Spectroscopic study of honey from Apis mellifera from different regions in Mexico

Accepted Manuscript Spectroscopic study of honey from Apis mellifera from different regions in Mexico

C Frausto-Reyes, R Casillas-Peñuelas, JL Quintanar-Stephano, E Macías-López, JM Bujdud-Pérez, I Medina-Ramírez PII: DOI: Reference:

S1386-1425(17)30097-5 doi: 10.1016/j.saa.2017.02.009 SAA 14931

To appear in:

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Received date: Revised date: Accepted date:

5 October 2016 3 February 2017 4 February 2017

Please cite this article as: C Frausto-Reyes, R Casillas-Peñuelas, JL Quintanar-Stephano, E Macías-López, JM Bujdud-Pérez, I Medina-Ramírez , Spectroscopic study of honey from Apis mellifera from different regions in Mexico. The address for the corresponding author was captured as affiliation for all authors. Please check if appropriate. Saa(2017), doi: 10.1016/j.saa.2017.02.009

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ACCEPTED MANUSCRIPT SPECTROSCOPIC STUDY OF HONEY FROM Apis Mellifera FROM DIFFERENT REGIONS IN MEXICO Frausto-Reyes Ca*, Casillas-Peñuelas Rb*, Quintanar-Stephano JLc, Macías-López Ea, Bujdud-Pérez JMa, Medina-Ramírez I d a

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Universidad Autónoma de Aguascalientes, Departamento de Tecnología de Alimentos.

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Centro de Investigaciones en Óptica, A.C., Unidad Aguascalientes.

Universidad Autónoma de Aguascalientes, Departamento de Fisiología y Farmacología,

Universidad Autónoma de Aguascalientes, Departamento de Química.

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Centro de Ciencias Básicas.

Abstract

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The objective of this study was to analyze by Raman and UV-Vis-NIR Spectroscopic techniques, Mexican honey from Apis Mellífera, using representative samples with

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different botanic origins (unifloral and multifloral) and diverse climates. Using Raman spectroscopy together with principal components analysis, the results obtained represent the

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possibility to use them for determination of floral origin of honey, independently of the region of sampling. For this, the effect of heat up the honey was analyzed in relation that it

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was possible to greatly reduce the fluorescence background in Raman spectra, which allowed the visualization of fructose and glucose peaks. Using UV-Vis-NIR, spectroscopy,

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a characteristic spectrum profile of transmittance was obtained for each honey type. In addition, to have an objective characterization of color, a CIE Yxy and CIE L*a*b*

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colorimetric register was realized for each honey type. Applying the principal component analysis and their correlation with chromaticity coordinates allowed classifying the honey samples in one plot as: cutoff wavelength, maximum transmittance, tones and lightness. The results show that it is possible to obtain a spectroscopic record of honeys with specific characteristics by reducing the effects of fluorescence. Keywords: Unifloral and Multifloral honey from Apis Mellifera; Raman Spectroscopy; UV-Vis-NIR Spectroscopy; Spectrocolorimetry; Principal Component Analysis. *Corresponding author: [email protected], [email protected]

ACCEPTED MANUSCRIPT 1. INTRODUCTION The amount of honey produced by bees is three times the quantity they need for survival; this has allowed honey producers to collect the remainder for consumption and posterior domestication of bees with the objective of harvesting honey, activity known as apiculture [1]. Honey has been used as a medicinal and food product since ancient times, being this one of the main reasons for its production and commercialization; therefore, such product

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needs to comply with determined characteristics for quality control in order to prevent harmful health effects.

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Modern apiculture in Mexico started after 1920, after two events took place: the introduction of the Italian bee after the Spanish arrived to Mexican territory, together with

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the use of mobile frameworks for modern apicultural activities. In 1950, Mexican apiculture and commercialization developed further, based on European bees [2]. In

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relation to exports, Mexico holds the third place worldwide and has a stock of 1.9 million beehives, with a workforce of 45 thousand apiculturists nationwide [3].

