A case study for geographical indication of organic milk in Korea using stable isotope ratios-based chemometric analysis

Effects of sampling time and location on the geographical origin traceability of protected geographical indication (PGI) Hongyuan yak milk: Based on stable isotope ratios

Hongyuan yak milk is a protected geographical indication (PGI) product of rich nutritional value, which is popular among consumers. Stable isotope ratio analysis (SIRA) is an effective way to protect the authenticity of the geographical origin of PGI products, and it is crucial to study the factors affecting stable isotopes. Firstly, we proved that the SIRA could be used to identify the geographical origin of Hongyuan yak milk, and that the identification accuracy in combination with δ13C and δ18O was 100 %. Secondly, we analyzed the effect of sampling selection on the stable isotopes of Hongyuan yak milk in practical applications, which showed that sampling time influenced the δ13C, δ2H, and δ18O, while the sampling locations did not. There were interactions between the effect of sampling time and location on δ2H and δ18O. These results provide a reliable method for identifying PGI products and also provide new guidance on sampling models.

Trace the origin of yak meat in Xizang based on stable isotope combined with multivariate statistics

In this study, the feasibility of tracing the origin of yak meat in Xizang Autonomous Region based on stable isotope combined with multivariable statistics was researched. The δ13C, δ15N, δ2H and δ18O in yak meat were determined by stable isotope ratio mass spectrometry, and the data were analyzed by analysis of variance, fisher discriminant analysis (FDA), back propagation (BP) neural network and orthogonal partial least squares discrimination analysis (OPLS-DA). The results showed that the δ13C, δ15N, δ2H and δ18O had significant differences among different origins (P < 0.05). The overall original correct discrimination rate of fisher discriminant analysis was 89.7 %, and the correct discrimination rate of cross validation was 88.2 %. The correct classification rate of BP neural network based on training set was 93.38 %, and the correct classification rate of BP neural network based on test set was 89.83 %. The OPLS-DA model interpretation rate parameter R2Y was 0.67, the model prediction rate parameter Q2 was 0.409, which could distinguish yak meat from seven different producing areas in Xizang Autonomous Region. The results showed that the origin of yak meat in Xizang Autonomous Region can be traced based on stable isotope combined with multivariate statistics.

Current State of Milk, Dairy Products, Meat and Meat Products, Eggs, Fish and Fishery Products Authentication and Chemometrics

Food fraud is a matter of major concern as many foods and beverages do not follow their labelling. Because of economic interests, as well as consumers' health protection, the related topics, food adulteration, counterfeiting, substitution and inaccurate labelling, have become top issues and priorities in food safety and quality. In addition, globalized and complex food supply chains have increased rapidly and contribute to a growing problem affecting local, regional and global food systems. Animal origin food products such as milk, dairy products, meat and meat products, eggs and fish and fishery products are included in the most commonly adulterated food items. In order to prevent unfair competition and protect the rights of consumers, it is vital to detect any kind of adulteration to them. Geographical origin, production methods and farming systems, species identification, processing treatments and the detection of adulterants are among the important authenticity problems for these foods. The existence of accurate and automated analytical techniques in combination with available chemometric tools provides reliable information about adulteration and fraud. Therefore, the purpose of this review is to present the advances made through recent studies in terms of the analytical techniques and chemometric approaches that have been developed to address the authenticity issues in animal origin food products.

Application of multiple stable isotopes to aid identification of the origin of regional and organic animal products in Hesse, Germany

There is an increasing global demand for regional and organic produce. However, the growth of these markets depends on consumers' trust. Thus, novel methods must be developed to aid the verification of the origin of produce. We built on our previous study to identify the geographical origin and production method of animal-derived food products. Thirty-samples of eggs, 99 of milk, 34 of beef, and 62 of pork were collected from different regions in central Germany and analysed for their stable isotopic composition. The analysis followed a single-variate authentification approach using five isotope signatures, δ18O, δ2H, δ13C, δ15N, and δ34S. The best-performing indicators for verification of the geographical origin were δ15N and δ34S for beef; δ18O, δ2H, and δ13C for milk, and δ2H and δ13C for pork. These tracers indicated statistically significant differences among regions with the exception of pork; the results recorded for eggs were inconclusive. It was possible to distinguish between production methods by means of δ15N and δ34S (beef); all five tracers (eggs), and δ13C, δ15N, and δ34S (milk). This study demonstrated how the analysis of stable isotopes can be employed to determine the geographic region of origin and production method of animal-derived products in Germany.

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.

