Journal of Soil Science and Plant Nutrition (2023) 23:1678–1693
https://doi.org/10.1007/s42729-023-01187-6

ORIGINAL PAPER

Demonstration of Borage Salinity Tolerance as affected by Si
Application Through Biochemical and Physiological Responses,
and Growth Attributes
Farideh Feghhenabi1· Hashem Hadi1 · Habib Khodaverdiloo2 · Martinus Th. van Genuchten3,4 · Lachlan Lake5

Received: 23 April 2022 / Accepted: 14 February 2023 / Published online: 5 April 2023
© The Author(s) under exclusive licence to Sociedad Chilena de la Ciencia del Suelo 2023

Abstract
Borage (Borago officinalis L.) is an oilseed that is being increasingly grown in areas where salinity affects yield. Silicon (Si)supplementation is considered a promising method to improve plant growth in saline conditions, however, there is currently
very little information on the effect of Si application on the physiochemical properties of borage under saline conditions. The
study aimed to elucidate if the degree of borage resistance to salinity is changed by Si through the physiochemical properties.
We conducted a pot experiment to explore photosynthetic pigments, chlorophyll fluorescence parameters, osmolyte content,oxidative stress, and antioxidant response as influenced by increasing salinity levels and Si applications (priming, foliar
spray, and priming × foliar spray). Salinity-stressed plants had a noticeable decline in chlorophyll a (56.6%) and b (64.2%),
carotenoid content (57.5%), chlorophyll fluorescence parameters (Fv/Fm (7.2%), ETR (23.2%), and ΦPSII (15.2%)), and growth
characteristics. Salinity increased oxidative damage through excessive production of malondialdehyde and increased electrolyte
leakage in leaves. The salinity-stressed plants also showed high antioxidant activities of catalase and superoxide dismutase
and increased accumulation of glycine betaine and soluble sugars compared to non-stressed plants. Si treatments resulted in asignificant reduction in oxidative damage and increased antioxidant activity reducing lipid peroxidation and electrolyte leakage
in the salinity-stressed leaves. The priming × foliar spray was the most effective at enhancing borage salinity tolerance. We,
therefore, assumed that the investigated physicochemical properties could clearly describe the physiological context of salinity
tolerance in borage and that Si could be used as a mediator of salinity tolerance and positively affect growth characteristics.
Keywords Antioxidant · Foliar spray · Lipid peroxidation · Osmolyte · Salinity · Silicon

1 Introduction
Borage (Borago officinalis L.) is an herbaceous annual,belonging to the Boraginaceae family. Borage is grown
for its seeds which contain almost 30–40% oil with a high* Farideh Feghhenabi
faride.feghenabi@gmail.com
1

Department of Agronomy and Plant Breeding, Urmia
University, Urmia, Iran2

Department of Soil Science, Urmia University, Urmia, Iran3

Department of Earth Sciences, Utrecht University, Utrecht,
Netherlands

4

Center for Environmental Studies, CEA, São Paulo State
University, Rio Claro, SP, Brazil

5

South Australian Research and Development Institute, Schoolof Agriculture, Food and Wine, The University of Adelaide,
Waite Campus, Urrbrae, SA, Australia

13

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percentage (22– 23%) of gamma-linolenic acid (GLA), an oil
used for medicinal purposes (Montaner et al. 2022). Salinity,
as one of the pre-eminent stresses facing global agriculture, isa challenge for borage growth and productivity, particularly
in arid and semiarid areas (Jaffel et al. 2011), where salinity
levels often surpass EC < 4 dS ­m−1 to reduce borage emergence(Feghhenabi et al. 2021). The response of plants to salinity
is multifaceted and involves changes in plant morphology,
physiology, and metabolism (Shalaby 2018). Salinity changes
the ionic homeostasis and osmotic potential of the cell, which
inhibits the ability of the plant to take up water as well as essential
minerals and ions, such as K
­ + and C­ a2+, which then reduces
photosynthesis and growth (Subramanyam et al. 2019). Cereals
exposed to salinity adjust their internal osmotic potential bycompartmentalization of either synthesised osmolytes in thecytoplasm or inorganic ions in the vacuole to sustain water uptake(Isayenkov and Maathuis 2019). Compartmentalization of ions in
the vacuole is a form of stress avoidance via active exclusion

Journal of Soil Science and Plant Nutrition (2023) 23:1678–1693

of toxic ions (Isayenkov and Maathuis 2019). When salinity
levels exceed the plant’s capacity for compartmentalization,
reactive oxygen species (ROS) are produced (Ahanger et al.
2020; Kohil et al. 2019; Mansoor et al. 2022).
Production of ROS adversely affects the cytoplasmic
membrane, and cell metabolism, increasing electrolyte
leakage (EL) and lipid peroxidation (Alkahtani et al. 2020;
Ouzounidou et al. 2016). However, ROS are also considered
to be involved in signaling cascades leading to increased
antioxidative protection (Alkahtani et al. 2020). In thecase of salinity stress, the superoxide radical (­ O2•−) was
found to play a crucial role in signaling the NaCl-induced
upregulation of antioxidative enzyme activities and stress
tolerance (Kováčik et al. 2009). Among several protective
enzymes, superoxide dismutases (SODs) remove superoxide
radicals by catalyzing their conversion into hydrogen peroxide ­(H2O2), which in turn can be broken down by catalase(CAT), ascorbate peroxidase (APX), and guaiacol peroxidase (GPX) to yield oxygen and water (Ahanger et al. 2020;
Kohil et al. 2019; Mansoor et al. 2022). Previous reports on
quinoa, lettuce, basil, and alfalfa exposed to salinity haveindicated increased activities of non-enzymatic and enzymatic antioxidant systems such as SOD and peroxidase catalase (Ouhibi et al. 2014; Panuccio et al. 2014; Tarchoune
et al. 2010; Wang et al. 2009). In contrast in turnip, Noreen
et al. (2010) reported that salinity substantially decreased
the activities of SOD and peroxidase catalase. These contrasting responses demonstrate that plant salinity tolerance
is a complex process and not exclusively associated withantioxidant capacity (Noreen et al. 2010). Additionally,
addressing changes in biochemical properties and defense
mechanisms can partially reflect important changes in plant
growth parameters such as plant height, plant dry weight,
and leaf area under abiotic stresses (Alkahtani et al. 2020).
The content of photosynthetic pigments is directly proportional to the plant’s photosynthetic rate (Sheteiwy et al.
2021). Salinity has been shown to decrease photosynthetic pigments in common beans (Taïbi et al. 2016). Thisis more likely due to the increased activity of the chlorophyll-degrading enzyme chlorophyllase which is caused
by increased N­ a+ (Maghsoudi et al. 2016). The deficiencyof magnesium caused by salinity is another reason for the
reduction of chlorophyll (Łuczak et al. 2021). Reduced photosynthetic pigments cause inhibition of ribulose-1,5-bisphosphate degrading the photosynthetic apparatus (Liu et al.
2019). The destruction of photosynthetic pigments and theinhibition of cellular response and electron transport from
PSI to PSII may also reduce Fv/Fm and PSII efficiency(Sheteiwy et al. 2021). Salinity also reduces photosynthetic­O2 evolution and reduces fluorescence, which is associatedwith decreased activity of the PSII complex (Anjum 2011;
Hernández 2019). The use of chlorophyll fluorescence analysis is an easy and robust technique used in plant physiology

