Volatile metabolites or pollen characteristics as regional markers of monofloral thyme honey?

Machine Learning Algorithms Applied to Semi-Quantitative Data of the Volatilome of Citrus and Other Nectar Honeys with the Use of HS-SPME/GC-MS Analysis, Lead to a New Index of Geographical Origin Authentication

The scope of the current study was to monitor if semi-quantitative data of volatile compounds (volatilome) of citrus honey (ch) produced in different countries could potentially lead to a new index of citrus honey authentication using specific ratios of the identified volatile compounds in combination with machine learning algorithms. In this context, the semi-quantitative data of the volatilome of 38 citrus honey samples from Egypt, Morocco, Greece, and Spain (determined by headspace solid phase microextraction coupled to gas chromatography mass spectrometry (HS-SPME/GC-MS)) was subjected to supervised and unsupervised chemometrics. Results showed that honey samples could be classified according to the geographical origin based on specific volatile compounds. Data were further evaluated with additional nectar honey samples introduced in the multivariate statistical analysis model and the classification results were not affected. Specific volatile compounds contributed to the discrimination of citrus honey in different amounts according to geographical origin. These were lilac aldehyde D, dill ether, 2-methylbutanal, heptane, benzaldehyde, α,4-dimethyl-3-cyclohexene-1-acetaldehyde, and herboxide (isomer II). The numerical data of these volatile compounds was summed up and divided by the total semi-quantitative volatile content (R_ch, Karabagias-Nayik index) of citrus honey, according to geographical origin. Egyptian citrus honey had a value of R_ch = 0.35, Moroccan citrus honey had a value of R_ch = 0.29, Greek citrus honey had a value of R_ch = 0.04, and Spanish citrus honey had a value of R_ch = 0.27, leading to a new hypothesis and a complementary index for the control of citrus honey authentication.

Response Surface Methodology to Optimize the Isolation of Dominant Volatile Compounds from Monofloral Greek Thyme Honey Using SPME-GC-MS

This study aimed at an experimental design of response surface methodology (RSM) in the optimization of the dominant volatile fraction of Greek thyme honey using solid-phase microextraction (SPME) and analyzed by gas chromatography-mass spectrometry (GC-MS). For this purpose, a multiple response optimization was employed using desirability functions, which demand a search for optimal conditions for a set of responses simultaneously. A test set of eighty thyme honey samples were analyzed under the optimum conditions for validation of the proposed model. The optimized combination of isolation conditions was the temperature (60 °C), equilibration time (15 min), extraction time (30 min), magnetic stirrer speed (700 rpm), sample volume (6 mL), water: honey ratio (1:3 v/w) with total desirability over 0.50. It was found that the magnetic stirrer speed, which has not been evaluated before, had a positive effect, especially in combination with other factors. The above-developed methodology proved to be effective in the optimization of isolation of specific volatile compounds from a difficult matrix, like honey. This study could be a good basis for the development of novel RSM for other monofloral honey samples.

Honey Volatiles as a Fingerprint for Botanical Origin-A Review on their Occurrence on Monofloral Honeys

Honeys have specific organoleptic characteristics, with nutritional and health benefits, being highly appreciated by consumers, not only in food but also in the pharmaceutical and cosmetic industries. Honey composition varies between regions according to the surrounding flora, enabling its characterization by source or type. Monofloral honeys may reach higher market values than multifloral ones. Honey's aroma is very specific, resulting from the combination of volatile compounds present in low concentrations. The authentication of honey's complex matrix, according to its botanical and/or geographical origin, represents a challenge nowadays, due to the different sorts of adulteration that may occur, leading to the search for reliable marker compounds for the different monofloral honeys. The existing information on the volatiles of monofloral honeys is scarce and disperse. In this review, twenty monofloral honeys and honeydews, from acacia, buckwheat, chestnut, clover, cotton, dandelion, eucalyptus, fir tree, heather, lavender, lime tree, orange, pine, rape, raspberry, rhododendron, rosemary, strawberry tree, sunflower and thyme, were selected for volatile comparison purposes. Taking into consideration the country of origin, the technique of isolation and analysis, the five main volatiles from each of the honeys are compared. Whereas some compounds were found in several types of monofloral honey, and thus not considered good volatile markers, some monofloral honeys revealed characteristic volatile compounds independently of their provenance.

Valorization of Prickly Pear Juice Geographical Origin Based on Mineral and Volatile Compound Contents Using LDA

In the present work the mineral content and volatile profile of prickly pear juice prepared from wild cultivars was investigated. Fruits used in the study originated from three areas of the Peloponnese Peninsula. Twenty-five macro- and micro-minerals (K, Na, P, Ca, Mg, Al, B, Ba, Be, Co, Cr, Cu, Fe, Li, Mn, Mo, Ni, Sb, Se, Si, Sn, Ti, Tl, V, Zn) were determined using inductively coupled plasma atomic emission spectroscopy (ICP-OES). Furthermore, analysis of the mineral content of soil samples with ICP-OES showed a perfect correlation with those of fruit juices. Volatile compounds (alcohols, aldehydes, hydrocarbons, terpenoids, and others) were identified using an optimized headspace solid phase microextraction coupled to gas chromatography mass spectrometry (HS-SPME/GC-MS) method. Multivariate analysis showed significant differences (p < 0.05) among the investigated parameters with respect to juice geographical origin. Prickly pear juice samples were classified according to geographical origin by 85.7% and 88.9% using 7 minerals and 21 volatile compounds, respectively.