T12-03 Modeling for Predicting the Growth of Salmonella in Chicken Fillets under Different Temperatures

Wednesday, July 12, 2017: 2:00 PM
Room 16 (Tampa Convention Center)
Haiying Pang , Zhejiang University, College of Biosystems Engineering and Food Science , Hangzhou , China
Wen Wang , Institute of Quality and Standard of Agricultural Products, Zhejiang Academy of Agricultural Sciences , Hangzhou , China
Xingning Xiao , Zhejiang University, College of Biosystems Engineering and Food Science , Hangzhou , China
Jianming Zhang , South China Agricultural University , Guangzhou , China
Ming Liao , South China Agricultural University , Guangzhou , China
Yanbin Li , University of Arkansas, Department of Biological and Agricultural Engineering , Fayetteville , AR
Introduction: Salmonella has been considered as one of the major pathogens associated with poultry around the world. Various empirical models have been developed for predicting the growth of Salmonellain chickens. However, the comparison of these models under different temperatures is needed for quantitative microbial risk assessment.

Purpose:  The objective of this study was to compare the performance of empirical models for predicting the growth kinetics of Salmonella in chicken fillets under different temperatures.

Methods: Chicken fillets (size: 2cm by 1cm by 1cm; weight: 2±0.3g) were inoculated with three-strains of cocktail Salmonella (ATCC 14028, 50335, 51957) at the initial contamination level of four to five log CFU/g, and then stored at temperatures of 13, 16, 25, 33, and 37°C. Growth data were collected for fitting into four primary models; namely modified Gompertz model, Huang model, Buchanan linear model, and Baranyi model. Three secondary models (Arrhenius-type model, Ratkowsky square root model, and Huang square root model) were selected for describing the maximum growth rates derived from primary models. Statistical indices of R2 and RMSE were used for model evaluation. Independent trials were conducted, and Bias factors (Bf) and Accuracy factors (Af) were calculated for model validation.

Results:   The modified Gompertz model described growth data the best, followed by Huang model. The average maximum growth rates of Salmonella in chicken fillets were 0.076, 0.116, 0.582, 0.687, 0.785/h at 13, 16, 25, 33 and 37°C, respectively. R2 for Arrhenius-type model describing the maximum growth rate obtained from the modified Gompertz model was 0.99, which was the best among selected secondary models (RMSE=0.047, Bf=1.01, Af=1.04).

Significance:  The selected model was able to predict the growth of Salmonella in chicken fillets under different temperatures in processing and storage conditions, which may be used in quantitative microbial risk assessment.