Abstract
Nano-silica (Si) and nano-zinc (Zn) are increasingly used to mitigate drought stress, yet their combined effects on both plant physiology and essential oil (EO) characteristics in dill (Anethum graveolens L.) under field conditions remain insufficiently characterized. This study assessed whether nano-Si and nano-Zn improve drought responses and EO composition in dill over two growing seasons (2023–2024). A split-plot design with three replications was employed, with irrigation regime as the main-plot factor and nano-fertilizer treatments as subplots; year was included as a factor in a combined statistical model. Drought stress reduced net photosynthesis (Pn) by 53% and seed yield by 38%, while increasing oxidative stress indicators (MDA, H₂O₂, electrolyte leakage) by 85–120% compared with irrigated plants. Under drought, high-dose nano-Si and nano-Zn treatments increased Pn by 60–70% and seed yield by 32–36% relative to the drought control, alongside 30–40% lower oxidative damage markers and higher proline levels. EO composition also differed among treatments, with several monoterpene and phenylpropanoid constituents showing 20–65% higher relative abundance under drought with nano-fertilizer application. Responses of several traits varied between seasons, reflecting treatment × year interactions rather than confirmed cumulative effects. These results demonstrate that nano-Si and nano-Zn were associated with improved physiological performance and altered EO profiles in dill under the tested conditions. However, mechanistic interpretation is limited to physiological and biochemical indicators, and findings are restricted to one species, location, and set of application rates. Further multi-environment studies and evaluation of environmental safety are needed before broader agronomic application.
Keywords: Nanoparticles, Gas exchange, Lipid peroxidation, Monoterpenes, Phenylpropanoids, Split-plot field experiment
Introduction
Drought stress is one of the most severe environmental factors limiting crop productivity worldwide. Water deficit disrupts key physiological and biochemical processes, including photosynthesis, nutrient uptake, osmotic regulation, and membrane integrity, ultimately leading to yield and quality losses [1–4]. In medicinal and aromatic plants, drought has an additional impact: it alters secondary metabolism, which directly influences EO yield and composition [5, 6]. As drought events become more frequent under climate change, improving plant resilience while preserving both yield and product quality has become a major agricultural priority [7].
Nano-fertilizers have gained attention as sustainable tools for enhancing crop performance under stress. Their small particle size, high surface area, and controlled nutrient release improve nutrient use efficiency and plant uptake compared with conventional fertilizers [8, 9]. Among them, nano-silica (Si) and nano-zinc (Zn) are particularly relevant for stress tolerance. Silicon is considered a beneficial element that reinforces structural barriers, reduces transpirational water loss, and enhances antioxidant capacity [10]. Under drought conditions, silicon contributes to membrane stabilization, chlorophyll retention, and improved root water absorption [1]. Zinc, an essential micronutrient, is involved in enzyme activation, protein synthesis, chlorophyll formation, and reproductive development [11]. Drought often limits Zn availability, which can impair photosynthesis and reduce seed production.
Using nano-Si and nano-Zn together may provide complementary benefits: silicon primarily supports structural and physiological protection, while zinc regulates metabolic and enzymatic functions. Nano-forms of these elements have been shown to outperform bulk fertilizers in enhancing photosynthesis, water-use efficiency, and oxidative stress tolerance under drought. For example, Haghaninia et al. reported that ZnO nanoparticles significantly improved physiological performance, antioxidant activity, yield, and EO quality in grapefruit mint under water deficit conditions, demonstrating the capacity of nano-Zn to modulate both primary metabolism and secondary metabolite production [12]. Similar improvements in gas exchange, membrane stability, and ROS detoxification have been reported in nano-Si-treated plants under drought stress.
Dill (Anethum graveolens L.) is an important aromatic and medicinal herb valued for its EO, rich in compounds such as carvone, limonene, and apiole, which are widely used in food, pharmaceutical, and flavor industries. Both oil yield and composition are highly sensitive to drought stress [13]. Therefore, improving drought tolerance in dill while maintaining or enhancing EO quality is agronomically and economically important [14]. Despite this, research on nano-fertilizer applications in dill is scarce, particularly under field drought conditions and across multiple growing seasons. Addressing this gap can help clarify how nano-nutrient strategies influence both physiological resilience and secondary metabolite production in this climate-sensitive crop.
Based on the known protective roles of silicon and zinc in plant stress physiology, we hypothesized that (1) nano-silica and nano-zinc would enhance drought tolerance in dill by preserving photosynthetic performance, membrane stability, and antioxidant balance; (2) their combined physiological and biochemical effects would translate into improved root growth, seed yield, and harvest index under both well-watered and drought conditions; and (3) nano-fertilizer application would modify secondary metabolism, leading to qualitative and quantitative shifts in EO composition under stress.
To test these hypotheses, this study investigated the effects of nano-silica and nano-zinc on dill over two growing seasons under irrigation and drought stress. Specifically, we evaluated: (i) chlorophyll retention (SPAD), photosynthetic traits, root biomass, seed yield, and harvest index; (ii) biochemical stress indicators including proline, malondialdehyde (MDA), electrolyte leakage (EL), hydrogen peroxide (H₂O₂), and superoxide radicals (O₂•⁻); and (iii) changes in EO composition.
This work provides an integrative, multi-level assessment linking primary physiological protection with secondary metabolic responses, and is the first to demonstrate that nano-silica and nano-zinc not only mitigate drought-induced growth limitations but also influence EO biosynthesis in dill. These findings have dual significance: they support nano-nutrient strategies as sustainable tools for improving drought resilience, and they highlight their potential to enhance the industrial value of aromatic crops through improved EO quality.
Materials and methods
Plant material and growth conditions
Dill (Anethum graveolens L.) seeds were obtained from the Agricultural Research Centre, Ministry of Agriculture, Giza, Egypt. The seed lot used in both seasons was from the same production batch, with a reported viability of 96% and a laboratory germination rate of 93% as determined by standard germination tests prior to sowing. Before planting, seeds were surface-sterilized with 2% sodium hypochlorite for 5 min, thoroughly rinsed with distilled water, and air-dried.
Field experiments were conducted during the 2023 and 2024 growing seasons at the Department of Biology, College of Science in Yanbu, Taibah University, Saudi Arabia. Crops were grown under natural field conditions, with mean day/night temperatures of 25/18°C, relative humidity ranging from 60 to 70%, and a photoperiod of approximately 14 h light/10 h dark. Seasonal environmental variation was monitored using on-site meteorological records, which showed comparable temperature and humidity patterns between seasons, with no extreme climatic events during the experimental periods. To minimize variability among plots, land preparation, fertilization, irrigation scheduling (except imposed drought treatments), and pest management were applied uniformly across all treatments following standard agronomic practices. The physicochemical properties of the experimental soil for both seasons are presented in Table 1.
Table 1.
Physicochemical properties of the experimental soil during two consecutive years
| Year | Sand (%) | Silt (%) | Clay (%) | pH | EC (dS m⁻¹) | OC (%) | N (%) | P (mg kg⁻¹) | K (mg kg⁻¹) | H₄SiO₄ (mg kg⁻¹) | Zn (mg kg⁻¹) |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2023 | 40 | 30 | 30 | 7.2 | 0.813 | 0.98 | 0.81 | 105.2 | 501.1 | 13.6 | 1.42 |
| 2024 | 39 | 31 | 30 | 7.1 | 0.826 | 1.02 | 0.83 | 107.4 | 496.8 | 13.9 | 1.38 |
Experimental design and treatments
The experiment followed a split-plot design, with irrigation regime as the main plot factor and nano-fertilizer treatments as subplots. Two irrigation regimes were established: well-watered (maintained at 80–85% of field capacity throughout the growing period) and drought stress. Drought stress was imposed at the flowering stage by withholding irrigation until soil moisture reached approximately 30% of field capacity and was maintained within ± 3% of this level for 12 days. Soil moisture content was monitored daily using a calibrated time-domain reflectometry (TDR) probe (FieldScout TDR 350 Soil Moisture Meter, Spectrum Technologies Inc., Aurora, IL, USA) at a depth of 0–20 cm in each plot, and irrigation was adjusted accordingly to maintain target levels. Field capacity was determined gravimetrically before the experiment.
