EFFECT OF ONSET VARIABILITY OF RAINS ON MAIZE PRODUCTION IN SINYERERE AREA OF TRANS-NZOIA COUNTY KENYA
By
Mercy Waiganjo
Reg. No: N80/2943/2016
Signature: ………………………………… Date: ……………………..………
A Research Project Proposal Submitted in Partial Fulfillment of the Requirements for the Degree of Bachelor of Science (Environmental Education) in the School of Environmental Studies of Kenyatta University
Supervisor:
Dr. James Koske
Signature: …………………………………………… Date: ………………………….
Department of Environmental Sciences and Education
DECEMBER 2019
ABSTRACT
The research will investigate the effect of the onset variability of rains on maize production in the Sinyerere area of Trans-Nzoia County, Kenya. The adverse climatic condition shift has led to an increase in the poverty level due to increased losses in maize production, thus affecting people’s livelihood all over the world. Therefore, a proposal is written to create a guideline on what one will execute to come up with the proper findings. In the introduction chapter, the researcher has written a succinct background of the issue under study by demonstrating the importance of climate change affecting maize production. The researcher has also come up with three major objectives, which hasten the attainment of the set aims; To find out the relationship between the onset of rains and maize production and examine the maize production trend. Once completed, the study will enable one to portray how the onset variability of rainfall affects maize production in Sinyerere Area. The literature review has expounded on the concept of climate change and its impact on crop production. In chapter three, one has indicated that a mixed-method approach will be employed. Both statistical and non-numerical data will be used to portray the actual prevailing situation in Sinyerere. On the other hand, one will need to employ both cluster and random sampling procedures to identify one hundred and nine maize farmers targeted for the data collection. The use of this combination will help to reduce biases, thus, improving the validity of the anticipated results.
TABLE OF CONTENTS
1.1: Background Information. 1
1.2: Statement of the Problem.. 2
1.5: Research Hypotheses (Null) 3
1.6: Justification of Study. 3
2.2 Climate Change Impacts on Food Crop Yields. 10
3.7: Data Collection Procedure. 14
Appendix I: Questionnaire to Household Head. 18
1.0: INTRODUCTION
1.1: Background Information
Climate change is regarded as one of the most severe agendas discussed by the world-renowned bodies today. According to (Sarris, A. & Jamie, M, 2013), the adverse climatic condition shift has led to an increase in poverty, thus, affecting the livelihood of the majority all over the world. The possibility of climate change negatively impacting livelihood is further worsened because the majority of the world population relies on farming. (Sarris, et al., 2013) state that an average of 80% of the global population depends on rain-fed agriculture. Therefore, this means that any slight change in climatic patterns has the potential of impacting them negatively. Today’s climatic pattern, which is characterized by shorter, erratic, unseasonal, and heavy rainfall, fluctuations in temperatures, and unusual storms, has affected the average yield of crops produced per unit of land (Sarris, et al., 2013). The challenge is compounded by the fact that the majority practice rain-fed farming, meaning that any slight drop in the rainfall level or change in its patterns may induce high losses.
The global trend is further reflected in Kenya and in, particular, Trans-Nzoia County. In Kenya, more than 80% of the entire population relies on farming either directly or indirectly (Mathenge, L., Mary, K., & David, L. T., 2009) (Wandaka, 2013). More than 90% of the farmers rely on rain-fed agriculture until their land (Ministry of Agriculture, n.d.). In Trans-Nzoia County and Sinyerere Division, most farmers engage in small scale farming where a large percentage have less than 5 acres of land (Ministry of Agriculture, n.d.). Therefore, this means that it is hard to mechanize their land, making it impossible to engage in irrigation. Thus, the recent change in climatic patterns (change in the dates of rains) has negatively impacted it. Farmers have faced many difficulties in determining the appropriate times to plant maize, as it is hard to predict when the high season rain begins. The move has led to interference with their regular farming schedule, thus compromising the maize yield’s quality.
1.2: Statement of the Problem
The research problem cannot be immensely covered without highlighting the adverse impacts of a change in the region’s climatic patterns. The rainfall patterns are no longer reliable as the traditionally wet months, which occur between April and October, maybe dry (Wandaka, 2013). Thus, this has induced losses to maize farmers because of failed calculation on when they are supposed to sow their maize seeds. Inadequate rainfall when growing maize dries up the crop, thus, lowering the level of yield. There are also some instances of having heavy rains at the beginning of the years, which catches farmers unaware (Kiiru, 2016). They do not have a chance to tap into such opportunities, making them not realize their optimal maize productivity. The onset of shorter rains in October and November during the harvesting period has also resulted in heavy losses as the already dry maize in the cobs develops aflatoxins (Kiiru, 2016). The condition has given rise to substantial losses as the quality of their yield also lowers.
