Novel Technologies Aim To Restore Trust in Honey Authenticity
Spectroscopy and DNA tools promise faster, more reliable honey authentication.
Honey has long been prized for its flavor, nutritional value and health-promoting properties. But with recent reports showing widespread adulteration, consumers and regulators alike are demanding better methods to ensure authenticity. Speaking at Technology Networks’ “Advances in Food & Beverage Testing 2025”, Dr. Maria Anastasiadi, senior lecturer in Bioinformatics at Cranfield University, unveiled innovative approaches combining spectroscopy, DNA analysis and machine learning to safeguard the honey supply chain.
Why honey authenticity matters
“Honey is a valuable commodity which is appreciated by consumers for its flavor, nutritional value and health-promoting properties,” said Anastasiadi. “However, there are concerns regarding the authenticity of products on the market, and there is no single definitive method that can prove honey authenticity.”
Adulteration often involves mixing pure honey with cheaper sugar syrups from rice, corn or sugar beet. Without robust testing methods, these fraudulent products reach supermarket shelves, undermining both consumer trust and producers of authentic honey.
Raman spectroscopy and machine learning
Anastasiadi’s team explored spatially offset Raman spectroscopy (SORS), a non-destructive technique that can analyze honey even through its jar. By shining a laser and collecting the spectral fingerprint, they could detect chemical differences between pure and adulterated samples.
“We don’t even need to take the honey out of the jar,” she explained. “The laser measurement gives us the chemical fingerprint of the honey.”
The spectra are then processed with algorithms. A machine learning model based on random forests was able to distinguish pure honey from samples spiked with sugar syrups at levels as low as 10%. “The algorithm correctly predicted all the samples and even told us what percentage of syrup had been added,” Anastasiadi said.
Crucially, this method is field-deployable. “The Raman device is also available as a handheld tool, so it can be taken to beehives, collection plants, or supermarket shelves for quick screening,” she noted.
DNA barcoding for hidden additives
Spectroscopy provides rapid screening, but DNA-based methods allow for precise targeting. The team developed qPCR markers that can identify DNA traces from plants used to produce adulterating syrups.
“We created specific markers for rice, corn, and beet,” Anastasiadi said. “The most successful were rice and corn, which we could detect even at 1% adulteration.”
She emphasized that the method is cost-effective and adaptable. “It’s similar to a COVID qPCR test – quick, cheap and reliable,” she explained.
Beyond honey: Meta-barcoding and global impact
Taking DNA analysis further, the researchers applied DNA metabarcoding to sequence all plant DNA fragments in honey. This revealed both botanical origin and adulteration. “In one test, we spiked heather honey with 25% rice syrup and were able to identify rice DNA alongside the floral sources,” Anastasiadi said.
This approach also has global applications. “We are working with African producers to detect pesticide contamination and with Australian producers to map botanical origins,” she added.
Building consumer confidence
The implications for trust are clear. “Using these methods, we can establish whether a honey labeled as Scottish heather honey truly originates there,” Anastasiadi said. For organic claims, spectroscopy can also be extended to pesticide detection.
Ultimately, Anastasiadi envisions an integrated approach: Raman spectroscopy for fast, non-destructive screening and DNA barcoding for confirmatory testing. “Source can flag inconsistencies, and then DNA testing can confirm whether there is an issue,” she summarized.
Looking ahead
A new four-year PhD project, supported by Rowse Honey, will expand the research to authenticate imported honeys, which dominate the UK market. “We’re adopting a holistic approach – combining molecular methodology, spectroscopy, and statistical modeling – to minimize the risk of adulterated honey reaching supermarket shelves,” said Anastasiadi.
With global honey fraud estimated in billions, these tools could restore consumer confidence while protecting honest producers. As Anastasiadi concluded, “Our aim is to make sure that the honey in the market is pure honey.”
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