Storage duration impact on the nutritional quality of honey from Burkina Faso

Introduction

Natural honey is a major product, one of the most widely consumed and produced foods worldwide, requiring no further processing. It has pleasant sensory characteristics, such as a light color and an easily identifiable flavor and aroma (Tripodi et al., 2025). The main nutritional and health-promoting components are carbohydrates, primarily fructose and glucose, as well as several oligosaccharides (Hossain et al., 2023; Santos-Buelga and González-Paramás, 2025). In addition, it contains low concentrations of proteins, enzymes, amino acids, minerals, trace elements, vitamins, aromatic compounds, methylglyoxal, and polyphenols (Mduda and Kalonga, 2025). This composition has the potential to display biological properties. Honey plays an essential role in human nutrition as a natural alternative to sugar, and it also serves as a raw material in many industrial products (Mduda et al., 2025). Contrary to popular belief, the glycemic index of honey can vary significantly, ranging from 32 to 85 depending on the botanical source. It is important to note that not all bee products have the same glycemic profiles, and that honey’s impact on blood sugar levels is not solely related to its glycemic index, but also to other specific biological characteristics. For instance, despite the potential risks associated with wild honey, it is still produced using traditional methods and marketed as an alternative remedy for various health conditions, such as hyperglycemia and pain (Vit et al., 2025). Some varieties of honey have high antioxidant and antimicrobial properties and are generally known as “medicinal honey” or “apitherapeutic honey.” Honey has been shown to positively affect blood pressure and reduce the risk of cardiovascular events, such as heart attacks and strokes (Vit et al., 2025). These properties are attributed to the presence of antioxidant compounds, minerals, and vitamins (Velimirović et al., 2023). Research has indicated that the floral origin of honey can impact its nutritional profile. Honey is a natural product that can contain high concentrations of amino acids, vitamins such as B6, thiamine, niacin, riboflavin, and pantothenic acid (Chua et al., 2013). These components contribute to the product’s immune-boosting properties (Gebreyes et al., 2025). Honey is a natural product that contains significant amounts of essential minerals such as calcium, copper, iron, magnesium, and manganese (Haider et al., 2024; Altunatmaz et al., 2018). Research has shown that the presence of copper and manganese in honey is directly linked to its ability to stimulate hemoglobin production in the body (Santos-Buelga and González-Paramás, 2025). The most significant enzymes present in honey are invertase, amylase, and glucose oxidase. They are indispensable to produce honey from sugar. Research indicates that the enzyme glucose oxidase facilitates the breakdown of glucose into gluconic acid, which contributes to calcium absorption, and hydrogen peroxide, which exhibits antimicrobial properties (Pavlović et al., 2025). In addition, invertase catalyzes the conversion of sucrose into reducing sugars, with fructose and glucose as the primary products. Concurrently, amylase enzymes digest long chains of starch, yielding dextrin and maltose. Catalase, an enzyme found in honey, plays a vital role in protecting the body from free radicals (Gebreyes et al., 2025). By breaking down hydrogen peroxide into oxygen and water, catalase ensures a healthy balance in the body. These nutritional qualities make honey a food that is highly prized by consumers for its health and wellness benefits (Tripodi et al., 2025). However, storage conditions and duration can significantly influence these properties.

Previous studies have shown that high storage temperatures can increase 5-Hydroxymethylfurfural (5-HMF) levels and reduce enzymatic activity in honey, thereby affecting its quality (Sawarkar, 2024). During storage, 5-HMF formation in honey results from the thermal dehydration of sugars, particularly fructose and glucose (Yang et al., 2019). Therefore, accurate quantitative analysis of 5-HMF is of great importance, as high 5-HMF content is a key indicator of the impact of heat or adulteration practices on honey.

