## 3 Results and Discussion
### Texture Profile Analysis of Bread
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Batch**} & Crust & 47.209 & \(\pm\)0.686 \({}^{\text{c}}\) & 14.911 & \(\pm\)0.262 \({}^{\text{b}}\) & 27.876 & \(\pm\)0.239 \({}^{\text{c}}\) \\  & Crumb & 47.164 & \(\pm\)0.814 \({}^{\text{\gamma}}\) & 9.044 & \(\pm\)0.120 \({}^{\text{\gamma}}\) & 19.722 & \(\pm\)0.258 \({}^{\text{g}}\) \\ \hline \multirow{2}{*}{Ctrl} & Crust & 41.549 & \(\pm\)0.529 \({}^{\text{d}}\) & 14.939 & \(\pm\)0.222 \({}^{\text{b}}\) & 23.583 & \(\pm\)0.658 \({}^{\text{d}}\) \\  & [PERSON] & 47.267 & \(\pm\)0.547 \({}^{\text{\gamma}}\) & 9.866 & \(\pm\)0.112 \({}^{\text{b}}\) & 21.853 & \(\pm\)0.138 \({}^{\text{\gamma}}\) \\ \hline \multirow{2}{*}{GFB8} & Crust & 35.643 & \(\pm\)1.130 \({}^{\text{e}}\) & 13.969 & \(\pm\)0.355 \({}^{\text{c}}\) & 18.725 & \(\pm\)0.556 \({}^{\text{e}}\) \\  & [PERSON] & 41.776 & \(\pm\)0.662 \({}^{\text{g}}\) & 12.781 & \(\pm\)0.148 \({}^{\text{a}}\) & 23.848 & \(\pm\)0.586 \({}^{\text{b}}\) \\ \hline \hline \end{tabular} 
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Batch**} & Crust & 47.209 & \(\pm\)0.686 \({}^{\text{c}}\) & 14.911 & \(\pm\)0.262 \({}^{\text{b}}\) & 27.876 & \(\pm\)0.239 \({}^{\text{c}}\) \\  & Crumb & 47.164 & \(\pm\)0.814 \({}^{\text{\gamma}}\) & 9.044 & \(\pm\)0.120 \({}^{\text{\gamma}}\) & 19.722 & \[PERSON] and [PERSON] [54] concluded that texture parameters are suitable to discriminate between commercial GFBs. However, they described a great variability in texture parameters among marketed products. Our samples were in the lowest range reported by these authors for hardness and chewiness and our cohesiveness and resilience were higher than their mean values. These authors found positive correlation between hydration properties, cohesiveness and resilience; in our case, there was a lowered aw tendency from GFBS to GFB8, together with a slight decline in those texture parameters. [PERSON] et al. [31] studied the combined effect of APP and water content on GF formulations on cohesiveness and resilience and they observed that increasing only APP brought decreasing values for both parameters. At the same time, this effect was corrected by increased water addition, as was carried out in this work (Table 1). Values compiled by these authors for cohesiveness and resilience were consistent with the values reported in our samples. However, in our case, chewiness was the clearest attribute discriminating between samples containing or not containing APP, as apple addition significantly decreased values in comparison with both control (highest values) and CP. A similar effect was described for hardness, as well; [PERSON] et al. [55] evaluated the quality of Sangak bread (a traditional Iranian bread) that included APP (1 to 7% \(w/w\) of flour) indicating that adding apple pomace can reduce the hardness of bread texture. Other authors described increasing hardness with higher APP amount in several bakery products [7]. Nevertheless, it should be noted that changes from  
Figure 1: Mean values for texture parameters from the instrumental texture profile analysis. Bread formulations (batches): Ctrl, control batch; CP, control with protein added; GFB5, GFB6, and GFB8, gluten-free bread with protein and apple pomace powder added at 5%, 6% or 8%. Resilience, springiness and cohesiveness data must be read as \(\times 10^{-1}\). Ctrl and CP to APP-containing samples are due not only to APP addition, but also to a proportional reduction in flours and increased water content. Increasing APP required more water to be added to the mixture as it had a high water holding capacity and trapped free water, limiting available water for dough manipulation and fermentation. As described by [PERSON] et al. [31], water addition helps to correct texture parameters when these are modified by increasing APP addition.