Coconut Census Report.pdf

ABD-DANIDA/CDA

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BASELINE SURVEY REPORT

May 2007

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BASELINE SURVEY REPORT

BY Githende Gachanja

Institution Development & Management Services

Zachary Odhiambo Coast Development Authority

&

Muli Musinga Alternative Finance Technologies Ltd

May 2007

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Table of Contents Executive summary …………………………………………………………………… vi Acknowledgements …………………………………………………………………… x List of abbreviations …………………………………………………………………… xi

PART ONE: CONTEXT OF THE SURVEY

1. INTRODUCTION 1.1 Overview …………………………………………………………………………………………………………………………………. 1 1.2 Background ………………………………………………………………………………………………………………………………. 1 1.3 Objectives ……………………………………………………………………………………………………………………. 2 1.4 Methodology …………………………………………………………………………………………………………………… 2 2. THE COAST PROVINCE 2.1 Overview ……………………………………………………………………………………………………………………………….. 4 2.2 Position ……………………………………………………………………………………………………………………………….. 4 2.3 Population ……………………………………………………………………………………………………………………………….. 4 2.4 Agricultural land ………………………………………………………………………………………………………………….. 6 2.5 Agro-ecological zones …………………………………………………………………………………………………….. 7 2.6 Economic base …………………………………………………………………………………………………………………. 7 2.7 Tree crops …………………………………………………………………………………………………………………… 7 2.8 Coconut production ……………………………………………………………………………………………………… 8 3. COCONUT FARMING: INFORMATION FROM LITERATURE 3.1 Overview ……………………………………………………………………………………………………………………………….. 9 3.2 Historical background ……………………………………………………………………………………………………… 9 3.3 Coconut varieties …………………………………………………………………………………………………….. 10 3.4 Coconut products …………………………………………………………………………………………………….. 10 3.5 Agronomy …………………………………………………………………………………………………………………. 12 3.6 Pests and diseases ……………………………………………………………………………………………………. 12 3.7 Marketing of coconut products ……………………………………………………………………………………….. 13 3.8 Legislation …………………………………………………………………………………………………………………. 13

PART TWO: RESULTS OF THE SURVEY

4. MAGNITUDE OF THE SUB-SECTOR 4.1 Overview ……………………………………………………………………………………………………………………………… 16 4.2 Population of trees …………………………………………………………………………………………………… 16 4.3 Number of farmers …………………………………………………………………………………………………… 17 4.4 Acreage …………………………………………………………………………………………………………………………. 18 4.5 Production …………………………………………………………………………………………………………….. 20

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5. SECTOR DYNAMICS 5.1 Overview …………………………………………………………………………………………………………………………. 22 5.2 The age of trees …………………………………………………………………………………………………………….. 22 5.3 Growth in the population of trees ……………………………………………………………………… 23 5.4 Coconut varieties cultivated in Kenya ……………………………………………………………………… 25 6. PRODUCTS AND MARKET ISSUES 6.1 Overview …………………………………………………………………………………………………………………………. 28 6.2 Mature nuts ……………………………………………………………………………………………………………. 28 6.3 Immature nuts (madafu) …………………………………………………………………………………. 29 6.4. Wine ………………………………………………………………………………………………………………………… 29 6.5 Roofing materials (Makuti) …………………………………………………………………………………. 30 6.6 Brooms ………………………………………………………………………………………………………………………… 31 6.7 Coco-wood ……………………………………………………………………………………………………………. 31 6.8 Copra …………………………………………………………………………………………………………………………. 32 7. PRODUCTION CLUSTERS AND SPATIAL VARIATIONS 7.1 Overview …………………………………………………………………………………………………………………………. 34 7.2 Tree population based production clusters……………………………………………………………………. 34 7.3 Product-specific production clusters……………………………………………………………………………. 43

7.3.1 Mature Nuts clusters ………………………………………………………………………………………… 43 7.3.2 Madafu clusters ……………………………………………………………………………………….. 44 7.3.3 Wine clusters ……………………………………………………………………………………………………. 45 7.3.4 Makuti clusters ……………………………………………………………………………………….. 46 7.3.5 Brooms clusters ……………………………………………………………………………………….. 47 7.3.5 Coco-wood clusters ……………………………………………………………………………………….. 47

8. CHALLENGES TO REALIZATION OF SECTOR POTENTIAL 8.1 Overview ………………………………………………………………………………………………………………………………. 49 8.2 Constraints and challenges facing farmers ……………………………………………………………… 49 8.3 Production challenges ……………………………………………………………………………………………………. 50

8.3.1 Weather and the question of better adapted varieties ……………………….. 50 8.3.2 Pests and diseases ……………………………………………………………………………………….. 50 8.3.3 Access to planting materials ………………………………………………………………………….. 50

8.4 Markets and marketing constraints ………………………………………………………………………….. 51

8.4.1 Prices ………………………………………………………………………………………………………………… 51 8.4.2 Market access …………………………………………………………………………………………………… 51 8.4.3 Poor road infrastructure to markets …………………………………………………………. 51

8.5 Other Constraints …………………………………………………………………………………………………… 52

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9. CONCLUSIONS AND RECOMMENDATIONS 9.1 Overview …………………………………………………………………………………………………………………………. 53 9.2 Conclusions ……………………………………………………………………………………………………………. 53 9.3 Recommendations …………………………………………………………………………………. 55 References ……………………………………………………………………………………………………………………….. 57

Appendices: 1. Survey Methodology 2. List of key GOK and other stakeholder officials who participated

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Executive Summary In December 2006, the Agricultural Business Development (ABD) program of the Danish International Development Agency (DANIDA) in collaboration with the Coast Development Authority (CDA) commissioned Institution Development & Management Services (IDM Services) to undertake a survey of coconut trees in four Districts of Coast Province – Kwale, Kilifi, Malindi and Mombasa. The Consultants were also required to develop mechanisms to make estimates for Lamu and Tana River Districts. Using a mix of qualitative and quantitative approaches, the exercise was carried out in the months of January through mid March 2007. The Survey used the administrative structures of the Ministry of Agriculture to collect data from villages in the coconut growing areas of the four districts and covering a sample of farmers in Lamu and Tana River Districts. Primary data collection was done by a team of over 400 Enumerators independently hired at the village level and supervised on a daily basis by MoA frontline staff at every Location with oversight and coordination of an IDM Research Coordinator for each district. In total, 63,223 farmers were interviewed in 1,723 villages across the six Districts of Coast Province targeted in the survey. A thorough literature review was also conducted to contextualize and benchmark findings of the survey. Data processing was done using SPSS software and part of the information included in GIS for pictorial presentation. From a careful analysis and interpretation of data obtained during the study, the survey team makes the following six main conclusions: 1. The size of the coconut sub-sector is much larger than what it has been thought to be in the past. The magnitude of the coconut sector has generally been understated. Although a part of this general understatement appears to have been as a result of estimation errors in the absence of a comprehensive survey, the key reason for understatement has been due to failure to recognize the importance of other products of the coconut tree, some of which are even more important than the dry nut. This understatement therefore seems to have been perhaps deliberate, particularly owing to the legality question under which coconut wine fell into for many years until the lid was lifted under the current Government administration. This does not however explain the full story, as other important products of the tree did not fall into the legality question. Information from the survey shows that the population of trees stands at 7.4 million - 3 million higher than the 4.4 million trees which were thought to exist in the past. Taking all products into consideration, the value of the coconut sub-sector at the farm level is estimated to be Kshs 3.2 billion with 60% of the value accounted for by palm wine; 24% by nuts; and the balance accounted for by makuti (12%); brooms (3%) and other products of the coconut tree produced at the farm level including coco-wood and coir (0.5%). Although coconut wine is still embroiled in legality1, religious and social image questions, it is clear that this is the product that is currently driving growth in the sub-sector and it is likely to remain so as signals from the emerging fully commercialized market for this product indicate that this is where the returns are. Worldwide, a major reason why coconut is cultivated is for its copra, the dried endosperm or kernel of the coconut, which is further processed into oil for use in the soap industry, cosmetics, candle manufacture and some even refined further for edible oil. For a long time copra has been regarded as the main product of the coconut tree in Kenya at the farm level. Results of the survey however indicate that the situation has

1 We take note though, that the Finance Minister has recently lifted the ban on traditional brews in his Gazette notice of May 2007. This is a positive move that is expected to further spur growth in the palm wine industry.

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changed and copra in no longer a major product of the coconut tree at the farm level as used to be the case up to the 1980s. Farmers are no longer involved in producing copra at the farm level largely as a result of poor prices offered and a general lack of a market for this product. The price of copra at the farm level is Kshs 7 per kilogram which generally takes 5 – 7 dry nuts to produce. To many farmers, it therefore makes more business sense to sell the dry nut even at the lowest prices of Kshs 2 per nut than spend time crashing the nuts to obtain copra which with fetch a much lower per unit price. Some of the 8 main industries that used to deal in copra have since closed down and those in operation are now largely dependent on imported palm oil from Malaysia or buy dry nuts to produce copra at the factory level for some of the specialized lines that require coconut oil. 2. The population of coconut trees is on the rise and it is not true that farmers have not been planting trees Dynamics in the coconut sub-sector show that there is a general rise in the population of trees and fears that the population of trees is likely to go down as most trees are in the senile stage of over 60 years (and farmers are cutting them down) is not true. The population of trees aged over 60 years is only 8.2% of the total population or just slightly over 600,000 and not the 2.2 million (50%) thought to exist in the past. The survey shows that contrary to generally held views, farmers have actually been planting more coconut trees and the proportion of trees in the age before the start of production now stands at slightly over 14%. Overall, the population of trees is growing at a rate of 2.2% annually with the highest growth rates experienced in Kilifi and Malindi, partly explained by a vibrant market for some of the coconut products especially palm wine and opening up on new settlements. The rise in population of trees is lowest in Kwale with only a marginal growth rate of 1.4%. As is perhaps expected, there is a negative growth rate in the population of trees in Mombasa (-36.5%), pushed by the pressures of urbanization. Overall, however, the population of coconut trees past the age of optimal productivity of 30 years is still large (44%) suggesting the need for increased replanting of trees if high productivity in the sub-sector is to be achieved. 3. There are clearly identifiable production clusters in the coconut sub-sector The distribution of the population of coconut trees in Coast Province is in such a way that there are clearly identifiable production clusters. Defined as areas of concentration in the population of trees within a small zone with a radius of 5-7 Kilometers, the Survey identified at least 36 production clusters in the province with Kwale and Kilifi districts having the highest number of clusters (each with 13). Besides these general production clusters, there are specific clusters for the various products. Mature nuts and coconut wine have the largest number of clusters, although those related to wine are much more developed and vibrant. Overall, Kilifi district has the largest number of well developed clusters indicating a much more developed market for coconut products at the farm level. These clusters are important growth points of the whole sub-sector from where innovations and transformation will come from and, therefore present excellent points for intervention. 4. Only a small proportion (about 25%) of the potential of the sub-sector is currently exploited From an assessment of the current developments in production of the various products of the coconut tree, rough estimations of potential indicate that this could be a much bigger sub-sector, reaching to even over Kshs 20 billion with the current population of trees and current growth trends. Average nut production currently stands at 21 nuts per tree which is quite low compared to optimal productivity levels of over 100

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nuts expected in good yielding varieties. The low participation of farmers in production of the other products is another indicator that the potential could be much higher. Wine production involves only 36% of farmers, brooms 21% and makuti 64%. The low participation rate of farmers is generally due to poor development of the markets for some of the products. 5. Production and market related constraints are the key challenges to full potential The main challenges facing farmers at production level include accessibility of quality planting materials and the menace of pests and diseases. Effects of the prolonged drought which extended to over 4 years in some areas was however mentioned by most farmers interviewed during the Survey as a foremost outstanding challenge facing farmers at the production level. From a development perspective, this can be viewed as a challenge for finding more tolerant varieties – which is one of the key research areas that should be focused on. On the market end, key challenges relate to low prices and large flactuations during peak production periods; and actual market access by farmers for their products. The distribution and marketing channels are generally dominated by traders and middlemen who play an important role in getting farmers’ produce to the market. Without proper organization at the farmer level, however, the cost of bulking and the inefficiencies of facing the market without any joint action is placing farmers at a disadvantaged position to benefit fully from the sub-sector. In general, farmers complain that the incentives offered by the market currently are not enough to make them invest substantively in their farms. This has led to the current low productivity in their farms – fixing itself as a vicious circle which must be broken for a momentum for growth of the sub-sector to take place. In some product lines such as palm wine, makuti and madafu for some clusters, however, this vicious circle is already broken and vibrancy is already starting to be seen. This is what needs to be built-on, nurtured and replicated across the entire coconut belt. 6. Coconut farming is deeply entrenched in coastal farming systems and forms an important leverage point for improving the livelihoods of millions of people in coast province Coconut is a crop that is deeply entrenched in the cultures, practices and ways of life of coastal communities, some dating as far back as a couple of centuries. This cultural value has dictated that almost every farming household in the coastal belt where coconut trees can grow, particularly those with a coastal origin, has at least a few trees. This partly explains why some farmers will attempt to grow the crop even in fairly marginal areas. Overall, this cultural attachment has contributed to the large population of trees and seems bound to continue holding ground, continually encouraging farmers to plant the crop. The cultural entrenchment is however beyond the cultivation and is even more entrenched and widespread in the consumption of the products. Many coastal meals will have a sprinkling (if not immersion) of coconut milk; a normal way of quenching thirst is by madafu, the normal house (even increasingly more so, a coastal hotel) will be thatched with makuti and the general broom in coastal Kenya (and indeed Kenya) is the coconut broom. Coconut wine is also deeply entrenched as a local drink of choice. This cultural entrenchment in consumption of some of the major products plays a major part in driving the market for coconut products. It is however clear that market expansion must go beyond just the coastal populations who have a cultural attachment to the products. As a positive mark, this trend is already there and it only needs to be further propelled. It is also noted that efforts must be made to make sure that some of the past practices in the cultivation of the crop do not become a hindrance to its development. A good case is the now longstanding neglect of the crop that make some farmers think a coconut tree doesn’t need to be weeded, manured or sprayed with agrochemicals.

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Overall, it is clear that coconut farming is a central part of the livelihood of most coastal households and will continue to be so into the foreseeable future. Integrating this commodity sector into the market as an important cash crop will directly affect the livelihoods of many households in the Coast Province. Ignoring the crop will mean wasted opportunity to utilize an important economic base for coastal populations.

Acknowledgements

We would sincerely wish to express our gratitude to many individuals and organizations who have significantly contributed to the successful conclusion of the Coconut Survey exercise in Coast Region. We take this opportunity to thank the Danish Government for the financial support through the Agricultural Business Development (ABD) program of the Agricultural Sector Program Support (ASPS) implemented in collaboration with the Ministry of Agriculture, Government of Kenya. Special thanks go to the ABD team in Coast Province, particularly George Mazuri in charge of Kilifi/Malindi, Kennedy Mayende in charge of Kwale, G. Nyale in Malindi and the ABD Senior Advisor, Mr. Christian Sorenson for the support and approval for the survey. Thanks to the Coast Development Authority especially Mr. Hemed Mwabudzo who chaired the Palm Working Group under which the terms of reference for the survey was drawn. The success of the survey was a joint effort by the staff of the Ministry of Agriculture from the six Districts of Coast Province and farmers. We register our appreciation to the Provincial Director of Agriculture, Mrs Phoebe Odhiambo, the District Agricultural Officers, the DAO Malindi, Mr. B.K. Mureithi and his deputy Mr. B.M. Mwangangi; DAO, Kilifi Mr. P.M. Mburu and his deputy madam J.M. Kanamu; DAO Mombasa Madam Jacinta Simba and her Deputy Mr.S.M. Baabu and the DAO Kwale, Mr.A.I. Kimani and his deputy, Mr.J. Singi. The Provincial Administration deserves special mention for their support on the ground. We particularly acknowledge the Chiefs, Assistant Chiefs and the Village Elders for working very closely with MoA Location Staff and our Enumerators collecting information from every farmer in all the villages of Coast Province where coconut is grown. Thanks go to the team of over 400 Enumerators for the many hours put for data collection in every village. We particularly, would wish to recognize the good work performed by Jonathan Mwatata (Malindi), Sulleiman Kinda (Mombasa), Sulleiman Mkotah (Kwale) and Kazungu (Kilifi). Special thanks for the data processing exercise that was carried out by a team dedicated young officers from IDM Services who worked beyond the hours, sometimes late into the night, and for a stretch of one month, without consideration of weekends to complete the data entry and cleaning exercise in time. It is also important to record the contribution of the coconut stakeholders’ task force that provided valuable critique that shaped the final outcomes of the report. We are particularly indebted to Mr. Mwangi Njoya of Msabweni Development Company, Mr. Jimmy Davis of Kocos Kenya, Dr. Enoch J. Mrabu, Mr. Edward B. Kingi, and Mr. Mng’ong’o for their very valuable written contributions. While many individuals and organizations have participated in varied ways to the outcome of this report including providing useful comments and observations, the opinions expressed in this report (or any errors therein) are solely those of the authors of the report and should not be misconstrued as the official position of ABD-DANIDA, CDA, MoA or any other institution or persons that helped in accomplishing this work. To all those mentioned above and others who may in one way or the other have contributed to the success of this project we are indeed very grateful. Githende Gachanja Project Lead Consultant INSTITUTION DEVELOPMENT & MANAGEMENT SERVICES – May 2007

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List of Abbreviations AAEO - Assistant Agricultural Extension Officer

ABD - Agricultural Business Development.

AEZ - Agro – Ecological Zones

CDA - Coast Development Authority.

CDO - Community Development Officer

CL - Coastal Lowlands

DAEO - District Agricultural Extension Officer

DANIDA - Danish International Development Agency

DAO - District Agricultural Officer.

DCDO - District Crop Development Officer

FEO - Frontline Extension Officer

FEW - Frontline Extension Workers

GDP - Gross Domestic Product

IDM - Institutions Development and Management Services

MOA - Ministry of Agriculture

PDA - Provincial Director of Agriculture.

