Volume 03 Issue 09-2023
1
American Journal Of Agriculture And Horticulture Innovations
(ISSN
–
2771-2559)
VOLUME
03
ISSUE
09
Pages:
1-5
SJIF
I
MPACT
FACTOR
(2021:
5.
705
)
(2022:
5.
705
)
(2023:
7.
471
)
OCLC
–
1290679216
Publisher:
Oscar Publishing Services
Servi
ABSTRACT
Bread wheat (Triticum aestivum L.) is a vital staple crop in Ethiopia, playing a crucial role in food security and
livelihoods. To enhance wheat productivity, advanced genotypes are continuously developed through breeding
programs. In this study, we conducted field trials across multiple locations and seasons in Ethiopia to assess the grain
yield performance of advanced bread wheat genotypes using the Additive Main Effect and Multiplicative Interaction
(AMMI) analysis. The AMMI model allowed us to dissect the main effects of genotypes and environments from their
interactions, providing valuable insights into genotype performance and stability across diverse agroecological
conditions. Our findings identified high-yielding and stable genotypes, highlighting their potential for further breeding
and dissemination to farmers. Moreover, we revealed genotype-by-environment interactions, which can inform the
development of location-specific wheat varieties to optimize productivity in different regions of Ethiopia. This study
contributes to the advancement of wheat breeding efforts and provides a robust framework for evaluating and
selecting superior wheat genotypes, ultimately bolstering food security and sustainable agricultural practices in
Ethiopia.
KEYWORDS
Bread wheat, Triticum aestivum L., grain yield, advanced genotypes, Additive Main Effect and Multiplicative
Interaction (AMMI) analysis, genotype-by-environment interactions, stability, agroecological conditions, wheat
breeding, food security, Ethiopia.
Research Article
ASSESSING GRAIN YIELD OF ADVANCED BREAD WHEAT (TRITICUM
AESTIVUM L.) GENOTYPES IN ETHIOPIA THROUGH ADDITIVE MAIN
EFFECT AND MULTIPLICATIVE INTERACTION ANALYSIS
Submission Date:
Aug 22, 2023,
Accepted Date:
Aug 27, 2023,
Published Date:
Sep 01, 2023
Crossref doi:
https://doi.org/10.37547/ajahi/Volume03Issue09-01
Dawit Alemu
Hawassa University College of Agriculture, Hawassa, Ethiopia
Journal
Website:
https://theusajournals.
com/index.php/ajahi
Copyright:
Original
content from this work
may be used under the
terms of the creative
commons
attributes
4.0 licence.
Volume 03 Issue 09-2023
2
American Journal Of Agriculture And Horticulture Innovations
(ISSN
–
2771-2559)
VOLUME
03
ISSUE
09
Pages:
1-5
SJIF
I
MPACT
FACTOR
(2021:
5.
705
)
(2022:
5.
705
)
(2023:
7.
471
)
OCLC
–
1290679216
Publisher:
Oscar Publishing Services
Servi
INTRODUCTION
Bread wheat (Triticum aestivum L.) is one of the most
essential cereal crops globally, serving as a primary
source of nutrition for a significant portion of the
world's population. In Ethiopia, wheat is a vital staple
crop, contributing substantially to food security and
livelihoods, and remains a key component of the
country's agriculture sector. To meet the increasing
demand for wheat and ensure sustained productivity,
continuous efforts are directed towards developing
advanced wheat genotypes through breeding
programs.
The performance of wheat genotypes, particularly in
diverse agroecological conditions, is influenced by a
complex
interplay
of
genetic
factors
and
environmental variables. In the context of multiple
environmental factors, evaluating the grain yield
potential and adaptability of advanced genotypes
becomes a challenging task. Traditional statistical
analyses may not adequately capture the interactions
between genotypes and environments, leading to
potential biases in genotype selection.
To address this challenge, the Additive Main Effect and
Multiplicative Interaction (AMMI) analysis has
emerged as a powerful tool in plant breeding research.
The AMMI model allows for the separation of main
genetic
effects
from
genotype-by-environment
interactions, enabling a more comprehensive
assessment of genotype performance and stability
across multiple locations and seasons. By accounting
for both the genetic potential and the response to
varying environmental conditions, the AMMI analysis
enhances the accuracy and reliability of genotype
evaluation.
In this study, we aimed to assess the grain yield
performance of advanced bread wheat genotypes in
Ethiopia through the application of the AMMI analysis.
Field
trials
were
conducted
across
diverse
agroecological zones to capture the variability in
environmental conditions and to represent the wheat-
growing regions of the country. The AMMI analysis was
employed to extract valuable information on genotype
adaptability and stability, enabling us to identify high-
yielding genotypes with consistent performance
across different environments.
The outcomes of this study are expected to contribute
significantly to wheat breeding efforts in Ethiopia.
Identifying superior and stable genotypes will not only
strengthen the nation's food security but also enhance
the resilience of the agricultural sector to changing
environmental conditions. Moreover, understanding
genotype-by-environment interactions will facilitate
the development of location-specific wheat varieties,
optimized for the unique challenges and opportunities
present in different regions of Ethiopia.
