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Main text The CCQM Isotope Ratio Working Group (IRWG) determined that an additional key comparison of carbon isotope delta measurements was required to capture the progress of this field. Vials containing 0.25 mg of vanillin were prepared at NRC, and evaluated for bottle-to-bottle homogeneity prior to distribution to the eight participating institutes. Participants were able to choose any suitable method and reference materials for carbon isotope delta measurements, and report a carbon isotope delta value and the associated uncertainty, and analysis details. To determine the key comparison reference value (KCRV) and its associated uncertainty, the NRC in collaboration with the NIST, developed a multivariate Bayesian random laboratory effects model, which also incorporates the uncertainty due to bottle-to-bottle homogeneity and any correlations between the reported results that arise due to the use of common reference materials. The KCRV for this study was determined to be -25.833 ‰ relative to the VPDB, with associated uncertainty of 0.028 ‰, and expanded uncertainty of 0.056 ‰ (k=2). All the results reported by the participants in this study were considered equivalent to the KCRV. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/. The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

This paper focuses on the analysis and identification of two prehistoric lamps from Zgornje Radvanje (NE Slovenia). The analysis of the organic residues and experimental archaeology allowed us to characterize the fuel source and the wick remains of oval-formed ceramic artefacts from the Copper Age settlement. Infrared spectroscopy (ATR IR), GC-MS and GC-C-IRMS were used to study organic compounds in two archaeological samples, with comparative composition data yielding experiments with modern wicks, linseed oil and animal fats. ATR IR showed traces of plant fibres in the sample of charred residues from one of the lamps. A comparably higher frequency of straight-chain compounds with odd numbers of carbon atoms provided the extracted lipids from the ceramics of the second oval-formed ceramic artefact. We interpret these to mean that carbonised organic residues from the inner surface of the ceramic object are the result of smouldering, with the identified residues of plant fibres probably associated with the remnants of the wick. The GC-MS analysis showed a higher frequency of straight-chain compounds with odd numbers of carbon atoms (especially C15:0 fatty acids) together with two double bond positional isomers of C18:1 in the second oval-formed artefact. The presence of C18:2 and C18:3 fatty acids that are typical for linseed oils was also detected. These analysis together with GC-C-IRMS analysis suggest a predominant use of ruminant fat as fuel for lighting possibly in combination with plant oils. Burns similar to those on the original artefact were observed on replicas of the artefact after they were used as lamps.

An international project developed, quality-tested, and measured isotope-delta values of 10 new food matrix reference materials (RMs) for hydrogen, carbon, nitrogen, oxygen, and sulfur stable isotope-ratio measurements to support food authenticity testing and food provenance verification. These new RMs, USGS82 to USGS91, will enable users to normalize measurements of samples to isotope-delta scales. The RMs include (i) two honeys from Canada and tropical Vietnam, (ii) two flours from C3 (rice) and C4 (millet) plants, (iii) four vegetable oils from C3 (olive, peanut) and C4 (corn) plants, and (iv) two collagen powders from marine fish and terrestrial mammal origins. An errors-in-variables regression model included the uncertainty associated with the measured and assigned values of the RMs, and it was applied centrally to normalize results and obtain consensus values and measurement uncertainties. Utilization of these new RMs should facilitate mutual compatibility of stable isotope data if accepted normalization procedures are applied and documented.

The objective of this study was to optimize sample preparation using a microwave system (ULTRAWAVE) for the determination of the multi-elemental composition of fruit samples by inductively coupled plasma mass spectrometry (ICP-MS) detection. Standard reference materials, SRMs (SRM 1547 Peach Leaves, SRM 1570a Spinach Leaves, SRM 1568b Rice Flour, SRM 1567b Wheat Flour), grain RM 8436 Durum Wheat and fruit samples were digested in concentrate nitric acid (1 mL HNO3 or 2.5 mL HNO3) or a mixture of nitric acid and hydrogen peroxide (2.5 mL HNO3 and 1 mL H2O2) for simultaneous determination of 27 elements, Na, Mg, Al, P, S, K, Ca, V, Cr, Mn, Fe, Co, Cu, Zn, As, Se, Rb, Sr, Mo, Cd, Sn, Sb, Cs, Ba, Hg, Pb and U. Efficiency was evaluated using SRMs. The results indicated that there was no difference between either method. A more straightforward, economical and environmentally friendlier method of just using 1 mL of concentrate HNO3, which allows using smaller amounts of acid and avoiding H2O2, was proposed for fruits samples.

Gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) for the analysis of key volatile compounds sampled using headspace solid phase microextraction (HS-SPME) is an appropriate tool for authenticity assessment of apple aromas. The current research characterises 18 laboratory produced and 15 commercial apple recovery aroma samples, establishes a database of δ13C values of 16 aroma compounds with respect to their origin (synthetic and natural), and assesses the authenticity of commercially available aroma compounds. Analysis of so-called natural aroma products, revealed δ13C values that were within the expected authentic range although the data did reveal possible falsifications. The sensitivity of the method was evaluated through simple isotope mass balance calculation. Falsification identification is possible for most aromatic substances when the amount of added synthetic compound is in tens of percent.