SAPs - Structural Adjustment Programmes

TORs - Terms of Reference

USAID - United States Agency for International Development

COGENT - International Coconut Genetic Reserve Network

PART ONE

CONTEXT OF THE SURVEY

Baseline Survey Report, May, 2007 Institution Development & Management Services

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1 INTRODUCTION

1.1 Overview This report presents findings of a baseline survey of coconut trees in Coast Province commissioned in December 2006 by the Agricultural Business Development (ABD) program of the Danish International Development Agency (DANIDA) in collaboration with the Coast Development Authority (CDA). Contracted to a private consulting firm based in Mombasa (IDM Services), the work was carried out over a three month period using the administrative structures of the Ministry of Agriculture (MoA). Data collection was carried out in the months of February and March 2007 using a team of over 400 Enumerators hired at the village level and supervised on a daily basis by MoA frontline staff at every Location with oversight and coordination of an IDM Research Coordinator for each of the survey districts besides the MoA line staff at the Division and District levels. The exercise could therefore be easily regarded as a MoA activity where the consultants were merely brought in to coordinate and manage the activity mainly at the design and data processing, analysis and reporting stages. While all the six districts of Coast Province with significant coconut farming were covered, survey of trees was carried out only in Kwale, Kilifi, Malindi and Mombasa Districts. Lamu and Tana River districts were however also covered using qualitative estimation methods combined with a sample survey of selected farmers. Taita Taveta was left out all together since the district doesn’t have significant coconut farming activities. It is information generated through this approach that is the basis of this report. Section 1.4 below provides further details of the survey methodology. The whole step-by-step methodology of the survey is also provided in detail as Appendix 1. 1.2 Background Coconut (cocos nucifera) growing was introduced in Kenya in the 16th century by the Portuguese and since then, the coconut palm has grown to become one of the key sources of livelihood for many households in the coastal region. The coconut palm is traditionally known for many uses ranging from the leaves, fruit and the trunk. There are hardly any parts of the coconut that are left unused. The coconut palm produces food and drink for people, copra for oil, copra cake/meal, palm wine, building materials in the form of poles for construction and leaves (makuti) for roofing as well as timber for furniture; fibre for ropes, mats, brushes, and brooms; and shells for the manufacture of utensils and ornaments. The list goes on and on. In general terms, the coconut sub-sector demonstrates an immense potential to drive economic development in the main coastal belt. This potential is however far from exploited and coconut farmers remain among the poorest in Kenya. To address constraints holding back the full realization of the potential of the coconut sub-sector, a number of stakeholders have made efforts to develop various initiatives targeted at different points of the value chain. Some of these are development agencies such as ABD-DANIDA, the Coast Development Authority (CDA), the Government, Palm International; while others are private business initiatives or even individuals interested in development of the sub-sector or coast region in general. To share information and make inroads towards a coordinated force from the various interested parties in development of the sub-sector, a number of stakeholders in the sector have in the last couple of years


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come together – currently referred to as the Palm Working Group to incorporate other palms besides the coconut tree/palm. Currently chaired (and housed) by CDA, this group meets on a periodic basis and, overtime, one thing (among a number of others) that has come out as a common stabling block in the work of the various stakeholders is reliability of information available on the sub-sector. For instance, initiatives geared at developing the emergent high-value niche market for coco-wood realized there were unanswered questions of how many trees there are in the senile stage (of over 60 years) when they become suitable for wood purposes (as hardwood). To many stakeholders, information that the total population of coconuts trees was about 4.4 million with about 50% (or 2.2 million) in the category suitable for wood needed to be credible enough to warrant efforts aimed at developing a fully fledged coco-wood market. Other stakeholders in the sub-sector had similar questions with regard to information relevant for planning and programming their activities effectively. In general, all basic information available in relation to the population of coconut trees, their geographical and age distribution, and holding per farmer looked outdated and generally unreliable for planning purposes. As is the case of any sector, the need for reliable information is a critical component in effective planning and development of the coconut sub-sector has been an obvious gap to many stakeholders .It is for this reason that ABD-DANIDA in collaboration with CDA under the auspices of the Palm Working Group commissioned the Survey of coconut trees in coast province which is the subject of this report. 1.3 Objectives The main purpose of the Coconut Survey exercise was to establish a reliable estimate of the total population of coconut trees in the coast province, de-aggregated by age and geographical areas of distribution. Besides generating this basic information, the survey was also expected to yield important information on the various products of the coconut palm, their markets and the key challenges facing farmers in their farming activities. 1.4 Methodology By design, the coconut survey was formulated to take a Census format which by definition is largely a quantitative research task. The main methodology used in undertaking the exercise was therefore largely quantitative. IDM however also adopted participatory approaches for gathering qualitative information that was used in guiding the survey and enriching analysis and interpretation of the generated results.

Primary data was collected from farmers using two structured questionnaires – a main questionnaire administered to all farmers in the survey areas and a supplementary questionnaire administered on 5% of the farmers to obtain further, more detailed information. The first questionnaire, used as the main survey instrument, was structured to be brief with one-page sheet able to capture information from up to 17 farmers (see Appendix 1). Information sought under this instrument related to the total population of coconut trees in the farm, disaggregated by age (age-groups) and variety; land holding, ownership of both the land and the trees in the farm; nut production in the last 12 months (2006); the presence of dead trees in the farm (defined as trees without a tip but still standing); and number of trees cut down or planted over the last 12 months. Information was also sought on coconut seedlings not yet transplanted in the farm. Gender de-aggregation of the farmer was also made. By design, this survey instrument was structured to be simple/brief enough to be administered to up to 25 farmers per day by a trained Enumerator.


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The supplementary questionnaire was designed to generate information on the various products of the coconut tree produced by farmers at the farm level, the quantities sold, and the average selling prices. To address fears that a lot of farmers where cutting down their coconut trees, this instrument also sought the reasons for cutting down trees among farmers who had felled their trees. Information was also sought on constraints facing the farmer in his/her coconut farming activities. This instrument was administered to a sample of the farmers (5%) picked out in a systematic approach as every 20th farmer to be interviewed in the administration of the main survey questionnaire.

As briefly mentioned in Section 1.1, the data collection exercise was carried out by a team of slightly over 400 Enumerators identified at the village level to make sure they have full local knowledge of the survey area and are acceptable among farmers. This team was trained over a 1 day period by IDM in conjunction with MoA district level officers on the survey approach and instruments. In the actual implementation of the data collection exercise, this team of enumerators was supervised on a day-to-day basis by MoA Location level staff with backstopping from their line supervisors at the divisional and district levels. The exercise was planned to take place over a two week period starting the first week of February, 2007. Due to concentration of coconut farmers in some zones, however, the exercise was extended by a varying number of days per the requirements of the different sub-Locations/villages to make sure the exercise was successfully completed. Work in more than 70% of sub-Locations was however completed within the span of 10 days. Overall, the exercise took 11.5 working days for data collection to be completed in all the survey areas.

To authenticate and cross check the quality of work done by the Enumerators, Location level staff as well as division and district supervisors (including the team from IDM) made frequent spot checks among farmers. The first activity was to see whether the farmer was visited and the second was to cross-check the authenticity of the information collected. Overall, IDM is satisfied that the quality of work on the ground was carried out successfully to give the necessary credence to the results of the survey presented in this report.

For purposes of cross-checking possibilities of undercounts or double counting, an exercise of spot checks was conducted at the end of the data collection exercise under the supervision of IDM services and attended by officials from ABD-DANIDA. A spot-check was done on randomly selected zones of each sub-Location on 10 farmers (in a row), checking whether they were covered in the survey. The information gathered during this exercise was analyzed and used in computing any error adjustment factors for undercounts/double counting (see Appendix 1).

Data processing and analysis was carried out using SPSS statistical software (version 14.0 for windows).


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2 THE COAST PROVINCE

2.1 Overview This section sets the context of the coconut survey exercise by exploring background information on Coast Province that is important in understanding and interpreting results of the survey. It opens with a brief overview of the geographical position of the province, demographic factors and agro-ecological context before looking at the broad coast economy and the place of the coconut sub-sector. Information provided here is from review of literature and secondary information and should be interpreted as such, particularly when it comes to past estimations of the coconut sub-sector. 2.2 Position Coast Province is one of the eight provinces in the Republic of Kenya. Until late 2006 the province had seven administrative districts namely; Kwale, Mombasa, Kilifi, Malindi, Tana River, Lamu and Taita Taveta. The number has since increased to ten districts following the creation of three additional districts with Kaloleni district curved out from Kilifi district, Kinango from Kwale district and Kilindini from Mombasa district. For the purpose of this study (Coconut Survey), the focus of discussion is on the six districts of Kwale, Kilifi, Mombasa, Malindi, Tana River, and Lamu before the creation of the additional 3 districts and leaving out Taita Taveta. These six districts which boarder Indian Ocean are considered to have high concentration of coconut tree population and have a total coastline of 640 km, which forms part of the western border of the Indian Ocean, The Kenyan coast runs in a south-westerly direction from the Kenya-Somali border in the north, at 1o41’S to 4o40’S at the border with Tanzania (see Fig. 1). It lies in the hot tropical region where the weather is influenced by the great monsoon winds of the Indian Ocean (UNEP, 1998). 2.3 Population Coast Province had a population of 2.5 million people in 1999 with inter-censal growth rate of 3.1%. This population is currently estimated at 3.0 million people taking into account the impact of HIV/AIDS in the Province (table 1). This accounts for 10% of the total Kenyan population. The population density of Coast Province varies from one district to another and is highly influenced by the rainfall patterns and economic activities. Coast Province recorded a population density of 22 persons per square kilometer in 1989, which increased to 30 persons per square kilometer in 1999 and is currently estimated at 36 persons per square kilometer.


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Figure 1 The Kenyan Coastline

and

Elevation -Area above sea level


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Low density is recorded in arid and semi-arid areas of the province, which accounts for 61% of the total area and highest population densities are recorded in urban areas. For instance, Mombasa town currently has a population density of about 3,609 people per square km. Mombasa district as the main urban area in Coast Province has been experiencing a rapid population growth rate of way over the 3% average for the province largely attributed to natural growth rate and immigration due to rural –urban migration especially among school leavers seeking employment opportunities. It had a population of 375,298 in 1979, which increased to 461, 753 in 1989, and 665,018 in 1999 and is presently estimated to be 828,514 people. This has created the need for conversion of agricultural land to other competing uses e.g. housing construction, industrial and other infrastructure development. 65% of the total population of the coastal region is found in rural areas and are engaged in various primary production and the remaining 35% are in urban and peri-urban areas (CBS: Population Projection).

Table 2.1 Population Distribution and Density in the Coast Province by Districts, 2006 projections

District Area in Km Population Density per Sq Km

Total Population

Mombasa 229.6 3,609 828,514 Kwale 8,295.3 69 575,026 Kilifi 4,779.2 137 653,143 Malindi 7,750.6 47 345,872 Tana River 38,466.3 6 222,228 Lamu 6,166.7 14 83,503 Taita Taveta 17,128.3 16 276,101 Total: Coastal Districts 82,816 36 2,975,387

Source: CBS; 1999 Population & Housing Census 2.4 Agricultural land Coast Province covers a total area of 82,816 Km2 with 32,529 Km2 (39%) suitable for crop production and the remaining 61% is Arid and semi Arid land (ASAL) supporting livestock production and game parks. The area supports 252.090 farm families with majority (32.2%) found in Kwale, 21.6% in Kilifi 17.3% in Taita Taveta and 13.7% in Malindi (table 2)

Table 2.2 Agricultural land by District

District Area in Km2 Agricultural land in Km2 No. of Farm Families Mombasa 229.6 90 6,152 Kwale 8,295.3 7,151 81,215 Kilifi 4,779.2 3,949 54,528 Malindi 7,750.6 1,148 34,625 Tana River 38,466.3 8,850 22,130 Lamu 6,166.7 5,517 9,712 Taita Taveta 17,128.3 5,824 43,728 Total: 82,816 32,529 252,090

Source: Ministry of Agriculture, 2006


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2.5 Agro-ecological Zones The Coast Province has five (5) agro-ecological zones of coastal lowland (CL) namely; CL2, CL3, CL4, CL5 and CL6 which covers four topographical features that include the coastal plain, foot plateau, coastal range and the Nyika plateau. These features with marked altitude differences are also characterized by different average annual rainfall ranging from 400 mm in the hinterland to 1200mm at the coastal belt, which explains why Coast Province experiences diverse climatic conditions.

i) CL2 – Sugarcane Zone This is the wettest zone with an average rainfall of over 1,400 mm per year. In terms of precipitation, this zone wuld be classified as high-potential, but due to low soil fertility, poor drainage and salinity, it can be more apltly described as medium-potential. It is most suitable for sugarcane but a large variety of crops can also be grown throughout the year.

ii) CL3 – Coconut – Cassava Zone The zone has the highest potential for crops. It spreads along the coastal uplands and low-level coastal plains with mean annual temperatures of 24o C -260 C, and annual precipitation of 1000mm -1200mm. Key crops grown in this zone are tree crops, vegetables and food crops.

iii) CL4 – Cashewnut –Cassava Zone This stretches northwards along the coastal plain with annual precipitation of 850-1100mm and average annual temperatures of 24.90C -26.60C. The major crops grown are Cashew nuts and cassava.’

iv) CL5 – Lowland Livestock – Millet zone The zone is of less potential with annual precipitation of 700mm -900mm and mean temperature of 24.90C -26.60C.It is suitable for dry land farming including irrigated agriculture and livestock dairy ranching.

v) CL6 – Lowland Ranching Zone. It varies in altitude of 90m-300m above the sea level with annual precipitation of 350mm-

700mm and annual temperature of 24.90C -270C. Major activities include ranching, wildlife, bee keeping and mining.

2.6 Economic Base The principal economic activities in the province in terms of employment and their contribution to the Coast province economy (GDP) are tourism - 45%, port and shipping activities - 15%, non-agricultural industries - 8%, agricultural production and processing - 7%, fisheries - 6%, forestry - 4%, mining - 2% and other services – 13%. Most of these economic activities (with exemption of shipping activities, non-agricultural industries and other services) depend on the natural environment and employs 65% of the total population. 2.7 Tree crops Coast region is endowed with favorable climate for the growth of a number of tree crops namely; Coconut, Cashewnut, Citrus, Mangoes and Bixa which are the most important cash crops for the local farmer. The major food crops grown in the region include; maize, cassava, rice, cow peas and pulses.


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The Coconut as one of tree crops in the province has become an important source of income to the majority of small-scale farmers found in rural areas of the coastal region. Coconuts grow well mainly in the Agro ecological Coastal Lowland (CL) zone (CL3 and CL4) but can also be found in the lower parts of CL5. Coconuts are also grown in a smaller scale in the arid and semi arid areas in CL6 along the rivers and sections with sundy soils. Coconut requires 800 – 1400mm of rainfall per annum with an average temperature of 26oC in the coastal lowlands and 27oC in the hinterland. 2.8 Coconut production: information available from literature Existing information shows that the main coconut producing districts in Kenya are Kwale, Kilifi and Malindi with some significant production from Mombasa, Lamu and Tana River. Information available before this Survey estimated that the region had a population of 4 million coconut trees of which majority were planted during the colonial era and is currently supporting over 400,000 households as the main source of income (CDA; 2004).

Table 2.3 Ministry of Agriculture Estimations on Coconut Production by District, 2004

District Area under Coconut (Ha) Production (Tonnes) - nuts Kwale 18,109 27,320 Mombasa 785 517 Kilifi and Malindi 21,795 30,750 Lamu 1,605 2,970 Tana River 57 417 Taita Taveta 82 74 TOTAL 42,433 62,068

Source: MoA Annual report, Coast province, 2005


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3 COCONUT FARMING:

INFORMATION FROM LITERATURE 3.1 Overview This section further contextualizes the coconut survey by reviewing available literature on coconut farming particularly as it relates to Kenya. It opens with an overview of the historical background of coconut farming in the coast, touches on the introduction of the different coconut varieties in Eastern Africa and their suitability for different products, and moves on to look at issues of agronomy, pest and disease control, as well as the different coconut products and their markets. The last part of this section highlights some of the legislative issues that have relevance to the state of the coconut industry in Kenya. Just like Section 2, this section is intended to provide a context (or some sort of benchmark) from which to interpret and critically analyze results of the coconut survey. 3.2 Historical Background Kenya has been growing coconut for a longer period than most other countries in Africa (estimated to date from the 16th century) along the coastal region among the Mijikenda. Untill 20th century the Rabai and Ribe remained the main growers and producers of palm wine. Other Mijikenda continued to go to Rabai to buy palm wine and, for their own trees, they employed tapers from Rabai (Herlehy 1984). Although the Mijikenda also consumed fresh nuts, the taping of palm wine was for long the most popular and important use of the palm. Palm wine was used in nearly all social and ritual affairs and traded for economic gain. Currently, Kenya is ranked seventh among the eight coconut producing countries2 in Africa with share contribution of copra production of 4.5% and recorded export of copra lastly in 1995 (FAO, year book, 2006). This has resulted in the country importing annually Kshs. Over 14 billion worth of vegetable oil which coconut has the potential to substitute by 30% especially coconut oil for soap making. Research development of coconut sector in Kenya has been very slow as compared to the case of some of the other Eastern Africa countries such as Tanzania and Mozambique. It has also not been actively participating in some of the important network organizations in coconut such as the International Coconut Genetic Reserve Network (COGENT) which has played a leading role in introducing new varieties based on trials in participating countries. Low priority given to the sub-sector has limited the ability to undertake research and development activities with a view to introducing drought tolerant varieties, improvement on crop husbandry, processing and marketing of the products and by – products. 2 Benin, Cote d’Ivoire, Ghana, Kenya, Mozambique, Nigeria, Modagascar, Seycheles and Tanzania


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3.3 Coconut Varieties Along the Coastal region of Eastern Africa, there are three major varieties of coconut. The three varieties are; the East African Tall (EAT), the Dwarf and the Hybrid. The EAT are the most common in Kenya and they yield nuts with good quality copra and toddy but the immature nuts are wanting i.e. it produces small quantity of Madafu juice, but thick copra and quality wine. EAT variety is the most popular variety among the farmers and it takes 5 – 7 years to start producing nuts. It is more tolerant to drought, produces an average of over 60 nuts per year under good husbandry, lives between 60 - 100 years and grows to a height of 15m (E. Krain and P.M.D Kalange, 1992). In 1996/97 attempts to measure productivity were made in Mtwapa whereby a selection of high yielding Palms of EAT of twelve trees ages varying between 15 and 25 years was done. The results drawn from 20 years observation indicated that the yield ranged between 18 and 128 nuts per palm with the best tree giving consistent yield of over 100 nuts per year. The dwarf coconut variety produces excellent sweeter coconut juice (from madafu) but little copra. This implies they are good for “madafu” but more are needed in production of oil compared to the EAT variety. They start to produce at the age of 3 -5 years and have the ability to produce over 100 nuts per year. It requires a lot of rainfall or water, fertile and well drained soil and good crop husbandry. In Kenya, it is mainly grown around the homestead for ease of watering (but also for ornamental purposes) and can live between 40 – 50 years. On a pure stand, dwarf coconut trees can yield up to 12,000 nuts per ha under recommended spacing of 9m x 9m On the other hand, hybrid (Minazi Chotora) is a cross breed of EAT and dwarf variety and therefore contains the characteristics of both varieties. It starts producing at the age of 4 – 5 years and produces nut with thick copra flesh and has good quality immature nuts, hence good for both Madafu and oil production. It has the ability to produce an average of 60 nuts per annum and can live for more than 60 years. It requires a fertile and a well drained soil, a lot of rain and good management. Hybrid variety was imported from Ivory Coast and established at Mtwapa (20 Plants) and Msabaha (15 plants) in 1978. They performed dismally and have since died. The cause of death was lethol bole rot disease (W. Mwangi and J. Njoba, 2000). The current research status in Kenya shows that there has been no research on coconut since 1990 at Mtwapa except for maintenance of germ plasm. This has been due to national research priorities, which have given coconut a low rating, inadequate personnel and lack of funds. 3.4 Coconut Products Worldwide, the major coconut products include; Copra,Copra cake, Toddy, Leaves, Brooms, Baskets and Mats, Oil, Desiccated Coconut, Coconut Cream, Coconut Shell, Shell Flours, Shell Charcoal, Activated Carbon, Charcoal Briquettes, Coir Fibre, Coir Dust, and Fresh Coconut Juice. In Kenya, existing literature indicates that coconut is mainly used for making copra and very little has been achieved in terms of developing and promoting other uses of coconut products. Copra is the most important coconut product that is further processed into oil, which is mainly used in the soap industry, cosmetics, candle manufacture and some oil has been refined to edible quality.


