Reaction of pomegranate trees to sustained deficit irrigation in terms of morphophysiological and biochemical traits

Abstract

Water stress is one of the most important challenges affecting crops worldwide, particularly in arid and semi-arid regions, leading to diverse plants responses. While previous studies have examined drought responses in various crops, the mechanisms underlying vegetative responses in different pomegranate cultivars remain underexplored, particularly under varying water stress. This research investigates the effects of water scarcity on the pomegranate cultivars ‘Shishecap’ and ‘Malas-Yazdi,’ focusing on their morphophysiological and biochemical reactions to water stress conditions. Irrigation treatments included 50% of the water requirement (severe stress), 75% of the water requirement (mild stress), and 100% of the water requirement (Control). This study assessed the impact of water deficit stress on morphophysiological and biochemical characteristics, including leaf area (LA), chlorophyll (a, b, and total), carotenoid content, electrolyte leakage (EL), relative water content (RWC), proline content, soluble carbohydrates content, and the activities of catalase (CAT), superoxide dismutase (SOD), and peroxidase (POD). The results showed that EL, proline, and soluble carbohydrates content increased, whereas chlorophyll (a, b, and total), carotenoid content, RWC and LA decreased with reduced irrigation levels in both cultivars across both years. Additionally, the activities of CAT, POD, and SOD increased when the water restriction level increased. These findings suggest that the accumulation of biochemical compounds such as proline, the increased activity of antioxidant enzymes, and the reduction of LA act as adaptive mechanisms to water stress in pomegranate trees. These findings could serve as a basis for future research aimed at understanding and increasing the tolerance of pomegranate trees to water stress conditions.

Introduction

Iran is one of the largest producers of pomegranates in the world, and it has been reported that ‘Shishecap’, and ‘Malas-Yazdi’ are two major commercial cultivars of pomegranate in the country¹. In recent years, severe water stress and significant groundwater depletion have resulted in the widespread decline of pomegranate orchards in several arid regions². In arid and semi-arid regions (such as Iran), especially during spring and summer, water stress causes a significant decrease in growth, quantity, and quality in many plants³. Abiotic stresses, including water stress, lead to an accumulation of reactive oxygen species (ROS) in plant cells. ROS are inevitable byproducts of many plant processes related to metabolism⁴.

It has also been found that ROS activity destroys nucleic acids, degradation of proteins, hydrolysis of lipids, inhibition of enzyme activity, and stimulation of the cell death pathway, eventually leading to plant death. Plants have developed several enzymatic and non-enzymatic antioxidant defense mechanisms to eliminate ROS⁵. Antioxidant systems, both enzymatic and non-enzymatic, may collaborate to reduce oxidative damage in plant tissues under stress conditions⁶. In this regard, superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), ascorbate peroxidase (APX), glutathione reductase (GR), and glutathione peroxidase (GPX) are examples of enzymatic antioxidants. In contrast, carotenoids, anthocyanins, ascorbate, glutathione, tocopherol, alkaloids, phenolic compounds, and flavonoids are examples of non-enzymatic antioxidants⁷. Antioxidant systems typically maintain the equilibrium of ROS in different cell compartments; when this balance is disrupted, oxidative damage occurs⁵. Consequently, modern strategies aimed at improving water use efficiency such as sustained deficit irrigation (SDI) and the selection of drought tolerant cultivars and rootstocks have been proposed to mitigate the impact of drought conditions⁸. Currently, identifying the optimal deficit irrigation regime is essential for minimizing excessive water use and ensuring sustainable resource management. The pomegranate trees (Punica granatum L.) are drought tolerant plants with characteristics such as the ability to combat stress caused by drought through supplementary stress avoidance and stress tolerance strategies, as well as maintaining high relative apoplastic water content⁹. Nevertheless, to attain optimal vegetative and reproductive growth, pomegranate cultivation necessitates the application of deficit irrigation, especially in arid and semi-arid environments¹⁰.

It has been found that certain physiological features of plants, such as water potential, relative water content (RWC), stomatal reactions, photosynthesis, osmotic adjustment, carbohydrate accumulation, ROS, and antioxidative enzymatic responses are strong indicators of tolerance to water stress⁸. Additionally, under water stress conditions, proline accumulation increases as an adaptive response to regulate osmotic potential¹¹.

The primary objective of this investigation was to explore the impact of water stress on the morphophysiological and biochemical parameters of two commercially important Iranian pomegranate cultivars. This study hypothesizes that sustained SDI enhances the drought tolerance of pomegranate trees through physiological and biochemical adaptations. Several morphophysiological and biochemical features may be affected by water stress, including leaf area (LA), leaf chlorophyll (a, b, and total) content, carotenoid content, electrolyte leakage (EL), RWC, proline content, soluble carbohydrates, and the activity of catalase (CAT), peroxidase (POD) and superoxide dismutase (SOD).

