This research is concerned some main challenges on crop production in Somaliland particularly small scale farms in Dilla Area.

1. Crop production
CHALLENGES OF CROP PRODUCTION
Challenges Facing Crop Production among Small Scale Farmers in Rural Areas of Dilla
District, Somaliland
Abdikadir A. Bade
Amoud University
A Thesis Submitted in Partial Fulfillment of the Requirements for the Award of the
Degree of Master of Science in Rural Development and Pastoral Economics
July 2015

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DECLARATION AND APPROVAL
Declaration by the Student
I, Abdikadir Ali Bade, declare that this thesis titled “Challenges Facing Crop
Production among Small Scale Farmers in Dilla District, Somaliland” is my original work
and to the best of my knowledge, it has not been submitted to any University or Institution for
an academic award whatsoever.
………………………………………. Date ………………………
Abdikadir Ali Bade
MRD/01/0096/2013
Approval by the Supervisor
This thesis was prepared under my supervision and has been submitted to the School
of Research and Postgraduate Studies for examination by my approval as candidate’s
supervisor.
…………………………… Date ……………………………
Dr. Oso Willis Yuko
School of Research and Postgraduate Studies
Amoud University, Somaliland

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DEDICATION
This thesis is dedicated to my dearly loved mom Amina, my lovely dad Ali, my
beautiful wife Naima, my beloved baby and also dear and beloved sisters and brothers.

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ACKNOWLEDGEMENTS
All my thanks to My Allah for his protection and providing me with the ability to do
work. I am so grateful to the Welthungerhilfe (German Agro Action) for helped me to study
Master of Science in Rural Development and Pastoral Economics. My special and heartily
thanks to my research supervisor, Dr. Oso, W. Yuko (PhD), School of Research and
Postgraduate Studies who encouraged and directed me. It was his guidance that this work to a
completion. I am also deeply thankful to my classmates. Their names cannot be disclosed, but
I want to acknowledge and appreciate their help and encouragement towards this thesis.
My heartfelt thanks to my all lectures, the librarians (Mohamed and Sakariye), staff
of Amoud Postgraduate School Office and my dear lovely wife (Naima Hussein Yabal) for
supporting me to accomplish this study. Last not but least, I would like to thank my lovely
family, my dear friend Hassan Jimcale and Mohamed Hamud Jama (GAA project manager)
who encouraged me and prayed for me throughout the time of my studies. May the Almighty
Allah richly bless all of you.
Abdikadir A. Bade
July 2015

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TABLES OF CONTENTS
DECLARATION AND APPROVAL ...................................................................................... II
DEDICATION.........................................................................................................................III
ACKNOWLEDGEMENTS.....................................................................................................IV
TABLES OF CONTENTS .......................................................................................................V
LIST OF FIGURES .................................................................................................................IX
LIST OF TABLES....................................................................................................................X
LIST OF ABBREVIATION AND ACRONYMS...................................................................XI
ABSTRACT........................................................................................................................... XII
CHAPTER ONE: INTRODUCTION........................................................................................1
1.1 Background of the Study ...............................................................................................1
1.2 Statement of the Problem...............................................................................................5
1.3 Research Objectives.......................................................................................................6
1.3.1 General Research Objective...........................................................................................6
1.3.2 Specific Research Objectives.........................................................................................6
1.4 Research Hypotheses .....................................................................................................6
1.4.1 General Research Hypothesis ........................................................................................6
1.4.2 Specific Research Hypotheses .......................................................................................7
1.5 Research Questions........................................................................................................7
1.5.1 General Research Questions ..........................................................................................7
1.5.2 Specific Research Questions..........................................................................................7
1.6 Scope of the Study .........................................................................................................8
1.7 Significance of the Study...............................................................................................8
1.8 Limitations of the Study.................................................................................................9
1.9 Conceptual Framework..................................................................................................9

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CHAPTER TWO: REVIEW OF RELATED LITERATURE.................................................11
2.1 Introduction..................................................................................................................11
2.2 Infrastructural Development and Crop Production......................................................11
2.3 Environmental Factors and Crop Production...............................................................12
2.4 Agricultural Technologies and Crop Production.........................................................13
CHAPTER THREE: RESEARCH METHODOLOGY ..........................................................15
3.0 Introduction..................................................................................................................15
3.1 Research Area..............................................................................................................15
3.2 Research Design...........................................................................................................15
3.3 Study Population..........................................................................................................16
3.3.1 Target Population.........................................................................................................16
3.3.2 Accessible Population..................................................................................................16
3.4 Sample and Sampling ..................................................................................................17
3.4.1 Sample Size..................................................................................................................17
3.4.2 Sampling Techniques...................................................................................................17
3.5 Data Collection ............................................................................................................18
3.5.1 Data Collection Methods .............................................................................................18
3.6.3 Reliability of Instruments ............................................................................................21
3.7 Data Analysis...............................................................................................................22
3.8 Ethical Considerations .................................................................................................24
CHAPTER FOUR: RESULTS AND FINDINGS...................................................................25
3.1 Introduction..................................................................................................................25
4.2 Demographic Characteristics of Respondents ...............................................................25
4.2.1 Gender of Respondents................................................................................................26
4.2.2 Marital Status of Respondents .....................................................................................27

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4.2.3 Age of Respondents .....................................................................................................27
4.2.4 Distribution of Respondents of Level of Education ....................................................28
4.2.5 Distribution of Respondent by Village of Origin ........................................................29
4.3 Crop Production and Associated Challenges...............................................................30
4.3.1 Measurement of Variables...........................................................................................30
4.3.2 Infrastructural Development and Crop Production......................................................32
4.3.3 Environmental Factors and Crop Production...............................................................35
4.3.4 Agricultural Technologies and Crop Production.........................................................38
CHAPTER FIVE: DISCUSSION, CONCLUSION AND RECOMMENDATIONS.............42
5.1 Introduction..................................................................................................................42
5.2 Summary of Findings...................................................................................................42
5.3 Discussion....................................................................................................................44
5.4 Conclusion ....................................................................................................................47
5.5 Recommendations........................................................................................................48
5.5.1 General Recommendations..........................................................................................48
5.5.2 Recommendations for Further Research......................................................................49
REFERENCES ........................................................................................................................50
APPENDIX I: RESEARCH BUDGET ...................................................................................62
APPENDIX II: WORK PLAN ................................................................................................63
APPENDIX III: QUESTIONNAIRE FOR SMALL SCALE FARMERS..............................64
APPENDIX IV: OBSERVATION CHECKLIST ...................................................................69
APPENDIX V: TABLE OF SAMPLE SIZE ..........................................................................70
APPENDIX VI: MAP OF DILLA DISTRICT........................................................................71
APPENDIX VII: RELIABILITY SCORES - TEST ...............................................................72
APPENDIX VIII: SAMPLE RESEARCH DATA..................................................................73

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APPENDIX IX: LETTERS OF APPROVAL.........................................................................78

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LIST OF FIGURES
Figure 1. Conceptual framework of factors influencing small scale farmers............................9
Figure 2. Gender of the respondents........................................................................................26
Figure 3. Marital Status of the respondents. ............................................................................27
Figure 4. Age of the respondents.............................................................................................28
Figure 5. Level of Formal Education of the respondents.........................................................29
Figure 6. Village of Origin.......................................................................................................30

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LIST OF TABLES
Table 1: Assessment Report from Experts...............................................................................20
Table 2: Scoring and Weighting of Variables..........................................................................32
Table 3: Crop Production with Infrastructural Development ..................................................33
Table 4: Regression Analysis of Crop Production on Infrastructural Development ...............34
Table 5: Crop Production with Environmental Factors ...........................................................36
Table 6: Regression Analysis of Crop Production on Environmental Factors........................37
Table 7: Crop Production with Agricultural Technologies......................................................39
Table 8: Regression Analysis of Crop Production on Agricultural Technologies...................40

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LIST OF ABBREVIATION AND ACRONYMS
CVI - Content Validity Index
EAVO - East Africa Voluntary Organization
FAO - Food and Agriculture Organization
FSNAU - Food Security and Nutrition Analysis Unit
GAA - German Agro Action
UNDP - United Nation Development Program

