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Rapid Assessment and Prediction of Wheat and Gluten Baking Quality With the 2-g Direct Drive Mixograph Using Multivariate Statistical Analysis

¹School of Food Biosciences, PO Box 226, Whiteknights, The University of Reading, Reading, RG6 6AP, UK. ²Corresponding author. E-mail: b.dobraszczyk@reading.ac.uk.

A computerized 2-g direct drive mixograph was used to study the mixing characteristics of flours milled from a range of breadmaking cultivars obtained from five separate locations around the UK, providing 54 flour samples. Fifteen parameters were extracted from each mixograph trace using the Mixsmart software program and correlated with baking volume using partial least squares multiple regression statistical analysis to give a prediction of baking volume. Location had a considerable influence on the prediction of baking volume. Excellent predictions of baking volume were obtained from flours from individual locations (R² = 0.805–0.995), but predictions based on all cultivars without discriminating locations were poor. When mixograph and baking volume data for each cultivar were averaged over all five locations, a very high correlation was obtained (R² = 0.999). Preparation of flour samples using rapid, small-scale milling procedures (Brabender Quadrumat Jr. mill and Perten 3100 hammer mill) did not have any adverse effect on prediction of baking volume. Mixograph parameters obtained from six commercial glutens of varying quality gave good correlations with test baking volumes, based on 6% gluten addition to a control flour.