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

Application of stable isotopes and mineral elements fingerprinting for beef traceability and authenticity in inner mongolia of China

In recent years, the origin and safety of counterfeit meat products have raised significant concerns among consumers. Therefore, there was an urgent need to develop a new method using fingerprinting techniques for meat product traceability. This study aimed to evaluate the traceability and authenticity of beef from Inner Mongolia by measuring the δ13C and δ15N values, as well as 13 mineral elements. In the complex environment of feeding regimes and agricultural types, δ15N, δ13C, and Se were selected as characteristic variables to differentiate feeding regimes, while Fe, K, Tl, Sr, Mn, and δ13C were chosen as characteristic variables for tracing the origin of the beef. Linear discriminant analysis achieved an accuracy rate of up to 100 %. This research confirmed the effectiveness of combining stable isotopes with mineral elements in accurately determining the origin of Inner Mongolian beef and verifying the authenticity of typical feed, providing a valuable strategy for traceability.

Beef Traceability Between China and Argentina Based on Various Machine Learning Models

Beef, as a nutrient-rich food, is widely favored by consumers. The production region significantly influences the nutritional value and quality of beef. However, current methods for tracing the origin of beef are still under development, necessitating effective approaches to ensure food safety and meet consumer demand for high-quality beef. This study aims to establish a classification model for beef origin prediction by analyzing elemental content and stable isotopes in beef samples from two countries. The concentrations of elements in beef were analyzed using ICP-MS and ICP-OES, while the stable carbon isotope ratio was determined using EA-IRMS. Machine learning algorithms were employed to construct classification prediction models. A total of 83 beef samples were analyzed for the concentrations of 52 elements and the stable carbon isotope ratio. The classification accuracy of the PLS-DA model built on these results was 98.8%, while the prediction accuracy was 94.12% for the convolutional neural network (CNN) and 82.35% for the Random Forest algorithm. The PLS-DA model demonstrated higher classification accuracy compared to CNN and Random Forest, with an explanatory power (R2) of 0.924 and predictive ability (Q2) of 0.787. Combining the analysis of 52 elements and the stable carbon isotope ratio with machine learning algorithms enables effective tracing and origin prediction of beef from different regions. Key factors influencing beef origin were identified as Fe, Cs, As, δ13C, Co, V, Sc, Rb, and Ru.

Interactions between arbuscular mycorrhizal fungi and phosphate-soluble bacteria affect ginsenoside compositions by modulating the C:N:P stoichiometry in Panax ginseng

The biomass production as well as the accumulation of secondary metabolites of plant is highly determined by the absorption of nutritional elements, in particular nitrogen (N) and phosphorus (P). Arbuscular mycorrhizal fungi (AMF) can absorb soluble P and transport it to plants, while phosphate solubilizing bacteria (PSB) can increase the content of solubilizing P in soil. Previous studies have identified the effects of either AMF or PSB inoculation on altering plant C:N:P stoichiometry, whether AMF interact with PSB in promoting plant growth and changing elemental concentration and composition of secondary metabolites by altering plant C:N:P stoichiometry remains ambiguous. In this study, we investigated the effects of inoculation of AMF, PSB, and their co-inoculation AMP (AMF and PSB) on the biomass growth, the C:N:P stoichiometry, the core microorganisms of rhizosphere soil, and the ginsenoside compositions of ginseng (Panax ginseng). The results showed that compared to control or single inoculation of AMF or PSB, co-inoculation of AMF and PSB significantly increased the AMF colonization rate on ginseng roots, increased the biomass of both above and under-ground parts of ginseng. Similarly, co-inoculation of AMF and PSB substantially increased the concentrations of N and P, reduced the ratios of C:P and N:P in the above-ground part of ginseng. The co-inoculation of AMF and PSB also increased concentrations of total ginsenosides and altered the compositions of ginsenosides in both the above and under-ground parts of ginseng. Analysis the rhizosphere microorganism showed that the co-inoculation of AMF and PSB recruited distinct core microorganisms that differ from the control and treatments with single inoculation of AMF or PSB. Our results suggested that PSB inoculation enhanced the positive effect of AMF in improving the absorption of nutrimental elements, altered the C:N:P stoichiometry and, ginsenosides concentration and composition of ginseng, influenced the plant rhizosphere microbial community. These findings offer valuable insights into enhancing plant biomass production and promoting secondary metabolites by improving the plant-fungi-bacterial relationships.

A Whole Range of Cattle-An Isotopic Perspective on Roman Animal Husbandry in Lower Austria and Burgenland (Austria)

In this study, we try to combine traditional archaeozoological biometry, based on outer bone measurements, with stable isotope analyses of bone collagen. Right from the start of archaeozoological research in Central and Western Europe, the important size variability in Roman domestic cattle has puzzled scholars. According to an established view, these differences in bone size are attributed either to the simultaneous presence of different types or even breeds or to the result of crossbreeding of smaller, native, and larger Roman cattle. Likewise, the episodic import of large-sized animals has been considered. First, we selected thirty proximal phalanges of cattle from three sites including five archaeological contexts from eastern Austria (Roman provinces of Noricum and Pannonia). The bone sample comprised the whole hitherto observed metric variability in Roman provincial cattle, and we tried to include minimal and maximal specimens. The results from stable isotope analyses (δ15N, δ13C, δ18O, δ2H) carried out on thirty proximal phalanges indicated that isotope signals were rather site-specific and, generally, not related to bone size. Therefore, we conclude that at least in the area investigated, small and large cattle types were raised and herded in the same areas and not spatially separated. There are, however, uncertain indicators of intra-site differences in isotope signals related to bone size, which should be checked on much larger sample sets.

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.

Aromatic Characterisation of Moscato Giallo by GC-MS/MS and Validation of Stable Isotopic Ratio Analysis of the Major Volatile Compounds

Among the Moscato grapes, Moscato Giallo is a winegrape variety characterised by a high content of free and glycosylated monoterpenoids, which gives wines very intense notes of ripe fruit and flowers. The aromatic bouquet of Moscato Giallo is strongly influenced by the high concentration of linalool, geraniol, linalool oxides, limonene, α-terpineol, citronellol, hotrienol, diendiols, trans/cis-8-hydroxy linalool, geranic acid and myrcene, that give citrus, rose, and peach notes. Except for quali-quantitative analysis, no investigations regarding the isotopic values of the target volatile compounds in grapes and wines are documented in the literature. Nevertheless, the analysis of the stable isotope ratio represents a modern and powerful tool used by the laboratories responsible for official consumer protection, for food quality and genuineness assessment. To this aim, the aromatic compounds extracted from grapes and wine were analysed both by GC-MS/MS, to define the aroma profiles, and by GC-C/Py-IRMS, for a preliminary isotope compound-specific investigation. Seventeen samples of Moscato Giallo grapes were collected during the harvest season in 2021 from two Italian regions renowned for the cultivation of this aromatic variety, Trentino Alto Adige and Veneto, and the corresponding wines were produced at micro-winery scale. The GC-MS/MS analysis confirmed the presence of the typical terpenoids both in glycosylated and free forms, responsible for the characteristic aroma of the Moscato Giallo variety, while the compound-specific isotope ratio analysis allowed us to determine the carbon (δ13C) and hydrogen (δ2H) isotopic signatures of the major volatile compounds for the first time.

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.

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.

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.