Sweetpotato is a major staple food in the world. It is a good source of carbohydrates, vitamin A, vitamin C and protein. The maximum production potential of the crop is being hampered by severe drought which ravages most parts of Africa. The main aim of this study therefore was to screen accessions of sweetpotato for drought tolerance in a quick screening method, followed by field screening with a view to identify accessions that can perform well under water stress conditions. Fifty sweetpotato accessions consisting of cultivars and breeding lines collected from the ARC-VOPI gene bank were planted for drought screening in the glass house for six weeks during which water was withheld to induce stress. Observations were made on number of dead plants and days to wilting point. The results were analyzed and 12 best performing accessions were selected for field trials. The field trial was carried out in Lwamondo, Limpopo province, a drought prone area in South Africa, under rain-fed conditions. The best performing accessions were Zapallo, Tacna, Ejumula, 2004-9-2 and Ndou.
Rainfed agriculture covers 80% of the world’s cultivated land, and is responsible for about 60% of crop produc- tion [1] . Drought, amongst other environmental factors, contributes to about 75% yield loss each year in the world [2] . Agriculture is the largest consumer of water in the world and in the drier areas of the world including South Africa which is regarded a water-stressed country [3] . The use of water for agriculture can exceed 90 per- cent of consumption [4] . Global warming is also predicted to affect developing countries severely where agri- cultural systems are most vulnerable to climatic conditions. [5] predicted considerable increases in number of hot days due to climate change in Limpopo Province South Africa, a popular sweetpotato growing region which will be detrimental to productivity.
The Food and Agricultural Organization of the United Nations [2] estimates that by 2025 approximately 480 million people in Africa could be living in areas with very scarce water, and that as [1] climatic conditions dete- riorate, 600,000 km2 currently classed as moderately constrained will become severely limited. It is thus essen- tial to improve water use efficiency in agriculture. This will require an integrated approach to water resources management to encourage an efficient and equitable use of the resource, and to ensure sustainability. The identi- fication of crop varieties with increased tolerance to drought is therefore an important strategy to meet global food demands with less water. According to [2] the inadequate knowledge of varieties and environmental condi- tions is causing drought to have such a high impact on yield.
Sweetpotato (Ipomoea batatas) is a major staple food in Africa, Asia, the Caribbean, and South America, where they are important sources of carbohydrates, vitamins A and C, fiber, iron, potassium, and protein [6] . Sweetpotato is also used as animal feed. Increasing recognition of the great potential of the sweetpotato crop as a nutritious food for humans and animals has resulted in intensified research efforts to enhance production and consumption in recent decades [7] . It has the advantage over other crops in the fact of providing a quick yield during a short growth period and providing a stable productivity less affected by climatic factors [8] . Sweetpo- tato also has flexible planting and harvesting times, tolerates high temperatures and low fertility soils. It is drought tolerant and easy to propagate. Furthermore, compared to other crops, sweetpotato requires fewer inputs and labour making it particularly suitable for households threatened by migration or diseases such as HIV/AIDS [9] . The crop is grown over a broad range of environments and cultural practices and is commonly grown in low-in- put agriculture systems [10] .
Sweetpotato, despite being a hardy crop by nature, is sensitive to water deficits particularly during the estab- lishment period including vine development and storage root initiation [11] . Drought often is a major environ- mental constraint for sweetpotato production in areas where it is grown under rain fed conditions [12] . However, different genotypes may respond differently to limited quantities of soil water [12] [13] . Selection for good cul- tivar performance under drought conditions is thus considered to be of major importance. Drought necessitates additional irrigation periods, and this increases the overhead production costs. South Africa is regarded as being susceptible to water stress conditions due to prevalence of drought [14] . Research into drought tolerant plants is being intensified in order to minimize its overall impact on the agricultural enterprise. The development of drought tolerant sweetpotato varieties will increase profitability to farmers by potentially limiting irrigation and associated production overhead costs.
Genotypic variability exists for drought tolerance with some clones performing better under drought condi- tions [13] . Selection and improvement of adapted genotypes for a particular environment can therefore, be done with the appropriate equipment and using selection criteria associated with drought tolerance [13] . With this ge- netic management option, drought-tolerant varieties, once developed, would be a low economic input technolo- gy that may be readily acceptable by resource-poor, rain fed, small land holding farmers. Consequently, the ob- jectives of this study is to screen breeding lines and land races for drought tolerance in a quick screening me- thod, evaluate the selected breeding lines and land races for drought tolerance under field condition and iden- tify accessions that can perform well under water stress conditions without a significant loss of yield and qual- ity.
2. Materials and Methods2.1. Pre-Screening
The pre-screening was carried out in the drought screening glass house at Agricultural Research Council-Vege- table and Ornamental Plant Institute (ARC-VOPI), South Africa (Latitude 25.604˚S, Longitude 28.345˚E and Altitude 1159 m). The plant materials used for this experiment were 50 sweetpotato accessions obtained from the gene bank of ARC-VOPI (Table 1). The materials consisted of local cultivars, imported accessions and ARC breeding lines/accessions. The pre-screening of accessions was done between March and August 2008. Stem cuttings of the 50 accessions were planted in plastic boxes of size 155 cm × 77 cm × 23 cm. The boxes were filled with a special soil mixture (5:2:2 sand:soil:vermiculite). Sweetpotato cuttings of about 30 cm long from each accession were cut and planted 2 eyes/nodes below the surface and 3 eyes/nodes above the surface for uniformity of development. Eight accessions were planted in each box with the plant spacing 15 cm between rows and 10 cm between plants and a box contained ten rows (5 plants/row). In each box 8 accessions and 2 control accessions were planted to serve as positive and negative controls namely Lethlabula (drought tolerant and positive control) and Resisto (drought sensitive and negative control). The design was randomized complete block design (RCBD) with 6 replicates consisting of a total of 38 boxes. The experiment was watered for 10 - 14 days for establishment after which water was withheld to induce stress. The experiment was concluded 60 DAP when 60% - 70% of the plants showed severe stress and wilting.