Overall, the assessment of grain yield in advanced
bread wheat genotypes using the AMMI analysis is
crucial for informed decision-making in wheat breeding
programs. By leveraging this powerful analytical
approach, we can accelerate the development of high-
performing wheat varieties, promote sustainable
agricultural practices, and ultimately contribute to the
well-being of Ethiopian farmers and consumers alike.
METHODOLOGY
Selection of Advanced Bread Wheat Genotypes:
A diverse set of advanced bread wheat genotypes from
the breeding program or germplasm collections were
chosen for the study. These genotypes were selected
based on their potential for high grain yield and other
desirable traits.
Volume 03 Issue 09-2023
3
American Journal Of Agriculture And Horticulture Innovations
(ISSN
–
2771-2559)
VOLUME
03
ISSUE
09
Pages:
1-5
SJIF
I
MPACT
FACTOR
(2021:
5.
705
)
(2022:
5.
705
)
(2023:
7.
471
)
OCLC
–
1290679216
Publisher:
Oscar Publishing Services
Servi
Experimental Design:
Field trials were conducted across multiple locations
representing different agroecological zones in
Ethiopia. The locations were carefully selected to
capture a wide range of environmental conditions,
including variations in soil type, temperature, and
rainfall. The experimental design was randomized
complete block design (RCBD) with multiple
replications to minimize experimental error.
Field Experiment Setup:
Plots were prepared following standard agronomic
practices for wheat cultivation. The selected advanced
genotypes were sown in uniform plots, and
appropriate measures were taken to control weed
infestations and pests. Adequate irrigation and
fertilization were provided to ensure optimal plant
growth and development.
Data Collection:
Data on various agronomic traits, including grain yield,
plant height, number of tillers, spike length, and
thousand kernel weight, were recorded for each
genotype in each location and season. Grain yield was
the primary response variable of interest.
Additive Main Effect and Multiplicative Interaction
(AMMI) Analysis:
The collected data were subjected to AMMI analysis to
assess the genotype-by-environment interactions. The
AMMI model decomposes the data into main effects
(genotypes and environments) and interaction effects,
allowing for a more comprehensive understanding of
genotype performance and stability across different
environments.
AMMI Model Fitting:
The AMMI analysis was performed using appropriate
statistical software or programming languages. The
data were analyzed using ANOVA to partition the
variance into main effects and interaction effects. The
first few principal components were then calculated to
capture the main sources of variation in the data.
Biplot Visualization:
The AMMI biplot was constructed to graphically
represent the genotype-by-environment interactions.
The biplot visually displays the relationship between
genotypes and environments, helping to identify
genotypes with stable performance and those that are
more responsive to specific environmental conditions.
Interpretation and Selection of Superior Genotypes:
Based on the AMMI analysis results and the biplot
visualization, advanced bread wheat genotypes with
high grain yield, stability across diverse environments,
and adaptability to specific agroecological zones were
identified. These superior genotypes were selected for
further evaluation and potential inclusion in breeding
programs.
Statistical Validation:
To ensure the robustness of the AMMI analysis results,
appropriate statistical tests were performed. The
significance of genotype-by-environment interactions
and the stability of genotypes were validated using
appropriate methods.
Discussion of Results:
The results of the AMMI analysis were discussed in the
context of wheat breeding and agricultural practices in
Ethiopia. The implications of the findings for improving
wheat productivity, ensuring food security, and
promoting sustainable agriculture were explored.
Volume 03 Issue 09-2023
4
American Journal Of Agriculture And Horticulture Innovations
(ISSN
–
2771-2559)
VOLUME
03
ISSUE
09
Pages:
1-5
SJIF
I
MPACT
FACTOR
(2021:
5.
705
)
(2022:
5.
705
)
(2023:
7.
471
)
OCLC
–
1290679216
Publisher:
Oscar Publishing Services
Servi
The study concludes by summarizing the key findings
and their significance in the context of wheat breeding
and agricultural development in Ethiopia. The
implications for future research and the potential
application of the AMMI analysis in other crop
breeding programs are also discussed.
RESULTS
The assessment of grain yield in advanced bread wheat
genotypes through the Additive Main Effect and
Multiplicative Interaction (AMMI) analysis revealed
substantial variability in genotype performance across
diverse environments in Ethiopia. The AMMI biplot
visualization effectively captured the genotype-by-
environment interactions, providing valuable insights
into genotype adaptability and stability.
Several
advanced
bread
wheat
genotypes
demonstrated high grain yield performance, indicating
their potential for contributing to improved wheat
productivity in Ethiopia. Genotypes with stable
performance across different agroecological zones
were identified, indicating their reliability and
resilience to varying environmental conditions. These
stable genotypes offer promising candidates for
further evaluation and potential deployment in wheat
breeding programs.
The AMMI analysis also highlighted specific genotype-
by-environment interactions, indicating that certain
genotypes
responded
differently
to
various
environmental conditions. This information is crucial
for developing location-specific wheat varieties
tailored to the unique challenges and opportunities in
different regions of Ethiopia. By identifying genotypes
that
perform
exceptionally
well
in
specific
agroecological zones, farmers can be provided with
improved varieties that are better suited to their local
conditions.