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ABSTRACT
Crop production is a way of growing or raising food in the required quantity at optimum
time. In many developing countries, increasing crop production is one of the most important
priorities for agricultural development programs. Global food per capita crop production
deficit of 34.5% was reported in 2012. In Africa, food production declined by 8% between
2010-2014. In Somaliland, crop production declined by 9.25% between 2010-2014. In Dilla
district which is one of the agricultural districts of Somaliland, crop production declined by
2.05% between 2010-2014. But while declining crop production was so evident, the
challenges facing crop production among small scale famers in rural areas of Dilla district
had been not empirically determined. While infrastructural development, environmental
factors and agricultural technology had been advanced as some of the major factors in crop
production in the third world, their applicability to Somaliland and to the rural areas of Dilla
district in particular had not been determined, and remained largely undocumented. If these
challenges remained unknown, food insecurity may not be fully managed now and in future
leading to undue suffering to the local and global populations. Guided by the Theory of
Development, this study investigated the challenges facing crop production among small
scale farmers in Dilla district along three specific objectives: to establish the effect of
infrastructural development; to assess the effect of environmental factors and to determine the
effect of agricultural technologies on crop production of small scale farmers in Dilla district.
The study was conducted through a cross sectional survey design. Data was collected from
147 active small scale farmers in Dilla district using questionnaire in March 2015, and
analyzed using simple regression technique. The study found that infrastructural
development, (F [1, 145] = 8.352, p = .004, R2
adj = .048); environmental factors, (F [1, 145]
= 5.204, p = .024, R2
adj = .035); and agricultural technologies, (F [1, 145] = 9.212, p = .003,
R2
adj = .053) all had significant effect on crop production of small scale farmers in Dilla
district, and respectively account for 4.8%, 3.5% and 5.3% of the variance in crop production
of small scale farmers in Dilla district. The study concluded that the agricultural technology
is the most significant factor influencing crop production of small scale farmers in Dilla
district. The study recommends that Ministry of Agriculture and Environment improve
infrastructural development of the small scale farmers through creating access roads,
protecting water catchments and supporting the farmers to acquire modern storage facilities;
that the government of Somaliland should initiate environment awareness campaign program
to enlighten the community on the effect of deforestation on crop production and the
advantages of conservation farming; and that the government should create a scheme that
can support the small scale farmers to acquire plows and threshers at district level, and
construct irrigation systems to support small scale farmers at the village level. Lastly, the
researcher recommends that a study be conducted to design and develop appropriate
technologies specific to small scale farmer in rural areas of Dilla district. Such technologies
should be culture sensitive and should suit the farming styles of the people. This will ensure
that appropriate technology is used and crop production is improved.

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CHAPTER ONE
INTRODUCTION
1.1 Background of the Study
Over the past 30 years, while increasing amount of crop production has met part of
increasing populations’ needs, modern technology has also led to erosion of natural resources
(Tilman, Matson & Polasky, 2002). Agriculture is a critical sector of the world economy,
contributing 24% of global Gross Domestic Product and providing employment to 1.3 billion
people, or 22% of the world's population (Soubbotina & Sheram, 2000). In many of the
developing countries, increasing crop production is one of the most important priorities for
agricultural development programs (Ellis, 2003). While it is generally agreed that distribution
of fertilizers, improving infrastructure, development and providing capacity building to
farmers all have positive impact on the improvement of crop production, the global crop
production has steadily declined over the years (James, 2010).
In Africa, crop farming plays a central and strategic role in development, economic
growth, increased incomes, improved living standards, poverty eradication and enhanced
food security (Gabre-Madhin & Haggblade, 2004). Crop production also presents new
opportunities by emphasizing the productive values of natural, social and human capital, all
assets that Africa either has in abundance or that can be regenerated at low financial cost
(Pierce, 2002). While food production has increased in some countries, the global food
production has generally declined (Kendall, 2014). The world annual food production was
538,000,000 metric tons against a total requirement of 821,258,963 metric tons in 2012
(FAO, 2012). This reflected a food deficit of 283,258,963 metric tons (World Bank, 2012).
In Somalia, crop farming is one of the main drivers of the economy (Coppel, Dumont
& Visco, 2001). It offers a flexible and integrated approach to agriculture and natural
resource management, and could provide substantial benefits to Somalia given its

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current economic and environmental circumstances and limited natural resource base
(Leach Mearns, 2013). In Somaliland, crop farming is one of the major sectors dominating
the economy. It ranks second to livestock with about 39,000 farm families (20%-25%) of the
population involved in crop farming, and cultivating about one-third of the total area suitable
for crop farming (Murray, 2004). Rain-fed crops include sorghum, maize, cowpeas,
groundnut and sesame while irrigated crops are citrus, papaya, guava, water melons and
vegetables such as tomato, onion, cabbage, carrot, and peppers (Van der Lee, Schiere,
Bosma, de Olde, Bol & Cornelissen, 2006). But the major rain-fed crops are maize and
sorghum (Overholt & Polaszek, 2002), and this study focused on these.
Small scale farmers are farmers who produce food primarily to meet household
consumption needs (Bacon, 2005). It also refers to those who have access to very small
pieces of land sometimes only a couple of hundred square meters and they could possibly
access between three to five hectares. But active small scale farmers were those farmers that
produce enough food to their families for their livelihood throughout the year. A rural area is
an open swath of land that has few homes and not very many people and away from the Dilla
town around 3 km.
Crop production is a complex business, requiring many skills (such as biology,
agronomy, mechanics, and marketing) and covering a variety of operations throughout the
year (Epa, 2012). Crop production is also defined as a way of growing or raising food in the
required quantity at optimum time (Herren, 2014). Crop production is also a complex
undertaking of growing of staple food crops, fruits, nuts and other food crops and commercial
crops (Fernandes, 2009), or to the process cultivating plants that are grown on a large scale
commercially, especially a cereal, fruit or vegetable (Allard, 1999). But crop production
refers to yield of a crop, or to the cultivation of plants for food, animal foodstuffs or other
commercial uses (Cowell & Parkinson, 2003). In this study crop production was defined as

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the process of cultivating crops in the required quantity at optimum time. The main elements
of effective crop production are increasing food security, yields of desired quality at
minimum costs and increasing market access (Wichelns, 2001). Other elements are quantity,
financial viability and unlimited access to services and markets (Doran & Vogel, 2009),
agricultural income, food security and poverty reduction (Hazell, Poulton, Wiggins &
Dorward, 2007). This study focused on the quantity, not oblivious of other aspects of crop
production.
According to records of Food Security Unit Analysis (FSUA), crop production has
continually declined in Somaliland over the years. Maize production declined from 9,097
tons to 8,900 tons between 2010 and 2014 reflecting a decline of 197 tons in five years, or a
decline of 0.433% per annum. The production of sorghum declined from 39,307 tons to
17,100 tons within the same period, reflecting a total fall of 22,207 tons, or 11.29% per
annum. But generally, production of both crops declined from 48,404 tons to 26,000 tons
within the same period which reflects a decline of 9.25% per annum. The same trend was
reflected in Dilla district, which is the backbone of agricultural activities in Awdal region.
Sorghum production in Dilla district declined from 4,378 tons to 4,150 tons between
2010 and 2014 reflecting a decline of 228 tons in five years, or a decline of 1.04% per
annum. The production of maize declined from 435 tons to 168 tons within the same period,
reflecting a total decline of 267 tons over five years, or a decline of 12.75% per annum. But
generally, the production of both crops declined from 4,813 tons to 4,318 tons within the
same period which reflects a decline of 2.05% per annum. Crop farming is the predominant
occupation in Dilla district. All communities in Dilla depend on agricultural production for
their livelihoods (Horst, 2007). While farming was generally still intensively practised in the
district, the production had declined over the years, and is generally not sustainable.

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In adequate production can be caused by a lack of arable land, adverse weather, and
lower farming skills or by a lack of technology or resources needed for the higher yields
(Altieri, 2009). The dangers of inadequate food production need not be over emphasized.
Globally, it has led to poverty, low income and malnutrition (Harrigan, 2008). In Africa, it
has led to inefficiency of food utilization, nutrition, and food safety (Herrero, 2010). But
specifically in Somaliland, inadequate food production has led to low quantity of products,
crop failure and famine (Hillbruner & Moloney, 2012). While the falling crop production is
not in doubt, the challenges facing crop production had not been empirically investigated.
Common challenges in crop production include the amount of precipitation,
temperatures, the amount of sunlight, fertilization and crop rotation (Loomis, 2004).
According to Nepal and Satdobato (2009), basic factors in crop production are the unusual
weather patterns such as drought, a prolonged rainy season, frosts, pests, available equipment
and innovation. Altieri (2002) however considers the key factors in crop production to be
multi cropping, pesticide use, soil health, organic fertilizer use, and water conservation. In
this study, challenges were characterized by infrastructural development, environmental
factors and agricultural technology. These factors subsume most of the variables enumerated
by the authors above.
Infrastructures are the basic physical systems of a region like roads, bridges and
storage facilities for crops (Gleick, 2006). Infrastructure is a vital aspect of rain-fed crop
production because it influences costs of delivering inputs to and of taking produce out to
markets (African Development Bank, 2002). Environmental factor is any factor, whether a
biotic or abiotic, that influences a living organism (Dunson, 2000). Environmental factors
include rainfall, soil type and land size (Singh, 2007). Agricultural technologies refer to the
tools and machinery that are used primarily or entirely in order to support agricultural
enterprise (Zijp, 1994), or the application of techniques to control the growth and harvesting