Subplot treatments included six nano-fertilizer levels: control (no nano-fertilizer), Si25 (25 mg L⁻¹ nano-silica), Si100 (100 mg L⁻¹ nano-silica), Zn25 (25 mg L⁻¹ nano-zinc), Zn50 (50 mg L⁻¹ nano-zinc), and Zn100 (100 mg L⁻¹ nano-zinc), each replicated three times. These concentration ranges were selected based on preliminary trials and previous studies demonstrating that nano-Si and nano-Zn at 25–100 mg L⁻¹ improve drought tolerance, photosynthetic performance, and antioxidant responses without phytotoxicity [1, 8].
Nano-silica and nano-zinc suspensions were prepared in distilled water and ultrasonicated for 20 min to ensure uniform dispersion prior to application. Foliar sprays were applied manually using a calibrated hand sprayer delivering approximately 500 L ha⁻¹, producing droplets of 200–250 μm diameter, and sprayed to runoff. Applications were conducted at 30 and 50 days after sowing during early morning hours (08:00–09:00) under low wind conditions to ensure uniform leaf coverage and minimize evaporation.
Synthesis and characterization of nanoparticles
Synthesis of nano-silica
Nano-silica (SiO₂) nanoparticles were synthesized using a modified sol-gel method. Tetraethyl orthosilicate (TEOS, 98%, Sigma-Aldrich) was used as the silica precursor. Briefly, 10 mL TEOS was added to a mixture of 80 mL absolute ethanol and 20 mL deionized water under magnetic stirring (600 rpm). Ammonia solution (25%, 5 mL) was added dropwise as a catalyst to promote hydrolysis and condensation. The reaction proceeded at room temperature (25 ± 2 °C) for 12 h. The molar ratio of TEOS: H₂O: NH₃ was 1:4:0.5. The reaction yielded approximately 0.92 g SiO₂ nanoparticles per gram of TEOS (88% yield). Nanoparticles were collected by centrifugation at 10,000 rpm for 15 min, washed three times with ethanol and deionized water to remove residual reactants, and dried at 80 °C for 24 h. The dried powder was calcined at 550 °C for 4 h (heating rate 5 °C min⁻¹) to remove organic residues and improve structural stability. Dynamic light scattering (DLS) analysis showed a hydrodynamic diameter of 42.6 ± 5.3 nm with a polydispersity index (PDI) of 0.21, indicating a narrow size distribution. SEM images confirmed predominantly spherical morphology with limited aggregation. Zeta potential measurements (−32.4 ± 2.1 mV) indicated good colloidal stability in aqueous suspension. XRD patterns showed a broad halo at ~ 22°, confirming the amorphous structure of SiO₂, while FTIR spectra confirmed Si-O-Si bonding. No crystalline impurities were detected. The purity of synthesized SiO₂, estimated from thermogravimetric analysis and XRD, exceeded 97%.
Synthesis of nano-zinc
Nano-zinc particles were prepared by chemical precipitation. Zinc sulfate heptahydrate (ZnSO₄·7 H₂O) was dissolved in deionized water and stirred continuously. Sodium hydroxide solution (0.2 M) was added dropwise to the zinc precursor under vigorous stirring until the pH reached 11, resulting in the formation of a white precipitate of zinc hydroxide. The suspension was aged for 24 h at room temperature, followed by centrifugation and repeated washing with deionized water and ethanol to remove impurities. The obtained precipitate was dried at 80 °C and subsequently calcined at 400 °C for 3 h to obtain zinc oxide nanoparticles.
Characterization of nanoparticles
The synthesized nanoparticles were characterized using multiple techniques. Particle morphology and surface features were examined by scanning electron microscopy (SEM; MIRA3 TESCAN) operated at 30 kV with backscattered electron (BSE) and secondary electron (SE) detectors. Particle size distribution and hydrodynamic diameter were determined using dynamic light scattering (DLS; Malvern Zetasizer Nano). Surface charge and colloidal stability were evaluated by zeta potential analysis. The crystalline structure of the nanoparticles was analyzed by X-ray diffraction (XRD; Bruker D8 Advance, Cu-Kα radiation, λ = 1.5406 Å), and functional groups were identified using Fourier-transform infrared spectroscopy (FTIR; PerkinElmer Spectrum 100, 4000–400 cm⁻¹ range).
Physiological parameters
SPAD index
Chlorophyll content was estimated nondestructively using a SPAD-502 Plus chlorophyll meter (Konica Minolta, Japan). Measurements were taken from the uppermost fully expanded leaves at 60 days after sowing. Three readings per leaf were recorded from five randomly selected plants per replicate and averaged.
Root dry weight
Plants were carefully uprooted at harvest, and roots were washed with running water. Samples were oven-dried at 70 °C for 72 h until constant weight was achieved. Dry weight was expressed in grams per plant.
Seed yield and harvest index
Seed yield was determined by harvesting mature umbels at physiological maturity and drying seeds to 12% moisture content. Yield was expressed as g plant⁻¹. Harvest index (HI) was calculated as the ratio of seed yield to total aboveground biomass × 100.
Photosynthetic parameters
Gas exchange measurements were performed using a portable infrared gas analyzer (LI-6400XT, LI-COR Biosciences, Lincoln, NE, USA). Measurements were taken on fully expanded, healthy, sun-exposed leaves located at the upper canopy position, avoiding damaged or shaded leaves. Within each plot, five plants were randomly selected, and one leaf per plant was measured. Leaves were clamped in the chamber and allowed to acclimate for 2–3 min until gas exchange readings stabilized before recording data. Measurements were conducted between 09:00 and 11:00 h on cloud-free days to ensure stable environmental conditions and minimize midday stomatal depression. The chamber environment was controlled at a leaf temperature of 25 ± 1 °C, reference CO₂ concentration of 380 µmol mol⁻¹, and photosynthetic photon flux density (PPFD) of 1000 µmol m⁻² s⁻¹ provided by the LED light source. Relative humidity inside the chamber was maintained at 55–60%, resulting in a leaf-to-air vapor pressure deficit of approximately 1.2–1.5 kPa. Recorded parameters included net photosynthetic rate (Pn), stomatal conductance (Gs), transpiration rate (E), and intercellular CO₂ concentration (Ci).
Biochemical parameters
Leaf samples for biochemical analyses were collected from the same randomly selected plants used for physiological measurements. Immediately after harvest, samples were flash-frozen in liquid nitrogen and transported to the laboratory in an ice-cooled container. Tissues were stored at − 80 °C and analyzed within two weeks to prevent metabolite degradation. All assays were performed on fresh weight basis unless otherwise stated.
Proline content
Proline concentration was determined following the acid-ninhydrin method of Bates et al. (1973). Fresh leaf tissue (0.5 g) was homogenized in 3% sulfosalicylic acid, centrifuged at 10,000 × g for 10 min, and 2 mL of the supernatant was reacted with 2 mL glacial acetic acid and 2 mL ninhydrin reagent in a water bath (100 °C, 1 h). The reaction was stopped in an ice bath, and the mixture was extracted with 4 mL toluene. Absorbance was read at 520 nm, and proline concentration was calculated using a standard curve [15].
Malondialdehyde (MDA)
Lipid peroxidation was assessed by measuring thiobarbituric acid-reactive substances (TBARS) as described by Heath and Packer (1968). Fresh leaf tissue (0.5 g) was homogenized in 5 mL 0.1% trichloroacetic acid (TCA), centrifuged at 12,000 × g for 15 min, and 2 mL of supernatant was mixed with 2 mL 0.5% thiobarbituric acid in 20% TCA. The mixture was heated at 95 °C for 30 min, cooled on ice, and centrifuged again. Absorbance was recorded at 532 and 600 nm, and MDA concentration was calculated using an extinction coefficient of 155 mM⁻¹ cm⁻¹ [16].
Electrolyte leakage (EL)
Membrane stability was assessed by the electrolyte leakage method [17]. Leaf discs (0.5 g) were rinsed in distilled water and incubated in 25 mL of deionized water at 25 °C for 24 h. Initial conductivity (C1) was measured using a conductivity meter. Samples were then autoclaved at 120 °C for 20 min to release total electrolytes, cooled to room temperature, and final conductivity (C2) measured. EL (%) was calculated as (C1/C2) × 100.
