Exploring Riboflavin Quantification in Honey via Spectrofluorimetry: A Statistical Examination of Influential Extrinsic Variables

doi:10.21203/rs.3.rs-3875508/v1

The present study is focused on the collection of honey samples from the different geographical and climatic conditions of Khyber Pakhtunkhwa and analyzing them for determination of riboflavin. Quantification of riboflavin being natively fluorescent, was accomplished using spectrofluorimetric method. Riboflavin has characteristic fluorescence spectra with maximum excitation at 464 nm followed by an emission peak at 525 nm. The procedure followed in this work comprised the construction of a calibration curve by plotting the fluorescence intensity of a series of riboflavin solutions versus concentration. This curve was used for quantification of riboflavin in the collected honey samples. The effect of several external factors such as the altitude of the sampling area, type of honey bee, type of flowers from which the nectar was collected, and sampling season on the concentration of riboflavin in the honey samples was statistically evaluated. It was concluded that the samples collected from lower altitudes have high concentration (1.156±0.08 μg g^-1) of riboflavin. Similarly, the samples collected in autumn were found to have a with a maximum average riboflavin concentration of 1.37±0.06 μg g^-1, which was higher in comparison to the samples collected in other seasons of the year. Likewise, the effect of flora on the concentration of riboflavin was also investigated and it was found that honey samples collected from areas where the nectar was collected from Ziziphus contains maximum riboflavin concentration averaged at 1.383±0.1 μg g^-1. Based on the size of the honey bees the samples collected from hives of small honey bees were found to have maximum riboflavin concentration of 1.176±0.07 μg g^-1. This study suggests that beside the studied vitamin, the rest of the vitamins and other nutritional components may vary in the honey samples depending upon external factors.

Riboflavin/vitamin B2

Spectrofluorometer

Calibration curve

Standard solution

Statistical analysis

Effect of altitude

flower type

season

bee size.

Honey, often referred to as "liquid gold," is a natural product renowned for its diverse composition and numerous health benefits. Among the myriad of bioactive compounds found in honey, riboflavin (vitamin B2) plays a vital role in various metabolic processes within the human body.[1] Riboflavin is not only essential for our health but also serves as a potential marker for the quality and authenticity of honey. Spectrofluorimetric analysis is a powerful analytical technique that can be employed to quantify riboflavin levels in honey samples. However, the accuracy and reliability of such analyses can be influenced by a range of external factors, including environmental conditions and sample preparation methods. This study aims to explore the application of spectrofluorimetry for the quantification of riboflavin in honey and to statistically evaluate the impact of these external factors, shedding light on the robustness and precision of this analytical approach. In doing so, we aim to contribute to the advancement of honey quality control methods and provide valuable insights for both the honey industry and consumers. According to Pearson (1976), "Honey is the saccharine product gathered by the bees from the nectar of flowers" is how honey is defined. Honey is a naturally sweet material that honey bees make by regurgitating and evaporating floral nectar.[2] It can also be made from the flowers of plants, their secretions, or the excretions of plant-eating insects.[3] Honeybees, however, gather nectar, alter it into other substances of their own, store it in the honeycomb, and allow it to develop and mature there.[4] Bees make nectar-based blossom honey and honeydew honey from honeydew. Small insects that feed on plants produce honeydew.[5] Honey offers enticing chemical characteristics for baking and is noticeably sweeter than table sugar. Honey has almost the same relative sweetness as granulated sugar and derives its sweetness from the monosaccharide’s fructose and glucose. Some people prefer honey over sugar and other sweeteners because of its particular flavor.[6] Honey is a food that contains about 200 different chemical compounds.[7, 8] These include sugars, water, proteins (enzymes), organic acids, vitamins (especially vitamin B6, thiamine, niacin, riboflavin, and pantothenic acid), minerals (including calcium, copper, iron, magnesium, manganese, phosphorus, potassium, sodium, and zinc)[9, 10], pigments, phenolic compounds, a wide range of volatile compounds, and solid particles derived from various sources.[11] These nutrients play important roles in the functions of nucleic acids[12], due their intermolecular interactions.[13] Factors affecting composition of honey: According to a study of the literature on honey composition, the composition of the honey depends on the source of the nectar.[14] Additionally, the internal and external variables that affect nectar production are significant contributors to the composition of honey.[15] Some of the internal elements have been proposed to include the size of the bloom and the nectary surface, the age and maturity of the flower on the plant, the species, variety, or cultivated races to which the plant belongs.[16] Additionally significant outside variables are soil moisture, soil type, fertilizer application, temperature, wind, season, length of day, and sunlight. Similar investigations described the internal and environmental elements that affect nectar secretion. On the composition of honey, the impact of beekeeping practices, honey extraction, and processing by beekeepers or commercial producers have been discussed.[17] Additional aspects that were involved in the commercial processing have also been discussed.[18] The storage circumstances have a significant impact on the composition of honey, and storage-related alterations have been documented.[19]