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Copra is the dried meat or kernel of the coconut (wikipedia). The name copra is derived from the Malayan word Kopra for dried coconut. Copra and the oil it contains are the principal products of the coconut palm (J.G. Ohler, 1984). A study conducted by UNIDO in 1984 showed that about 90% of copra produced in Kenya was dried through sun-drying (UNIDO, 1984). The study indicated that sun drying was the oldest method of drying copra and was still widely practiced in Kenya at the time. Apart from sun-drying, copra can also be dried using copra kilns. Some farmers are known to use small copra dryers (using direct heating systems) which they use whenever sun-drying is not possible. Studies on the quality of copra indicate that the quality of copra produced in the coast region has generally been of inferior quality (W.V.D Pieris, 1969). Copra sold to the mills has high moisture content and contains significant quantities of immature nuts. The poor quality of copra is attributed to the system of drying (that is insufficient drying) and harvesting. A study conducted in 1988 showed that despite the huge potential of producing up to 46,756 tons of copra per year, the average national production at the time was fluctuating between 5,000 – 10,000 tons per year (J.W. Mwaura, 1988). Given that 6,000 nuts are required to produce 1 ton of copra, then it would mean that between 30 million and 60 million nuts were being used in copra production at the time. In terms of coconut oil milling, Kenya has 9 major oil mills operating in Coast Province which can process copra. These include Eastern Oil Millers (Lola Lola) in Changamwe Mombasa, Diamond Oil Millers, Mombasa; Kisumu Wallah Millers in Shimanzi, Mombasa; Mombasa Oil Millers; Mafuta Oil Millers, Mombasa (now closed); Pereira & Sons Ltd, Mombasa; Coco Industries ltd, Mombasa; Pwani Oil Industries, in shimanzi, Mombasa; and Malindi Industries, Malindi. Msambweni Development Company, the largest coconut plantation also used to have an oil mill but this is now no longer in operation. Information from CDA shows that the combined milling capacity of these mills is estimated to be 30,000 tons with a potential production of 18,000 tons of oil per year. From literature, the other important coconut products in Kenya are palm wine (also known as Toddy) which is consumed locally and in major towns in the coast region, madafu from immature nuts, brooms and makuti, among others. Other products that can be developed for both domestic and export markets include desiccated coconut and coconut cream. In addition, the coconut shell can be used for making shell charcoal briquettes. The other product whose full potential has not been exploited is the husk. The by-products from husk include coir fibre. Coir fibre can be spinned into yarn for making mats, ropes, and can be used for upholstery and stuffing mattresses, brushes and brooms. It can also be rubberized for making various high value cushions or other products. The economic potential for coconut products and by-products is therefore wide and can be effectively utilized to enhance the income earnings of the local coconut farmers and in the process create employment opportunities mainly to school leavers. 3.5 Agronomy


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Coconut grows well in the Agro-ecological Coastal Lowland Zones CL2, CL3 and CL4 but frequent drought in these zones has been affecting coconut yields. The unavailability of drought tolerant varieties is making replanting of coconut in these zones difficult. Fertilizer trials were set at Mtwapa and Matuga most of which were abandoned due to tree variability and poor yield (Eijnatten, 1979). The result of these trials gave an indication that fertilized trees yielded more, especially in treatments where nitrogen was applied. In 1979 fertilizer experiment was set up to study the influence of Nitrogen (N), Potassium (P) and Calcium (K) on the productivity of mature tall coconuts and to observe the influence of normal weed control of natural vegetation and ring weeding and mulching in a grassed coconut planting. The result indicated that there was no significant difference among the treatment. The result may have been influenced by disease attack on the tree since it is known that coconut trees respond favorably to application of Fertilizer. According to the study conducted by Kinyua (1993), management is a major problem contributing to poor performance of the palms. Crop husbandry has not been observed in many fields resulting in low yields and poor quality palms. The old trees are neglected, usually growing in bushes. Weeding has shown to have positive effects on yields. Coconut under food crops and weed free plots has higher yields. The low yield reported in most of the farms in Kenya is as a result of combination of two factors; lack of maintenance of field hygiene and the old age of the trees. Most of the trees nearer 40 and 60 years for dwarf and EAT variety respectively have low rate of production per annum. This coupled with no maintenance and no fertilizer application has resulted in trees producing 3 to 4 nuts per bunch per season. Hence low yield are common phenomenon particularly in the dry zone, aged and poorly managed trees. The Government in an effort to ensure quality supply of seedlings had established nurseries that produced planting materials for farmers at a fee; however almost all the nurseries collapsed after sometime. This has made most of the farms in Kenya to be planted with seedlings obtained from relatives and friends, mainly unselected EAT. These are sometimes low yielding. 3.6 Pests and diseases Surveys have established that several diseases affect coconuts production in the region which has not made it possible for the trees to reach the optimal level of production. Bole rot disease which is caused by the fungus was shown to be the most important. The disease is capable of wiping out the whole coconut plantation (Odieki et al, 1979). It is the main cause of many dead standing trees in coconut field. Lethal Yellowing (LYD) is another disease caused by mycoplasma–like organisms. Surveys done in Kenya have shown that Kenyan palms are relatively free of this disease. Typical symptoms of LYD observed include premature nut fall, followed by necrosis of the inflorescence, yellowing and browning of leaves starting from the base to the crown. In advanced stage, the leaves fall down leaving only the trunk. The infected plants die within 4-6 months from the first symptoms. Sculling and Mpunami (1991) suggested that selections could be done in Kenyan genotypes in search of resistance of lethal yellowing. Long term solution to this problem lies in the introduction of resistant


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varieties and strict quarantine against importation of seed from locations know to have the lethal yellowing disease. Insect pests have also played a big role in decline of coconut production. The most important ones being rhinoceros beetle (Orctes monoceros) and coried bug (Pseudtheraptus wayi) which kills the coastal trees by destroying the terminal buds. Warui and Gethi (1980) gave a thorough review of these pests and proposed methods for controlling them. For rhinoceros beetle, the study proposed physical removal, killing using a wire and removal of dead logs to eliminate breeding grounds for the beetles. Omondi and Eijinatten (1980) further proposed use of chemical and biological control using Maji moto ants and Oecphylla lonnginoda. 3.7 Marketing of coconut products Until early 1980’s the coconut sub-sector had well established cooperative societies, which facilitated the marketing of copra. Liberalization of the economy as a result of Structural Adjustment Programme (SAP) implemented in the country in early 1980s coupled with mismanagement led to the collapse of the coconut sub – sector. This has created an opportunity for middlemen to take advantage of the situation to pay farmers uncompetitive prices for their produce Currently there are no strong cooperatives for coconut products and by-products. Marketing is generally carried out through middlemen and brokers with farmers selling on individual basis. Lack of organized marketing has denied farmers bargaining power and opportunity to exploit potential markets in upcountry and neighboring countries of Tanzania, Uganda, Rwanda and Burundi. Currently the major destination of coconut products and by-products are oil industries, local consumption and neighboring country of Tanzania. A diagnostic study conducted by CDA in Kilifi District in November 2000, indicated that the major constraints facing the farmers in marketing of their produce is unreliable market, lack of transport and low prices. 3.8 Legislation During the pre-independence period, the development of the coconut industry was governed by two Acts of parliament; Cap 331- “The Coconut Industry Act” and Cap 332, “Coconut Preservation Act”. Cap 331 was mainly concerned with the marketing of the coconut and coconut products, while Cap 332 concentrated with the crop husbandry/management. In post independence, powers were vested in the Minister of Agriculture who has never gazetted coconut as a special crop3 which would have facilitated the establishment of a Board to oversee the development of the sub sector. Lack of institutional support for the coconut sector has greatly contributed to low production, poor marketing and lack of research and development for the coconut in Kenya.

3 Cap 318 section 191 (1) of Agricultural Act ``Where a Crop is declared to be Special Crop under section 190, the minister shall after consultation with the Treasury, by order in the Gazette, establish an Authority for promoting and fostering the development of the crop for such area, and consisting of such members as the minister shall in order specify. Provided that nothing in this section shall prevent the Authority being made responsible for the development of more than one special crop’’


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PART TWO

RESULTS OF THE SURVEY


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4 MAGNITUDE OF THE SUB-SECTOR

4.1 Overview The size and magnitude of the Coconut sub-sector has generally been unclear for quite some time. Using population of trees, acreage and annual production of nuts, the Ministry of Agriculture (MoA) has been providing estimates which many (including MoA) considered as rough working figures which could be used in the absence of more reliable estimates. It is indeed, for this reason that the MoA has had in its annual plans for the Coast province, intentions of carrying out this type of a study to establish a more reliable estimate of the sub-Sector. This section presents information on size and magnitude of the coconut sub-sector from four parameters commonly used in measurement of sub-sectors – the population of trees; number of farmers; size of land under production; and the value of annual production, not just of nuts but of all major products of the coconut tree produced at the farm level. 4.2 Population of trees Results of the coconut survey show that the population of coconut trees in Coast Province is much higher than what has generally been thought to exist. Table 4.1 shows that there are 7.4 million coconut trees in the province – a figure well over two thirds higher than the 4.4 million trees generally quoted in the past as the total population of trees in the province. As will be discussed in Section 5, this much higher figure may be explained by the fact that, contrary to what has been the generally held view that farmers were not replanting coconut trees any more and most trees were very old, farmers have actually been replanting trees and there is quite a significant number of trees replanted in the last 20 years.

Table 4.1 Population of coconut trees in Coast Province by district

District Number of coconut trees Number of farmers Average trees per farmer Number % Age Number Per cent

Kwale 2,895,427 39.0% 26,201 32.2% 111 Kilifi 2,831,978 38.1% 28,739 35.3% 99 Malindi 986,997 13.3% 14,013 17.2% 70 Lamu 434,105 5.8% 6,768 8.3% 64 Tana River 140,414 1.9% 1,841 2.3% 76 Mombasa 136,938 1.8% 3,784 4.7% 36 Total 7,425,859 100% 81,347 100% 94

Source: ABD-DANIDA/CDA Coconut tree survey, February 2007 From a geographical distribution view, the survey shows that Kwale and Kilifi Districts have almost an equal number of coconut trees. Kwale is however leading with 2.9 million trees accounting for 39.0% of the total population of trees in the Province closely followed by Kilifi with 2.8 million trees (38.1%). From official statistics as well as indications on the ground, this close tie between Kwale and Kilifi is however a fairly recent phenomenon. The large numbers of trees in Kwale are generally accounted for by the large scale growers in the District, among them plantations such as the Msambweni Development Company with over 180,000 coconut trees. The rate of replanting of trees is however much lower in


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Kwale than in Kilifi. As discussions in Section 5 will show, the rate of growth in population of coconut trees is almost three times higher in Kilifi than in Kwale. The other two districts in Coast province with significant population of coconut trees are Malindi with almost 1 million trees (13.3% of total population) and Lamu with close to half a million coconut trees (5.8%). Together, these four districts account for over 96% of the total population of coconut trees in the province. From an overall perspective, Tana River and Mombasa districts are not significant producers of coconut although there are certain small pockets of the districts where there are significant concentrations (clusters) of coconut trees. These include Kipini in Tana River District and Kisauni and Likoni areas in Mombasa District. In terms of tree holding per farmer, the survey shows that while coconut growing is still a smallholder crop in Kenya with over 60% of the farmers with 50 trees or less, the number of trees owned per farmer is still much higher than for most other tree crops4(Table 4.2). On average, each farmer has 94 coconut trees which, with proper care and development of the sub-sector, could become a significant base for household livelihoods in the Coast Province.

Table 4.2 Number of trees per farmer

Number of trees Number of farms/farmers Per cent Up to 10 trees 16,870 20.7% 11 – 20 trees 11,297 13.9% 21 – 50 trees 21,155 26.0% 51 – 100 trees 14,903 18.3% 101 – 200 trees 9,479 11.7% 201 – 500 trees 5,863 7.2% 501 – 1,000 trees 1,328 1.6% 1,001 – 10,000 trees 447 0.5% 10,001 + trees 4 0.0%

Total 81,347 100.0% Source: ABD-DANIDA/CDA Coconut tree survey, February 2007 4.3 Number of farmers The number of farmers involved in coconut farming is not a straightforward figure easily discernable from responses obtained from questions of who owns the trees. Like in the case of other tree crops that outlive generations, ownership of coconut trees is shrouded in joint ownership by extended family members – i.e. the case of fathers and their adult sons. In coast province, this is further complicated by the significant squatter and absentee landlord issue. The coconut survey instrument was however designed in full view of these complications and attempted to cover all coconut trees regardless of their ownership. Table 4.1 (above) shows that there are 81,347 farmers who have distinct farms/plots planted with coconut trees. These farms have a designate owner or farmer but in many cases, the farm in question has other farmers within who do not have full authority over the coconut trees but carry out other 4 Though fairly limited in terms of geographical coverage, comparable studies for mangos and avocados show that more than 50% of mango and avocado farmers have less than 10 trees of the crop (USAID/Kenya BDS program).


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farming activities on the farm and are farmers in their own right. Using information from questions of who owns the land and who owns the trees, the results of the Survey suggest that the number of farmers who cultivate pieces of land planted with coconut trees are in the range of 140,000 to 200,000. Many of these farmers however only cultivate the land but do not have ultimate say on the coconut trees in that land, mainly because the trees were planted by their parents who are still the owners or ownership is joint along with other members of the extended family (in case where the parents are not alive). This figure of farmers is generally in line with past general view that there are between 120,000 – 200,000 farmers involved in coconut farming. From Ministry of Agriculture information that there are 252,090 farm families in Coast province, results of the Survey therefore suggest that although only 32.3% of farmers in Coast Province actually own trees, between 55.5% and 79.3% of farmers s in the province cultivate farms planted with coconut trees. Table 4.3 shows the gender dimensions in coconut farming. As would be expected from a cultural perspective where land and permanent crops are generally owned by men, only 14% of coconut farmers are women. This number generally reflects the number of women-headed households among coconut farmers. This does however not imply that women are not involved in coconut farming but merely the cultural practice where women are generally not regarded as de facto owners of the trees. Indeed, there are many cases where it is actually the woman who planted the trees but ownership will still be vested in their husbands. While the survey did not dwell on aspects of the youth (or age for that matter), it was quite clear that ownership of trees is generally in the hands of the elderly – generally reflecting the fact that most of the trees where planted by the generations who had land ownership in the 1970s or earlier. An interesting aspect revealed in Table 4.3 is that women generally own fewer trees than men. While the proportion of women who own trees is 13.8%, women only account for 9.8% of the tree population. Men on the other hand comprise 85.9% of the farmers but own 87.2% of the trees. A small but significant number of trees are owned by institutions – government institutions such as the Navy in Mtonwge, hotels, and registered farming companies like Msambweni Development Company in Kwale District.

Table 4.3 Gender dimension in coconut farming, ownership of trees by men and women

Farmers Number of trees Number Per cent Number Per Cent

Male 69,837 85.9% 6,476,989 87.2% Female 11,265 13.8% 730,923 9.8% Institution 221 0.3% 233,285 3.1% Total 81,340 100.0% 7,425,859 100.0%

Source: ABD-DANIDA/CDA Coconut tree survey, February 2007

4.4 Acreage As is the case with other tree crops cultivated by smallholders in Kenya, acreage under coconut cultivation is not a straightforward issue. This is because coconut farming among smallholders is hardly ever done in pure stand and trees are generally scattered across the farm sometimes in a manner in which seedlings sprouted on their own but many cases following certain pattern of portions of the farm that are suitable for the crop (sandy sections or along valleys/rivers. In most of the cases, coconut trees will be found intercropped with other trees crops – mangos, cashew, citrus, bixa and even some forestry


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crops. It is therefore difficult to estimate the exact acreage under coconut cultivation as some portions of land will have no trees at all while, even where there are trees, these are intermixed with other crops. During the coconut survey it came out clear that farmers generally know the total size of land they own but have difficulties in telling the exact size they have planted with coconut. Results of the survey show that Kenya’s total land under coconut cultivation currently stands at slightly over 200,000 hectares (Table 4.4). It is however important to note that this is the total size of land owned by coconut farmers in which certain portions are planted with coconut, generally mixed with other crops.

Table 4.4 Size of land under coconut production (in hectares)

District Number of trees Number of farmers

Total land under coconut

Size of land per farmer (ha)

Trees per hectare

Kwale 2,895,427 26,201 86,522 3.30 33 Kilifi 2,831,978 28,739 56,398 1.96 50 Malindi 986,997 14,013 27,268 1.95 36 Lamu 434,105 6,768 22,731 3.36 19 Tana River 140,414 1,841 4,862 2.66 28 Mombasa 136,938 3,784 4,534 1.20 30 Total 7,425,859 81,347 202,326 2.49 37

Source: ABD-DANIDA/CDA Coconut tree survey, February 2007 The general approach used by the Ministry of Agriculture in calculating acreage for tree crops is to estimate the number of trees there are and then impute the size of land they would occupy if they were planted on pure stand using recommended spacing dimensions. For coconut, the recommended spacing by MoA is 9mx9m and this is what the Ministry has been using to impute the land under coconut cultivation in the past. It is through this method that the MoA figures in Table 2.3 showing 42,433 hectares under coconut in 2004 were computed. For comparison purposes only, results of the survey show that, planted on pure stand and on the recommended 9mx9m spacing, the population of coconut trees now established to be in existence would occupy 60,128 hectares equivalent. On the ground, it is indeed interesting that trees are much more closely spaced many with 4 – 5 meter spacing, others even more squeezed. Hectarage imputed from recommended spacing is therefore not a very meaningful measure of size/magnitude of the sector. From an overall perspective, from the hectarage in the hands of coconut farmers it is clear that the potential for expansion in the population of trees is enormous. 4.5 Production Although official statistics have generally underestimated the magnitude of the coconut sub-Sector in terms of the population of trees and the related acreage, it is in the area of production where estimations have been grossly understated. While it is generally known that the coconut tree has many products,


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official statistics have only reported on nut production. Table 4.5 shows that, taking all products into consideration; the coconut sub-Sector is a Kshs 3.2 billion industry even just considering production at the farm level. Nut production account for less than a quarter (23.6%) of the value of production. The bulk (60.1%) of the value of production is accounted for by wine which is, on its own, a Kshs 1.9 billion industry at the farm level. Other significant products of the coconut palm at the farm level are Makuti (roofing materials) accounting for 12% of the value of production and brooms (3.3%). The emergent market for coco-wood of coconut trees, coir, coconut oil and other products of the coconut tree account for the remaining 1%of the value of the sub-sector. As will be discussed in Section 6, Copra is no longer a major product of coconut at the farm level.

Table 4.5

Value of annual production of various coconut products at farm level in 2006 (in Kshs million) District Mature Nuts Immature

Nuts (Madafu)

Wine Makuti Brooms Other Total

Kwale 191.31 18.24 248.47 79.07 8.68 7.85 553.62 Kilifi 234.77 32.18 1,177.30 167.58 83.50 9.73 1,705.06 Malindi 133.75 28.70 395.07 87.52 3.26 2.13 650.43 Lamu 67.08 7.33 10.79 27.39 0.84 - 113.43 Tana River 2.68 0.18 - 2.53 0.17 - 5.56 Mombasa 26.56 10.92 66.43 15.03 6.34 11.3 136.58 Total 656.15 97.55 1,898.06 379.12 102.79 31.01 3,164.68

Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007

The potential of the sub-sector in terms of production is however still understated by these figures owing to the fact that only a small proportion of the farmers are involved in production of some of the major products. Using information provided by farmers for year 2006, it is clear that while most (90%) farmers produce dry nuts, only 41% harvest the immature nut – madafu. The number of farmers involved in wine production is even much lower with only 36% of farmers, most in Kilifi District, involved in production. The proportion of farmers producing Makuti stands at 65% while the comparable proportion for those involved in broom production is only about a quarter (25.8%). In general, other than nut production which is widespread across all coconut growing areas, other products are in a large way localized to specific zones where a market has developed over time. An interesting finding of the survey is that a large proportion (83.0%) of reported production is marketed. This figure is much higher than most other tree crops in Kenya. It is however plausible given that the nature of most products of the coconut palm are, in a strict sense, non-food and therefore generally what is harvested is sold, otherwise it will not be harvested in the first place5. The remaining portion (17%) of production is generally what is consumed (or used) by the family or shared with friends and relatives. This portion is however, to a large extent accounted for by farmers who do not participate in the market (largely having few trees) at all rather than significant portions of reported production not getting to the market.

