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

The Contribution of Botanical Origin to the Physicochemical and Antioxidant Properties of Algerian Honeys

Honeys from different regions of Algeria were analyzed to determine their pollen characteristics and physicochemical properties (humidity, pH, electrical conductivity, diastase content, color, phenols, flavonoids and antioxidant activity). The antioxidant activity was investigated using the free radical scavenging and Ferric reducing/antioxidant power assays. The melissopalynological analysis revealed 129 pollen types from 53 botanical families. The pollen types found as dominant were Coriandrum, Bupleurum, Brassica napus type, Hedysarum coronarium, Ceratonia siliqua, Eucalyptus, Peganum harmala, Ziziphus lotus and Tamarix. Principal component analysis and cluster analysis were used to analyze significant relationships between the physicochemical variables and the botanical origin of the honeys and establish groupings based on the similarities of their physicochemical and antioxidant properties. The results showed that Ceratonia siliqua, Eucalyptus, Arbutus and honeydew honeys had a higher antioxidant contribution and higher phenolic and flavonoid contents than the rest of the honeys. In addition, the contributions of Mediterranean vegetation such as Myrtus and Phyllirea angustifolia were significant in this honey group. This paper demonstrates the diverse botanical variability for honey production in Algeria. However, there is a gap in its characterization based on its botanical origin. Therefore, these studies contribute positively to the needs of the beekeeping sector and the commercial valorization of the country's honey.

Honey Origin Authentication via Mineral Profiling Combined with Chemometric Approaches

In the present study, the potential of elemental analysis combined with statistical tools to identify honey origin was evaluated by mineral characterization of 173 honeys of 13 floral types (acacia, fir, spruce, linden, chestnut, lavender, coriander, thistle, honeydew, rosemary, sage, euphorbia and ziziphus plant species) collected from five geographical regions (Slovenia, Croatia, Bulgaria, Turkey, and Morocco). The objective of the study was to accurately and reliably differentiate the mineral composition among honey varieties. The aim was to establish traceability, to ensure product authenticity and to improve quality control measures within the honey industry. For this purpose, 18 major, minor and trace elements were quantified using microwave digestion, followed by ICP-MS measurement. Statistical evaluation of elemental concentration was undertaken using principal component analysis (PCA) to distinguish honey floral types. The research give light on the specific elements that can serve as indicators for determining the geographical and botanical source of honey. Our findings indicate that certain elements, such as Mn, K, and Ca, are primarily influenced by the type of pollen present in the honey, making them indicative of the floral source. On the other hand, levels of Na, Mg, and Fe were found to be more strongly influenced by environmental factors and can be considered as markers of geographical origin. One novel aspect of this research is the exploration of the relationship between honey minerals and honey botanical source. This was achieved through the analysis of chestnut tree samples and a subsequent comparison with the composition of chestnut honey.

Multivariate Statistical Approach for the Discrimination of Honey Samples from Galicia (NW Spain) Using Physicochemical and Pollen Parameters

Raw honey is a food with a close relation to the territory in which it is produced because of factors such as soil conditions, weather patterns, and plant communities living in the area together. Furthermore, beekeeping management affects the properties of honey. Protected Geographical Indication Miel de Galicia protects the honey produced in Galicia (Northwest Spain). Various types of honeys (362 samples) from this geographical area were analyzed using chemometric techniques. Principal component analysis was favorable to analyzing the physicochemical and pollen variables with the greatest weight in the differentiation of honey. The linear discriminant analysis correctly classified 89.8% of the samples according to the botanical origin using main pollen spectra and physicochemical attributes (moisture, pH, electrical conductivity, diastase content, phenols, flavonoids, and color). Regarding unifloral honey, blackberry, eucalyptus, and heather honeys were correctly grouped, while five chestnut honeys and fourteen samples of honeydew honeys were misclassified. The chestnut and honeydew honeys have similar physicochemical properties and frequently similar pollen spectra profiles complicating the differentiation. Experimental evidence suggests the potential of multivariate statistics in the characterization of honey of the same geographical origin. Therefore, the classification results were good, with electrical conductivity, total phenol content, total flavonoid content and dominant pollens Eucalyptus, Erica, Rubus and Castanea sativa as the variables of higher importance in the differentiation of botanical origin of honeys.

Insight into the Recent Application of Chemometrics in Quality Analysis and Characterization of Bee Honey during Processing and Storage

The application of chemometrics, a widely used science in food studies (and not only food studies) has begun to increase in importance with chemometrics being a very powerful tool in analyzing large numbers of results. In the case of honey, chemometrics is usually used for assessing honey authenticity and quality control, combined with well-established analytical methods. Research related to investigation of the quality changes in honey due to modifications after processing and storage is rare, with a visibly increasing tendency in the last decade (and concentrated on investigating novel methods to preserve the honey quality, such as ultrasound or high-pressure treatment). This review presents the evolution in the last few years in using chemometrics in analyzing honey quality during processing and storage. The advantages of using chemometrics in assessing honey quality during storage and processing are presented, together with the main characteristics of some well-known chemometric methods. Chemometrics prove to be a successful tool to differentiate honey samples based on changes of characteristics during storage and processing.

