Introduction

Strawberry (Fragaria × ananassa Duch) is becoming a popular small fruit in the gulf states and widely grown in the Midditerranian area. Due to its shallow root system, high fruit water content and wide leaf area, the plant is extremely sensitive to drought (Hancock 1999), which may limit its cultivation in region with water shortage. Drought in arid regions, such as Saudi Arabia, adversely affects plant growth, development, productivity and limits culture and germplasm exchange for most crops, including strawberry (Sardhara and Mehta 2018; Zhang et al. 2018; Saijo and Po-iian Loo 2020). Cultivar-dependent variations in abiotic stress toleranc have been reported in strawberry plants under in vivo (Klamkowski and Treder 2008; Tohmaa and Esitkena 2011) or in vitro conditions (Hussein et al. 2017). Therefore, the choice of relatively tolerant genotype would be of great impact in future breeding and extention efforts to help expand strawberry cultivation under conditions of water stress.

Studies on plant responses to drought stress in the field may be associated with non-uniform moisture availability and temperature fluctuations during the growing season. In addition, the described method requires a lot of planting space, time, material resources and equipment (Arvin and Donnelly 2010). In such studies, in vitro screening for abiotic stress tolerance would be beneficial to reduce the effect of changing external environments, screening of large number of genotypes under limited space and well-identified environment (Shatnawi et al. 2004; Bednarek and Orłowska 2020).

The utilization of nanomaterials is expected to help overcome many of the problems related to plant propagation (Helaly et al. 2014) and production (Nair et al. 2010; Zahedi et al. 2020b). Two of these nanoparticles (NPs) signaling molecules, SiO₂NPs and ZnONPs have been proved to play an active role, in inducing many physiological and biochemical changes within the cell, and allowing them to overcome stresses, including drought or salt stress (Marslin et al. 2017; Sun et al. 2020). Exogenous application of nanoelements has shown positive effects on growth and productivity, as well as enahnced tolerance to drought stress in several crops, including strawberry (Mozafari et al. 2018; Zahedi et al. 2020a); tomato (Faizan et al. 2018); potato (Mahmoud et al. 2020); pepper (García-López et al. 2019), among other crops. However, depending on the concentration and type of NPs, growing conditions, and species, previous research on the influence of NPs on plant growth revealed both positive and negative effects (Gruyer et al. 2013).

Under environmental stress, the plants are subjected to significant alterations in enzyme activities, and consequently their metabolism, causing increased production of reactive oxygen species (ROS) (Hasegawa et al. 2000; Parida and Das 2005), ultimately, this slows plant growth and increases damage to various parts of the plant. To overcome the abiotic stress and minimize the effects of oxidative stress, plants have evolved a variety of strategies for dealing with stressful conditions via synthesis of ROS scavenging. In this respect, the stimulation of the plant antioxidant capacity is one of the most important mechanisms of protection against the harmful impact of oxygen radicles (Sherwin and Farrant 1998). Peroxidase (POD) and catalase (CAT) are antioxidant enzymes that widely known by their high antioxidative effects (Apel and Hirt 2004; Kruk et al. 2005; Ikeda et al. 2011). In addition, some studies have suggested the amino acid proline (Bano et al. 2013) or chlorophyll accumulation (Dehghanipoodeh et al. 2018) to serve as indicator to abiotic stresses. However, further reaserch is required to monitor the relative changes in these biochemicals under the influnce of NPs treatments.

The present studies assessed the possible alleviation of drought stress by applying Zn and Si nanomolecules to strawberry (Fragaria × ananassa Duch) cultivras grown under PEG-induced water stress in vitro, and determine their relative tolerance to drought stress. Alterations on some physiological and biochemical markers associated with the application of NPs under drought stress was also investigated.

Materials and Methods

Plant materials

In vitro culture system was carried out at the Genomic and Biotechnology Laboratory, Department of Biological Sciences, King Abdulaziz University, KSA in collaboration with Plant Tissue Culture Unit, Horticulture Department, Faculty of Agriculture, Suez Canal University, Egypt during the period from March 2018 to May 2019. The two strawberry (Fragaria x ananassa Duch.) cultivars i.e., Sweet Charlie (SW) and Camarosa (CAM) were examined in the following two experiments.