17. Crop production
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of crop products (Oerke, 2006). While these factors were known to influence crop production
around the world, their status in Dilla district, and their influence on crop production in the
district had not been investigated. Yet the crop production had declined by over 2.05% in five
years.
Guided by the Theory of Development developed of Adelman (1961), this study
determined the challenges facing crop production among small scale farmers in rural areas of
Dilla district. The theory postulates that all societies progress through similar stages of
development, and that today's underdeveloped areas are thus in a similar situation to that of
today's developed areas at some time in the past. Therefore the task in helping the
underdeveloped areas out is to accelerate them along same supposed common path of
development through various means such as investment, technology transfers, and closer
integration into the world markets which are the same technologies the developed states have
used. This theory has been selected because it reflects the situation in Dilla District and in
Somaliland. They are at same stage where others had been and the strategies that were used
then can be adopted and used here.
1.2 Statement of the Problem
Food production capacity is faced with an ever-growing strain; the world population
is expected to grow to nearly 9 billion by 2050, and the ratio of arable land is fast falling to
the population. But despite this awareness, global food per capita crop production deficit of
34.5% was reported in 2012. In Africa, food production declined by 8% between 2010-2014.
In Somaliland, crop production declined by 9.25% between 2010-2014, while in Dilla
district, crop production declined by 2.05% between 2010-2014. But while declining crop
production is so evident, the challenges facing crop production among small scale famers in
rural areas like Dilla District had not been empirically determined. While infrastructural

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developments, environmental factors and agricultural technology had been advanced as the
most significant factors in crop production in the third world, Somaliland and to the rural
areas of Dilla district had not been determined, and remained largely undocumented. If these
challenges remained unknown, food insecurity might not be fully managed now and in future
leading to the declining crop production, and undue suffering to the local and global
population.
1.3 Research Objectives
1.3.1 General Research Objective
The general objective of this study was to assess the challenges facing crop
production among small scale farmers in rural areas of Dilla district.
1.3.2 Specific Research Objectives
The specific objectives of this study were:
1. Establish the effect of infrastructural development on crop production among small scale
farmers in rural areas of Dilla District.
2. Assess the effect of environmental factors on crop production among small scale farmers
in rural areas of Dilla District.
3. Find out the effect of agricultural technology on crop production among small scale
farmers in rural areas of Dilla District.
1.4 Research Hypotheses
1.4.1 General Research Hypothesis
This study was guided by the general hypothesis that infrastructural development,
environmental factors and agricultural technology taken individually and together have a

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significant effect on crop production among small scale farmers in rural areas of Dilla
District.
1.4.2 Specific Research Hypotheses
This study was guided by the hypothesis that:
1. Infrastructural development has significant effect on crop production among small scale
farmers in rural areas of Dilla District.
2. Environmental factors have significant effect on crop production among small scale
farmers in rural areas of Dilla District.
3. Agricultural technology has a significant effect on crop production among small scale
farmers in rural areas of Dilla District.
1.5 Research Questions
1.5.1 General Research Questions
This study was guided by a general research question – “What were the challenges
facing crop production among small scale farmers in rural areas of Dilla district?”
1.5.2 Specific Research Questions
This study sought to answer the following specific research questions:
1. Does infrastructural development affect crop production among small scale farmers in
rural areas of Dilla District?
2. How do environmental factors affect crop production among small scale farmers in rural
areas of Dilla District?
3. To what extent does agricultural technology affect crop production among small scale
farmers in rural areas of Dilla District?

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1.6 Scope of the Study
This study investigated the challenges facing the crop production among small scale
farmers in rural areas of Dilla District. It was conducted through a cross-sectional survey
research design with particular focus on infrastructure, environmental factors and agricultural
technology as they related to crop production. Data was collected by the researcher using
questionnaires in March 2015, analyzed by using regression technique and reported in tables
and figures.
1.7 Significance of the Study
This study has not only provided an assessment of the actual challenges facing crop
production, but it has also developed new models on challenges of crop production of small
scale farmers. The models can be used to determine the relationship between infrastructural
development, environmental factors and agricultural technology and crop production. This
study has also added new knowledge to the area of rural development and pastoral economic
because it is the first study to empirically assess the factors influencing crop production
among small scale farmers in rural areas of Dilla district. This has made its finding novel.
The study should be useful to the people of Dilla community as a foundation for intervention
for ensuring that crop production is sustained and improved. The study has also made
recommendations on how to improve and sustain crop production in the district. These
recommendations could be adopted into policy statements by the mostly agriculture for
improving crop production. Improved crop production means enhancement of the life quality
of agro pastoralists, and the community as a whole.

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1.8 Limitations of the Study
The study was localized in Dilla district, yet declining crop production is a problem in
the district and in the country as a whole. It would have been much better if the study was
conducted in the whole region or even the whole county. But resources dictated a smaller
area. The localization of the study to Dilla district only could reduce its applicability to other
areas. Hence generalization of this study to other populations was undertaken with this
limitation in mind.
1.9 Conceptual Framework
Guided by the Theory of Development, this study was based on the conceptual
framework in Figure 1.
Figure 1. Conceptual framework of factors influencing small scale farmers
Figure 1 depicts the hypothesized relationship between challenges of crop production,
and crop production. Challenges were viewed as infrastructural development, environmental
factors and agricultural technology; and crop production was measured by quantity of crop
Challenges Crop Production
- Quantity of crop production
in bags
- Quality of yield
Infrastructural Development
- Roads
- Water catchments
- Storage facilities
Environmental Factors
- Rainfall
- Soil type
- Land size
Agricultural Technology
- Plows
- Threshers
- Irrigation system

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production produced per bag and quality of yield. Infrastructural development was
operationalized as roads, water catchments and storage facilities; environmental factors as
rainfall, soil type and Land size. On the other hand, agricultural technology was
operationalized as plows, threshers and irrigation system. This framework held that the crop
production should increase in quantity and quality if these challenges are well-managed. This
was in line with the theory of Development that postulates that all societies progress through
similar stages of development, and that today's underdeveloped areas are thus in a similar
situation to that of today's developed areas at some time in the past.

23. Crop production
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CHAPTER TWO
REVIEW OF RELATED LITERATURE
2.1 Introduction
This chapter discusses literature related to challenges affecting crop production. It
focuses on infrastructural development, environmental factors and agricultural technology
and their influence on crop production.
2.2 Infrastructural Development and Crop Production
Infrastructural development is the basic physical systems like roads, bridges and
storage facilities for crops (Gleick, 2006). The physical infrastructure services are limited in
all rural areas, although they are important in stimulating agricultural investment and growth
(FAO, 2003). Infrastructure development involves changes in fundamental structures that are
required for the proper functioning of a community and society (Cerny, 2012). It increases
consumer demand in rural areas, and facilitates the integration of less-favored rural areas into
national economies (Morgan, 2003).
The basic infrastructural development for crop production in rural areas includes
roads, water catchment and storage facilities. Rural roads have a significant positive effect on
crop production, reduce transportation cost, stimulate demand for rural labour and improve
rural income (Lanjouw, 2001). Water catchment is an area where water is collected by the
natural landscape (Sliva, 2001). It is necessary because water catchment is used for crop
irrigation. Storage facilities both provide the same role of acting as a place where agricultural
produce can be amalgamated, either for the purpose of immediate sale or for transportation to
the next destination.
Studies on infrastructural development and crop production indicate a close
relationship between these variables. A study by Rosegrant (2003) who investigated factors

24. Crop production
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affecting crop production in rural areas in Sudan. Rosegrant (2003) found that infrastructural
development plays a key role in improving crop production. Another study by Fan and
Mukherjee (2005) demonstrated that the investment in physical infrastructures is essential to
increase farmers’ access to input and output markets, to stimulate the rural non-farm
economy and vitalize rural towns. Fan and Mukherjee (2005) also demonstrated that poor
infrastructural development can significantly affect crop production as it can damage the
market access of crops. It also agrees with the views of Dorward (2004) that poor
infrastructural development leads to production of fewer amounts of crops and difficult to
bring crops to market easily.
2.3 Environmental Factors and Crop Production
An environment is everything that makes up the surrounding and affects ability to live
on the earth (Cockell, 2006). An environmental factor is any factor, whether abiotic or biotic,
that influences living organisms (Martiny, 2006). Singh (2007) define an environmental
factor as terrain, climate, soil properties and relief. Thus an environmental factor is
essentially climatic, edaphic, biotic, physiographic, relief and socio-economic. Edaphic is a
nature related to soil such as the soil itself, drainage, texture, or chemical properties (Jenny,
2004).
Rainfall is the quantity of rain falling within a given area in a given time (Nicholson,
2008). Vermeulen (2012) demonstrated that rainfall has a measurable effect on the quality
and quantity of food produced globally. Soil types refers to all kinds of ways such as heavy,
light, sandy, clay, loam, poor or good. Soil type usually refers to the different sizes of mineral
particles in a particular sample (Hillel, 1998). Farmland size refers to the cultivable area and
measured by hectare (Hayward, 2006).

