Next Article in Journal
The Interplay of Pro-Innovative Behavior, Trust, and Farm Viability for Sustainability in the United Winemaking Agricultural Cooperative of Samos
Previous Article in Journal
Research on the Design of an Omnidirectional Leveling System and Adaptive Sliding Mode Control for Tracked Agricultural Chassis in Hilly and Mountainous Terrain
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agriculture
Volume 15
Issue 18
10.3390/agriculture15181922
agriculture-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Seasonal Variation in Nutritional, Physicochemical, and Mineral Composition of Honeybee Pollen in Southern Kazakhstan

by
Gaukhar Moldakhmetova
1,
Aibyn Torekhanov
1,
Aigul Tajiyeva
1,
Ulzhan Nuraliyeva
1,
Oleg Krupskiy
1,
Gulim Khalykova
1,
Nurgul Myrzabayeva
2 and
Maxat Toishimanov
2,*
1
Kazakh Research Institute of Livestock and Fodder Production, Almaty 050035, Kazakhstan
2
Food and Environment Safety Laboratory, Kazakh National Agrarian Research University, Almaty 050010, Kazakhstan
*
Author to whom correspondence should be addressed.
Agriculture 2025, 15(18), 1922; https://doi.org/10.3390/agriculture15181922
Submission received: 10 August 2025 / Revised: 6 September 2025 / Accepted: 8 September 2025 / Published: 10 September 2025
(This article belongs to the Section Agricultural Product Quality and Safety)
Browse Figures
Versions Notes

Abstract

Honeybee pollen is widely recognized as a functional apicultural product due to its rich nutritional profile, but its composition is strongly influenced by seasonality and floral availability. Understanding these seasonal dynamics is critical for optimizing the nutritional and bioactive quality of bee-collected pollen. This study investigated the seasonal variation in the physicochemical and mineral composition of honeybee pollen collected monthly from April to September 2024 from an apiary in the Tulkibas district, Turkistan region, Kazakhstan. Pollen samples were analyzed for key quality parameters, including moisture, protein, fat, fiber, carbohydrates, starch, ash, and minerals (Ca, P, K, Mg, Na, Cu, Fe, Zn). Moisture, protein, fat, fiber, starch, and ash were determined using standard AOAC methods, while minerals were quantified by flame atomic absorption spectrophotometry (Ca, Cu, Fe, Mg, Zn; Analytik Jena novAA 350), flame emission spectrophotometry (Na, K), and the molybdenum blue colorimetric method (P). The moisture content decreased significantly from 10.34 ± 1.74% in April to 5.23 ± 0.86% in June (p = 0.0030), while protein increased from 20.28 ± 2.13% to a peak of 23.66 ± 1.70% in June (p = 0.0268). The fat content reached its maximum in July at 8.67 ± 0.11% (p = 0.0446), and carbohydrates peaked at 14.41 ± 0.11% in the same month. Among minerals, Fe and Zn showed substantial increases, with iron rising from 47.51 ± 5.69 mg/kg in April to 143.39 ± 6.58 mg/kg in July (p = 0.0388), and Zn from 38.56 ± 2.36 mg/kg to 57.14 ± 8.54 mg/kg (p = 0.0302). Principal Component Analysis (PCA) and Pearson correlation confirmed strong seasonal clustering and nutrient interrelationships. These findings highlight the superior nutritional value of mid- to late-season pollen and underscore the importance of the harvest timing in optimizing the bioactive profile of bee-collected pollen for apicultural and functional food applications.

1. Introduction

Honeybee pollen is a valuable apicultural product widely recognized for its rich nutritional profile, containing a balanced composition of proteins, lipids, carbohydrates, vitamins, and minerals. It serves not only as the primary protein source for the hive but also as a highly regarded dietary supplement in human nutrition due to its antioxidant, antimicrobial, and immunomodulatory properties [1,2,3,4]. The chemical composition of bee-collected pollen can vary significantly depending on botanical origin, geographical region, and environmental factors [5,6]. Among these, seasonality—closely tied to the floral landscape—plays a pivotal role in determining the physicochemical and mineral characteristics of pollen [7,8,9]. Several studies have shown that pollen collected during different flowering seasons can vary in its macronutrient and micronutrient contents [10,11,12]. Early-spring pollen is often characterized by higher moisture and lower nutrient density due to early-bloom conditions, while mid- to late-summer pollen tends to be more concentrated in protein, fat, and bioavailable minerals such as zinc and iron [13]. These seasonal changes are not only critical for colony development and brood rearing but also affect the quality of bee pollen marketed as a functional food product.
While botanical origin and seasonal timing are well-established factors influencing pollen quality, the role of the honeybee breed has received comparatively less attention. In Kazakhstan, Apis mellifera carnica is the dominant subspecies used in apiculture, particularly in the southern and southeastern regions, due to its adaptability to local environmental conditions and favorable foraging behavior [14,15]. For instance, A. m. carnica, A. m. caucasica, and regional hybrids differ in their efficiencies of pollen collection and floral preferences, leading to measurable differences in the protein, lipid, and mineral contents of the harvested pollen [16,17]. Therefore, in studies aiming to characterize pollen quality, accounting for the genetic background of the bee population is critical. In this context, our research controlled such variability by using a single migratory apiary managed under uniform conditions throughout the flowering season, allowing us to isolate the influence of the seasonal floral dynamics while minimizing confounding effects from honeybee genetic variation.
Several studies have attempted to characterize seasonal changes in bee pollen compositions across Europe, South America, and Asia. For example, Almeida-Muradian et al. [18] reported significant increases in the protein and ash contents in Brazilian pollen collected during the dry season compared to the rainy season. Al-Kahtani et al. [19] noted seasonal variation in amino acids, showing distinct monthly patterns. Similarly, Negrão et al. [19] highlighted the effect of regional flora on the physicochemical quality of pollen collected in different seasons, emphasizing the importance of climate and landscape. However, most of these studies rely on multi-site sampling, introducing variability due to differing plant communities, elevations, and microclimates. This makes it challenging to isolate the true effect of seasonality on pollen composition.
The Turkistan region of southern Kazakhstan, characterized by a semi-arid climate and diverse flowering flora from spring to early autumn, provides an ideal natural setting to study such seasonal variation. According to melissopalynological surveys conducted in southern Kazakhstan [20], the main melliferous and polleniferous plants in the Tulkibas district include Salvia sp., Thymus sp., Tamarix sp., Artemisia sp., Helianthus annuus (sunflower), Onobrychis viciifolia (sainfoin), Gossypium hirsutum (cotton), and various Fabaceae and Asteraceae spp. These reflect clear spatial and phenological transitions across seasons [20]. Recent genetic and ecological surveys confirm that this region—along with southeastern Kazakhstan—features both a favorable climate and high floral biodiversity, supporting intensive beekeeping activity [21]. Moreover, migratory beekeeping is widespread in Kazakhstan—with nearly 90% of apiaries employing within-region hive movements—allowing colonies to track floral succession without long-distance relocation, thereby minimizing geographic confounding in pollen composition studies [22].
The present study aimed to investigate the seasonal dynamics in the physicochemical and mineral composition of bee pollen collected monthly from a migratory apiary in the Tulkibas district, Turkestan region, Kazakhstan. The quality parameters assessed included moisture, protein, fat, fiber, ash, carbohydrates, starch, and macro- and microelements (Ca, P, K, Mg, Na, Cu, Fe, Zn). In addition, PCA and Pearson correlation analysis were applied to detect patterns, clustering, and inter-variable relationships throughout the six-month harvest period. This study provides new regional insights into the nutritional value of Kazakhstani pollen and supports the standardization and valorization of bee pollen as a functional product.