The trend has led to the lowering of the residents’ livelihoods since most Sinyerere farmers rely on maize to meet their daily expenses. The price per 90-kilogram bag of maize has continued to lower, a loss that is also compounded by the decrease in yield per acre of land. Traditionally, Sinyerere farmers used to receive 25-30 bags of maize per acre, lowered to below 20 bags (Ministry of Agriculture, n.d.). The most devastating aspect is that the trend seems to be worsening with as the yield per acre appears to be shrinking, which ushers in the existence of a deemed future. The continuous exacerbation of the maize production trend maize impoverishes these people if an urgent solution is not found.
1.3: Research Questions
- How has the onset of rains in the Sinyerere area varied in the period 2015-2019?
- How has maize production in the Sinyerere area varied in the period 2015-2019?
- Is there any relationship between the onset of rains and maize yield in the Sinyerere area in the period 2015-2019?
1.4: Research Objectives
- To determine the effect of onset variability of rains on maize production in the Sinyerere Area of Trans-Nzoia County, Kenya.
- To examine the maize yield trend in the Sinyerere area in the period 2015-2019.
- To find out the relationship between the onset of rains and maize yield in Sinyerere in 2015-2019.
1.5: Research Hypotheses (Null)
- The onset of rains in the Sinyerere area has not significantly varied (p<0.05)in the period 2015-2019
- Maize yield in Sinyerere has not significantly varied (p<0.05) in the period 2015-2019.
- There is no significant relationship (Pearson r; p<0.05) between the onset of rains and maize yield in Sinyerere in 2015-2019.
1.6: Justification of the Study
The study will be highly significant, considering that it will help develop the right solution that has led to a decrease in the level of livelihoods of maize farmers in the Sinyerere Division. It will portray the adverse climatic change as a significant contributor to this, demonstrating why adequate corrective measures will need to be implemented. The study is justified considering that a sizeable number of the residents are not well educated, which makes them lack appropriate mechanisms for adapting to the climatic patterns. Despite the difference in the onset of rains and an increase in temperature in some rare months, they have stuck to the traditional maize planting routine. Nyerere farmers have continued realizing heavy losses due to a decrease in maize production quality and quantity. Therefore, the study’s completion will act as an eye-opener to them by bringing them to the reality of the negative impacts affiliated with the climatic changes. As farmers who rely on rain-fed agriculture, they will need to apply the recommendations of the project to avoid incurring substantial losses in the future.
The study will play a significant role in enabling farmers to overcome climate change challenges, which induces the onset variability of rains in the Sinyerere area. Key players such as the Ministry of Agriculture (MoA) and National Cereals and Produce Board (NCPB), among others, may utilize the content of the research findings and recommendations to advise the farmers appropriately. The research will seek to demonstrate why maize farming should be adequately planned and monitored to help farmers avoid huge losses that may impoverish them. The in-depth study of the rainfall patterns in 2015-2019 will help one come up with appropriate conclusions and recommendations. As a result, its practical application will automatically improve the livelihoods of farmers in the Sinyerere area.
1.7: Conceptual Framework
(Jabareen, 2008) states that a theoretical outline that portrays literature synthesis as made by the researcher. It plays a critical role in giving an in-depth explanation of a key phenomenon concerning the study area. The conceptual framework also creates a proper roadmap on the appropriate action that needs to be carried out based on the previously gathered knowledge and the observations made on the study (Jabareen, 2008). It helps create a link between variables (independents and dependent) and demonstrate how they are interlinked. The conceptual framework maps out what is to be investigated to come up with the anticipated findings. Therefore, a diagrammatic representation scheme should depict how independent variables are connected to the dependent variable.
In this study, the onset of Maize production in the Senyerere Area of Trans-Nzoia County will be the dependent variable. The level of maize production will depend on various factors, one of them being the onset variability of rains. The time is taken (beginning from January) for the long rain to begin will play an imperative role in determining the volume of harvest farmers in Sinyerere will enjoy. The intensity of rainfall due to the climatic variability will also be deemed another imperative independent variable that will determine the level of maize harvest realized by farmers in the area. The variability in the onset of rain in Sinyerere will play a critical role in determining rainfall intensity in the area. Another important independent variable that will also be depicted will be the length of the long rains. It will be measured by marking the onset dates and the last day of the rainy season. The infiltration rate of rainfall will also be measured where one will be required to determine the level of rainfall infiltration of rainwater into the soil based on the number of hours it rains in a day. The independent variable is measured based on the number of rainfall hours after the rainy season to determine the level of actual infiltration. The conceptual framework is represented, as indicated below.