25. Crop production
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Studies on environmental factors and crop production indicate a close relationship,
between these variables. Environmental factors have been shown to influence crop
production across the world. A study by Barko (2011) found that environmental factors like
light, temperature, water, and soil - greatly influence crop production and geographic
distribution. Another study by Eghball (1997) concluded that environmental factors
determine the suitability of a crop for a particular location, cropping pattern, management
practices, and levels of inputs needed.
2.4 Agricultural Technologies and Crop Production
Agricultural technologies are the tools and machineries that are used primarily or
entirely in order to support agricultural enterprise (Zijp, 1994). Oerke (2006) views
agricultural technologies as the application of techniques to control the growth and harvesting
of crop products. Harris (1999) on the other hand, regard agricultural technologies as method
of accepting new farm harvesting technique that is expected to have a better output than the
previous technique that has been using. Generally agricultural technologies are regarded as
tools, techniques, new inputs, methods and new innovations. The main aspects of agricultural
technologies are tools such as plow, thresher and irrigation system.
Plow is a tool used in farming for initial cultivation of soil in preparation for sowing
seed or planting to loosen or turn the soil (Lat & Hanson, 2007). Thresher is a device that first
separates the head of a stalk of grain from the straw, and then further separates the kernel
from the rest of the head (McLeod, 1998). McLeod (1999) points out that a thresher is a farm
machine for separating wheat, peas, soybeans, and other small grain and seed crops from
their chaff and straw. An irrigation system is a method of delivering water to an area where it
is needed, but not normally present in the required amounts (Oweis & Kijne, 1999). A study
by Snowdon (2010) also found that agricultural technology is application of techniques to

26. Crop production
14
control the growth and harvesting of crops. These findings generally show that the
agricultural technology has a positive effect on crop production.

27. Crop production
15
CHAPTER THREE
RESEARCH METHODOLOGY
3.0 Introduction
This chapter discusses a detailed methodology of the study. A research methodology
is a detailed process used to answer research questions.
3.1 Research Area
This study was conducted in Dilla District, one of the main districts of Awdal region.
The population of Dilla district was 1,133 inhabitants (UNDP, 2005). It is located 29 km
southeast of Borama district and lies at latitude 9.8° and longitude 43.30
(Gaa, 2014). Dilla
district was selected because it is where the most crop production in Awdal region is
produced. It could therefore be used as pointer to other districts in the region.
3.2 Research Design
The study was conducted through a cross-sectional survey design. Survey research is
a commonly used method of collecting information about a population of interest (Kraemer,
1993). In this study, survey design was used mainly because there was no manipulation.
Manipulation refers to a deliberate determination (directly or indirectly) of the various forms
(or levels, amounts, etc) that an independent variable may take, and which groups will get
which kinds of treatment (Oso, 2013). This study did not manipulate variables. The
researcher could not purposely alter the infrastructural development, environmental factors,
and agricultural technology of small scale farmers because they involve high cost which the
researcher could not afford. They could only be studied as they were. Absence of
manipulation made the choice of survey ideal (Oso, 2013).

28. Crop production
16
Cross-sectional survey design was used to enable the researcher describe the
challenges facing crop production from just a section of small scale farmers (Oso, 2013),
through collecting data from the farmers at one point in time (Oso, 2013). Longitudinal
survey takes a long time to collect repeated data from the same cases in a population (Oso,
2013). Cross sectional survey is mainly used when determining the frequency of a particular
attribute (Torralba, 2001), and to gather data from a sample of population at a particular point
in time (Torralba, 2001). Its main advantages include time and cost saving (Torralba, 2001).
Cross-sectional survey design was used to save time and cost which could have been incurred
in repeated data collections, if longitudinal survey was used. In adopting cross sectional
survey, data was collected from a large number of active small scale farmers at one point in
time. The researcher went to the small scale farmers in Dilla district and collected data from a
cross section of the small scale farmers at one point in time, and then made a report based on
that collected data at once. This enabled the researcher to present a picture of the challenges
facing crop production at a fairly lower cost and in a shorter time.
3.3 Study Population
3.3.1 Target Population
The target population consisted of the 1,133 small scale farmers in Dilla district
(Ministry of Agriculture and Environment, 2012). Dilla district was selected because there
had been low crop production in the last five years, yet it had more fertile land than its
neighboring districts.
3.3.2 Accessible Population
The accessible population of the study consisted of 252 active small scale farmers in
Dilla district (Ministry of Agriculture and Environment, 2012). Only active farmers were

29. Crop production
17
included. Small scale farmers are farmers who produce food primarily to meet their
household consumption needs (Bacon, 2005). But active small scale farmers were those
farmers that produce enough food to their families for their livelihood throughout the year.
3.4 Sample and Sampling
3.4.1 Sample Size
The sample consisted of 169 small scale farmers selected from the 252 active small
scale farmers in Dilla district. The sample size was determined according to (Krejcie and
Morgan, 1970 as cited by Oso, 2013). Krejcie and Morgan (1970) as cited in Oso (2013)
recommend a sample of 169 for a population of 252 at level of confidence 95%, and 5%
margin of error, which were the same boundaries set in this study (Appendix V).
3.4.2 Sampling Techniques
This study used simple random method to select a sample without bias from the
accessible population. Simple random sampling guaranteed that each small scale farmers in
Dilla district had an equal and independent chance of being included in the sample. The
chances were equal because they were selected randomly and they were independent because
they were free on one another (Fitch, 2005). This guaranteed that the sample was random and
a fair representation of all small scale farmers (Oso, 2013). Numbers were used to identify
the small scale farmers in Dilla district and the numbers picked one at a time without
replacement until the required sample was attained (Keskes, 2003).

30. Crop production
18
3.5 Data Collection
3.5.1 Data Collection Methods
The study used questionnaire and observation methods to collect data. A
questionnaire is a written set of questions that are given to people in order to collect facts or
opinions about something (Taguchi, 2010). Questionnaire was used to collect data from
active small scale farmers. Questionnaire was used because of the large of the sample size
and short period of time available. It was not possible to conduct interviews on 169
respondents within the limits of time and other resources available. The questionnaire
technique also provided sufficient time to the respondents to work at their speed without
strain from the interviewer.
Observation method was used to collect data on crop production. Observation is way
of gathering data by watching behavior, events, or noting physical characteristics in their
natural setting (Altmann, 2002). It was used here because small scale farmers were low
profile people who could not have much information on shape, colour and height of their
crops. It was necessary for the researcher to see these himself.
3.5.2 Data Collection Instruments
Semi-structured questionnaire and observation checklist were the major tools for
gathering data. A semi-structured questionnaire is a mix together of close-ended and open-
ended items in a single instrument (Oso, 2013) It enabled the respondents to answer
generously in their own words in some sections of the instruments (Withey, 2012). Semi
structured questionnaires also facilitated fast data analysis than completely unstructured
questionnaire (McColl, 2005). Its main purpose was to ensure that both quantitative and
qualitative data were collected for a detailed description of challenges facing crop production
(Oso, 2013). The questionnaire was self-constructed and had sections on background

31. Crop production
19
information, infrastructural development, environment factor, agricultural technology and
crop production. The observation checklist (Appendix IV) had eight items which sought
information on the quality and quantity of crops produced.
3.5.3 Research Procedures
The researcher obtained permission from School of Postgraduate Studies and
Research to proceed with the study. When the permit was granted, the researcher obtained
further permission from the regional office of the Ministry of Agriculture and Environment in
Borama District (Appendix X). Once the permits were granted, the researcher proceeded to
collect data from the 169 selected small scale farmers by using questionnaires, interview and
observation methods, through drop and collect method in March 2015. Data was analyzed
using regression techniques and presented using tables, figures and graphs.
3.6 Quality Control
3.6.1 Piloting
The instruments were piloted in Gabiley district which is the nearest district with
sufficient numbers of small scale farmers to facilitate piloting. Piloting was necessary to
ensure that the study attained validity and reliability coefficients at least .70 which is the
lowest acceptable indexes allowed in social science research (Oso, 2013).
3.6.2 Validity of Instruments
Validity is the extent to which an instrument measures what it is supposed to measure
and performs as it is designed to perform (Seha, 2010). Validity of the instruments was
assessed through expert judgment method. Expert judgment method is a method that assesses
the representativeness of the items in an instrument as they relate to the entire domain of the

32. Crop production
20
questions being asked by using people who are knowledgeable in the subject (Oso, 2013).
Experts are those individuals or group who possess specialized knowledge or training in
particular area (Seha, 2004). Two experts were asked to evaluate the questionnaire to ensure
that the items are relevant to the research objectives and they rated them on the scale of 1 – 4
where 1 = Not Relevant, 2 = Somehow Relevant, 3 = Fair Relevant and 4 = Very Relevant.
Validity was determined from items rated 3 and 4 by both judges as CVI = n3/4/N; where
n3/4 are questionnaires rated relevant and very Relevant by both judge, and N is the total
number of questionnaires. The results obtained were summarized in Table 1.
Table 1
Assessment report from experts
Judge 1
1 2 3 4 Total
Judge 2
1 0 0 0 0 0
2 0 0 1 0 1
3 0 2 10 5 17
4 1 3 12 11 27
Total 1 5 23 16 45
Note. The shaded region shows items rated relevant (3 or 4) by both judges.
A validity index of 38/45 = 0.84 was reported. This shows that out of any ten
equations in the questionnaire, at least eight of them measured what they were intended to
measure. Hence the instruments captured sufficient information needed to answer the

