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. [ABSTRACT FROM AUTHOR]