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Article

The Effect of Foliar Micronutrient Fertilization on Yield and Nutritional Quality of Maize Grain

by
Wacław Jarecki
1,*,
Ioana Maria Borza
2,
Cristina Adriana Rosan
3,
Cristian Gabriel Domuța
2 and
Simona Ioana Vicas
3
1
Department of Crop Production, University of Rzeszów, St. Zelwerowicza 4, 35-601 Rzeszów, Poland
2
Department of Agriculture, University of Oradea, Gen. Magheru, No. 26, 410048 Oradea, Romania
3
Department of Food Engineering, University of Oradea, Gen. Magheru, No. 26, 410048 Oradea, Romania
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(8), 1859; https://doi.org/10.3390/agronomy15081859
Submission received: 16 June 2025 / Revised: 15 July 2025 / Accepted: 30 July 2025 / Published: 31 July 2025

Abstract

Foliar fertilization is an effective practice that improves both the yield and quality of maize, a crop with high and specific micronutrient demands. This study hypothesized that foliar application of Fe, Cu, Mn, Mo, Zn and B would improve grain size and quality in GS210 maize compared to the control. The single-factor field experiment was conducted in 2023–2024 on Haplic Cambisol (Eutric) soil, under a variety of meteorological conditions. The application of Zn and B fertilizers significantly increased the soil plant analysis development (SPAD) index. Yield components (number of grains per ear, thousand-grain weight) and grain yield increased significantly following Zn foliar application compared to the control. Zn application increased grain yield by 0.59 t ha−1 and 0.49 t ha−1 in 2023 and 2024, respectively. Smaller but beneficial effects were observed with Cu and B applications. In contrast, the effects of fertilization with other micronutrients (Fe, Mn, Mo) were less pronounced than anticipated. Biochemical analyses revealed that foliar fertilization with Fe, Cu and Mo increased total phenolic content and antioxidant capacity, while Fe and Mo enhanced carotenoid accumulation, and Cu and B significantly influenced grain color parameters. The study highlights the potential of foliar fertilization to improve maize performance and grain quality, despite possible antagonisms between micronutrients.

1. Introduction

Mineral fertilizers are most commonly applied either to the soil or as foliar sprays, with the former method predominantly used for macronutrient fertilization. In contrast, foliar application complements soil fertilization and is often the only feasible method for supplying micronutrients. In agricultural practice, foliar spraying is often combined with pesticide treatments, which significantly reduces application costs [1]. A wide range of foliar fertilizers is commercially available, and new innovative products with improved chemical compositions continue to be introduced [2].
Maize is one of the crop species that effectively utilizes nutrients from both organic and mineral fertilizers. Previous research results have demonstrated high fertilization efficiency for this species using both macronutrients [3] and micronutrients [4]. Neumann et al. [5] have concluded that fertilization typically leads to increased yield and improved quality. However, cases of neutral or negative effects following foliar fertilization have also been reported. This occurs because fertilization outcomes depend on multiple factors, including fertilizer type, application rate, timing, plant species, and local habitat conditions [6,7,8,9]. According to Szulc and Kruczek [7], Poland is experiencing periodic droughts as a result of climate change. In such situations, the effects of water stress can be reduced with new fertilization techniques. Therefore, research in this area is considered important for maintaining high maize yields.
Faheed et al. [10] reported that combined soil and foliar fertilization exerted beneficial effects on maize cultivation. As a result of this treatment, optimal results were obtained, including the highest grain yield. Kruczek and Bober [11] showed that the ′Koka′ variety of maize grain was characterized by low copper, zinc, manganese, and iron content. However, various fertilization methods, including foliar fertilization, increased the content of copper (2.8–31.5%), zinc (6.5–31.9%), manganese (2–13.7%), and iron (1.4–23.1%) in the grain.
Research by Ghaffari et al. [12] showed that applying multiple nutrients to maize crops increased the fat content in grains. On the other hand, Mickiewicz and Wróbel [13] reported that boron and zinc fertilization increased maize yield, particularly when combined with simplified soil tillage practices for maize cultivation. Rácz et al. [14] demonstrated that foliar fertilization reduced environmental stress while increasing chlorophyll and photosynthetic pigment content in maize leaves. They believe that the need for foliar fertilization arises during soil water stress and during periods of rapid plant growth. A study by Amanullah et al. [15] also reported that maize fertilization increased yields under drought stress conditions. Therefore, they recommend foliar fertilization with the main macroelements (NPK). Later research by Brankov et al. [16] confirmed the beneficial effects of foliar fertilization on maize traits, though with significant cultivar-dependent variation. Moreover, adverse meteorological conditions reduced the treatment efficacy below projected levels.
The available literature has also demonstrated several key principles regarding foliar fertilization in maize cultivation. Ling and Silberbush [17] established that successful foliar nutrient application depends on adequate leaf surface area and effective pathogen control. Subsequent studies by Amanullah et al. [18] revealed enhanced efficacy when foliar treatments were administered during later growth phases compared to earlier stages. More recently, Škarpa et al. [19] and Khardia et al. [20] documented how strategic foliar nutrient supplementation can substantially reduce soil fertilizer requirements, offering both economic benefits and environmental advantages for maize production systems. Klofac et al. [21] have demonstrated that the chemical form of zinc significantly affects its efficacy in foliar applications, with chelated zinc showing the highest effectiveness in maize, followed by sulfate and oxide forms. However, they concluded that under field conditions, variable environmental factors often lead to inconsistent results from foliar fertilization. Bukvić et al. [22] identified zinc as the most crucial micronutrient in maize fertilization. Zinc fertilization, especially foliar, resulted in Zn concentration increase in the ear-leaf of the lines investigated. Furthermore, supplemental fertilization with boron [13], iron, copper, manganese [11], or molybdenum [23] may also be advisable in maize cultivation. It should therefore be stated that maize is an important crop that can be sown in variable soil conditions, although optimal plant growth and development requires a balanced fertilization strategy, including micronutrients [24].
This study aimed to evaluate maize response to foliar application of selected micro-nutrients (Fe, Cu, Mn, Mo, Zn, B) at their average content in the soil during two years, 2023 and 2024. The research was designed to assess not only the impact on grain yield but also on grain quality, with a particular focus on microelements, accumulation of bioactive compounds (polyphenols, flavonoids and carotenoids), antioxidant capacity, and color parameters. These attributes were investigated for their relevance to potential health benefits, highlighting the functional value of maize grain beyond its nutritional content.
The present study offers an extensive examination linking micronutrient fertilization with health-related functional quality of the maize grain, in contrast to the majority of previous research that only focuses on agronomic characteristics or limited biochemical properties.
The research hypothesis assumed that in a temperate climate, each of the applied micronutrients would positively affect the size and/or quality of maize grain yield compared to the control. This is due to the fact that the uptake of nutrients from the soil is not always sufficient for high-yielding varieties.

