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The sensory-chemical profiles of Finnish honeys (labeled as buckwheat, cloudberry-bog, lingonberry, sweet clover, willowherb and multifloral honeys) were investigated using a multi-analytical approach. The sensory test (untrained panel, n = 62) was based on scaling and check-all-that-apply (CATA) methods accompanied with questions on preference and usage of honey. The results were correlated with corresponding profiles of odor-active compounds, determined using gas chromatography coupled with mass spectrometry/olfactometry (GC–MS/O). Botanical origins and chemical compositions including sugars were evaluated using NMR spectroscopy. A total of 73 odor-active compounds were listed based on GC–O. Sweet and mild honeys with familiar sensory properties were preferred by the panelists (PCA, R2X(1) = 0.7) while buckwheat and cloudberry-bog honeys with strong odor, flavor and color were regarded as unfamiliar and unpleasant. The data will give the honey industry novel information on honey properties in relation to the botanical origin, and consumer preference.

A lot of research has been conducted in correlating the sensory properties of food with different analytical measurements in recent years. Various statistical methods have been used in order to get the most reliable results and to create prediction models with high statistical performance. The current review summarises the latest practices in the field of correlating attributes from sensory analysis with volatile data obtained by gas chromatographic analysis. The review includes the origin of the data, different pre-processing and variable selection methods and finally statistical methods of analysis and validation. Partial least squares regression analysis appears as the most commonly used statistical method in the area. The main shortcomings were identified in the steps of pre-processing, variable selection and also validation of models that have not gained enough attention. As the association between volatiles and sensory perception is often nonlinear, future studies should test the application of different nonlinear techniques.

The aroma profiles of thirteen different honey samples from four botanical origins: heather (Calluna vulgaris), raspberry (Rubus idaeus), rape (Brassica napus), alder buckthorn (Frangula alnus) and the blossoms of the four corresponding flowers were investigated to find odour-active compounds exclusively representing specific honeys based on odour-active compounds from the blossoms. Gas-chromatography-mass spectrometry (GC-MS) and gas-chromatography-olfactometry were used to determine and identify the odour-active compounds. Data was analysed using agglomerative hierarchical clustering and correspondence analysis. Honeys from the same botanical origin clustered together; however, none of the identified compounds were exclusive to a particular honey/blossom combination. Heather honey had the flavour profile most different to the others. Isophorone and 2-methylbutyric acid were found only in heather honeys. Heather honey was characterised by having more "sweet" and "candy-like" notes, raspberry honeys had more "green" notes, while alder buckthorn had more "honey" and "floral" notes.