HS-SPME-GC-MS Analysis of the Volatile Composition of Italian Honey for Its Characterization and Authentication Using the Genetic Algorithm
Carlotta Breschi,
Francesca Ieri,
Luca Calamai,
Alessandra Miele,
Silvia D’Agostino,
Fabrizio Melani,
Bruno Zanoni,
Nadia Mulinacci,
Lorenzo Cecchi
Affiliations
Carlotta Breschi
Department of Neurofarba, Nutraceutical Section, University of Florence, Via Ugo Schiff 6, Sesto Fiorentino, 50019 Florence, Italy
Francesca Ieri
National Research Council of Italy (CNR), Institute of Bioscience and BioResources (IBBR), Sesto Fiorentino, 50019 Florence, Italy
Luca Calamai
DAGRI—Department of Agriculture, Food, Environment and Forestry, Food Science and Technology Division, University of Florence, Piazzale delle Cascine 18, 50144 Florence, Italy
Alessandra Miele
DAGRI—Department of Agriculture, Food, Environment and Forestry, Food Science and Technology Division, University of Florence, Piazzale delle Cascine 18, 50144 Florence, Italy
Silvia D’Agostino
DAGRI—Department of Agriculture, Food, Environment and Forestry, Food Science and Technology Division, University of Florence, Piazzale delle Cascine 18, 50144 Florence, Italy
Fabrizio Melani
Department of Neurofarba, Nutraceutical Section, University of Florence, Via Ugo Schiff 6, Sesto Fiorentino, 50019 Florence, Italy
Bruno Zanoni
DAGRI—Department of Agriculture, Food, Environment and Forestry, Food Science and Technology Division, University of Florence, Piazzale delle Cascine 18, 50144 Florence, Italy
Nadia Mulinacci
Department of Neurofarba, Nutraceutical Section, University of Florence, Via Ugo Schiff 6, Sesto Fiorentino, 50019 Florence, Italy
Lorenzo Cecchi
DAGRI—Department of Agriculture, Food, Environment and Forestry, Food Science and Technology Division, University of Florence, Piazzale delle Cascine 18, 50144 Florence, Italy
Honey’s chemical and sensory characteristics depend on several factors, including its botanical and geographic origins. The consumers’ increasing interest in monofloral honey and honey with a clear indication of geographic origin make these types of honey susceptible to fraud. The aim was to propose an original chemometric approach for honey’s botanical and geographic authentication purposes. The volatile fraction of almost 100 Italian honey samples (4 out of which are from Greece) from different regions and botanical origins was characterized using HS-SPME-GC-MS; the obtained data were combined for the first time with a genetic algorithm to provide a model for the simultaneous authentication of the botanical and geographic origins of the honey samples. A total of 212 volatile compounds were tentatively identified; strawberry tree honeys were those with the greatest total content (i.e., 4829.2 ng/g). A greater variability in the VOCs’ content was pointed out for botanical than for geographic origin. The genetic algorithm obtained a 100% correct classification for acacia and eucalyptus honeys, while worst results were achieved for honeydew (75%) and wildflower (60%) honeys; concerning geographic authentication, the best results were for Tuscany (92.7%). The original combination of HS-SPME-GC-MS analysis and a genetic algorithm is therefore proposed as a promising tool for honey authentication purposes.