Preparation of ZnO-NPs and SiO2-NPs suspension

The two nanomaterials, ZnO and SiO₂ (Sigma–Aldrich Company, California, USA and Nanotechnology Unit, Beni-Sueif University, Egypt) were utilized in the current study. Suspensions of ZnONPs and SiO₂NPs were freshly prepared with distilled water and dispersed with a sonicator for 30 min at two concentrations of 15 and 30 mg L^-1 and 50 and 100 mg L^-1, respectively. Before being applied to the culture media, the nanoparticle suspensions were centrifuged (Helaly et al. 2014; Gowayed et al. 2017).

In vitro propagation

Sterilized runner meristem tip explants of the two strawberry cultivars were cultured in vitro, under aseptic conditions on shoot initiation medium composed of MS salts (Murashige and Skoog 1962), 3% sucrose, 100 mg L^-1 myo-inositol, and 1 mg L^-1 thiamin-HCl. After adjusting the pH of the medium to 5.7, it was solidified with 0.7 percent agar and autoclaved at 121^oC for 20 min at 15 psi. Cultures were maintained in a growth chamber for 4 weeks at 22 ± 2°C and 16 h photoperiod with an irradiance of 45 μmol m^-2 s^-1provided by white fluorescent lamps. To obtain enough stock plantlets for future experiments, meristem-derived plantlets were sub-cultured onto shoot multiplication MS medium supplemented with 0.3 mg L^-1 BA, 3% sucrose and incubated on the shelves of a growth room at the same conditions as above.

Response of strawberry to in vitro PEG-induced water stress and nanomolecules

Single plantlets excised from the proliferated shoot clusters of the two strawberry cultivars were subcultured onto glass jars (3 explants per jar) containing MS medium (30 mL per jar) supplemented with 0.3 mg L^-1 BA. Water stress was imposed by the addtion into the medium of 3 concentrations of PEG 6000 (0, 20 and 40 g L^-1), while stress alleviation was examined by supplemting the same medium with ZnONPs at 0, 15 and 30 mg L^-1(Exp. 1), or SiO₂NPs at 0, 50 and 100 mg L^-1(Exp. 2). Media preparation and culture conditions were similar to the above. Each experiment was 2*3*3 factorial in a complete randomized design (CRD) and five replicates. In both experiments, fully proliferated shoot clusters were obtained at six weeks from culture initiation. Data were taken on shoot cluster fresh weight (SFW) and number of shoots per cluster (NSC) using five randomly selected replicates (clusters) per treatment.

Relative water content, chlorophyll and proline determination

4*4 mm leaf disks were used to assess relative water content (RWC) and after calculating the fresh weight (FW), they were submerged overnight in distilled water, blotted dry on a paper towel, and the turgid weight (TW) was calculated. After drying for 48 h at 70°C, the sample dry weight (DW) was determined and the RWC was calculated using the formula:

% RWC= (FW-DW)/(TW-DW) × 100.

Chlorophyll was determined according to Lichtenthaler (1987). Leaves from the proliferated shoots (0.5 g) were homoginized in 80% acetone and the extracts were centrifuged at 3000 x g. Absorbance was recorded at 644 and 662 nm for chl a and chl b assay, respectively, using spectrophotometer model Unico UV/VIS 2100.

For proline determination, plant material (0.1 g) was homogenized in 2 mL of 3% aqueous sulphosalicylic acid before being filtered through Whatman No. 2 filter paper. 2 mL of filterate was mixed with 2 mL of glacial acetic acid and 2 mL of acid ninhydrin before being heated in a boiling water bath for 1 h. Place the tub in an ice bath to stop the reaction, then add 4 mL of toluene to the reaction mixture and stir for 20 sec. The red color intensity was measured at 520 nm after the toluene layer was separated (Sadasivam and Manickam 1991).

Quantitative determination of antioxidant enzymes

Plant samples (0.1–0.4 g in vitro shoots) were stored at -20°C before being processed according to Ni et al. (2001). Hammerschmidt et al. (1982) method was used to assess peroxidase (POD) activity. 1.5 mL pyrogallol (0.05 M) and 100 μL enzyme extract were applied to a spectrophotometer sample cuvette. At 420 nm, the reading was set to zero. The reaction was started by adding 100 μL of hydrogen peroxide (1%) to the sample cuvette. The activity of catalase (CAT) was determined using biodiagnostic kit No. CA 2517, which is based on Aebi (1984). spectrophotometric method. Catalase reacts with a known amount of hydrogen peroxide, and catalase inhibitor stops the reaction after 1 min. In the presence of peroxidase, the remaining H₂O₂ reacts with 3,5-dichloro-2-hydroxybenzene sulfonic acid and 4-aminphoenazone to form a chromophore with a color intensity inversely proportional to the amount of catalase in the sample to form a chromophore with a color intensity inversely proportional to the amount of catalase in the sample. The absorbance was assessed at 510 nm.

