Researchers have introduced innovative methods to identify sugar syrup additions in honey, setting the stage for quick and precise tests to uncover counterfeit products.
Researchers from Cranfield University have created novel techniques for detecting sugar syrup adulteration in honey, which could lead to rapid and accurate testing of fake products.
The demand for honey is on the rise, with the UK importing honey worth £89.8 million in 2023. However, due to its high value, honey is susceptible to fraud, as cheaper syrups are sometimes mixed in with pure honey. A European Commission report from 2023 revealed that 46% of 147 honey samples assessed were likely adulterated with inexpensive plant syrups.
Identifying counterfeit honey can be challenging due to the natural variations in honey’s characteristics, which depend on factors such as nectar sources, harvest seasons, and geographic regions. Traditional authenticity testing is often expensive and time-intensive, resulting in a pressing need for dependable testing methods and new regulations to combat this fraud.
Researchers at Cranfield University have now tested two effective methods to authenticate honey from the UK efficiently and accurately.
Identifying fake honey without jar opening
A research initiative led by Dr. Maria Anastasiadi, a Lecturer in Bioinformatics at Cranfield University, in collaboration with the Food Standards Agency and the UK’s Science and Technology Facilities Council (STFC), employed advanced light analysis to verify honey authenticity without needing to open the jar.
They tested UK honey samples tainted with rice and sugar beet syrups using a non-invasive method called Spatial Offset Raman Spectroscopy (SORS). Originally developed at STFC’s Central Laser Facility (CLF), this technique is often used in pharmaceuticals and security assessments. It was found to be highly effective in detecting sugar syrups in honey. SORS quickly identified the unique ‘fingerprint’ of each component in the product, and the researchers paired this method with machine learning to efficiently detect and classify sugar syrups from various plant origins.
The portability and simplicity of this method make it an excellent tool for screening honey throughout the supply chain.
Dr. Anastasiadi stated, “Honey is a high-value product that is in demand, which makes it a target for fraudsters. This situation financially damages legitimate suppliers and erodes consumer trust. Our method serves as a quick, effective tool for identifying questionable honey samples, supporting the industry in safeguarding consumers and ensuring genuine supply chains.”
The study titled Application of Spatial Offset Raman Spectroscopy (SORS) and Machine Learning for Sugar Syrup Adulteration Detection in UK Honey appears in Foods 2024, vol. 13.
Using DNA traces to differentiate real from fake honey
The second method involved DNA barcoding, undertaken in partnership with the Food Standards Agency and the Institute for Global Food Security at Queen’s University Belfast. This approach was utilized to identify rice and corn syrups mixed with UK honey samples.
The researchers analyzed 17 honey samples sourced from beekeepers across the UK, representing different seasons and floral sources. Additionally, they purchased four honey samples from UK supermarkets and online retailers, which were then mixed with corn and rice syrups produced across various countries.
DNA barcoding, a method already employed in food authentication to recognize plant species in products, proved effective in analyzing the composition of each sample, successfully detecting syrups even at a 1% adulteration level.
“To date, DNA techniques have not been extensively utilized to assess honey authenticity,” remarked Dr. Anastasiadi. “However, our research demonstrated that DNA barcoding is a sensitive, trustworthy, and robust way to identify adulteration and verify the origins of the syrups in honey.”
“Given the significant variability in honey composition, authenticating it can be particularly challenging. Thus, having this reliable technique as part of our testing arsenal could alleviate honey fraud issues.”
Sophie Dodd, who is currently pursuing her PhD focusing on honey authentication at Cranfield University, noted, “It’s essential to have samples with known origins and purity to validate our methods. We sincerely thank the Bee Farmers Association for their collaboration on our projects.”
The two methods developed can complement each other, enhancing the likelihood of detecting external sugar adulteration in honey.