2. Materials and Methods

2.1. Experimental Conditions

The field experiment was conducted during the 2023 and 2024 growing seasons at the Podkarpackie Agricultural Extension Center in Boguchwała (21°57′ E, 49°59′ N), Poland. The study evaluated foliar fertilization of maize with six micronutrients compared to an untreated control:
  • Control (spraying with water)
  • Iron
  • Copper
  • Manganese
  • Molybdenum
  • Zinc
  • Boron
The foliar fertilizers with micronutrients were purchased from INTERMAG company (Olkusz, Poland). Microelements in foliar fertilizers are mineral salts. The chemical composition of individual fertilizers was as follows:
  • Mikrovit® Iron (75 g L−1 Fe)
  • Mikrovit® Copper (75 g L−1 Cu)
  • Mikrovit® Manganese (160 g L−1 Mn)
  • Mikrovit® Molybdenum (33 g L−1 Mo)
  • Mikrovit® Zinc (112 g L−1 Zn)
  • Bormax® Boron (150 g L−1 B)
The growth stages of maize plants were assessed using the Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie (BBCH) standardized phenological classification system employed in the EU [25]. The micronutrients were applied twice during the growing season: at the 6–7 leaf stage (BBCH 16–17) and at the beginning of tassel emergence (BBCH 51). Each foliar spray application contained 1 L ha−1 of the respective micronutrient fertilizer (a total of 2 L ha−1 per growing season) with 300 L ha−1 of spray solution. The plants were sprayed in the evening using a 10-L manual sprayer.
A one-factor experiment was performed in four replicates in a randomized block design. The study utilized the GS 210 maize hybrid (Agro Seed, Brzezie, Poland), a triple-line crossbred variety developed for both grain and silage production, with flint-dent type grains. This is a variety characterized by high yields and good quality grain (protein 9.2–9.4%, starch 71–73%, fat 3.6–3.8%).

2.2. Soil Conditions

The experiment was carried out on Haplic Cambisol (Eutric) formed from loess [26]. The soil had a slightly acidic pH, moderate humus content, and low Nmin content. The macronutrient content (P, K, Mg) was very high or high, while the micronutrient content (Fe, Zn, Mn, Cu, B) was moderate. The chemical analysis of the soil (Table 1) was performed at the Regional Chemical and Agricultural Station in Rzeszów, according to Polish standards. The set of standards used (PN-ISO 10390:1997, PB 18, 3rd edition of 31.07.2017, PN-R-04023:1996, PN-R-04022:1996/Azl:2002, PN-R-04020:1996/AzI:2004, PN-92/R-04017, PN-92/R-04016, PN-92/R-04019, PN-93/R-04021:1994, PN-93/R-040 18) is given after Fotyma et al. [27].

2.3. Weather Conditions

Mean temperatures and total precipitation varied between the study years (Figure 1). The weather conditions were obtained from the Meteorological Station Podkarpackie Agricultural Advisory Centre in Boguchwała, located approximately 0.6 km from the experimental field.

2.4. Experimental Design and Crop Management

Potatoes were the preceding crop every year. Phosphorus–potassium fertilization was applied in autumn at rates of 90 kg ha−1 P2O5 (single superphosphate) and 120 kg ha−1 K2O (potassium salt), followed by winter plowing. In spring, harrowing was performed, and before sowing, a cultivator was used along with nitrogen fertilization. Urea with urease inhibitor (46% N) was applied for nitrogen fertilization at a dose of 80 kg N ha−1 before sowing and 70 kg N ha−1 at stage 14 BBCH [25].
Sowing was performed in the second half of April each year. The grains were treated with Redigo M 120 FS (metalaxyl, prothioconazole) according to the manufacturer’s recommendations. The row spacing was 75 cm, and the sowing depth was 5 cm. Eight viable grains were sown per square meter. The area of a single plot measured 22.5 m2 (4.5 m × 5 m). Plant protection treatments were carried out using pesticides authorized during the study years (Efica 960 EC, Notos 100 SC, Belavent, Karate Zeon 050 CS). The timing and dosages of chemicals were in accordance with manufacturers’ recommendations and regional agricultural practices.
Prior to harvest, 20 corncobs were collected from each plot for biometric measurements (ear number per plant, grain number per ear, thousand-grain weight). The thousand-grain weight (TGW) was determined by weighing 1000 randomly selected grains and adjusted to 14% moisture content. The harvest was conducted using a plot combine at full maturity stage, i.e., in the second half of October. The area of each plot on which the harvest was carried out was 22.5 m2. Grain yield was converted per hectare with a constant moisture content of 14%. Grain samples for chemical analysis were collected before harvest from each plot.

