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Objective monitoring of milk quality using a dynamic headspace gas chromatograph and computer-aided data processing

University of British Columbia

This research was undertaken because of the need to develop an objective method for quality control of milk. A major problem in the dairy industry is off-flavour often found in milk. Quality control of milk is heavily dependent upon sensory evaluations supported by microbiological and chemical analyses. The chief purpose of this research was to demonstrate a simple and economical system for quality control of milk using a gas chromatogf aph and computer-aided data processing. Two experiments were conducted: one using microbial off-flavours and another using chemically induced off-flavours. First, Ultra High Temperature (UHT)-sterilized milk was inoculated with Pseudomonas fragi, Psuedomonas fluorescens, Lactococcus lactis, Enterobacter aerogenes, Bacillus subtilis and a mixed culture (L. lactis: E. aerogenes: P. fragi = 1:1:1) with approximately 10⁴ CFU mL⁻¹. The samples were stored at 4°C up to 10 days for P. fragi and P. fluorescens and at 30°C up to 24 hours for L. lactis, E. aerogenes, B. subtilis and the mixed culture. Several multivariate analyses were applied to the standaridized peak areas of GC data. A new multivariate analysis technique, principal component similarity analysis (PCS), was capable of classifying milk samples with regard to bacterial species and storage time. Artificial neural networks (ANN), partial least squares regression analysis and principal component regression analysis were also applied. ANN provided the most accurate means of classification. Secondly, pasteurized milk was treated to develop different off-flavours (lightinduced, oxidized, cooked and heated) according to the procedures of the American Dairy Science Association. The same pasteurized milk samples as those used for gas chromatographic analysis were used for sensory evaluation. Gas chromatography (GC) combined with PCS was more effective than sensory evaluation as a means of distinguishing milk samples. It was concluded that a combination of GC and chemometric methods may have great potential in evaluating the chemical and microbial quality of milk.

Thesis/Dissertation

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2009-02-20

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http://hdl.handle.net/2429/4839

Food Science

University of British Columbia

UBCV

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