1679

studies to provide valuable insights into the state of the PSII
(Acosta-Motos et al. 2017).
Studies have shown that exogenous silicon (Si) applied asa foliar spray on sweet pepper leaves (Abdelaal et al. 2020)or seed priming in maize (Abdel Latef and Tran 2016) could
alleviate the adverse effects of salinity through regulating antioxidant activities. Seed priming is thought to enhance salinity
tolerance by increasing antioxidant enzyme activity and protecting cell membranes through decreased lipid peroxidation
as well as improving the photosynthetic pigments and chlorophyll fluorescence (Abdelhamid et al. 2019; Paul et al. 2017).
To our knowledge, there are no studies investigating theeffects of Si seed priming, foliar spray, or combination on
antioxidant or chlorophyll dynamics in salinity-stressedborage. The objective of this study was to investigate theefficiency of different Si application techniques in reducing
the side effects of salinity concerning the response trend of
the physiological, biochemical, and growth traits of borage.
The results of this study will contribute to our understanding of (i) the response trend of physiological andbiochemical traits of borage to different levels of salinity,(ii) the effect of different Si application techniques on the
response trend of osmolyte content, chlorophyll fluorescence, and photosynthetic pigments,and (iii) the effect of Si
application on oxidative stress and response trend of antioxidative enzymes.

2 Materials and Methods
2.1 Plant material and Experimental Design
Healthy and uniform-sized seeds of common borage (Borago
officinalis) were prepared by PAKAN BAZR (Isfahan,Iran). The mean 100-seed weight and seed moisture content were 2.03 g and 5–6%, respectively. Prior to the experiments, seeds exhibited a 100% germination rate at 25 °C, asassessed in Petri dishes. For priming, the seeds were soakedfor 6 h in a solution containing ­K2SiO3 (1.5 mM). This agent
and its specific concentration were selected following themethods of Feghhenabi et al. (2021). Once primed, the seeds
were thoroughly rinsed with tap water and then distilledwater, after which they were dried back to their original
moisture content under ambient conditions (about 25 °C and
42% relative humidity). The seeds returned to their initialmoisture content after 72 h. All seeds were subsequently
surface-sterilized in a 1% sodium hypochlorite solution for
10 min to be used in the main experiments.
We conducted two outdoor pot experiments, one in 2017and 2018. The experiments were factorial with seven salinity levels, three Si treatments, and three replicates arranged
in a randomized complete block design. The 2-year average maximum and minimum temperatures were 25.6 and

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Journal of Soil Science and Plant Nutrition (2023) 23:1678–1693

12.6 °C, the number of sunny hours was 9.4 h, and rainfall
throughout the growing season was 36.5 mm. Details of
weather data during the whole course of the study are given
in Table 1. The growth medium was field soil collectedfrom a 30-cm deep layer at an alfalfa farm. The field soil
was classified as loam soil with sand, silt, and clay percentages of 46, 33, and 21%, respectively. The soil was nonsaline (the electrical conductivity of the saturation paste
was 1.1 dS m
­ −1), containing 18.5% equivalent ­C aCO 3,
with a pH value of 7.7. The soil was air-dried, ground,and passed through a 2-mm sieve. In order to maintainthe growth of the seedling, a basal dose of urea, di-ammonium phosphate, and potassium sulfate (5, 16, 2 kg ­h−1,
respectively) was added and mixed well into the soil. A
small amount of urea was also applied as a top dressing.
A total of 16.4 kg of the field soil with a bulk density
typical of the plow layer of a cultivated field was placed
into each 18.5 L plastic pot. The amount of soil in eachpot was measured on a dry weight basis. Pot cultivation
was carried out manually at 3 cm depth. Seven seeds wereplanted per pot. The seedling density per pot was reduced
to three after emergence. The addition of saline solution
treatments was performed immediately after seed sowing
with salinity levels maintained until harvest. The amountof water required per pot to reach field capacity was 2.4 l.
Pots were then maintained at 70% field capacity with additional watering. Salinity treatments were 0, 3, 5, 6, 8, 10,
and 12 dS m
­ −1, and were obtained by diluting saline waterfrom Lake Urmia, in the northwest of Iran. Rainfall wasprevented from diluting saline treatments with the additionof a removable awning during rainfall events.
The application of Si at a concentration of 4 mM has
been shown as the most effective in modulating the effectsof salinity in wheat (Alzahrani et al. 2018; Bybordi 2015).
As such, we used this concentration for the foliar spray treatment. Tween 20 at 0.01% (v/v) was used as a surfactant
to increase foliar spray efficiency by increasing solution
penetration. Half of the pots were randomly selected andtreated with a foliar application of Si. The remaining pots
were considered “no-foliar-sprayed” pots. The foliar spray
was applied at 5-leaf and 10-leaf stages (32-day-old and46-day-old plants). The first application was applied before
sunset and the second just before dawn. 50 mL per plant of
Si solution was applied with a hand-operated small locallymade sprayer. Table 2 showed a summary of treatments.

2.2 Plant Sampling
Fresh samples were obtained from the youngest fully expanded
leaves of borage at the early flowering stage when 10% of theflowers had appeared. Then, they were frozen in liquid nitrogenand stored at − 80 °C. Liquid nitrogen was also used to powder
the frozen samples. Triturating was carried out at 5 °C.
After the borage plants were harvested, shoot length andshoot dry weight were determined.