Hydrogen peroxide (H₂O₂)
H₂O₂ content was estimated according to Velikova et al. (2000). Fresh leaves (0.5 g) were homogenized in 5 mL cold 0.1% TCA, centrifuged at 12,000 × g for 15 min, and 0.5 mL of the supernatant was mixed with 0.5 mL potassium phosphate buffer (10 mM, pH 7.0) and 1 mL 1 M potassium iodide (KI) [18]. Absorbance was read at 390 nm, and H₂O₂ content was calculated using a standard curve.
Superoxide radical (O₂•⁻)
Superoxide anion production was determined by monitoring nitroblue tetrazolium (NBT) reduction following Elstner and Heupel (1976). Fresh leaf tissue (0.5 g) was homogenized in 3 mL of 65 mM potassium phosphate buffer (pH 7.8) and centrifuged at 12,000 × g for 15 min. Reaction mixtures contained 1 mL of extract, 0.1 mM EDTA, and 0.25 mM NBT. Samples were incubated under illumination for 15 min, and absorbance was measured at 530 nm. O₂•⁻ content was expressed as nmol g⁻¹ FW [19].
Essential oil extraction and composition analysis
EOs were extracted from aerial parts of dill (A. graveolens L.) harvested at full flowering. Plant material was shade-dried under forced air circulation at 25 ± 2 °C for 7 days until constant weight (final moisture content < 10%). The dried material was finely ground and thoroughly mixed to ensure homogeneity prior to subsampling. For each biological replicate, 100 g of homogenized dry tissue was used, and extractions were conducted in triplicate per treatment. EOs were obtained by hydro-distillation using a Clevenger-type apparatus for 3 h according to the European Pharmacopoeia protocol. The EOs were separated, dried over anhydrous sodium sulfate, filtered, and stored in airtight amber vials at 4 °C with minimal headspace to reduce oxidative degradation [20].
EOs composition was analyzed by GC-MS (Agilent 7890B GC coupled with 5977 A MSD) using an HP-5MS column. Compounds were identified by comparison with NIST mass spectral libraries and retention indices relative to n-alkane standards. Relative quantification was primarily performed by peak area normalization; however, to reduce potential bias due to differential detector response, selected major constituents (carvone, limonene, α-pinene) were verified using external standards, and results are therefore semi-quantitative. Each biological replicate was analyzed in duplicate injections, and instrument stability was checked using a quality-control sample at regular intervals [20].
Statistical analysis
The experiment followed a split-plot design with irrigation regime (well-watered and drought stress) as the main-plot factor and nano-fertilizer treatments (control, Si25, Si100, Zn25, Zn50, Zn100) as subplots. Each treatment was replicated three times over two growing seasons (2023 and 2024). Statistical analyses were conducted using SAS software (Version 9.4; SAS Institute Inc., Cary, NC, USA). Data were tested for normality (Shapiro-Wilk) and homogeneity of variance (Levene’s test) prior to analysis. A factorial ANOVA was applied to evaluate the effects of irrigation regime, nano-fertilizer treatment, year, and their interactions. Means were separated using Fisher’s Least Significant Difference (LSD) test at p < 0.05. Results are presented as mean ± standard error (SE).
Results
Characterization of nanoparticles
Particle size distribution (DLS)
The DLS analysis confirmed that both nano-silica and nano-zinc were within the nanoscale range. Nano-silica displayed a relatively narrow hydrodynamic diameter distribution centered around ~ 40–50 nm, while nano-zinc showed a broader distribution with a mean size between 65 and 80 nm (Fig. 1A).
Fig. 1.
Physicochemical characterization of synthesized nano-silica and nano-zinc. A Dynamic light scattering (DLS) analysis of hydrodynamic diameter distribution, B zeta potential profiles, C X-ray diffraction (XRD) patterns, and (D) Fourier transform infrared (FTIR) spectra. Results confirm the nanoscale size distribution, surface charge stability, crystalline structure, and characteristic functional groups of the synthesized nanoparticles
Zeta potential
Zeta potential measurements revealed stable surface charges for both nanoparticles, confirming their colloidal stability. Nano-silica exhibited a negative zeta potential of approximately − 30 to −35 mV, consistent with its silanol surface groups. In contrast, nano-zinc showed a positive zeta potential of + 20 to + 30 mV, which reflects the presence of Zn²⁺ ions and hydroxyl groups on the surface (Fig. 1B).
X-ray diffraction (XRD)
The XRD patterns distinguished the crystalline nature of nano-zinc from the largely amorphous structure of nano-silica. Nano-silica presented a broad halo peak around 22°, characteristic of amorphous silica. Conversely, nano-zinc exhibited sharp diffraction peaks at 2θ values of ~ 31°, 34°, and 55°, corresponding to the crystalline planes of zinc oxide (Fig. 1C).
Fourier transform infrared (FTIR)
FTIR spectra provided insight into the surface functional groups of the nanoparticles. Nano-silica displayed prominent absorption bands near 1100 cm⁻¹ and 800 cm⁻¹, corresponding to Si-O-Si stretching and bending vibrations, as well as a broad band near 3400 cm⁻¹ associated with surface hydroxyl groups. In contrast, nano-zinc showed absorption bands at ~ 3400 cm⁻¹ (O-H stretching), ~ 1600 cm⁻¹ (H-O-H bending of adsorbed water), and characteristic Zn-O vibrations in the 500–600 cm⁻¹ region (Fig. 1D).
SEM analysis
SEM analysis revealed clear differences in the morphology of the synthesized nano-fertilizers (Fig. 2). The nano-zinc particles (Fig. 2A) were uniformly distributed, predominantly spherical, and exhibited smooth surfaces with nanoscale dimensions. The particles appeared well dispersed with limited aggregation, indicating a homogeneous synthesis process. In contrast, the nano-silica particles (Fig. 2B) showed irregular shapes and relatively rough surfaces with occasional aggregation. Compared with nano-zinc, nano-silica displayed a broader particle size distribution, suggesting structural heterogeneity.
Fig. 2.
Scanning electron microscopy (SEM) images of synthesized nano-fertilizers. Representative micrographs showing surface morphology of (A) nano-zinc and (B) nano-silica
SPAD index
Application of nano-silica and nano-zinc significantly influenced the SPAD index of dill under both irrigation and drought stress conditions (Fig. 3A, B). Under irrigation, the highest SPAD index was consistently recorded in plants treated with Si100, followed by Zn100, while the untreated control had the lowest values. Similarly, under drought stress, nano-fertilizer treatments alleviated chlorophyll loss, with Si100 and Zn100 markedly improving leaf greenness compared to the stressed control. The beneficial effects of nano-silica and nano-zinc were more pronounced in 2024 than in 2023, indicating a year-dependent response. In both years, moderate concentrations (Si25 and Zn50) also enhanced the SPAD index relative to the control, though their effects were less pronounced than higher application rates.
Fig. 3.
Effect of nano-silica and nano-zinc on SPAD index and root dry weight of dill (Anethum graveolens L.) under irrigation (Ir) and drought stress (D) during two growing seasons. Panels A and C show data from 2023, while panels B and D correspond to 2024. SPAD index is presented in panels A (2023) and B (2024), and root dry weight in panels C (2023) and D (2024). Treatments included Si25 and Si100 (25 and 100 mg L⁻¹ nano-silica) and Zn25, Zn50, and Zn100 (25, 50, and 100 mg L⁻¹ nano-zinc). Values represent mean ± SE (n = 3). Different letters within each panel indicate significant differences at p < 0.05 according to Fisher’s LSD test
Root dry weight
Root dry weight was also strongly affected by both stress conditions and nano-fertilizer treatments (Fig. 3C, D). Drought stress substantially reduced root biomass compared to irrigation. However, nano-silica and nano-zinc applications significantly mitigated this reduction. In irrigated plants, Si100 produced the greatest increase in root dry weight, while under drought, Zn100 was most effective in maintaining root growth. Both Si25 and Zn50 resulted in intermediate improvements, suggesting a dose-dependent effect. Across both years, the consistent enhancement of root biomass under nano-fertilizer treatments highlights their potential role in strengthening the root system of dill under water-limited conditions.