2.5. Chemical Analysis of Grains

The chemical composition of the grains was determined using near-infrared spectroscopy with an MPA FT-LSD spectrometer (Bruker Optik GmbH, Ettlingen, Germany) in the Laboratory of Plant Production at the University of Rzeszów.
Hectolitric weight kg hL−1 (MHL) and detailed chemical composition of the grain were determined in the laboratory Faculty of Environmental Protection, University of Oradea using Granolyser HL (Pfeuffer GMBH, Kitzingen, Germany) apparatus.
The maize grains were ground using a coffee grinder, the powder was passed through a 0.05 mm sieve and all samples were kept at 4 °C. The extraction of bioactive compounds from maize powder was performed using specific protocols adapted to the chemical nature of the targeted compounds.
The extraction of polyphenols was performed according to the protocol described by Suriano et al. [27] with slight modifications. A 0.5 g maize sample was homogenized with 4.5 mL of methanol acidified with 1N hydrochloric acid, then sonicated for 30 min at room temperature, and centrifuged at 5000 rpm for 15 min. The supernatant was retained, and the residue was re-dissolved in 4.5 mL of methanol acidified with 1 N HCl, followed by the repetition of the previous operations. The supernatants were combined and preserved at −20 °C for 48 h, subsequently centrifuged at 5000 rpm for 15 min. The collected supernatant was utilized to quantify bioactive compounds, including total phenols and flavonoids, and evaluate antioxidant capacity using four distinct methods: DPPH, FRAP, TEAC, and CUPRAC. The protocols used for the determination of antioxidant capacity are described in detail in our previous publication (Jarecki et al. [28]).
For carotenoids, a separate extraction method was employed, based on the use of non-polar organic solvents, adapted from Suriano et al. [27] to ensure optimal recovery of lipophilic compounds. Briefly, 1 g of maize powder was homogenized with 10 mL of extraction solvent acetone/ethanol; 1:1; v/v, containing 200 mg/L BHT. Then, the samples were sonicated for 15 min, followed by centrifugation at 5000 rpm for 15 min, and the supernatant was recorded at 450 nm. The formula used for the carotenoid determination was as follows:
C c a r o t e n o i d s   m g 100   g = A 470   ×   V   ×   10 4 ϵ   ×   l   ×   M
where A470 is the absorbance measured at 470 nm; V is total extract volume (mL); 104 is the conversion factor to express the results in mg/100 g; ϵ is the molar extinction coefficient (L·mol−1·cm−1); l is the length of the cuvette (cm); M is the sample mass (g).
The color parameters of ground corn samples were determined using a portable colorimeter (3nh TS7030, Shenzhen Threenh Technology Co., Ltd., Shenzhen, China), operating in the CIE Lab* color space. The device was calibrated prior to analysis of the samples using the white/black calibration provided by the manufacturer.
For each sample, approximately 5 g of sample was evenly spread in a glass Petri dish, and color was measured in triplicate. The color parameters recorded were L* (lightness), a* (green–red component), and b* (blue–yellow component). In addition, the chroma (C*), representing color saturation, and hue angle (h*), describing the perceived color tone, were calculated using the following formulas: C* = (a*2 + b*2)1/2 and h* = tan − 1 (b*⁄a*), respectively [29].
To assess differences in color compared to control sample, the total color difference (ΔE*) was calculated using the formula in Lab* space:
E = ( L s a m p l e L c o n t r o l ) 2 + ( a s a m p l e a c o n t r o l ) 2 + ( b s a m p l e b c o n t r o l ) 2
For elemental analysis, grain samples were mineralized in a mixture of HNO3, HClO4, and HS2O4 (at a ratio of 20:5:1) using an open-system Tecator heating block (FOSS Analytical A/S, Hillerød, Denmark). The content of Fe, Cu, Zn, and Mn were quantified by flame atomic absorption spectroscopy (FAAS) using a Hitachi Z-2000 spectrometer (Hitachi High-Tech Corporation, Tokyo, Japan).

2.6. Statistical Calculations

To verify the normality of the distribution, the Shapiro–Wilk test was performed and the homogeneity of variance was verified. A two-way repeated measures ANOVA (with fertilizer as a factor) was then performed. Growing seasons (year) were considered random effects. In order to determine and verify the relationships, Tukey’s post hoc test (HSD) was employed. Statistical analysis was performed using the TIBCO Statistica 13.3.0 package (TIBCO Software Inc., Palo Alto, CA, USA). Pearson correlation coefficients were calculated to identify relationships among agronomic, biochemical and quality traits. Principal component analysis (PCA) was used to reduce dimensionality and visualize patterns in the multivariate dataset. The PCA biplot and correlation matrix were generated in PAST 4.03.

