Clustering of variables around latent components: an application in consumer science

The present work proposes a method based on CLV (Clustering around Latent Variables) for identifying groups of consumers in L-shape data. This kind of datastructure is very common in consumer studies where a panel of consumers is asked to assess the global liking of a certain number of products and then, preference scores are arranged in a two-way table Y. External information on both products (physicalchemical description or sensory attributes) and consumers (socio-demographic background, purchase behaviours or consumption habits) may be available in a row descriptor matrix X and in a column descriptor matrix Z respectively. The aim of this method is to automatically provide a consumer segmentation where all the three matrices play an active role in the classification, getting homogeneous groups from all points of view: preference, products and consumer characteristics. The proposed clustering method is illustrated on data from preference studies on food products: juices based on berry fruits and traditional cheeses from Trentino. The hedonic ratings given by the consumer panel on the products under study were explained with respect to the product chemical compounds, sensory evaluation and consumer socio-demographic information, purchase behaviour and consumption habits.

Milk and dairy products: evaluation of bioactive components by analytical techniques

Milk and dairy products are important source of bioactive compounds useful to satisfy the nutritional and physiological needs of any newborns of mammalian species and useful to guarantee adequate growth and development of infants as well as provide a complete nourishment of adults. Physico-chemical, nutritional and organoleptic properties of the main constituents and the “minor” components have a crucial role in the quality of milk and milk products. Although in the past decades dietary milk fat was often regarded as harmful for the human health, recent researches suggest that milk contains specific fatty acids with nutritional and physiological health benefits. For these reasons, a major attention is given to the quantity and quality of total fat intake. In the recent years, as a result of the new concept of multifunctional agriculture and the changing behaviours about diet, consumer demands in favor of high-quality, security and safety dairy products are increased. Moreover, milk proteins and milk-derived bioactive peptides are recognized to have a high nutritive value, several health-promoting functional activities and excellent technological properties. Accordingly, growing interest in the development of functional dairy products and preparation of infant formulae for babies who cannot be breast-fed, has been give in order to meet the specific consumer’s requests. This manuscript presents the main results obtained during my PhD research aimed to evaluate the main bioactive lipids and proteins in milk and dairy products using innovative analytical techniques. The experimental section of this manuscript is divided in two sections where are reported the main results obtained during my research activities on dairy products and human milks in order to characterize their bioactive compounds for functional food applications.