Stable Isotope Ratio Analysis for Assessing the Authenticity of Food of Animal Origin

Analytical insights for ensuring authenticity of Greek agriculture products: Unveiling chemical marker applications

Food authentication, including the differentiation of geographical or botanical origin, the method of production i.e. organic vs. conventional farming as well as the detection of food fraud/adulteration, has been a rapidly growing field over the past two decades due to increasing public awareness regarding food quality and safety, nutrition, and health. Concerned parties include consumers, producers, and legislators. Thus, the development of rapid, accurate, sensitive, and reproducible analytical methods to guarantee the authenticity of foods is of primary interest to scientists and technologists. The aim of the present article is to summarize research work carried out on the authentication of Greek agricultural products using spectroscopic (NIR, FTIR, UV-Vis, Raman and fluorescence spectroscopy, NMR, IRMS, ICP-OES, ICP-MS) and chromatographic (GC, GC/MS, HPLC, HPLC/MS, etc.) methods of analysis in combination with chemometrics highlighting the chemical markers that enable product authentication. The review identified a large number of chemical markers including volatiles, phenolic substances, natural pigments, elements, isotopes, etc. which can be used for (i) the differentiation of botanical/geographical origin; conventional from organic farming; production procedure and vintage year, etc. and (ii) detection of adulteration of high quality plant and animal origin foods with lower value substitutes. Finally, the constant development of reliable analytical techniques in combination with law enforcement authorities will ensure authentic foods in terms of quality and safety for consumers.

Markers for meat provenance and authenticity with an account of its defining factors and quality characteristics - a review

Provenance is becoming increasingly important in meat supply chains as it lends products higher perceived quality. However, its precise definition and interpretation along with its associated characteristics factors have remained somewhat elusive. This review meticulously defines meat provenance while dissecting the essential factors and associated quality attributes that constitute its essence and are subsequently employed to establish pertinent markers for provenance. Meat provenance emerges as a multi-dimensional construct stemming from the adept management of a constellation of factors relating to geographical origin, farm production system, traceability, and authenticity. Through intricate interactions, these factors unveil innate originality that not only forges a distinct reputation but also imparts a unique typicity to the meat product. Gaining insights into a meat product's provenance becomes attainable by scrutinizing its pertinent composition and organoleptic quality traits. Trace elements and stable isotopes stand out as provenance markers, forging a direct connection to both geographical origin and dietary sources. While somewhat less direct in linkage, other markers such as plant biomarkers, fatty acid composition, pH levels, flavour and aromatic compounds along with organoleptic characteristics contribute to the overall understanding of provenance. Additionally, the identification of animal species and breeds serves as key markers, particularly in the context of protected geographical indications. The study findings are useful for the various stakeholders of how the information for meat provenance can be linked with intrinsic and extrinsic factors for meat quality and protecting the integrity of the supply chain with special reference to traceability and authenticity. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Stable isotope ratios and current-use pesticide levels in edible insects: Implications on chemical food safety

In the past years, the European Union (EU) has added edible insects to the list of novel foods, allowing an increasing number of insect-based products into the European market. With insects gaining more popularity in the Western world, it is crucial to investigate their chemical food safety. This study aimed at investigating possible isotopic patterns in different edible insect species (n = 52) from Asia, Africa and Europe using stable isotope ratio analysis (SIRA) to provide a framework for future investigations on food authenticity and traceability. Additionally, complementary mass-spectrometric screening approaches were applied to gain a comprehensive overview of contamination levels of current-use pesticides (CUPs) in edible insects, to assess their chemical food safety. SIRA revealed significant differences between countries in δ13CVPDB- (p < 0.001) and δ15Nair- (p < 0.001) values. While it was not possible to distinguish between individual countries using principal component analysis (PCA) and linear discriminative analysis (LDA), the latter could be used to distinguish between larger geographical areas (i.e. Africa, Europe and Asia). In general, African samples had a more distinct isotopic profile compared to European and Asian samples. When comparing the isotopic compositions of samples containing pesticides with samples with no detected pesticides, differences in sulphur compositions could be observed. Additionally, LDA was able to correctly classify the presence of pesticides in a sample with 76% correct classification based on the sulphur composition. These findings show that SIRA could be a useful tool to provide a framework for future investigations on food authenticity and traceability of edible insects. A total of 26 CUPs were detected using suspect screening and an additional 30 CUPS were quantified using target analysis, out of which 9 compounds had a detection frequency higher than 30%. Most detected pesticides were below the maximum residue levels (MRLs) for meat, suggesting low contamination levels. However, dichlorvos and fipronil could be detected in the same order of magnitude as the MRLs, even in samples purchased in Europe. These findings indicate a limited chemical risk for edible insects regarding pesticide contamination. Nevertheless, the study also highlights that further and more extensive investigations are needed to give a comprehensive assessment of the chemical risk of edible insects as a novel food source in Europe. With insects recently being potentially more incorporated into daily diets, more attention should be paid to possible chemical hazards to accurately assess their risk and to ensure food safety.

Influence of Geographical Origin on Isotopic and Elemental Compositions of Pork Meat

Pigs are a primary source of meat, accounting for over 30% of global consumption. Consumers' preferences are determined by health considerations, paying more attention to foodstuffs quality, animal welfare, place of origin, and swine feeding regime, and being willing to pay a higher price for a product from a certain geographical region. In this study, the isotopic fingerprints (δ2H, δ18O, and δ13C) and 29 elements of loin pork meat samples were corroborated with chemometric methods to obtain the most important variables that could classify the samples' geographical origin. δ2H and δ18O values ranged from -71.0 to -21.2‱, and from -9.3 to -2.8‱, respectively. The contents of macro- and micro-essential elements are presented in the following order: K > Na > Mg > Ca > Zn > Fe > Cu > Cr. The LDA model assigned in the initial classification showed 91.4% separation of samples, while for the cross-validation procedure, a percentage of 90% was obtained. δ2H, K, Rb, and Pd were identified as the most representative parameters to differentiate the pork meat samples coming from Romania vs. those from abroad. The mean values of metal concentrations were used to estimate the potential health risks associated with the consumption of pork meat The results showed that none of the analyzed metals (As, Cd, Sn, Pb, Cu, and Zn) pose a carcinogenic risk.