Statistical analysis

The experiments were 2 x 3 x 3 factorial in CRD design. In each experiment, data were subjected to the analysis of variance (ANOVA) with the aid of SPSS 14 for windows statistical package (IBM Corp., New York, USA). Means were compared with Duncan's multiple range test at P ≥ 0.05 (Snedecor and Cochran 1989).

Results

Experiment No. 1

Effects on the in vitro growth and shoot proliferation

Results of ANOVA for in vitro shoot cluster fresh weight (SFW) and proliferation potential, expressed as number of shoots/cluster (NSC), of the two strawberry cultivars: Sweet Charlie (SW) and Camarosa (CAM) in response to ZnONPs treatments under PEG-induced drought stress are shown in (Table 1). Results indicated that SFW was significantly affected by cultivar, PEG and ZnONPs treatments. The cv SW had 16% higher SFW and 72% more NSC than cv CAM. Drought stress induced by PEG at 20 or 40 g L^-1 significantly decreased SFW by 30 and 41%, respectively, compared to the control. Application of ZnONPs, especially at 30 mg L^-1, slightly reduced SFW and NSC when tested over cultivars and PEG levels. All interactions had no significant effect on SFW (Table 1). However, it could be estimated (Fig. 1A) that, under sever water stress (40 g L^-1 PEG), SFW was decreased in both cultivars, in varing degree (41% in cv SW and 53% in CAM). With the application of ZnONPs at 15 mg L^-1 under sever water stress, SFW was enhanced in both cultivars (Fig. 1A). Under moderate water stress (20 g L^-1 PEG), the same ZnONPs treatment improved SFW in cv CAM by 17.4%. The interaction of CV * PEG * ZnONPs significantly affected NSC, and the application of ZnONPs at 15 mg L^-1 under severe drought, had resulted in increased NSC by 18.8% (compared to 0 ZnONPs) in cv SW, while had no effect on CAM, indicating different magnitute of

Fig. 1: Three-way interaction effects of CV*PEG*ZnONPs on A) SFW; B) NSC; C) RWC; D) Chl; E) CAT; F) POD and G) proline in two strawberry cultivars.

T1 = Control, T2 = 15 mg L^-1 ZnONp, T3 = 30 mg L^-1 ZnONP, T4 = 20 g L^-1 PEG, T5 = 20 g L^-1 PEG + 15 mg L^-1 ZnONP, T6 = 20 g L^-1 PEG + 30 mg L^-1 ZnONP, T7 = 40 g L^-1 PEG, T8 = 40 g L^-1 PEG + 15 mg L^-1 ZnONP, T9 = 40 g L^-1 PEG + 30 mg L^-1 ZnONP

cultivar response to PEG * ZnONPs treatments (Fig. 1B).

Effects on RWC, Chl, antioxidant enzymes and proline

The RWC was significantly higher in cv SW than CAM (Fig. 1C). Drought stress (40 g L^-1 PEG) significantly decreased RWC, and this decline was more in cv CAM (13.2%) than SW (6.47%), as indicated by the significant CV * PEG interaction (Table 2 and Fig. 2A). In contrast, the application of ZnONPs at 15 mg L^-1increased RWC and the increase was more in cv SW than CAM (Table 2 and Fig. 3A).

ANOVA revealed that cultivar and PEG-induced water stress treatments had significant main effects on chlorophyll a+b (Chl) content in strawberry shoots (Table 2). The cv SW had more Chl than CAM and the increasing level of PEG, up to 40 g L^-1had resulted in signgificant decrease in Chl by 61.6% (Tables 2, 3 and Fig. 1A). This decline was found to be more in cv CAM than SW (Fig. 2B). Under moderate and severe water stress (PEG at 20 and 40 g L^-1, respectively), ZnONPs at 15 mg L^-1caused stability or slight increase in Chl content (Fig. 1D).