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Current intensified consumption of natural-origin products increases as well the need and demand of products which cover what consumers ask for. Such demand results in

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the rise of competitiveness as Mexican apiculture is not exempt of the effects that the globalization of markets brings [4]. Diverse types of commercialized honeys exist

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currently, both nationally and internationally to cover the demand of such product; nevertheless, this has resulted in intentional adulteration of the product in order to fulfill the

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need of honey [5]. Mexico has a wide variety of honey [6] due to its diverse climates and flora, which depend directly on the geographic origin, resulting in honey with particular

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physicochemical parameters for each blooming process. These parameters are dependent on pollen grains, allowing for honey classification in unifloral and multifloral [7]. Among the physicochemical analyses available for honey classification, the melisopalinological analysis is a labor-intense method, requiring for highly qualified and specialized personnel. The approach of using a single analysis method for floral origin determination has been taken, being some studies promising such as analysis of volatile compounds and spectroscopic in honey with statistical analysis using PCA, LDA or CA for botanic origin classification. Nevertheless, further studies are needed in order to develop a database of unifloral and multifloral honeys [7]. From spectroscopic methods Raman spectroscopy is

ACCEPTED MANUSCRIPT widely used. However in this technique the definition of the peaks of honey bee samples is often compromised by the presence of an intense fluorescence background that overlaps the Raman signal. There is no single strategy for reducing fluorescence background and several instrumental and mathematical methods have been proposed to reduce fluorescence in order to resolve and analyze Raman spectra, like using excitation wavelengths in the NIR region [8].

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This study presents a spectroscopic analysis of honey from Apis Mellífera bee from different regions in Mexico, with botanic and regional unique characteristics. This

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characterization was done using NIR Raman and UV-Vis-NIR spectroscopy, together with principal component analysis and colorimetry. For this analysis, it is experimentally

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shown that heat up the honey can reduce the fluorescence background having Raman peaks with better definition, independently of botanic or regional origin of the samples.

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That is, it is known that Raman systems with excitation sources in both the Vis and the NIR have advantages and disadvantages; to mention the effects of fluorescence noise. In

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several works, for reducing fluorescence effects, excitation source of longer wavelengths, like 1064 nm, have been used. So considering the proposed methodology, for honey

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samples analysis, it is shown that it is possible to reduce fluorescence effects when it is

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used a shorter wavelength like 830 nm.

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2. MATERIALS AND METHODS

2.1 Honey Bee samples

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Table 1 shows the honey samples used for this study, which are from different botanic and regional origin [9]. These samples are honeys produced by Apis Mellífera bee. Samples were collected in plastic containers, labeled and kept at room temperature without light exposure. The moisture content was obtained following a reported relation [10], where the refractive index of honey is related to the water content at 20 oC. The refractive index was measured with an Abbe refractometer Bausch and Lomb model 3L.

2.2 Heated honey

ACCEPTED MANUSCRIPT Honey samples were liquid and with an homogeneous visual appearance, but with small crystals under microscopic visualization. Due to these observations, honey samples were analyzed as well after heat up and melting of such crystals. For this process, honey samples were poured in 10 ml glass containers and set in a water bath at 60°C, for 30 minutes. This temperature value is lower than the temperature used for pasteurization of honey [11].

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Honey samples were held after heat up at room temperature and analyzed by spectroscopy.

2.3 Raman spectroscopic analysis

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The Raman spectra of the liquid samples were obtained by placing them onto an aluminum substrate and then under a DMLM microscope (Leica) integrated to the Raman system

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(Renishaw 1000B, approximated resolution of 2 cm-1). The Raman system was calibrated with a silicon semiconductor using the Raman peak at 520 cm-1. The excitation wavelength

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was 830 nm, and the laser beam was focused (spot size of approximately 2 m) on the surface of the sample with a 50x objective. The laser power irradiation over the samples

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was approximately 10 mW. Measurements were made at several points in each selected sample, 60 seconds in the range of 300 to 2000 cm-1, although only a representative

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spectrum is shown. The shown Raman spectra have not been smoothed and were normalized to the most intense peak, and do not have a base line. Considering that the main

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carbohydrates in honey are fructose and glucose, together with probable beewax presence, Raman spectra were obtained for the corresponding standard samples in solid state (aldrich,

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D-(_)-Fructose, alfa-D-Glucose anhydrous 96 %, beewax from Apis Mellífera) keeping the

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parameters of the Raman system for the honey samples.

2.4 UV-Vis-NIR Analysis The transmittance spectra of honey samples were measured using a UV/Vis Spectrometer (Perkin Elmer, Lambda12 model) in the wavelength range of 300 to 1100 nm, at 5 nm intervals. These measurements were performed under controlled environmental conditions (21°C temperature and 44% of humidity). For sample analysis, honey was held in quartz cells and distilled water was used as blank for transmittance spectra measurements.