Conceptual Framework
Independent variable Dependent variable
Intervening variables
Figure 1: Relationship between Independent and Dependent Variables (related to the Study)
1.9: Definition of Terms
For this proposal, the following words are used to explain the following.
The onset of rains means the date(s) of the start of the first rains marking the beginning
of the maize sowing for the first season. This will be calculated by counting thenumber of days to the first rains’ fall since the start of the year (1st January).
Maize yield means the number of 90 kg bags per ha of threshed maize harvested per
household in the first maize growing season.
Farmer perception means scores obtained by a farmer on a self-rating scale of 1-5
concerning various aspects on the understanding of rainfall variability as it affectsmaize yields in the Sinyerere area.
Farmer characteristics are individual attributes of the head of household, includingage, years of schooling, socio-economic status, gender, and household size.
2.0: LITERATURE REVIEW
2.1 Climate Change Concept
The climate change concept refers to the weather patterns’ variation over a long period, which may usually run into years (Schmidt-Thome, P & Greivings, S, 2013). On average, change in climatic patterns is measured over a period of 35-40 years (Asafu-Adjaye, 2010). Climate change is, therefore, regarded as a global challenge, which does not have any borders. It calls for the proper coordination between different parties in the world to control it effectively.
The climate change concept is highly affiliated with global warming as the two concepts work hand in hand. Many concerned parties, such as the environmentalists, consider climate change to culminate from excessive global warming. According to (Kusumasari 2016), the rise in global temperatures causes a variation in the climatic patterns. The deposition of greenhouse gases such as carbon dioxide in huge volumes because of the increased industrial activities has acted as the principal reason why earth’s average temperatures keep on rising (Waskey, n.d). The high rate of cutting of trees reduces the forest cover and the eventual decimation of carbon sink. Therefore, a sizeable level of greenhouse gases remains suspended in the atmosphere creating a blanket shield. The heat reflected from the earth does not escape into space but is retained between this blanket and the earth’s surface, thus leading to a sudden rise in the average temperatures.
As indicated earlier, global warming leads to adverse climate change variation, such as creating an imbalance in the physical, human, and biological systems (Schmidt-Thome, et al., 2013). Several predisposing factors are touted to be the main reason global warming takes place. Apart from the rise in greenhouse gases and deforestation, the increase in the population and destruction of marine ecosystems also leads to the global warming effect (Howarth, 2013). Therefore, this means that the continued rise in global temperatures can be affiliated to the global population’s continued increase. A large population of the people means that the percentage of carbon dioxide exhaled per unit time is high. As a result, this is likely to induce a greenhouse condition, which leads to a sudden rise in global temperatures. Any slight disturbance in the aquatic environment may also lead to a sudden rise in greenhouse gases. The large water bodies will not have the capacity to optimal greenhouses if they are polluted. The excessive deposition of lethal chemicals will also lead to the massive death of aquatic plants and animals, leading to the general rise in the production of greenhouse gases. Eventually, the trend creates a critical imbalance in the composition of different gases in the atmosphere, thus leading to the rise in average earth temperatures or albedo.
Diagrammatic Representation of Climate Change Concept
Figure 2: Relationship between Climate Change and Global Warming
2.2 Climate Change Impacts on Food Crop Yields
Climate change has culminated in various adverse impacts top among them being reduced agricultural production. The rise in the albedo has led to the sudden meltdown of ice in the Polar Regions, leading to the increase in the sea level (Stuch, B., Schaldach, R. & Schungel, J, 2013). The unfortunate trend has threatened flora and fauna in the coastal regions as some of the lands near the large water bodies continue being submerged (Fuhrer, J. & Gregory, P.J, n.d). The majority of the farmers in the coastal region count losses as their crops are submerged in water, thus counting total losses.