The activities of CAT and POD as well as proline contents in strawberry were significantly affected by cultivar, PEG and ZnONPs treatments (Table 2 and Fig. 1E, F and G). Shoots of cv CAM had more activity of CAT and POD than SW. However, proline content was significantly higher in cv SW. Under severe water stress, the activities of CAT, POD and proline contents were increased (P ≤ 0.001, Table 2) by 9.7, 86.5 and 38.8%, respectively. Application of ZnONPs at 15 and 30 mg L^-1significantly increased CAT by 54.7 and 71% and POD by 1.2 and 22.4%, respectively (Table 2 and Fig. 1E and F).

The CV * PEG interaction significantly affected CAT and POD activities (Table 2 and Fig. 2C and D) and shoots of cv CAM recorded higher increase in CAT and POD under severe water stress than SW. Similar trend was observed for proline content (Fig. 2E). Meanwhile, the two-way ANOVA indicated significant CV * ZnONPs interaction effect on antioxidant enzymes and proline (Table 2). In this regard, the application of ZnONPs at 30 mg L^-1 resulted in more increase in CAT activity (Fig. 3B) and proline content (Fig. 3D) in cv CAM than SW, while the reverse was true for POD activity (Fig. 3C).

A significant PEG * ZnONPs effect was detected on the activities of CAT, POD and proline contents (Table 2; Fig.3B, 4). The highest CAT was found in shoots exposed to ZnONPs at 15 mg L^-1 under non- and moderate water stress conditions (Fig. 4A), while POD (Fig. 4B) and proline (Fig. 4C) were the highest in shoots exposed to ZnONPs at 30 mg L^-1under svere water stress. ANOVA also indicated significant CV * PEG * ZnONPs interaction effects on CAT and POD activities and

Fig. 2: Effect of CVxPEG on A) RWC, B) Chl , C) CAT, D) POD and E) proline in two strawberry cultivars.

Fig. 3: Effect of CV*ZnONPs on A) RWC, B) CAT, C) POD, D) and proline in two strawberry cultivars.

proline content (Table 2). The highest CAT was recorded in cv CAM under non-stress or moderate stress conditions combined with ZnONPs at 30 mg L^-1 (Fig. 1E). Application of ZnONPs at 15 or 30 mg L^-1 under water stress, resulted in more increase in CAT than the observed increse induced by PEG alone. This was also true for POD activity (Fig. 1F) and proline content (Fig. 1G).

Table 1: Summary of analysis of variance for in vitro shoot fresh weight and shoot number in two strawberry cultivars under different treatments of PEG and ZnONPs

SOV	df	F value
SOV	df	SFW	NSC
Cultivars (CV)	1	7.56^**	515.79^***
PEG	2	30.97^***	2.39^ns
Zn	2	4.52^*	6.46^**
CV * PEG	2	0.85^ns	0.19^ns
CV * Zn	2	0.14^ns	6.54^**
PEG * Zn	4	1.02^ns	2.10^ns
CVPEGZn	4	0.86^ns	3.30^*
Error	72
Total	89
CV%		27.55%	23.85%

Table 2: Summary of analysis of variance for RWC, Chl, CAT, POD and proline in two strawberry cultivars under different treatments of PEG and ZnONPs

SOV	df	F value
SOV	df	RWC	Chl	CAT	POD	Proline
Cultivars (CV)	1	29.20^***	22.82^***	281.19^***	14.07^***	34.76^***
PEG	2	43.45^***	76.69^***	255.51^***	1493.76^***	1664.57^***
Zn	2	18.62^***	2.30^ns	2354.08^***	42.84^***	289.87^***
CV * PEG	2	5.34^**	6.83^**	5.63^**	126.87^***	49.06^***
CV * Zn	2	4.52^*	1.54^ns	233.30^***	152.95^***	127.83^***
PEG * Zn	4	0.51^ns	1.64^ns	245.34^***	26.35^***	84.43^***
CVEPGZn	4	1.38^ns	1.54^ns	55.68^***	50.63^***	244.86***
Error	36
Total	53
CV%		3.37%	21.99%	4.35%	8.89%	6.60%

Each column shows significant differences at P ≤ 0.05 (*), P ≤ 0.01(**), and P ≤ 0.001 (***) between three-factor factorial (i) cutivars, (ii) PEG, (iii) Zn by Duncan’s multiple range test (DMRT); ns – non-significant difference.