3. Results and Discussion

To establish significant differences, an ANOVA was conducted. Factor, year and interaction (Table 2) exhibited significant differences in all measured traits with a p-value of <0.0001.
In 2023, the SPAD index was significantly higher following foliar application of Zn, B and Cu compared to the control. Similar results were observed in the second year for Zn and B but not for Cu (Figure 2). Didal et al. [30] demonstrated that maize foliar fertilization significantly increased SPAD readings to 46.1 and 38.6 compared to control values of 37.1 and 29.9. Tóth et al. [31] and Jarecki [32] similarly observed that foliar fertilizers markedly improved plant nutritional status (SPAD index) compared to untreated controls.
Ears per plant remained unaffected by foliar treatments in both years. The number of grains per ear was most positively affected by Zn and B application, while Fe, Cu, Mn and Mo treatments resulted in moderate yet statistically significant (p < 0.05) increases relative to untreated controls. In 2024, the number of grains per ear was significantly higher than in 2023. The thousand-grain weight was highest following Cu and Zn fertilization, while the other micronutrients had no effect on this parameter (Table 3).
Afe et al. [33] found that multi-nutrient foliar fertilization did not alter grain number per ear but significantly increased thousand-grain weight (TGW) compared to the control. Similarly, Didal et al. [30] reported that foliar application significantly improved maize biometric traits, including yield components and final grain yield, while Hu et al. [34] did not obtain the expected results following this treatment under drought and salinity stress conditions.
The highest hectoliter weight (HW) was recorded following the application of Fe, Mo and B, while significantly lower values were observed after Mn treatment and in the control. On average, HW reached 77.5 kg/hL, which was consistent with the findings of Eremi et al. [35], who reported values ranging from 71.55 to 83.70 kg hL−1.
Maize yield showed significant variation between the study years (Figure 3). Foliar applications of Zn, B and Cu exerted the most beneficial effect on grain yield compared to the control. These results were consistent in the years of the study. However, fertilization with Fe and Mn increased the yield only in 2024. The difference in grain yield after Zn application compared to the control was 0.59 and 0.49 t ha−1 in 2023 and 2024, respectively.
Jakab et al. [36] reported average maize grain yields ranging from 11.37 to 12.86 t ha−1, with foliar fertilizers increasing yields by 0.24–1.49 t ha−1, though these differences were not statistically significant. Khalafi et al. [37] demonstrated that soil fertilization significantly enhanced Fe and Zn uptake in maize plants. However, equally effective results were obtained with foliar application or fertigation of these micronutrients. Ehsanullah et al. [38] also obtained favorable results from foliar Zn application compared to both soil fertilization and untreated controls. In a study by Tóth et al. [31], maize yield increased by 10% following Zn application, mainly due to increased grain weight per ear. In addition, Amanullah et al. [4] demonstrated that early foliar Zn application produced more favorable results compared to later treatments. Consequently, the varying foliar application timings resulted in significantly different grain yields.
Grain protein content was lowest in the control group, while significantly higher levels were obtained following Cu, Mo and Zn applications. Starch content was highest in the control treatment and significantly lower after foliar application of Fe and Zn. On the other hand, fat and ash contents were not affected by foliar fertilization (Table 4). Fiber content was higher in the control group compared to treatments with individual micronutrients. Significant differences in grain composition were observed between study years. In 2023, grains contained more protein and fiber but less fat and starch compared to 2024. The opposite trend was observed in 2024, with higher fat and starch content but lower protein and fiber levels.
Khalafi et al. [37] demonstrated that while fertilization could increase grain protein content, the effect varied in significance, with foliar application and fertigation showing more beneficial results compared to traditional soil fertilization. Building on this, Crista et al. [39] obtained optimal protein enrichment (11.62%) through combined foliar application of nitrogen, boron and zinc, while also observing increased fiber content from zinc treatments without affecting ash levels. Notably, Sharifi et al. [40] reported increased nutritional quality through zinc supplementation, particularly using nano-zinc formulations, which elevated both crude protein and carbohydrate levels. Moreover, Radulov et al. [41] demonstrated that foliar fertilization not only increased protein content in maize but also altered the amino acid profile. In the latter study, protein content in maize grain ranged from 7% to 10%. The synergistic benefits of combined fertilization approaches were confirmed by Ivanova et al. [42], who documented improvements in both yield and protein content during foliar fertilization. A comparative analysis by Zapałowska and Jarecki [43] revealed a clear advantage of mineral NPK fertilization (9.5% protein) over control (8.5%) and organic treatments, underscoring the importance of selecting an appropriate fertilization strategy to optimize grain quality.
The total phenolic content showed a significant increase following fertilization with Fe, Cu and Mo compared to the two other micronutrient treatments and the control group. Foliar fertilization with Fe, Mn and Mo significantly increased the total flavonoid content compared to the untreated control. The highest total carotenoid content was recorded following Fe and Mo application, while the control group had the lowest values (Table 5).
Salinas-Moreno et al. [44] have argued that maize is one of the cereals richest in phenolic compounds. The consumption of these compounds is important for human health due to their well-documented antioxidant activity. Research by Peniche-Pavía et al. [45] identified flavonoids in maize grains, recognized for their beneficial effects on human health. Complementing these findings, Zurak et al. [46] have established that maize contains high levels of carotenoids, although their bioavailability in feed applications is often limited.
Different foliar micronutrient treatments induced variable antioxidant responses in maize grains, depending on the assay used. Foliar fertilization significantly altered the antioxidant content, as measured by DPPH, FRAP and TEAC assays, while no differences were observed using the CUPRAC method. Both the DPPH and FRAP assays showed an increase in antioxidant capacity following foliar application of Fe and Cu. On the other hand, the FRAP and TEAC methods indicated that foliar application of Mo improved antioxidant properties (Table 6). These results suggest that the effect of micronutrient application on antioxidant capacity is assay-dependent and may reflect differences in the mechanisms targeted by each method.
