Abstract
The paper presents practical utilization of an electronic nose prototype, based on the FIGARO semiconductor sensors, in fast classification of Polish honey types—acacia flower, linden flower, rape, buckwheat and honeydew ones. A set of thermostating modules of the prototype provided gradient temperature characteristics of barbotage-prepared gas mixtures and stable measurement conditions. Three chemometric data analysis methods were employed for the honey samples classification: principal component analysis (PCA), linear discriminant analysis (LDA) and cluster analysis (CA) with the furthest neighbour method. The investigation confirmed usefulness of this type of instrument in correct classification of all aforementioned honey types. In order to provide optimum measurement conditions during honey samples classification the following parameters were selected: volumetric flow rate of carrier gas—15 L/h, barbotage temperature—35 °C, time of sensor signal acquisition since barbotage process onset—60 s. Chemometric analysis allowed discrimination of three honey types using PCA and CA and all five honey types with LDA. The reproducibility of 96% of the results was within the range 4.9%–8.6% CV.
Highlights
Food safety and suitable quality of food products are fundamental issues that must be addressed at each stage of its production and distribution in order to avoid health and life hazards of potential consumers [1,2,3]
Depending on the chemometric method applied the prototype of electronic nose provided different classification capability with respect to honey of various botanical origins
The following measurement parameters were the optimum ones for the barbotage process, the electronic nose prototype used and for all three chemometric methods applied: sample volume—5 mL, volumetric flow rate of carrier gas—15 L/h, barbotage temperature—35 °C, time of sensor signal acquisition since barbotage process onset 60 s
Summary
Food safety and suitable quality of food products are fundamental issues that must be addressed at each stage of its production and distribution in order to avoid health and life hazards of potential consumers [1,2,3]. Headspace analysis can be a source of valuable information on the properties of particular food products [13,14,15,16,17,18]. Such an approach is frequently utilized in many food producing facilities. It takes advantage of sensory analysis, which exhibits numerous shortcomings due to the limitations of human senses [19,20,21,22]. That is why the authors have made an attempt to evaluate particular food product, honey, with a selected instrumental technique
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