Fig. 4: Effects of PEG x* ZnONPs on A) CAT, B) POD and C) proline content in two strawberry cultivars.

Experiment 2

Effects on the in vitro growth and shoot proliferation

The results indicated significant increase in growth performance of cv SW over CAM in terms of SFW (16.2%) and NSC (72%). PEG-induced water stress at 20 and 40 g L^-1 resulted in significant decrease in SFW by 35.5 and 42%, respectively over the control. Application of SiO₂NPs at 50 mg L^-1 significantly increased SFW (15.7%) and NSC (23%). A significant CV * SiO₂NPs interaction effect was detected on NSC, and the increase in NCS at 50 mg L^-1 was more in cv SW than CAM (Table 3; Fig. 7A). The interaction of CV * PEG * SiO₂NPs did not affect SFW and NSC (Fig. 5). However, SiO₂NPs improved SFW and NSC (Fig. 9b) in both cultivars, under moderate water stress.

Effects on RWC, Chl, antioxidant enzymes and proline

Results indicated significant decline in RWC % under high level of PEG-induced drought. The application of SiO₂NPs significantly increased RWC%, and the increase was more in cv SW than CAM (Table 4).

Fig. 5: Three-way interaction effect of CV*PEGxSi-NPs on A) SFW; B) NSC; C) RWC; D) Chl; E) CAT; F) POD and G) proline in two strawberry cultivars.

T1 = Control, T2 = 50 mg L^-1 SiO₂NPs, T3 = 100 mg L^-1 SiO₂NPs, T4 = 20 g L^-1 PEG, T5 = 20 g L^-1 PEG + 50 mg L^-1 SiO₂NPs, T6 = 20 g L^-1 PEG + 100 mg L^-1 SiO₂NPs, T7 = 40 g L^-1 PEG, T8 = 40 g L^-1 PEG + 50 mg L^-1 SiO₂NPs, T9 = 40 g L^-1 PEG + 100 mg L^-1 SiO₂NPs

Accumulation of Chl a+b in strawberry shoots was significantly decreased under PEG-induced water stress at 20 and 40 g L^-1 by 36 and 64%, respectively. On the other hand, the application of SiO₂NPs at 50 mg L^-1 significantly increased Chl content by 11.3%. Under moderate water stress, SiO₂NPs at 50 mg L^-1 enhanced Chl in shoots of both strawberry cultivars (Fig. 5D).

Drought stress, induced by PEG at 40 g L^-1, significantly (P ≤ 0.001) increased the activities of CAT, POD and proline content in shoots of strawberry. With the increasing level of SiO₂NPs, up to 100 mg L^-1, the activities of both antioxidant enzymes CAT and POD, as well as proline content were also increased by 35.1, 21, and 21.5%, respectively (Table 4). The Table 3: Summary of analysis of variance for in vitro shoot fresh weight and shoot number in two strawberry cultivars under different treatments of PEG and SiO₂NPs

SOV	df	F value
SOV	df	SFW	NSC
Cultivars (CV)	1	13.75^***	356.26^***
PEG	2	43.56^***	7.60^**
Si	2	4.27^**	6.46^**
CV * PEG	2	1.70^ns	0.34^ns
CV * Si	2	2.62^ns	3.85^*
PEG * Si	4	1.42^ns	2.31^ns
CVPEGSi	4	1.54^ns	0.18^ns
Error	72
Total	89
CV%		24.81%	28.18%

two-way ANOVA indicated significant (P ≤ 0.001) CV *PEG effects on the activities of CAT, POD and proline content (Table 4, Fig. 6). In this regard, the increase over control treatment in CAT (Fig. 6A) and POD (Fig. 6B) under severe water stress was more in cv CAM than SW, in contrast to proline content which was higher in cv SW than CAM (Fig. 6C). The two strawberry cultivars significantly (P ≤ 0.001) recorded different CAT and POD activities in response to SiO₂NPs treatment (Fig. 7B and C). In contrast to cv CAM, the cv SW had shoots with lower proline content with the increase in SiO₂NPs level in the medium (Fig. 7D). The interaction of PEG * SiO₂NPs significantly (P ≤ 0.001) affected CAT, POD and proline, which were the highest under severe water stress and 100 mg L^-1 SiO₂NPs treatment (Fig. 8A, B and C). A significant CV * PEG * SiO₂NP interaction effect on antioxidant enzyems and proline (Table 4) indicated differences in the magnitute of increase in CAT and POD activities and proline content between the two examined strawberry cultivars under the influence of drought stress and SiO₂NPs levels (Fig. 5E, F and G, respectively).