Materials and methods

Plant material and experimental conditions

This study was conducted over two consecutive growing seasons at the Yazd Agricultural and Natural Resources Research Center, Yazd province, located at an elevation of 1230 meters above sea level in central Iran (31° 54′ N, 54° 24′ E). A randomized complete block design (RCBD) with three replicates was used, and each block was considered as one replicate with two trees in each replicate. The trees were planted in a 4 m × 3 m pattern, and the pomegranate growing season typically spans from late March to late October. During this period, no rainfall occurred, and the average relative humidity (RH) was consistently below 25%. Table 1 displays the average physical and chemical properties of the irrigation water and soil. Soil samples were taken from six locations within the trial site at depths of 0–30 cm, 30–60 cm, and 60–90 cm to determine soil properties. Moreover, irrigation water parameters were measured at three different stages during the growing season (spring and summer).

Table 1.

The investigation’s soil and irrigation water’s physical and chemical characteristics.

Soil depth (cm)	Texture	ECe (dS m− 1)	pH	CaCO3%	OC %	P	K	Cu	Mn	Fe	Zn
						(mg kg− 1 soil)
characteristics of soil
0–30	SL	3.85	7.9	23.2	0.19	9.8	110	0.34	1.8	4.2	0.64
30–60	SL	4.90	7.8	22.6	0.09	11.3	150	0.86	3.4	5.8	0.70
60–90	SL	6.18	7.8	21.7	0.17	11.7	165	0.87	3.8	5.8	0.76

HCO− 3 (meq L− 1)	pH	EC (dS m− 1 )	Cl (meq L− 1)		SO4 − 2 (meq L− 1)		Ca2+ (meq L− 1)		Mg2+ (meq L− 1)		Na+ (meq L− 1)
Characteristics of water for irrigation
2.7	7.35	3.99	24.5		13.9		13.3		10.3		17.5

OC Organic Carbon, SL Sandy loam, ECe Saturated soil paste electrical conductivity, EC Electrical conductivity.

Irrigation schedule details

Eight-year-old pomegranate (Punica granatum L.) trees of the cultivars “Shishecap” and “Malas-Yazdi” were used in this experiment. Three irrigation regimes were applied, including full irrigation (control, 100% water requirement), 75% of the plant’s water requirement (mild water stress), and 50% of the plant’s water requirement (severe stress). The net irrigation water depth has been computed as follows¹²:

where : Net irrigation water depth (m),: Soil water content at field capacity (volumetric percentage),: Soil water content before irrigation (volumetric percentage), and D: Effective root depth (meters).

where : Net irrigation volume (liters/tree) and A: Wetted area (m²/tree)

where : Gross irrigation volume (liters/tree), Ea: Irrigation efficiency (%), and T: Irrigation regime (%).

Plant leaf area

Twenty leaves per replicate were randomly selected from different parts of the tree. A leaf area meter was used to measure LA (AAM-8, Hayashi Denko Co. Ltd., Japan).

Chlorophyll and carotenoid content

The concentrations of chlorophyll a, b, total, and carotenoids were measured using the dimethyl sulfoxide (DMSO) method^13,14. Each sample was incubated in a glass vial containing 7 mL of DMSO at 65 ^ºC for 30 h in the dark. After incubation, the extract was filtered and diluted with DMSO to a final volume of 10 mL. Absorbance was measured at 645, 663, and 470 nm using a spectrophotometer (Bio Tek VT 05404-0998, USA), with DMSO used as the blank. The concentrations of chlorophylls and carotenoids (mg g^− 1 FW) were calculated using the following formula:

Leaf EL

Leaf EL was determined using a modified version of the previously described method¹⁵. Fully developed, uniform leaves were randomly selected from each plant and washed well with deionized water. To measure EL, leaf discs with 1 cm diameter were excised. Ten leaf discs from each treatment were placed into test tubes containing 10 mL of deionized water and shaken at 250 rpm for 1 h at room temperature. Afterward, the initial electrical conductivity (EC₁) was measured using a conductivity meter. The test tubes were subsequently autoclaved at 120 °C for 15 min to ensure maximum ion release, then allowed to cool at room temperature for 2 h. The final electrical conductivity (EC₂) was measured, and electrolyte leakage was calculated as a percentage of total conductivity using the following formula:

Leaf RWC

The RWC of leaves was measured using the following method for each cultivar. Ten leaves were collected from each replicate and immediately weighed to record their fresh weight. The leaves were then immersed in deionized water for 24 h to achieve full saturation. After 24 h, excess surface water was gently removed, and the leaves were weighed (turgid weight) following the 24-h leaf saturation period. The leaves were oven-dried at 70 °C for 72 h to determine their dry weight¹⁶. RWC was calculated as a percentage using the following formula:

Proline content

Liquid nitrogen was used to grind the samples into a powder. Briefly, 0.5 g of the powdered sample was homogenized in 10 mL of 3% (W/V) liquid sulfosalicylic acid. The homogenate was then filtered through Whatman No. 1 filter paper. From the filtered extract, 2 mL was transferred to glass tubes along with 2 mL of ninhydrin and 2 mL of glacial acetic acid. The mixture was heated in boiling water for 60 min and then quickly transferred to an ice bath. Subsequently, 4 mL of toluene was added to the mixture, which was vigorously mixed for 15–20 s. The absorbance of the solution was measured at 520 nm using a visible spectrophotometer, with toluene as the blank. The proline content was determined using a calibration curve and expressed as µmoles of proline per gram of fresh weight. The calculation was performed using the following formula:¹⁷.

