Tracing the geographical origin of food: The application of multi-element and multi-isotope analysis

Study on stable carbon isotope fractionation of rape honey from rape flowers (Brassica napus L.) to its unifloral ripe honey

A new idea and strategy for honey traceability and identification was provided by studying the carbon isotope fractionation of rape honey and its components in the different ripening process, as well as the fractionation from rape flowers, stamens, nectar to rape honey. The results showed the moisture content of rape honey continued to decrease, and the glucose and fructose content continued to increase during the ripening process. The δ¹³C of rape honey and its protein were less affected by honey ripeness, while the δ¹³C of sugars in rape honey were greatly affected by this. At the same time, the fractionation of carbon isotope from rape flowers to honey was significant. The δ¹³C of rape honey and its protein, disaccharide, fructose, and glucose had a strong correlation, and the δ¹³C of rape honey and its components were mainly related to rape flowers and its stamens.

Discrimination of Geographical Origins of Wolfberry (Lycium barbarum L.) Fruits Using Stable Isotopes, Earth Elements, Free Amino Acids, and Saccharides

To develop sophisticated approaches for distinguishing goji origins, 325 wolfberry fruit samples of a certain cultivar, plant age, drying method, and collection season were gathered from 26 producing areas across Northwest China in 2017 and 2018. We employed 49 indices, including stable isotopes, earth elements, soluble amino acids, and saccharides, to identify the regions of origin of these goji fruits. Analysis of variance (ANOVA) and heritability analysis were used to assess the effects of the environment (producing areas), cultivar, plant age, drying process, and collection season. Samples from the same place can be classified and partially discriminated using principal component analysis (PCA). We were able to distinguish fruits produced in Zhongning County from those produced in the other five producing provinces using orthogonal projection to latent structure-discriminant analysis (OPLS-DA). Calcium (Ca), manganese (Mn), ornithine (Orn), cystine (Cys-Cys), glutamate (Glu), phenylalanine (Phe), phosphoserine (Ps), serine (Ser), lysine (Lys), taurine (Tau), proline (Pro), and tyrosine (Tyr) indices were chosen using S-plots and heritability analysis, and their repeatability was established with samples collected in 2018. The indices selected in this study can distinguish goji berries produced in Zhongning County from fruits originating from five other Provinces with high repeatability, which was validated with various cultivars, drying methods, harvest seasons, and plant ages and with heritability analysis.

Elemental Chemometrics as Tools to Depict Stalked Barnacle (Pollicipes pollicipes) Harvest Locations and Food Safety

The stalked barnacle Pollicipes pollicipes is an abundant species on the very exposed rocky shore habitats of the Spanish and Portuguese coasts, constituting also an important economical resource, as a seafood item with high commercial value. Twenty-four elements were measured by untargeted total reflection X-ray fluorescence spectroscopy (TXRF) in the edible peduncle of stalked barnacles sampled in six sites along the Portuguese western coast, comprising a total of 90 individuals. The elemental profile of 90 individuals originated from several geographical sites (N = 15 per site), were analysed using several chemometric multivariate approaches (variable in importance partial least square discriminant analysis (VIP-PLS-DA), stepwise linear discriminant analysis (S-LDA), linear discriminant analysis (LDA), random forests (RF) and canonical analysis of principal components (CAP)), to evaluate the ability of each approach to trace the geographical origin of the animals collected. As a suspension feeder, this species introduces a high degree of background noise, leading to a comparatively lower classification of the chemometric approaches based on the complete elemental profile of the peduncle (canonical analysis of principal components and linear discriminant analysis). The application of variable selection approaches such as the VIP-PLS-DA and S-LDA significantly increased the classification accuracy (77.8% and 84.4%, respectively) of the samples according to their harvesting area, while reducing the number of elements needed for this classification, and thus the background noise. Moreover, the selected elements are similar to those selected by other random and non-random approaches, reinforcing the reliability of this selection. This untargeted analytical procedure also allowed to depict the degree of risk, in terms of human consumption of these animals, highlighting the geographical areas where these delicacies presented lower values for critical elements compared to the standard thresholds for human consumption.

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.

Geographical identification of strawberries based on stable isotope ratio and multi-elemental analysis coupled with multivariate statistical analysis: A Slovenian case study

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.