33. Crop production
21
research questions. This was an accepted measure because it was higher than the .70 value
recommended by in social science research (Oso, 2013).
3.6.3 Reliability of Instruments
Reliability is an index that estimates dependability (consistency) of scores (Mitchell,
2006). Reliability is the overall consistency of a measure (Anderson, 2009). Reliability refers
to the consistency of the results in research (Golafshani, 2003). Reliability of instrument is
vital in research, because it tests if the study fulfills its predicted aims and hypothesis and
also ensures that the results are due to the study and not any possible extraneous
variables. The reliability of this study was controlled by the use of test-re-test method. Test-
re-test reliability is a measure of reliability obtained by administering the same test twice over
a period of time to a group of individuals (Oso, 2013).
The researcher carried out the questionnaires to the similar sample of 30 respondents
in Gabiley district two times within two weeks and then linked the results from the two
administrations using correlation method (Oso, 2013). At first test stage; every respondent
was asked to answer 45 questions and each question coded 1 regardless of response. The
responses for each respondent were added together to obtain the total score of 45 for each
respondent on the instrument. At this stage, the researcher had 30 scores of 45 for each
respondent. After 14 days, the same questionnaires were asked to the same sample of 30
respondents. The responses were coded such that if a respondent provided the same response
to the same item as in the test stage, it was coded 1, but it was coded 2 if the response was
different no matter how different. Reliability was calculated as r = =
= .87. T1 is the post-testing while T2 is re-testing (Appendix VIII). It was

34. Crop production
22
reported that the reliability value is .87 and means that out of ten questions in the
questionnaire; at least nine were found the same at different times. Therefore the research
instruments could produce constant results over time. Because of this, the reliability is the
degree to which an assessment tool produces stable and consistent results over period of time
(Charles, 2012).
3.7 Data Analysis
Data was analyzed using regression technique. Regression is a statistical process for
estimating the relationships among variables (Eriksson, 2001). Regression analysis is a
statistical tool for the investigation of relationships between variables (Cohen, 2013).
Regression analysis is a statistical technique for studying linear relationships (Harrell, 2013).
Typically, a regression analysis is done for one of two purposes: In order to predict the value
of the dependent variable for individuals for whom some information concerning the
explanatory variables is available, or in order to estimate the effect of some explanatory
variable on the dependent variable (Clark, 2001). It usually assumes the model of;
Y = ax + b …… Eq.1.
where a is the coefficient of regression, and b is the constant term with Y and X. Y is the
dependent variable while X is the independent variable. Regression analysis was done in
order to estimate the effect of infrastructural development, environmental factors and
agricultural technology on crop production. It was forecasted that crop production is
dependent on infrastructural development, environmental factor and agricultural technology,
and it was necessary to investigate this relationship both in direction and magnitude.
In this study, the researcher investigated:

35. Crop production
23
i. R which is the relationship between infrastructural development, environmental factors
and agricultural technology and crop production in terms of strength both in terms of
strength and direction between;
ii. R2
which is the variance in crop production explained from the knowledge of
infrastructural development, environmental factors and agricultural technology. But R2
adj is the estimated variance in the population and was used because R2
is always known
to overestimate the goodness of the model when applied in real life (Oso, 2013). R2
adj
= , where n = simple size and k = number of variables.
iii. F which is the overall significance of the model.
Regression is usually based on the assumption that (i) the relationship between the
independent variable and the dependent variable is linear in nature; (ii) for each population
denoted by values of X, the variances of these populations are equal; (iii) for each population
donated by the value of X, the distribution of Y value is normal (Oso, 2013). Normal
distribution is when the mean, median and mode of a distribution are all equal (Campbell,
1995). A linear is any statistical function that graphs to a straight line (Hammer, 2001). Equal
variance means that the scatter plots are evenly distributed about the line of the best fit. In
other words, the variability is the same from column to column (Oso, 2013).
Regression was used to determine if there was significant relationship between
challenges and crop production at 95% level of confidence, .05 level of significance and at
5% margin of error. These values are the commonly used values in social science research
(Oso, 2013). A confidential level refers to the percentage of all possible samples that can be
expected to include the true population parameter and 95% confidence level implies that 95%
of the confidence intervals would include the true population parameter (Lewis, 2011). The
significance level (also known as the alpha-level) of a statistical test is the probability of

36. Crop production
24
rejecting the null hypothesis in a statistical test when it is true. This indicates that the
probability of wrongly rejecting the null hypothesis is only 5 in 100 (Kampenes, 2006). But
5% margin of error indicates that the maximum expected difference between the true
population parameter and a sample estimate of that parameter cannot exceed ± 5 (Oso, 2013).
The level of significance indicates that the maximum probability of rejecting a null
hypothesis if it were true is 5 in 100.
3.8 Ethical Considerations
The researcher obtained all the necessary permitted and approval letters before
proceeding with the study. The researcher obtained informed consent from every respondent
before administering the instruments. To protect the respondents’ identities, data was
reported data as a block instead of highlighting individual cases. The researcher also ensured
that data collected is not made to conform to a predetermined opinion. Further, the researcher
treated all information provided with highest privacy and confidentiality, and no information
was passed to a third party without express permission from the respondents.

37. Crop production
25
CHAPTER FOUR
RESULTS AND FINDINGS
3.1 Introduction
This study investigated the challenges facing crop production among small scale
farmers in rural areas of Dilla district. A challenge is a problem or a difficulty encountered to
crop production, and was characterized by infrastructural development, environmental factors
and agricultural technology (Verburg, 2009). Crop production is a complex business,
requiring many skills (such as biology, agronomy, mechanics, and marketing) and covering a
variety of operations throughout the year (Epa, 2012). The study arose from the fact that the
crop production in Dilla district had declined by 2.05% between 2010-2014 which pointed to
potential food insecurity in one of the districts with the highest agricultural production
potential in the country. Data was collected from 147 out of intended 152 active small scale
farmers. This was a 96.71% response-return-rate which was acceptable since it was more
than the 70% return-rate recommended in social science research (Oso, 2013). Data was
collected from the five main villages in Dilla district on the demographic characteristics of
the respondent and on infrastructural development, environmental factors and agricultural
technology. This chapter reports how data was compiled, analyzed and interpreted, and the
findings of these procedures in the line with the research objectives. But demographic
characteristics are presented first.
4.2 Demographic Characteristics of Respondents
The demographic information on respondents was collected on gender, marital status,
age, level of formal education and location of origin. Data demographic characteristics are
presented to allow for determination of the extent of the generalization of findings by the end

38. Crop production
26
users. Data on demographic characteristics was organized using percentages technique, and
the results are presented in the following subsections.
4.2.1 Gender of Respondents
Respondents were asked to indicate their gender. The issue of gender was necessary
to determine whether the female gender was equally involved in agricultural activities. The
responses are summarized in Figure 2.
Figure 2. Gender of the respondents.
Figure 2 shows the distribution of respondents by gender. It shows that majority
(83%) of the respondents were males while the remaining (17%) were females. This shows
that most of the agricultural activities are carried out by males. This is in the line with the
Somali culture where men are responsible for farming activities while women are responsible
for home activities and for child care. Thus increasing crop production in quality and quantity
is heavily dependent on the male farmers.

39. Crop production
27
4.2.2 Marital Status of Respondents
Respondents were also asked to indicate their marital status. This information was
important as a way of projecting the people likely to be affected by declining food
production. They responded as shown in Figure 3.
Figure 3. Marital Status of the respondents.
Figure 3 shows the distribution of respondents by marital status. It shows that a
majority (61.2%) of the small scale farmers surveyed were married whereas 7.5% were
divorced. This means that the majority of the small scale farmers are family people and
therefore declining agricultural production affects more than single person who provide
information. Hence low food production affects more people than those reported in here.
4.2.3 Age of Respondents
Respondents were also asked to indicate their age as a basis for gauging their
experience and maturity in agricultural activities. They responded as shown in Figure 4.

40. Crop production
28
Figure 4. Age of the respondents.
Figure 4 shows the distribution of respondents by age. It shows that most (32.0%) of
respondents were aged above 45 years while only 9% of respondents were aged less than 15
years. This indicates that most of the small scale farmers surveyed were mature people with
sufficient experience of agricultural activities. They were therefore in a good position to
describe the challenges they are facing in producing crops.
4.2.4 Distribution of Respondents of Level of Education
The respondents were also asked to indicate their highest level of formal education as
one of the demographic characteristics. Level of education affects all aspects of life,
including farming methods and techniques. They responded as summarized in Figure 5.

41. Crop production
29
Figure 5. Level of Formal Education of the respondents.
Figure 5 shows the distribution of respondents by level of education. It shows that
most (44.9%) of the respondents had no formal education, while 22.4% had primary level
education. But some 9.0% had secondary level education, and only 3.4% of the respondents
had college or university education. This indicates that the level of education among small
scale farmers in Dilla district is rather low, and this could hinder efforts to increase crop
production. They may not have adequate understanding of the modern farming methods.
4.2.5 Distribution of Respondent by Village of Origin
The respondents were also asked to indicate their village of origin. This was necessary
as an indicator of the representativeness of the sample. They responded as summarized in
Figure 6.

