International Journal of Agriculture and Crop Sciences.
Available online at www.ijagcs.com
IJACS/2012/4-21/1627-1636
ISSN 2227-670X ©2012 IJACS Journal
Evaluation of genetic diversity in land races of
bread wheat under irrigated and rainfed conditions
Mahin Ahmadi*1, Ezatollah Farshadfar*1, Sheida Veisi1
1. Faculty of Agriculture, Razi University, Kermanshah, Iran
*Corresponding author email: [email protected]
ABSTRACT: In order to investigate genetic diversity and drought resistance of 30 bread wheat
genotypes an experiment was conducted in a randomized complete block design (RCBD) with three
replications under irrigated and rainfed conditions at College of Agriculture, Razi University,
Kermanshah, Iran during 2010-2011. Analysis of variance and mean comparisons revealed
significant differences between the genotypes in both conditions. Mean values showed that all of the
agronomic and phenological traits responded to drought stress because their means values
decreased in stress condition. The most productive genotype in stress condition was number 17
(WC-5001) (6.21 ton/ha), while number 15 (WC-47615) was the least productive. In non-stress
condition genotype number 25 (Pishgam) was the most productive (7.80 ton/ha), while number 6
(WC-47578) was the least productive. Correlation analysis in drought stress condition indicated
positive significant correlation between grain yield with thousand seed weight (TSW), number of
spikes per m2 (NSP), harvest index (HI) and biological yield (BY), wherease exhibited negative
significant correlation between grain yield with days to flowering (DF= earliness) and plant height
(PH). Correlation coefficients in non-sress condition displayed positive significant correlation
between grain yield with number of seeds per spike (NSPS) and thousand seed weight (TSW).
Cluster analysis using Ward method based on yield and yield components, morphological and
phenological characteristics classified genotypes in stress and non-stress conditions in three groups.
The grouped accessions in both conditions were very similar with some minor dissimilarity. The
results indicated a high genetic diversity among the genotypes under investigation.
Key words: agronomic and morphological traits, genetic diversity, stress and non-stress conditions,
wheat landraces.
INTRODUCTION
Wheat is one of the most important cereal crops in the world. Its global consumption is behind rice and
maize and is widely grown as a rainfed crop in semi-arid areas, where large fluctuations occur in the amount
and frequency of rainfall events. The development of resistant cultivars, however, has been limited by low
heritability for drought resistance and lack of effective selection strategies (Kirigwi et al., 2004). With the
steadily growth of the world population, the demand for the food production is continually expanding (Lee et al.,
1998; Hoisington et al., 1999). To keep pace with the anticipated growth of human population, the predicted
demand for the year 2020 varies between 840 (Rosegrant et al., 1995) and 1050 million tons (Kronstad, 1998).
Given the fact that much existing arable land is decreasing due to urban and industrial development or natural
erosion such as expanding deserts (Reif, 2004), genetic improvement of crops is considered as the most viable
and sustainable approach to increase agricultural productivity (Foulkes et al., 2007; Reynolds et al., 2009).
Effective crop improvement depends on the extent of genetic diversity in the gene pools. Over the past
century, the achievements of plant breeding have contributed a lot to increase crop productivity and needs of
societies by systemically genetic improvements with utilization efficiency of agricultural inputs (Warburton et al.,
2002). However, these gains have often been accompanied by decreased genetic diversity within elite gene
pools (Lee, 1998; Fernie et al., 2006). Although landraces have a diverse genetic base, they are therefore
rarely integrated into the plant breeding programs due to their low productive performance. New varieties are
usually derived from a set of genetically related modern high-yielding varieties. As a result, many landraces
were continually replaced by modern wheat cultivars and crop improvement (Fernie et al., 2006). It has been
presumed that modern breeding practices with intensive selection leads inevitably to a loss of the genetic
diversity in crops (Cluies-Ross, 1995; Tanksley & McCouch, 1997).
