Establishment Of Quality Evaluation Model Of Fresh-cut Lettuce And Application

Fresh-cut lettuce is a ready-to-eat processed product produced by sorting,cutting,cleaning,packaging and storage of fresh lettuce.It is mainly used in the catering and catering industry and has a huge market size.However,fresh-cut lettuce lacks uniform quality standards.Product production mainly relies on manual subjective evaluation,and the quality fluctuates greatly,making it difficult to achieve large-scale production and hindering the development of the industry.In order to solve this problem,this study established a quality evaluation model of fresh-cut lettuce to lay the foundation for its quality standard evaluation.To study and evaluate the quality characteristics of fresh-cut lettuce in terms of nutrition,physicochemical and flavor,and calculate the core quality indicators of fresh-cut lettuce through stepwise multiple linear regression,principal component analysis and analytic hierarchy process,and establish a fresh-cut lettuce quality evaluation model.The correlation coefficient and standard error of the models were compared,and the best fresh-cut lettuce quality evaluation model was selected.The model was further applied to the optimization and verification of process parameters of heat shock,pulsed light,ethanol immersion,modified atmosphere packaging and combined processing technologies.The main results are as follows.(1)The quality evaluation model of fresh-cut lettuce was established.A total of 216 samples were collected in this study,including 141 modeling sets,47 validation sets,and 28 application sets,Stepwise multiple linear regression,principal component analysis and analytic hierarchy process were used to classify and reduce the dimensions of fresh-cut lettuce quality-related indicators,established a fresh-cut lettuce quality evaluation model,and compared the correlation coefficient,determination coefficient and standard error of the model.The results show that:in the above three models,the stepwise multivariate linear model expression is SQ(comprehensive score)=110.86-41.14×browning degree-2.35×a*value-5.21×phenylalanine ammonia lyase activity(U/g)+5.43×chlorophyll content(mg/100g)-0.90×moisture content(%)-3.19×W1W+1.30×W1S.The correlation coefficients of the prediction set and the measured set are 0.814 and 0.707,the standard errors are 3.496 and 4.06,the determination coefficient and accuracy of the model are 0.662 and 86.01%,respectively,and the prediction effect is the best.(2)Optimization and verification of process and technical parameters for the quality of fresh-cut lettuce treated with heat shock.Using a stepwise multiple linear regression model to predict that the best condition for heat shock treatment is 50℃heat shock treatment.Under the treatment conditions,the phenylalanine ammonia lyase activity,peroxidase activity and browning degree were inhibited by 8.72%,33.81%and 42.27%respectively compared with the ck group,and the soluble solid content increased from 1.9%to 2.1%%,the chlorophyll content decreased slowly,which was 1.6 times that of the ck group,and the highest sensory evaluation score was 15.5,which was 23.33%higher than that of the ck group.Therefore,the prediction results of the stepwise multiple linear regression model are true and reliable.(3)Optimization and verification and verification of process and technical parameters for the quality of fresh-cut lettuce treated with pulsed light.The stepwise multiple linear regression model predicted that the optimal condition for pulsed light treatment was 6 J/cm2.Compared with the ck group,the polyphenol oxidase activity and peroxidase activity of the samples in the optimal treatment condition group decreased by 48.04%and 54.52%,respectively,and the soluble solid content and total phenolic content increased by 22.38%and 37.5%,respectively.The content is kept at 90%,which significantly inhibits enzyme activity and maintains its nutrients.Therefore,the prediction results of the stepwise multiple linear regression model are true and reliable.(4)Optimization and verification of process and technical parameters for the quality of fresh-cut lettuce treated with ethanol soaking.The stepwise multiple linear regression model predicted the optimal condition for ethanol soaking to be 20%.Compared with the ck group,the treatment conditions reduced the browning degree by 43.08%,the peroxidase activity and the phenylalanine ammonia lyase activity by 50.01%and 20.14%,and the soluble solid content was the highest at 3.33%.It has a positive effect on maintaining the nutrients and maintaining the green color of fresh-cut lettuce.Therefore,the prediction results of the stepwise multiple linear regression model are true and reliable.(5)Optimization and verification of process and technical parameters for the quality of fresh-cut lettuce treated with modified atmosphere packaging.Stepwise Multiple Linear Regression Model Predicting Optimal Conditions of Modified Atmosphere Packaging 3%O2+30%CO2+67%N2.The fresh-cut lettuce under this treatment has a slow metabolism,the peroxidase activity and browning degree are the lowest at 11.92 U/g and 0.208,and the phenylalanine ammonia lyase activity,polyphenol oxidase activity and total phenol content are lower than those in the ck group 15.62%,26.42%and 24.05%,maintain the chlorophyll content and soluble solid content at 1.45 mg/100g and 2.3%,the flavor is close to the fresh cut lettuce,and also reduce the loss of nutrients.Therefore,the prediction results of the stepwise multiple linear regression model are true and reliable.(6)Optimization and verification of process and technical parameters for the quality of fresh-cut lettuce treated with combined treatment.The stepwise multiple linear regression model predicts the optimal conditions for combined treatment of 50℃ heat shock combined with modified atmosphere packaging(3%O2+30%CO2+67%N2),that is,fresh-cut lettuce is heat-shocked in 50℃ water for 1 min,then placed in cold water.Wash in medium for 1 min,take out centrifugal dehydration,and carry out modified atmosphere packaging of the centrifuged fresh-cut lettuce according to 3%O2+30%CO2+67%N2.The treatment conditions inhibited the activity of phenylalanine ammonia lyase and peroxidase by 21.05%and 69.43%,respectively,the degree of browning was reduced by 8.02%,the moisture content was maintained at 90%,and the highest sensory evaluation score was 15.38%higher than that of the ck group.Therefore,the prediction results of the stepwise multiple linear regression model are true and reliable.