Stable Isotope and Element Profiling for Determining the Agroclimatic Origin of Cow Milk within a Tropical Country

Information on the geographic origin of milk is important in determining quality attributes and for economic gain through building brand value associated with origin. Stable isotope signatures and trace element concentrations have been increasingly used in authentication of milk, though information on the power of such technology in verifying agroclimatic origin in small continents with diverse climatic, environmental conditions, and animal management practice is scarce. Therefore, the main objective of this study was to investigate the possibility of using a stable isotope composition of C, N, O, and H and element fingerprints to determine the agroclimatic origin of milk produced in different agroclimatic zones of Sri Lanka. Stable isotopes ratios of C, N, H, and O, and elemental fingerprints of milk samples were determined by IRMS and ICP-MS, respectively. Significant variations were observed in stable isotope ratios, especially δ¹⁸O and the mean content of Li, Al, Cr, Mn, and Sr in the bulk milk samples obtained from different agroclimatic zones. A linear discriminant analysis differentiated cow milk produced from four agroclimatic zones based on stable isotope ratios, and the inclusion of elemental ratios enhanced the discriminating ability.

A modern baseline for the paired isotopic analysis of skin and bone in terrestrial mammals

We present the isotopic discrimination between paired skin and bone collagen from animals of known life history, providing a modern baseline for the interpretation of archaeological isotopic data. At present, the interpretation of inter-tissue variation (Δ_(skin-bone)) in mummified remains is based on comparisons with other archaeological material, which have attributed divergence to their contrasting turnover rates, with rapidly remodelling skin collagen incorporating alterations in environmental, cultural and physiological conditions in the months prior to death. While plausible, the lack of baseline data from individuals with known life histories has hindered evaluation of the explanations presented. Our analysis of a range of animals raised under a variety of management practices showed a population-wide trend for skin collagen to be depleted in ¹³C by -0.7‰ and enriched in ¹⁵N by +1.0‰ relative to bone collagen, even in stillborn animals. These results are intriguing and difficult to explain using current knowledge; however, on the basis of the findings reported here, we caution any results which interpret simply on differing turnover rates. We hypothesize that there may be a consistent difference in the routing of dietary protein and lipids between skin and bone, with potentially on-site synthesis of non-essential amino acids using carbon and nitrogen that have been sourced via different biochemical pathways.

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.

Distinguishing Korean and Chinese red pepper powder using inductively coupled plasma and X-ray fluorescence-based analysis

This study aimed to distinguish between Korean and Chinese red pepper powder (RPP) using inorganic elemental analysis data combined with orthogonal partial least squares-discriminant analysis (OPLS-DA). Elemental concentrations were obtained for 31 Korean and 31 Chinese RPP samples that were collected in Korea. Energy dispersive X-ray fluorescence spectroscopy detected 11 elements in these samples. Rb and Cl concentrations were selected as the variables which best allowed distinguishing between Korean and Chinese RPP using an S-plot from OPLS-DA. Rb and Cl concentrations in the Korean RPP samples were ≤ 1.6 mg/100 g (measured by inductively coupled plasma-optical emission spectroscopy) and ≤ 215 mg/100 g, respectively. A blind trial demonstrated that Korean RPP containing ≥ 50 g/100 g of Chinese RPP could be identified by applying predetermined ranges of Rb and Cl concentrations, suggesting that analysis of these two elements is a possible approach to distinguish between Korean and Chinese RPP.

Multielement Characterization and Antioxidant Activity of Italian Extra-Virgin Olive Oils

Food product safety and quality are closely related to the elemental composition of food. This study combined multielement analysis and chemometric tools to characterize 237 extra-virgin olive oil (EVOO) samples from 15 regions of Italy, and to verify the possibility of discriminating them according to different quality factors, such as varietal or geographical origin or whether they were organically or traditionally produced. Some elements have antioxidant properties, while others are toxic to humans or can promote oxidative degradation of EVOO samples. In particular, the antioxidant activity of oils’ hydrophilic fraction was estimated and the concentrations of 45 elements were determined by inductively coupled plasma mass spectrometry (ICP-MS). At first, univariate and multivariate analyses of variance were used to compare the element concentrations, and statistically significant differences were found among samples from different regions. Successively, discriminant classification approaches were used to build a model for EVOO authentication, considering, in turn, various possible categorizations. The results have indicated that chemometric methods coupled with ICP-MS have the potential to discriminate and characterize the different types of EVOO, and to provide “typical” elemental fingerprints of the various categories of samples.

