Using Physiological Traits to Evaluating Resistance of Different Barley Promising Lines to Water Deficit Stress

International Journal of Scientific Research in Environmental Sciences, 2(6), pp. 209-219, 2014

Available online at http://www.ijsrpub.com/ijsres

ISSN: 2322-4983; 2014 IJSRPUB

http://dx.doi.org/10.12983/ijsres-2014-p0209-0219

209

Full Length Research Paper

Using Physiological Traits to Evaluating Resistance of Different Barley Promising

Lines to Water Deficit Stress

Soleyman Mohammadi1, Behzad Sorkhi Lalehloo

2, Mahdi Bayat

3, Soran Sharafi

4, Farshad Habibi

*5

1West Azerbaijan Agricultural and Natural Resources Research Center, Miyandoab, West Azerbaijan, Iran

2Seed and Plant Improvement Institute, Cereal Department, Karaj, Albors, Iran 3Islamic Azad University, Mashhad Branch, Mashhad, Razavi Khorasan, Iran

4

Islamic Azad University, Mahabad Branch, Mahabad, West Azerbaijan, Iran 5Islamic Azad University, Miandoab branch, Miandoab, West Azerbaijan, Iran

*Corresponding author: E-mail: [email protected]

Received 23 February 2014; Accepted 07 May 2014

Abstract. To study waterstress-tolerant barley varieties, 20 barley lines were cultivated under full irrigation and limited irrigation conditions where irrigation was stopped at anthesis stage in two separate field experiments during the 2007-2009

growing seasons at the Saatloo Research Farm, Azerbaijan, Iran. The experiments were laid out using RCBD with three

replications. The results from combined analysis of variance in both normal and stress conditions indicated that there were

significant differences among genotypes with regard to all studied traits which were due to high variation among the genotypes.

It was found that the activity of enzymes including SOD, GPX and CAT were increased under drought stress conditions, so

that tolerant genotypes had more changes in enzyme activity. On the other hand, MDA, Dityrosine and 8-oHdg were increased

under stress conditions where sensitive genotypes had stronger enzyme activity. Calculations of the correlation coefficients

among the studied traits under both stress and normal conditions also indicated that there were negative and significant

differences between antioxidant activity, lipid, protein, and DNA decadence. Finally, with regard to all traits, it was revealed

that in normal conditions genotypes 18 and 19 were the best performing lines, whereas the genotype 14 was least adapted line.

Therefore, genotypes 18 and 19 showed higher levels of resistance to water stress and the genotype 15 was more sensitive to

the drought conditions. The results also indicated that selecting more tolerant genotypes under stress conditions was the way to

overcome water deficit stress under terminal drought conditions.

Keywords: Antioxidant enzymes, Waterstress, Barley, Terminal drought conditions.

Abbreviations: CAT- Catalase; GPX- Glutathione Peroxidase; MDA- Malondialdehyde; RCBD- Randomized Complete

Block Design; ROS- Reactive Oxygen Species; SOD- Superoxide Dismutase; 8-oHdg- 8-hydroxy-2'-deoxyguanosine.

1. INTRODUCTION

One of the most Environment restricting factors

negatively affecting plant growth in the majority of

the worlds agricultural lands could be defined as a drought stress (Tas and Tas, 2007), and greatly limits

crop production worldwide (Zhang et al., 2010). As a

common consequence of drought stress, the

production of reactive oxygen species (ROS), such as

superoxide radical (O2-

), hydrogen peroxide (H2O2),

and hydroxyl radical (OH) is increased (Valentovic et

al., 2006) which is due to the enhanced leakage of

electrons to molecular oxygen (Arora et al., 2002).

Plant cell mitochondria and chloroplast are the two

major intracellular generators of reactive oxygen

species (Pan et al., 2006). These ROS are among

reactive cytotoxic for cells (Movahhedy-Dehnavy et

al., 2009) which could cause severe damage to DNA,

proteins, and lipids, and also alteration of stop natural

metabolism of plants (Clement et al., 2008). Plants are

immobile and unable to escape stressful environments

(Chai et al., 2005). Hence, they use some strategies

(including enzymatic and non-enzymatic antioxidant

defense systems) to eliminate or reduce the toxicity of

ROS (Creissen and Mullineaux, 2002). Some

antioxidant enzymes, including SOD (Nayyar and

Gupta, 2006), CAT (Zhenmei et al., 2009), GPX

(Zhen et al., 2009), and GRD (Demiral et al., 2005)

also play key roles in the formation and degradation

of H2O2. Levels of damage may become limited by

enzymatic and non-enzymatic scavengers of free

radicals (Aroca et al., 2003).

Mohammadi et al.

Using Physiological Traits to Evaluating Resistance of Different Barley Promising Lines to Water Deficit Stress

210

Due to low annual precipitation, many regions of

Iran suffer from water deficit. Therefore, due to

drought stress, barley production is decreased.

Understanding the physiological and biochemical

mechanisms conferring drought tolerance; thus, could

play a crucial role in developing appropriate selection

methods and breeding strategies.

The aim of this study was to investigate the effect

of drought stress on the activities of 20 barley

promising line/ cultivar antioxidant enzymes (CAT,

GPX, and SOD), lipid, protein, and DNA oxidation

(MDA, Dityrosine and 8-oHdg content).

2. MATERIALS AND METHODS

To evaluating resistance of twenty barley promising

lines/cultivars (Table 1) to water deficit stress with

physiological traits such as enzymes up regulated or

down regulated, lipid and protein concentration two

separate field experiments (normal and drought stress

conditions) were conducted in the 2007-2009

cropping seasons at the Saatloo Agricultural Research

Station (1338 m altitude, 35N, 45E), West Azerbaijan,

Iran. Saatloo has a 375mm annual rainfall on a long-

term average with a soil texture of clay-loom (30%

clay, 53% silt, and 17% sand), 1.27% organic matter,

pH of 7.5, and an EC of 2.5dS/m. The experiments

were conducted using a randomized complete block

design (RCBD) with three replications. Control plots

were watered at stem elongation, flowering, and

grain-filling stages whereas irrigation of stress plots

were stopped before occurring the flowering phase.