2.5 Colorimetric analysis

ACCEPTED MANUSCRIPT For color determination, the transmittance spectra were processed with a Labview platform-based program to calculated C IE Yx y and C IE L*a*b* colorimetric parameters. For this processing the wavelength range of 400-700nm, at 10 nm intervals, a C I E D65 illuminant, and a CIE 1964 standard colorimetric observer (100 ) were considered [12].

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2.6 PCA analysis

For classification and monitoring of probable spectra behavior of honey samples, a

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principal component analysis was performed (PCA). To achieve this, a MatLab platformbased program was developed, considering normalized Raman spectra to its maximum

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intensity. For UV-Vis–NIR spectra, no previous processing was performed.

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3. RESULTS AND DISCUSSION 3.2 Raman Analysis

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Considering that carbohydrates are the main component of these foods, Figure 1 shows the Raman spectra obtained from standard samples of fructose and glucose. Taking into

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account as well probable presence of wax in honey samples, the same figure shows spectra for beewax of Apis Mellífera bee. Similar to the study by De Gelder et al. [13], Raman

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peaks with higher intensity for these carbohydrates are observed in the 350 to 650 cm-1 region. For fructose, the peak with higher intensity is located at 626 cm -1 assigned to Ring

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deformation [13-15]. The Raman peaks with higher intensity for glucose are located approximately between 407 and 541 cm_1 [13]. In the 200 a 600 cm-1 region, Raman bands

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are mainly attributed to the skeletal vibrational motions with major contributions from the deformation modes of C-C-C, C-C-O, C-C, and C-O groups of saccharides [15-19]. It can also be observed that the peaks with higher intensity for beewax are located approximately between 1296 (CH2-twist) and 1444 cm-1 (CH2-deformation), originated from carbohydrates (also cyclic) modes [20, 21], falling out of the skeletal vibrational motions region, where the peaks with higher intensity for carbohydrates are located. This is important for classification and monitoring of Raman data, by means of PCA, and at the same time information related to beewax can be omitted. The above when considering there are cleaner honeys than others in relation to the quantity of beewax with operculum

ACCEPTED MANUSCRIPT presence during the sampling process, which has a direct effect in the amount of beewax that is present. Raman spectroscopic analysis of liquid honey was done following two treatments: the first one without heat up, and the second one using a water bath for crystals dissolution of samples that contained small. Without heat up, some honey samples did not present Raman signal, only fluorescence was detected (Altiplano, multifloral from Chiapas,

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Tizimín, avocado, citrics and honey bell), for this cases, Figure 2 only shows Raman spectrum for honey from Chiapas. Nevertheless, after temperature treatment, all of the

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samples except the avocado origin one, presented Raman peaks with different visibility depending on their fluorescence. Also, Figure 2 shows Raman spectrum of Chiapas heated

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honey sample. Defined Raman peaks 427, 540 and 630 are observed, possibly associated to glucose and fructose [15-18]; this could be related to a more homogeneous sample. Luiz

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Fernando et al. report spectra of honey samples, from Brazil, warming them in a water bath, nevertheless in such study, Raman analysis was done with a wavelength of 1064 nm,

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therefore the effects of fluorescence in the definition of Raman peaks were not observed because fluorescence is not an issue under these excitation wavelength conditions [16].

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Luiz Fernando C. De Oliveira et al. obtained a peak for crystalized honey samples at 421cm-1 and, similar to this study, fluid samples showed a peak at 423 cm-1 considering

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they were heated [16]. Stefan Söderholm et al. report in their study Raman Spectra of Fructose and Glucose in the Amorphous and Crystalline States, how the intensity profiles

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of the spectra vary for each state and depending as well on water content. This could be the reason why intensity profiles of Raman spectra of honey samples are different when

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compared with standards in crystalline state (see Figures 1 and 2) [19]. As better defined Raman peaks were obtained, spectroscopic analysis of honey samples from different regions was performed considering heated honey samples and botanic origin (unifloral and multifloral). Figure 3 shows Raman spectra of unifloral honey samples (avocado, honey bell, Tizimín, Altiplano, mesquite Noria de Angeles Zacatecas, mesquite Zacatecas, mangle) normalized to the maximum intensity. It can be observed that Raman peaks definition depends on the fluorescence background of each sample. Mangle honey spectrum shows the Raman peaks with better definition and avocado honey did not show Raman peaks. For