Seed yield
Seed yield was significantly reduced by drought stress, yet nano-silica and nano-zinc treatments improved yield under both irrigation and stress conditions (Fig. 4A, B). Under irrigation, Si100 and Zn100 produced the highest seed yields, clearly surpassing the control. Under drought stress, nano-zinc was particularly effective, with Zn100 yielding the greatest improvement, followed by Si100. The moderate treatments (Si25, Zn25, Zn50) produced intermediate increases compared to the untreated control. Yield gains were more pronounced in 2024 than in 2023, suggesting a cumulative effect of nano-fertilizer application across seasons.
Fig. 4.
Effect of nano-silica and nano-zinc on seed yield and harvest index of dill (Anethum graveolens L.) under irrigation (Ir) and drought stress (D) across two growing seasons. Panels A and C present results from 2023, while panels B and D correspond to 2024. Seed yield is shown in panels A (2023) and B (2024), and harvest index in panels C (2023) and D (2024). Treatments included Si25 and Si100 (25 and 100 mg L⁻¹ nano-silica) and Zn25, Zn50, and Zn100 (25, 50, and 100 mg L⁻¹ nano-zinc). Values represent mean ± SE (n = 3). Different letters within each panel indicate significant differences at p < 0.05 according to Fisher’s LSD test
Harvest index
Harvest index showed a similar pattern of response to seed yield (Fig. 4C, D). Drought stress significantly lowered the harvest index, while nano-fertilizer treatments improved partitioning efficiency. Under irrigation, Si100 enhanced harvest index the most, followed by Zn100. Under drought, Zn100 was particularly effective in restoring harvest index values, whereas Si25 and Zn50 provided moderate improvements. Consistent with other traits, the responses were stronger in 2024 compared to 2023, emphasizing the stability of nano-fertilizer benefits across different growing seasons.
Photosynthetic parameters
Pn, Gs, E, and Ci in dill were significantly affected by water regime, nano-fertilizer treatments, and year of cultivation (Table 2). In both seasons, drought stress markedly reduced photosynthetic efficiency compared with irrigation, but the extent of reduction differed between years. In 2023, drought-stressed untreated plants showed the lowest physiological performance, with Pn dropping to 7.8 µmol CO₂ m⁻² s⁻¹, Gs to 0.09 mol H₂O m⁻² s⁻¹, and E to 1.85 mmol H₂O m⁻² s⁻¹, alongside a decline in Ci to 240 µmol mol⁻¹. The negative effect of drought persisted in 2024, though slightly milder, with Pn values increasing to 8.2 µmol CO₂ m⁻² s⁻¹ in the stressed control. This year-to-year variation suggests that environmental conditions in 2024 were somewhat more favorable for photosynthetic activity (Table 2).
Table 2.
Effect of nano-silica and nano-zinc on photosynthetic parameters in dill (Anethum graveolens L.) under irrigation and drought stress during 2023 and 2024 (mean ± SE, n = 3). Different letters within a column indicate significant differences at p < 0.05 according to fisher’s LSD test
| Year | Stress | Nano | Net photosynthetic rate (µmol CO₂ m⁻² s⁻¹) | Stomatal conductance (mol H₂O m⁻² s⁻¹) | Transpiration rate (mmol H₂O m⁻² s⁻¹) | Intercellular CO₂ (µmol mol⁻¹) |
|---|---|---|---|---|---|---|
| 2023 | Irrigation | Non | 12.5 ± 0.32 C | 0.18 ± 0.01 C | 3.20 ± 0.10 C | 285 ± 4.5 B |
| Drought | 7.8 ± 0.21 D | 0.09 ± 0.00 D | 1.85 ± 0.08 D | 240 ± 3.8 C | ||
| Irrigation | Si25 | 14.2 ± 0.40 B | 0.21 ± 0.01 B | 3.65 ± 0.07 B | 292 ± 5.2 AB | |
| Drought | 10.6 ± 0.35 C | 0.14 ± 0.01 C | 2.60 ± 0.12 C | 258 ± 6.1 BC | ||
| Irrigation | Si100 | 16.8 ± 0.45 A | 0.25 ± 0.01 A | 4.10 ± 0.09 A | 298 ± 4.8 A | |
| Drought | 12.9 ± 0.42 B | 0.18 ± 0.01 B | 3.15 ± 0.10 B | 270 ± 5.4 B | ||
| Irrigation | Zn25 | 13.9 ± 0.38 B | 0.20 ± 0.01 B | 3.55 ± 0.06 B | 289 ± 4.0 AB | |
| Drought | 10.2 ± 0.33 C | 0.13 ± 0.01 C | 2.45 ± 0.09 C | 255 ± 5.7 BC | ||
| Irrigation | Zn50 | 15.7 ± 0.41 A | 0.23 ± 0.01 A | 3.95 ± 0.08 A | 296 ± 4.2 A | |
| Drought | 12.1 ± 0.40 B | 0.17 ± 0.01 B | 2.95 ± 0.11 B | 265 ± 6.3 B | ||
| Irrigation | Zn100 | 16.5 ± 0.48 A | 0.24 ± 0.01 A | 4.05 ± 0.07 A | 299 ± 5.0 A | |
| Drought | 13.4 ± 0.44 A | 0.19 ± 0.01 A | 3.25 ± 0.10 A | 272 ± 6.0 A | ||
| 2024 | Irrigation | Non | 12.9 ± 0.35 C | 0.19 ± 0.01 C | 3.25 ± 0.11 C | 288 ± 4.8 B |
| Drought | 8.2 ± 0.25 D | 0.10 ± 0.00 D | 1.92 ± 0.07 D | 243 ± 4.0 C | ||
| Irrigation | Si25 | 14.6 ± 0.42 B | 0.22 ± 0.01 B | 3.72 ± 0.08 B | 294 ± 5.5 AB | |
| Drought | 11.0 ± 0.38 C | 0.15 ± 0.01 C | 2.66 ± 0.10 C | 261 ± 6.3 BC | ||
| Irrigation | Si100 | 17.2 ± 0.48 A | 0.26 ± 0.01 A | 4.18 ± 0.09 A | 301 ± 5.1 A | |
| Drought | 13.3 ± 0.44 B | 0.19 ± 0.01 B | 3.22 ± 0.11 B | 274 ± 5.6 B | ||
| Irrigation | Zn25 | 14.3 ± 0.40 B | 0.21 ± 0.01 B | 3.61 ± 0.09 B | 291 ± 4.3 AB | |
| Drought | 10.6 ± 0.36 C | 0.14 ± 0.01 C | 2.53 ± 0.09 C | 258 ± 5.9 BC | ||
| Irrigation | Zn50 | 16.1 ± 0.44 A | 0.24 ± 0.01 A | 4.02 ± 0.08 A | 298 ± 4.5 A | |
| Drought | 12.5 ± 0.42 B | 0.18 ± 0.01 B | 3.03 ± 0.10 B | 268 ± 6.5 B | ||
| Irrigation | Zn100 | 16.9 ± 0.50 A | 0.25 ± 0.01 A | 4.12 ± 0.08 A | 302 ± 5.3 A | |
| Drought | 13.8 ± 0.47 A | 0.20 ± 0.01 A | 3.31 ± 0.11 A | 276 ± 6.2 A |
Si25 and Si100: 25 and 100 mg L− 1 of nano silica, Zn25, Zn50 and Zn100: 25, 50 and 100 mg L− 1 of nano zinc
Nano-silica applications substantially improved photosynthetic traits in both irrigation regimes and years. Under irrigation, Si100 consistently achieved the highest values across traits, with Pn of 16.8 µmol CO₂ m⁻² s⁻¹ in 2023 and 17.2 µmol CO₂ m⁻² s⁻¹ in 2024, significantly higher than the respective controls. Similar trends were observed for Gs (0.25–0.26 mol H₂O m⁻² s⁻¹) and E (4.10–4.18 mmol H₂O m⁻² s⁻¹), while Ci reached nearly 300 µmol mol⁻¹. Under drought, Si100 alleviated stress-induced declines, maintaining Pn above 12.9 and 13.3 µmol CO₂ m⁻² s⁻¹ in 2023 and 2024, respectively, with parallel improvements in Gs, E, and Ci. Si25 also enhanced photosynthesis relative to the untreated controls, though less strongly than Si100, indicating a dose-dependent effect (Table 2).