The geographical classification and authentication of strawberries were attempted using discriminant and class-modelling methods applied to stable isotopes of light elements and elemental composition. The work involved creating a database of 92 authentic Slovenian strawberry samples and 32 imported samples. All samples were harvested between 2018 and 2020. A good geographical classification of Slovenian and non-Slovenian strawberries was obtained despite different production years using discriminant approaches. However, for verifying compliance with a given specification (geographical indications), a class-modelling approach was used to build an unbiased verification model. Class models generated by data-driven soft independent modelling of class analogy (DD-SIMCA) had high sensitivity (96% to 97%) and good specificity (81% to 91%) on a yearly basis, while a more generalised model combining total yearly data gave a lower specificity (63%). Of the 33 commercially available samples (test samples) with declared Slovenian origin, 39% were from outside of Slovenia.

An international project developed, quality-tested, and measured isotope−delta values of 10 new food matrix reference materials (RMs) for hydrogen, carbon, nitrogen, oxygen, and sulfur stable isotope-ratio measurements to support food authenticity testing and food provenance verification. These new RMs will enable users to normalize measurements of samples to isotope−delta scales. The RMs span a range of δ2HVSMOW values from −207.4 to −43.3 mUr or ‰, for δ13CVPDB from −30.60 to −13.72 mUr, for δ15Nair from +1.78 to +14.96 mUr, for δ18OVSMOW from +18.20 to +26.33 mUr, and for δ34SVCDT from −20.25 to +17.49 mUr. The RMs include (i) a pair of honeys from Canada and tropical Vietnam, (ii) flours from C3 (rice) and C4 (millet) plants, (iii) four vegetable oils from C3 (olive, peanut) and C4 (corn) plants, and (iv) collagen powders from marine fish and terrestrial mammal origins. After thorough homogenization of the bulk materials, multiple aliquots were sealed in glass under vacuum or noble gas to exclude oxygen and to potentially extend the shelf life to decades when stored at –18 °C in the dark. A total of six laboratories from five countries used various analytical approaches and instrumentation for two- or multiple-point isotopic normalization against international RMs. The use of reference waters and organic liquids in silver tubes allowed direct normalization of δ2H values of organic materials against isotopic reference waters following the principle of identical treatment, minimizing interference from atmospheric moisture. An errors-in-variables regression model that included the uncertainty associated with the measured and assigned values of the RMs was applied centrally to normalize results and obtain consensus values and measurement uncertainties reported here for new RMs USGS82 to USGS91. Because of exchangeable hydrogen and H2O in some RMs (especially in honeys, collagens, and flours), sample loading in contact with laboratory air and different types of pre-treatment can result in significant bulk δ2H variance. Utilization of these new RMs should foster mutual compatibility of δ2H values if harmonized technical/analytical approaches are followed and documented in data reports.

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 δ13Ccas 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.

The maternal diet and living environment can affect levels of chemical elements and fatty acid (FA) composition and their stable isotopes (δ13CFA) in human milk. Information obtained from questionnaires is frequently imprecise, thus limiting proper associations between external and internal exposures as well as health effects. In this study, we focused on seafood as a source of potentially toxic and essential elements and nutritional FAs. Concentrations of selected elements in human milk (As, Cd, Cu, Mn, Pb, Se and Zn) were determined using inductively coupled plasma mass spectrometry (ICP-MS) and Hg using cold vapour atomic-absorption spectrometry (CV-AAS). The identification and quantification of FAs in maternal milk were performed by an in-situ trans-esterification method (FAMEs), and the characterization of FAMEs was performed by gas chromatography with a flame ionisation detector (GC-FID). δ13CFA was determined by gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS). Seventy-four lactating Slovenian women from the coastal area of Koper (KP), with more frequent consumption of seafood, and the inland area of Pomurje (MS), with less frequent seafood consumption, were included in this study. Along with basic statistical analyses, data mining approaches (classification and clustering) were applied to investigate whether FA composition and δ13CFA could improve the information regarding dietary sources of potentially toxic elements. As and Hg levels in milk were found to be statistically higher in populations from KP than in those from MS, and 71% of individual FAs and 30% of individual δ13CFA values in milk differed statistically between the studied areas. In 19 cases, the levels of FAs in milk were higher in KP than in MS; these FAs include C20:5ω3 and C22:6ω3/C24:1ω9, which are typically contained in fish. In 16 cases, the mean percentage of FAs was higher in MS than in KP; these FAs include the PUFAs C18:2ω6, C18:3ω3, and C20:4ω6 which are important for human and infant growth. The difference in δ13C levels of C10:0, C12:0, C14:0, C16:1, C16:0, C18:1ω9c, C22:6ω3, and δ13C 18:0-16:0 in the study groups was statistically significant. In all seven cases where δ13C of FA significantly differed between KP and MS, δ13C was higher in KP, indicating a higher proportion of a marine-based diet. The data mining approaches confirmed that the percentage of selected FAs (iC17:0, C4:0, C18:2ω6t, aC17:0, CLA, and C22:4ω6) and δ13CFA of C18:1ω9c in human milk could be used to distinguish between high and low frequency of fresh seafood consumption.

