Assessment of the In Vivo and In Vitro Release of Chemical Compounds from Vespa velutina.

Vespa velutina has been rapidly expanding throughout Galicia since 2012. It is causing human health risks and well-known losses in the beekeeping sector. Control methods are scarce, unspecific, and ineffective. Semiochemicals are insect-derived chemicals that play a role in communication and they could be used an integrated pest management tool alternative to conventional pesticides. A previous determination of the organic chemical profile should be the first step in the study of these semiochemicals. HS-SPME in living individuals and the sting apparatus extraction followed by GC-MS spectrometry were combined to extract a possible profile of these compounds in 43 hornets from Galicia. The identified compounds were hydrocarbons, ketones, terpenes, and fatty acid, and fatty acid esters. Nonanal aldehyde appeared in important concentrations in living individuals. While pentadecane, 8-hexyl- and ethyl oleate were mainly extracted from the venom apparatus. Ketones 2-nonanone, 2-undecanone and 7-nonen-2-one, 4,8-dimethyl- were identified by both procedures, as was 1,7-Nonadiene, 4,8-dimethyl-. Some compounds were detected for the first time in V. velutina such as naphthalene, 1,6-dimethyl-4-(1-methylethyl). The chemical profile by caste was also characterized.

Description of the volatile fraction of Erica honey from the northwest of the Iberian Peninsula.

Heather honey is highly appreciated by consumers for its sensorial profile, which varies depending on the flora used by the honeybees. Volatile compounds contribute to these qualities. Characterisation of the volatile profile related to the botanical origin is of great interest for the standardization of unifloral honey. For this reason, 33 heather honey samples from northwest of the Iberian Peninsula were analysed by headspace solid-phase microextraction (HS-SPME) to identify the key volatile compounds in this type of honey. The aim of this research was to provide a descriptive analysis of these compounds, and to find whether there is any relationship with the main Erica species. A total of 58 volatile organic compounds were found, with hotrienol, phenylacetaldehyde, and cis-linalool being the most abundant. A principal component analysis and Spearman's rank correlation showed the homogeneity of the volatile profile in the samples, and their close relationship with the main pollen types.

Differentiation of oak honeydew and chestnut honeys from the same geographical origin using chemometric methods.

Oak honeydew and chestnut honeys often share the same production area in Atlantic landscapes. Consequently these honeys have common physicochemical properties and pollen composition, making their differentiation by routine methods, a difficult task. The increase in the demands of consumers for clear honey labelling, identifying floral make-ups and the substantial health properties of both honey types, make it necessary to improve methods to differentiate the honeys. Statistical multivariate techniques were used to study the differences in the physicochemical composition and pollen spectra between chestnut honey and oak honeydew honey. Palynological analysis, moisture, pH, electrical conductivity, hydroxymethylfurfural, diastase number, colour, phenolic content, minerals and sugars were used for this purpose. The variables that had more weight in the differentiation by principal component analysis were Castanea, Cytisus type, CIELab coordinates (a* and L), RSA, Mg and trehalose; 97.6% of the honey samples were correctly classified by linear discriminant analysis.

Near infrared spectroscopy applied to the rapid prediction of the floral origin and mineral content of honeys.

Consumers demand to know the floral origins of honeys. Therefore, the use of simple and reliable techniques for differentiating among honeys by their origins is necessary. Multivariate statistical techniques and near infrared spectroscopy applied to palynological and mineral characteristics make it possible to differentiate among the types of honey collected from Northwestern Spain. Prediction models using a modified partial least squares regression for the main pollen types (Castanea, Eucalyptus, Rubus and Erica) in honeys and their mineral composition (potassium, calcium, magnesium and phosphorus) were established. Good multiple correlation coefficients (higher than 0.700) and acceptable standard errors of cross-validation were obtained. The ratio performance deviation exhibited a good prediction capacity for Rubus pollen and for Castanea pollen, whereas for minerals, for Eucalyptus pollen and for Erica pollen the ratio performance deviation was excellent. Near infrared spectroscopy was established as a rapid and effective tool to obtain equations of prediction that contribute to the honey typification.