INTRODUCTION

Honey is a natural product, defined by the Codex Alimentarius as “the natural sweet substance produced by honey bees from the nectar of plants or from secretions of living parts of plants or excretions of plant-sucking insects on the living parts of plants, which the bees collect, transform by combining with specific substances of their own, deposit, dehydrate, store and leave in the honeycomb to ripen and mature” (FAO/WHO, 2019). The major components of such supersaturated solution of sugars are the monosaccharides fructose and glucose, whereas minor components are represented by the disaccharides sucrose, maltose and other oligosaccharides (White, 1957). Honey also contains small quantities of other substances such as enzymes, vitamins, phenolic compounds (e.g., flavonoids), terpenes, organic acids, and hydrogen peroxide (Crane, 2009; Mabry et al., 1970; Machado De-Melo et al., 2018). Such a variety of components of different nature explains the capacity of honey to absorb ultraviolet radiation and its biological activity (Cianciosi et al., 2018; Isla et al., 2011; Majtan, 2014).

Honey is one of the three most adulterated foods worldwide, only after olive oil and dairy products. It is adulterated through different practices, including the addition of sugary syrups (derived from corn, sugar cane, sugar beet, rice, and others), passage through ion exchange resins to eliminate residues and reduce its colour, misassignment of botanical/geographical origin, and by mechanical dehydration of immature honey (García, 2018; Se et al., 2019; Stefas et al., 2021). The method used to detect adulterations depends on the specific situation (Apimondia, 2020). In general, highly sensitive and complex techniques such as isotopic analysis and Nuclear Magnetic Resonance are applied (Amadei Enghelmayer et al., 2022). In this regard, UV-Vis spectroscopy is an analytical method widely used in chemical laboratories due to its simplicity, speed, low cost, and accessibility. Although its low selectivity, it has been successfully used in the analysis of foods, and when associated with chemometrics, it is particularly applied to analyze bee products (Ansari et al., 2018; Maldonado et al., 2020; Martelo-Vidal and Vázquez, 2016).

The honey maturation process within the colony, which goes from the collection of nectar by foraging bees to the capping of honey, is much more complex than it appears. Since differences in chemical composition and biological activity have been verified between immature honeys and mature honeys (Guo et al., 2020; Maldonado et al., 2011), the present study aims to validate a methodology based on UV-Vis spectroscopy coupled with chemo­metric analysis to differentiate the nectar recently collected by bees from partially mature and honey for each colony.

MATERIALS AND METHODS

Samples collection

Samples of nectars, partially mature honeys and honeys with different botanical and geographical origins were collected from two different locations within Argentina: Tucumán, where the nectar flow occurs at the beginning of the beekeeping season, and in Entre Ríos at the end of the beekeeping season.

The samples from Tucumán were specifically collected in a town called Sauce Huacho (Latitude: -27.021940, Longitude: -65.436065) in the department of Famaillá. The hives were located very close to a commercial lemon (Citrus limon) plantation, in a typical natural forest of the foothill area of Tucumán, where the predominant plant species include Sauce Criollo (Salix humboldtiana), Afata (Cordia trichotoma), Guaran (Tecoma stans), Tipa (Tipuana tipu), and Pacará (Enterolobium contortisiliquum).

The samples from Entre Ríos were collected at Estación Experimental Concordia of the Instituto Nacional de Tecnología Agropecuaria (INTA; Latitude: -31.374422, Longitude: -58.116903), in Yuquerí Station, Provincial Road 22, and railroad tracks in Concordia. The hives were located in a field surrounded by Eucalyptus of different ages and varieties (mainly hybrids of Eucalyptus grandis), and this flower supply is predominant during the period of the year in which the trial was carried out.

Five hives were randomly selected for both trials. The hives were acquired from commercial apiaries applied by Beekeeping Program (INTA-PROAPI) technological path for the production of Argentinian-quality honey. Each one consisted of eight breeding squares, a population of more than ten squares covered with bees (Category i) from the genetics of INTA-PROAPI. In each hive of the trial, three frames with new combs were selected in the brood chamber for nectar sampling and three new frames of honeycombs for sampling partially mature honey and honey.

To take samples of nectar recently collected by the bees and partially mature honey, the frames of each hive were shaken separately on plastic trays covered with polyethylene film (which are suitable to store food) at the moment of maximum nectar flow. Then, the sample was extracted from the trays using a 20 ml syringe and placed in 50 ml Falcon tubes with a screw cap. The procedure was repeated until the honeycombs were capped in more than 80% by the bees. To take samples of honey, the capped combs were scraped, the honey and wax dragged from the caps, and collected in jars with lids of 250 g to 500 g capacity. All the samples were labelled and immediately refrigerated at -20°C until they were analysed. The following coding was used: firstly a number identifying the hive sampled (1, 2, 3, 4, 5), followed by acronyms according to the type of sample: honey (hny or HNY), partially ripe honey (prh or PRH), nectar (nct or NCT) and finally a number to indicate the sampling order (1, 2, 3). Lower case letters were used for the trial performed in Tucumán, whereas capital letters were for the one performed in Entre Ríos. More details are indicated in table 1.

