A statistical method to determine whether micro-organisms are randomly distributed in a food matrix, applied to coliforms and Escherichia coli O157 in minced beef

Abstract

A method is presented to determine whether micro-organisms are distributed randomly or not in a batch of food. This is important information for quantitative microbiological risk assessment (QMRA). If micro-organisms are distributed randomly, this variation in numbers of micro-organisms between samples from a batch of food theoretically agrees with a Poisson distribution, with a fixed value for parameter λ. Other sources for variation (such as clustering of micro-organisms or experimental error) can lead to an increase of variation of the data, which can be described by a Poisson distribution with a Gamma distributed λ (Poisson(Gamma)). The Poisson and Poisson(Gamma) distributions were used to describe the effect of grinding on the variation of endogenous flora of coliforms and artificial, clustered contamination of Escherichia coli O157 in minced beef. In addition, the Poisson and Poisson(Gamma) distributions were compared to the Lognormal distribution. Coliforms were enumerated in 25 samples in the starting material and in the mince produced after grinding once, twice and three times. E. coli O157 was spiked into the starting material in 1 or 10 clusters, and enumerated in 25 samples after grinding once and twice. Coliforms were not randomly distributed in the starting material. Grinding resulted in random and non-random distributed coliforms and E. coli O157, respectively. Generally, the Lognormal and Poisson(Gamma) distribution fitted equally well to the data, but only the Poisson(Gamma) distribution is useful to determine whether micro-organisms are randomly distributed or not.