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Screening of Bread Wheat (Triticum aestivum L.) Genotypes for Waterlogged Area in Highlands of Ethiopia

Published in Plant (Volume 12, Issue 2)
Received: 1 April 2024     Accepted: 18 April 2024     Published: 17 May 2024
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Abstract

Due to a serious waterlogging issue, Ethiopia's agricultural productivity has been severely limited, yielding much lower than expected results. In this study conducted on screening of 49 for first year and 60 for second year bread wheat genotypes selected from international nursery. An experiment was undertaken at two locations namely, Ginchi Agricultural Research Sub Center and Tulu Bolo farmer field in Ethiopia in 2018/19 and 2019/20 cropping seasons. The main objective of this study was to select best performed genotypes in waterlogged areas for next variety development and future breeding program. The experiment was conducted using apha lattice with three replications. Data on yield and associated traits were collected and analyzed using SAS version 9.3 software. The results revealed that the separate analysis of variance over the two years conducted at Ginchi showed statistically significant (P ≤ 0.01) differences among the genotypes for all phenotypic traits except Septoria disease severity, Number of tiller and biomass yield considered in this study. The results revealed that the separate analysis of variance over the two years conducted at Tulu bolo showed statistically non-significant (P <0.01) differences among the genotypes for all phenotypic traits except days to heading, plant height, Septoria disease severity agronomic score, hectoliter weight and thousand kernel weight considered in this study. In general from the two locations the maximum and minimum were revealed 29.85qt/ha and 2.32qt/ha respectively. This indicated that almost all genotypes were showed low performed and the wheat breeder give more attentions to provide resistance genotypes for waterlogging.

Published in Plant (Volume 12, Issue 2)
DOI 10.11648/j.plant.20241202.11
Page(s) 19-24
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Alpha Lattice, Bread Wheat, Low Oxygen, Waterlogging

1. Introduction
World wheat production is almost totally reliant on two modern species: hexaploid bread wheat (Triticum aestivum L., 2n = 6X = 42, AABBDD) and tetraploid wheat (Triticum turgidum subsp. durum, 2n = 4X = 28, AABB) . Wheat may be grown in Ethiopia's highlands, which are located between 6o and 16o N, 35o and 42o E, and longitude at altitudes ranging from 1500 to 3000 m.a.s.l. Wheat's optimal altitude is from 1900 to 2700 meters above sea level . Wheat is not only for making bread, biscuit and pastry products, but also for the Production of starch and gluten . Wheat (Triticum aestivum L.) is the staple food for a large part of the world population including Ethiopia. It is one of the most important cereals cultivated in Ethiopia. It is cultivated on a total area of 2.1 million hectares (1.7 million ha rain-fed and 0.4 million ha irrigated) with a total production of 6.7 million tonnes of grain at an average productivity of 3.0 and 4.0 t/ha under rain-fed and irrigated conditions, respectively .
Water-logging is a significant limitation that impacts crops worldwide. The primary cause of this stress is when water from precipitation or irrigation accumulates in the soil profile for an extended length of time as a result of excessive rainfall, soil compaction, flat topography, or poor drainage systems . Wheat (Triticum aestivum L.) is one of the most intolerant crops to waterlogging . The primary problem of watered logged soils is a lack of oxygen. Underground roots, like other tissues, require oxygen to respire. In a typical soil, gas exchange occurs easily through air-filled gaps between soil particles. The rate of oxygen transport in water is extremely slow, and as a result, waterlogged soils are almost completely deoxygenated .
Currently, almost all of the bread wheat genotypes are highly affected by waterlogging problems. This results in high yield loss. Resistance breeding is a solution to prevent this loss. Identifying the resistant materials is the basic thing for resistance breeding. Therefore; the activity was designed to select best performed genotypes in waterlogged areas for next variety development and future breeding program.
2. Material and Methods

2.1. Description of the Experimental Site and Materials

Tulu Bolo is located in the Southwest Shewa Zone of the Oromia Region in Ethiopia, 80km from Addis Ababa on the way to Jimma. It is located at 8o 40’’N latitude and 38o 13’’E longitude with an elevation of 2193 m.a.s.l. While, Ginchi is located in the west Shewa Zone of the Oromia Region in Ethiopia. It is located at 09o 30’’N latitude and 38o 30’’E longitude with an elevation of 2200 m.a.s.l. The first year 49 and the second year 60 bread wheat genotypes selected from introduced materials from CIMMYT lines. The field experiment was laid down on alpha lattice design with three replications.