5 The Survey instrument was framed to capture “what was harvested” and “what was sold”.


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5 SECTOR DYNAMICS

5.1 Overview This section looks at the dynamics of the coconut sub-sector, the changes taking place that are influencing the current situation in the sector and the likely trends in the future. It begins by exploring the age structure of the existing tree population and goes further to look at the rate at which farmers are planting new trees or cutting down old ones to give a of picture of the entire pipeline of trees from planting to old-age and felling. The section also looks at the different varieties of trees and the extent to which farmers are adopting newer varieties. 5.2 The age of trees Results of the Survey show that contrary to earlier generally held view that about 50% of all coconut trees are over 60 years of age, a much smaller proportion of coconut trees accounting for only 8.2% of the total population are actually in this category of senile trees (see Table 5.1 (a) & (b)). On the other hand, young trees before the bearing age (0-5)6 constitute 14.1% of the trees while the next age category of 6 – 20 year-old trees account for 25.8%. Together, these two young age categories of trees of 0 – 20 years account for 40% of the total population of trees, unequivocally allaying earlier held fears that most of coconut trees are already too old and farmers are not replanting new trees. The largest proportion of trees is in the age category of 21 – 40 years, accounting for 31.8% of the total population of trees while trees in the age category of 41 – 60 comprise 20.2% of the population of trees.

Table 5.1 (a) The age of coconut trees in coast province

Age category Kwale Kilifi Malindi Lamu T. River Mombasa Total 0 – 5 years 395,716 340,956 160,627 113,217 19,750 19,964 1,050,230 6 – 20 years 692,770 642,797 336,458 160,799 51,007 30,490 1,914,321 21 – 40 years 891,379 959,473 334,849 80,488 69,346 29,251 2,364,786 41 – 60 years 606,877 676,843 118,591 69,615 861 26,257 1,499,044 61 + years 324,773 220,242 26,137 4,513 155 32,780 608,600 Total 2,895,427 2,831,978 986,997 434,105 140,414 136,938 7,425,859 Source: ABD-DANIDA/CDA Coconut tree survey, February 2007

Table 5.1(b) The age of coconut trees in coast province (per centages)

Age category Kwale Kilifi Malindi Lamu T. River Mombasa Total 0 – 5 years 13.7% 12.0% 16.3% 26.1% 14.1% 14.6% 14.1% 6 – 20 years 23.9% 22.7% 34.1% 37.0% 36.3% 22.3% 25.8% 21 – 40 years 30.8% 33.9% 33.9% 18.5% 49.4% 21.4% 31.9% 41 – 60 years 21.0% 23.9% 12.0% 16.0% 0.6% 19.2% 20.1% 61 + years 11.2% 7.8% 2.7% 1.0% 0.1% 23.9% 8.2% Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% Source: ABD-DANIDA/CDA Coconut tree survey, February 2007

6 The Tall variety starts producing at the age of 5 – 7 while the Dwarf variety starts at 3 – 5 years.


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On the whole, the overall picture emerging is that things are not as bleak as earlier held views seemed to suggest. While it is true that productivity in the sub-sector cannot be optimized when there is still large portions (currently 28.4%) of trees in the declining-productivity age categories of over 40 years, the overall position looks fairly healthy where there seems to be a fairly good impetus towards replenishing old trees. From Kwale to Lamu, farmers are planting new trees and have been doing so for many years now. Information showing that optimal productivity of coconut is achieved in trees up to the age of 30, however reminds us that it is important that the trend towards increased replanting of trees is build on as the proportion of trees beyond this optimal productivity age of 30 years is slightly over 44%. One possible explanation for the variance between the reality on the ground and generally held perceptions that most trees are old, is that a large proportion of the trees we have today has not come from planting of new trees by farmers who were doing coconut farming in the colonial and early years of the 1960s, but rather from new entrants in the farming of coconut. Only 17.6% of farmers have trees aged over 60 years while on the other hand, 57% of farmers have trees in the 0 – 5 year age category. The situation on the ground is that while in the 60s and early 70s most coconut trees were in the hands of few but larger-scale farmers (including plantations in the whole stretch of Likoni through Msambweni), things have changed over time and many more farmers, many of them interlard in new settlements and further from the main roads have entered into coconut farming. Peoples’ perceptions have however continued to be driven by the high visibility of the increasingly aging and neglected trees in the old areas of high concentration of trees. A drive through the districts, for instance Kilifi through Kaloleni, Msambweni through Shimba hills or even the settlement schemes of Lamu district easily confirms to the keen eye that it is not true that most coconut trees are in the senile age. Table 5.1(b) shows that although the general age structure applies across the districts, there are geographical variations in the distribution of trees particularly in the older age categories. For senile trees, for instance, the Table shows that Kwale and Mombasa disproportionately have more trees in this age category than the other districts and together hold almost 60% of all senile trees, with Kwale alone having over 50% of this category of trees. For Kwale, this situation is generally accounted for by the old plantations in the district and in Mombasa it is largely due to low rate of replanting of trees pushed by the pressures of urbanization. 5.3 Growth in the population of trees Computations generated from a comparison of the number of coconut trees planted in year 2006 against the number of trees cut down during the year shows that the population of coconut trees is generally on the rise at a crude annual rate of 2.2 %. Overall, farmers are planting well over 300,000 coconut trees every year. On the other hand, farmers are cutting down slightly over 150,000 trees each year for varying range of reasons giving a net growth of slightly over 160,000 trees every year (Table 5.2). Further analysis of Survey data reveals that a significant part of the growth in trees is accounted for by farmers who are new entrants in farming of the crop. Table 5.3 shows that almost 8% of the farmers involved in coconut farming today have started cultivation of the crop only in the last 5 years accounting for slightly over 9% of young trees in the age group of 0 – 5 years. This Table further reveals that although Kwale District has a disproportionately lower number of new farmers entering into coconut cultivation, those who get in, on average, plant more trees than their counterparts in the other districts.


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Table 5.2

Estimated rate of coconut re-planting District Number of

trees in 2006 Coconut trees planted in 2006

Coconut trees cut down in 2006

Net trees planted in 2006

Ratio of planted: cut down

Growth rate

Kwale 2,895,427 87,518 46,171 41,347 2.1 1.4% Kilifi 2,831,978 166,377 39,885 126,492 4.2 4.5% Malindi 986,997 54,291 11,588 42,703 4.7 4.3% Lamu 434,105 - - - - Tana River 140,414 - - - - Mombasa 136,938 5,305 55,243 -49,938 -10.4 -36.5 Total 7,425,859 313,491 152,887 160,604 2.1 2.2% Source: ABD-DANIDA/CDA Coconut tree survey, February 2007 This is partly explained by the lower population density in Kwale and the related availability of land, and suggests a trend towards a return of larger-scale coconut farming in Kwale compared to the other Districts. On the reverse however, these results show a higher adoption rate in coconut farming among farmers in the other districts.

Table 5.3 Number of farmers who have entered into coconut farming over the last 5 years, by District

District Number of farmers Number of trees Average trees per farmer Kwale 1,267 33,078 25.2 Kilifi 1,615 26,564 15.0 Malindi 1,888 22,716 10.8 Lamu 1,003 12,096 12.1 Tana River 182 581 3 Mombasa 500 4,156 8.3 Total 6,456 99,191 15.4 Source: ABD-DANIDA/CDA Coconut tree survey, February 2007 Referring back to Table 5.2, results of the Survey show that the growth rate in tree population varies by district with the highest growth taking place in Kilifi District (4.5%) closely followed by Malindi with an annual growth rate of 4.3%. Kwale district has a growth rate of only 1.4% partly explained by the higher rate of cutting down of trees and fewer farmers entering into the cultivation of the crop. The more than triple growth rate in tree population in Kilifi compared to Kwale may explain how Kilifi has edged up over the years to now almost have the same population of trees as Kwale which in the past was considered as the clear leader in coconut farming. At this trend, it will not take long before Kilifi takes lead in the population of trees as it has already become leading in terms of coconut farmers. An interesting finding depicted in Table 5.2 is that coconut farming is fast declining in Mombasa district. The Table shows that the rate of growth of trees in Mombasa is negative 36.5% meaning that, at this rate, many areas of Mombasa will no longer be considered to have significant coconut farming activities in a few years and coconut trees will become more ornamental/aesthetic just like it has become in the island and other parts of urban Mombasa. This is of course easy to understand as this is a phenomenon driven by pressures of urbanization. A significant part of the heavy cutting down of trees in 2006 is however also explained by the squatter/absentee landlord issue where squatters in a few areas (Bamburi, Likoni) cut down trees as part of their strategy for claiming rights of ownership. It is perhaps, from this aspect that there are also quite a number of new trees planted during the year.


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Table 5.4 shows key areas to watch in the process of ensuring a continued growth in the population of trees. One of these areas relates to the availability of seedlings at the farmer level. Results of the survey show that few farmers have good access to quality seedlings. The other factor relates to the population of dead trees. While many of the dead trees are as a result of age, there are strong indications that drying in some areas is as a result of other factors – drought, flooding, soil conditions and diseases. An important thing to note from Table 5.4 is however that combining the number of dead trees with those in the senile category of over 60 years gives us a total of almost 1.4 million trees that could be immediately available for coco-wood exploitation.

Table 5.4 The stock of coconut trees in various points of the pipeline

District Total life trees in farm Coconut Seedlings – not yet transplanted

Dead trees (still standing in farm)

Total stock coconut trees

Kwale 2,895,427 122,312 283,412 3,301,151 Kilifi 2,831,978 100,193 279,039 3,211,210 Malindi 986,997 53,075 195,367 1,235,439 Lamu 434,105 - - 434,105 Tana River 140,414 - - 140,414 Mombasa 136,938 4,272 22,077 163,287 Total 7,425,859 279,852 779,895 8,485,606

Source: ABD-DANIDA/CDA Coconut tree survey, February 2007 5.4 Coconut Varieties Information from Literature shows that there are three broad varieties of coconut grown around the World – the Tall variety, Dwarf variety and Highbrid variety obtained from a mix of the Tall and Dwarf varieties. There are however many sub-varieties found among each of these main varieties. For instance, in Africa alone, there are about 11 sub-varieties of the Tall variety, each generally associated with a region such as the East African Tall (EAT) variety generally found along Eastern Africa. There are three major sub-varieties of the Dwarf Variety – the Yellow Dwarf, Orange Dwarf, and Green Dwarf. Out of these varieties, there are numerous highbrid varieties developed for suitability for various products and agro-ecological adaptability. From literature and information generated during the survey pre-testing stage, it was established that the only major varieties in Kenya ere the EAT and the Dwarf varieties. The survey instrument therefore had questions on desegregation of the total number of trees owned by the farmer between the EAT variety and the Dwarf variety. For simplicity, the varieties in the questionnaire were distinguished as “Tall” and “Short” for “East African Tall variety” and “Dwarf variety”, respectively. Since the questionnaires were administered in local languages, during training of Enumerators, the local terms for these two varieties “Kongoo” for EAT and “Mitsemire” for the Dwarf variety were used and enumerators instructed to use these local terms. From the first batch of questionnaires returned from the field, it came out that there were significant numbers of Dwarf trees contrary to expectations. All District Teams were therefore reminded to re-instruct enumerators to use the local terms to distinguish


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the varieties to eliminate the possibility of returns showing Dwarf variety when the farmer on meant the trees that are still short in height (and not necessarily of the dwarf variety)7. Results of the Survey show that Kenya cultivates only two of the main varieties – the East African Tall and the Dwarf varieties8. Table 5.5 shows that the majority of coconut trees are of the East African Tall variety accounting for slightly over 87% of the trees with only 12% of the trees being of the Dwarf variety. While this pattern holds across all districts, there are variations observed in some areas that have a higher concentration of the Dwarf variety than others, with Malindi having a disproportionately higher percentage of this newer variety.

Table 5.5 Geographical distribution of coconut trees in coast province by variety

District Tall variety Dwarf Variety Total

Number Per cent Number Per cent Number Per cent Kwale 2,547,539 88.0% 336,609 12.0% 2,895,427 100.0% Kilifi 2,548,780 90.0% 282,931 10.0% 2,831,978 100.0% Malindi 760,975 77.1% 226,127 22.9% 986,997 100.0% Lamu 401,981 92.6% 31,933 7.4% 434,105 100.0% Tana River 136,763 97.4% 3,600 2.6% 140,414 100.0% Mombasa 126,120 82.1% 10,855 7.9% 136,938 100.0% Total 6,501,404 87.6% 924,455 12.4% 7,425,859 100.0% Source: ABD-DANIDA/CDA Coconut tree survey, February 2007 Table 5.6 shows that EAT is not just the variety with the highest number of tree population but also the one most widely adopted by farmers with 95% of coconut farmers cultivating this variety. This is not surprising given that this is the, so to speak, traditional / ‘indigenous’ variety introduced in Kenya. It is therefore interesting that there are actually a small but significant proportion of farmers (4%) who have opted to only concentrate in cultivating the Dwarf variety.

Table 5.6

Distribution of coconut tree varieties among farmers District Tall variety Dwarf Variety Total

Number Per cent Number Per cent Number Per cent * Kilifi 27,511 95.7% 9,358 32.6% 28,739 100.0% Kwale 25,299 96.6% 9,329 35.6% 26,201 100.0% Malindi 12,982 92.6% 4,888 34.9% 14,013 100.0% Lamu 6,116 90.4% 1,955 28.9% 6,768 100.0% Tana River 1,808 98.2% 564 30.6% 1,841 100.0% Mombasa 3,419 90.4% 919 24.3% 3,784 100.0% Total 77,136 94.8% 27,012 33.2% 81,347 100.0% Note: * Row total reflects total population of coconut farmers in district rather than raw total Source: ABD-DANIDA/CDA Coconut tree survey, February 2007

7 Though the Survey team took these necessary steps in getting enumerators to ask the right question to farmers regarding varieties, it is still possible that some of the returns (responses) for Dwarf variety actually mean just short trees of the EAT variety. Results of the survey under this section of “Varieties” should therefore be treated with this caution. 8 It is however noteworthy that a number of the sub-varieties of the Dwarf variety – Yellow, Orange and Green Dwarfs were also observed among farmers. The Survey however only picked out differences between the East African Tall and the Dwarf varieties.


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Much more recently introduced in Kenya, the Dwarf variety is now cultivated by 33% of coconut farmers. While the Survey did not go into details of why farmers opt to cultivate one variety and not the other or the combinations they have of the two, indications are that the introduction of new varieties has not been properly guided and farmers have generally been left to make decisions on the variety to grow based on their own observations or what they hear from others. Given that cultivar selection is a critical factor in determining productivity and management of costs and possible risks (from pest/disease; and drought tolerance through selection of more tolerant varieties), it is obvious that the area of varieties is a key aspect that calls for attention at research level.


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6 PRODUCTS AND MARKET ISSUES

6.1 Overview This section explores the various products of the coconut tree to look at the true value of the sub-sector and analyze the various segments (products) that may be driving or slowing down growth among farmers. As discussed in Section 4, there are six main products of the coconut tree produced at the farm level – the mature nut, immature nut (madafu), wine, roofing materials (makuti), and the wood of the tree which is a high value hardwood once the tree becomes senile and no longer productive, generally after 60 years. Each of these products is analyzed, looking at the proportion of farmers involved in production, the total volume of production, proportion of production that is marketed and the prevailing prices in the different geographical areas. 6.2 Mature Nuts Mature nut, the coconut per se, is many times considered as the main product of the coconut tree and it is indeed this product that has conventionally been captured in official documents in Kenya regarding production of the coconut sub-sector. From our discussions in Section 4 earlier, it was however clearly shown that this product comprises only a small portion (20%) of the total value of production of the sub-sector. It is however still one of the most important products – the second in overall ranking of value. From a perspective of participation of farmers, the mature nut can however still be regarded as the most commonly produced product and therefore, perhaps the most important across the board of all farmers. Unlike most of the other products, almost all farmers who cultivate the coconut palm are involved in production of mature nut (Table 6.1). The number of farmers not in production generally reflects new-comer farmers whose trees are not yet in the production age as well as a few farmers whose trees are very old or planted in zones unsuitable for coconut farming that they are hardly producing any nuts. A few farmers may also not be producing nuts because they have decided to exclusively focus on wine production which generally means cutting off the inflorescence for the wine tapping purpose.

Table 6.1 Annual production and marketing of mature nuts in 2006

District Total farmers

Number of farmers involved

in production

Total volume of production

(in pieces)

Per cent of production marketed

Average prices (in Kshs)

Value of production

(in Kshs mln) Kwale 26,201 24,267 (92.6%) 53,141,203 91.7% 3.60 191.31 Kilifi 28,739 25,377 (88.3%) 61,780,829 80.0% 3.80 234.77 Malindi 14,013 12,011 (85.7%) 29,076,249 82.0% 4.60 133.75 Lamu 6,768 6,345 (93.8%) 13,415,540 90.0% 5.00 67.08 Tana River 1,841 1,657 (90.0) 382,615 74.7% 7.00 2.68 Mombasa 3,784 3,037 (80.3%) 4,579,885 69.1% 5.80 26.56 Total 81,347 72,486 (89.1%) 162,376,321 85.1% 4.00 656.15 Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007


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Table 6.1 shows that Kilifi is the leading producer of mature nuts with an annual production of close to 62 million pieces, closely followed by Kwale district with annual production 53 million pieces. Out of the total production, 85% is marketed with Kwale leading in the proportion of production marketed (91.7%) compare to Mombasa where only 69% of production is sold. Surprisingly though, it is also in Kwale were prices are lowest averaging Kshs 3.60 per nut across the District during the year (2006). This is perhaps due to the large portion of marketed production, or possibly due to smaller size of nuts as quite a number of the trees are much older than in the other districts. 6.3 Immature Nuts (Madafu) In official statistics Madafu are normally combined with mature nuts to give an indication of production of the coconut sub-sector. This is because madafu is merely the same nut only that it is harvested before it matures, generally to be consumed as a soft beverage. The farmer has therefore the option of selling the immature nut or waiting until it matures to sell it as dry nut. Table 6.2 however suggests that the question of selling madafu or waiting to sell the mature nut may not be a simple decision in the hands of the farmer but more so dictated by the market. From a price perspective, it would appear that simple business sense would dictate that farmers should sell their nut as madafu as the price for this product across the board is generally higher than that of the dry (mature) nut. Why would the farmer then wait for many more weeks for the nut to mature only to sell it for a lower price? From Table 6.2 there are strong suggestions that the market for madafu is not widespread and it is, perhaps driven by a ready urban market. It also appears to be a fairly narrow market, particularly given the bulky nature of the product and the fact that it is much more perishable than the mature nut. Perhaps due to the high concentration of the Dwarf variety coconut and possibly the vibrant tourist market, Malindi is the leading producer of madafu. On a proportional perspective (per farmer) however, Mombasa stands out as the highest producer of madafu, again possibly explained by the drive of the Mombasa urban market. Prices for madafu are generally in the range of Kshs 5.00 per piece although in some areas they range from as low as Kshs 1 -2 to as high as Kshs 7 – 10 in areas close to the market.

