External application of growth regulators modulates morpho-physiological traits and biochemical profiles of fennel

Kamal Mohammadi; Mozhgan Mohammadi; Yavar Vafaee; Rahele Ghanbari Moheb Seraj; Jalal Khorshidi

doi:10.1038/s41598-025-25569-1

. 2025 Nov 24;15:41667. doi: 10.1038/s41598-025-25569-1

External application of growth regulators modulates morpho-physiological traits and biochemical profiles of fennel

Kamal Mohammadi ¹, Mozhgan Mohammadi ¹, Yavar Vafaee ^1,^2,^✉, Rahele Ghanbari Moheb Seraj ¹, Jalal Khorshidi ^1,²

PMCID: PMC12644539 PMID: 41286082

Abstract

Fennel (Foeniculum vulgare Mill) is a valuable medicinal plant from the Apiaceae family, cultivated for its essential oil, seeds, and leaves, which are used in the pharmaceutical, food, and cosmetics industries. This study tested the hypothesis that plant growth regulators (PGRs) positively modulate the morphological, physiological, and phytochemical properties of fennel. To test this hypothesis, a factorial experiment was carried out with foliar applications of four plant growth regulators, including salicylic acid (SA: 1 and 2 mM), gibberellic acid (GA: 0.25 and 0.5 mM), gamma-aminobutyric acid (GABA: 5 and 10 mM), and sodium nitroprusside (SNP: 1.25 and 2.5 mM). The results showed that SNP2.5 and GA0.5 treatments achieved the greatest improvement in growth and morphological traits. For the SNP2.5 treatment, morphological traits exhibited percentage changes ranging from 36.5 to 198.6%. SNP2.5 and SA2 treatments resulted in the highest values for physiological traits. The SNP2.5 treatment caused significant increases in flavonoid and phenolic contents, DPPH radical scavenging activity, and chlorophyll and carotenoid levels, with increases ranging from about 39% to 231% compared to the control. Meanwhile, SA (1 and 2 mM) and GA0.25 had superior effects on phytochemical traits, including essential oil yield and secondary metabolites. GABA10 also positively influenced all traits, though to a lesser extent than other treatments. Control plants consistently exhibited the lowest values across all traits. Metabolite analysis using GC-MS identified a total of 150 compounds, among which 41 showed significant differences among treatments. Notably, six major metabolites accounted for about 70% of the total metabolite content, including apiol (0.742–1.299), camphene hydrate (0.407–0.708), cis-anethole (0.328–0.975), estragole (0.916–1.059), phenyl acetate (5.005–9.705), and limonene (3.902–1.647) respectively for SA1 and SA2. Among these, cis-anethole (40–75%) and limonene (6.5–19%) were identified as the predominant components in the essential oil of the leaves. These findings suggest that certain plant growth regulators, especially SNP and SA, can be used as effective agricultural tools for improving the growth and phytochemical quality of fennel.

Keywords: Essential oil, Hormones, Medicinal plants, Metabolic profiling, PGRs

Subject terms: Metabolomics, Biochemistry, Physiology, Plant sciences

Introduction

Fennel (Foeniculum vulgare Mill.), a member of the Apiaceae family, is an important edible, medicinal, and cosmetic plant commonly cultivated in arid and semi-arid regions¹. Iran is a leading global producer of fennel seeds, with cultivation predominantly concentrated in its eastern, northern, and western regions^2,3. Fennel seeds are renowned for their rich composition of carbohydrates, alkaloids, phenols, flavonoids, dietary fiber, proteins, and essential nutrients such as iron, magnesium, and manganese⁴. Similarly, fennel leaves are an important dietary component, valued for their nutrient density and therapeutic potential. These leaves are rich in essential oils, vitamins (A, C, and E), and minerals, along with bioactive compounds like flavonoids and phenolics, which contribute to their strong antioxidant and anti-inflammatory properties^5,6. The essential oils found in fennel leaves, including trans-anethole, estragole, and limonene, not only provide a distinctive flavor but also exhibit antimicrobial and digestive health benefits, making them integral to traditional diets and medicinal formulations^7,8.

One effective strategy to enhance plant growth and secondary metabolite production is the application of elicitors⁹. Plant activities are primarily regulated by phytohormones and growth regulators, which improve tolerance to adverse conditions¹⁰. Among these, salicylic acid (SA), gibberellic acid (GA3), γ-amino butyric acid (GABA), and sodium nitroprusside (SNP) play critical roles in modulating physiological processes and enhancing productivity.

SA, a phenolic compound, regulates key physiological processes such as photosynthesis, nitrogen and proline metabolism, and antioxidant defense¹¹. By stimulating secondary metabolite production, SA enhances antioxidant levels, thereby improving plant growth and development¹². Its effects depend on factors such as plant species, developmental stage, application method, and concentration¹³. Foliar application of SA significantly increased essential oil yield from 30% to 60% compared to the control in Thymbra spicata L.¹⁴.

GA3, a member of the gibberellin family of tetracyclic diterpenoids, promotes plant growth and development by influencing processes such as flowering, leaf expansion, stem elongation, germination, and biomass production^15,16. Additionally, GA3 has been shown to induce the biosynthesis of secondary metabolite^17,18. The application of GA3 stimulates plant growth, increases and biomass, enhances photosynthetic efficiency, and improves the nutritional status and antioxidant machinery of plants by decreasing malondialdehyde content, initiating hydrogen peroxide (H₂O₂) production and decreasing electrolyte leakage (%) in the roots and leaves of Coriandrum sativum seedlings¹⁹.

GABA (γ-aminobutyric acid) is a four-carbon, non-protein amino acid synthesized from L-glutamate via the GABA shunt in the tricarboxylic acid (TCA) cycle^20,21. Beyond its role as an osmolyte, GABA acts as a signaling molecule that mitigates the effects of abiotic stress, particularly salinity²². This protective role is facilitated through the GABA bypass pathway, which scavenges free radicals and enhances antioxidant activity²³. Shala et al.²⁴ indicated that the foliar application of GABA at 40 mM can alleviate the adverse effects of salinity on French lavender by improving vegetative growth and root characteristics, reducing chlorophyll degradation, maintaining high leaf relative water content, and increasing proline accumulation and antioxidant activity.

SNP, a nitric oxide (NO)-releasing compound, acts as a biological messenger in plants. NO regulates diverse physiological processes, including photosynthesis, stomatal conductance, antioxidant activity, and nutrient uptake, while also mitigating oxidative stress^25–27. Additionally, it enhances seed germination, growth, and resistance to abiotic stresses such as metal toxicity, drought, and extreme temperatures^28–30. Jabeen et al.³¹ reported that SNP application significantly ameliorated the negative effects of salinity stress by regulating antioxidant mechanisms. Their results highlighted the pivotal roles of SNP on salinity tolerance in soybean, including cell wall repair, sodium ion sequestration in the vacuole, and maintenance of normal chloroplasts without swelling of thylakoids.

Therefore, the aim of this study was to investigate the effects of different concentrations of four plant growth regulators (salicylic acid, gibberellic acid, gamma-aminobutyric acid, and sodium nitroprusside) on the morphological, physiological, and phytochemical characteristics of fennel. Special emphasis was placed on evaluating their impact on essential oil composition and antioxidant compounds. The novelty of this research lies in the comprehensive, comparative analysis of multiple elicitors under identical conditions, providing new insights into the specific roles and mechanisms by which these growth regulators influence the biosynthesis of key secondary metabolites in fennel. This work addresses a gap in the literature concerning the integrated response of fennel to diverse PGRs, particularly in terms of essential oil profile modulation.