42. Crop production
30
Figure 6. Village of Origin.
Figure 6 shows the distribution of respondents by village of origin. It shows that most
(49%) of the respondents came from Dilla Village while 24% came from Jarahoroto Village.
Another 15% came from Dharar-waxar village and 7% came from Geedi-diqsi village.
Another 5% of the respondents came from Saba-wanag village. While the proportions are not
equal, it shows that data was collected from all villages in the district. Hence the report has
captured views of the whole region of crop production.
4.3 Crop Production and Associated Challenges
4.3.1 Measurement of Variables
The researcher proceeded to determine the challenges facing crop production among
small scale farmers in rural areas of Dilla district. The challenges were hypothesized as
infrastructural development, environmental factors and agricultural technology. The study
pursued three specific objectives: to determine the effect of infrastructural development,

43. Crop production
31
effect of environmental factors and effect of agricultural technology on crop production
among small scale farmers in rural areas of Dilla district.
Infrastructural development was operationalized as roads, water catchment and
storage facilities; environmental factors were operationalized as rainfall, soil type and land
size; while agricultural technology was operationalized as plows, thresher and irrigation
system. Respondents were requested to react to several statements on each subsidiary
variable. The response in each subsidiary variable was scored between 1 to 3. The scores on
each subsidiary variable were added to obtain the total score and rating on the variable.
The scores on infrastructural development ranged from 10-47 and were divided into
an interval of three such that scores of 10-21 were rated poor and weighted 1; scores of 22-33
were rated fair and weighted 2; scores of 34-47 were rated good and weighted 3. The scores
on environmental factors ranged from 9-45 and were rated such that scores of 9-20 were rated
poor and weighted 1; scores of 21-32 were rated fair and weighted 2; scores of 33-45 were
rated good and weighted 3. The scores on agricultural technology ranged from 8-31. Scores
of 8-15 were poor and weighted of 1; scores of 16-23 were rated fair and weighted 2; scores
of 24-31 were rated good and weighted 3. The variables were scored, weighted and
interpreted as summarized in Table 2.

44. Crop production
32
Table 2
Scoring and Weighting of Variables
Score/ Weight/Status
Hypothesized Challenges Good = 3 Fair = 2 Poor = 1
Infrastructural Development 34 – 47 22 - 33 10 – 21
Environmental Factors 33 – 45 21 - 32 9 – 20
Agricultural Technology 24 – 31 16 - 23 8 – 15
Crop production was measured from its characteristics of quantity and quality using
document analysis checklist in Appendix VII. Respondents were asked to react to a statement
on each of the items intended to assess the overall status of the item. Each variable was
scored between 1 to 5, and crop production was obtained from the sum total of the individual
scores on each variable. The scores were then expresses as a percentage of 56 as the base as
summarized in Appendix VIII.
4.3.2 Infrastructural Development and Crop Production
The first objective of this study was to establish the effect of infrastructural
development on crop production among small scale farmers in Dilla district. Infrastructural
development was characterized as roads, water catchment and storage facilities. Respondents
were asked to react to several statements on the status of roads, water catchment and storage
facilities for small scale farmers. The responses were scored and used to determine the
overall status of infrastructural development. The results summarized in Table 3 were
obtained.

45. Crop production
33
Table 3
Crop Production with Infrastructural Development
Infrastructural
Development
Crop Production (%) N N-Percent S
Poor 39.25 119 80.95 14.37
Fair 44.20 20 13.61 15.10
Good 54.25 8 5.44 22.11
Total 39.25 147 100.00 15.40
Note. N = Sample, S = Standard deviation.
Table 3 shows the crop production of small scale farmers in Dilla district against the
status of infrastructural development. It indicates that 119 small scale farmers had poor
infrastructural development and an average crop production of 39.25%. Another 20 small
scale farmers had fair infrastructural development with an average crop production of
44.20%; while 8 small scale farmers had good infrastructural development with an average
crop production of 54.25%. Table 3 further shows that small scale farmers with good
infrastructural development had higher crop production (M = 54.25%, S = 22.11) than small
scale farmers with fair infrastructural development (M = 44.20%, S = 15.10), and small scale
farmers with poor infrastructural development (M = 39.25%, S = 14.37). The overall crop
production of small scale farmers in Dilla district was only 39.25% (S = 15.40).
The statistics in Table 3 suggest that crop production of small scale farmers in Dilla
district depend on the status of infrastructural development; the better infrastructural
development, the higher the crop production of the small scale farmers. Further, Table 3
shows that the majority (80.95%) of small scale farmers surveyed in Dilla district had poor

46. Crop production
34
infrastructural development while 13.61% of small scale farmers surveyed had fair
infrastructural development. Only 5.44% of small scale farmers surveyed had good
infrastructural development. Thus infrastructural development for small scale farmers in Dilla
district was poor.
The data in Table 3 was analyzed using regression technique to determine if
infrastructural development has significant effect on crop production of small scale farmers,
under the null hypothesis that;
H01: Infrastructural development does not have significant effect on crop production
of small scale farmers in Dilla district.
The results of the analysis are summarized in Table 4.
Table 4
Regression Analysis of Crop Production on Infrastructural Development
Model B R R2
R2
adj Std.ϵ F Sig.
Constant 32.517 3.104 .000
Infrastructural
development
6.607 .233 .054 .048 2.286 8.352 .004
Note. F(1, 145) = 3.91; R2
adj = R2
adjusted.
R shows the correlation between crop production and infrastructural development. R
= .233 indicates that there is a low positive association between infrastructural development
and crop production of small scale farmers in Dilla district and that crop production increases
with increasing infrastructural development. R2
is the proportion of the variance in crop
production that can be explained from the knowledge of the status of infrastructural

47. Crop production
35
development. However R2
adj. is a better estimate of R2
. R2
adj = .048 shows that 4.8% of the
variance in the crop production of small scale farmers in Dilla district can be explained from
the knowledge of infrastructural development. The rest of 95.2% are due to other factors not
investigated in this study.
B (6.607) is the unstandardized regression coefficient, showing the weight of
infrastructural development and its strength in the regression model. From the value of B and
the constant term, a regression equation was developed as;
CP1
= 32.517 + 6.607I…Eq 2;
where C1
= predicted crop production and I = infrastructural development. This shows that
for a unit change in infrastructural development, crop production changes by about 6 units.
F is the probability that the null hypothesis for the full model is true. F (1, 145) =
8.352, p = .004, and Fo = 8.352 > F (1, 145) = 3.91; which led to the rejection of the null
hypothesis. The result proposed by the data in Table 3 was therefore upheld. A small scale
farmer with good infrastructural development has higher crop production than the small scale
farmer with poor or fair infrastructural development. The study therefore established that
infrastructural development have a significant effect on crop production of small scale
farmers in Dilla district. Therefore availability and absence of roads, storage facilities and
water catchment have significant effect on the crop production of small scale farmers in Dilla
district.
4.3.3 Environmental Factors and Crop Production
The second objective of this study was to establish the effect of environmental factors
on crop production of small scale farmers in Dilla district. Environmental factors were
characterized by rainfall, soil type and land size. Selected small scale farmers were asked to
react to several statements on rainfall, soil type and water. The responses were scored and

48. Crop production
36
used to determine the overall status of environmental factors. The results summarized in
Table 4 were obtained.
Table 5
Crop Production with Environmental Factors
Environmental
Factors
Crop Production (%) N N-Percent S
Poor 39.35 74 50.34 13.13
Fair 39.81 62 42.18 15.78
Good 55.36 11 7.48 20.66
Total 40.74 147 100.00 15.39
Note. N = Sample, S = Standard deviation.
Table 5 indicates the crop production of small scale farmers in Dilla district against of
environmental factors. It shows that 74 small scale farmers surveyed were under poor
environmental factors and had an average crop production of 39.35%. Another 62 small scale
farmers surveyed were under fair environmental factors and reported an average crop
production of 39.81%; while 11 of the small scale farmers surveyed were under good
environmental factors and reported an average crop production of 55.36%. Table 4 further
shows that small scale farmers under good environmental factors had higher crop production
(M = 55.36%, S = 20.66) than small scale farmers under fair environmental factors (M =
39.81%, S = 15.78), and small scale farmers under poor environmental factors (M = 39.35%,
S = 13.13). The overall crop production of small scale farmers in Dilla district was only
40.74% (S = 15.39).

