Predicting hot-press wheat tortilla quality using flour, dough and gluten properties

A cost-effective, faster and efficient way of screening wheat samples suitable for tortilla production is needed. This research aimed to develop prediction models for tortilla quality (diameter, specific volume, color and texture parameters) using grain, flour and dough properties of 16 wheat flours. Another set of 18 samples was used to validate the models. The prediction models were developed using stepwise multiple regression. Dough rheological tests had higher correlations with tortilla quality than grain and flour chemical tests. Mixograph mixing time and dough resistance to extension (from extensibility test using a texture analyzer) were correlated best with tortilla quality, particularly tortilla diameter (r1⁄4 0.87 and 0.86 respectively, P< 0.01). Insoluble polymeric proteins (IPP) and gluten index were significantly correlated with tortilla diameter (r1⁄4 0.70 and 0.67 respectively, P< 0.01) and specific volume (r1⁄4 0.73, P< 0.01). Tortilla diameter was the quality parameter best explained (R21⁄4 0.86) by the prediction models using mixing time and dough resistance to extension. Rheological parameters such as rupture distance and maximum force were also successfully predicted. These prediction models, developed from linear equations, will be an easy and fast tool for breeders to advance or eliminate wheat lines specifically bred for tortilla production. 2010 Elsevier Ltd. All rights reserved.