Materials and methods

Plant materials and culture condition

Fennel seeds (Foeniculum vulgare) were obtained from Pakan Bazr Co. (Isfahan, Iran). The seeds were moisturized for 12 h before sowing. They were then planted in 4-liter pots filled with a 1:1:1 ratio of sand, manure, and garden soil, at a depth of 1 cm in early May. During the growth period, weeds were removed, and irrigation was performed twice a week.

Experiment site and design

This research was conducted in the research greenhouse at the University of Kurdistan (UOK), located at geographical coordinates 46°51’E and 35°8’N. The greenhouse conditions were as follow: 24/18°C Day/night temperature, a 16/8-hour light/dark photoperiod, 60–70% relative humidity, and photosynthetically active radiation (PAR) ranging from 650 to 1200 mol m^− 2 s ^− 1. The experimental design was completely randomized with eight replications (80 pots).

Treatments

The treatments used in this experiment included SA, GA, GABA and SNP. Each compound was applied used with two different concentrations: SA (1 and 2 mM), GA (0.25 and 0.5 mM), GABA (5 and 10 mM) and SNP (1.25 and 2.5 mM) based on concentrations recommended in previous studies. Methanol and sodium hydroxide (NaOH) were used to dissolve SA and GA, respectively, while water served as the solvent for GABA and SNP. Foliar spraying of the solutions was performed three times during the vegetative stage and twice during the reproductive stage, with each spray volume was set at 250 ml.

Morphological parameters

Sampling was conducted at the full flowering stage (90 days after planting, DAP), corresponding to the peak vegetative and reproductive phases of fennel. Morphological measurements were taken 15 days after the final treatment (i.e., 75 days after planting, or 45 days after the first treatment application). For sampling, five plants per treatment were randomly selected and carefully uprooted to retain intact root systems. The roots were gently washed to remove soil particles. Morphological traits—including petiole length, leaf length/width, plant height, stem diameter, and root volume—were measured immediately after harvesting. The parameters of petiole length, leaf length, leaf width, and plant height were measured with a ruler; fresh and dry weights were measured using a scale; and stem diameter was determined with a caliper. To measure total root volume, the roots were removed from the pot, and the other parts of the plant were separated. The sample was then placed in a graduated cylinder filled with a specific volume of water, and the difference between the initial volume of water and the volume of water displaced by the roots was calculated as root volume.

Physiological parameters

Chlorophyll a, b, total and carotenoid

The method developed by Lichtenthaler and Buschmann (2001)³² was utilized to measure the amounts of chlorophyll and carotenoids. According to this procedure, 0.1 g of the pre-powdered sample was frozen using liquid nitrogen and then ground completely in a Chinese mortar containing 10 ml of 80% acetone and 0.01 g of magnesium oxide. The resulting solution was transferred to a 15 ml Falcon tube and centrifuged at 3000 rpm for 10 min. The supernatant was then collected, and its absorbance was measured at 663, 645, and 470 nm using a UV-2100 spectrophotometer (SUV New Jersey S2100 model). The amounts of chlorophyll a, chlorophyll b, total chlorophyll, and carotenoid were calculated using the following formulas and expressed in mg/g of fresh weight:

Total phenol

The total phenol content of the sample extract was measured using the Folin Ciocalteu³³ method. According to this procedure, 0.5 g of the frozen sample was mixed with 12 ml of acetone, water, and acetic acid. After centrifugation for 15 min at 3000 rpm, 0.5 ml of the supernatant was removed. One milliliter of Folin-Ciocâlteu reagent (FCR) was added to the samples, and after 6 min, 10 ml of 7.5% sodium carbonate was added to each sample. The total volume of the samples was then adjusted to 25 ml with distilled water. After allowing the samples and standards to stand at room temperature for 2 h, their optical absorption was measured using a spectrophotometer (UV-S2100) at a wavelength of 750 nm. Concurrently, standards of gallic acid with concentrations of 50, 100, 250, and 500 ppm were prepared, and the entire testing process was conducted based on the standard curve (R2 = 0.99) in terms of milligrams of gallic acid per 100 g of fresh weight and results were calculated as mg GAE/g DW.

Flavonoids

Total flavonoid content was measured using aluminum chloride colorimetry, following the method of Toor and Savage (2005)³⁴. In this method, distilled water was added to 500 µl of sample extract prepared with acidic methanol to achieve a final volume of 5 ml. Next, 0.3 ml of 5% NaNO₂ was added to the solution, and after five minutes, 0.6 ml of 10% AlCl₃ was incorporated. Subsequently, 2 ml of 1 M NaOH and 2 ml of distilled water were added, and the absorption intensity was measured at 510 nm using a spectrophotometer (UV-S2100). The concentration of the samples was determined using the quercetin standard curve (0–500 µg/mL calibration curve, R2 = 0.98). Results were expressed as milligrams of quercetin equivalents (QE) per gram dry weight (mg QE/g DW).

DPPH

To measure the antioxidant capacity, the method described by Brand-Williams et al.³⁵ was utilized. In this procedure, 0.2 g of the powdered sample was dissolved in 10 ml of a buffer solution (acetone and water in a 70:30 ratio) and incubated in a bain-marie at 45 °C for two hours. Following this, the samples were centrifuged for 10 min at 5000 rpm. A volume of 0.1 ml of the supernatant was then mixed with 4 ml of DPPH solution (concentration of 40 × 10^{− 6} M) and allowed to sit in the dark for 30 min. Finally, the absorbance of the samples was measured at a wavelength of 515 nm using a UV-S2100 spectrophotometer, and the results were calculated using the LC50 formula.

Phytochemical parameters

Essential oil extraction

For essential oil extraction, three independent biological replicates per treatment were conducted, with the resulting essential oils pooled together. Each replicate consisted of pooled leaf material from five randomly selected plants to ensure representative sampling. After drying the leaf material, the leaves from each replicate were ground into powder using a grinder (IKA A11, Germany). Approximately 30–40 g of dried powder from each replicate was subjected to hydrodistillation for 3 h using a Clevenger apparatus with 300–400 mL of distilled water. The extracted essential oils were collected in amber vials, stored in the dark at 4 °C, and subsequently analyzed via GC-MS.

GC-MS analysis

GC/MS analysis was performed to determine and quantify the constituents of essential oil using an Agilent 70990B gas chromatograph connected to a 5977 A mass spectrometer with an HP-5MS capillary column (5% Phenyl-Methylpolysiloxane, 30 m in length, 0.25 mm inner diameter, and 0.25 μm film thickness). The temperature was programmed to increase from 60 °C to 280 °C at a rate of 4 °C per minute. Helium was used as the carrier gas with a flow rate of 1 mm/min. The ionization energy was set at 70 electron volts, while the injection and detector temperatures were established at 240 °C and 260 °C, respectively. The injection was performed in split mode at a ratio of 1:24, and mass spectra were obtained in the range of 40–500 m/z. A mixture of aliphatic hydrocarbons (C8-C40, Sigma-Aldrich, USA) was injected according to the temperature schedule. MSD ChemStation software, the NIST mass spectral search program, and internal programs were used to calculate the relative inhibition index of essential oil components. Some of the main components were identified alongside the injection with valid standards (Sigma-Aldrich, USA). Essential oil samples were diluted in a ratio of 1:50 in hexane and the injected volume was 1 µl.