Rapid Identification of Geographical Origin of Commercial Soybean Marketed in Vietnam by ICP-MS

Inductively coupled plasma mass spectrometry (ICP-MS) analytical method was used to determine the content of 40 elements in 38 soybean samples (Glycine Max) from 4 countries. Multivariate statistical methods, such as principal components analysis (PCA), were performed to analyze the obtained data to establish the provenance of the soybeans. Although soybean is widely marketed in many countries, no universal method is used to discriminate the origin of these cereals. Our study introduced the initial step to the identification of the geographical origin of commercial soybean marketed in Vietnam. The analysis pointed out that there are significant differences in the mean of 33 of the 40 analyzed elements among 4 countries' soybean samples, namely, ¹¹B, ²⁷Al, ⁴⁴Ca, ⁴⁵Sc, ⁴⁷Ti, ⁵⁵Mn, ⁵⁶Fe, ⁵⁹Co, ⁶⁰Ni, ⁶³Cu, ⁶⁶Zn, ⁶⁹Ga, ⁷⁵As, ⁷⁸Se, ⁸⁵Rb, ⁸⁸Sr, ⁸⁹Y, ⁹⁰Zr, ⁹³Nb, ⁹⁵Mo, ¹⁰³Rh, ¹³⁷Ba, ¹⁶³Dy, ¹⁶⁵Ho, ¹⁷⁵Lu, ¹⁷⁸Hf, ¹⁸¹Ta, ¹⁸²W, ¹⁸⁵Re, ¹⁹⁷Au, ²⁰²Hg, ²⁰⁵Tl, and ²⁰⁸Pb. The PCA analysis showed that the soybean samples can be classified correctly according to their original locations. This research can be used as a prerequisite for future studies of using the combination of elemental composition analysis with statistical classification methods for an accurate provenance establishment of soybean, which determined a variation of key markers for the original discrimination of soybean.

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.

Research progress on mutton origin tracing and authenticity

With the globalization of the food market and the convenience of food transportation between countries, consumers are increasingly worried about the source and safety of the food they eat. Traceability has been identified as an important tool for ensuring food safety and quality. This review mainly introduces the principles of five food traceability technologies, summarizes the progress in mutton application, comprehensively compares and analyzes the five traceability technologies, and discusses their application prospects, advantages and disadvantages. It is aimed at promoting research and application of traceability technology in mutton safety, promoting establishment and improvement of food traceability system.

Tracing the Geographical Origin of Thai Hom Mali Rice in Three Contiguous Provinces of Thailand Using Stable Isotopic and Elemental Markers Combined with Multivariate Analysis

Rice is a staple food for more than half of the world’s population. The discrimination of geographical origin of rice has emerged as an important issue to prevent mislabeling and adulteration problems and ensure food quality. Here, the discrimination of Thai Hom Mali rice (THMR), registered as a European Protected Geographical Indication (PGI), was demonstrated. Elemental compositions (Mn, Rb, Co, and Mo) and stable isotope (δ¹⁸O) in the rice were analyzed using inductively coupled plasma mass spectrometry (ICP-MS) and elemental analyzer isotope ratio mass spectrometry (EA-IRMS), respectively. The recoveries and precisions of all elements were greater than 98% and lower than 9%, respectively. The analytical precision (±standard deviation) was below ±0.2‰ for δ¹⁸O measurement. Mean of Mn, Rb, Co, Mo, and δ¹⁸O levels was 14.0 mg kg⁻¹, 5.39 mg kg⁻¹, 0.049 mg kg⁻¹, 0.47 mg kg⁻¹, and 25.22‰, respectively. Only five valuable markers combined with radar plots and multivariate analysis, linear discriminant analysis (LDA) could distinguish THMR cultivated from three contiguous provinces with correct classification and cross-validation of 96.4% and 92.9%, respectively. These results offer valuable insight for the sustainable management and regulation of improper labeling regarding geographical origin of rice in Thailand and other countries.