2. Materials and Methods

2.1. Sample Collection

Pollen samples were collected from a single nomadic beekeeping operation located within the Balykty settlement area of the Tulkibas district, Turkistan region, Kazakhstan (42°35′05.2″ N, 70°02′14.0″ E), as shown in Figure 1. A total of 37 honeybee colonies were used for sampling, all belonging to the species Apis mellifera carnica. The uniqueness of this study lies in the fact that all samples originated from one apiary, which practices seasonal migration within the same locality to follow the floral availability. Pollen loads were collected monthly from April to September during active foraging periods using standard pollen traps installed at the hive entrances.
Pollen was harvested using pre-flight pollen traps mounted on the front walls of standard beehives. These traps were designed to close both the upper and lower hive entrances from the outside and forced forager bees to pass through a pollen-collecting grid composed of holes with a diameter of 4.9 ± 0.1 mm. As bees entered the hive, part of the corbicular pollen loads were mechanically dislodged and fell into a collection tray located beneath the grid. This tray was covered with a mesh net featuring holes of 3.0–3.8 mm in diameter, which retained the pollen while allowing smaller debris to pass through.
Pollen collection was conducted throughout the entire active foraging season, beginning in early spring (upon removal of hives from the wintering facility) and continuing until late autumn (before returning the colonies to wintering). Samples were removed from the traps every three days. Following each collection, pollen loads were manually cleaned to remove extraneous material, such as wax particles and plant debris. For each month, the pooled pollen collected from all 37 colonies was thoroughly homogenized and divided into four sterile tubes, which served as four independent replicates (n = 4) for subsequent analyses. The monthly mean values reported in this study were calculated based on the analytical results of these four replicate subsamples. The composite monthly samples were then transported under ambient conditions to the laboratory for further analysis.
According to melissopalynological surveys conducted in southern Kazakhstan [20], the main melliferous and polleniferous plants in the Tulkibas district include Salvia, Thymus, Tamarix, Artemisia, Helianthus annuus (sunflower), Onobrychis viciifolia (sainfoin), Gossypium hirsutum (cotton), and various Fabaceae and Asteraceae species. These floral sources dominate different flowering periods across spring, summer, and autumn and likely contributed to the seasonal variation observed in the composition of the collected pollen.
Seasonal variation in the composition of bee pollen is strongly influenced by the availability of floral resources, which differ in botanical origin and nutritional value throughout the foraging period. In southern Kazakhstan, the Tulkibas district is characterized by diverse melliferous and polleniferous flora that bloom sequentially from early spring to autumn. Understanding these floral dynamics is important for interpreting the nutritional and mineral composition of bee pollen. Although the present study did not directly determine the floral origin of the samples, previous floristic and melissopalynological surveys from this region have documented the dominant plant species that serve as pollen sources during different months of the foraging season [20]. A summary of these monthly floral sources is presented in Table 1, providing ecological context for the observed seasonal variation in the bee pollen quality.

2.2. Chemicals, Reagents, and Standards

All chemicals and reagents used were of analytical grade. Kjeldahl tablets (K2SO4 + CuSO4 catalyst) were purchased from Velp Scientifica (Usmate Velate, Italy). Sodium hydroxide (NaOH) was purchased from Lecreactiv (Moscow, Russia). Concentrated sulfuric acid (H2SO4), hydrochloric acid (HCl), and nitric acid (HNO3) were supplied by Baza No. 1 Khimreaktivov (Moscow region, Russia). Petroleum ether for Soxhlet extraction and ethanol (≥99.5%) were purchased from Sigma-Aldrich (St. Louis, MO, USA). Analytical-grade glucose (≥99%, Sigma-Aldrich, St. Louis, MO, USA) was used as a standard for sugar analysis, while KH2PO4 was obtained from Labkhimprom (Moscow, Russia) as a phosphorus calibration standard. Multi-element stock solutions (1000 mg/L) for the atomic absorption spectrophotometry calibration of Ca, Cu, Fe, Mg, Zn, Na, and K were purchased from Ecroskhim Co., Ltd. (Moscow, Russia). Deionized water (18.2 MΩ·cm) was prepared using a Milli-Q Purification System (Millipore, Billerica, MA, USA).

2.3. Sample Analysis

2.3.1. Nutritional and Physicochemical Analysis

Moisture Content
The moisture content was determined by drying approximately 2 g of homogenized pollen in a drying oven (ULAB UT 4630, ULAB Scientific, Nanjing, China) at 105 °C until a constant weight was achieved, indicating the complete evaporation of free water, following AOAC 925.10 [24].
Protein Content
The protein content was measured using the Kjeldahl method (AOAC 984.13), which involved the acid digestion (UDK 129, Velp Scientifica, Italy) of the sample to convert organic nitrogen into ammonium, followed by neutralization and titration to quantify the total nitrogen, which was then multiplied by a conversion factor of 6.25 to estimate the crude protein [25].
Crude Fat
The crude fat content was determined by continuous solvent extraction in accordance with AOAC 920.39 [26]. Approximately 2.0 g of finely ground pollen sample was weighed into a cellulose extraction thimble and placed in a Soxhlet extractor (Soxtec 8000, FOSS Analytical, Hillerød, Denmark). Petroleum ether (boiling range: 40–60 °C) was used as the extraction solvent at a ratio of ~150 mL per sample. The extraction was performed for 6–8 h at a condensation rate of 4–6 cycles per hour, ensuring exhaustive lipid removal. Following extraction, the solvent was evaporated under reduced pressure, and the lipid residue was dried to a constant weight in a drying oven (UT 4630, ULAB Scientific, Shanghai, China) at 105 °C. The crude fat content was expressed as a percentage of dry matter. The instrument calibration and method reliability were confirmed by duplicate analyses and compliance with AOAC guidelines.
Crude Fiber
The crude fiber was determined according to the AOAC Official Method 978.10 [27]. Defatted pollen samples (~2.0 g) obtained after Soxhlet extraction were subjected to sequential acid and alkaline digestion. Samples were first boiled under reflux for 30 min with 1.25% (w/v) sulfuric acid using a controlled heating system (LH-253, LOIP, St. Petersburg, Russia). The residue was then filtered, washed with hot distilled water, and subjected to a second boiling step for 30 min with 1.25% (w/v) sodium hydroxide. Following alkaline digestion, the residue was again filtered, washed with hot distilled water, treated with 1% HCl to remove residual alkali, and rinsed with ethanol and petroleum ether. The remaining residue was dried to a constant weight at 105 °C in a convection oven (UT 4630, ULAB Scientific, Shanghai, China) and incinerated at 550 °C in a muffle (SNOL 6/7, AB UMEGA Group, Utena, Lithuania), and the crude fiber content was calculated as the difference in weight before and after ashing.
Starch
Starch was determined by the polarimetric method with matrix-specific modifications for bee pollen. Briefly, dried and ground pollen (0.5 g) was first washed 3× with 80% (v/v) ethanol (10 mL each, vortex, centrifuge) to remove soluble sugars that may have interfered with optical rotation. The residue was then treated with hot dilute HCl to dissolve starch, proteins were precipitated, and the solution was filtered. The optical rotation of the starch solution was measured at 20 ± 2 °C using a polarimeter (Polax-2L, Atago Co. Ltd., Tokyo, Japan) [27].
Ash Content
The ash content was measured by incinerating samples in a muffle furnace at 550 °C muffle (SNOL 6/7, AB UMEGA Group, Utena, Lithuania) for several hours to eliminate organic matter, leaving behind inorganic mineral residue, following AOAC 923.03 [28]
Total Sugars
Soluble sugars were determined using the phenol–sulfuric acid method. Dried and ground pollen (0.5 g) was extracted three times with 80% ethanol at 80 °C, and the combined extracts were adjusted to volume. An aliquot (1 mL) was mixed with 1 mL of 5% phenol and 5 mL of concentrated H2SO4, left for 10 min, shaken, and incubated at 30 °C for 20 min. Absorbance was measured at 490 nm using the Agilent Cary 60 UV-Visible spectrophotometer (Agilent Technologies, Santa Clara, CA, USA) against a glucose calibration curve [29].