The effect of foliar microelement fertilization on the maize flour color parameters was evaluated and the results are shown in Table 7. The L* value corresponds to the lightness and ranged from 74.53 (zinc) to 77.48 (copper). Higher L* values represent lighter flour, whilst lower values indicate darker or more highly pigmented samples.
The a* values (green to red axis) were generally near to neutral, with slight shifts toward the red in few cases. The b* values (blue to yellow axis) were more pronounced, showing maize’s intrinsic yellow coloration due to carotenoid concentration. Samples with higher b* values (control, boron) were more brightly yellow and were often correlated with higher quantities of lutein and zeaxanthin, which are nutritionally important pigments.
Color characteristics such as chroma (C*) and hue angle (h*) provided additional information about saturation and perceived color type. The chroma, C*-value, of the maize flour samples is a measure of color purity [28]. Boron and molybdenum recorded the highest values (30.79 and 30.24, respectively). Iron has the lowest values of the chroma. Hue angle values, which represent the actual hue of the flour, ranged from 76.54 to 79.30, placing the samples predominantly in the yellow region of the color space.
The total color difference (ΔE*) compared to the control flour sample ranged between 1.13 and 2.41. According to generally accepted thresholds, ΔE* values between 1 and 3 are perceptible through close observation. In this study, samples (copper, boron) showed a ΔE* > 2, suggesting color differences compared to the control sample.
Foliar fertilization significantly altered the content of specific micronutrients in maize grain (Table 8). The study revealed that foliar application of Cu, Mn and Zn significantly reduced grain Fe content. Mo application reduced Cu content, while Mn decreased Zn content. Conversely, Cu and Zn fertilization lowered Mn levels. In addition, the concentration of micronutrients in the grain was significantly higher in 2024 compared to 2023.
Crista et al. [39] found that sulfur and boron application significantly increased copper and zinc concentrations in maize kernels. Supplementing these findings, Jarecki [32] showed that multi-component foliar fertilizers improved both protein content and protein yield per hectare. The highest concentrations of Zn and Fe in grain were achieved following foliar application of a fertilizer containing both micronutrients and amino acids. Manzeke et al. [47] highlighted that levels of zinc (Zn) and iron (Fe) in staple cereals such as maize, sorghum, fine millet and peas in Zimbabwe are generally insufficient to meet adequate human nutritional needs. This suggests a direct link between micronutrient management in agriculture and potential health benefits. According to the authors, improving fertilizer management and soil conditions can increase Zn and Fe concentrations in cereals, which are essential for addressing micronutrient deficiencies in human diets. However, micronutrient levels in cereals often remain below recommended thresholds for human health, highlighting the need for integrated strategies to improve the nutritional quality of food crops and combat micronutrient deficiencies in smallholder farming systems.
Principal component analysis (PCA) and Pearson correlations analysis revealed significant association between foliar micronutrient treatments, agronomic performance, and grain functional quality in maize. The PCA biplot (PC1 = 38.27%, PC2 = 21.92%) distinctly shows the impact of micronutrient treatments on maize grain characteristics (Figure 4). Zn and Cu treatments were positively associated with grain yield, SPAD index, number of grains per cob, mass of a thousand grains, and antioxidant parameters (TPh, DPPH, FRAP, ABTS), indicating their dual contribution to both agronomic and functional quality improvement. In contrast, Fe, Mn, and Mo treatments were positioned on the opposite site of the plot, suggesting a less favorable or even antagonistic impact. Boron showed moderate association with color attributes (a*, b*), while starch and fiber content were negatively associated with antioxidant traits and yield, possibly reflecting a trade-off between storage and defense-related metabolism. The control group (untreated) was clearly separated from all treatments, further supporting the beneficial effect of foliar micronutrient application. The PCA also included mineral accumulation (Fe, Cu, Zn, Mn) in grain composition. In particular, Fe and Cu contents were positioned in the positive quadrant of PC1, closely aligned with yield, SPAD, and antioxidant parameters, indicating their association with enhanced physiological and nutritional quality. In contrast, Zn and Mn were located in the negative quadrant, opposite to yield and quality traits, suggesting that increased accumulation of these elements may reflect antagonistic interactions or metabolic trade-offs under the tested conditions.
The correlation analysis (Figure 5) revealed strong and significant relationships between total phenolic content (TPh) and antioxidant activity parameters, particularly FRAP (r = 0.911), DPPH (r = 0.939), and ABTS (r = 0.805), indicating the major contribution of phenolics to the overall antioxidant potential of maize grains. Total flavonoids (TFLAV) were also positively correlated with ABTS (r = 0.839) and FRAP (r = 0.800), suggesting their relevant role in radical scavenging activity. Grain yield was positively and significantly correlated with the number of grains per cob (r = 0.831), mass of a thousand grains (r = 0.910), and SPAD index (r = 0.916), underlining the close association between physiological status, yield formation, and grain quality. Interestingly, ash content was positively associated with both TPh (r = 0.624) and DPPH (r = 0.683), while starch content was negatively correlated with antioxidant parameters and ash, possibly indicating a trade-off between carbohydrate accumulation and antioxidant-related metabolism. Among micronutrients, zinc showed strong positive correlations with content of carotenoids (r = 0.783), and grain yield (r = 0.691), highlighting its dual role in improving both carotenoids and agronomic traits. In contrast, manganese exhibited consistent negative correlations with multiple quality parameters, including antioxidant parameters, mass of 1000 grains (r = −0.783), Hectolitric weight (r = −0.799) and grain yield (r = −0.561), suggesting potential antagonistic or stress-inducing effects at the applied levels. Overall, the combined PCA and correlation analysis provided an integrated view of how micronutrient applications shape both the agronomic performance and the functional grain quality of maize.