Before planting, the soil tillage was practiced based

on the research station/s routine. Fertilizers were

applied before sowing (100kg ha-1

P2O3 and 50kg ha-1

N) in October, and at stem elongation (50kg ha-1

N) in

March.

Table 1: Codes and Parentage of the studied barley lines/cultivars

Code Genotpye Code Genotpye

1 Rhn-03//L.527/NK1272 11 Mnitou//Alanda/Zafraa

2 Manitou//Alanda/Zafraa 12 Kny/K-273

3 Pamir-149/ Victoria 13 Pamir-065

4 AcuarioT75/Azaf 14 Pamir-168

5 Pamir-146//EA389-3/EA475-4 15 Prodcutiv/3/Rono//Alger/Ceres362-1-1

6 Alpha/Durra/Pamir-160 16 Belt67-1608/Slr/3/Dicktoo/Cascade//Hip/4/CWB117-77-9-7

7 Pamir-013/Sonata 17 Belt67-1608/Slr/3/Dicktoo/Cas

8 Robur/WA2196-68//Wysor 18 U.Sask.1766/Api//Cel/3Weeah/4/Lignee527/NK1272/5/Express

9 Bugar/DZ48-232 19 TWWd85-37/Kavir

10 Rhn-03//Lignee527/NK1272/5/Lignee527/Chn-

01/4/Lignee527/

20 Bahman

Table 2: Analysis of variance for contents of 8-hydroxy-2-deoxyguanosine (8-oHdg), Dityrosine, Malondialdehyde (MDA),

Glutathione Peroxidase (GPX), Catalase (CAT) and Superoxide Dismutase (SOD) measured under normal conditions Mean

Square

Df GPX

(u mg-1

protein)

CAT

(u mg-1

protein)

SOD

(u mg-1

protein)

8-oHdg

(nmol mg

protein)

Dityrosine

(nmol mg

protein)

MDA

(nmol mg

protein)

Year 1 429.4 * 630.2 35811.1 61.6 598.5 154.1

Ea 4 40.0 811.7 6790.2 12.3 112.9 51.8

Genotype 19 27497.4 ** 27349.5 ** 4869926.9

**

226.9 ** 4253.0 ** 3537.7 **

Genotype Year 19 47.9 96.2 18301.8 1.6 32.4 14.8

Eb 76 72.6 285.5 14080.4 3.3 52.3 23.7

CV (%) 5.7 5.7 5.9 10.9 4.8 5.2

* and **: significant at the 5% and 1% levels of probability, respectively. Mean squares without symbols are non-significant

To quantify antioxidant enzymatic activity in 20

barley genotype/ line, fifteen leaf samples were taken

randomly from each plot and were placed in liquid

nitrogen and then stored at -80C pending

biochemical analysis. In order to prepare samples for

the enzyme assays and protein measurement, the

leaves from each plant were washed with distilled

water and homogenized in a 0.16M Tris buffer

(pH=7.5) at 4C. Then, 0.5 mL of total homogenized

solution was used for protein determination using the

Lowry et al. (1951) method. Based on the amount of

protein per volume of homogenized solution, the

following enzymes were assayed in the volume

containing a known protein concentration in order to

calculate the specific activities of the enzymes. In this

study, chemical and biochemical characteristics were

measured based on blow methods:


211

Catalase (CAT) activity Paglia and Valentine

(1987)

(1)

Glutathion peroxidase (GPX) activity Paglia and Valentine

(1987)

(1)

Superoxide dismutase (SOD) activity Dhindsa et al. (1980) (2)

Lipid peroxidation (malondialdehyde Content) Sairam et al. (1998) (3)

Protein Damage (dityrosine content) Amado et al. (1984) (4)

Determination of 8-Hydroxy-2-Deoxyguanosine (8-oHdg) Bogdanov et al. (1999) (5)

Table 3: Analysis of variance for contents of 8-hydroxy-2-deoxyguanosine (8-oHdg), Dityrosine, Malondialdehyde (MDA),

Glutathione Peroxidase (GPX), Catalase (CAT) and Superoxide Dismutase (SOD) measured under normal conditions

Mean Square

Df

GPX

(u mg-1

protein)

CAT

(u mg-1

protein)

SOD

(u mg-1

protein)

8-oHdg

(nmol mg

protein)

Dityrosine

(nmol mg

protein)

MDA

(nmol mg

protein)

Year 1 644.0 806.0 11388.0 9.6 29.0 385.2

Ea 4 164.4 974.4 26298.0 0.8 98.6 36.2

Genotype 19 34074.8 ** 29755.4 ** 6670689 ** 364.6 ** 5172.3 ** 3999.7 **

Genotype Year 19 159.0 280.7 6608.8 6.1 * 11.1 77.7

Eb 76 166.1 312.8 14995.0 3.5 30.1 112.1

CV (%) 7.2 5.2 5.1 9.9 3.2 9.0

* and **: significant at the 5% and 1% levels of probability, respectively. Mean squares without symbols are non-significant.

2.1. Statistical analysis

Main and interaction effects of experimental factors

were determined using analysis of variance (ANOVA)

in SAS software Ver. 9.12. The assumptions of

variance analysis were tested by ensuring

homogeneity of the residuals. The LSMEANS

command was used to compare means at a P

Mohammadi et al.