Statistical analyses

Data were analyzed using SPSS software. Means were compared using Duncan’s multiple range test at the 5% probability level. The Shapiro-Wilk test (p > 0.05) confirmed normal distribution of residuals for all datasets. Additionaly Levene’s test (p > 0.05) validated homogeneity across treatments. Graphs were created using Excel 2013 software. Statistical analysis of all morpho-physiological and phytochemical data was conducted using SPSS 16. The data were analyzed using ANOVA for completely random design (CRD) with treatments as fixed effects and replicates as random effect. Mean quantities were compared by the Duncan test at a 5% significance level. Pearson correlation coefficient was calculated for all parameters. All figures and tables are provided in the Word and Excel 2013 programs.

Results

The variance analysis results indicated that all morphological and physiological parameters were significant at the 0.05 level, but in phytochemical characteristics, only 41 of the 150 identified metabolites had significant differences at the 0.05 level among different treatments.

Morphological and agronomic traits

Based on the results presented in Table 1, all treatments resulted in significant changes in morphological characteristics compared to the control group. Generally, the GA0.5 treatment had the most pronounced effect on most traits. The highest number of leaves was observed in the GA0.5 treatment (61.33 ± 2.88), followed by SNP2.5 (48 ± 3.46) and SA2 (54.33 ± 3.51). The control treatment had the lowest number of leaves (31.33 ± 2.51), with significant differences were observed between these treatments. Leaf length was highest in the GA0.5 treatment (27.48 ± 1.27 cm), followed by GABA10 (28.18 ± 1.57 cm), and SNP2.5 (28.04 ± 1.92 cm). The control treatment exhibited the shortest leaf length (15.38 ± 1.36 cm). The leaf width was also highest in the GA0.5 treatment (18.29 ± 1.94 cm), while SNP2.5 (15.72 ± 1.20 cm) and GABA10 (15.54 ± 1.26 cm) showed significant increases. The control treatment had the smallest leaf width (6.82 ± 1.29 cm).

Table 1.

Mean comparison of morphological parameters of fennel (Foeniculum vulgare Mill) using different levels of treatments SA, gibberellic acid (GA), γ-Amino Butyric acid (GABA), and sodium Nitroprusside (SNP).

Parameters	Control	SA1	SA2	GA0.25	GA0.5	GABA5	GABA10	SNP1.25	SNP2.5
Leaf number	31.33 ± 2.51^d	40.66 ± 5.13^c	54.33 ± 3.51^a	38 ± 1.0^c	61.33 ± 2.88^a	42.33 ± 3.78^b	47.66 ± 1.52^b	61.33 ± 7.40^a	48 ± 3.46^b
Leaf length (cm)	15.38 ± 1.36^c	25.46 ± 1.78^ab	25.98 ± 2.31^ab	23.03 ± 0.71^b	27.48 ± 1.27^a	21.20 ± 0.78^b	28.18 ± 1.57^a	23.7 ± 1.06^b	28.04 ± 1.92^a
Leaf width (cm)	6.82 ± 1.29^d	12.92 ± 1.04^b	13.34 ± 1.29^b	13.08 ± 1.37^b	18.29 ± 1.94^a	9.61 ± 1.19^c	15.54 ± 1.26^a	9.66 ± 1.08^c	15.72 ± 1.2^a
Petiole length (cm)	5.41 ± 0.93^d	7.86 ± 0.88^a	7.07 ± 1.35^bc	5.65 ± 0.53^b	7.99 ± 1.58^a	7.39 ± 0.78^b	6.09 ± 0.17^c	6.47 ± 0.59^bc	7.87 ± 0.93^a
Root volume (cm³)	3.31 ± 0.30^d	6.24 ± 0.77^b	6.29 ± 0.35^b	3.53 ± 0.43^d	7.56 ± 0.62^a	5.33 ± 0.68^c	7.69 ± 0.69^a	5.57 ± 0.52^c	7.46 ± 0.84^a
Plant height (cm)	67.37 ± 7.04^cd	74.03 ± 7.73^c	81.85 ± 7.62^b	91.54 ± 1.80^a	97.62 ± 8.82^a	84.16 ± 2.01^b	72.51 ± 4.49^c	59.48 ± 4.51^d	91.93 ± 2.75^a
Stem diameter (cm)	4.07 ± 0.60^d	7.14 ± 0.40^b	7.97 ± 0.18^b	5.99 ± 0.20^c	6.53 ± 0.56^bc	5.37 ± 0.56^c	6.70 ± 0.37^bc	5.35 ± 0.22^c	8.71 ± 0.72^a
Stem fresh weight (g)	17.51 ± 2.33^c	30.79 ± 2.50^b	35.19 ± 2.91^ab	35.06 ± 3.56^ab	45.66 ± 4.76^a	30.90 ± 4.66^b	27.98 ± 3.86^b	30.30 ± 2.86^b	45.0 ± 3.47^a
Leaf fresh weight (g)	10.76 ± 1.32^c	19.20 ± 2.77^b	23.77 ± 2.97^ab	18.69 ± 2.43^b	25.33 ± 3.05^a	18.37 ± 1.20^b	28.58 ± 2.97^a	20.38 ± 2.49^b	31.94 ± 2.93^a
Root fresh weight (g)	6.28 ± 0.14^c	10.12 ± 0.68^a	10.12 ± 1.33^a	6.66 ± 0.69^c	11.36 ± 0.59^a	6.39 ± 0.77^c	8.85 ± 1.17^b	7.19 ± 0.68^bc	9.21 ± 1.33^b
Stem dry weight (g)	2.76 ± 0.29^c	5.21 ± 0.36^b	6.04 ± 0.42^ab	5.7 ± 0.54^ab	7.01 ± 0.75^a	4.47 ± 0.67^bc	4.05 ± 0.55^bc	4.38 ± 0.51^bc	6.51 ± 0.61^a
Leaf dry weight (g)	1.44 ± 0.15^c	2.68 ± 0.37^b	3.32 ± 0.39^a	2.86 ± 0.72^b	3.28 ± 0.51^a	2.49 ± 0.20^b	3.76 ± 0.33^a	2.80 ± 0.30^b	4.30 ± 0.42^a
Root dry weight (g)	1.16 ± 0.03^c	2.01 ± 0.2^a	2.02 ± 0.33^a	1.27 ± 0.08^b	2.13 ± 0.25^a	1.22 ± 0.37^b	1.75 ± 0.39^a	1.40 ± 0.32^b	1.85 ± 0.17^a
Umbell number	11.33 ± 0.57^d	17.66 ± 0.57^bc	30.66 ± 2.51^a	10.33 ± 1.73^d	14 ± 2.0^c	12.66 ± 1.15^cd	14.33 ± 0.57^c	23.66 ± 2.08^b	33 ± 4.72^a

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Different letters in each row indicate significances by DMRT tests at p < 0.05. Each abbreviation in the columns refers to the following treatments: SA1, 1 mM salicylic acid; SA2, 2 mM salicylic acid; GA0.25, 0.25 mM gibberellic acid; GABA5, 5 mM γ-Amino butyric acid; GABA5, 10 mM γ-Amino butyric acid; SNP1.25, 1.25 mM sodium nitroprusside (SNP); SNP2.5, 2.5 mM sodium nitroprusside (SNP).

For petiole length, the highest values were recorded in the SA1 (7.86 ± 0.88 cm) and GA0.5 (7.99 ± 1.58 cm) treatments. The control treatment exhibited the shortest petiole length (5.41 cm). Root volume was highest in the GA0.5 treatment (7.56 ± 0.62 cm³), with significant increases were also observed in the SNP2.5 (7.46 ± 0.84 cm³) and GABA10 (7.69 ± 0.69 cm³) treatments. The control treatment had the lowest root volume (3.31 ± 0.30 cm³). The highest plant height was recorded in the GA0.5 (97.62 ± 8.82 cm) and SNP2.5 (91.93 ± 2.75 cm) treatments, while the control treatment had the shortest plant height (67.37 ± 7.04 cm). The highest stem diameter was found in the SNP2.5 treatment (8.71 ± 0.72 cm), followed by GA0.5 (6.53 ± 0.56 cm). The control treatment had the smallest stem diameter (4.07 ± 0.60 cm).

