Differential Morphophysiological and Biochemical Responses of Cotton Genotypes Under Various Salinity Stress Levels During Early Growth Stage

Munawar, Wajeeha; Hameed, Amjad; Khan, Muhammad Khashif Riaz

doi:10.3389/fpls.2021.622309

ORIGINAL RESEARCH article

Front. Plant Sci., 11 March 2021

Sec. Plant Abiotic Stress

Volume 12 - 2021 | https://doi.org/10.3389/fpls.2021.622309

This article is part of the Research Topic Salt Tolerance: Molecular and Physiological Mechanisms and Breeding Applications View all 27 articles

Differential Morphophysiological and Biochemical Responses of Cotton Genotypes Under Various Salinity Stress Levels During Early Growth Stage

$\r\nWajeeha Munawar$ Wajeeha Munawar

Amjad Hameed^* $Muhammad Khashif Riaz Khan\r\n$ Muhammad Khashif Riaz Khan

Nuclear Institute for Agriculture and Biology College, Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan

Cotton is a primary agriculture product important for fiber use in textiles and the second major oil seed crop. Cotton is considered as moderately tolerant to salt stress with salinity threshold of 7.7 dS/m at seedling stage. Salinity causes reduction in the growth of seedlings and cotton production that limits fiber quality and cotton yield. In this study, initially, 22 cotton genotypes were screened for relative salt tolerance using germination test in Petri plates (growth chamber). Selected 11 genotypes were further tested in pot experiment (sand) with 0, 15, and 20 dS/m NaCl treatments under glass house conditions. At four-leaves stage, different morphological and physiological traits were measured for all genotypes while biochemical analysis was performed on selected seven highly tolerant and sensitive genotypes. NaCl treatment significantly reduced plant biomass in two genotypes IR-NIBGE-13 and BS-2018, while NIAB-135, NIAB-512, and GH-HADI had least difference in fresh weight between the control and NaCl-treated plants. Photosynthetic rate was maintained in all the genotypes with the exception of SITARA-16. In two sensitive genotypes (IR-NIBGE-13 and 6071/16), Na⁺ ion accumulated more in leaves as compared to K⁺ ion under stress conditions, and an increase in Na⁺/K⁺ ratio was also observed. The lesser accumulation of malondialdehyde (MDA) content and higher activity of enzymatic antioxidants such as superoxide dismutase (SOD), peroxidase (POD), and ascorbate peroxidase (APX) in stressed plants of NIAB-135, NIAB-512, and FH-152 indicated that these genotypes had adaption capacity for salinity stress in comparison with sensitive genotypes, i.e., IR-NIBGE-13 and 6071/16. The observed salt tolerance was corelated with plant biomass maintenance (morphological), photosynthetic rate, and ionic homeostasis (K⁺/Na⁺ ratio, physiological) and biochemical stress marker regulations. After a series of experiments, it was concluded that NIAB-135, NIAB-512, and FH-152 could be utilized in breeding programs aimed at improving salinity tolerance in cotton and can expand cotton cultivation in saline area.

Introduction

Soil salinization is rapidly increasing day by day and became a global environmental problem (Ahammed et al., 2018). It decreases average yields of most major crops like wheat, rice, and cotton over and above 50% on a global scale (Bartels and Sunkar, 2005). The excessive concentration of salt (above from threshold, i.e., 3–4 dS/m) in the soil, water, and plant is called salinity (Hussain et al., 2019). Exposure to salt stress triggers many adverse physiological and biochemical changes in plants leading to yield reduction. Currently, out of 230 m ha of irrigated land, 45 m-ha area is under the influence of salt (Athar and Ashraf, 2009). Cotton is a primary agriculture crop that covered the biggest textile manufacturing industries devising a strong yearly influence on country economic value of $600 billion all over the world (Jabran et al., 2019). The cotton fiber consumption is increasing as human population grows. Gossypium hirsutum (90%) (high-yielding characteristics and early cultivation system, Campbell et al., 2010) and Gossypium barbadense (8%) (extralong staple fiber source, Wang et al., 2015) play a very important role in cotton production due to their high yield potential and competitive benefit to cotton textiles producers (Hu et al., 2019). According to the 2019 report survey, India, China, United States, Pakistan, Brazil, Australia, Uzbekistan, and Turkey are included in the list of top cotton-producing countries (Ali et al., 2019). Although Pakistan is placed among the globally top 5 cotton-producing countries, on the other hand, its yield lags behind other top most countries due to low yield per unit area and increasing cotton import. However, cotton is proposed as a medium salt-tolerant crop with salinity threshold of 7.7 dS/m (Maas and Hoffman, 1977). However, low yield, poor plant growth, and germination are the main constraints that are affected by salinity and alkalinity of soil that limit cotton growth at the early stages of development (Ashraf and Ahmad, 2000; Bolek, 2010).

