Open Collections

Shelf-life prediction and flavour quality assessment of pasteurized milk by multivariate analysis of dynamic headspace gas chromatographic data

University of British Columbia

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<.001) In addition, the zone of “good” or “normal” flavour groups could be visualized in two dimensional canonical plots. Thus any sample deviating from this zone could be considered a defective product. Since any test for keeping quality of milk must emphasize those organisms (initially present in low numbers) that can spoil the product under refrigeration, preliminary incubation before volatile detection was included. Using DH-GC for shelf-life prediction and flavour quality assessment of pasteurized milk, results were available in 20 h (18h preliminary incubation + 2h detection and data processing). Although other rapid instrumental techniques have been proposed for milk shelf-life prediction, dynamic headspace gas chromatography coupled to mass spectrometry (DH-GC-MS) as reported in this thesis is the only method that allows the chemical identification of milk volatiles, which are ultimately the cause of off-flavours and termination of shelf-life. Linear discriminant analysis of gas chromatographic data allowed the identification of milk volatiles that contributed most significantly (p<0.01) to the discrimination among flavour quality groups. The analytical system established in this thesis may prove to be a useful quality control tool for the dairy industry.

Thesis/Dissertation

application/pdf

2008-12-17

For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.

http://hdl.handle.net/2429/3038

Food Science

University of British Columbia

UBCV

DSpace