2.2. Field Experiment
The field trial was done at Lwamondo Agricultural Station in Thohoyandou in Limpopo Province, South Africa between March and September 2009. It lies at 23.06'S latitude and 30.38'E longitude with an altitude of 618 m above sea level. Climate conditions are subtropical with average annual rainfall of 752 mm with over 80% oc- curring between October and December. The average maximum and minimum temperature in the area is be- tween 28.5˚C and 13.7˚C.
The 12 accessions used for the field trials were Zapallo, Resisto, Ejumula, Tacna, 1999-3-1, 2004-16-1, 2004- 5-2, 2004-9-2, W-119, Phala, 2003-24-2 and Ndou. These consisted of 10 accessions selected based on the re- sults of the pre-screening trial (Table 2), Resisto, the drought sensitive negative control and Ejumula which was an addition from the previous box experiment. Ejumula was found in previous experiment to be drought tolerant and was therefore used as a replacement for cultivar Japon Tresmesino Selecto which did not have enough planting material available for the field trial. An area of land measuring 20 m × 60 m was used for the trial. Field preparation included making ridges of 0.3 m high and spaced 1 m between the center of the ridges. Before planting Limestone Ammonium Nitrate (LAN, 28% N) was applied at 150 kg/ha (110 g/plot) and super grow (18.5% P) was applied at 150 kg/ha (110 g/plot) to the field by broadcasting method and incorporated into the soil. The cuttings were planted the next day in a triple row of 8 plants per row (24 plants/plot) with spacing of 1 m between rows and 0.3 m between plants and replicated 5 times. The design was randomized complete block design (RCBD). Two border rows were planted on each side of each block. The whole plot was watered using overhead irrigation for 7 days to facilitate plant establishment after which water was withheld till the end of the experiment. Weeding was done manually to remove unwanted plants.
2.3. Data Collection2.3.1. Plastic Box Pre-Screening
Visual observations were made weekly on the condition of the plants. The date was recorded when the plants in a plot showed severe wilting. At the end of the experiment (60 DAP) the number of dead plants per plot were also counted and recorded. The number of days to severe wilting was then calculated. Data analysis for tolerance parameters such as number of days to death and number of dead plants were performed with [15] and included an analysis of variance (ANOVA) to obtain mean values, and the student’s protected t-LSD test was calculated at the 0.01 probability level. The multiple t-distribution test procedure [16] was performed to group the lines as sensitive, intermediate or tolerant to drought stress.
2.3.2. Field Experiment
Data were collected on two plants at the middle rows at 42 days after planting (DAP), 84 DAP and 120 DAP and the following parameters were recorded and evaluated.
2.3.3. Plant Growth
Lengths of the shoots were measured using a meter tape and two plants were selected from each plot and meas-
Sweetpotato accessions used for box screening and their characteristics
No
Cultivar
Origin
Skin color
Flesh color
Storage root shape
1
Wit Blesbok
RSA
Copper
Dark cream
Obovate-Long elliptic
2
Lobed JIII
RSA
Purple
Cream
Long irregular
3
TO-1-1-B
RSA
Purple
Cream
Long irregular-Long oblong
4
Malavuwe III VM-5B
RSA
Purple
White
Long oblong
5
Hlabisa 4
RSA
Pink cream
White
Very long elliptic
6
3 Maande wit
RSA
White
White
Long irregular-Long oblong
7
6 Maande wit
RSA
White
White
Long irregular-Long oblong
8
Chingowa
Zambia
Cream
Cream
Long oblong-Long irregular
9
Xushu 18
Taiwan
Purple
White
Long elliptic-Oblong
10
Yan Shu 1
Taiwan
Pale purple
White
Heavy oblong
11
Atacama
Peru
Dark purple
White
Obovate-Round elliptic
12
Tacna
Peru
Copper
