2. Chemistry & Toxicology

Exploration of novel technologies to provide rapid and cost-effective methods for counteracting food fraud

Project Reference:

08-2014

Status:

Completed

Commencement Date:

October, 2014

Project Duration:

24 months

Abstract:

Food fraud is now recognised as a serious and global whole food chain phenomenon with negative impacts on consumer confidence and potentially their health and well-being. There is now an urgency to develop cost-effective, rapid and reliable analytical methodologies that can be used for screening suspect foods for their authenticity. This report details an investigation into the viability of a number of analytical techniques for application in food authenticity testing. Researchers at the Institute for Global Food Security at Queen's University Belfast, in collaboration with the Irish Equine Centre in Co. Kildare, investigated the application of modern analytical techniques for the detection of food fraud by applying these techniques to a range of foods including cheese, meat, fish and rapeseed oil. A number of analytical techniques and associated equipment were investigated for this purpose, namely (1) benchtop Nuclear Magnetic Resonance (60MHz), (2) the loop-mediated isothermal amplification (LAMP) assay, and (3) Rapid Evaporative Ionisation Mass Spectrometry (REIMS).

60MHz NMR was not as effective at untargeted vegetable oil classification analysis as other spectroscopic techniques including FT-IR which had clear advantages in terms of cost, sample acquisition procedure, speed of analysis and versatility of the instrumentation used. That said, there is potential for application of NMR to food authentication due to its ease of use and quick analysis time.  The LAMP assay was applied to cheese, fish and meat speciation and proved most suitable for single species identification in small sample volumes. Using LAMP, some goat’s cheese samples were found to contain significant levels of sheep DNA. However, further surveying of cheese samples would be necessary to determine if this finding is indicative of fraudulent activity. The LAMP method was easy to use, was highly sensitive and had the additional benefit of being multiplex. REIMS was used for speciation of meat and fish as well as the method of “catch” (trawler vs line caught) while its application in determining the geographic origin of beef showed some tentative discrimination. Application of the REIMS technique for the rapid lipidomic profiling of food-grade meat products was successfully performed for the first time. REIMS has the capability to accurately differentiate between five similar white fish species rapidly using their phospholipid profiles. Therefore, REIMS technology could be applied to detect fish fraud within the global seafood supply chain with fast and accurate results being obtainable. It was also possible to differentiate between line and trawl caught haddock samples although it wasn’t clear if this distinction was due to catch method or dietary differences.

Key recommendations

  • REIMS coupled with advanced data processing and chemometrics could potentially be used in many areas related to food integrity.
  • The LAMP assay could be used for speciation of meat, fish and cheese and was found to be quicker than PCR. However further work is necessary to make this a high throughput technique.
  • NMR (60MHz) showed some potential for detected rapeseed oil adulteration but 400MHz NMR. However, FT-IR and Raman spectroscopies would work just as well or even better.

Principal Contractor(s):

Prof Chris Elliott, Queen’s University of Belfast

Dr Simon Haughey

Collaborator(s):

Prof Tom Buckley, IEC

Dr Olivier Chevallier, QUB Mass Spectrometry Centre

Dr Tassos Koidis, Queen’s University of Belfast

Outputs:

Report:

Exploration of novel technologies for counteracting food fraud (PDF, 5MB)

Bulletin 1 - Meat speciation (PDF, 1MB)

Bulletin 2 - Fish speciation (PDF, 1MB)

Peer review:

Connor Black, Olivier P. Chevallier, Simon A. Haughey, Julia Balog, Sara Stead, Steven D. Pringle, Maria V. Riina, Francesca Martucci, Pier L. Acutis, Mike Morris, Dimitrios S. Nikolopoulos, Zoltan Takats and Christopher T. Elliott. A real time metabolomic profiling approach to detecting fish fraud using rapid evaporative ionisation mass spectrometry. Metabolomics (2017) 13:153, pp2-13.