Abstract
A comparative study of linear methods for prediction of sensory profiles from gas chromatography (GC) measurements was performed. The data used came from an experiment on the effect of storing apples at various oxygen concentrations. Partial least-squares regression and continuum regression showed the best performance, measured by a two-step cross-validation principle. The traditional prediction error sum of squares (PRESS) overestimated the predictive ability of a multiple linear regression approach. The quality of the predictions of sensory properties from GC analyses was measured in terms of a ‘panel size equivalent’. Thus, the predictions obtained in the present study were as accurate as predictions from an assessor panel consisting of 4–9 assessors, depending on the sensory property in question.
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