Instrument: Spectroflourophotometer (RF-5301 PC, Shimadzu, Japan) having 150-watt Xenon lamp as excitation source with 1.0 cm quartz cell was used throughout the experimental work for
fluorescence measurements. The emission and excitation slit were 4 nm for fluorimetric
operation. Required chemicals were weighed using an electrical digital balance (Shimadzu
ATY 224) and stirring of the reaction mixture was carried out with the help of magnetic
heating stirrer (Heidolph). Borosilicate glassware and apparatus were used for the respective
operation. Chemicals used in this study were riboflavin of analytical grade, glacial acetic acid, and distilled water obtained from distillation plant. The honey samples collection was made in the years 2022-2023. A total of twenty (20) honey samples from different agroecological zones were collected by taking into consideration the altitude of the sampling area, the season in which the honey was made, flowers of the area in the respective season, climatic conditions, bees’ types, and size, etc. All the samples were carried in glass stoppered vials from the concerned beekeepers and photodecomposition was prevented by storing the samples in a dark cupboard at ambient temperature until they were needed for laboratory analyses. The spectrofluorimetric method was employed to determine riboflavin in all the collected samples. In which the fluorescence intensity of riboflavin (RF) was measured at 525 nm following excitation at 464 nm.

2.1 Analysis of honey samples for the determination of riboflavin

A calibration curve was constructed by plotting Fluorescence Intensity (FI) of a series of standard riboflavin (RF) solutions versus concentration for the analysis of honey samples.

2.2 Preparation of stock solution of RF: Riboflavin Stock Solution (100 ug/ml) was prepared by dissolving 0.01 g of riboflavin in 50 ml of distilled water. A few drops of glacial acetic acid were added because riboflavin is stable in its presence. Then it was transferred to 100 ml of a volumetric flask and diluted up to the mark. This stock solution was stored at 4ºC and was covered with a black plastic bag for prevention from photodecomposition. For the preparation of standard solution of RF for calibration curve, riboflavin working standards in the range of 0.005-0.3 µg ml^-1 solution were prepared using the dilution formula C₁V₁ = C₂V₂ and FI of each solution was measured using a spectrofluorometer. The range of 0.005-0.3 µg ml^-1. These solutions were protected from light by covering them with a black plastic bag. Then fluorescence intensity was measured through a spectrofluorometer.

2.3 Preparation of sample solution and measurement of FI

Preparation of sample solution: In a small beaker 5.0 g of each sample was taken. Dissolved it in 50 ml of distilled water added a few drops of Glacial acetic acid and diluted up to the mark in 100 ml of volumetric flask. Covered the sample solution with a black plastic bag to prevent photodecomposition of RF. Fluorescence measurement: Each sample was taken in a quartz cuvette and placed in the sample holder of the pre-calibrated spectrofluorometer and FI was measured at an emission wavelength of 525 nm following an excitation wavelength at 464 nm. The measurement was done in triplicates. Calculation of concentration of RF: The concentration of RF in each sample was calculated from the average FI using the straight-line equation of the calibration curve which is given below.

