To fit a lognormal distribution to a complex set of microbial data, including detection data (eg
presence or absence in 25g) and enumeration data (eg 30cfu/g), we compared two models …

The accurate estimation of true prevalence and concentration of microorganisms in foods is
an important element of quantitative microbiological risk assessment (QMRA). This …

Estimating probability distributions that describe bacterial concentrations in food products is
a key element of quantitative microbial risk assessments. Standard bacteriological protocols …

Every year hundreds of thousands, if not millions, of samples are collected and analyzed to
assess microbial contamination in food and water. The concentration of pathogenic …

The estimation of the concentration of microorganisms in a sample is crucial for food
microbiology. For instance, it is essential for prevalence studies, challenge tests (growth …

The actual physical distribution of microorganisms within a batch of food influences
quantification of microorganisms in the batch, resulting from sampling and enumeration by …

The distributions of microorganisms in foods impact the likelihood that a foodstuff will cause
illness and therefore also impact the consequential public health burden. As part of food …

A novel method is proposed for fitting microbial inactivation models to data on liquid media:
the Most Probable Curve (MPC) method. It is a multilevel model that makes a separation …

Indicator organisms, such as generic Escherichia coli (GEC) and coliforms, can be used to
measure changes in microbial contamination during the production of food products. Large …

Quantitative microbiological risk assessment (QMRA) is influenced by the choice of the
probability distribution used to describe pathogen concentrations, as this may eventually …