In terms of fresh and dry weights, the GA0.5 treatment showed the highest stem fresh weight (45.66 ± 4.76 g), while the SNP2.5 treatment had the highest leaf fresh weight (31.94 ± 2.93 g) and root fresh weight (9.21 ± 1.33 g). For dry weight, the GA0.5 treatment showed the highest stem dry weight (7.01 ± 0.75 g), and the SNP2.5 treatment showed the highest leaf dry weight (4.30 ± 0.42 g) and root dry weight (1.85 ± 0.17 g). For umbrella number, the SNP2.5 treatment had the highest count (33 ± 4.72), followed by SA2 (30.66 ± 2.51) and GA0.5 (27.48 ± 1.27). The control treatment had the lowest number of umbrellas (11.33 ± 0.57).

These results indicate that different treatments positively impacted the morphological traits of fennel. The GA0.5, SNP2.5, and GABA10 treatments exhibited the best growth, while the control treatment exhibited the lowest values for most traits. These findings emphasize the importance of using plant growth regulators to enhance the growth and production of fennel.

Physiological parameters

According to Fig. 1, the highest amount of inflorescence flavonoids was observed in the SNP2.5 treatment (191.88 ± 7.33 mg/g DW), which was significantly higher than that of all other treatments. The SA1 (141.6 ± 6.09 mg/g DW) and SA2 (140.73 ± 8.79 mg/g DW treatments also exhibited high flavonoid levels, followed by GA0.25 (128.85 ± 1.95 mg/g DW), GA0.5 (131.09 ± 3.73 mg/g DW), GABA5 (130.23 ± 3.61 mg/g DW), and SNP1.25 (122.65 ± 8.46 mg/g DW), which showed statistically similar results. The control group displayed the lowest flavonoid content (67.72 ± 3.22 mg/g DW), significantly lower than all other treatments.

Similar to inflorescence flavonoids, the highest leaf flavonoid content was recorded in the SNP2.5 treatment (223.92 ± 11.51 mg/g DW), significantly exceeding that of all other treatments. The SA2 treatment (193.26 ± 15.29 mg/g DW) followed closely, and comparable levels were observed in SA1 (183.61 ± 13.31 mg/g DW), GA0.25 (179.31 ± 14.04 mg/g DW), and GABA5 (172.94 ± 3.91 mg/g DW). The control group again showed the lowest leaf flavonoid content (109.70 ± 16.73 mg/g DW) (Fig. 2) (109.70 ± 16.73 mg/g DW) (Fig. 2).

Fig. 2 — Effect of different concentrations of growth regulators on leaf flavonoid content in fennel (*Foeniculum vulgare* Mill). Data were analyzed using Duncan’s Multiple Range Test (DMRT) at p < 0.05. Different letters above bars represent significant differences between treatments. Each abbreviation in the columns refers to the following treatments: SA1, 1 mM salicylic acid; SA2, 2 mM salicylic acid; GA0.25, 0.25 mM gibberellic acid; GA0.5, 0.5 mM gibberellic acid; GABA5, 5 mM γ-aminobutyric acid; GABA10, 10 mM γ-aminobutyric acid; SNP1.25, 1.25 mM sodium nitroprusside; SNP2.5, 2.5 mM sodium nitroprusside. Error bars represent the percentage (%) variation from the mean for each treatment.

Total phenolic content in fennel leaves exhibited significant variation across treatments (Fig. 3). The highest phenolic content was recorded in SA2 treatment (201.12 ± 8.83 mg/g DW), which was significantly higher than all other treatments (P < 0.05). SNP2.5 treatment showed the second highest phenolic content (182.11 ± 13.06 mg/g DW), statistically similar to SA2. An intermediate group comprising SA1 (176.22 ± 1.44 mg/g DW), GA0.25 (164.57 ± 9.73 mg/g DW), GA0.5 (172.5 ± 9.73 mg/g DW), and GABA10 (164.3 ± 4.29 mg/g DW) displayed statistically similar phenolic contents. GABA5 (138.33 ± 10.96 mg/g DW) and GA0.5 (147.03 ± 6.13 mg/g DW) demonstrated moderately lower values. The control treatment exhibited significantly lower phenolic content (111.03 ± 9.82 mg/g DW) compared to all elicitor treatments. These results suggest that elicitor applications, particularly SNP2.5 and SA2, effectively enhanced the accumulation of phenolic compounds in fennel leaves, resulting in nearly a two-fold increase compared to the control treatment.

The DPPH radical scavenging activity varied significantly among treatments in both inflorescences and leaves (Figs. 4 and 5). In inflorescences, the highest antioxidant activities were observed in GABA10 (79.13 ± 0.64%), SA2 (78.03 ± 1.12%), SNP2.5 (76.03 ± 1.78%), and SA1 (74.8 ± 2.77%), which were statistically similar (P < 0.05). Intermediate levels of DPPH radical scavenging activity were recorded in SNP1.25 (64.9 ± 6.10%), GA0.5 (62.83 ± 1.62%), and GABA5 (61.56 ± 2.84%). The control and GA0.25 treatments showed significantly lower antioxidant activities of 48.0 ± 2.49% and 51.73 ± 3.88%, respectively. In leaf tissues, SNP2.5 treatment exhibited the highest DPPH radical scavenging activity (83.73 ± 5.04%), followed by SA2 (75.83 ± 5.06%), with both treatments showing significantly higher values compared to others. GA0.5 (72.3 ± 3.05%) and SNP1.25 (73.8 ± 1.90%) demonstrated moderately high antioxidant activities, while the control treatment showed the lowest DPPH radical scavenging activity (60.2 ± 6.0%). These results indicate that elicitor treatments generally enhanced antioxidant capacity in both tissues, with SNP2.5 and SA2 being particularly effective at stimulating antioxidant activity in both inflorescences and leaves.

Fig. 4 — Effect of different concentrations of growth regulators on inflorescence DPPH in fennel (*Foeniculum vulgare* Mill). Data were analyzed using Duncan’s Multiple Range Test (DMRT) at p < 0.05. Different letters above bars represent significant differences between treatments. Each abbreviation in the columns refers to the following treatments: SA1, 1 mM salicylic acid; SA2, 2 mM salicylic acid; GA0.25, 0.25 mM gibberellic acid; GA0.5, 0.5 mM gibberellic acid; GABA5, 5 mM γ-aminobutyric acid; GABA10, 10 mM γ-aminobutyric acid; SNP1.25, 1.25 mM sodium nitroprusside; SNP2.5, 2.5 mM sodium nitroprusside. Error bars represent the percentage (%) variation from the mean for each treatment.

Fig. 5 — Effect of different concentrations of growth regulators on leaf DPPH in fennel (*Foeniculum vulgare* Mill). Data were analyzed using Duncan’s Multiple Range Test (DMRT) at p < 0.05. Different letters above bars represent significant differences between treatments. Each abbreviation in the columns refers to the following treatments: SA1, 1 mM salicylic acid; SA2, 2 mM salicylic acid; GA0.25, 0.25 mM gibberellic acid; GA0.5, 0.5 mM gibberellic acid; GABA5, 5 mM γ-aminobutyric acid; GABA10, 10 mM γ-aminobutyric acid; SNP1.25, 1.25 mM sodium nitroprusside; SNP2.5, 2.5 mM sodium nitroprusside. Error bars represent the percentage (%) variation from the mean for each treatment.