Geographical origin discrimination of "Ntopia" olive oil cultivar from Ionian islands using volatile compounds analysis and computational statistics

The aim of the present study was to characterize the aroma profile of olive oil of the "Ntopia" (local) cultivar from the Ionian islands (Zakynthos, Kefalonia, Leukada, and Kerkyra) (Greece), and investigate whether specific volatile compounds could be considered as indicators of olive oil geographical origin, using computational statistics. In this context, 137 olive oil samples were subjected to headspace solid phase microextraction coupled to gas chromatography/mass spectrometry using the internal standard method. Computational statistics on the semi-quantitative data of olive oil samples, as rapid machine learning algorithms, showed that specific volatile compounds could be used as indicators of geographical origin of olive oil of the "Ntopia" cultivar, among the four main Ionian islands. Volatile compounds such as ethanol, pentanal, 2,4-dimethylheptane, 3,7-dimethyl-1,3,6-octatriene (E), 2,5-dimethylnonane, 1-hexanol, 6-methyl-5-hepten-2-one, octanal, dl-Limonene, acetic acid hexyl ester and dodecane could aid to the geographical origin discrimination of "Ntopia" olive oil cultivar when two (Zakynthos and Kefalonia) or four (Zakynthos, Kefalonia, Leukada and Kerkyra) Ionian islands are subjected to statistical analysis. The discrimination rate using the cross-validation method was 100% and 85.7%, respectively. These results were further evaluated using training and holdout partitions, during which a comparable classification rate was obtained.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00217-021-03863-2.

Multi-chemical analysis combined with chemometrics to characterize PDO and PGI Italian apples

BACKGROUND

The use of PDO (protected designation of origin) and PGI (protected geographical indication) labels allows to protect and promote agricultural products characterized by unique features related to the place of origin and traditional know-how. However, the presence of non-authentic products in the market represents a fraud that can be tackled applying analytical techniques combined with chemometric analysis. In this study, we applied multi-element and multi-isotope analysis to characterize PDO and PGI apples cultivated in northern Italy, comparing them with Italian apples without labels of geographical indications.

RESULTS

The multi-element and multi-isotope approach allowed to characterize the apples cultivated in northern Italy. Despite a significant effect of the sampling sites on the apple composition, the comparison of the multi-chemical fingerprint of the apples significantly varied among cultivation areas. Results of this characterization were used to classify samples according to their cultivation area applying a linear discriminant analysis (LDA). Outputs of the LDA showed that correct sample classification can be successfully achieved (balanced accuracy > 96%). Moreover, using a selection of variables, it was possible to correctly classify samples also at regional level.

CONCLUSION

The presented evidences indicate that the multi-element and multi-isotope fingerprint can be successfully applied to traceability studies. The combination of this characterization with chemometric tools allows the classification of Italian apples based on their origin both on a national and regional scale. This approach represents an interesting tool to enhance and protect PDO and PGI Italian products. © 2021 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Construction of IsoVoc Database for the Authentication of Natural Flavours

Flavour is an important quality trait of food and beverages. As the demand for natural aromas increases and the cost of raw materials go up, so does the potential for economically motivated adulteration. In this study, gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) analysis of volatile fruit compounds, sampled using headspace-solid phase microextraction (HS-SPME), is used as a tool to differentiate between synthetic and naturally produced volatile aroma compounds (VOCs). The result is an extensive stable isotope database (IsoVoc—Isotope Volatile organic compounds) consisting of 39 authentic flavour compounds with well-defined origin: apple (148), strawberry (33), raspberry (12), pear (9), blueberry (7), and sour cherry (4) samples. Synthetically derived VOCs (48) were also characterised. Comparing isotope ratios of volatile compounds between distillates and fresh apples and strawberries proved the suitability of using fresh samples to create a database covering the natural variability in δ¹³C values and range of VOCs. In total, 25 aroma compounds were identified and used to test 33 flavoured commercial products to evaluate the usefulness of the IsoVoc database for fruit flavour authenticity studies. The results revealed the possible falsification for several fruit aroma compounds.