In addition to being an indicator of the degree of spoilage or aging in honey, 5-sulfooxymethylfurfural (SMF), an electrophilic metabolite of 5-HMF, is toxic when its concentration is too high (Bauer-Marinovic et al., 2012). Consequently, Abraham et al. (2011) and Elmaoğulları et al. (2020) confirmed, respectively, the presence of urinary and reproductive disorders in laboratory rats after the ingestion of high levels of 5-HMF. Furthermore, recent research by Qin et al. (2026) has shown that 5-HMF is highly toxic to human intestinal epithelial cells. Therefore, the Codex Alimentarius Commission (2022) and European Union (EU) standards limit its content to 80 mg/kg in honeys produced in tropical regions.

In Burkina Faso, honey is widely produced under tropical conditions where high temperatures and traditional storage practices may accelerate quality deterioration. However, limited studies have evaluated the effect of storage duration on its nutritional quality. Taking this requirement into account, this study aims to evaluate the effect of storage time on honey produced at the beekeeping center in Koudougou, Burkina Faso.

Materials and methods

Sample collection site

The honey samples were collected at the beekeeping center located in sector 5 of the city of Koudougou (12°15′03.2″N, 02°19′52.2″W), in the municipality of Boulkiemdé, Burkina Faso (Figure 1). This beekeeping center purchases honey from the honey-producing regions of Burkina Faso and stores it in warehouses before processing it.

Biological material

The biological material used for this study is honey produced by the West African honeybee species, Apis mellifera adansonii Latreille. The stratified sampling method was used to collect honey samples. The collection consists of fifteen (15) samples, grouped into three (3) batches of five samples each, according to their respective harvest dates in 2020, 2021, and 2022. These samples originate from honey harvested during the peak March honey flow in four regions of Burkina Faso: Centre-West, Cascades, Hauts-Bassins and Boucle du Mouhoun. The samples were collected in amber bottles between March and August 2022. All samples were extracted by pressing and subsequently stored at room temperature in the honey house’s storage facilities. Following collection, the samples were meticulously labeled by geographic origin (Table 1) and transported to the designated laboratory. They were then stored at room temperature under relative humidity and temperature conditions set at 35%–65% and 25 °C–32 °C, respectively.

TABLE 1. Codes of the fifteen honey samples according to the year of harvest and their geographical origin.

Analytical methods

electrical conductivity

The electrical conductivity of honey was measured with a conductivity meter (Thermo Fisher Scientific, USA) following the protocol described by Bogdanov (2002). This measurement depends on the electrical resistance of the solution. The electrical conductivity of the honey solution was measured using an electrode with an electrical conductivity cell. The results are expressed in millisiemens per centimeter (mS/cm).

Determination of free acidity and pH

The pH and acidity of the honey samples were determined using the method described by Bogdanov (2002). Ten (10) g of each honey sample were homogenized in 75 mL of distilled water, and the pH of the solution was measured using a pH meter (PHS-25w, China). After measuring pH, the same honey solution from each sample was titrated with a 0.1 M NaOH solution to a pH of 8.3. The free acidity was calculated using the following formula (Equation 1):

F A c m e q K g = V x 10 (1)

FAc: Free acidity in milliequivalents of acid/kg of honey.

V: mL of NaOH poured.

Brix degree

The total soluble solids (TSS) at 20 °C, also known as sucrose content or refractive index (°Brix) of honey, were evaluated according to the protocol described by Bogdanov (2002).

A few drops of each sample were collected with a handheld digital refractometer (Atago Co., Ltd., Tokyo, Japan) to measure °Brix. The TSS results were expressed as Brix = % sucrose.

Determination of moisture content

The moisture content of honey samples was determined using the refractometric method described by Bogdanov (2002). The moisture content was estimated in g/100 g after subtracting 0.2% because the refractometer is calibrated at 20 °C.

Total polyphenol content

Total polyphenols were determined according to the method described by Singleton et al. (1999). Honey samples (1 g) were diluted in 10 mL of 80% (v/v) methanol and centrifuged at 2000 rpm. After centrifugation, the supernatant of the alcoholic honey extract was analyzed. The determination of total phenolic content (T was performed by the method of using Folin & Ciocalteu’s reagent. Optical densities were read at 760 nm using a UV-visible spectrophotometer. Total polyphenol content was determined using the gallic acid reference curve. The results were expressed in milligrams of gallic acid equivalent per 100 g of honey (mg GAE/100 g).