Pale yellow
Elliptic-Heavy elliptic
13
ST87.030
Peru
Pale light yellow
Light yellow
Round ell-Obovate
14
Zapallo
Peru
Pale orange
Orange cream
Round
15
Japon Tresmesino Selecto
Peru
Pink, cream
Orange cream
Ovate-Round
16
Jewel
USA
Orange brown
Orange
Long oblong
17
Cemsa 74-228
Cuba
Cream
Cream
Long oblong-Long irregular
18
Tanzania
Uganda
Cream
White
Long oblong-Long irregular
19
Toquecita
Puerto Rico
Cream
Cream
Long oblong-Long irregular
20
2004-3-8
ARC
Yellow orange
Orange
Obovate-Elliptic
21
2004-3-9
ARC
Purple
Pale orange
Obovate-Elliptic
22
2004-5-2
ARC
Yellow orange
Orange
Elliptic-Obovate
23
2004-9-1
USA
Purple
Orange
Elliptic-Long elliptic
24
2004-9-2
USA
Pink purple
Orange
Round elliptic-Short oblong
25
2004-9-5
USA
Pale red pink
Dark orange
Elliptic-Obovate
26
2004-10-1
ARC
Purple pink
Dark orange
Obovate-Elliptic
27
2004-11-8
ARC
Bright pink red
Dark orange
Elliptic-Round elliptic
28
2004-14-5
ARC
Yellow orange
Dark orange
Obovate-Elliptic
29
2004-16-1
ARC
Bright purple
Orange
Round elliptic-Obovate
30
2004-17-5
ARC
Dark purple red
Very dark orange
Elliptic-Obovate
31
2004-17-8
ARC
Orange
Dark orange
Obovate-Elliptic
32
Bosbok
ARC
Purple
White
Oblong-Long Oblong
33
Ndou
ARC
Dark cream
Dark cream
Round elliptic-Long elliptic
34
W-119
USA
Pink purple
Orange
Long elliptic-Long irregular
35
1999-1-3
ARC
Pale orange
Pale orange
Round elliptic
36
1999-9-4
ARC
White
White
Round
37
Hernandez
USA
Orange brown
Dark orange
Oblong
38
Impilo
ARC
Cream orange
Pale orange
Round elliptic
39
2000-3-1
ARC
Cream-white
Cream
Long elliptic-Obovate
40
1999-3-1
ARC
Pink copper-pale purple
Dark cream
Long elliptic-Round elliptic
41
2000-10-7
ARC
Pale pink
Orange
Obovate-Round elliptic
42
2001-5-2
ARC
Dark purple
Dark orange
Oblong-Long irregular
43
2002-21-1
ARC
Orange
Orange
Round elliptic-Obovate
44
2003-11-3
ARC
Pale orange
Dark orange
Obovate-Elliptic
45
2003-20-1
ARC
Cream orange
Dark orange
Elliptic-Obovate
46
2003-23-6
ARC
Dark purple red
Dark orange
Obovate-Elliptic
47
2002-24-2
ARC
Pale orange
Dark orange
Elliptic-Round elliptic
48
Khano
ARC
Pale red purple
Dark orange
Long elliptic
49
Phala
ARC
Purple
Cream
Oblong
50
Amasi
ARC
Cream brown
Cream orange
Oblong
ured with the meter tape and the lengths of the shoots were recorded.
2.3.4. Dry Matter Content
Plants were harvested and the fresh weight of both the roots and the shoots were taken separately using a mea- suring scale. The fresh roots were washed of soil particles and weighed for fresh weight and then cut into pieces and put in a labeled envelope and then oven-dried at 72˚C for 24h00 to get the dry weight. The shoots were placed in a labeled envelope and oven-dried at 40˚C for 24h00 to get the dry weight. The weights were recorded in a data sheet. The dry matter was calculated as follows:
2.3.5. Canopy Temperature
Recordings of the temperature of the canopy were done in the early hours of the morning using an infra-red thermometer (Raytek Raynger ST20). This was taken at 1 m from the plot edge and 50 cm above the canopy, focusing on the leaves only to reflect exact reading.
2.3.6. Yield
The storage roots of the whole plot were harvested at 120 DAP. The storage roots were thereafter graded into marketable, unmarketable based on their shapes, sizes, weights and defects. Marketable roots were greater than 100 g with a diameter of 3 cm and above when measured and no noticeable pest attack or diseases. Unmarketa- ble roots those less than 100 g and the diameter is less than 3 cm and those showing defects (cracks, irregular shape) and pest infestation.
2.4. Data Analysis
Data collected were subjected to statistical analysis using computer software [17] . Analysis of variance (ANOVA) was computed and means were compared by the least significance difference at 1% probability level.