Cotton seed germination is an important phase, but unfortunately, it is also a very sensitive stage for harsh climate conditions. Salinity can hinder seed germination by reducing plant water uptake ability, impose drought to the plant, and deploy it from nutrients by disturbing the ions uptake mechanism (Wang et al., 2011). In salt stress condition, the plant undergoes cellular injury that occurs in transpiring leaves because of large amount of salt accumulation (Khan et al., 1995). It is also considered that the growth rate is directly related with stomatal conductance; the higher the stomatal conductance, the higher will be the CO₂ absorption and energy production. However, salt stress decreases CO₂ fixation; as a result, reactive oxygen species (ROS) is produced by the leakage of electron into O₂ (Ahammed et al., 2018). Cotton growth and plant development comprising plant height, fresh and dry weights, plant weight, root to shoot ratio, leaf area and canopy development, and other physiological parameters like photosynthesis (Pn), transpiration rate (Tr), stomatal conductance (St), overall yield, and primarily fiber quality were severely affected by salinity (Loka et al., 2011). These detrimental effects of salt (NaCl) on cotton differ in accordance with the change in salt concentration (i.e., 10, 20 dS/m, etc.), depending upon the time period of salt exposure (how long it will be) and growth stage in which the plant is exposed to stress (i.e., germination or emergence). Cotton is referred as a salt-tolerant crop after barley, but its yield falls by 5% per unit dS/m with the increase in stress limit (Chinnusamy et al., 2005). Thus, the 200 mM NaCl (20 dS/m) stress treatment would induce an approximately 60% yield reduction underneath the field conditions (Higbie et al., 2010).

Salt stress induced many physiological and biochemical impairments in plants such as photosynthesis, ionic imbalance, and oxidative injury to proteins (enzymes) (Zhu, 2001; Xiong and Zhu, 2002; Muchate et al., 2016). However, the main factor under salt stress condition in cotton is the positive ion (Na⁺) instead of (Cl^–) (Gouia et al., 1994). Under salinity stress, the Na⁺ content in the shoots (cotyledon, leaves, and stems) is greater than that in the roots. In leaves, different types of cells have different capacity of sodium accumulation, which is more in the epidermal cell rather than in the mesophyll cell, and this was mainly noted in sensitive genotypes (Peng et al., 2016). Similarly, the salt-tolerant genotypes have aptitude of maintaining K⁺/Na⁺ ratios. For osmotic adjustment, the Na⁺ sequestration into the vacuole is very important in order to minimize the Na⁺ concentration in cell cytoplasm (Maathuis, 2013). For this purpose, Na⁺/H⁺ antiporters (Apse et al., 1999; Shi and Zhu, 2002) V-ATPase and V-PPase [vacuolar (V)], two H⁺ pumps, are involved in Na⁺ compartmentalization into the vacuoles (Dietz et al., 1969). Similarly, the salt-tolerant genotype has more capability of Na⁺ repossession into the vacuoles. High concentration of NaCl mainly causes ion toxicity, osmotic stress, and mineral disruption (such as those of K⁺ and Ca²⁺) in plants (Zhu, 2003; Munns and Tester, 2008).

