Growth prediction models of Vibrio parahaemolyticus with different serotypes
Objective To study the growth heterogeneity of different serotypes of Vibrio parahaemolyticus(VP)under different culture conditions,and to establish growth prediction models for epidemic strains(O3:K6,O10:K4).Methods Seventeen VP strains of different serotypes were selected as the research objects,and different culture conditions were set,including salinity(0.5%-10.0%),pH(3.0-11.0)and temperature(16-50℃).The modified Gompertz model was used to establish the primary growth model.The optimal growth range was determined by comparing the maximum OD value(Ymax),the Lag time(λ)and maximum specific growth rate(μmax).The second-order response surface growth model was established by Design-Expert 13 software.Results There was growth heterogeneity among VP strains.The coefficient of variation for differences in growth parameters μmax and Ymax between VP strains at salinity levels of 1.0%-3.0%,pH of 7.0-9.0,and temperatures of 20-40℃was lower than that under other culture conditions.The growth ability of the epidemic strains(serotype O3:K6,O10:K4)was significantly greater than that of other serotypes when the salinity was 7.0%,the pH was 10.0,and the temperature was 16℃,with a statistically significant difference(P<0.05).The determination coefficients of the first-order growth models fitted under different salinity and temperature were greater than 0.98,and the correlation coefficients under different pH were greater than 0.9.The second-order response surface growth model was significant(P<0.05),and the determination coefficient was greater than 0.94.Conclusion There is growth heterogeneity among VP strains,but in certain extreme conditions,there are more obvious growth differences between different serotypes.The modified Gompertz model and the second-order response surface growth model can be used to analyze and predict the growth of VP under different experimental conditions,which can provide reliable and safe prediction for the growth trend of VP.
Vibrio parahaemolyticusserotypegrowth prediction model
万方数据
维普