UV-Vis spectra obtention and pre-treatment

The honey was manually separated from the capping wax. Then, nectar, partially ripe honey and honey samples were diluted with 80% ethanol (prepared by diluting ethanol 96% vol. with distilled water), filtered through Whatman N° 1 filter paper, and an aliquot placed in quartz cuvettes with 1 cm optical path. Spectra were determined in quintuplicate using a spectrophotometer (Hewlett Packard model 8452A, USA), absorbances between 190 nm and 420 nm were recorded at 2 nm intervals (Marcinkevicius et al., 2021; Roshan et al., 2013), and exported to Microsoft Excel 2016; absorbances for each wavelength were organized in columns and the samples in rows. Subsequently, spectra were pre-processed, which included baseline correction and normalization (SNV) (Noviyanto et al., 2016) using Orange software version 3.31.1 (https://orangedatamining.com/) (Demšar et al., 2013).

Chemometric analysis

Three methods based on projections were applied. Firstly, an exploratory analysis was performed using Principal Component Analysis (PCA) to determine if the samples could be separated by their spectral information. Then, using FreeViz projection, the relationship between wavelengths and type of samples was analyzed. Finally, through Linear Discriminant Analysis (LDA) of means, the capacity of spectra to differentiate samples of nectar, partially mature honey and honey was established. The wavelength range for the analysis was narrowed between 196 nm and 420 nm to rule out possible interference from the air, quartz cuvette defects, and other possible causes (Perkampus et al., 2013). Thus, 113 variables were initially considered. For PCA and LDA analyses, the statistical software Infostat version 2019 was used (Di Rienzo et al., 2011), whereas, for FreeViz projection, Orange software version 3.31.1 was used.

RESULTS

UV-Vis spectra of the samples

The spectra are the result of the sum of absorptions of various types of molecules present in small quantities in honey, such as phenolic compounds, organic acids, enzymes, and vitamins. Each compound has a characteristic absorption spectrum and its intensity varies with the wavelength.

The shape of the spectral curves obtained for the samples from the Tucumán and Entre Ríos trials were consistent with those reported for honeys from different botanical and geographic origins (Orfanakis et al., 2021; Roshan et al., 2013) and are shown in figure 1 a and b. It is observed that both types of honeys absorbed more UV radiation than the partially ripe honeys and the nectars. In addition, the spectra of the Entre Ríos samples, originating from Eucalyptus, were of greater intensity than those from Tucumán, originating from Citrus limon.

Principal component analysis

The principal component analysis (PCA) made it possible to reduce the number of initial variables under study and generate new ones called principal components (PC). The PC are orthogonal and result from the linear combination of the initial ones, which explains the total variability of the system.

For the trials carried out in Tucumán and Entre Ríos, seven and six components were obtained that explain the total variance, respectively. The distribution of the samples in the space defined by PC1 and PC2 is presented in figure 2 a and b. However, good separation between honey, partially mature honey and different types of nectar was not achieved, particularly between the latter two types of samples. In general, it can be seen that the samples tended to separate better according to sampling order (1,2,3).

Relationship between wavelengths and the type of samples

The FreeViz projection was used to analyze the relationship between wavelengths with honey, partially ripe honey and nectars because UV-Vis spectroscopy is a low selectivity technique. FreeViz projection is based on the attraction of the elements of the same group, repulsion of different groups and the resulting forces are exerted, in this case, on the vectors that represent the wavelengths. The optimized projection is the one in which the best separation between groups and the minimum potential energy of the system are achieved. (Demšar et al., 2007). For both regions, the circular and optimized projections are shown in figure 3.

Linear Discriminant Analysis

The total variability with 4 discriminant functions achieved after linear discriminant analysis (LDA) was performed and is explained in table 2. The space defined by canonical functions 1 and 2 explained 81.69% and 95.78% of the total variance for the trial carried out in Tucumán and Entre Ríos, respectively.

The absolute value of the coefficients of the discriminant functions calculated using standardized data allows establishing the weight of each wavelength on the discriminant power. For the trial carried out in Tucumán, the low wavelengths (less than 260 nm) had a great incidence on function 1 (f1) and had a great discriminating capacity, while the range between 320 nm and 420 nm would not have a significant effect and could be neglected to reduce the complexity of the calculation (figure 4 a). Regarding the trial carried out in Entre Ríos, an important contribution to the discriminant power of wavelengths (less than 290 nm) was observed through function 2 (f2); then, a decrease was observed until 370 nm approximately and started increasing to the end of the range (figure 4 b).

