Modelling dried noodle quality: Contribution of starch and protein physicochemical properties of 32 wheat cultivars

Abstract

30 mainstream wheat breeds from China and 2 from Australian were evaluated to analyze the correlation between grain quality traits, protein/starch properties and the comprehensive quality of fine dried noodles (FDN), with a multiple regression analysis conducted to establish predictive equations. Results showed FDN quality was both determined by the protein content and quality, as well as the starch properties, especially pasting characteristics. The balance between gluten strength and starch swelling characteristics was a key point to produce high quality FDN. Zhoumai32 and APW were found to be excellent cultivars for FDN production. Gluten content and index, SDS sedimentation value, dough extensibility, setback and peak viscosity could be served as indicators for specializing FDN flour. The established predictive equations could well explain over 60% of the variation in noodle color, cooking time, hardness, chewiness, and extensibility. These results were hoped to be a fundamental step towards developing the related standards or regulations for specializing FDN flour and rapid noodle quality prediction.

Keywords: Noodle; Prediction model; Protein quality; Starch; Wheat.