Statistical methods in food recipes design

Abstract

A methodology based on statistical methods for optimizing multicomponent compositions is applied for meat product recipes design. Using raw materials of animal and plant origin, virtual arrays of input variables (raw materials) are developed and chemical (protein, fat), mineral and vitamin compositions are calculated for each data array. The calculation of balance and rationality of the amino acid composition in the feedstock is established by clustering method. As a result, the recipe of cooked sausage based on raw materials of plant and animal origin is developed. The optimal recipe for the developed meat product has a high utilitarian coefficient (0.856), the amino acid rate of the limiting amino acid is 0.87. The manufactured prototype is distinguished by high organoleptic characteristics (average organoleptic indicator – 4.8 points). The finished product yield to the unsalted raw materials mass is equal to 120.3%.