Optimization and Quality Evaluation of Ohmic-Heated Gluten-Free Bread Formulated with Soybean, Sorghum, and Red Bean Flours Using Response Surface Methodology

Authors

  • Jenri Parlinggoman Hutasoit Universitas Negeri Medan
  • Yuni Yolanda Universitas Negeri Medan
  • Dela Febrianti Universitas Teknologi Sumbawa

DOI:

https://doi.org/10.29303/profood.v12i1.613

Keywords:

Gluten-free bread, Legume flour, Mixture design, Ohmic heating, Response surface methodology

Abstract

Ohmic heating has emerged as an alternative volumetric baking technology capable of improving the quality of gluten-free bread; however, its effectiveness is strongly influenced by the starch and protein composition of the ingredients used. This study aimed to optimize the formulation of gluten-free bread processed by ohmic heating using soybean flour, sorghum flour, and red kidney bean flour as complementary protein–starch sources. A mixture design Response Surface Methodology (RSM) was applied to evaluate the effects of flour proportions on specific volume and proximate composition. Soybean flour (50-80%), sorghum flour (10-30%), and red kidney bean flour (10-20%) were selected as independent variables. The optimal formulation consisted of 71.39% soybean flour, 10.00% sorghum flour, and 18.61% red kidney bean flour, yielding a specific volume of 2.79 ± 0.07 cm³/g and a protein content of 22.68 ± 0.05%. Model validation confirmed no significant differences between predicted and experimental values (p>0.05). The results demonstrate that synergistic interactions between protein-rich and starch-rich flours under ohmic heating significantly enhance bread structure and nutritional quality. This study provides a systematic formulation strategy for developing high-quality gluten-free bread using ohmic heating technology.

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Published

2026-05-31

How to Cite

Hutasoit, J. P. ., Yolanda, Y., & Febrianti, D. . (2026). Optimization and Quality Evaluation of Ohmic-Heated Gluten-Free Bread Formulated with Soybean, Sorghum, and Red Bean Flours Using Response Surface Methodology. Pro Food, 12(1), 12–29. https://doi.org/10.29303/profood.v12i1.613