2.3 Measurement of Photosynthetic Pigments
Chlorophyll a (Chl a) and b (Chl b) as well as carotenoid(CAR) content were determined according to Lichtenthaler
and Wellburn (1983), with slight modifications. Samples(0.01 mg) of the youngest fully expanded leaves of borage
at the early flowering stage were taken and extracted with95% methanol. Absorption was read using a spectrophotometer (T60UV-Visible-1100 nm, PG Instruments, UK) atwavelengths 470, 645, and 663 nm. Chlorophyll contents
were calculated using the following equations:chl a(𝐦𝐠 𝐠−1 𝐅𝐖) =

) (
)]
[(
12.25 × 𝐎𝐃663 − 2.79 × 𝐎𝐃645

) (
)]
) [(
(
chl b 𝐦𝐠 𝐠−1 𝐅𝐖 = 21.21 × 𝐎𝐃645 − 5.1 × 𝐎𝐃663
CAR (𝐦𝐠 𝐠−1 𝐅𝐖) =

[(

(3)

where ­ODx is the absorbance of the extracts at wavelength x.

Total monthly

Mean relative

Sunny hours

Month

Maximum

Minimum

Mean

Rainfall (mm)Humidity (%)(h/day)March–April 2017
April–May 2017
May–June 2017
June–July 2017
March–April 2018
April–May 2018
May–June 2018
June–July 2018

18.9
22.7
29.7
33.4
18.9
19.5
27.1
34.6

5.0
11.1
14.9
19.3
6.9
9.5
13.9
19.9

21.4
28.3
22.3
26.4
12.9
24.3
20.5
27.3

53.9
19.9
1.8
_
56.7
132.6
27.2
_

53
51
39
39
50
61
51
32

7.5
8.8
11.6
11.3
7.9
6.2
10.2
12.0

13

(2)

)
]
1000 × 𝐎𝐃470 − 1.82 × 𝐜𝐡𝐥 𝐚 − 85.02 × 𝐜𝐡𝐥 𝐛 ∕193

Table 1  Meteorological data during the course of study
Monthly temperature(°C)(1)

Journal of Soil Science and Plant Nutrition (2023) 23:1678–1693

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Table 2  Summary of salinity
and Si treatments
Salinity treatment
Si treatment (­ K2SiO3)

Salinity
Priming
Foliar spray
Priming × Foliar spray
Control

2.4 Measurement of Chlorophyll Fluorescence
Parameters
Chlorophyll fluorescence (CF) was measured on the youngest
fully expanded leaves of 50-day-old plants (at 10% of the flowering stage) using a portable fluorometer (PAM-2000, Walz,
Germany) following Genty et al.’s (1989) method. After sunset,
the fluorometer was connected to a leaf-clip holder with a trifurcated fiberoptic and a computer equipped with data acquisition software. The minimal fluorescence level (Fo) with all PSII
reaction centers open, and the maximal fluorescence level (Fm)with all PSII reaction centers closed, were determined on darkadapted leaves. Then the leaves were continuously illuminatedwith a white actinic light at an irradiance of 180 µmol ­m−2 ­s−1
to measure the steady-state value of fluorescence (Fs), which
occurred six minutes after the initiation of white actinic light.
The maximal fluorescence level in the light-adapted state (Fm')
was recorded after subjecting the leaves to a second saturating
pulse at 8000 µmol ­m−2 ­s−1. The minimal fluorescence level inthe light-adapted state (Fo') was determined by exposing the leaf
to far-red light for three seconds. We used the light and dark fluorescence data to calculate the parameters presented in Table 3.

2.5 Measurement of Osmolyte Content
2.5.1 Glycine Betaine
The amount of Glycine betaine (GB) was estimatedaccording to the method of Grieve and Grattan (1983).

Implementation

Treatment
abbreviation

0, 3, 5, 6, 8, 10, 12 dS m
­ −1
1.5 mM for 6 h, on seeds
4 mM at 5-leaf and 10-leaf stages
P×F
no priming and no foliar spray

–
P
F
P×F
C

Frozen samples were mechanically shaken with 20 mLof deionized water for 24 h at 25 °C. The samples werethen filtered and filtrates were diluted to 1:1 with 2N­H2SO4. Aliquots were kept in centrifuge tubes and cooledin ice water for 1 h. Cold KI–I 2 reagent was added andthe reactants were gently stirred with a vortex mixer. The
tubes were stored at 4 °C for 16 h and then centrifuged
at 10,000 rpm for 15 min at 0 °C. The supernatant was
carefully aspirated with a fine glass tube. The periodide
crystals were dissolved in 9 mL of 1,2-dichloroethane.
After 2 h, the absorbance was measured at 365 nm using
GB as standard (0–350 mg ­L −1) and calculated as mg­g−1 dry weight.
2.5.2 Soluble Sugars
Soluble sugars were extracted by boiling a known
weight of liquid nitrogen-powdered samples in distilledwater for 1 h in a water bath. The extract was cooled
and centrifuged at 5000 rpm for 10 min, after that thesupernatant was made up to a known volume. The totalsoluble sugars in the extract were determined with ananthrone sulfuric acid reagent. Briefly, 0.5 mL of theextract was mixed with 4.5 mL of anthrone-sulfuric
acid reagent and boiled in a water bath for 7 min. Aftercooling, the developed blue-green color was measured
at 620 nm against a water reagent blank. The content
of sugars was determined using glucose as a standard
and calculated as mg glucose ­g −1 fresh weight (Yemmand Willis 1954).

Table 3  Chlorophyll fluorescence (CF) parameters and associated formulas
Parameter

FormulaDescription

Fv
Fv/Fm
Qp
qN
φPSII
NPQ
ETR

Fm–Fo
(Fm–Fo)/ Fm(Fm'–Fs)/( Fm'–Fo')
1–(Fm'–Fo')/( Fm–Fo)(Fm'–Fs)/ Fm'(Fm–Fm')/ Fm'
ΔF/Fm' × PPFD × 0.5 × 0.84

Maximum variable chlorophyll fluorescence yield in a dark-adapted state
The maximal efficiency of PSII photochemistry in the dark-adapted state
The photochemical quenching coefficient
Non-photochemical quenching coefficient
The actual quantum yield of PSII electron transport in the light-adapted state
Non-photochemical quenching
Apparent photosynthetic electron transport rate

Fo the minimal fluorescence level, Fm the maximal fluorescence level, Fo' the minimal fluorescence level in the light-adapted state, Fm' the maximal fluorescence level in the light-adapted state, Fs the steady-state value of fluorescence

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Journal of Soil Science and Plant Nutrition (2023) 23:1678–1693

2.5.3 Soluble Proteins
Frozen samples were homogenized in ice-cold extraction
buffer (50 mM potassium phosphate, pH 7.4, 1 mM EDTA).
The extracts were centrifuged at 15,000 rpm for 20 min,and the resulting supernatants were used for the estimationof soluble protein content and protein oxidation damage.
Protein content was assayed by following Bradford’s (1976)
method with Bovine serum albumin (BSA) as standard.