49. Crop production
37
The statistics in Table 5 suggest that crop production of small scale farmers in Dilla
district depend on the status of environmental factors; the better environmental factors, the
higher the crop production of small scale farmers. Further, Table 4 shows that the majority
(50.34%) of small scale farmers surveyed were under poor environmental factors while
42.18% of small scale farmers surveyed were under fair environmental factors. Only 7.48%
of small scale farmers were under good environmental factors. Thus environmental factors
for small scale farmers in Dilla district were generally poor.
The data in Table 5 was analyzed using regression technique to determine if
environmental factors had significant effect on crop production of small scale farmers, under
the null hypothesis that;
H02: Environmental factors do not have significant effect on crop production of small
scale farmers in Dilla district.
The results of the analysis are summarized in Table 6.
Table 6
Regression Analysis of Crop Production on Environmental Factors
Model B R R2
R2
adj Std.ϵ F Sig.
Constant 33.597 3.373 .000
Environmental Factors 4.547 .186 .035 .028 1.993 5.204 .024
Note. F(1, 145) = 3.91; R2
adj = R2
adjusted.
R shows the correlation between crop production and environmental factors. R = .186
indicates that there is a low positive association between environmental factors and crop
production of small scale farmers in Dilla district, and that the crop production of small scale

50. Crop production
38
farmers increases under good environmental factors. R2
is the proportion of the variance in
the crop production that is explained from the knowledge of environmental factors. But R2
adj. is a better estimate of R2
. R2
adj = .035 indicates that 3.5% of the variance in the crop
production of small scale farmers in Dilla district can be explained from the knowledge of
environmental factors. The rest of 96.5% of the variance are due to other factors not
investigated in this study.
B (4.547) is the unstandardized regression coefficient, showing the weight of
environmental factors and its strength in the regression model. From the value of B and the
constant term, a regression equation was developed as;
C1
= 33.597 + 4.547E…Eq 3;
where C1
= predicted crop production and E = Environmental factors. This indicates that for a
unit change in environmental factors, crop production changes by about 4 units.
F is a measure of the overall significance of the regression model. F (1, 145) = 5.204,
p = .024, which led to the rejection of the null hypothesis. The hypothesis that environmental
factors do not have significant effect on crop production of small scale farmers in Dilla
district was therefore rejected. The result suggested by the data in Table 5 was therefore
allowed. A small scale farmer under good environmental factors has higher crop production
than a small scale farmer under poor or fair environmental factors. The study therefore
established that environmental factors have a significant effect on crop production by small
scale farmers in Dilla district. Therefore rainfall, soil type and water have significant effect
on the crop production of small scale farmers in Dilla district.
4.3.4 Agricultural Technologies and Crop Production
The last objective of this study was to determine the effect of agricultural
technologies on crop production of small scale farmers in Dilla district. Agricultural

51. Crop production
39
technologies were characterized by plows, threshers and irrigation system. Selected small
scale farmers were asked to react to statements on plows, threshers and irrigation system. The
responses were scored and used to determine the overall status of agricultural technologies.
The results summarized in Table 5 were obtained.
Table 7
Crop Production with Agricultural Technologies
Agricultural Technologies Crop Production (%) N N-Percent S
Poor 38.76 87 59.18 13.68
Fair 38.75 36 24.49 13.38
Good 50.92 24 16.33 20.08
Total 40.74 147 100.00 15.39
Note. N = sample; S = Standard Deviation.
Table 7 shows the crop production of small scale farmers in Dilla district against the
status of agricultural technologies. It shows that 87 of the small scale farmers surveyed had
poor agricultural technologies and their average crop production was 38.76%. Another 36 of
the small scale farmers surveyed had fair agricultural technologies and reported an average
crop production of 38.75%. But 24 of the small scale farmers surveyed had good agricultural
technologies and reported an average crop production of 50.92%. Table 7 also shows that
small scale farmers with good agricultural technologies had higher crop production (M =
50.92%, S = 20.08) than small scale farmers with fair agricultural technologies (M = 38.75%,
S = 13.38), and small scale farmers with poor agricultural technologies (M = 38.76%, S =
13.68). The statistics in Table 7 suggest that crop production of small scale farmers in Dilla

52. Crop production
40
district depend agricultural technologies; the better agricultural technologies, the higher the
crop production of small scale farmers. Further, Table 5 shows that majority (59.18%) of
small scale farmers surveyed had poor agricultural technologies while 24.49% of small scale
farmers surveyed had fair agricultural technologies. And 16.33% of small scale farmers had
good agricultural technologies. Thus agricultural technologies of small scale farmers in Dilla
district were generally poor.
The data in Table 7 was analyzed using regression technique to determine if
agricultural technologies had significant effect on crop production of small scale farmers,
under the null hypothesis that;
H03: Agricultural technologies do not have significant effect on crop production of
small scale farmers in Dilla district.
The results of the analysis are summarized in Table 8.
Table 8
Regression Analysis of Crop Production on Agricultural Technologies
Model B R R2
R2
adj Std.ϵ F Sig.
Constant 32.946 2.850 .000
Agricultural Technologies 4.961 .244 .060 .053 1.635 9.212 .003
Note. F (1, 145) = 3.91; Std. = standard error; R2
adj = R2
adjusted.
In Table 8, R shows the correlation between crop production and agricultural
technologies. R = .244 indicates that there is a low positive association between agricultural
technologies and crop production of the small scale farmers. But crop production of small
scale farmers in Dilla district increases with improvement in agricultural technologies. R2
is

53. Crop production
41
the proportion of the variance in the crop production of small scale farmers that is explained
from the knowledge of agricultural technologies. But R2
adj. is a better estimate of R2
. R2
adj
= .053 shows that 5.3% of the variance in the crop production of small scale farmers in Dilla
district can be explained from the knowledge of agricultural technologies. The rest of 94.7%
are due to other factors which were not investigated in this research.
B (4.961) is the unstandardized regression coefficient, showing the weight of
environmental factors and its strength in the regression model. From the value of B and the
constant term, a regression equation was developed as;
C1
= 32.946 + 4.961AT…Eq 4;
where C1
= predicted crop production and AT = Agricultural technologies. This indicates
that for a unit change in agricultural technology, crop production changes by about 5 units.
F is the test statistic used to decide whether the model as a whole has a statistically
significant predictive capability. F (1, 145) = 9.212, p = .003, and Fo = 9.212 > F (1, 145) =
3.91, which led to the rejection of the null hypothesis. The hypothesis that agricultural
technologies do not have significant effect on crop production of small scale farmers in Dilla
district was therefore rejected. Small scale farmers with good agricultural technologies had
higher crop production than Small scale farmers with poor or fair agricultural technologies.
The study therefore established that agricultural technologies have a significant effect on crop
production of small scale farmers in Dilla district. Therefore plows, threshers and irrigation
system have significant effect on the crop production of small scale farmers in Dilla district.

54. Crop production
42
CHAPTER FIVE
DISCUSSION, CONCLUSION AND RECOMMENDATIONS
5.1 Introduction
This study investigated the challenges facing crop production among small scale
farmers in Dilla district. Data was collected from 147 active small scale farmers in Dilla
district, analyzed using regression and reported in chapter four. This chapter presents a
summary of the findings, draws a conclusion based on the findings and makes general and
specific recommendations for the improvement of crop production in Dilla district.
5.2 Summary of Findings
The first objective of this study was to determine the effect of infrastructural
development on crop production of small scale farmers in Dilla district. Infrastructural
development was characterized by roads, water catchment and storage facilities. The majority
(80.95%) of small scale farmers surveyed had poor infrastructural development with an
average crop production 39.25%, (S = 14.37). Infrastructural development for small scale
farmers in Dilla district was judged to be poor. But infrastructural development was found to
have significant effect on crop production of small scale farmer in Dilla district, (F [1, 145] =
8.352, p = .004) and to account for 4.8% of the variance in crop production of small scale
farmers in Dilla district (R = .233, R2
adj = .048, p = .004). Therefore roads, water catchment
and storage facilities have a significant effect on crop production of small scale farmers in
Dilla district.
The second objective of this study was to determine the effect of environmental
factors on crop production of small scale farmers in Dilla district. Environmental factors were
characterized by rainfall, soil type and land size. The majority (50.34%) of small scale
farmers surveyed were under poor environmental factors and had an average crop production

55. Crop production
43
of 39.35% (S = 13.13). Environmental factors for small scale farmers in Dilla district were
found to be generally poor. Further environmental factors were found to have a significant
effect on crop production of small scale famers in Dilla district, (F [1, 145] = 5.204, p =
.024), and to account for 3.5% of the variance in the crop production of small scale farmers in
Dilla district (R = .186, R2
adj = .035, p = .024). Therefore rainfall, soil type and water had a
significant effect on the crop production of small scale farmers in Dilla district.
Lastly, this study determined the effect of agricultural technologies on crop
production of small scale farmers in Dilla district. Agricultural technologies were
characterized by plows, threshers and irrigation system. The majority (59.18%) of small scale
farmers surveyed had poor agricultural technologies with an average crop production of
38.76% (S = 13.68). An agricultural technology of small scale farmers in Dilla district was
found to be poor. But agricultural technologies were found to have a significant effect on
crop production of small scale famers in Dilla district, (F [1, 145] = 9.212, p = .003), and to
account for 5.3% of the variance of the crop production of small scale farmers in Dilla district
(R = .244, R2
adj = .053, p = .003). Consequently plows, threshers and irrigation system have
a significant effect on the crop production of small scale farmers in Dilla district. Therefore,
the study established that;
i. Infrastructural development have significant effect on crop production of small scale
farmer in Dilla district, F (1, 145) = 8.352, p = .004.
ii. Environmental factors have a significant effect on crop production of small scale famers in
Dilla district, F (1, 145) = 5.204, p = .024.
iii. Agricultural technologies have a significant effect on crop production of small scale famers
in Dilla district, F (1, 145) = 9.212, p = .003.

