Zinc and potassium fertilizer recommendation for cotton seedlings under salinity stress based on gas exchange and chlorophyll fluorescence responses

South African Journal of Botany 130 (2020) 155
164

Contents lists available at ScienceDirect

South African Journal of Botany journal homepage: www.elsevier.com/locate/sajb

Zinc and potassium fertilizer recommendation for cotton seedlings under salinity stress based on gas exchange and chlorophyll fluorescence responses Zahra Hatama, Mohammad Sadegh Sabetb,*, Mohammad Jafar Malakoutia, Ali Mokhtassi-Bidgolic, Mehdi Homaeed a

Department of Soil Science, Tarbiat Modares University, Tehran 14115-336, Iran Department of Plant Genetics and Breeding, Faculty of Agriculture, Tarbiat Modares University, Tehran 14115-336, Iran Department of Agronomy, Faculty of Agriculture, Tarbiat Modares University, Tehran 14115-336, Iran d Department of Irrigation and Drainage, Tarbiat Modares University, Tehran 14115-336, Iran b c

A R T I C L E

I N F O

Article History: Received 28 November 2018 Revised 7 November 2019 Accepted 22 November 2019 Available online xxx Edited by KI Ananieva Keywords: Non-photochemical quenching Photosynthesis rate Stomatal conductance Transpiration rate Yield of photosystem II photochemistry

A B S T R A C T

Cotton is typically grown in warm regions in which salinity and nutrient deficiency stresses are ubiquitous and often simultaneously influence plant growth. Under saline conditions, fertilizer recommendation is highly challenging, since nutrient application may increase or decrease plant salt tolerance, which may complicate prediction of crop yield. So far, no investigations have been conducted in salt-affected soils to determine optimum concentrations of potassium (K) and zinc (Zn) fertilizers based on chlorophyll fluorescence (ChlF) and gas exchange (GEx) responses in upland cotton (Gossypium hirsutum L.). Accordingly, in this study, a factorial experiment was conducted in a complete block design with six replicates under controlled conditions. Treatments included various K2SO4 (0, 50, 100, and 150 kg ha
1), and ZnSO4 (0, 50, and 100 kg ha
1) concentrations applied to soil before planting. Cottonseeds were sown in non-saline soils and soils formerly salinized with natural saline water diluted to 15 dS m
1. One month after sowing, results showed that salinity significantly decreased dry weight, chlorophyll content index, photosynthesis rate (A), leaf to air vapor pressure, transpiration rate (E), stomatal conductance, and minimum fluorescence of dark-adapted leaf, but increased root to shoot ratio (R/Sh). Under salinity, combined application of K and Zn boosted physiological properties including yield of photosystem II photochemistry (KPSII), A, and E without improving biomass. Combined application of K and Zn at highest concentrations decreased R/Sh by 93% compared to the control. Rate of increase was higher in E than that of A leading to reduction in water use efficiency. High Zn concentration in saline soils increased non-photochemical quenching and energy loss in form of heat. Under nonsaline condition, Zn application significantly decreased A probably due to inhibitory effect on electron transfer within photosystem II. K significantly increased stomatal conductance and accordingly E. GEx parameters were more sensitive to used treatments than ChlF parameters. Based on GEx and ChlF responses, the most salt-tolerant cotton seedlings were obtained under combined application of 50 kg K2SO4 ha
1 and 50 kg ZnSO4 ha
1, thus these concentrations are recommended for optimal establishment of cotton seedlings under salinity stress. © 2019 SAAB. Published by Elsevier B.V. All rights reserved.

1. Introduction Soil and water salinity is a global problem annually imposing huge damages to agricultural ecosystems. According to statistics, approximately 20% of cultivated and 33% of irrigated agricultural lands are subjected to salinity stress (Shrivastava and Kumar, 2015).

* Corresponding author. E-mail addresses: [email protected] (Z. Hatam), [email protected] (M.S. Sabet), [email protected] (M.J. Malakouti), [email protected] (A. Mokhtassi-Bidgoli), [email protected] (M. Homaee). https://doi.org/10.1016/j.sajb.2019.11.032 0254-6299/© 2019 SAAB. Published by Elsevier B.V. All rights reserved.

Moreover, saline regions are annually extending by almost 10% as a result of climate change (e.g., low precipitation and high evaporation), and inefficient management (e.g., excessive exploitation of underground water resources and poor farming practices). It is predicted that more than 50% of arable lands will be salinized by 2050 (Jamil et al., 2011). According to a research conducted in California, annual costs caused by losses of agricultural production will increase to 1.7
7.0 billion dollars by 2030 (Schuler et al., 2018). Indeed, soil salinity is a serious abiotic constraint to plant growth and crop production. It can reduce root water uptake and induce physiological drought in plants (Homaee and Schmidhalter, 2008;

156

Z. Hatam et al. / South African Journal of Botany 130 (2020) 155
164

Abbreviations DW R/Sh GEx CCI

dry weight [g plant
1] root to shoot ratio gas exchange

A gs E WUE

photosynthesis rate [mmol CO2 m s ] stomatal conductance [mol CO2 m
2 s
1] transpiration rate [mmol H2O m
2 s
2] water use efficiency [AE; mmol CO2 mmol H2O
1] leaf to air vapor pressure [kPa] chlorophyll fluorescence; Photosystem II minimum and maximum fluorescence of dark-adapted leaf variable fluorescence of dark- and lightadapted leaf [(Fm-F0); (Fm0 -F00 )] minimum and maximum fluorescence of light-adapted leaf maximal photochemical efficiency of darkand light-adapted leaf steady state chlorophyll fluorescence yield of PSII photochemistry [(Fm0 -Fs0 )/Fm0 ] non-photochemical quenching [(Fm-Fm0 )/Fm0 ]

VPD ChlF; PSII F0, Fm Fv, Fv0 F00 , Fm0 Fv/Fm, Fv0 /Fm0 Fs0 KPSII NPQ

chlorophyll content index [%% Transpiration Transpiration
2

931 mn 953 mn]


1

Evelin et al., 2009). Excessive accumulation of ions such as Na+ in plants can cause ion toxicity (Hasana and Miyake, 2017). Furthermore, nutrient deficiency or nutritional imbalance is another deleterious influence of salinity on plant growth and development due to competition between Na+ and Cl
with nutrients such as K+, Ca+2 and NO3
(Hu and Schmidhalter, 2005; Esmaili et al., 2008). Salinity may also contribute to production of reactive oxidative species causing oxidative damages in plants (Gupta and Huang, 2014). Macro- and micronutrients are essential for optimal growth and development of crops. Upon nutrient uptake by plants, soils are gradually depleted from nutrients. Therefore, for sustainable crop production, it is essential to apply nutrients to soils according to requirements of the plants. However, all existing fertility models (Mitcherlich-Baule or Liebig-sprengel) have been developed only for non-saline conditions, and they cannot be used for saline soils (Pessarakli, 1994). To obtain a certain designated yield in a given crop, it should be mentioned that nutrient requirements are not the same under saline and non-saline conditions. Under salinity stress, fertilizer recommendation is highly controversial, because nutrient application may increase or decrease plant salt tolerance and crop production. When both salinity and nutrient deficiency reduce plant growth at the same rate, a decrease in the salinity stress by increasing nutrient levels can enhance crop yield. However, when fertility is the most limiting factor, fertilization may enhance plant salt tolerance. But once salinity serves as dominating limit, fertilization may impose even further osmotic potential and reduce plant growth (Grattan and Grieve, 1998). Obviously, such inconsistency in crop yield prediction is a significant constrain to sustainable farming. In the absence of fertility models originally developed for saline conditions, robust qualitative investigations are pivotal to help farmers detect early responses of plants to stresses (e.g., salinity and nutrient deficiency) and applied treatments. Malfunction in gas exchange (GEx) and photosynthesis are the first responses of plants to environmental stresses. Despite some responsive physiological mechanism, no symptoms may come early into sight. However, some symptoms such as wilting, chlorosis, and necrosis often accompanied with non-compensable yield losses may later appear. Therefore, early detection of stresses by monitoring physiological properties would be more helpful than studying morphological

