| Abstract: | Nowadays in Argentina, cookies, crackers, and cakes are made of flour obtained from bread wheat with additives or enzymes that decrease the gluten strength but increase production costs. The present research work aims to study the relationship between flour physicochemical composition (particle size average PSA], protein, damaged starch DS], water soluble pentosans WSP], total pentosans TP], and gluten), alkaline water retention capacities behavior, solvent retention capacities profile (SRC) and cookie‐making performance in a set of 51 adapted soft wheat lines with diverse origin to identify better flour parameters for predicting cookie quality. Cookie factor (CF) values were 5.06–7.56. High and significant negative correlations between sucrose SRC (–0.68), water SRC (–0.65), carbonate SRC (–0.59), and CF were found, followed by lactic SRC that presented a low negative but significant correlation (r = –0.35). The flour components DS (r = –0.67), WSP (r = –0.49), and TP (r = –0.4) were negatively associated to CF. PSA showed a negative correlation with CF (r = –0.43). Protein and gluten were the flour components that affected cookie hardness, but no significant correlation were found with pentosan or DS content. A prediction equation for CF was developed. Sucrose SRC, PSA, and DS could be used to predict 68% of the variation in cookie diameter. The cluster analysis was conducted to assess differences in flour quality parameters among genotypes based on CF. Clusters 1 and 4 were typified by lower CF (5.70 and 5.23, respectively), higher DS, pentosan content, and SRC values. Cluster 2 with a relative good CF (6.47) and Cluster 3 with the best cookie quality, high CF (7.32) and low firmness, and the lowest DS, TP, WSP content, and sucrose SRC values. |
