Fingerprinting food spoilage microorganisms
Microorganisms such as bacteria, yeasts and moulds could be lurking in the tubes that convey milk to cartons, lying in wait on the floor or even floating in the air where sausages are being packaged. They are poised to contaminate food and cause food spoilage and deterioration during food production.
Currently the food industry uses observation and testing to troubleshoot the risks of contamination during production. Now, Norwegian researchers have developed new methods to identify potential sources of food and beverage contamination. These may stop unwanted bacteria, yeasts and moulds from causing major problems for the food industry as well as consumers.
The participants in a research project carried out by the research institute Nofima Mat and packaging company Elopak have developed a more effective method of identifying infection sources that is faster and more economical to use.
Using a spectrometer, the researchers are able to detect undesirable microorganisms in finished products and trace them back to the various steps in the production process.
Scientists have long used Fourier transform infrared (FTIR) spectroscopy as a method of chemical analysis, and for the last two decades for identifying bacteria as well. The method can also detect all types of microorganisms in air, fluids and many other substances.
“But no one had so far used the method for identifying food contaminants,” says Henri-Pierre Suso, a researcher at Elopak.
He headed a user-driven project that received funding under the Research Council’s Food Programme: Norwegian Food from Sea and Land.
Researchers at Nofima Mat have taken spectral readings of various microbes collected from a wide variety of foods, including juice and milk. Each microbe has its own unique spectral profile, which functions much like a fingerprint and was used for identification purposes.
“In the project we developed a database of information about the samples, where we have stored approximately 20,000 spectral profiles of different microbes. We’ve also implemented sound laboratory routines to ensure the readings are reproducible,” explains Suso. “Whenever we found an unknown microbe, we took a spectral reading of it, then we compared its profile with those already entered in the database.”
Suso says there are currently a number of methods used for locating sources of contamination in the food industry, “but we are convinced that ours is the most cost-effective solution. It is a very precise and high-capacity method, with the additional advantage that technicians don’t need to be specialists in mycology in order to identify the microorganisms.”
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