How Chemometrics Can Fight Milk Adulteration

Adulteration and fraud are amongst the wrong practices followed nowadays due to the attitude of some people to gain more money or their tendency to mislead consumers. Obviously, the industry follows stringent controls and methodologies in order to protect consumers as well as the origin of the food products, and investment in these technologies is highly critical. In this context, chemometric techniques proved to be very efficient in detecting and even quantifying the number of substances used as adulterants. The extraction of relevant information from different kinds of data is a crucial feature to achieve this aim. However, these techniques are not always used properly. In fact, training is important along with investment in these technologies in order to cope effectively and not only reduce fraud but also advertise the geographical origin of the various food and drink products. The aim of this paper is to present an overview of the different chemometric techniques (from clustering to classification and regression applied to several analytical data) along with spectroscopy, chromatography, electrochemical sensors, and other on-site detection devices in the battle against milk adulteration. Moreover, the steps which should be followed to develop a chemometric model to face adulteration issues are carefully presented with the required critical discussion.

Near-infrared techniques for fraud detection in dairy products: A review

The dairy products sector is an important part of the food industry, and their consumption is expected to grow in the next 10 years. Therefore, the authentication of these products in a faster and precise way is required for the sake of public health. This review proposes the use of near-infrared techniques for the detection of food fraud in dairy products as they are faster, nondestructive, environmentally friendly, do not require sample preparation, and allow multiconstituent analysis. First, we have described frequent forms of food fraud in dairy products and the application of traditional techniques for their detection, highlighting gaps and counterproductive characteristics for the actual global food chain, as longer sample preparation time and use of reagents. Then, the application of near-infrared spectroscopy and hyperspectral imaging for the detection of food fraud mainly in cheese, butter, and yogurt are described. As these techniques depend on model development, the coverage of different dairy products by the literature will promote the identification of food fraud in a faster and reliable way.

Proposing Two Local Modeling Approaches for Discriminating PGI Sunite Lamb from Other Origins Using Stable Isotopes and Machine Learning

For the protection of Protected Geographical Indication (PGI) Sunite lamb, PGI Sunite lamb samples and lamb samples from two other banners in the Inner Mongolia autonomous region were distinguished by stable isotopes (δ¹³C, δ¹⁵N, δ²H, and δ¹⁸O) and two local modeling approaches. In terms of the main characteristics and predictive performance, local modeling was better than global modeling. The accuracies of five local models (LDA, RF, SVM, BPNN, and KNN) obtained by the Adaptive Kennard–Stone algorithm were 91.30%, 95.65%, 91.30%, 100%, and 91.30%, respectively. The accuracies of the five local models obtained by an approach of PCA–Full distance based on DD–SIMCA were 91.30%, 91.30%, 91.30%, 100%, and 95.65%, respectively. The accuracies of the five global models were 91.30%, 91.30%, 91.30%, 100%, and 91.30%, respectively. Stable isotope ratio analysis combined with local modeling can be used as an effective indicator for protecting PGI Sunite lamb.

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.

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.

Dietary homogenization and spatial distributions of carbon, nitrogen, and sulfur isotope ratios in human hair in South Korea

Dietary homogenization has progressed worldwide due to westernization and the globalization of food production systems. We investigated dietary heterogeneity in South Korea by examining the spatial distribution of carbon (C), nitrogen (N), and sulfur (S) isotope ratios using 264 human hair samples. Overall, variation in isotope values was small, indicating low dietary heterogeneity. We detected differences in δ13C, δ15N, and δ34S values between administrative provinces and metropolitan cities; inter-regional differences were typically < 1 ‰. Values of δ34S were significantly lower in hair samples from inland regions relative to those from coastal locations, and a similar pattern was observed in δ15N values. Understanding geographic variation in δ34S and δ15N values in human hair is useful for provenancing humans in South Korea.