Soluble carbohydrates

Soluble sugar content was measured using the phenol-sulfuric acid method with modifications, and colorimetric determination was performed at 490 nm using an Epoch Microplate Spectrophotometer¹⁸. Leaf samples were ground into a fine powder using liquid nitrogen, and 0.1 g of the dry powder was mixed with 13 mL of 80% ethanol. The mixture was centrifuged at 5000 rpm for 10 min, and the supernatant was collected. Subsequently, 1 mL of the supernatant was transferred to a test tube, followed by the addition of 5 mL of 5% phenol solution and 5 mL of sulfuric acid. The mixture was vortexed for 30 s and then placed on ice to bring it to room temperature. Finally, the total sugar concentration was determined and expressed as mg of soluble carbohydrates per gram of dry weight, calculated using a glucose calibration curve.

Extraction of samples for determination of antioxidative enzyme activity

Leaf samples (1 g) were homogenized with 10 mL of 50 mmol L⁻¹ phosphate buffer (pH 7.0). The homogenate was centrifuged at 10,000 × g for 15 min at 4 °C in a refrigerated centrifuge. The supernatant was filtered through a layer of cheesecloth and used for enzymatic activity measurements. Prior to biochemical analysis, the homogenized leaf tissues were stored at − 80 °C⁸.

Leaf CAT activity

The decomposition of H₂O₂ at 240 nm was measured using a UV spectrophotometer to determine CAT activity¹⁹. Briefly, 0.1 mL of the enzyme extract was mixed with 2.8 mL of phosphate buffer (pH 7.4, 0.1 mol L⁻¹) containing 4 mM Na₂EDTA to prepare the reaction mixture. The reaction was initiated by adding 0.1 mL of 0.01 mol L⁻¹ H₂O₂, and H₂O₂-free samples served as the blank. The changes in optical density (OD) at 240 nm were recorded at 30-s intervals for 2 min following the initiation of the reaction to determine CAT activity. One unit of CAT activity was defined as a change in absorbance of 0.01 units per minute. Finally, the CAT enzyme activity was expressed as U g⁻¹ fresh weight (FW).

Leaf POD activity

The activity of POD was measured using the method of Tuna et al.,²⁰ with minor modifications. Briefly, 100 µL of the leaf extract was mixed with 3 mL of the reaction solution containing 13 mmol L⁻¹ guaiacol, 5 mmol L⁻¹ H₂O₂, and 50 mmol L⁻¹ Na-phosphate buffer (pH 6.5). A UV spectrophotometer (Shimadzu UV-1700) was used to monitor the increase in absorbance at 470 nm over a period of three minutes at 25 °C. POD activity was expressed as U g⁻¹ fresh weight (FW), where one unit was defined as an absorbance change of 0.01 units per minute.

Leaf SOD activity

Superoxide dismutase (SOD) activity was assessed by measuring the absorbance of the superoxide-nitro blue tetrazolium (NBT) complex, which forms as a result of enzyme activity. For this, 3 mL of the reaction mixture, consisting of 50 mM phosphate buffer (pH 7.8), 0.1 mM EDTA, 13 mM L-methionine, 75 µM NBT, 4 µM riboflavin, and 250 µL of enzyme extract, were mixed in a cuvette. The cuvettes were then exposed to light (two 15-watt lamps) for 15 min. A black fabric was used to cover the cuvettes during the reaction. One cuvette without the enzyme extract served as the control, while another containing the reaction mixture but kept in the dark was used as the blank. Absorbance was measured at 560 nm using a UV spectrophotometer. One unit of enzyme activity was defined as the amount that reduces the absorbance by 50% compared to the control. SOD activity was reported as U g⁻¹ fresh weight (FW)²¹.

Statistical analysis

For both pomegranate varieties, each treatment was applied in triplicate. Mean values and standard errors were calculated using Microsoft Excel (Office 2016). All data were analyzed using a three-way analysis of variance (ANOVA), and Duncan’s multiple range test was applied to assess mean differences (P ≤ 0.05). The values are presented as error bars in all figures, representing the standard errors of the means. Correlation analysis between the measured parameters was performed using Pearson’s correlation coefficient (PROC CORR).

Plant material statement

Plant materials in this research comply with relevant institutional, national, and international guidelines and legislation.

Results and discussion

Leaf area

According to the results presented in Table 2, a significant difference was observed in leaf area (LA) between the first and second years. Therefore, the 2-year results are presented separately (Fig. 1). The effect of irrigation levels on LA was significant (P ≤ 0.001) (Table 2). As indicated by the results, LA decreased with increasing severity of stress in both cultivars (Fig. 1). For the ‘Shishecap’ cultivar, the moderately stressed and fully watered trees did not differ significantly from each other. However, a significant difference was observed between mild and severe stress across both years in this cultivar (Fig. 1).

Table 2.

Findings from the study year’s analysis of variance, cultivar, and irrigation, as well as how these factors interacted to affect the biochemical variables that were examined (mean comparison based on Duncan test, p < 0.05).

