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Food Leaders: UGent Professor Frank Devlieghere on lean labels and predictive microbiology

Food Leaders: UGent Professor Frank Devlieghere on lean labels and predictive microbiology

In Food Leaders, experts share their views on the macro trends in the food sector. Frank Devlieghere, professor of food microbiology and conservation techniques at the UGent, talks about the evolution towards lean labels and the strength of predictive microbiology.

 

From ‘clean label’ to ‘lean label’

"The emergence of clean labels is perhaps the most profound evolution of the food industry in recent years," says Professor Frank Devlieghere. "A clean label does not mean additives. This poses many problems for producers in terms of food safety and shelf live. Legislators and retailers are beginning to see that."

"For clarity: approved additives have been examined in detail. We are therefore certain that they are doing their job and are fully safe. This is not always the case with natural preservatives, which, moreover, often have an unfavourable effect on the flavour and smell of products.’

 

"Lean Labels will therefore replace clean labels in the coming years. Producers will be able - to a limited extent - to re-use additives, provided that they communicate in a transparent manner. They will have to critically evaluate each time whether an additive is necessary and substantiate its use. This would help to strike a better balance between food safety and reducing food waste. This will benefit everyone: producer, retailer and consumer.’


"A lean label strikes a better balance between food security and the reduction of food waste" - Professor Frank Devlieghere


Powerful forecasting models

Professor Devlieghere and his colleagues strongly believe in the power of forecasting microbiology. "We make mathematical models that can predict the behavior of micro-organisms. That requires a lot of complex labo and computer work. But once you have such a model, you have an incredibly powerful tool available to predict the impact of preservation  techniques without doing experiments."