Climate change induces violent weather patterns such as drought and fires. It is worth indicating that the rate of desertification is at an alarming level. The arable lands are no longer productive due to reduced (Stuch, et al., 2013). Therefore, the average agricultural productivity in such land has continued to reduce on an annual basis. The frequent outbreaks of fires in forests also lead to huge losses in farms adjacent to such gazette areas (Fuhrer, et al., n.d). Most of these fire outbreaks can be affiliated with the rise in temperatures and drying of various vegetation. As a result, adverse changes in the climatic patterns. Such changes have also led to the flooding of agricultural lands, thus, leading to huge losses. These floods usually wash away crops in the field and also cause suffocation. They may also lead to the eventual death of such crops, leading to a reduction in the expected yield level.
3.0: METHODOLOGY
3.1: Study Area
The study will cover farmers in Sinyerere Division, Cherangany Sub-County, Trans-Nzoia County, in Western Kenya. Senyerere Division has a population of 18,000 people in approximate. Maize farming is the backbone of the local economy, meaning that any slight decrease in the crop’s production level can negatively impact the livelihoods of the residents. Sinyerere, just like the rest of other parts of the larger Trans-Nzoia County, receive average temperatures, which ranges between instances of having 10°C to 27°C. Therefore, this means that there is a conducive environment for maize production. However, these temperatures have continued rising with some possibilities of having more than 30°C in some months.
Figure3: Sinyerere Map
3.2: Study Design
The study will employ a mixed-method research method or design. According to (Macnair 2014), mixed-method research designs refer to the technique that uses qualitative and quantitative techniques to analyze the provided data. Therefore, one will manage to carry out thematic analysis to come up with a proper conclusion concerning issues being investigated. (Badke, 2014) states that thematic analysis is a tool used in determining the value of qualitative data by highlighting, recording patterns, and examining their meaning. One will need to come up with different themes based on the interviewees’ responses to make the intended conclusions. Quantitate data will need to be analyzed through the use of tables and graphs. Such a resolution will enable one to determine specific percentages and ratios exhibited in each of the presented questions and their responses.
3.3: Population
Sinyerere Area has a population of approximately 18,000 people, where a majority of them are maize farmers. Therefore, this will induce the need to carry out an intensive survey of the area and their main economic activity, maize farming. The large population means that approximately 1500 practice maize farming directly. It is this population that the researcher will target when trying to analyze how variability in the onset of rainfall affects maize production in the area. However, it will be imperative to divide this into different clusters, depending on the specific locality people practice farming. The move will ensure that there is uniformly deriving of the anticipated and important data.
3.4: Sampling Procedures
Sampling procedures refer to the researcher’s selection methods to pave the way for the collection of relevant data (Badke, 2014). In this case, one will be expected to employ effective sampling procedures to improve valid and important data collection. The researcher will use two sampling procedures to improve coverage of all farmers, thus, ensuring the relevant data are captured. One of the sampling procedures that will be used is cluster sampling. (Macnair, 2014) observes that cluster sampling involves grouping the study population into different categories to improve coverage and collection of the relevant data. Therefore, one will need to cluster the study population into different groups to reduce the overrepresentation or underrepresentation of an area within Sinyerere. The researcher will proceed to use a simple random sampling technique in identifying the sample population. Therefore, each maize farmer will have equal chances of being selected during the development of the study.
3.5: Sample Size
The sample size referred to the exact number of respondents or subjects under study and used as a representative of the whole population (Macnair, 2014). The deductions made are generalized and assumed to portray the entire population’s characteristics and traits (Badke, 2014). The use of the sample is determined by several factors, one of them being driven by the lack of capacity to collect data from the entire population, especially when huge (Badke, 2014). However, such the sample size must be large enough to be deemed a perfect representation of the entire population under study. According to the Yamane formula 1967, the sample size will be.
N is the population size (10% of the target population)
n is the desired sample size
e is the level of precision (0.05)
In this case, one will need to have a sample size of 109 respondents, where only maize farmers will be targeted. However, the respondents will be divided based on the demarcation of the areas used to collect the relevant data. The sample size will play a critical role in enabling one to collect relevant data concerning the impact of the variability in the onset of rains on maize production in Sinyerere. It will act as the mirror upon which the general deductions of this variability will be made on the rest of the population.
3.6: Instruments
One will rely on the use of a questionnaire as the appropriate mechanism for collecting the intended data. According to (Mertens, D.M. & Pauline, E.G., 2009), a questionnaire is referred to as a set of questions (that are either open-end or closed), which are meant to facilitate the collection of important data concerning research. In this case, the researcher will use a questionnaire to collect the relevant data from the selected sample size. The questionnaires will be administered in English, meaning that the respondents will be required to offer their answers and responses in the same language.
