RMIT: Science takes guesswork out of cheese production and reduces waste

Researchers are helping take the guesswork out of cheese manufacturing by using science to better predict and control the ripening process.

Making cheese leaves a lot to chance as a batch could be ripened for months or even years before a problem is discovered, which could send a prized batch of cheddar to be sold off cheap as an ingredient for processed cheese.

It’s 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.

But new research from RMIT University allows quality to be checked much earlier and more precisely in the process, giving manufacturers a better chance to react to issues with the ripening process.

Dr Roya Afshari said the team devised a method to expose cheese’s biomarkers – or fingerprints – to show unique combination of things like chemicals and milk-derived components that make up the perfect block.

“Once we know the chemical profile of a successful cheese, we can compare it to new batches as soon as 30 days into the ageing process,” she said.

“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.

“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 kind of 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, because they can check to see if the key compounds have developed early in the ripening process or just as importantly that the bad ones haven’t – like having a crystal ball.

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 accurately assess for quality.

“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.

Chief supervisor of this research project Professor Harsharn Gill 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 to 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.”

Led by Gill, RMIT researchers – including Professor Mark Osborn, Dr Daniel Dias and Dr Christopher Pillidge – are continuing development in this area, including investigating new ways to interpret the millions of data points extracted from food samples.

“As new tools become available, we’ll have more power to inspect and interpret chemical data from food from many different angles, leading to more sustainable manufacturing,” Gill said.