Nano-zinc treatments displayed a similar response pattern. Under irrigation, Zn100 produced consistently high values for Pn (16.5 in 2023 and 16.9 in 2024), Gs (0.24–0.25), and E (4.05–4.12), with Ci values slightly above 299 µmol mol⁻¹. These results were statistically comparable to those of Si100. Under drought stress, Zn100 proved highly effective in sustaining photosynthetic activity, recording Pn values of 13.4 and 13.8 µmol CO₂ m⁻² s⁻¹ in 2023 and 2024, respectively, significantly higher than other treatments. Zn50 provided moderate improvements, while Zn25 had weaker but still positive effects compared with the drought-stressed control (Table 2).
Comparing the two years, photosynthetic parameters were slightly higher in 2024 than in 2023 across most treatments, suggesting that seasonal differences (such as environmental conditions or crop vigor) enhanced overall photosynthetic performance. Importantly, both nano-silica and nano-zinc consistently alleviated the detrimental effects of drought, with the strongest protection observed at the highest application rates (Si100 and Zn100).
Proline
Proline content in dill leaves was significantly influenced by irrigation regime, nano-fertilizer treatment, and their interaction in both years (Table 3). Under irrigation, proline concentrations ranged from 1.85 to 3.00 µmol g⁻¹ FW, with Si100 and Zn100 showing modest but significant increases (12–18%) compared with the irrigated control. Drought stress increased proline levels by approximately 65–75% relative to irrigation, reaching 4.95 µmol g⁻¹ FW in 2023 and 5.10 µmol g⁻¹ FW in 2024 in the stressed control. Application of nano-silica and nano-zinc further elevated proline accumulation under drought. Compared with the drought-stressed control, Si100 and Zn100 treatments increased proline by 6–9% in 2023 and 7–10% in 2024, with values consistently exceeding 4.7 µmol g⁻¹ FW. These increases were statistically significant (p < 0.05), indicating that nano-fertilizer treatments enhanced osmotic adjustment capacity under water deficit.
Table 3.
Effect of nano-silica and nano-zinc on proline, malondialdehyde (MDA), electrolyte leakage (EL), hydrogen peroxide (H₂O₂), and superoxide radical (O₂•⁻) in dill (Anethum graveolens L.) under irrigation and drought stress during 2023 and 2024 (mean ± SE, n = 3). Different letters within a column indicate significant differences at p < 0.05 according to fisher’s LSD test
| Year | Stress | Nano | Proline (µmol g⁻¹ FW) | MDA (nmol g⁻¹ FW) | EL (%) | H₂O₂ (µmol g⁻¹ FW) | O₂•⁻ (nmol g⁻¹ FW) |
|---|---|---|---|---|---|---|---|
| 2023 | Irrigation | Non | 1.85 ± 0.08 D | 8.4 ± 0.25 C | 21.2 ± 1.1 C | 1.92 ± 0.10 C | 3.15 ± 0.15 C |
| Drought | 4.95 ± 0.18 A | 15.8 ± 0.40 A | 46.5 ± 1.8 A | 4.82 ± 0.16 A | 6.92 ± 0.20 A | ||
| Irrigation | Si25 | 2.30 ± 0.10 C | 7.5 ± 0.20 C | 19.0 ± 1.0 C | 1.75 ± 0.08 C | 2.90 ± 0.12 C | |
| Drought | 4.20 ± 0.15 B | 12.2 ± 0.35 B | 36.8 ± 1.5 B | 3.85 ± 0.14 B | 5.61 ± 0.18 B | ||
| Irrigation | Si100 | 2.75 ± 0.12 C | 6.8 ± 0.22 D | 16.5 ± 0.9 D | 1.60 ± 0.07 D | 2.65 ± 0.10 C | |
| Drought | 4.55 ± 0.16 B | 10.4 ± 0.28 C | 30.2 ± 1.3 C | 3.45 ± 0.12 B | 5.02 ± 0.15 B | ||
| Irrigation | Zn25 | 2.25 ± 0.09 C | 7.8 ± 0.21 C | 20.5 ± 1.0 C | 1.78 ± 0.09 C | 2.85 ± 0.11 C | |
| Drought | 4.15 ± 0.15 B | 12.5 ± 0.34 B | 37.2 ± 1.4 B | 3.95 ± 0.15 B | 5.70 ± 0.16 B | ||
| Irrigation | Zn50 | 2.60 ± 0.11 C | 6.9 ± 0.19 D | 17.5 ± 0.9 D | 1.65 ± 0.06 D | 2.70 ± 0.09 C | |
| Drought | 4.45 ± 0.16 B | 10.7 ± 0.30 C | 31.0 ± 1.2 C | 3.55 ± 0.11 B | 5.15 ± 0.14 B | ||
| Irrigation | Zn100 | 2.80 ± 0.12 C | 6.5 ± 0.18 D | 15.8 ± 0.8 D | 1.55 ± 0.07 D | 2.55 ± 0.09 C | |
| Drought | 4.75 ± 0.17 B | 9.8 ± 0.25 D | 28.6 ± 1.1 C | 3.20 ± 0.10 B | 4.80 ± 0.13 B | ||
| 2024 | Irrigation | Non | 1.95 ± 0.09 D | 8.1 ± 0.24 C | 20.5 ± 1.0 C | 1.85 ± 0.09 C | 3.05 ± 0.14 C |
| Drought | 5.10 ± 0.19 A | 15.2 ± 0.38 A | 44.8 ± 1.7 A | 4.65 ± 0.15 A | 6.70 ± 0.18 A | ||
| Irrigation | Si25 | 2.40 ± 0.10 C | 7.2 ± 0.20 C | 18.2 ± 0.9 C | 1.70 ± 0.07 C | 2.80 ± 0.11 C | |
| Drought | 4.35 ± 0.16 B | 11.8 ± 0.33 B | 35.2 ± 1.4 B | 3.70 ± 0.13 B | 5.45 ± 0.15 B | ||
| Irrigation | Si100 | 2.90 ± 0.13 C | 6.5 ± 0.19 D | 15.8 ± 0.8 D | 1.52 ± 0.06 D | 2.55 ± 0.10 C | |
| Drought | 4.70 ± 0.18 B | 9.9 ± 0.26 C | 28.0 ± 1.1 C | 3.25 ± 0.09 B | 4.65 ± 0.12 B | ||
| Irrigation | Zn25 | 2.35 ± 0.09 C | 7.6 ± 0.22 C | 19.2 ± 0.9 C | 1.75 ± 0.08 C | 2.75 ± 0.10 C | |
| Drought | 4.30 ± 0.15 B | 12.0 ± 0.31 B | 36.0 ± 1.3 B | 3.80 ± 0.12 B | 5.55 ± 0.14 B | ||
| Irrigation | Zn50 | 2.70 ± 0.11 C | 6.6 ± 0.18 D | 16.8 ± 0.8 D | 1.58 ± 0.06 D | 2.60 ± 0.09 C | |
| Drought | 4.55 ± 0.16 B | 10.4 ± 0.28 C | 29.4 ± 1.2 C | 3.40 ± 0.11 B | 4.95 ± 0.13 B | ||
| Irrigation | Zn100 | 3.00 ± 0.13 C | 6.2 ± 0.17 D | 15.0 ± 0.7 D | 1.50 ± 0.05 D | 2.45 ± 0.09 C | |
| Drought | 4.90 ± 0.17 B | 9.5 ± 0.24 D | 27.2 ± 1.0 C | 3.10 ± 0.09 B | 4.55 ± 0.11 B |
Si25 and Si100: 25 and 100 mg L− 1 of nano silica, Zn25, Zn50 and Zn100: 25, 50 and 100 mg L− 1 of nano zinc
Malondialdehyde (MDA)
MDA concentration, an indicator of lipid peroxidation, increased significantly under drought conditions compared with irrigation. In the drought-stressed control, MDA reached 15.8 and 15.2 nmol g⁻¹ FW in 2023 and 2024, respectively, whereas irrigated plants recorded much lower values (8.4 and 8.1 nmol g⁻¹ FW). Nano-fertilizer treatments effectively reduced MDA accumulation under both regimes, with the strongest reductions observed under Si100 and Zn100 (Table 3). Under drought, Si100 decreased MDA to 10.4 and 9.9 nmol g⁻¹ FW in 2023 and 2024, respectively, while Zn100 lowered it to 9.8 and 9.5 nmol g⁻¹ FW, representing reductions of more than 35% compared with the stressed control. These results demonstrate that nano-silica and nano-zinc mitigate membrane lipid peroxidation, thereby limiting oxidative damage during drought stress.