212

stress conditions, respectively (Table 6). So it can be

stated that although the GPX production varies from

one genotype to another, it was higher under stress

conditions in all studied genotypes. Bybordi et al.,

(2010) stated that, due to increasing ROS and

macromolecule decadence in plants, the levels of

antioxidant enzymes in stress conditions increase

significantly in environmental stresses such as drought,

salinity, and heat. The ranges of antioxidant levels in

normal and stress conditions were 201.00 and 222.17,

respectively; hence, it can be said that the level of

GPX in stress conditions was higher than in normal

conditions. These results had enough correlation with

the studies of Ananeiva et al. (2002). The results from

correlation coefficients between both traits of GPX

production and other traits in both normal and stress

conditions (Table 7) indicated that there was a

positive and significant correlation between GPX

levels and CAT and SOD levels, yet a negative and

significant correlation with MDA, Dityrosine, and 8-

oHdg. These results were logical and predictable,

because of reverse relations between antioxidant

enzyme contents and the decadence of

macromolecules due to the free radicals scavenging

effects of GPX. Therefore, genotypes with high

antioxidant enzyme content are the best volunteer

genotypes to cultivate in stress conditions because of

their higher resistance to drought conditions. Dat et al.

(2000) believed that plants with higher levels of

antioxidant enzymes (GPX and CAT) had more

ability to scavenge ROS in stress conditions, which

makes them more resistant to stress conditions. Thus,

these genotypes can be used for cultivation in regions

with a high potential for the occurrence of stress.

3.2. Catalase enzyme (CAT)

Means comparison of CAT levels indicated that in

normal conditions genotypes 11, 18, 19 and genotype

14 had maximum and minimum levels, respectively

(Table 4), so by the Aronachalam and Bandyopandyay

rankings method, these are situated in the upper and

lower positions, respectively. In drought conditions

genotypes 18, 19 and genotype 14 had maximum and

minimum CAT levels, respectively (Table 5), so

according to Aronachalam and Bandyopandyay

rankings, these are situated in the upper and lower

positions, respectively. Calculations of statistical

parameters indicated that average and standard

deviations were 296.64 and 67.51 in normal

conditions, and 337.36 and 70.42 in stress conditions,

respectively (Table 6). Therefore, according to these

results, the levels of CAT as for GPX were not only

different in all studied traits but were also higher in

stress conditions. On the other hand, the ranges of

change of CAT were 226.17 and 234.17 in normal and

stress conditions, respectively, which showed that the

amounts of enzyme were decrease in stress conditions.

The results from the correlation coefficient analysis of

CAT production and other traits in both normal and

stress conditions (Table 7) indicated that these had a

positive and significant correlation with contents of

GPX and SOD, yet a negative and significant

correlation with MDA, Dityrosine, and 8-oHdg. CAT

is one of the most important antioxidant enzymes

which plays a key role in decreasing damage from

peroxides. The increase of this enzyme under stress

conditions, therefore, causes a decrease in damage to

plasma membrane lipids, proteins, DNA, and RNA

within plant cells. An increase in antioxidant

production leads to a decrease in the decadence of

lipids, proteins, DNA, and RNA, so there is a negative

relation between antioxidant content and

macromolecule decadence. These results correspond

with the results from Prasad (2003). In another work,

Noctor and Foyer (1998) reported a positive

correlation in the activity of antioxidant enzymes.

Acclimation of plants to drought is considered to

promote antioxidant defense systems to face the

increased levels of activated oxygen species (AOS),

which in turn, causes membrane damage through lipid

peroxidation and indicated by malondialdehyde

(MDA) content, which is a main parameter for

evaluating membrane oxidation extent and is toxic for

cells (Shao et al., 2005). The same results were

reported by Dolatabadian et al. (2008), who showed

that salt stress increased lipid peroxidation (MDA

content) in canola cultivars.

3.3. Superoxide Dismutase enzyme (SOD)

SOD is one antioxidant enzyme that has a key role in

the process of scavenging hydrogen peroxides.

Therefore, this enzyme is an important criterion for

detecting barley genotypes resistant to drought

stresses. Superoxide dismutases (SODs), a group of

metalloenzymes, are considered the first defense

against ROS (Gratao et al., 2005). The results from

means comparison for SOD indicated that the contents

of SOD in genotypes 11, 18, 19 and genotypes 14, 15,

20 had maximum and minimum levels of SOD,

respectively (Tables 4 and 5), so according to

Aronachalam and Bandyopandyay rankings (1984),

these are situated in the upper and lower positions,

respectively. Calculations of statistical parameters

also indicated that average and standard deviations

were 1984.28 and 900.92 in normal conditions and

2401.46 and 1054.41 in stress conditions, respectively

(Table 6). According to these results, the levels of

SOD as for CAT and GPX were not only different in

all studied traits but were also higher in stress

conditions. Jin et al. (2006) stated that an increase in


213

drought stress causes an increase in activity of SOD

after 24 hours. It can be concluded that this rise is a

consequence of stress conditions to scavenging free

radicals. This enzyme is known as a main component

of the plant protective mechanism to overcome

environmental stresses. The ranges of SOD changes

in both normal and stress conditions were 2610.17 and

3370.67, respectively, which reveals that the ranges of

change in stress conditions are wider than in normal

conditions. The results from correlation coefficients

between SOD production and other traits in both

conditions indicated that there is a positive and

significant correlation between GPX and CAT and a

negative and significant one with MDA, Dityrosine,

and 8-oHdg (Table 7). Shan and Guo (2009) stated

that environmental stresses increased activity of

almost all antioxidant enzymes with a positive

correlation as well as a negative correlation with

macromolecule decadence. They also stated that

increased levels of antioxidant enzymes caused an

increase in plant resistance to environmental stresses

(Mirnoff, 1998).