Differentiating wild from captive animals: an isotopic approach

Background

Wildlife farming can be an important but complex tool for conservation. To achieve conservation benefits, wildlife farming should meet a variety of criteria, including traceability conditions to identify the animals' origin. The traditional techniques for discriminating between wild and captive animals may be insufficient to prevent doubts or misdeclaration, especially when labels are not expected or mandatory. There is a pressing need to develop more accurate techniques to discriminate between wild and captive animals and their products. Stable isotope analysis has been used to identify animal provenance, and some studies have successfully demonstrated its potential to differentiate wild from captive animals. In this literature review, we examined an extensive collection of publications to develop an overall picture of the application of stable isotopes to distinguish between wild and captive animals focusing on evaluating the patterns and potential of this tool.

Survey methodology

We searched peer-reviewed publications in the Web of Science database and the references list from the main studies on the subject. We selected and analyzed 47 studies that used δ13C, δ15N, δ2H, δ18O, and δ34S in tissues from fish, amphibians, reptiles, birds, and mammals. We built a database from the isotope ratios and metadata extracted from the publications.

Results

Studies have been using stable isotopes in wild and captive animals worldwide, with a particular concentration in Europe, covering all main vertebrate groups. A total of 80.8% of the studies combined stable isotopes of carbon and nitrogen, and 88.2% used at least one of those elements. Fish is the most studied group, while amphibians are the least. Muscle and inert organic structures were the most analyzed tissues (46.81% and 42.55%). δ13C and δ15N standard deviation and range were significantly higher in the wild than in captive animals, suggesting a more variable diet in the first group. δ13C tended to be higher in wild fishes and in captive mammals, birds, reptiles, and amphibians. δ15N was higher in the wild terrestrial animals when controlling for diet. Only 5.7% of the studies failed to differentiate wild and captive animals using stable isotopes.

Conclusions

This review reveals that SIA can help distinguish between wild and captive in different vertebrate groups, rearing conditions, and methodological designs. Some aspects should be carefully considered to use the methodology properly, such as the wild and captivity conditions, the tissue analyzed, and how homogeneous the samples are. Despite the increased use of SIA to distinguish wild from captive animals, some gaps remain since some taxonomic groups (e.g., amphibians), countries (e.g., Africa), and isotopes (e.g., δ2H, δ18O, and δ34S) have been little studied.

Effects of different floral periods and environmental factors on royal jelly identification by stable isotopes and machine learning analyses during non-migratory beekeeping

It is crucial to monitor the authenticity of royal jelly (RJ) because the qualities of RJs produced by different floral periods vary substantially. In the context of non-migratory beekeeping, this study aims to identify rape RJ (RRJ), chaste RJ (CRJ), and sesame RJ (SRJ) based on δ13C, δ15N, δ2H, and δ18O combined with machine learning and to evaluate environmental effect factors. The results showed that δ13C (-27.62‰ ± 0.24‰), δ15N (2.88‰ ± 0.85‰), and δ18O (28.02‰ ± 1.30‰) of RRJ were significantly different from other RJs. The δ13C, δ2H, and δ18O in CRJ and SRJ were strongly correlated with temperature and precipitation, suggesting that these isotopes are influenced by environmental elements such as sunlight and rainfall. In addition, the artificial neural network (ANN) model was superior to the random forest (RF) model in terms of accuracy, sensitivity, and specificity. This study revealed that combining stable isotopes with ANN models and the unique correlation between stable isotopes and environmental factors could provide promising ideas for monitoring the authenticity of RJ.

Verifying origin claims on dairy products using stable isotope ratio analysis and random forest classification

Scientifically underpinning geographic origin claims will improve consumer trust in food labels. Stable isotope ratio analysis (SIRA) is an analytical technique that supports origin verification of food products based on naturally occurring differences in isotopic compositions. SIRA of five relevant elements (C, H, N, O, S) was conducted on casein isolated from butter (n = 60), cheese (n = 96), and whole milk powder (WMP) (n = 41). Samples were divided into four geographic regions based on their commercial origin: Ireland (n = 79), Europe (n = 67), Australasia (n = 29) and USA (n = 22). A random forest machine learning model built using δ13C, δ2H, δ15N, δ18O and δ34S values of all products (n = 197) accurately (88% model accuracy rate) predicted the region of origin with class accuracy of 95% for Irish, 84% for European, 71% for Australasia, and 94% for US products.

Isotope Fingerprinting as a Backup for Modern Safety and Traceability Systems in the Animal-Derived Food Chain

In recent years, due to the globalization of food trade and certified agro-food products, the authenticity and traceability of food have received increasing attention. As a result, opportunities for fraudulent practices arise, highlighting the need to protect consumers from economic and health damages. In this regard, specific analytical techniques have been optimized and implemented to support the integrity of the food chain, such as those targeting different isotopes and their ratios. This review article explores the scientific progress of the last decade in the study of the isotopic identity card of food of animal origin, provides the reader with an overview of its application, and focuses on whether the combination of isotopes with other markers increases confidence and robustness in food authenticity testing. To this purpose, a total of 135 studies analyzing fish and seafood, meat, eggs, milk, and dairy products, and aiming to examine the relation between isotopic ratios and the geographical provenance, feeding regime, production method, and seasonality were reviewed. Current trends and major research achievements in the field were discussed and commented on in detail, pointing out advantages and drawbacks typically associated with this analytical approach and arguing future improvements and changes that need to be made to recognize it as a standard and validated method for fraud mitigation and safety control in the sector of food of animal origin.

