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摘要： 中国传统熟肉肉制品口独特，深受消费者青睐。但传统加工工艺和贮藏手段容易滋生腐败菌，衍生出各种食品安全问题。预测食品微生物学是以数学、微生物学、统计学和计算机科学为基础建立起来的新兴学科。本课题从上海徐汇、闵行和奉贤区的农贸市场、夜市、超市和连锁熟食店采集烧鸭、酱鸭、酱牛肉、熏猪肉、烧鸡等样品27份，对其腐败微生物进行分离，采用形态观察，革兰氏染色和生理生化试验对分离菌株进行初步分类鉴定，分析了上海常见熟肉制品中优势腐败菌的分布规律，测定了典型传统肉制品酱牛肉在冷藏条件下优势微生物的生长动态和品质变化趋势，最后通过Modified Gompertz方程构建了冷藏条件下菌落总数与贮藏时间的一级模型。研究结果如下：（1）市场上的熟肉制品中的优势腐败菌为肠杆菌属、芽孢杆菌属、乳酸菌、葡萄球菌属、微球菌属，其他菌株较少；（2）以酱卤牛肉制品作为典型传统肉制品研究对象，测定其初始理化参数平均值分别为：pH 值为 6.32±0.10，TVB-N（挥发性盐基氮）值为 12.30±1.00mg/100g，菌落总数为 103-106cfu/g；（3）酱卤牛肉制品在贮藏期间的菌落总数和优势腐败菌大肠菌群数量不断增长，pH值下降，肉色a值、DE值不断降低，挥发性盐基氮呈上升趋势，其中菌落总数与TVB-N的关联最密切；（4）根据冷藏温度4℃下的菌落总数曲线构建Modified Gompertz方程为N(t)=2.062+(6.889-2.062)×{Exp[-Exp[(0.021×2.718/(6.889-2.062))×(75-t)+1]]}39013
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毕业论文关键词： 腐败菌 卤肉制品 挥发性盐基氮 菌落总数 一级模型
Isolation and Identification of Predominant Spoilage Bacteria and the Storage Characteristics of Cooked Meat in Shanghai
Abstract: Chinese cooked meat is populuar in China for its unique taste. However, traditional cooking and storage methods were caused some food safety problems. Predictive food microbiology is a new subject based on mathematics, microbiology, statistics and computer science. In this paper, we isolated a total of 27 traditional meat product samples from farmers' markets, night markets, supermarkets and chain delicatessens in Xuhui, Minhang and Fengxian in Shanghai, and then identified bacteria strains according to physiological and biochemical methods。Inadditonal, we aimed to evaluate the total population microbiology growth curve and quality of spiced beef during cold storage and build the Modified Gompertz equation. Results were as following:
(1) The predominant spoilage bacteria were Enterobacter sp., Bacillus sp., Lactobacillus sp., Staphylococcus sp. and Micrococcus sp., (2) the results of spiced beef characteristics were showed that the initial pH value, TVB-N and total number of bacteria were 6.32 ± 0.10, 12.30 ± 1.00mg / 100g and 103-106cfu / g, respectively. (3) During cold storage, the population of the total plate count (TPC) and TVB-N (total volatile basic nitrogen) level were increased. On the contrary，the pH, a and DE value were reduced. Especially, the pearson indexes of TPC and TVB-N was maximum. (4) The predictive model of shelf life was constructed at 4℃ as follows: N(t)=2.062+(6.889-2.062)×{Exp[-Exp[(0.021×2.718/(6.889-2.062))×(75-t)+1]]}
Key Words : Braised meat Spoilage bacteria Total volatile basic Nitrogen Aerobic plate count Primary modeling
目录
1前言 1
1.1熟肉制品概述 1
1.1.1熟肉制品的简介 1
1.1.2熟肉制品的类型 1
1.1.3熟肉制品的卫生标准 1
1.1.4熟肉制品的市场 1
1.2腐败菌概述 2