Purity Assessment of Honey Based on Compound Specific Stable Carbon Isotope Ratios Obtained by LC-IRMS.

BACKGROUND: The use of stable carbon isotope ratios (δ13C) of sugar fractions of honey is a powerful tool to detect adulteration with sugar syrups. This is accomplished by calculating differences of the δ13C values between individual honey saccharides and comparing them to published purity criteria. A liquid chromatography-isotope ratio mass spectrometry (LC-IRMS) method for the determination of δ13C values of sugars in honey was previously validated by an interlaboratory comparison but no further guidance was given how to include the obtained precision figures of the compound specific δ13C values in the purity assessment of honey. OBJECTIVE: To use existing data to estimate the standard deviation of the repeatability (sr) and reproducibility (sR) of differences (Δ Î´13C) between the δ13C values of individual honey saccharides. METHODS: Previously published δ13C values were used to calculate differences (Δ Î´13C values) between δ13C fructose-δ13C glucose, δ13C glucose-δ13C disaccharides, etc in a honey sample; sr and sR of Δ Î´13C values were calculated according to ISO 5725-2:2019. RESULTS: The Δ Î´13C sr and sR values were essentially of the same magnitude as the sr and sR values of δ13C values of the sugar fractions. The precision of the Δ Î´13C values was used to estimate the critical difference for comparing a test result with a reference value according to ISO 5725-6:1994. This varied between 0.02 ‰ and 0.40 ‰. CONCLUSION: The estimated critical differences can be used to determine whether a honey test result complies with published Δ Î´13C purity criteria. HIGHLIGHT: The proposed procedure will increase the confidence in decisions based on compound specific δ13C values regarding the conformity of honey with published purity criteria.

Detection and Quantification of Botanical Impurities in Commercial Oregano (Origanum vulgare) Using Metabarcoding and Digital PCR.

DNA technology for food authentication is already well established, and with the advent of Next Generation Sequencing (NGS) and, more specifically, metabarcoding, compositional analysis of food at the molecular level has rapidly gained popularity. This has led to several reports in the media about the presence of foreign, non-declared species in several food commodities. As herbs and spices are attractive targets for fraudulent manipulation, a combination of digital PCR and metabarcoding by NGS was employed to check the purity of 285 oregano samples taken from the European market. By using novel primers and analytical approaches, it was possible to detect and quantify both adulterants and contaminants in these samples. The results highlight the high potential of NGS for compositional analysis, although its quantitative information (read count percentages) is unreliable, and other techniques are therefore needed to complement the sequencing information for assessing authenticity ('true to the name') of food ingredients.

DNA Accounting: Tallying Genomes to Detect Adulterated Saffron.

The EU General Food Law not only aims at ensuring food safety but also to 'prevent fraudulent or deceptive practices; the adulteration of food; and any other practices which may mislead the consumer'. Especially the partial or complete, deliberate, and intentional substitution of valuable ingredients (e.g., Saffron) for less valuable ones is of concern. Due to the variety of products on the market an approach to detect food adulteration that works well for one species may not be easily applicable to another. Here we present a broadly applicable approach for the detection of substitution of biological materials based on digital PCR. By simultaneously measuring and forecasting the number of genome copies in a sample, fraud is detectable as a discrepancy between these two values. Apart from the choice of target gene, the procedure is identical across all species. It is scalable, rapid, and has a high dynamic range. We provide proof of concept by presenting the analysis of 141 samples of Saffron (Crocus sativus) from across the European market by DNA accounting and the verification of these results by NGS analysis.

Results of an Interlaboratory Comparison of a Liquid Chromatography-Isotope Ratio Mass Spectrometry Method for the Determination of 13C/12C Ratios of Saccharides in Honey.