Special interview sessions will be conducted in instances where it will be determined that the selected respondents will not be capable of understanding or speaking in English. However, one will need to seek a local interpreter or administrator’s assistance when engaging such respondents as their responses will need to be translator into English.
3.7: Data Collection Procedure
As indicated above, the data collection exercise will entail questionnaires, meaning that several procedures will need to be observed. First, the targeted respondents will be handed the main questionnaires to fill manually in the researcher’s presence. The appropriate guidance will be offered for anyone who will seek the researcher’s assistance. In this case, it will be highly imperative for the researcher to ensure that neutrality is observed by not acting to guide the respondents in giving out the intended opinions (Mertens, D.M. & Pauline, E.G., 2009). Therefore, this procedure will help to improve the validity of the collected data. This will also enhance the creation of a perfect picture regarding the issue under the study.
The interview sessions will also be established in instances where the researcher will need to engage respondents who will encounter communication challenges. The language barrier will trigger one to use this procedure. However, it will be imperative for the researcher not to compel the respondents to participate in the study by answering the provided questions. Instead, it will be highly imperative not to interfere with their freedom in choosing what to say and what not to say. The researcher will be compelled to rely on the provided data only in making the intended conclusions and findings. The researcher will also need to provide relevant information such as the letter of authorization to the respondents to demonstrate the purpose and the validity of the study.
3.8: Data Analysis
Data analysis refers to the scrutiny procedure conducted on the respondents’ responses concerning a study topic (Kennedy-Clark, 2013). It is an in-depth investigation that entails diagrams, tables, and graphs to come up with the appropriate findings (Macnair, 2014). The study will use special software called Statistical Packages for Social Sciences (SPSS) to transform the raw data into useful information that can be used to make appropriate deductions regarding the study. The raw data will be coded to enable SPSS to understand them and produce the appropriate information. Therefore, one will use graphs, bar charts, pie charts, and histograms, among other schematic representations, to portray the relationship between the onset variability of rains and maize production in Sinyerere.
It will also be imperative to conduct a thematic analysis of qualitative data where one will be expected to portray different themes on the respondents’ views. One will need to classify views that portray a similar opinion under one category while differentiating them from varying opinions. The use of thematic analysis will play a significant role in augmenting what will already be identified in the SPSS analysis.
REFERENCES
Asafu-Adjaye, J. (2010). The Economic Impacts of Climate Change in Sub-Saharan Africa. The International Journal of Climate Change: Impacts and Responses, 103-118.
Badke, W. (2014). Research Strategies: Finding Your Way through the Information Fog. California: Bloomington Universe.
Fuhrer, J. & Gregory, P.J. (n.d). Climate Change Impact and Adaptation in Agricultural Systems- Introduction. Climate Change Impact and Adaptation in Agricultural Systems., 1-6.
Howarth, C. (2013). A Climate Change Information Framework for Behaviour Change: Applications to UK Travel. The International Journal of Climate Change: Impacts and Responses, 55-75.
Jabareen, Y. (2008). A New Conceptual Framework for Sustainable Development, 192-197.
Jamie, S. &. (2013). Food Security in Africa: Market and Trade Policy for Staple Foods in Eastern and Southern Africa. Massachusetts, USA: Edward Elgar Publishing.
Kiiru. (, 2016). Climate Change Impact on Agriculture: Challenges on Maize production in Uasin Gishu and Trans-Nzoia Counties. A Dissertation in partial fulfillment for the award of Masters of Science in Climate Change in the Department of meteorology., 1-95.
Kusumasari, B. (2016). Climate Change and Agricultural Adaptation in Indonesia. MIMBAR Jurnal Sosial dan Pembangunan, 243.
Macnair, R. H. (2014). Research Strategies for Community Practice. New Delhi: Routledge.
Mathenge, L. Mary, K., David, L. T. (2009). Off-farm work and farm production decisions: Evidence from maize-producing households in rural Kenya. Egerton University, Kenya: Tegemeo Institute of Agricultural Policy and Development Working Paper 33.
Mertens, D.M. & Pauline, E.G. (2009). The Handbook of Social Research Ethics. . SAGE.
Sarris, A. & Jamie, M. (2013). Food Security in Africa: Market and Trade Policy for Staple Foods in Eastern and Southern Africa. Massachusetts, USA: Edward Elgar Publishing.
Schmidt-Thome, P & Greivings, S. (2013). Introducing the Pan-European Approach to Integration on Climate Change Impacts and Vulnerabilities into Regional Development Perspectives. European Climate Vulnerabilities and Adaptations, 1-4.