properties to manage stresses and prevent yield losses (Hazrati ~o et al., 2017). In this regard, chlorophyll fluoreset al., 2016; Negra cence (ChlF) and GEx parameters have been widely assessed for detection of salt stress. Reduction in net photosynthesis, stomatal conductance, internal CO2 concentration, efficiency of light harvesting of photosystem II, and photochemical quenching have been reported under salinity stress in different plant species (Huang et al., 2016; Kalaji and Pietkiewicz, 1993; Kalaji et al., 2011, 2016; Melgar et al., 2009; Penella et al., 2016). Enhancement in water use efficiency under salinity stress has been reported for cotton (Zhao et al., 2015) due to increased water uptake as a result of aquaporin formation and reduced transpiration rate. Likewise, many studies have been carried out on the influences of nutrient application on GEx and ChlF parameters. However, there are only few studies considering interaction effects of salinity and nutrients on GEx and ChlF parameters, although plants are often influenced simultaneously by these stresses especially in arid and semiarid regions. Because saline soils and waters are found more abundantly and ubiquitously in these climates, in comparison with other regions (Gleick, 1993). In addition, due to low organic carbon content of the soil, higher carbonate concentration and soil pH, along with antagonistic interaction between nutrients and Na+, Cl
, soil nutrient availability is low and plants are subjected to combined stresses e.g., nutrient deficiency and salinity. Therefore, plants might be inevitably subjected to stresses from germination stage. Germination and seedling stages are the most significant and determining growth stages. Crop yield and resource use efficiency depend on successful plant establishment in the field. Salt-induced loss of seeds and seedlings undoubtedly leads to noncompensable yield reduction even upon optimal management in further growth stages (Finch-Savage and Bassel, 2015). Cotton (Gossypium hirsutum L.) is a strategic cash crop typically cultivated in arid and semi-arid regions (Isaacman and Roberts, 1995). Generally, farmers cultivate cottonseeds in the field and irrigate the crop with available water (Rochester and Peoples, 2005). Therefore, if saline water is the only available source for irrigation, cotton plants will be inevitably subjected to salinity stress from germination stage. In almost all investigations on the influence of salinity stress on ChlF and GEx parameters in cotton, experimental designs have not resembled real conditions encountered by the farmers in the fields. In fact in these studies, seed germination and seedling emergence have been processed under nonsaline conditions and seedlings continued to grow within nonsaline Hogland solutions. After a while, seedlings are subjected to salinity stress using synthetic NaCl solution imposing more stress to the plant than natural saline water (Kalaji et al., 2016; Saadat et al., 2005; Zhang et al., 2014). Obviously, plant responses to salinity and nutrition depend on culture medium (i.e., soil or hydroponic), plant age at the time of exposure to salinity stress (i.e., germination or seedling), along with source of salinity stress (i.e., natural saline water or synthetic NaCl solutions) and nutrients (e.g., common fertilizers used by farmers or Hogland solutions). So far, a comprehensive study has not been conducted to investigate separate and combined influences of pre-planted potassium (K) and zinc (Zn) fertilizers applied to soil on ChlF and GEx parameters in cotton seedlings exposed to natural saline water from germination stage. Furthermore, determination of optimal K and Zn concentrations is challenging under salinity stress for better establishment of cotton at early growth stage. Because, the plant may respond quite inconsistently, and its salinity tolerance may increase or decrease under nutrient application. Therefore, this research was conducted to address existing gaps and recommend optimal concentrations of these nutrients mainly based on GEx and ChlF responses of the cotton. Indeed, findings of this study can be helpful in improving our perceptions towards some physiological mechanisms and plant strategies regulated by K and Zn for survival under saline conditions.

Z. Hatam et al. / South African Journal of Botany 130 (2020) 155
164

2. Materials and methods

157

Table 2 Some chemical properties of natural saline water before dilution.

2.1. Plant material and treatments

pH

A factorial experiment was conducted in a complete block design with six replicates in a research greenhouse located in the Faculty of Agriculture at Tarbiat Modares University, Tehran, Iran. One salinity treatment (15 dS m
1) besides control treatment, four K2SO4 concentrations (0, 50, 100, and 150 kg ha
1), and three ZnSO4 concentrations (0, 50, and 100 kg ha
1) were considered as main factors. A sandy soil was used in this experiment. Some of soil physicochemical properties are given in Table 1. Natural saline water was provided from Cheshmeh-Shour Spring (35° 50 10.400 N; 50° 590 14.8500 E; 790 m above sea level) and diluted to 15 dS m
1. Some chemical properties of saline water before dilution is shown in Table 2. Delinted seeds of upland cotton (Gossypium hirsutum L., cv. Varamin), were provided from Cotton Research Institute of Iran. An amount of 43 kg of sandy soil was placed within 48-cell plastic trays. Each cell had a dimension of 5.5 £ 5.5 £ 6.5 cm in length, width, and depth, respectively. Soils were washed five times with saline water. Electrical conductivity (EC) of drained water was measured using a conductivity meter (Jenway 4520, Bibby Scientific US, Burlington, USA) to make sure that EC of soil is similar to EC of saline water (15 dS m
1). To prevent nutrient deficiency stress, N, P, Fe, Mn, and Cu fertilizers were equally applied pre-planting to all cells based on soil test. Then, K and Zn fertilizers were applied using K2SO4 and ZnSO4. Fertilizers were dissolved in distilled water and were applied to soils by pipetting before planting. Then, cottonseeds were sown at a depth of 2 cm. Soil moisture was kept at field capacity using distilled water. Over the entire experiment, no water was drained from bottom of cells and no further salinity was applied. Therefore, there was no salt gain or loss besides uptake by the plants. 2.2. Physiological parameters Plants were grown under 14:10 h light/dark cycles. Air humidity and temperature in the greenhouse were measured using SHT75 (Sensirion, Switzerland). Air humidity was equal to 50
55% during the day and it declined to 40
45% at night. Furthermore, temperature was equal to 25 § 2 °C and 18 § 2 °C during the day and night, respectively. Light intensity was determined using TLS2550 (Taos, USA). Maximum light intensity was 1400
1500 mmol photons m
2 s
1 from 11:00 a.m. to around 1:00 p.m. in July during which measurements were taken. Position of cultivation trays in the greenhouse was changed weekly to reduce any effects of localized variation in light intensity and air temperature. GEx and ChlF measurements were taken one month after planting. GEx parameters were measured using an infrared, open GEx system LI-6400 (Li-Cor, Inc., Lincoln, NE, USA). The LI-6400 leaf chamber area was 6 cm2. Within measuring chamber, the following conditions were maintained: leaf temperature of 35 °C, reference CO2 content of 350 mmol CO2 mol
1, and photosynthetic active radiation (PAR) of 550 mmol photons m
2 s
1. IRGA (infra-red gas analyzer) was manually adjusted and levels of reference CO2 and reference H2O became stable before performing the measurements. A leaf with proper size was initially clamped in the leaf chamber and after about 3 min, when assimilation rate shown on Li-Cor monitor was stabilized; photosynthetic rate

8.1

EC (dS m
1)

SO42


196

176

Cl


CO32


HCO3
(mmolc L

1388

5.5

54

K+

Mg2+

Ca2+

Na+

142

128

1313


1

)