The vulnerability of crops against pests and diseases and the ability to respond to changes in
environmental conditions can be drastically influenced and threaten the sustained genetic improvement (Donini
et al., 2000; Ashraf and Harris, 2005). Reduction in diversity can be counterbalanced by introgression of novel
Intl J Agri Crop Sci. Vol., 4 (21), 1627-1636, 2012
germplasm. However, it should be noted that only a small proportion of the available genetic variation of the
gene pools has been exploited for plant breeding so far (Frankel, 1977; Tanksley & McCouch, 1997; Fernie et
al., 2006), but most of the exotic pools remain untapped, uncharacterized and underutilized (Fernie et al.,
2006). Therefore, the genetic variation provided by the current and expanded gene pools should be examined
and harnessed for further crop improvement.
Diversity can be generally characterized either by apparent diversity reflecting the different
performance of crops across environments and management or by latent diversity referring to the genealogical
and molecular measurements which are not necessarily expressed in crop performance (Smale et al., 2002).
Morphological traits (syn. phenotypic traits ) are commonly used to evaluate genetic variation because
their measurements are simple. Diversity analysis, based on morphological traits alone, may not be completely
reliable because the traits are limited in number and influenced by environment (Fufa et al., 2005). Despite
these limitation, phenotypic characters have been successfully used for genetic variation studies and cultivar
development. Agronomic, morphological and phenological traits are very important for grouping wheat genetic
resources, and also are essential and useful for plant breeders seeking to improve existing germplasm by
introducing novel genetic variation for certain traits into the breeding populations (Zarkti et al,. 2010; Najaphy et
al,. 2012).
The objectives of the present investigation were (i) assessment of apparent genetic diversity in
landraces of bread wheat genotypes based on agro-phenological traits and (ii) screening drought tolerant
genotypes.
MATERIALS AND METHODS
Plant genetic materials and site description
Thirty land races of common wheat (Triticum aestivum L.) kindly provided from Dr. M. Aghaee the
head of Seed and Plant Improvement Institute of Karaj, Iran for the study of genetic diversity and screening
drought tolerant genotypes using agronomic, phenological and morphological traits (Table 1). Experiments
were conducted at Agricultural Faculty of Razi University, Kermanshah, Iran during 2010-2011. Sowing was
done in November in all experiments. The seeds were sown in four rows 2 m in length, with row to row and plot
to plot distances of 0.25m and 0.50m, respectively. The experiment was laid out in a randomized complete
block design (RCBD) with three replications under rainfed and irrigated conditions. Non-stress plots were
irrigated until maturity while, stress plots received no water. Weed control was done by hand.
Measurement of phenological and agro-morphological traits
To avoid border effects the central two rows were used for measurements. Ten random plants from
each plot were selected and the different traits were measured. One square meter in each plot was harvested
to calculate yield and yield components. The phenological traits recorded in this study were days to flowering
(DF) and physiological maturity date (PMD). The agro-morphological characters were peduncle length (PL),
spike length (SL), awn length (AL), plant height (PH), ratio of peduncle length to plant height (PL/PH), spike
density (SD), number of spikes per m2 (NSP), number of seeds per spike (NSPS), thousand seed weight
(TSW), grain yield (GY), straw yield (SY), biological yield (BY) and harvest index (HI).
Statistical analysis
Analysis of variance and mean comparisons using least significant difference (LSD) method were
done by MSTAT-C software. Correlation analysis and cluster analysis based on Ward method were performed
by SPSS software.
RESULTS AND DISCUSSION
Analysis of variance
All agro-morphological and phenological traits measured revealed significant differences among the
genotypes indicating a high genetic diversity and possible detection of drought tolerant genotypes (Table 2).
The results of combined analysis of variance (Table 2) showed highly significant differences among
environments (irrigated and rainfed conditions) for all traits except spike length(SL), days to flowering (DF),
plant height (PH), awn length (AW) and peduncle length/plant height (PL/PH) exhibiting that drought stress had
significant effect on most of the traits. Genotype × environment interaction was significant for number of spike
per m2(NSP m2), number of seed per spike (NSPS) and thousand seed weight (TSW) indicating that yield
components are sensitive to environmental fluctuations.
