ARS | Publication request: Modeling of dough mixing profile under thermal and non thermal constraint for evalution of breadmaking quality of Hard Spring Wheat flour

Submitted to: Cereal Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 30, 2011
Publication Date: February 1, 2012
Citation: Ohm, J., Simsek, S., Mergoum, M. 2012. Modeling of dough mixing profile under thermal and non thermal constraint for evalution of breadmaking quality of Hard Spring Wheat flour. Cereal Chemistry. 89:135-141.

Interpretive Summary: The mixolab has the capability to characterize not only flour mixing properties but also dough thermal properties during heating. This research was initiated to maximize the potential of the mixolab for the evaluation of flour breadmaking quality. Flour samples from 30 hard spring wheat were analyzed by a mixolab standard procedure at optimum water absorptions. The mixolab torque profile was divided into six different stages and torque measurements of individual stages were modeled to nonlinear curve fitting equations using a compound of two solution searching procedures. Mixing patterns followed exponential equations and dough rheological patterns under heat constraint were described by a sigmoid logistic equation as functions of time. Novel parameters that were generated from the equations were identified to be useful for the evaluation of flour breadmaking quality. Specifically, the mixolab parameters were greatly effective in the prediction of flour breadmaking quality when they were combined together using the multivariate methods. These results indicate that the mixolab has great potential to enhance the precision in prediction of flour breadmaking characteristics.

Technical Abstract: This research was initiated to investigate the association between flour breadmaking traits and mixing characteristics and empirical dough rheological property under thermal stress. Flour samples from 30 hard spring wheat were analyzed by a mixolab standard procedure at optimum water absorptions. Mixolab profile was divided into six different stages and torque measurements of individual stages were modeled by nonlinear curve fitting using a compound of genetic algorithm and multidimensional unconstrained nonlinear minimization. Mixing patterns followed exponential equations and dough rheological patterns under heat constraint were described by a sigmoid logistic equation as functions of time. Breadmaking parameters had significant associations with some novel parameters generated from the equations. Specifically, multivariate continuum regression was employed to develop prediction models of baking traits using the mixolab parameters. The coefficients of determination estimated from the prediction models and cross validation were greater than 0.98 for bake water absorption, mixing time and bread loaf volume, indicating that the mixolab has a great potential to enhance the precision in prediction of flour breadmaking characteristics.