence for most regions analyzed in this study. The wine verification accuracy of four French wine producing regions of Bordeaux, Burgundy, Languedoc-Roussillon and Rhone using an Artificial Neural Network (ANN) method was 98.2%. The results also show that ANN is more suitable than Discriminant Analysis for this verification purpose. The most important variables for French wine regional traceability were Mg, Mn, Na, Sr, Ti and Rb., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Beef is a common staple food in many countries, and there is a growing concern over misinformation of beef products, such as false claims of origin, species and production methods. In this study, we used a mass spectrometry-based metabolomics approach to study the metabolite profiles of beef samples purchased from local retailers in Hong Kong. Using multivariate analysis, beef samples from different a) geographical origins, namely the United States (US), Japan and Australia, and b) feeding regimes could be differentiated. We identified twenty-four metabolites to distinguish beef samples from different countries, ten metabolites to identify Angus beef samples from others and seven metabolites to discriminate Australian beef produced by the organic farming from that produced using other farming modes. Based on results of this study, it is concluded that metabolomics provides an efficient strategy for tracing and authenticating beef products to ensure their quality and to protect consumer rights., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020. Published by Elsevier Ltd.)

The trace and rare earth elements content of 93 honeys of different botanical type and origin have been studied through ICP-MS. Discriminant Analysis (DA) was successful for botanical type and geographical origin classification while Cluster Analysis (CA) was successful only for botanical type. Through Probabilistic Neural Network (PNN) analysis, 85.3% were correctly classified by the network according to their geographical origin and 73.3% according to their organic characterization. A Partial Least Squares (PLS) model was constructed, giving a prediction accuracy of more than 95%. Information obtained using Rare Earths (Y, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu) and trace elements (Li, Mg, Mn, Ni, Co, Cu, Sr, Ba, Pb) via chemometric evaluation facilitated classification of honey samples., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Thirty one samples from different macroalgae species have been studied to determine the influence of several parameters such as the harvesting season, the geographical origin, the species or a pretreatment procedure on their volatile composition. A Multiple Head Space Sorptive Extraction methodology coupled to Gas Chromatography with Mass Spectrometry Detection (MHSSE-GC-MS) has been used to analyze 44 volatile compounds that can be found in the different samples. Of all the factors, the collection season proved to be the most influential, followed by origin with significantly lower volatile compounds concentrations found in the samples collected in spring and in southern Spain. A Principal Component Analysis showed that beta ionone, benzaldehyde, 6-methyl-5-hepten-2-one, together with some acids were the most strongly affected by the season, with highest values in those samples that had been collected in the autumn. On the other hand, the pretreatment (raw, salting or dehydration) proved to have a low influence., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Rice is one of the most important cereals for human nutrition and is a basic staple food for half of the global population. The assessment of rice geographical origins in terms of its authenticity is of great interest to protect consumers from misleading information and fraud. In the present study, a head space gas chromatography mass spectrometry (HS-GC-MS) strategy for characterising volatile organic compounds (VOCs) profiles to distinguish rice samples from China, India and Vietnam is described. Partial Least Square Discriminant Analysis (PLS-DA) model exhibited a good discrimination (R 2  = 0.98182, Q 2  = 0.9722, and Accuracy = 1.0) for rice samples from China, India and Vietnam. Moreover, Data-Driven Soft Independent Modelling of Class Analogy (DD-SIMCA) and K-nearest neighbors shown good specificity 100% and accuracy 100% in identifying the origin of samples. The present study established VOC fingerprinting as a highly efficient approach to identify the geographical origin of rice., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Celery (Apium graveolens L. var dulce) is a widely cultivated vegetable which is popularly consumed due to its nutrient content and contains bioactive metabolites with positive effects on human physiology. In this study, 1 H NMR spectroscopy coupled with multivariate statistical analyses was used to distinguish celery stem and leaf samples from different geographical origins. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were employed to investigate the differences between celery extracts from three geographical origins: Australia, Taiwan and China. Sugars, amino acids and organic acids were found to contribute significantly to the differentiation between origins, with mannitol identified as an important discriminating metabolite. It was demonstrated that NMR-based metabolomics is an effective approach for establishing reliable metabolomic fingerprints and profiles, enabling the identification of metabolite biomarkers for the possible discrimination of geographical origin., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The assessment of durum wheat geographical origin is an important and emerging challenge, due to the added value that a claim of origin could provide to the raw material itself, and subsequently to the final products (i.e. pasta). Up to now, the typical approach presented in literature is the evaluation of different isotopic ratios of the elements, but other techniques could represent an interesting and even more powerful alternative. In this study, using a non-targeted high-resolution mass spectrometry approach, a selection of chemical markers related to the geographical origin of durum wheat was provided. Samples of the 2016 wheat campaign were used to set up the model and to select the markers, while samples from the 2018 campaign were used for model and markers validation. Including in the samples set different geographies across different continents, a discrimination through Italian, European and Not European samples is now possible., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Some minor constituents of honey samples were determined through a fluorometric-chemical characterization method and related multifactorially with their antibacterial activity against Staphylococcus aureus and Pseudomonas aeruginosa and with their geographical origin. Rotated principal component analysis identified five significant components in honey: three related to antibacterial activity and linked to phenolic compounds; Maillard products; proteins; the concentration of H 2 O 2 at 3 and 24 h of incubation; and a tyrosine-containing entity. On the other hand, five constituents (phenolic compounds were the most relevant) allowed the classification of honey samples by geographical origin with 87% certainty. The results showed that phenolic compounds and Maillard products are related to the sustained production of H 2 O 2 over time, which in turn boosts the antibacterial activity of honey. Native flora could promote this capability. The results showed the effect of geographic origin on the content of the analyzed minor constituents of honey, particularly phenolic compounds., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)