2.9

(A), transpiration rate (E), leaf stomatal conductance (gs), and leave to air vapor pressure deficit (VPD) were measured (Skillman, 2008). Water use efficiency (WUE) was calculated as ratio between A to E (Kalaji et al., 2011). ChlF parameters were measured using a portable chlorophyll fluorometer (MINI-PAM, Walz, Effeltrich, Germany) equipped with a standard 2030-B leaf clip holder (Rascher et al., 2000) according to the protocol described by Kumari et al. (2005). For dark adaptation, the leaf sample was held in leaf-clips by closed shutter for 30 minutes. Afterwards, 30 min dark-adapted minimum (F0), and maximum (Fm) chlorophyll fluorescence were measured. To induce the F0 level, the pulses (0.15 mmol photons m
2 s
1 PAR) were set at 3 ms long and were repeated at a frequency of 600 Hz. Fm was determined using a 0.8 saturation light pulse (18,000 mmol photons m
2 s
1 PAR). Afterwards, photosynthesis was activated by an actinic light source with 550 mmol photons m
2 s
1 intensity. To measure light-adapted maximum fluoresce (Fm0 ) and steady state (Fs0 ) fluorescence, chlorophyll was excited by saturating light pulses from light-emitting diodes for 0.8 s (650 nm, 18,000 mmol photons m
2 s
1 PAR). The light adapted minimum fluorescence (F00 ) was measured when actinic light was turned off (Hazrati et al., 2016). In all measurements, data were recorded when chlorophyll fluorescence parameters became stable. Then, maximal photochemical efficiency of dark- and light-adapted leaves (Fv/Fm; Fv0 /Fm0 ), yield of PSII photochemistry (KPSII), and non-photochemical quenching (NPQ) were calculated according to the following formulas (Kalaji et al., 2017a, 2017b, 2017c):
FPSII ¼ Fm0
Fs0 =Fm0
0 0 NPQ ¼ Fm
Fm =Fm The CCM-200 (Opti-Sciences, Inc., Hudson, NH, USA) optical meter was used to determine the relative chlorophyll concentration. It has a sampling area of 71 mm2. Chlorophyll content index (CCI) is the output of CCM-200 defined as the ratio of transmission of radiation from a light emitting diode (LED) centered at 931 nm to transmission of radiation from LED centered at 653 nm (Kalaji et al., 2017a, 2017b, 2017c; Parry et al., 2014). It provides a unitless index ranging from 0 to 100, which is proportional to chlorophyll content of the leaves. During these measurements, special care was taken not to change ambient conditions, e.g., angle of the leaf or shading. 2.3. Morphological properties Trays were monitored daily to record the time of seedling emergence to figure out any delay caused by salinity stress compared to non-saline soils. One month after planting, seedlings were harvested and total seedling dry weight along with root to shoot ratio (R/Sh) was determined. For this purpose, initially soil blocks containing the seedlings were picked out of the cells in cultivation trays, and then

Table 1 Some physicochemical properties of soil. Sand (%)

Silt (%)

Clay (%)

SP (%)

EC (dS m
1)

pH

SOC (%)

80 Zn (mg kg
1) 0.5

10 Fe (mg kg
1) 1.2

10 Cu (mg kg
1) 0.44

30 S (mg kg
1) 11

0.2 B (mg kg
1) 1

7.8 K (mg kg
1) 80

0.33 P (%) 4.6

SP, Saturation percentage; EC, Electrical conductivity; SOC, Soil organic carbon.

158

Z. Hatam et al. / South African Journal of Botany 130 (2020) 155
164 Table 3 Analysis of variance (mean squares) for the effects of salinity, zinc and potassium rates on dry weight (DW); root to shoot ratio (R/Sh), chlorophyll content index (CCI), photosynthesis rate (A), transpiration rate (E), stomatal conductance (gs), leaf to air vapor pressure deficit (VPD), and water use efficiency (WUE) in cotton. Source of variation

Df

DW

R/Sh

CCI

A

E

gs

VPD

WUE

Salinity (Sal) Zinc (Zn) Potassium (K) Sal*Zn Sal*K Zn*K Sal*Zn*K Error CV. (%)

1 2 3 2 3 6 6 5

0.73** 0.021** 0.012** 0.004ns 0.008ns 0.001ns 0.002ns 0.001 12.25

0.02** 0.466** 0.066** 0.062** 0.066** 0.090** 0.121** 0.004 13.37

587.3** 1928ns 893** 2169** 248.2ns 221.9ns 243ns 165.74 55.67

0.975* 3.615** 5.797** 0.037ns 1.946** 0.641* 1.848** 8.23 11.34

2.035** 0.438* 0.476* 0.001ns 0.215** 0.092ns 0.037ns 0.047 43.320

0.006** 0.004ns 0.001** 0.0000ns 0.0000ns 0.0000ns 0.0000ns 0.0000 50.380

11.27** 2.028* 0.428ns 0.547ns 0.432ns 0.201ns 0.296ns 0.201 6.25

834.18** 451.26** 308.09** 117.67** 43.71* 82.70** 72.91** 14.05 29.72

ns,

* and ** are non-significant, significant at 0.05 and 0.01 probability levels, respectively.

were immersed shortly in a bucket of tab water to get soils off the roots. Afterwards, seedlings were carefully divided at the boundary between epicotyl and hypocotyl. Then, the samples were oven-dried at 60 °C for 48 h and were weighed to assess R/Sh. Seed remainders  and Herben, 2018). at root surface were not measured (Maskova 2.4. Statistical analysis of data Main and interaction effects of experimental factors were determined through analysis of variance (ANOVA) using general linear model (GLM) procedure in Statistical Analysis System (SAS) software. PROC UNIVARIATE procedure within SAS software was used to test assumptions of ANOVA, and residuals were normally distributed. Least significant difference (LSD) test at 0.05 probability level was used to check significant differences between means. When an F-test indicated statistical significance at P < 0.01 or P < 0.05, protected least significant difference (protected LSD) was used to separate means of main effect and significant interactions were separated by slicing method. 3. Results 3.1. Analysis of variance In Supplementary Tables 1
5, all the obtained data related to 19 parameters are presented; however, ANOVA results are shown and discussed only for the parameters, which were significantly altered at P < 0.01 or P < 0.05 by applied treatments. Analysis of variance showed that salinity, K, and Zn significantly influenced all the six GEx parameters (Table 3). A significant main effect of salinity was observed in gs, and VPD. Main effect of K was significant for CCI and gs and main effect of Zn was significant for E, DW, and VPD. There was a two-way interaction between salinity and Zn for F0, NPQ and Table 4 Analysis of variance (mean squares) for the effects of salinity, zinc and potassium minimum chlorophyll fluorescence yield obtained with dark-adapted leaf (F0), yield of photosystem II photochemistry (KPSII), and non-photochemical quenching (NPQ) in cotton. Source of variation

df

F0

KPSII

NPQ

Salinity (Sal) Zinc (Zn) Potassium (K) Sal*Zn Sal*K Zn*K Sal*Zn*K Error CV. (%)

1 2 3 2 3 6 6 51

0.00004* 0.00002ns 0.00001ns 0.000002* 0.00002ns 0.000006ns 0.000003ns 0.000003 21.14

0.045* 0.024ns 0.719** 0.421** 0.336** 0.111* 0.130* 0.050 42.48

2.627* 2.003ns 1.627ns 1.782* 1.00ns 0.359ns 0.359ns 0.28 45.65

* Significant at 0.05 probability levels. ** Significant at 0.01 probability levels. ns not significant at 0.05 probability levels.