2.2. Data Collected

The data were collected based on plant and plot basis those are days to heading and, plant height, agronomic score, number of tillers, biomass yield, thousand kernel weight, hectoliter weight, grain yield and diseases data.

2.3. Statistical Analysis

Using SAS 9.3@ version , the data analysis was conducted to an ANOVA based on a general linear model. The ANOVA for each location conforms to the model:
Pijk=µ+ gi+ bk(j) + rj+ eijk
Where; Pijk = phenotypic value of ith genotype under jth replication and Kth incomplete block within replication j; µ = Grand mean; gi = the effect of the ith genotype; bk(j) = the effect of incomplete block “K” within replication “j”; rj = the effect of replication “j”; eijk = the residual/random error effect.
3. Results and Discussion
Analysis of Variance
F max tests were used to confirm heterozygosity in error variances. The two locations had heterozygous error variances. As a result, data were collected and analyzed independently based on location and year. The results of the separated analysis of variance across the two location and year are presented on (Tables 1, 2, 3 and 4).
The separated analysis of variance conducted, 2018/19 at Ginchi showed statistically significant (P<0.01) highly significant differences among the genotypes for all phenotypic traits except Septoria tritici blotch considered in this study. While conducted 2019/20 at Ginchi showed that statistically highly significant except Septoria disease, biomass yield and number of tillers. From this studied conducted at Ginchi the maximum and minimum were observed 7.54qt/ha and 2.32qt/ha from the first year while 29.85qt/ha and 9.74qt/ha from the second year respectively. The finding of this study is similar to previous findings for grain yield and plant height . The finding of this study is similar to previous findings for grain yield it was conducted on” Yield response of restricted-tillering wheat to transient waterlogging on duplex soils.”
Table 1. Mean squares results from the separate analysis of variance for yield and associated traits of wheat genotypes assessed at Ginchi, 2018/19 cropping season.

Traits (y)

MSG /48/

MS Rep /2/

MS Blk /Rep/

MSE /78/

Mean

CV (%)

R2

LSD (5%)

PTH

48.200847**

425.170068**

36.585477ns

23.817794

59.32

8.23

0.68

7.9331

SDS

52.128324ns

119.047619ns

98.400399ns

76.80382

93.95

9.33

0.44

14.246

NT

0.51053470*

0.49884354ns

0.59716284*

0.30230831

3.14

17.50

0.61

0.8938

AgrSc

0.60191653**

1.52714286**

0.80907900**

0.24156785

2.28

21.52

0.71

0.7989

TKW

16.3534714**

12.7259864*

13.6729305**

2.899256

33.21

5.13

0.84

2.7678

GYLD

3746.0952**

1813.5580ns

3579.3196ns

2098.6094

142.05

32.25

0.60

74.466

(*, ** and ns) = highly significant @ 1%, significant @ 5% and non-significant respectively.
Table 2. Mean squares results from the separate analysis of variance for yield and associated traits of wheat genotypes assessed at Ginchi, 2019/20 cropping season.

Traits

MSG /59/

MS Rep /2/

MS Blk /Rep/

MSE /91/

Mean

CV (%)

R2

LSD (5%)