The application of elicitors significantly influenced chlorophyll content in fennel leaves (Fig. 6). Maximum total chlorophyll content was observed in the SA2 treatment (3.03 ± 0.09 mg/g DW), followed by GA0.25 and GABA10 (both 2.69 ± 0.12 mg/g DW), and SNP2.5 (2.64 ± 0.06 mg/g DW). This pattern was consistent for both chlorophyll a (2.26 ± 0.07, 2.00 ± 0,09, 2.00 ± 0.01, and 1.97 ± 0.04 mg/g DW, respectively) and chlorophyll b (0.77 ± 0.03, 0.68 ± 0.02, 0.68 ± 0.02, and 0.67 ± 0.01 mg/g DW, respectively). Intermediate chlorophyll levels were recorded in the SA1, GA0.5, GABA5, and SNP1.25 treatments, showing statistically similar values ranging from 2.08 ± 0.12 to 2.23 ± 0.18 mg/g DW for total chlorophyll. The control treatment exhibited significantly lower chlorophyll content, with the lowest values for chlorophyll a (1.24 ± 0.02 mg/g DW), chlorophyll b (0.42 ± 0.05 mg/g DW), and total chlorophyll (1.66 ± 0.11 mg/g DW).

The carotenoid content was highest in the SA2 (0.48 ± 0.03 mg/g DW), GA0.25 (0.46 ± 0.02 mg/g DW) and GABA10 (0.46 ± 0.02 mg/g DW) treatments, followed by SA1 (0.43 ± 0.02 mg/g DW), and SNP2.5 (0.43 ± 0.01 mg/g DW). The lowest amount of carotenoid (0.25 ± 0.01 mg/g DW) was observed in the control treatment (Fig. 7).

Fig. 7 — Effect of different levels of four growth regulators on carotenoid. Data were analyzed using Duncan’s Multiple Range Test (DMRT) at p < 0.05. Different letters above bars represent significant differences between treatments. Each abbreviation in the columns refers to the following treatments: SA1, 1 mM salicylic acid; SA2, 2 mM salicylic acid; GA0.25, 0.25 mM gibberellic acid; GABA5, 5 mM γ-Amino butyric acid; GABA5, 10 mM γ-Amino butyric acid; SNP1.25, 1.25 mM sodium nitroprusside (SNP); SNP2.5, 2.5 mM sodium nitroprusside (SNP). Error bars represent the percentage (%) variation from the mean for each treatment.

Correlation, principle and cluster analyses

The correlation analysis revealed significant relationships among the morphological and physiological characteristics of fennel (Fig. 8). Photosynthetic pigments showed exceptionally strong positive correlations (r > 0.99) among chlorophyll a, chlorophyll b, and total chlorophyll content, indicating coordinated pigment synthesis. Antioxidant activities demonstrated strong positive correlations with phenolic compounds, particularly between leaf antioxidant activity (L-DPPH) and leaf total phenol (LTP). Among the morphological parameters, leaf dimensions showed strong correlations, with leaf length (LL) and leaf width (LW) exhibiting a high positive correlation of 0.89. Plant height (PH) displayed moderate to strong positive correlations with stem diameter and biomass parameters. Fresh and dry biomass parameters were strongly correlated across all plant organs (stems, leaves, and roots), suggesting balanced growth responses to the treatments. Leaf number (LN) emerged as an important indicator of overall plant development, showing positive correlations with various growth parameters. These correlations indicate that the application of growth regulators induced coordinated changes across multiple physiological and morphological traits in fennel.

Principal Component Analysis (PCA) was performed to explore the multivariate relationships among morphological and physiological parameters of fennel in response to different plant growth regulator treatments (Fig. 9). The first two principal components (PC1 and PC2) explained a cumulative variance of approximately 78% of the total variation, with PC1 accounting for 59% and PC2 accounting for 19%.

Fig. 9 — Principal Component Analysis (PCA) of studied morphological and physiological characteristics in fennel (*Foeniculum vulgare* Mill). Each abbreviation in the columns refers to the following treatments: Chl a, chlorophyll a; Chl b, chlorophyll b; TChl, total chlorophyll; L-DPPH, leaf antioxidant activity; I-DPPH, inflorescence antioxidant activity; LTP, leaf total phenol; ITP, inflorescence total phenol; LTF, leaf total flavonoid; ITF, inflorescence total flavonoid; LN, leaf number; LL, leaf length, LW, leaf width; PL, petiole length; RV, root volume; PH, plant height; SD, stem diameter; SFW, stem fresh weight; LFW, leaf fresh weight; RFW, root fresh weight; SDW, stem dry weight; LDW, leaf dry weight; RDW, root dry weight.

PC1 was primarily characterized by positive loadings from most morphological traits (including leaf dimensions, plant height, stem diameter, and biomass parameters) and physiological traits (including chlorophyll content, flavonoid content, and antioxidant activity). This suggests a strong interrelationship between growth and physiological responses to the applied treatments. PC2 was mainly defined by antioxidant parameters (L-DPPH and I-DPPH) and phenol content, indicating that these parameters varied somewhat independently from the general growth response.

The PCA biplot revealed distinct clustering of treatments, with the control group positioned in the negative quadrant of PC1, clearly separated from all PGR treatments. This confirms the overall positive effect of growth regulators on fennel’s morpho-physiological traits. The SNP2.5 and GA0.5 treatments were positioned furthest along the positive axis of PC1, confirming their superior effects on overall plant growth and development. SA2 was positioned strongly along the PC2 axis, reflecting its pronounced effect on antioxidant capacity and phenolic content.

Interestingly, GABA treatments (especially GABA10) showed an intermediate position between the growth-promoting effects of GA and SNP and the antioxidant-enhancing effects of SA, suggesting a balanced influence on both growth and physiological parameters. The GA0.25 and SNP1.25 treatments were positioned more centrally in the biplot, indicating moderate effects on both growth and physiological parameters compared to their higher concentration counterparts.

Hierarchical cluster analysis of the metabolite profile (Fig. 10) revealed distinct chemometric patterns among treatments. Two major clusters of metabolites were identified: the first cluster was dominated by highly abundant compounds including cis-anethole and limonene, which represented the major components of fennel essential oil across all treatments. The second cluster comprised moderately abundant compounds including apiol, camphene-hydrate, estragole, and fenchyl-acetate.

Treatment-specific clustering demonstrated that SA treatments (1 mM and 2 mM) and the control condition generated similar metabolic profiles, despite significant differences in compound abundances. These treatments were characterized by elevated levels of beta-cubebene, beta-trans-ocimene, bornyl-valerate, and myristicin. The SNP treatments (1.25 and 2.5 mM) formed a separate cluster with generally lower compound abundances but similar metabolite proportions. GABA10 treatment induced a distinctive metabolic response, particularly affecting the accumulation of benzyl-alcohol, alpha-ethyl-p-methoxy, gamma-eudesmol, (-)-spathulenol, alpha-eudesmol, and viridiflorol. Similarly, GA0.5 treatment showed unique patterns in anisketone, benzaldehyde, tau-cadinol, and caryophyllene-oxide levels, while GA0.25 specifically influenced eucalyptol and tau-cadinol accumulation.

The clustering pattern suggests treatment-specific regulation of metabolic pathways in fennel. SA treatments primarily enhanced phenylpropanoid pathway metabolites, GA treatments influenced both mono- and sesquiterpene biosynthesis, GABA treatments promoted the accumulation of oxygenated sesquiterpenes and alcoholic derivatives, while SNP treatments had a more moderate effect on the overall metabolite profile despite their pronounced impact on morphological and physiological traits.

