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Keywords:

  • Chopin Consistograph;
  • dough mixing;
  • partial least square regression;
  • semolina

Summary

Partial least square regression analysis was used to study the correlation between X variables (semolina quality, hydration level and mixing time) and Y variables, which were, in a first model, dough consistency during mixing, and, in a second model, dough properties after mixing (strength, elasticity, density) and leavening (maximum volume). The first model showed a predictive residual sum of squares (PRESS) of 2.98 and a predictive R2 (Q2) of 0.92, and highlighted the key role of hydration and mixing time on dough consistency. The second model had the best PRESS (8.25) and Q2 (0.94) values for dough volume and indicated that the volume increased with increasing mixing time until the dough consistency decreased of 20–30%. Dough volume was primarily affected by hydration. The model indicated that maximum volume after leavening, corresponding to optimum mixing time, was obtained with a soft and elastic dough, with a low-density value.