CCI (Tables 3 and 4). There was a two-way interaction between salinity and K for DW, and E. There was a three-way interaction between salinity, K, and Zn for KPSII, A, WUE, and R/Sh. Two-way and threeway interactions between K, Zn, and salinity along with the individual influences of K, Zn, or salinity on cotton are discussed below. In the following paragraphs, only the results which appeared to be significantly altered by selected treatments are discussed. 3.2. DW, R/Sh, CCI The highest DW was observed at 100 kg Zn ha
1 where this upsurge was equal to 32% compared to Zn control (Fig. 1A). Salinity decreased DW significantly by 36% compared to non-saline condition under no K or Zn application (Fig. 1B). Under non-saline condition, maximum DW was obtained at 150 kg K ha
1 where this upturn was equal to 100% compared to the control (no fertilizer application). Under 15 dS m
1, application of 50, 100, and 150 kg K ha
1 had no effect on plant tolerance to salinity compared to the control. Under salinity stress, R/Sh showed significant rise by almost 80% compared to non-saline condition (Table 5). Under non-saline condition, 50 kg Zn ha
1 significantly decreased R/Sh by 23% and higher concentration had no effect on this ratio compared to the control. Under saline condition, 50 and 100 kg Zn ha
1 decreased R/Sh by 25 and 87%, respectively. Under salinity stress, 100 and 150 kg K ha
1 decreased this ratio by 47 and 41%, respectively while 50 kg K ha
1 had no effect on this ratio compared to the control. In salt-affected soils, application of 50, 100, and 150 kg K ha
1 contributed to a significant reduction in R/Sh by 80, 73, and 52% compared to the control. The highest concentrations of K and Zn resulted in the lowest R/Sh at 0 and 15 dS m
1. In fact, 100 kg Zn ha
1 synergized 150 kg K ha
1 compared to lack of Zn application and reduced R/Sh by 43 and 83% at 0 and 15 dS m
1, respectively. Application of 100 and 150 kg K ha
1 resulted in 94% rise in CCI (Fig. 2A). Moreover, salinity and nutrient deficiency, decreased CCI values significantly by 64% compared to non-saline condition (Fig. 2B). Under non-saline condition, various Zn concentrations had no effects on CCI; however, under salinity stress, application of 50 and 100 kg Zn ha
1 contributed to 258 and 474% increase in CCI compared to the control. 3.3. Gas exchange parameters 3.3.1. gs, E, VPD Under non-saline condition, application of 100 and 150 kg K ha
1 significantly improved gs by 100 and 140% compared to the control (Fig. 3). A 200% reduction in gs was observed under salinity stress compared to non-saline condition (Table 6). Under no salinity stress, application of 100 kg Zn ha
1 resulted in a 60% increase in E compared to the control (Fig. 4A). Salinity significantly decreased E by 6% in absence of fertilizer application (Fig. 4B). Application of 100 kg K ha
1 resulted in maximum E at 0 and 15 dS m
1, where this upward trend was equal to 158 and 254%, respectively. Under application of

Z. Hatam et al. / South African Journal of Botany 130 (2020) 155
164

159

Fig. 1. Main effect of zinc (A) and potassium £ salinity (dS m
1) interaction (B) on seedling dry weight (DW). Significant differences at 0.05 probability level are indicated by different letters.

Table 5 Salinity £ zinc £ potassium interaction on root to shoot ratio (R/Sh) in cotton. Zinc (kg ha
1) 0

50

100

Potassium (kg ha
1) Salinity (dS m
1) 0 15

0

50 b

0.75 1.34a

100 bc

0.63 0.27fg

150 de

0.40 0.36ef

0 d

0.44 0.64cd

50 c

0.58 1.00b

100 abc

0.67 0.73c

150 bc

0.65 0.30f

0 ef

0.35 0.53de

50 bc

0.60 0.18g

100 def

0.36 0.35ef

150 fg

0.28 0.34f

0.25g 0.10g

Means within a row followed by the same letter are not significantly different at 0.05 probability level.

150 kg K ha
1 in non-saline soils, E remained unchanged compared to the control; however, at 15 dS m
1 it showed a 56% reduction. Under non-saline condition, application of 50 and 100 kg Zn ha
1 significantly decreased VPD from 7.54 in the control to 7.12 and 6.84, respectively (Fig. 5). Salinity significantly decreased VPD from 7.6 to 6 in the absence of K or Zn application (Table 6).

3.3.2. A, WUE Salinity significantly decreased A by 42% compared to the control. At 0 and 15 dS m
1, application of 100 kg Zn ha
1 increased A by 38 and 44%, respectively. In non-saline soils, only the highest K concentration (150 kg ha
1) increased this parameter by 72% whereas under salinity stress 50, 100, and 150 kg K ha
1 almost equally increased A

Fig. 2. Main effect of potassium (A) and zinc £ salinity (dS m
1) interaction (B) on chlorophyll content index (CCI). Significant differences at 0.05 probability level are indicated by different letters.

160

Z. Hatam et al. / South African Journal of Botany 130 (2020) 155
164

Fig. 5. Main effect of zinc on vapor pressure deficit (VPD). Significant differences at 0.05 probability level are indicated by different letters. Fig. 3. Main effect of potassium on leaf stomatal conductance (gs). Significant differences at 0.05 probability level are indicated by different letters. Table 6 Main effects of salinity stress on stomatal conductance (gs), and leaf to air vapor pressure deficit (VPD) in cotton. Salinity (dS m
1)

gs (mol H2O m
2 s
1)

VPD (kPa)

0 15

0. 12a 0.04b

6.68b 7.60a

Table 7 Salinity £ zinc £ potassium interaction on photosynthesis rate (A) and water use efficiency (WUE) in cotton. Zinc (kg ha
1)

0

15

0

A (mmol CO2 m


2

0

Means within a column followed by the same letter are not significantly different at 0.05 probability level. 50

by 22% and difference between these concentrations was not significant. Minimum value of A was observed at the highest Zn concentration (100 kg ha
1) where this decline was 35% compared to the control (Table 7). However, when it was accompanied with application of 50, 100, and 150 kg K ha
1, A increased by 65, 110, and 124% indicating synergistic effects of these nutrients on this parameter. The greatest values of A was obtained at 150 kg K ha
1 as well as

Potassium (kg ha
1)

100

0 50 100 150 0 50 100 150 0 50 100 150

4.70ef 4.70ef 3.60f 8.10a 4.80e 4.10cd 7.20b 3.80cd 2.90f 4.80c 6.10b 6.80ab


1

s

2.70d 3.30bc 3.30bc 3.00ab 3.00d 3.70bcd 3.20bc 3.60bc 3.90ab 4.50a 3.60ab 3.20bcd

)

15

WUE (mmol CO2 mmol H2O
1) 22.08a 12.22bcd 6.00e 5.55e 9.40cde 15.00b 4.73e 12.97bc 7.13cde 7.31cde 5.13e 6.38de

19.95b 30.2a 13.07de 11.38cde 33.78a 35.00a 11.87cde 17.25cd 11.55cd 8.50e 5.43e 14.10cd

Means within a column followed by the same letter are not significantly different at the 0.05 probability level.

Fig. 4. Main effect of zinc (A) and potassium £ salinity (dS m
1) interaction (B) on transpiration rate (E). Significant differences at 0.05 probability level are indicated by different letters.

Z. Hatam et al. / South African Journal of Botany 130 (2020) 155
164

161

fertilizer application as it declined by only 9% (Table 7). Under nonsaline condition, application of 50 and 100 kg Zn ha
1 decreased WUE by 57 and 68%, respectively. However, at 15 dS m
1, only 50 kg Zn ha
1 resulted in 70% increase in WUE. In non-saline soils all K concentrations decreased WUE by 45, 73, and 75%, respectively. Under salinity stress, applying 50 kg K ha
1 increased WUE by 51%; however, higher K concentrations reduced WUE by 35 and 43%, respectively. Under K and Zn application, the highest WUE value was obtained when both nutrient concentrations were equal to 50 kg ha
1 whereas the lowest WUE was acquired when both K and Zn concentrations were equal to 100 kg ha
1. Under salinity stress, applying 50 kg Zn ha
1 synergized 150 kg K ha
1 and raised WUE by 134%. However, when Zn was raised to 100 kg ha
1, it antagonized 50 and 100 kg K ha
1, which resulted in a decrease in WUE by 72 and 58%, respectively. 3.4. Chlorophyll fluorescence parameters

Fig. 6. Potassium £ salinity (dS m
1) interaction on minimum fluorescence of dark adapted leaves (F0). Significant differences at 0.05 probability level are indicated by different letters.