3. Results and Discussion3.1. Drought Response during Pre-Screening
The results of the pre-screening trial are shown in Table 2. The entries survived between 46 and 60 days before dying. The mean number of days to death was 56.44. The accession with the shortest days to wilting was Yan Shu1 (46.57) and those with the longest day to wilting were Atacama and 2004-16-1 (60.00). Most of the acces- sions started wilting at 57 days when the experiment was almost concluded indicating that the accessions are generally tolerant to water stress. According to [18] , the physiological responses of plants to a deficit of water include leaf wilting, a reduction in leaf area, leaf abscission, and the stimulation of root growth by directing nu-
Result of plastic box screening experiment
Nr
Line/Variety*
DTD
SD
Group
Nr
Line/Variety
No Dead
SD
Group
11
Atacama
60.00
0.0
T
11
Atacama
0.00
0.00
T
29
2004-16-1
60.00
0.0
T
29
2004-16-1
0.00
0.00
T
22
2004-5-2
59.50
0.8
T
22
2004-5-2
0.50
0.84
T
15
Japon Tres
59.17
2.0
T
15
Japon Tres
0.83
2.04
T
24
2004-9-2
59.17
2.0
T
24
2004-9-2
0.83
2.04
T
35
1999-1-3
59.17
2.0
T
34
W-119
0.83
2.04
T
47
2003-24-2
59.03
1.9
T
35
1999-1-3
0.83
2.04
T
12
Tacna
59.00
2.0
T
47
2003-24-2
0.83
1.33
T
42
2001-5-2
59.00
2.0
T
12
Tacna
1.00
2.00
T
20
2004-3-8
58.70
2.1
T
20
2004-3-8
1.00
2.00
T
23
2004-9-1
58.70
2.1
T
23
2004-9-1
1.00
2.00
T
38
Impilo
58.67
2.0
T
42
2001-5-2
1.00
2.00
T
14
Zapallo
58.53
2.3
T
14
Zapallo
1.17
2.04
I
40
1999-3-1
58.33
2.6
T
38
Impilo
1.33
1.97
I
34
W-119
58.17
4.5
T
19
Toquecita
1.50
1.87
I
41
2000-10-7
58.03
3.1
T
13
ST87.030
1.67
2.58
I
13
ST87.030
57.73
3.7
T
40
1999-3-1
1.67
2.58
I
+C
Lethlabula
57.72
-
T
41
2000-10-7
1.67
2.58
I
2
Lobed JIII
57.67
2.3
T
+C
Lethlabula
1.80
-
I
48
Khano
57.62
2.9
T
28
2004-14-5
2.00
2.45
I
8
Chingovwa
57.50
2.7
T
48
Khano
2.00
2.45
I
16
Jewel
57.50
2.7
T
49
Phala
2.00
2.45
I
19
Toquecita
57.50
2.2
T
39
2000-3-1
2.17
2.32
I
21
2004-3-9
57.50
2.7
T
2
Lobed JIII
2.33
2.34
I
28
2004-14-5
57.50
3.3
T
33
Ndou
2.33
2.58
I
32
Bosbok
57.50
2.7
T
8
Chingovwa
2.50
2.74
I
36
1999-9-4
57.40
2.5
T
16
Jewel
2.50
2.74
I
39
2000-3-1
57.33
2.3
T
21
2004-3-9
2.50
2.74
I
49
Phala
57.20
3.4
T
27
2004-11-8
2.50
2.74
I
50
Amasi
56.53
2.0
T
32
Bosbok
2.50
2.74
I
45
2003-20-1
56.40
2.9
T
37
Hernandez
2.50
2.74
I
46
2003-23-6
56.33
2.0
T
−C
Resisto
2.55
-
I
33
Ndou
56.17
5.5
T
36
1999-9-4
2.60
2.51
I
27
2004-11-8
56.10
4.4
T
50
Amasi
2.83
2.40
I
−C
Resisto
56.10
-
T
44
2003-11-3
3.00
2.28
I
25
2004-9-5
55.77
3.9
T
45
2003-20-1
3.00
2.45
I
44
2003-11-3
55.50
3.3
T
46
2003-23-6
3.17
2.23
S
37
Hernandez
55.00
7.7
T
1
Wit Blesbok
3.33
2.58
S
9
Xushu 18
54.97
2.5
T
7
6 Maande wit
3.33
1.86
S
18
Tanzania
54.37
6.2
T
17
Cemsa 74-228
3.33
1.63
S
3
TO-1-1-B
54.33
3.4
T
18
Tanzania
3.33
2.58
S
7
6 Maande wit
53.77
3.0
T
25
2004-9-5
3.33
2.58
S
1
Wit Blesbok
53.69
6.4
T
5
Hlabisa 4
3.50
2.07
S
26
2004-10-1
53.63
4.1
T
3
TO-1-1-B
3.67
2.16
S
17
Cemsa 74-228
52.57
5.7
I
26
2004-10-1
3.67
1.75
S
5
Hlabisa 4
52.00
5.2
S
31
2004-17-8
3.67
1.51
S
6
3 Maande wit
51.58
4.7
S
6
3 Maande wit
3.79
1.60
S
31
2004-17-8
50.43
6.1
S
4
Malavuwe III VM-5B
3.83
1.47
S
4
Malavuwe III VM-5B
49.00
6.2
S
10
Yan Shu 1
4.25
1.17
S
10
Yan Shu 1
46.57
3.8
S
9
Xushu 18
4.33
1.21
S
Mean
56.44
Mean
2.23
Probability
<0.001
Probability
<0.001
SEM
1.32
SEM
0.76
LSD
4.88
LSD
2.12
CV%
5.8
CV%
83.7
*2002-21-1 and 2004-17-5 had poor vine material and did not establish well, no data collected; DTD = Days to Death, S = Sensitive, I = Intermediate, T = Tolerance, SD = Standard Deviation, −Control = Negative, +Control = Positive, SEM = Standard Error of Means.
trients to the underground parts of the plants. Observations made on the number of dead plants after the experi- ment were a better measure to discriminate the entries in terms of drought response. The least number of dead plants were found in Atacama and 2004-16-1, namely zero. In contrast entries at the bottom of the table had lost 4 plants during drought stress and were very sensitive to drought stress. The best performing accessions that were selected for field trials had potential drought tolerance capabilities which allow them to still flourish under prolong water stress. In addition, imported varieties which performed well in similar pre-screening experiments were also selected. It is expected that these accessions will also show acceptable yield when subjected to peri- odic moisture stress under field condition.
Success in breeding for drought tolerance has not been as pronounced as for many other traits. This is partly due to lack of simple, cheap, and reliable screening methods to select drought-tolerant plants and progenies from the segregating populations and partly due to the complexity of factors involved in drought tolerance. [19] described a simple wooden box pre-screening method showing good correlation with drought tolerance at vegeta- tive and reproductive stages, to select drought-tolerant plants at the seedling stage. Several experiments on drought screening under greenhouse conditions have also been reported in many crops [20] -[24] . Wooden box seedling screening is suitable screening large numbers of accessions. It is essential in its ability to determine stress at developmental stages. [19] applied this method in screening large number of cowpea accessions. The parameters used for evaluation were moisture content, flowering, yield and wilting point.
