Multielemental + isotopic fingerprint enables linking soil, water, forage and milk composition, assessing the geographical origin of Argentinean milk

Evaluating Source Complexity in Blended Milk Cheese: Integrated Strontium Isotope and Multi-Elemental Approach to PDO Graviera Naxos

Graviera Naxos, a renowned cheese with Protected Designation of Origin status, is crafted from a blend of cow, goat, and sheep milk. This study focused on assessing the Sr isotopic and multi-elemental composition of both the processed cheese and its ingredients, as well as the environmental context of Naxos Island, including samples of milk, water, soil, and feed. The objective was to delineate the geochemical signature of Graviera Naxos cheese and to explore the utility of Sr isotopes as indicators of geographic origin. The 87Sr/86Sr values for Graviera Naxos samples ranged from 0.70891 to 0.70952, indicating a relatively narrow range. However, the Sr isotopic signature of milk, heavily influenced by the feed, which originates from geologically distinct areas, does not always accurately reflect the local breeding environment. Multi-elemental analysis revealed variations in milk composition based on type and season; yet, no notable differences were found between raw and pasteurized milk. A mixing model evaluating the contributions of milk, sea salt, and rennet to the cheese's Sr isotopic signature suggested a significant average contribution of 73.1% from sea salt. This study highlights the complexities of linking dairy products with their geographical origins and emphasizes the need for sophisticated geochemical authentication methods.

Elemental Profile in Chicken Egg Components and Associated Human Health Risk Assessment

Egg is a food product of high nutritional quality, extensively consumed worldwide. The objectives of this study were the determination of the elemental profile in eggs (egg white, yolk, and eggshell), the estimation of the non-carcinogenic health risk associated with the presence of heavy metals in investigated egg samples, and the development of statistical models to identify the best predictors for the differentiation of egg components. The assessments were carried out in a total set of 210 samples, comprising home-produced and commercial eggs, using inductively coupled plasma mass spectrometry. The results suggested measurable differences amongst hen eggs coming from different husbandry systems. The statistical models employed in this study identified several elemental markers that can be used for discriminating between market and local producer samples. The non-carcinogenic risk related to the consumption of the analyzed egg samples was generally in the safe range for the consumers, below the maximum permitted levels set by Romanian and European legislation. Food contamination is a public health problem worldwide, and the risk associated with exposure to trace metals from food products has aroused widespread concern in human health, so assessing the heavy metal content in food products is mandatory to evaluate the health risk.

Effect of cocooning conditions on the structure, carbon and nitrogen isotope ratios of silks

The stable isotope technique provides the possibility to trace ancient textiles because the technique is associated with advantages such as trace indication, fast detection, and accurate results. Since different cocooning conditions may impact cocoons even under identical habitats, it is important to investigate the effects of different cocooning temperatures and humidity on the isotope incorporation values in the cocoons. In this study, silk fibers were reeled under different conditions of temperature and humidity, followed by analysis of the secondary structure of cocoon proteins and isotope incorporation patterns. We found that the deviations in carbon isotope values of silk under different cocooning conditions could reach up to 0.76‰, while the deviation in carbon isotope values at different locations of a single silk was 2.75‰. Further, during the cocooning process, depletion of the 13C-isotope at different locations of the silk fibers was observed, reducing the δ13C values. We proposed that the changes in carbon isotopes in silk were related to the content of sericin and silk fibroin in silk. Finally, we did not observe a significant difference in isotope ratios in degummed cocoons. In summary, the 13C isotope was enriched in sericin, whereas 15N was enriched in fibroin, and these findings provide basic information for tracing the provenance of silks.

