The objective of this study was to screen the antibacterial and antioxidant activity of thirty nine honey samples from Finland, Sweden, Norway and Denmark. Their physicochemical properties were analysed, antioxidant activity was evaluated by DPPH assay and antibacterial activity against Pseudomonas aeruginosa and Staphylococcus aureus was assessed by microdilution assay. The honey samples obtained were buckwheat, caraway, clover, dandelion, fireweed, heather, lime tree, lingonberry, rape, raspberry, sweet clover, willow, mire, honeydew and polyfloral. Eleven honey samples showed high antioxidant activity. With 15% honey dilution, three unifloral honeys had over 85% inhibition against growth of P. aeruginosa and ten honey samples against S. aureus. The buckwheat, raspberry and honeydew honeys showed the highest antibacterial and antioxidant activity. An unexpectedly high amount of methylglyoxal was found in mire and forest honeys. Some phenolic compounds are shown to be plant species-specific floral markers due to their appearance in specific unifloral honey samples.

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The availability of light within the tree canopy affects various leaf traits and leaf reflectance. We determined the leaf reflectance variation from 400 nm to 2500 nm among three canopy layers and cardinal directions of three genetically identical cloned silver birches growing at the same common garden site. The variation in the canopy layer was evident in the principal component analysis (PCA), and the influential wavelengths responsible for variation were identified using the variable importance in projection (VIP) based on partial least squares discriminant analysis (PLS-DA). Leaf traits, such as chlorophyll, nitrogen, dry weight, and specific leaf area (SLA), also showed significant variation among the canopy layers. We found a shift in the red edge inflection point (REIP) for the canopy layers. The canopy layers contribute to the variability in the reflectance indices. We conclude that the largest variation was among the canopy layers, whereas the differences among individual trees to the leaf reflectance were relatively small. This implies that within-tree variation due to the canopy layer should be taken into account in the estimation of intraspecific variation in the canopy reflectance.

We present a new autofluorescence-imaging method for bone analysis. This method, based on the autofluorescence of bone, provides color images in microscopic scale. The color images are created from three monochrome images acquired with optimal excitation-and emission-wavelengths combinations. The choice of these combinations were determined from the study of two-dimensional distributions of bone-features-bispectral autofluorescence in the visible-and ultraviolet-spectral range. We demonstrate that main-bone features visualized with MG-staining method can also be visualized in the autofluorescence-color image. Furthermore, the autofluorescence-color image presents features hardly distinguished in a histological-bone section.

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Performance of recently proposed multispectral imaging system for fast acquisition of two dimensional distribution of reflectance spectrum is experimentally studied. The system operation is based on a subspace vector model in which any reflectance spectrum is described in the compressed form as a linear combination of few spectral functions. A key element of the proposed system is a light source which includes a set of light-emitting diodes with different central wavelengths. The light source provides illumination of the object by fast-switchable sequences of spectral bands whose energy distributions are proportional to mutually orthogonal spectral functions (calculated in-advance). Object illumination is synchronized with a monochrome digital camera. The system allows us fast acquisition of reflectance spectra in a compressed form with high spatial resolution. A model of the system calibration by using standard white matte sample is proposed. Reconstruction of the reflectance spectrum from the compressed data collected after illumination of selected color samples from the Munsell book by 7 mutually orthogonal spectral functions is demonstrated. Parameters of the system, which affect the accuracy of the spectrum reconstruction, are analyzed and discussed.

Dental lesions such as calculus and initial caries can be challenging to distinguish in RGB colour images due to a poor contrast. The visibility of dental lesions can be improved by using spectrally optimised light sources. In this paper, the optimal spectral shapes of illuminants for the visibility enhancement of various lesions are determined. These optimal spectral shapes are determined computationally by using spectral images captured from extracted human teeth, and numerical optimisation.

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