Discussion

In the present study, shoot growth and prolieferation potential, physiological changes and antioxidant enzymes activities in two strawberry cultivars were examined in response to the application of ZnONPs or SiO₂NPs under drought stress. Results revealed that drought imposed by PEG treatment had resulted in significant decline in shoot FW, number of shoots/cluster (NSC) and leaves RWC. Similar findings were reported by Gopal and Iwama (2007) on in vitro screening of potato under drought stress. The decline in RWC and subsequantly in shoot FW may be due to restricted water and nutrient absorption as a result of decrease in water potential of the medium supplemented with PEG, and/or cell elongation suppression due to low turger pressure (Jaleel et al. 2009). Drought stress imposed by PEG also reduced growth of in vitro-grown grapevine, decrease indole acetic acid (IAA) and increase abscisic acid (ABA) levels (Cui et al. 2016). This growth promoter/inhibitor imbalance contributed to the obsereved reduction in (NSC) in strawberry under water stress. Drought stress had a negative impact on plant growth parameters including leaf area, plant height, and stem diameter by altering a number of morphological, physiological and metabolic processes (Fard et al. 2011). Garcı́a-Sánchez et al. (2002) reported that the reduction in growth under water stress might be due to ion toxicity and imbalance, or change in growth regulators biosynthesis. Hence, any water deficit leads to a growth pause (Aslanpour et al. 2019).

Strawberry cultivars examined in the current study showed differential response to water stress condition and cv SW exhibited lower PEG-induced reduction in SFW, NSC, RWC and chlorophyll content, than cv CAM, at the highest level of PEG-induced water stress. In addition, the CAT activity and proline accumulation were more in shoots of cv SW than in CAM. In several reports, plants exposed to water stress showed enhanced proline content (Sultan et al. 2012) or antioxidant enzyme activity (Yosefi et al. 2020) were identified as tolerant to drought, which may explain the relative tolerance of cv SW to drough stress compared to cv CAM. Similar variation in antioxidant enzyme activities were reported in strawberry cultivars exposed to salt stress (Turhan et al. 2008).

Our results also indicated significant enhancement of shoot proliferatin and RWC of strawberry with the application of ZnONPs at 15 mg L^-1 in cv SW or at 30 mg L^-1 in cv CAM under PEG-induced drought stress (Fig. 9a). This increased shoot proliferation ability with ZnONPs under water stress could be attributed to Zn's function in improving plant water status (Helaly et al. 2014), as well as management of reactive oxygen species and protection of plant cells from oxidative stresses (Sheikh et al. 2009). Recently, it was suggested that modifications in the endogenous melatonin synthesis were invoved in the ZnONPs induced drought tolerance in maize (Sun et al. 2020). In accordance with present study results, in vitro callus induction and plant regeneration were increased in tomato cultivars undere abiotic stress in the presence of ZnONPs in the medium (Alharby et al. 2016).

Results also showed that SiO₂NPs treatments significantly incresed shoot FW, NSC, RWC and chlorophyll accumulation under PEG-induced water stress, but with different degrees of influence between strawberry cultivars (Fig. 9b). This beneficial effect could be attributed to silicon treatment, which can raise gibberellic acid levels in cells and has a plant hormone-like property that could aid cell division and elongation (Soundararajan et al. 2014). Previous studies have shown that applying Si-NPs to plants under saline stress increased chlorophyll content, stomatal conductance and plant water use quality (Hattori et al. 2005; Ahmed et al. 2011). In accordance with present study results, application of SiONPs to strawberry plants accumulated high proline under water stress, assoicated with the tolerance mechanism (Dehghanipoodeh et al. 2018).