The wooden box method was recommended because it is simple and non-destructive and it can easily be used to screen large number of accessions. In previous experiments, accessions were screened for drought in rain-out shelters [25] . Drought tolerance was measured in terms of yield reduction and drought sensitivity index (DSI) of [26] . The results of the screening in plastic boxes and planting on the field indicated a relation between number of days to wilting and DSI. These results therefore show that the boxes method is quick, simple and reliable and can be very effective especially for screening large number of accessions. [27] also conducted experiments in rainout shelters on sweetpotato to determine the effect of prolonged restriction of water on yield; accessions were planted in a rain out shelter and irrigated using different water regimes. It was concluded that there was a significant reduction in marketable storage yield with the best yield coming from the accessions supplied with higher volume of water. In general in vitro screening method proves to be an ideal method to screen large set of germplasm with less effort, accurately and the growth pattern differences are due to accessions with least envi- ronmental factor.
3.2. Drought Effect on Growth and Development
There were significant differences among the accessions in respect to canopy temperature at 42 DAP. The highest mean canopy temperature was found in W-119 with an average of 27.24˚C while the lowest of 20.62˚C was rec- orded in 2003-24-2 (Table 3). These figures are quite low and attest to the drought tolerant capabilities of these accessions. A lower canopy temperature in a drought stressed plant indicate a better capacity for taking up soil moisture and for maintaining better plant water status [28] . [29] used canopy temperature of drought stressed wheat accessions to characterize yield stability under various moisture conditions. A positive correlation was found between a DSI and canopy temperature in a stressed environment. Infrared canopy temperature provides an efficient method for rapid non-destructive monitoring of plant response to water stress. The average stem length of 38 cm which is the longest was recorded in Zapallo while the shortest was found in 2004-5-2 with a length of 28.6 cm. [30] observed that the reduction in stem length (relative to the control) of 15 accessions exposed to drought stress varied considerably from 16.1% to 46.0%. Internode diameter was reduced by 12% to 50% across the accessions. Ejumula had the highest number of leaves with a mean value of 37.4 while the least mean value was found in both Phala and 2004-16-1.
The severity of the stress condition became intense at 84 DAP (Table 4). There were also little or no differ- ences in the responses of the accessions to the canopy temperature at that stage and the lowest temperature of 13.5˚C was recorded in 2004-9-2 while the highest was recorded in Ndou (17.8˚C). There was however a significant difference among the accessions in the stem lengths. The longest length of 40 cm was recorded in both Tacna and Ndou while the lowest length was found in 2004-5-2. The highest mean values for number of leaves were recorded in Zapallo (40.00), the lowest value of 22 was found in 2004-5-2. According to [31] , drought stress significantly decreases Relative Water Content (RWC) and has a strong effect on photosynthetic rate and this also leads to increase in leaf and canopy temperature. For 42 DAP the highest root dry matter percentage was recorded in W-119 with a value of 23.09%, Ejumula followed with 22.94% (Table 3). The rest of the ac- cessions did have a dry matter percentage ranging between 15 and 20 percent. There was a significant difference
Growth parameters collected at 42 DAP
S/N
Cultivar
Canopy temperature (˚C)
Root dry matter (%)
Shoot dry matter (%)
Number of leaves (count)
Stem length (cm)
1
Tacna
22.62
19.83
17.94
28.20
31.40
2
Zapallo
21.50
17.07
15.80
32.80
38.80
3
Ndou
22.02
20.99
19.10
29.00
31.20
4
Phala
24.08
16.10
19.27
16.60
28.80
5
Ejumula
22.66
22.94
19.33
37.40
37.40
6
1999-3-1
21.24
21.93
25.63
21.00
31.60
7
W-119
27.24
23.09
23.06
30.80
32.80
8
2003-24-2
20.62
18.82
21.97
22.60
29.60
9
2004-16-1
25.26
19.20
20.47
16.60
34.40
10
2004-5-2
24.64
15.86
14.17
18.80
28.60
11
2004-9-2
22.76
18.08
15.73
23.20
30.40
12
Resisto
21.02
18.42
24.37
18.20
30.00
MS
19.61
30.13
63.31
23.78
53.18
Grand mean
22.97
19.36
19.47
24.6
32.08
CV%
22.97
16.70
17.14
24.6
32.08
LSD
5.981
4.188
4.314
10.160
6.464
Growth parameters collected at 84 DAP
S/N
Cultivar
Canopy temperature (˚C)
Root dry matter (%)
Shoot dry matter (%)
Number of leaves (count)
Stem length (cm)
1
Tacna
16.80
31.08
27.81
36
40
2
Zapallo
16.50
49.09
39.31
40
39
3
Ndou
17.80
56.85
41.79
28
40
4
Phala
17.40
43.71
40.01
25
38
5
Ejumula
16.60
44.31
37.32
36
38
6
1999-3-1
16.00
44.42
31.14
26
29
7
W-119
16.20
46.45
46.41
36
35
8
2003-24-2
17.60
46.48
29.62
24
37
9
2004-16-1
15.50
38.52
57.72
23
33
10
2004-5-2
16.30
59.39
44.66
22
25
11
2004-9-2
13.50
37.92
54.13
30
33
12
Resisto
16.00
60.90
67.08
26
42
MS
2.94 ns
394.59 ns
700.46 ns
187.24 ns
122.15 ns
Grand mean
16.51
46.96
43.08
29.26
33.75
CV (%)
10.60
36.60
8.51
36.11
21.32
LSD
2.441
21.776
4.672
13.471
9.712
among the accessions in the percentage shoot dry matter, the highest was recorded in 1999-3-1 having 25.63% and it was closely followed by W-119 and 2004-9-2 with 15.75%. The lowest percentage shoot dry matter of 14.17% was recorded in 2004-5-2. There was a general reduction in the root dry matter in all the accessions un- der water stress conditions. [32] indicated that storage root drymass is correlated positively with vegetative growth. Similarly, [11] reported a reduction in root dry mass under stress conditions. [11] reported a reduction in root dry mass under water stress condition. The variation in dry matter content can also be dependent on various factors such as soil type, pest, diseases, cultivar and climate [33] .