Exploring the Potential of 87Sr/86Sr Isotope Ratio with Strontium and Rubidium Levels to Assess the Geographic Origin of Saffron

Saffron is regarded as the most expensive spice, mainly because of its laborious harvest. Only a few countries dominate the global saffron market, with Iran producing by far the most saffron, and the saffron production of all other countries thus being much smaller. However, the respective national production (not only of saffron) is usually preferred by local consumers with respect to foreign products and often has a higher price. Cases of saffron with mislabeled geographic origin have repeatedly occurred. Thus, to protect local saffron production, control of the declared geographic origin is required. In the present case, differentiation of the geographic origin by 87Sr/86Sr is performed. The results show the saffron of several countries of origin to vary within the range of marine carbonates; however, saffron samples of Moroccan and Indian origin mainly show elevated 87Sr/86Sr values. Within the Indian saffron samples, one sample from Kishtwar Valley can be differentiated from the Kashmir saffron samples. The results are thus promising, especially when using the combination of Sr and Rb concentrations to differentiate geographic origin whenever the regions are of homogenous bedrock geology within and of different geology between the regions. However, the reported findings need to be checked and confirmed by further and additional saffron samples.

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.

Impact of Potentially Toxic Compounds in Cow Milk: How Industrial Activities Affect Animal Primary Productions

Potentially toxic elements (PTEs) and polycyclic aromatic hydrocarbons (PAHs) frequently coexist in soils near industrial areas and sometimes in environmental compartments directly linked to feed (forage) and food (milk) production. However, the distribution of these pollutants along the dairy farm production chain is unclear. Here, we analyzed soil, forage, and milk samples from 16 livestock farms in Spain: several PTEs and PAHs were quantified. Farms were compared in terms of whether they were close to (<5 km) or far away from (>5 km) industrial areas. The results showed that PTEs and PAHs were enriched in the soils and forages from farms close to industrial areas, but not in the milk. In the soil, the maximum concentrations of PTEs reached 141, 46.1, 3.67, 6.11, and 138 mg kg^-1 for chromium, arsenic, cadmium, mercury, and lead, respectively, while fluoranthene (172.8 µg kg^-1) and benzo(b)fluoranthene (177.4 µg kg^-1) were the most abundant PAHs. Principal component analysis of the soil PTEs suggested common pollution sources for iron, arsenic, and lead. In the forage, the maximum contents of chromium, arsenic, cadmium, mercury, and lead were 32.8, 7.87, 1.31, 0.47, and 7.85 mg kg^-1, respectively. The PAH found in the highest concentration in the feed forage was pyrene (120 µg kg^-1). In the milk, the maximum PTE levels were much lower than in the soil or the feed forages: 74.1, 16.1, 0.12, 0.28, and 2.7 µg kg^-1 for chromium, arsenic, cadmium, mercury, and lead, respectively. Neither of the two milk samples exceeded the 20 µg kg^-1 limit for lead set in EU 1881/2006. Pyrene was the most abundant PAH found in the milk (39.4 µg kg^-1), while high molecular weight PAHs were not detected. For PTEs, the results showed that soil-forage transfer factors were higher than forage-milk ratios. Our results suggest that soils and forages around farms near industries, as well as the milk produced from those farms, have generally low levels of PTE and PAH contaminants.

Atrazine pollution in groundwater and raw bovine milk: Water quality, bioaccumulation and human risk assessment

Atrazine herbicide can bioaccumulate over time and thus affect humans for generations to come. However, scarce studies have evaluated its bioaccumulation potential in bovine milk, a nutritional staple for children and the elderly both domestically and internationally. This study aimed to determine its concentration in groundwater and bovine milk, as well as the risks it is likely to pose for human health. Eighteen dairy farms in the Pampean plain of Argentina were analyzed. A strong correlation was found between the chemical composition and the geomorphological characteristics of the plain. In addition, increased salinity was observed in the groundwater at greater distances from the aquifer's recharge area. Atrazine was quantified in 50 % of the groundwater samples (at values ranging from 0.07 to 1.40 μg/L), and in 89 % of the bovine milk samples (from 2.51 to 20.97 μg/L). Moreover, atrazine levels in 44.4 % of the groundwater samples and 11.1 % of the bovine milk samples (n = 18) exceeded the limits internationally established as safe for human consumption. The hazard quotient (HQ) values of the compound were negligible for children and adults, both in groundwater (child = 9.7E-4, adult = 4.5E-4) and in milk (child = 1.0E-2, adult = 1.6E-3). The estimated cancer risk (CR) values need further evaluation (child = 7.8E-6, adult = 3.6E-6 in groundwater; child = 6.6E-5, adult = 1.3E-5 in milk). In both types of samples, the HQ and CR of residual atrazine were higher for children than for adults. Nevertheless, bioaccumulation factors suggest that dairy cows have a moderate capacity to incorporate atrazine from abiotic matrices. This is the first report on residual atrazine in bovine milk in Argentina. The results presented here indicate that the status of atrazine contamination in the area should continue to be monitored in order to assess its long-term impact on public health.

