News

The Royal Society of Chemistry’s “Advances in the Chemical Analysis of Food V” conference, last week, included a number of talks and posters on various aspects of food authenticity testing.  The keynote, from Professor Chris Elliot, was on the use of data fusion to improve untargeted classification models by aggregating information from multiple analytical approaches.

One presentation, from Nathan O’Neill at the University of East Anglia (a FAN Centre of Expertise) raised new suspicions about turmeric authenticity.

Conventional wisdom (and Seasoning & Spice Association guidance) is that a significant vulnerability point for turmeric adulteration is when the roots are ground.  However, in this case, Nathan sourced intact roots from both UK and overseas online sellers.  Only reputable sellers were used but there were no prior assumptions about sample authenticity.  Chemometric feature selection and modelling (using two orthogonal untargeted analytical techniques) highlighted some of the samples whch were clear outliers.  These outlying classifications were consistent between replicate analyses and between the two orthogonal test methods.

The next planned research stage is to build reference databases for each method, then check if these outliers are mislabelled or if it reflects honest variation within turmeric taxonomy and production.

Details of the conference programme and speakers can be found here

Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks to public health and the environment. Therefore, the development of analytical techniques that can rapidly detect fraud and verify the authenticity of such products is of paramount importance.

Traditionally, a wide variety of targeted approaches, such as chemical, chromatographic, molecular, and protein-based techniques, among others, have been frequently used to identify animal species, production methods, provenance, and processing of food products. Although these conventional methods are accurate and reliable, they are destructive, time-consuming, and can only be employed at the laboratory scale. On the contrary, alternative methods based mainly on spectroscopy have emerged in recent years as invaluable tools to overcome most of the limitations associated with
traditional measurements. The number of scientific studies reporting on various authenticity issues investigated by vibrational spectroscopy, nuclear magnetic resonance, and fluorescence spectroscopy has increased substantially over the past few years, indicating the tremendous potential of these techniques in the fight against food fraud.

This manuscript reviews the state-of-the-art research advances since 2015 regarding the use of analytical methods applied to detect fraud in food products of animal origin, with particular attention paid to spectroscopic measurements coupled with chemometric analysis. The opportunities and challenges surrounding the use of spectroscopic techniques and possible future directions are also be discussed.

Read full paper here.