Application of Stable Isotope Analysis for Detecting the Geographical Origin of the Greek Currants "Vostizza": A Preliminary Study

There is a plethora of food products with geographical indications registered in the European Union without any study about their discrimination from other similar products. This is also the case for Greek currants. This paper aims to analyze if stable isotope analysis of C, N, and S could discriminate the Greek currants "Vositzza", registered as a product of Protected Designation of Origin, from two other currants registered as products of Protected Geographical Indication coming from neighboring areas. The first results show that the stable isotope ratio of sulfur is not detectable due to the very low sulfur content in the samples, and the analysis should be based on the stable isotope ratios of carbon and nitrogen to discriminate these products. The mean value of δ¹⁵N (1.38‱) of PDO "Vostizza" currants is lower than that of currants grown outside the PDO zone (2.01‱), while the mean value of δ¹³C of PDO "Vostizza" currants is higher (-23.93‱) in comparison to that of currants grown outside the PDO zone (-24.83‱). Nevertheless, the results indicate that with only two isotopic ratios, discrimination could not be achieved, and further analysis is required.

Characterization of Beef Coming from Different European Countries through Stable Isotope (H, C, N, and S) Ratio Analysis

The need to guarantee the geographical origin of food samples has become imperative in recent years due to the increasing amount of food fraud. Stable isotope ratio analysis permits the characterization and origin control of foodstuffs, thanks to its capability to discriminate between products having different geographical origins and derived from different production systems. The Framework 6 EU-project "TRACE" generated hydrogen (²H/¹H), carbon (¹³C/¹²C), nitrogen (¹⁵N/¹⁴N), and sulphur (³⁴S/³²S) isotope ratio data from 227 authentic beef samples. These samples were collected from a total of 13 sites in eight countries. The stable isotope analysis was completed by combining IRMS with a thermal conversion elemental analyzer (TC/EA) for the analysis of δ(²H) and an elemental analyzer (EA) for the determination of δ(¹³C), δ(¹⁵N), and δ(³⁴S). The results show the potential of this technique to detect clustering of samples due to specific environmental conditions in the areas where the beef cattle were reared. Stable isotope measurements highlighted statistical differences between coastal and inland regions, production sites at different latitudes, regions with different geology, and different farming systems related to the diet the animals were consuming (primarily C3- or C4-based or a mixed one).

Fatty Acid and Multi-Isotopic Analysis (C, H, N, O) as a Tool to Differentiate and Valorise the Djebel Lamb from the Mountainous Region of Tunisia

The objective of this study was to distinguish between the Tunisian Djebel lamb meat and meat from typical Tunisian production systems (PSs) through the fatty acids (FAs) profile and the stable isotope ratio analysis (SIRA). Thirty-five lambs from three different regions and PSs (D = Djebel, B = Bou-Rebiaa, and O = Ouesslatia) were considered for this purpose. The results demonstrated that the PS and the geographic origin strongly influenced the FA profile of lamb meat. It was possible to discriminate between the Djebel lamb meat and the rest of the dataset thanks to the quantification of the conjugated linoleic acids (CLA) and the branched chain FAs. Moreover, statistically different concentrations of saturated, monounsaturated and polyunsaturated FAs and a different n-6/n-3 ratio were found for grazing (D and BR) and indoor (O) lambs, making it possible to discriminate between them. As for the stable isotope ratio analysis, all parameters made it possible to distinguish among the three groups, primarily on the basis of the dietary regimen (δ(¹³C) and δ(¹⁵N)) and breeding area (δ(¹⁸O) and δ(²H)).

A comprehensive evaluation of sulfur isotopic analysis (δ34S and δ33S) using multi-collector ICP-MS with characterization of reference materials of geological and biological origin

Sulfur isotope ratios are often used as biogeochemical tracers to gain understanding of abiotic and biological processes involved in the sulfur cycle in both modern and ancient environments. There is however a lack of matrix-matched well-characterized isotopic reference materials that are essential for controlling the accuracy and precision. This study therefore focused on expanding and complementing the currently available sulfur isotope ratio data by providing the bulk sulfur isotopic composition, as determined using multi-collector inductively coupled plasma-mass spectrometry (MC-ICP-MS), for a comprehensive set of commercially and/or readily available biological and geological reference materials. A total 7 isotopic reference materials and 41 elemental reference materials were studied. These reference materials include standards of terrestrial and marine animal origin, terrestrial plant origin, human origin, and geological origin. Different sample preparation protocols, including digestion and subsequent chromatographic isolation of S, were evaluated and the optimum approach selected for each matrix type. For achieving enhanced robustness, the sample preparation and sulfur isotope ratio measurements were done at two different laboratories for selected reference materials, while at one of the laboratories the measurements were additionally performed using two different MC-ICP-MS instruments. Determined δ³⁴S_VCDT and δ³³S_VCDT values compared well between the different laboratories, as well as between the different generation MC-ICP-MS instruments, and for standards that were previously characterized, our data are similar to literature values. The δ³⁴S_VCDT ranges determined for the different categories of the reference materials - terrestrial animal origin: +2 to +9‰, marine animal origin: +15 to +20‰, human origin: +6 to +10‰, terrestrial plant origin: -20 to +7‰, and geological origin: -12 to +21‰ - fit the expected values based on previous studies of similar types of matrices well. No significant mass-independent fractionation is observed when considering the expanded uncertainties for Δ³³S_V-CDT.

