Browse
Submit Data
Databases
API
Help

Dataset Information

32 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Combination of Stable Isotopes and Fatty Acid Composition for Geographical Origin Discrimination of One Argan Oil Vintage.

ABSTRACT: Quality control and traceability of Argan oil requires precise chemical characterization considering different provenances. The fatty acid profile is an essential parameter that certifies the quality and purity of Argan oil. In addition, stable isotopes were recently shown to be accurate as an indicator for geographical origin. In this study, fatty acid composition by gas chromatography (GC) and stable isotope ratio by isotope ratio mass spectrometry (IRMS) were investigated for classifying Argan oil according to its geographical origin. Forty-one Argan oil samples, belonging to six geographical origins of Moroccan natural Argan population (Safi, Essaouira, Agadir Ida Outanane, Taroudant, Tiznit and Sidi Ifni) were collected and extracted under the same conditions. The results show that the isotope δ¹³C, palmitic acid (C16:0), linoleic acid (C18:2) and unsaturated fatty acids (UFA) were strongly influenced by ecological parameters. Linear discriminant analysis (LDA) was performed to discriminate the six studied provenances. Discriminant models predicted the origin of Argan oil with 92.70% success. Samples from Safi, Essaouira and Agadir Ida Outanane presented the highest classification rate (100%). In contrast, the lowest rate was reported for samples from Tiznit (85.70%). The findings obtained for fatty acids and isotope combination might be considered as an accurate tool for determining the geographical origins of Argan oil. Moreover, they can potentially be used as specific markers for oils labeled with Protected Geographical Indication (PGI).

SUBMITTER: Elgadi S

PROVIDER: S-EPMC8229091 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Authenticating the geographical origin of the Chinese yam (Tiegun) with stable isotopes and multiple elements.

Project description:The Chinese yam, an important orphan crop with both high nutrient and health promoting value, is mainly produced in the Yellow-Huai-Hai plain near the river basins in China. The protected designation of origin (PDO)-labeled Chinese yam differs greatly from others in market acceptance and price, which has led to fakes and the need for reliable authentication methods. Hence, stable isotope ratios of δ 13C, δ 15N, δ 2D, and δ 18O and 44 multielemental contents were used to explore the authentication of geographical origins and the effect of environmental factors. Twenty-two elements and δ 15N were selected as the key variables to authenticate Chinese yams from three river basins as well as to authenticate them among traditional PDOs and others in the Yellow River basin. Moreover, six environmental factors, including the moisture index, maximum temperature, photosynthetically active radiation, soil organic carbon, total nitrogen and pH, were found to be highly related to these variances.

| S-EPMC10149263 | biostudies-literature

Effects of Geographical Origin and Tree Age on the Stable Isotopes and Multi-Elements of Pu-erh Tea.

Project description:Pu-erh tea is a famous tea worldwide, and identification of the geographical origin of Pu-erh tea can not only protect manufacture's interests, but also boost consumers' confidence. However, tree age may also influence the fingerprints of Pu-erh tea. In order to study the effects of the geographical origin and tree age on the interactions of stable isotopes and multi-elements of Pu-erh tea, 53 Pu-erh tea leaves with three different age stages from three different areas in Yunnan were collected in 2023. The δ13C, δ15N values and 25 elements were determined and analyzed. The results showed that δ13C, δ15N, Mg, Mn, Fe, Cu, Zn, Rb, Sr, Y, La, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu had significant differences among different geographical origins (p < 0.05). Mn content was significantly influenced by region and tree age interaction. Based on multi-way analysis of variance, principal component analysis and step-wised discriminant analysis, 24 parameters were found to be closely related to the geographical origin rather than tree age, and the geographical origin of Pu-erh tea can be 100.0% discriminated in cross-validation with six parameters (δ13C, δ15N, Mn, Mg, La, and Tb). The study could provide references for the establishment of a database for the traceability of Pu-erh tea, and even the identification of tea sample regions with different tree ages.

| S-EPMC10855849 | biostudies-literature

Fatty Acid Composition of Cosmetic Argan Oil: Provenience and Authenticity Criteria.

Project description: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.

| S-EPMC7570657 | biostudies-literature

Validation and analysis of the geographical origin of <i>Angelica sinensis</i> (Oliv.) Diels using multi-element and stable isotopes.