Total flavonoid content

Total flavonoids were quantified according to the method described by Guenné et al. (2020). The supernatant from the methanolic extracts of the honey samples was analyzed using the aluminum trichloride (AlCl3) method. The absorbance was measured at 415 nm using a UV-visible spectrophotometer. The total flavonoid content was expressed in milligrams of quercetin equivalent per 100 g of honey (mg EQ/100 g).

soluble carbohydrate content

Soluble sugar content is determined using the phenol-sulfuric acid method described by Dubois et al. (1956). In the presence of concentrated sulfuric acid. Sugars are dehydrated into compounds of the furfural derivative family (C₅H₆O₂). These products condense with phenol to form yellow-orange complexes. The formation of these complexes is monitored by measuring the increase in optical density using a UV-visible spectrophotometer at 490 nm. Concentrations were determined from a previously plotted D-glucose calibration curve. The soluble carbohydrate content was expressed in mg, E.G.,/100 mg of honey.

5-Hydroxymethylfurfural (HMF) content

The HMF content of the samples was estimated according to the method described by White (1979). This method is based on determining the absorbance of HMF at 284 nm. To avoid interference from other components at this wavelength, the difference between the absorbances of the aqueous honey solution and the same solution after the addition of sodium bisulfite was determined. Absorbances (A) were determined for the test solution at 284 nm and (B) for the reference solution at 336 nm using a UV spectrophotometer. If absorbance A was greater than 0.6, the test solution was diluted with distilled water, and the reference solution was diluted with the reference solution in equal amounts, and absorbance A was corrected for the dilution.

The absorbance B was subtracted from that of A. Then, using the calibration curve for pure HMF, the HMF concentration of each honey sample was determined and expressed in mg of HMF per kilogram of honey (mg/kg).

Evaluation of antioxidant activity by DPPH reduction test

The method for determining DPPH radical inhibition in the extract was described by Lamien-Meda et al. (2008). The principle of this method is the reduction of the stable free radical 1,1-diphenyl-2-picrylhydrazyl or α-diphenyl-β-picrylhydrazyl (DPPH) at a wavelength of 517 nm in reaction with an antioxidant. In the presence of the hydrogen atom provider, DPPH is reduced, and its initially dark purple color changes to yellow. The degree of color change is proportional to the concentration and potency of the antioxidants. A large decrease in the absorbance of the reaction mixture indicates significant scavenging activity of the compound under test (Pereira et al., 2014). The measured absorbances allowed us to calculate the percentage of DPPH radical inhibition according to the formula of (Miliauskas et al., 2004) (Equation 2):

% I = A c − A s A c × 100 (2)

(%) I: Percentage of DPPH inhibition.

Ac: Absorbance of negative control (DPPH absorbance).

As: Absorbance of the extract.

From these inhibition percentages, IC₅₀ values in mg/mL were determined.

Evaluation of antioxidant activity using iron reducing power (FRAP) test

The total antioxidant capacity of each honey sample was determined using the method of Hinneburg et al. (2006). The FRAP (Ferric Reducing Antioxidant Power) test is a method based on the reduction of ferric ions (Fe³⁺) to ferrous ions (Fe²⁺). It evaluates the reducing power of compounds in the extract. In the presence of reducing or antioxidant compounds, ferric ions are reduced to ferrous ions, whose absorption maximum is located around 700 nm. The reducing potential of the iron in honey was expressed in mg EAA/100 mg of honey using an ascorbic acid standard curve.

Statistical analysis

The results were processed and formatted using Excel 2019. The statistical analysis of our results was performed using XLSTAT 2016. It consisted of an analysis of variance (ANOVA) with Tukey’s test at a 5% significance level to compare means. R version 4.5.0 (2025–04-11ucrt) was used to perform principal component analysis (PCA) and generate the graphs.