Salt stress also affects the metabolic activities of plant tissues by overproduction of reactive oxygen species (such as O^2–, ¹O₂, and ^∙OH) in the cell, which oxidize different biochemical compounds like proteins, lipids, DNA, and RNA and enters the plant into oxidative stress (Munns and Tester, 2008; Miller et al., 2010). Plants possess various extensive antioxidative mechanisms in order to regulate the reactive oxygen species, for instance, ascorbate peroxidase (APX) pathway and superoxide dismutase (SOD) pathway for protection against reactive oxygen destruction. SOD pathway is a first course of action against ROS. It is employed as ROS scavenger to cope with salt stress by converting O^2– into H₂O₂ and O₂ in roots (Alscher et al., 2002). Similarly H₂O₂ could get H₂O and O₂ by reduction reaction in catalase (CAT) pathway confined in peroxisomes organelle (Miller et al., 2010). Peroxidase (POD) is a heme-containing glycoprotein, which catalyzes the H₂O₂ in reduction reaction by using different electron donors for example phenolic compounds and secondary metabolites (Hiraga et al., 2001; Zhao et al., 2013). The superoxide dismutase (SOD) activity is enhanced under salt stress. Likewise, malondialdehyde (MDA) content is increased with the rising in lipoxygenase (LOX) activity, as LOX act as a catalyst in the production of fatty acid. Antioxidant enzymes activity like POD and catalase (CAT) is lower in salt-sensitive cultivars than in the tolerant cotton genotypes. In addition, cotton genotypes that are tolerant to salinity exhibit greater activities of SOD, ascorbate, POD, and glutathione reductase with less CAT activity as the amount of salt increases (Jabran et al., 2019). In cotton, the expression of SOD enhanced with respect to the rise in NaCl concentration, whereas POD activity is up to 53% higher in tolerant cultivars. Higher POD activity has improved photosynthesis, which shows the part of antioxidants defense system to alleviate salinity stress (Zhang and Lin, 2014; Sharif et al., 2019). Ascorbate/ascorbic acid is another essential non-enzymatic antioxidant that is higher in the cytoplasm and cell chloroplast when exposed to salt stress. Ascorbic acid has the ability to maintain the photosynthetic apparatus in chloroplast under salinity. In many genotypes, more ascorbic acid in their cell at early growth stages seems to be an indication of tolerance (Aslam et al., 2013).

The present study is designed to screen salt-tolerant genotypes at their seedling stage. As the seedling stage is the most critical stage in proper development of plant systems and processes, therefore, it is important to examine the changes and modifications that arise due to salt stress. The information obtained from this work would be use to identify salt-tolerant and salt-susceptible genotypes and the proper utilization of saline and arid land in order to expand cotton cultivation area. Moreover, this study also provides effective breeding strategies to enhance salt tolerance in cotton.

Materials and Methods

Collection of Cotton Germplasm

In order to conduct the present study, healthy seeds of 22 genotypes were collected from the Central Cotton Research Institute (CCRI) Multan and Nuclear Institute for Agriculture and Biology (NIAB) Faisalabad (Table 1).

TABLE 1

Table 1. List of genotypes used in first experiment (Petri plate).

Initial Screening Using Germination Test in Petri Plates

First of all, the delinted seeds were imbibed in 15 mM aerated CaSO₄.2H₂O for 3 h and then treated with fungicide 1% Topsin M for 2–3 min. After washing the treated seeds with distilled water three times, they were placed on the germination paper (filter) in Petri plates that had been moistened with 0, 7.5, and 15 dS/m NaCl solutions. Each plate contained 10 seeds arranged in equal distance, and plates were properly labeled according to genotype as well as treatment. The Petri plates were placed in a growth chamber at running 29/19°C (day/night) temperature with light intensity of 550 μm m^–2 s^–1 16/8 h (light/dark) photoperiod. After 4 days, the germination data were recorded. If the emerging radical of the seed was longer than of seed length or the length of radical taken was ≥ 0.5 cm, then it was considered as germinated seed. The Petri plates were kept for 10 days in a growth chamber, and germination data were recorded regularly for analysis. The relative germination rate was calculated as follows:

RGR = (no. of germinated seed in salt stress condition/no. of germinated seed in control condition) × 100%

Germination Parameters

Final germination (FG), mean germination time (MGT), and germination index (GI) were estimated using the following formulae:

FG = (final no . of germinated seed / no . of seeds in Petri plate) \times 100

MGT = (n1 \times t1 + t2 \times n2 + t3 \times n3 \dots) / (n1 + n2 + n3 + n4 \dots)

where n = no. of germinated seed.

t = germination time interval.