Table 4: Means comparison of the different traits of barley genotypes and Aronachalam and Pandyopandyay Ranking in two

years under normal condition

3.4. Hydroxyl-2-deoxy guanosine-8 (8-oHdg)

Means comparison of 8-oHdg indicated that

genotypes 11 and genotypes 18, 19 had maximum

contents in both normal and stress conditions (Tables

4 and 5), so according to Aronachalam and

Bandyopandyay rankings (1984), these are situated in

the upper and lower positions, while genotypes 14, 15

and 20 had minimum 8-oHdg contents in both normal

and stress conditions, so according to Aronachalam

and Bandyopandyay rankings (1984), these are

situated in the upper and lower positions. Also,

calculations of statistical parameters indicated that

average and standard deviations were 16.52 and 6.15

in normal conditions, while they were 19.02 and 7.79

in stress conditions, respectively (Table 6). Overall, it

can be concluded that the content of 8-oHdg among

all studied genotypes are very different and

particularly more in stress conditions. The important

point in this study was the lesser amounts of 8-oHdg

Code GPX Rank CAT Rank SOD Rank 8-

oHdg Rank Dityrosine Rank MDA Rank

Total

Rank

1 255.5

a 8

358.0

b 5

2711.0 b 4

12.3 ed 4.5

140.2 ef 5.5

86.3 ed 4.5

31.5

2 192.0

b 7

325 bc 4.5

2640.2 b 4

12.3 ed 4.5

137.7 ef 5.5

82.5 e 5

30.5

3 108.7

e 4

297.8

c 4

2126.8 c 3

13.7 d 4

146.0 df 5

91.0 ce 4

24

4 183.0

bc 6.5

291.7

c 4

2579.8 b 4

12.7 d 4

136.8 ef 5.5

84.7 de 4.5

28.5

5 86.7 fg 2.5 236 ed 2.5 1118.3 d 2 20.3 b 2 168.7 b 2 111.2 b 2 13

6 103.5

ef 3.5

230 ed 2.5

994.3 d 2

19.5 bc 2.5

167.8 b 2

109.7 b 2

14.5

7 127.0

d 5

299.0

c 4

2110.8 c 3

15.7 cd 3.5

159.5 bd 3

97.7 c 3

21.5

8 104.8

e 4

243.5

d 3

1137.0 d 2

21.3 b 2

162.2 bc 2.5

108.7 b 2

15.5

9 187.2

bc 6.5

345.0

b 5

2549.5 b 4

15.5 d 4

140.0 ef 5.5

87.8 ce 4

29

10 84.0 g 2 236 ed 2.5 962.5 d 2 21.8 b 2 166.0 bc 2.5 110.0 b 2 13

11 243.0

a 8

398 a 6

3260.8 a 5

8.0 f 6

109.2 g 7

54.2 f 6

38

12 176.8

bc 6.5

325 bc 4.5

2550.5 b 4

12.0 de 4.5

133.8 f 6

83.2 e 5

30.5

13 129.7

d 5

290.8

c 4

2123.7 c 3

15.8 cd 3.5

161.0 bd 3

84.0 de 4.5

23

14 61.8 h 1 185.2 f 1 695.0 e 1 27.7 a 1 195.2 a 1 138.3 a 1 6

15

54.5 h 1

205.5

ef 1.5

650.7 e 1

26.8 a 1

193.5 a 1

137.5 a 1

6.5

16 172.3

c 6

344.5

b 5

2461.5 b 4

14.3 d 4

134.0 f 6

82.3 e 5

30

17 131.0

d 5

292.8

c 4

2000.8 c 3

15.5 d 4

152.2 ce 4

94.0 cd 3.5

23.5

18 255.2

a 8

402.2

a 6

3127.0 a 5

8.5 fe 5.5

109.8 g 7

57.2 f 6

37.5

19 249.8

a 8

411.3

a 6

3229.7a 5

8.7 fe 5.5

111.2 g 7

57.0 f 6

37.5

20

58.3 h 1

214.8

ef 1.5

655.5 e 1

27.8 a 1

199.3 a 1

130.5 a 1

6.5

Means within each column with common letter(s) are not significantly different at 5% of probability.

Mohammadi et al.


214

in variants resistant to drought stress in comparison

with genotypes sensitive to drought stresses, so it

would be as a result of more production of antioxidant

enzymes (GPX, CAT, and SOD) in genotypes

resistant to drought stress. Manavalan et al. (2009)

showed that enzymatic antioxidant content played an

important role in scavenging harmful oxygen species.

The activities of antioxidant enzymes were altered

when plants were subjected to stress. Previously, an

increase in the level of antioxidants was reported with

an increase in stress intensity in maize and soybean by

Vasconcelos et al., (2009). Also, the ranges of trait

changes were 19.83 and 24.83 in both normal and

stress conditions; it suggests that the change of 8-

oHdg content in stress conditions was higher than in

normal conditions. On the other hand, the results from

correlation coefficients between 8-oHdg production

and other traits in both normal and drought conditions

(Table 7) revealed that there is a negative and

significant correlation between 8-oHdg content and

other traits such as GPX, CAT, and SOD, yet a

positive and significant correlation with Dityrosine

and MDA. Moreover, Lee et al. (2009) reported a

positive and significant correlation between CAT,

SOD, and Ascorbate Peroxidase (APX) under both

well-irrigated and water-deficit-stress conditions.

Furthermore, Lobato et al. (2008) also found a

positive and significant correlation between contents

of antioxidants.

Table 5: Means comparison of the different traits of barley genotypes and Aronachalam and Pandyopandyay Ranking in two

years under stress condition

3.5. Dityrosine

The protein content of plants is a fraction that is most

sensitive to oxidative stress due to high trends of ROS

to the amino acids of proteins for deactivating them.