BACKGROUND: Stable carbon isotope analysis of sugars in honey by LC-isotope ratio mass spectrometry (IRMS) is a useful tool for detecting adulteration of honey with extraneous sugar. Purity criteria based on 13C/12C ratios of saccharides in honey, determined by LC-IRMS of a large number of authentic honey samples, have been elaborated. However, no interlaboratory comparison (ILC) has yet been performed to estimate the precision of the method under reproducibility conditions. OBJECTIVE: To address this knowledge gap an ILC involving 14 laboratories and using six honey samples was conducted. METHODS: The participants were allowed to use their LC-IRMS-based method of choice for sample preparation and compound separation. RESULTS: The precision figures were estimated according to ISO 5725:1994. The repeatability relative standard deviation (RSDr) for the determination of δ13C values of fructose and glucose varied between 0.3 and 0.5%, with 0.3 and 1.0% for disaccharides, and 0.7 and 2.8% for trisaccharides. The RSDR varied between 0.8 and 1.8% for the monosaccharides, 1.0 and 1.5% for disaccharides, and 1.4 and 2.8% for trisaccharides. CONCLUSION: Based on the obtained precision data the LC-IRMS method for the determination of 13C/12C ratios of saccharides in honey was considered fit for the conformity assessment of honey with established purity criteria. HIGHLIGHTS: Precision estimates for a LC-IRMS method to determine 13C/12C ratios of saccharides in honey were obtained through an ILC. The data created can form the basis for the standardization of the method by interested standards-developing organizations for use in official control.

High-resolution melting of multiple barcode amplicons for plant species authentication.

In recent years, species identification in herbs has attracted considerable attention due to several cases of fraud; hence inexpensive high-throughput authentication methods are highly welcomed. Species authentication is often performed through DNA analysis and several specific regions (barcodes) are considered suitable. Each barcode (Bar) possesses different qualities in terms of universality and discrimination power. A multiplexed format where information can be extracted simultaneously from several barcode regions is seemingly appropriate to ensure the power of both universality and discrimination. In this approach, we amplified DNA from five different barcode regions in a multiplexed PCR format followed by high-resolution melting (HRM). This multiplexed Bar-HRM approach was first applied to plants spanning the plant kingdom and then gradually narrowing down the genetic variability within the Lamiaceae and the Solanaceae families to finally reach closely related cultivars. Universality was demonstrated through distinct melting profiles obtained for species originating from 29 different families spanning the angiosperms, gymnosperm, mosses, and liverwort (Marchantiophyta). Discrimination power was retained for species, sub-species, and a few cultivars through the application of multivariate statistics to the high-resolution melting profiles. This preliminary investigation has shown the potential to discriminate a vast amount of species within the whole plant kingdom. It requires no a priori knowledge of the species' DNA sequence and occurs in a closed system within 2.5 h at a reduced cost per sample compared to other DNA based approaches.

Metabolomics for organic food authentication: Results from a long-term field study in carrots.

Increasing demand for organic products and their premium prices make them an attractive target for fraudulent malpractices. In this study, a large-scale comparative metabolomics approach was applied to investigate the effect of the agronomic production system on the metabolite composition of carrots and to build statistical models for prediction purposes. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) was applied successfully to predict the origin of the agricultural system of the harvested carrots on the basis of features determined by liquid chromatography-mass spectrometry. When the training set used to build the OPLS-DA models contained samples representative of each harvest year, the models were able to classify unknown samples correctly (100% correct classification). If a harvest year was left out of the training sets and used for predictions, the correct classification rates achieved ranged from 76% to 100%. The results therefore highlight the potential of metabolomic fingerprinting for organic food authentication purposes.

Novel nuclear barcode regions for the identification of flatfish species.

The development of an efficient seafood traceability framework is crucial for the management of sustainable fisheries and the monitoring of potential substitution fraud across the food chain. Recent studies have shown the potential of DNA barcoding methods in this framework, with most of the efforts focusing on using mitochondrial targets such as the cytochrome oxidase 1 and cytochrome b genes. In this article, we show the identification of novel targets in the nuclear genome, and their associated primers, to be used for the efficient identification of flatfishes of the Pleuronectidae family. In addition, different in silico methods are described to generate a dataset of barcode reference sequences from the ever-growing wealth of publicly available sequence information, replacing, where possible, labour-intensive laboratory work. The short amplicon lengths render the analysis of these new barcode target regions ideally suited to next-generation sequencing techniques, allowing characterisation of multiple fish species in mixed and processed samples. Their location in the nucleus also improves currently used methods by allowing the identification of hybrid individuals.

Review on proteomics for food authentication.

