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 product

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

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 isotope

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

Fatty acid and stable carbon isotope composition of Slovenian milk

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

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-CIRMS) 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 δ$^{13}$C 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

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

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

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

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&mdash;discriminant analysis (OPLS-DA) were performed to discriminate between argan oils from Essaouira, Taroudant, Tiznit, Chtouka-A&iuml;t Baha and Sidi Ifni. The correct classification rate was highest for argan oil from the Chtouka-A&iuml;t 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 (&ge;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