Differentiation of Apricots of Different Geographic Origin in Central and Southern Europe by Applying 87Sr/86Sr Analysis: Potential and Limitations

Consumers prefer food commodities of certain origins over the same products of other provenances and are willing to pay higher prices for them. Thus, it is possible to increase profit simply by giving an incorrect geographic origin to a product. To effectively control the declared geographic origin of food, the product itself has to be investigated to discover whether it actually originates from the declared origin, or if it has been mislabeled. Conventionally, control of a geographic origin is conducted by stable isotope analysis of the main elements, which has proven to be successful in numerous cases, but often reference data have to be produced anew for every harvest to control, resulting in additional costs and delays. Applying entirely geogenic parameters for the control of provenance requires reference data to be produced only once. As they do not vary between years and harvests, they can often be used for different (food) commodities. Here, we investigate whether the geographic origin of apricot samples can be controlled by their 87Sr/86Sr ratios measured by TIMS. The results show that Slovak and Hungarian apricots can be differentiated from the Wachau apricots, a well-known regional Austrian brand, and those from other regions in Austria, even though the differentiation from the latter is only partial. 87Sr/86Sr investigations can be a very potent tool; however, its success depends on the exact question that needs to be answered.

An overview on multi-elemental profile integrated with chemometrics for food quality assessment: toward new challenges

Food products, especially those with high value-added, are commonly subjected to strict quality controls, which are of paramount importance, especially for attesting to some peculiar features related, for instance, to their geographical origin and/or the know-how of their producers. However, the sophistication of fraudulent practices requires a continuous update of analytical platforms. Different analytical techniques have become extremely appealing since the instrumental analysis tools evolution has substantially improved the capability to reveal and understand the complexity of food. In light of this, multi-elemental composition has been successful implemented solving a plethora of food authentication and traceability issues. In the last decades, it has existed an ever-increasing trend in analysis based on spectrometry analytical platforms in order to obtain a multi-elemental profile that combined with chemometrics have been noteworthy analytical methodologies able to solve these problems. This review provides an overview of published reports in the last decade (from 2011 to 2021) on food authentication and quality control from their multi-element composition in order to evaluate the state-of-the-art of this field and to identify the main characteristics of applied analytical techniques and chemometric data treatments that have permit achieve accurate discrimination/classification models, highlighting the strengths and the weaknesses of these methodologies.

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.

Differentiation Between Argentine and Austrian Red and White Wines Based on Isotopic and Multi-Elemental Composition

In this work, the characterization of white and red wines from Austria and Argentina was carried out based on the isotopic and multi-elemental profile data. They were determined using vanguard techniques such as isotope ratio mass spectrometry and inductively coupled plasma mass spectrometry. In particular, Al, As, B, Ca, Co, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Pb, Rb, Sr, V, Zn, δ18O, and δ13C were determined. The results show that the samples of wines from Argentina generally present higher concentrations of the elements analyzed compared to Austrian wines. δ18O values from wine water were characteristic of each country, while δ13C values from ethanol did not present any geographical distinction. Linear discriminant analysis using isotopes and elements allowed us to classify 100% of the wines according to the origin and additionally, 98.4% when separately investigating red and white wines. The elements Sr, Li, V, Pb, B, Mn, Co, Rb, As, Na, Mg, Zn, and δ18O were identified as sensitive indicators capable of differentiate wines according to their production origin. Furthermore, Sr, Li, Na, δ13C, δ18O, Ca, B, Fe, Mn, V, Mg, Co, and Zn contributed to the differentiation of wines according to origin and color. To our knowledge, it is the first work that involves the measurement of a wide range of elements and stable isotopes in white and red wines in Argentina, as well as in Austria. This research highlights the power of the application of stable isotopes and multi-element data in multivariate statistical analysis, in order to obtain an accurate differentiation of wines origin.

