The Establishment Of Tilapia Microbial Growth Forecast Model

Aquatic products become the main source of high quality animal protein intakeof people. They have many good characteristics, such as high protein, low fat, goodnutritional balance et al. Aquatic products have perishable characteristics and the mainfactor leading to the corruption is the microorganisms. The cold chain logistics is animportant way to ensure the quality of the aquatic products during the transportation.However, only part of the microorganisms are involved in the corruption process ofthe aquatic products, which is called the specific spoilage organisms. Predictivemicrobiology contains the relationship between microorganisms and food spoilage.The establishment of microbial predictive model can be used to predict the quality,safety and microbiological changes of the food in the storage process. In this research,chilled tilapia is chosen as object. The research determined the specific spoilageorganisms of the tilapia in refrigerated conditions by the separation and identificationof the main spoilage bacteria in the end of the aquatic products shelf period. Topredict the microbiological changes and the remaining shelf life of the tilapia inrefrigerated conditions, the microorganisms prediction model of the specific spoilagewere built. Research achievements are as follows:1.The specific spoilage organisms in tilapia during storage at0°C、4°C、10°Cwere analyzed, based on the colony morphology, selective medium and the16SrRNAidentification method. The result demonstrated that Pseudomonas spp. was the specialspoilage organisms of tilapia stored at0°C、4°C、10°C, which accounted for about87.6%、84.1%、88.3%of all bacteria at the end of shelf stage at0°C、4°C、10°C.2.The relationship between the OD value and the number of the Pseudomonaswas tested, and the OD changing of the Pseudomonas in the liquid medium at0°C、4°C、10°C、15°C was determined. The growth curve of the Pseudomonas in liquidmedium was established using the relationship. The primary and the second-dary growth model of Pseudomonas in the liquid medium was developed using the Curve Expert1.4software, and the growth model was verifiedby measuring value of8°C storage conditions. The error is relatively low, whichproofs that the mathematical model can well predict the dynamic growth o-f Pseudomonas in liquid medium. The growth curve of Pseudomonas in the matrix oftilapia meat was determined and the primary, secondary growth prediction model ofPseudomonas in tilapia meat matrix was established. Basic errors between predictedvalue and real value was lower than10%at8oC respectively, which suggestedmicrobial growth models built in our research were valuable for good predictor of thedynamic, growth of Pseudomonas in tilapia meat matrix. The results show thatthe modified Gompertz function equation described the growth dynamics of Pseudo-monas accurately. The Belehradek equation of the kinetic parameters of Pseudomonasshowed a good linear relationship. Experimental value of the validation tests verifiesthat the compliance of the dynamic growth model of Pseudomonas was good.3.The initial bacterial counts, the smallest amount of corruption, the largestbacterial counts, the maximum specific growth rate, and the lag phase at the end of theshelf life was obtained according to the sensory evaluation, TVBN value, the totalnumber of bacteria, the primary and secondary growth prediction model of tilapiain0°C、5°C、10°C、15°C storage conditions, and then the shelf life prediction modelwas established. Basic errors between predicted shelf life and real shelf life were lowat4°C、8°C respectively, which suggested microbial growth models built in ourresearch were valuable for rapid and realistic prediction of the microbial quality andremaining shelf life of cultured tilapia stored aerobically from0°C to15°C. At last,the research investigated the growth prediction model of Pseudomonas in tilapia meatmatrix after adding chitosan and potassium sorbate. The results showed that themodified Gompertz equation regression can always be used to establish the growthforecast model of Pseudomonas in tilapia meat matrix after adding chitosan andpotassium sorbate.