G I = n 1 / d 1 + n 2 / d 2 + n 3 / d 3 \dots

where n = no. of germinated seed.

d = 1st, 2nd, and 3rd day, respectively.

Screening of Salinity Tolerance at Seedling Stage Under Glasshouse Conditions

Eleven genotypes were selected (including sensitive and tolerant) on the basis of germination parameters, i.e., MGT and GI, etc. through the initial screening of Petri plates experiment. These genotypes were further screened under control and saline conditions with increased salt concentration (Table 2).

TABLE 2

Table 2. Selected genotypes for seedling experiment under glass house conditions.

Seeds were planted during November 2019 in circular pots (top width, 27 cm; bottom width, 20.5 cm) that were filled with 4 kg sand. All the pots were watered at field capacity before sowing. For sowing, linted seeds were soaked in 15 mM aerated CaSO₄.2H₂O overnight. In the next morning, 8–10 seeds were sown approximately 2 cm deep in a sand pot. Every genotype with three replicates and treatments of 0, 15, and 20 dS/m of NaCl was maintained in completely randomized design. Glasshouse temperature was kept at ∼35°C daytime and ∼20°C nighttime using electric bulbs with a light intensity at 2500 lx for 14 h. After 3–4 days of sowing, the pots were watered with Hoagland solution of one-eighth strength with field capacity of sand, and this strength was subsequently increased to one-fourth when the cotyledon leaves emerged (Figure 1). When the first true leaves appeared after 15 days of sowing, they were maintained under one-half strength of NaCl-free Hoagland solution until the second true leaf appeared. At the early emergence of the third true leaf, the first salt stress of 50 mM was given, which was increased afterward and maintained one set under 15 dS/m (150 mM) and another one at 20 dS/m (200 mM) of NaCl; however, no NaCl was added to the set that served as control, respectively. After treatment, different physiological traits were recorded between 11 AM and 2 PM on the day before harvesting. Afterward, the plants along with the roots were harvested, and then, different morphological traits were measured.

FIGURE 1

Figure 1. Visual appearance of seedling emergence under glass house conditions: (A) sowing of seeds in sand pots; (B,C) epicotyl emergence of cotyledon leaf 4 DAT sowing; (D,E) full emergence of cotyledon leaves; (F) first and second true leaves emergence; (G,H) seedlings at fourth true leave stage; and (I) the overall view of sand pots before the day of harvesting.

Morphological Parameters

At three true leaves stage, the following morphological data were recorded for analysis: The plants of each genotype were rinse with dH₂O thoroughly, and then, the root and shoot lengths were measured in centimeters. The mean values for each genotype were calculated in each treatment for further analysis. The weight of the whole plant along with roots, shoots, and leaves was measured with the help of weighing balance. After recording the fresh weight, plants were kept in drying oven at 70°C for 48 h. Then, dry weights of plants were estimated on an electrical weighing balance.

Physiological Parameters

Different physiological traits like photosynthesis, stomatal conductance, transpiration, and chlorophyll content were measured by using LI-1600 Steady State Porometer and chlorophyll content by using SPAD-502; Na⁺/K⁺ ratio was also measured.

Stomatal conductance (mmol m^–2 s^–1) of control and treated plants was recorded with the help of a porometer and then calculated by using the formula:

Stomatal conductance (Sc) = 1/Dr × CF

Dr = diffusible resistance, which was calculated from the porometer;

CF = correction factor, which was calculated using formula: LT × constant.

The constant value at 25°C for durum was 411.8, and leaf temperature (LT) was also measured by the porometer. In the same manner, stomatal conductance of each control and treatment plants was calculated. Photosynthetic rate (μmol m^–2 s^–1) was calculated from transpiration rate and stomatal conductance by using the formula:

Phr = Sc (mmol m^–2 s^–1)/Tr (μg cm^–2 s^–1) × 10

Sc = stomatal conductance; Tr = transpiration rate.