These multivariate analyses confirm the differential responses of fennel to various growth regulators and highlight the complex interplay between growth, physiological processes, and metabolite accumulation. The distinct positioning of treatments in both the PCA and cluster analysis supports the conclusion that targeted application of specific growth regulators can modulate particular aspects of fennel’s growth, physiology, and phytochemical profile according to desired agricultural or industrial outcomes.

Phytochemical analysis

Gas chromatography-mass spectrometry (GC-MS) analysis revealed significant variations in the chemical composition of fennel leaf essential oils in response to different elicitor treatments. From these, 41 compounds with significant differences were subjected to hierarchical clustering analysis, and their relative abundances were visualized (Fig. 11).

Fig. 11 — The phytochemical profile of fennel plants (*Foeniculum vulgare* Mill) treated under different treatments. The heatmap displays the relative concentration of various essential oil components (rows) across different treatments (columns), with red indicating higher values and green indicating lower values according to the color scale shown on the right (0–70%). The dendrogram shows hierarchical clustering of both compounds and treatments, revealing patterns in phytochemical responses to the different applied substances. Each abbreviation in the columns refers to the following treatments: SA1, 1 mM salicylic acid; SA2, 2 mM salicylic acid; GA0.25, 0.25 mM gibberellic acid; GA0.5, 0.5 mM gibberellic acid; GABA5, 5 mM γ-Amino butyric acid; GABA10, 10 mM γ-Amino butyric acid; SNP1.25, 1.25 mM sodium nitroprusside (SNP); SNP2.5, 2.5 mM sodium nitroprusside (SNP); Control, untreated plants.

Hierarchical cluster analysis demonstrated clear chemometric patterns among compounds and treatments. Notably, cis-anethole and limonene exhibited the highest abundance across most treatments and were clustered together, indicating similar biosynthetic regulation. A second distinct cluster included apiol, camphene-hydrate, e, and fenchyl-acetate, which showed moderately high abundance but remained distinct from the primary cluster.

Treatment-specific clustering revealed that SA1 (1 mM SA), SA2 (2 mM SA), and control conditions generated similar metabolic profiles, characterized by elevated levels of beta-cubebene (0.89, 0.74, 1.29% respectively) beta-trans-Ocimene (1.16, 0.40, 0.70% respectively), Bornyl-valerate (0.58, 0.32, 0.97% respectively), and Myristicin (1.67, 0.91, 1.05% respectively). SNP treatments (1.25 and 2.5 mM) demonstrated comparable metabolite profiles, albeit with generally lower compound abundances.

GABA10 treatment induced distinct metabolic responses, particularly affecting the accumulation of Benzyl-alcohol, alpha-ethyl-p-methoxy (47.81%), gamma-Eudesmol (2.90%), (-)-Spathulenol (0.40%), alpha-Eudesmol (3.90%), and Viridiflorol (1.64%). Similarly, GA0.5 treatment showed unique patterns in Anisketone (1.92%), Benzaldehyde (5.00%), tau-Cadinol (9.70%), and Caryophyllene-oxide (2.02%) levels, while GA0.25 specifically influenced Eucalyptol (20.28%) and tau-Cadinol (1.72%) accumulation. These treatments formed distinct clusters in the hierarchical analysis, suggesting unique mechanisms of metabolic regulation.

The majority of identified metabolites showed relative abundance values between 0 and 10 (depicted in green in the heatmap), indicating moderate baseline levels across treatments. This pattern suggests a complex regulatory network controlling essential oil biosynthesis in fennel leaves, with specific elicitor treatments capable of modulating distinct aspects of the metabolic network.

Discussion

Various studies conducted by researchers worldwide have demonstrated the additive effect of growth regulators on a range of plant characteristics, from appearance to physiological traits and metabolites^22,36. These growth regulators were applied either individually or in combination. In this study, we compared the effects of four regulators—salicylic acid (SA), gibberellic acid (GA), gamma-aminobutyric acid (GABA), and sodium nitroprusside (SNP)—on the morpho-physiological and phytochemical traits of fennel. SA and GA are naturally occurring plant hormones that support growth and development, whereas GABA, as a non-protein amino acid and physiological regulator, and SNP, with its antioxidant properties, contribute to enhanced growth and stress adaptation. The following sections explore the effects of these regulators on various plant traits in greater detail.

Morphological, agronomic, and yield-related responses

Overall, the use of these growth regulators enhanced the growth and development of fennel compared to the control, although their effects varied depending on the type and concentration of the treatment. Among the treatments, GA0.5 and SNP2.5 showed the most pronounced positive effects on the plant’s morphological and growth traits, likely due to their underlying physiological mechanisms. GA₃ (present in GA0.5) promotes growth by stimulating cell division and elongation, enhancing photosynthetic capacity, and regulating hormone pathways associated with reproductive processes. Its application results in increased plant height, extended flowering periods, and greater flower production, thereby improving overall plant performance³⁷. Moreover, GA₃ has been shown to induce early flowering by reducing the concentration of abscisic acid (ABA) in shoots while simultaneously regulating floral stimuli and increasing flower number³⁸. Additionally, GA₃ enhances photosynthetic efficiency by increasing leaf number and surface area, thereby improving resource allocation to reproductive organs³⁹.

On the other hand, SNP at a concentration of 2.5 µM, as a nitric oxide (NO) donor, plays a crucial role in modulating physiological processes that support plant growth. It promotes cell division and differentiation—particularly in roots and shoots—and facilitates cell elongation, contributing to increased biomass accumulation. SNP also elevates chlorophyll content and photosynthetic rate, leading to greater production of organic matter and improvements in both fresh and dry weight of the plant. Moreover, NO interacts synergistically with endogenous hormones such as auxins and cytokinins, further accelerating vegetative development, especially under in vitro conditions^40–43.

After GA0.5 and SNP2.5, GABA10 and SA2 also promoted growth, though to a lesser extent, while GA0.25 and SNP1.25 showed the weakest effects, likely due to suboptimal concentrations insufficient to trigger strong physiological responses. Similar findings have been reported in other studies examining the effects of GA₃ and SNP on plant growth and development. Chauhan et al.⁴⁴ investigated the effects of exogenous SNP and GA₃ on Dahlia and reported that GA₃ at 200 mg L⁻¹ produced the highest plant height, branch number, flower count, stem length, and tuber number. Stem diameter and tuber yield were maximized at 100 and 150 ppm GA₃, respectively. Although SNP also enhanced growth relative to the control, GA₃ was more effective in improving a wider range of traits, likely due to its stronger influence on cell division and elongation.

Supporting the role of SNP in stress mitigation, Hassanein et al.⁴⁵ observed significant improvements in the yield characteristics of lupine plants treated with SNP under salt or nickel stress, suggesting that NO plays a protective and growth-promoting role under abiotic stress conditions. Similarly, Zhang et al.⁴⁶ reported enhanced growth, pod yield, and quality in peanut following foliar application of SNP. In Aronia melanocarpa cultured in vitro, SNP treatment resulted in significant improvements in growth parameters⁴³, reinforcing its general effectiveness across species.

As for GA₃, Pazuki et al.⁴⁷ demonstrated its efficacy in Stevia, where it produced the highest biomass, number of leaves, fresh-to-dry weight ratio, and leaf area compared to hormone-free controls, again confirming GA₃’s role in promoting vegetative growth through enhanced cell activity and resource allocation.