4. Conclusions

The most optimal results in maize cultivation were obtained after Zn, B and Cu foliar applications. Other micronutrients produced smaller and less consistent effects across the years of the study. The 2024 growing season was more favorable for maize yields due to more optimal weather conditions compared to 2023. Foliar fertilization with Zn, B and Cu had the most beneficial effect on grain yield and this effect was reproducible over the study years. Foliar fertilization with Fe and Mn also increased grain yield, but only in 2024. Thus, the research hypothesis that foliar fertilization with the studied micronutrients would be justified in corn cultivation was partially confirmed. Foliar treatments significantly influenced the basic chemical composition of the grain protein, starch and fiber as well as the concentration of micronutrients. Antagonism was shown for some micronutrients. Application of one of them reduced the content of the others. In addition, foliar fertilization resulted in a “dilution effect” of micronutrients, which resulted in an increase in grain yield.
The results demonstrated that specific foliar applications of microelements can significantly enhance the functional quality of maize grains. The Zn treatment promoted carotenoid accumulation while Fe and Mo were most effective in increasing antioxidant capacity and the content of health-relevant bioactive compounds. In contrast, B and Mn treatment had limited influence. These results demonstrate the potential of individualized micronutrient fertilization techniques to enhance maize’s nutritional and functional value as an important crop in addition to improving the yield of crops.
These experimental results were further supported by PCA and Pearson correlation results, which offered a comprehensive view of the relationships between treatments and measured traits. PCA clearly separated the most effective treatments (Zn, Cu, B) from those with limited or inconsistent effects (Mn, Mo), while correlation analysis confirmed strong positive associations between grain yield, antioxidant activity, SPAD index, and phenolic content. In contrast, antagonistic interactions between micronutrients were reflected by negative correlations and opposing vector directions. Together, these multivariate tools validated the observed treatment effects and highlighted the potential of Zn and Cu in enhancing both agronomic and functional grain properties.
Optimizing foliar fertilization techniques to enhance nutrient accumulation in the maize grain should be the main goal of future studies. The bioavailability of iron and zinc may be enhanced by research into the application of chelated forms or nanoformulations.

Author Contributions

Conceptualization, W.J., I.M.B. and S.I.V.; methodology, W.J., I.M.B., C.A.R., C.G.D. and S.I.V.; formal analysis, W.J.; data curation, W.J., I.M.B., C.A.R., C.G.D. and S.I.V.; writing—original draft preparation, W.J., I.M.B., C.A.R., C.G.D. and S.I.V.; writing—review and editing, W.J., I.M.B., C.A.R., C.G.D. and S.I.V.; visualization, W.J.; supervision, W.J.; project administration, W.J.; funding acquisition, W.J., I.M.B., C.A.R., C.G.D. and S.I.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the author on request.

