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J Dairy Sci. 2001 Jan;84(1):12-20.

Quantitative descriptive analysis and principal component analysis for sensory characterization of ultrapasteurized milk.

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1
Dept. of Food Science, Cornell University, Ithaca, NY 14853, USA. kwc3@cornell.edu

Abstract

Quantitative descriptive analysis was used to describe the key attributes of nine ultrapasteurized (UP) milk products of various fat levels, including two lactose-reduced products, from two dairy plants. Principal components analysis identified four significant principal components that accounted for 87.6% of the variance in the sensory attribute data. Principal component scores indicated that the location of each UP milk along each of four scales primarily corresponded to cooked, drying/lingering, sweet, and bitter attributes. Overall product quality was modeled as a function of the principal components using multiple least squares regression (R2 = 0.810). These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring UP fluid milk product attributes that are important to consumers.

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