Project description:BackgroundPlace of origin is an important factor when determining the quality and authenticity of Angelica sinensis for medicinal use. It is important to trace the origin and confirm the regional characteristics of medicinal products for sustainable industrial development. Effectively tracing and confirming the material's origin may be accomplished by detecting stable isotopes and mineral elements.MethodsWe studied 25 A. sinensis samples collected from three main producing areas (Linxia, Gannan, and Dingxi) in southeastern Gansu Province, China, to better identify its origin. We used inductively coupled plasma mass spectrometry (ICP-MS) and stable isotope ratio mass spectrometry (IRMS) to determine eight mineral elements (K, Mg, Ca, Zn, Cu, Mn, Cr, Al) and three stable isotopes (δ13C, δ15N, δ18O). Principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) were used to verify the validity of its geographical origin.ResultsK, Ca/Al, δ13C, δ15N and δ18O are important elements to distinguish A. sinensis sampled from Linxia, Gannan and Dingxi. We used an unsupervised PCA model to determine the dimensionality reduction of mineral elements and stable isotopes, which could distinguish the A. sinensis from Linxia. However, it could not easily distinguish A. sinensis sampled from Gannan and Dingxi. The supervised PLS-DA and LDA models could effectively distinguish samples taken from all three regions and perform cross-validation. The cross-validation accuracy of PLS-DA using mineral elements and stable isotopes was 84%, which was higher than LDA using mineral elements and stable isotopes.ConclusionsThe PLS-DA and LDA models provide a theoretical basis for tracing the origin of A. sinensis in three regions (Linxia, Gannan and Dingxi). This is significant for protecting consumers' health, rights and interests.

| S-EPMC8351574 | biostudies-literature

Geographical origin discrimination of "Ntopia" olive oil cultivar from Ionian islands using volatile compounds analysis and computational statistics.

Project description:The aim of the present study was to characterize the aroma profile of olive oil of the "Ntopia" (local) cultivar from the Ionian islands (Zakynthos, Kefalonia, Leukada, and Kerkyra) (Greece), and investigate whether specific volatile compounds could be considered as indicators of olive oil geographical origin, using computational statistics. In this context, 137 olive oil samples were subjected to headspace solid phase microextraction coupled to gas chromatography/mass spectrometry using the internal standard method. Computational statistics on the semi-quantitative data of olive oil samples, as rapid machine learning algorithms, showed that specific volatile compounds could be used as indicators of geographical origin of olive oil of the "Ntopia" cultivar, among the four main Ionian islands. Volatile compounds such as ethanol, pentanal, 2,4-dimethylheptane, 3,7-dimethyl-1,3,6-octatriene (E), 2,5-dimethylnonane, 1-hexanol, 6-methyl-5-hepten-2-one, octanal, dl-Limonene, acetic acid hexyl ester and dodecane could aid to the geographical origin discrimination of "Ntopia" olive oil cultivar when two (Zakynthos and Kefalonia) or four (Zakynthos, Kefalonia, Leukada and Kerkyra) Ionian islands are subjected to statistical analysis. The discrimination rate using the cross-validation method was 100% and 85.7%, respectively. These results were further evaluated using training and holdout partitions, during which a comparable classification rate was obtained.Supplementary informationThe online version contains supplementary material available at 10.1007/s00217-021-03863-2.

| S-EPMC8450699 | biostudies-literature

Discrimination factors of carbon and nitrogen stable isotopes in meerkat feces.

Project description:Stable isotope analysis of feces can provide a non-invasive method for tracking the dietary habits of nearly any mammalian species. While fecal samples are often collected for macroscopic and genetic study, stable isotope analysis can also be applied to expand the knowledge of species-specific dietary ecology. It is somewhat unclear how digestion changes the isotope ratios of animals' diets, so more controlled diet studies are needed. To date, most diet-to-feces controlled stable isotope experiments have been performed on herbivores, so in this study I analyzed the carbon and nitrogen stable isotope ratios in the diet and feces of the meerkat (Suricata suricatta), a small omnivorous mammal. The carbon trophic discrimination factor between diet and feces (?13Cfeces) is calculated to be 0.1 ± 1.5‰, which is not significantly different from zero, and in turn, not different than the dietary input. On the other hand, the nitrogen trophic discrimination factor (?15Nfeces) is 1.5 ± 1.1‰, which is significantly different from zero, meaning it is different than the average dietary input. Based on data generated in this experiment and a review of the published literature, carbon isotopes of feces characterize diet, while nitrogen isotope ratios of feces are consistently higher than dietary inputs, meaning a discrimination factor needs to be taken into account. The carbon and nitrogen stable isotope values of feces are an excellent snapshot of diet that can be used in concert with other analytical methods to better understand ecology, diets, and habitat use of mammals.

| S-EPMC5472036 | biostudies-literature

Discrimination of the Geographical Origin of Soybeans Using NMR-Based Metabolomics.

