Electronic nose technology in quality assessment: monitoring the ripening process of Danish blue cheese

Rapid, objective assessments for monitoring the ripening process of fermented food products are of great interest in the food industry. Instrumental techniques and sensory panels can be expensive and require trained personnel. An electronic-nose (e-nose) system offers less skill required, lower investment needed, automated artificial intelligence, and can be easily used as a screening method. In this work, headspace samples from 2 types of Danish blue cheese (traditional cheese and from pasteurized milk) were analyzed with an e-nose system. Features from the responses of the chemical sensors were used to model the changes that occur during shelf life (5, 8, 12, 20, and 33 wk after brining) by multivariate analysis methods. Multiplicative scatter correction (MSC) also corrected signals for instrument artifacts occurring with time. Traditional cheeses from a 2nd unit, as well as cheeses made with pasteurized milk from the same unit were tested for their similarities to the traditional ripening model. Differences were recorded by the e-nose both between dairy units and products within the same unit. The differences, reflected in the cheese smell, were larger at early ripening stages but were eliminated with time. Classification of the unknown traditional cheeses (from a 2nd unit) as well as new type cheeses by ripening stage was possible with the use of the e-nose system. The current results indicate that the e-nose technology can be directly applied in quality assessment of Danish blue cheese products and ripening monitoring of this type of cheese.