Maria Plessi

Detection of Honey Adulteration by Sugar Syrups Using One-Dimensional and Two-Dimensional High-Resolution Nuclear Magnetic Resonance

The importance of honey adulteration detection has recently increased owing to the limited production levels in recent years and the relative high price of honey; therefore, this illegal practice has become more and more attractive to producers. Hence, the need has arisen for more effective analytical methods aiming at detecting honey adulteration. The present research presents an effective method to detect adulteration in honey falsified by intentional addition of different concentrations of commercial sugar syrups, using one-dimensional (1D) and two-dimensional (2D) nuclear magnetic resonance (NMR) coupled with multivariate statistical analysis. Sixty-three authentic and 63 adulterated honey samples were analyzed. To prepare adulterated honeys, seven different sugar syrups normally used for nutrition of bees were used. The best discriminant model was obtained by 1D spectra, and leave-one-out cross-validation showed a predictive capacity of 95.2%. 2D NMR also furnished acceptable results (cross-validation correct classification 90.5%), although the (1)H NMR sequence is preferable because it is the simplest and fastest NMR technique.

Classification of Italian honeys by 2D HR-NMR.

The importance of honey has been recently increased because of its nutrient and therapeutic effects, but the adulteration of honey in terms of botanical origin has increased, too. The floral origin of honeys is usually determined using melisso-palynological analysis and organoleptic characteristics, but the application of these techniques requires some expertise. A number of papers have confirmed the possibility of characterizing honey samples by selected chemical parameters. In this study high-resolution nuclear magnetic resonance (HR-NMR) and multivariate statistical analysis methods were used to identify and classify honeys of five different floral sources. The 71 honey samples (robinia, chestnut, citrus, eucalyptus, polyfloral) were analyzed by HR-NMR using both 1H NMR and heteronuclear multiple bond correlation spectroscopy (HMBC). Spectral data were analyzed by application of unsupervised and supervised pattern recognition and multivariate statistical techniques such as principal component analysis (PCA) and general discriminant analysis (GDA). The use of 1H-(13)C HMBC coupled with appropriate statistical analysis seems to be an efficient technique for the classification of honeys.

Separation by solid phase extraction and quantification by reverse phase HPLC of sulforaphane in broccoli

Abstract The separation and quantification of sulforaphane [1-isothiocyanato-4-(methyl-sulfinyl)-butane] from the florets, stalks and leaves of broccoli is described. The procedure uses solvent extraction, followed by purification of extracts using solid phase extraction (SPE) and reverse phase HPLC analysis. The HPLC method is compared with a spectrophotometric assay. To obtain information about the usefulness of acid hydrolysis of glucosinolates, the florets were left to autolyze at room temperature or were treated with concentrated hydrochloric acid, then analysed. The method proves reliable and reproducible as regards both SPE purification and chromatographic determination. Quantities of sulforaphane were found in the florets, stalks and leaves. The highest content of sulforaphane (110 μgg−1) was found in the leaves.

Application of one- and two-dimensional NMR spectroscopy for the characterization of Protected Designation of Origin Lambrusco wines of Modena.

Lambrusco is a Protected Designation of Origin (PDO) red wine of Modena (Italy) produced according to the production regulation (Decreto Ministeriale (DM) July 27, 2009; GU no. 184-187-188, 13/08/2009). Here the use of (1)H NMR spectroscopy as molecular fingerprints of several PDO Lambrusco wines was proposed to serve as indicators of authenticity and quality control. Application of partial least squares discriminant analysis (PLS-DA) revealed a good varietal discrimination by analyzing the low-frequency spectral region. This model explains 68.8% of the variance for the Y vector (classification factor: varietal source). In particular, the signals of 2,3-butanediol, lactic, succinic and malic acids, and threonine were found to be the most statistically significant variables in the model. These findings seem to be very promising in the attempt to extend the study to geographical discrimination.