The role of species and geography in the elemental profiles of farm-raised shrimp from Indonesia

Elemental profiling is being explored as a traceability tool in many seafood products. However, the extent that elemental profiling can be used at finer geographical scales in cultured shrimp is unknown. Additionally, few studies have included multiple species in the same discriminant models, which would be useful in applications where one species is common, and the other is not. Here, elemental profiling was used to discern the provenance of black tiger shrimp Penaeus monodon and whiteleg shrimp Litopenaeus vannamei from the regions of North Kalimantan, Sulawesi Seletan, and Aceh in Indonesia. ICP-MS was used to determine elemental concentrations of 41 elements in shrimp muscle tissue and was the basis for multivariate and univariate statistical analyses. A MANOVA showed that multivariate differences exist in regions and between species of shrimp sampled. Univariate comparisons were utilized after the significance of the MANOVA and showed that 19 of the 24 elements above detection limits had significant differences. Classification via random forest was used to access the ability to discern, region, species, and region × species group combinations. The lowest model accuracy was the region × species combinations at 78.9%, while the highest accuracy was species irrespective of geographical origin at 93.59%. Elements that were routinely important in classification included As, B, Ba, Li, Na, Rb, Se, and Zn. Elemental profiles of white leg shrimp and black tiger shrimp are varied and potentially should not be used in the same classification models. Altogether, these results suggest that elemental profiling of farmed shrimp at finer geographic scales needs refinement as a traceability tool.

Isotopic and Elemental Fingerprint of Edible Egg Parts-The Health Risk Assessment Based on Potentially Toxic Elements Content

The present study investigated the isotopic and elemental profile (by IRMS and ICP-MS) of edible egg parts (29 egg whites and 29 yolks) mainly collected from Romania. In order to differentiate the egg white and yolk coming from different hen rearing systems (backyard and barn), Partial Least Square-Discriminant Analysis (PLS-DA) models were developed. The models' accuracies for the discrimination according to the hen growing system were 96% for egg white and 100% for egg yolk samples, respectively. Elements that proved to have the highest discrimination power for both egg white and yolk were the following: δ¹³C, Li, B, Mg, K, Ca, Mn, Fe, Co, Zn, Rb, Sr, Mo, Ba, La, Ce, and Pb. Nevertheless, the important compositional differentiation, in terms of essential mineral content, between the edible egg parts (egg white and egg yolk) were also pointed out. The estimated daily intake (EDI), the target hazard quotient (THQ) for Cr, Mn, Fe, Co, Ni, Cu, Zn, Se, Cd, Pb, and As, as well as the hazard index (HI) were used to assess non-carcinogenic human health risks from egg consumption. The obtained results showed no noticeable health risks related to egg consumption for humans from the point of view of the potentially toxic metals.

Rapid discrimination of the authenticity and geographical origin of bear bile powder using stable isotope ratio and elemental analysis

Bear bile powder (BBP) is one of the most famous traditional Chinese medicines derived from animals. It has a long history of medicinal use and is widely used in the treatment of hepatobiliary and ophthalmic diseases. Due to its similar morphological characterizations and chemical composition compared with other bile powders, it is difficult to accurately identify its authenticity. In addition, there are very few methods that could analyze the geographical origins of BBP. In this study, elemental analysis isotope ratio mass spectrometry (EA-IRMS) and inductively coupled plasma mass spectrometry (ICP-MS) were used to determine stable isotope ratios and elemental contents, respectively. Combined these variables with chemometrics, the discrimination models were established successfully for identifying the authenticity and geographical origins of BBP. Meanwhile, the discrimination markers were identified by calculating the variable importance for the projection (VIP) value of each variable. A total of 13 discrimination markers (δ¹³C, δ¹⁵N, C, Li, Mg, K, Ca, Cr, Ni, Zn, As, Se, and Sr) were used to further establish the fingerprint of BBP. According to similarity analysis, the authenticity and geographical origins of BBP could be identified without chemometrics. In conclusion, the present study established a reliable method for authenticity identification and origin traceability of BBP, which will provide references for the quality control of bile medicines.

Innovation to limit seafood fraud post-COVID-19

Seafood is an important source of protein and micronutrients, but fishery stocks are increasingly under pressure from both legitimate and illegitimate fishing practices. Sustainable management of our oceans is a global responsibility, aligning with United Nations Sustainable Development Goal 14, Life Below Water. In a post-COVID-19 world, there is an opportunity to build back better, where locally sourced food via transparent supply chains are ever-more important. This article summarises emerging research of two innovative case studies in detecting and validating seafood provenance; and using alternative supply chains to minimise the opportunity for seafood fraud in a post-COVID-19 world.

Proteomics-Compatible Fourier Transform Isotopic Ratio Mass Spectrometry of Polypeptides

Measuring the relative abundances of heavy stable isotopes of the elements C, H, N, and O in proteins is of interest in environmental science, archeology, zoology, medicine, and other fields. The isotopic abundance measurements of the fine structure of immonium ions with ultrahigh resolution mass spectrometry obtained in gas-phase fragmentation of polypeptides have previously uncovered anomalous deuterium enrichment in (hydroxy)proline of bone collagen in marine mammals. Here, we provide a detailed description and validation of this approach and demonstrate per mil-range precision of isotopic ratio measurements in aliphatic residues from proteins and cell lysates. The analysis consists of proteomics-type experiment demanding sub-microgram amounts of a protein sample and providing concomitantly protein sequence data allowing one to verify sample purity and establish its identity. A novel software tool protein amino acid-resolved isotopic ratio mass spectrometry (PAIR-MS) is presented for extracting isotopic ratio data from the raw data files acquired on an Orbitrap mass spectrometer.

Stable Isotope Analysis for the Discrimination of the Geographical Origin of Greek Bottarga ‘Avgotaracho Messolongiou’: A Preliminary Research

Consumers are increasingly interested in the geographical origin of the foodstuff they consume as an important characteristic of food authenticity and quality. To assure the authenticity of the geographical origin, various methods have been proposed. Stable isotope analysis is a method that has been extensively used for products such as wine, oil, meat, while only a few studies have been conducted for the discrimination of seafood origin and especially for mullet roes or bottarga products. Analysis of the stable isotopes of C, N and S of Bottarga samples from four different origins were carried out. The values of δ¹⁵N (5.45‰) and δ³⁴S (4.66‰) for the Greek Bottarga Product named ‘Avgotaracho Messolongiou’, from Messolongi lagoon were lower than other areas while δ¹³C values were higher (−14.84‰). The first results show that the stable isotopes ratios of carbon, nitrogen and sulphur could be used to discriminate the Greek Protected Designations of Origin Bottarga product ‘Avgotaracho Messolongiou’ from other similar products.