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Intl J Agri Crop Sci. Vol., 4 (21), 1627-1636, 2012
Table 1. Codes and names of genotypes investigated
Code
1
2
3
4
5
6
7
8
9
10
Genotypes
WC-4594
WC-4924
WC-4582
WC-4592
WC-47341
WC-47578
WC-4965
WC-4840
WC-4958
WC-47380
Code
11
12
13
14
15
16
17
18
19
20
Genotype
WC-47399
WC-4600
WC-4987
WC-47637
WC-47615
WC-4612
WC-5001
WC-4983
WC-4994
WC-47638
Co
21
22
23
24
25
26
27
28
29
30
Genotype
WC-47583
WC-47522
WC-47569
pishtaz
pishgam
WC-47640
WC-47467
WC-4553
WC-4583
WC-4554
Table 2. Combined analysis of genotypes in stress and non-stress conditions
MS
S.O.V
df
SY
BY
HI
Condition
1
142.22
460.03
0.04
*
90.63
E1
4
3.21
9.89
0.002
2.54
Genotype
29
11.81
C×G
29
6.27
E2
116
CV%
ns
ns
23.23
11.22
GY
**
4.91
ns
0.90
0.006
ns
0.003
DPM
**
DF
1531.25
29.66
**
28.25
ns
1.05
TSW
160.55
ns
ns
ns
3032.77
44.10
11.71
176.41
111.21
10.10
ns
19.22
6.66
7.68
80.37
14.64
2.40
14.64
6.02
18.10
14.28
18.65
17.06
1.74
2.27
7.96
NSP
*
7322961.45
NSPS
*
942.74
SD
*
646.13
47068.61
51.51
47.15
Table 2 continued
S.O.V
Condition
df
1
E1
4
Genotype
C×G
E2
CV%
29
29
116
PH
832.73
ns
268.49
**
1365.07
ns
127.44
PL/PH
ns
0.20
AL
ns
0.82
0.11
0.25
0.13
ns
67.75
0.13
ns
ns
0.8
MS
PL
6.66
ns
29.10
86.10
**
16.73
ns
449.61
**
21889.71
224.15
*
**
**
**
75.93
121.04
0.12
1.32
18.64
12982.36
40.67
10.15
16.36
24.11
20.91
19.52
15.74
687.11
ns
45.58
ns
29.84
ns
12.44
SL
ns
2.39
1.40
8.59
2.3
**
ns
1.26
11.92
Mean comparisons
Mean values of the traits measured in drought stress-condition are presented in Table 3. According to
DF and DPM, gonotypes 13 and 29 were the earliest accessions, while number 20 was the latest entry. Days to
flowering ranged from 160.7 to 180.3 with an average of 167.34 for AL. The entry no. 24 was awn-less. The
tallest awn belonged to genotype no. 25 while the shortest awn was related to genotype no. 26. The awn length
of most accessions was at interval of 4-6 cm. The character difference for peduncle length (PL), plant height
(PH) and peduncle length/plant height (PL/PH) ranged from 0 to 13.44. Genotype number 5 had the shortest
peduncle (11.94cm). Plant height ranged from 74.22 to 133.7 cm. The tallest genotype was number 2
(133.7cm). Genotypes number 29 and 30 revealed the highest PL/PH (0.25) and genotype number 3 exhibited
the shortest PL/PH (0.10). Spike length differed between 6.67 to 12.13. Genotype number 25 (Pishgam) - the
new released and high awn length cultivar - displayed the highest spike density (64.97) and genotype number
15 showed the shortest one (29.13). On average, number of spikes per m2 (NSP) was limited. Number of seeds
per pike (NSPS) ranged from 26.27 in genotype 30 to 51.97 in genotype 4. Thousand seed weight (TSW)
differed from 17.59 g to 33.11 g with an overall mean of 26.72 g. Accession 30 was the best from this point of
view, while had low number of seeds per spike. Grain yield varied from 2.39 to 6.21 ton/ha. The most
productive genotype was number 17(6.21 ton/ha) while, number 15 was the least productive. Harvest Index
varied from 0.15 to 0.32 and genotype number 13 had the highest harvest index. Genotype number 18
revealed the highest biological yield and straw yield, wherease genotype number 8 exhibited the lowest
biological yield and straw yield.