2.3.2. Mineral Analysis

Phosphorus was determined using the molybdenum blue colorimetric method after wet digestion. Dried and ground pollen (0.5 g) was digested with concentrated HNO3 and H2O2 until clear and then diluted to a known volume. An aliquot (5 mL) was mixed with 5 mL of ammonium molybdate reagent in 5 N H2SO4 and 1 mL of 0.1 M ascorbic acid, diluted to 25 mL with distilled water, and left for 20 min at room temperature. Absorbance was read at 882 nm using the Agilent Cary 60 UV-Visible spectrophotometer (Agilent Technologies, Santa Clara, CA, USA) against a KH2PO4 calibration curve [30].
All measurements were carried out in triplicate. Calibration curves for each element were constructed using certified standard solutions, and reagent blanks were included in each set of determinations. The final results are presented as mean concentrations (mg/kg) ± standard deviation.
Calcium (Ca), copper (Cu), iron (Fe), magnesium (Mg), and zinc (Zn) contents were determined by flame atomic absorption spectrophotometry (AAS) using an Analytik Jena novAA 350 instrument (Analytik Jena, Jena, Germany), while sodium (Na) and potassium (K) were determined by flame emission spectrophotometry on the same instrument in emission mode. Approximately 0.5 g of dried pollen was dry-ashed at 550 °C for 4 h, and the resulting ash was digested with concentrated nitric acid (HNO3) and diluted to a known volume with deionized water. Flame AAS for Ca, Cu, Fe, Mg, and Zn was conducted under optimized conditions using an air–acetylene flame, element-specific hollow cathode lamps, and wavelength settings of 422.7 nm (Ca), 324.8 nm (Cu), 248.3 nm (Fe), 285.2 nm (Mg), and 213.9 nm (Zn). Flame emission measurements for Na and K were performed at 589.0 nm and 766.5 nm, respectively. Standard solutions (0.5–10 mg/L) were prepared from high-purity single-element stock standards. Calibration curves were used to quantify mineral concentrations, and quality control included reagent blanks, duplicate samples, and recovery tests. All analyses were conducted in triplicate, and results were expressed as mg/kg ± standard deviation (SD) [31].

2.4. Statistical Analysis

All experimental data were expressed as means ± SD based on triplicate determinations. One-way analysis of variance (ANOVA) was performed to assess significant differences in the pollen quality parameters across the collection months. When ANOVA indicated statistical significance (p < 0.05), Tukey’s Honest Significant Difference (HSD) post hoc test was applied to identify pairwise differences between means. Superscript letters are used in the tables to denote statistically distinct groups.
PCA was performed using JMP Pro 16.0 (SAS Institute, Cary, NC, USA) to reduce data dimensionality and explore grouping patterns and correlations among physicochemical and mineral variables. PCA biplots were constructed based on normalized and mean-centered data to visualize the sample distribution and variable loadings across the collection months.
Additionally, Pearson correlation coefficients (r) were calculated to evaluate the linear relationships between variables. Correlation heatmaps and pairwise scatterplot matrices were generated to visualize the strength and direction of associations. Significance was set at p < 0.05 for all statistical tests.

3. Results

3.1. Seasonal Variation in the Nutritional and Physicochemical Composition of Honeybee Pollen

The quality parameters of the honeybee pollen exhibited notable variations across the harvest months (April to September), as shown in Figure 2, with several components showing statistically significant seasonal trends (Table 2).
The moisture content significantly decreased from April (10.34 ± 1.74%) to June (5.23 ± 0.86%), with Tukey’s HSD confirming April > June and July (p < 0.05), and it remained relatively stable until September (7.97 ± 0.31%) (p = 0.0030), suggesting drier pollen collection in summer. The protein content ranged from 20.28 ± 2.13% in April to a peak of 23.66 ± 1.70% in June, then slightly declined (p = 0.0268, Tukey’s HSD: June > April, September). The fat content also increased significantly during warmer months, reaching a maximum of 8.67 ± 0.11% in July (p = 0.0446), differing from April and May (p < 0.05).
Although the fiber, starch, ash, phosphorus, and magnesium contents did not show statistically significant differences across months (p > 0.05), the other parameters varied considerably. The carbohydrate content increased significantly during June–August, peaking in July (14.41 ± 0.11%) (p = 0.0108).

3.2. Seasonal Variation in Mineral Composition of Honeybee Pollen

Among the minerals, calcium showed significant monthly variation, with the highest value in May (113.75 ± 16.09 mg/kg) and the lowest in September (91.58 ± 1.41 mg/kg) (p = 0.0078). The potassium levels increased significantly from April to September (p = 0.0351), while sodium, copper, iron, and zinc also exhibited significant monthly fluctuations (p < 0.05 for all). Notably, the iron content was the highest in July (143.39 ± 6.58 mg/kg), nearly threefold higher than in both April and September (47.51 ± 5.69 mg/kg) (Tukey’s HSD: July > April, September). Zinc peaked in July (57.14 ± 8.54 mg/kg), indicating enhanced micronutrient accumulation during midsummer.
In summary, the pollen collected during the peak summer months (June–August) was generally richer in protein, fat, carbohydrates, and key minerals, highlighting a seasonal influence on the nutritional and biochemical composition of bee-collected pollen.

3.3. Principal Component Analysis of Honeybee Pollen Composition

PCA was conducted to visualize patterns and relationships among the chemical and mineral quality parameters of the honeybee pollen across the different collection months. The first two principal components (PC1 and PC2) accounted for a total of 63.0% of the cumulative variance, with PC1 explaining 43.6% and PC2 explaining 19.4% of the variation (Figure 3).
PC1 was heavily loaded with positive contributions from carbohydrates (0.72), starch (0.80), fat (0.68), protein (0.65), Zn (0.76), Fe (0.78), and Cu (0.67). This component reflects the overall nutritional richness of the pollen, with higher scores indicating samples with elevated energy (carbohydrates and starch), macronutrients (protein and fat), and trace minerals (Zn, Fe, Cu). Negative loadings on PC1 were observed for moisture (ࢤ0.70) and calcium (ࢤ0.60), indicating an inverse relationship between the moisture and nutrient density.
PC2, which explained 19.4% of the variance, was characterized by high positive loadings for magnesium (0.70), sodium (0.66), ash (0.62), calcium (0.65), and fiber (0.55). This component primarily represented the mineral matrix and fibrous fraction of the pollen, distinguishing mineral-dense samples (e.g., September) from those with lower mineral contents (e.g., July).
The biplot (Figure 3) revealed distinct monthly groupings in the composition of the honeybee pollen. April and May samples were located on the negative side of PC1, associated with higher moisture and calcium but lower concentrations of protein, fat, and trace minerals, likely reflecting early floral sources with more moisture-retentive characteristics. In contrast, samples collected in June, July, and August clustered positively along PC1, indicating higher nutritional value, with elevated levels of protein, fat, sugars, Fe, Zn, and Cu—characteristics of peak floral abundance and diversity. September samples were positioned positively along PC2 and moderately along PC1, corresponding to the increased ash, potassium, magnesium, and sodium levels, thus indicating a more mineral-rich profile typical of late-season pollen. In contrast, spring samples (April–May) were positioned on the negative side of PC1, characterized by higher moisture and lower nutrient density, while autumn samples (September) were separated along PC2, driven by higher sugars and K, indicating a shift toward energy-rich late-season pollen. Each month appears as four points in the biplot, corresponding to the four replicate subsamples (n = 4) analyzed per month from the pooled pollen of 37 colonies, thus representing biological replication rather than duplication.

