foodsystFood systemsПищевые системы2618-97712618-7272Федеральный научный центр пищевых систем им. В.М. Горбатова РАН10.21323/2618-9771-2024-7-4-543-550foodsyst-625Research ArticleСтатьиPredicting composition of a functional food product using computer simulationПрогнозирование состава функционального пищевого продукта с использованием компьютерной симуляцииhttps://orcid.org/0000-0002-8313-4105НикитинаМ. А.NikitinaM. A.

Никитина Марина Александровна — доктор технических наук, доцент, ведущий научный сотрудник, руководитель направления Информационные технологии Центра «Экономико-аналитических исследований и информационных технологий»

109316, Москва, ул. Талалихина, 26

Тел.: +7–495–676–95–11 доб. 297

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)

m.nikitina@fncps.ruhttps://orcid.org/0000-0003-4298-0927ЧернухаИ. М.ChernukhaI. M.

Чернуха Ирина Михайловна  — доктор технических наук, профессор, академик РАН, Руководитель Отдела координации инициативных и международных проектов

109316, Москва, ул. Талалихина, 26

Тел.: +7–495–676–95–11 доб. 109

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)

imcher@inbox.ruhttps://orcid.org/0000-0001-8372-3594АртамоноваМ. П.ArtamonovaM. P.

Артамонова Марина Петровна — кандидат технических наук, профессор, кафедра конструирования функциональных продуктов питания и нутрициологии

125080, Москва, Волоколамское шоссе, 11

Tel: +7–499–750–01–11(6015)

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)

ya.artmarina@yandex.ruhttps://orcid.org/0000-0002-2193-0624КусайА. Т.QusayA. T.

Кусай Абу Траби — аспирант, Кафедра конструирования функциональных продуктов питания и  нутрициологии

125080, Москва, Волоколамское шоссе, 11; Площадь Асси, Хама, Сирия

Tel: +7–499–750–01–11(6015)

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)

usay2077@gmail.comФедеральный научный центр пищевых систем им. В. М. ГорбатоваРоссияV.M. Gorbatov Federal Research Center for Foods SystemsRussian FederationРоссийский биотехнологический университет (Росбиотех)РоссияRussian Biotechnological University (Rosbiotech)Russian FederationРоссийский биотехнологический университет (Росбиотех); Университет ХамыРоссияRussian Biotechnological University (Rosbiotech); University of HamaRussian Federation20240102202574543550Copyright © Nikitina M.A., Chernukha I.M., Artamonova M.P., Qusay A.T., 20252025Никитина М.А., Чернуха И.М., Артамонова М.П., Кусай А.Т.Nikitina M.A., Chernukha I.M., Artamonova M.P., Qusay A.T.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.fsjour.com/jour/article/view/625

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.

Одним из фронтиров науки является разработка цифрового двойника пищевого продукта для прогнозирования состава и свойств будущего продукта. Однако в настоящее время для прогнозирования состава пищевого продукта используют компьютерную симуляцию (моделированию). Цель нашего исследования сопоставить значения показателей пищевой ценности цифровой модели и реального пищевого продукта, и оценить адекватность полученных данных. Объектами исследования были эмульгированный мясорастительный продукт на основе традиционного блюда «Мухаммара» и цифровая модель (компьютерный симулятор) рецептуры эмульгированного мясорастительного продукта. На примере разработки эмульгированного мясорастительного продукта на основе традиционного блюда «Мухаммара» показаны этапы разработки цифрового двойника пищевого продукта. Показана некорректность использования цифровой модели без подкрепления ее данными (числовыми значениями), полученных с приборов, датчиков. В исследовании сравнили расчетные показатели с данными, полученными эмпирическим путем (в результате лабораторного эксперимента) в трех блоках: физико-химические показатели, витамины и минеральные вещества. Симуляцию и расчет абсолютной и относительной ошибки осуществляли в программной среде R Studio. Расхождение в данных расчетных и эмпирических, вопервых, можно объяснить средними значениями показателей, которые содержаться в базах данных пищевых продуктов. В базах данных на данный момент времени содержаться усредненные данные, не учитывающие индивидуальные характеристики сырья животного и растительного происхождения. Во-вторых, необходимо учитывать коэффициент потерь (или коэффициент сохранения) пищевых нутриентов при тепловой или термической обработке пищевого продукта. Установлено, что только разработка точного цифрового двойника с учетом всех параметров поможет отслеживать параметры качества на каждом этапе производства, что позволит оперативно реагировать на отклонения и улучшать качество конечного продукта.

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The authors declare that there are no conflicts of interest present.