Study Of The Shelf Life Prediction For Chicken Products

Chicken products are more popular than beast because of higher contents of proteinand lower contents of fat. The processed meat products are greatly popular because of theire dibble convenience, high added value, emphasizing nutrition balance, and their production and consumption are growing with each passing day. Most of them are the quick-frozen processed meat products in our country, and Chuanxiang Jiliu is one of the typical products. The short shelf life which was caused by the microorganism contamination is the main bottle neck. Affecting the microbial growth of internal and external factors, temperature is one of the most important external factors. So it is necessary to understand the growth and patterns of the microorganisms and predict their growth at different temperatures by microbiological predictions.This paper mainly studied the change of qulity in fresh chicken and prepared chicken. The change of phase composition of bacteria was analyzed by modem molecular techniques. The growth of Pseudomonas spp.at 0℃、5℃、10℃、15℃、20℃and 25℃was observed. We fitted the results with the Gompertz function and Logistic function and established a model to predict the remaining shelf life.Results showed that: （1）The microbial diversity of fresh chicken and prepared chicken were different. The microbial structure of fresh chicken and the previous six days of prepared chicken was relative stable. The microbial diversity of the eighth day of prepared chicken changed differently. （2） The correlation coefficient between the growth of Pseudomonas spp.and the total number of bacter are 0.981 and 0.977 respectively. The correlation between Pseudomonas spp. and other indicator such as TVBN value、pH value is statistically significant （P<0.01）. So it is feasible to use a Pseudomonas growth model to predict the extent of spoilage of fresh chicken and prepared chicken under different storage conditions. The Ns of Pseudomonas in fresh chicken is 10^5.4cfu/g , while in prepared chicken is 10^5.9cfu/g. （3） Statsoft statistical soft ware was used to analyze Pseudomonas spp. growth at different temperatures. The Gompertz function and Logistic function were good predictors of Pseudomonas spp. growth in both fresh chicken and prepared chicken and the growth curve were typical S-type. The square root model was used to consider the maximum specifc growth rate and lag phase of Pseudomonas spp. and temperature （（μmax）1/2/（1/λ）1/2）. It showed that the square root model could describe the effects of different temperature on the microbial growth well and the Gompertz equation are better than the Logistic equation.（4） By comparing the residuals of observed values with those of the predicted values in 10℃and 15℃to verify the models, the predicted values fluctuated in a range of about 10%. The differences between predicted and observed values（Af）were less than 24% by the Gompertz equation, while 28% by the Logistic equation. （5） The equations were established to predict the shelf life of fresh chicken and prepared chicken respectively provided that the initial number of Pseudomonas organisms （No） and the actual temperature are known.