Classification of microbial defects in milk using a dynamic headspace gas chromatograph and computer-aided data processing .1. Principal component similarity analysis

There is a need for reliable objective tests for the detection of off-flavors of milk, some of which are caused by bacteriological growth. The objective of the study was to distinguish abnormal from normal milk samples using a low-cost headspace gas chromatograph and principal component similarity analysis. UHT-sterilized milk was inoculated with Pseudomonas fragi, Pseudomonas fluorescens, Bacillus subtilis, Enterobactor aerogenes, Lactococcus Lactis, and a mixed culture (P. fragi:E. aerogenes:L. lactis = 1:1:1) to approximately 4.0 log(10) CFU mL(-1). The samples were stored at 4 degrees C for 10 days for P. fragi and P. fluorescens and 30 degrees C for 24 h for the remaining bacteria. A new multiavariate analysis technique, principal component similarity analysis, was capable of distinguishing milk samples inoculated with P. fragi, P. fluorescnes, L. lactis, E. aerogenes, and a mixed culture from uninoculated samples.