2.6 Measurement of Oxidative Stress Indicators

2.7 Data Analysis

2.6.1 Electrolyte Leakage
Electrolyte leakage (EL) was used to assess the membrane
permeability. This procedure was based on Lutts et al.
(1996). EL was measured using an electrical conductivity meter. Fresh leaf samples were placed in individual
stoppered vials containing 10 mL of deionized water after
three rounds of washing with distilled water to remove
surface contamination. These samples were incubated atroom temperature (25 °C) on a shaker (100 rpm) for 24 h.
The electrical conductivity (EC) of the bathing solution­(EC1) was recorded after incubation. The same samples
were then placed in an autoclave at 120 °C for 20 min andthe second reading (­ EC2) was determined after cooling thesolution to room temperature. EL was then calculated as:

EL(%) = (𝐄𝐂1 ∕𝐄𝐂2 ) × 100(4)

2.6.2 Malondialdehyde Content
Lipid peroxidation (MDA content) was determined using thiobarbituric acid reactions (Bailly et al. 1996), with slight modifications. The MDA content was calculated using:[](𝐎𝐃532 − 𝐎𝐃600 )∕155 × 5()−1
MDA𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝛍𝐦𝐨𝐥𝐠 𝐅𝐖 =0.1
(5)
where ­ODx is the absorbance of the extract at a given wavelength x.
2.6.3 Measurement of Antioxidant Enzyme Activities
One gram from the youngest fully expanded leaves was homogenized in 3 mL of 0.05 M sodium phosphate buffer (pH 7.8),
including 1 mM EDTA and 2% (w/v) Polyvinylpyrrolidone(PVP). The homogenates were centrifuged at 13,000 × g for
20 min at 4 °C. Supernatants were used for enzyme activity
and protein content assays. All steps in the preparation of the
enzyme extracts were carried out at 4 °C. The extracts were used
for measuring the enzyme activity of CAT, APX, and SOD.

13

Catalase (CAT) and ascorbate peroxidase (APX), activities were measured according to Cakmak and Marschner(1992), Nakano and Asada (1981), and Egley et al. (1983),
respectively. Activities of the extracts were expressed asmM ­g−1 ­FWmin−1. One unit of SOD activity was definedas the amount of enzyme which caused 50% inhibition ofphotochemical reduction of nitro blue tetrazolium (NBT)
at 560 nm according to the method of Giannopolitis andRies (1977). SOD activities of the extracts were expressed
as % inhibition ­g−1 ­FWmin−1.

Data are presented as an average of the 2-year data set, withphotosynthetic pigments and osmolyte content, oxidative
stress indicators, and antioxidant enzyme activities, reported
as means of six replications, while chlorophyll fluorescenceparameters were reported as means of three replicates. The
data were subjected to analysis of variance (ANOVA) using
SAS Statistical software version 9.4. Multiple comparisonswere performed using the protected least significant difference(PLSD) test at the p < 0.05 level of significance. Excel 2017
and Sigmaplot 14.0 (Systat software) were used to create thefigures and conduct the regression analysis.

3 Results
3.1 The Effect of Salinity and Si Application
on Photosynthetic Pigments
The interaction effect of the Si treatments × salinity on chl
a, chl b, and CAR was significant (Fig. 1). Salinity caused asignificant (p < 0.05) reduction in photosynthetic pigments.
The pigments showed the highest decrease at the highest
salinity level. Their changes were minor at EC ≤ 6 dS ­m−1,
while beyond EC 6 dS m
­ −1 the rate of reduction increased.
Pooled across seasons chl a, chl b, and CAR decreased by
56.6, 64.2, and 57.5% respectively, at EC 12 dS ­m−1. Siapplication improved the resilience of chl a, chl b, and CAR
and resulted in reductions of 52.2, 59.7, and 53.9%, respectively. Priming was better than foliar spray at maintaining
chl a and CAR (Fig. 1a, c). The combination treatment was
the most successful strategy to minimize damage across all
photosynthetic pigments (Fig. 1a, b, c).

3.2 The Effect Of salinity on Chlorophyll
Fluorescence Parameters Under Si Application
Results showed that salinity affected CF parameters (except
ΦPSII and qP) differentially, depending on the Si application
method and the salinity level (Figs. 2, 3, and Table 4). Figure 2

Journal of Soil Science and Plant Nutrition (2023) 23:1678–1693

1683

shows the effect of Si application on FV/Fm, ΦPSII, qP, and ETR.
In Table 4, we present the regression coefficients of qN and NPQ
measured at different salinity levels as influenced by Si application. FV/Fm and ETR were altered by Si application and salinity, but there was no interaction. The highest values of FV/Fmand ETR were observed for foliar spray and the combination
treatment (Fig. 2a, b). The effect of priming on both parameters
was not different from the control. Values of FV/Fm and ETR
declined linearly in response to increasing salinity (Fig. 3). At asalinity of EC12 dS ­m−1, FV/Fm and ETR in leaves decreased by
7.2 and 23.2%, respectively. Like FV/Fm and ETR, priming had
no significant effect on ΦPSII and qP. Instead, foliar spray andcombination treatment increased ΦPSII and qP by an average of
15.2 and 25.9%, respectively (Fig. 2a). The non-photochemical
8-1

Chl a (mg gfw )

(a)
6
4
2

C, y = -0.0332x + 0.1819x + 4.5869, R² = 0.96
P, y = -0.0347x2 + 0.1608x + 5.746, R² = 0.98
F, y = -0.0348x2 + 0.2071x + 4.8251, R² = 0.96
P*F, y = -0.0364x2 + 0.177x + 6.1417, R² = 0.99

2
0

(b)

-1

Chl b (mg gfw )3
2
C, y = -0.0151x2 + 0.049x + 2.4718, R² = 0.95
P, y = -0.0132x2 + 0.026x + 2.6755, R² = 0.94
F, y = -0.0158x2 + 0.0539x + 2.6744, R² = 0.96
P*F, y = -0.0141x2 + 0.0285x + 2.8632, R² = 0.96