Source	DF	LA	Chl a	Chl b	Total chl	Carotenoid	EL
Year	1	11.61 ***	5.05 *	1.66 ns	5.97 *	8.74 **	7.27 *
CUL	1	0.98 ns	5.51 *	0.09 ns	10.96 **	0.97 ns	0.42 ns
IRR	2	25.64 ***	94.87 ***	16.10 ***	225.42 ***	173.96 ***	314.74 ***
Year × CUL	1	0.06 ns	31.25 ***	0.04 ns	55.74 ***	0.11 ns	16.09 ***
Year × IRR	2	0.10 ns	8.00 **	0.02 ns	15.07 ***	2.27 ns	0.00 ns
CUL× IRR	2	0.90	7.93 **	0.58 ns	13.53 ***	0.32 ns	0.11 ns
Year × CUL× IRR	2	0.04 ns	7.81 **	0.75 ns	17.46 ***	0.11 ns	15.66 ***
Source	DF	RWC	Proline	Soluble carbohydrate	CAT	POD	SOD
Year	1	264.16 ***	105.31 ***	287.05 ***	318.75 ***	0.36 ns	53.52 ***
CUL	1	6.05 *	0.06 ns	13.04 ***	198.04 ***	20.36 ***	46.88 ***
IRR	2	948.19 ***	816.63 ***	140.91 ***	304.46 ***	1418.73 ***	1331.11 ***
Year × CUL	1	3.41 ns	1.65 ns	6.20 *	3.57 ns	20.29 ***	2.81 ns
Year × IRR	2	24.44 ***	7.23 **	0.65 ns	61.46 ***	1.30 ns	34.35 ***
CUL× IRR	2	37.36 ***	7.78 **	0.09 ns	55.90 ***	5.72 **	22.06 ***
Year × CUL× IRR	2	1.28 ns	2.37 ns	0.07 ns	1.72 ns	5.60 **	1.55 ns

DF degree of freedom, CUL Cultivar, IRR Irrigation, Chl Chlorophyll, EL Electrolyte leakage, RWC Relative water content, CAT Catalase, POD Peroxidase, SOD Superoxide dismutase.

Fig. 1.

Influence of varying amounts of irrigation (a = control, b = mild stress, and c = severe stress) on the leaf area of two Iranian pomegranate cultivars (SH= ‘Shishecap’ and M= ‘Malas-Yazdi’). The same lettering above each column denotes variations between irrigation levels that are not statistically significant at P ≤ 0.05.

In the ‘Malas-Yazdi’ cultivar, a significant difference was found between all irrigation regimes across both years of the experiment, except between the 75% and 50% plant water requirement regimes in the first year (Fig. 1). These findings are consistent with previous studies that demonstrated a decrease in LA under water stress conditions to prevent excessive transpiration by decreasing the leaf surface area exposed to sunlight^22–24. One of the primary responses to water stress is the inhibition of cell growth and expansion, resulting from reduced turgor pressure when soil water availability is limited^22,25.

Effective strategies to ameliorate drought effects include enhancing root depth for greater water uptake, developing an extensive root system, reducing water loss through stomatal closure, rolling leaves to reduce radiation absorption, and minimizing evapotranspiration²⁶. Furthermore, reducing LA is an essential adaptive response, as it helps lower transpiration rates. A lower leaf-to-root ratio has been identified as an adaptive strategy to minimize water requirements²⁷. It has also been reported that under water stress, plant cell elongation and growth are suppressed due to a reduction in leaf water capacity, decreased turgor pressure, and stomatal closure²⁵. The correlation results (Table 3) showed a significant negative relationship between LA and leaf soluble carbohydrate content (r = -0.97, P ≤ 0.001) at the end of the growing season.

Table 3.

Pearson correlation coefficients of the biochemical parameters in the two Iranian pomegranate cultivars.

Variables	Leaf area	Chl a	Chl b	Total Chl	Carotenoid	EL	RWC	Proline	SC	CAT	POD	SOD
Leaf area	1
Chl a	0.83 ***	1
Chl b	0.64 **	0.76 ***	1
Total Chl	0.86 ***	0.96 ***	0.68 **	1
Carotenoid	0.93 ***	0.89 ***	0.75 ***	0.89 ***	1
EL	− 0.92 ***	− 0.82 ***	− 0.59 **	− 0.87 ***	− 0.93 ***	1
RWC	0.94 ***	0.94 ***	0.71 ***	0.95 ***	0.95 ***	− 0.92 ***	1
Proline	− 0.96 ***	− 0.88 ***	− 0.63 **	− 0.92 ***	− 0.95 ***	0.96 ***	− 0.96 ***	1
SC	− 0.97 ***	− 0.85 ***	− 0.70 **	− 0.88 ***	− 0.94 ***	0.92 ***	− 0.93 ***	0.95 ***	1
CAT	− 0.61 **	− 0.83 ***	− 0.47 *	− 0.88 ***	− 0.68 ***	0.67 **	− 0.75 ***	0.74 ***	0.62 **	1
POD	− 0.92 ***	− 0.90 ***	− 0.69 **	− 0.94 ***	− 0.94 ***	0.90 ***	− 0.95 ***	0.97 ***	0.92 ***	0.80 ***	1
SOD	− 0.89 ***	− 0.91 ***	− 0.75 ***	− 0.93 ***	− 0.96 ***	0.91 ***	− 0.94 ***	0.95 ***	0.91 ***	0.80 ***	0.98 ***	1

Chl Chlorophyll, EL electrolyte leakage, RWC Relative water content, SOD Superoxide dismutase, CAT Catalase, POD Peroxidase, SC Soluble carbohydrate.