Table 6.2 Annual production and marketing of immature nuts (madafu) in 2006



in production


(in pieces)


Average prices (in Kshs)

Value of production

(in Kshs mln) Kwale 26,201 8,293 (31.7%) 3,647,114 82.2% 5.00 18.24 Kilifi 28,739 12,283 (42.7%) 4,839,810 54.8% 6.65 32.18 Malindi 14,013 7,330 (52.3% 5,519,098 61.1% 5.20 28.70 Lamu 6,768 4,230 (62.1%) 1,465,484 15.5% 5.00 7.33 Tana River 1,841 1,473 (80.0%) 35,364 23.2% 5.00 0.18 Mombasa 3,784 1,596 (42.2%) 1,851169 84.6% 5.90 10.92 Total 81,347 35,205 (40.4%) 17,358,039 67.5% 5.50 97.55 Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007 6.4 Palm Wine (Toddy) As highlighted briefly in Section 4.5, in terms of value of production, coconut wine can be regarded as the main product of the coconut tree and it appears to be the one that is driving growth in the sub-sector. This is however a difficult product that is embroiled in faith-based (religious) and legality questions. It is therefore perhaps from this perspective that many have shied away from viewing this product as the


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growth engine of the sub-sector. Compared to the other products, prices are good, the market seems to be there even at the local level, and perhaps even most attractive, the income flow is on a daily basis unlike the nature of the other products. From a geographical distribution view, it is quite clear that religion plays a major role and wine production is generally heavy outside areas where the Islamic faith has strong roots. It is perhaps from this consideration that Kwale, Lamu and Tana River districts have fairly small production of wine compared to Kilifi, Malindi and Mombasa where this has evolved to a level of an industry on its own, generating hundreds of millions of shillings annually. It is however noteworthy that, even in the districts of low production such as Kwale, wine is still the product contributing highest to the total value of production. Irrespective of religious, legislative or social prejudices (and image) of coconut wine, the reality on the ground is that this is the commodity that is generating the highest value from the coconut tree and seems set to continue doing so as a nascent market seems to be sending signals to farmers that this is where he returns are. At the moment, only 36% of farmers are involved in production, but the stage seems to be all set for larger numbers to join in.

Table 6.3 Annual production and marketing of coconut wine in 2006



in production


(in 750ml bottles)


Average prices

(in Kshs)

Value of production

(in Kshs mln) Kwale 26,201 4,479 (17.8%) 18,005,342 83.5% 13.80 248.47 Kilifi 28,739 15,904 (55.3%) 65,405,688 79.2% 18.00 1,177.30 Malindi 14,013 5,808 (41.5%) 21,014,383 93.1% 18.80 395.07 Lamu 6,768 846 (12.5%) 539,279 100.0% 20.00 10.79 Tana River 1,841 184 (10.0%) - - - - Mombasa 3,784 1,261 (33.3%) 3,496,267 92.2% 19.00 66.43 Total 81,347 28,482 (36.1%) 108,460,959 83.9% 17.45 1,898.06 Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007 6.5 Roofing materials (Makuti) Makuti as a product of the coconut trees can be regarded as a secondary product, not sold exactly in its original form of production. It is generated from the coconut leave locally called Kanja which, at times is also sold to those involved in makuti making, usually at a fairly low price averaging Kshs 2. The makuti making process is predominantly carried out by women although increasingly there are also many men involved as the value chain has increasingly become commercialized. Table 6.4 shows that this is the third major product of the coconut tree, after wine and mature nuts. From a perspective of participation by farmers, however, this can be regarded as the second most important (widespread) product after dry nuts as, overall, 65% of all coconut farmers are involved in its production. Kilifi District has the highest level of participation by farmers.


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Table 6.4 Annual production and marketing of roofing materials (makuti) in 2006



in production

Total volume of production (in pieces)


Average prices

(in Kshs)

Value of production

(in Kshs mln) Kwale 26,201 15,670 (59.8%) 20,809,132 85.5% 3.80 79.07 Kilifi 28,739 21,077 (73.3%) 33,515,404 80.2% 5.00 167.58 Malindi 14,013 8,797 (62.8%) 19,448,467 81.1% 4.50 87.52 Lamu 6,768 4,653 (68.8%) 3,912,795 79.7% 7.00 27.39 Tana River 1,841 1,289 (70.0%) 549,931 12.8% 4.60 2.53 Mombasa 3,784 1,956 (51.7%) 2,660,118 52.6% 5.65 15.03 Total 81,347 53,442 (64.7%) 80,895,847 80.1% 4.50 379.12 Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007 6.6 Brooms Brooms constitute the other major product obtained from the coconut leave (Kanja). Just like makuti, brooms are a secondary product, again, predominantly processed and traded by women. The production of brooms is however not as widespread among farmers as some of the other products and it only 27% of all farmers who are involved in its production. Table 6.5 shows that this is a product generally produced for the market as 87% of production is marketed at prices that vary from one district to another by generally average in the region of Kshs 11 per piece. Some of the price differentials shown in Table 6.5 may be accounted for by different sizes of the brooms produced from different clusters.

Table 6.5 Annual production and marketing of brooms in 2006



in production

Total volume of production (in pieces)


Average prices

(in Kshs)

Value of production

(in Kshs mln) Kwale 26,201 4,452 (17.0%) 1,057,975 90.2% 8.20 8.68 Kilifi 28,739 12,284 (42.7%) 6,549,032 86.2% 12.75 83.50 Malindi 14,013 2,115 (15.1%) 322,773 80.3% 10.10 3.26 Lamu 6,768 1,692 (25.050 63,108 61.7% 13.30 0.84 Tana River 1,841 736 (40.0%) 17,367 88.5% 10.00 0.17 Mombasa 3,784 695 (18.4%) 749,999 89.7% 8.45 6.34 Total 81,347 21,974 (27.0%) 8,760,254 86.9% 11.10 102.79 Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007

6.7 Coco-wood In year 2006, 21% of coconut farmers cut down one or more of their trees. Although the reasons for cutting down the trees varied – some for clearing the land for other uses, others for ridding the farm of unproductive trees, some to obtain building/fencing poles, others taking advantage of available market opportunities – 75% of the farmers sold the trees they cut down. This reflects the emerging market for coco-wood. Well matured to over 60 years, the coconut tree produces a hardwood in the class of mahogany and other high-value hardwoods. While this is true and coco-wood furniture is a highly priced product generally for high-value niche markets, Table 6.6 shows that this market has not yet fully developed to reach the farmer with benefits of high prices. In general, prices are highly varied ranging from as low as Kshs 50 or less per tree to as high as Kshs 500 in some areas. The average price


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however is in the region of Kshs 250 – 300 per good sized tree going to the furniture industry. Prices are much lower for trees used for building/fencing poles making the general average price stand at Kshs 212.

Table 6.6 Annual production and marketing of coco-wood in 2006



in production

Total volume of production (in trees)


Average prices

(in Kshs)

Value of production

(in Kshs mln) Kwale 26,201 6,414 46,171 82.2% 170 7.85 Kilifi 28,739 7,998 39,885 83.8% 244 9.73 Malindi 14,013 2,007 11,588 63.8% 184 2.13 Lamu 6,768 - - - - - Tana River 1,841 - - - - - Mombasa 3,784 763 55,243 65.8% 204 11.3 Total 81,347 17,182 152,887 75.3% 212 31.01 Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007 6.8 Copra Copra used to be one of the major products of the coconut tree at the farm level in the past. Information from the 62,644 coconut farmers interviewed during the survey across the 1,723 villages in Coast Province marking the coconut belt however indicate that the situation has changed and copra in no longer a main product at the farm level. To many people knowledgeable of the coconut industry in Kenya, this is a surprising outcome as copra used to be the main product of coconut with 9 main milling industries established in the coastal region to produce coconut oil for various end uses including soap manufacture, cosmetics, candle and some even refined further as edible oil. Following an initial vetting of the draft survey report with a small number of experts on the coconut industry in Kenya, the survey team made follow-up interviews with all the major Coconut Oil milling industries9 (both in operation and those that have closed down), as well as a number of the coconut traders10 who used to supply copra to the milling industries. The team also made some 10 repeat visits to a sample of 40 randomly selected villages in the four survey districts. Information obtained from this post-survey assessment confirms that copra is no longer a significant product at the firm level. In general, the indication is that copra is no longer a profitable product at the farmer level as a kilogram of copra is bought at Kshs 5 – 7, farm gate. Since it takes 5 – 7 nuts to produce a kilogram of copra, farmers would rather sell their nuts in the form of dry nut at prevailing prices instead of spending time to crash them to obtain copra which is then sold for a much lower per unit price. Over the years, the Tanzanian market has opened up as a key destination for Kenyan nuts and this has pushed up prices significantly from what they used to be in the past. While the general farm gate prices are still low, sometimes ranging as low as 2- 3 shillings per nut is some areas, this price is still much higher than that of copra. Discussions with the oil millers show that while some have closed down and others stopped producing coconut oil, there are still some that are in operation dealing in coconut oil. Unlike in the

9 Eastern oil Millers (Lola Lola) in Changamwe Mombasa; Diamond Oil Millers, Mombasa; Kisumu Wallah Millers in Shimanzi, Mombasa; Mombasa Oil Millers; Mafuta Oil Millers, Mombasa (now closed); Pereira & Sons Ltd, Mombasa; Coco Industries ltd, Mombasa; Malindi Industries, Malindi; Pwani Oil millers; and Msambweni Development Company’s oil mill, Msambweni (no longer in operation). 10 Mr. Samuel Nyale of Kilifi/Malindi (over 20 years in coconut business); Ali Omar Mwamtitiyo of Tiwi, Kwale (over 10 years in coconut) and Mr. Mohamed Mwachome, a trader in Msambweni, Kwale (over 20 years in coconut business).


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past, however, where the millers would buy copra produced by farmers, those millers interested in copra are now forced to buy the dry nut and crush it themselves. This is the same line of story told by the traders who are very clear that particularly due to price increases caused by competition for nuts from traders from Tanzania, copra has become an unattractive product to farmers across the coast region.


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7 PRODUCTION

CLUSTERS AND SPATIAL VARIATIONS 7.1 Overview Development theory and practice gives a lot of importance to the phenomenon of enterprise clustering in driving innovations, growth and overall transformation of sectors. This section explores the question of production clusters in the coconut sub-sector in Coast Province. It looks at clusters from two perspectives – the mere concentration of the population of trees in certain areas and the concentration of production of specific coconut products within certain geographical areas. To the extent to which production clusters can be said to exist in the case of coconut and be actually identifiable, then it would mean that the sub-sector has nodes from which business relations can easily be developed. From a development perspective, these are also areas where targeted interventions can be made geared at influencing growth of the entire sub-sector. 7.2 Tree population-based production clusters There is no standard way of defining production clusters in agriculture. In general however, a production cluster is an area of high concentration of a certain crop (in our case coconut trees) and its producers (the farmers) within a short distance, say a radius of 5 or so Kilometers which makes it easy to enjoy economies of scale such as joint sourcing of services and attracting customers to the market due to volume of production. Usually, the cluster will be in such a way that producers have some common points such access road or a shopping centre (ease to organize into a common collection point or route) and possibly a common defining feature such as a sub-Location (village) etc which makes it easy for them to find a common unifying point in the event of organization. For the purposes of this report, we have defined a production cluster to be an area with a concentration of upwards of 50,000 coconut trees within a radius of 5-8 Kilometers. Using the definition of a cluster adopted in this report, results of the Survey show that the distribution of the population of coconut trees in Coast Province is in such a way that there are clearly identifiable production clusters. Table 7.1 (and Map 1) shows that there are 36 production clusters across the entire stretch of the coastal belt, stretching from Msambweni in Kwale District to Mkomani in Lamu. The major clusters are however concentrated in Kwale and Kilifi, each with 13 clusters. Some of these clusters are really big in terms of number of trees with Mivumoni and Kinondo clusters in Kwale District being the largest each with well over 400,000 trees – partly explained by the large scale producers in these areas. On the other hand, although Kilifi does not have any cluster with over 400,000 trees, the concentration of trees is more evenly spread across most of the clusters in a way that, overall the size of the 13 clusters in the district are almost the same size as the 13 clusters in Kwale. Malindi has 6 production clusters mainly in Magarini and Malindi Divisions. Mombasa on the other hand does not have the size of trees concentrations found in the other districts but, all the same, has three areas that


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could also be regarded as production clusters (albeit using a more relaxed definition). These are Jomvu Kuu in Miritini, Junda in Kisauni and Mwakirunge in Bamburi. All taken together, the production clusters identified account for 71% of the total population of trees in Coast Province though they represent only 42% of the farmers. These are the growth nodes of the sub-sector from where innovations and transformation will most likely come from.

Table 7.1

Production clusters in the coconut sub-sector Cluster description – location Number of

trees Number of

farmers Average trees per farmer

Kwale District 1. Kinondo cluster: (Ganzi – Kinondo sub-locs), Msambweni 587,702 1,748 336 2. Mivumoni – Kikoneni: (Bumbani, Mivimoni), Msambweni 469,429 3,446 136 3. Mkongani Cluster: (Mkonga –Tiribe-Mtsamviani areas) 174,634 1,504 116 4. Mwaluphamba Cluster: (mlafyeni – Kizibe stretch) 146,525 1,262 116 5. Diani cluster: (Gombato – Bongwe – Ukunda areas) 134,393 1,371 98 6. Milalani cluster: (Milalani area, Msambweni loc) 115,372 636 181 7. Boyani Cluster: (majimboni Loc, Kubo) 114,610 205 559 8. Shirazi – Kingwende cluster 98,728 1,169 84 9. Pongwe Kidimu cluster (Majoreni – Mzizima areas) 94,591 636 147 10. Tsimba cluster: (Kindutsi – Mazumalume areas) 83,098 1,011 82 11. Majoreni cluster: (Majoreni area – Pongwe kidimu) 51,131 510 100 12. Simkumbe (Tiwi) Cluster 50,340 758 66 13. Mokobe - Cluster: (makobe area of Majimboni, Kubo) 50,718 140 362 Sub-Total 2,171,271 14,396 151 Kilifi District 1. Junju cluster (Kuruwitu, Junju, Vipingo areas; Kikambala) 363,883 1,678 217 2. Roka Cluster: (Chumani – Roka areas, Bahari Div) 333,020 1,221 273 3. Matsangoni cluster: (Uyombo-Mkongani – Matsangoni) 210,488 1,641 128 4. Tezo Cluster: (Mtondia – Kibarani areas, Tezo, Bahari Div) 155,363 1,389 112 5. Kizingo (Mwarakaya, Chonyi Div) 148,544 360 413 6 Jibana cluster: (Kwale-Nyalani-Chilulu), Kaloleni 134,658 1,546 87 7. Ruruma cluster: (Mleji – Miyuni areas), Kaloleni 129,932 1,079 120 8. Ziani cluster: (Ziani – Ng’ombeni areas), Zaini, Chonyi 125,074 810 154 9. Kaloleni cluster: (Kaloleni – chalani/Mihingoni areas) 110,040 1,437 77 10. Zowerani Cluster: (Zowerani area, Ngerenya Loc, Bahari 85,105 397 214 11. Banda ra Salama Cluster, Chonyi 74,773 664 113 12. Kambe – Mbwaka/Kikomani Cluster 61,765 519 119 13. Chasimba cluster (Chasimba area, Chonyi) 60,487 577 105 Sub-Total 1,993,132 13,318 150 Malindi District 1. Dabaso-Mida Cluster: (Dabaso and Mida areas of Gede) 192,834 1,158 167 2 Ngomeni (Gongoni area, Magarini Div) 166,879 777 215 3. Jimba – Mbaraka/Chembe cluster, Watamu 105,141 646 163 4. Kijiwetanga-Shella cluster, Malindi Div 82,803 1,124 74 5. Nganda-Msabaha cluster: 63,089 889 71 6. Marereni Cluster: (Marereni area, Fundisa Loc, Magarini) 56,929 400 142 Sub-total 667,675 4,994 134 Lamu 1. Mkomani Cluster 139,384 - - 2. Shella Cluster 93,609 - -


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3. Tchundwa Cluster 54,533 - - Tana River District 1. Kipini Cluster 81,173 - - Mombasa District 1. Jomvu Kuu, Miritini Cluster 21,917 332 66 2. Junda (Kisauni) 25,329 491 52 3. Mwakirunge (Bamburi) 18,568 504 37 65,814 1,327 49 TOTAL 5,266,591 34,035 154 Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007


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Map 1: Coconut trees population density (trees per sq km) in Coast Province, 2007 Map1: Coconut tree population density in Coast Province


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Map 2: Coconut trees population density, Kwale district


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Map 3: Coconut tree population density, Kilifi District


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Map 4: Coconut tree population density in Malindi District, 2007


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Map 5: Coconut tree population in Mombasa District, 2007


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Map 6: Coconut tree population density, Tana River and Lamu Districts


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7.3 Product-specific production clusters After looking at the production clusters in general in terms of the population of trees and farmers in Section 7.2 above, this section narrows down to products to establish whether there are specific clusters associated with any of the major products of the coconut tree. For each product, a specific cut-off is defined largely driven by the volumes that would make serious sense from a business perspective. 7.3.1 Mature nuts production clusters As discussed in Section 6, Mature Nuts is the product with the most widespread production across the entire coconut production belt. There are however still clearly identifiable production clusters. Table 7.2 identifies 6 main production clusters in Kwale District, 7 in Kilifi, and 2 in Malindi. With a relaxed cut-oof point of annual production of 500,000 nuts, Mombasa can also be said to have up to 4 identifiable production clusters. Information provided for Lamu and Tana River Districts could not allow for rigorous statistical manipulations to ascertain the existence of nut production clusters in these two districts. Together, these identified clusters account for 38% of the total nut production. From a geographical distribution perspective, it is worthy noting that although Kilifi has a larger number of production clusters, Kwale District has some of the largest clusters in production of dry (mature) nuts. These include the Kinondo, Bumbani, and Golini clusters. Information on the ground shows that these are well known and attract buyers not just from Kenya but also from neighbouring Tanzania. In Kilifi, Chonyi seems to have some of the largest clusters in Mature Nuts production. From the look of things in Kilifi, however, one can say that coconut farming for the market seems to have taken root. Malindi District has two Nut production clusters but one is really big, indeed much bigger than even the largest clusters in Kwale and Kilifi. This is the Ngomeni cluster with over 166,000 trees. Though much smaller compared to those in other districts, four clusters in Mombasa are clearly discernible, generally driven by the population of trees.

Table 7.2 Mature nut production clusters by district (based on 2006 annual production figures)

Cluster description – location Number of farmers

Number of trees

Production (in pcs)

Kwale District 1. Kinondo cluster, Msambweni 1,221 288,925 7,046,028 2. Bumbani, Kikoneni cluster 2,291 323,280 4,509,390 3. Golini, Matuga cluster 819 46,475 3,372,920 4. Mivumoni cluster 1,155 146,149 2,530,025 5. Tiribe , Mkongani cluster 549 50,868 2,446,700 6. Kingwende, (Kingwende/shirazi) cluster 541 41,677 2,316,109 Sub-total 6,576 897,374 22,221,172 Kilifi District 1. Zowerani, Ngerenya cluster 397 85,105 6,307,779 2. Ziani, cluster (Chonyi) 516 67,043 2,362,921 3. Junju (Junju, Kikambala) cluster 868 109,540 2,906,568 4. Uyombo,, Matsangoni cluster 537 81,737 2,375,840 5. Chumani, Roka cluster 710 204,921 3,234,339 6. Chasimba, , (Chasimba, chonyi) cluster 577 60,487 3,489,939 7. Mkomboani, Kaloleni cluster 301 37,492 2,050,594 7,288 1,143,397 22,727,980 Malindi District


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1. Ngomeni, Gongoni cluster 777 166,879 11,496,708 3. Dabaso, Gede cluster 508 131,048 2,613,233 1,285 297,927 14,109,941 Lamu District - - - - - Tana River - - - - - Mombasa 1. Shanzu cluster 126 9,069 685,510 2. Mwembe Legeza cluster 145 6,620 805,068 3. Kisauni cluster 160 10,482 780,775 4. Jomvu Kuu, Miritini cluster 332 21,917 594,337 763 48,088 2,865,690 TOTAL 15,912 2,386,786 61,924,783 Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007 7.3.2 Madafu production clusters From the number and size of clusters with a focus on production of madafu it appears safe to say that the madafu value chain is not as well developed as some of those of the other products. With a fairly relaxed cut-off point for annual production, it can be said that there are about 14 madafu production clusters in all with Malindi having a larger number perhaps to reflect the more developed market for this product in the District as discussed in Section 6.