Fig. 7. Zinc £ salinity (dS m-1) interactions on non-photochemical quenching (NPQ). Significant differences at 0.05 probability level are indicated by different letters.

3.4.1. F0, KPSII, NPQ, Fv/Fm Results obtained regarding measurement of the parameters by the chlorophyll fluorometer i.e., F0, F00 , Fm, Fm0 , Fv, Fv0 and Fs0 required for calculation of KPSII, NPQ, Fv/Fm and Fv0 /Fm0 are presented in Supplementary Tables 1
3. Among these measured parameters, only F0 was significantly influenced by applied treatments. In fact, under saline condition, F0 declined by 50% without Zn; however, at 100 kg Zn ha
1 F0 was raised by 50% compared to the control (Fig. 6). Salinity had no effects on KPSII under no K or Zn application (Table 8). Under nonsaline condition, 50 and 100 kg Zn ha
1 increased KPSII by 62 and 166% compared to the control; however, at 15 dS m
1 this increase was equal to 180 and 15%, respectively. 100 and 150 kg K ha
1 increased this parameter by 257 and 271% under non-saline condition, whereas 50, 100, and 150 kg K ha
1 caused an increase in the KPSII by 135, 185, and 240%, respectively. Application of 50 kg Zn ha
1 synergized the effect of 50 kg K ha
1 by 138 and 130% at 0 and 15 dS m
1, respectively compared to the control. Maximum value of KPSII was obtained at 100 kg Zn ha
1 accompanied with 100 or 150 kg K ha
1 under non-saline condition. However, at 15 dS m
1, the highest KPSII value was acquired at 150 kg K ha
1 without Zn though the difference between 100 kg Zn ha
1 + 150 kg K ha
1 was insignificant with that treatment. Under no salinity, Zn application did not influence NPQ significantly compared to the control (Fig. 6). However, under salinity stress, 50 and 100 kg Zn ha
1 resulted in 111 and 40% upsurge in NPQ compared to these treatments under normal condition. Maximum photochemical efficiency of PSII (Fv/Fm) was not significantly influenced by neither separate nor combined application of salinity, K, and Zn (Supplementary Table 2). 4. Discussion

50 kg Zn ha
1 + 100 kg K ha
1, where the difference between these treatments was not significant. Under salinity stress, the lowest value of A was acquired in the absence of K or Zn application; however, synergistic effect of 50 kg Zn ha
1 with 100 kg K ha
1 contributed to the highest A value, where this increase was equal to 66% compared to the control. WUE was not significantly influenced by salinity under no

According to our observations, regardless of Zn and K concentrations, seedling emergence delayed two weeks under salinity stress and growth rate was much lower. However, in these soils, chlorophyll content index was much higher under K and Zn application compared to non-saline condition. Such delay can be ascribed to

Table 8 Salinity £ zinc £ potassium interaction on yield of photosystem II photochemistry (KPSII). Zinc (kg ha
1) 0

50

100
1

Potassium (kg ha
1

Salinity (dS m 0 15

)

)

0

50

100

150

0

50

100

150

0

50

100

150

0.21e 0.20d

0.23e 0.47b

0.75ab 0.57ab

0.78ab 0.68a

0.34d 0.56ab

0.50c 0.46b

0.55c 0.56ab

0.60bc 0.50ab

0.56c 0.51ab

0.68bc 0.20d

0.86a 0.33c

0.78ab 0.53ab

Means within a row followed by the same letter are not significantly different at 0.05 probability level.

162

Z. Hatam et al. / South African Journal of Botany 130 (2020) 155
164

reduction in osmotic potential around seeds and reduction in seed imbibition, disruption in seed enzyme activities, and ion toxicity (Hasana and Miyake, 2017). Moreover, salinity can disrupt metabolism of fat and protein and reduce seed food storage. Germination delay is also attributed to reduction in the activity of seed growth regulators e.g., gibberellic acid as a growth promoter (Milewska-Hendel et al., 2017). Under non-saline condition, application of K and Zn substantially improved growth of seedlings and plants became pale green due to nutritional dilution effect. However, their photosynthesis rate, stomatal conductance, transpiration rate, and leaf to air vapor pressure deficit were in much better circumstances compared to saltaffected darker green leaves. One month after sowing, prior to harvest, the seedlings grown at 15 dS m
1, were apparently much smaller and maximum number of visible leaves per plant occurred across various K and Zn treatments; nonetheless, those seedlings grown under non-saline condition were much taller and contained 7 leaves at most. Salinity significantly reduced DW of seedlings compared to non-saline condition. Effects of salinity stress on plants include physiological drought due to reduction in root water uptake (osmotic effect), direct toxicity at high concentration of cytoplasmic Na+ and Cl
, nutritional imbalance, and induced oxidative stress (Gupta and Huang, 2014). It should be noted that when seedlings are suddenly subjected to salinity, as in most research, their salt tolerance might be lower compared to the same seedlings grown under saline condition from germination stage, as in our study. In an investigation, Souza et al. (2016) showed that in Physalis angulata L, APX gene encoding ascorbate peroxidase was up regulated almost 7 times higher in germination stage under 14 dS m
1 salinity compared to that of seedling stage under 4 dS m
1 salinity. Furthermore, expression of HAK1 gene encoding high-affinity K transporter protein, which is pivotal for salt tolerance of plant was higher at germination stage than that in seedling stage. Therefore, in real farming methods, seedlings are likely to be more tolerant to salinity compared to those suddenly exposed to salinity stress, and this needs to be considered in interpretation of data to make them applicable to farms. Zn and K are essential nutrients for plant growth, and our results showed a significant increase in the DW of seedlings under application of these nutrients in non-saline soil. It seems that at 15 dS m
1, K (Fig. 1B) and Zn were not effective in biomass production as difference between treatments was not significant compared to the control. But instead, to help plant survival under salinity stress, these nutrients were used to improve other mechanisms such as E (Fig. 4B), A, and WUE (Table 7) under salinity suggesting that under K and Zn application, cotton seedlings restrict some metabolic processes and enhance some more important ones to keep survive under salinity stress. This finding is novel, as it has not been reported previously in the literature. In this regard, CCI is a virtual witness of such strategy implemented by cotton seedlings for survival. Since under no K or Zn application, DW (Fig. 1B) and CCI (Fig. 2B) were much lower in saltaffected soils compared to non-saline soils; however, when nutrients were applied, CCI significantly increased while DW remained unchanged. An increase in CCI can be an indication of improvement in cotton photosynthesis and metabolic processes, since excessive Na+ can produce reactive oxygen species (ROS), causing chlorophyll degradation and membrane lipid peroxidation (Taïbi et al., 2016). Our results demonstrated a significant upward trend in CCI under Zn application (Fig. 2B). Zn has antioxidant-like properties detoxifying ROS (Hennig et al., 1999). It also activates antioxidants such as ascorbate peroxidase, poliphenoloxidase (Weisany et al., 2012). In our research, under non-saline condition, K deficiency resulted in low CCI while application of 100 and 150 kg K ha
1 significantly enhanced chlorophyll content. In a research on upland cotton, reduction of A under K deficiency was attributed to low chlorophyll content, poor chloroplast ultrastructure, and restricted saccharide translocation rather than limited stomatal conductance (Zhao et al., 2001). In fact, shoot growth was enhanced more compared to root growth under

