Predicting composition of a functional food product using computer simulation
https://doi.org/10.21323/2618-9771-2024-7-4-543-550
Abstract
One of the frontiers of science is the development of a digital twin for a food product to predict composition and properties of a future product. Today, however, computer simulation (modeling) is used for predicting the composition of a food product. The aim of our research is to compare the levels of the nutritional value parameters from a digital model and a real food product and to assess adequacy of the obtained data. The objects of the research were the emulsified meat-and-plant product based on the traditional meal “Mukhamar” and a digital model (computer simulator) of the recipe of the emulsified meat-andplant product. By the example of the development of the emulsified meat-and-plant product based on the traditional meal “Mukhamar”, stages of the development of a digital twin of a food product are shown. It was demonstrated that it is incorrect to use a digital model without supporting it with data (numerical values) obtained from apparatus, sensors. The calculated parameters were compared with the data obtained empirically (as a result of the laboratory experiment) in three blocks: physicochemical indicators, vitamins and minerals. Simulation and calculation of the absolute and relative errors were performed in the program environment R Studio. Differences between the calculated and empirical data can be explained, firstly, by the average values of parameters in food product databases. As for now, databases contain averaged data, which do not take into account individual characteristics of animal and plant raw materials. Secondly, it is necessary to take into consideration the coefficient of losses (or coefficient of preservation) of food nutrients during thermal treatment of food. It has been established that only the development of the precise digital twin with regard to all parameters will help to trace quality parameters at each stage of the production, which will allow reacting timely to deviations and improving quality of the final product.
About the Authors
M. A. NikitinaRussian Federation
Marina A. Nikitina, Doctor of Technical Sciences, Docent, Leading Scientific Worker, Head of the Direction of Information Technologies of the Center of Economic and Analytical Research and Information Technologies
26, Talalikhin str., 109316, Moscow
Tel: +7–495–676–95–11 (297)
I. M. Chernukha
Russian Federation
Irina M. Chernukha, Doctor of Technical Sciences, Professor, Academician of the Russian Academy of Sciences, Head of the Department for Coordination of Initiative and International Projects
26, Talalikhin str, 109316, Moscow
Tel: +7–495–676–95–11 (109)
M. P. Artamonova
Russian Federation
Marina P. Artamonova, Candidate of Technical Sciences, Professor, Department of Design of Functional Food Products and Nutrition
11, Volokolamsk highway, 125080, Moscow
Tel: +7–499–750–01–11(6015)
A. T. Qusay
Russian Federation
Abu T. Qusay, Postgraduate Student, Department of Design of Functional Food Products and Nutrition
11, Volokolamsk highway, 125080, Moscow; Assi Square, Hama, Syria
Tel: +7–499–750–01–11(6015)
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Review
For citations:
Nikitina M.A., Chernukha I.M., Artamonova M.P., Qusay A.T. Predicting composition of a functional food product using computer simulation. Food systems. 2024;7(4):543-550. (In Russ.) https://doi.org/10.21323/2618-9771-2024-7-4-543-550