Acknowledgments

We fully appreciate the editors and all anonymous reviewers for their constructive comments on this manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Weather conditions.
Figure 1. Weather conditions.
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Figure 2. The effect of foliar fertilization on the SPAD value. Different lower case letters indicate significant differences between plants fertilized with particular microelements (p < 0.05). Different capital letters indicate the difference between years (p < 0.05). The standard error is marked on the columns.
Figure 2. The effect of foliar fertilization on the SPAD value. Different lower case letters indicate significant differences between plants fertilized with particular microelements (p < 0.05). Different capital letters indicate the difference between years (p < 0.05). The standard error is marked on the columns.
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Figure 3. Grain yield in t ha−1. Different lower case letters indicate significant differences between plants fertilized with particular microelements (p < 0.05). Different capital letters indicate the difference between years (p < 0.05). The standard error is marked on the columns.
Figure 3. Grain yield in t ha−1. Different lower case letters indicate significant differences between plants fertilized with particular microelements (p < 0.05). Different capital letters indicate the difference between years (p < 0.05). The standard error is marked on the columns.
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Figure 4. Principal component analysis (PCA) biplot showing the relationships between foliar micronutrient treatments and measured variables in maize (var. GS210). The plot is based on PC1 and PC2, which explain 38.27% and 21.92% of the total variance, respectively. Variables include agronomic traits (e.g., cobs/plant, grains/cob, 1000-grain weight, SPAD, grain yield), biochemical parameters (TPh, TFLAV, CAROT, DPPH, FRAP, ABTS, CUPRAC), and mineral content (Fe, Cu, Zn, Mn). Treatments are represented by points, and vectors indicate the direction and strength of variable contributions. PCA was performed using PAST v4.03.
Figure 4. Principal component analysis (PCA) biplot showing the relationships between foliar micronutrient treatments and measured variables in maize (var. GS210). The plot is based on PC1 and PC2, which explain 38.27% and 21.92% of the total variance, respectively. Variables include agronomic traits (e.g., cobs/plant, grains/cob, 1000-grain weight, SPAD, grain yield), biochemical parameters (TPh, TFLAV, CAROT, DPPH, FRAP, ABTS, CUPRAC), and mineral content (Fe, Cu, Zn, Mn). Treatments are represented by points, and vectors indicate the direction and strength of variable contributions. PCA was performed using PAST v4.03.
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Figure 5. Pearson correlation matrix showing the relationships among agronomic traits, antioxidant parameters, grain composition, and micronutrient content in maize. The color scale indicates the strength and direction of the correlation (blue: positive, red: negative). The size and shape of the ellipses represent the correlation coefficient, with outlined ellipses indicating statistically significant correlations (p < 0.05). Correlations were calculated and visualized using PAST software v4.03. A—total phenols content, B—total flavonoids content, C—carotenoids content, D—FRAP, E—DPPH, F—CUPRAC, G—ABTS, H—Number of cobs per plant, I—Number of grains per cob, J—Mass of 1000 grains (g), K—Hectolitric weight kg/hL (MHL), L—Grain yield (t/ha), M—SPAD, N—fat, O—ash, P—starch, Q—fiber, R—L*, S—a*, T—b*, U—Fe, V—Cu, W—Zn, X—Mn.
Figure 5. Pearson correlation matrix showing the relationships among agronomic traits, antioxidant parameters, grain composition, and micronutrient content in maize. The color scale indicates the strength and direction of the correlation (blue: positive, red: negative). The size and shape of the ellipses represent the correlation coefficient, with outlined ellipses indicating statistically significant correlations (p < 0.05). Correlations were calculated and visualized using PAST software v4.03. A—total phenols content, B—total flavonoids content, C—carotenoids content, D—FRAP, E—DPPH, F—CUPRAC, G—ABTS, H—Number of cobs per plant, I—Number of grains per cob, J—Mass of 1000 grains (g), K—Hectolitric weight kg/hL (MHL), L—Grain yield (t/ha), M—SPAD, N—fat, O—ash, P—starch, Q—fiber, R—L*, S—a*, T—b*, U—Fe, V—Cu, W—Zn, X—Mn.
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Table 1. Chemical soil properties before the field experiment (0–30 cm).
Table 1. Chemical soil properties before the field experiment (0–30 cm).
ParameterUnit2023Evaluation2024Evaluation
pH in KCl-6.2slightly acidic5.9slightly acidic
Humus%1.5moderate1.3moderate
Nminkg ha−162low58low
P2O5mg kg−1213very high195high
K2O258very high228high
Mg95very high86high
Fe2536moderate3569moderate
Cu5.3moderate5.8moderate
Mn485moderate512moderate
Zn12.9moderate14.5moderate
B1.5moderate1.8moderate
Table 2. Multivariate significance tests, effect sizes and powers.
Table 2. Multivariate significance tests, effect sizes and powers.
EffectWilks’ lambda ΛFEffect DfError Dfp
Factor0.00000029.7162102.15320.000000
Year0.002219266.52716.00000.000000
Factor × Year0.0002751.9162102.15320.000232
Table 3. Corn yield components and hectolitric weight.
Table 3. Corn yield components and hectolitric weight.
Tested FactorNumber of Cobs per PlantNumber of Grains per CobMass of 1000 Grains (g)Hectolitric Weight kg/hL (MHL)
Foliar fertilization (F)
control1.1442.5 c289.3 b76.4 b
iron1.2455.3 b292.5 b77.5 ab
copper1.2457.6 b306.4 a79.5 a
