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Abstract

An objective analytical system for shelf-life prediction and flavour quality monitoring of pasteurized milk was established. Dynamic headspace capillary gas chromatography (DH-GC) was optimized to achieve adequate resolution and maximum recovery of volatiles isolated from milk. The simultaneous factor optimization approach used for establishing purge and trap conditions during milk volatile isolation resulted in a method of high sensitivity and reproducibility. Volatiles, psychrotrophic bacterial counts and sensory evaluation were monitored during refrigerated storage of pasteurized milk and multivariate statistics were applied to accumulated data. Multivariate statistical analysis, including principal components regression and linear discriminant analysis was applied to 46 peak areas from 134 chromatograms. Principal components regression of gas chromatographic data and flavour related shelf-life was successful in developing a model for milk shelf-life prediction. The resulting standard error of the estimate of less than two days in shelf-life was an excellent approximation for shelf-life prediction purposes. Linear discriminant analysis was able to classify milk into good, marginal and poor quality or into fruity, rancid and normal flavour groups at a greater than 80% success rate (p