Combination of Stable Isotopes and Fatty Acid Composition for Geographical Origin Discrimination of One Argan Oil Vintage

Quality control and traceability of Argan oil requires precise chemical characterization considering different provenances. The fatty acid profile is an essential parameter that certifies the quality and purity of Argan oil. In addition, stable isotopes were recently shown to be accurate as an indicator for geographical origin. In this study, fatty acid composition by gas chromatography (GC) and stable isotope ratio by isotope ratio mass spectrometry (IRMS) were investigated for classifying Argan oil according to its geographical origin. Forty-one Argan oil samples, belonging to six geographical origins of Moroccan natural Argan population (Safi, Essaouira, Agadir Ida Outanane, Taroudant, Tiznit and Sidi Ifni) were collected and extracted under the same conditions. The results show that the isotope δ¹³C, palmitic acid (C16:0), linoleic acid (C18:2) and unsaturated fatty acids (UFA) were strongly influenced by ecological parameters. Linear discriminant analysis (LDA) was performed to discriminate the six studied provenances. Discriminant models predicted the origin of Argan oil with 92.70% success. Samples from Safi, Essaouira and Agadir Ida Outanane presented the highest classification rate (100%). In contrast, the lowest rate was reported for samples from Tiznit (85.70%). The findings obtained for fatty acids and isotope combination might be considered as an accurate tool for determining the geographical origins of Argan oil. Moreover, they can potentially be used as specific markers for oils labeled with Protected Geographical Indication (PGI).

Authenticating bioplastics using carbon and hydrogen stable isotopes - An alternative analytical approach

RATIONALE

A combination of stable carbon (δ¹³ C) and hydrogen (δ² H) isotope ratios and carbon content (% C) was evaluated as a rapid, low-cost analytical approach to authenticate bioplastics, complementing existing radiocarbon (¹⁴ C) and Fourier transform infrared (FTIR) analytical methods.

METHODS

Petroleum- and bio-based precursor materials and in-market plastics were analysed and their δ¹³ C, δ² H and % C values were used to establish isotope criteria to evaluate plastic claims, and the source and biocontent of the samples. ¹⁴ C was used to confirm the findings of the isotope approach and FTIR analysis was used to vertify the plastic type of the in-market plastics.

RESULTS

Distinctive carbon and hydrogen stable isotope ratios were found for authentic bio-based and petroleum-based precursor plastics, and it was possible to classify in-market plastics according to their source materials (petroleum, C3, C4, and mixed sources). An estimation of C4 biocontent was possible from a C4-petroleum isotope mixing model using δ¹³ C which was well correlated (R²  = 0.98) to ¹⁴ C. It was not possible to establish a C3-petroleum isotope mixing model due to δ¹³ C isotopic overlap with petroleum plastics; however, the addition of δ² H and % C was useful to evaluate if petroleum-bioplastic mixes contained C3 bioplastics, and PLS-DA modelling reliably clustered each plastic type.

CONCLUSIONS

A combined dual stable isotope and carbon content approach was found to rapidly and accurately identify C3 and C4 bio-based products from their petroleum counterparts, and identify instances of petroleum and bio-based mixes frequently found in mislabelled bioplastics. Out of 37 in-market products labelled as bioplastic, 19 were found to contain varying amounts of petroleum-based plastic and did not meet their bio-based claims.

Analytical strategies for Sr and Pb isotopic signatures by MC-ICP-MS applied to the authentication of Champagne and other sparkling wines

Wine is one of the most counterfeit product and therefore, requires certifying of its origin and provenance. For authentication purposes, analytical strategies for the determination of Sr and Pb isotopic ratios were adapted for Champagne and sparkling wines. All analytical steps have been carefully adapted and optimized regarding sample preparation, mineralization, and purification by resins as well as isotopic composition measurements on 3 different MC ICP-MS instruments. Further, a global approach using an "in-house" reference material of Champagne (ChRM) was realized and used throughout as well as routine analytical conditions to guaranty samples isotopic quality determination over 3 years. These developments allowed to select the best conditions at all steps for reaching the best precision and accuracy to be used under routine conditions for samples origin discrimination. The best condition of mineralization was obtained with a hot block system allowing both efficiency in digestion and high sample throughput. Detailed conditions of purification for both Sr and Pb isotopes were also optimized and discussed. These different optimization steps on the whole analytical chain allowed to estimate a global precision suitable to be used routinely to discriminate the origin of different Champagne samples. For Sr isotopic analysis (⁸⁷Sr/⁸⁶Sr), the overall external precision based on preparation replicates of ChRM was 2σ = 0.000024 (n = 36) and for the Pb isotopes analysis (²⁰⁸Pb/²⁰⁶Pb), the precision obtained on ChRM was 2σ = 0.0024 (n = 15). Finally, we have applied these developments by combining both Sr and Pb isotopic ratios in order to discriminate the origin of sparkling wines from around the world. The combined isotopic signature, using both Sr and Pb isotopes ratios, permitted a clear discrimination between certified Champagne wines and other European and Non-European sparkling wines.