Results and discussion

Results

The results for physicochemical parameters such as electrical conductivity, pH, free acidity, Brix, and moisture content are recorded in Table 2 below. These parameters are essential for honey quality. Analysis of variance (ANOVA) reveals highly significant differences among the physicochemical characteristics. Electrical conductivity ranges from 0.57 ± 0.00 (HN7-2021) to 1.18 m/cm ± 0.06 (HN2-2022 and HN6-2021). Only honeys (HN2-2022) and (HN6-2021) have an electrical conductivity above 1 m/cm. The pH and free acidity ranged from 4.02 ± 0.00 (HN10-2020, HN18-2020, HN2-2022) to 4.43 ± 0.00 (HN21-2022), and from 4.67 ± 0.57 (HN21-2022) to 15.33 meq/kg ±2.08 (HN6-2021), respectively. The °Brix of the honeys ranged from 76.97 ± 0.12 (HN4-2022) to 82.00% ± 0.1 (HN13-2021). The moisture content ranged from 16.53 ± 0.06 (HN20-2021) to 22.30% ± 0.17 (HN4-2022).

TABLE 2. Physicochemical parameters of honey samples.

HN5-2020: Honey from Batch 5 of 2020; HN7-2021: Honey from Batch 7 of 2021; HN1-2022: Honey from Batch 1 of 2022.

ECd: Electrical Conductivity; FAc: Free Acidity; MC: Moisture content.

Codex Alimentarius Commission (CXS, 12–1981, revised 1987, 2001; amended 2019, 2022).

Averages in the same column but not sharing the same letter are significantly different (P < 0.05).

There is no linear trend among the physicochemical characteristics in Table 2. However, the statistical data on average physicochemical parameters as a function of honey age (Figure 2) show significant differences (p < 0.05) in pH, moisture, free acidity, and °Brix. Thus, the comparison of the average pH, free acidity, and moisture shows that the 2020 honeys are more acidic with a higher moisture content compared to the 2021 and 2022 honeys. Conversely, the average °Brix of the 2021 honeys is higher, followed by that of the 2020 honeys, and then that of the 2022 honeys.

The total phenolic compounds, flavonoids, soluble carbohydrates, and HMF content of the 15 honey samples are presented in Table 3. Analysis of variance (ANOVA) reveals highly significant differences among the levels of these biochemical compounds. The total polyphenol content ranged from 635.86 ± 2.33 (HN12-2021) to 2,784.65 mg GAE/100 g ± 1.90 (HN20-2021), with high values (1,702.23 ± 4.84 to 2,037.64 ± 26.07) recorded in the 2020 honeys. As for flavonoids, the content ranged from 0.29 ± 0.13 (HN3-2022) to 5.58 mg QE/100 g ± 1.07 (HN21-2022).

TABLE 3. Biochemical compound content of honey.

SCC: soluble carbohydrate content; HMF: hydroxymethylfulfural; GAE: gallic acid equivalent; QE: quercetin equivalent; GE: glucose equivalent.

Averages in the same column but with different letters are significantly different (P < 0.05).

Total soluble carbohydrate and HMF levels ranged from 39.34 ± 0.2 (HN13-2021) to 88.74 mg, E.G.,/100 mg ± 2.03 (HN8-2020), and from 192.61 ± 13.34 (HN4-2022) to 1,270.63 mg/kg ± 6.72 (HN13-2021), respectively. The values of these two parameters are higher in the 2020 honeys. The high HMF content of the 2020 honey samples indicates that HMF formation is influenced by storage time.

Figure 3 shows a significant difference between the mean polyphenol, 5-HMF, and total soluble carbohydrate levels as a function of honey age (p < 0.05). Comparing these averages shows that the 2020 honeys have a higher polyphenol, 5-HMF, and total soluble carbohydrate content compared to the 2021 and 2022 honeys.

The iron-reducing power (FRAP) and DPPH radical-inhibiting power of the different honey samples are presented in Table 4. Analysis of variance (ANOVA) reveals significant differences in the antioxidant activities of our honey extracts.