Transpiration rate (mmol m^–2 s^–1) was measured in μg cm^–2 s^–1, as relative value was calculated by the transpiration value from the porometer divided by 10,000 and multiplied with 1000. A chlorophyll meter (Model: SPAD 502 plus Japan) was used to measure the chlorophyll contents in the leaves before and after salt stress. The chlorophyll meter SPAD was placed on the uppermost leaf of a plant to measure the chlorophyll. The day before harvesting, physiological data were recorded for analysis under control and saline conditions.

Na⁺/K⁺ Ratio

Sodium (Na⁺) and potassium (K⁺) concentrations were measured on a flame photometer (Model; Jenway PFP 7). First of all, to digest dried ground material, 0.05g of the leaf material was taken in digestion tubes. Then, 1 ml of conc.H₂SO₄ was added on the dried sample for the sake of digestion. All the tubes were kept in the dark for overnight incubation at room temperature. The next day, 0.5 ml of H₂O₂ (35%) was added, and the tubes were shifted in a digestion block and heated at 350°C up to the production of fumes. After 30 min of heating, the digestion tubes were removed from the block to cool down. H₂O₂ (0.5 ml) was added gradually, and the tubes were positioned back into the digestion block. The above mentioned step was repeated until the color of the digestion material turned transparent. Then, the volume of the digestion extract made up 25 ml of the volumetric flasks. After the extract was filtered, it used to analyze K⁺ and Na⁺.

Stress Susceptibility Index

Stress susceptibility index (SSI) was calculated for the tested genotypes under 15 and 20 dS/m salt stress and non-stress conditions by using this formula (Fischer and Maurer, 1978):

SSI = 1 - (Ys / Yp) / SI

Ys = means of characters under salt stress conditions;

Yp = mean of character under non-stress condition.

While for stress intensity (SI):

SI = 1 - (Ŷs / Ŷ p)

Ŷs = means of all the genotypes under stress conditions.

Ŷp = means of all the genotypes under non-stress condition.

Stress Tolerance Index

Stress tolerance index (STI) was calculated for the determination of stress tolerance potential of genotypes under 15 and 20 dS/m salt stress and non-stress conditions by using following formulae (Fernandez, 1993):

Root length STI = (root length of stressed plant/root length of non-stressed plant) × 100

Shoot length STI = (shoot length of stressed plant/shoot length of non-stressed plant) × 100

Stomatal conductance STI = (stomatal conductance of stressed plant/stomatal conductance of non-stressed plant) × 100

Photosynthetic rate STI = (photosynthetic rate of stressed plant/photosynthetic rate of non-stressed plant) × 100

Transpiration rate STI = (transpiration rate of stressed plant/transpiration rate of non-stressed plant) × 100

Chlorophyll content STI = (chlorophyll content of stressed plant/vhlorophyll content of non-stressed plant) × 100

Biochemical Analysis

After morphophysiological analysis, treatment-induced biochemical modifications in plant leaves were analyzed. The genotypes were selected on the basis of variance analysis of morphophysiological parameters, SSI and STI; the two sensitive and five tolerant genotypes were selected and further tested by biochemical analysis (Table 3).

TABLE 3

Table 3. Selective sensitive and tolerant genotypes for biochemical analysis.

Extraction for Antioxidant Enzyme Activities

First of all, after weighing, 0.1 g fresh leaf from all cotton genotypes was extracted in 1 ml of 50 mM potassium phosphate buffer with pH 7.4, and then, ground samples were centrifuged at 14,000 × g for 10 min at 4°C. The resultant supernatant was separated and utilized for determination of different enzymatic and non-enzymatic analysis. All the data were taken in duplicate.

