Abstract

ABSTRACTProlamins in wheat, barley, and rye cause celiac disease (CD), non‐celiac gluten sensitivity (NCGS), and wheat allergies (WA). Although rice can be a suitable alternative, gluten‐free rice flour products are less technologically advanced. However, coconut flour and xanthan gum could enhance product quality, fiber content, and functional properties. This study employed a response surface D‐optimal mixture design to investigate the impact of substituting Sadri Hashemi rice flour (RF) (15.60%–31.19%) with low‐fat desiccated coconut flour (CF) (0%–15.59%) and xanthan gum (XG) (0%–0.31%) in 17 runs based on batter weight. Eleven responses were analyzed and exhibited significant and valid models (p < 0.0001), with satisfactory coefficient of determination (R2 > 0.85) values and non‐significant lack of fit (p > 0.1). Substitution at all levels significantly increased batter viscosity (R2 = 0.990) and specific weight (R2 = 0.995). Differences in cake crumb color (ΔE) decreased when RF was substituted with CF, while maximum ΔE elevation was observed with 0.31% XG due to synergistic effects with 5.09% CF (R2 = 0.974). Increasing the RF/XG ratio (0% CF) resulted in decreased water activity (aw), while increasing CF increased aw synergistically (R2 = 0.986). Moisture and texture hardness increased significantly with RF substitution up to 7.518% CF and 0.170% XG and 8.944% CF and 0.285% XG, respectively (R2 = 0.976 and 0.993). The volume index decreased with CF and XG (R2 = 0.989). Sensory acceptances were reduced by increasing XG while improved with optimal CF levels, predicted at 6.415% (R2 = 0.997), 6.784% (R2 = 0.999), 9.001% (R2 = 0.999), and 5.924% (R2 = 0.999) for color, taste, texture, and overall acceptance, respectively. Two‐sided prediction interval confirmation runs with 95% confidence (p ≤ 0.05) validated the models' accuracy and prediction of optimized combinations. The optimized gluten‐free cake formula (23.395% RF, 7.795% CF, 0% XG) achieved an 88.0% desirability score. Developing valid regression models facilitates a comprehensive investigation of cake quality and sensory properties, ensuring a viable gluten‐free product for individuals with gluten‐related disorders.

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