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.

Determination of geographical origin of concentrated apple juice through analysis of stable isotopic and mineral elemental fingerprints: preliminary results

BACKGROUND

With increasing attention being paid to food authenticity, the geographic origin of food has become a topic of interest for both consumers and producers. As far as we know, there are relatively few studies on the origin traceability of concentrated apple juice. The most commonly used methods of origin tracing research is by using stable isotopes and mineral elements technology, because these indicators are directly related to local geographical environment.

RESULTS

In this study, a discriminant model was established by determining the content of the stable isotopes (δ¹³ C, δ¹⁸ O) and 13 mineral elements (B, Mn, Co, Ni, Cu, Sr, V, Ba, Fe, Mg, Na, Ca and Cr) in concentrated apple juice. Linear discriminant analysis (LDA), principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were employed for regional classification of samples. After data conversion and correlation analysis, spatial and quantitative prediction models were established using multiple linear regressions. Finally, the experimental results showed that the eight key variables(δ ¹³ C, δ ¹⁸ O, B, Ca, Mg, Cu, Sr and Na) selected by the analysis can be used to further characterize the production area.

CONCLUSION

The results showed that the carbon and oxygen isotopes combined with certain mineral elements can be used to indicate the origin of concentrated apple juice. © 2020 Society of Chemical Industry.

Chemical Analysis Combined with Multivariate Statistical Methods to Determine the Geographical Origin of Milk from Four Regions in China

Traceability of milk origin in China is conducive to the implementation of the protection of regional products. In order to distinguish milk from different geographical distances in China, we traced the milk of eight farms in four neighboring provinces of China (Inner Mongolia autonomous region, Hebei, Ningxia Hui autonomous and Shaanxi), and multivariate data analysis was applied to the data including elemental analysis, stable isotope analysis and fatty acid analysis. In addition, orthogonal partial least squares discriminant analysis (OPLS-DA) is used to determine the optimal classification model, and it is explored whether the combination of different technologies is better than a single technical analysis. It was confirmed that in the inter-provincial samples, the combination of the two techniques was better than the analysis using a single technique (fatty acids: R² = 0.716, Q² = 0.614; fatty acid-binding isotopes: R² = 0.760, Q² = 0.635). At the same time, milk produced by farms with different distances of less than 11 km in each province was discriminated, and the discriminant distance was successfully reduced to 0.7 km (Ningxia Hui Autonomous Region: the distance between the two farms was 0.7 km, R² = 0.771, Q² = 0.631). For short-distance samples, the combination multiple technologies are not completely superior to a single technique, and sometimes, it is easy to cause model over-fitting.

Discrimination of goat, buffalo, and yak milk from different livestock, regions, and lactation using microelement contents

This study aims at investigating whether the livestock, lactation stage, or geographical origin of specialty milk in China could be classified by the elemental contents. Samples of goat, buffalo, and yak milk were collected from main production provinces in China and the contents of nine elements in milk from different livestock, regions, and lactation stages were determined. Statistical analysis indicated that the contents of Mn, Cu, As, Se, Cs, and Mo in mature milk were significantly different between the three livestock (p < 0.05). The trends of Mn and Cs contents of the goat milk and buffalo milk increased first and then decreased gradually during lactation. The contents of Se, Cs, Ba, and Mo in mature milk of three livestock were significantly different between the three regions (p < 0.05). The result of linear discriminant analysis (LDA) and partial least squares discrimination analysis (PLS-DA) showed that the total correct classification rates in different livestock for mature milk reached 86.7 and 90%. For goat milk, the total correct classification rates of different lactations and regions reached 88.9 and 77.8% for LDA (100 and 87.5% for PLS-DA), and followed by yak milk of different regions which achieved 88.9% for LDA (88.9% for PLS-DA). In summary, the microelements in milk showed a significant correlation with livestock, region, and lactation of goat, buffalo, and yak milk. The elemental fingerprints combined with the LDA could be potential for classifying the livestock, lactation stage, and geographical origin of milk. PRACTICAL APPLICATION: According to study the contents of miroelements in milk from different livestock, regions, and lactation stages, provide evidence and support for classifying the livestock, lactation stage, and geographical origin of milk.

