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As a basis for development of new, and rationalisation of existing products, consumer preferences in commercial filter coffees were examined in a quantitative approach with multivariate mapping. Coffees were brewed from 12 ground bean blends and served to 150 consumers as drunk normally – black, whitened and/or sweetened. In a complete block design with two sessions of six coffees, employing randomisation to reduce order effects, hedonic data on a five‐point scale were collected then processed using Q‐mode principal component analysis yielding preference maps for each presentation. Conventional descriptive profiling provided information on blend characters allowing soft modelling to determine sensory attributes driving preference scoring. From univariate data analyses, gender was a significant factor for presentation style: addition of milk increased preference scores for blends in males and sugar reduced preference ratings for females. The outcome was a series of consumer segmentations for different coffee presentations.

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