higher chlorophyll content (Fig. 2), A, and WUE (Table 7). Under salinity stress and nutrient deficiency, upturn in R/Sh is a survival strategy to increase source to sink ratio of water and nutrients (Abdollahi and Jafari, 2012). Produced abscisic acid (ABA) in root is transferred to leaves leading to depolarization of guard cell plasma membrane and up-regulation of Kout channels. K and Cl
efflux from guard cell leads to stomata closure (Roberts and Snowman, 2000). Reduced mesophyll conductance decreases E as shown in our research (Table 6 and Fig. 4). On the other hand, ABA produced in leaves moves to root and stimulates genes encoding aquaporin proteins to enhance water uptake and root growth (Hu et al., 2012). Reduction in R/Sh under separate and combined application of K and Zn indicates that plant condition has been improved for growth and metabolic processes. It seems that K is more effective than Zn in decreasing R/Sh; however, synergistic effects of these nutrients especially at maximum concentrations is noticeable compared to their individual application. In line with our findings (Table 6), it has been shown that in spruce (Picea rubens L.), stomatal conductance decreases by increasing VPD accompanied with a reduction in the seedling growth (Day, 2000; Marsden et al., 1996). Reduction in stomatal conductance can restrict CO2 transfer into leaf contributing to a reduction in CO2 assimilation. Under salinity stress, synergistic interactions between 50 kg K ha
1 and 100 kg Zn ha
1 resulted in 43% increase in A compared to the control (Table 7). Interestingly, it can be seen that the lowest WUE was obtained in this treatment, as well (Table 7). Therefore, such drop in WUE can be attributed to substantial improvement in E as a result of K and Zn application under salinity stress. It suggests that rate of increase in E was more remarkable compared to that of A. Surprisingly, under non-saline condition, the minimum A value was observed at 100 and 50 kg Zn ha
1, respectively, under no K application. In this regard, inhibitory effect of ZnSO4 alone on activity of electron transfer within photosystem II has been proven by several investigations under non-saline conditions (Paunov et al., 2018; Tripathy and Mohanty, 1980). On the other hand, as mentioned above, application of Zn improved CCI values under salinity stress. These results may mirror the fact that applying Zn probably enhances salt tolerance and chlorophyll content mostly through other mechanisms such as detoxification of ROS. In our research, A, E, and gs values in cotton under salinity stress were almost similar to those reported by Soares et al. (2018). In various researches, differences in these values might be resulted from cultivar difference, date of measurement, and fertilizer management. F0 is minimal fluorescence level when all antenna pigment complexes are open in dark-adapted leaves with respect to photosynthesis. In this research, salinity significantly reduced F0 (Fig. 6), which might be associated with a decrease in the chlorophyll content (Everard et al., 1994). As shown in Fig. 2B, salinity stress decreased CCI by 30% compared to the control. However, when Zn concentration increased from 50 kg ha
1 to 100 kg ha
1, a significant increase was observed in F0 by almost 30%. Increased F0 might be a representative of degradation in photosystem II (D1 protein) or troubles in energy transfer into reaction center (Calatayud et al., 2006). Such increase in F0 at high Zn concentration might be partly attributed to ZnSO4 inhibitory effect on activity of electron transfer within photosystem II (Paunov et al., 2018). However, it should be noted that F0 by itself is not very informative and any alteration in F0 can be controversial as this parameter can be changed as a result of any variables. This result is similar to findings by Li et al. (2018) reporting that salinity stress significantly reduced F0 in Phragmites australis and also Spartina alterniflora. Likewise, Heidari et al. (2014) demonstrated that F0 declined significantly under salinity stress in sunflower over the first and second weeks of plant subjection to NaCl, and then it increased over the following weeks. Everard et al. (1994) also showed that F0 decreased significantly under salinity stress in celery with a decrease in the rez-Pe rez et al. (2007) showed that salinity chlorophyll content. Pe did not influence F0. NPQ is the amount of dissipated excessive

Z. Hatam et al. / South African Journal of Botany 130 (2020) 155
164

irradiation into heat (Calatayud et al., 2006). In salt-affected soils, under no K or Zn application, NPQ and KPSII remained unchanged compared to non-saline condition. Our results showed that under salinity stress, NPQ increased by elevating Zn concentration indicating energy loss in the form of heat. This can be also caused by changes in photosynthetic capacity to enhance cyclic electron transport (Brestic et al., 2016) or the changes in ratio of PSII to PSI or distribution of € light energy between two photosystems (Zivcak et al., 2015). Ogren € and Oquist (1984) stated that an upsurge in NPQ contributed to reduction in F0, which is quite in agreement with our results. KPSII evaluates efficiency of photosynthesis and photochemistry at different photon flux densities. At 0 and 15 dS m
1, K and Zn application improved KPSII compared to the control treatments. However, under saline condition, high concentrations of K and Zn led to much lower KPSII, probably due to additional osmotic potential and salinity stress imposed by these fertilizers. In salt-affected soils under no K or Zn application, NPQ and KPSII were not changed compared to the nonsaline control. In majority of previous research studying the influence of salinity stress on seedlings, plants have been initially brought up under normal conditions and then have been subjected to salinity i. e., quite far from what is done by farmers in reality. Most often, they have found large differences between ChlF parameters under severe salinity stress compared to those plants not subjected to salinity stress. It seems that such seedlings are more vulnerable compared to seedlings grown up under saline conditions from germination stage, as in our study. This is probably due to lower concentration of antioxidants as previously proven by Souza et al. (2016). Therefore, in our research, probably ChlF parameters were not as sensitive as GEx parameters to detect difference between parameters at 0 and 15 dS m
1. Lower sensitivity of ChlF to salinity stress may be caused by activity of alternative electron transport processes keeping photochemical processes high even when CO2 assimilation decreases (Psidov a et al., 2018). Furthermore, regarding GEx parameters, stomatal response is very sensitive to stress whereas electron transport can be redirected to alternative electron pathway and hence no effect on ChlF may be detected (Kalaji et al., 2017a, 2017b, 2017c).

163

and adversely influenced physiological properties. However, application of K and Zn increased seedling salt tolerance of seedlings as shown by improvement of physiological properties though biomass production still remained unchanged. It was found that all studied GEx parameters (gs, E, VPD, A, and WUE) were significantly altered by K, Zn, salinity stress and their combination. However, among the eleven studied ChlF parameters, only F0, KPSII, and NPQ were significantly influenced by separate and combined effects of K and Zn with different concentrations at 0 and 15 dS m
1. Therefore, it seems that in cotton seedlings, salinity stress can be detected more quickly and efficiently through GEx measurements compared to the ChlF ones under K and Zn application. Separate application of 100 kg K ha
1 or 100 kg Zn ha
1 or combined application of 50 kg K ha
1 and 50 kg Zn ha
1 is recommended for proper establishment of cotton seedlings in salt-affected soils. According to literature review, it seems that when plants are subjected to salinity stress at germination stage, which is more common in real farm conditions, seedlings become more salt tolerant. However, when germination and emergence occur under normal conditions and then seedlings are subjected to similar salinity rates, seedlings would be more salt-sensitive and fastidious. Also, natural saline water may impose more stress to the plant compared to NaCl solutions (Saadat et al., 2005). Therefore, for more realistic and applicable results regarding ChlF and GEx parameters, it is recommended to design further experiments close to real farm practices. Acknowledgements This research was granted by Tarbiat Modares University, Grant Number IG-39713. We thank Cotton Research Institute of Iran (AREEO) especially Dr. Kamal Ghasemi Bezdi for providing and delinting cottonseeds. Supplementary materials Supplementary material associated with this article can be found in the online version at doi:10.1016/j.sajb.2019.11.032.

