Within the ASSET Centre in IGFS, there are a wide range of spectroscopic instrumentation for use in untargeted and targeted analysis. These include the high end iS50 multi-spectroscopic instrument (FT-IR, NIR, Raman), iS5 FT-IR, Antaris II NIRS, Delta Nu Raman (1064nm) and various handheld instruments e.g. SCiO NIR, Micro-NIR, Spectrolytic MIR. Analysis using the spectroscopic techniques gives rise to unique fingerprint profiling and coupled with powerful chemometric software can produced application models for qualitative and quantitative analysis. Models have been developed to detect adulteration in a wide range of commodities at risk from fraud. These include edible oils and feed oils, herbs and spices and soya bean meal. Be-spoke proximate analysis models using NIR have also been developed in conjunction with animal feed companies.
Examples of some our projects employing Spectroscopic Fingerprinting:
Food fraud is an extremely topical and important issue. Globally it has been estimated to cost up to $US49b annually. The National Food Crime Unit estimates that it costs British families £1.17b per year. The British Retail Consortium suggest 1 in 10 consignments of imported basmati rice has been adulterated, whilst our recent work on oregano fraud showed 25% of retail product, on UK shelves, was adulterated with this pattern repeated globally. Economic gain is often the goal with authentic products substituted with (or diluted by) inferior/ cheaper products, as was exemplified by the 2013 horsemeat scandal. However, there are also health implications, for example the largest allergen based food recall in history occurred in the US (2014) and was due to fraud (presence of peanut) in the spice cumin or the 2008 adulteration of Chinese infant formula which saw over 300,000 babies hospitalised with multiple mortalities.
Traditional methods used to determine food authenticity are laboratory based, require skilled operators, are expensive or time consuming and can take days or even weeks to complete. Meanwhile the product passes along the supply chain and in many cases reaches the supermarket shelf or consumer tables before results are reported. New and better ways of checking the authenticity of foods and their ingredients are required. Methods capable of rapid detection anywhere, anytime, in the food supply chain are what industry are demanding. Invest NI Proof of Concept funding is supporting our research into food fraud detection using handheld spectroscopic analysis in conjunction with chemometric modelling. Within this project rapid portable tools that will determine food authenticity within a few minutes will be developed. Analysis will be taken out of the laboratory and put into the hands of food industry stakeholders at the point of interest. In order to achieve this, we are using a range of commercially available handheld instruments to produce a database of food “fingerprints” for a variety of at-risk commodities identified within the UK supply chain, by a team comprising QUB staff and industry experts, then constructing bespoke chemometric models that will identify authenticity issues. Furthermore, we have engaged with international retailer and auditing companies to not only obtain the invaluable authentic samples but to also incorporate end user feedback through real life validation and food trials.
Many consumers nowadays pursue products that are sourced from sustainable sources. The majority of pastry and snacks, convenient food in the supermarkets globally is rich in palm oil which is a good source of saturated, low trans fat. In fact an average person consumes more than 15 kg of palm oil per year, most of it from non-sustainable sources. The spectroscopy based technology that was developed at ASSET labs at the IGFS by a team led by Dr Tassos Koidis, can identify the quantity of palm oil in most of these products as well as in blends of oils with good accuracy in just a matter of seconds. Funded by two consecutive DEFRA UK projects over the course of 3 years, the QUB researchers developed generic state-of-the art chemometric models and a web based analytical platform using the spectral fingerprints of thousands of vegetable oils sourced globally. This method is now considered for adoption as a screening tool for UK Public Analysts. Next challenge for the team is to identify sustainable from non-sustainable palm oil linking elemental content with specific geographical locations.
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