Table 4: Summary of analysis of variance for RWC, Chl, CAT, POD and proline in two strawberry cultivars under different treatments of PEG and SiO₂NPs

SOV	df	F value
SOV	df	RWC	Chl	CAT	POD	Proline
Cultivars (CV)	1	2.60^ns	0.13^ns	0.83^ns	432.55^***	239.38^***
PEG	2	10.30^***	53.59^***	345.81^***	1590.16^***	811.32^***
Si	2	7.50^**	2.58^*	169.82^***	53.39^***	239.76^***
CV * PEG	2	0.080^ns	0.94^ns	43.09^***	207.59^***	58.71^***
CV * Si	2	1.29^ns	0.84^ns	63.74^***	50.28^***	635.61^***
PEG * Si	4	1.79^ns	1.07^ns	165.64^***	7.50^***	131.50^***
CVEPGSi	4	0.23^ns	0.34^ns	22.06^***	58.27^***	174.43^***
Error	36
Total	53
CV%		4.31%	27.93%	8.65%	7.78%	6.95%

Each column shows significant differences at P ≤ 0.05 (*), P ≤ 0.01(**), and P ≤ 0.001 (***) between three-factor factorial (i) cutivars, (ii) PEG, (iii) Zn by Duncan’s multiple range test (DMRT); ns – non-significant difference.

Fig. 6: Effect of CV* PEG on A) CAT, B) POD and C) proline in two strawberry cultivars.

Fig. 7: Effect of CV * SiO₂NPs on A) NSC, B) CAT, C) POD and D) proline in two strawberry cultivars

Fig. 8: Effect of PEG * SiO₂NPs on A) CAT, B) POD and C) proline in two strawberry cultivars.

Fig. 9: Infleunce of different concentrations of A) ZnONPs and B) SiO₂NPs on the in vitro growth and shoot proliferation in strawberry cv. Sweet Charlie under PEG-induced drought, 4 weeks from culture initiation

In the present study, results showed significant increase in CAT and POD activity as well as proline contents, especially under severe drought and high levels of NPs. Recent report indicated that plants may protect themselves from drought stress by accumulating compatible solutes such as sugars, amino acids and enzymes for osmotic adjustment (Khodabin et al. 2020). According to Ashraf and Foolad (2007) and Gao et al. (2020), enzyme activity will appear to be scavenging of phospholipid hydroperoxides, thereby protecting cell membranes from peroxidative damage under abiotic stress and improving the ability of plant tissues to scavenge O₂ radicals. Our results are also in agreement with Bano et al. (2013), who recognized proline as one of the most common amino acid accumulating as a result of disturbances in osmotic balance, and it can serve as an indicator of abiotic stress. Other studies have linked the accumulation of proline to drought stress in strawberry (Radhi and Abudl-Hasan 2020), which could play a protective role against the osmotic potential generated by water stress (Farooq et al. 2012).

The variation between strawberry cultivars in their response to different treatments, whether drought or other NPs was reported in earlier studies under field conditions (Klamkowski and Treder 2008), which may explain the inconsistent findings of our study. Strawberry cv Sweet Charlie is largely preferred by strawberry growers in our region for its high yield and early fruiting habit. The current study has provided evidence of the relative tolerance of strawberry to drought stress, especially under the influence of ZnONPs and SiO₂NPs at early stage of in vitro growth, which may help expanding strawberry propagation and/or cultivation using micro-propagated stock plants, better adapted to drought conditions.

Conclusion

Negative consequences of drought stress on the in vitro growth and proliferation ability in strawberry were cultivar-dependent and could be alleviated by application of ZnONPs or SiO₂NPs. This enhanced tolerance was accompanied by increases in RWC and activities of antioxidant enzymes: catalase and peroxidase and increased accumulation of proline content in shoots of drought-affected plants. Further studies are needed to explain the relashionship between the in vitro and ex vitro respones of strawberry to nanomaterials under abiotic stresses.

Acknowledgements

This project was funded by the Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, under grant no. (G: 355-130-1440). The authors, therefore, acknowledge DSR for technical and financial support.

Author Contributions

Isam Abu Zeidconceived the research, designed the figures and tables and participated in the discussion results, reviewed several draft of the manuscript, read and approved the manuscript and Fouad Mohamed and Ehab Metwali performed the experiment, analyzed data, conducted statistical analysis and wrote the manuscript.

Conflict of Interest

The author declear that they have no conflict of interest.

Data Availability

The author affirm that data will be available on a fair request to the corresponding author

Ethics Approval

Not applicable to this paper

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