3.4. Correlation Analysis of Honeybee Pollen Quality Parameters

The correlation analysis revealed that the moisture content was negatively associated with several key quality parameters, including protein (r = ࢤ0.48), fat (r = ࢤ0.32), sugar (r = ࢤ0.64), starch (r = ࢤ0.50), and zinc (r = ࢤ0.70), indicating that drier pollen, typically collected during summer, tends to be nutritionally richer, as shown in Figure 4. Strong positive correlations were observed among protein, fat, and sugar (r = 0.90–0.82), suggesting a synchronized accumulation of macronutrients. Similarly, iron and zinc were highly correlated (r = 0.85), reflecting parallel trends in the micronutrient contents. Mineral elements showed strong interrelationships, particularly between phosphorus and potassium (r = 0.93), phosphorus and magnesium (r = 0.82), and potassium and magnesium (r = 0.86), pointing to their coordinated enrichment in late-season pollen. The ash content also correlated moderately with fat (r = 0.53) and phosphorus (r = 0.42). Interestingly, calcium exhibited weak or no significant correlations with most parameters, implying a distinct behavior or source compared to other elements. Additionally, fiber was moderately correlated with protein (r = 0.46) and fat (r = 0.42), suggesting it may co-accumulate with the nutrient content during peak bloom. Overall, the correlation matrix confirms that pollen moisture is inversely related to quality, while the nutritional and mineral parameters are tightly interlinked, especially during mid- to late-season flowering. These correlations reinforce the PCA findings, highlighting that peak nutritional and mineral values coincide with lower moisture content and mid- to late-season pollen collection.
The scatterplot matrix of the honeybee pollen parameters revealed clear clustering and linear trends that support the statistical correlations. Notably, protein, fat, and sugar exhibited strong positive linear relationships, with tight clusters and upward slopes, reflecting consistent co-accumulation across samples. A similar linear trend was visible between Zn and Fe, confirming their coupled enrichment in high-quality pollen. Scatterplots of P vs. K and P vs. Mg also showed strong linear alignments, supporting the hypothesis of shared mineral uptake pathways or botanical sources. Conversely, moisture displayed inverse patterns with protein, fat, and Zn, showing downward slopes, wide dispersion, and separation by month (e.g., April-May with higher moisture, June–August with lower). Fiber and ash had more dispersed or elliptical distributions with other variables, indicating moderate or variable associations. These pairwise scatterplots not only reinforce the Pearson correlation coefficients but also visually confirm the seasonal clustering and trade-offs between the moisture and nutrient density observed in the PCA.

4. Discussion

The present study demonstrated that honeybee pollen collected from April to September in southern Kazakhstan exhibits significant seasonal variation in its physicochemical and mineral composition. These patterns align with the seasonal dynamics of the floral availability and environmental conditions in the Turkistan region.
The moisture content declined significantly from April (10.34 ± 1.74%) to June (5.23 ± 0.86%), stabilizing at lower values during the summer months. This trend corresponds with the typical decrease in atmospheric humidity and the shift toward more arid conditions, as well as changes in the floral moisture retention capacity. Similar reductions in moisture across summer months have been reported by Almeida-Muradian et al. [18] in Brazilian pollen and Negrão et al. [19] in pollen collected from Apis mellifera in southeastern Brazil. One study examining the nutritional composition of honeybee pollen reported a range of moisture content from 9.51% to 10.55% and indicated seasonal reductions corresponding to drier, warmer conditions in the summer months [32]. The findings underline how climatic factors—particularly atmospheric humidity and temperature—strongly influence pollen moisture, with lower moisture values typically recorded during the hottest, driest parts of the year. This supports the hypothesis that environmental factors play a crucial role in determining the physicochemical properties of floral resources available to pollinators.
The protein content peaked in June (23.66 ± 1.70%) and remained elevated throughout summer, confirming previous observations that mid-season floral sources provide higher protein nutrition. This supports the findings of Topal et al. [13], who reported a summer maximum in the protein concentration in pollen from fixed honeybee colonies. Furthermore, a study on honeybee-collected pollen in different regions reported protein contents ranging from 8.5% to 37.3%, with averages clustering around 21.68%. The authors emphasized that seasonal and regional differences in protein contents are largely due to shifts in plant phenology and the availability of high-protein pollen sources during the summer [33]. This further validates the observed trend of increased pollen protein contents in mid-season, reinforcing the notion that environmental and botanical factors are critical drivers of pollen nutritional quality.
In our study, the fat content also increased significantly during the warmer months, reaching 8.67 ± 0.11% in July, a pattern mirrored in studies from Poland and Brazil, where the lipid contents in pollen were closely tied to flowering plant species rich in fatty acids [1,7]. A study on the nutritional value of bee pollen across seasons found that the fat content varies significantly by season and botanical origin, linked to the diversity of flowering plants like sunflower, alfalfa, and date palm blooming at different times [34].
The sugar content peaked at 14.41 ± 0.11% in July, suggesting synchronization with high nectar flow and floral carbohydrate production. Several studies confirm that sugars are a major component of pollen, often ranging from 13% to 55%, predominantly composed of monosaccharides like glucose and fructose, along with varying amounts of sucrose, maltose, and other disaccharides. For example, bee pollen, which includes pollen mixed with nectar and bee secretions, generally shows a sugar profile dominated by glucose and fructose [35,36]. The carbohydrate profile of pollen is influenced by its botanical origin and environmental conditions, which could explain the peak in the carbohydrate content during certain months like July, when floral nectar production is also at its highest and the nectar is typically rich in glucose and fructose, with varying glucose/fructose ratios depending on the species and conditions [37].
Among the mineral elements, Fe and Zn showed the most pronounced seasonal trends. Fe increased nearly threefold from April (47.51 ± 5.69 mg/kg) to July (143.39 ± 6.58 mg/kg), while Zn reached a maximum of 57.14 ± 8.54 mg/kg in the same month. Studies indicate that the Fe and Zn concentrations in pollen exhibit significant variability influenced by both seasonal factors and botanical composition. For example, the elemental contents in bee pollen vary widely, with Fe ranging approximately from 52.3 to 133 mg/kg and Zn from 3.0 to 67.5 mg/kg, depending on the pollen taxa and season, which is consistent with the current observation of a marked Fe increase and Zn peak in July [38,39].
The calcium levels, in contrast, peaked in May (113.75 ± 16.09 mg/kg) before declining through September. This distinct behavior may reflect botanical specificity in early-season plants, as calcium-rich species dominate spring bloom—a pattern similarly observed by Lau et al. [40] in their study on seasonal pollen across four U.S. regions. Calcium is essential for pollen tube growth, mainly by participating in cell wall stabilization through cross-linking acidic pectin residues, and by acting as a signaling molecule modulating secretion and cytoplasmic processes. The peak calcium level in May could coincide with increased pollen germination and tube growth activity during this flowering season [41].
The phosphorus (P) levels in the present study ranged from 28.14 ± 7.85 mg/kg in August to 37.67 ± 8.50 mg/kg in June, without statistically significant seasonal variation. However, correlation analysis revealed that P was strongly and positively associated with both potassium and magnesium (r = 0.93 and r = 0.82, respectively), suggesting coordinated accumulation pathways or common botanical sources. Similar co-variation between these elements has been reported by Valverde et al. [38], who found significant P–K correlations in Spanish bee pollen linked to leguminous and composite plant dominance during late-season flowering. In a study of Brazilian pollen, Almeida-Muradian et al. [18] also noted stable phosphorus values across seasons but emphasized strong mineral interrelationships driven by botanical origin. Compared with the study by Adaškevičiūtė et al. [42], who reported P contents of 24.2–39.8 mg/kg in Lithuanian bee pollen depending on floral origin, our results fall within a similar range but display less intersample variability. This late-season enrichment may reflect a shift toward floral sources with naturally higher K contents, such as sainfoin and certain Asteraceae, which dominate autumn pastures in southern Kazakhstan [20,43].
K, an essential osmotic regulator in plant and bee physiology, exhibited significant seasonal changes (p = 0.0351), increasing from 510.23 ± 42.29 mg/kg in April to a peak of 647.52 ± 9.19 mg/kg in September. Comparable late-season K enrichment was observed by Negrão et al. [19] in southeastern Brazil and by Komosinska-Vassev et al. [10] in Polish pollen, both attributing the trend to the prevalence of K-rich floral species, such as Asteraceae and Fabaceae, in late summer and autumn. Furthermore, Nicolson and Worswick [44] reported that the potassium concentrations in floral nectar often exceed those of sodium by an order of magnitude, a pattern mirrored in our pollen data, where the K levels were approximately 8–12 times higher than the Na levels, potentially shaping foraging preferences.
The Na concentrations also varied significantly (p = 0.0163), with the highest value recorded in June (72.67 ± 8.11 mg/kg). Khan et al. [45] highlighted that honeybees actively seek sodium-containing resources to meet their physiological demands, especially under conditions of brood rearing and thermoregulation. This behavioral tendency, combined with seasonal floral sodium availability, as noted by Nicolson and Worswick [44], could explain the observed Na maxima during early summer in our study.
Copper (Cu), a trace element critical for enzymatic functions in bees, displayed a clear upward trend from spring to autumn (p = 0.0296), increasing from 5.17 ± 1.31 mg/kg in May to 10.28 ± 1.69 mg/kg in September. Comparable Cu increases toward the end of the flowering season have been recorded in Moroccan pollen by El Ghouizi et al. [35] and in samples by Valverde et al. [38], suggesting that late-season floral sources and environmental stressors may enhance Cu accumulation in pollen. Such enrichment may have implications for bee physiology, as Cu is involved in antioxidant defense and cuticle sclerotization.
Together, the patterns observed for P, K, Na, and Cu indicate that the mineral composition of bee pollen is not only seasonally dynamic but also shaped by botanical succession and regional edaphoclimatic conditions. Late-season pollen, in particular, appears to be more enriched in K and Cu, complementing the elevated protein and micronutrient (Fe, Zn) profiles detected during mid-to-late summer and reinforcing the potential nutritional benefits of harvesting during this period.
Overall, our findings indicate that the nutritional and mineral quality of bee pollen is maximized during the mid-to-late-flowering season. These results align with prior reports from other temperate and semi-arid regions and further validate the influence of the floral phenology and environmental conditions on the pollen quality. Importantly, the use of a single migratory apiary and uniform Apis mellifera carnica population minimized external variability, enabling the precise detection of seasonal patterns.
The fiber content of the bee pollen exhibited marked seasonal variation, with higher values typically recorded in late-season samples. As shown in the correlation matrix (Figure 4), fiber displayed moderate positive correlations with protein (r = 0.46) and fat (r = 0.46), suggesting that pollens richer in structural carbohydrates also tended to contain higher levels of macronutrients. Recent work by Zheng et al. [46] demonstrated that soluble dietary fiber from bee pollen, depending on the extraction method, can exhibit distinct structural characteristics that influence its fermentability in the gut microbiota. Such functional attributes underline the potential health benefits of fiber-rich pollen collected during late-season flowering periods. Similarly, studies in Spain have shown that the crude fiber levels in bee pollen can vary substantially with botanical origin, ranging from 3.4% to 20.4% on a dry-matter basis [47], values comparable to the seasonal range observed in the present study. These variations highlight the influence of floral diversity and phenology on the structural carbohydrate profile of bee pollen.
The starch content, although less variable than that of fiber, showed moderate positive correlations with sugar (r = 0.32) and several minerals, including potassium (r = 0.39) and magnesium (r = 0.37). These relationships imply that starch-rich pollens may originate from floral species with both high carbohydrate reserves and mineral accumulation capacities. Such patterns are often associated with early- to mid-season-flowering plants, where pollen grains serve as the primary nutrient storage for developing gametophytes [2]. According to Bertoncelj et al. [48], starch and other storage carbohydrates in pollen not only serve as an immediate energy source for pollinators but also contribute to pollen’s functionality in human nutrition.
The ash content, representing the total mineral fraction, varied significantly across months and demonstrated notable correlations with potassium (r = 0.53), phosphorus (r = 0.42), and magnesium (r = 0.45) (Figure 4). These findings support the view that ash can serve as an indirect indicator of the mineral richness of pollen, reflecting shifts in the floral composition and soil mineral availability during the foraging season. Similar associations between ash contents and mineral concentrations have been reported in multi-floral bee pollen and temperate ecosystems [10,49].
The components analyzed in this study were selected as key markers of bee pollen quality due to their established nutritional and physicochemical importance. The moisture content is a primary determinant of shelf stability and microbial safety. According to international standards, the moisture levels in bee pollen should remain below 8–10% to minimize the risk of fermentation and mold development [50]. In our study, moisture decreased significantly from April to June, reaching levels within the acceptable threshold, thereby ensuring the better storability of mid-season pollen. The protein content is a critical quality marker, as protein provides essential amino acids for brood rearing and is equally valued in human nutrition; protein levels above 20% are considered indicative of high-quality bee pollen [51]. Lipids (fat content) serve as an important energy source and provide essential fatty acids that influence both bee physiology and the functional food properties of pollen. Carbohydrates, including sugars and starch, are vital energy components, supporting bee activity and adding to the caloric density of pollen as a dietary supplement [52]. Ash and minerals reflect the inorganic nutritional profile of pollen, with elements such as Fe and Zn contributing to the antioxidant defense and immune function in both bees and humans, making them important indicators of pollen bioactivity.
This study has some limitations that should be acknowledged. First, while monthly composite samples provided robust seasonal trends, pooling may have masked within-colony or between-colony variation in the pollen composition. Second, only proximate composition and mineral elements were assessed; other important bioactive components, such as phenolic compounds, flavonoids, and vitamins, were not included but could also contribute to pollen quality. Third, the identification of floral sources was based on regional surveys rather than a melissopalynological analysis of the collected samples, which may have limited precision in linking the compositional variation to specific plant taxa. Finally, environmental factors such as rainfall and temperature, which are known to affect pollen yields and compositions, were not systematically integrated into this study. These limitations suggest that future research should include colony-level replicates, detailed pollen source identification, and a broader profiling of bioactive compounds.
Future research should explore year-to-year variability and the contribution of specific plant species to nutritional peaks using melissopalynological techniques. Integrating amino acid and antioxidant profiling would also provide a more comprehensive assessment of the bioactive potential.