TABLE 4. Antioxidant power of raw honey extracts.

IC50: Median Inhibitory Concentration; FRAP: Ferric Reducing Antioxidant Power.;GAE: gallic acid equivalent; EAA: ascorbic acid equivalent.

Averages in the same column but not sharing the same letter are significantly different (P < 0.05).

The IC₅₀ and iron-reducing power range from 4.07 ± 0.06 (HN8-2020) to 31.67 mg GAE/mL ± 2.89 (HN6-2021), and from 1.72 ± 0.04 (HN1-2022) to 4.22 mg EAA/100 mg ± 0.16 (HN18-2020), respectively. As indicated by the average IC₅₀ and iron-reducing power (Figure 4), the best free radical scavenging (low IC₅₀) and reducing power of ferric ions (Fe³⁺) to ferrous ions (Fe²⁺) are exhibited by the honeys from the 2020 batches. Therefore, it could be argued that the storage time of honey may improve its antioxidant capacity.

Based on the data in Table 5, the results show a negative correlation between pH and free acidity (r = −0.599), total soluble carbohydrate content (r = −0.533), and 5-HMF content (r = −0.707). Similarly, a negative correlation was observed between moisture content and °Brix (r = −0.983). Conversely, a positive correlation existed between total polyphenol content and total soluble carbohydrate content (r = 0.646), electrical conductivity (r = 0.510), and free acidity (r = 0.721). Furthermore, a positive correlation was observed between electrical conductivity and free acidity (0.790). Compared with the analyzed samples, we observed that the 3-year-old honey samples (2020 honey) and those from batches HN6-2021, HN20-2021, and HN2-2022 exhibited higher levels of total phenolic compounds, HMF, soluble carbohydrates, free acidity, electrical conductivity, and antioxidant activity (FRAP).

TABLE 5. Correlation matrix between variables (Pearson).

PC: phenolic content; FC: flavonoid content; SCC: soluble carbohydrate content; ECd: Electrical Conductivity; FAc: Free Acidity; MC: moisture content; IC50: Median Inhibitory Concentration; FRAP: ferric reducing antioxidant power; HMF: hydroxymethylfulfural.

Bold indicates r greater than or equal to 0.5: positive correlation between two variables. r less than or equal to −0.5: negative correlation between two variables

Principal component analysis (PCA) of the parameters shelf life, physicochemical characteristics, biochemical compounds, and antioxidant capacity revealed variation between the parameters studied and between the samples themselves (Figure 5). The results showed that the first two principal components accounted for 54.4% of the total variation (Table 6), with the first axis alone accounting for 33.4% of this variation (Figures 5, 6). Eleven characteristics primarily contributed to the overall variability of the samples studied, notably physicochemical characteristics, biochemical compounds, and antioxidant capacity. Dim1 (33.4%) was primarily characterized by positive co-variation with FRAP, total phenolic content (TP), free acidity (FAc), electrical conductivity (ECd), moisture content (MC), and 5-hydroxymethylfurfural (HMF), while IC50, total flavonoid content (TF), and pH exhibited an inverse variation along this axis. For Dim2 (21%), FRAP, HMF, TF, and IC50 showed positive associations, whereas the remaining variables exhibited inverse associations with this component (Figure 5). The first principal component Dim1 (33.4%) appears to allow for better separation between regions than the second component (Dim2). The two-dimensional plot (Figure 6), based on the geographic origin of the samples (Cascades, Boucle du Mouhoun, Centre-Ouest, and Hauts-Bassins), revealed an overlap of the confidence ellipses.

TABLE 6. Percentage of variance explained by each principal component.