1

(c)

2.0

-1

CAR (mg gfw )

2.5

1.5

quenching parameters, qN and NPQ also exhibited a somewhat
similar pattern, showing significant differences across all salinity levels as affected by Si application method (Table 4). The qN
and NPQ derived from control and priming exhibited uniformchanges with increasing salinity so that the slope of their change
was between 0.3 and 1.5% per unit increase in salinity. The slopeof changes in qN and NPQ as affected by foliar spray and the
combination application was negative. Compared to the control
and priming, the foliar spray and combination treatment showed
the highest values of qN and NPQ at EC ≤ 6 dS ­m−1 (Table 4).
There was no significant difference (p > 0.05) between foliar
spray and combination treatment on qN and NPQ. At EC ≤ 6
dS ­m−1 and compared to the control and priming, qN and NPQ
increased by an average of 0.68- and 2.1-fold, respectively, by
foliar spray and combination treatment. The difference among
the application methods was lessened at EC > 6 dS ­m−1.

3.3 The Effect of Salinity on Osmolyte Content
Under Si application
Osmolyte content was significantly affected by salinity × Si
treatment (p < 0.05; Fig. 4). Soluble sugar and GB increased
and soluble protein decreased with increasing salinity(Fig. 4a). GB content for the control and Si treatments
increased up to EC 6 dS m
­ −1, beyond which it decreased. The
positive effect of Si treatments on GB content was observedat all salinity levels. Priming and combination treatment weremore efficient than foliar spray across all salinity treatments(P < 0.05). The change in slope of the soluble sugar content
of the control was such that it became 2.6-fold higher at EC
12 dS ­m−1 (Fig. 4b). Compared to the control, the response
trend of soluble sugar content to increasing salinity was
not changed by priming (p > 0.05). In contrast, foliar sprayand the combination treatment increased the soluble sugar
content at all salinity levels. The soluble protein content forthe control was reduced to less than half at EC 12 dS m
­ −1
(Fig. 4c). Si application increased the soluble protein content
at all salinity levels, with foliar spray and the combination
treatment having the greatest effects (Fig. 4b, c).

3.4 The Effect of Salinity on Oxidative StressIndicators Under Si Application

1.0
2C, y = -0.0046x - 0.007x + 1.2971, R² = 0.99
P, y = -0.0035x2 - 0.0286x + 1.6298, R² = 0.96
F, y = -0.0041x2 - 0.0184x + 1.459, R² = 0.99
P*F, y = -0.0059x2 - 0.0124x + 1.8421, R² = 0.97

0.5
0.0
0

2

4

6

8

10

12

-1

Salinity (dS m )Fig. 1  Changes in Chl a (a), Chl b (b), and CAR (c) as affected bydifferent salinity levels. Each plot point represents the mean ± SD.
Chl a, chlorophyll a; Chl b, chlorophyll b; CAR, carotenoid; C, Control; P, Priming; F, Foliar spray

EL% and MDA increased significantly (p < 0.05) withincreasing salinity (Fig. 5). The maximum accumulation in
EL% (84.3%) and MDA content (7.9 µmol ­g−1 FW) occurredin the control and was attained at the highest level of salinity (EC 12 dS ­m−1). The positive effect of Si application on
EL% and MDA occurred across all salinity levels (significant
interaction effect of the Si treatments × salinity, p < 0.05).
For all salinity levels, the combination treatment was themost effective at reducing EL% (Fig. 5a) and MDA content

13

1684

0.9
chlorophyll fluorescenceparameters

Fig. 2  The effect of treatments
on chlorophyll fluorescence.
Data is the mean (± SD) of
three replicates. Different lettersabove the data columns indicate
significant differences between
the samples determined by
ANOVA, PLSD test (p < 0.05).
Detailed information on each
CF parameter is presented inTable 2

Journal of Soil Science and Plant Nutrition (2023) 23:1678–1693

Fv/Fm
b

qP

ΦPSII
b

a)

a

a

0.8

a

a

0.7
b

0.6

b

a

a
b

0.5

b

0.4
32

b)

a

a

foliar spraypriming*foliar
spray

30

ETR

28
26

b
c

24
22
20

priming

Treatments

0.9

32

Fv/Fm, y = -0.0053x + 0.8679, R² = 0.9648
ETR, y = -0.61x + 29.978, R² = 0.9719

0.88

30

0.86

28

0.84

26

Fv/Fm

Fig. 3  Changes in Fv/Fm andETR as affected by different
salinity levels. Each plot point
represents the mean ± SD.
Detailed information on each
CF parameter is presented inTable 2

0.82
0.8
0

13

24

Fv/Fm
ETR
2

22
4
6
8
Salinity (dS m-1)

10

12

ETR

controlJournal of Soil Science and Plant Nutrition (2023) 23:1678–1693

1685

Table 4  Regression coefficients between CF parameters and salinity as affected by Si treatments and control
CF

Si treatments

parameter

ControlPriming

Foliar spray

P×F

qN
NPQ

y = 0.0086x + 0.3456
y = 0.0154x + 0.5318

y = 0.003x + 0.358
y = 0.0087x + 0.5727

y =  − 0.0247x + 0.7094
y =  − 0.1154x + 1.7107

y =  − 0.0291x + 0.7244
y =  − 0.1066x + 1.6892

Detailed information on each CF parameter is presented in Table 3-1

Glycine betaine (mg dw )

4

2

-1

Soluble sugar (µg gfw )C, y = -0.0347x2 + 0.537x + 0.6882, R² = 0.76
2P, y = -0.0429x + 0.6577x + 0.6193, R² = 0.91
F, y = -0.0377x2 + 0.5671x + 0.7585, R² = 0.77
2
P*F, y = -0.0431x + 0.6616x + 0.7357, R² = 0.92

1

5

(b)

4
3
2

C, y = 0.2155x + 1.5509, R² = 0.90
P, y = 0.2088x + 1.5839, R² = 0.90
F, y = 0.2512x + 2.049, R² = 0.90
P*F, y = 0.2489x + 2.0466, R² = 0.92

1
0

-1

(a)

3

0

Soluble protein (mg fw )3.5 The Effect of Salinity on Antioxidant Enzyme
Activities Under Si Application

1.2

3.6 The Effect of Salinity and Si Application
on Growth Characteristics

(c)