Chlorophyll A, B, and total

A 2-year combined analysis of variance revealed significant year-to-year variation in chlorophyll a and total chlorophyll content (Table 2). As a result, the findings for chlorophyll a and total chlorophyll from the two years are presented separately (Fig. 2). However, the 2-year analysis of variance for chlorophyll b showed no significant year-to-year effect, so the average of the two years was calculated and presented (Fig. 2).

Fig. 2.

Influence of varying amounts of irrigation (a = control, b = mild stress, and c = severe stress) on the chlorophyll a, b, total, and carotenoid content of two Iranian pomegranate cultivars (SH= ‘Shishecap’ and M= ‘Malas-Yazdi’). The same lettering above each column denotes variations between irrigation levels that are not statistically significant at P ≤ 0.05.

The analysis of variance results indicated that the main effects of year, cultivar, and irrigation level, as well as their interactions, were significant for chlorophyll a content (Table 2). The highest amounts of chlorophyll a were found in the control treatment for ‘Malas-Yazdi’ (4.18 mg g⁻¹ FW) in the first year and for ‘Shishecap’ (4.14 mg g⁻¹ FW) in the second year. Additionally, the mean comparison results showed that chlorophyll a content significantly decreased with increasing levels of deficit irrigation. The analysis of variance further indicated that only the main effect of irrigation treatment significantly affected chlorophyll b content (Table 2). Specifically, the control treatment and severe water stress exhibited the highest and lowest levels of chlorophyll b, respectively, in both cultivars (Fig. 2).

The analysis of variance revealed that the main effects of year, cultivar, and irrigation level, along with their interactions, significantly influenced total leaf chlorophyll content (Table 2). The findings indicated that, over two consecutive years, increased water stress led to a reduction in chlorophyll content in the leaves of both cultivars. Reduced concentrations of chlorophyll and carotenoids due to water stress have also been reported in olive²⁸ trees and pomegranates²⁹. Leaf chlorophyll content is a key physiological characteristic that decreases under water stress³⁰. A previous study indicated that water stress can reduce chlorophyll and carotenoid concentrations in plant tissues by generating ROS in the thylakoids²⁵. Insufficient water supply can hinder chlorophyll synthesis or cause damage that reduces chlorophyll content in plants⁶. Chlorophyll content is an important indicator of environmental stress, as it decreases under stress conditions, reducing the total light absorption capacity of the plant³¹. Additionally, severe water stress may lead to photooxidative damage due to excessive light energy absorption, exacerbating chlorophyll degradation⁶.

The correlation analysis (Table 3) revealed a strong positive correlation between chlorophyll a and total chlorophyll content, while a negative correlation was observed between chlorophyll a and superoxide dismutase (SOD) activity.

Carotenoid content

The two-year combined analysis of variance indicated that the effect of year on carotenoid concentration was insignificant (Table 2). Consequently, the average carotenoid content across the two years is presented (Fig. 2). The analysis also showed that irrigation treatments had a significant effect on carotenoid content (Table 2). Across both years, the highest and lowest carotenoid levels were observed in the control treatment and severe water-stressed plants, respectively, in both cultivars.

Our results demonstrated that severe water stress either reduces carotenoid and chlorophyll synthesis or increases their degradation compared to mild water stress and the control treatment (Fig. 2). These findings align with previous studies on pomegranates³² and maize³³. It has been shown that drought reduces chlorophyll and carotenoid content due to their close relationship with the carbon exchange rate³³. Additionally, carotenoids in plants act as powerful non-enzymatic antioxidants, neutralizing ROS under water stress conditions³⁴. In the photosynthetic system, carotenoids play a crucial role in scavenging singlet oxygen and dissipating excess energy³⁰.

Goodarzian Ghahfarokhi et al.³⁰ suggested that water stress reduces photosynthesis by damaging PSI and PSII reaction centers. Since carotenoid pigments are closely associated with these photosynthetic reaction centers, their content decreases under water stress.

In our study, a strong positive correlation was found between leaf carotenoid concentration and leaf relative water content (RWC) toward the end of the growing season (r = 0.96, P ≤ 0.001).

Leaf EL

The combined 2-year analysis of variance revealed significant differences in electrolyte leakage (EL) (Table 2), leading to the independent presentation of results for each year. Variance analysis showed that irrigation treatments had a significant impact on EL (P ≤ 0.05). Additionally, the triple interaction effects of year, cultivar, and irrigation treatment were significant for EL.

