Taking the guesswork out of cheese production

RMIT University

Wednesday, 03 March, 2021



Taking the guesswork out of cheese production

Researchers have devised a method that is designed to allow cheese quality to be checked much earlier and more precisely, making cheese production more efficient.

The RMIT University research team sought to remove the guesswork out of cheese production, giving manufacturers a better chance to react to issues with the ripening process.

Currently, the method for identifying problems in cheese production is slow and complicated, taking potentially years for the issue to surface.

RMIT researcher Dr Roya Afshari said it is part of why cheese is so complex and expensive to make.

“A factory could invest lots of time and money into what they think will be a top-graded batch, only to discover it’s a flop when it’s too late to fix.”

The team devised a method to expose cheese’s biomarkers — or fingerprints — to show unique combinations of chemicals and milk-derived components that make up the perfect block.

Afshari said once scientists know the chemical profile of a successful cheese, they can compare it to new batches as soon as 30 days into the ageing process.

“It’s like a pregnancy screening test for cheese — we analyse the biological data early in the development to see if there are any red flags,” she said.

“This could be done alongside traditional analyses like tasting to highlight future potential problems.”

The team looked at different commercial cheddar cheeses in Australia and applied multi-omics — a biological analysis typically used in human medicine to detect diseases early.

Researchers studied the biological make-up of different brands and grades of cheese and worked with data experts to interpret and compare the results for known batches.

“Once we knew the unique properties of a finished cheese, we compared them to ripening batches and worked out which compounds distinguished the best cheeses,” Afshari said.

With larger datasets, it will be possible for these techniques to let manufacturers know if their batch will age properly. This is because they can check to see if the key compounds have developed early in the ripening process or that the bad ones haven’t.

What’s more, the practice of grading a cheese’s quality and maturity will no longer need to be left to subjective human senses.

Afshari said incorporating multi-omics analysis into testing cheese gives professional cheese graders more tools to assess quality accurately.

“Cheese chemical fingerprints can be compared against those found in the perfect product, along with traditional grading methods. Now we can identify different types and grades of cheese more accurately than a taste test.”

The researchers have published three recent studies demonstrating how interpreting the biological profile of cheese can aid manufacturing and grading.

In separate studies, they used multi-omics analyses to differentiate cheddar cheeses based on their age and brand, compare cheese of varying quality and group artisanal and industrial cheddar cheeses based on type and brand.

From cheese to wine

The method devised by the RMIT team is scalable and, with more development, could be used to test just about any food or beverage product, including wine, for quality and authenticity.

This is significant, as counterfeit wines are a multi-billion-dollar problem plaguing the industry.

Professor Harsharn Gill, Chief supervisor of this research project, said the days of counterfeit food and drink products could be numbered as bioanalysis technology becomes commercially available.

“Some product’s fingerprints are so unique and detailed that we can narrow down a sample to its origin,” he said.

“Clues like the type of grapes used in the fermenting process can be answered by studying wine and comparing results to a trusted sample.

“We’re still a long way off from having the technology affordable and therefore widely accessible, but we’re open to working with industry using facilities in the RMIT Food Research and Innovation Centre.”

Image credit: ©stock.adobe.com/au/Igor Dutina

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