Discrimination of honeys using colorimetric sensor arrays, sensory analysis and gas chromatography techniques

• A low-cost and simple colorimetric sensor array was fabricated.
• This technique was used to discriminate honey of different botanical origin.
• Characteristic sensory profile was determined using descriptive sensory analysis.
• GC–MS was used to identify the volatile compounds in different honey samples.
• The relationship between sensory profiles and the GC–MS data was modelled by partial least squares regression.

Aroma profiles of six honey varieties of different botanical origins were investigated using colorimetric sensor array, gas chromatography–mass spectrometry (GC–MS) and descriptive sensory analysis. Fifty-eight aroma compounds were identified, including 2 norisoprenoids, 5 hydrocarbons, 4 terpenes, 6 phenols, 7 ketones, 9 acids, 12 aldehydes and 13 alcohols. Twenty abundant or active compounds were chosen as key compounds to characterize honey aroma. Discrimination of the honeys was subsequently implemented using multivariate analysis, including hierarchical clustering analysis (HCA) and principal component analysis (PCA). Honeys of the same botanical origin were grouped together in the PCA score plot and HCA dendrogram. SPME-GC/MS and colorimetric sensor array were able to discriminate the honeys effectively with the advantages of being rapid, simple and low-cost. Moreover, partial least squares regression (PLSR) was applied to indicate the relationship between sensory descriptors and aroma compounds.