The comparison results indicated that the highest electrolyte leakage (EL) levels in both the first and second years were observed under extreme drought stress, significantly surpassing those in other treatments (Fig. 3). EL is widely recognized as a reliable indicator of plasma membrane damage following stress exposure. Environmental stresses typically alter plant membranes, increasing their permeability and compromising membrane integrity. Evidence suggests that under water stress, enhanced membrane fluidity resulting from lipid peroxidation may contribute to elevated EL.This supports the hypothesis that water stress can induce membrane lipid peroxidation¹⁶. The findings of this study demonstrated that the leaf plasma membranes of the ‘Shishecap’ and ‘Malas-Yazdi’ cultivars exhibited similar tolerance to water stress, with EL increasing as water stress intensified.

Fig. 3.

Influence of varying amounts of irrigation (a = control, b = mild stress, and c = severe stress) on the electrolyte leakage of two Iranian pomegranate cultivars (SH= ‘Shishecap’ and M= ‘Malas-Yazdi’). The same lettering above each column denotes variations between irrigation levels that are not statistically significant at P ≤ 0.05.

Moreover, our results revealed a significant positive correlation between proline content and EL (Table 3).

RWC

The combined two-year analysis of variance revealed a significant year-to-year difference in RWC (Table 2). Consequently, the findings for each year are presented separately (Fig. 4). The results showed that the triple interaction effects of year, irrigation treatment, and cultivar on RWC were not significant. However, the interaction effects of year and irrigation treatment, as well as cultivar and irrigation treatment, were significant for RWC (Table 2).

Fig. 4.

Influence of varying amounts of irrigation (a = control, b = mild stress, and c = severe stress) on the RWC of two Iranian pomegranate cultivars (SH= ‘Shishecap’ and M= ‘Malas-Yazdi’). The same lettering above each column denotes variations between irrigation levels that are not statistically significant at P ≤ 0.05.

The findings indicated significant differences in RWC between the cultivars. Specifically, ‘Malas-Yazdi’ exhibited a higher RWC (55.1%) compared to ‘Shishecap’ (53.2%). The highest RWC was observed in the leaves of control trees, while the lowest RWC was found in trees irrigated with 50% of their water requirement in both cultivars.

Previous studies have reported that water stress significantly reduces leaf water potential^4,24,37,38. Our results are consistent with these findings, showing a dramatic decrease in RWC under water stress. RWC is regarded as one of the most reliable indicators of plant water status and is a crucial measure for assessing plant sensitivity or tolerance to water stress. Furthermore, our results showed a strong correlation between leaf RWC and leaf proline content (Table 3).

Proline content

The combined variance analysis of the two years revealed a significant year-to-year difference in proline content (Table 2). Consequently, the data for each year are presented separately (Fig. 5). As shown in Table 2, a significant interaction was observed between year and irrigation rate on proline levels (P ≤ 0.05). Proline concentrations increased in both cultivars under all water-stress conditions compared to the fully irrigated treatment. Across both cultivars and years, the highest and lowest proline levels were recorded under severe water stress and full irrigation, respectively (Fig. 5).

Fig. 5.

Influence of varying amounts of irrigation (a = control, b = mild stress, and c = severe stress) on the proline concentration of two Iranian pomegranate cultivars (SH= ‘Shishecap’ and M= ‘Malas-Yazdi’). The same lettering above each column denotes variations between irrigation levels that are not statistically significant at P ≤ 0.05.

The highest proline content was observed under extreme stress conditions in ‘Shishecap’ (191.07 mM g⁻¹ FW in the first year and 166.63 mM g⁻¹ FW in the second year). In contrast, the lowest proline content was found under full irrigation in the ‘Malas-Yazdi’ cultivar (96.6 mM g⁻¹ FW in the first year and 78.27 mM g⁻¹ FW in the second year). These findings align with earlier studies on pomegranate^5,39.

Low molecular weight osmolytes, such as proline, glycine betaine, organic acids, and polyols, play a critical role in maintaining cellular function under drought stress⁴⁰. Proline accumulation under water-stress conditions is known to reduce water loss and restore cell turgor¹¹. Furthermore, proline is regarded as one of the most crucial compatible solutes, and its content is often used as an indicator to identify drought-tolerant cultivars⁵. Proline helps to maintain homeostasis and balance redox during water stress⁵¹. Osmotic adjustment, which helps maintain water balance during osmotic stress, is achieved through the accumulation of osmotically active molecules and ions, such as proline, soluble sugars, sugar alcohols, glycine betaine, organic acids, and minerals like calcium, potassium, and chloride⁴¹.

Our results revealed a strong positive correlation between proline concentration and the activity of antioxidative enzymes in pomegranate leaves (Table 3). Conversely, proline accumulation showed a significant negative correlation with RWC (r = − 0.96, P ≤ 0.001) (Table 3).

Leaf soluble carbohydrate content

The combined analysis of variance for the two years revealed significant year-to-year variation in soluble carbohydrate content. Consequently, the results for each year are presented separately (Fig. 6). Table 2 indicates a significant interaction between cultivar and year on soluble carbohydrate content (P ≤ 0.05). Additionally, irrigation levels significantly affected soluble carbohydrate concentration (P ≤ 0.001). The findings demonstrated that water scarcity led to a substantial increase in soluble carbohydrate levels in both cultivars across both years (Fig. 6). The highest soluble carbohydrate content was observed under extreme stress. At the same time, the lowest was recorded in the fully irrigated treatment for both cultivars and years.

