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Research projects have developed fresh ways to detect sugar syrup adulteration in honey and uncover fake products.

Credit: Cranfield University

New projects funded by the Science and Technology Facilities Council (STFC) and led by researchers from Cranfield University have developed new ways to detect sugar syrup adulteration in honey.

This paves the way for fast and accurate tests to discover fake products in a market worth many millions of pounds.

There is growing consumer demand for honey, with £89.8 million worth of honey imported to the UK in 2023 alone.

But such a high-value product is vulnerable to fraud, with syrups being added to dilute the pure honey and increase profits for the seller.

A report from the European Commission in 2023 found 46% of 147 honey samples tested were likely to have been adulterated with cheap plant syrups.

Difficult to detect

It can be very difficult and complex to detect adulterated honey products, particularly because honey’s characteristics vary immensely due to sources of nectar, season of harvest and geography.

Existing authentication methods have been costly and time consuming, and there is a growing appetite for reliable testing and the adoption of new rules to try and combat fraud.

Now scientists at Cranfield University have successfully tested two new methods to authenticate UK honey quickly and accurately thanks to support from STFC’s Food Network+ research programme.

Detecting fake honey without lifting the lid

A research project led by Dr Maria Anastasiadi, Lecturer in Bioinformatics at Cranfield University, with support from the Food Standards Agency and STFC, used a specialist light analysis technique to detect fake honey without opening the jar.

Samples of UK honeys spiked with rice and sugar beet syrups were tested at STFC’s Central Laser Facility (CLF).

Tests were done using the non-invasive Spatial Offset Raman Spectroscopy (SORS) method, a technique developed originally at CLF that is more commonly used in pharmaceutical and security diagnostics.

This method proved highly accurate in detecting sugar syrups present in the honey.

SORS rapidly identified the ‘fingerprint’ of each ingredient in the product, and the scientists combined this technique with machine learning to successfully detect and identify sugar syrups from various plant sources.

Demonstrating the potential of SORS

Dr Sara Mosca, Raman Spectroscopy Scientist at STFC’s CLF, yesterday said:

It was a pleasure to contribute to this exciting research, using our SORS expertise to support Dr Anastasiadi’s project and help open up a significant new application area for this technology.

The results of this study demonstrate the potential of SORS, in combination with machine learning, to rapidly check the authenticity of honey samples and the detection of any added sugar syrups that may have been added to them. The major advantage of the SORS technique developed by our team is that it is a rapid, non-invasive method deployable in the field with potential application at all stages of the supply chain.

Dr Anastasiadi yesterday commented:

Honey is expensive, and in demand – and can be targeted by fraudsters, which leaves genuine suppliers out of pocket and undermines consumers’ trust. This method is an effective, quick tool to identify suspicious samples of honey, helping the industry to protect consumers and verify supply chains.

DNA traces in honey used to decipher real from fake

A second project funded by STFC’s Food Network+ programme used DNA barcoding to detect rice and corn syrups spiked in UK honey samples.

The Cranfield University team worked in collaboration with the Food Standards Agency and the Institute for Global Food Security at Queen’s University of Belfast.

The team used 17 honey samples collected from bee farmers around the UK, representing different seasons and floral nectar sources, and bought four samples of UK honey from supermarkets and online retailers.

The samples were then spiked with corn and rice syrups produced in a range of countries.

DNA barcoding, a method already used in food authentication to identify plant species in products, was effective in breaking down the composition of each sample, to successfully detect syrups even at 1% adulteration level.

Dr Anastasiadi yesterday commented:

To date, DNA methods haven’t been widely used to examine honey authenticity.  But our study showed that this is a sensitive, reliable and robust way to detect adulteration and confirm the origins of syrups added to the honey.

Together these two new methods increase the chances of detecting sugar adulteration in honey before it reaches the consumer.

Further information

The paper Detection of sugar syrup adulteration in UK honey using DNA barcoding was published in Food Control, vol. 167.

The paper Application of Spatial Offset Raman Spectroscopy (SORS) and Machine Learning for Sugar Syrup Adulteration Detection in UK Honey was published in Foods 2024, vol. 13.