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Анотація
У статті обґрунтовано та апробовано використання штучного інтелекту при встановленні оптимальних параметрів біокаталітичної технології виробництва структурованих ліпідів шляхом ферментативного ацидолізу соняшникової олії каприловою кислотою у безперервному реакторі з нерухомим шаром біокаталізатора, в якості якого було обрано ферментний препарат Lipozyme RM IM («Novozymes», Данія). Цей препарат є sn-1,3-специфічною мікробною ліпазою Rhizomucor miehei, іммобілізованою на макропористій аніонообмінній смолі. Критерієм оптимізації слугувало максимальне включення ацилів каприлової кислоти у sn-1,3-положення триацилгліцеринів. Як керовані фактори було обрано: мольне співвідношення кислоти до олії (від 3:1 до 8:1), температура (30–75 °C), та гідродинамічний час перебування (15–60 хв.). Методологічну основу дослідження становило поєднання моделей штучного інтелекту та еволюційного методу оптимізації, а саме алгоритму рою частинок. Експериментальні дані сформовано за ортогонально-максимінним планом латинського гіперкуба та використано для порівняння дев’яти регресійних моделей із застосуванням вкладеної крос-валідації. Встановлено, що найкращу точність і найменшу міжфолдову варіабельність забезпечує регресія на основі опорних векторів з радіально-базисним ядром. Обрану модель використано як функцію пристосованості в алгоритмі рою частинок, що дозволило визначити оптимальні умови процесу ферментативного ацидолізу: мольне співвідношення каприлової кислоти до соняшникової олії 5:1, температура 60 °C і час перебування 45 хвилин. Перевірочний експеримент у п’яти незалежних повторностях підтвердив адекватність отриманого оптимуму.
Ключові слова:
штучний інтелект, ацидоліз, ліпаза, структурований ліпід, алгоритм рою частинок
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Як цитувати
Nekrasov, P., Nekrasov, O., Tkachenko, N., Berezka, T., Gudz, O., & Molchenko, S. (2026). МЕТОДИ ШТУЧНОГО ІНТЕЛЕКТУ В МОДЕЛЮВАННІ І ОПТИМІЗАЦІЇ ПАРАМЕТРІВ БІОКАТАЛІТИЧНОЇ ТЕХНОЛОГІЇ ВИРОБНИЦТВА СТРУКТУРОВАНИХ ЛІПІДІВ ОЗДОРОВЧОГО ПРИЗНАЧЕННЯ. Food Science and Technology, 20(1), 27-39. https://doi.org/10.15673/fst.v20i1.3358
Номер
Розділ
Біопроцеси, біотехнологія харчових продуктів, БАР
Посилання
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2. Raven DB, Chikkula Y, Patel KM, Al Ghazal AH, Salloum HS, Bakhurji AS, et al. Machine learning and conventional approaches to process control and optimization: industrial applications and perspectives. Comput Chem Eng. 2024;189:108789. doi:10.1016/j.compchemeng.2024.108789.
3. Castro-Amoedo R, Granacher J, Maréchal F. A combined genetic algorithm and active learning approach to build and test surrogate models in process systems engineering. Comput Chem Eng. 2024;181:108517. doi:10.1016/j.compchemeng.2023.108517.
4. Hassoun A, Prieto MA, Carpena M, Bouzembrak Y, Marvin HJP, Pallarés N, et al. Exploring the role of green and Industry 4.0 technologies in achieving sustainable development goals in food sectors. Food Res Int. 2022;162(Pt B):112068. doi:10.1016/j.foodres.2022.112068.
5. Ghobakhloo M, Iranmanesh M, Tseng ML, Grybauskas A, Stefanini A, Amran A. Behind the definition of Industry 5.0: a systematic review of technologies, principles, components, and values. J Ind Prod Eng. 2023;40(6):432-47. doi:10.1080/21681015.2023.2216701.
6. Abass T, Itua EO, Bature T, Eruaga MA. Innovative approaches to food quality control: AI and machine learning for predictive analysis. World Journal of Advanced Research and Reviews. 2024;21(3):823-8. doi:10.30574/wjarr.2024.21.3.0719.
7. Esmaeily R, Razavi MA, Razavi SH. A step forward in food science, technology and industry using artificial intelligence. Trends Food Sci Technol. 2024;143:104286. doi:10.1016/j.tifs.2023.104286.
8. Harris N, Gonzalez Viejo C, Barnes C, Fuentes S. Non-invasive digital technologies to assess wine quality traits and provenance through the bottle. Fermentation. 2023;9(1):10. doi:10.3390/fermentation9010010.
9. Zhou Q, Zhang H, Wang S. Artificial intelligence, big data, and blockchain in food safety. Int J Food Eng. 2022;18(1):1-4. doi:10.1515/ijfe-2021-0299.
10. Barthwal R, Kathuria D, Joshi S, Kaler RSS, Singh N. New trends in the development and application of artificial intelligence in food processing. Innov Food Sci Emerg Technol. 2024;92:103600. doi:10.1016/j.ifset.2024.103600.