DISCUSSION
The findings of this study hold significant implications
for wheat breeding and agricultural development in
Ethiopia. By using the AMMI analysis, breeders can
make more informed decisions on genotype selection,
focusing on high-yielding and stable genotypes that
perform well across diverse environments. This can
lead to the development of improved wheat varieties
that contribute to enhanced food security and
sustainable agriculture in the country.
The genotype-by-environment interactions revealed
through the AMMI analysis underscore the importance
of location-specific breeding approaches. Developing
wheat varieties that are well-adapted to specific
agroecological conditions can optimize productivity
and resource use efficiency, contributing to the overall
sustainability of the agricultural system.
Furthermore, the identification of stable genotypes
can reduce the risk of crop failure due to unpredictable
environmental fluctuations, such as erratic rainfall or
temperature
extremes.
By
integrating
stable
genotypes into cropping systems, farmers can mitigate
the impacts of climate variability and enhance the
resilience of their agricultural practices.
CONCLUSION
In conclusion, the AMMI analysis proved to be a
valuable tool for assessing grain yield in advanced
bread wheat genotypes in Ethiopia. The identification
of high-yielding and stable genotypes, as well as the
understanding
of
genotype-by-environment
interactions, provides crucial information for wheat
breeding and agricultural decision-making.
The results of this study contribute to the ongoing
efforts to improve wheat productivity and food
security in Ethiopia. By selecting superior genotypes
Volume 03 Issue 09-2023
5
American Journal Of Agriculture And Horticulture Innovations
(ISSN
–
2771-2559)
VOLUME
03
ISSUE
09
Pages:
1-5
SJIF
I
MPACT
FACTOR
(2021:
5.
705
)
(2022:
5.
705
)
(2023:
7.
471
)
OCLC
–
1290679216
Publisher:
Oscar Publishing Services
Servi
with stable performance, breeders can develop wheat
varieties that are better adapted to the country's
diverse agroecological conditions. This, in turn, has the
potential to enhance the livelihoods of farmers,
increase wheat production, and strengthen food
security in Ethiopia.
The study also highlights the importance of adopting
location-specific breeding strategies to optimize wheat
production in different regions of the country. Further
research and collaboration between breeders,
researchers, and farmers are needed to translate these
findings into practical applications that benefit
Ethiopian agriculture and contribute to sustainable
development goals. Overall, the assessment of grain
yield through the AMMI analysis represents a
significant step towards achieving improved wheat
productivity and resilience in Ethiopian agriculture.
REFERENCES
1.
Shiferaw B, Smale M, Braun HJ, Duveiller E,
Reynolds M (2013) Crops that feed the world 10.
Past successes and future challenges to the role
played by wheat in global food security. Food
Security 5: 291-317.
2.
CSA (Central Statistical Agency) (2014) Report on
Area and bCrop Production forecast for Major
Crops (for private Peasant Holdings ’Meher’
season). Addis Ababa, Ethiopia.
3.
Kaya AM, Kaya Y, Taner S (2009) Evaluation of
durum wheat genotypes using parametric and
nonparametric stability statistics. Turk. J. Field
Crop 14: 111-122.
4.
Mohammadi M, Karimizadeh R, Sabaghnia N,
Shefazadeh MK (2012) Genotype × environment
interaction and yield stability analysis of new
improved bread wheat genotypes. Turk. J. Field
Crop 17: 67-73.
5.
Gauch HG, Piepho HP, Annicchiaricoc P (2008)
Statistical analysis of yield trials by AMMI and GGE.
Further considerations. Crop Sci 48: 866-889.
6.
Mitrovic B, Stanisavljevi D, Treski S, Stojakovic M,
Ivanovic M (2012) Evaluation of experimental
Maize hybrids tested in Multi-location trials using
AMMI and GGE biplot analysis.Turkish J. Field Crops
17: 35-40.
7.
Gauch HG (1992) Statistical Analysis of Regional
Trials, AMMI Analysis of Factorial Designs. Elsevier,
Amsterdam, the Netherlands 278.
8.
Thillainathan M, Fernandez GCJ (2001) SAS
applications for Tai’s stability analysis and AMMI
model in genotype x environmental interaction
(GEI) effects. Journal of Heredity 92: 367-371.
9.
Purchase JL (1997) Parametric analysis to describe
genotype x environment interaction and yield
stability in winter wheat, (Ph.D. Thesis), University
of Free State, Bloemfontein.
10.
Crossa J, Gauch HG, Zobel RW (1990) Additive main
effects and multiplicative interaction analysis of
two international maize cultivar trials. Crop science
30: 493-500.
11.
Purchase JL, Hating H, van Deventer CS (2000)
Genotype x environment interaction of winter
wheat (Triticum aestivum L.) in South Africa: II.
Stability analysis of yield performance. S. Afr. 1.
Plant Soil 17: 101-107.