56. Crop production
44
5.3 Discussion
This section discusses the findings of the study as summarized in 5.2. The study
investigated three specific objectives and consequently made three key findings. First, the
study found that infrastructural development of small scale farms in Dilla district was poor.
This was deduced from fact that the majority (80.95%) of small scale farmers surveyed had
poor infrastructural development. However infrastructural development was found to have
significantly influence the crop production of small scale farmers in Dilla District, (F [1, 145]
= 8.352, p = .004), and to account for 4.8% of the variance in crop production of the small
scale farmers, R2
= R2
adj = .048, p = .004.
The find that infrastructural developments have a significant effect on crop production
is important for several reasons. Firstly, infrastructure development involves changes in
fundamental structures that are required for the proper functioning of a community and
society (Cerny, 2012). It increases consumer demand in rural areas, and facilitates the
integration of less-favored rural areas into national economies (Shimokawa, 2006). This
means that inadequate infrastructural development can be a serious constraint to growth and
crop production (Grey, 2007). The main factors of infrastructural development for small scale
farmers are water catchment, roads and storage facilities for produce. These factors have been
shown to have direct influence on crop production (Molden, 2003). The finding that there is
poor infrastructural development indicates that the small scale farmers in Dilla district have
poor roads, they lack water catchment and they have poor storage facilities. These could
negatively affect their crop production. This finding supports the view of Rosegrant (2003)
who investigated factors affecting crop production in rural areas in Sudan. Rosegrant (2003)
found that infrastructural development plays a key role in improving crop production. This
finding also supports Mukherjee’s (2005) that poor infrastructural development can
significantly affect crop production as it can damage the market access of crops. Moreover, it

57. Crop production
45
also agrees with the views of Dorward (2004) that poor infrastructural development leads to
production of fewer amounts of crops and difficult to bring crops to market easily. In general,
poor infrastructural development of small scale farmers in Dilla district is one of the
challenges facing the crop production of the small scale farmers.
Secondly, this study found that environmental factors of small scale farmers in Dilla
district were poor. Majority (50.34%) of small scale farmers surveyed were under poor
environmental factors. Moreover, environmental factors were found to have a significant
effect on crop production of small scale farmers in Dilla district, (F [1, 145] = 5.204, p =
.024), and to account for 3.5% of the variance in crop production of the small scale farmers,
R2
= R2
adj = .035, p = .024. The finding that environmental factors have a significant effect
on crop production can be understood from the definition of an environmental factor. An
environmental factor is any factor, whether abiotic or biotic, that can influence a living
organism (Thieltges, 2008). It refers to external (climate, geographic, technology) and
internal elements (community culture, stakeholder relationships) which can negatively impact
on crop production (Sietchiping, 2006), or to anything that changes the local environment
including natural forces like weather and human effects (Schwartz, 2003). Viewed this way,
an environmental factor is the natural force that affects crop production. Its status therefore
has a direct influence on crop production.
Environmental factors that are known to directly affect crop production of small scale
farmers are soil type, rainfall and farm land. The fact that an environmental factor of small
scale farms in Dilla district was poor implies that rainfall was largely insufficient, soil type
was degraded and farm lands were generally small. These conditions can definitely reduce a
farmers’ productivity. This finding agrees with the view of Yengoh (2010) who investigated
trends in agriculturally-relevant rainfall characteristics for small-scale agriculture in northern
Ghana and found that the amount of rainfall and its distribution over the year (especially

58. Crop production
46
during the farming season) greatly affects the productivity of agriculture in a region. It also
agrees with the view of Murage (2000) who studied economic efficiency and farm size
among wheat farmers in Nakuru district, Kenya. Murage (2000) found that differences in soil
quality led to differences in soil productivity which affected the output of the small farmers.
Babatunde (2008) also studied the impact of small scale irrigation technologies on crop
production by Fadama users in Kogi State, Nigeria and found that farmland size had a
positive relationship with the crop production (output). Hence the fact that poor
environmental factors had led to reduced crop production of small scale farmers in Dilla
district is just a replica of these concluded studies. They cannot produce differently under
poor environmental factors.
Agricultural technology of small scale farms in Dilla district was found to be poor.
Agricultural technology was also found to significantly influence the crop production of
small scale farmers in Dilla District, (F [1, 145] = 9.212, p = .003). It accounted for 5.3% of
the variance in crop production of the small scale farmers, R2
= R2
adj = .053, p = .003.
Like in the case of environmental factors, the finding on the influence of agricultural
technologies on crop production can be understood from the meaning of agricultural
technology. Agricultural technologies are the machines used on farming system (Wang,
2006). It is the application of techniques to control the growth and harvesting of products
(Brosnan, 2001). Agricultural technology generally focuses on technological processes used
in agriculture to create an understanding of how processes, equipment and structures are used
to sustain and maintain quality of crops and to promote its quantity Chel, 2010). The main
elements of agricultural technologies investigated in this study were plows, threshers and
irrigation systems. The finding that there are poor agricultural technologies implies that the
small scale farmers in Dilla district have poor or non use plows and threshers and that

59. Crop production
47
irrigation systems for small scale farmers are generally poorly developed. This can impact
negatively on crop production.
This study is in line with the views of Yohanna (2011) and Dinku (2004). Yohanna
(2011) conducted a survey of mechanization problems of the small scale (Peasant) farmers in
the Middle Belt of Nigeria and found that application of machines to agriculture led to
increased production. Poor agricultural technology of small scale farmers in Dilla district
could result into poor production as Yohanna found in Nigeria. Dinku (2004) also
investigated two irrigation systems in eastern Oromia, Ethiopia and found that irrigation
system improved food production where it was well managed by lowering the risk of crop
failure. Lowering crop failure is synonymous to increasing crop production. Both studies
reported declining crop production due to non or inappropriate use of technology. This is also
the finding of this present study. The finding that was poor agricultural technology by small
scale farmers in Dilla district had led to reduced crop production of small scale farmers is
similar to results that had been found elsewhere.
5.4 Conclusion
This section draws the conclusion of the study in line with purpose statement, and
taking into account the findings and the discussions already made in the above sections. The
purpose of this study was to determine the challenges facing crop production among small
scale farmers in Dilla district, but with specific focus on infrastructural development,
environmental factors and agricultural technologies. The study found that infrastructural
development, (F [1, 145] = 8.352, p = .004, R2
adj = .048); environmental factors, (F [1, 145]
= 5.204, p = .024, R2
adj = .035); and agricultural technologies (F [1, 145] = 9.212, p = .003,
R2
adj = .053) all had significant effect on crop production of small scale farmers in Dilla
district, and respectively account for 4.8%, 3.5% and 5.3% of the variance in crop production

60. Crop production
48
of small scale farmers in Dilla district. From analysis of the findings, the study concludes that
agricultural technology is the most significant factor influencing crop production of small
scale farmers in Dilla district. This is because it accounts for the largest variance (5.3%) of
the significant factors of crop production among small scale farmers in Dilla district. Hence
the low crop production among small scale farmers in Dilla district is due to poor or non use
plows and threshers, and poorly developed irrigation systems.
5.5 Recommendations
5.5.1 General Recommendations
Referring to the findings and conclusion presented in 5.3 and 5.4, the study makes the
following recommendations: First the study recommends that Ministry of Agriculture and
Environment improve infrastructural development of the small scale farmers through creating
access roads, protecting water catchments and supporting the farmers to acquire modern
storage facilities.
The study also found that environmental factors under which the small scale farmers
work was poor and this had reduced crop production and greatly affected the livelihoods of
small scale farmers. The study recommends that Somaliland government initiate environment
awareness campaign program to enlighten the community on the effect of deforestation on
crop production and the advantages of conservation farming. Small scale farmers should be
educated on, encouraged and supported to acquire green houses. This should ensure that the
negative impact of environmental factors on crop production is reduced.
Finally, the study found that agricultural technology of small scale farmers in Dilla
district was poor and had also reduced crop production of the small scale farmers Dilla
district. More importantly, the small scale farmers in Dilla district did not use or poorly used
plows and threshers, and irrigation system for small scale farmers were generally poorly

61. Crop production
49
developed. The study recommends that the government of Somaliland create a scheme that
can support the small scale farmers to acquire plows and threshers at district level, and
construct irrigation systems to support small scale farmers at the village level. This should
improve the quantity and quality of crops produced by small scale farmers in Dilla district.
5.5.2 Recommendations for Further Research
This study investigated challenges facing crop production of small scale farmers in
Dilla district, but it focused on infrastructural development, environmental factors and
agricultural technology. It was observed in the course of this study that available technologies
for the small scale farmers in Dilla district were not being fully utilized. But despite this
realization, the time and resources available could not allow the researcher to investigate this
further. But it was clear that the technology were not welcome by the farmers. The researcher
recommends that a study be conducted to design and develop appropriate technologies
specific to small scale farmer in rural areas of Dilla district. Such technologies should be
culture sensitive and should suit the farming styles of the people. This will ensure that
appropriate technology is used and crop production is improved.

62. Crop production
50
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