5. Conclusions

This study provides the first detailed assessment of seasonal changes in the nutritional, physicochemical, and mineral composition of honeybee pollen collected in southern Kazakhstan under controlled migratory beekeeping conditions. The findings demonstrate that pollen harvested in mid-to-late summer (June–August) is characterized by lower moisture and higher nutritional density, with significant increases in protein, fat, carbohydrates, and key minerals, particularly Fe, Zn, K, and Cu. The phosphorus content remained relatively stable but exhibited strong correlations with K and Mg, indicating coordinated mineral accumulation, while sodium showed distinct mid-season peaks. Late-season pollen was especially enriched in K and Cu, complementing its elevated macronutrient and micronutrient profiles.
Future research should integrate the melissopalynological identification of floral sources and expand the analytical scope to include bioactive compounds, as well as environmental drivers such as climate and floral diversity. Such approaches will strengthen the link between pollen origin and quality and further support the development of pollen as a standardized functional food. By minimizing the variability from apiary locations and bee subspecies, this study offers a robust baseline for regional pollen quality standards and supports the valorization of Kazakhstani pollen as a high-value apicultural product.

Author Contributions

Conceptualization, G.M. and A.T. (Aibyn Torekhanov); methodology, M.T.; software, M.T.; validation, U.N., and G.K.; formal analysis, G.M., G.K., N.M., A.T. (Aigul Tajiyeva), and M.T.; investigation, U.N.; resources, O.K. and A.T. (Aigul Tajiyeva); data curation, O.K.; writing—original draft preparation, G.M. and M.T.; writing—review and editing, M.T. and A.T. (Aibyn Torekhanov); visualization, M.T.; supervision, U.N.; project administration, U.N.; funding acquisition, U.N. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Ministry of Agriculture of the Republic of Kazakhstan, grant number BR22885831, “Development of an integrated management system for the genetic resources of beekeeping and technologies for the effective use of bees in pollination and production of organic products”.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
PCAPrincipal component analysis
PPhosphorus
CaCalcium
KPotassium
MgMagnesium
NaSodium
AASAtomic absorption spectrophotometry
CuCopper
FeIron
ZnZinc
SDStandard deviation
ANOVAOne-way analysis of variance
HSDTukey’s honest significant difference