Physicochemical Properties of Honey from Contract Beekeepers, Street Vendors and Branded Honey in Sabah, Malaysia

The chemical properties of honey depend on the source of collection to packaging, but little is known about honey in Sabah. The aim of this study was to distinguish between the physicochemical properties and mineral content of 76 honey samples from local sources and supermarkets in Sabah, which were from contract beekeepers, unknown sources and branded honey. Raw honey was collected from contract beekeepers, while honey from unknown source was obtained from street vendors and wet markets, while branded honey was purchased from local supermarkets. The chemical parameters of the honey were assessed using established methods, while the mineral content of the honey was determined using inductively coupled plasma optical emission spectroscopy (ICP-OES). Significant differences were found in several parameters measured in honey from different sources, with principal component analysis (PCA) showing clear separation between the measured parameters, yielding five factors that accounted for up to 72.25% of the total explained variance. Honey from contract beekeepers showed significant differences and higher mineral content (Ca, Cu, Fe, K, Mg, Na and Zn) compared to honey from unknown source and branded honey. Potassium was the most important element in the study with an average of 2.65 g/kg and 629.4 mg/kg for sources from contract beekeepers and branded honey, respectively. The honey from the contract beekeepers was of better quality due to its high mineral content. The results suggest that honey from contract beekeepers could be a good choice when it comes to high mineral content.

Detection of syrup adulterants in manuka and jarrah honey using HPTLC-multivariate data analysis

High-Performance Thin-Layer Chromatography (HPTLC) was used in a chemometric investigation of the derived sugar and organic extract profiles of two different honeys (Manuka and Jarrah) with adulterants. Each honey was adulterated with one of six different sugar syrups (rice, corn, golden, treacle, glucose and maple syrups) in five different concentrations (10%, 20%, 30%, 40%, and 50% w/w). The chemometric analysis was based on the combined sugar and organic extract profiles’ datasets. To obtain the respective sugar profiles, the amount of fructose, glucose, maltose, and sucrose present in the honey was quantified and for the organic extract profile, the honey’s dichloromethane extract was investigated at 254 and 366 nm, as well as at T (Transmittance) white light and at 366 nm after derivatisation. The presence of sugar syrups, even at a concentration of only 10%, significantly influenced the honeys’ sugar and organic extract profiles and multivariate data analysis of these profiles, in particular cluster analysis (CA), principal component analysis (PCA), principal component regression (PCR), partial least-squares regression (PLSR) and Machine Learning using an artificial neural network (ANN), were able to detect post-harvest syrup adulterations and to discriminate between neat and adulterated honey samples. Cluster analysis and principal component analysis, for instance, could easily differentiate between neat and adulterated honeys through the use of CA or PCA plots. In particular the presence of excess amounts of maltose and sucrose allowed for the detection of sugar adulterants and adulterated honeys by HPTLC-multivariate data analysis. Partial least-squares regression and artificial neural networking were employed, with augmented datasets, to develop optimal calibration for the adulterated honeys and to predict those accurately, which suggests a good predictive capacity of the developed model.

Prediction of Physicochemical Properties in Honeys with Portable Near-Infrared (microNIR) Spectroscopy Combined with Multivariate Data Processing

There is an increase in the consumption of natural foods with healthy benefits such as honey. The physicochemical composition contributes to the particularities of honey that differ depending on the botanical origin. Botanical and geographical declaration protects consumers from possible fraud and ensures the quality of the product. The objective of this study was to develop prediction models using a portable near-Infrared (MicroNIR) Spectroscopy to contribute to authenticate honeys from Northwest Spain. Based on reference physicochemical analyses of honey, prediction equations using principal components analysis and partial least square regression were developed. Statistical descriptors were good for moisture, hydroxymethylfurfural (HMF), color (Pfund, L and b* coordinates of CIELab) and flavonoids (RSQ > 0.75; RPD > 2.0), and acceptable for electrical conductivity (EC), pH and phenols (RSQ > 0.61; RDP > 1.5). Linear discriminant analysis correctly classified the 88.1% of honeys based on physicochemical parameters and botanical origin (heather, chestnut, eucalyptus, blackberry, honeydew, multifloral). Estimation of quality and physicochemical properties of honey with NIR-spectra data and chemometrics proves to be a powerful tool to fulfil quality goals of this bee product. Results supported that the portable spectroscopy devices provided an effective tool for the apicultural sector to rapid in-situ classification and authentication of honey.

Antioxidant Activity in Bee Products: A Review

Bee products have been used since ancient times both for their nutritional value and for a broad spectrum of therapeutic purposes. They are deemed to be a potential source of natural antioxidants that can counteract the effects of oxidative stress underlying the pathogenesis of many diseases. In view of the growing interest in using bioactive substances from natural sources to promote health and reduce the risk of developing certain illnesses, this review aims to update the current state of knowledge on the antioxidant capacity of bee products such as honey, pollen, propolis, beeswax, royal jelly and bee venom, and on the analytical methods used. The complex, variable composition of these products and the multitude of analytical methods used to study their antioxidant activities are responsible for the wide range of results reported by a plethora of available studies. This suggests the need to establish standardized methods to more efficiently evaluate the intrinsic antioxidant characteristics of these products and make the data obtained more comparable.

Honey: Chemical Composition, Stability and Authenticity

This Special Issue contains innovative research papers on the characterization, chemical composition and physical properties of honey. This constitutes very useful information to avoid frauds and to guarantee the authenticity of this food product. The knowledge of the particularities of honey is increasingly demanded by beekeepers and consumers, and also by labs to typify honeys according to their botanical origin and to check their quality. Melissopalynological, sensorial and physicochemical techniques are being used to study the characteristics of honeys samples from different plant sources and geographical areas. The combination of these analytical techniques with mathematical and statistical methods or chemometrics allows researchers to identify a set of variables or individual parameters that define independent samples, providing a practical solution to classify honey according to the geographical or the botanical origin.