Research on Food Processing Optimization and Nutrition Retention Based on Multivariate Statistical Analysis

Abstract

This study explores the optimization method of food processing with potato crisps as an example. The experimental data were analyzed by principal component analysis using one-way and response surface tests with crushing force, oil content, L* value, sensory score, composite score and volatile components detected by electronic nose as indexes. The regression effect of the quadratic polynomial regression model established with the normalized composite score obtained from the principal component analysis as the response value was highly significant (p<0.01, R²=0.9591). Determine the optimal pretreatment process parameters of potato for the bleaching temperature of 92 ℃, bleaching time of 4min, slice thickness of 4mm and freezing time of 3h, in this condition to get the normalized composite score of 0.9633, close to the predicted value (0.9696), indicating that the combination of the principal component analysis and the response surface analysis method of the potato crisps processing process optimization of the comprehensive evaluation method is accurate and feasible. In order to optimize the food processing process, this paper proposes food nutrition retention measures from two aspects of cooking methods and processes, ingredient selection and procurement, respectively.