Development of a Hierarchical Rate-All-That-Apply (HRATA) methodology for the aromatic characterisation of wine

Abstract

Wine aromatic characterisation is generally a complex task, even for well-trained assessors. To facilitate such characterisation, aroma terms are typically arranged in some sort of hierarchical structure, such as aroma wheels. However, information about this structure is lost with existing data acquisition and treatment methods. To fill this gap, we propose a new approach, Hierarchical-Rate-All-That-Apply (HRATA), for the characterisation of products. It combines the Rate-All-That-Apply (RATA) methodology with a hierarchical structuring of general and specific attributes. The aim is first to facilitate data acquisition and, secondly, to account for the hierarchical links among attributes during data analysis. We applied an HRATA approach to the characterisation of five rosé wines by 66 subjects based on 118 hierarchically structured aromatic attributes. Using monadic evaluation, assessors were asked to select all the attributes that characterised each wine and to rate their intensity on a three-point scale. For the data analysis, an initial coding step was carried out to represent the hierarchical structure of the attributes, which also made it possible to manage a large amount of non-evaluated data. After that, statistical tests and multivariate analyses were tailored for both the identification of discriminating attributes and the determination of a product map. Finally, the characterisation obtained with HRATA was compared to the results obtained from a descriptive analysis (DA) conducted by a trained panel. HRATA represents an interesting alternative for obtaining aromatic characterisation using a panel of subjects without collective common training or with diverse skill sets.