Study On Sterilization Technology Of Self-heating Food And Shelf Life Prediction Based On Changes In Storage Quality

With the acceleration of the social rhythm and the improvement of the economic level,the human diet has gradually changed from independent cooking at each meal to purchasing convenient and efficient instant foods,which has enabled the rapid development of the instant food industry.As a healthy and delicious instant food,self-heating food has been favored by consumers.However,in the current research,most of them are for the upgrading and optimizing of heating devices.There are few reports on extending and predicting the shelf life of self-heating foods,reducing consumer expectations of food nutrition and quality,and increasing the company’s production costs caused by miscalculating shelf life,which limits the further development of the self-heating food industry.In this thesis,the self-heating food is used as the research object.We determined the optimal packaging material for self-heating food by comparing the effects of different packaging on quality changes,investigated the effect of electron beam irradiation combined with low-intensity heat on the sterilization effect and quality of self-heating food.The effect of temperature on storage quality of self-heating food was explored by using accelerated shelf life.Based on the change of quality,the shelf life predicting models of self-heating food were established to predict the shelf life,using chemical kinetics model,Q₁₀ model and BP neural network model.The main research contents and results are as follows:（1）Effect of packaging materials on quality changes of self-heating foodThe effects of two kinds of packaging materials on the quality of self-heating foods were investigated through sensory score,pH value,color value,total volatile basic nitrogen（T-VBN）content,and malondialdehyde content（TBARS）.The results show that at 60℃,the shelf life of self-heating food packaged with PET/Al/PA/CPP material is 1.8 times that of PA/CPP.At the same time,PET/Al/PA/CPP material can reduce the reaction rate of food oxidation and hydrolysis,and keep the color stable.（2）Sterilization effect of electron beam irradiation combined with low-intensity heat on spores of self-heating foodThe plate counting method was used to investigate the sterilization effect of electron beam irradiation and the combination of electron beam and low-intensity heat on spores in self-heating foods.The results showed that the electron beam had a significant sterilization effect on spores,and the effect became more pronounced as the dose increased.Under the same conditions,combined with low-intensity heat can effectively increase the sterilization rate of electron beam irradiation.Through the analysis of the effects of different treatment on color difference,lipid oxidation,and sensory acceptability of self-heating food,9 k Gy electron beam irradiation combined with heating at 85℃ for 20 minutes is the best way to sterilize self-heating food.（3）Effect of temperature on storage quality of self-heating foodAccording to sensory evaluation,the shelf life of self-heating food at 40℃,50℃ and 60℃ was 140 days,112 days,and 70 days,respectively.As the temperature increased,the pH of the food changed more drastically,and the color stability became worse,the reaction rate of lipid oxidation and protein hydrolysis was accelerated,resulting in an increase in the content of malondialdehyde and total volatile base nitrogen,which affects the sensory attributes and nutritional value of food.（4）Construction of shelf life prediction model for self-heating foodCorrelation analysis found that the TBARS value and TVB-N value had a great correlation with the shelf life of self-heating food,and could be used as the landmark indicator for shelf life prediction.Based on the TBARS value,a chemical reaction kinetic model and a Q₁₀ model were established.The BP neural network model was trained,taking the temperature,TBARS value and TVB-N value as input and the remaining shelf life as output.The error analysis and predictive power comparison showed that the BP neural network model based on the prior condition is most suitable for shelf life prediction of self-heating food,which predicts that the shelf life of braised potato and beef dishes at 25℃ is 430 days.