References

  1. Mărgăoan, R.; Stranț, M.; Varadi, A.; Topal, E.; Yücel, B.; Cornea-Cipcigan, M.; Campos, M.G.; Vodnar, D.C. Bee Collected Pollen and Bee Bread: Bioactive Constituents and Health Benefits. Antioxidants 2019, 8, 568. [Google Scholar] [CrossRef] [PubMed]
  2. Campos, M.G.R.; Bogdanov, S.; de Almeida-Muradian, L.B.; Szczesna, T.; Mancebo, Y.; Frigerio, C.; Ferreira, F. Pollen Composition and Standardisation of Analytical Methods. J. Apic. Res. 2008, 47, 154–161. [Google Scholar] [CrossRef]
  3. Yucel, B.; Topal, E.; Kosoglu, M. Bee Products as Functional Food. In Superfood and Functional Food—An Overview of Their Processing and Utilization; Waisundara, V., Ed.; IntechOpen: London, UK, 2017; Volume 1, pp. 15–33. [Google Scholar]
  4. Camacho-Bernal, G.I.; Cruz-Cansino, N.d.S.; Ramírez-Moreno, E.; Delgado-Olivares, L.; Zafra-Rojas, Q.Y.; Castañeda-Ovando, A.; Suárez-Jacobo, Á. Addition of Bee Products in Diverse Food Sources: Functional and Physicochemical Properties. Appl. Sci. 2021, 11, 8156. [Google Scholar] [CrossRef]
  5. Becerril-Sánchez, A.L.; Quintero-Salazar, B.; Dublán-García, O.; Escalona-Buendía, H.B. Phenolic Compounds in Honey and Their Relationship with Antioxidant Activity, Botanical Origin, and Color. Antioxidants 2021, 10, 1700. [Google Scholar] [CrossRef]
  6. Feás, X.; Vázquez-Tato, M.P.; Estevinho, L.; Seijas, J.A.; Iglesias, A. Organic Bee Pollen: Botanical Origin, Nutritional Value, Bioactive Compounds, Antioxidant Activity and Microbiological Quality. Molecules 2012, 17, 8359–8377. [Google Scholar] [CrossRef]
  7. Carpes, S.T.; Morais, M.; Alencar, S.M.; Masson, M.L. Harvesting Season and Botanical Origin Interferes in Production and Nutritional Composition of Bee Pollen. An. Acad. Bras. Ciênc. 2018, 90, 325–332. [Google Scholar] [CrossRef]
  8. Pereira, L.J.; Estevinho, L.M.; Moreira, L.L.; Dias, L.G.; Pereira, A.P. Botanical Source Investigation and Evaluation of the Effect of Seasonality on Brazilian Propolis from Apis mellifera L. Sci. Agric. 2020, 77, 6. [Google Scholar] [CrossRef]
  9. Denisow, B.; Denisow-Pietrzyk, M. Biological and Therapeutic Properties of Bee Pollen: A Review. J. Sci. Food Agric. 2016, 96, 4303–4309. [Google Scholar] [CrossRef]
  10. Komosinska-Vassev, K.; Olczyk, P.; Kaźmierczak, J.; Mencner, Ł.; Olczyk, K. Bee Pollen: Chemical Composition and Therapeutic Application. Evid. Based Complement. Altern. Med. 2015, 2015, 297425. [Google Scholar] [CrossRef]
  11. Roulston, T.H.; Cane, J.H. Pollen Nutritional Content and Digestibility for Animals. Plant Syst. Evol. 2000, 222, 187–209. [Google Scholar] [CrossRef]
  12. Coffey, M.F.; Breen, J. Seasonal Variation in Pollen and Nectar Sources of Honey Bees in Ireland. J. Apic. Res. 1997, 36, 63–76. [Google Scholar] [CrossRef]
  13. Topal, E.; Çakıcı, N.; Mărgăoan, R.; Takma, Ç.; Güney, F.; Kösoğlu, M.; Cornea-Cipcigan, M.; Atmaca, H. Annual Development Performance of Fixed Honeybee Colonies Linked with Chemical and Mineral Profile of Bee Collected Pollen. Chem. Biodivers. 2022, 19, e202200468. [Google Scholar] [CrossRef]
  14. Nuraliyeva, U.A.; Spatay, N.N.; Davletova, A.M.; Toishimanov, M.R.; Moldakhmetova, G.A.; Kussainova, Z.A.; Khudaiberdiev, A.A.; Khrapova, S.N.; Baimukanov, D.A. The Impact of Environment on the Morphometric Characteristics of Honeybees Apis mellifera carnica in South-East Kazakhstan. OnLine J. Biol. Sci. 2023, 23, 520–527. [Google Scholar] [CrossRef]
  15. Nuralieva, U.; Tajiyev, K.; Sheralieva, Z.; Toishimanov, M.; Moldakhmetova, G.; Temirbayeva, K.; Tajieva, A. Geometric Morphometric Characteristics of Apis mellifera Honeybee in Kazakhstan. Biodiversitas 2023, 24, 821. [Google Scholar] [CrossRef]
  16. Köppler, K.; Vorwohl, G.; Koeniger, N. Comparison of pollen spectra collected by four different subspecies of the honey bee Apis mellifera. Apidologie 2007, 38, 341–353. [Google Scholar] [CrossRef]
  17. Malagnini, V.; Cappellari, A.; Marini, L.; Zanotelli, L.; Zorer, R.; Angeli, G.; Ioriatti, C.; Fontana, P. Seasonality and Landscape Composition Drive the Diversity of Pollen Collected by Managed Honey Bees. Front. Sustain. Food Syst. 2022, 6, 865368. [Google Scholar] [CrossRef]
  18. Almeida-Muradian, L.B.; Pamplona, L.C.; Coimbra, S.; Barth, O.M. Chemical composition and botanical evaluation of dried bee pollen pellets. J. Food Compos. Anal. 2005, 18, 105–111. [Google Scholar] [CrossRef]
  19. Negrão, A.F.; Barreto, L.M.R.C.; Orsi, R.O. Influence of the Collection Season on Production, Size, and Chemical Composition of Bee Pollen Produced by Apis mellifera L. J. Apic. Sci. 2014, 58, 175–181. [Google Scholar] [CrossRef]
  20. Kurmanov, R.G. Resources of melliferous and polleniferous plants of Central Asia and Kazakhstan based on melissopalynological analysis. Russ. J. Nat. Conserv. 2023, 59, 367–377. [Google Scholar] [CrossRef]
  21. Gritsenko, D.; Temirbayeva, K.; Taskuzhina, A.; Kostyukova, V.; Pozharskiy, A.; Kolchenko, M.; Khusnitdinova, M.; Krupskiy, O.; Mayer, A.; Nuralieva, U.; et al. First Evaluation of Genetic Diversity among Honeybee Populations in Kazakhstan. Apidologie 2023, 54, 61. [Google Scholar] [CrossRef]
  22. Association of Young Beekeepers (ICYB). Beekeeping in Kazakhstan. ICYB—International Conference of Young Beekeepers, n.d. Web Page, Accessed on 2 August 2025. ICYB Kazakhstan—Beekeeping in Kazakhstan. Available online: https://www.icyb.cz/kazakhstan/ (accessed on 3 July 2025).
  23. Kazakh Research Institute of Livestock and Fodder Production. Fodder Resources of the Republic of Kazakhstan. Available online: https://www.kazniizhik-pastures.kz/Maps/FodderResources (accessed on 11 May 2025).
  24. AOAC. Official Method 925.10: Moisture in Honey. In Official Methods of Analysis of AOAC International, 20th ed.; AOAC International: Rockville, MD, USA, 2016. [Google Scholar]
  25. AOAC. Official Method 984.13: Protein (Crude) in Animal Feed—Kjeldahl Method. In Official Methods of Analysis of AOAC International, 20th ed.; AOAC International: Rockville, MD, USA, 2016. [Google Scholar]
  26. AOAC. Official Method 920.39: Fat (Crude) or Ether Extract in Animal Feed. In Official Methods of Analysis of AOAC International, 20th ed.; AOAC International: Rockville, MD, USA, 2016. [Google Scholar]
  27. GOST 10845-98; Starch Methods of Determination. Interstate Council for Standardization, Metrology and Certification: Moscow, Russia, 1999; Interstate Standard.
  28. AOAC. Official Method 923.03: Ash of Flour. In Official Methods of Analysis of AOAC International, 20th ed.; AOAC International: Rockville, MD, USA, 2016. [Google Scholar]
  29. Dubois, M.; Gilles, K.A.; Hamilton, J.K.; Rebers, P.A.; Smith, F. Colorimetric Method for Determination of Sugars and Related Sub-stances. Anal. Chem. 1956, 28, 350–356. [Google Scholar] [CrossRef]
  30. Wieczorek, D.; Żyszka-Haberecht, B.; Kafka, A.; Matras, E.; Jamroz, J. Determination of Phosphorus Compounds in Plant Tissues: From Colourimetry to Advanced Instrumental Analytical Chemistry. Plant Methods 2022, 18, 22. [Google Scholar] [CrossRef]
  31. Toishimanov, M.; Abilda, Z.; Daurov, D.; Daurova, A.; Zhapar, K.; Sapakhova, Z.; Kanat, R.; Stamgaliyeva, Z.; Zhambakin, K.; Shamekova, M. Phytoremediation Properties of Sweet Potato for Soils Contaminated by Heavy Metals in South Kazakhstan. Appl. Sci. 2023, 13, 9589. [Google Scholar] [CrossRef]
  32. Al-Kahtani, S.; Taha, E.-K.A. Seasonal Variations in Nutritional Composition of Honeybee Pollen Loads. J. Kans. Entomol. Soc. 2020, 93, 105–112. Available online: https://www.jstor.org/stable/27101812 (accessed on 6 June 2025). [CrossRef]
  33. Simanonok, M.P.; Otto, C.R.V.; Iwanowicz, D.D.; Boswell, K.M.; Cornman, R.S. Honey Bee-Collected Pollen Richness and Protein Content across an Agricultural Land-Use Gradient. Apidologie 2021, 52, 1291–1304. [Google Scholar] [CrossRef]
  34. Al-Kahtani, S.N.; Taha, E.-K.A.; Farag, S.A.; Taha, R.A.; Abdou, E.A.; Mahfouz, H.M. Harvest Season Significantly Influences the Fatty Acid Composition of Bee Pollen. Biology 2021, 10, 495. [Google Scholar] [CrossRef] [PubMed]
  35. El Ghouizi, A.; Bakour, M.; Laaroussi, H.; Ousaaid, D.; El Menyiy, N.; Hano, C.; Lyoussi, B. Bee Pollen as Functional Food: Insights into Its Composition and Therapeutic Properties. Antioxidants 2023, 12, 557. [Google Scholar] [CrossRef]
  36. Lagera, A.J.; Balinado, L.O.; Baldomero, J.R.; Rotairo, H.F.I.; Tero, N.L.; Maghinay, M.S.; Baluyo, I.F.; Reyes, M.R.; Galve, R.; Sibao, S.A.; et al. Varying Sugars and Sugar Concentrations Influence In Vitro Pollen Germination and Pollen Tube Growth of Cassia alata L. J. Young Investig. 2017, 33, 42–45. [Google Scholar] [CrossRef]
  37. Denisow, B.; Masierowska, M.; Antoń, S. Floral Nectar Production and Carbohydrate Composition and the Structure of Receptacular Nectaries in the Invasive Plant Bunias orientalis L. (Brassicaceae). Protoplasma 2016, 253, 1489–1501. [Google Scholar] [CrossRef]
  38. Valverde, S.; Tapia, J.A.; Pérez-Sanz, A.; González-Porto, A.V.; Higes, M.; Lucena, J.J.; Martín-Hernández, R.; Bernal, J. Mineral Composition of Bee Pollen and Its Relationship with Botanical Origin and Harvesting Period. J. Food Compos. Anal. 2023, 119, 105235. [Google Scholar] [CrossRef]
