The Application Of Microbial Time-temperature Integrator On Yogurt Quality Management

Yogurt,as a perishable food,is widely welcomed by consumers due to its unique flavor and health benefits.Yogurt is a fermented milk product with homofermentative lactic acid bacteria Streptococcus salivarius ssp.thermophilus and Lactobacillus delbrueckii ssp.bulgaricus,and its quality depends on the cold chain distribution and storage mostly.The ideal distribution temperature for yogurt is 4-6?.While in practice,the cold chain might be broken,or the actrol temperature could not meet the requirement due to several reasons,resulting in fluctuations in quality of yogurt.Therefore,real-time monitoring of the actual temperature experienced by yogurt during the distribution process becomes essential.In this paper,the microbial TTI(Time-Temperature Integrator)was made according to the color change of pH indicator caused by the lactic acid produced by the lactic acid bacteria.And the purpose of accepting microbial TTI is to indicate the quality of the yogurt.The contents of this research are as follows:(1)The yogurt was made by adding yogurt starter into milk in the laboratory.The quality factors of yogurt as lactic acid bacteria count,acidity and pH value was studied in the kinetics,and the regressions were conducted in the different temperature over time.As a result,the acidity has the best linear performance,and related to the mouthfeel of consumers directly.Thus,the acidity was selected as the best quality factor of yogurt,and its temperature dependence was obtained as 67.5 kJ/mol.Combined the logistic function and Arrhenius equation,the prediction model of yogurt was obtained.(2)The SPG membrane technique was accepted to make the microbial microcapsules.The microorganisum used is Weissella cibaria CIFP 009,and the wall material is sodium alginate.Because the uniform particle size is conducive to enhancing the stability of the activation energy and reaction time of microbial TTI,the SPG membrane technique is used to narrow the particle size distribution of the microcapsules.The CaCl2 was used for the stabilization of the microcapsules.After the comparison and improvement,the mix-and-shake method was chosen as the best method to stabilize.The method has the characteristics of simple making process and high recovery rate.(3)The state and recipe of the microbial TTI was determined.Compared to the liquid type,the more practical and stable solid TTI was selected for the follow-up studies.It consisted of the substate and the microcapsules.The substate included MRS agar,4%(w/v)glucose,15%(w/v)glycerol and 10%(v/v)pH indicator.Among,the pH indicator was made by by adding bromocresol purple(0.04%,w/v)in ethyl alcohol(95%,v/v),bromocresol green(0.05%,w/v)in ethyl alcohol(95%,v/v),and methyl orange(0.1%,w/v)in ethyl alcohol(95%,v/v)in a ratio of 1:1:1.It was then mixed with the optimum ratio of microcapsules and substrate(w:v,1:2).The TTI mixture was pipetted into the sterile container with 500 ul for each one.Finally the TTI system was sealed using LDPE film after the solidification.The kinetics of the microbial TTI was also studied,and the CIE b* value was selected as the color response for the best linear performance than other CIE L*a*b* parameters.The regressions were conducted under different temperature over time,and the activation energy of the micarobial TTI was obtained as 50.2 kJ/mol.The color change history of the TTI was also obtained.(4)The yogurt distribution system was simulated in the laboratory.There were three time-temperature histories that were accepted into the yogurt quality prediction computation,set temperature,data logger and TTI.For the comparison,the mean of acidity predicted results of set point was 91.8°T,data logger was 93.3°T and TTI was 92.4°T.While the mean of measured values was 92.1°T.The mean value could reflect the overall prediction accuracy,and in order to suggest the accuracy of individual prediction,the sum of squares for error(SSE)between predicted and measured values was accepted.The SSE of predicted results of set point was 81.5,data logger was 118.9 and TTI was 5.76.Both statistics showed the TTI had the best performace.The Monte-Carlo simulation was accepted for prediction under the mass production and transportation of yogurt subsequently.The certain value was replaced by the probability distribution to participate the computation.As a result,the TTI also had the most realistic prediction.The application method of the TTI was discussed combined with the SMAS system,and the good application on yogurt quality management was verified.The developed microbial TTI in this research had the good application property due to the improvement of the SPG membrane method.The yogurt distribution system was simulated in the laboratory,and the accuracy of TTI used in the yogurt qulity monitoring and management was verified.The application of the Monte-Carlo simulation method in the monitoring and management of yogurt quality was also explored,which provided ideas for the nass commercial application of TTI.