Predictive Models for Growth of L euconostoc citreum and Its Dynamics in Pickled Vegetables with Low Salinity

The strain of L euconostoc citreum   L ‐33 ( L . citreum   L ‐33) is a critical microorganism in the processing of pickled vegetables with low salinity. In this study, effects of temperature, initial pH and sodium chloride concentration on cell growth of L . citreum   L ‐33 and its growth prediction models were achieved in order to predict the growth situation of L . citreum   L ‐33 under definite conditions. By use of Man‐Rogosa‐Sharpe broth medium at different initial pH and sodium chloride concentration, the strain of L . citreum   L ‐33 was incubated at different temperature. Furthermore, first‐order and secondary growth prediction models of L . citreum were established, respectively, according to the fitting curve and data process by Origin software. The results demonstrated that in the experimental conditions, the growth prediction of L . citreum   L ‐33 can be described by the G ompertz equation with four parameters. High fitting accuracy values of most of the first‐order growth models were over 0.99 according to the A djusted R ‐squared. Relation between the maximum specific growth rate obtained by the G ompertz equation and temperature as well as initial pH can be described by the R atkowsky equation. However, a relation between the maximum specific growth rate and sodium chloride concentration could be described by polynomial equations. The secondary model obtained was validated by the medium data. The bias and accuracy factors are between 0.9–1.0 and 1.0–1.1, respectively, within an acceptable range. Temperature, initial pH and sodium chloride concentration are important factors influencing the cell growth of L . citreum   L ‐33. The growth prediction models for the crucial microorganism L . citreum   L ‐33 in low‐salinity pickled vegetable processing could be conducted under definite conditions. Practical Applications The microorganisms play important role in the processing and preservation of pickled vegetables, especially in the conditions of low concentration of salt. A critical microorganism of L euconostoc citreum   L ‐33 ( L . citreum   L ‐33) in pickled vegetable processing involved, its growth prediction models under different environmental conditions were established. The established models can provide a more accurate estimation for growth of L . citreum and theoretical support for production processing optimization of pickled vegetables, as well as valuable data for developing mathematic models of food microbiology. These findings could be applied in pickled vegetable processing practice by means of growth prediction of crucial microorganisms impacting on quality and safety of the product.