Tompson et al. (1987) introduced Dityrosine as a

criterion for determining intracellular proteins. Means

comparison of Dityrosine revealed that genotypes 11,

Code GPX Rank CAT Rank SOD Rank 8-

oHdg Rank Dityrosine Rank MDA Rank

Total

Rank

1 296.3

a 8

409 bc 5.5

2912 b 5

12.7 gi 8

156.2 ij 9.5

117.7

bd 3

39

2 222.2

b 7

352.3

d 4

2932 b 5

13.3 fh 8

154.2 ij 9.5

108.5

cd 3.5

37

3 126.7

ef 3.5

348.7

d 4

2353 c 4

15.8 eg 6

168.0 gh 7.5

109.0

cd 3.5

28.5

4 211.5

b 7

360.7

d 4

3036 b 5

14.7 eg 6

159.8 hi 8.5

116.0

bd 3

33.5

5

104.0 f 3

273.2

ef 2.5

1662 d 3

26.5 b 2

197.2 c 3

127.5

bc 2.5

16

6 135.7

e 4

273.0

ef 2.5

1284e 2

22.5 cd 3.5

194.5 cd 3.5

127.7

bc 2.5

18

7 174.8

d 5

353.2

d 4

2536 c 4

17.5 e 5

172.7 fg 6.5

118.0

bd 3

27.5

8 124.0

ef 3.5

264.7

ef 2.5

1338 e 2

22.3 d 4

193.0 ce 4

130.3

bc 2.5

18.5

9 206.3

b 7

369.0

d 4

2927 b 5

15.7 eg 6

155.2 ij 9.5

109.8

bd 3

34.5

10 102.7

fg 2.5

278.0

e 3

1621 d 3

26.3 bc 2.5

183.7 df 5

132.2 b 2

18

11 289.5

a 8

422 ab 6.5

4243 a 6

9.8 hi 8.5

125.8 k 11

81.3 e 5

45

12 206.2

b 7

351.5

d 4

2986 b 5

14.8

efg 6

156.2 ij 9.5

104.2 d 4

35.5

13 174.5

d 5

365.0

d 4

2479 c 4

16.8 ef 5.5

181.5 ef 5.5

115.5

bd 3

27

14

74.3 h 1

215.7

g 1

871.8 f 1

33.7 a 1

211.0 b 2

158.7 a 1

7

15

74.2 h 1

239.5

fg 1.5

908.2 f 1

32.8 a 1

222.8 a 1

169.0 a 1

6.5

16

205 bc 6.5

374 cd 4.5

2448 c 4

17.2 ef 5.5

145.8 j 10

108.0

cd 3.5

34

17

177 cd 5.5

362.3

d 4

2430 c 4

17.7 e 5

179.7 f 6

113.0

bd 3

27.5

18 294.7

a 8

449.8

a 7

4037 a 6

8.8 i 9

128.8 k 11

72.8 e 5

46

19 288.3

a 8

448.7

a 7

4147 a 6

8.8 i 9

128.7 k 11

69.8 e 5

46

20 76.7

gh 1.5

236.2

fg 1.5

880.3 f 1

32.5 a 1

222.8 a 1

158.2 a 1

7

Means within each column with common letter(s) are not significantly different at 5% of probability.


215

18, 19 had maximum levels of Dityrosine in both

normal and stress conditions (Tables 4 and 5), so


(1984) rankings, these are situated in the upper and

lower positions. Genotypes 14, 15, 20 in normal

conditions (Tables 4) and genotypes 15, 20 (Table 5)

in stress conditions had minimum levels of Dityrosine,

so according to Aronachalam and Bandyopandyay

rankings (1984), these are situated in the upper and

lower positions. Also, calculations of statistical

parameters indicated that average and standard

deviations were 151.20 and 26.62 in normal

conditions and 171.88 and 29.36 in stress conditions,

respectively (Table 6). Overall, it can be concluded

that the contents of Dityrosine among studied

genotypes are very different. Nevertheless, the

amounts of Dityrosine were higher in stress conditions

in all studied traits. Thus, an important point is that

there are lesser amounts of Dityrosine in genotypes

resistant to drought stresses than those that are

sensitive, due to the production of more antioxidant

enzymes (GPX, CAT, and SOD) in resistant

genotypes. The ranges of trait change were 90.17 and

97.00 in both normal and stress conditions (Table 6);

it suggests that the changes of Dityrosine content in

stress conditions were more than in normal conditions.

On the other hand, the results from the correlation

coefficient between Dityrosine production and other

traits in both normal and drought conditions (Table 7)

revealed that there is a negative and significant

correlation between 8-oHdg contents and other traits

such as GPX, CAT, and SOD, while there is a positive

and significant correlation with 8-oHdg and MDA.

Table 6: Univariate statistics for the traits studied under normal and stress conditions

Statistics Condition

GPX

(u mg-1

protein)

CAT

(u mg-1

protein)

SOD

(u mg-1

protein)

8-oHdg

(nmol mg

protein)

Dityrosine

(nmol mg

protein)

MDA

(nmol mg

protein)

Maximum Normal 255.50 411.33 3260.83 27.83 199.33 138.33

Drought Stress 296.33 449.83 4242.50 33.67 222.83 169.00

Minimum Normal 54.50 185.17 650.67 8.00 109.17 54.17

Drought Stress 74.17 215.67 871.83 8.83 125.83 69.83

Range Normal 201.00 226.17 2610.17 19.83 90.17 84.17

Drought Stress 222.17 234.17 3370.67 24.83 97.00 99.17

Average Normal 148.24 296.64 1984.28 16.52 151.20 94.38

Drought Stress 178.22 337.36 2401.46 19.02 171.88 117.36

Standard

Deviation

Normal 67.70 67.51 900.92 6.15 26.62 24.28

Drought Stress 75.36 70.42 1054.41 7.79 29.36 25.82

Table 7: Correlation coefficient for the content of 8-hydroxy-2-deoxyguanosine (8-oHdg), Dityrosine, Malondialdehyde

