Response Surface Optimization of Barbari Bread‐Making Process Variables: Interrelationship of Texture, Image and Organoleptic Characteristics; Using Image Analysis for Quality and Shelf Life Prediction

Digital image processing technique is a useful tool for bread texture analysis. In the current study, to improve bread features (cell wall thickness, fractal dimension, circularity, solidity, crust lightness, crumb lightness, mean cell area [MCA], cell count and density, porosity, specific loaf volume [SLV], hardness and sensory attributes), final proofing time (FPT), dough mixing time in low (MTLS; 63 rpm) and high speed (MTHS; 180 rpm) were considered as the independent variables. Result showed rising FPT up to 60 min led to significant (P ≤ 0.05) enhancement of SLV and MCA up to 4.62 cm³/g and 4.63 mm², respectively, and decrease in crust lightness, crumb lightness and hardness. Cell count and density were strongly affected by MTHS. Crust lightness may be presumably considered as an indicator for hardness (r = 0.767) and SLV (r = −0.843) prediction. The optimized conditions were 60‐min FPT, 5.30‐min MTLS and 8.05‐min MTHS, which can be applied for large‐scale production of bread. PRACTICAL APPLICATIONS: Generally, analysis of changes in quality, shelf life and sensory features of bread during bread‐making process is time consuming. This research shows that survey of these properties can be carried out in quick time with correlation between image attributes and other characteristics. Furthermore, representative‐optimized conditions are useful for improvement of bread quality factors.