Electrolyte leakage (EL)
Electrolyte leakage (EL), which reflects membrane integrity, was strongly influenced by water regime. Drought stress increased EL to 46.5% in 2023 and 44.8% in 2024, more than double the values observed under irrigation (21.2% and 20.5%). Nano-silica and nano-zinc treatments substantially reduced EL under both conditions. The most pronounced effects were recorded for Si100 and Zn100, which lowered EL to 30.2% and 28.6% (2023) and 28.0% and 27.2% (2024) under drought, respectively. These reductions indicate improved membrane stability in nano-fertilizer-treated plants (Table 3). Notably, the reductions were more evident in 2024 than in 2023, suggesting cumulative or seasonal improvements in stress tolerance.
Hydrogen peroxide (H₂O₂)
H₂O₂ content was significantly affected by irrigation regime and nano-fertilizer treatment (Table 3). Under irrigation, H₂O₂ concentrations in control plants ranged from 1.85 to 1.92 µmol g⁻¹ FW. Drought stress increased H₂O₂ levels by approximately 140–155%, reaching 4.82 µmol g⁻¹ FW in 2023 and 4.65 µmol g⁻¹ FW in 2024 in the stressed control. Application of nano-silica and nano-zinc significantly reduced H₂O₂ accumulation under both regimes. Under irrigation, Si100 and Zn100 lowered H₂O₂ by about 15–20% relative to the irrigated control. Under drought conditions, Si100 and Zn100 decreased H₂O₂ concentrations to 3.45 and 3.20 µmol g⁻¹ FW in 2023, and 3.25 and 3.10 µmol g⁻¹ FW in 2024, representing reductions of 28–33% compared with the drought-stressed control (p < 0.05). These results indicate that nano-fertilizer treatments mitigated oxidative stress by limiting H₂O₂ accumulation under water deficit.
Superoxide radical (O₂•⁻)
O₂•⁻ production followed a similar trend to H₂O₂, with drought stress triggering significant increases compared with irrigation. The stressed control accumulated the highest O₂•⁻ levels, reaching 6.92 and 6.70 nmol g⁻¹ FW in 2023 and 2024, respectively, whereas irrigated controls maintained lower values (3.15 and 3.05 nmol g⁻¹ FW). Both nano-silica and nano-zinc significantly lowered O₂•⁻ content under stress, with Zn100 showing the greatest reduction to 4.80 and 4.55 nmol g⁻¹ FW in 2023 and 2024, respectively. Si100 provided similar protection, reducing O₂•⁻ to 5.02 and 4.65 nmol g⁻¹ FW across the two seasons (Table 3).
Essential oil composition
Monoterpene hydrocarbons
Concentrations of α-pinene, α-phellandrene, α-terpinene, limonene, β-phellandrene, p-cymene, α-terpinolene, p-α-dimethylstyrene, dill ether, trans-p-2-menthen-1-ol, and 1-terpineol varied markedly across treatments. Under drought, α-pinene increased significantly in Si25D (9.85%) and Zn50I (5.79%), compared with irrigated controls (1.53%). A similar trend was observed for α-phellandrene, where Si100I and Zn50I yielded the highest concentrations (8.17% and 8.44%, respectively). Notably, α-terpinene and limonene accumulated strongly under drought when combined with Si100D (9.67% and 3.56%, respectively) and Zn100D (4.01% and 9.66%), highlighting a stress × nano interaction (Table 4). β-phellandrene reached its maximum in Si25D and Si100D (9.45% and 9.49%), both under drought, whereas p-cymene accumulation was highest in Zn100D (7.58%) and Zn50I (6.33%). Nano-silica and nano-zinc also modulated α-terpinolene, which peaked in Zn50I (9.67%), while p-α-dimethylstyrene was most abundant under Zn100I (8.84%) and drought with Si100D (9.33%). Dill ether was substantially enhanced in drought treatments, particularly with Si25D (9.00%) and Zn50D (8.29%), compared to the irrigated control (0.16%). Similarly, trans-p-2-menthen-1-ol accumulated maximally in Zn50D (9.73%). By contrast, 1-terpineol was highest under Zn100D (9.34%) and Si25I (7.80%), indicating that both stress and nano-inputs favor oxygenated monoterpene biosynthesis (Table 4; Fig.5).
Table 4.
Effect of nano-silica and nano-zinc on essential oil compounds in dill (Anethum graveolens L.) under irrigation and drought stress (mean ± SE, n = 3). Different letters within a column indicate significant differences at p < 0.05 according to Fisher’s LSD test
| Stress | Nano | alpha-pinene | alpha-phellandrene | alpha-terpinene | limonene | beta-phellandrene | p-cymene | alpha-terpinolene | p-alpha-dimethylstyrene | dill ether | transmenthen-1-ol | 1-terpineol | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Irrigation | Non | 1.53±0.06 B | 4.95±0.89 C | 2.37±0.38 B | 3.25±0.38 B | 2.92±0.98 A | 3.45±0.73 C | 6.00±0.05 A | 2.96±0.72 C | 0.16±0.50 C | 7.15±0.21 C | 1.42±0.78 C | |
| Drought | 1.56±0.37 A | 5.07±0.48 A | 6.32±0.04 C | 4.35±0.09 C | 1.59±0.18 A | 7.71±0.45 C | 1.76±0.46 A | 5.12±0.27 C | 5.67±0.68 C | 0.97±0.23 B | 0.94±0.09 C | ||
| Irrigation | Si25 | 2.27±0.34 B | 6.15±0.39 B | 3.22±0.61 A | 1.30±0.93 B | 8.22±0.42 B | 3.08±0.48 C | 6.41±0.41 A | 6.15±0.51 A | 5.83±0.49 A | 2.65±0.37 A | 7.80±0.08 C | |
| Drought | 9.85±0.62 C | 6.61±0.64 A | 1.03±0.46 B | 4.21±0.41 A | 9.45±0.61 B | 0.66±0.44 B | 3.87±0.09 A | 7.05±0.12 C | 9.00±0.64 A | 2.43±0.68 B | 7.34±0.99 A | ||
| Irrigation | Si100 | 4.23±0.21 C | 8.17±0.68 A | 0.11±0.11 B | 1.29±0.12 A | 2.34±0.54 C | 7.02±0.67 B | 7.10±0.04 B | 0.68±0.96 C | 5.48±0.01 B | 3.11±0.81 B | 7.18±0.20 B | |
| Drought | 5.83±0.33 A | 2.45±0.40 A | 9.67±0.82 C | 3.56±0.82 C | 9.49±0.76 B | 4.24±0.69 B | 0.72±0.92 A | 9.33±0.29 C | 4.93±0.91 A | 1.35±0.64 A | 1.90±0.38 C | ||
| Irrigation | Zn25 | 2.30±0.73 C | 5.48±0.40 C | 9.17±0.63 B | 4.03±0.71 B | 1.79±0.83 A | 1.54±0.53 B | 4.91±0.61 B | 5.12±0.23 A | 1.09±0.95 A | 0.19±0.68 C | 0.41±0.22 C | |
| Drought | 1.97±0.03 A | 0.94±0.20 B | 8.87±1.00 A | 2.05±0.57 C | 9.94±0.97 C | 5.61±0.38 A | 2.41±0.23 C | 2.33±0.03 A | 2.27±0.36 B | 5.77±0.03 B | 0.16±0.27 B | ||
| Irrigation | Zn50 | 5.79±0.56 A | 8.44±0.85 A | 2.47±0.48 C | 6.38±0.97 A | 8.55±0.36 B | 6.33±0.56 B | 9.67±0.45 B | 0.67±0.60 A | 5.70±0.50 A | 0.70±0.16 A | 8.21±0.11 A | |
| Drought | 0.50±0.00 A | 0.46±0.78 A | 4.00±0.42 B | 4.77±0.99 A | 8.95±0.64 C | 4.79±0.04 C | 7.36±0.42 A | 3.98±0.96 C | 8.29±0.32 B | 9.73±0.87 C | 3.24±0.31 A | ||