UNLABELLED: Consumers have the right to know what is in the food they are eating. Accordingly, European and global food regulations require that the provenance of the food can be guaranteed from farm to fork. Many different instrumental techniques have been proposed for food authentication. Although traditional methods are still being used, new approaches such as genomics, proteomics, and metabolomics are helping to complement existing methodologies for verifying the claims made about certain food products. During the last decade, proteomics (the large-scale analysis of proteins in a particular biological system at a particular time) has been applied to different research areas within food technology. Since proteins can be used as markers for many properties of a food, even indicating processes to which the food has been subjected, they can provide further evidence of the foods labeling claim. This review is a comprehensive and updated overview of the applications, drawbacks, advantages, and challenges of proteomics for food authentication in the assessment of the foods compliance with labeling regulations and policies. SIGNIFICANCE: This review paper provides a comprehensive and critical overview of the application of proteomics approaches to determine the authenticity of several food products updating the performances and current limitations of the applied techniques in both laboratory and industrial environments.

Defining the wheat gluten peptide fingerprint via a discovery and targeted proteomics approach.

UNLABELLED: Accurate, reliable and sensitive detection methods for gluten are required to support current EU regulations. The enforcement of legislative levels requires that measurement results are comparable over time and between methods. This is not a trivial task for gluten which comprises a large number of protein targets. This paper describes a strategy for defining a set of specific analytical targets for wheat gluten. A comprehensive proteomic approach was applied by fractionating wheat gluten using RP-HPLC (reversed phase high performance liquid chromatography) followed by a multi-enzymatic digestion (LysC, trypsin and chymotrypsin) with subsequent mass spectrometric analysis. This approach identified 434 peptide sequences from gluten. Peptides were grouped based on two criteria: unique to a single gluten protein sequence; contained known immunogenic and toxic sequences in the context of coeliac disease. An LC-MS/MS method based on selected reaction monitoring (SRM) was developed on a triple quadrupole mass spectrometer for the specific detection of the target peptides. The SRM based screening approach was applied to gluten containing cereals (wheat, rye, barley and oats) and non-gluten containing flours (corn, soy and rice). A unique set of wheat gluten marker peptides were identified and are proposed as wheat specific markers. SIGNIFICANCE: The measurement of gluten in processed food products in support of regulatory limits is performed routinely. Mass spectrometry is emerging as a viable alternative to ELISA based methods. Here we outline a set of peptide markers that are representative of gluten and consider the end user's needs in protecting those with coeliac disease. The approach taken has been applied to wheat but can be easily extended to include other species potentially enabling the MS quantification of different gluten containing species from the identified markers.

Comparative transcriptome profiling in winter wheat grown under different agricultural practices.

Wheat (Triticum aestivum L.), one of the three most important cereal crops worldwide, has a dominant position in Europe due to its adaptability and consumer acceptance particularly as an organic food commodity. Organic agriculture is developing rapidly, and its authenticity is presently a subject of great concern to food authorities, as incorrect labeling can represent commercial fraud. A comparative transcriptome profiling was conducted on winter wheat flag leaves of several cultivars growing in open fields under different agricultural production systems. Performing a microarray study, 10 transcripts differentially expressed in organic and conventional growing conditions were identified in Tommi and Centenaire cultivars. Transcript abundance profiles of selected probe sets were independently confirmed by quantitative reverse-transcription PCR analysis, tested on Tommi, Centenaire, and Cubus cultivars from different growing-year and geographical sites. Univariate and multivariate statistical analysis showed that the global wheat transcriptome is influenced by the agricultural system indicating a promising approach for analytical verification of the production system of wheat at the farm level.

Current challenges in detecting food allergens by shotgun and targeted proteomic approaches: a case study on traces of peanut allergens in baked cookies.

There is a need for selective and sensitive methods to detect the presence of food allergens at trace levels in highly processed food products. In this work, a combination of non-targeted and targeted proteomics approaches are used to illustrate the difficulties encountered in the detection of the major peanut allergens Ara h 1, Ara h 2 and Ara h 3 from a representative processed food matrix. Shotgun proteomics was employed for selection of the proteotypic peptides for targeted approaches via selective reaction monitoring. Peanut presence through detection of the proteotypic Ara h 3/4 peptides AHVQVVDSNGNR (m/z 432.5, 3+) and SPDIYNPQAGSLK (m/z 695.4, 2+) was confirmed and the developed method was able to detect peanut presence at trace levels (≥10 µg peanut g(-1) matrix) in baked cookies.

Analytical methods for detection of gluten in food--method developments in support of food labeling legislation.