(MDA), Glutathione Peroxidase (GPX), Catalase (CAT) and Superoxide Dismutase (SOD) studied under normal (above

diagonal) and stress (below diagonal) conditions

3.6. Malondialdehyde (MDA)

Fatty acids and lipids are more sensitive to ROS and

fall under oxidation rapidly. The studies revealed that

cellular and organellar membranes are the first parts

damaged in stress conditions affected by reactive

oxygen species (Candan and Tarhan, 2003) because of

the emission of cellular electrolytes following the

degradation of membranes and the increase in MDA

contents (Demiral and Turkan, 2005). So it can be

said that MDA is an appropriate candidate for

determining the levels of plant response to

environmental stresses (Bandeoglu et al., 2004). We

used MDA as a lipid peroxidation index. Means

comparison of results indicated that genotypes 11, 18,

19 and genotypes 14, 15, 20 had maximum and

minimum MDA content in both normal and drought

stress conditions, respectively (Tables 4 and 5), so


rankings (1984), these are situated in the upper and

lower positions, respectively, Also, calculations of

statistical parameters indicated that the average and

standard deviations were 94.38 and 24.28 in normal

conditions and 117.36 and 25.82 in stress conditions,

respectively (Table 6). Overall, it can be concluded

that the content of MDA among the studied genotypes

is very different. Nevertheless, the amounts of

Dityrosine were more in stress conditions in all

Traits GPX CAT SOD 8-oHdg Dityrosine MDA

GPX 0.95 ** 0.94 ** -0.91 ** -0.92 ** -0.91 **

CAT 0.95 ** 0.97 ** -0.93 ** -0.95 ** -0.96 **

SOD 0.94 ** 0.96 ** -0.97 ** -0.95 ** -0.96 **

8-oHdg -0.93 ** -0.96 ** -0.94 ** 0.97 ** 0.97 **

Dityrosine -0.92 ** -0.94 ** -0.96 ** 0.94 ** 0.97 **

MDA -0.87 ** -0.92 ** -0.94 ** 0.94 ** 0.95 **

**: significant at 1% level of probability

Mohammadi et al.


216

studied traits. Thus, an important point is that there is

a lesser amount of MDA in genotypes resistant to

drought stresses than in those sensitive due to the

production of more antioxidant enzymes (GPX, CAT,

and SOD) in resistant genotypes in comparison with

sensitive genotypes. Bhattacharjee and Mukherjee

(2002) believed that the content of MDA in plant

tissue is a representation of the levels of a membrane

lipids decadence, because of their release following lipid peroxidation and degradation. They stated that

levels of MDA in plants under stress are higher than

those in normal conditions. Also, the ranges of trait

change were 99.17 and 84.17 in both normal and

stress conditions; this suggests that the changes of

MDA content in stress conditions were more than

those in normal conditions. On the other hand, the

results from correlation coefficients between MDA

production and other traits in both normal and drought

conditions (Table 7) revealed that there is a negative

and significant correlation between MDA content and

other traits such as GPX, CAT, and SOD, while a

positive and significant correlation exists with 8-oHdg

and Dityrisine. Meloni et al. (2003) reported a

negative correlation between the increasing activity of

GPX with a decrease in lipid peroxidation. Also,

Shalata and Neumann (2001) believed that antioxidant

enzymes lead to a decrease in lipid peroxidation and

MDA contents due to scavenging ROS, so that an

increase in the activity of antioxidant enzymes leads

to a decrease in lipid degradation, and in turn that

caused an increase in plant resistance to oxidative

stresses (Sreenivasulu et al., 2000).

4. CONCLUSION

The production of reactive oxygen species (ROS)

upon occurrence of environmental stresses such as

salinity, drought, and cold is one of the substantial

factors damaging plants. In such conditions plants

respond to stress through enzymatic and non-

enzymatic systems in order to either neutralize or

decrease the levels of damage due to ROS. According

to results, there were significant differences among

traits studied under both normal and stress conditions

for deter mine the resistant barley cultivar/line. The

results demonstrated that the traits were significantly

different for the genotypes with regard to their levels

of adaptation and resistance against drought stress. It

was also revealed that the antioxidant levels varied in

different genotypes and were higher under stress

conditions. Additionally, a negative and significant

correlation between antioxidant production and

macromolecule damage was found, so that the

production of more antioxidant enzymes led to the

production of less macromolecular damage increasing

plant tolerance to stress conditions due to the

protective effects of cell membranes on lipids. Overall,

it can be concluded that genotypes 18 and 19 were the

best performers and acquired acceptable levels of

tolerance under stress conditions. Once under drought

conditions, these genotypes were capable of the

production of more antioxidant enzymes offering less

reduction of damage to the macromolecules. The

results of this study also revealed that SOD, CAT, and

GPX respectively could play key roles in plant

tolerance to drought stress. Lipids, proteins, and DNA

are more sensitive to drought stress conditions,

respectively. Therefore, determination of SOD

activity and lipid peroxidation are useful indices to

select the best genotypes for cultivating in regions

with high risk of drought conditions.

REFERENCES

Amado R, Aeschbach R, Neukom H (1984).

Dityrosine: in vitro production and

characterization. Methods Enzymol., 107: 377388.

Ananeiva, DH, Rusterucci C, Holt BF, Dietrich RA,

Parker JE, Dangl JL (2002). Runaway cell

death, but not basal disease resistance, in Isd1 is

SA- and NIM1/NPR1-dependent. The Plant

Journal, 29: 381391. Aroca R, Irigoyen JJ, Sanchez-Diaz M (2003).

Drought enhances maize chilling tolerance. II.

Photosynthetic traits and protective mechanisms

against oxidative stress. Physiologia Plantarum,

117: 540549. Arora A, Sairam RK, Sriuastava GC (2002).

Oxidative stress and antioxidative system in

plants. Current Science, 82: 12271238. Arunachalam V, Bandyopadhyay A (1984). A Method

To Make Decisions Jointly On A Number of

Dependent Characters. The Indian Journal of

Genetics and Plant Breeding, 44: 419-424.

Bandeoglu E, Eyidogan F, Yucel M, Oktem HA

(2004). Antioxidant response of shoots and roots

of lentil to NaCl Salinity stress. Plant Growth

Regulation, 42: 69-77.

Bhattacharjee S, Mukherjee AK (2002). Salt stress

induced cytosolute accumulation, antioxidant

response and membrane deterioration in three

rice cultivars during early germination. Seed

Science and Technology, 30: 279- 287.

Bogdanov MB, Beal MF, Meccabe DR, Griffin RM,

Matson WR (1999). A carbon column based

LCEC approach to routine 8-hydroxy-2-

deoxyguanosine measurements in urine and

other biological matrices, Free. Rad. Biol. Med.,

27: 647-666.

