Optimization and validation of an HS-SPME/GC-MS method for determining volatile organic compounds in dry-cured ham.

The formation of volatile organic compounds (VOCs) in dry-cured ham is a result of different biochemical and enzymatic processes. Moreover, accurately quantifying these VOCs is challenging since ham is a complex matrix, which contains compounds from various chemical families and a wide range of volatilities of different molecular masses. In this study, we systematically optimized and validated an analytical method for quantifying VOCs in dry-cured ham using headspace solid phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Optimal SPME conditions were determined through both an experimental procedure (one-factor-at-a-time) and response surface methodology (RSM), revealing that a 60-min equilibration at 70°C, a 60-min extraction at the same temperature, and a 4-min desorption time at 250°C provided the most favorable results. To enhance quantitation, twelve multiple internal standards (ISTDs) were employed to address and improve the quantitation of the 12 VOCs. Method validation covered aspects of linearity, limits of detection (LOD: 0.03-1.13 mg kg-1), limits of quantitation (LOQ: 0.09-3.41 mg kg-1), and working ranges (0.01-19.1 mg kg-1). The practical application of this optimized method was demonstrated by analyzing dry-cured ham samples (n = 4), sourced from the Slovenian market. The initial statistical evaluation indicates that different types of dry-cured hams can be differentiated (with an 83.1% of accuracy) according to their aromatic profile. However, a larger sample size would be required to provide a more comprehensive assessment.

From language models to large-scale food and biomedical knowledge graphs.

Knowledge about the interactions between dietary and biomedical factors is scattered throughout uncountable research articles in an unstructured form (e.g., text, images, etc.) and requires automatic structuring so that it can be provided to medical professionals in a suitable format. Various biomedical knowledge graphs exist, however, they require further extension with relations between food and biomedical entities. In this study, we evaluate the performance of three state-of-the-art relation-mining pipelines (FooDis, FoodChem and ChemDis) which extract relations between food, chemical and disease entities from textual data. We perform two case studies, where relations were automatically extracted by the pipelines and validated by domain experts. The results show that the pipelines can extract relations with an average precision around 70%, making new discoveries available to domain experts with reduced human effort, since the domain experts should only evaluate the results, instead of finding, and reading all new scientific papers.

Determining the Authenticity of Spirulina Dietary Supplements Based on Stable Isotope and Elemental Composition.

While the demand for Spirulina dietary supplements continues to grow, product inspection in terms of authenticity and safety remains limited. This study used the stable isotope ratios of light elements (C, N, S, H, and O) and the elemental composition to characterize Spirulina dietary supplements available on the Slovenian market. Forty-six samples were labelled as originating from the EU (1), non-EU (6), Hawaii (2), Italy (2), Japan (1), Portugal (2), Taiwan (3), India (4), and China (16), and nine products were without a declared origin. Stable isotope ratio median values were -23.9‱ (-26.0 to -21.8‱) for δ13C, 4.80‱ (1.30-8.02‱) for δ15N, 11.0‱ (6.79-12.7‱) for δ34S, -173‱ (- 190 to -158‱) for δ2H, and 17.2‱ (15.8-18.8‱) for δ18O. Multivariate statistical analyses achieved a reliable differentiation of Hawaiian, Italian, and Portuguese (100%) samples and a good separation of Chinese samples, while the separation of Indian and Taiwanese samples was less successful, but still notable. The study showed that differences in isotopic and elemental composition are indicative of sample origins, cultivation and processing methods, and environmental conditions such that, when combined, they provide a promising tool for determining the authenticity of Spirulina products.

Characterization of Botanical Origin of Italian Honey by Carbohydrate Composition and Volatile Organic Compounds (VOCs).

Honey is a natural sweetener constituted by numerous macro- and micronutrients. Carbohydrates are the most representative, with glucose and fructose being the most abundant. Minor honey components like volatile organic compounds (VOCs), minerals, vitamins, amino acids are able to confer honey-specific properties and are useful to characterize and differentiate between honey varieties according to the botanical origin. The present work describes the chemical characterization of honeys of different botanical origin (multifloral, acacia, apple-dandelion, rhododendron, honeydew, and chestnut) produced and collected by beekeepers in the Trentino Alto-Adige region (Italy). Melissopalynological analysis was conducted to verify the botanical origin of samples and determine the frequency of different pollen families. The carbohydrate composition (fourteen sugars) and the profile of VOCs were evaluated permitting to investigate the relationship between pollen composition and the chemical profile of honey. Statistical analysis, particularly partial least squares discriminant analysis (PLS-DA), demonstrates the importance of classifying honey botanical origin on the basis of effective pollen composition, which directly influences honey's biochemistry, in order to correctly define properties and value of honeys.