Y = 2513.2x + 13.17 (1)

Here Y is the fluorescence intensity of sample X in the above equation 1 is concentration which is calculated by rearranging equation 1 as

X = (Y -13.17) / 2513.2 (2)

To calculate the concentration of RF in µg g^-1 of honey the following equation was used.
Conc (µg g^-1) = (X (µg mL^-1)) (100 ml)/5g (3)
Conc (µg g^-1) = X (µg g^-1) (4)

3.1 Calibration curve for quantification of RF in honey samples

In order to quantify the concentration of Riboflavin (RF) in honey samples, a crucial step was the construction of a calibration curve, also known as a working curve. This curve was meticulously constructed by plotting the Fluorescence Intensity (FI) against the concentration of standard Riboflavin solutions, spanning the range of 0.005 to 0.3 µg ml^-1. The results, which provide a clear insight into the relationship between FI and RF concentration, are presented in Table 1 and visually depicted in Figure 1. Table 1 outlines the calibration curve, detailing the corresponding FI values at various RF concentrations. Notably, as the RF concentration increases, so does the FI. This direct correlation between the two parameters is vital for the accurate quantification of Riboflavin in honey samples. Figure 1 complements the tabulated data, offering a graphical representation of this relationship, enabling an even more intuitive understanding of the calibration curve. Such a well-constructed calibration curve forms the cornerstone of precise analytical methods, allowing for the accurate determination of Riboflavin levels in honey samples, a fundamental aspect of quality control and authenticity assessment in the honey industry.

Table 1 Calibration curve for quantification of RF in honey samples

Concentration (µg ml^-1)	FI
0.005	15.153
0.008	22.795
0.01	29.497
0.03	92.374
0.05	139.844
0.08	228.754
0.1	276.864
0.2	533.608
0.3	747.449

3.2 Quantification of RF concentration in honey samples

For the purpose of quantification of RF concentration, all the collected samples were analyzed by spectrofluorimetric measurement and subsequent calculation of RF in (µg g^-1). Honey composition and its relationship with various environmental and seasonal factors are examined here. The data given in Table 2, present information about 20 honey samples, with altitude from sea surface (in feet), flower type, season of collection, bee size is considered as variable factor, and the concentration of riboflavin (RF) in each sample along with standard deviations. For instance, the concentration of riboflavin (µg g^-1) varies considerably across the samples, ranging from as high as 2.74±0.02 in a Ziziphus honey collected at an altitude of 1497 feet, to as low as 0.08±0.02 in Brassica honey collected at an altitude of 4194 feet. The diverse flower types, seasons, and bee sizes also appear to have a potential influence on riboflavin content in honey. This dataset beckons further exploration and analysis, offering valuable insights into the multifaceted nature of honey composition and its dependence on external factors. It opens the door to questions regarding the significance of altitude, flower type, and bee size in determining the nutritional content and quality of honey. Such investigations can provide critical knowledge for honey producers and enthusiasts alike, contributing to a deeper understanding of this beloved natural sweetener.

Table 2 Concentration of RF (µg g^-1) in honey samples

Sample No	Altitude from sea surface (ft)	Flowers	Season	Bee size	Conc of RF (µg g^-1) ±SD
1	1497	Ziziphus	Jan-18	Small	2.74±0.02
2	2478	Ziziphus	Nov17	Medium	1.34±0.04
3	3487	Multifloral	Jul-17	Small	1.2±0.1
4	3407	Multifloral	Apr-18	Small	1.32±0.02
5	5433	Commercial	Dec-17	Unknown	0.26±0.02
6	4194	Brassica	Apr-18	Medium	0.08±0.02
7	2353	Ziziphus	Oct-18	Medium	1.4±0.02
8	3655	Brassica	Apr-18	Medium	0.313±0.04
9	2310	Multifloral	Apr-18	Medium	0.25±0.01
10	1805	Ziziphus	Dec-17	Small	0.826±0.01
11	3655	Acacia	Jun-17	Medium	1.167±0.04
12	2310	Acacia	Jun-17	Medium	0.92±0.04
13	1897	Ziziphus	Dec-17	Medium	1.74±0.02
14	1869	Acacia	Jul-17	Small	0.67±0.05
15	1890	Acacia	Jun-17	Medium	1.38±0.02
16	1517	Ziziphus	Dec-17	Big	1.32±0.02
17	1880	Acacia	Jun-17	Big	0.51±0.05
18	1805	Multifloral	Apr-18	Medium	0.22±0.02
19	1880	Acacia	Jun-17	Medium	1.04±0.02
20	4190	Ziziphus	Jan-18	Small	0.34±0.04

3.3 Statistical analysis

For statistical evaluation of the individual effect of different variables like altitude of sampling site, season of honey formation, Bee size, and flower type on the concentrationof RF (µg g^-1), SPSS V. 23 was used.