ACCEPTED MANUSCRIPT standard samples represented in Figure 1, the region with peaks of highest intensity is located approximately between 350 and 650 cm-1. In this same region, it can be seen the ratio intensity changes of peaks between 423 and 630 cm-1. Mangle honey has its highest peak at 630 cm-1, while mesquite honey samples have the highest peak at 423 cm-1. These differences in the intensity of the peaks are useful for honey characterization, as it has been reported that sugars constitute approximately 95% of dry weight of honey. It has also been

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referenced that the relative amount of fructose and glucose could be useful to define the

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botanic origin of honey [7]. Other studies report presence of other sugars such as sucrose

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with intense peaks between 350 and 650 cm-1, which could also have an impact on the intensity differences of this region [16].

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Figure 4 shows corresponding Raman spectra for multifloral honey samples (Chiapas, Oaxaca, citric and Zacatecas) normalized to the maximum intensity. Similar to

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spectra in Figure 3, the intensity profiles are alike and definition of Raman peaks depended on the fluorescence background. Different from what was observed in unifloral honey samples, when intensity rates are compared, the peak at 423 cm-1 (fructose and glucose)

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was highest in intensity than the peak at 630 cm-1 (fructose). As both peaks’ intensity does

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not vary equally, the peak at 423 is probably related to glucose rather than to fructose. A statistics tool frequently used to classify data is the Principal Component Analysis

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as it does not require any previous knowledge of the samples under study, and can provide patterns, groupings, detection of outliers, etc. [7, 22]. This tool was applied to the Raman

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spectra data of the different regional zones considering normalized spectra to the maximum intensity and considering as well the range between 350 to 650 cm-1, where the peaks of the

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main carbohydrates with higher intensity were observed (Figure 1). Figure 5 shows the graph of PC1 vs PC2 which hold a 97 % of the variance. PC1 axis gives a classification base on the fluorescence background of Raman spectra; where avocado honey samples presented the highest fluorescence, and mangle and mesquite honey samples had the lowest. PC2 axis show a tentative classification considering the rate of intensity of glucose and fructose peaks; where mangle honey samples have a peak with higher intensity for fructose and avocado honey samples had the lowest intensity. PC1 and PC2 allow the classification of Raman spectra of honey samples into three main groups: unifloral honey samples with higher and lower fluorescence, and multifloral honey samples. The group in

ACCEPTED MANUSCRIPT the dotted line box corresponds to multifloral honey samples, and the groups in the broken lines boxes corresponds to unifloral honey samples with lower and higher fluorescence background.

3.3 UV-Vis-NIR Analysis

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For UV-Vis-NIR analysis, heated liquid honey samples were utilized, similar to Raman

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previous tests. Figure 6 shows transmittance spectrums for the different honey samples in the region from 300 to 1100nm. The transmittance spectra profile is characteristic of the

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different honey samples; i.e. all samples had a kind of cutoff wavelength where transmittance begins to be close to zero. Honey samples with extreme readings are the

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mezquite and avocado samples with cutoff wavelengths approximately at 380 and 630nm, respectively. Additionally, there are maximum transmittance levels in the range of 900 to

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1050nm that previous research [23] finds it related to the presence of glucose, fructose, and sucrose. In this region, honeys with the highest and lowest transmittance were the samples

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from the Altiplano and the mesquite, respectively.

Similarly to the Raman spectrums, the UV-Vis-NIR analysis was conducted with

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the PCA, without any previous sample preprocessing. Figure 7 shows the results for PC1 and PC2, together these results include 99.5% of the variance. Along the PC1 axis the

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samples are classified from the minimum (mesquite) to the maximum (Altiplano) transmittance. PC1 and PC2 together (as indicated by the arrow) also classified the spectra

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extremes.

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in terms of their cutoff wavelength, with the mesquite and Altiplano samples at the

3.4 Colorimetric analysis The UV-Vis-NIR transmittance spectrum values shown in Figure 6 and the visible region of the electromagnetic spectrum (400 a 700 nm) were used to determine the color coordinates for each of the honey samples in the CIE Yxy and CIE L*a*b* color spaces. In Table 2 are shown the color coordinates for each of the honey samples. The colorimetric parameters Y and L* indicate how light or dark is a tone with chromaticity coordinates x, y or a* (red/ green), b* (yellow/ blue) [12, 24-26]. The chromaticity coordinates values

ACCEPTED MANUSCRIPT obtained indicate that the tone of the honey samples, having different lightness, is located in the yellow and red region of the color spaces.

