Quality and sensory profiling of gluten free bread as a function of quinoa, corn and xanthan content: Statistical analysis and modeling study

Abstract

In the study, the effect of compositional parameters (Xanthan, Corn flour and quinoa flour content) on sensory characteristics and image features of gluten free bread were evaluated. Results showed, addition of quinoa and corn flour significantly decreased L* value and increased a* value of crust and crumb of gluten free bread. Also, increased percentage of corn flour has led to decreased amount of FDL* that indicates the area appears less nonhomogeneous on surface of gluten- free bread. The results also showed that using complete flour of quinoa causes softness in bread due to the presence of bran and networking, therefore, resulting in increased contrast, homogeneity and entropy, and decreased energy and correlation of produced breads. The results of sensory analysis showed that all samples containing quinoa flour have higher overall acceptance score than that of the control treatment. Correlation analysis showed a good linear relationship between image features and overall acceptance of gluten- free bread. Results showed that the optimized Adaptive Neuro-Fuzzy Inference System (ANFIS model) provide best accurate prediction method for overall acceptance of gluten-free bread (R2= 0.994 and MSE= 0.0015) and it could be a useful tool in the food industry to design and develop novel products.

Keywords

• image processing
• sensory analyzer
• gluten free bread
• anfis model