Stuch, B., Schaldach, R. & Schungel, J. (2013). A Model-Based Method to Assess Climate Change Impacts on Rain-Fed Farming Systems: How to Analyze Crop-Yield variability? Knowledge Systems of Societies for Adaptation and Mitigation of Impacts of Climate Change., 489-510.
Wandaka, L. M. (2013). The Economic Impact of Climate Change on Maize Production in Kenya. A Research Paper Submitted in Partial Fulfillment of the Requirement for the Award of the Degree of Master of Arts Economics of the University of Nairobi., 1-44.
Waskey, A. J. (n.d). Global warming. Encyclopedia of Global warming & Climate Change., 311.
Appendix I: Questionnaire to Household Head
Please indicate your response by ticking against the answer that is the most appropriate.
SECTION A: DEMOGRAPHIC INFORMATION
- Age in years
- Gender
Male Female
- Educational background
Primary Secondary
Certificate Diploma
Degree Others (specify)
- Do you plant maize?
Yes.
No
SECTION B: FARM INPUTS AND MAIZE YIELDS
- 5. What type of maize seed have you been planting on your farm?
Certified Uncertified
- 6. Do you use organic fertilizer in your maize crop?
Yes No
- 7. Is the price of maize seed and fertilizer affordable to you?
Yes No
- 8. Have you experienced maize pre and post-harvest losses?
Yes No
SECTION C: Onset variability of rains on maize production in Sinyerere area, Tranzoia County
- the Onset of rains has varied in the Sinyerere area in the period 2015-2019?
Yes No
- Onset of the rains have not varied in the period 2015-2019
Yes No
- Has the maize production in Sinyerere varied in the period 2015-2019?
Yes No
12.Do you think the onset of rains and maize yields have any relationship?
Yes No
- Has rainfall been reliable for maize production in your locality?
Yes No
- Has your maize crop been affected by high temperatures
Yes No
………………….THANK YOU…………………
Appendix II: Work Plan
| S/N | Activity | Year | |||||||
| 2019 | 2020 | ||||||||
| Sept | Oct | Nov | Dec | Jan | Feb | Mar | Apr | ||
| 1. | Development of Section 2 Review of Literature of proposal and listing of references | ||||||||
| 2. | Title confirmation and Concept Development | ||||||||
| 3. | Proposal Draft Sections 1-3 | ||||||||
| 4. | Proposal Section 1 | ||||||||
| 5. | Formulation of Questions | ||||||||
| 6. | Formulation of Objectives and Hypotheses | ||||||||
| 7. | Development of other parts of Section 1 of the proposal | ||||||||
| 8. | Development of Section3 Methodology: Area of study and Map | ||||||||
| 9. | Development of Section 3: Methodology: Questionnaires and Piloting | ||||||||
| 10. | Writing of proposal abstract. | ||||||||
| 11. | Submission of Proposal | ||||||||
| 12. | Field administration of questionnaires and collection of data | ||||||||
| 13. | Revision of Chapters 1, 2 and 3 | ||||||||
| 14. | Chapter 4: Drafting and data Analysis | ||||||||
| 15. | Chapter 4: Discussion and Results and the making of tables, charts, and graphs | ||||||||
| 16. | Chapter 5: Conclusions and Recommendations Drafting | ||||||||
| 17. | Writing of final report. | ||||||||
| 18. | A full compilation of project Report (Chapters 1, 2, 3, 4 & 5, References and Appendices) | ||||||||
| 19. | Submission of Research Project Report | ||||||||
Appendix III: Budget
| S/No | Item | Total (Ksh) |
| 1 | Stationery (writing paper, pens, notebooks, folders) | 4,000.00 |
| 2 | Traveling costs | 1,000.00 |
| 3 | Laptop hire and internet bundles | 3,000.00 |
| 4 | Camera hire | 2,000.00 |
| 5 | Proposal printing 4 copies of 22 pages @ Kshs.3.00 per page | 800.00 |
| 6 | Binding 4 proposal copies @Kshs.40 per copy | 160.00 |
| 7 | Printing 100 questionnaires of 2 pages each @ Kshs.3.00 per page | 6,000.00 |
| 8 | Printing 2 Project reports copies of 50 pages @ Kshs.3.00 per page | 300.00 |
| 9 | Binding of 2 copies of projects reports @ Kshs.100 per copy | 200.00 |
| Total | 17,460.00 |