Detection of exogenous sugars in pineapple juice using compound-specific stable hydrogen isotope analysis

An improved procedure for determining 2H/1H isotope ratios, using gas chromatography-isotope ratio mass spectrometry, has been used to detect the addition of exogenous C4-plant-derived sugars to pineapple juice. Isotopic techniques are commonly used to identify the addition of low-cost sugars to fruit juices and are difficult to subvert as it is not economically viable to change the isotopic ratios of the sugars. However, the addition of cane sugar to pineapple juice has presented a significant challenge that is only detected by site-specific 13C analysis of the methyl and methylene positions of ethanol derived from pineapple sugars, measured by nuclear magnetic resonance. This new GC-IRMS-based procedure utilises the trifluoroacetate derivative of sucrose to allow direct measurement of the carbon-bound non-exchangeable hydrogen. This provides advantages over alternative isotopic methods in terms of analysis time and sensitivity. This feasibility study has demonstrated the potential to reliably differentiate between authentic pineapple juices and those adulterated with commercial beet and cane sucrose.

Elemental and Isotopic Characterization of Tobacco from Umbria

Umbrian tobacco of the Virginia Bright variety is one of the most appreciated tobaccos in Europe, and one characterized by an excellent yield. In recent years, the Umbria region and local producers have invested in introducing novel practices (for production and processing) focused on environmental, social, and economic sustainability. Due to this, tobacco from Umbria is a leading commodity in the global tobacco industry, and it claims a high economic value. The aim of this study is then to assess if elemental and isotopic compositions can be used to protect the quality and geographical traceability of this particular tobacco. For the first time the characteristic value ranges of the stable isotope ratios of the bio-elements as a whole (δ²H, δ¹³C, δ¹⁵N, δ¹⁸O, and δ³⁴S) and of the concentration of 56 macro- and micro-elements are now available, determined in Virginia Bright tobacco produced in two different areas of Italy (Umbria and Veneto), and from other worldwide geographical regions. The ranges of variability of elements and stable isotope ratios had slightly different results, according to the three geographical origins considered. In particular, Umbria samples presented significantly lower content of metals potentially dangerous for human health. The results of this first exploratory work highlight the possibility of characterizing tobacco from Umbria, and suggest widening the scope of the survey throughout Italy and foreign regions, in order to be used to describe the geographical origin of tobacco in general and verify the origin of the products on the market.

Discrimination of geographical origin and species of China's cattle bones based on multi-element analyses by inductively coupled plasma mass spectrometry

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.

An origin identification model for labeling of shiitake (Lentinula edodes)

With the increasing globalization of the food trade across countries and continents, reliable identification of the geographical origin of products is critical. In this study, we describe the limitations of the current origin labeling system for non-soil-based agricultural products and suggest alternative strategies for the identification of the geographical origin of such products. An origin identification model based on stable isotope ratio analysis combined with discriminant analysis is used to evaluate the similarities and dissimilarities between domestic and foreign shiitake mushrooms, including Chinese inoculated sawdust blocks and Chinese origin. The results show a classification sensitivity of 92.0%, classification specificity of 91.5%, and overall accuracy of 93.5%. In particular, δ¹⁵N was the most important isotope marker for the identification of the origin of shiitake mushrooms. Hence, the current origin labeling system for mushroom species has to be revised to establish fair trade and avoid improper origin labeling in the global shiitake market.