5. Conclusions Cotton is a precious cash crop, and seedling stage is the most crucial period for cotton establishment. It is the most sensitive stage to salinity stress, which may contribute to non-compensable yield losses even under optimal management in further stages. Optimal nutrient management can improve plant tolerance to salinity stress. Our results demonstrated that GEx responses can be used as a robust approach for optimal recommendation of Zn and K in salt-affected soils for cotton at early growth stage. Because they are more sensitive than ChlF parameters to the interactive effects of these treatments. In some cases, K2SO4 at high concentration (150 kg ha
1) can improve plant physiological properties, but once it is combined at lower concentrations (50 and 100 kg ha
1) with even low rates of ZnSO4 (50 kg ha
1), seedlings become more salt-tolerant. However, Zn alone at high (100 kg ha
1) concentration may show inhibitory effects on some GEx and ChlF parameters (e.g., KPSII, and A) and may increase the energy loss in form of heat in cotton. On the whole, it seems that implementation of 50 kg K ha
1 + 50 kg Zn ha
1 is promising for optimal establishment of cotton seedlings under 15 dS m
1. Seedlings produced higher biomass under non-saline condition and due to dilution effect showed lower CCI and showed chlorosis symptoms. Although they required higher nutrient concentrations, all GEx parameters were at much favorable status compared to those suffering from salinity stress, but contained sufficient nutrient rates. This may suggest that GEx parameters are more sensitive to salinity stress than nutrient deficiency stress, however; further research is required to prove this. Salinity was imposed from germination stage similar to real conditions. Salinity decreased biomass, raised root to shoot ratio

References Abdollahi, F., Jafari, L., 2012. Effect of nacl and KNO3 priming on seed germination of canola (Brassica Napus L.) under salinity conditions. International Journal of Agriculture, Research and Review 2, 573–579. Brestic, M., Zivcak, M., Kunderlikova, K., Allakhverdiev, S.I., 2016. High temperature specifically affects the photoprotective responses of chlorophyll b-deficient wheat mutant lines. Photosynthesis Research 130 (1
3), 251–266. Calatayud, A., Roca, D., Martínez, P.F., 2006. Spatial-temporal variations in rose leaves under water stress conditions studied by chlorophyll fluorescence imaging. Plant Physiology and Biochemistry 44 (10), 564–573. Day, M.E., 2000. Influence of temperature and leaf-to-air vapor pressure deficit on net photosynthesis and stomatal conductance in red spruce (Picea rubens L.). Tree Physiology 20 (1), 57–63. Esmaili, E., Kapourchal, S.A., Malakouti, M.J., Homaee, M., 2008. Interactive effect of salinity and two nitrogen fertilizers on growth and composition of sorghum. Plant Soil and Environment 56 (12), 537–546. Everard, J.D., Gucci, R., Kann, S.C., Flore, J.A., Loescher, W.H., 1994. Gas exchange and carbon partitioning in the leaves of celery (Apium graveolens L.) at various levels of root zone salinity. Plant Physiology 106, 281–292. Evelin, H., Kapoor, R., Giri, B., 2009. Arbuscular mycorrhizal fungi in alleviation of salt stress: a review. Annals of Botany 104 (7), 1263–1280. Finch-Savage, W.E., Bassel, G.W., 2015. Seed vigor and crop establishment: extending performance beyond adaptation. Journal of Experimental Botany 67 (3), 567–591. Gleick, P.H., 1993. Water in Crisis: a Guide to the World’s Fresh Water Resources, 1st ed Oxford University Press, New York. Gupta, B., Huang, B., 2014. Mechanism of salinity tolerance in plants: physiological, biochemical, and molecular characterization. International Journal of Genomics 24, 1–18. Hasana, R., Miyake, H., 2017. Salinity stress alters nutrient uptake and causes the damage of root and leaf anatomy in maize. KnE Life Science 3 (4), 219–225. Hazrati, S., Tahmasebi-Sarvestani, Z., Modarres-Sanavy, S.A.M., Mokhtassi-Bidgoli, A., Nicola, S., 2016. Effects of water stress and light intensity on chlorophyll fluorescence parameters and pigments of Aloe vera l. Plant Physiology and Biochemistry 106, 141–148.

164

Z. Hatam et al. / South African Journal of Botany 130 (2020) 155
164

Heidari, A., Bandehagh, A., Toorchie, M., 2014. Effects of nacl stress on chlorophyll content and chlorophyll fluorescence in sunflower (Helianthus annuus L.) lines. € € zu € ncu € Yıl Universitesi Yu Tarım Bilimleri Dergisi 24 (2), 111–120. Homaee, M., Schmidhalter, U., 2008. Water integration by plants root under non-uniform soil salinity. Irrigation Science 27, 83–95. Grattan, S.R., Grieve, C.M., 1998. Salinity-mineral nutrient relations in horticultural crops. Sci Hort 78 (1), 127–157. Hennig, B., Meerarani, P., Toborek, M., McClain, C.J., 1999. Antioxidant-like properties of zinc in activated endothelial cells. Journal of the American College of Nutrition 18 (2), 152–158. Hu, Y., Schmidhalter, U., 2005. Drought and salinity: a comparison of their effects on mineral nutrition of plants. Journal of Plant Nutrition and Soil Science 168 (4), 541–549. Hu, W., Yuan, Q., Wang, Y., Cai, R., Deng, X., Wang, J., Zhou, S., Chen, M., Chen, L., Huang, C., Ma, Z., 2012. Overexpression of a wheat aquaporin gene, TAAQP8, enhances salt stress tolerance in transgenic tobacco. Plant and Cell Physiology 53 (12), 2127–2141. Huang, M., Shan, S., Zhou, X., Chen, J., Cao, F., Jiang, L., Zou, Y., 2016. Leaf photosynthetic performance related to higher radiation use efficiency and grain yield in hybrid rice. Field Crops Research 193, 87–93. Isaacman, A., Roberts, R., 1995. Cotton, colonialism, and Social History in Sub-Saharan Africa, 1st ed. Heinemann, Africa. Jamil, A., Riaz, S., Ashraf, M., Foolad, M.R., 2011. Gene expression profiling of plants under salt stress. Critical Reviews in Plant Sciences 30 (5), 435–458. _ Kalaji, H.M., Bosa, K., Koscielniak, J., Zuk-Go»aszewska, K., 2011. Effects of salt stress on photosystem II efficiency and CO2 assimilation of two Syrian barley landraces. Journal Environmental and Experimental Botany 73, 64–72. Kalaji, H.M., Dabrowski, ˛ P., Cetner, M.D., Samborska, I.A., ºukasik, I., Brestic, M., Zivcak, M., Tomasz, H., Mojski, J., Kociel, H., Panchal, B.M., 2017. A comparison between different chlorophyll content meters under nutrient deficiency conditions. Journal of Plant Nutrition 40 (7), 1024–1034. Kalaji, M.H., Goltsev, V.N., Zuk-Go»aszewska, K., Zivcak, M., Brestic, M., 2017. Chlorophyll Fluorescence: Understanding Crop Performance-Basics and Applications, 1st ed. CRC Press, Abingdon, UK. Kalaji, H.M., Jajoo, A., Oukarroum, A., Brestic, M., Zivcak, M., Samborska, I.A., Cetner, M.D., ºukasik, I., Goltsev, V., Ladle, R.J., 2016. Chlorophyll a fluorescence as a tool to monitor physiological status of plants under abiotic stress conditions. Acta Physiologiae Plantarum 38 (4), 102–110. Kalaji, M.H., Pietkiewicz, S., 1993. Salinity effects on plant growth and other physiological processes. Acta Physiologiae Plantarum 15 (2), 53–58. Kalaji, H.M., Schansker, G., Brestic, M., Bussotti, F., Calatayud, A., Ferroni, L., Goltsev, V., Guidi, L., Jajoo, A., Li, P., Losciale, P., 2017. Frequently asked questions about chlorophyll fluorescence, the sequel. Photosynthesis Research 132 (1), 13–66. Kumari, N., Sharma, V., Mikosch, M., Unfried, C., Gessler, A., Fischer-Schliebs, E., Luettge, U., 2005. Seasonal photosynthetic performance and nutrient relations of butea monosperma TAUB. in comparison to two other woody species of a seasonal deciduous forest in SE-Rajasthan and to planted trees in the area. Indian Journal of Forestry 28 (2), 116–126. Li, S.H., Ge, Z.M., Xie, L.N., Chen, W., Yuan, L., Wang, D.Q., Li, X.Z., Zhang, L.Q., 2018. Ecophysiological response of native and exotic salt marsh vegetation to waterlogging and salinity: Implications for the effects of sea-level rise. Scientific Reports 8 (1), 2441–2450. Marsden, B.J., Lieffers, V.J., Zwiazek, J.J., 1996. The effect of humidity on photosynthesis and water relations of white spruce seedlings during the early establishment phase. Canadian Journal of Forest Research 26 (6), 1015–1021. , T., Herben, T., 2018. Root: shoot ratio in developing seedlings: how seedlings Maskova change their allocation in response to seed mass and ambient nutrient supply. Ecology and Evolution 8 (14), 7143–7150. Melgar, J.C., Mohamed, Y., Serrano, N., García-Galavís, P.A., Navarro, C., Parra, M.A., Benlloch, M., Fern andez-Escobar, R., 2009. Long term responses of olive trees to salinity. Agricultural Water Management 96 (7), 1105–1113. z,  ska, E., 2017. Fate of neu_ D., Kurczyn Milewska-Hendel, A., Zubko, M., Karcz, J., Stro tral-charged gold nanoparticles in the roots of the hordeum vulgare L. cultivar Karat. Scientific Reports 7 (1), 3014–3020. ~o, S., Schmo € ckel, S.M., Tester, M., 2017. Evaluating physiological responses of Negra plants to salinity stress. Annals of Botany 119 (1), 1–11.