DHT

21.998534**

1.688889ns

2.526015ns

2.187763

67.94

2.18

0.90

2.3989

PTH

45.794783*

350.138889**

41.109176ns

29.924261

71.78

7.62

0.67

8.8721

SDS

21.096429ns

62.751936*

25.157039ns

19.864004

10.99

40.54

0.56

7.2285

AgrSc

0.24313565**

4.09305556**

0.35156390**

0.12258238

2.49

14.07

0.75

0.5678

NT

0.39474340ns

1.68888889*

0.45970676ns

0.47849970

2.83

24.46

0.50

1.1219

BMY

0.33084466ns

8.13872722**

0.52256717ns

0.33374174

1.66

34.86

0.64

0.937

TKW

36.003740**

10.006722ns

17.021634*

9.373950

35.77

8.56

0.79

4.9657

HLW

40.557375**

1.514056ns

22.244720**

10.985195

73.49

4.51

0.76

5.3755

GYLD

35888.656**

109781.264**

67392.547**

19584.766

562.23

24.89

0.72

226.97

y = abbreviations refer to table 1.
The separated analysis of variance conducted 2018/19 at Tulu-bolo showed statistically significant (P<0.01) non-significant differences among the genotypes for all phenotypic traits except thousand kernel weight considered in this study. While conducted 2019/20 at Tulu-bolo showed that statistically highly significant except grain yield, biomass yield and number of tillers. The detail information’s are presented (Tables 3, 4). The significant of the traits indicated that the existence of enormous amount of genetic variability for grain yield and yield attributes. From this studied conducted at Tulu bolo the maximum and minimum were observed 23.36 qt/ha and 7.08qt/ha from the first year while 25.40qt/ha and 12.38qt/ha from the second year respectively. The finding of this study is similar to previous findings for days to heading and plant height .
The first year grain yield interactions almost all the genotypes of the grain yield was observed at Tulu bolo better performed than Ginchi (Figure 1). The second year grain yield the of the genotypes of the grain yield was revealed at Tulu bolo equal performed with Ginchi (Figure 2).
Table 3. Mean squares results from the separate analysis of variance for yield and associated traits of wheat genotypes assessed at Tulu-bolo, 2018/19 cropping season.

Traits

MSG /48/

MS Rep /2/

MS Blk /Rep/

MSE /78/

Mean

CV (%)

R2

LSD (5%)

PHT

29.507773ns

269.695578**

104.631273**

25.768110

67.60

7.51

0.70

8.2515

SDS

77.712143ns

31.422433ns

129.468431ns

64.13564

13.11

61.08

0.54

13.018

AgrSc

0.32192203ns

0.93367347*

1.09466434**

0.26617985

2.10

24.54

0.70

0.8386

TKW

31.412318**

69.955397**

33.724583**

8.631548

41.50

7.08

0.79

4.7757

HLW

70.546267ns

96.503929ns

261.781460**

48.36552

68.82

10.11

0.71

11.305

GYLD

19319.960ns

81095.754ns

87459.863**

20903.992

353.18

40.94

0.67

235.02

y = abbreviations refer to table 1.
Figure 1. Interactions of mean grain of grain yield of bread wheat genotypes from two locations.
Table 4. Mean squares results from the separate analysis of variance for yield and associated traits of wheat genotypes assessed at Tulu-bolo, 2019/20 cropping season.

Traits

MSG /59/

MS Rep /2/

MS Blk /Rep/

MSE /91/

Mean

CV (%)

R2

LSD (5%)

