ABSTRACT
Fresh alkaline noodles prepared from patent flours of the Canadian wheat class Canadian Prairie Spring White (CPSW) AC Karma and AC Vista were characterized by image analysis to numerically evaluate the time-dependent formation of dark areas (spots) on the noodle surface. The system was able to rapidly detect, measure, and characterize such undesirable discolorations, which commonly form on the surface of raw noodles with time. Variations in minimum spot detection size (0.050–0.250 mm2), in combination with a darkness threshold setting (Δ grey scale units of 2, 5, and 10) were investigated. A linear increase in the number of spots was observed over time for both cultivars with nine combinations of size and darkness. The total number of discolored spots measured was dependent on both detection size and sensitivity (threshold setting). Significant differences (P < 0.05) in the number of darkened spots were detected between the two cultivars only after 24 hr. Similarly, significant differences (P < 0.05) in size of the spots between the two cultivars was observed at 24 hr. Darkening was most rapid within the first hour for both cultivars, followed by a period of stability before a significant (P < 0.05) further increase by 24 hr. Characterization of the darkness distribution indicated significantly different distribution profiles for the two cultivars examined, which was consistent with their noodle brightness (L*) values.