  39. Filipiak, M.; Kuszewska, K.; Asselman, M.; Denisow, B.; Stawiarz, E.; Woyciechowski, M.; Weiner, J. Ecological Stoichiometry of the Honeybee: Pollen Diversity and Adequate Species Composition Are Needed to Mitigate Limitations Imposed on the Growth and Development of Bees by Pollen Quality. PLoS ONE 2017, 12, e0183236. [Google Scholar] [CrossRef]
  40. Lau, P.; Bryant, V.; Ellis, J.D.; Huang, Z.Y.; Sullivan, J.; Schmehl, D.R.; Cabrera, A.R.; Rangel, J. Seasonal Variation of Pollen Collected by Honey Bees (Apis mellifera) in Developed Areas across Four Regions in the United States. PLoS ONE 2019, 14, e0217294. [Google Scholar] [CrossRef]
  41. Winship, L.J.; Rounds, C.; Hepler, P.K. Perturbation Analysis of Calcium, Alkalinity and Secretion during Growth of Lily Pollen Tubes. Plants 2017, 6, 3. [Google Scholar] [CrossRef] [PubMed]
  42. Adaškevičiūtė, V.; Kaškonienė, V.; Kaškonas, P.; Barčauskaitė, K.; Maruška, A. Comparison of Physicochemical Properties of Bee Pollen with Other Bee Products. Biomolecules 2019, 9, 819. [Google Scholar] [CrossRef]
  43. Moldakhmetova, G.; Kurmanov, R.; Toishimanov, M.; Tajiyev, K.; Nuraliyeva, U.; Sheralieva, Z.; Temirbayeva, K.; Suleimenova, Z. Palynological, physicochemical, and organoleptic analysis of honey from different climate zones of Kazakhstan. Casp. J. Environ. Sci. 2023, 21, 703–714. Available online: https://cjes.guilan.ac.ir/article_6931.html (accessed on 11 August 2025).
  44. Nicolson, S.W.; Worswick, P.V. Sodium and Potassium Concentrations in Floral Nectars in Relation to Foraging by Honey Bees. S. Afr. J. Zool. 1990, 25, 93–96. Available online: https://hdl.handle.net/10520/AJA00445096_570 (accessed on 14 July 2025). [CrossRef]
  45. Khan, K.A.; Ghramh, H.A.; Ahmad, Z.; El-Niweiri, M.A.A.; Mohammed, M.E.A. Honey Bee (Apis mellifera) Preference towards Micronutrients and Their Impact on Bee Colonies. Saudi J. Biol. Sci. 2021, 28, 4429–4436. [Google Scholar] [CrossRef]
  46. Zheng, H.; Sun, Y.; Zeng, Y.; Zheng, T.; Jia, F.; Xu, P.; Xu, Y.; Cao, Y.; He, K.; Yang, Y. Effects of Four Extraction Methods on Structure and In Vitro Fermentation Characteristics of Soluble Dietary Fiber from Rape Bee Pollen. Molecules 2023, 28, 4800. [Google Scholar] [CrossRef] [PubMed]
  47. Serra Bonvehí, J.; Escolà Jordà, R. Nutrient Composition and Microbiological Quality of Honeybee-Collected Pollen in Spain. J. Agric. Food Chem. 1997, 45, 725–732. [Google Scholar] [CrossRef]
  48. Bertoncelj, J.; Lilek, N.; Korošec, M. Bee Pollen Carbohydrates Composition and Functionality. In Pollen Chemistry & Biotechnology; Bayram, N.E., Kostic, Ž., Can Gercek, A.Y., Eds.; Springer: Cham, Switzerland, 2023; pp. 49–70. [Google Scholar] [CrossRef]
  49. Estevinho, L.M.; Rodrigues, S.; Pereira, A.P.; Feás, X. Portuguese bee pollen: Palynological study, nutritional and microbiological evaluation. Int. J. Food Sci. Technol. 2012, 47, 429–435. [Google Scholar] [CrossRef]
  50. Campos, M.G.; Anjos, O.; Chica, M.; Campoy, P.; Nozkova, J.; Almaraz-Abarca, N. Standard Methods for Pollen Research. J. Apic. Res. 2021, 60, 1–109. [Google Scholar] [CrossRef]
  51. Nicolson, S.W.; Da Silva Das Neves, S.; Human, H.; Pirk, C.W.W. Digestibility and Nutritional Value of Fresh and Stored Pollen for Honey Bees (Apis mellifera scutellata). J. Insect Physiol. 2018, 107, 302–308. [Google Scholar] [CrossRef] [PubMed]
  52. Taha, E.K.A. Chemical Composition and Amounts of Mineral Elements in Honeybee-Collected Pollen in Relation to Botanical Origin. J. Apic. Sci. 2015, 59, 75–88. [Google Scholar] [CrossRef]
Agriculture 15 01922 g001
Figure 1. Pollen samples were collected from an apiary located in the Tulkibas district, Turkistan region, Kazakhstan. (a) Map of Kazakhstan indicating Turkistan region. (b) Map of Turkistan region highlighting Tulkibas district. (c) Topographic map of Tulkibas district showing the sampling location. (d) Satellite view of the apiary with approximate positions of beehives.
Figure 1. Pollen samples were collected from an apiary located in the Tulkibas district, Turkistan region, Kazakhstan. (a) Map of Kazakhstan indicating Turkistan region. (b) Map of Turkistan region highlighting Tulkibas district. (c) Topographic map of Tulkibas district showing the sampling location. (d) Satellite view of the apiary with approximate positions of beehives.
Agriculture 15 01922 g001
Agriculture 15 01922 g002
Figure 2. Representative bee pollen samples collected from the Tulkibas district during different months of the foraging season (from left to right: April, May, June, July, August, September).
Figure 2. Representative bee pollen samples collected from the Tulkibas district during different months of the foraging season (from left to right: April, May, June, July, August, September).
Agriculture 15 01922 g002
Agriculture 15 01922 g003
Figure 3. PCA biplot of honeybee pollen quality parameters by month.
Figure 3. PCA biplot of honeybee pollen quality parameters by month.
Agriculture 15 01922 g003
Agriculture 15 01922 g004
Figure 4. Pearson correlation matrix between physicochemical parameters and mineral contents of bee pollen samples collected from April to September in Tulkibas district, Turkistan region, Kazakhstan. The circle size and intensity indicate the strength of the correlation, with red representing positive correlations and blue representing negative correlations.
Figure 4. Pearson correlation matrix between physicochemical parameters and mineral contents of bee pollen samples collected from April to September in Tulkibas district, Turkistan region, Kazakhstan. The circle size and intensity indicate the strength of the correlation, with red representing positive correlations and blue representing negative correlations.
Agriculture 15 01922 g004
Table 1. Floral sources of honeybee pollen in southern Kazakhstan by month [20,23].
Table 1. Floral sources of honeybee pollen in southern Kazakhstan by month [20,23].
MonthDominant Floral Sources (Genera/Species)
AprilSalix sp. (willow), Psoralea drupacea, Tamarix sp., Barbarea sp. (wintercress), Sinapis sp. (mustard), Inula sp., Echium vulgare
MayOnobrychis sp. (sainfoin), Vicia sp. (vetch), Melilotus sp. (sweet clover), Sophora sp., Rubus idaeus (raspberry), Cucurbitaceae family, Geum sp.
JuneHelianthus annuus (sunflower), Gossypium hirsutum (cotton), Eremurus sp., Salvia sp. (sage), Linaria vulgaris, Leonurus quinquelobatus, Euphorbia sp.
JulyAmoria hybrida (hybrid clover), Solidago virgaurea (goldenrod), Cichorium intybus (chicory), Onobrychis sp., Echium vulgare, Origanum vulgare (oregano)
AugustThymus sp., Tamarix sp., Artemisia sp., Euphorbia sp., Nonea pulla
SeptemberArtemisia sp., Asteraceae family (composites), Viburnum opulus, Origanum vulgare, Euphorbia sp.
Floral sources were not directly measured in this study; information is based on regional surveys and published records of melliferous plants in southern Kazakhstan.
Table 2. Nutritional, physicochemical, and mineral composition of honeybee pollen collected during different months of the foraging season in southern Kazakhstan.
Table 2. Nutritional, physicochemical, and mineral composition of honeybee pollen collected during different months of the foraging season in southern Kazakhstan.
MonthAprilMayJuneJulyAugustSeptemberp-Value by Month
Moisture, %10.34 ± 1.74 a6.78 ± 0.99 b5.23 ± 0.86 c5.29 ± 0.97 c5.62 ± 0.31 c7.97 ± 0.31 b0.0030
Protein, %20.28 ± 2.13 b21.87 ± 1.19 ab23.66 ± 1.70 a22.49 ± 0.16 ab22.23 ± 0.13 ab21.81 ± 0.78 ab0.0268
Fat, %7.56 ± 0.82b6.93 ± 1.18 b8.63 ± 0.35 a8.67 ± 0.11 a8.64 ± 0.09 a8.24 ± 0.06 ab0.0446
Fiber, %1.50 ± 0.421.33 ± 0.482.50 ± 0.311.91 ± 0.891.93 ± 0.252.31 ± 0.17NS
Sugar, %12.46 ± 1.48 b12.29 ± 1.03 b14.36 ± 0.43 a14.41 ± 0.11 a14.38 ± 0.41 a13.61 ± 0.32 ab0.0108
Starch, %6.56 ± 0.4310.31 ± 2.939.51 ± 1.3312.37 ± 2.7313.49 ± 0.599.12 ± 0.42NS
Ash, %4.74 ± 0.544.69 ± 0.245.11 ± 0.644.89 ± 0.864.82 ± 0.235.92 ± 0.92NS
Ca, mg/kg99.11 ± 8.42 b113.75 ± 16.09 a94.52 ± 9.28 b99.58 ± 2.82 b96.50 ± 7.07 b91.58 ± 1.41 b0.0078
P, mg/kg32.8 ± 4.1235.36 ± 8.0537.67 ± 8.5033.51 ± 6.3628.14 ± 7.8537.25 ± 4.41NS
K, mg/kg510.23 ± 42.29 b517.75 ± 32.62 b565.67 ± 84.79 ab521.47 ± 57.98 b478.54 ± 4.25 b647.52 ± 9.19 a0.0351
Mg, mg/kg385.62 ± 48.45379.50 ± 25.66445.67 ± 48.58383.70 ± 14.14388.52 ± 37.07462.58 ± 31.53NS
Na, mg/kg55.45 ± 8.12 c60.25 ± 6.52 bc72.67 ± 8.11 a63.54 ± 5.12 bc66.98 ± 12.13 ab63.58 ± 3.53 bc0.0163
Cu, mg/kg5.64 ± 0.565.17 ± 1.31 c6.82 ± 1.98 b7.11 ± 1.36 b9.53 ± 1.85 a10.28 ± 1.69 a0.0296
Fe, mg/kg47.51 ± 5.69 d48.04 ± 5.21 d103.65 ± 9.85 b143.39 ± 6.58 a96.74 ± 7.22 c81.17 ± 2.59 c0.0388
Zn, mg/kg38.56 ± 2.36 c42.81 ± 3.69 bc47.88 ± 5.32 b57.14 ± 8.54 a42.77 ± 5.20 bc38.17 ± 6.98 c0.0302
Values are means ± standard deviation. Superscripts (a, b, c, etc.) indicate significant differences between months according to Tukey’s HSD test (p < 0.05). Values with the same letter are not significantly different.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Moldakhmetova, G.; Torekhanov, A.; Tajiyeva, A.; Nuraliyeva, U.; Krupskiy, O.; Khalykova, G.; Myrzabayeva, N.; Toishimanov, M. Seasonal Variation in Nutritional, Physicochemical, and Mineral Composition of Honeybee Pollen in Southern Kazakhstan. Agriculture 2025, 15, 1922. https://doi.org/10.3390/agriculture15181922