1.0
0.8
0.6
0.4

C, y = -0.0623x + 0.9134, R² = 0.91
P, y = -0.0591x + 0.947, R² = 0.92
F, y = -0.0802x + 1.1439, R² = 0.93
P*F, y = -0.0764x + 1.1766, R² = 0.92

0.2
0.0

0

CAT and SOD activities were significantly affected (p < 0.05)
by salinity (Fig. 6), while the interaction effect of the Si treatments × salinity was significant only for APX activity (Fig. 7).
Salinity increased CAT and SOD activities with the highest
enzyme activities occurring at EC 12 dS m
­ −1 where SOD
was increased fourfold and CAT by 2.5-fold (Fig. 6). In thecontrols APX activity initially increased up to EC5 dS m
­ −1
after which there was a significant (p < 0.05) decrease. All Si
treatments caused an increase in APX activity across all salinity levels, with the biggest increases being for the combination
treatment (Fig. 7). The Si treatments also caused a significant
increase in CAT and SOD activities (excluding priming on
SOD, Table 5). The combination treatment caused the greatest
increases in CAT and SOD activity. Priming, foliar spray, andthe combination treatment increased the CAT activity by 12.3,
10.5, and 21.4%, respectively, and increased SOD activity by
0.5, 8.3, and 10%, respectively (Table 5).

2

4

6

8

10

12

-1

Salinity (dS m )Fig. 4  Changes in glycine betaine, soluble sugar, and soluble protein
as affected by different salinity levels. Each plot point represents themean ± SD. C, Control; P, Priming; F, Foliar spray(Fig. 5b). For the combination treatment and at EC 12 dS­m−1, the MDA content was reduced by 3 and 31% more thanthe priming and foliar spray, respectively (Fig. 5b).

The interaction effect of the Si treatments × salinity on shootlength and shoot dry weight was significant (p < 0.05; Fig. 8).
A significant decrease was observed for both characteristics
with increasing salinity. The declining slope was steeper forshoot dry weight. The shoot dry weight and length declined toless than 50% of their initial value at EC > 12 and EC 5 dS m
­ −1,
respectively. These reductions were moderated with Si treatments at all salinity levels. The declining slope was reduced
for shoot length by Si treatments particularly priming with a
12% reduction (Fig. 8a). Moreover, shoot length driven from Si
treatments was more than the control shoot length at all salinity
levels, especially at higher salinity. Among Si treatments, thecombination treatment was the most effective (Fig. 8a). In spiteof been steepened the declining slope of shoot dry weight by
Si treatments, its values increased. Furthermore, the effect ofSi treatments was greater at low salinities. For instance, at EC
0 dS m­ −1, the shoot dry weight increased by 4.3, 6, and 11.3
units with priming, foliar spraying, and combination treatment,
respectively. While at EC 12 dS ­m−1, it increased by 0.58, 0.29,
and 2.3 units with mentioned treatments, respectively (Fig. 8b).

13

1686

Journal of Soil Science and Plant Nutrition (2023) 23:1678–1693

Fig. 5  Changes in EL and
MDA as affected by different
salinity levels. Each plot point
represents the mean ± SD. EL,
electrolyte leakage; MDA,
malondialdehyde; C, Control; P,
Priming; F, Foliar spray

EL (%)

100

C, y = 3.1836x + 44.292, R² = 0.95
F, y = 3.4317x + 40.29, R² = 0.94
P, y = 2.6015x + 43.8, R² = 0.91
P*F, y = 0.2257x2 - 0.0138x + 43.627, R² = 0.98(a)C, y = 0.5012x + 2.0488, R² = 0.94
F, y = 0.5057x + 1.4417, R² = 0.97
P, y = 0.3314x + 1.2044, R² = 0.94
P*F, y = 0.3704x + 0.5275, R² = 0.96

(b)

80
60
40

-1

MDA (µmol g FW)

10
8
6
4
2
0

0

2

4

6

8

10

12

Salinity (dS m-1)
4 Discussion
Salinity caused a significant reduction in photosynthetic
pigments. This reduction has also been reported in Phaseolus vulgaris L. (Taïbi et al. 2016) and on Cucurbita pepo
L. (Siddiqui et al. 2014). The reduction in chlorophyllin salinity-stressed plants has been considered a typicalsymptom of oxidative stress and may be attributed to theinhibition of chlorophyll synthesis, together with the degradation caused by the enzyme chlorophyllase (Hanin et al.
2016). Decreased chl a due to salinity might be the main
reason for the decrease of PSII exciting capacity (Oxborough 2004). As such, chlorophyll content can be a usefultrait to measure the salinity tolerance of a plant (Saddiq
et al. 2019). Reduced chlorophyll, as a result of either slow
synthesis or fast breakdown, indicates a possible activation

13of the photoprotection mechanism through reducing lightabsorbance (Taïbi et al. 2016). Previously, Muneer et al.
(2014) demonstrated that the application of Si as a nutrient solution helped to prevent the degradation of photosynthetic pigments in Solanum lycopersicum L. In rice,
Si applied as a nutrient solution alleviated the salinityinduced deficiency of N and increased chlorophyll content(Ávila et al. 2010). At lower N levels, Si treatment tended
to increase the transcript levels of certain genes involvedin N uptake and assimilation, potentially identifying a
feedback response mechanism operating under reduced N
availability. Kochanová et al. (2014) concluded that under
the presence of Si, maize reacted fast to salt stress and its
answer to high salt stress is to supply the plant body with
N substances (by increasing the ammonia assimilation),
necessary for its survival.