On the other hand, the univariate analysis of variance indicated that the contribution of the wavelengths in the spectra discriminating capacity was highly significant (p≤0.01); it was 96.5% and 93.8% of the total range for the trials carried out in Tucumán and Entre Ríos, respectively. From these results, it is necessary to consider the full range for the linear discriminant analysis.

DISCUSSION

UV-Vis spectra of the samples

The samples collected in Tucumán and Entre Ríos locations exhibited spectra with two absorption bands (figure 1 a and b); the first was narrower and with greater intensity at low wavelengths, and related to the presence of phenolic compounds and sugars such as glucose and fructose (Orfanakis et al., 2021) whereas the second followed the first and was broader, with less intensity and shoulder-shaped, which gradually disappeared to the end of the range analyzed. For wavelengths between 270 and 300 nm, this second band is associated with the presence of aromatic acids (Suhandy and Yulia, 2021), while at 320 nm, absorption may be due mainly to the presence of flavonols and non-flavonoid compounds (Orfanakis et al., 2021).

The dispersion was observed in the spectra throughout the analyzed range and for the different types of samples, as indicated for some wavelengths in figure 1. It is typical of the method applied and can also be due to differences among the hives. Dispersion is represented in vertical lines, denoting the maximum and minimum values obtained, plotted alternately; only honey, partially mature honey from the second sampling, and nectars from the first sampling were considered to facilitate visualization. The dispersion was reduced during the pre-processing through SNV normalization that performs the centring of the spectra and the scaling by their standard deviation.

Relationship between wavelengths and the type of samples

Honey was likely to be more related to the wavelengths between 274 nm and 300 nm for the trial carried out in Tucumán, and between 268 nm and 312 nm for the one carried out in Entre Ríos, as observed in the circular projections in figure 3 (a) and (A), respectively. This outcome indicated a higher contribution of phenolic compounds (Mabry et al., 1970). On the other hand, results for partially ripe honey and nectars suggested that they have greater bonding with a wider range of wavelengths, which corresponded to other types of molecules. More research needs to be carried out to establish the nature of such types of compounds. Finally, the circular projections also showed that some nectars and partially ripe honey could be associated with the same rank as the honey; yet, the optimized projections showed that they were well-differentiated groups and that there were no overlaps (figure 3 (b.B)).

Linear Discriminant Analysis

LDA is a supervised method, so before the analysis, we defined the groups to be differentiated/classified and the belonging of each sample to a specific group. For both trials, LDA allowed grouping of the samples of honey, partially ripe honey and nectar among themselves, clearly differentiating the groups by their nature and sampling (figure 5 a and b).

The validity of the result was verified using the cross-classification test (table 3). A 0% error indicated that all the samples assigned to each group were correctly classified. Moreover, these results indicated that changes in the chemical composition occur during the transformation processes from nectar to partially ripe honey, and from this one into honey (Eyer et al., 2016; Guo et al., 2020; Semkiw et al., 2008), which in term caused changes in the resulting UV-Vis spectra that could be evidenced by chemometric analysis although it is not easy to perceive them directly.

Considering the scales of the canonical axes 1 and 2 for both trials, it is also observed that the distances of the nectar and partially mature honey groups were greater compared to the honey group in the trial carried out in Entre Ríos. This result suggested that the chemical changes that occurred during the process of transformation of nectar into honey were greater in those kinds of honey that originated from Eucalyptus than in those from Citrus lemon. Likewise, in both trials, the nectar of samples 1 and 2 were also clearly differentiated, indicating that changes may have occurred in the chemical composition of nectar collected over time.

CONCLUSION

This study demonstrated that the methodology based on UV-Vis spectroscopy coupled with chemometric analysis allows differentiating nectars, partially ripe honeys and honey from different geographical and botanical origins. Furthermore, the wavelength range between 196 nm and 420 nm was identified to be highly significant for the discrimination ability. Even differences between different types of nectars collected on different sampling dates could be detected using the described methodology. Efforts are now focused on analyzing the possibility to apply UV-Vis spectroscopy coupled with chemometric analysis to discriminate among authentic honey, that is, honey naturally matured in the honeycombs from other kinds of honey obtained by artificial dehydration of nectar and partially mature honey.

Acknowledgments

ACKNOWLEDGEMENTS

Beekeeping Program (INTA-PROAPI)

PE I017 “Development of the organized, sustainable and competitive beekeeping sector”

INTA-NEXCO Agreement

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Notes

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