Isotopic and elemental characterization of Romanian pork meat in corroboration with advanced chemometric methods: A first exploratory study

In this study 93 pork meat samples (tenderloin) were analyzed via isotope ratios mass spectrometry (δ2H, δ18O, δ13C) and inductively coupled plasma - Mass spectrometry (55 elements). The meat samples are coming from Romania and abroad. Those from Romania are originating from conventional farms and yard rearing system. The analytical results in conjunction with linear discriminant analysis (LDA) and artificial neural networks (ANNs) were used to assess: The geographical origin, and animal diet. The most powerful markers which could differentiate pork meat samples concerning the geographical origin were δ18O, terbium, and tin. The results of chemometric models showed that, along with 13C signature, rubidium concentration, and a few rare earth-elements (lanthanum, and cerium) were efficient to discriminate animal diet in a percent of 97.8% (initial classification) and 94.6% (cross-validation), respectively. Some of predictors for feeding regime differentiation by using LDA were identified also to be the best markers to distinguish corn-based diet by using ANNs (δ13C, Rb, La).

Stepwise Approach for Tracing the Geographical Origins of the Manila Clam Ruditapes philippinarum Using Dual-Element Isotopes and Carbon Isotopes of Fatty Acids

While there are many studies that have reported methods for tracing the geographical origin of seafoods, most of them have focused on identifying parameters that can be used effectively and not the direct application of these methods. In this study, we attempted to differentiate the geographical origins of the Manila clam R. philippinarum collected from different sites in Korea, the Democratic People’s Republic of Korea, and China using a combination of analyses based on dual-element isotopes, fatty acids (FAs), and compound-specific isotopic analysis of FAs. We hypothesized that a stepwise application of new parameters to unclassified samples could achieve this objective by integrating new information while reducing time and labor. The FA profiles and compound-specific carbon isotopic values of FAs were found to enhance the discrimination power of determining the geographic origin up to 100%. Our findings demonstrate the advantageousness of using several parameters simultaneously over the conventional method of employing individual analytical methods when identifying geographic origins of the Manila clam, which could have implications for tracing the origins of different shellfish species or other food products as well.

Probabilistic Machine Learning for the Authentication of the Protected Designation of Origin of Greek Bottarga from Messolongi: A Generic Methodology to Cope with Very Small Number of Samples

Consumers are increasingly interested in the geographical origin of foodstuff, as an important characteristic of food authenticity and quality. To assure the authenticity of the geographical origin, various methods have been proposed. Stable isotope analysis is a method that has been extensively used for products like wine, oil, and meat by using large datasets and analysis. On the other hand, only few studies have been conducted for the discrimination of seafood origin and especially for mullet roes or bottarga products, and even fewer investigate a small number of samples and datasets. Stable isotopes of Carbon (C), Nitrogen (N), and Sulfur (S) analysis of bottarga samples from four different origins were carried out. The first results show that the stable isotopes ratios of C, N, and S could be used to discriminate the Greek PDO Bottarga (Messolongi) from other similar products by using a probabilistic machine learning methodology. That could use limited sample data to fit/estimate their parameters, while, at the same time, being capable of describing accurately the population and discriminate individual samples regarding their origin.

Predictive Model for Oral Status in Elderly People in a Taiwanese Nursing Home Using a High-Protein Black Soybean Koji Food

With increased age, the appetite, chewing, swallowing, and digestive ability gradually decrease. Previous studies have shown that poor oral health is associated with an inadequate intake of macro and micronutrients and malnutrition. Therefore, improving the diet of elderly people and promoting nutrient absorption will help to improve the quality of life for elderly people. However, few studies have predicted their oral ability based on different food textures and other factors. The purpose of this study was to explore the correlation between oral assessment and texture parameters of high-protein black soybean koji products in elderly people in a nursing home. We used cross-sectional study design for seventy-nine residents aged 65 years and older were recruited. Three different texture of cookies, including normal cookie hardness (1.4 × 105 N/m2), minced cookie hardness (4.4 × 104 N/m2), and pureed cookie hardness (1.4 × 104 N/m2) were provided to participants to test the oral status. An oral assessment scale was used by a dentist to evaluate the oral status of the elderly participants. Different cookie textures showed a significant positive correlation with pronunciation (r = 0.237, p < 0.05), face (r = 0.371, p < 0.01), tongue (r = 0.362, p < 0.01), pharynx (r = 0.256, p < 0.05), swallowing (r = 0.272, p < 0.05), breathing (r = 0.315, p < 0.01), and the total oral score (r = 0.339, p < 0.01). We also used the high-protein black soybean koji products combined with elderly people's comprehensions in a predictive model that had a moderately high correlation to predict the oral status in the elderly group (r = 0.612). We concluded that the high-protein black soybean koji product was associated with the oral ability of elderly people in a nursing home in Taiwan. Our findings indicated that elderly people could immediately understand the correct food texture.

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.

Geographical Origin Assessment of Extra Virgin Olive Oil via NMR and MS Combined with Chemometrics as Analytical Approaches

Geographical origin assessment of extra virgin olive oil (EVOO) is recognised worldwide as raising consumers’ awareness of product authenticity and the need to protect top-quality products. The need for geographical origin assessment is also related to mandatory legislation and/or the obligations of true labelling in some countries. Nevertheless, official methods for such specific authentication of EVOOs are still missing. Among the analytical techniques useful for certification of geographical origin, nuclear magnetic resonance (NMR) and mass spectroscopy (MS), combined with chemometrics, have been widely used. This review considers published works describing the use of these analytical methods, supported by statistical protocols such as multivariate analysis (MVA), for EVOO origin assessment. The research has shown that some specific countries, generally corresponding to the main worldwide producers, are more interested than others in origin assessment and certification. Some specific producers such as Italian EVOO producers may have been focused on this area because of consumers’ interest and/or intrinsic economical value, as testified also by the national concern on the topic. Both NMR- and MS-based approaches represent a mature field where a general validation method for EVOOs geographic origin assessment could be established as a reference recognised procedure.