Mean values of traits measured in non-stress condition (Table 4) exhibited that genotypes 11 and 27
were the earliest accessions, while number 3 was the latest. Days to flowering ranged from 160 to 181.7 with
an average of 169.22. Genotype number 4 had the shortest peduncle (13.05cm). Plant height ranged from
73.09 to 138 cm. The tallest genotype was number 2 (138cm). Spike length differed between 7 to 12.75.
Genotype number 25 (Pishgam) had the highest spike density (85.76) and genotype number 15 indicated the
shortest (25.65). Genotype 11 displayed minimum number of spikes (374.7) and maximum number of spike
belonged to genotype 1 (839).
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Intl J Agri Crop Sci. Vol., 4 (21), 1627-1636, 2012
Table 3. Mean values of phenological and agro-morphological traits measured in stress condition with LSD 5% test
Genotype
code
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Average
Max
Min
LSD 5%
TSW
(gr)
26.11
31.78
23.93
24.56
21.32
23.05
17.59
22.88
31.61
29.12
29.43
30.13
25.04
25.48
25.79
26.49
28.31
27.89
30.35
21.37
28.47
20.61
25.29
28.22
29.34
27.19
25.45
32.99
28.75
33.11
26.72
33.11
17.59
4.04
AL(cm)
PL(cm)
7.06
5.71
6.63
6.81
5.88
6.44
8.73
5.88
0.31
0.37
3.66
5.22
0.73
7.77
6.88
5.82
0.35
1.25
0.39
4.33
0.5
6.31
7.03
0
13.44
0.16
7.37
5.54
3.77
6.55
4.70
13.44
0
1.89
15.54
20.11
13.91
11.94
28.88
18.11
14.54
23.28
25.22
22.81
24.61
21.9
17.86
15.55
20.39
21.38
24.47
18.48
23.54
16.55
18.27
20.22
20.33
20.38
18.28
19.33
17.92
26.05
27.67
26.16
20.45
28.88
11.94
8.13
PH(cm)
99.41
133.7
128.7
74.22
128.2
114.2
102.5
113.8
119.2
119.3
106.6
109.5
92.61
86.17
109.6
121.8
128.1
126.5
125.4
90.77
118.6
100.3
108.5
103.9
95.94
124.4
95.84
122.3
110.3
104.8
110.50
133.7
74.22
13.84
NSPS
31.60
39.83
40.07
51.97
39.07
30.33
44.13
32.40
38.60
33.23
47.13
33.57
40.77
38.60
35.22
36.77
33.47
42.20
33.77
45.40
38.20
41.40
33.73
38.73
43.87
39.2
42.6
33.4
41.33
26.27
38.22
51.97
26.27
8.76
NSP.m
2
898.7
448.7
575.3
571.3
628.7
626.7
635.3
758
759.3
670.7
522.7
608.7
523.3
666
585.3
811.3
825.3
676
743.3
658.7
520
581.3
912.7
682
519.3
558
686
568.7
560.7
640
647.4
912.7
448.7
203.1
DPM
(day)
204.7
207
207.3
211.3
205.7
206
208
207.3
207.7
206
206.3
206.3
200.3
206
206.3
206.7
207
206.3
207
212
208
205.3
206.7
207.7
206.7
205.3
207
207.7
203
206.3
206.15
212
200.3
2.89
SD
31.58
43.15
35.67
56.41
46.09
38.22
48.42
31.57
37.86
37.39
52.47
30.79
61.1
43.52
29.13
39.38
38.61
40.07
34.71
57.15
33.92
44.61
30.53
43.08
64.97
36.52
51.38
36.38
49.67
35.92
42.00
64.97
29.13
6.80
SL(cm)
10.25
9.23
11.3
9.3
8.43
7.93
9.04
10.3
10.23
8.85
8.93
10.91
