Abstract
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.
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Abbreviations
- PCA:
-
Principal component analysis
- PLS:
-
Partial least-squares
- HS-SPME:
-
Headspace solid-phase micro-extraction
- HRGC:
-
High-resolution gas chromatography
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Acknowledgements
We thank the State Scholarships Foundation of Greece (IKY) for support greatly appreciated by the authors. We would also like to thank Lorraine Allan for excellent technical support.
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Koussissi, E., Paterson, A. & Piggott, J.R. Sensory profiling of aroma in Greek dry red wines using rank-rating and monadic scoring related to headspace composition. Eur Food Res Technol 225, 749–756 (2007). https://doi.org/10.1007/s00217-006-0478-7
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DOI: https://doi.org/10.1007/s00217-006-0478-7