Background: The characterization of three types of Marche (Italy) honeys (Acacia, Multifloral, Honeydew) was carried out on the basis of the their quality parameters (pH, sugar content, humidity) and mineral content (Na, K, Ca, Mg, Cu, Fe, and Mn). Pattern recognition methods such as principal components analysis (PCA) and linear discriminant analysis (LDA) were performed in order to classify honey samples whose botanical origins were different, and identify the most discriminant parameters. Lastly, using ANOVA and correlations for all parameters, significant differences between diverse types of honey were examined.
Results: Most of the samples' water content showed good maturity (98%) whilst pH values were in the range 3.50 - 4.21 confirming the good quality of the honeys analysed. Potassium was quantitatively the most relevant mineral (mean = 643 ppm), accounting for 79% of the total mineral content. The Ca, Na and Mg contents account for 14, 3 and 3% of the total mineral content respectively, while other minerals (Cu, Mn, Fe) were present at very low levels. PCA explained 75% or more of the variance with the first two PC variables. The variables with higher discrimination power according to the multivariate statistical procedure were Mg and pH. On the other hand, all samples of acacia and honeydew, and more than 90% of samples of multifloral type have been correctly classified using the LDA. ANOVA shows significant differences between diverse floral origins for all variables except sugar, moisture and Fe.
Conclusion: In general, the analytical results obtained for the Marche honeys indicate the products' high quality. The determination of physicochemical parameters and mineral content in combination with modern statistical techniques can be a useful tool for honey classification.
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http://dx.doi.org/10.1186/1752-153X-1-14 | DOI Listing |
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College of Food Science and Engineering, Gansu Agricultural University, Lanzhou 730070, China.
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The cross-linking process of collagen is one of the more important ways to improve the mineralization ability of collagen. However, the regulatory effect of dynamic cross-linking on biomineralization in vitro remains unclear. Dynamic-cross-linked mineralized collagen under different cross-linking processes, according to the process of cross-linking and mineralization of natural bone, was prepared in this study.
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Centre for Functional Ecology: Science for People & Planet, Marine Resources, Conservation and Technology-Marine Algae Lab, Department of Life Sciences, University of Coimbra, 3000-456 Coimbra, Portugal.
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View Article and Find Full Text PDFBiosensors (Basel)
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In this study, 3,4-diaminobenzoic acid (DABA) was introduced into the porphyrin metal-organic framework (PCN-224) for the first time to prepare a ratiometric fluorescent probe (PCN-224-DABA) to quantitatively detect ferric iron (Fe(III)) and selenium (IV) (Se(IV)). The fluorescence attributed to the DABA of PCN-224-DABA at 345 nm can be selectively quenched by Fe(III) and Se(IV), but the fluorescence emission peak attributed to tetrakis (4-carboxyphenyl) porphyrin (TCPP) at 475 nm will not be disturbed. Therefore, the ratio of I/I with an excitation wavelength of 270 nm can be designed to determine Fe(III) and Se(IV).
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