CAT, y = 0.33x + 3.4986, R² = 0.9929
SOD, y = 12.642x + 25.948, R² = 0.9118

8.4

CAT activity (mM gFW-1
min-1)

Fig. 6  Changes in CAT and
SOD as affected by different
salinity levels. Each plot point
represents the mean ± SD. CAT,
catalase; SOD, superoxide
dismutase

1687

7.5

165

6.6

136

5.7

107

4.8

78

3.9
0

-1

-1

APX (mM gFW min )

49

CAT
SOD

3

Fig. 7  Changes in APX as
affected by different salinity levels. Each plot point represents
the mean ± SD. APX, ascorbate
peroxidase. C, Control; P, Priming; F, Foliar spray

194

2

4
6
8
Salinity (dS m-1)

10

SOD activity (units gFW-1)

Journal of Soil Science and Plant Nutrition (2023) 23:1678–1693

20
12

4
3
2
1
C, y = -0.0362x2 + 0.2147x + 2.5415, R² = 0.94
P, y = -0.0316x2 + 0.1845x + 2.9043, R² = 0.87
F, y = -0.0554x2 + 0.4264x + 2.6351, R² = 0.92
P*F, y = -0.051x2 + 0.3957x + 2.9572, R² = 0.89

0
-1
0

2

4

6

8

10

12

Salinity (dS m-1)
Table 5  Effect of Si treatments
and control on CAT (catalase)and SOD (superoxide
dismutase) activities

EnzymeCAT​
SOD

Si treatments
ControlPriming

Foliar spray

P×F

5.02 ± 0.81c
100.69 ± 34.22b5.64 ± 0.83b
101.19 ± 30.60b5.54 ± 0.88b
109.02 ± 26.11a

6.09 ± 0.90a
110.75 ± 16.20a

Different letters indicate a significant difference (p < 0.05) among the four treatments according to the
PLSD. The values are mean ± SD

13

1688

Journal of Soil Science and Plant Nutrition (2023) 23:1678–1693

40

Fig. 8  Changes in shoot lengthand dry weight as affectedby different salinity levels.
Each plot point represents themean ± SD. C, Control; P, Priming; F, Foliar spray(a)

Shoot length (cm)

35
30
25
C, y = -1.3401x + 34.471, R² = 0.96

20P, y = -1.1847x + 36.78, R² = 0.92
F, y = -1.2461x + 35.209, R² = 0.99

1560

P*F, y = -1.2322x + 37.816, R² = 0.95

(b)Shoot dry weight (g)

50
40
30
20
10

C, y = -3.5462x + 41.909, R² = 0.95

0F, y = -4.2606x + 50.928, R² = 0.94

P, y = -4.0818x + 49.217, R² = 0.94

P*F, y = -4.4232x + 55.727, R² = 0.97

0

2

4

6

8

10

12

Salinity (dS m-1)
CF parameters can detect small changes in photosynthetic activity and have been broadly used as a tool to study
both abiotic and biotic stress responses in rice (Faseela
et al. 2020), lettuce (Shin et al. 2020), and sweet pepper(Alkahtani et al. 2020). Fv/Fm reflects the maximum lightenergy conversion efficiency of PSII after adaptation to darkness, hence photoinhibition reflects the efficiency of lightenergy conversion in the active center of PSII (Adhikari
et al. 2019). In the current study, salinity stress caused asignificant decrease in Fv/Fm. This may be due to salinity
inhibiting electron transport, damaging the reaction centers

13

at the PSII sites as well as the oxygen-evolving complex.
Our results were consistent with a study on sweet pepperthat also showed a reduced Fv/Fm in response to salinity(Alkahtani et al. 2020). Our results demonstrated that theapplication of Si as either foliar or combination treatment
caused a significant increase in Fv/Fm in salinity-stressed
plants. Li et al. (2018) concluded that the improvement of
Fv/Fm by Si was likely via the Si-induced protection of the
PSII electron transfer chain as well as the promotion of lightutilization efficiency. The salinity-induced reduction in ETR
is thought to be caused by photochemical downregulation

Journal of Soil Science and Plant Nutrition (2023) 23:1678–1693(Perez et al. 2014). Our demonstrated foliar and combination
Si-mediated increase in ETR suggests an improved capacity
to convert photon energy into chemical energy.
ΦPSII and qP are typically known as photochemical
quenching parameters. ΦPSII accounts for the efficiency oflight use for electron transport by PSII and the principal
factor assessing this efficiency is the ability of photosynthetic system to remove electrons from the quinone acceptors of PSII (Faseela et al. 2020). Photochemical quenchingof PSII under light conditions indicates the proportion ofreaction centers that are open and is used to indicate thephotoinhibition and determine the level of photoprotective
quenching of fluorescence (Shin et al. 2021). In the current
study, ΦPSII and qP had uniform reductions with increased
salinity. In contrast, Shin et al. (2020) found that in lettuce
ΦPSII and qP had the highest reductions only at the highest
NaCl concentration. Our research shows that Si applied aseither a foliar spray or a combination treatment increased
ΦPSII and qP.
The slope of qN and NPQ in response to increasing salinity was positive for the control and primed plants but negative for plants treated with either foliar spray or combination
treatment. qN estimates the rate constant for heat loss from
PSII. Increasing qN and NPQ indicates the enhancementof the thermal energy dissipation through the xanthophyll
cycle (Shin et al. 2021). The decrease they observed at thehighest NaCl concentration (400 mM) implies photo-oxidative damage and that ROS were being generated in thechloroplasts (Shin et al. 2020). Our results suggest that Si
application particularly in form of foliar spray and combination treatment could decrease salinity-induced damage to
the PSII. Si leads to increased efficiency of PSII by reducing oxidative damage (Dhiman et al. 2021). Si regulates
photosynthesis-related proteins during stress and increases
antioxidant enzyme activity (Dhiman et al. 2021). Further
studies involving chloroplast proteomic expression analysis have shown that light-harvesting complexes (LHCs) are
upregulated, cytochrome b6f (Cytb6f), and ATP-synthase
complex reduction is mitigated in Si- and salt-treated tomato
plants (Dhiman et al. 2021).
Stress-induced accumulation of GB, soluble sugars
and proteins act to protect the cell by maintaining theosmotic strength of cytosol with that of the vacuole andthe external environment (Soni et al. 2021). This study
showed that salinity triggered the accumulation of GB,
possibly as an adaptive response. Similar responses
have been demonstrated in sunflower exposed to salineconditions (Akram et al. 2012). The increase in soluble sugars that we observed in response to salinity has
also been demonstrated in barley, water dropwort, andrice (Hassan et al. 2021; Paul et al. 2017; Soni et al.
2021). Increased concentrations of soluble sugars may
be due to the higher enzymatic activities that help in the