Enzymatic Antioxidants

Ascorbate oxidase activity

For estimation of APX activity, leaf sample was homogenized in 50 mM potassium phosphate buffer, and APX was measured using the method explained by Dixit et al. (2001). The required reagent R1 assay buffer was prepared by using 0.2 M potassium phosphate buffer (pH 7.0), 10 mM of ascorbic acid, and then 20 ml of 0.5 M ethylenediaminetetraacetic acid (EDTA) mixing to get assay buffer. The second reagent R2 was 4 mM H₂O₂, and then the sample was extracted. For the estimation of APX activity, 1 ml assay buffer and 50 μl sample were added, and the reaction was initiated after adding 1 ml of 10% H₂O₂. The decrease in oxidation rate of ascorbic acid in absorbance at 290 nm after every 30 s was measured.

Superoxide dismutase activity

First, cotton leaves were ground in 50 mM potassium phosphate buffer (pH 7.0), 0.1 mM EDTA, and 1 mM dithiothreitol (DTT) as described in Dixit et al. (2001). For estimation of SOD activity, the samples after adding reagents [400 μl water, 250 μl of 0.2 M potassium phosphate buffer, 100 μl L-methane, 100 μl Triton X, 100 μl nitroblue tetrazolium (NBT)] were kept under the white light for 10 min. SOD activity was analyzed by assessing its ability to prevent the photochemical reduction in NBT that is present in chemical reagents, as explained in the method in Giaanopolitis and Ries (1977). Thus, 1 U of SOD activity is explained by the amount that produced 50% resist photochemical reduction in NBT.

Peroxidase activity

In order to analyze the POD activity, cotton leaves were homogenized in 50 mM potassium phosphate buffer having pH 7.0 and POD activity estimated by using this method (Maehly and Chance, 1955) with certain amendments. Thus, as to POD measurement, the assay solution prepared by mixing distilled water (535 μl), 200 mM phosphate buffer with pH 7.0, 200 mM guaiacol, 400 mM H₂O₂, and 15 μl extracted sample. After adding the enzyme extract, reaction was began and absorbance at 470 nm was recorded after every 20 s. The increasing trend in absorbance was observed, and enzyme activity was explained on the basis of leaves weight. Thus, 1 U of POD activity was defined as an absorbance change of 0.01/min.

Catalase activity

For the estimation of catalase activity, cotton leaves were emulsified in 50 mM potassium phosphate buffer (pH 7.0) and 1 mM dithiothreitol (DTT), and estimation was done by the method explained by Beers and Sizer (1952). The required assay solution for CAT activity contained 50 mM potassium phosphate buffer with same pH 7.0, 59 mM H₂O₂, and 0.1 ml sample (enzyme extract). The reaction was started after adding the sample and decreasing pattern in absorbance at 240 nm was recorded after every 20 s. Thus, 1 U of CAT activity described as change in absorbance of 0.01/min and enzyme activity expressed on the basis of leaves weight.

Total antioxidant capacity

The reagent 1 (R1), 400 mmol/l acetate buffer solution (pH 5.8), was prepared by suspending 54.432 g of CH₃COONa.3H₂O in 1 L deionized water. A 60-ml acetic acid was mixed with sodium acetate solution. The reagent 2 (R2), 30 mmol/l acetate buffer solution (pH 3.6), was prepared by adding 2.46 g CH₃COONa suspended in 1 L of deionized water. Acetic acid after dilution was mixed with sodium acetate solution. Then, 278 μl was removed from R2, and the same amount was added from 35% of H₂O₂ solution. 2,2′-Azinobis-3-ethylbenzthiazolin-6-sulfonic acid (ABTS) (0.549 g) was suspended in 100 ml of already equipped solution (final concentration, 10 mmol/L). The characteristic color of ABTS appeared after incubation for 1 h at room temperature. Colored reagent is unstable for 6 months if stored at 4°C. The first absorbance of this assay was taken before mixing R1 and R2, which served as blank, and the next absorbance was measured after mixing R1 and R2 (after 5 min incubation at room temperature).

