The main consumer trends in food sector are two: on the one hand there is a growing demand for modernity (functional foods, convenience foods, healthy foods such as low calories and low-sodium foods), on the other hand there is a increasing demands for naturalness (organic foods, natural foods, local products and typical products). Moreover, in recent years consumers’ fears of novel food technologies are well documented and several psychometric scales were tested for the analysis of consumer’s attitude towards new technology. Therefore the ability to identify population segments that have greater or lesser neophobia/neophilia, thus enabling identification of early adopters of innovative products, would be more and more useful. A survey which bore such considerations in mind was conducted on a representative sample of 355 people interviewed shortly after their shopping trip to super- and hyper-markets in Campania region. A questionnaire was submitted to sample in spring 2010. The questionnaire collected information about the perception of new food technologies, the perception of naturalness and their roles in determining consumer preferences for different food products. To collect information about consumers perceptions we adopted the FTNS scale (Food Technology Neophobia Scale) which represents a useful tool for assessing receptivity to foods produced by novel technologies. A specific section of the questionnaire covered a case study and gathered information about the willingness to buy food products that consumers can associate to a greater or lesser use of modern technologies and belonging to a specific set of six food categories: functional foods, low calories foods, convenience foods (ready to eat) typical foods, organic foods, short chain products. First findings confirm that FTNS scale is a good instrument for predicting individuals’ willingness to try foods produced using modern technologies Moreover first results are consistent across the different types of products and technologies tested and thus provide consistent evidence of predictive validity.