1689

regulation of cellular structures and functions throughthe interaction with macromolecules (Ibrahimova et al.
2019). Results of the current study showed that the soluble protein content decreased significantly with increasing salinity. Similar observations have been reported by
Migahid et al. (2019) on Silybum marianum (L.) plants
and Jaleel et al. (2008) on Catharnathus roseus seedlings. In durum wheat which is considered a more salinity-tolerant crop (Katerji et al. 2005), Soni et al. (2021)
showed an increase in the soluble protein content in bothroots and shoots in response to salinity. Excess accumulation of ­Na + in plants results in the production of ROS
which alters plants’ metabolism by causing oxidative
stress and protein degradation. Salt stress downregulates
proteins due to a decrease in the expression of genes
involved in the metabolic pathway, signal transduction,and gene regulation (Dhiman et al. 2021).
It is well documented that increased accumulation ofosmolytes plays a significant role in the protection of various
vital enzymes, membranes, and proteins in the plant cells or
tissues having a key role in scavenging ROS. In line with our
results, Gong et al. (2005) showed that the application of Si
improved soluble protein content and protein synthesis andmetabolism in wheat under drought stress.
We found a general increase of EL% in salt-stressedborage, which suggests the occurrence of cell membrane
damage (Chiconato et al. 2021). In salinity stressed barley
EL% also increased (Hassan et al. 2021). Salinity causes
both cell membrane permeability increases and selectivity decreases, increasing EL% (Hanin et al. 2016; Negrão
et al. 2017). The reduction in EL% through the application of Si as either a foliar spray or combination treatment has also been demonstrated in salinity-stressed capsicum (Manivannan et al. 2016). Our results indicated anincrease in MDA under saline conditions also indicates
oxidative damage to membrane lipids (Rios et al. 2017).
In line with our results, Rios et al. (2017) reported thatsalinity-induced increased MDA was significantly lowered by Si treatment. The borage plants treated with Si
showed improved cell membrane stability with decreased
formation of MDA in leaves. Dhiman et al. (2021) statedthat Si-mediated salinity tolerance was conferred by anincreased level of ­H+-ATPase in roots and SOD in leaves,and a reduced EL% and content of MDA in leaves.
The antioxidative enzymatic system in plants has
an efficient ROS scavenging strategy to maintain thesteady-state levels of ROS in cells. Higher antioxidant
enzyme activity has a role in imparting stress tolerance(Riasat et al. 2018). In this experiment, the activities
of CAT, APX, and SOD in borage leaves were significantly upregulated under salinity (except APX at EC > 5
dS ­m−1). The Si treatments also increased their activity.
Increased SOD activity under saline conditions occurs

13

1690

because it converts O­ 2 into H­ 2O2. However, CAT, one of
the most potent catalysts known, decomposes H­ 2O2 into
water and oxygen (Debona et al. 2017). The combined
activity of these two enzymes in borage under salinity
can be used as an indicator of tolerance. The beneficial
effect of the Si treatments in borage may be partially
due to enhanced CAT, APX, and SOD activity. Undersalinity, Si significantly increased the activity of antioxidant enzymes GPX and APX, suggesting that Si may
also be involved in metabolic or physiological activities (Abdelaal et al. 2020). Our results are in agreementwith salinity-stressed bugwang and sweet pepper where
Si also prevented oxidative damage by up-regulating theactivities of antioxidant enzymes (Abdelaal et al. 2020;
Manivannan et al. 2016). Furthermore, Haghighi and
Pessarakli (2013) showed that salt-stressed plants treatedwith Si have shown increased chlorophyll content, leaf
photosynthetic activity, decreased permeability of plasma
membranes, and maintenance of cell form and structure
due to the increased antioxidative enzymes SOD andCAT. Totally, Si supplementation is considered one ofthe promising methods to improve plant resilience undersalt stress. Si supplementation affects the phytohormonaland antioxidant responses under salinity as a key factor
defining improved resilience (Dhiman et al. 2021).
It is generally accepted that the first symptom ofsalt-stressed plants is a reduction in growth (Ouzounidou et al. 2016), as demonstrated here with borage. The
salinity leads to hormones-induced sequential reactions,which can diminish the stomatal opening, ­CO2 assimilation (Sarker and Oba 2020), increase leaf chlorosis, premature senescence (Polash et al. 2019), and ultimately,a declined photosynthetic rate and growth (Kumar et al.
2021; Subramanyam et al. 2019). Another reason for the
reduction in growth characteristics might be the diversionof energy from growth and yield to the homeostasis ofsalinity stress, production of antioxidants, and action ofantioxidant enzymes (Kumar et al. 2021; Sarker and Oba2020). However, when our Si treatments were applied
to borage, particularly combination treatment, there wasa higher plant shoot dry weight and length. There weresome potential mechanisms of Si to increase plant tolerance to stress. It has been proposed that under stressconditions, Si modifies cell wall metabolism to enhancetissue extensibility and remain horizontal delaying thesenescence of leaves, increasing leaf content of chlorophyll and activity of ribulose-bisphosphate carboxylase(Ouzounidou et al. 2016). Furthermore, Si decreases thepermeability of cell plasma membranes, increasing membranes stabilities and reducing inorganic leakage (i.e.,EL) that resulted from increased activities of enzymaticand non-enzymatic antioxidants can become an important assistant mechanism (Merwad et al. 2018).

13

Journal of Soil Science and Plant Nutrition (2023) 23:1678–1693

5 Conclusion
The results of this study confirm that salinity causes a significant reduction in the photosynthetic pigments, chlorophyll fluorescence parameters, and growth characteristics
and also increases the ROS production within the cell. Our
results also demonstrated oxidative stress with an increase in
EL% and MDA content. In response to salinity, borage produced osmolytes and increased the production of antioxidant
enzymes, however, these responses were insufficient to prevent
damage. The application of Si treatments to salinity-stressedborage reduced damage and improved tolerance, as evidenced
by improved concentrations of photosynthetic pigments, chlorophyll fluorescence parameters, osmolyte content, and activities
of antioxidative enzymes. Si treatments also caused a decreasein EL% and MDA content and increases in Fv/Fm and ΦPSII.
The most effective method of Si application was the priming × foliar spray treatment. The results of this study suggestthat Si application may be an option to improve the growth andyield of borage growing under saline conditions with potential
applications for other crops grown in saline conditions. To further studies, it would be interesting to have deep look at the role
Si plays in cellular defense or cell wall protection.
Author Contribution All authors contributed to the study’s conception
and design. Material preparation, data collection, and analysis were
performed by Faride Feghhenabi, Hashem Hadi, and Habib Khodaverdiloo. The first draft of the manuscript was written by Faride Feghhenabi and all authors commented on previous versions of the manuscript.
All authors read and approved the final manuscript.
Data Availability The datasets generated during and/or analyzed during the current study are available from the corresponding author upon
reasonable request.

Declarations
Conflict of Interest The authors declare no competing interests.

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