Modeling the Reduction of <i>Salmonella</i> spp. on Chicken Breasts and Wingettes during Scalding for QMRA of the Poultry Supply Chain in China

The objective of this study was to develop predictive models for describing the inoculated <i>Salmonella</i> reductions on chicken during the scalding process in China. <i>Salmonella</i> reductions on chicken breasts at a 100 s treatment were 1.12 &#177; 0.07, 1.38 &#...

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Bibliographic Details
Main Authors: Xingning Xiao, Wen Wang, Xibin Zhang, Jianmin Zhang, Ming Liao, Hua Yang, Qiaoyan Zhang, Chase Rainwater, Yanbin Li
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Microorganisms
Subjects:
Online Access:https://www.mdpi.com/2076-2607/7/6/165
Description
Summary:The objective of this study was to develop predictive models for describing the inoculated <i>Salmonella</i> reductions on chicken during the scalding process in China. <i>Salmonella</i> reductions on chicken breasts at a 100 s treatment were 1.12 &#177; 0.07, 1.38 &#177; 0.01, and 2.17 &#177; 0.11 log CFU/g at scalding temperatures of 50, 60 and 70 &#176;C, respectively. For chicken wingettes, 0.87 &#177; 0.02, 0.99 &#177; 0.14 and 1.11 &#177; 0.17 log CFU/g reductions were obtained at 50, 60 and 70 &#176;C after the 100 s treatment, respectively. Greater bacterial reductions were observed on chicken breasts than on chicken wingettes (<i>p</i> &lt; 0.05). A logistic (&#8722;1.12, 0.06) distribution could describe the bacterial reductions on chicken breasts at 50&#8722;60 &#176;C. Weibull, exponential and log-linear models were compared for describing the bacterial reduction on chicken breasts at 70 &#176;C and the Weibull model showed the best fit as indicated by the pseudo-<i>R</i><sup>2</sup>, root mean square error (RMSE) and standard error of prediction (SEP) values. For chicken wingettes, a logistic (&#8722;0.95, 0.07) distribution could be used to describe the bacterial reduction at 50&#8722;70 &#176;C. The developed predictive models could provide parts of the input data for microbial risk assessment of the poultry supply chain in China.
ISSN:2076-2607