The Provenance of Slovenian Milk Using 87Sr/86Sr Isotope Ratios

This work presents the first use of Sr isotope ratios for determining the provenance of bovine milk from different regions of Slovenia. The analytical protocol for the determination of ⁸⁷Sr/⁸⁶Sr isotope ratio was optimised and applied to authentic milk samples. Considerable variability of ⁸⁷Sr/⁸⁶Sr ratios found in Slovenian milk reflects the substantial heterogeneity of the geological background of its origin. The results, although promising, cannot discount possible inter-annual or annual variation of the Sr isotopic composition of milk. The ⁸⁷Sr/⁸⁶Sr ratios of groundwater and surface waters are in good correlation with milk, indicating that the Sr isotopic fingerprint in milk is reflective of cow drinking water. The ⁸⁷Sr/⁸⁶Sr ratio has the potential to distinguish between different milk production areas as long as these areas are characterised by geo-lithology. Discriminant analysis (DA) incorporating the elemental composition and stable isotopes of light elements showed that ⁸⁷Sr/⁸⁶Sr ratio together with δ¹³C_cas and δ¹⁵N_cas values have the main discrimination power to distinguish the Quaternary group (group 6) from the others. Group 1 (Cretaceous: Carbonate Rocks and Flysch) is associated with Br content, 1/Sr and δ¹⁸O_w values. The overall prediction ability was found to be 63.5%. Pairwise comparisons using OPLS-DA confirmed that diet and geologic parameters are important for the separation.

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.

Fatty Acid Composition of Cosmetic Argan Oil: Provenience and Authenticity Criteria

In this work, fatty-acid profiles, including trans fatty acids, in combination with chemometric tools, were applied as a determinant of purity (i.e., adulteration) and provenance (i.e., geographical origin) of cosmetic grade argan oil collected from different regions of Morocco in 2017. The fatty acid profiles obtained by gas chromatography (GC) showed that oleic acid (C18:1) is the most abundant fatty acid, followed by linoleic acid (C18:2) and palmitic acid (C16:0). The content of trans-oleic and trans-linoleic isomers was between 0.02% and 0.03%, while trans-linolenic isomers were between 0.06% and 0.09%. Discriminant analysis (DA) and orthogonal projection to latent structure-discriminant analysis (OPLS-DA) were performed to discriminate between argan oils from Essaouira, Taroudant, Tiznit, Chtouka-Aït Baha and Sidi Ifni. The correct classification rate was highest for argan oil from the Chtouka-Aït Baha province (90.0%) and the lowest for oils from the Sidi Ifni province (14.3%), with an overall correct classification rate of 51.6%. Pairwise comparison using OPLS-DA could predictably differentiate (≥0.92) between the geographical regions with the levels of stearic (C18:0) and arachidic (C20:0) fatty acids accounting for most of the variance. This study shows the feasibility of implementing authenticity criteria for argan oils by including limit values for trans-fatty acids and the ability to discern provenance using fatty acid profiling.

Milk Authentication: Stable Isotope Composition of Hydrogen and Oxygen in Milks and Their Constituents

This paper summarises the isotopic characteristics, i.e., oxygen and hydrogen isotopes, of Slovenian milk and its major constituents: water, casein, and lactose. In parallel, the stable oxygen isotope ratios of cow, sheep, and goat's milk were compared. Oxygen stable isotope ratios in milk water show seasonal variability and are also 18O enriched in relation to animal drinking water. The δ18Owater values were higher in sheep and goat's milk when compared to cow milk, reflecting the isotopic composition of drinking water source and the effect of differences in the animal's thermoregulatory physiologies. The relationship between δ18Omilk and δ18Olactose is an indication that even at lower amounts (>7%) of added water to milk can be determined. This procedure once validated on an international scale could become a reference method for the determination of milk adulteration with water.

Fatty Acids and Stable Isotope Ratios in Shiitake Mushrooms (Lentinula edodes) Indicate the Origin of the Cultivation Substrate Used: A Preliminary Case Study in Korea

Shiitake mushroom (Lentinula edodes) is commonly consumed worldwide and is cultivated in many farms in Korea using Chinese substrates owing to a lack of knowledge on how to prepare sawdust-based substrate blocks (bag cultivation). Consequently, issues related to the origin of the Korean or Chinese substrate used in shiitake mushrooms produced using bag cultivation have been reported. Here, we investigated differences in fatty acids (FAs) and stable isotope ratios (SIRs) in shiitake mushrooms cultivated using Korean and Chinese substrates under similar conditions (strain, temperature, humidity, etc.) and depending on the harvesting cycle. The total FA level decreased significantly by 5.49 mg∙g⁻¹ as the harvesting cycle increased (p < 0.0001); however, no differences were found in FAs between shiitake mushrooms cultivated using Korean and Chinese substrates. Linoleic acid was the most abundant FA, accounting for 77–81% of the total FAs during four harvesting cycles. Moreover, the SIRs differed significantly between the Korean and Chinese substrates, and the harvesting cycles resulted in smaller maximum differences in SIR values compared to those of the cultivation substrate origins. Our findings contribute to the identification of the geographical origin of shiitake mushrooms and may have potential applications in international shiitake-mushroom markets.