Despite the severity of the stress, some accessions still showed good traits reflecting in their dry matter accu- mulation at 84 DAP. The highest root dry matter of 60.90% was recorded in Resisto and this was followed by 2004-5-2 (59.39%) and Ndou (56.85%) (Table 4). Most of the rest of the accessions had mean values ranging between 37% to 49% with the lowest of 31.08 recorded in Tacna. Equally, Resisto had the highest shoot dry matter and the lowest was found in Tacna.
Observations made at 120DAP indicated that the accessions were matured for harvesting as they all showed signs of stress with most of the plant already wilting (Table 5). There was no significant difference in the canopy temperature among the accessions. 2004-9-2 has the lowest canopy temperature of 26.2˚C while the highest ca- nopy temperature of 30˚C - 33˚C were found in W-119, 2003-24-2, 2004-16-1 and 2004-5-2. There was a noti- ceable difference in the stem length among the accessions; the longest stem length of 50 cm was recorded in Re- sisto while the shortest length of 27.0 cm was found in W-119. The highest number of leaves was found in Za- pallo (60.6) while the lowest number was recorded in 2004-16-1 (14.8).
At 120 DAP Ejumula had the highest root dry matter percentage of 37.49% followed by Phala (37.49%). The lowest of 23.68% was found in 1999-3-1. Other accessions performed well having values ranging between 23 to 37% (Table 5).
3.3. Drought Effect on Root Yield
Water stress is a common phenomenon and it severely reduces yields of field crops grown under rain fed condi- tions [34] . The marketable yield in the present study ranged from 0.58 t∙ha−1 to 3.83 t∙ha−1 (Table 6). The high- est marketable yield was recorded in Zapallo (3.83 t∙ha−1), Tacna (3.63 t∙ha−1) and Ndou (3.12 t∙ha−1). The low-
Data collected at 120 DAP (at harvest)
S/N
Cultivar
Canopy temperature (˚C)
Root dry matter (%)
Shoot dry matter (%)
Number of leaves (count)
Stem length (cm)
1
Tacna
28.34
28.09
31.20
48.60
47.80
2
Zapallo
29.24
33.90
33.49
60.60
41.00
3
Ndou
26.84
34.38
31.89
30.20
38.20
4
Phala
27.12
37.49
37.79
44.60
50.40
5
Ejumula
26.90
37.73
35.41
30.00
40.40
6
1999-3-1
26.78
23.68
28.11
25.00
36.80
7
W-119
31.34
28.72
34.01
28.80
27.00
8
2003-24-2
32.62
35.51
31.10
26.40
40.00
9
2004-16-1
30.08
25.50
36.15
14.80
30.60
10
2004-5-2
30.52
24.55
29.67
18.20
30.40
11
2004-9-2
26.24
28.43
32.20
25.40
40.60
12
Resisto
27.96
31.83
43.65
36.20
50.00
MS
21.564 ns
124.43 ns
97.28 ns
861.67 ns
286.212 ns
Grand mean
28.67
30.81
33.47
23.40
39.43
CV (%)
16.36
15.71
32.09
54.30
38.49
LSD
5.976
6.172
13.692
22.442
19.344
Yield data collected at harvest at 120 DAP
S/N
Cultivar
MYLD (t/ha)
T-YLD (t/ha)
Survival rate (%)
Root dry matter (%)
1
Tacna
3.63
9.24
81.66
28.23
2
Zapallo
3.83
6.16
77.49
33.49
3
Ndou
3.12
4.50
75.00
31.89
4
Phala
1.05
1.91
59.99
37.79
5
Ejumula
2.31
3.81
75.83
35.41
6
1999-3-1
1.83
3.00
81.66
28.11
7
W-119
1.83
3.23
77.50
34.01
8
2003-24-2
0.58
1.97
64.16
31.10
9
2004-16-1
1.31
2.18
68.33
36.15
10
2004-5-2
0.96
1.69
53.33
29.67
11
2004-9-2
2.02
5.58
66.66
32.20
12
Resisto
1.23
2.31
59.16
43.65
MS
5.67
25.48
448.54
97.28 ns
Grand mean
1.979
3.801
70.069
33.470
CV (%)
31.30
28.48
16.70
32.09
LSD
0.789
1.379
14.918
13.692
est marketable yield of 0.58 t∙ha−1 was found in 2003-24-2. The ANOVA showed that there were significant differences among the accessions. Also, the three accessions with the highest marketable yield mostly had the highest total yield. The highest total yield was recorded in Tacna (9.24 t∙ha−1), Zapallo (6.16 t∙ha−1) and 2004-9-2 (5.58 t∙ha−1). These yield values were comparable to the average yield values of 5-10 t∙ha−1 normally recorded for sweetpotato grown under subsistence farming under rain-fed conditions. The lowest yield was rec- orded in 2004-5-2 (1.69 t∙ha−1). This result is also consistent with the observations of [30] [27] on yield of sweetpotato accessions subjected to prolonged restriction of water.
