Microbial Forecasting Software Development For Halal Beef And Mutton Products

The quality chilled beef and low-temperature meat products has become the main portion of the production of raw meatin both domestic and foreign markets for its good tasteand rieh nutrition. Although the production and the consumption are under the control of low temperature,However,due to the imperfections of the entire cold chain,as well as microbial contamination in the processing, distribution,sales process,that causing them spoilage.The experiments using chilled beef as research object, the variation of the total number of colonies,volatile basic nitrogen (TVB-N), pH,water loss rate and the main spoilage bacteria were studied when chilled beef was stored at4℃, the correlation of them were also analyzed. Modidied Gompertz model,square root model of Peudomonas and the shelf life prediction model were established according to the experimental datas of Pseudomonas growth rhythm on chilled beef at4℃,7℃,10℃,15℃and20℃. Then the models were validated.On this basis,the growth analog system of Pseudomonas (Third model) was developed,that made using computer to predict the shelf life of chilled beef into reality.Using three kinds of cooked meat of halal beef and mutton (Halogen tripe,boiled mutton,Whitewater sheep miscellaneous)as research object,the variation of the total number of colonies, moisture content,pH,thiobarbituric acid value, sensory scores and the main spoilage bacteria were studied when they were stored at4,7,10℃. Modidied Gompertz model, square root model of the total number of colonies and the shelf life prediction model were established according to the experimental datas of the growth rhythm of the total number of colonies.Then the models were validated. On this basis, the growth analog system of the total number of colonies (Third model)for three kinds of cooked meat were developed,that made using computer to predict the shelf life into reality.The results showed that:(1)When the chilled beef and three kinds of cooked meat (halogen tripe, mutton, whitewater sheep miscellaneous) were stored, physical-chemical indexes and microbial indexes would change.The number of microorganisms can reflect the freshness of meat in some way. Studies have shown that: Pseudomonas was the dominant spoilage bacteria in chilled beef and Lactic acid bacteria was the dominant spoilage bacteria in three kinds of cooked meat.(2)When chilled beef was stored, pH showed an upward trend after the first fall,TVB-N showed a gradual upward trend, but increased rapidly during the first12d,exceeding the national standards set forth in the value15mg/100g,the correlation analysis showed that:The total number of colonies and Pseudomonas were significantly correlated with TVB-N at the0.05level but had little correlation with pH; Taking changes in physical-chemical indexes and microbial indexes into consideration, combining cluster analysis, we knew the minimum allowable amount of Pseudomonas was108.42cfu/g;During storage,pH first increased slightly and then declined,TBA value and moisture content was rising,sensory score was declining in three kinds of cooked meat.(3)Using MATLAB to fit the growth status of microorganisms in a variety of meat at a constant temperature. The results showed that Medified Gompertz equation could well reflect the growth status of Pseudomonas in chilled beef and the total number of colonies in three kinds of cooked meat. The growth curve showed a typical "S" shape;Using the square root model to fit the maximum specific growth rate-temperature curve and the lag time-temperature curve,we got Secondary Model.The residual analysis showed that the square root model could be used to describe the effects of different temperatures on the growth of microorganisms.(4)Established the remaining shelf life equation of chilled beef and three kinds of cooked meat. Then the models were validated.The results showed that relative error between the predicted and measured values for shelf life of each meat were less than10%,the model was credible.As long as we know the initial number of bacteria and storage temperature,we can predict the remaining shelf life of products in time.(5)On the basis of primary and secondary model model, by VB language program,developed prediction software which could quickly and accurately predict the growth status of Pseudomonas in chilled beef and he total number of colonies in three kinds of cooked meat.