Table 7.3 Madafu production clusters


Number of trees

Total production

(pcs) Kwale District 1. Golini Cluster 819 46,475 1,015,105 2. Vingujini, Msambweni cluster 566 34,206 316,598 3. Kiwegu, Vanga cluster 355 35,879 482,822 Sub-Total 1,740 116,560 1,814,525 Kilifi District 1. Mtsara-wa-tsatsu 756 28,264 425,555 2. Mwarakaya, Chonyi cluster 355 20,143 1,804,166 3. Mazeras/Mugumo Patsa 359 17,106 360,944 4. Vinagoni 176 6,033 344,680 Sub-Total 1,646 71,546 2,935,345 Malindi District 1. Ngomeni cluster 777 166,879 1,666,048 2 Fundisa cluster 306 16,314 715,692 3. Marereni cluster 400 56,929 596,571 4. Shella, Malindi cluster 549 24,173 453,433 5. Kijiwetanda cluster 575 58,630 360,264 Sub-total 2,607 322,925 3,792,008 Lamu - - - - - Tana River District - - - - - Mombasa District 1. Shanzu 126 9,069 959,510 2. Mwembe Legeza 145 6,620 340,391


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3. Kisauni 160 10,482 278,434 431 26,171 1,578,335 Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007 7.3.3 Wine production clusters Although only 36% of coconut farmers are involved in wine production, Table 7.4 shows that the wine industry is fairly well developed at the production stage, particularly in Kilifi and Malindi Districts. Unlike the other products, however, this is not just a tree-population driven commodity where production comes in because the trees are already there and they will somehow produce when in season. Wine production is a deliberate business decision by the farmer and the production clusters are not necessarily ones with the highest number of trees. Although Kilifi and Malindi have the largest number of clusters where millions of shillings change hands on a daily basis, there are specific zones in Kwale District which are also quite active. Indeed, information from the survey suggests that the second largest palm wine production cluster in Coast Province is in this District – Mwaluvanga.

Table 7.4 Coconut wine production clusters


Number of trees Total production (750 ml bottles)

Kwale District 1. Mwaluvanga 262 39,012 2,812,528 2. Golini 819 46,475 1,339,541 3. Mivumoni 1,155 146,149 1,022,827 4. Milalani 636 115,372 741,685 5. Mbunguni 428 31,595 680,605 6. Dumbule 283 6,511 539,903 7. Mlafyeni 725 89,256 516,127 Sub-Total 4,308 444,370 7,653,216 Kilifi District 1. Jimba, Ruruma cluster 381 22,364 2,668,731 2. Vinagoni 176 6,033 2,486,613 3. Kiriba/Magawani 346 14,841 1,882,897 4. Roka 511 128,099 1,763,136 5. Chalani/Mihingoni, Kaloleni 876 51,611 1,963,885 6.

Pingilikani

404

46,146

1,551,467

7. Nyalani, Jibana 451 45,738 1,308,491 8. Mwarakaya, Chonyi 355 20,143 1,407,090 9. Matsangoni, 582 96,630 1,210,909 10. Mbwaka/Kikomani 519 61,765 1,193,296 Sub-Total 5,357 521,634 18,898,346 Malindi District 1. Fundisa 306 16,314 3,875,699 2 Ngomeni 777 166,879 2,784,978 3. Kakoneni 489 8,575 1,752,430 4. Marikebuni 468 34,151 1,856,931 5. Marereni 400 56,929 1,479,258 6. Masindeni 185 6,044 1,283,217 7. Mida 650 61,786 1,348,322 8. Msabaha 508 39,815 1,189,917


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Sub-total 3,783 390,493 15,570,754 Lamu - - - - Tana River District - - - - Mombasa District 1. Mwakirunge 504 18,568 905,913 2. Bamburi 240 8,693 607,494 744 27,261 1,513,407 Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007 7.3.4 Makuti production clusters As discussed in Section 6, Makuti is the second most widely produced coconut product. Table 7.5 however shows that, the production process is not as well developed on the ground. Kwale District has only two main production clusters, Kilifi has 5 and Malindi has 4. From the overall size of production (total value), fairly good prices in the market place and the good production base build around the population of trees, this is a value chain that seems to be operating quite below its potential.

Table 7.5

Makuti production clusters Cluster description – location Number of

farmers Number of

trees Total

production (in pcs)

Kwale District 1. Mivumoni 1,155 146,149 1,549,599 2. Bumbani, Kikoneni 2,291 323,280 1,151,168 Sub-Total 3,446 469,429 2,700,767 Kilifi District 1. Chumani 710 204,921 4,900,929 2 Ng’ombeni 294 58,031 3,770,229 3. Ziani 516 67,043 3,517,957 3. Roka 511 128,099 1,578,636 4. Kiriba/Wangwani, Takaungu Mavueni 346 14,841 1,2-3,424 5. Vipingo 382 43,499 1,200,005 Sub-Total 2,759 516,434 16,171,180 Malindi District 1. Ngomeni 777 166,879 6,933,027 2 Msabaha 508 39,815 1,892,716 3. Mambrui 229 6,828 1,582,744 4. Kijiwetanga 575 58,630 1,407,206 Sub-total 2,089 272,152 11,815,693 Lamu - - - - Tana River District - - - - Mombasa District 1. Vyemani, Likoni 228 5,538 735,821 228 5,538 735,821 Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007 7.3.5 Brooms production clusters


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Table 7.6 shows that the market for coconut brooms is almost exclusively driven by production clusters in Kilifi District. This is surprising given that, just like Makuti, the material for making the broom is the same – the Kanja. One would therefore expect to see a population of trees-driven production pattern. This is however not the case and Kwale District, with some of the largest tree population clusters has only one main production cluster. Kilifi and Mombasa therefore remain as the only major brooms production clusters. In Kilifi, Ziani (in Chonyi) and Junju (Kikambala) stand out as the major brooms production clusters. It is surprising that Malindi does not have any serious brooms production clusters.

Table 7.6 Brooms production clusters


Number of trees

Total production

(in pcs) Kwale District 1. Golini 619 46,475 373,896 Sub-Total Kilifi District 1. Ziani, Chonyi 516 67,043 1,441,558 2. Chasimba, Chonyi 577 60,487 457,602 3. Junju 868 109,540 697,862 4. Chilulu, Jibana 526 44,530 338,027 5. Chalani/ Mihingoni 558 58,429 262,012 6. Zowerani, Ngerenya – Bahari 397 85,105 279,995 7. Ng’ombeni 294 58,031 382,013 8. Kizingo 360 148,544 228,857 9. Ngerenya, Bahari Div. 425 39,164 251,348 10. Mbwaka/Kikomani, Kambe, Kaloleni 519 61,765 248,318 Sub-Total 5,040 732,638 4,587,593 Malindi District - - - - Sub-total Lamu - - - - - Tana River District - - - - Mombasa District 1. Maunguja - - 176,597 2. Jomvu Kuu 332 21,917 170,416 3. Kisauni 160 10,482 164,824 4. Junda 491 25,329 162,028 983 57,728 673,865 Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007 7.3.6 Coco-wood production clusters For coco-wood, we did not look at the pattern of cutting down trees on the ground as the basis for indicating to us areas of production clusters. This is because farmers cut down their trees for a varied range of reasons some of which are not for the coco-wood market. We therefore looked at possible production clusters from an analysis of concentration of old trees which would constitute the pool for coco-wood. Again, rather than look at this merely from the currently available trees in the senile stage, we have combined this category of senile trees with that of trees aged 41 – 60 years to give an indication of the size of the coco-wood clusters not just from the pool of ready to harvest trees but also from those to be next in line.


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Table 7.7 shows that it is only Kwale that has significant production clusters for coco-wood, particularly looked at from available stock of ready-to-harvest trees. From a consideration of the trees next in line however, Chumani, Kizingo and Kuruwitu clusters in Kilifi come out as important clusters to watch.

Table 7.7 Coco-wood production clusters

Cluster description – location Total trees 41 – 60 yrs

Total trees 61+ yrs

Total old trees

Kwale District 1. Gazi 67,738 98,779 166,517 2. Kinondo 78,646 8,640 87,286 3. Milalani 41,192 33,586 74,778 4. Mivumoni 47,641 8,329 55,970 5. Bumbani 38,128 14,510 52,638 Sub-Total 273,345 163,844 437,189 Kilifi District 1. Chumani 149,557 2,183 151,739 2. Kizingo 36,138 31,159 67,296 3. Kuruwitu 28,830 30,519 59,348 Sub-Total 214,525 30,519 278,383 Malindi District - - - - Sub-total Lamu - - - - Tana River District 1. - - - - Mombasa District - - - - TOTAL 487,870 194,363 682,233 Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007


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8 CHALLENGES TO REALIZATION OF

SUB-SECTOR POTENTIAL 8.1 Overview Information generated by the Survey and discussed under the last four Sections of this report (see Sections 4 through 7) suggests that only a small percentage of the full potential of the coconut sub-sector is currently exploited. Looking at average productivity per tree for the different products (i.e. 21 nuts per tree per year), the number of farmers involved in production of some of the other major products and the extent to which production reaches the market, our estimations are that barely is 25% of the current potential of the sub-sector exploited. Even at current prices, further exploitation of this potential would mean adding billions of shillings in the hands of coconut farmers and their households. This section looks at the constraints and challenges facing farmers towards realization of this potential. 8.2 Constraints and challenges facing farmers Table 8.1 presents farmers’ perceptions on the key problems and challenges they are currently facing in their coconut farming activities. It shows that, overall, production related issues dominate the challenges they are facing, closely followed by markets and marketing related problems.

Table 8.1 Major problems/challenges perceived by farmers

Problem/challenge Per cent of farmer mentioning this as a major problem Total (weighted) Ranked 1st Ranked 2nd Ranked 3rd

Production related problems/challenges: 56.4% 41.8% 33.4% 43.9% Unfavourable weather (drought) 25.3% 17.0% 11.9% 18.1% Pests and diseases 17.1% 12.0% 8.0% 12.4% In-access to quality seedlings 12.5% 11.1% 9.4% 11.0% Shortage of labour at critical times 1.5% 1.7% 4.1% 1.9%

Markets & marketing problems 28.4% 41.3% 41.6% 37.1% Low prices for products 17.5% 18.2% 16.7% 17.5% Poor market outlets 7.5% 14.7% 12.2% 11.5% High transportation costs to mkts 1.4% 4.9% 8.6% 5.0% Poor roads to markets 2.0% 3.5% 4.1% 3.2%

Lack of financial services 4.3% 7.9% 6.3% 6.2% Theft of products in farms 5.2% 3.3% 8.4% 5.6% Land tenure issues 3.4% 3.6% 4.1% 3.7% Other 1.7% 0.7% 1.7% 1.4%

Missing (no response) - 1.1% 2.2% - Total 100.0% 100.0% 100.0% 100.0% Source: ABD-DANIDA/CDA Coconut tree survey, Feb 2007


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8.3 Production challenges One thing that stands out clearly as one drives through the whole stretch of the coconut belt right from Lunga Lunga (Kwale) to Lamu, is an obvious neglect of the coconut tree from an agronomy perspective. While of course one notices that there are very many trees, one also sees that most of the trees are totally in the bush and with the land around the trees hardly ever cultivated/cleared. From an understanding of the effects of good agricultural practices in increasing quality and productivity, it can easily be said that this abandon and neglect of the coconut tree from an agronomy perspective is perhaps the most pressing challenge facing the sub-sector and holding back quality and productivity. This neglect is however the summation of a lot of underlying issues facing the farmer and, to many farmers, it is a conscious decision made in view of the current returns (per the returns they get from the tree). It is however also possible that many farmers are not actually aware the extent to which adoption of good agronomy practices (even just simple orchard management practices) would increase productivity and generate a good return, even at current prices. From the farmer’s perspective, there are three major challenges they face at the production level: harsh weather conditions (particularly the prolonged drought experienced over two years ago); pest and disease control; and accessibility to quality planting materials. 8.3.1 Weather and the question of better adopted varieties The harsh weather conditions of the last couple of years (prolonged drought which in some parts extended for almost six years) and the recent flooding were highlighted by farmers as the most critical problem they have faced in their coconut farming activities. The drought forced many trees to dry up or to tip-off and stop producing, particularly those planted in the marginal zones of CL5 or higher undulating ground. While this is the problem seen by the farmer, it can perhaps be interpreted as a research challenge on cultivar selection for adoptability. From a review of literature, a key aspect of research in other countries has been the identification and selection of cultivars that are most suitable for various agro-ecological zones. This is however an area that Kenya has extremely lagged behind and farmers are left to plant what is available without any guidance on suitability in their areas. This is an area that must be addressed if the sub-sector is to be expected to grow and reach its potential. 8.3.2 Pests and diseases Like in other crops, pests and diseases is one of the major challenges coconut farmers have to battle with in their farming activities. Some of the main diseases include Bole rot (fungal) which is capable of wiping many trees in a short period and is indeed responsible for many dead standing trees seen in the fields. Pests include Rhinoceros beetle (Orctes monoceros) and Coried bug (Pseudtheratus wayi) which also attacks the terminal buds in coconut making many dry-up. Knowledge of the pests and diseases affecting coconut trees and ways of dealing with them stands out as perhaps the major challenge facing farmers. 8.3.3 Access to planting materials Unlike in the (fairly distant) past, there are no-longer well established nurseries with a good supply of quality planting materials in coconut. Farmers generally rely on their current crop to get a few seedlings to plant and, at times, merely pick what has fallen down and germinated on itself. Given the critical importance of selection of quality planting materials as a determinant to yields and likely returns from the


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orchard, it is obvious that this current state of affairs is a major hindrance to growth and productivity in the sub-sector. It is indeed, very likely that the low number of seedlings planted is partly as a result of unavailability of well established nurseries for coconut seedlings. 8.4 Markets and marketing constraints Markets and marketing related challenges constitute the second most pressing challenge facing coconut farmers. These comprise of low and unreliable prices; poor/lack of sufficient market for their products; and the physical inaccessibility of markets due to poor road infrastructure. 8.4.1 Prices At the top of the list among markets/marketing issues facing farmers is what farmers view as low and unreliable prices for their products, disproportional to the efforts they have to make in production. In Section 6, we provided information on prices for different coconut products in the various districts. Information from the Survey shows large variability in prices, not uncommon in undeveloped markets for agricultural (and other primary) commodities. Prices vary by season, distance (from the market), quality and also from buyer to buyer. The distribution and marketing outlets are generally dominated by traders and middlemen (some, brokers) and there are rarely any direct linkages between the farmer and the market. This is even the case in the lucrative palm wine industry. Generally, farmers sell individually and rarely through collective action. To the farmer, the generally low price and the fact that they are not sure what the price will be is the major market related challenge discouraging them in their coconut farming activities. 8.4.2 Poorly developed markets Farmers complain that they are, many times, not able to sell all their produce. This particularly applies to dry nuts. Yet, perhaps this is even a bigger problem when it comes to Makuti and brooms where the market is not as well developed and, many farmers actually do not participate because of lack of any one to buy their products. This is also the case even in the appearingly more developed wine industry. Even here, other than in some of the well developed clusters in Kilifi and Malindi, the commodity can easily fail to get a buyer. Market access and development is therefore a key problem facing farmers and, perhaps the key to adoption of good agricultural practices in the cultivation of the crop. After all, farmers argue, why would one take care of his trees if he is not going to get a buyer for the product? 8.4.3 Poor road infrastructure to markets The marketing of coconut products is further curtailed by poor roads infrastructure in the districts. Due to the poor roads, the cost of transporting the commodities to markets sometimes completely wipes out the margins and, in return affects the farmer by forcing the traders/middlemen to offer the very low prices for them to make a margin or not to get to some locations at all. In extreme cases, roads are totally impassable during certain times and the farmer cannot get his product to the market at all. This is obviously a general development challenge that must eventually get addressed if rural farmers are to effectively benefit from the market economy. 8.5 Other constraints


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Other key challenges facing farmers include accessibility of credit and other financial services, insecurity of products while still in their farms (through theft) and issues surrounding land tenure, particularly the known squatter problem in Coast province.


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9 CONCLUSIONS AND

RECOMMENDATIONS 9.1 Overview This Section brings into conclusion discussions made through the previous 8 sections, particularly those related to results of the Survey (Sections 4 – 8). It highlights in a summary form the key findings of the Survey and uses this as a basis to highlight some of our thoughts on a way forward in the form of recommendations. The recommendations outlined should however be viewed merely as thoughts to build on, since, in essence, the purpose of this study was merely to lay bare the facts on the coconut sub-sector so that different players and stakeholders can take these up and draw their own conclusions depending on their line of interest in the sub-sector. The part on recommendations is therefore fairly narrow and more so directed at those likely to be interested in the sub-sector from a development perspective. It is in no way exhaustive to possibilities that could be available, particularly from a private business perspective. 9.2 Conclusions From a careful look at the discussions made in this report, six major conclusions appear to be worthy noting: 9.2.1 Coconut farming is deeply entrenched in coastal farming systems and forms an important part of the coastal economy. Coconut is perhaps the most important crop among coastal farmers. It is a crop that is deeply entrenched in the cultures, practices and ways of life of coastal communities, some dating as far back as a couple of centuries ago. This cultural value has dictated that almost every farming household in the coastal belt, particularly those with a coastal origin, has at least one tree. This partly explains why some farmers will attempt to grow the crop even in fairly marginal areas. Overall, this cultural attachment has contributed to the large population of trees and seems bound to continue holding ground, continually encouraging farmers to plant the crop. The cultural entrenchment is however beyond the cultivation and is even more widespread in the consumption of the products. Many coastal meals will have coconut milk as one of the ingredients; a normal way of quenching thirst is the madafu, the normal house (even increasingly more so, a coastal hotel) will be thatched with makuti and the general broom is the coconut broom. Coconut wine is also deeply entrenched as a local drink of choice. This cultural entrenchment in consumption of some of the major products plays a major part in driving the market for coconut products. It is however clear that market expansion must go beyond just the coastal populations who have a cultural attachment to the products. Luckily so, this trend is already there and it only needs to be further propelled. It is also noted that efforts must be made to make sure that some of the cultural (actually traditional) practices in the cultivation of the crop do not become an hindrance to its development. A good case is the now longstanding neglect of the crop that make some farmers think a coconut tree doesn’t need to be weeded, manured or sprayed with agrochemicals. Overall, it is clear that coconut farming is a central part of the livelihood of most coastal households and will continue to be so into the foreseeable future. Integrating this commodity sector into the market as an