Reply to Horacek, M. The Need to Consider Geochemistry When Interpreting Sr-Isotopes. Comment on "Gregorcic et al. The Provenance of Slovenian Milk Using 87Sr/86Sr Isotope Ratios. Foods 2021, 10, 1729".

We appreciate Dr Horacek's interest in our paper and his feedback [...].

Geographical identification of strawberries based on stable isotope ratio and multi-elemental analysis coupled with multivariate statistical analysis: A Slovenian case study.

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.

Construction of IsoVoc Database for the Authentication of Natural Flavours.

Flavour is an important quality trait of food and beverages. As the demand for natural aromas increases and the cost of raw materials go up, so does the potential for economically motivated adulteration. In this study, gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) analysis of volatile fruit compounds, sampled using headspace-solid phase microextraction (HS-SPME), is used as a tool to differentiate between synthetic and naturally produced volatile aroma compounds (VOCs). The result is an extensive stable isotope database (IsoVoc-Isotope Volatile organic compounds) consisting of 39 authentic flavour compounds with well-defined origin: apple (148), strawberry (33), raspberry (12), pear (9), blueberry (7), and sour cherry (4) samples. Synthetically derived VOCs (48) were also characterised. Comparing isotope ratios of volatile compounds between distillates and fresh apples and strawberries proved the suitability of using fresh samples to create a database covering the natural variability in δ13C values and range of VOCs. In total, 25 aroma compounds were identified and used to test 33 flavoured commercial products to evaluate the usefulness of the IsoVoc database for fruit flavour authenticity studies. The results revealed the possible falsification for several fruit aroma compounds.

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 δ13Ccas and δ15Ncas 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 δ18Ow 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.

Differences in the Levels of the Selected Phytoestrogens and Stable Isotopes in Organic vs. Conventional Hops and Beer.

Xanthohumol (XN), isoxanthohumol (IX) and 8-prenylnaringenin (8-PN) are important prenylflavonoids present in hops with potential beneficial properties. In this study, we examined differences in the content of XN, IX and 8-PN in hops and beer produced under organic and conventional production regimes. A An ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) method for analysing XN, IX and 8-PN in hops and beer was developed and validated, with LOQ ranging from 0.5 to 10 ng/mL. Finally, we examined 15N/14N and 12C/13C isotope ratios in the hops and beer using isotope ratio mass spectrometry (IRMS). The results show no statistically significant difference in the content of the selected prenylflavonoids between organic and conventionally produced hops and beer-in the whole sample group, as well as between the matched pairs. Stable isotope analysis indicated that only δ15N values are statistically higher in organically produced hops and beer. However, the differentiation according to the type of production could not be made solely based on the δ15N signature, but it could be used to provide supporting evidence.

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.

Compound-specific carbon and hydrogen isotope analysis of volatile organic compounds using headspace solid-phase microextraction.

Natural flavouring materials are in high demand, and a premium price is paid for all-natural flavourings, making them vulnerable to fraud. At present, compound-specific isotope analysis (CSIA) is perhaps the most sophisticated tool for determining flavour authenticity. Despite promising results, the method is not widely used, and the results are limited to the most common volatile organic compounds (VOCs). This paper describes a robust protocol for on-line measurements of δ13C and δ2H using HS-SPME coupled with GC-C-IRMS and GC-HTC-IRMS for common fruit VOCs. To achieve reproducible and accurate results, a combination of a peak size/linearity correction with drift correction were used. Finally, the results were normalised by multiple point linear regression using the known and measured values of reference materials. Special care was taken to avoid irreproducible isotopic fractionation and the effects of equilibration, adsorption, desorption times and temperatures on δ13C or δ2H values were examined. Method validation was performed, and the average combined measurement uncertainty (MU) was 0.42‰. All the δ13CVPDB values were below ±3*MU, regardless of analytical conditions. In contrast, for δ2HVSMOW-SLAP values, only low temperature (30 °C) with equilibration time (15 min) and shorter adsorption time (between 10 and 20 min) can produce an isotopic difference of <10‰. Therefore, method optimisation can minimise MU, and data normalisation and method validation are essential for obtaining meaningful data for use in flavour authenticity studies.

Fatty Acid and Stable Carbon Isotope Composition of Slovenian Milk: Year, Season, and Regional Variability.