Authentication and Traceability Study on Barbera d’Asti and Nizza DOCG Wines: The Role of Trace- and Ultra-Trace Elements

Barbera d’Asti—including Barbera d’Asti superiore—and Nizza are two DOCG (Denominazione di Origine Controllata e Garantita) wines produced in Piemonte (Italy) from the Barbera grape variety. Differences among them arise in the production specifications in terms of purity, ageing, and zone of production, in particular with concern to Nizza, which follows the most stringent rules, sells at three times the average price, and is considered to have the highest market value. To guarantee producers and consumers, authentication methods must be developed in order to distinguish among the different wines. As the production zones totally overlap, it is important to verify whether the distinction is possible or not according to metals content, or whether chemical markers more linked to winemaking are needed. In this work, Inductively Coupled Plasma (ICP) elemental analysis and multivariate data analysis are used to study the authentication and traceability of samples from the three designations of 2015 vintage. The results show that, as far as elemental distribution in wine is concerned, work in the cellar, rather than geographic provenance, is crucial for the possibility of distinction.

Geographical verification of Slovenian milk using stable isotope ratio, multi-element and multivariate modelling approaches

This work examines the use of stable isotopes and elemental composition for determining geographical origin and authenticity of cow milk from four geographical regions of Slovenian. Samples (277) were collected during summer and winter (2012-2014). It was possible to discriminate milk samples according to the year, season and production region using discriminant analysis (DA). The overall temporal prediction variability was 84.6% and 56.4% for regional differences. It was also possible to discriminate milk from three geographic regions, although Alpine samples overlap with Dinaric and Pannonian ones. Prediction ability was the highest for the Pannonian (82.1%) and lowest (26.9%) for the Alpine region. Pairwise comparison using OPLS-DA also displaying good regional predictability (≥0.77) with δ¹³C_cas values and Br content carrying the most variance. A model based on DD-SIMCA was also developed and applied to the control of Slovenian milk. The results revealed the mislabeling of three Slovenian milk products.

Carbon and Nitrogen Isotope Ratios of Food and Beverage in Brazil

Several previous studies on targeted food items using carbon and nitrogen stable isotope ratios in Brazil have revealed that many of the items investigated are adulterated; mislabeled or even fraud. Here, we present the first Brazilian isotopic baseline assessment that can be used not only in future forensic cases involving food authenticity, but also in human forensic anthropology studies. The δ13C and δ15N were determined in 1245 food items and 374 beverages; most of them made in Brazil. The average δ13C and δ15N of C3 plants were -26.7 ± 1.5‱, and 3.9 ± 3.9‱, respectively, while the average δ13C and δ15N of C4 plants were -11.5 ± 0.8‱ and 4.6 ± 2.6‱, respectively. The δ13C and δ15N of plant-based processed foods were -21.8 ± 4.8‱ and 3.9 ± 2.7‱, respectively. The average δ13C and δ15N of meat, including beef, poultry, pork and lamb were -16.6 ± 4.7‱, and 5.2 ± 2.6‱, respectively, while the δ13C and δ15N of animal-based processed foods were -17.9 ± 3.3‱ and 3.3 ± 3.5‱, respectively. The average δ13C of beverages, including beer and wine was -22.5 ± 3.1‱. We verified that C-C4 constitutes a large proportion of fresh meat, dairy products, as well as animal and plant-based processed foods. The reasons behind this high proportion will be addressed in this study.