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The fate of Salmonella enteritidis PT4 in home‐made mayonnaise prepared with citric acid solution (citric acid concentration of Ð4·98% (w/v)) was investigated. It was found that pH of mayonnaise is closely related to the ratio of egg yolk to citric acid, and the inactivation rate of the micro‐organisms increases as the ratio decreases and/or incubation temperature increases. To achieve Salm. enteritidis PT4‐free home‐made mayonnaise prepared with pure lemon juice (citric acid concentration Ð5% (w/v)), it is recommended that the pH should be 3·30 or below, or, in practice, at least 20 ml pure lemon juice per fresh egg yolk should be used. For the use of 20–35 ml pure lemon juice per egg yolk, the product should be held at 22 °C or over for at least 72 h and for the use of over 35 ml pure lemon juice per egg yolk, for at least 48 h before consumption or refrigeration.

Purpose -Traditional microbiological methods to monitor the growth or survival of microbes are very labour-intensive and rather expensive and the knowledge acquired is not cumulative. Predictive microbiology as an alternative approach has been developed utilizing mathematical models to predict the microbial inactivation, survival or growth during food processing. The purpose of this paper is to review the evolutions and limitations of primary mathematical models in predictive microbiology. Design/methodology/approach -Primary models deal with the variation of microbial populations against time under particular environmental and cultural conditions. According to the behaviour of micro organisms during food processing and storage, primary models can be divided into inactivation/survival models and growth models. Literature is reviewed to assess the performance of these mathematical models. Findings -In order to predict microbial survival or growth curves, some empirical mathematical models have been used. Most of them have no or little microbiological or physiological basis, which make the interpretation of some model parameters difficult and their performances do not match observed microbiological outcomes. To produce a more accurate mathematical model, more mechanisms are necessary to interpret model parameters with a biological basis. Originality/value -The paper reviews the evolution and limitations of primary mathematical models, which may help future model development.