What offal is lurking in your mince?

Is your minced beef all beef, or does it contain offal as well? Now there is fast and accurate way to find out.

University of British Columbia Professor Xiaonan Lu and his students have found a way to get the answer to this problem in under five minutes.

The team used a laser-equipped spectrometer and statistical analysis to determine with 99% accuracy whether ground beef samples included offal or other animal parts. Not only could they identify the animal parts, they could also determine their concentration — all with 80% accuracy.

This speed and accuracy makes the method potentially transformative for government and industry food inspectors and quality assurance.

While DNA testing is efficient and accurate in identifying foreign species in meat products, it is unable to identify offal — hearts, livers, kidneys and stomachs — mixed in with meat of the same species. With this UBC technique, the detection of this type of food fraud will be simpler, faster and easier.

Food fraud is the intentional misrepresentation of food products for economic gain. When producers hold an excess supply of meat or by-products for which there is relatively little market demand, the potential exists for unscrupulous operators to try to pass those products off as something else.

How it works

Yaxi Hu loads a spectrometer with a sample of ground beef in the food sciences lab at UBC. Image credit: Paul Joseph/UBC.

To establish their method, the UBC researchers aimed a spectrometer at meat samples they had prepared by grinding together beef and offal from local supermarkets at various concentrations. Because animal products all have different chemical compositions, their molecules absorb and scatter energy from the spectrometer’s laser in different ways. The spectrometer captures these signals — or spectra — to produce an ‘image’ of each substance. These spectral images can serve as a library for comparison with other samples.

Whether a meat sample is authentic or adulterated with offal can be determined by comparing its spectral image with the pre-established library, to see if there’s a match.

The method improves on existing techniques that are more complicated and time-consuming. For example, liquid chromatography works well, but it requires meat samples to be liquefied with solvents before testing, which can take more than an hour.

The instrumentation required is not complex and personnel would not have to be highly trained to do rapid screening tests. All they would need is a spectrometer and user-friendly software that connects to a robust library of spectral images. As more types of meat and offal are analysed and the results stored, accuracy would improve even further.

Hu analyses the meat sample’s spectra against those that have been previously collected in a library. Image credit: Paul Joseph/UBC.

To make it even easier, the researchers’ ultimate goal is to create an affordable smart device that could be used by consumers at home for the authentication of different food products, much like the pregnancy test strip.

Top image credit: Paul Joseph/UBC.