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important cash crop will directly affect the livelihoods of many households in the Coast Province. Ignoring the crop will mean wasted opportunity to utilize an important economic base for coastal populations. 9.2.2 The size of the sector much larger than what it has been thought to be in the past and deserves due recognition as others sectors of similar magnitude in the country The magnitude of the coconut sector has generally been understated. Although a part of this general understatement appears to have been as a result of estimation errors in the absence of a full Survey, they key reason for understatement has been due to failure to recognize the importance of other products of the coconut tree some of which are even more important than the nut. This understatement therefore seems to have been perhaps deliberate, particularly owing to the legality question under which coconut wine fell into for many years until the lid was lifted under the current Government administration. This does not however explain the full story, as other important products of the tree did not fall into the legality question. Information from the Survey shows that the population of trees stands at 7.4 million - 3 million higher than the 4.4 million trees which were thought to exist. Taking all products into consideration, the value of the coconut sub-sector at the farm level is estimated to be Kshs 3.2 billion with 60% of the value accounted for by Wine, 24% by nuts; and the balance accounted for by makuti (12%); Brooms (3%) and the emerging market for coco-wood (0.5%). Although coconut wine is still embroiled in legality, religious and social image questions, it is clear that this is the product that is currently driving growth in the sub-sector and it is likely to remain so as signals from the emerging full commercialization of the market indicate that this is where the returns are. 9.2.3 The population of coconut trees is on the rise and there is a general growth trend across all districts with the exception of Mombasa. Dynamics in the coconut sub-sector show that there is a general rise in the population of trees and fears that the population of trees is likely to go down as most trees are over 60 years (and farmer are cutting them down) is not true. The population of trees aged over 60 years is only 8.2% of the total population or just slightly over 600,000 and not the 2.2 million (50%) thought to exist in the past. The survey shows that contrary to generally held views, farmers have actually been planting more coconut trees and the proportion of trees in the age before start of production is slightly over 14%. Overall, the population of trees is growing at a rate of 2.2% annually with the highest growth rates experienced in Kilifi and Malindi, propelled by a vibrant market for some of the coconut products among other factors. The rise in population of trees is lowest in Kwale with only a marginal growth rate of 1.4%. As is perhaps expected, there is a negative growth rate in the population of trees in Mombasa, pushed by the pressures of urbanization. Overall, however, the proportion of trees over the age of optimal productivity (of 30 years) is estimated to be 44% arguing for the need for initiatives towards increased replanting to increase the proportion of trees in the high productivity age categories for improvements productivity in the sub-sector. 9.2.4 There are clearly identifiable production clusters in the coconut sub-sector The distribution of the population of coconut trees in Coast Province is in such a way that there are clearly identifiable production clusters. Defined as areas of concentration in the population of trees within a small zone with a radius of 5-7 Kilometers, the study identified 36 production clusters in the the province with Kwale and Kilifi having the highest number of clusters (each with 13). Besides these general production clusters, there are specific clusters for the various products. Mature nuts and coconut wine have the largest number of clusters, although those related to wine are much more developed and vibrant. Overall, Kilifi


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has the largest number of well developed clusters indicting a much more developed market for coconut products at the farm level. These clusters are important growth points of the whole sub-sector from which innovations and transformation will come from. Efforts towards further development of these clusters could easily catalyse a forward thrust of the entire sub-sector towards full transformation and growth. 9.2.5 Only about a quarter of the potential of the sub-sector is currently exploited. From a look at the current development in production of the various products of the coconut tree, rough estimations of potential indicate that this could be a much bigger sub-sector, reaching well over Kshs 15 billion with the current population of trees and current growth trends. Average nut production currently stands at 21 nuts per tree which is much lower compared to optimal productivity levels of over 100 Nuts expected in good yielding varieties. The low participation of farmers in production of the other products is another indicator that the potential could be much higher. Wine production involves only 36% of farmers, brooms 21% and makuti 64%. The low participation rate of farmers is generally due to poor development of the markets for some of the products. Initiatives in further development of markets must therefore constitute an essential element of any development efforts targeted at the sub-sector. 9.2.6 Production and market related constraints are the key challenges to full potential The main challenges facing farmers at production level include accessibility of quality planting materials and the menace of pests and diseases. Effects of the prolonged drought which extended to over 4 years in some areas was however brought out as the most outstanding challenge faced by farmers at the production level. From a development perspective, this can be viewed as a challenge for finding more tolerant varieties – which is a key research area for the coconut sub-sector. On the market end, key challenges relate to price level and general reliability and actual market access by farmers for their products. The distribution and marketing channels are generally dominated by traders and middlemen who play an important role in getting farmers’ produce to the market. Without proper organization at the farmer level, however, the cost of bulking and the inefficiencies of facing the market without any joint action is placing farmers at a disadvantaged position to benefit fully from the sub-sector. In general, farmers complain that the incentives offered by the market currently are not enough to make them invest substantively in their farms. This has led to the current low productivity in their farms – fixing itself as a vicious circle which must be broken for a momentum for growth of the sub-sector to take place. In some product lines such as wine, makuti and madafu for some clusters, this vicious circle is already broken and a vibrancy is already starting to be seen. This is what needs to be build-on, nurtured and replicated across the entire coconut belt. 9.3 Recommendations From our view, one of the major reasons why the coconut sub-sector is not mainstreamed is basically because it has not been visible. While part of this may fall on issues of geo-politics (distance from the centre of power), it is true to say that coconut is not a highly visible sub-sector. This is where efforts of mainstreaming the sector must start. The general public, government, development practitioners and the business community need to know about the sector and its potential, not just in the coastal economy but also at the national level. Some of the areas requiring intervention are quite obvious from information generated by the Survey. It is however important that targeted interventions are guided by further analyses of each of the important value chains – Nuts; Wine; Makuti and even brooms. These analyses will take information generated from this


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Survey as the base and trace each value chain to the market so as to identify the specific leverage points for unblocking potential of the sub-sector. The coconut sub-sector continues to be embroiled and held back by legality questions. From information generated from the Survey, it is clear that the driving force in the sub-sector is the wine and unless there is a clear legality stand point on this product, development of the sub-sector will always be kind of clandestine with no proper structures and business support systems. Clear recognition and legal position would for instance allow farmers to use their wine production ventures openly in seeking credit for investment in the sub-sector. This is an important area that needs to be picked up and conclusively brought to rest. Pubic image will most likely pick up from there and overtime, start judging the coconut wine industry less harshly as it deserves. Research & Development is an important base for development of any sector. Coconut must therefore get included in the national Government agricultural research agenda if the sector is to experience a properly structured growth. Immediate points of research relate to germplasm improvements (collection, conservation, breeding and evaluation); pest and disease control; as well as post-harvets handling and utilization of coconut products. More focused and market-driven research will also be required in product development, testing and introductions in the market. Our hope is that different stakeholders will pick from here and draw the many possible conclusions and intervention areas necessary to move this important sub-sector forward. From a perspective of this survey, it is important that further research is carried out on the situation of copra to understand the causes of the shift from farmers from producing copra at the farm level to other products and whether this situation needs to be reversed or allowed to take root. It is also important for further diagnostics to be made on the question coconut varieties to validate information generated by the survey and establish the reasons why other varieties have not found acceptance among farmers.


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References CDA (2000): Coconut Diagnostic Survey in Kilifi District, Unpublished. CDA (2003): Coast Development Authority Statistical Abstract 2004, Unpublished. CDA (2003): Coast Development Authority Strategic Development Plan 2003 – 2008. Government Printers Eijanatten, C.L.M (1979): Improved productivity of Coconut through fertilization? Coast Agricultural Research Station (CARS). Communication 14, Mtwapa Kenya. Food and Agricultural Organization (2005); FAO Production Year Book 2005 Vol 60; Rome GOK (2003): Economic recovery strategy for wealth and employment creation-2003-2007. Prepared by the Government of Kenya Kinya C. (193) Demonstration to farmers on Management of Coconut land Coast Agricultural Research Station (CARS). Mtwapa Kenya. Krain, E. and P. Kabonge (1992): Kanuni za Kilimo Bora Cha Mnazi; Dar-el salaam University Press Mwangi, W and J Njoba (2000): Coconut Development in Kenya. Paper presented during and International Coconut Workshop for Africa, Mombasa –Kenya Republic of Kenya (1999): Population and Housing Survey 1999 Vol.I. Central Bureau of Statistics, Government Printers, Nairobi. Republic of Kenya (1999): Population and Housing Survey 1999 Vol.VII. Analytical Report on Population Projection. Central Bureau of Statistics, Government Printers, Nairobi. Republic of Kenya (2002): Kilifi District Development Plan 2002 –2007 Ministry of Planning and National Development Republic of Kenya (2002): Kwale District Development Plan 2002 –2007 Ministry of Planning and National Development Republic of Kenya (2002): Lamu District Development Plan 2002 –2007 Ministry of Planning and National Development Republic of Kenya (2002): Malindi District Development Plan 2002 –2007 Ministry of Planning and National Development Republic of Kenya (2002): Mombasa District Development Plan 2002 –2007 Ministry of Planning and National Development Republic of Kenya (2002): Tana River District Development Plan 2002 –2007 Ministry of Planning and National Development Sculling, M. and Mpunami, A (1991): Lethal Yellowing disease of Coconut in Global Perspective UNEP (1998): East Africa Atlas of Coastal Resources 1: Kenya. UNEP, Nairobi, Kenya,

Waijenberg, H.(1993) The Coconut Palm in Coast Province of Kenya, Tree of life and bone of contention. PHD Thesis, Netherlands Warui, N and Gethi (1980): The History of Coconut Growing and Lethal disease in the Coastal districts of Kenya


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Appendix 1

Survey Methodology The study utilized the household information contained in 1999 Kenya National Population and Housing Survey to develop the coconut survey framework of the targeted four districts of Coast province. According to the population survey, the four districts (Kwale , Mombasa, Kilifi and Malindi) had total population of 418,609 households and not all are involved in coconut production since, some are in non-coconut producing areas and others are in urban centers. Based on the knowledge of the area and information collected during the planning meetings with MOA staff at the district level, IDM was able to isolate non – coconut producing areas and derived the percentage of households involved in coconut production in each district and used the same to estimate the number of households targeted in each district (Table A.1). To this end, IDM therefore targeted and administered questionnaire to least 100,885 households, with 37,037 in Kwale, 36,124 in Kilifi, 14,683 in Mombasa and 13,041 in Malindi districts Table A.1. District No of Households 1999 % of farmers household Adjusted farmers H.H in the district

Kwale 92,594 40% 37,037 Mombasa 183,540 8% 14,683 Kilifi 90,311 40% 36,124 Malindi 52,164 25% 13,041 418,609 100,885

A.1 Approach IDM Services used the Ministry of Agriculture structure to undertake the survey exercise and therefore held a series of meeting with ministry officials including Provincial Director of Agriculture (PDA) who expressed support for the exercise. In this regard, conducted two planning meetings in each district with major focus on mapping of the geographical coconut growing areas and isolating areas where there are no coconut trees; training on data collection instruments i.e. the main survey and supplementary questionnaires (Annex 2) and logistics arrangements during the survey. During the training a number of issues were raised which formed the basis for refining the instruments as outlined in section A.3

A.2 Instruments The survey exercise used structured questionnaire which was administered to households in the target survey areas and a supplementary questionnaire which was administered to 5% of the household (every 20th household). Trained enumerators recruited from each village of the survey geographical area and supervised by the MOA Frontline officer with backstopping from IDM District co-ordinators, administered


2

the questionnaires. In total, the number of personnel employed in each district was as indicated in table A.3 below. A.3 Pre Test

A pilot survey was conducted to pre-test the survey instruments (Main Survey and Supplementary questionnaire) with a view to refine the instruments and improve in overall planning process. In this regard IDM recruited three enumerators one from Mombasa - (Kauma location), Kwale - (Ngombeni location) and Kilifi- (Mtwapa location) to pre-test the Draft questionnaires in their respective villages. The rationale of recruiting local enumerators was to increase confidence or avoid any resistance from the farmers. The pre-test took four days and the data from the three sites was analyzed with the major focus on problems encountered in getting information from the respondents (farmers) and the ability to deliver the deliverables stipulated in terms of reference (TOR) which commissioned the study. The Questionnaires were then revised accordingly in line with the findings which include:

a) The enumerators experienced some difficulties in getting information concerning the age of the tree as per the specified brackets, but since it is one of the basic requirements, it was agreed that the exercise would continue as it was. However the first bracket was adjusted to coincide with average year the trees start producing i.e from (0-7) to (0-5) years.

b) Some of the important information which were not captured in the pre-tested Survey questionnaire, was included in the reversed version and include;

i) Nut production (including Madafu) in 2006 ii) The Number of dead coconut trees in the farm

iii) The number of seedlings in the nursery iv) The Number of trees planted in 2006 v) The number of trees cut down in 2006

vi) The number of coconut by variety i.e Short or Tall variety c) In the supplementary Questionnaire, two questions were deleted since they had been captured in the main Survey Questionnaire. The 2 questions are; B.01 – What are the varieties of coconut trees you have? B.05- How many trees did you cut down in total?. In view of this, the Supplementary Questionnaire was also revised to include one question on the problems faced by the farmers in production and marketing process of the product and by-products. d) Another instrument used in the exercise was the Sub-location Maps. For the purpose of presenting information up to the village level using GIS, Sub location Maps were generated and given to the MOA staff (Frontline Offer) to draw the village boundaries in consultation with the village elders.

A.4 Coverage and Personnel

The exercise covered six districts of coast province namely; Kwale, Mombasa, Kilifi, Malindi, Tana River and Lamu districts with major focus on coconut producing areas which translated to the following divisions, locations and sub location in each respective district.


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Table A. 2 Administrative areas covered in the survey District No of Divisions

covered No of Location covered

No of Sub-location covered

Kwale 5 36 75 Mombasa 3 9 22 Kilifi 7 34 97 Malindi 3 17 51 Tana River 2 4 4 Lamu 5 8 8 Total 25 91 257

In order to ensure adequate and effective coverage of the survey exercise, IDM engaged the services of the MOA staff from the district to location level. In addition, IDM recruited four coordinators, one in each district to liaise with MOA District coordinators. In total the number of staff employed in each district is as indicated on the table 3.2 below. Table A.3: Survey Personnel Personnel Kwale Kilifi Malindi Mombasa Total 1 District Coordinator 1 1 1 1 4 2 IDMS Liaison Officer 1 1 1 1 4 3 Division Coordinator 6 7 3 5 21 4 Frontline Officer 37 36 14 5 92 5 Enumerators 136 137 80 48 401 Total 181 182 99 60 522 During the exercise, IDM adopted participatory approaches that yield qualitative information which are to be utilized in the enriching this report.

A.5 Data Processing and Analysis Data processing was managed by a team of trained data input and coding clerks. Upon receiving the questionnaires, the coding clerk undertook the responsibility of verifying the entries and codes for each District, Division, Location and Sub location. He also confirmed the totals of summary reports to facilitate easy entry in the computer. Data processing and analysis started with data cleaning to remove the gaps and ensure consistency. Data entry, processing and analysis was carried out using SPSS statistical software. An important aspect in the data analysis stage was computation of weights for adjusting for any undercounts experienced in the field. As discussed in section 1.4, spot checks were done in the field for every sub-Location to check the extent of undercount. Instructions were that each Location level staff supervising the work of enumerators would do a spot check of to 10 farmers in a row but starting within a randomly selected point in the sub-Location. This process generated information of the number of farmers out of the 10 who were actually counted in the Survey. Table A.4 below presents an outline of the resuts


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obtained in this process which became the numbers used in formulation of adjustment factors for every sub-Location.

Table A-4 Number of households in survey areas by Location; 1999

Division Location Sub-locations # of households

Percent complete

Adjustment

District

1.1 Kinango 1.1.1 Kinango 1. Kingango 1,055 95% 1.05

2. Dumbule 891 90% 1.11

1.1.2 Gandini 1. Kibandaongo 1,010 Covered 1.00

2. Gandini 1,558 70% 1.43

1.1.3 Vigurungani 1. Vigurungani 1,058 Left out 1.00

2. Busa 717 Left out 1.00

1.1.4 Puma 1. Mazola 724 80% 1.25

2. Kifyonzo 1,157 80% 1.25

1.1.5 Ndavaya 1. Ndavaya 722 85% 1.18

2. Gulanze 654 85% 1.18

3. Mwandimu 891 Left out 1.00

1.1.6 Mtaa 1. Mtaa 447 90% 1.11

2. Mabesheni 177 90% 1.11

3. Bofu 796 90% 1.11

1.2 Kubo 1.2.1 Majimboni 1. Shimba Hills 252 8/10 1.25

2. Boyani 242 8/10 1.25

3. Majimboni 254 8/10 1.25

4. Kipambani 135 8/10 1.25

5. Msulwa 168 8/10 1.25

6. Mokobe 176 8/10 1.25

1.2.2 Mwaluvanga 1. Mwaluvanga 229 9/10 1.11

2. Manyatta 315 9/10 1.11

1.2.3 Mkongani 1. Mkomba 848 10/10 1.00

2. Titibe 681 10/10 1.00

3. Mtsamviani 721 10/10 1.00

1.2.4 Mwaluphamba 1. Mlafyeni 1,522 9/10 1.11

2.Kizibe 1,259 9/10 1.11

1.2.5 Mangawani 1. Mangawani 663 10/10 1.00

2. Mbegani 676 10/10 1.00

1.2.6 Lukore 1. Lukore 479 10/10 1.00


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1.3 Matuga 1.3.1 Tiwi 1. Mkoyo 1,460 8/10 1.25

2. Simkumbe 1,804 7/10 1.42

1.3.2 Waa 1. Matuga 1,556 8/8 1.00

2. Kombani 650 7/7 1.00

3. Kitivo 931 6/6 1.00

1.3.3 Ng’ombeni 1. Kiteje 599 5/10 2.00

2. Ng’ombeni 1,751 7/10 1.42

3. Pungu 640 4/10 2.50

1.3.4 Tsimba 1. Kundutsi 1,252 9/10 1.11

2. Mazumalume 779 10/10 1.00

1.3.5 Golini 1. Golini 2,243 9/10 1.11

1.3.6 Mbuguni 1. Mbunguni 760 10/10 1.00

1.4 Msambweni

1.4.1Kingwende/Shiraz

1. Shiraz 937 10/10 1.00

2. Kingwende 771 7/10 1.42

3. Funzi 152 Not done 1.00

1.4.2 Kinondo 1. Kinondo 2,489 10/10 1.00

2. Ganzi 809 10/10 1.00

1.4.3 Pongwe /Kidimu

1. Wasini/Mkwiro 208 9/10 1.11

2. Majoreni 881 9/10 1.11

3. Shimoni 563 9/10 1.11

4. Mzizima 961 9/10 1.11

1.4.4 Diani 1. Gombato 5,146 10/10 1.00

2. Ukunda 6,869 10/10 1.00

3. Bongwe 1,554 10/10 1.00

1.4.5 Msambweni 1. Vingujini 2,053 10/10 1.00

2. Milalani 815 9/10 1.11

1.4.6 Vanga 1. Jego 896 90% 1.11

2. Vanga 684 80% 1.25

3. Kiwegu 732 90% 1.11

1.4.7 Mivumoni 1. Mivumoni 1,680 8/10 1.25

1.4.8 Kikoneni 1. Bumbani 2,717 10/10 1.00

1.4.9 Lunga Lunga 1. Sega 2,365 7/10 1.42

2. Kasemeni 891 10/10 1.00

1.4.10 Mwereni 1. Mwena 2,242 8/8 1.00


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2. Kilimangodo 2,508 10/10 1.00

