Hamburgers that turn out to be horse, not beef. Honey sweetened with high-fructose corn syrup. Old, grey olives dipped in copper sulfate solution to make them look fresh and green. Fraudulent foods such as these make up as much as five to ten percent of the offerings on supermarket shelves, according to experts—but which food is most likely to be faked, and what does that tell us about our food system? Join us this episode as we put on our detective hats to investigate food fraud's long history and the cutting-edge science behind food forensics today—as well as what you can do to make sure what's on your plate is what you think it is.
In 2013, Britain was rocked by a scandal. Horsegate, as it came to be known, broke when horse meat was initially discovered in a brand of cheap supermarket burgers. Over the following weeks, horse DNA was found in all kinds of prepared foods that were never supposed to contain horse: frozen lasagna, jars of bolognese sauce, ready-to-eat chile con carne. In response, the U.K. set up a new national food crime unit. According to Andy Morling, its new head, this is the first of its kind in the world, a police unit devoted solely to fighting food fraud.
Though the British public was shocked by the scope of the scandal, Britain has long been a leader in fake food, according to food historian Bee Wilson. In her book, Swindled, she documents how the country's Industrial Revolution opened the door to food crime on a much more systemic scale. From carefully crafted fake peppercorns made from linseed oil and dust in the 18th century, to pricey Manuka honey stretched with cheap corn syrup today, in this episode, Morling and Wilson reveal the dark arts of food fraudsters past and present, as well as the harm their deceptions have caused. Meanwhile, Nicola Temple, author of Sorting the Beef from the Bull, joins us to discuss how modern forensic tests have evolved to detect even the most sophisticated food fakes—but also why we can't rely on science to save us. And John Spink, founding director of the pioneering Food Fraud Initiative at Michigan State University, shares his insights into how both companies and individual eaters can avoid being the victim of food crime. Listen in now for horrifying tales of melamine-laced baby food and copper-painted tea leaves, but also for the surprisingly appetizing ways in which eaters can defend themselves against scams.
Andy Morling and the National Food Crime Unit
The UK's National Food Crime Unit was founded in 2014, in response to horsegate. Andy Morling joined the unit as its first head in 2015, after a distinguished career in law enforcement, during which he specialized in covert surveillance and fighting online child sex abuse. Keep your eye on his Twitter feed, as the unit will be bringing its earliest cases to trial in the coming months.
Bee Wilson's Swindled
Bee Wilson has been a firm favorite here at Gastropod ever since she appeared in our very first episode, The Golden Spoon. You can also catch her in our episode on learning to eat, First Foods, and we refer to her work in our honey episode, too. We highly recommend her fantastic book on this episode's topic: Swindled: The Dark History of Food Fraud, from Poisoned Candy to Counterfeit Coffee.
Nicola Temple's Sorting the Beef from the Bull
Biologist turned science writer Nicola Temple is co-author, with biogeochemist Richard Evershed, of Sorting the Beef from the Bull: The Science of Food Fraud Forensics. It's worth a read for its astonishing step-by-step manual to assembling a fake egg alone.
John Spink, MSU Food Fraud Initiative
John Spink founded Michigan State University's Food Fraud Initiative in 2009. His 2011 paper, "Defining the Public Health Threat of Food Fraud," serves as a working definition of food fraud, but also highlights his own focus on prevention as opposed to intervention. Spink also joined Gastropod on stage at our April 2017 Live Show at Michigan State University Science Festival.
For a transcript of the show, please click here. Please note that the transcript is provided as a courtesy and may contain errors.