The use of an ‘electronic nose’ device to monitor the ripening process of anchovies

Abstract

Summary Qualitative changes in flavour profiles that are associated with the ripening of anchovies were investigated. Samples, either commercially processed or ripened on a laboratory scale, were analysed by a device known as an electronic nose, which is based on conductive polymers. Operational parameters were optimized by means of screening factorial designs using the discriminating power between samples as the objective function. Electronic nose measurements need no sample preparation and the results indicated that the ripening process of anchovies could be followed by using this technique. Several chemometric techniques (principal component analysis, k-nearest neighbour, soft independent modelling of class analogy and multilayer feed forward artificial neural networks) were applied to model the ripening process and to classify samples into separate classes as a function of the ripening stage, and all produced satisfactory results. The ability and limitations of these predictive models are discussed, especially the influence that other factors have in affecting the raw material quality and characteristics in the developed models. These defined the conditions to be met in order to produce reliable predictions, thus establishing the real value of the electronic nose models in the monitoring of quality control of the anchovy maturation process and production.