Relationship Between Physicochemical Properties of Wheat Flour, Wheat Protein Composition, and Textural Properties of Cooked Chinese White Salted Noodles
Hou, G.G.; Saini, R.; Ng, P.K. W.
Cereal Chemistry 90(5): 419-429
ISSN/ISBN: 0009-0352 DOI: 10.1094/cchem-10-12-0137-r
Physicochemical properties and protein composition of 39 selected wheat flour samples were evaluated and correlated with the textural properties of Chinese hard-bite white salted noodles. Flour samples were analyzed for their protein and wet gluten contents, sedimentation volume, starch pasting properties, and dough mixing properties by farinograph and extensigraph. Molecular weight distribution of wheat flour proteins was determined with size-exclusion (SE) HPLC, SDS-PAGE, and acid-PAGE. Textural properties of Chinese hard-bite white salted noodles were determined through texture profile analysis (TPA). Hardness, springiness, gumminess, and chewiness of cooked noodles were found to be related to the dough mixing properties. Both protein content and protein composition were found to be related to TPA parameters of noodles. The amount of total flour protein was positively correlated to hardness, gumminess, and chewiness of noodles. The absolute amounts of different peak proteins obtained from SE-HPLC data showed positive correlations with the hardness, gumminess, chewiness, and springiness of noodles. The proportions of these peak proteins were, however, not significantly related to texture parameters. The proportions of low-molecular-weight glutenins/gliadins and albumins/globulins, as observed from SDS-PAGE, were correlated positively and negatively, respectively, to the hardness, gumminess, and chewiness of cooked noodles. Among the alcohol-soluble proteins (from acid-PAGE data), beta-gliadins showed strong correlations with the texture properties of cooked noodles. For the selected flour samples, the total protein content of flour had a stronger relationship with the noodle texture properties than did the relative proportion of different protein subgroups. Prediction equations were developed for TPA parameters of cooked noodles with SE-HPLC and rapid visco analysis data of the 30 flour samples, and it was found that about 75% of the variability in noodle hardness, gumminess, and chewiness values could be explained by protein composition and flour pasting properties combined together. About 50% of the variations in cohesiveness and springiness were accounted for by these prediction equations.