3.3.1 Effect of altitude on RF concentration in honey

The effect of the altitude of the sampling site on RF concentration in honey was investigated. Herethe dependent variable is RF concentration (µg g^-1) whereas altitude is considered as theindependent variable. The results are given in Table 3 and shown in Figure 2. In the results given in Table 3, the coefficient of altitude = -0.271 indicates that there is negative effect of altitude on RF concentration i.e. for one thousand ft increase in altitude from sea level, an average of 0.271 µg g^-1 decrease will occur in RF concentration. The p value = 0.044 indicates that the effect of altitude on the RF concentration in honey is statistically significant.

Table 3 Effect of altitude on RF concentration in honey

Model	Coefficients		t-value	P-value
Model	β	Std. Error	t-value	P-value
(Constant)	1.674	0.360	4.654	0.000
Altitude	-0.271	0.125	-2.170	0.044

a. Dependent variable: RF Concentration (µg g^-1) b. Independent variable: Altitude

3.3.2 Effect of season of honey formation on RF concentration

To study the effect of season on RF concentration in honey, RF concentration was taken asthe dependent variable while the season (i.e. winter, spring, summer and autumn) was considered as the independent variable. Since season is a categorical variable therefore, the concept of dummy variable is used in regression. As there are four categories of the season therefore three dummy variables, winter, spring, and summer were included in the regression and the left-over category i.e. autumn was taken as the base category. The results are given in Table 4 and shown in Figure 3. From the results given in Table 4 it can be observed that the value of left-over category of season (i.e. autumn) = 1.370 indicating that on the average RF concentration in honey is 1.370 (µg g^-1) in autumn season. And P-value indicates that the result is statistically significant. The coefficients of winter season = -0.171 shows that RF concentration in winter season decreases by 0.171 (µg g^-1) from autumn season, but is not statistically significant. Whereas the coefficient of spring season = -0.937 shows that RF concentration in spring season decreases by 0.937 (µg g^-1) from autumn season and P-value = 0.048 indicates that the result is statistically significant. Similarly, the coefficient of summer season = -0.386 shows that RF concentration in summer season decreases by 0.386 (µg g^-1) from autumn season and P-value = 0.044 indicates that the result is statistically significant.

Table 4 Effect of sampling season on RF concentration in honey

Model	Coefficients		t	Significance
Model	β	Std. Error	t	Significance
(Constant)	1.370	0.436	3.141	0.006
Winter	-0.171	0.504	-0.339	0.739
Spring	-0.937	0.516	-2.316	0.048
Summer	-0.386	0.495	-2.780	0.044

Dependent variable: Rf concentration (µg g^-1)
Independent variables: seasons

3.3.3 Effect of bee size on RF concentration in honey

Investigating the effect of bee size on RF concentration in honey, the dependent variable is RF concentration whereas bee size (i.e. small, medium, big) is considered as the independent variable. Since bee size is a categorical variable therefore, the concept of dummy variable is used in regression. As there are three categories of the bee size therefore, 2 dummy variables middle and big are included in the regression and the left-over category i.e. small is taken as the base category. The results are given in table 5 and shown in Figure 4. While the Table 5 shows the regression results of RF concentration on bee size. From the results it can be observed from the value of left-over category of bee size (i.e. small) = 1.176 indicating that on the average RF concentration in honey is 1.176 (µg g^-1) from small size bee. The P-value indicates that the result is statistically significant. The coefficients of medium size bee = -0.333 which shows that RF concentration from medium size bee decreases by 0.333 (µg g^-1) from small size bee and the results are statistically significant as the P-value = 0.033. Whereas, the coefficient of big size bee = -0.263 shows that RF concentration from big size bee decreases by 0.937 (µg g^-1) from small size bee but the results are not statistically significant as clear from the P-value = 0.638.