Multivariate analysis for organic milk authentication

To differentiate organic milk (OM) from conventional milk (CM), an orthogonal projection to latent structure-discriminant analysis (OPLS-DA) model was constructed using δ¹³C, δ¹⁵N, δ¹⁸O, 51 elements and 35 fatty acids (FAs) as the variables. So far, most reported studies barely use three or more types of variables, but more variables could avoid one-sidedness and get stabler models. Our multivariate model combines geographical and nutritional parameters and displays better explanatory and predictive abilities (R²X = 0.647, R²Y = 0.962 and Q² = 0.821) than models based on fewer variables for differentiating OM and CM. In particular, δ¹⁵N, Se, δ¹³C, Eu, K and α-Linolenic acid (ALA) are found to be critical parameters for the discrimination of OM. These results show that the multivariate model based on stable isotopes, elements and FAs can be used to identify OM, and can potentially expand the global databases for quality and authenticity of milk.

Sociomedical and oral factors affecting masticatory performance in an older population

OBJECTIVES

To assess the sociomedical and oral factors affecting masticatory performance in a community-dwelling older population.

MATERIALS AND METHODS

Community-dwelling persons over 60 years were investigated using medical and dental oral interviews, oral and denture examination (natural teeth, tooth mobility, number of occluding tooth pairs, and removable dentures' prevalence and quality), and evaluation of masticatory performance using a mixing ability test.

RESULTS

A total of 130 participants with a mean age of 73.9±8.5 years were recorded. Fifty-eight (44.6%) used various types of removable prostheses. Twenty were edentulous and used a pair of complete dentures. Univariate analyses revealed statistically significant associations (p≤0.05) between masticatory performance and aging, marital status, subjective chewing ability, use of removable dentures, use of various combinations of complete dentures, pain caused by maxillary denture, number of teeth, tooth mobility, posterior chewing pairs, all chewing contacts natural or prosthetic, retention of mandibular partial dentures, and dentures' occlusion. The multivariable quantile regression analysis revealed that fewer natural teeth (95% CI: -0.02-0.01, p<0.001), being edentulous and using a pair of complete dentures (95% CI: 0.09-0.35, p=0.001), and larger percentage of severely mobile teeth (95% CI: 0.07-0.82, p=0.020) were associated with lower masticatory performance.

CONCLUSIONS

Poor masticatory performance in older adults was associated with fewer teeth, being edentulous and using a pair of complete dentures, and increased prevalence of severe tooth mobility.

CLINICAL RELEVANCE

Retaining the natural dentition and preventing and treating periodontal disease are important measures to maintain masticatory performance in older adults.

Isotope partitioning between cow milk and farm water: A tool for verification of milk provenance

RATIONALE

The oxygen and hydrogen isotope compositions of the water component of the milk from nine Italian dairy farms were studied together with the farm water for one year. The aim was to verify the importance of farm water and seasonal temperature variation on milk isotope values and propose mathematical relations as new tools to identify the milk origin.

METHODS

Milk was centrifuged to separate the solids and then distilled under vacuum to separate water. δ(¹⁸ O/¹⁶ O) and δ(² H/¹ H) analyses of the water molecules were carried out using a water equilibrator online with a mass spectrometer. For oxygen and hydrogen isotope determination, water was equilibrated with pure CO₂ for 7.5 h and with pure H₂ for 5 h, respectively. The isotope ratio value is indicated with δ (expressed on the VSMOW/SLAP scale) as defined by IUPAC.

RESULTS

The average annual isotope value of milk at the different cattle sheds is mostly related to the farm water suggesting that the drinking water is the most important factor influencing the isotopic values of the milk water. The milk/water fractionation factor correlates with the milking time and, thus, the seasonal temperature is best described by a 4^th order polynomial regression line. A two-level check model was used to verify the milking provenance.

CONCLUSIONS

This study shows that it is essential to analyze both milk and farm water to indicate provenance. A two-step verification tool, based on the difference between the measured and calculated δ(¹⁸ O/¹⁶ O)_M values, and the difference between the calculated and estimated milk-water fractionation factors, allowed the source determination of milk. Both conditions must be met if the milk is considered to be from the Parmigiano-Reggiano production region. Although this approach was developed for this region, it can easily be tested and adapted to other dairy production areas.

Overcoming the lack of reliability associated to monodimensional gas chromatography coupled to isotopic ratio mass spectrometry data by heart-cut two-dimensional gas chromatography

The use of IRMS as a GC detector has a history going back decades, however the critical issue of wrong δ¹³C measurements resulting from impure peaks has been often underestimated. To this regard, multidimensional separation techniques are effective tools to improve the reliability of the data, with respect to those obtained after monodimensional analysis. The present research aims to draw attention to one critical issue, related to the reliability of the δ¹³C data obtained by means of monodimensional GC-C-IRMS. Although already known from the literature, such aspect has been greatly overlooked, as is reflected in the few papers reporting the use of MDGC, among the plethora of published research dealing with GC-C-IRMS applications. Hereby, a set of natural samples of complex composition were analysed to investigate the presence of minor or even undetected coelutions, and to which extent it affected the isotope ratio determination. Apart from chromatographic effects, and issues related to analytes conversion to CO₂ prior to IRMS measurement, unpredictable co-elutions with compounds, either resulting from oxidation or intentionally added in fraudulent practices, could also contribute to a shift of the δ¹³C data, up to 10‰ and higher. Last, the influence of column bleed was investigated, as affecting the determination of the δ¹³C data for compounds that were eluted at high temperatures. It was finally demonstrated by the selected key studies that implementation of MDGC separation is mandatory to prevent the aforementioned issues, aiming to guarantee accurate results. In the light of the above conclusions, and considering the level of automation of heart-cut devices nowadays available, routine practice of MDGC results highly recommendable in any IRMS applications.

