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ARS Home » Plains Area » Fargo, North Dakota » Edward T. Schafer Agricultural Research Center » Cereal Crops Research » Research » Publications at this Location » Publication #253245
Title: Modeling of Mixolab Profiles by Nonlinear Curve Fitting and Prediction of Breadmaking Parameters

Author
item Ohm, Jae-Bom
item SIMSEK, SENAY - North Dakota State University
item MERGOUM, MOHAMED - North Dakota State University

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 5/1/2010
Publication Date: 9/1/2010
Citation: Ohm, J., Simsek, S., Mergoum, M. 2010. Modeling of Mixolab Profiles by Nonlinear Curve Fitting and Prediction of Breadmaking Parameters. Meeting Abstract. 55:A29.

Interpretive Summary:

Technical Abstract: Prediction of breadmaking parameters is a crucial step in wheat quality evaluation for breeders and end-users. This research was performed to investigate the association of flour breadmaking parameters with mixing characteristics and the rheological property of dough subjected to thermal constraint. Individual flour from 30 hard spring wheat was analyzed by a Mixolab standard procedure. The Mixolab profile was divided into six different stages, and torque measurements of individual stages were modeled by nonlinear curve fitting using multidimensional unconstrained nonlinear minimization. Specifically, mixing patterns were fitted to exponential equations and dough rheological patterns were described by Sigmoid logistic equations as functions of time. The new parameters calculated from fitted equations presented significant associations with breadmaking parameters. In particular, bread loaf volume (LV) had a significant correlation (r=-0.77, P<0.001) with a model parameter which was related to rate of torque decrease during heating due to protein weakening. This parameter also had a significant partial correlation with LV when effect of flour protein content was removed, indicating that it can supplement protein content to predict LV. Torque measurements between 6.5 to 16.0 min also had significant and positive correlations with LV. Multivariate continuum regression was employed to develop prediction models of breadmaking characteristics using Mixolab parameters. The calculated prediction models explained over 95% variations in bake water absorption, mix time and LV. Taken together, these results indicate that Mixolab is effective for evaluation of flour breadmaking parameters. The new parameters generated from equations fitted to Mixolab torque profiles appear to have great potential to aid in the evaluation of flour breadmaking quality.