Comparative Study of Several Machine Learning Algorithms for Classification of Unifloral Honeys.

ABSTRACT: Unifloral honeys are highly demanded by honey consumers, especially in Europe. To ensure that a honey belongs to a very appreciated botanical class, the classical methodology is palynological analysis to identify and count pollen grains. Highly trained personnel are needed to perform this task, which complicates the characterization of honey botanical origins. Organoleptic assessment of honey by expert personnel helps to confirm such classification. In this study, the ability of different machine learning (ML) algorithms to correctly classify seven types of Spanish honeys of single botanical origins (rosemary, citrus, lavender, sunflower, eucalyptus, heather and forest honeydew) was investigated comparatively. The botanical origin of the samples was ascertained by pollen analysis complemen

SUBMITTER: Mateo F 

PROVIDER: S-EPMC8303996 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature