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United States Department of Agriculture

Agricultural Research Service

Title: A Rapid Small-Scale Method to Evaluate Dough Viscoelastic Properties

Authors
item Xie, Feng - KANSAS STATE UNIV
item Seabourn, Bradford

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: June 1, 2007
Publication Date: October 7, 2007
Citation: Xie, F., Seabourn, B.W. 2007. A rapid small-scale method to evaluate dough viscoelastic properties [abstract]. Cereal Foods World. 52:A69.

Technical Abstract: Dough viscoelastic properties are of special interest to bakers and wheat breeders. Dough extensibility (DE) and resistance to extension (RE) influence each step of the baking process as well as product end-use quality, and thus are important quality factors to consider in wheat breeding programs. The objective of this study was to develop a rapid small-scale method to evaluate dough DE and RE properties. A total of 20 hard red winter wheat flour samples varying in protein content (8.9 - 14.3%), Farinograph optimum water absorption (55.8 - 68.0%), Farinograph dough development time (4.5 - 23 min), and Farinograph mixing tolerance (7.0 - 59.8 min) were studied. Doughs were mixed to optimum at optimum water absorption by Farinograph. The standard Extensigraph method (AACCI approved Method 54-10) was compared to a small-scale method which utilized the Texture Analyzer (TA) equipped with a Kieffer rig. Correlation of determination (R2) of DE measured by Extensigraph versus by TA was 0.77, while that of RE measured by each instrument was 0.46. The potential of near-infrared reflectance spectroscopy (NIR) for measuring DE and RE was also investigated. The NIR technique showed great potential in predicting both DE and RE as determined by Extensigraph. The highest R2 was 0.84 for DE and 0.81 for RE, with a standard error of prediction of 49.34 and 9.66, respectively. Spearman rank correlation coefficients of DE and RE predicted by the Extensigraph-based model and TA-based model were 0.97 and 0.68, respectively. Results show that these two model’s ability to differentiate DE was similar.

Last Modified: 11/21/2014
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