Journal
JOURNAL OF DAIRY SCIENCE
Volume 84, Issue 1, Pages 12-20Publisher
AMER DAIRY SCIENCE ASSOC
DOI: 10.3168/jds.S0022-0302(01)74446-3
Keywords
quantitative descriptive analysis; principal component analysis; ultrapasteurized
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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 (R-2 = 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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