DESIGN OF FUNCTIONAL AND SPECIALIZED PRODUCTS WITH FORECASTING PROPERTIES
doi: 10.25712/ASTU.2072-8921.2021.04.010
Keywords:
blends of unrefined vegetable oilsl, complex indicators, forecasting, specialized and functional products, fatty acidsAbstract
To improve the effectiveness of product quality forecasting, we need a single systematic approach based on hierarchy and multidimensional quality, taking into account the degree of influence of each indicator on the quality as a whole. Such an approach is the qualimetric model. The purpose of the study was to use a qualimetric model for the design of functional and specialized products based on oilseeds. The objects of the study were blends of unrefined vegetable oils of safflower, mustard, ginger and milk thistle, balanced according to the optimal ratio of polyunsaturated fatty acids. To determine the actual qualimetric model, the following research methods were used in the work: to determine the indicators of nutritional value and biological effectiveness, a calculation method was used using experimental data on the fatty acid composition of blends obtained by gas chromatography, the method of organoleptic analysis (profile method). When developing the qualimetric model, reference points were guided with the selection of a nomenclature of indicators characterizing the quality of blends of unrefined oils. It is proved that the developed basic quality indicators, weighting coefficients for basic indicators and groups of indicators, can be used to predict the functional and consumer properties of vegetable oil blends. The actual indicators determined empirically confirm the effectiveness of the developed products in relation to the basic ones. The authors propose to use a qualimetric model to predict consumer properties instead of or in addition to mathematical models that cannot take into account the anisotropy of product properties.
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Copyright (c) 2021 Ekaterina Yu. Volf, Victoria N. Strizhevskaya, Victoria M. Kozyreva, Inna V. Simakova, Alexei A. Volf
This work is licensed under a Creative Commons Attribution 4.0 International License.