Relationship between soft wheat flour physicochemical composition and cookie-making performance

MALENA MOIRAGHI; LEONARDO VANZETTI; CARLOS BAINOTTI; MARCELO HELGUERA; ALBERTO LEÓN; GABRIELA PÉREZ

CEREAL CHEMISTRY

AMER ASSOC CEREAL CHEMISTS

Año: 2011 vol. 88 p. 130 - 160

0009-0352

Nowadays in Argentina, cookies, crackers, and cakes are made of flourobtained from bread wheat with additives or enzymes that decrease thegluten strength but increase production costs. The present research workaims to study the relationship between flour physicochemical composition(particle size average [PSA], protein, damaged starch [DS], watersoluble pentosans [WSP], total pentosans [TP], and gluten), alkalinewater retention capacities behavior, solvent retention capacities profile(SRC) and cookie-making performance in a set of 51 adapted soft wheatlines with diverse origin to identify better flour parameters for predictingcookie quality. Cookie factor (CF) values were 5.06–7.56. High and significantnegative correlations between sucrose SRC (–0.68), water SRC(–0.65), carbonate SRC (–0.59), and CF were found, followed by lacticSRC 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 withCF (r = –0.43). Protein and gluten were the flour components that affectedcookie hardness, but no significant correlation were found withpentosan or DS content. A prediction equation for CF was developed.Sucrose SRC, PSA, and DS could be used to predict 68% of the variationin cookie diameter. The cluster analysis was conducted to assess differencesin flour quality parameters among genotypes based on CF. Clusters1 and 4 were typified by lower CF (5.70 and 5.23, respectively), higherDS, 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 lowfirmness, and the lowest DS, TP, WSP content, and sucrose SRC values.