Project description:With the increase in soybean trade between countries, the intentional mislabeling of the origin of soybeans has become a serious problem worldwide. In this study, metabolic profiling of soybeans from the Republic of Korea and China was performed by nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistical analysis to predict the geographical origin of soybeans. The optimal orthogonal partial least squares-discriminant analysis (OPLS-DA) model was obtained using total area normalization and unit variance (UV) scaling, without applying the variable influences on projection (VIP) cut-off value, resulting in 96.9% sensitivity, 94.4% specificity, and 95.6% accuracy in the leave-one-out cross validation (LOO-CV) test for discriminating between Korean and Chinese soybeans. Soybeans from the northeastern, middle, and southern regions of China were successfully differentiated by standardized area normalization and UV scaling with a VIP cut-off value of 1.0, resulting in 100% sensitivity, 91.7%-100% specificity, and 94.4%-100% accuracy in a LOO-CV test. The methods employed in this study can be used to obtain essential information for the authentication of soybean samples from diverse geographical locations in future studies.

| S-EPMC7922469 | biostudies-literature

Physicochemical, Spectroscopic, and Chromatographic Analyses in Combination with Chemometrics for the Discrimination of the Geographical Origin of Greek Graviera Cheeses.

Project description:Seventy-eight graviera cheese samples produced in five different regions of Greece were characterized and discriminated according to geographical origin. For the above purpose, pH, titratable acidity (TA), NaCl, proteins, fat on a dry weight basis, ash, fatty acid composition, volatile compounds, and minerals were determined. Both multivariate analysis of variance (MANOVA) and linear discriminant analysis (LDA) were applied to experimental data to achieve sample geographical discrimination. The results showed that the combination of fatty acid composition plus minerals provided a correct classification rate of 89.7%. The value for the combination of fatty acid compositions plus conventional quality parameters was 94.9% and for the combination of minerals plus conventional quality parameters was 97.4%. When cheeses of the above five geographical origins were combined with previously studied graviera cheeses from six other geographical origins collected during the same seasons in Greece, the respective values for the discrimination of geographical origin of all eleven origins were 89.3% for conventional quality parameters plus minerals; 94.0% for conventional quality parameters plus fatty acids; 94.1% for minerals plus fatty acids; and 95.2% for conventional quality parameters plus minerals plus fatty acids. Such high correct classification rates demonstrate the robustness of the developed statistical model.

| S-EPMC7435398 | biostudies-literature

High-throughput screening of argan oil composition and authenticity using benchtop <sup>1</sup> H NMR.

Project description:We use 60-MHz benchtop nuclear magnetic resonance (NMR) to acquire 1 H spectra from argan oils of assured origin. We show that the low-field NMR spectrum of neat oil contains sufficient information to make estimates of compositional parameters and to inform on the presence of minor compounds. A screening method for quality and authenticity is presented based on nearest-neighbour outlier detection. A variety of oil types are used to challenge the method. In a survey of retail-purchased oils, several instances of fraud were found.

| S-EPMC8653893 | biostudies-literature

Terroir and vintage discrimination of Malbec wines based on phenolic composition across multiple sites in Mendoza, Argentina.

Project description:This study evaluated the phenolic profiles of Malbec wines made from grapes of 23 parcels distributed in 12 geographical indications (GIs) from Mendoza, Argentina. Wines were elaborated under standardized winemaking conditions over three consecutive vintages (2016-2018). Data discriminated wines from different GIs and parcels, based on an integrative data analysis by chemometric tools. Vintage effect and specific phenolic compounds were associated with some GIs or parcels. As well, regional climate conditions allowed partial discrimination of the GIs (and also some parcels). A random forest analysis correctly identified 11 out of 23 individual parcels across the different vintages. The most notorious compounds associated with such classification were p-coumaric acid, delphinidin-3-O-glucoside, caffeic acid, quercetin and peonidin-3-O-glucoside. The presented research allows to individualize, through phenolic profiles, parcels with unique characteristics over years. This is the first report characterizing Malbec wines coming from several GIs (and individual parcels) in different vintages. These results are strongly related to terroir features of wines, contributing to a better communication to consumers and to position Argentinean wines.

| S-EPMC7859225 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data