The growth-promoting effects of GABA and SA have also been documented. Ullah et al.⁴⁸ reported that exogenous GABA effectively mitigated salt-induced growth reductions in mungbean. These findings are consistent with earlier studies^49–51, which support GABA’s function in stress resistance and metabolic regulation. Bayanloo et al.⁵² found that γ-aminobutyric acid significantly increased plant height, stem diameter, and leaf number in treated plants compared to controls. Moreover, foliar application of salicylic acid (SA) positively affected plant height and stem diameter^53,54, suggesting a role for SA in modulating morphological traits, possibly through its interaction with endogenous hormones and defense signaling pathways.

Physiological responses

Regarding physiological characteristics, treated plants showed distinct responses compared to the control. The highest levels of physiological compounds were generally observed in the SNP2.5 and SA2 treatments, followed by SA1 and GABA10. Both GA concentrations also enhanced physiological compounds, though to a lesser extent.

SNP enhances plant physiological traits through several coordinated mechanisms. It boosts photosynthesis by increasing chlorophyll content, net photosynthetic rate, stomatal conductance, and CO₂ assimilation^46,55. SNP also reduces oxidative damage by lowering H₂O₂ levels and enhancing antioxidant enzyme activity⁵⁶. Furthermore, it promotes ionic balance by increasing K⁺ and Ca²⁺ uptake and encourages the accumulation of osmotic regulators, such as proline, while activating flavonoid biosynthesis via phenylalanine ammonia-lyase (PAL), which supports plant growth and reduces oxidative stress^57,58.

Ragaey et al.⁵⁹ suggested that the positive effects of exogenous SNP treatment on wheat salinity tolerance could be attributed to enhanced leaf water content, photosynthetic pigment levels, and the accumulation of osmoprotectant compounds and an antioxidative defense system. The NO molecule, which is produced by SNP, plays a crucial role as a signaling molecule that permeates cell membranes and mediates key physiological responses in plants⁶⁰. Sheikhalipour et al.⁶¹ found that high concentrations of SNP significantly enhanced plant growth, photosynthetic traits, and alleviated oxidative stress under saline conditions. Additionally, SNP improved the salinity tolerance of sage by increasing relative water content, proline, total carbohydrates, phenolic and flavonoid content, and antioxidant enzyme activities.

Simaei et al.⁶² demonstrated that treatment with NaCl, SA, SNP, or a combination of SA and SNP significantly increased flavonoid content in soybean leaves, which in turn enhanced salt stress resistance in seedlings. Similarly, SNP treatments have been shown to boost the phenolic content of plants^59,63,64. However, in contrast to our findings, Hassanein et al.⁴⁵ reported that exogenous SNP treatment resulted in a significant reduction in total phenol and flavonoid contents, both under normal and stress conditions (e.g., salinity or Ni stress).

SA, a phenolic compound and important plant hormone, enhances physiological performance by regulating various metabolic and physiological processes, including photosynthesis, osmotic adjustment, antioxidant enzyme activity, and membrane stability, as seen in Rosa hybrida and cornmint⁶⁵. SA stimulates the activity of enzymes like ascorbate peroxidase (APX) and PAL, which are involved in reducing reactive oxygen species and maintaining cellular health⁶⁶. Additionally, SA promotes the biosynthesis of phenolic compounds and flavonoids, increasing levels of secondary metabolites such as anthocyanins, quercetin, and other protective compounds⁶⁷. It also regulates gene expression, particularly for PAL, with effects that depend on tissue type (e.g., root or leaf) and application method (e.g., seed soaking or hydroponics). SA contributes to improved photosynthetic rates, ionic homeostasis, and nutrient uptake, enhancing plant growth and stress tolerance, particularly under salinity stress⁶⁸. Furthermore, in cell and callus cultures, SA promotes the accumulation of secondary metabolites like steviol glycosides and andrographolide⁶⁹. Since its discovery in 1979 as a systemic acquired resistance inducer against tobacco mosaic virus (TMV), SA has been recognized as a regulator of plant defense, growth, abiotic stress tolerance, and soil microbiome interactions⁷⁰.

GABA, a key signaling molecule, plays a crucial role in plant growth and development by interacting with hormones (IAA, ABA, ethylene, JA), polyamines, and NO, regulating their biosynthesis and signaling. It also modulates reactive oxygen species (ROS), enhancing stress tolerance and optimizing physiological and metabolic processes, thereby improving growth under conditions such as salinity or drought⁷¹.

Exogenous GABA has been shown to improve chlorophyll concentration in salinity-stressed plants, suggesting that GABA mitigates the damaging effects of salt stress on photosynthetic pigments by reducing H₂O₂ production and improving plant growth. GABA treatment also resulted in significant increases in carotenoid levels compared to untreated controls⁴⁸. Similarly, GABA enhanced chlorophyll synthesis in maize and lettuce under salinity stress^50,72,73. Ullah et al.⁴⁸ found that the application of exogenous GABA further increased soluble sugars, proline, soluble proteins, and total phenolic content, suggesting that GABA protected mungbean plants from salt stress and enhanced their tolerance to salinity.

Finally, both SA and GABA were effective in protecting against As-induced damage by enhancing the antioxidant defense system. This protection was achieved through the activation of superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) activities, along with an increase in osmolytes⁷⁴. Bayanloo et al.⁵² observed that the highest catalase activity occurred in the 2 mM SA treatment, while the highest peroxidase activity was observed in the GABA and 2 mM SA treatments.

Correlation analysis highlights the coordinated physiological and morphological responses of fennel to growth regulator treatments. In particular, increases in leaf area were strongly associated with higher chlorophyll a, chlorophyll b, and total chlorophyll levels, indicating that larger leaves support enhanced chlorophyll biosynthesis. This expanded leaf surface improves light capture and photosynthesis, contributing to greater energy efficiency and overall plant vigor⁷⁵.

Additionally, the positive correlations between antioxidant activity and phenolic compounds, such as leaf antioxidant activity (L-DPPH) and LTP, highlight the interconnectedness between morphological and physiological traits. The accumulation of phenolic compounds, which play a critical role in the plant’s antioxidant defense system, is closely tied to the observed increases in leaf area. A larger leaf area likely provides a greater capacity for synthesizing and storing these compounds, which helps neutralize reactive oxygen species and enhances the plant’s stress resilience^76,77. This coordinated increase in both leaf area and antioxidant activity reflects an adaptive metabolic shift aimed at combating oxidative stress, a common response in fennel and other medicinal plants⁶⁸.

Moreover, morphological parameters such as plant height, leaf number, and biomass exhibit strong correlations, indicating a balanced and synchronized growth pattern driven by the growth regulator treatments. The leaf number, which is a key indicator of vegetative growth, shows robust relationships with both biomass and physiological parameters, further emphasizing its role in overall plant development. These findings align with previous research suggesting that growth regulators stimulate coordinated changes in both morphological and physiological traits, optimizing nutrient and hormonal balance.

Finally, the strong correlations among fresh and dry biomass parameters across different plant organs suggest efficient resource allocation within the plant. This indicates that the treatments effectively support systemic growth, as they promote both the enhancement of photosynthetic capacity and the efficient use of resources, ultimately leading to greater biomass production⁷⁵.

Phytochemical responses

Of the 41 metabolites studied, the numbers detected in each treatment group were as follows: 17 in the control, 12 in SA1, 15 in SA2, 20 in GA0.25, 24 in GA0.5, 26 in GABA5, 24 in GABA10, 17 in SNP1.25, and 22 in SNP2.5. The total metabolites for these treatments were 98.30, 99.42, 98.75, 116.25, 96.65, 75.14, 84.55, 56.26, and 75.19. Notably, plants treated with GA0.25, SA1, and SA2 exhibited the highest total metabolite content, despite SA1 and SA2 having fewest metabolites. Conversely, GA0.5, GABA5, and GABA10 had the highest number of metabolites, but GABA5, along with two concentrations of SNP, had the lowest total metabolite content. In contrast to morpho-physiological parameters, phytochemical parameters were significantly lower in SNP treatments.

