| Now people have given more and more attention to the safety and quality of the products with the improvement of safety awareness. There are many effecting freshness factors of the chilled pork. The various internal and external factors could change the meat quality and that is the bottleneck of the meat to extend the shelf life and ensure the safety. Mathematical statistics method could look for major spoilage indicators. It could rapid assess the shelf life and security of the chilled pork by predictive microbiology model without traditional analysis. The research object of this study is the naturally contaminated chilled pork obtained from the plant. The chilled pork with modified atmosphere packaging was examined microorganism, chemical and sensory evaluation indicators to determine the spoilage indicator was Pseudomonas spp. by principal component analysis and cluster analysis and determine the limit of Pseudomonas spp. in chilled pork. This article used predictive microbiology to optimize gas ratio and studied the growth characterization of Pseudomonas spp. at 7,15,20 and 25℃, respectively, selected the Gompertz model to fit growth data and chose the square root model to describe the relationships between the temperature and growth rate, lag phase. At last we established shelf life prediction model of the chilled pork.The results showed that:(1) By comprehensive evaluating the quality indicators of different gas system modified atmosphere packaged chilled pork, the changes of total viable counts, Pseudomonas spp., lactic acid bacteria, Enterobacteriaceae, Brochothrix thermosphacta, electrical conductivity, pH, TVBN and electronic nose were different. The difference was significant between the proportions of gas systems. Gas ratio was an important hurdle factor that could affect the quality of chilled pork.(2) Through using component plot in rotated space of principal component analysis and clustering analysis, Pseudomonas spp. was determined to be the spoilage indicator of the modified atmosphere packaged chilled pork. This method was more intuitively clear than traditional pearson correlation coefficient for multi-variables. (3) The nonlinear regression procedure of SAS 9.1 statistical soft ware was used to fit the experimental data of Pseudomonas spp. with Gompertz models at different Gas ratios. Based on the relationship between gas ratio and lag phase, modeling to optimize gas ratio, the final optimization results was 40%CO2+40%O2+20%N2. Comparing the optimal combination with the common gas ratio, the experimental result showed that the optimal combination was better to extend the shelf life.(4) Using the optimum combination of modified atmosphere packaging of chilled pork as the research object, Gompertz model was selected to fit the experimental data of Pseudomonas spp. at different gas ratios. Establishing the secondary models according to the relationship between the temperature and the lag phase, growth rate, the result showed that the role of the MAP was not very obvious in the high temperature. In this case the lag phase was very short and the growth rate was very fast. However in the low temperature conditions under modified atmosphere packaging, the preservation effect is obvious. It could extend the shelf life of the chilled pork combine the low temperature with modified atmosphere packaging. So temperature and different gases are the important hurdle factors that affect the product quality. The hurdle technology formed by low temperature combined with modified atmosphere could extend the shelf life of chilled pork.(5) The present study provides equations to predict the shelf life of chilled pork under modified atmosphere packaging provided that the initial number of Pseudomonas organisms (No) and the actual temperature are known. |
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