Geographical origin classification of Argentinean honeys using a digital image-based flow-batch system

Abstract

In this paper a geographic origin classification of honey samples from Argentina was proposed. For this reason, a conventional flow-batch system with a simple webcam to capture digital images was employed. In this methodology, analytical information is generated from color histograms obtained from the digital images employing different color models (RGB (red-green-blue), HSB (hue-saturation-brightness) and Grayscale). Three chemometric tools were employed for geographic origin classification (SPA-LDA (successive projections algorithm-linear discriminant analysis), SIMCA (soft independent modeling for class analogy), and PLS-DA (partial least squares-discriminant analysis)). The proposedmethod is a good option to be used in quality control laboratories for the classification of honey samples according to their geographical origin.