Classification of some lactic acid bacteria from vacuum-packed meats by direct probe mass spectrometry

Observations on the succession dynamics of lactic acid bacteria populations in chill-stored vacuum-packaged beef

Drip samples were collected at 4-week intervals from 10 vacuum-packaged beef striploins stored for 16 weeks at -1.5 degrees C and assayed for populations of lactic-acid bacteria (LAB), pH and spoilage-causing fermentation products. A total of 15 LAB species were identified using pulsed-field gel electrophoresis and biochemical analysis. A pattern of succession was observed during storage between strains of Carnobacterium, Lactobacillus, Leuconostoc and Pediococcus. Acetic acid production was associated with increasing LAB populations generally and butyric acid production was associated with the development of a particular strain of Leuconostoc. Changes in pH is postulated as a driver of succession.

Comparison of pattern recognition techniques for the identification of lactic acid bacteria

AIMS

The goal of this study was to evaluate three pattern recognition methods for use in the identification of lactic acid bacteria.

METHODS AND RESULTS

Lactic acid bacteria (21 unknown isolates and 30 well-characterized strains), including the Lactobacillus, Lactococcus, Streptococcus, Pediococcus and Oenococcus genera, were tested for 49 phenotypic responses (acid production on carbon sources). The results were scored in several ways. Three procedures, k-nearest neighbour analysis (KNN), k-means clustering and fuzzy c-means clustering (FCM), were applied to the data.

CONCLUSION

k-Nearest neighbour analysis performed better with five-point-scaled than with binary data, indicating that intermediate values are helpful to classification. k-Means clustering performed slightly better than KNN and was best with fuzzified data. The best overall results were obtained with FCM. Genus level classification was best with FCM using an exponent of 1.25.

SIGNIFICANCE AND IMPACT OF THE STUDY

The three pattern recognition methods offer some advantages over other approaches to organism classification.