6.67
8.72
12.13
9.34
8.63
10.56
9.75
7.96
11.30
9.27
10.97
8.96
6.75
10.67
8.28
9.17
8.33
7.5
9.32
12.13
6.67
1.69
Table 3. continued
Genotype
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Average
Max
Min
LSD 5%
DF(day)
167.3
169.7
180.3
165.7
168.3
174.7
174.3
162.7
165.7
165.7
160.7
163
161
161.7
176.7
169.7
165.3
165.7
167
170.3
169
172
167.3
167.7
170.3
171.7
161
163.3
161.3
163.3
167.34
180.3
160.7
5.55
PL/PH
0.15
0.15
0.10
0.16
0.22
0.15
0.14
0.20
0.21
0.19
0.23
0.19
0.19
0.18
0.18
0.17
0.19
0.14
0.18
0.18
0.15
0.20
0.18
0.19
0.19
0.15
0.18
0.21
0.25
0.25
0.18
0.25
0.10
0.05
GY(T/ha)
4.44
4.24
4.32
4.57
3.66
3.52
3.70
4.07
6.15
5.42
3.89
3.76
4.88
4.79
2.39
4.92
6.21
5.26
5.10
4.34
3.21
3.63
4.26
5.00
5.11
4.19
4.49
4.53
4.62
4.45
4.44
6.21
2.39
1.29
HI
0.24
0.22
0.26
0.25
0.19
0.21
0.21
0.28
0.29
0.27
0.25
0.23
0.32
0.27
0.15
0.25
0.30
0.25
0.26
0.23
0.21
0.22
0.25
0.28
0.29
0.22
0.27
0.23
0.25
0.24
0.25
0.32
0.15
0.073
SY(T/ha)
13.95
14.76
12.35
13.56
14.80
12.94
13.83
10.40
14.51
13.98
11.64
12.03
12.25
13.21
13.61
14.48
14.25
15.74
15.36
14.32
11.85
12.56
12.34
13.06
12.75
15.54
12.17
14.53
13.11
13.41
13.07
15.74
10.40
4.06
BY
(T/ha)
18.39
19
16.67
18.13
18.47
16.47
17.53
14.47
20.67
19.40
15.53
15.80
15.13
18
16
19.4
20.47
21
20.47
18.67
15.07
16.2
16.6
18.07
17.87
19.73
16.67
19.07
17.73
17.87
17.71
21
14.47
4.38
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Intl J Agri Crop Sci. Vol., 4 (21), 1627-1636, 2012
Table 4. Mean values of phenological and agro-morphological traits measured in non- stress condition
Genotype
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Average
Max
Min
LSD 5%
TSW(gr)
29.03
40.11
41.05
36.94
26.23
28.88
24.31
30.12
41.95
43.81
34.66
32.74
31.71
37.73
30.17
40.21
42.13
33.35
39.14
25.42
38.58
29.67
30.77
35.85
38.13
36
32.52
40.36
37.35
39.06
34.93
43.81
24.31
3.98
SD
DF(day)
34.21
47.97
43.53
63.0
56.3
40.81
53.07
34.86
43.78
42.54
42.39
29.94
68.9
51.11
25.65
40.52
33.53
44.1
43.69
59.11
31.26
47.49
33.36
48.39
85.76
38.67
49.89
38.71
45.85
49.52
45.80
85.76
25.65
10.64
167.7
168.3
181.7
165
172
177.3
175
167.3
169.7
166.3
160
164.7
161
161.3
181
173.3
171
170.3
170.3
171.3
170
175.3
171.7
162.3
174
176.7
160
170.3
161.3
160.7
169.22
181.70
160
6.27
AL
(cm)
7.75
6.80
7.27
7.55
5.94
7.05
7.30
7.00
0.24
0.42
4.12
5.91
0
6.93
6.66
3.81
0.39
0.61
0.11
5.12
0.87
6.20
7.87
0.24
14.27
0.26
8.10
5.18
4.36
6.70
4.83
14.27
0
1.85
NSPS
35.73
44.90
50.53
54
56.2
36.5
50.73
36.77
48
43.5
46.37
25.27
48.53
49.77
26.8
48.67
34.2
48.5
44.87
41.23
31.17
43.6
30.8
41.97
60
37.43
42.23
45.47
39.4
41.03
42.80
60
25.27
9.63
PH
108
138
117
75.6