Mass spectrometry-based protein and peptide profiling for food frauds, traceability and authenticity assessment

The ever-growing use of mass spectrometry (MS) methodologies in food authentication and traceability originates from their unrivalled specificity, accuracy and sensitivity. Such features are crucial for setting up analytical strategies for detecting food frauds and adulterations by monitoring selected components within food matrices. Among MS approaches, protein and peptide profiling has become increasingly consolidated. This review explores the current knowledge on recent MS techniques using protein and peptide biomarkers for assessing food traceability and authenticity, with a specific focus on their use for unmasking potential frauds and adulterations. We provide a survey of the current state-of-the-art instrumentation including the most reliable and sensitive acquisition modes highlighting advantages and limitations. Finally, we summarize the recent applications of MS to protein/peptide analyses in food matrices and examine their potential in ensuring the quality of agro-food products.

Efficacy of using stable isotopes coupled with chemometrics to differentiate the production method and geographical origin of farmed salmonids

The δ²H and δ¹⁸O of 105 salmonids cultured in freshwater and seawater and from different regions were combined with linear discriminant analysis (LDA), k-nearest neighbor (KNN), and random forest (RF) to create discrimination models. To assess the stability of the discrimination models, seasonal variation in δ²H and δ¹⁸O in salmonids cultured in different systems was studied. δ²H and δ¹⁸O were significantly different between salmonids cultured in freshwater and seawater and from different geographical origins. δ²H and δ¹⁸O of salmonids cultured in an open system were vulnerable to seasonal effects. The KNN model had 100% accuracy for identifying the production methods of salmonids and was less affected by seasonal variation. The RF model had the highest accuracy for identifying the geographical origins of salmonids with an accuracy of over 80%. Thus, δ²H and δ¹⁸O were more effective for identifying the production methods of salmonids than their geographical origins.

Determining the geographical origin of milk by multivariate analysis based on stable isotope ratios, elements and fatty acids

To construct a reliable discrimination model for determining milk geographical origin, stable isotope ratios including δ¹³C, δ¹⁵N and δ¹⁸O, 51 elements and 35 fatty acids (FAs) in milk samples from Australia, New Zealand and Austria were detected and analyzed. It is found that all of the stable isotope ratios in the milk samples of Australia are the highest, followed by those of the samples from New Zealand and Austria. In addition, 14 elements and 8 FAs show different contents in the samples of different countries at the significance level of P < 0.05. Based on these results, a multivariate model with good robustness and predictive ability for authenticating milk origin (R²X = 0.693, Q² = 0.854) was successfully constructed. Element contents and stable isotope ratios are more reliable variables for milk origin discrimination and Rb, δ¹⁸O, Tl, Ba, Mo, Sr, δ¹⁵N, Cs, As, Eu, C20:4n6, Sc, C13:0, K, Ca and C16:1n7 are the critical markers in the multivariate model for verifying milk origin.

Assessment of multiple stable isotopes for tracking regional and organic authenticity of plant products in Hesse, Germany

As demand for regional and organically produced foodstuff has increased in Europe, the need has arisen to verify the products' origin and production method. For food authenticity tracking (production method and origin), we examined 286 samples of wheat (Triticum aestivum), potatoes (Solanum tuberosum), and apples (Malus domestica) from different regions in Germany for their stable isotope compositions of oxygen, hydrogen, carbon, nitrogen and sulphur. Single-variate authentication methods were used. Suitable isotope tracers to determine wheat's regional origin were δ¹⁸O and δ³⁴S. δ¹³C helped to distinguish between organic and conventional wheat samples. For the separation of the production regions of potatoes, several isotope tracers were suitable (e.g. δ¹⁸O, δ²H, δ¹⁵N, δ¹³C and δ³⁴S isotopes in potato protein), but only protein δ¹⁵N was suitable to differentiate between organic and conventional potato samples. For the apple samples, ²H and ¹⁸O isotopes helped to identify production regions, but no significant statistical differences could be found between organically and conventionally farmed apples. For food authenticity tracking, our study showed the need to take the various isotopes into account. There is an urgent need for a broad reference database if isotope measurements are to become a main tool for determining product's origin.

Preliminary Study on Tracing the Origin and Exploring the Relations between Growing Conditions and Isotopic and Elemental Fingerprints of Organic and Conventional Cavendish Bananas (Musa spp.)

The stable isotopic ratios and elemental compositions of 120 banana samples, Musa spp. (AAA Group, Cavendish Subgroup) cultivar Williams, collected from six countries (Colombia, Costa Rica, Dominica Republic, Ecuador, Panama, Peru), were determined by isotope ratio mass spectrometry and inductively coupled plasma mass spectrometry. Growing conditions like altitude, temperature, rainfall and production system (organic or conventional cultivation) were obtained from the sampling farms. Principal component analysis (PCA) revealed separation of the farms based on geographical origin and production system. The results showed a significant difference in the stable isotopic ratios (δ¹³C, δ¹⁵N, δ¹⁸O) and elemental compositions (Al, Ba, Cu, Fe, Mn, Mo, Ni, Rb) of the pulp and peel samples. Furthermore, δ¹⁵N was found to be a good marker for organically produced bananas. A correlation analysis was conducted to show the linkage of growing conditions and compositional attributes. The δ¹³C of pulp and peel were mainly negatively correlated with the rainfall, while δ¹⁸O was moderately positively (R values ~0.5) correlated with altitude and temperature. A moderate correlation was also found between temperature and elements such as Ba, Fe, Mn, Ni and Sr in the pulp and peel samples. The PCA results and correlation analysis suggested that the differences of banana compositions were combined effects of geographical factors and production systems. Ultimately, the findings contribute towards understanding the compositional differences of bananas due to different growing conditions and production systems linked to a defined origin; thereby offering a tool to support the traceability of commercial fruits.