AMA Style

Moldakhmetova G, Torekhanov A, Tajiyeva A, Nuraliyeva U, Krupskiy O, Khalykova G, Myrzabayeva N, Toishimanov M. Seasonal Variation in Nutritional, Physicochemical, and Mineral Composition of Honeybee Pollen in Southern Kazakhstan. Agriculture. 2025; 15(18):1922. https://doi.org/10.3390/agriculture15181922

Chicago/Turabian Style

Moldakhmetova, Gaukhar, Aibyn Torekhanov, Aigul Tajiyeva, Ulzhan Nuraliyeva, Oleg Krupskiy, Gulim Khalykova, Nurgul Myrzabayeva, and Maxat Toishimanov. 2025. "Seasonal Variation in Nutritional, Physicochemical, and Mineral Composition of Honeybee Pollen in Southern Kazakhstan" Agriculture 15, no. 18: 1922. https://doi.org/10.3390/agriculture15181922

APA Style

Moldakhmetova, G., Torekhanov, A., Tajiyeva, A., Nuraliyeva, U., Krupskiy, O., Khalykova, G., Myrzabayeva, N., & Toishimanov, M. (2025). Seasonal Variation in Nutritional, Physicochemical, and Mineral Composition of Honeybee Pollen in Southern Kazakhstan. Agriculture, 15(18), 1922. https://doi.org/10.3390/agriculture15181922

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop