Python/RGB Color Data Analysis Platform for Rapid Detection of Reducing Sugar Concentration
Article
Figures
Metrics
Preview PDF
Reference
Related
Cited by
Materials
Abstract:
A new method for determining reducing sugar concentration through food biochemical experiments using python was investigated in this study. Reducing sugar-containing samples were diluted to different concentrations and placed on the 96-well plates, before being scanned by the scanner to obtain the color images in tiff. The RGB color data of the samples were collected by the RGB analysis module of the online analysis platform developed by our research group. By investigating the conditions such as the sampling size and optimal image resolution, a rapid detection method for reducing sugar in food based on RGB color system was established. For glucose detection, the fitting coefficient was higher than 0.98 when the concentration of glucose remained the same with the sample size as 100 μL and the image resolution as 1200 dpi. The accuracy of the relationship between RGB color data and the concentration of reducing sugar was higher, and the result was similar to the that obtained by spectrophotometry, but this method is more convenient and faster and allowed multi-channel processing. At the same time, through measuring the content of reducing sugar in the real sample and comparing with the results obtained by spectrophotometry, the reliability and feasibility of using Python/RGB color data analysis platform to determine quickly the concentration of reducing sugar in food were verified.
