Simultaneous analysis of consumer variables, acceptability and sensory characteristics of dry-cured ham. (November 2016)

• Record Type: Journal Article
• Authors: Sugimoto, Masahiro; Obiya, Shinichi; Kaneko, Miku; Enomoto, Ayame; Honma, Mayu; Wakayama, Masataka; Tomita, Masaru
• Is Part Of: Meat science. Volume 121(2016:Nov.)
• Page Start: 210
• Page End: 215
• Publication Date: 2016-11
• Subjects: Dry-cured ham -- Sensory evaluation -- Consumer acceptability -- External preference mapping -- Hierarchical analysis; Meat -- Periodicals; Meat industry and trade -- Periodicals; Viande -- Périodiques; Viande -- Industrie -- Périodiques; Meat; Meat industry and trade; Periodicals; 641.36
• DOI: 10.1016/j.meatsci.2016.06.015
• Languages: English
• ISSNs: 0309-1740

Abstract

Abstract: We conducted a consumer acceptability analysis of dry-cured ham based on sensory evaluation. Consumer acceptability data are rendered heterogeneous by the diverse backgrounds and assessment abilities of the participants, requiring versatile analytical methods for their interpretation. Totally, 9 sensory attributes of 12 kinds of dry-cured ham samples collected from Japan ( n = 9), Italy ( n = 1), Spain ( n = 1), and Germany ( n = 1) were tasted by 117 Japanese consumers who showed acceptable evaluation abilities during blind sampling. Common techniques, such as hierarchical clustering, principal component analysis, and external preference mapping, were simultaneously utilized to analyze each characteristics scored in modified hedonic scale. These analyses revealed the relationships between the features and preferences of the assessors. For example, consumers aged 20–30 with smoking and drinking habits preferred sweetness and saltiness, and gave high ratings to Spanish Jómon serrano and Italian prosciutto. Our approach could assist ham marketers to identify potential purchasers and the preferred characteristics of their products. Highlights: Consumer acceptability of dry-cured ham was analyzed by sensory evaluation. Clustering, principal component analysis and external preference mapping were used. These methods can help to identify potential purchasers.