Non-enzymatic Antioxidants

Total phenolic content

A total phenolic content (TPC) estimation method as explained in Ainsworth and Gillespie (2007) was applied with certain modifications in order to estimate TPC. First of all, 0.05 g of leaves sample was weighed, and for homogenization, it was placed in the dark for 48 h after adding 500 μl chilled 95% methanol and then centrifuged at 14,000 × g for 5 min. The supernatant was separated and used for TPC estimation. The assay protocol was as follows: 150 μl of 10% (v/v) F-C reagent mixed with 100 μl sample vortex thoroughly and then added 1.2 ml of 700 mM Na₂CO₃. Then, samples were left for 1 h incubation at room temperature. Blank corrected absorbance of samples was recorded at 765 nm. Phenolic content (gallic acid equivalents) of samples was determined by using linear regression equation.

Tannins

The supernatant from TPC assay was not discarded after recording readings from a spectrophotometer. PVP.P (0.1 g) was added in TPC samples and vortexed for 2–3 min. Then, these samples were centrifuged at 14,000 × g, and the supernatant was used for absorbance at 765 nm so as to estimate tannins in cotton leaves sample.

Ascorbic acid

The 2,6-dichloroindophenol (DCIP) method was used for ascorbic acid determination as explained by Hameed et al. (2005). For concise description, each molecule of vitamin C converted DCIP molecule into DCIPH₂ molecule, and this reaction was examined as a decreasing trend in absorbance at 520 nm was observed. A standard curve and linear regression equation was used to find the ascorbate concentration in the samples.

Alpha amylase activity

The alpha amylase activity of the cotton leaves was determined by the method in Varavinit et al. (2002) with certain modifications. Two reagents were required for α-amylase estimation. One is 3,5-dinitrosalicyclic acid (DNS) (prepared with 1 g DNS in dH₂O, then added 30 g of sodium potassium tatrate tetrahydride, and 20 ml of 2 N NaOH made up volume up to 100 ml), and the second was 1% starch solution. After adding 0.2 ml sample and 1% starch solution, the reaction mixture was incubated for 3 min and placed in water bath for 15 min after adding DNS, and then made up volume up to 9 ml with dH₂O. Absorption was observed at 540 nm spectrometrically.

Reducing sugars (sugar content)

The reducing sugar level in cotton leaves was estimated by using dinitrosalicyclic acid method explained in Miller (1959). Thus, the total soluble sugar contents of cotton leaves were also measured by phenol-sulfuric acid reagent method (Dubois et al., 1956). In this way, the non-reducing sugars were determined by the difference in reducing and total soluble sugars.

Other Biochemical Parameters

Pigment analysis

The amount of chlorophyll (a and b) and carotenoids was calculated by using method described in Arnon (1949). In the first step, 0.075 g of cotton leaves samples was homogenized in 80% chilled acetone and incubated at room temperature for 24 h in dark. After 24 h, it was centrifuged at 14,000 × g for 5 min. Absorbance of supernatant was measured at 645, 663, 505, 453, and 470 nm.

Total oxidant status

Total oxidant status (TOS) in cotton leaves samples was determined by the method described in Erel (2005). This method is based on the oxidation of Fe⁺² ions into Fe⁺³ by oxidants that are present in the sample acidic medium and measurement of ferric ions by xylenol orange. The assay mixture contained reagent R1, which is stock xylene orange solution containing 0.38 g in 500 μl of 25 mM H₂SO₄, 0.4 g of NaCl, 500 μl of glycerol, and volume up to 50 ml with 25 mM H₂SO₄. The reagent R2 contained 0.0317 g of o-dianisidine and 0.0196 g of ferrous ammonium sulfate and sample extract. After 5 min of adding R2, the absorption was measured at 560 nm by using a spectrophotometer. A standard curve was prepared using hydrogen peroxide. The results were expressed in μM H₂O₂ equivalent per L.

Total soluble proteins

To determine the protein content, leaves samples were homogenized in a medium of potassium phosphate buffer. Quantitative protein determination was done by using the method Bradford (1976). The assay protocol contained 5 μl of supernatant of the sample extract, 0.1 N NaCl, and then mixed with 1.0 ml of Bradford dye. This mixture was kept for 5 min to form protein dye complex before taking readings. Blank-corrected reading was calculated at 595 nm by a spectrophotometer.

