Abstract
Sugar is consumed worldwide and so the quality control of sugar cane is necessary. Solid impurities are an inherent part of industrial sugar processing. Dark particles and adulteration with sand must be controlled. Sixty-four samples of white crystal cane sugar analysis in the presence of both kinds of impurities (dark particles and sand) were assessed using an affordable digital image system and a multivariate calibration strategy. The quality parameters for the multivariate calibration models obtained to estimate sugar content were remarkable. Color descriptors from digital images allowed identification of different levels of sugar content for the following three ranges: 0-49.99 wt%, 50.03-78.99 wt%, and 82.99-100 wt%. The multivariate model using red (R), green (G), Blue (B), and luminosity (L) color descriptors showed low standard errors of cross-validation (SECV) and validation (SEV) of 7.63 and 6.01 wt%, respectively. The method is affordable and reliable, and might aid quick screening in situations where access to a laboratory or instrumentation is restricted. © 2021 Society of Chemical Industry.
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