Bybordi A, Tabatabaei SJ, Ahmadev A (2010). Effect

of salinity on fatty acid composition of Canola


217

(Brassica napus L). J. Food. Agric.Environ, 8:

113-115.

Candan N, Tarhan L (2003). The correlation between

antioxidant enzyme activities and lipid

peroxidation levels in Mentha pulegium organs

grown in Ca2+

, Mg2+

, Cu2+

, Zn2+

and Mn2+

stress

conditions. Plant Sci, 163: 769-779.

Chai T, Fadzillah M, Kusnan M (2005). Water stress-

induced oxidative damage and antioxidant

responses in micropropagated banana plantlets.

Biol Planta 49:153-156.

Clement M, Lambert A, Heroulart D, Boncompagni E

(2008). Identification of new up-regulated genes

under drought stress in soybean nodules. SO

Gene 426: 15-22.

Creissen GP, Mullineaux PM (2002). The molecular

biology of the ascorbatelutathione cycle in

higher plants. In: Oxidative Stress in Plants, D.

Inze, M. V. Montgan (Eds.). 15: 247-270

Dacosta M, Huang B (2007). Changes in antioxidant

enzyme activities and lipid peroxidation for

bentgrass species in responses to drought stress.

Journal of the American Society for

Horticultural Science, 132: 319326. Dat J, Vandenabeele S, Vranova E, Van Montagu M,

Inze D, Van Breusegem F (2000). Dual action

of the active oxygen species during plant stress

responses. Cellular and Molecular Life

Sciences. 57: 779795. Demiral T, Turkan I (2005). Comparative lipid

peroxidation, antioxidant defense systems and

proline content in roots of two rice cultivars

differing in salt tolerance. Environ. Exp. Bot.

53: 247-257.

Demiral MA, Aydin M, Yorulmaz A (2005). Effect of

salinity on growth chemical composition and

antioxidative enzyme activity of two Malting

Barley (Hordeum vulgare L.) cultivars. Turkish

Journal of Botany, 29: 117-123.

Dhindsa RS, Dhindsa PP, Thorpe TA (1980). Leaf

senescence correlated with increased levels of

membrane permeability and lipid-peroxidation

and decreased levels of superoxide dismutase

and catalase. Journal of Experimental Botany,

32: 93101. Dolatabadian A, Modarres-Sanavy S, Ahmadian-

Chashmi N (2008). The effects of foliar

application of ascorbic acid (vitamin C) on

antioxidant enzymes activities, lipid

peroxidation and proline accumulation of canola

(Brassica napus L.) under conditions of salt

stress. J Agron and Crop Sci., 194: 206-213.

Giannopolitis CN, Ries SK (1977). Superoxide

dismutases occurrence in higher plants. Plant

Physiology, 59: 309314.

Gratao PL, Polle A, Lea PJ, Azevedo RA (2005).

Making the life of heavy metal-stressed plants a

little easier. Functional Plant Biology, 32: 481494.

Hernandez JA, Jimenez A, Mullineaux P, Sevilla F

(2000). Tolerance of pea (Pisum sativum L.) to

long term salt stress is associated with induction

of antioxidant defences. Plant Cell Environ., 23: 853-862.

Jin J, Ningwei SH, Jinhe B, Junping G (2006).

Regulation of ascorbate peroxides at the

transcript level is involved in tolerance to post

harvest water deficit stress in the cut Rose (Rose

hybrida L.) CV. Samantha. J. Agri. Sci. Tech.,

7: 90-103.

Johnson SM, Doherty SJ, Croy PR (2003). Biphasic

superoxide generation in potato tubers: a

response to stress. Plant Physiol., 13: 1440-

1449.

Lee BR, Li L, Jung WJ, Jin Y, Avice J, Ouryy A, Kim

T (2009). Water deficit-induced oxidative stress

and the activation of antioxidant enzymes in

white clover. Bio Plantaru, 53: 505-510.

Lobato AKS, Costa RC, Oliveira Neto CF, Santos

Filho BG, Cruz FJR, Freitas JMN, Cordeiro FC

(2008). Physiological and biochemical behavior

in soybean (Glycine max L.) plants under water

deficit. Aus J of Crop Sci 2: 25-32.

Lowry O, Rosebrough A, Far A, Randall R (1951).

Protein measurement with Folin Phenol

Reagent. J Bio Chem 193: 680-685.

Manavalan LP, Guttikonda SK, Tran LSP (2009).

Physiological and Molecular Approaches to

Improve Drought Resistance in Soybean. Plant

Cell Physiol. 50: 1260-1276.

Meloni DA, Oliva MA, Martinez CA, Cambraia J

(2003). Photosynthesis and activity of

superoxide dismutase, peroxidase and

glutathione reductase in cotton under salt stress.

Brazilian Journal of Plant Physiology. 15: 12-

21.

Mirnoff N (1998). Plant resistance to environmental

stress. Curr. Opin. Biotechnol. 9: 214-219.

Misra N, Gupta AK (2006). Effect of salinity and

different nitrogen sources on the activity of

antioxidant enzymes and indole alkaloid content

in catharantus roseus seedlings. J. Plant Physiol.

163: 11-18.

Movahhedy-Dehnavy M, Modarres-Sanavy SAM,

Mokhtassi-Bidgoli A (2009). Foliar application

of zinc and manganese improves seed yield and

quality of safflower (Carthamus tinctorius L.)

grown under water deficit stress. Ind crop Prod

doi:10.1016/j.indcrop.2009.02.004.

Nayyar H, Gupta D (2006). Differential sensitivity of

C3 and C4 plants to water deficit stress:

Mohammadi et al.


218

Association with oxidative stress and

antioxidants. Environmental and Experimental

Botany, 58: 106113. Noctor G, Foyer CH (1998). Ascorbate and

glutathione: Keeping active oxygen under

control. Annu. Rev. of plant physiol. and plant

Mol. Biol.49: 249-279.