Fig. 6.

Influence of varying amounts of irrigation (a = control, b = mild stress, and c = severe stress) on the soluble carbohydrate concentration of two Iranian pomegranate cultivars (SH= ‘Shishecap’ and M= ‘Malas-Yazdi’). The same lettering above each column denotes variations between irrigation levels that are not statistically significant at P ≤ 0.05.

These results align with previous studies on the impact of water stress on soluble carbohydrate concentrations in pomegranates⁴². Prior research has shown that water stress reduces carbohydrate reserves due to decreased trees photosynthesis⁴³. The reduction in carotenoid and chlorophyll pigments observed in this study under limited irrigation conditions is directly associated with the decline in carbohydrate storage in tree leaves.

Plants adapt to water scarcity by increasing the concentration of low molecular weight organic solutes, such as soluble sugars, proline, and amino acids. This osmotic adjustment enhances their ability to absorb water under drought conditions⁴⁴. It has also been reported that the accumulation of osmolytes like soluble carbohydrates and proline is a key strategy to mitigate the adverse effects of drought stress⁴⁵.

Water stress impairs the photosynthetic system, leading to reduced photosynthetic efficiency and, consequently, lower carbohydrate storage rates⁴⁶. Damage to the photosynthetic system can result from mesophyll cell dehydration, metabolic disruptions, chloroplast alterations, and reduced chlorophyll content, all of which lower photosynthetic activity and carbohydrate production⁴⁴. Furthermore, an increased respiration rate under water stress exacerbates the depletion of carbohydrate reserves⁴². Correlation analysis revealed the strongest positive relationship between soluble carbohydrate concentration and pomegranate LA (Table 3).

Activity of antioxidative enzymes (CAT, POD, and SOD)

CAT activity

The combined analysis of variance (ANOVA) for both years indicated that the effect of the year on CAT activity was significant. Consequently, the results for each year are presented separately. Statistical analysis revealed significant variations in CAT activity across irrigation treatments, years, cultivars, and their triple interaction (Table 2). The results showed that increasing water restriction led to a rise in CAT activity in the leaves of both cultivars (Fig. 7).

Fig. 7.

Influence of varying amounts of irrigation (a = control, b = mild stress, and c = severe stress) on the activity of CAT enzyme of two Iranian pomegranate cultivars (SH= ‘Shishecap’ and M= ‘Malas-Yazdi’). The same lettering above each column denotes variations between irrigation levels that are not statistically significant at P ≤ 0.05.

In ‘Malas-Yazdi,’ CAT activity under severe stress was 2.27 times higher than in the control treatment during the first year. However, in the second year, the differences in CAT activity across irrigation treatments were smaller, nevertheless the increasing severity of water stress consistently elevated CAT activity across both years. In ‘Shishecap’, severe stress resulted in CAT activity levels 1.35 and 1.3 times higher than the control treatment in the first and second years, respectively.

Previous studies have reported that greater water stress tolerance is often associated with a more effective antioxidative system⁴⁵. During severe water stress, both pomegranate cultivars (‘Shishecap’ and ‘Malas-Yazdi’) exhibited high CAT activity, consistent with other findings^42,44,46. Under water stress conditions, the photosynthetic system is impaired, ROS activity increases, and membrane lipids undergo oxidation, leading to increased permeability and compromised membrane integrity⁴⁷.

Research suggests that ROS levels increase under water stress, necessitating elevated antioxidant activity to mitigate damage and enhance stress tolerance. When cell membranes are damaged by water stress, the plant’s ability to neutralize free radicals may diminish⁴⁰. The balance between ROS production and the antioxidant system’s capacity to neutralize them determines the extent of ROS-induced damage⁴⁸.

CAT and POD are two critical enzymes for detoxifying H₂O₂ and converting it to water and oxygen under drought conditions⁴⁹. CAT, found in all cells and particularly abundant in peroxisomes, plays an essential role in directly converting H₂O₂ into water and oxygen⁵⁰.

Our findings revealed a significant positive correlation between antioxidant enzyme activity and osmotic adjustment components, such as proline and soluble carbohydrates. Additionally, as the growing season progressed, a significant positive correlation was observed between antioxidant enzyme activity and leaf electrolyte leakage (EL) (Table 3).

POD activity

The findings for POD activity were reported separately for each year because the combined analysis of variance revealed a significant year-to-year difference (Fig. 8). According to the results (Table 2), the triple interaction of year, cultivar, and irrigation levels significantly influenced POD activity (P ≤ 0.01). POD enzyme activity increased in both cultivars under all water stress conditions compared to the control treatment.

Fig. 8.

Influence of varying amounts of irrigation (a = control, b = mild stress, and c = severe stress) on the activity of POD enzyme of two Iranian pomegranate cultivars (SH= ‘Shishecap’ and M= ‘Malas-Yazdi’). The same lettering above each column denotes variations between irrigation levels that are not statistically significant at P ≤ 0.05.