Among the 41 metabolites, 6 were dominant, accounting for over 70% of the total metabolite value. These dominant metabolites included apiol, Camphene-hydrate, cis-anethole, estragole, fenchyl-acetate, and limonene. The highest amounts were found for cis-anethole (ranging from 40 to 75) and limonene (ranging from 6.5 to 19).

The results show that plant growth regulators significantly affected fennel’s metabolite profile. Notably, SA (both SA1 and SA2) promoted high accumulation of key phenylpropanoid compounds—cis-anethole, estragole, and fenchyl acetate—despite a relatively low total number of metabolites, suggesting that SA directs metabolism toward a few dominant, functionally important compounds. These findings are in line with those of Abbasi et al.⁷⁸, who reported enhanced phytochemical production in Ajuga integrifolia in response to SA, and Mohtashami et al.⁷⁹ and Ghanbari moheb seraj⁸⁰ who found increased essential oil content in fennel treated with SA. Additionally, Faraji et al.⁸¹ observed a significant increase in thymol content in summer savory with 2 mM SA, while Sarrou et al.⁸² showed that SA altered essential oil composition, increasing compounds such as limonene and linalool.

On the other hand, gibberellic acid (GA) at 0.25 mM increased the overall metabolite content, particularly monoterpenes like limonene and camphene hydrate, indicating a role in terpene biosynthesis enhancement. At the higher concentration (GA0.5), a wider variety of metabolites were detected, including sesquiterpenes like τ-cadinol and caryophyllene oxide, although the total metabolite content was comparatively lower. This may indicate a competition between metabolic pathways or a dilution of metabolic flux, where the increased diversity of metabolites reduces the concentration of individual compounds. Similar to our findings, Sarrou et al.⁸² reported that GA influenced essential oil composition, and Abbasi et al.⁷⁸ noted a downregulation of phytochemical biosynthesis in Ajuga cultures treated with GA.

GABA, particularly at 10 mM, increased oxygenated sesquiterpenes and alcoholic derivatives such as α-eudesmol, globulol, and γ-eudesmol, but had minimal effect on the major phenylpropanoids. This pattern implies that GABA may increase metabolite diversity without significantly enhancing the accumulation of key bioactive compounds. Salvatore et al.⁸³ similarly showed that GABA promotes metabolite diversification in L. theobromae, while Feizi et al.⁸⁴ and Garoosi et al.³⁶ emphasized GABA’s role in stress tolerance and secondary metabolism modulation.

In contrast, SNP (especially SNP2.5) improved morpho-physiological traits but had little effect on the phytochemical profile. Low levels of dominant compounds suggest that nitric oxide mainly promotes primary metabolism and growth, though minor increases in β-terpinyl acetate and limonene indicate a subtle role in regulating specific aroma-related terpenes, consistent with Sheikhalipour et al.⁶¹.

Overall, the observed patterns suggest a treatment-specific effect on distinct classes of compounds: SA predominantly boosted phenylpropanoid pathways, GA enhanced both mono- and sesquiterpenes, GABA promoted the accumulation of oxygenated sesquiterpenes and alcoholic derivatives, and SNP had minor but selective effects on terpenes. These findings highlight the potential of PGRs to steer the phytochemical biosynthesis in fennel, thereby enhancing its medicinal and industrial value.

Different growth regulators had varying effects on fennel’s growth, physiological traits, and phytochemical properties. GA0.5 mainly enhanced morphological growth (height, leaf number) but had a limited impact on secondary metabolites, indicating a trade-off between rapid growth and metabolite accumulation. In contrast, SA treatments (SA1 and SA2) improved both physiological traits, such as antioxidant activity, and the production of key secondary metabolites like anethole and estragole. SNP also enhanced physiological traits but had less effect on metabolites. These findings suggest that regulator choice can balance growth and metabolite production depending on the desired goal.

Conclusion

This study evaluated the effects of two concentrations of SA, GA, GABA, and SNP on fennel’s morphological, physiological, and phytochemical traits. GA0.5 and SNP2.5 most effectively enhanced growth and morphological traits, while SNP2.5 and SA2 promoted the highest physiological compound production. SA and GA0.25 notably increased phytochemical compounds, including essential oils, improving fennel’s nutritional and medicinal quality. GABA10 also had positive, though less pronounced, effects on all traits. Overall, the control showed the lowest values. These findings highlight the potential of growth regulators, especially SNP and SA, to optimize fennel cultivation and metabolite production, warranting further investigation into their underlying molecular mechanisms.

Author contributions

Kamal Mohammadi 25% Performed research, Analyzed data, conducted experimentsMozhgan Mohammadi 25% Performed research, Analyzed data, conducted experimentsYavar Vafaee 20% Designed study, Analyzed data, SupervisorRahele Ghanbari Moheb Seraj 15% Wrote the paper, Analyzed dataJalal Khorshidi 15% Advice research.

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

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[CR27] 27.Rasheed, R., Ashraf, M. A., Ali, S., Iqbal, M. & Zafar, S. Plant metabolism adjustment in exogenously applied NO under stress. In Nitric Oxide in Plant Biology 261–296 (Academic Press, 2022).

[CR28] 28.Amooaghaie, R. & Roohollahi, S. Effect of sodium nitroprusside on responses of Melissa officinalis to bicarbonate exposure and direct Fe deficiency stress. Photosynthetica55, 153–163 (2017). [Google Scholar]

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[CR31] 31.Jabeen, Z. et al. Sodium nitroprusside application improves morphological and physiological attributes of soybean (Glycine max L.) under salinity stress. PLoS One. 16, e0248207 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar] [Retracted]

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[CR38] 38.Phengphachanh, B., Naphrom, D., Bundithya, W. & Potapohn, N. Effects of day-length and gibberellic acid (GA3) on flowering and endogenous hormone levels in Rhynchostylis gigantea. (Lindl) Ridl J. Agric. Sci.4, 217–222 (2012). [Google Scholar]

[CR39] 39.Sharifuzzaman, S. M., Ara, K. A., Rahman, M. H., Kabir, K. & Talukdar, M. B. Effect of GA3, CCC and MH on vegetative growth, flower yield and quality of chrysanthemum. Int. J. Expt Agric.2, 17–20 (2011). [Google Scholar]

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PERMALINK

External application of growth regulators modulates morpho-physiological traits and biochemical profiles of fennel

Kamal Mohammadi

Mozhgan Mohammadi

Yavar Vafaee

Rahele Ghanbari Moheb Seraj

Jalal Khorshidi

Abstract

Introduction

Materials and methods

Plant materials and culture condition

Experiment site and design

Treatments

Morphological parameters

Physiological parameters

Chlorophyll a, b, total and carotenoid

Total phenol

Flavonoids

DPPH

Phytochemical parameters

Essential oil extraction

GC-MS analysis

Statistical analyses

Results

Morphological and agronomic traits

Table 1.

Physiological parameters

Fig. 1.

Fig. 2.

Fig. 3.

Fig. 4.

Fig. 5.

Fig. 6.

Fig. 7.

Correlation, principle and cluster analyses

Fig. 8.

Fig. 9.

Fig. 10.

Phytochemical analysis

Fig. 11.

Discussion

Morphological, agronomic, and yield-related responses

Physiological responses

Phytochemical responses

Conclusion

Author contributions

Data availability

Declarations

Competing interests

Footnotes

References

Associated Data

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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