120
108
95.1
105
118
126
103
96.2
93.5
80.3
99.5
114
121
129
121
73.9
103
92.2
103
88.5
95.3
118
86.9
125
98
135
106.19
138
73.90
21.33
Yp
(T/ha)
4.66
6.23
65.1
7.48
4.86
3.70
6.02
5.24
7.14
7.27
5.86
3.74
5.80
7.76
3.77
6.83
6.55
6.37
6.57
5.03
4.79
5.12
4.85
6.65
7.80
5.76
5.65
6.29
5.42
6.01
5.86
7.80
3.70
1.56
SL
(cm)
9.81
9.34
11.63
8.56
10
8.9
9.56
10.53
10.9
10.2
9.6
8.55
7.02
9.73
10.34
12.75
10.14
11.01
10.27
7.12
9.88
9.16
9.23
8.64
7
9.7
8.48
11.81
8.40
8.33
9.55
12.75
7
1.96
Table 4. continued
Genotype
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Average
Max
Min
LSD 5%
PL/PH
0.21
0.19
0.14
0.17
0.26
0.16
0.21
0.20
0.18
0.20
0.26
0.22
0.21
0.16
0.18
0.15
0.20
0.17
0.17
0.23
0.21
0.23
0.23
0.20
0.18
0.17
0.17
0.17
0.21
0.20
0.19
0.26
0.14
0.051
NSP/m
839
495.3
484.7
502.7
539.3
514
682
613.3
446.7
519.3
374.7
572
440.7
539.3
599.3
434.7
478
474.7
434
693.3
516
550
532.7
543.3
377.3
554.7
508
458.7
428.7
458.7
519.83
839
374.7
167.7
2
PL (cm)
1.99
26.96
16.94
13.05
31.33
17.83
20.63
20.88
21.11
25.72
26.83
21.27
19.90
13.33
17.72
17.97
24.37
22.94
21.02
17.53
21.41
21.16
24.10
18.49
17.22
20
15.18
21.78
21.56
25
20.84
31.33
13.05
5.78
SY(T/ha)
16.61
14.54
16.85
12.57
15.71
15.01
14.26
16.64
16.95
16.48
15.4
11.86
13.63
14.20
13.54
16.14
19.68
21.17
16.13
13.16
14.12
12.76
14.45
13.33
14.74
13.72
14.17
14.32
15.07
17.42
15.03
21.17
11.86
4.36
BY(T/ha)
21.27
20.77
23.36
20.05
20.58
18.70
20.28
21.88
24.09
23.75
21.27
15.6
19.43
21.96
17.31
22.98
26.24
27.53
22.71
18.19
18.91
17.88
19.31
19.98
22.55
19.48
19.82
20.61
20.5
23.43
20.89
27.53
15.6
4.67
HI
0.22
0.30
0.28
0.37
0.23
0.2
0.3
0.24
0.3
0.31
0.27
0.24
0.3
0.35
0.22
0.30
0.25
0.23
0.29
0.27
0.25
0.28
0.25
0.33
0.34
0.32
0.29
0.30
0.26
0.25
0.28
0.37
0.20
0.089
DPM(day)
211
214.3
215
218.7
212
212
214
213
212
212
211
211
205.7
211
213
213
211.7
211.7
212.7
218.3
213
211
212.7
213
213
212
212
213
208.7
212.7
212.47
218.70
205.7
2.09
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Intl J Agri Crop Sci. Vol., 4 (21), 1627-1636, 2012
Number of seeds per spike (NSPS) ranged from 25.27 in genotype 12 to 60 in genotype 25. Thousand
seed weight (TSW) differed from 24.31 g to 43.81 g with an overall mean of 34.93 g. Grain yield varied from
3.70 to 7.80 ton/ha. The most productive genotype was number 25 (Pishgam) (7.80 ton/ha) while number 6
was the least productive. Harvest index varied from 0.20 to 0.37. Genotype number 4 had the highest harvest
index. Genotype number 18 showed the highest biological yield and the highest straw yield, while genotype
number 12 revealed the lowest biological yield and straw yield.
