Predictive modelling of flour, dough, and bread quality based on key soft wheat grain characteristics

Makpal Rakhymbayeva, Аuyelbek Iztayev, Talgat Kuralbekovich Kulazhanov, V. Ya. Chernykh, Ainur Аbitbek, А.С. Боранкулова

2026

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DOI 10.5219/scifood.89
Data confidence 70 medium
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Abstract

This study aimed to develop generalized regression models describing the relationships between soft wheat grain quality characteristics and the technological properties of flour, dough, and bread. Ten soft wheat cultivars, including five spring cultivars (Kazakhstanskaya 10, Egemen, Almeken elite, Kazakhstanskaya Early-Ripening, and Mereke) and five winter cultivars (Steklovidnaya 24, Bogarnaya 56, Almaken, Sapaly, and Stepnaya 75), were investigated. Comprehensive analyses of grain, flour, dough, and bread quality parameters were performed using twenty grain samples. Regression equations were developed based on four primary grain quality indicators: moisture content (W), test weight (N), vitreousness (S), and gluten content (K). The developed models described the influence of grain characteristics on the quality indicators of grain, flour, dough, and bread. Protein content was found to depend primarily on grain vitreousness and reached a maximum value of 16.64% at a vitreousness of 50%. The highest flour gluten content (36.7%) was obtained at a grain moisture content of 10.6%, test weight of 745 g/L, and grain gluten content of 35.0%. Dough quality, evaluated by deformation work, reached a maximum value of 358.97 erg at W = 10.5%, N = 801 g/L, S = 63%, and K = 28%. The maximum predicted loaf volume was 811.8 cm³/100 g flour at W = 9.96%, N = 801 g/L, and S = 50%. The regression models adequately described the experimental data and enabled the identification of optimal grain quality ranges associated with favorable flour functionality, dough rheology, and breadmaking performance. The proposed mathematical models can be used for quality prediction, process optimization, and decision support in wheat processing and bakery production.