A digital image-based traceability tool of the geographical origins of Argentine propolis

Abstract

Propolis is a hive product prepared by honeybees (Apis mellifera L.) widely used in pharmaceutical and food preparations that plays beneficial roles beyond basic nutrition and therapeutic properties. These benefits are related with its quality, which depends on various factors, such as geographical origin, botanical sources, collecting seasons, races of honeybees, climatic conditions and also the method of harvest. In this sense, it would be helpful the implementation of a simple, fast and reliable analytical methodology for quality monitoring of propolis samples as a traceability tool of its geographical origin. Thus, this work proposes the use of digital images and chemometrics for the classification of raw propolis from six different geographical origins of the Buenos Aires Province, Argentina. For this purpose, different combinations between a color model (Grayscale, RGB and HSI) and a multivariate classifier (PCA–LDA, SIMCA, kNN, PLS-DA and SPA–LDA) were tested. The best analytical performance was achieved by SPA–LDA using Intensity histograms, classifying correctly a 100% of the samples in both training and test sets, taking in account the 27 variables selected by SPA. As a consequence, the proposed methodology serves to support local apiculturists, guaranteeing the offer of products with a clear indication of geographical origin, and enhancing regional capabilities.