Using Bioelements Isotope Ratios and Fatty Acid Composition to Deduce Beef Origin and Zebu Feeding Regime in Cameroon

The purpose of this study was to address the lack of knowledge regarding the stable isotopic composition of beef from zebu cattle reared in tropical Africa. Sixty beef carcasses belonging to the most common zebu breeds (Goudali, white Fulani, and red Mbororo) were selected and classified according to their subcutaneous fat color (white, cream or yellow). The stable isotope ratios of five bioelements—H, O, C, N, and S—in muscle fractions and the fatty acids composition were analyzed. Zebu meat from Cameroon shows peculiar δ¹³C values, related to the almost exclusive intake of grazed tropical grasses with photosynthetic cycle C4. It also shows δ²H and δ¹⁸O values higher than those reported in other areas of the world and correlated with the isotopic composition of animal drinking water. The white subcutaneous fat (“white type”) zebu showed higher δ²H and lower δ¹³C than the “yellow type”, that is correlated with a higher content of polyunsaturated fatty acid (PUFA) and a lower amount of saturated fatty acid (SFA) and monounsaturated fatty acid (MUFA). Multielement analysis seems to provide promising results for tracing the regional origin of Cameroon beef and some aspects of the livestock system, such as the nutritional status of the animals.

Spatial Fingerprinting: Horizontal Fusion of Multi-Dimensional Bio-Tracers as Solution to Global Food Provenance Problems

Building the capacity of efficiently determining the provenance of food products represents a crucial step towards the sustainability of the global food system. Despite species specific empirical examples of multi-tracer approaches to provenance, the precise benefit and efficacy of multi-tracers remains poorly understood. Here we show why, and when, data fusion of bio-tracers is an extremely powerful technique for geographical provenance discrimination. Specifically, we show using extensive simulations how, and under what conditions, geographical relationships between bio-tracers (e.g., spatial covariance) can act like a spatial fingerprint, in many naturally occurring applications likely allowing rapid identification with limited data. To highlight the theory, we outline several statistic methodologies, including artificial intelligence, and apply these methodologies as a proof of concept to a limited data set of 90 individuals of highly mobile Sockeye salmon that originate from 3 different areas. Using 17 measured bio-tracers, we demonstrate that increasing combined bio-tracers results in stronger discriminatory power. We argue such applications likely even work for such highly mobile and critical fisheries as tuna.

A Multi-Elements Isotope Approach to Assess the Geographic Provenance of Manila Clams (Ruditapes philippinarum) via Recombining Appropriate Elements

The increasing global consumption of seafood has led to increased trade among nations, accompanied by mislabeling and fraudulent practices that have rendered authentication crucial. The multi-isotope ratio analysis is considered as applicable tool for evaluating geographical authentications but requires information and experience to select target elements such as isotopes, through a distinction method based on differences in habitat and physiology due to origin. The present study examined recombination conditions of multi-elements that facilitated geographically distinct classifications of the clams to sort out appropriate elements. Briefly, linear discriminant analysis (LDA) analysis was performed according to several combinations of five stable isotopes (carbon (δ¹³C), nitrogen (δ¹⁵N), oxygen (δ¹⁸O), hydrogen (δD), and sulfur (δ³⁴S)) and two radiogenic elements (strontium (⁸⁷Sr/⁸⁶Sr) and neodymium (¹⁴³Nd/¹⁴⁴Nd)), and the geographical classification results of the Manila clam Ruditapes philippinarum from Democratic People’s Republic of Korea (DPR Korea), Korea and China were compared. In conclusion, linear discriminant analysis (LDA) with at least four elements (C, N, O, and S) including S revealed a remarkable cluster distribution of the clams. These findings expanded the application of systematic multi-elements analyses, including stable and radiogenic isotopes, to trace the origins of R. philippinarum collected from the Korea, China, and DPR Korea.

Prediction of stable isotopes and fatty acids in subcutaneous fat of Iberian pigs by means of NIR: A comparison between benchtop and portable systems

The potential of a portable Near Infrared spectrophotometer compared with that of NIR benchtop equipment is assessed to determine the¹³C/¹²C relationship of stable isotopes and the fatty acid content. 105 samples of subcutaneous fat of Iberian pigs collected at the time of their slaughter have been analyzed. The analysis of stable isotopes and gas chromatography were the methods of reference used. The samples were analyzed without prior handling (portable and benchtop NIR) and after extracting the fat (benchtop NIR). The results show that with the portable equipment it is possible to determine δ¹³C (‰), 12 fatty acids, and 5 summations of fatty acids (SFA, MUFA, PUFA, w3, and w6), while with the benchtop NIR equipment it is possible to measure δ¹³C (‰), 16 fatty acids, and the 5 summationsof fatty acids. The correlation coefficients of the portable equipment were slightly lower than those of the NIR benchtop equipment.

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.

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).

Regional Characterization Study of Fatty Acids and Tocopherol in Organic Milk as a Tool for Potential Geographical Identification

Reliable geographical identification can protect producers of excellent agroproducts, and also provide reliable purchasing information to satisfy consumers. Therefore, this study aimed to evaluate the regional and monthly variation in fatty acid (FA) and tocopherol (TOC) in organic milk (OM) and develop a geographical discriminant model of OM in Korea. In this study, OM had α-TOC and showed a regional or monthly difference of 3-5%. Moreover, C16:0, C18:1 n9 cis + trans, C18:0, and C14:0 were the predominant FAs in OM, and OM mostly had higher ∑UFA, including nutritionally desirable FAs; but lower ∑SFA among four regions or in April and August (p < 0.001). The model prepared using stepwise discriminant analysis showed a classification accuracy of 100% for original and cross-validated sample sets. Our results have characterized regional and monthly nutritional variations of OM, thereby potentially suggesting the applicability of a reliable Korean geographical identification labeling system using nutrient compositional analysis of OM.