DHT

8.4936059**

3.0055556*

0.7695668ns

0.7019478

71.06

1.18

0.90

1.3588

PTH

58.029244**

55.972222ns

91.177073**

25.197157

82.56

6.08

0.76

8.1413

SDS

48.198014*

84.752761ns

33.678239ns

31.578602

10.23

54.92

0.59

9.1141

AgrSc

0.26926318**

0.08888889ns

0.24538579**

0.10655831

3.01

10.84

0.72

0.5294

NT

1.44992206ns

10.15555556**

2.27410953ns

1.4537135

4.54

26.56

0.58

1.9555

BMY

0.22672808ns

0.41921056ns

0.37503897ns

0.19784022

1.85

24.05

0.59

0.7214

TKW

22.097706**

4.546889ns

7.232008*

3.868593

33.99

5.79

0.83

3.19

HLW

17.171893**

4.956292ns

15.444858ns

9.910490

76.34

4.12

0.61

5.1058

GYLD

17920.150ns

74288.237**

64260.077

14081.945

602.19

19.71

0.72

192.46

y = abbreviations refer to table 1.
Figure 2. Interactions of mean grain of grain yield of bread wheat genotypes from two locations.
4. Conclusion
The waterlogged area-based screening technique was effective in distinguishing wheat genotypes, making it appropriate for early tolerance testing. It can also be applied to the crossing program. This finding encourages us to conduct additional research to test the resistance/tolerance capacities of various genotypes. Tolerance in specific genotypes is important for identifying cultivars for particular conditions and future use in wheat breeding program. The screening results for waterlogged tolerance of wheat genotypes are based on the particular environmental conditions of the Ginchi site. They may vary in different waterlogged regions; thus, waterlogged tolerance should be evaluated in specific areas of importance. More research is urgently needed to investigate the tolerance genotypes for waterlogged soil situations.
Abbreviations
ANOVA: Analysis of Variance
CIMMYT: International Maize and Wheat Improvement Center
t/ha: Tone Per Hectares
m.a.s.l.: Meters Above Sea Level
Acknowledgments
The author I would like to thank the Ethiopian Institute of Agricultural Research for financial support. They also appreciate the facilitation by the Holetta Agricultural Research Center. The author also express their gratitude to the farmers for their active engagement and proper management of the farms.
Author Contributions
Endashaw Girma is the sole author. The author read and approved the final manuscript.
Conflicts of Interest
The author declares no conflicts of interest.
References
[1] Amri, M., El, Ouni, M. H and Salem, M. B., 2014. Waterlogging affect the development, yield and components, chlorophyll content and chlorophyll fluorescence of six bread wheat genotypes (Triticum aestivum L.)." Bulg. J. Agric. Sci 20(3), 647-657.
[2] Bekele H, Verkuiji W, Mawangi T., 2000. Adaptation of improved heat technologies in Addaba and Doddola Worede’s of the Bale highlands of Ethiopia. CIMMYT/EARO, Addis Ababa, Ethiopia.
[3] Central Statistics Agency for Ethiopia. Agricultural sample survey of area and production of major crops. Available from:
[4] Collaku, A. and Harrison, S. A., 2002. Losses in wheat due to waterlogging. Crop Science, 42(2), pp. 444-450.
[5] Condon, A. G. and Giunta, F., 2003. Yield response of restricted-tillering wheat to transient waterlogging on duplex soils. Australian Journal of Agricultural Research, 54(10), pp. 957-967.
[6] Hanson H, Borlaug NE and Anderson RG, 1982. Wheat in the third world. West view press. 192p.
[7] Ma, Y., Zhou, M., Shabala, S. and Li, C., 2016. Exploration and utilization of waterlogging-tolerant barley germplasm. Exploration, Identification and Utilization of Barley Germplasm, pp. 153-179.
[8] SAS. 2012. Statistical analysis system, version 9.3 editions. SAS Institute Inc. Cary, NC.
[9] Sears, E. R., 1966. Nullisomic-tetrasomic combinations in hexaploid wheat. In Chromosome Manipulations and Plant Genetics: The contributions to a symposium held during the Tenth International Botanical Congress Edinburgh 1964 (pp. 29-45).
[10] Singh, G., Kumar, P., Gupta, V., Tyagi, B. S., Singh, C., Sharma, A. K. and Singh, G. P., 2020. Characterizing waterlogging tolerance using multiple selection indices in bread wheat (Triticum aestivum). The Indian Journal of Agricultural Sciences, 90(3), pp. 662-665.
[11] Thomson, C. J., Colmer, T. D., Watkin, E. L. J. and Greenway, H., 1992. Tolerance of wheat (Triticum aestivum cvs Gamenya and Kite) and triticale (Triticosecale cv. Muir) to waterlogging. New Phytologist, 120(3), pp. 335-344.
[12] Van Gínkel, M., Sayre, K. and Boru, G., 1997. La tolerancia al anegamiento en el trigo: problemas relacionados con el fitomejoramiento. Explorando altos rendimientos de trigo, p. 193.
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    Girma, E. (2024). Screening of Bread Wheat (Triticum aestivum L.) Genotypes for Waterlogged Area in Highlands of Ethiopia. Plant, 12(2), 19-24. https://doi.org/10.11648/j.plant.20241202.11