Mean values of the traits measured in two conditions showed that all of the traits responded into drought stress.
As their means decreased in stress condition. Kirby & Jones (1997) and Giunta et al. (1993) also reported that
mean decreased in grain yield because of drought stress. Maximum yield in non-stress and stress conditions
belonged to genotypes number 25 (Pishgam) and number 17 (WC-5001), respectively.
Minimum grain yield, harvest index and spike density was attributed to the genotype 15 (WC-47615) in
both conditions. Cecarelli (1998) investigation reaches to a conclusion that the largest genetic gain in barley
was obtained when using landraces and direct selection under severe stress-conditions. On the other hand, in
soybean Sneller and Dombek (1997) reported that selection from irrigated trials would improve yield in drought
environment better than selection from non-irrigated trials. Mean of HI indicator slaked and from 0.28% in nonstress condition decreased to 0.25% in stress-condition. Decrease of HI under drought stress reported by
Ehdaie & Waines (1996) and Gardner et al. (1985). Grain yield was also decreased in drought stress condition.
Decline of grain yield reported in many researches (Gooding et al., 2003; Ozturk & Aydin, 2004; Shah &
Paulsenl, 2003; Wardlaw, 2002). Our results are also in agreement with those of Sio-se Mardeh et al. (2006)
that there is a low level of consistency in yield performance of genotypes under stress and non-stress
conditions. High yield and drought adaptation are often based on different and, to some extent, conflicting
mechanisms (Rizza et al., 2004). The situation emphasizes the need to select genotypes in target
environments to improve their yield under drought stress condition.
Cluster analysis
The clustering pattern of the wheat genotypes based on phenotypic data using Ward method, is
depicted (Fig 1 and 2) . In drought stress-condition cluster analysis assigned the genotypes into three groups
(Fig 1). Group1 included fourteen accessions characterized by high yielding genotypes. Second cluster
contained thirteen genotypes with the lowest spike density (SD) and harvest index (HI). In the third cluster,
three genotypes (number 4, 13 and 20) were classified with average traits. In the non-stress condition cluster
analysis classified the genotypes into three groups (Fig 2). Group1 consisted of nine genotypes characterized
by maximum plant height (PH) and thousand seed weight (TSW). Fifteen genotypes situated in group 2 with
minimum amount of thousand seed weight (TSW), grain yield (GY), spike density (SD) and harvest index (HI).
Third cluster included six genotypes with the highest grain yield (GY), spike density (SD), harvest index (HI)
and the lowest plant height (PH). Grouping pattern was confirmed by discriminant analysis. The grouping
pattern in both conditions was very similar with some minor dissimilarity. Agronomic, morphological and
phenological traits are very important with well potential for grouping wheat genetic resources, and also are
essential and useful for plant breeders seeking to improve existing germplasm by introducing novel genetic
variation for certain traits into the breeding populations (Lage et al., 2003; Pagnotta et al., 2005; Salem et al.,
2008; Pagnotta et al., 2009; Zarkti et al,. 2010; Najaphy et al,. 2012).
Correlation analysis
Correlation analysis in drought stress condition (Table 5) showed positive and significant associations
between grain yield with TSW, NSP, HI and BY and indicated negative and significant correlation between
grain yields with DF. Plant height (PH) revealed positive and significant correlation with PL, SL and SY, while
showed negative and significant correlation with AL and SD. Spike density (SD) displayed positive and
significant correlation with NSPS and negative significant correlation with NSP.
Correlation analysis in non-sress condition (Table 6) exhibited a positive significant correlation between
grain yield with NSPS, SD, HI, TSW and BY whereas, negative significant correlation was found with NSP and
PL/PH. Spike Length (SL) exhibited a positive significant association with PH, DF and BY. A positive significant
correlation was also observed between grain yield with NSPS and TSW. In stress condition our results are in
agreement with those of Moral et al. (2003) and Simanne et al. (1993) who reported a negative correlation
between TSW and NSPS and a significant positive association between grain yield with HI and BY. High
significant positive correlation between BY and GY has also been reported in other studies (Ehdaie, 1998;
Gardner et al ., 1985; Kobata et al., 1992).