Advances in Troubleshooting Fish and Seafood Authentication by Inorganic Elemental Composition

The demand for fish and seafood is growing worldwide. Meanwhile, problems related to the integrity and safety of the fishery sector are increasing, leading legislators, producers, and consumers to search for ways to effectively protect themselves from fraud and health hazards related to fish consumption. What is urgently required now is the availability of reliable, truthful, and reproducible methods assuring the correspondence between the real nature of the product and label declarations accompanying the same product during its market life. The evaluation of the inorganic composition of fish and seafood appears to be one of the most promising strategies to be exploited in the near future to assist routine and official monitoring operations along the supply chain. The present review article focuses on exploring the latest scientific achievements of using the multi-elemental composition of fish and seafood as an imprint of their authenticity and traceability, especially with regards to the geographical origin. The scientific literature of the last 10 years focusing on the analytical determination and statistical elaboration of elemental data (alone or in combination with methodologies targeting other compounds) to verify the identity of fishery products is summarized and discussed.

Development and Validation of the Perceived Authenticity Scale for Cheese Specialties with Protected Designation of Origin

Authenticity has become increasingly important in the modern market as consumers seek products more resonant of tradition and originality. This study aimed to develop and validate a perceived authenticity scale for food specialties. Furthermore, this work exposed the causal relationship between authenticity and consumer behaviour, by quantitatively analysing the effects of perception of authenticity and identification with a product on consumers’ willingness to consume the cheese Algovian Emmentaler, an iconic dairy product produced in southern Germany and protected with the designation of origin. Three surveys were conducted over two different timeframes. One served as a pre-test in Germany with a representative sample for the second two in Germany and Italy with a gourmet sample. Both objective authenticity and subjective authenticity were considered, with the former comprising concepts such as whether the respondent was sure of the cheese’s origin and the latter what the cheese embodied. Identification with Algovian Emmentaler was also surveyed. Exploratory factor analysis and confirmatory factor analysis were conducted on the survey data in order to construct an authenticity scale. Based on this scale, structural equation models were constructed. Objective authenticity was found to positively contribute to stated willingness to consume, as well as mediate subjective authenticity, which itself mediated the effects of identification. Subjective authenticity was a large contributing factor to willingness to consume among German consumers, whereas the effects of objective authenticity were higher in Italy compared with the former. Expectedly, identification with Algovian Emmentaler also had a high direct effect on willingness to consume in Germany.

Rapid Geographical Origin Identification and Quality Assessment of Angelicae Sinensis Radix by FT-NIR Spectroscopy

Angelicae Sinensis Radix is a widely used traditional Chinese medicine and spice in China. The purpose of this study was to develop a methodology for geographical classification of Angelicae Sinensis Radix and determine the contents of ferulic acid and Z-ligustilide in the samples using near-infrared spectroscopy. A qualitative model was established to identify the geographical origin of Angelicae Sinensis Radix using Fourier transform near-infrared (FT-NIR) spectroscopy. Support vector machine (SVM) algorithms were used for the establishment of a qualitative model. The optimum SVM model had a recognition rate of 100% for the calibration set and 83.72% for the prediction set. In addition, a quantitative model was established to predict the content of ferulic acid and Z-ligustilide using FT-NIR. Partial least squares regression (PLSR) algorithms were used for the establishment of a quantitative model. Synergy interval-PLS (Si-PLS) was used to screen the characteristic spectral interval to obtain the best PLSR model. The coefficient of determination for calibration (R2C) for the best PLSR models established with the optimal spectral preprocessing method and selected important spectral regions for the quantitative determination of ferulic acid and Z-ligustilide was 0.9659 and 0.9611, respectively, while the coefficient of determination for prediction (R2P) was 0.9118 and 0.9206, respectively. The values of the ratio of prediction to deviation (RPD) of the two final optimized PLSR models were greater than 2. The results suggested that NIR spectroscopy combined with SVM and PLSR algorithms could be exploited in the discrimination of Angelicae Sinensis Radix from different geographical locations for quality assurance and monitoring. This study might serve as a reference for quality evaluation of agricultural, pharmaceutical, and food products.