This study examined the percentage and stable isotope ratios of fatty acids in milk to study seasonal, year, and regional variability. A total of 231 raw cow milk samples were analyzed. Samples were taken twice per year in 2012, 2013, and 2014, in winter and summer, covering four distinct geographical regions in Slovenia: Mediterranean, Alpine, Dinaric, and Pannonian. A discriminant analysis model based on fatty acid composition was effective in discriminating milk according to the year/season of production (86.9%), while geographical origin discrimination was less successful (64.1%). The stable isotope composition of fatty acids also proved to be a better biomarker of metabolic transformation processes in ruminants than discriminating against the origin of milk. Further, it was observed that milk from Alpine and Mediterranean regions was healthier due to its higher percentage of ω-3 polyunsaturated fatty acid and conjugated linoleic acid.

Can We Discover Truffle's True Identity?

This study used elemental and stable isotope composition to characterize Slovenian truffles and used multi-variate statistical analysis to classify truffles according to species and geographical origin. Despite the fact that the Slovenian truffles shared some similar characteristics with the samples originating from other countries, differences in the element concentrations suggest that respective truffle species may respond selectively to nutrients from a certain soil type under environmental and soil conditions. Cross-validation resulted in a 77% correct classification rate for determining the geographical origin and a 74% correct classification rate to discriminate between species. The critical parameters for geographical origin discriminations were Sr, Ba, V, Pb, Ni, Cr, Ba/Ca and Sr/Ca ratios, while from stable isotopes δ18O and δ13C values are the most important. The key variables that distinguish T.magnatum from other species are the levels of V and Zn and δ15N values. Tuber aestivum can be separated based on the levels of Ni, Cr, Mn, Mg, As, and Cu. This preliminary study indicates the possibility to differentiate truffles according to their variety and geographical origin and suggests widening the scope to include stable strontium isotopes.

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 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.

Species and geographic variability in truffle aromas.

The gastronomic relevance and price of truffles are related mainly to its unique aroma. In this study, we explore the impact that different volatile compounds have on the aroma quality of fresh truffles using gas chromatography-mass spectrometry (GC-MS). Four hundred sixty fresh ascocarps of nine truffle species (Tuber aestivum, Tuber magnatum, Tuber melanosporum, Tuber mesentericum, Tuber brumale, Tuber excavatum, Tuber rufum, Tuber indicum and Tuber macrosporum) harvested in 2018/19 and 2019/2020 from 11 different countries (Slovenia, Croatia, Bosnia in Herzegovina, Macedonia, Italy, Spain, France, United Kingdom, Germany, Poland and China) were collected. Our investigation included the classification of species based on their aroma profile, a study of the differences in the volatile organic composition of truffle species over a geographical area, and, in more detail, a study of T. aestivum from four natural truffle growing sites in Slovenia. Our models can distinguish between groups, with small classification error. These models could form the basis of a predictive framework to detect fraud concerning truffle products and to determine the influence of different growing parameters on the aroma profile of truffles.

C and H stable isotope ratio analysis using solid-phase microextraction and gas chromatography-isotope ratio mass spectrometry for vanillin authentication.

It is possible to distinguish precious vanillin from Vanilla species (planifolia or tahitensis) from much less expensive synthetic and nature-identical vanillin on the basis of the stable isotope ratios of H and C (2H/1H, 13C/12C). Analysis is usually performed using GC-IRMS (Gas Chromatography - Isotope Ratio Mass Spectrometry) after solvent extraction of vanillin from the sample. Recently, head-space solid-phase microextraction (HS-SPME) has been proposed as an alternative for determining 13C/12C. The aim of this study was to develop a method to analyse 2H/1H in vanillin using SPME-GC-IRMS for the first time, by testing different operating conditions and comparing the results with those obtained after solvent extraction. The ultimate scope was to develop a quick, robust and effective method to measure 2H/1H and 13C/12C in vanillin to assess the authenticity of labelling. Almost 50 authentic samples from vanilla pods, nature-identical (ex) and synthetic vanillin and 4 commercial food products were taken into account. All the samples were subjected to HS-SPME-GC-IRMS analysis and most of them to GC-IRMS analysis after solvent extraction of vanillin. The SPME method developed for 2H/1H analysis guarantees the absence of isotopic fractionation, repeatability and reproducibility standard deviation of below 7‰ and savings in terms of time (from 30 to 5 min) and solvent. HS-SPME GC-IRMS analysis of δ2H and δ13C can be proposed as a rapid and robust method to discriminate different types of vanillin and assess the authenticity of natural vanillin, also contained in food matrices.

Authentication of key aroma compounds in apple using stable isotope approach.

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.