Discussion

Physicochemical parameters of honey

The assessment of the impact of storage time on the physicochemical parameters of honey first shows that the moisture content of 14 of 15 samples complies with the 21% limit set by the Codex Alimentarius (2022). The moisture content of the honey samples shows a nonlinear trend. The study by Baloš, Popov and Jakši (2023) showed that the moisture content of honey remains stable, then decreases during storage in airtight containers. Therefore, the results of this study are similar to those found by Nombré et al. (2010), who reported no change in the moisture content of honeys stored for 4 years at ambient laboratory temperature. However, when the packaging is not airtight, the honey’s moisture content can increase during storage in periods of very high humidity (July, August, and September) or decrease during warmer periods (March, April) due to evaporation. Therefore, the absorption of water by honey is not related to storage time but to the hygroscopic nature of its sugars. This situation could explain why sample HN4-2022 had a moisture content exceeding the Codex Alimentarius standard (2022). A lack of airtight packaging during storage, or an early harvest, could also explain the increase or decrease in the honey’s moisture content. Conversely, according to Bakar (2020), honey loses water through evaporation when stored in non-airtight packaging during warmer periods. Furthermore, the moisture content of honey depends on the harvest period or the earliness of the harvest (Bogdanov et al., 2004; Nombré et al., 2010). A high moisture content leads to honey deterioration through fermentation (Nombré et al., 2010; Lokossou et al., 2017), resulting in high free acidity.

The °Brix, or Total Soluble Solids (TSS), is the total soluble sugar content in honey. It indicates the number of solids dissolved in a liquid (Son et al., 2009). It is a quality parameter dependent on moisture content. Therefore, the negative correlation between °Brix and moisture content shows that the variation in °Brix depends on moisture content. Consequently, honeys with a high °Brix value conversely have a low moisture content. This parameter depends on the honey’s maturity level in the hive. The nonlinear evolution of the °Brix values suggests that this parameter does not influence shelf life. However, dehydration from the evaporation of free water in the honey would increase the Brix.

Like electrical conductivity, honeydew honeys are characterized by higher pH and free acidity values than nectar honeys (Recklies et al., 2021). These two parameters are also interdependent honey quality parameters. The observed negative correlation between them confirms this independence. The significant difference observed between the mean pH and free acidity values of the samples indicates that storage time may affect the evolution of these parameters. Consequently, the 2020 honey samples had a lower mean pH and, conversely, a higher free acidity content than the 2021 and 2022 samples (Figure 2). These results corroborate those found by Julika et al. (2022) and Chou et al. (2020) regarding the increase in free acidity content in honeys over storage time. This increase could be explained by the enzymatic or non-enzymatic hydrolysis of lactones in honeys into hydroxycarboxylic acids (Yi, et al., 2005), lactones being carboxylic acids that contribute to the acidity profile of honey.

Electrical conductivity is an indicator of the organic and inorganic content of honey. It therefore serves as a criterion for botanical classification and for determining honey quality. According to Baloš, Popov, and Jakši (2023), storage time has no effect on electrical conductivity. The lack of significance at p < 0.05 in the mean electrical conductivity values of the samples (Figure 2) indicates that this quality parameter does not depend directly on the honey’s storage time but rather varies with the levels of ionizable organic and inorganic substances (Estevinho et al., 2013). The positive correlation between electrical conductivity and free acidity indicates that electrical conductivity varies with free acidity content in honey. The electrical conductivity values are similar to those obtained by Nombré et al. (2010) in honeys stored for 1–4 years. Among our samples, only HN6-2021 (honey from the Boucle du Mouhoun) and HN2-2022 (honey from the Hauts-Bassins) each have a value greater than 0.8 m/cm. These two samples are thought to consist primarily of honeydew or a mixture of flower honeys (Bogdanov et al., 2004).

Biochemical composition of honey

Total soluble carbohydrates are the most abundant primary biochemical compounds in honey. Their content generally does not exceed 82.3% (Baglio, 2018). The total soluble carbohydrate content of all honey samples is within the limits set by the standard of Codex Alimentarius (2001). Statistical data reveal that time has a significant effect on the total soluble carbohydrate content of honey. Honeys from 2020 had a higher average total soluble carbohydrate content than honeys from 2021 and 2022. Considering the production date, the 2020 samples have higher values than those of the 2021 and 2022 samples. Prolonged storage of honey could lead to an increase in invert sugars (glucose and fructose) through the continuous enzymatic hydrolysis of disaccharides in nectar or honeydew. However, the total soluble carbohydrate content of honey varies depending on the initial sugar content in the flower nectar (Can et al., 2015).