Achieving Food Authenticity and Traceability Using an Analytical Method Focusing on Stable Isotope Analysis

High-value agricultural products are characterized by the geographical conditions of the production areas such as climatic and soil conditions. These products are protected by the geographical indication (GI) protection system, which has been introduced in more than 100 countries. Because GI products are expensive in the market, products are often mislabeled as GI. Thus, there is an urgent need for the development of analytical methods that enable the tracing of geographical origins of food materials. Stable isotope analysis is used to trace the geographical origin of food materials. In this study, we review the applications for tracing the geographical origin of agricultural products (especially rice, beef, and honey) focusing on an analytical method for analyzing stable isotopes (δD, δ13C, δ15N, δ18O, and δ34S).

Discrimination of mutton from different sources (regions, feeding patterns and species) by mineral elements in Inner Mongolia, China

The traceability of mineral element fingerprints to mutton in a small area of China was studied. The element data of 104 sheep and 24 goat samples from Inner Mongolia were measured, and the data were analyzed by multivariate statistical analysis from different origins, species and feeding patterns. The results shows that 11 elements (Mg, Al, K, Ca, Mn, Fe, Cu, Zn, Rb, Sr, Ba) in sheep meat had significant differences between different regions (P < 0.05), and the results of linear discriminant analysis (LDA) showed that the accuracy of the original classification rate was 95.2%, and the cross-validation rate was 85.9%. Goat meat and sheep meat samples from Alxa League were also clearly identified with LDA results showing that the cross-validation accuracy of the two species was 70.2%. Then the feeding patterns of sheep meat were effectively classified. The results showed that the multi-element analysis has certain potential as a method to distinguish mutton in a small area.

Geostatistical evaluation of the design of the precipitation stable isotope monitoring network for Slovenia and Hungary

A detailed knowledge of the stable isotope signature of precipitation is the basis of investigations in a variety of scientific fields and applications. To obtain robust and reliable results, the representativity of the currently operating (at least, as of 2018) precipitation stable isotope monitoring stations across Slovenia (n = 8) and Hungary (n = 9) was evaluated on the basis of amount-weighted annual averages with the aim of revealing any redundantly (i.e. over-) represented or un(der)represented areas. In the case of the latter, optimal locations for additional sites were suggested in Slovenia and Hungary. The networks of both countries are design-based systems that need to be fine-tuned for long-term optimized operation. The evaluation of the monitoring network was performed taking into consideration the stations operating in Slovenia and Hungary, as well as closely situated ones operating in neighboring countries. The evaluation was carried out in nine different combinations, using spatial simulated annealing, with regression kriging variance as a quality measure. The results showed that (i) there are over- and un(der)represented areas in the network, an issue requiring remedial action, (ii) the mutual information exchange of the precipitation stable isotope monitoring networks of Slovenia and Hungary increases the precision of precipitation δ¹⁸O estimation by ~0.3‰ in a 15-30 km wide zone near the borders, and (iii) by an even greater degree in the neighboring countries' stations. The current research may be termed pioneering in the matter of the detailed geostatistical assessment of spatial representativity of a precipitation stable isotope monitoring network, and as such, can serve as an example for future studies aiming for the spatial optimization of other regional precipitation stable isotope monitoring networks.

Food Authentication: Species and Origin Determination of Truffles (Tuber spp.) by Inductively Coupled Plasma Mass Spectrometry and Chemometrics

The aim of this study was to develop a protocol for the authentication of truffles using inductively coupled plasma mass spectrometry. The price of the different truffle species varies significantly, and because the visual differentiation is difficult within the white truffles and within the black truffles, food fraud is likely to occur. Thus, in the context of this work, the elemental profiles of 59 truffle samples of five commercially relevant species were analyzed and the resulting element profiles were evaluated with chemometrics. Classification models targeting the species and the origins were validated using nested cross validation and were able to differentiate the most expensive Tuber magnatum from any other examined truffle. For the black truffles, an overall classification accuracy of 90.4% was achieved, and, most importantly, a falsification of the expensive Tuber melanosporum by Tuber indicum could be ruled out. With regard to the geographical origin, for Italy and Spain, one-versus-all classification models were calculated each to differentiate truffle samples from any other origins by 75.0 and 86.7%, respectively. The prediction was still possible according to an internal mathematical normalization scheme using only the element ratios instead of the absolute element concentrations. The established authentication protocol was successfully tested with an external sample set of five fresh truffles. Our results show the high potential of the element profile for the parallel species and origin authentication of truffles.