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- Studies on honey from the Algarve in view of its valorizationPublication . A. Ulloa, P.; Brigas, Amadeu F.; Figueira, Ana C.Several studies were conducted with different Portuguese honey samples from South area (Algarve) in view of exploiting its properties and increasing the commercial value of some types of honey. Initially, the effects of honey storage for long periods were evaluated in terms of physicochemical parameters and bioactivity (Chapter 3) and it was concluded that after three years most of the properties of honey remained unchanged except for the freshness indicators, which were, as expected, reasonably far from the regulated values. Several commercial samples of honey with different floral origins were subjected to the conventional studies, including melissopalynology pollen analysis, physiochemical and biological (antioxidant properties) analysis. Honey from strawberry tree (Arbutus unedo L.), a typical plant in Algarve, was the focus of this study. This kind of honey has low acceptability by consumers probably because of unawareness of its existence and/or of its beneficial biological properties. Also, it may not be an obvious preference, due to its exquisite bitter taste, thus being locally called “bitter honey” (Chapter 4). Artisanal bitter honey was compared with other commercial honeys that are appreciated by Portuguese consumers (Chapter 5). This research consisted in the study of the physicochemical parameters, bioactive compounds and sensorial evaluation; done in comparison with sunflower (Helianthus annuus) honey, french lavender (Lavandula stoechas) honey, orange blossom (Citrus spp.) honey and commercial strawberry tree honey. Finally, in the last stage of the work (Chapter 6), new methods for determination of botanical origin of honey were explored as potential alternatives to the traditional analysis method (melissopalynological). These non-invasive techniques namely electronic tongue, UV-Vis spectroscopy and Vis-NIR spectroscopy, were used with the help of multivariate analysis (principal component analysis, PCA), for the interpretation of data’s obtained with above techniques. It is hoped that this research will represent an enrichment of knowledge on honey from the Algarve and, especially for Arbutus unedo honey, it has been demonstrated that it has the characteristics of similar gourmet honey from Italy existing, therefore, the potential of increasing its commercial value, which would also be advantageous for the interior region of the Algarve where, since the Arab occupation, the strawberry tree is abundant.
- Determination of the botanical origin of honey by sensor fusion of impedance e-tongue and optical spectroscopyPublication . Ulloa, P. A.; Guerra, Rui Manuel Farinha das Neves; Cavaco, A. M.; Costa, Ana M. Rosa da; Figueira, A.C.; Fernandes, A.The aim of this study was to discriminate four commercial brands of Portuguese honeys according to their botanical origin by sensor fusion of impedance electronic tongue (e-tongue) and optical spectroscopy (UV–Vis–NIR) assisted by Principal Component Analysis (PCA) and Cluster Analysis (CA). We have also introduced a new technique for variable selection through one-dimensional clustering which proved very useful for data fusion. The results were referenced against standard sample identification by classical melissopalynology analysis. Individual analysis of each technique showed that the e-tongue clearly outperformed the optical techniques. The electronic and optical spectra were fitted to analytical models and the model coefficients were used as new variables for PCA and CA. This approach has improved honey classification by the e-tongue but not by the optical methods. Data from the three techniques was then considered simultaneously. Simple concatenation of all matrices did not improve the classification results. Multi-way PCA (MPCA) proved to be a good option for data fusion yielding 100% classification success. Finally, a variable selection method based on one-dimensional clustering was used to define two new approaches to sensor fusion, and both yielded sample clusters even better defined than using MPCA. In this work we demonstrate for the first time the feasibility of sensor fusion of electronic and optical spectroscopy data and propose a new variable selection method that improved significantly the classification of the samples through multivariate statistical analysis.