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Cold-pressed fruit seed oils from blackcurrant, raspberry, and strawberry are gaining market share and – as relatively high value oils – are potential targets for adulteration. This study (open access) used identified 28 triacylglycerides (TAGs) as significant markers for distinguishing the 3 oils.  These were identified from chemometric analysis of full tryglyceride profiles.  Triglycerides were measured by ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry. Lipidomic analysis identified 215 glycerides in the three oils. Chemometric analysis revealed that TAG profiles were superior to diacetylglyceride (DAG) profiles for oil differentiation and detecting adulteration. OPLS-DA identified 28 TAGs as significant markers for distinguishing the three oils.

The authors reported that comparison of glyceride profiles of pure and adulterated samples demonstrated that adulteration with 5 % or more sunflower or rapeseed oil could be detected. Targeted metabolomic analysis using specific markers for sunflower oil confirmed adulteration in raspberry and strawberry commercially purchased fruit seed oils.

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The authors of this study developed a targeted proteomics approach using LC–MS/MS and cross-species marker peptides with the potential to quantify meat in vegan and vegetarian foods. The method is designed to achieve the threshold of 0.1% w/w that is commonly applied for unintended cross-contamination.

 Protein extraction and digestion were optimized for rapid, simplified, and highly efficient sample preparation. Three matrix calibrations (0.1–5.0% w/w meat, each) were applied to vegan sausages and burger patties spiked with pork, chicken, or beef meat. The four markers DFNMPLTISR, DLEEATLQHEATAAALR, IQLVEEELDR, and LDEAEQLALK showed the highest accuracies for the determination of meat contents (recovery rates of 80–120%).

Although purchase is required for the full paper (here) the work builds upon previous publications and this supporting information is available free of charge (following the same link).  This includes detailed description of the statistical analysis; meat marker peptides before and after their re-evaluation; pea marker peptides; details of the LC runs; base materials and further ingredients for the vegan sausages and vegan burger patties; defatting/dehydration efficiencies of PLE and in-tube defatting/dehydration; comparison of extraction buffers and trypsin concentrations (matrix: vegan sausage with chicken meat); properties and comparison of different trypsins; chromatograms of the meat marker peptides from different matrixes; linear regressions derived from the quantifiers of the meat marker peptides in different matrixes; trueness and precision; mean signal-to-noise ratios at given meat contents.

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Mechanically Separated Meat (MSM – sometimes called Mechanically Recovered Meat, MRM) must be declared on-pack if used in meat products.  Testing for undeclared MSM can be a significant analytical challenge.  Traditional official control methods rely on microscopy, which requires experienced interpretation and can be highly subjective. 

This paper (open access) builds upon previous published work from the same researchers to develop targeted LC-MSMS methods that are suitable for official control applications..

In contrast to a comparable study on MSM from poultry, the authors report that the use of cartilage/intervertebral disc material was not useful for porcine MSM. They therefore report a new marker protein from porcine MSM, protegrin-4, which allows the detection of 5/3/1 mm MSM. The validity of the developed assay was ensured by the investigation of 182 blinded samples. After unblinding, all samples containing 5/3/1 mm MSM and all negative control samples were correctly classified. Additional new results related to the investigation of the species specification of chicken, turkey, and pork also are presented.

They concluded that LC-MS/MS-based detection of of undeclared MSM has been successfully extended from poultry to porcine MSM. The assay was successfully transferred to a triple quadrupole LC-MS system to facilitate routine use.

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This paper (open access) introduces the workflow MEATiCode, a comprehensive proteomic liquid chromatography tandem mass spectrometry (LC-MS/MS) method for the simultaneous identification of species in meat authentication.

This novel database search approach enabled the differentiation of meat species (as demonstrated for beef, pork, chicken and lamb) in raw and cooked food products following a simple sample preparation procedure and LC-MS/MS analysis of extracted meat peptides.  Peptides and proteins were characterised from reference samples using an untargeted protocol.  The MEATiCode database was then constructed in the Mascot Server search engine, with the objective of creating artificial proteins comprising the concatenated amino acid sequences of the peptides identified as specific for each species.

The authors report that the efficacy of the MEATiCode method was demonstrated through its application to a range of meat products, achieving high sensitivity (0.5 % Limit of Detection (LoD)) and reliability in the detection of adulteration, even in highly processed or cooked meats.

This paper (purchase required) reports a method to differentiate pork gelatin from beef gelatin (down to 0.01% cross-contamination levels) based on the LC-MSMS analysis of 13 peptide marker ions (8 for bovine, 5 for porcine).  The authors report that their method was validated at three concentration levels and accurately identified the gelatin species in pharmaceutical capsules and gels.

LC-MSMS analysis of peptides provides an alternative approach to DNA testing, which has known difficulties in application to highly processed products like gelatin due to the low amount of viable DNA or distinctive fragments.  LC-MSMS is the approach described in a recent Defra research report which is referenced on the FAN research pages (scroll down table to FA0177).