From Table 2, it can be observed that the honey samples with the most lightness difference are the avocado honey, being the darkest (Y=0.0805, L*= 0.7274), and the Altiplano sample for being the lightest (Y=28.523, L*= 60.3583). The same trend is

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observed in Figure 7 where samples are classified according to their lightness along the

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PC2 axis. Therefore, it could be stated that the PC2 axis is related to the Y and L*

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colorimetric values of each honey sample. Also, from Table 2, it can be observed that the chromaticity coordinates of Tizimín honey have a higher tendency towards the red tones;

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while the Altiplano honey coordinates leans towards the yellow tones. Considering this, it can be seen from Figure 7 that there is a group of honey samples (2, 6, 7 and 9) that tend

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towards the red tones and other group of honey samples (3, 5, 8, 10 and 11) that tend towards the yellow tones. On the other hand, from Table 2, taking into account achromatic

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tendencies (low values of chromaticity coordinates), mesquite honey (sample 4) leans towards the white color, while the avocado honey (samples 1) leans towards the black

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color. The same it is observed in Figure 7, where samples 1 and 4 are located at the extremes of the cutoff wavelength, shown by the arrow. Additionally, when achromatic

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samples (1 and 4) are removed from analysis, it can be stated that the PC2 also shows chromaticity tendencies towards yellow or red tones. From this it can be observed that

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when the L* parameter has a large value, in general the b* parameter for yellowness has also a large value. Despite the fact that there is not a tendency of the honey samples based

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on their botanical origin, the UV-Vis-NIR spectrometry, combined with the colorimetry and principal component analysis, is an objective methodology for classifying honey samples.

It is known that the color and flavor of honeys are different depending on the nectar source (the blossoms) visited by the honey bees. Although there are some exceptions, the color can be related to the flavor, light honeys may be have a milder flavor and dark honeys may be have a stronger flavor [10]. In addition, there are other reported studies about the color of honey and its relation with its chemical composition. Bertoncelj et al. reported a correlation between the color of Slovenia honey and its total phenolic content

ACCEPTED MANUSCRIPT (highest in darker honeys and lower in lighter honeys) and antioxidant activity [26, 27]. It is likely that polyphenols are oxidized by air to dark materials [10]. The color of honey to consist of melanoidin from the amino-carbonyl reaction and flavonoids pigments extracted from pollen by the nectar and honey [10]. The effect of the acid environment on the sugars and the reaction of the phenolic materials with iron contributed to color [10]. Most likely, the results of these studies could be applied to characterize the honeys from

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Mexico in terms of color and chemical composition.

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4. CONCLUSSIONS

It was demonstrated experimentally that heat up honey samples assists in the

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reduction of the fluorescence background, thus providing better defined Raman peaks corresponding to the main carbohydrates in the samples, when compared with not heated

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samples.

The use of Raman and Uv-Vis-NIR techniques allowed the study of o variety of

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Mexican honey bee samples by the development of a spectroscopy record with specific characteristics for each individual sample according to their botanical origin. The Raman

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spectroscopy may provide the possibility to be used as a mechanism to determine the floral origin of the diverse honey samples; with importance for the apicultural market, due to the

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great variety and diversity of honey samples. Thus, supporting their use to add value to honey samples based on their characteristics dependent on their botanical origin.

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By means of the UV-Vis-NIR spectral analysis, it was possible to classify the honey samples due to the transmittance spectrum, being characteristic to each honey sample. In

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addition, through the colorimetric spectral analysis in the CIE1931 and CIE 1976 color spaces we were able to obtain a color record for each of the different honeys. The principal components analysis was fundamental to classify the Raman spectrum data of the honey samples according to their botanical origin. In similar fashion, this analysis aids in the reading and interpretation of the UV-Vis-NIR spectrum results and their correlation with color, thus allowing the classification of honeys by the same chart, based on: cutoff wavelength, maximum transmittance (possibly related to main sugar components), tone and lightness of honeys.

ACCEPTED MANUSCRIPT Finally it can be stated that this research work was able to characterize by the use of two different spectroscopy techniques the different types of honey samples based on botanical origin and regional characteristics; however, despite the fact that the results were representatives these will have to be expanded by the use of additional samples from

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different regional sources.