5-HMF is an important indicator of honey quality. An excessively high concentration of 5-HMF (>80 meq/kg) indicates advanced honey spoilage. The 5-HMF levels are significantly higher than the Codex Alimentarius (2022) HMF limit of 80 mg/kg for countries in tropical zones. Statistical data indicate a significant difference in average 5-HMF levels among samples by harvest year. To this end, the 2020 samples had an average 5-HMF content significantly higher than that of 2021 and 2022, indicating that storage time increases 5-HMF content in honey. The results are corroborated by those of Nombré et al. (2010) and Chou et al. (2020) on the effect of storage time on honey. Studies conducted by Sawarkar (2024) have shown that processing or storing honey at temperatures above 45 °C for 5 h increases HMF levels from 33.55 to 48.21 mg/kg. The negative correlation observed between 5-HMF content and pH values, associated with a highly significant p-value (p = 0.000), indicates that honey pH plays a determining role in 5-HMF formation. Indeed, a low pH promotes an increase in this molecule. This result is consistent with the work of Yang et al. (2019), who demonstrated faster formation of 5-HMF in acidic environments. Given the furan structure of 5-HMF, its formation would primarily result from the dehydration of fructose in acidic conditions (Kowalski et al., 2013; Yang et al., 2019). According to Bogdanov (1999), the time required to form 40 mg/kg of HMF in honey at 20 °C is between 2 and 4 years. Consequently, it seems advisable for beekeeping centers to strengthen their honey-processing capacities upon receipt to limit prolonged storage, particularly in tropical countries with naturally high temperatures.

Phytochemicals such as polyphenols are secondary metabolites with antioxidant properties. The medicinal properties of honeys depend on their composition of these secondary metabolites. Honeys are considered therapeutic for their phenolic content, as these compounds play an important role in the proper functioning of the body by counteracting oxidative stress by eliminating free radicals (Can et al., 2015). Storage time appears to influence the concentration of total polyphenols in honey, as evidenced by the significant difference in the mean total polyphenol content among the honey samples. Consequently, the total polyphenol content of the 2020 honeys is high compared to the 2021 and 2022 honeys. Monggudal et al. (2018), Chou et al. (2020), and Yaacob et al. (2020) also observed a significant increase in total polyphenol concentration in honeys over time. The work of Mouhoubi (2007) showed that the phenolic compound content increases during honey storage at 35 °C.

The positive correlations observed among total polyphenol content, soluble carbohydrate content, electrical conductivity, and free acidity suggest a close relationship among these parameters. This relationship could increase total polyphenol content through complex chemical or physicochemical interactions among these parameters. Peng et al. (2025) demonstrated that the epigallocatechin-3-gallate content increased when they prepared the covalent polysaccharide-epigallocatechin-3-gallate complex.

The absence of significant differences between the mean total flavonoid content (Figure 3) indicates that this parameter does not increase in honey over its storage time. Šari et al (2020) confirmed in their work a non-significant change in total flavonoid content in honey over time.

Antioxidant capacity of honey (DPPH and FRAP)

Honey samples from 2020 exhibited significantly higher scavenging (DPPH) and reducing (FRAP) capacities than honeys from 2021 and 2022. Therefore, storage time could influence the increase in the scavenging and reducing capacities of our honey extracts. The works of Turkmen et al. (2006) and Mouhoubi (2007) showed that the reducing and scavenging capacities of honey increase over time. However, Chou et al. (2020) observed a decrease in antioxidant activity over time. Indeed, during storage, the Maillard reaction and non-enzymatic browning, which exhibit antioxidant activity, could compensate for the loss of natural antioxidants in honey. The increase in scavenging and reducing activity would thus be linked to aging and the products formed in honey during storage. One of the compounds that could be formed by the Maillard reaction or by non-enzymatic browning is 5-HMF. The higher free radical scavenging activity observed in the 2020 honeys is likely due to their higher 5-HMF content. Zhao et al. (2013) demonstrated the free radical-scavenging activity of 5-HMF in vitro at doses ranging from 0.8 to 6.4 mM.