The quantity and composition of fatty acids (FAs) in milk can influence an infant's growth and development through maternal diet. Therefore, associations between maternal diet and FA composition in 74 mature human milk samples were investigated. This study aimed to obtain FA patterns in mature milk arising from different dietary habits in two geographically different areas in Slovenia: Koper (KP), a coastal area, and Pomurje (MS), an inland area. The results revealed statistically significant differences in the dietary intake of game, freshwater fish, and fresh and frozen seafood between the study areas. Among the mean percentages of 35 individual FAs in milk, 19 were higher in KP and 16 were higher in MS. In KP, despite the higher intake of fresh seafood, the levels of saturated and monounsaturated FAs were higher and the levels of PUFAs, ω-3, and ω-6 were lower compared to those in MS. The ω-6:ω-3 ratio did not differ significantly between the study areas. This finding was not expected and indicates a discrepancy between the measured and self-reported data - the latter lack reliable data on dietary supplements. Therefore, determination of FA profile is important as a promising biomarker of dietary intake in environmental health studies.

To link and harmonize different knowledge repositories with respect to isotopic data, we propose an ISO-FOOD ontology as a domain ontology for describing isotopic data within Food Science. The ISO-FOOD ontology consists of metadata and provenance data that needs to be stored together with data elements in order to describe isotopic measurements with all necessary information required for future analysis. The new domain has been linked with existing ontologies, such as Units of Measurements Ontology, Food, Nutrient and the Bibliographic Ontology. To show how such an ontology can be used in practise, it was populated with 20 isotopic measurements of Slovenian food samples. Describing data in this way offers a powerful technique for organizing and sharing stable isotope data across Food Science.

Forensic application of carbon isotope ratio measurements of honey and honey protein to investigate the degree of adulteration with high fructose corn syrup or other C4 plant sugars is well established. These measurements must use methods that exhibit suitable performance criteria, particularly with regard to measurement uncertainty and traceability – low levels of adulteration can only be detected by methods that result in suitably small measurement uncertainties such that differences of 1‰ or less can be reliably detected. Inter-laboratory exercises are invaluable to assess the state-of-the art of measurement capabilities of laboratories necessary to achieve such performance criteria. National and designated metrology institutes from a number of countries recently participated in an inter-laboratory assessment (CCQM-K140) of stable carbon isotope ratio determination of bulk honey. The same sample material was distributed to a number of forensic isotope analysis laboratories that could not participate directly in the metrological comparison. The results from these studies have demonstrated that the majority of participants provided isotope delta values with acceptable performance metrics; that all participants ensured traceability of their results; and that where measurement uncertainties were reported; these were fit-for-purpose. A number of the forensic laboratories only reported precision rather than full estimates of measurement uncertainty and this was the major cause of the few instances of questionable performance metrics. Reporting of standard deviations in place of measurement uncertainties is common practice outside metrology institutes and the implications for interpretations of small differences in isotopic compositions are discussed. The results have also highlighted a number of considerations that are useful for organisers of similar inter-laboratory studies in the future.

The main objective in multi-elemental analysis in food is to obtain the best results in the shortest time and with minimal contamination and reagent consumption. Three different methods were investigated in the present study to obtain the elemental content in milk samples: energy dispersive X-ray fluorescence spectrometry (EDXRF), k0-instrumental nuclear activation analysis (k0-INAA) and the inductively coupled plasma mass spectrometry (ICP-MS). Quality assurance including intercomparison exercises of these measurements proved entirely satisfactory and was typical of that previously established for this technique. It was found that EDXRF was the cheapest, simplest and environmental friendly method for analysis of multi-elemental composition (P, S, Cl, K, Ca, Zn, Br, Rb, Sr) in milk samples, while for determination of Mn, Fe, Cu, Se content and possible identification of pollutants such as As, Cd and Pb ICP-MS was a method of choice due to its excellent sensitivity and accuracy. These two methods were also used to determine the multi-elemental composition in Slovenian raw cow milk from different geographical regions: Alpine, Mediterranean. Dinaric and Panoninan in December 2013. Linear discriminant analysis (LDA) was used to explore multi-elemental analysis of milk samples to obtain classification according to geographical regions. Regional discrimination was most successful taking into account Ca, S, P, K, and Cl with prediction ability of 66.7%.