Our findings align with those of previous research⁴², which reported that water stress induces oxidative stress, leading to increased membrane damage⁶. POD, located in the cytosol and chloroplasts is a critical enzyme for scavenging H₂O₂. Unlike CAT, which is absent in chloroplasts, POD detoxifies H₂O₂ within these organelles, playing a vital role in mitigating oxidative damage under water stress conditions⁴².

SOD activity

As shown in Table 2, the year-to-year variation in SOD activity was significant; therefore, the results for each year were presented separately (Fig. 9). The interaction between irrigation levels and cultivars, as well as between irrigation levels and year, significantly influenced SOD activity. The findings revealed that increasing the severity of water stress considerably enhanced SOD activity in both cultivars and across both years (Fig. 9). In this study, the highest SOD activity was observed in severely stressed trees, while the lowest activity was found in fully irrigated trees for both cultivars (Fig. 9).

Fig. 9.

Influence of varying amounts of irrigation (a = control, b = mild stress, and c = severe stress) on the activity of SOD enzyme of two Iranian pomegranate cultivars (SH= ‘Shishecap’ and M= ‘Malas-Yazdi’). The same lettering above each column denotes variations between irrigation levels that are not statistically significant at P ≤ 0.05.

Previous research has demonstrated that water stress induces the hyperaccumulation of ROS in plant cells⁶. Overaccumulation of ROS under limited water may cause cell injury⁵¹. SOD and CAT enzymes play crucial roles in protecting plant tissues from oxidative damage caused by abiotic stresses⁵². These findings are consistent with earlier studies on pomegranate and Siam tulip^42,50.

H₂O₂, a toxic compound, is directly converted into water and oxygen by CAT⁴⁹. SOD catalyzes the breakdown of superoxide radicals into H₂O₂ and O₂, along with the absorption of two protons, thereby reducing the risk of hydroxyl radical formation in the cellular environment. Subsequently, the H₂O₂ produced in this reaction is converted into water by ascorbate peroxidase⁴².

In this investigation, the activities of CAT, POD, and SOD increased under water deficit conditions. This enhancement may represent a plant strategy to mitigate oxidative stress and minimize cellular damage in water-limited environments. However, it is crucial to note that prolonged water stress can overwhelm the antioxidant system’s detoxification capacity, leading to an imbalance between ROS production and antioxidant defense. This imbalance can result in extensive cellular damage and ultimately cell death⁴.

Principal component analysis (PCA)

Principal Component Analysis (PCA) was conducted to assess the effects of deficit irrigation on the morphophysiological and biochemical parameters of two Iranian pomegranate cultivars. PCA is a valuable tool for explaining the overall variability of traits. The analysis revealed two principal components, PC1 and PC2, with eigenvalues of 10.23 and 0.529, respectively, which together accounted for 97.80% of the total variation. PC1 was strongly positively correlated with proline (PC1 = 3.30), while PC2 showed the highest positive correlation with CAT activity (PC2 = 0.43). Additionally, PC1 exhibited negative correlations with chlorophyll a, chlorophyll b, total chlorophyll, carotenoids, LA, and RWC. Similarly, PC2 demonstrated negative correlations with chlorophyll a, total chlorophyll, EL, proline content, and soluble carbohydrates (Fig. 10).

Fig. 10.

Principal component analysis biplot of data for chlorophyll a, b and total chlorophyll, carotenoid content, electrolyte leakage, relative water content (RWC), proline, soluble carbohydrate, superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD). The treatments and cultivars including ‘Shishecap- control’ (A), ‘Shishecap—mild stress’ (B), ‘Shishecap—severe stress’ (C), ‘Malas-Yazdi—control’ (D), ‘Malas-Yazdi—mild stress’ (E) and ‘Malas-Yazdi—severe stress’ (F) (36 samples in total due to two experiment years).

Conclusion

The results demonstrated that the ‘Shishecap’ and ‘Malas-Yazdi’ pomegranate cultivars exhibited different levels of tolerance to water stress. Water stress adversely affected several parameters, including reductions in chlorophyll, carotenoids, LA, and RWC. However, both cultivars employed adaptive mechanisms to mitigate the adverse effects of water stress, which included osmotic adjustment: enhanced synthesis and accumulation of osmolytes such as proline and soluble sugars to maintain osmotic balance. Turgor maintenance: resistance to reductions in cellular RWC, helping to preserve turgor pressure under water-deficit conditions. Oxidative stress management: increased activity of antioxidant enzymes such as CAT, POD, and SOD, which regulate ROS and minimize oxidative damage.

The elevated levels of SOD, POD, and CAT activity in stressed plants highlighted the critical role of these enzymes in managing ROS at the cellular level during drought conditions. Among the two cultivars, ‘Malas-Yazdi’ displayed greater drought tolerance than ‘Shishecap’. This was evidenced by its better ability to maintain RWC and LA, coupled with higher oxidative enzyme activity, contributing to its superior growth performance under water stress.

Future research should focus on exploring the effects of SDI on fruit yield and quality, in addition to the vegetative growth performance of these cultivars.

Author contributions

M.N. Conducting experiment, Data analysis, Writing draft; A. R. Supervision, Equipments; S. E. Data Validation, Advisor. D.V. Advisor, Equipments, Data Validation. All authors reviewed the manuscript.

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.