Rank-rating and monadic scoring were compared in profiling sensory aroma character of 27 Greek dry red wines with 16 attributes. In parallel wine headspace volatiles were quantified using solid-phase micro-extraction gas chromatography but not identified. In rank-rating, 14 aroma attributes showed discriminations with P<0.05 and 11 P<0.001. In scoring, 6 of 16 attributes showed P<0.05. Principal component analysis (PCA) explained 88% variance in rank-rating data, with six significant components (PCs), in scoring 40% in two PCs. PCA analysis of 83 common flavour volatiles explained 48% variance in six PCs. Partial least-squares regression (PLS1) modelling achieved more and better models for attributes using rank-rating, 8 of 14, than for scoring, 3 of 16; PLS2 explained greater variance in rank-rating. For wine sensory/instrumental correlation studies, rank-rating has distinct advantages over monadic scoring in deciding volatiles contributing to sensory character prior to identification strategies such as HRGC–mass spectrometry.
- flavour modelling
- sensory profiling
- PLS regression
Koussissi, E., Paterson, A., & Piggott, J. R. (2007). Sensory profiling of aroma in Greek dry red wines using rank-rating and monadic scoring related to headspace composition. European Food Research and Technology, 225(5-6), 749-756. https://doi.org/10.1007/s00217-006-0478-7