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Acknowledgements

Authors would like to acknowledge to Cuauhtemoc Nieto Silva and Norma

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Rodríguez Vital (laboratorio de colorimetría, Centro de Investigaciones en Optica, A.C.,

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Unidad Aguascalientes) for helping in the UV-Vis-NIR spectroscopy.

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ACCEPTED MANUSCRIPT FIGURE CAPTIONS

Figure 1. Raman spectra of beewax from Apis Mellífera bee, fructose, and glucose.

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Figure 2. Raman spectra of heated and not heated honey samples from Chiapas.

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Figure 3. Raman spectra of heated unifloral honey samples.

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Figure 4. Raman spectra of heated multifloral honey samples.

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Figure 5. PCA analysis of Raman spectra of heated honey samples.

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Figure 6. UV-Vis-NIR Spectrum of heated honey samples

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Figure 7. PCA analysis of UV-Vis-NIR spectra of heated honey samples from 3001100nm.

ACCEPTED MANUSCRIPT TABLE LEGENDS

Table 1. Honey samples from Apis Mellífera bee from different regions in Mexico and various botanic origins, and their corresponding water content.

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Table 2. Colorimetric parameters for honey samples, considering a CIE D65 illuminant,

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and a CIE 1964 standard colorimetric observer.

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Figure 2

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Figure 7

ACCEPTED MANUSCRIPT Table 1. Honey samples from Apis Mellífera bee from different regions in Mexico and various

Botanic Origin

Harvest Season

Water content (%)

1

Puebla

Spring

18.7

2

Oaxaca

Fall

IP

18.5

3

Zacatecas

Spring

14.7

4

Noria de Ángeles, Zacatecas

Spring

14.9

5

Alvarado, Veracruz

Spring

21

6 7 8 9

Tizimín, Yucatán Chiapas Oaxaca NorthVeracruz State

Spring Spring Fall Fall

20 16.9 16.7 17.5

10 11

Altiplano, Puebla Noria de Ángeles, Zacatecas

Avocado (Unifloral) Honey bell (Unifloral) Mesquite (Unifloral) Mesquite (Unifloral) Mangle (Unifloral) Multifloral Multifloral Multifloral Citric combination Multifloral Multifloral Multifloral

Fall Fall

19.7 15.1

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Sample Number

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botanic origins, and their corresponding water content.

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Table 2. Colorimetric parameters for honey samples, considering a CIE D65 illuminant, and a CIE 1964 standard colorimetric observer.

7 8 9

10 11

x

0.1785

0.0805

0.0232 0.6326

4.1542

2.3799

0.0838 0.6277

y

a*

b*

0.7274

4.1975

0.9182

0.359 6

17.366 3

32.469

28.7258

20.9056 19.8052 2.6727 0.4819

0.456 5

51.616 2 10.6501 58.1783

12.4301 12.8702 9.1472 0.3608

0.373 6

42.567

1.5875

12.967

60.029 7

9.9511

62.6253

8.9052

28.426

14.3042

0.285 4

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0.456 7 0.334 1.8979 0.9897 0.0723 0.6412 4 0.320 1.4307 0.717 0.0899 0.6394 4 0.435 15.3402 12.1999 0.4694 0.5477 6 29.1926 28.1563 4.3053 0.4735

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0.404 5 0.456 33.381 28.523 0.5775 0.5343 5 0.430 26.5263 26.9931 9.1408 0.4233 8

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Avocado (Unifloral) Campanilla (Unifloral) Mezquite (Unifloral) Mezquite (Unifloral) Mangle (Unifloral) Multifloral (Yucatán) Multifloral (Chiapas) Multifloral (Oaxaca) Citrics Combination (Multifloral) (Veracruz) Multifloral (Puebla) Multifloral (Zacatecas)

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Sample Number

5.5938

3.8687

0.1007 0.5849

6.4765 26.6878 9.8624 41.532 1 24.4997 64.7963

23.232 5 25.5639 38.5945 60.358 3 23.9672 95.687 58.967 9 3.9174 41.2651

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Graphical abstract

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Mexican Apis Mellífera honey from different botanic and regional origin. Raman and UV-Vis-NIR spectroscopic analysis of honey samples. Heated honey could be used for fluorescence noise reduction. The Raman spectroscopy and PCA could be used to determine the floral origin. Colorimetric parameters were calculated for each of the different honeys from UV-Vis.