Principal component analysis (PCA)

Principal component analysis (PCA) revealed a structured pattern of variability among the honey samples studied, reflecting strong interrelationships between physicochemical characteristics, biochemical compounds, antioxidant capacity, and shelf-life parameters. The first two principal components accounted for more than half of the total variation (54.4%), indicating that these axes effectively summarize the key information contained in the dataset, with the first component alone explaining 33.4% of the variability. The first principal component represents a major gradient describing the overall evolution of honey quality. It is primarily determined by variables associated with acidity, electrical conductivity, phenolic compound content, antioxidant capacity, and the formation of degradation products such as 5-hydroxymethylfurfural. In contrast, variables related to higher pH, certain antioxidant measures (IC50), and flavonoid content contribute negatively to this axis. This pattern suggests that Dim1 reflects a continuum from more stable, less processed honey samples to those exhibiting greater maturation, biochemical transformation, or degradation. The second principal component, primarily associated with antioxidant properties and specific bioactive compounds, indicates that antioxidant responses are not fully captured by the main compositional gradient and may be influenced by secondary biochemical processes or variations in the distribution of bioactive molecules. Overall, the multivariate structure suggests that honey quality is governed by interconnected processes involving acidification, ionic enrichment, the accumulation of phenolic compounds, and the formation of storage-related compounds. This finding is consistent with recent studies highlighting strong interactions among these various quality indicators (Schaffel et al., 2025; Filipe et al., 2024). These processes likely result from the combined effects of storage duration, environmental conditions, and botanical origin, acting simultaneously on the physicochemical and functional properties of honey. Recent research led by Gela et al. (2023) confirms that the nutritional quality of honey is primarily influenced by its botanical and environmental origins. Furthermore, the overlap observed in the PCA plot indicates that honey samples from different regions share broadly similar physicochemical, biochemical, and antioxidant profiles in accordance with their geographic origin. Nevertheless, the incomplete overlap of the confidence ellipses suggests partial discrimination among samples by geographic origin.

Conclusion

This study examined the impact of storage time on the quality of honeys produced at the Koudougou beekeeping center. The study found that honey storage time did not affect electrical conductivity but did affect pH, free acidity, °Brix, and moisture content. Despite the effect of time, the values of the physicochemical parameters of the fifteen samples were within the range of the Codex Alimentarius standards (2022). Except for flavonoid content, all biochemical parameters, as well as the free radical-scavenging and reducing capacities of the analyzed honeys, showed significant changes with age. The 2020 honeys were distinguished by their superior antioxidant activity and high levels of total soluble carbohydrates and total phenolic compounds. However, they also exhibit particularly high concentrations of 5-HMF. The high levels of 5-HMF in the 2020 samples indicated that spoilage intensifies during room-temperature storage of honey. In this context, the alternative for significantly reducing 5-HMF formation over a long period is to store honey at a temperature below 20 °C. In the absence of cold storage, facilities that increase the processing capacity of honey houses in Burkina Faso could be an alternative to reduce the 5-HMF content in honey. Furthermore, immediate measurement of 5-HMF levels before receipt of honey could be considered to detect honey that has been heated during harvesting or extraction. To further assess honey quality, research could focus on the following areas:

• Determining the diastase activity of collected honeys;
• Evaluating the biological effects of honey on an experimental animal model of asthma.

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Footnotes

Edited by: Vinay Kumar Pandey, Graphic Era Deemed to be University, India

Reviewed by: Aline Rodrigues, Federal University of Paraná, Brazil

Rohini Sharma, Dr. Yashwant Singh Parmar University of Horticulture and Forestry, India