Modeling and optimization of functional bread formulations: a comprehensive review

In the context of the growing interest in healthy nutrition and functional food products, bakery products are considered a promising object for the targeted formation of functional properties. The modern development of food technologies necessitates a transition from empirical recipe selection to scientifically grounded methods for modeling and optimizing the composition of bakery products. The aim of this review article is to systematize and analyze contemporary approaches to the modeling and optimization of functional bread formulations with predefined technological, nutritional, and consumer properties. The paper examines the main research directions related to the use of functional ingredients, as well as mathematical, computational, and data-driven methods for formulation modeling. The scientific significance of the study lies in the comprehensive generalization of modern methods for modeling functional bread formulations and in identifying their advantages and limitations. The practical significance is determined by the potential application of the reviewed approaches in the development of new bakery products with predictable properties and stable quality. The research methodology is based on the analysis and synthesis of scientific publications indexed in international databases, employing methods of system analysis, comparative analysis, and classification. As a result of the conducted review, key trends in the development of functional bread formulation modeling were identified, and the effectiveness of mathematical optimization and computer modeling methods in shaping targeted functional properties was demonstrated. A conclusion was drawn regarding the перспективность of integrating digital and intelligent technologies into bakery product development processes. The value of the study lies in establishing a scientific foundation for further research in the field of functional bakery product modeling. The practical relevance of the results consists in their applicability in scientific research, educational activities, and the baking industry.

1. Siro, I., E. Kapolna, B. Kapolna, and A. Lugasi. 2008. “Functional Food: Product Development, Marketing and Consumer Acceptance.” Appetite 51 (3): 456–467.

2. Jones, P. J., and S. Jew. 2007. “Functional Food Development: Concept to Reality.” Trends in Food Science & Technology 18 (7): 387–390.

3. Bigliardi, B., and F. Galati. 2013. “Innovation Trends in the Food Industry: The Case of Functional Foods.” Trends in Food Science & Technology 31 (2): 118–129.

4. Purlis, E. 2019. “Baking Process Design Based on Modelling and Simulation: Toward Optimization of Bread Quality.” Food Control 100: 45–52.

5. Singh, R. P., and D. R. Heldman. 2014. Introduction to Food Engineering. Academic Press, 37–48.

6. Aguilera, J. M. 2018. “Relating Food Engineering to Cooking and Gastronomy: Modeling, Simulation, and Visualization.” Annual Review of Food Science and Technology 9: 191–210.

7. Siro, I., E. Kapolna, B. Kapolna, and A. Lugasi. 2008. “Functional Food: Product Development, Marketing and Consumer Acceptance.” Appetite 51 (3): 456–467.

8. Miranda, J., et al. 2016. “Nutritional Enhancement of Bread with Functional Ingredients: A Review.” Food Research International 80: 1–17.

9. Dziki, D., R. Różyło, U. Gawlik-Dziki, and M. Świeca. 2014. “Current Trends in the Enhancement of Antioxidant Activity of Wheat Bread.” Journal of Food Science and Technology 51: 423–434.

10. Van Boekel, M. A. J. S. 2008. “Kinetic Modeling of Food Quality: A Critical Review.” Comprehensive Reviews in Food Science and Food Safety 7 (2): 144–158.

11. Singh, R. P., and D. R. Heldman. 2014. Introduction to Food Engineering. Academic Press.

12. Baş, D., and İ. H. Boyacı. 2007. “Modeling and Optimization I: Usability of Response Surface Methodology.” Journal of Food Engineering 78 (3): 836–845.

13. Purlis, E. 2019. “Baking Process Design Based on Modelling and Simulation: Toward Optimization of Bread Quality.” Food Control 100: 45–52.

14. Bevilacqua, M., et al. 2020. “Artificial Intelligence Applications in Food Process Modeling.” Journal of Food Engineering 287: 110126.

15. Zhu, F. 2021. “Applications of Machine Learning in Food Science and Technology.” Food Chemistry 342: 128199.

16. Miranda, J., et al. 2016. “Nutritional Enhancement of Bread with Functional Ingredients: A Review.” Food Research International 80: 1–17.

17. Balestra, F., and E. Cocci. 2020. “Functional Bakery Products: Trends and Challenges.” Journal of Cereal Science 93.

18. Dziki, D., R. Różyło, U. Gawlik-Dziki, and M. Świeca. 2014. “Current Trends in the Enhancement of Antioxidant Activity of Wheat Bread.” Journal of Food Science and Technology 51: 423–434.

19. Tranfield, D., D. Denyer, and P. Smart. 2003. “Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review.” British Journal of Management 14 (3): 207–222.

20. ISO. 2009. ISO 712: Cereals and Cereal Products — Determination of Moisture Content. Geneva: International Organization for Standardization.

21. ISO. 2019. ISO 7305: Milled Cereal Products — Determination of Acidity. Geneva: International Organization for Standardization.

22. AACC International. 2010–2019. Approved Methods of Analysis. 11th ed. Methods 10-05.01; 74-09.01. St. Paul, MN.

23. AOAC International. 2016. Official Methods of Analysis. 20th ed. Method 985.29. Gaithersburg, MD.

24. Baş, D., and İ. H. Boyacı. 2007. “Modeling and Optimization I: Usability of Response Surface Methodology.” Journal of Food Engineering 78: 836–845.

25. Ali, Zainab N., Iman Askerzade, and Saddam Abdulwahab. 2021. “Estimation Model for Bread Quality Proficiency Using Fuzzy Weighted Relevance Vector Machine Classifier.” Applied Bionics and Biomechanics 2021 (February 26): 6670316.