3.4. Drought Effect on Survival Rates
Accessions Tacna and 1999-3-1 had the highest survival rate (Table 6) of 81.66% followed by W-119 (77.50%) Zapallo (77.49%), Ejumula (75.83%) and Ndou (75.0%). This result was an indication that these accessions had a very good mechanism to tolerate water stress. The lowest was found in 2004-5-2 (53.33%). It is therefore evi- dent that yield and growth parameters such as leaf growth, dry biomass, root dry weight and internodes length can be used to successfully determine drought tolerant accessions in sweetpotato. In addition, [27] found a re- duction in photosynthetic rate, stomatal conductance and expansion of leaf canopy related to reduction in yield of sweetpotato.
4. Conclusion
Among the 50 accessions pre-screened for drought 12 accessions were found to be drought tolerant based on the number of days to wilting. The accessions include Tacna, Zapallo, 2004-9-2, Ndou, 2004-16-1, 2003-24-2, Re- sisto, W-119, Ejumula, Phala, 2004-5-2, 1999-3-1. These 12 pre-screened accessions were further evaluated in field trials and five accessions (Tacna, Zapallo, 2004-9-2, Ndou and Ejumula) were considered to have the greatest tolerance to water stress. Based on the above findings, these five best performing accessions were there- fore recommended to be included as parents in the drought tolerant sweetpotato breeding program.
Acknowledgements
The first author acknowledges the financial support provided by National Research Foundation (NRF), South Africa, Agricultural Research Council (ARC) and University of South Africa (UNISA) to carry out this research. The Madzivhandila College of Agriculture is also highly appreciated for providing a trial plot. Mr. R. N. Laurie and Ms. Lingani Marageni are gratefully acknowledged for their technical assistance.
NOTESReferencesWWAP (2009) World Water Assessment Programme. The United Nations World Water Development Report 3. Water in a Changing World. http://www.unesco.org/new/fileadmin/MULTIMEDIA/HQ/SC/pdf/WWDR3_FactsFood and Agricultural Organization (FAO) (2007) Living with Climate Change. Rome, Italy.http://www.fao.org/newsroom/en/news/2007/1000654/index.htmlMuller, M., Schreiner, B., Smith, L., van Koppen, B., Sally, H., Aliber, M., Cousins, B., Tapela, B., van der Merwe-Botha, M., Karar, E. and Pietersen, K. (2009) Water Security in South Africa. Development Planning Division. Working Paper Series No.12. DBSA, Midrand.UN-Water (2005) Facts and Trends. http://www.unwater.org/downloads/Water_facts_and_trends.pdfFranke, A.C., Haverkort, A.J. and Steyn, J.M. (2013) Climate Change and Potato Production in Contrasting South African Agro-Ecosystems 2. Assessing risks and Opportunities of Adaptation Strategies. Potato Research, 56, 51-66.http://dx.doi.org/10.1007/s11540-013-9229-xWoolfe, J.A. (1992) Sweetpotato: An Untapped Food Resource. Cambridge University Press, Cambridge.Yamakawa, O. and Yoshimoto, M. (2002) Sweetpotato as Food Material with Physiological Functions. Acta Horticulturae, 583,179-85.Kubota, F. (2003) The Effects of Drought Stress and Leaf Ageing on Leaf Photosynthesis and Electron Transport in Photosystem II in Sweetpotato. Photosynthetica, 41, 253-258.http://dx.doi.org/10.1023/B:PHOT.0000011958.29441.01Jayne, T.S., Villareal, M., Pingali, P. and Hemrich, G. (2004) Interactions between the Agricultural Sector and the HIV/AIDS Pandemic: Implications for Agricultural Policy. ESA Working Paper No. 04-46. Agricultural and Development Economics Division, The Food and Agriculture Organization of the United Nations.http://led.co.za/system/files/documents/95.pdfPrakash C.S. ,et al. (1994)Sweetpotato Biotechnology: Progress and Potential Biotechnology and Development Monitor 18, 18-19.Indira, P. and Kabeerathumma, S. (1988) Physiological Reponse of Sweetpotato under Waterstress. Effect of Water Stress during the Different Phases of Tuberisation. Root Crops, 14, 37-40.Anselmo, B.A., Ganga, Z.N., Dadol, E.O., Heimer, Y.M. and Nejidat, A. (1988) Screening Sweet for Drought Tolerance in the Philippines Highlands and Genetic Diversity among Selected Accessions. Tropical Agriculture, 75, 189196.Ekanyake, I.J., Malagamb, P. and Midmore, D.J. (1988) Effect of Water Stress on Yield Indices of Sweetpotatoes. Proceeding of the 8th Symposium ISTRC, Bangkok, 