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    Girma, E. Screening of Bread Wheat (Triticum aestivum L.) Genotypes for Waterlogged Area in Highlands of Ethiopia. Plant. 2024, 12(2), 19-24. doi: 10.11648/j.plant.20241202.11

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    AMA Style

    Girma E. Screening of Bread Wheat (Triticum aestivum L.) Genotypes for Waterlogged Area in Highlands of Ethiopia. Plant. 2024;12(2):19-24. doi: 10.11648/j.plant.20241202.11

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  • @article{10.11648/j.plant.20241202.11,
      author = {Endashaw Girma},
      title = {Screening of Bread Wheat (Triticum aestivum L.) Genotypes for Waterlogged Area in Highlands of Ethiopia
    },
      journal = {Plant},
      volume = {12},
      number = {2},
      pages = {19-24},
      doi = {10.11648/j.plant.20241202.11},
      url = {https://doi.org/10.11648/j.plant.20241202.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.plant.20241202.11},
      abstract = {Due to a serious waterlogging issue, Ethiopia's agricultural productivity has been severely limited, yielding much lower than expected results. In this study conducted on screening of 49 for first year and 60 for second year bread wheat genotypes selected from international nursery. An experiment was undertaken at two locations namely, Ginchi Agricultural Research Sub Center and Tulu Bolo farmer field in Ethiopia in 2018/19 and 2019/20 cropping seasons. The main objective of this study was to select best performed genotypes in waterlogged areas for next variety development and future breeding program. The experiment was conducted using apha lattice with three replications. Data on yield and associated traits were collected and analyzed using SAS version 9.3 software. The results revealed that the separate analysis of variance over the two years conducted at Ginchi showed statistically significant (P ≤ 0.01) differences among the genotypes for all phenotypic traits except Septoria disease severity, Number of tiller and biomass yield considered in this study. The results revealed that the separate analysis of variance over the two years conducted at Tulu bolo showed statistically non-significant (P <0.01) differences among the genotypes for all phenotypic traits except days to heading, plant height, Septoria disease severity agronomic score, hectoliter weight and thousand kernel weight considered in this study. In general from the two locations the maximum and minimum were revealed 29.85qt/ha and 2.32qt/ha respectively. This indicated that almost all genotypes were showed low performed and the wheat breeder give more attentions to provide resistance genotypes for waterlogging.
    },
     year = {2024}
    }
    

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  • TY  - JOUR
    T1  - Screening of Bread Wheat (Triticum aestivum L.) Genotypes for Waterlogged Area in Highlands of Ethiopia
    
    AU  - Endashaw Girma
    Y1  - 2024/05/17
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    PB  - Science Publishing Group
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    UR  - https://doi.org/10.11648/j.plant.20241202.11
    AB  - Due to a serious waterlogging issue, Ethiopia's agricultural productivity has been severely limited, yielding much lower than expected results. In this study conducted on screening of 49 for first year and 60 for second year bread wheat genotypes selected from international nursery. An experiment was undertaken at two locations namely, Ginchi Agricultural Research Sub Center and Tulu Bolo farmer field in Ethiopia in 2018/19 and 2019/20 cropping seasons. The main objective of this study was to select best performed genotypes in waterlogged areas for next variety development and future breeding program. The experiment was conducted using apha lattice with three replications. Data on yield and associated traits were collected and analyzed using SAS version 9.3 software. The results revealed that the separate analysis of variance over the two years conducted at Ginchi showed statistically significant (P ≤ 0.01) differences among the genotypes for all phenotypic traits except Septoria disease severity, Number of tiller and biomass yield considered in this study. The results revealed that the separate analysis of variance over the two years conducted at Tulu bolo showed statistically non-significant (P <0.01) differences among the genotypes for all phenotypic traits except days to heading, plant height, Septoria disease severity agronomic score, hectoliter weight and thousand kernel weight considered in this study. In general from the two locations the maximum and minimum were revealed 29.85qt/ha and 2.32qt/ha respectively. This indicated that almost all genotypes were showed low performed and the wheat breeder give more attentions to provide resistance genotypes for waterlogging.
    
    VL  - 12
    IS  - 2
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