manganese1.1455.9 b292.2 b75.6 b
molybdenum1.1456.1 b291.5 b78.2 a
zinc1.2465.3 a306.4 a78.0 a
boron1.2468.7 a295.6 b77.6 ab
Year (Y)
20231.1435.6 b294.276.37 b
20241.2479.1 a298.378.71 a
ANOVA p value
Fn.s.******
Yn.s.*n.s.**
F × Yn.s.n.s.n.s.n.s.
Statistically significant differences are marked with different letters. ***, **, *—indicate significant differences at p < 0.001, p < 0.01 and p < 0.05, respectively; n.s.—non-significant according to Tukey’s honestly significant difference (HSD) test.
Table 4. Chemical composition of grain in % of dry matter.
Table 4. Chemical composition of grain in % of dry matter.
Tested FactorProteinFatAshStarchFiber
Foliar fertilization (F)
control8.2 b3.81.0974.0 a2.56 a
iron9.1 ab3.91.1972.4 b2.12 b
copper9.3 a3.71.1872.7 ab2.08 b
manganese9.1 ab3.61.1572.6 ab2.11 b
molybdenum9.2 a3.71.1372.8 ab2.05 b
zinc9.5 a3.71.1872.0 b2.02 b
boron8.6 b3.91.1173.5 ab2.09 b
Year (Y)
20239.55 a3.45 b1.2871.8 b2.28 a
20249.13 b4.06 a1.0273.9 a2.02 b
ANOVA p value
F**n.s.n.s.**
Y**n.s.***
F × Yn.s.n.s.n.s.n.s.n.s.
Statistically significant differences are marked with different letters. **, *—indicate significant differences at p < 0.01 and p < 0.05, respectively; n.s.—non-significant according to Tukey’s honestly significant difference (HSD) test.
Table 5. Bioactive compound content in corn grains subjected to different foliar fertilization treatments.
Table 5. Bioactive compound content in corn grains subjected to different foliar fertilization treatments.
Tested FactorTotal Phenols Content (mg GAE/g dw)Total Flavonoid Content (mg QE/g dw)Total Carotenoids (μg/g)
Foliar fertilization (F)
control1.06 c0.53 b4.21 c
iron1.30 a0.68 a4.83 a
copper1.25 a0.61 ab4.35 bc
manganese1.18 b0.67 a4.69 ab
molybdenum1.25 a0.73 a4.93 a
zinc1.13 bc0.59 ab5.43 b
boron1.15 b0.55 ab4.68 ab
Year (Y)
20231.09 b0.594.64
20241.29 a0.644.82
ANOVA p value
F*****
Y*n.s.n.s.
F × Yn.s.n.s.n.s.
Statistically significant differences are marked with different letters. ***, *—indicate significant differences at p < 0.001 and p < 0.05, respectively; n.s.—non-significant according to Tukey’s honestly significant difference (HSD) test.
Table 6. Antioxidant capacity in D.M.
Table 6. Antioxidant capacity in D.M.
Tested FactorDPPH Method (µmol TE/g)FRAP Method (µmol TE/g)TEAC Method (µmol TE/g)CUPRAC Method (µmol TE/g)
Foliar fertilization (F)
control3.09 c4.28 c4.49 ab0.15
iron3.74 a4.90 a4.24 bc0.18
copper3.80 a4.71 ab4.49 ab0.17
manganese3.56 ab4.49 b4.35 ab0.15
molybdenum3.62 ab4.99 a4.69 a0.16
zinc3.38 b4.17 c4.10 cd0.14
boron3.50 b4.40 b3.76 d0.14
Year (Y)
20233.41 b4.49 b4.25 b0.14 b
20243.65 a4.63 a4.35 a0.18 a
ANOVA p value
F*******n.s.
Y****
F × Yn.s.n.s.n.s.n.s.
Statistically significant differences are marked with different letters. ***, **, *—indicate significant differences at p < 0.001, p < 0.01 and p < 0.05, respectively; n.s.—non-significant according to Tukey’s honestly significant difference (HSD) test.
Table 7. Color parameters of maize flour samples.
Table 7. Color parameters of maize flour samples.
Tested FactorL*a*b*C*h*ΔE
Foliar fertilization (F)
control 75.03 ab7.18 a30.26 a31.11 a76.63 c0.00
iron76.24 ab5.59 b27.64 c28.20 c78.58 ab1.90
copper77.48 a5.43 b28.73 abc29.24 abc79.30 a2.37
manganese75.21 ab6.39 ab28.10 abc28.82 c77.19 abc1.64
molybdenum75.34 ab6.27 ab29.58 ab30.24 ab78.01 ab1.26
zinc74.53 b6.89 ab28.79 abc29.61 abc76.54 c1.24
boron75.91 ab6.59 ab30.08 a30.79 ab77.66 abc2.50
Year (Y)
202375.946.4229.71 a30.01 a77.98-
202475.426.2428.35 b29.43 b77.42-
ANOVA p value
F************-
Yn.s.n.s.**n.s.-
F × Yn.s.n.s.n.s.n.s.n.s.-
Statistically significant differences are marked with different letters. ***, **, *—indicate significant differences at p < 0.001, p < 0.01 and p < 0.05, respectively; n.s.—non-significant according to Tukey’s honestly significant difference (HSD) test.
Table 8. Microelement content in grain (mg kg−1).
Table 8. Microelement content in grain (mg kg−1).
Tested FactorFeCuZnMn
Foliar fertilization (F)
control22.52 ab2.37 ab18.57 ab5.53 ab
iron23.69 a2.31 ab18.43 ab5.56 ab
copper21.52 b2.43 a18.67 ab5.41 b
manganese21.37 b2.24 ab17.68 b5.63 a
molybdenum22.68 ab2.18 b18.53 ab5.52 ab
zinc21.44 b2.29 ab19.41 a5.44 b
boron23.73 a2.29 ab19.01 a5.59 ab
Year (Y)
202321.33 b2.15 b16.4 b4.71 b
202423.50 a2.45 a20.8 a6.35 a
ANOVA p value
F****
Y*********
F × Yn.s.n.s.n.s.n.s.
Statistically significant differences are marked with different letters. ***, **, *—indicate significant differences at p < 0.001, p < 0.01 and p < 0.05, respectively; n.s.—non-significant according to Tukey’s honestly significant difference (HSD) test.
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Jarecki, W.; Borza, I.M.; Rosan, C.A.; Domuța, C.G.; Vicas, S.I. The Effect of Foliar Micronutrient Fertilization on Yield and Nutritional Quality of Maize Grain. Agronomy 2025, 15, 1859. https://doi.org/10.3390/agronomy15081859

AMA Style

Jarecki W, Borza IM, Rosan CA, Domuța CG, Vicas SI. The Effect of Foliar Micronutrient Fertilization on Yield and Nutritional Quality of Maize Grain. Agronomy. 2025; 15(8):1859. https://doi.org/10.3390/agronomy15081859

Chicago/Turabian Style

Jarecki, Wacław, Ioana Maria Borza, Cristina Adriana Rosan, Cristian Gabriel Domuța, and Simona Ioana Vicas. 2025. "The Effect of Foliar Micronutrient Fertilization on Yield and Nutritional Quality of Maize Grain" Agronomy 15, no. 8: 1859. https://doi.org/10.3390/agronomy15081859

APA Style

Jarecki, W., Borza, I. M., Rosan, C. A., Domuța, C. G., & Vicas, S. I. (2025). The Effect of Foliar Micronutrient Fertilization on Yield and Nutritional Quality of Maize Grain. Agronomy, 15(8), 1859. https://doi.org/10.3390/agronomy15081859

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