A New Approach for Determination of the Botanical Origin of Monofloral Bee Honey, Combining Mineral Content, Physicochemical Parameters, and Self-Organizing Maps

From the Soil to the Wine-Elements' Migration in Monovarietal Bulgarian Wines

Bulgarian wines are renowned worldwide and serve as a symbol of the country. However, ensuring wine authenticity and establishing reliable methods for its assessment are critical challenges in wine quality control. This study investigates the migration of chemical elements within the soil/grape/wine system and utilizes the findings to develop a method for identifying specific elements capable of distinguishing the geographical origin of wine. Additionally, it explores the potential to determine its botanical origin. Thirty monovarietal Bulgarian wines, specifically produced for this study with precisely known geographical and botanical origins, were analyzed for 20 chemical elements. These included macroelements such as Al, B, Ba, Ca, Cu, Fe, K, Mg, Mn, Na, P, Sr, and Zn, as well as microelements like As, Cd, Co, Cr, Li, Ni, and Pb. The study encompassed white wines from Chardonnay, Muscat Ottonel, Sauvignon Blanc, Tamyanka, and Viognier varieties, as well as red wines from Egiodola, Broad-Leaved Melnik, Cabernet, Cabernet Franc, Cabernet Sauvignon, Marselan, Melnik, Merlot, Pinot Noir, and Syrah. The chemical composition was determined in soil extracts (using acetate and EDTA extract to represent the bioavailable fraction), vine leaves, primary musts, and raw wines before clarification and stabilization. Statistically significant correlation coefficients were calculated for the soil/leaves, soil/must, and must/wine systems, enabling an analysis of the migration of chemical elements from soil to wine and the concentration changes throughout the process. The results identified elemental descriptors capable of indicating the geographical origin of wine.

Graphical Discrimination of New Zealand Honey from International Honey Using Elemental Analysis

This study investigated the potential of utilising the elemental fingerprinting of honey to differentiate New Zealand (NZ) honey from that of international origin. Twenty elements were analysed by ICP-MS in 352 honeys from 34 various countries. Of these, 323 honeys (245 New Zealand honeys, 78 international) and two subsets of data (NZ and European origin, n = 306, and, NZ and Denmark/Germany, n = 280) were visualised using principal component analysis (PCA). For the NZ/Europe subset, 42.2% of data was explained in the first two principal components. Statistical classification rules were also derived using linear discriminant analysis (LDA) and decision tree analysis. Various combinations of elements were explored for classification, considering the effect of soil-derived elements and those from anthropogenic sources. A high degree of accuracy (at least 90%) for the characterisation of New Zealand honey was observed for all statistical models, showing the robustness of these analyses. When using decision tree analysis to distinguish New Zealand samples from international samples, a tree with five terminal nodes (using Cs, Ba and Rb) was created with 92.4% accuracy. This work has demonstrated that elemental fingerprints of honey are a promising tool for categorising New Zealand honey from other geographical locations.

Elemental Fingerprinting Combined with Machine Learning Techniques as a Powerful Tool for Geographical Discrimination of Honeys from Nearby Regions

Discrimination of honey based on geographical origin is a common fraudulent practice and is one of the most investigated topics in honey authentication. This research aims to discriminate honeys according to their geographical origin by combining elemental fingerprinting with machine-learning techniques. In particular, the main objective of this study is to distinguish the origin of unifloral and multifloral honeys produced in neighboring regions, such as Sardinia (Italy) and Spain. The elemental compositions of 247 honeys were determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The origins of honey were differentiated using Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Random Forest (RF). Compared to LDA, RF demonstrated greater stability and better classification performance. The best classification was based on geographical origin, achieving 90% accuracy using Na, Mg, Mn, Sr, Zn, Ce, Nd, Eu, and Tb as predictors.

Multi-Element Profile Characterization of Monofloral and Polyfloral Honey from Latvia

Honey is of scientific interest mainly due to its health-promoting and antibacterial properties, which are also associated with its floral origins. However, the methods for confirming honey floral origins are quite limited and require improvements. One method suggested in the search for a multi-method approach to evaluating the floral origins of Latvian honey is inductively coupled plasma mass spectrometry (ICP-MS). This study investigated the multi-element profile of 83 honey samples of well-specified floral origins. The main findings included using Ba, Ca, Cs, Fe, and Rb as indicator elements for heather honey. The chemometric evaluation supported the use of ICP-MS for distinguishing heather honey from other types of honey. The Latvian polyfloral honey multi-element profile was defined and compared to honey samples with other geographical origins. Additionally, the multi-element profiles of buckwheat, clover, and polyfloral honey proteins were investigated to clarify whether the majority of elements were bound with proteins or not. Preliminary results indicated that Ca, K, Mg, Mn, Na, and Sr were mainly found in non-protein-bound forms, while the majority of Al, Cu, Ni, and Zn were in the form of large chemical structures (>10 kDa).

Identification of Seasonal Honey Based on Quantitative Detection of Typical Pollen DNA

Monofloral honey is produced from the nectar of a single predominant botanical species in a particular season and has certain unique properties. Valuable monofloral honey produced in a particular season with unique properties is often targeted for adulteration. Herein, a method for the identification of monofloral honey and determination of its production season was developed. Major nectar plants, including Prunus sp., Robinia pseudoacacia, Castanea sp., and Kalopanax sp., were selected to evaluate the honey produced between April and July in South Korea. Results showed that the highest amount of DNA from each plant was detected in the corresponding flowering season. The pollens tended to accumulate in the honeycomb after the flowering season. The accumulations result in an increase in the diversity of pollen detected in honey. Additionally, DNA quantity of each plant decreased in the samples as the number of plant DNA types increased from May to July. Moreover, the authenticity of the commercial monofloral honey samples showed only cherry blossom honey was found authentic, which exhibited the expected high amount of Prunus sp. DNA. This molecular tool is expected to be useful in verifying the origin of monofloral honey and its production season.

Multi-Elemental Analysis as a Tool to Ascertain the Safety and the Origin of Beehive Products: Development, Validation, and Application of an ICP-MS Method on Four Unifloral Honeys Produced in Sardinia, Italy

Despite unifloral honeys from Sardinia, Italy, being appreciated worldwide for their peculiar organoleptic features, their elemental signature has only partly been investigated. Hence, the principal aim of this study was to measure the concentration of trace and toxic elements (i.e., Ag, As, Ba, Be, Bi, Cd, Co, Cr, Cu, Fe, Hg, Li, Mn, Mo, Ni, Pb, Sb, Sn, Sr, Te, Tl, V, and Zn) in four unifloral honeys produced in Sardinia. For this purpose, an original ICP-MS method was developed, fully validated, and applied on unifloral honeys from asphodel, eucalyptus, strawberry tree, and thistle. Particular attention was paid to the method’s development: factorial design was applied for the optimization of the acid microwave digestion, whereas the instrumental parameters were tuned to minimize the polyatomic interferences. Most of the analytes’ concentration ranged between the relevant LoDs and few mg kg⁻¹, while toxic elements were present in negligible amounts. The elemental signatures of asphodel and thistle honeys were measured for the first time, whereas those of eucalyptus and strawberry tree honeys suggested a geographical differentiation if compared with the literature. Chemometric analysis allowed for the botanical discrimination of honeys through their elemental signature, whereas linear discriminant analysis provided an accuracy level of 87.1%.