An analytical method for determination of quality parameters in cotton plumes by digital image and chemometrics

This paper proposes an analytical method based on the use of digital images and multivariate calibration for the determination of degree of yellowness (+b), reflectance (Rd) and content of wax (WAX) in samples of white cotton plumes and naturally colored plumes. Digital images acquisition of cotton plumes was carried out through a webcam and histograms containing frequency distributions of color index in red-green-blue (RGB), hue (H), saturation (S), value (V), and grayscale channels were obtained. Models of multivariate calibration based on Regression by partial least squares (PLS) using the complete histogram, as well as multiple linear regression (MLR) with the selection of variables by successive projections algorithm (SPA) were developed, validated and compared. Satisfactory prediction results were obtained for both models with Root Mean Square Error of Prediction (RMSEP) values varying from 0.76-0.83, 2.49-2.53% and 0.30-0.33% for +b, Rd and wax, respectively. According to a paired t-test at a 95% confidence level, no statistically significant difference was found between the predicted and reference values. An F-test at 95% confidence level does not indicate significant differences between the RMSEP values obtained with the full-histogram PLS and MLR-SPA models. It is a simple and low-cost method that does not use reagent, does not destroy the sample and performs analysis with comparable results to the reference method. (C) 2016 Elsevier B.V. All rights reserved.