Combining Multivariate Analysis and Pollen Count to Classify Honey Samples Accordingly to Different Botanical Origins
|Eduardo Corbella1 and Daniel Cozzolino2*|
This study reports the combination of multivariate techniques and pollen count analysis to classify honey samples accordingly to botanical sources, in samples from Uruguay. Honey samples from different botanical origins, namely Eucalyptus spp. (n = 10), Lotus spp. (n = 12), Salix spp. (n = 5), “mil flores” (Myrtaceae spp.) (n = 12) and coronilla (Scutia buxifolia Reissek) (n = 10) were analysed using Melissopalynology (pollen identification). Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to classify the honey samples accordingly to their botanical origin based on a pollen count. Honey samples of higher percentage (> 70%) of Eucalyptus, Lotus and Scutia pollen were 100% correctly classified, whilst samples from Myrtaceae spp. and Salix were 80 and 66% correctly classified, respectively. The use of PCA and LDA combined with pollen identification proved useful in characterizing honey samples from different botanical origins.
|Keywords: honey, Uruguay, principal component analysis, linear discriminant analysis, pollen analysis. |
|1 Instituto Nacional de Investigación Agropecuaria, Estación Experimental INIA La Estanzuela, Ruta 50-km 12, Colonia, Uruguay. E-mail: firstname.lastname@example.org |
2 The Australian Wine Research Institute, Waite Road, Glen Osmond, PO Box 197, Adelaide, Australia, 5064. Email: Daniel.Cozzolino@awri.com.au *Corresponding author.