Chemical and Functional Characterization of Italian Propolis Obtained by Different Harvesting Methods

The composition and antioxidant activity of Italian poplar propolis obtained using three harvesting methods and extracted with different solvents were evaluated. Waxes, balsams, and resins contents were determined. Flavones and flavonols, flavanones and dihydroflavonols, and total phenolics were also analyzed. To characterize the phenolic composition, the presence of 15 compounds was verified through HPLC-MS/MS. The antioxidant activity was evaluated through 1,1-diphenyl-2-picrylhydrazyl radical and reducing power assays. The ability of propolis to inhibit lipid oxidation was monitored by analyzing hydroperoxide and TBARS formation in lipids incorporated into an oil-in-water (O/W) emulsion. Acetone shows the highest extraction capacity. Wedge propolis has the highest concentration of active phenolic compounds (TP = 359.1 ± 16.3 GAEs/g; TFF = 5.83 ± 0.42%; TFD = 7.34 ± 1.8%) and seems to be the most promising for obtaining high-value propolis more suitable to prepare high-quality dietary supplements (TBARS = 0.012 ± 0.009 mmol std/g; RP = 0.77 ± 0.07 TEs/g).

Chemical composition of Italian propolis of different ecoregional origin

The aim of this work was studying and identifying the main physicochemical properties and active constituents of Italian propolis derived from resident hives throughout the peninsula. The data, potentially useful to establish important propolis quality criteria, were compared to those typical of poplar type propolis and used to build a classification model to link the propolis characteristics to its ecoregion of origin. HPLC-ESI-TQ MS was used to quantify 21 phenolic compounds in propolis extracts. Considering the bioactive substances and the antioxidant activity, statistically significant characteristics can distinguish propolis from the considered Italian ecoregions: Mediterranean and temperate division and, due to the high presence of poplar trees, the Po plain province as part of temperate division. Chrysin is the most abundant flavonoid in all the samples followed by galangin and pinocembrin. Regarding phenolic acids the samples from temperate and Mediterranean ecoregions are characterized by high amount of ferulic and isoferulic acids. Composición química del propóleos italiano de diferente origen ecorregional El objetivo de este trabajo fue el estudio e identificación de las principales propiedades fisicoquímicas y componentes activos del propóleos italiano derivados de las colmenas residentes en toda la península. Los datos, potencialmente útiles para establecer importantes criterios de calidad del propóleos, se compararon con los típicos de los álamos y se utilizaron para construir un modelo de clasificación que vinculara las características del propóleos con su ecorregión de origen. Se utilizó HPLC-ESI-TQ MS para cuantificar veintiún compuestos fenólicos en extractos de propóleos. Considerando las sustancias bioactivas y la actividad antioxidante, las características estadísticamente significativas pueden distinguir al propóleos de las ecorregiones italianas consideradas: división mediterránea y templada y, debido a la alta presencia de álamos, la provincia de la llanura del Po como parte de la división templada. La crisina es el flavonoide más abundante en todas las muestras, seguido de la galangina y la pinocembrina. En cuanto a los ácidos fenólicos, las muestras de las ecorregiones templadas y mediterráneas se caracterizan por una elevada cantidad de ácidos ferúlicos e isoferúlicos.

Novel 2D-NMR Approach for the Classification of Balsamic Vinegars of Modena

The aim of this work is to evaluate the possibility of using 2D-NMR for the construction of classification models for balsamic vinegars of Modena. The goal was to obtain an indirect indicator of authenticity and a quality control tool. The spectral data were analyzed by chemometric methods, aiming to discriminate the samples in relation to their origin. Application of general discriminant analysis (GDA) revealed a good discrimination; the two obtained models explained 83.9% and 97.3% of the total variance with a predictive capacity of 98.6% and 98.4%, respectively. The signals of 5-HMF, β-glucose, 2,3-butanediol, 6-acetyl glucose, and different aliphatic signals of sugars were the most significant variables. These results are very promising for giving an important contribution in quality control and characterization of such very valuable foods.