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 proposed method is a good option to be used in quality control laboratories for the classification of honey samples according to their geographical origin.