1632
Intl J Agri Crop Sci. Vol., 4 (21), 1627-1636, 2012
Table 5. Correlation coefficients between traits in stress condition
TSW(1)
DF(2)
Ys(3)
HI(4)
PH(5)
AL(6)
PL(7)
PL/PH(8)
SL(9)
SD(10)
NSPS(11)
NSP(12)
DPM(13)
BY(14)
SY(15)
(1)
1
-0.42*
0.39*
0.25
0.32
-0.31
0.46**
0.32
-0.02
-0.22
-0.31
-0.10
-0.09
0.34
0.20
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
13)
14)
1
-0.40*
-0.52**
0.25
0.24
-0.39*
-0.63**
0.34
-0.18
0.02
-0.11
0.22
-0.04
0.18
1
0.82**
0.09
-0.36
0.15
0.11
-0.32
0.18
0.00
0.37*
-0.005
0.68
0.29
1
-0.17
-0.22
0.01
0.17
-0.42*
0.32
-0.04
0.25
-0.23
0.15
-0.28
1
-0.40*
0.50**
-0.13
0.37*
-0.54**
-0.41
0.04
-0.12
0.37
0.43
1
-0.32
-0.08
-0.17
0.22
0.10
-0.07
0.13
-0.32
-0.20
1
0.78**
-0.11
-0.23
0.41*
0.07
-0.27
0.22
0.20
1
-0.39
0.14
-0.16
-0.003
-0.28
-0.05
-0.13
1
-0.74**
-0.15
0.20
0.18
-0.07
0.09
1
0.75**
-0.43*
0.01
-0.04
-0.16
1
-0.43*
0.28
-0.03
-0.04
1
0.08
0.29
0.16
1
0.22
0.29
1
0.89
Table 6. Correlation coefficients between traits in non-stress condition
NSP(1)
NSPS(2)
SD(3)
SL(4)
PL/PH(5)
PL(6)
AL(7)
PH(8)
HI(9)
DF(10)
Yp(11)
TSW(12)
DPM 13)
BY 14)
SY (15)
(1)
1
-0.36*
-0.29
-0.05
0.21
-0.08
0.18
-0.27
-0.30
0.18
-0.45*
-0.62**
0.22
-0.35
0.14
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
(13)
(14)
1
0.79**
0.007
-0.13
-0.08
0.17
-0.008
0.59**
-0.04
0.70**
0.13
0.14
0.42
-0.15
1
-0.58**
0.06
-0.20
0.31
-0.32
0.57**
-0.20
0.50**
-0.06
0.07
0.09
0.44
1
-0.38*
0.15
-0.26
0.53**
-0.14
0.37*
0.13
0.34
0.08
0.41
-0.12
1
0.62**
-0.01
-0.14
-0.27
-0.29
-0.38*
-0.47**
-0.18
-0.26
0.38
1
-0.24
0.66**
-0.41*
-0.07
-0.20
0.005
-0.27
0.21
-0.21
1
-0.29
0.003
0.15
-0.10
-0.31
0.29
-0.21
0.61
1
-0.29
0.19
0.07
0.44*
-0.14
0.52
0.02
1
-0.23
0.80**
-0.41*
0.23
0.06
-0.19
1
-0.21
-0.15
0.32
-0.08
0.25
1
0.64**
0.16
0.64
0.29
1
-0.01
0.51
0.90
1
-0.01
-0.11
1
0.90
15)
1
1633
15
1
Intl J Agri Crop Sci. Vol., 4 (21), 1627-1636, 2012
Figure 1. Cluster analysis of wheat genotypes using Ward method in stress condition
1634
Intl J Agri Crop Sci. Vol., 4 (21), 1627-1636, 2012
Figure 2. Cluster analysis of wheat genotypes using Ward method in non-stress condition
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