The current essential therapy of celiac disease is a strict adherence to a gluten-free diet. Besides food products that are naturally gluten-free, "very low gluten" and "gluten-free" bakery products have become available. The availability of immunochemical and other analytical methods to determine gluten markers in foods is of utmost importance to ensure the well being of gluten-sensitive individuals. The aim of this review was to evaluate if currently available methodologies are suitable to meet the requirements of food labeling standards for individual gluten source declaration, in order to achieve policy objectives. Codex Alimentarius and European Union (EU) legislation and gluten detection methodologies applicable at present have been summarized and compared. In 2009, the European Commission issued Regulation No. 41/2009 concerning the composition and labeling of foodstuffs suitable for people intolerant to gluten. This review constitutes a basis to investigate the possibility to develop a proteomic-based method for the specific detection of gluten-containing cereals in food products, especially at or around the limits specified in EU legislation.

Reference genes for gene expression studies in wheat flag leaves grown under different farming conditions.

BACKGROUND: Internal control genes with highly uniform expression throughout the experimental conditions are required for accurate gene expression analysis as no universal reference genes exists. In this study, the expression stability of 24 candidate genes from Triticum aestivum cv. Cubus flag leaves grown under organic and conventional farming systems was evaluated in two locations in order to select suitable genes that can be used for normalization of real-time quantitative reverse-transcription PCR (RT-qPCR) reactions. The genes were selected among the most common used reference genes as well as genes encoding proteins involved in several metabolic pathways. FINDINGS: Individual genes displayed different expression rates across all samples assayed. Applying geNorm, a set of three potential reference genes were suitable for normalization of RT-qPCR reactions in winter wheat flag leaves cv. Cubus: TaFNRII (ferredoxin-NADP(H) oxidoreductase; AJ457980.1), ACT2 (actin 2; TC234027), and rrn26 (a putative homologue to RNA 26S gene; AL827977.1). In addition of these three genes that were also top-ranked by NormFinder, two extra genes: CYP18-2 (Cyclophilin A, AY456122.1) and TaWIN1 (14-3-3 like protein, AB042193) were most consistently stably expressed.Furthermore, we showed that TaFNRII, ACT2, and CYP18-2 are suitable for gene expression normalization in other two winter wheat varieties (Tommi and Centenaire) grown under three treatments (organic, conventional and no nitrogen) and a different environment than the one tested with cv. Cubus. CONCLUSIONS: This study provides a new set of reference genes which should improve the accuracy of gene expression analyses when using wheat flag leaves as those related to the improvement of nitrogen use efficiency for cereal production.

Natural radioactivity in winter wheat from organic and conventional agricultural systems.

The distribution of natural radionuclides was studied in winter wheat plants collected from three sites in Belgium during 2004-2007. Activity concentrations of (40)K, (226)Ra, (228)Ra and (228)Th in organically and conventionally grown wheat, and in the corresponding soil samples, were determined using ultra low-level gamma-ray spectrometry. The observed soil-to-wheat concentration ratios were calculated for the different parts of the wheat plant (root, stem and grain) in the two agricultural systems (organic and conventional). There were large variations in radionuclide activity concentrations between the sites and fields, but no significant difference between conventionally and organically grown wheat plants was observed.

Population genetic structure of wild Phaseolus lunatus (Fabaceae), with special reference to population sizes.

To set up an in situ conservation strategy for Phaseolus lunatus, we analyzed the genetic structure of 29 populations in the Central Valley of Costa Rica. Using 22 enzyme loci, we quantified the proportion of polymorphic loci (P(p)), the mean number of alleles per locus (A), and the mean effective number of alleles per locus (A(e)), which equaled to 10.32%, 1.10, and 1.05, respectively. The total heterozygosity (H(T)), the intrapopulation genetic diversity (H(S)), and the interpopulation genetic diversity (D(ST)) were 0.193, 0.082, and 0.111, respectively. The genotypic composition of the analyzed populations showed a deviation from the Hardy-Weinberg proportions (F(IT) = 0.932). This disequilibrium was due to either genetic differentiation between populations (F(ST) = 0.497) or nonrandom mating within populations (F(IS) = 0.866). From the level of genetic differentiation between populations and the private alleles frequencies estimates, gene flow was calculated: Nm(W) = 0.398 and Nm(S) = 0.023, respectively. The results suggested that wild Lima bean maintains most of its isozyme variation among populations. Significant positive correlation was observed between population size and P(p), A, and H(o) (observed heterozygosity), whereas no correlation was observed with the average fixation index of population (F). The loss of genetic variability in populations was attributed to inbreeding and the bottleneck effects that characterized the target populations. In situ conservation and management procedures for wild Lima bean are discussed.