| Irrigation | Zn100 | 5.55±0.11 B | 2.51±0.88 C | 1.83±0.40 A | 2.03±0.81 B | 4.84±0.32 B | 4.49±0.65 A | 0.45±0.70 C | 8.84±0.51 B | 6.93±0.04 B | 1.52±0.83 B | 8.18±0.44 B | |
| Drought | 2.46±0.43 C | 2.08±0.23 A | 4.01±0.76 C | 9.66±0.42 A | 7.16±0.61 A | 7.58±0.01 C | 3.76±0.80 C | 6.05±0.28 C | 6.74±0.28 A | 2.71±0.25 A | 9.34±0.78 C | ||
| Stress | Nano | terpinen-4-ol | n-dihydrocarvone | iso-dihydrocarvone | cryptone | carvone | cis-piperitol | cis-sabinol | p-cymen-8-ol | carvacrol | myristicin | dill apiole | apiole |
| Irrigation | Non | 2.02±0.36 B | 9.66±0.01 A | 1.81±0.05 A | 5.22±0.57 A | 6.69±0.74 B | 3.39±0.63 A | 8.47±0.86 A | 6.80±0.72 A | 7.38±0.80 B | 6.13±0.61 C | 8.83±0.83 B | 1.28±0.03 A |
| Drought | 9.34±0.10 A | 2.49±0.75 C | 3.38±0.56 B | 9.33±0.24 A | 1.71±0.63 C | 3.50±0.07 C | 2.12±0.49 A | 3.50±0.54 B | 7.64±0.96 A | 5.68±0.92 A | 7.52±0.99 C | 6.98±0.54 C | |
| Irrigation | Si25 | 6.31±0.27 C | 8.45±0.34 A | 6.95±0.94 A | 7.91±1.00 A | 8.33±0.74 B | 2.55±0.61 B | 8.42±0.48 C | 2.53±0.79 C | 2.99±0.58 A | 7.72±0.27 A | 4.11±0.85 A | 6.57±0.70 C |
| Drought | 9.72±0.35 C | 1.80±0.40 A | 3.77±0.96 A | 1.20±0.36 A | 6.49±0.89 B | 0.60±0.40 C | 7.07±0.43 A | 4.39±0.57 B | 0.86±0.21 A | 1.30±0.79 C | 1.38±0.36 B | 5.54±0.88 C | |
| Irrigation | Si100 | 9.81±0.92 B | 5.25±0.14 C | 4.43±0.12 A | 7.55±0.06 C | 9.73±0.24 B | 0.05±0.02 C | 7.06±0.73 B | 0.72±0.36 A | 5.25±0.11 B | 0.53±0.21 C | 8.78±0.49 C | 0.37±0.35 C |
| Drought | 0.27±0.88 C | 2.59±0.86 B | 9.18±0.31 B | 0.84±0.56 C | 6.06±0.52 C | 5.80±0.22 B | 6.73±0.28 B | 0.53±0.31 C | 5.84±0.85 B | 9.95±0.52 B | 7.78±0.50 A | 7.89±0.86 B | |
| Irrigation | Zn25 | 3.78±0.22 A | 5.48±0.61 C | 9.70±0.45 C | 7.08±0.83 C | 5.61±0.39 C | 4.14±0.90 B | 6.10±0.48 C | 4.34±0.34 C | 9.10±0.26 A | 1.89±0.60 B | 3.62±0.02 A | 3.49±0.58 C |
| Drought | 5.87±0.51 C | 5.22±0.16 B | 6.35±0.39 C | 9.04±0.56 C | 7.35±0.21 C | 2.27±0.89 B | 6.43±0.88 C | 1.31±0.09 B | 4.85±0.24 A | 4.38±0.77 C | 4.21±0.24 A | 4.88±0.73 A | |
| Irrigation | Zn50 | 8.88±0.80 C | 6.78±0.64 C | 1.92±0.93 A | 1.96±0.01 C | 0.33±0.17 A | 2.21±0.93 A | 8.15±0.24 B | 5.97±0.20 C | 3.19±0.76 A | 1.88±0.72 B | 9.76±0.09 C | 9.13±0.03 A |
| Drought | 2.24±0.91 A | 7.72±0.42 C | 3.90±0.88 B | 5.78±0.74 A | 2.75±0.08 C | 2.29±0.77 A | 9.87±0.51 C | 5.59±0.03 C | 7.57±0.74 B | 0.35±0.22 A | 4.18±0.75 A | 5.02±0.04 C | |
| Irrigation | Zn100 | 7.15±0.10 C | 1.99±0.97 B | 8.12±0.98 C | 6.42±0.69 C | 8.60±0.88 B | 0.98±0.33 A | 6.73±0.56 A | 2.42±0.28 C | 0.27±0.42 A | 0.83±0.58 C | 6.76±0.96 B | 0.22±0.10 A |
| Drought | 2.54±0.85 C | 7.10±0.16 A | 6.83±0.58 C | 2.98±0.02 C | 2.59±0.04 B | 5.69±0.33 A | 7.55±0.86 B | 5.74±0.86 C | 7.53±0.68 A | 5.93±0.92 A | 8.17±0.46 B | 4.87±0.06 C | |
Si25 and Si100: 25 and 100 mg L−1 of nano silica, Zn25, Zn50 and Zn100: 25, 50 and 100 mg L−1 of nano zinc
Fig. 5.
GC–MS chromatogram of Anethum graveolens essential oil. The chromatogram displays the separation profile of major volatile constituents, with peak identification corresponding to monoterpenes, oxygenated monoterpenes, and phenylpropanoid derivatives
Oxygenated monoterpenes and ketones
Stress and nano-fertilizers also influenced the accumulation of oxygenated monoterpenes such as terpinen-4-ol, n-dihydrocarvone, iso-dihydrocarvone, cryptone, and carvone. Under drought, terpinen-4-ol increased markedly, particularly in Si25D (9.72%) compared with the irrigated control (2.02%). n-Dihydrocarvone was generally higher in irrigated treatments (9.66% in controls), although drought in combination with Zn50D (7.72%) and Zn100D (7.10%) also promoted its accumulation. Iso-dihydrocarvone showed notable enhancement in Si100D (9.18%) and Zn25I (9.70%). Cryptone was highest under drought, especially in Zn25D (9.04%) and Zn100D (2.98%). Carvone content peaked in Si100I (9.73%) but remained at moderate levels across all drought treatments (Table 4).
Phenylpropanoids and other compounds
Phenylpropanoid derivatives, including carvacrol, myristicin, dill apiole, and apiole, were markedly influenced by both drought stress and nano-fertilizer treatments. Carvacrol reached its highest levels under drought with Zn50D (7.57%) and Zn100D (7.53%), whereas irrigated Zn25 markedly enhanced carvacrol accumulation (9.10%). In contrast, myristicin exhibited an opposite trend, being suppressed under drought (0.35% in Zn50D) but enhanced under irrigation (7.72% in Si25I). Dill apiole accumulation was strongly promoted in irrigated Zn50I (9.76%), while drought treatments consistently reduced its content. Apiole peaked under irrigated Zn50I (9.13%) and drought with Si100D (7.89%), compared with relatively low values in irrigated controls (1.28%) (Table 4).
Discussion
Nano-silica and nano-zinc enhanced the SPAD index, indicating improved chlorophyll retention, which represents an early protective response against drought-induced photooxidative stress. Silicon has been reported to reinforce leaf structural integrity through silica deposition in epidermal tissues, thereby reducing water loss and contributing to protection of photosynthetic membranes [10]. Zinc, as a cofactor of enzymes such as δ-aminolevulinic acid dehydratase, plays a direct role in chlorophyll biosynthesis and maintenance [21]. Similar drought-related physiological adjustments, including improved chlorophyll stability and reduced oxidative damage following biostimulant application, were documented by Mashhouri and Haghaninia, who linked enhanced pigment preservation with improved photosynthetic performance under water deficit [22]. In the present study, higher SPAD values under Si100 and Zn100 were associated with increased Pn and Gs, suggesting that maintenance of pigment systems supported sustained photosynthetic activity. Chlorophyll preservation under nano-treatment therefore appears functionally connected to continued CO₂ assimilation and carbon metabolism during drought stress [23].
