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

Quantitative descriptive analysis was used to describe the key attributes o f 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 fo r 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 scale s primarily corresponded to cooked, drying/lingering, sweet, and bitter att ributes. Overall product quality was modeled as a function of the principal components using multiple least squares regression (R-2 = 0.810). These fi ndings demonstrate the utility of quantitative descriptive analysis for ide ntifying and measuring UP fluid milk product attributes that are important to consumers.