Table 5 Effect of bee size on RF concentration in honey

Model	Coefficients		t	P-value
	β	Std. Error
(Constant)	1.176	0.275	4.277		0.001
Medium	-0.333	0.337	-0.990		0.033
Large	-0.263	0.550	-0.479		0.638

Dependent variable: RF concentration (µg g^-1)
Independent variable: Bee size

3.3.4 Effect of flower type on RF concentration in honey

The effect of flower type on RF concentration in honey was studied in which the dependent variable is RF concentration whereas flower type (i.e. Ziziphus, Multi floral, Brassica and Acacia flowers) is considered as the independent variable. Since flower type is a categorical variable therefore, the concept of dummy variable is used in regression. As there are four categories of the flower type therefore 3 dummy variables multi floral, brassica and acacia are included in the regression and the left-over category i.e. Ziziphus is taken as the base category. The results are given in the table 6 and shown in Figure 5. While Table 6 shows the results of regression RF concentration on flower type. From the results it can be observed that the value of left-over category of flower type (i.e. Ziziphus) = 1.242 indicating that on the average RF concentration in honey is 1.242 (µg g^-1) from Ziziphus flower and P-value indicates that the result is statistically significant. The coefficients of multi floral samples = -0.497 which shows that RF concentration from multiflora flower is less than Ziziphus flower by 0.497 (µg g^-1), and from P-value = 0.021 the result is statistically significant. Whereas, the coefficient of brassica flower = -1.052 which shows that RF concentration from brassica flower is less than Ziziphus flower by 1.052 (µg g^-1) and P-value = 0.048 indicates that the result is statistically significant. Similarly, the coefficient of acacia flower = -0.294 which shows that RF concentration from acacia flower is less than Ziziphus flower by 0.294 (µg g^-1). P-value indicates that the result is not statistically significant.

Table 6 Effect of flower type on RF concentration in honey

Model	Coefficients		t value	Significance
Model	β	Std. Error	t value	Significance
(Constant)	1.242	0.219	5.663	0.000
Multifloral	-0.497	0.380	-1.307	0.021
Brassica	-1.052	0.490	-2.144	0.048
Acacia	-0.294	0.335	-0.876	0.394

Dependent variable: RF concentration (µg g^-1)
Independent variable: flower type

The primary objective of this study was to gather honey samples from diverse geographical and climatic regions within Khyber Pakhtunkhwa and subsequently analyze them to determine their riboflavin content. The quantification of riboflavin, which inherently exhibits fluorescence, was achieved through the use of spectrofluorimetry. Riboflavin exhibits distinct fluorescence spectra, characterized by its maximum excitation at 464 nm, followed by an emission peak at 525 nm. Furthermore, we investigated the influence of various external factors on the riboflavin concentration in the collected honey samples. These factors included the species of honey bees, the altitude of the sampling locations, the types of flowers from which the nectar was sourced, and the seasons during which the samples were collected. Statistically, we evaluated how these factors affected the riboflavin levels in the honey. Our findings revealed that honey samples collected from lower altitudes exhibited a notably higher riboflavin concentration, averaging at 1.156 ± 0.08 µg g^− 1. Similarly, samples gathered during the autumn season consistently demonstrated the highest average riboflavin concentration, reaching 1.37 ± 0.06 µg/g^− 1, surpassing those collected during other seasons. Additionally, we delved into the influence of the floral source of nectar and discovered that honey samples obtained from regions where nectar was derived from Ziziphus plants boasted the highest riboflavin concentration, averaging at 1.383 ± 0.1 µg g^− 1. Moreover, we explored the connection between the size of honey bees and riboflavin concentration, finding that samples collected from hives of smaller honey bees displayed the maximum riboflavin concentration, measuring 1.176 ± 0.07 µg g^− 1. This study underscores, the composition of honey may vary significantly based on external factors, encompassing an array of vitamins and other nutritional constituents.

Acknowledgment: The authors extend their appreciation to the Researchers supporting project number (RSP2023R349) King Saud University, Riyad, Saudi Arabia

Declaration of interest: Not applicable

Funding: The current study was supported by Researchers supporting project number (RSP2023R349) King Saud University, Riyad, Saudi Arabia

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No competing interests reported.

Exploring Riboflavin Quantification in Honey via Spectrofluorimetry: A Statistical Examination of Influential Extrinsic Variables

Status:

Version 1

Abstract

Figures

1. Introduction

2. Experimental Section

3. Results and Discussion

4. Conclusions

Declarations

References

Additional Declarations

Status:

Version 1