30 October-5 November 1988, 520-528.Bennie, A.T.P. and Hensley, M. (2001) Maximizing Precipitation Utilization in Dryland Agriculture in South Africa— A Review. Journal of Hydrology, 241, 124-139. http://dx.doi.org/10.1016/S0022-1694(00)00377-2GenStat (2012) GenStat Executable Release 15.2. Lawes Agricultural 425 Trust, Rothamstead Experimental Station, Harpenden, Clarendon 426 Press, London.Gupta, S.S. and Panchapakesan, S. (1979) Statistical Selection Procedures in Multivariate Models. p. 1986.Agronomix (2008) Agrobase Generation II. Agronomix Software, Inc., Winnipeg.Muhammad, W., Asghar, A., Tahir, M., Nadeem, M.A., Ayub, M., Asif, T., Ahmad, R. and Hussain, M. (2011) Mechanism of Drought Tolerance in Plant and Its Management through Different Methods. Continental Journal of Agricultural Science, 5, 10-25.Singh, B.B., Mai-Kodomi, Y. and Terao, T. (1999) A Simple Screening Method for Drought Tolerance in Cowpea. Indian Journal of Genetics, 59, 211-220.Govindaraj, M., Shanmugasundaram, P., Sumathi, P. and Muthiah, A.R. (2010) Simple, Rapid and Cost Effective Screening Method for Drought Resistant Breeding in Pearl Millet. Journal of Plant Breeding, 1, 590-599.Pereyra-Irujo, G.A., Velázquez, L., Granier, C. and Aguirrezábal, L.A.N. (2007) A Method for Drought Tolerance Screening in Sunflower. Plant Breeding, 126, 445-448. http://dx.doi.org/10.1111/j.1439-0523.2007.01375.xGholami, M., Rahemi, M. and Rastegar, S. (2012) Use of Rapid Screening Methods for Detecting Drought Tolerant Accessions of Fig (Ficus carica L.). Scientia Horticulture, 143, 7-14. http://dx.doi.org/10.1016/j.scienta.2012.05.012Winter, S.R., Musick, J.T. and Porter, K.B. (1988) Evaluation of Screening Techniques for Breeding Drought-Resistant Winter Wheat. Crop Science, 28, 512-516. http://dx.doi.org/10.2135/cropsci1988.0011183X002800030018xIjaz, R.N. and Khaliq, I. (2007) An Efficient Technique for Screening Wheat (Triticum aestivum L.) Germplasm for Drought Tolerance. Pakistan Journal of Botany, 39, 1539-1546.Laurie, R.N., Du Plooy, C.P. and Laurie, S.M. (2009) Effect of Moisture Stress on Growth and Performance of Orange Fleshed Sweetpotato Varieties. African Crop Science Conference Proceedings, 9, 235-239.www.acsj.info/website/images/stories/PART%201/AGRONOMY/22.pdfFischer, R.A. and Maurer, R. (1978) Drought Resistance in Spring Wheat Accessions. I. Grain Yield Response. Australian Journal of Agricultural Research, 29, 897-907. http://dx.doi.org/10.1071/AR9780897van Heerden, P.D.R. and Laurie, R.N. (2008) Effects of Prolonged Restriction in Water Supply on Photosynthesis, Shoot Development and Storage Root Yield of Sweetpotato. Physiologia Plantarum, 134, 99-109.http://dx.doi.org/10.1111/j.1399-3054.2008.01111.xBlum, A. (2009) Effective Use of Water (EUW) and Not Water-Use Efficiency (WUE) Is the Target of Crop Yield Improvement under Drought Stress. Field Crop Research, 112, 119-123. http://dx.doi.org/10.1016/j.fcr.2009.03.009Blum, A., Shipiler, L., Golan, G. and Mayer, J. (1989) Yield Stability and Canopy Temperature of Wheat Accessions under Drought Stress. Field Crop Research, 22, 289-296. http://dx.doi.org/10.1016/0378-4290(89)90028-2Saraswati, P., Johnston, M., Coventry, R. and Holtum, J. (2004) Identification of Drought Tolerant Sweetpotato (Ipomoea batatas (L.) LAM) Accessions. Proceedings of the 4th International Crop Science Congress, Brisbane, 26 September-1 October 2004. http://www.cropscience.org.au/Siddique, M.R.B., Hamid, A. and Islam, M.S. (2010) Drought Stress Effects on Water Relations of Wheat. Botanical Bulletin Academia Sinca, 41, 35-39.Demagante, A.L., Opena, G.B. and Van der Zaag, P. (1989) Influence of Soilmoisture on Sweetpotato (Ipomoea batatas) Growth and Yield. CIPRegion VII Working Paper No. 89-13, Los Banos, 119-130.Rose, I.M. and Vasanthakaalam, H. (2011) Comparison of the NutrientComposition offour Sweetpotato Varieties Cultivated in Rwanda. American Journal of Food and Nutrition, 1, 34-38.Jangpromma, N., Kitthaisong, S., Lomthaisong, K., Daduang, S., Jaisil, P. and Thammasirirak, S. (2010) A Proteomics Analysis of Drought Stress-Responsive Proteins as Biomarker for Drought-Tolerant Sugarcane Accessions. American Journal of Biochemistry and Biotechnology, 6, 89-102. http://dx.doi.org/10.3844/ajbbsp.2010.89.102