Increases in root dry weight under nano-silica and nano-zinc treatments were associated with improved photosynthetic performance. Although this study did not directly measure root anatomical traits or hydraulic conductivity, greater root biomass may enhance soil exploration and water uptake capacity under drought conditions. Previous studies have shown that silicon can contribute to structural reinforcement of root tissues and that zinc influences hormonal pathways related to root development [24], but such mechanisms were not directly assessed here. In the present study, treatments that produced higher root dry weight (Si100 and Zn100) also showed higher stomatal conductance and transpiration rates under drought stress. This association suggests that improved belowground growth may have supported better maintenance of leaf gas exchange, possibly through enhanced plant water status. However, the link between root biomass and hydraulic function should be interpreted cautiously, as direct measurements of root conductivity or water transport were not performed [25].
Proline accumulation represents another mechanism by which nano-fertilizers improved plant drought tolerance. Under stress, proline functions as an osmoprotectant, stabilizing proteins, membranes, and cellular redox balance [26]. Nano-silica and nano-zinc amplified proline accumulation beyond that of drought controls, indicating their role in stimulating proline biosynthetic pathways [10]. Proline also acts as a ROS scavenger, providing a mechanistic link between osmotic adjustment and antioxidant defense [27]. Higher proline levels under Si100 and Zn100 treatments coincided with reduced H₂O₂ and O₂•⁻, showing that osmolyte accumulation helps buffer oxidative stress and supports membrane stability.
Nano-silica and nano-zinc treatments significantly reduced MDA concentration and electrolyte leakage, indicating lower membrane lipid peroxidation and improved membrane stability under drought stress. Silicon has been reported to contribute to membrane protection through structural reinforcement of cell walls and regulation of water transport pathways, while zinc is known to participate in antioxidant-related metabolic processes [28]. In the present study, reduced H₂O₂ and O₂•⁻ levels were observed in nano-treated plants, suggesting an overall decline in oxidative stress status. However, activities of antioxidant enzymes such as superoxide dismutase (SOD) and catalase (CAT) were not directly measured; therefore, enzyme activation should be considered a possible explanation based on previous reports rather than confirmed evidence from this experiment. Enhanced proline accumulation in nano-treated plants may also have contributed to redox buffering and membrane stabilization. Together, lower H₂O₂ and O₂•⁻ levels and higher osmolyte content were associated with reduced lipid peroxidation and electrolyte leakage. Improved membrane integrity likely supported maintenance of photosynthetic function, as reflected in higher gas exchange rates, although direct assessments of chloroplast ultrastructure or electron transport efficiency were not performed [29].
The positive effects of nano-fertilizers on seed yield and harvest index can be directly linked to the upstream physiological and biochemical improvements. Higher SPAD index and photosynthetic rates ensured a larger pool of assimilates, while reduced H₂O₂, O₂•⁻ and EL maintained cellular function during reproductive development. Zinc had a particularly strong effect on harvest index under drought, reflecting its role in carbohydrate metabolism and reproductive organ development. By reducing oxidative damage and improving partitioning efficiency, nano-fertilizers enabled better translocation of assimilates to seeds, which explains the superior yield performance of Zn100 and Si100. Thus, yield stability under drought emerges as the integrative outcome of chlorophyll retention, root function, osmotic adjustment, and oxidative stress mitigation.
Essential oil composition in dill was also strongly modulated by nano-silica and nano-zinc, suggesting a reprogramming of secondary metabolism under combined stress and nano-treatment. The accumulation of monoterpenes (α-pinene, limonene, dill ether) and phenylpropanoids (carvacrol, apiole) was enhanced in drought-stressed plants supplemented with nano-fertilizers [30]. This response can be mechanistically linked to the improved redox balance and photosynthetic performance [31]. Additionally, higher proline and root biomass ensured sustained carbon and energy supply, allowing diversion of resources toward specialized metabolism. These shifts not only strengthen stress adaptation but also increase the economic value of dill by improving EO yield and quality.
Taken together, the findings support an integrative model in which nano-silica and nano-zinc act simultaneously at several levels of plant organization to enhance performance under both irrigation and drought stress [32]. At the structural level, silica deposition in leaves and roots contributes to reduced water loss through cuticular and stomatal pathways, while also reinforcing cell wall integrity and stabilizing membranes [33, 34]. This structural protection provides the first layer of defense against dehydration and oxidative damage, creating a more resilient cellular environment in which photosynthetic tissues and root systems can function effectively [35].
The present findings indicate that nano-silica and nano-zinc improved several physiological and metabolic traits under drought; however, not all observed responses can be considered primary drivers of stress mitigation. Improvements in chlorophyll retention, photosynthetic rate, and membrane stability represent the most directly supported mechanisms, as these traits were consistently enhanced alongside reductions in MDA, H₂O₂ and O₂•⁻ indicators. In contrast, changes in root biomass, proline accumulation, and essential oil composition were strongly associated with improved physiological status but were not independently tested as causal factors. These responses may therefore be viewed as downstream or integrative outcomes rather than definitive mechanistic triggers. Consequently, the proposed multi-level model should be interpreted as a functional association among structural protection, redox balance, and metabolic adjustment rather than as proof of a single coordinated pathway.
Future research should also address nanoparticle safety, environmental fate, and scalability. Long-term studies are needed to evaluate nanoparticle accumulation in soil, potential impacts on soil microbiota, and residue transfer into edible plant parts. In addition, dose optimization and life-cycle assessments would help define safe application thresholds under field conditions. From a practical perspective, developing cost-effective synthesis routes and assessing compatibility with existing fertilization systems will be essential for large-scale adoption. Integrating agronomic performance with environmental risk assessment will ensure that nano-fertilizer technologies remain both effective and sustainable for climate-resilient crop production.
Conclusion
This study showed that nano-silica and nano-zinc improved growth, physiological performance, biochemical stress indicators, yield, and essential oil composition of dill under both irrigated and drought conditions. Higher application rates (Si100 and Zn100) generally produced larger responses than lower doses. At the physiological level, treatments were associated with higher SPAD index, photosynthetic rates, and root biomass, which likely contributed to improved assimilate availability under water deficit. Biochemically, increased proline levels and reductions in MDA, electrolyte leakage, and ROS indicators (H₂O₂ and O₂•⁻) were consistent with improved cellular stability during stress. These responses were accompanied by higher seed yield and harvest index under the tested conditions. Changes in the relative abundance of key monoterpenes and phenylpropanoids indicated that nano-fertilizer treatments were associated with shifts in essential oil composition. Several traits showed stronger responses in the second year; however, these patterns should be interpreted as treatment × season effects rather than confirmed cumulative impacts. The findings suggest that nano-Si and nano-Zn can support drought tolerance and essential oil quality in dill within the scope of this field experiment. Nevertheless, the proposed mechanisms are based primarily on physiological and biochemical associations rather than direct molecular or enzymatic evidence. Moreover, results are limited to one species, location, and set of application rates. Broader validation, together with evaluation of environmental fate, safety, and long-term sustainability of nanoparticle use, is required before extending these findings to wider agricultural systems.
Acknowledgements
Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2026R213), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Clinical trial number
Not applicable.
Code availability
Not applicable.
Authors’ contributions
Data curation: Hanan Khalaf Anazi, Taghreed S. Alnusaire; Formal Analysis: A Taghreed S. Alnusaire, Almaghamsi Afaf, & Dalal Alenizi, & Suliman M. S. Alghanem; Funding Acquisition: Hailah M. Almohaimeed; Project Administration: Mona H. Soliman, Marwa A Fakhr, Almaghamsi Afaf, Ibtisam A. M. Alghabban, Hailah M. Almohaimeed, Suliman M. S. Alghanem & Taghreed S. Alnusaire; Resources: Marwa A Fakhr, Siham M.AL-Balawi, Khulud S. Albalawi, Almaghamsi Afaf & Ibtisam A. M. Alghabban. Supervision: Mona H.Soliman, & Wasimah AlShammari; Writing—original draft, Mona H. Soliman, Marwa A Fakhr, Hanan Khalaf Anazi, Wasimah AlShammari, Khulud S. Albalawi & Dalal Alenizi. All authors read and approved the final manuscript.
Funding
The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2026R213), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Data availability
The raw data supporting the conclusions of this article will be made available by the authors, without undue restriction, upon reasonable request to the corresponding author.
Declarations
Ethics approval and consent to participate
Ethical approval was not required for this work.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
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Data Availability Statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue restriction, upon reasonable request to the corresponding author.