Malondialdehyde content

The lipid peroxidation level in cotton leaves was assessed regarding MDA (a product from lipid peroxidation) content measured by thiobarbituric acid (TBA) method described in Heath and Packer (1968) with slight modification of the method in Dhindsa et al. (1981). The 0.1-g leaves sample was homogenized in 0.1% TCA. This extract was centrifuged at 14,000 × g for 5 min. To 1 ml aliquot of the supernatant, 20% TCA containing 0.05% TBA was added. The mixture was heated at 95°C for 30 min and then quickly cooled in an ice bath. After centrifuging at 14,000 × g for 10 min, the absorbance of the supernatant was recorded at 532 nm, and the value for the non-specific absorption at 600 nm was subtracted. The MDA content was estimated by using extinction coefficient of 155 mM^–1 cm^–1.

Total flavonoids

The total flavonoid (TF) content was determined by using aluminum chloride colorimetric method (Ainsworth and Gillespie, 2007). Each sample extract was mixed with 0.1 ml of 10% aluminum chloride hexadihydrate, 0.1 ml of 1 M potassium acetate and 2.8 ml of deionized water. After 40 min of incubation at the room temperature, the absorbance of the sample was determined by a spectrophotometer at 415 nm.

Statistical Analysis

Data were presented in the graphs as mean values and standard error. Statistical analysis was based on variance analysis and Tukey [honestly significant difference (HSD)] test at p < 0.05. The different letters above the bars in the same genotypes under stress and non-stress conditions indicated significant differences with tolerance 0.0001. Bars with similar letters in the same genotypes under treatments were non-significant. Principal component analysis (PCA) and correlation (Pearson test) were performed by using XL-STAT 2012.1.02 with 95% confidence interval. Cluster analysis was also performed by agglomerative hierarchical clustering (AHC) of cotton genotypes under control and salt stress conditions.

Results

Seed Germination Test

The initial screening was done at seed germination stage. In this experiment, seeds were tested against 0, 7.5, and 15 dS/m salt stress. Genotypes with 0% germination even in control, i.e., MNH-1020, CMB-CLEAN-COTTON, WEAL-AG-08, and IUB-69, were excluded. Salt stress inhibited seed germination in many genotypes. In NIAB-512, seed germination percentage remained the same as in control and under 15 dS/m, but 30% germination was increased under 7.5 dS/m salt stress condition. Similarly, 6071/16 also showed increase in 30% germination under 7.5 dS/m, and both genotypes behaved as moderately tolerant. In IR-NIBGE-13, seed germination occurred in control but not under stress conditions and was regarded as sensitive genotype at germination stage. The seed germination was slightly attenuated by salt stress in NIAB-135, as only 20% germination occurred. Moreover, in FH-152, germination was increased by 20% under stress conditions (Figures 2A, 3).

FIGURE 2

Figure 2. (A) Final seed germination of cotton, (B) mean germination time (MGT), (C) germination index (GI), and (D) germination energy (GE) in growth chamber under control and salt stress conditions.

FIGURE 3

Figure 3. (A) Cotton seeds germination in growth chamber under salinity stress and normal condition. The tolerant cotton seed germination occurs in both salt stresses but no germination in sensitive genotypes.

The relative increase in mean germination time (MGT) was observed in ROHI-1, SITARA-16, FH-326, 6071/16NIAB-135, and NIAB-512 under stress conditions as compared to that under non-stress condition. Salt stress showed no significant effect in FH-152, as MGT of seeds remained the same under control and stress conditions (Figure 2B).

Salt stress significantly decreased germination index (GI) in FH-326 and NIAB-135. The maximum GI was recorded in NIAB-135, afterward in FH-326, under non-stress condition. In contrast, GI was increased in FH-152 under stress conditions. However, the least differences between control and stress were observed in ROHI-1, SITARA-16, and NIAB-512 (Figure 2C).

In addition, seed germination energy (GE) was highly retarded by salt stress. An increased in GE was observed more under non-stress as compared to salt stress conditions in all the genotypes. The maximum GE was recorded in NIAB-135 and then in FH-326 under non-stress condition (Figure 2D).