€ € Ogren, E., Oquist, G., 1984. Photoinhibition of photosynthesis in Lemna gibba as induced by the interaction between light and temperature. III. Chlorophyll fluorescence at 77 K. Plant Physiology 62 (2), 193–200. Parry, C., Blonquist, Jr, J.M., Bugbee, B., 2014. In situ measurement of leaf chlorophyll concentration: analysis of the optical/absolute relationship. Plant, Cell and Environment 37 (11), 2508–2520. Paunov, M., Koleva, L., Vassilev, A., Vangronsveld, J., Goltsev, V., 2018. Effects of different metals on photosynthesis: cadmium and zinc affect chlorophyll fluorescence in durum wheat. The International Journal of Molecular Sciences 19 (3), 787–795.  rez, J.G., Syvertsen, J.P., Botía, P., García-Sa nchez, F., 2007. Leaf water relations Perez-Pe and net gas exchange responses of salinized carrizo citrange seedlings during drought stress and recovery. Annals of Botany 100 (2), 335–345. Penella, C., Landi, M., Guidi, L., Nebauer, S.G., Pellegrini, E., San Bautista, A., Remorini, D.,  pez-Galarza, S., Calatayud, A., 2016. Salt-tolerant rootstock increases Nali, C., Lo yield of pepper under salinity through maintenance of photosynthetic performance and sinks strength. The Journal of Plant Physiology 193, 1–11. Pessarakli, M., 1994. Handbook of Plant and Stress Crop, 2nd ed CRC Press, New York.  ca  k, M., Stojnic, S., Orlovic, S., Go € mo € ry, D., Kucerova, J., Ditmarova, L., Psidova, E., Ziv , K., Brestic, M., Kalaji, H.M., 2018. Altitude of origin influences the Strelcova responses of PSII photochemistry to heat waves in European beech (Fagus sylvatica L.). Environmental and Experimental Botany 152, 97–106. € ttge, U., 2000. Evaluation of instant light-response curves of Rascher, U., Liebig, M., Lu chlorophyll fluorescence parameters obtained with a portable chlorophyll fluorometer on site in the field. Plant, Cell and Environment 23, 1397–1405. Roberts, S.K., Snowman, B.N., 2000. The effects of aba on channel
mediated K+ transport across higher plant roots. Journal of Experimental Botany 51 (350), 1585–1594. Rochester, I., Peoples, M., 2005. Growing vetches (Vicia villosa L.) in irrigated cotton systems: inputs of fixed N, N fertilizer savings and cotton productivity. Plant and Soil 271 (1
2), 251–264. Saadat, S., Homaee, M., Liaghat, A.M., 2005. Effect of soil solution salinity on the germination and seedling growth of Sorghum plant. Water and Soil Science 19, 243–254. ~ edo-Argu € elles, M., Hintz, W.D., Dyack, B., Birk, S., Relyea, R.A., 2018. Schuler, M.S., Can Regulations are needed to protect freshwater ecosystems from salinization. Philosophical Transactions of the Royal Society B 374 (1764), 20180019. Shrivastava, P., Kumar, R., 2015. Soil salinity: a serious environmental issue and plant growth promoting bacteria as one of the tools for its alleviation. Saudi Journal of Biological Sciences 22 (2), 123–131. Skillman, J.B., 2008. Quantum yield variation across the three pathways of photosynthesis: not yet out of the dark. Journal of Experimental Botany 59 (7), 1647–1661. Soares, L.A.D.A., Fernandes, P.D., Lima, G.S.D., Suassuna, J.F., Pereira, R.F., 2018. Gas exchanges and production of colored cotton irrigated with saline water at different ^ncia Agrono ^ mica 49 (2), 239–248. phenological stages. Revista Cie Souza, M.O., Pelacani, C.R., Willems, L.A., Castro, R.D., Hilhorst, H.W., Ligterink, W., 2016. Effect of osmopriming on germination and initial growth of physalis angulata L. under salt stress and on expression of associated genes. The Anais da Academia ^ncias 88, 503–516. Brasileira de Cie Taïbi, K., Taïbi, F., Abderrahim, L.A., Ennajah, A., Belkhodja, M., Mulet, J.M., 2016. Effect of salt stress on growth, chlorophyll content, lipid peroxidation and antioxidant defense systems in Phaseolus vulgaris l. South African Journal of Botany 105, 306–312. Tripathy, B.C., Mohanty, P., 1980. Zinc-inhibited electron transport of photosynthesis in isolated barley chloroplasts. Plant Physiology 66 (6), 1174–1178. Weisany, W., Sohrabi, Y., Heidari, G., Siosemardeh, A., Ghassemi-Golezani, K., 2012. Changes in antioxidant enzymes activity and plant performance by salinity stress and zinc application in soybean (Glycine max L.). Plant Omics 5 (2), 60–68. Zhao, D., Oosterhuis, D.M., Bednarz, C.W., 2001. Influence of potassium deficiency on photosynthesis, chlorophyll content, and chloroplast ultrastructure of cotton plants. Photosynthetica 39 (1), 103–109. € ller, J., Stahr, K., 2015. Zhao, X., Othmanli, H., Schiller, T., Zhao, C., Sheng, Y., Zia, S., Mu Water use efficiency in saline soils under cotton cultivation in the tarim river basin. Water (Basel) 7, 3103–3122. Zhang, L., Ma, H., Chen, T., Pen, J., Yu, S., Zhao, X., 2014. Morphological and physiological responses of cotton (Gossypium hirsutum L.) plants to salinity. PLoS One 9 (11), e112807. Zivcak, M., Brestic, M., Kunderlikova, K., Sytar, O., Allakhverdiev, S.I., 2015. Repetitive light pulse-induced photoinhibition of photosystem I severely affects CO2 assimilation and photoprotection in wheat leaves. Photosynthesis Research 126 (2
3), 449–463.