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United States Department of Agriculture

Agricultural Research Service

Research Project: MICROBIAL MODELING AND BIOINFORMATICS FOR FOOD SAFETY AND SECURITY

Location: Residue Chemistry and Predictive Microbiology

Title: Development and Validation of a Predictive model for Listeria monocytogenes Scott A as a function of Temperature, pH and Lactate and Diacetate Mixture

Authors
item Abou-Zeid, K. - UNIV. OF MARYLAND
item Yoon,, K. - UNIV. OF MARYLAND
item OSCAR, THOMAS
item Whiting, R. - FDA

Submitted to: Journal of Microbiology and Biotechnology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 8, 2009
Publication Date: March 1, 2009
Citation: Abou-Zeid, K.A., Yoon,, K.S., Oscar, T.P., Whiting, R.C. 2009. Development and Validation of a Predictive model for Listeria monocytogenes Scott A as a function of Temperature, pH and Lactate and Diacetate Mixture. Journal of Microbiology and Biotechnology. 19(7):718-726.

Interpretive Summary: Lactate and acetate salts have antimicrobial activity in laboratory broth and food products (e.g., meat juices or slurries). They are commercially available in liquid (60% wt/wt) form and are widely used in processed meat formulations. The recent interest in use of these salts is attributed to their potential to inhibit both spoilage and pathogenic bacteria, especially the foodborne pathogen Listeria monocytogenes. Predictive growth modeling of Listeria monocytogenes has received a lot of attention because of listeriosis outbreaks, predominantly associated with ready-to-eat (RTE) food. A mathematical model was developed and validated in the present study that predicts the behavior of Listeria monocytogenes as a function of temperature, pH and lactate and acetate salt concentrations. This model can be utilized by the food industry and risk assessors to control the safety and quality of foods containing lactate and acetate salts and to quantify the effects of changes in lactate and acetate salt levels in processed meat formulations on the behavior of the pathogen and thus, save money associated with conducting challenge studies to verify the effects of new product formulations on food safety.

Technical Abstract: Kinetic data for development of models that predict growth of pathogens in broth are widely used by food industries and risk assessors to evaluate food safety. However, establishment of criteria for acceptable prediction values are needed to determine whether a model provides valid predictions of pathogen growth. In this study, quadratic and cubic polynomial models were developed and validated for effects of temperature (4-37C), pH (5.5-7.0), and lactate/diacetate mixture concentration (0-3.0%) on lag time (LT) and specific growth rate (SGR) of L. monocytogenes in broth. Models were evaluated for model performance using the prediction bias (Bf) and accuracy factors (Af), as well as the acceptable prediction zone method in which models with 70% prediction or relative errors (%RE) in an acceptable prediction zone from -30 to 15% for SGR, and -60 to 30% for LT were classified as acceptable. One-hundred twenty growth curves were fitted to the Baranyi primary model that directly estimated LT and SGR. The effects of the variables on L. monocytogenes growth kinetics were modeled by response surface analysis using quadratic and cubic polynomial models of the natural logarithm transformation of both LT and SGR. All models provided acceptable predictions of pathogen growth. Comparison of predicted versus observed values of SGR indicated that the cubic model was better than the quadratic model, particularly at 4 and 10C. The Bf and Af for SGR were 1.00 and 1.10 for the cubic model and 0.97 and 1.19 for the quadratic model, respectively. For cubic and quadratic models, the %RE for the dependent SGR data were 92.9 and 74.7, respectively. For the independent SGR data, the %RE were 92.6 for the cubic model and 81.2 for the quadratic model. Although cubic and quadratic models were developed for LT, the cubic model did not predict LT better than the quadratic model with a similar %RE of 94 and 96 for the dependent and independent data, respectively. The Bf of 0.96 and Af of 1.07 for independent data were obtained for both quadratic and cubic models, indicating acceptable predictions for LT. Overall, this study showed that the secondary, quadratic and cubic polynomial models for LT and SGR provided acceptable predictions of L. monocytogenes growth in broth as a function of temperature, pH, and lactate/diacetate concentration.

Last Modified: 9/29/2014
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