11. Bidyalakshmi T, Jyoti B, Mansuri SM, Srivastava A, Mohapatra D, Kalnar YB, et al. Application of artificial intelligence in food processing: current status and future prospects. Food Eng Rev. 2025;17:27-54. doi:10.1007/s12393-024-09386-2.
12. Alves V, de Figueiredo Furtado GDF, Roman MAS, Delboni LDMP, Alves Macedo JA, Vianna CLDC, et al. Palm oil-free structured lipids: a novel structuring fat for sandwich cookie fillings. Foods. 2026;15(1):178. doi:10.3390/foods15010178.
13. Witasari LD, Jason B, Salim JS, Pratama Y, Nusantoro BP. Enzymatic synthesis of zero-trans structured lipids from red palm oil (Elaeis guineensis) and sacha inchi oil (Plukenetia volubilis) blends. Food Biosci. 2025;69:106981. doi:10.1016/j.fbio.2025.106981.
14. Prasanna Rani KN, Kaki SS, Kezia Rani K, Kranthi Kumar B, Anjaneyulu E, Thirupathi A, et al. Production of healthier palm-based edible oil blends and enzymatic interesterified structured lipids for cooking and trans-free fat formulation applications. J Am Oil Chem Soc. 2024;101(3):269-82. doi:10.1002/aocs.12752.
15. Yuan T, Guo L, Gao X, Song G, Wang D, Li L, et al. Enzymatic synthesis and characterization of structured lipids: medium- and long-chain triacylglycerols enriched with lauric acid and diverse long-chain fatty acids. Food Biosci. 2025;64:105956. doi:10.1016/j.fbio.2025.105956.
16. Ijaz H, Sun S. A review on preparation and application of low-calorie structured lipids in food system. Food Sci Biotechnol. 2025;34(1):49-64. doi:10.1007/s10068-024-01689-8.
17. Guo Y, Cai Z, Xie Y, Ma A, Zhang H, Rao P, et al. Synthesis, physicochemical properties, and health aspects of structured lipids: a review. Compr Rev Food Sci Food Saf. 2020;19(2):759-800. doi:10.1111/1541-4337.12537.
18. Hong CR, Jeon BJ, Park KM, Lee EH, Hong SC, Choi SJ. An overview of structured lipid in food science: synthesis methods, applications, and future prospects. J Chem. 2023;2023:1222373. doi:10.1155/2023/1222373.
19. Mota DA, Rajan D, Heinzl GC, Osório NM, Gominho J, Krause LC, et al. Production of low-calorie structured lipids from spent coffee grounds or olive pomace crude oils catalyzed by immobilized lipase in magnetic nanoparticles. Bioresour Technol. 2020;307:123223. doi:10.1016/j.biortech.2020.123223.
20. Zou X, Jiang X, Wen Y, Wu S, Nadege K, Ninette I, et al. Enzymatic synthesis of structured lipids enriched with conjugated linoleic acid and butyric acid: strategy consideration and parameter optimization. Bioprocess Biosyst Eng. 2020;43(2):273-82. doi:10.1007/s00449-019-02223-5.
21. Ji S, Wu J, Xu F, Wu Y, Xu X, Gao H, et al. Synthesis, purification, and characterization of a structured lipid based on soybean oil and coconut oil and its applications in curcumin-loaded nanoemulsions. Eur J Lipid Sci Technol. 2020;122(10):2000086. doi:10.1002/ejlt.202000086.
22. Ji S, Xu F, Zhang N, Wu Y, Ju X, Wang L. Dietary a novel structured lipid synthesized by soybean oil and coconut oil alter fatty acid metabolism in C57BL/6J mice. Food Biosci. 2021;44:101396. doi:10.1016/j.fbio.2021.101396.
23. Tsuji K, Tsuchiya Y, Yokoi K, Yanagimoto K, Ueda H, Ochi E. Eicosapentaenoic acid and medium-chain triacylglycerol structured lipids improve endurance performance. Nutrients. 2023;15(17):3692. doi:10.3390/nu15173692.
24. Martínez-Galán JP, Ontibón-Echeverri CM, Campos Costa M, Batista-Duharte A, Guerso Batista V, Mesa Salgado VM, et al. Enzymatic synthesis of capric acid-rich structured lipids and their effects on mice with high-fat diet-induced obesity. Food Res Int. 2021;148:110602. doi:10.1016/j.foodres.2021.110602.
25. Bohorquez-Peña MJ, Vargas-Suaza B, Garzón-Alonso KE, Rendón-Londoño JC, Franco-Tobón YN, Gómez-Herrera CL, et al. Production of MLM-type structured lipids from avocado oil catalyzed by immobilized lipase on corn cob powder: assessment of antiproliferative potential on Hep-G2 cell line. Food Biosci. 2025;69:106824. doi:10.1016/j.fbio.2025.106824.
26. Yue C, Tang Y, Chang M, Wang Y, Peng H, Wang X, et al. Dietary supplementation with short- and long-chain structured lipids alleviates obesity via regulating hepatic lipid metabolism, inflammation and gut microbiota in high-fat-diet-induced obese mice. J Sci Food Agric. 2024;104(9):5089-5103. doi:10.1002/jsfa.13344.
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