Paglia DE, Valentine WN (1987). Studies on the

quantitative and qualitative characterization of

glutation proxidase. J. Lab. Med. 70: 158-165.

Pan Y, Wu LJ, Yu ZL (2006). Effect of salt and

drought stress on antioxidant enzymes activities

and SOD iso enzymes of liquor ice

(Glycyrrhizauralensisfisch), Plant Growth

Regul. 49: 157-165.

Prasad TK (2003). Mechanisms of chilling-induced

oxidative stress injury and tolerance in

developing maize seedlings: changes in

antioxidant system, oxidation of proteins and

lipids, and protease activities, The Plant Journal. 10: 10171026.

Sairam RK, Desmukh PS, Saxena DC (1998). Role of

antioxidant systems in wheat genotypes tolerant

to water stress. Biol Plant 41: 38794. Sairam RK, Verrabhadra RK, Srivastava GC (2002).

Differential response of wheat genotypes to long

term salinity stress in relation to oxidative

stress. Plant Sci. 163: 1037-1046.

Selote DS, Khanna-Chopra R (2004). Drought-

induced spikelet sterility is associated with an

inefficient antioxidant defense in rice panicles.

Plant Physiol, 121: 462471. Shalata A, Neumann PM (2001). Exogenous ascorbic

acid (vitamin C) increases resistance to salt

stress and reduces lipid peroxidation. J. of Exp.

Bot. 52: 22072211. Shan WX, Guo HJ (2009). Changes of proline

content, activity and active isoforms of

antioxidative enzymes in two alfalfa under salt

stress. Agri. Sci. 8: 431-440.

Shao HB, Liang ZS, Shao MA (2005). Changes of

some anti-oxidative enzymes under soil water

deficits among 10 wheat genotypes at

maturation stage. Colloids Surf. B: Bio

interfaces . 45: 713. Sreenivasulu N, Grimm B, Wobns U, Weschke W

(2000). Diffrentl response of antioxidant

compounds to salinity stress in salt-tolerant and

salt-sensetive seedling of foxtail millet.

Physiology Plantarum. 109: 435-442.

Tas S, Tas B (2007). Some physiological responses of

drought stress in wheat genotypes with different

ploidity in Turkiye. World Journal of

Agricultural Sciences, 3: 178183. Tompson JE, Ledge RL, Barber RF(1987). The role of

free radicals in senescence and wounding. New

Phytol. 105: 317-344.

Valentovic P, Luxova M, Kolarovic L, Gasparikova

O (2006). Effect of osmotic stress on compatible

solutes content, membrane stability and water

relations in two maize cultivars, Plant Soil

Environment. 52: 186-191.

Vasconcelos AC, Zhang XZ, Ervin EH, Kiehl JD

(2009). Enzymatic antioxidant responses to

boistimulants in maize and soybean subjected to

drought. Sci Agricola. 66: 395-402.

Zhang H, Jiao H, Jiang C, Wang S, Wei Z, Luo J

(2010). Hydrogen sulfide protects soybean

seedlings against drought-induced oxidative

stress. Acta Physiol Plant, 32: 849857. Zhen Y, Miao L, Su J, Liu S, Yin Y, Wang S, Pang

Y, Shen H, Tian D, Qi J, Yang Y (2009).

Differential Responses of Anti-Oxidative

Enzymes to Aluminum Stress in Tolerant and

Sensitive Soybean Genotypes. J of Plant Nurt,

32: 1255-1270.

Zhenmei LU, LiyaSang P, ZimuLi H (2009). Catalase

and superoxide dismutase activities in a

Stenotrophomonas maltophilia WZ2 resistant to

herbicide pollution. Ecotox Environ Safe,

72:136143.


219

Assistant Professor Dr. Soleiman Mohammadi obtained his first degree from Tabriz University in

Agronomy and Plant Breeding in 1992. He later pursued master in Agronomy in Tabriz University and

graduated in 1995. Dr. Soleiman Mohammadi received his doctorate from Tehran Azad University of

Science and Research branch in 2003 with major in Crop Physiology. He has published over 100

scientific articles in professional journals/proceeding and sits as the Editorial Member for two Iranian

journals. At present, Dr. Mohammadi works in West Azerbaijan Agricultural research and Natural

Recourses Center as a Cereal Researcher.

Mahdi Bayat is a Ph.D candidate in Department of Agronomy, Faculty of Agriculture, Urmia University,

Urmia, Iran. He received his first degree from guilan University in 2005 awarded with Master of Science

in agricultural science, plant breeding. His current research is focuses on saffron (Crocus sativus L.) in

respect of agronomy and breeding. To date, he has published several scientific articles in ISI and Iranian

journals, also has published 4 books, in Iran, related to apply SAS, MINITAB, SPSS and MSTAT-C

softwars in agricultural researches.

Dr. Soran Sharafi obtained his PhD in Agronomy at the Islamic Azad University of Science and

Research of Tehran Iran in 2011. He is currently Assistant Professor in Agronomy at the Islamic Azad University of Mahabad Iran teaching Agroecology & Agronomy. His research has focused on Plant Stress & Plant Nutrition. He has published several scientific articles in professional journals and

conference proceedings. He has also participated in various conferences, talks and seminars.

Assistant Professor Dr. Farshad Habibi obtained his PhD in Agronomy at the Islamic Azad University

of Science and Research of Tehran Iran in 2011. He has published several scientific articles in professional ISI journals and Iranian journals. He is currently Assistant Professor in Agronomy at the

Islamic Azad University of Miandoab Iran, teaching plant physiology & Agronomy. He has also participated in various conferences, talks and seminars. His research has focused on cereal Stress &

Nutrition also has published 1 book, in Iran, related to application of Information Technology in

agricultural (ISBN: 978-964-10-0848-4).

Documents

Using Physiological Traits to Evaluating Resistance of Different Barley Promising Lines to Water Deficit Stress