TEM Journal | 2026
Authors: Kularbphettong K.; Sirichokworrakit S.; Aukkanit N.; Sangsuwan C.
DOI: 10.18421/TEM151-04
Journal: TEM Journal
Year: 2026
Publisher: UIKTEN - Association for Information Communication Technology Education and Science
Document Type: Article
Open Access: All Open Access; Gold Open Access
Cited by: 0
– The increasing demand for functional foods has stimulated the creation of healthier bakery items. Riceberry flour, sourced from Thai purple rice, is abundant in antioxidants and dietary fiber, rendering it a viable substitute for wheat flour in donut recipes. Nonetheless, its incorporation can profoundly modify sensory characteristics including texture, hue, and general palatability. Hydrocolloids such as Hydroxypropyl Methylcellulose (HPMC) and Methylcellulose (MC) are frequently included to enhance moisture retention and diminish oil absorption; nevertheless, their interactions with Riceberry flour are intricate and nonlinear. In this study, the use of machine learning approaches for predicting the sensory qualities of Riceberry flour-formulated functional donuts is investigated. Three regression models—Gaussian Process Regression (GPR), Support Vector Regression (SVR), and Random Forest Regression—were assessed for their efficacy in predicting Overall Liking, Taste, and Texture scores based on constituent composition. The findings indicated that GPR consistently surpassed the other models, attaining the lowest MAE and RMSE values for all sensory targets. SVR offered competitive performance, however Random Forest displayed elevated prediction errors, especially for Texture. These findings underscore the efficacy of kernel-based models in elucidating nonlinear ingredient-sensory connections within tiny, noisy datasets. This study illustrates the viability of using machine learning into nascent product development, facilitating enhanced precision and efficiency in sensory optimization for functional food design. © (2026), (UIKTEN - Association for Information Communication Technology Education and Science). All rights reserved.
functional donuts; ingredient interaction; machine learning; Riceberry flour; sensory prediction