1.4.11 Dzombo 1. Mrima/Malamba 4,699 9/10 1.11

1.5 Samburu 1.5.1 Taru 1. Taru 395 Left out N/A

2. Dupharu 733 Left out N/A

1.5.2 Kasemeni 1. Mazeras 1,176 9/10 1.11

2. Mwamdudu 250 10/10 1.00

3. Mnyenzeni 1,113 40% 2.5

4. Chigato 561 10/10 1.00

1.6.3 Macknnon Road

1. Macknon rd 844 Left out N/A

2. Kilibasi 273 Left out N/A

1.6.4 Makamini 1. Vinyunduni 702 90% 1.11

2. Makamini 757 90% 1.11

1.6.5 Samburu 1. Matope 1,190 Left out N/A

2. Kinagoni 982 Left out N/A

1.6.6 Chengoni 1. Chengoni 561 Left out N/A

2. Silaloni 433 Left out N/A

3. Maji ya Chumvi 273 Covered 1.00

1.6.7 Mwavumbo 1. Kalalani 1,378 90% 1.11

2. Mwabila 649 90% 1.11

1.6.8 Mwatate 1. Matumbi 546 70% 1.42

2. Mwatate 1,204 70% 1.42

5 37 83 92,594

Kilifi 2.1 Bahari 2.1.1 Roka 1. Roka 816 8/10 1.25

2. Chumani 832 6/10 1.67

2.1.2 Kilifi Township

1. Konjora 1,155 16/18 1.13

2. Sokoni 1,798 10/10 1.00

3. Hospital 3,653 100% 1.00

4. Mnarani 1,642 100% 1.00

2.1.3 Tezo 1. Mtondia/Majaoni 1,542 9/10 1.11

2. Kibarani 1,085 60% 1.67

2.1.4 Matsangoni 1. Matsangoni 452 6/9 1.50

2. Mkongani 533 6/9 1.50

3. Uyombo 585 4/4 1.00

2.1.5 Ngerenya 1. Ngerenya 502 7/10 1.42

2. Ezamoyo 376 90% 1.11


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3. Zowerani 526 6/10 1.67

2.2 Bamba 2.2.1 Ndigiria 1.Mwambani 298 Left out N/A

2. Ndigiria/Mapotea 377 Left out N/A

3. Mihirini 315 Insig’t 1.00

2.2.2 Mitangani 1. Mnagoni 162 Insig’t 1.00

2. Gede 130 Left out N/A

3. Midoina 171 Insig’t 1.00

4. Dangarani 195 Insig’t 1.00

2.2.3 Bamba 1. Mwakwala 483 Insig’t 1.00

2. Paziani 661 Insig’t 1.00

3. Mtsara-wa-Tsatsu 966 Insig’t 1.00

2.2.4 Bandari 1. Mitsemereni 228 Insig’t 1.00

2. Kidemu 334 Insig’t 1.00

3. Mikamini 244 Left out N/A

2.3 Chonyi 2.3.1 Banda ra Salama

1. Pingilikani 710 85% 1.18

2. Mwembe Kati 829 85% 1.18

2.3.2 Chasimba 1. Chasimba 851 85% 1.18

2. Kitsoeni 848 85% 1.18

3. Mwakambi 695 85% 1.18

2.3.3 Ziani 1. Ziani 1,360 85% 1.18

2. Ng’ombeni 688 85% 1.18

2.3.4 Mwarakaya 1. Kizingo 1,419 85% 1.18

2. Mwarakaya 715 85% 1.18

2.4 Ganze 2.4.1 Kauma 1. Magogoni 319 75% 1.33

2. Vinagoni 416 75% 1.33

3. Vyambani 406 75% 1.33

4. Mdangarani 118 75% 1.33

2.4.2 Jaribuni 1. Marere 223 75% 1.33

2. Mwapula 201 75% 1.33

3. Chivara 301 75% 1.33

2.4.3 Palakumi 1. Palakumi/Mugumomiri 558 75% 1.33

2. Vitsapuni/Mariani 454 75% 1.33

2.4.4 Ganze 1. Petanguo 309 75% 1.33

2. Ganze/Tsangalaweni 766 75% 1.33

2.4.5 Dungicha 1. Mweza/Migodomani 203 75% 1.33


8

2. Dungucha/Muhoni 238 75% 1.33

2.5 Kaloleni 2.5.1 Ribe 1. Chauringo 753 85% 1.18

2.5.2 Kambe 1. Mbwaka/Kikomani 1,002 90% 1.11

2. Pangani/Maereni 773 90% 1.11

2.5.3 Rabai 1. Kisurutini/Mwelesi/Sim 1,140 80% 1.25

2. Buni/Chisimani 1,486 80% 1.25

3. Kalingombe/Jimba 1,386 80% 1.25

4. Mazeras/Mugumo Patsa 1,702 80% 1.25

2.5.3 Jibana 1. Kwale 566 9/10 1.11

2. Nyalani 801 9/10 1.11

3. Chilulu 499 5/10 2.00

4. Tsagwa 336 9/10 1.11

2.5.4 Ruruma 1. Mleji 1,195 6/10 1.67

2. Miyuni 999 4/5 1.25

3. Jimba 581 4/5 1.25

2.5.5 Mwawesa 1. Mikahani 437 80% 1.25

2. Mwamutsunga 619 80% 1.25

3. Bwagamoyo 771 80% 1.25

2.5.6 Mariakani 1. Mariakani/Mitangoni 4,326 9/10 1.11

2. Kawala/Kadzonzo 1,335 9/10 1.11

2.5.7 Kaloleni 1. Kaloleni/Vish./Tsaka 2,308 7/10 1.42

2. Chalani/Mihingoni 761 7/10 1.42

3. Mikiriani 647 7/10 1.42

4. Birini/Mwamuleka 459 7/10 1.42

5. Mkomboani 532 7/10 1.42

2.5.8 Kayafungo 1. Miyani 345

2. Kinagoni 285 80% 1.25

3. Murimani 730 80% 1.25

4. Mbalamweini 998 80% 1.25

2.5.9 Mwanamwinga

1. Kithengwani/Mazia 935 9/10 1.11

2. Kibwabwani 499 9/10 1.11

3. Virogoni 820 9/10 1.11

2.5.10 Tsangatsini 1. Tsangatsini 685 Left out N/A

2. Munyenzeni 404 Left out N/A

2.6 Kikambala 2.6.1 Mtwapa 1. Kijipwa 1,518 90% 1.11


9

2. Shimo la Tewa 7,905 75% 1.33

3. Kanamai 2,690 9/10 1.11

4. Kidutani/Nawamba 1,072 80% 1.25

2.6.2 Junju 1. Vipingo 1,778 75% 1.33

2. Junju 1,329 50% 2.00

3. Kuruwitu 1,095 75% 1.33

2.6.3 Takaungu Mavueni

1. Mavueni/Majajani 929 75% 1.33

2. Kiriba/Wangwani 469 75% 1.33

3. Takaungu 949 75% 1.33

4. Mkwajuni/Mkomani 973 75% 1.33

2.7 Vitengeni 2.7.1 Mrima wa Ndege

1. Mrima wa Ndege 202 Left out N/A

2. Dulukiza 210 Left out N/A

3. Milore 323 Left out N/A

2.7.2 Vitengeni 1. Madawani 1,025 90% 1.11

2. Vitengeni 247 90% 1.11

3. Mitsendini 153 90% 1.11

2.7.3 Sokoke 1. Magogoni 570 80% 1.25

2. Pare 312 80% 1.25

3. Nyari 499 80% 1.25

4. Dida 701 80% 1.25

2.7.4 Mwahera 1. Mwahera 391 80% 1.25

2. Kaembeni 447 80% 1.25

3. Dzikunze 353 80% 1.25

4. Ndumnani 368 80% 1.25

7 35 107 90,311

3. Malindi

3.1 Magarini 3.1.1 Gongoni 1. Ngomeni 826 9/10 1.11

2. Shomela 230 left out 1.00

3. gongoni 1,871 8/10 1.25

3.1.2 Magarini 1. Mambrui 1,703 12/15 1.25

2. Marikebuni 913 9/13 1.44

3. Pumwani 649 9/10 1.11

4. Bomani 1,099 10/12 1.20

3.1.3 Fundisa 1. Fundisa 1,021 12/15 1.25

2. Marereni 2,146 12/12 1.00


10

3.2 Malindi 3.2.1 Watamu 1. Watamu 1,642 10/10 1.00

2. Jimba 1,430 8/8 1.00

3. Mbaraka Chembe 1,053 8/8 1.00

4. Chembe Kibaba Muche 547 6/6 1.00

3.2.2 Chakama 1. Makongeni 591 4/4 1.00

2. Matolani 102 1.00

3. Kisiki Cha Wangiriama 256 1.00

3.2.3 Malindi 1. Sabaki 1,900 9/10 1.11

2. Barani 6,109 10/12 1.20

3. Kijiwetanga 1,362 6/6 1.00

4. Shella 7,501 10/10 1.00

5. Central 2,530 9/10 1.11

3.2.4 Langobaya 1. Langobaya 634 8/10 1.25

2. Makobeni 286 9/10 1.11

3. Malanga 705 18/20 1.11

4. Mkondoni 292 9/10 1.11

3.2.5 Gede 1. Mijomboni 588 10/10 1.00

2. Dabaso 1,601 14/15 1.07

3. Mida 665 15/15 1.00

4. Mkenge 415 10/10 1.00

3.2.6 Ganda 1. Ganda 517 8/8 1.00

2. Msabaha 917 14/15 1.07

3. Mere 579 12/12 1.00

3.2.7 Jilore 1. Kakoneni 674 10/10 1.00

2. Jilore/Zian 433 10/10 1.00

3. Girimacha 293 Left out 1.00

3.2.8 Goshi 1. Kakuyuni 512 30/30 1.00

2. Madunguni 362 8/8 1.00

3. Paziani 412 10/10 1.00

4. Malimo 567 10/10 1.00

5. Mongotini 147 3/3 1.00

3.3 Marafa 3.3.1 Adu 1. Ramada 718 Left out 1.00

2. kadzndani 178 Left out 1.00

3. Adu 281 Left out 1.00


11

4. Kamale 297 8/10 1.25

3.3.2 Marafa 1. Bore 697 Insign’t 1.00

2. Mambasa 546 Left out 1.00

3. Madina 756 Insign’t 1.00

3.3.3 Garashi 1. Singwaya 212 85% 1.18

2. Masindeni 293 10/10 1.00

3. Mikuyuni 400 90% 1.11

3.3.4 Bungale 1. Baricho 208 9/10 1.11

2. Gandini 191 10/10 1.00

3. Dakacha 1,103 5/6 1.20

3.3.5 Dagamra 1. Bate 563 4/4 1.00

2. Bura 443 4/4 1.00

3. Kaya 228 5/6 1.20

3 16 56 52,164

6. Mombasa

6.1 Changamwe

6.1.1 Changamwe 1. Changamwe 2,923 100% 1.00

6.1.2 Port Reitz 1. Port Retz 16,765 100% 1.00

6.1.3 Kipevu 1. Kipevu 15,022 100% 1.00

6.1.4 Mikindani 1. Kwa shee 5,685 100% 1.00

2. Birikani 3,952 100% 1.00

6.1.5 Miritini 1. Miritini 4,252 9/10 1.11

2. Jomvu Kuu 4,413 100% 1.00

6.2 Island 6.2.1 Ganjoni 1. Ganjoni 2,616

2. Kizingo 1,343

6.2.2 Railway 1. High Level 714

2. Shimanzi 1,419

6.2.3 Tononoka 1. Tononoka 4,051

2. Bondeni 1,568

6.2.4 Tudor 1. Tudor 4,238

2. Tudor Four 2,984

6.2.5 Majengo 1. Majengo 3,909

2. Mwembe Tayari 1,461

3. Majengo (King’orani) 3,074

6.2.6 Old Town 1. Mji wa Kale 1,736


12

2. Old Town/Makadara 1,864

6.3 Kisauni 6.3.1 Kongowea 1. Kongowea 14,702

2. Maweni 11,634

6.3.2 Kisauni 1. Kisauni 14,599

2. Magogoni 15,384

3. Junda 4,240 9/10 1.11

6.3.3 Bamburi 1. Bamburi 2,569

2. Mwakirunge 932 9/10 1.11

3. Mwembe Legeza 3,977

4. Shanzu 1,841

6.4 Likoni 6.4.1 Likoni 1. Bofu 8,545

2. Timbwani 6,305

3. Likoni 5,083

6.4.2 Mtongwe 1. Mtongwe 5,649

6.4.3 Shika Adabu 1. Vyemani 2,583 9/10 1.11

2. Vijiweni 1,508 9/10 1.11

4 17 35 183,540

Total 32 165 321 469,792


13

ABD-DANIDA/COAST DEVELOPMENT AUTHORITY COCONUT SURVEY – COAST PROVINCE (2007)

SUPPLEMENTARY QUESTIONNAIRE

SECTION A: To be administered to every 20th respondent interviewed in the Survey NO. QUESTIONS ANSWER CATEGORIES CODE A.01 Enumerator name A.02 District A.03 Division A.04 Location A.05 Sub-Location A.06 Village Date of interview [ ]/[ ]/2007

SECTION B: B.01 What are the main

products you get from your coconut trees?

Product Units harvested (in 2006)

Units sold (2006)

Unit selling price

1. Nuts (Numbers) 2. Madafu (numbers) 3. Wine (Bottles) 4. Makuti (Stacks) 5. Brooms (Numbers) 6. Timber (Running Feet) 7. Other

B.02 Have you cut down any of your coconut trees in the last 12 months?

1= Yes 2=No

B.03 If YES, please state why?

1 = To use wood for building/fencing/poles 2 = To sell wood/timber 3 = To clear land for other use 4 = To rid farm old trees 5 = To rid farm of diseased trees 6 = Other (Specify)

B.04 Which are the 3 main constraints you face in production and marketing of coconut products?

Tick only three (3) critical problems Facing the farmer

Indicate the 3 numbers starting with the most critical one

1=High incidence of pest and diseases 2= Lack of quality seeds/seedlings 3= Unfavorable weather condition e.g. drought or heavy rains 4= Unfavorable land tenure system 5= Lack of credit facilities 6=Lack of adequate market outlets 7=Low prices of the products and By-products 8= Poor road infrastructure 9= High transport cost to the markets 10= Lack of labour 11= High rate of theft 12= Others Specify…………………


1

MAIN SURVEY QUESTIONNAIRE ABD – DANIDA & COAST DEVELOPMENT AUTHORITY SERIAL NO………………

COCONUT SURVEY – COAST PROVINCE (2007) DATE…………………….. District ………………………. Location ………………………... Village/Estate ………………………

Division ………………………. Sub-Location ………………….. Enumerator Name ………………… Name of the Farmer Sex Number of coconut trees in farm by age No.

of dead Trees

No. of seedlings in nursery

Size of land in acres

No. of Nut production -2006

Who owns the land?

Who owns the trees?

No. of Trees Cut Down - 2006

No. of Trees Planted - 2006 M F 0 – 5

yrs 6–20 yrs

21–40 yrs

41– 60 yrs

61+ yrs

Total by Variety 1-Self 2- Family 3- Others

1-Self 2-Family 3- Others Total Tall Short

Total Name of supervisor (Loc) ………………………Date cross checked …………. Signature ……………….


2

Appendix 2 List of key GOK and other stakeholders officials who partcipated

PROVINCIAL AGRICULTURAL STAFF

Phoebe A. Odhiambo (Mrs) Provincial Director of Agriculture

Coast Province

MOMBASA DISTRICT MOA STAFF

Name Position Division Telephone

1. Joel M. Gatuthu Div. Crop Dev. Officer Kisauni 0726685744

2. Abdalla M. Ahmed Div. Env & Land Dev. Off Changamwe 0722 654349

3. Dorren C. Njumwa Frontline Ext Officer Likoni 0735 661719

4. Tabitha Odhiambo Frontline Ext Officer Likoni 0733 994678

5. Aminah Mwajambza Div. Crop Dev. Officer Likoni 0734 255397

6. Nassir Mohammed Frontline Ext Officer Kisauni 0722 705276

7. Okoth Kagungu Frontline Ext Officer Changamwe 0733 677385

8. Babu S. M Dist. Ext. Res. Liason Training Mombasa 0722 836373

9. Godson k. Kazungu F.E.O.I Kisauni 0735 661719

10. Felix N. Piko Div. Env. & Land Dev. Officer Kisauni 0722 484800

11. Jacinta Simba Dist. Agricultural Officer Mombasa

MALINDI DISTRICT MOA STAFF

Name Position Division Telephone 1. B. K. Muirithi Div. Agricultural Officer Malindi 0724 237601

2. Bernard Mwangangi Dist/Div Agricultural Officer Malindi 0734 570908

3. Safari Kirao FEW Watamu 0735 712469

4. Daniel Ngome Div. Agricultural & Env. Officer Malindi 0721 257190

5. Irene M. Chingawa FEW Goshi 0725 918825

6. Cosmas N. Makanda FEW Jilore 0722 372848


3

7. Malusi S. S. FEW Libaya 0723 995175

8. G.M Mwavitta Div. GHMO Malindi 0734 436397

9. Ireri Felix Div. Agricultural & Env. Officer Marafa 0720 876189

10. Swaleh Atik FEO Garashi 0720 894945

11. B. Mwangala FEO Ganda Loc. 0726 280841

12. Edward N. Nguma FEO Bungale Loc 0726 755053

13. James K. Ndeto FEO Fundissa Loc.0733 231141

14. Thomas m. Mwalimu FEO Gongoni 0736 276545

15. Haron Mwangoma Div. Crop Dev. Officer Magarani 0722 297586

16. David M. Baya FEO Gede 0721 403378

17. Daniel K. Charo FEO Chakama 0721 645195

KWALE DISTRICT MOA STAFF

Name Position Division Telephone 1. D.T.O Nyandoto DERITO DAO’s Office 0726 608852

2. F. K. Chapsat DAEO Samburu 0720 256003

3. Alice M. Thome DAEO Lunga Lunga 0734 518242

4. Benrad Mainga AAEO Matuga 0721 309119

5. D.D. Murithi DAEO Kinango 0735 484147

6. Kagundu E.N DAEO Kubo 0721 754161

7. Digodziru M. K. Div. Crop Officer Samburu 0720 483526

8. Juma B. kizuka Div. Agric. Dev. Officer Samburu 0723 592195

9. Soud Kombo Div. Env. Land Dev. Off. Msambweni 0721 658427

10. Ndung’u Kibera FEW Samburu 0726 862246

11. John K. Chengo FEW Kubo 0734 864665

12. Victor Mzinga Div. Crop Officer Lunga Lunga 0722561846

13. E. Mwambire Div. Crop Officer Kinango 0721 982151

14. Tunje C. G. Div Env. Land Dev. Off. Kinango 0736 514156

15. Iddi Mwambire SAA Samburu 0724 150105

16. Elizabeth Nzoka Div. GMO Samburu 0720 251334

17. Mballa ARB Div. CDO Matuga 0723 630919

18. Ali saidi Siri FEO TSMBLO Matuga 0736 936183


4

19. M.M. Chombo Div. Agric. Dev. Officer Msambweni 0736 832754

20. W.M. Mwakio Div. Crop Dev. Officer Msambweni 0734 317175

21. Martin Maluki Div. Env. & Land Dev Off Kubo 0734 875892

22. Esther M. Odundo Div Agric & Env Officer Msambweni 0722 276823

23. Goretta M. Maveke GHMO Msambweni 0721 445307

24. Margaret Otiende GHMO Matuga 072- 688225

25. Gideon N. Mutua F.E.O Kinango 0734 957560

26. Peter M. Muindi FEW Lunga Lunga 0727 743208

27. Josephine Mwania FEW Msambweni 0720 307792

28. Nderitu Moses DM & EO Kwale 0721 599525

29. Singi J. DCDO DAO’S Office 0733 625589

30. A.I Kimani DAO Kwale 0720 368636

KILIFI DISTRICT MOA STAFF

Name Position Division Telephone 1. Jane M. Kanamu Dist . Crop Dev Officer Head Quarters 0726 788937

2. Caroline a Akinyi DAEO Kaloleni 0721 654497

3. Nelson C. Mwadima Div. Crop Dev. Officer Chonyi 0720 846219

4. Mwanduni M. A Div. ADO Kikambala 0725 804869

5. Peter M. Igogo DAEO Ganze 0726 393081

6. Mtsanganyiko Ndaa Div. Crop Dev.Officer Vitengenii 0722 551499

7. A. M. Jilani Division Crop Dev. Officer Bahari 0725 368794

8. Opiyo K. James DAEO Bamba 0722 674451

9. Aoko Fredrick DAEO Chonyi 0722459645

10. Ronald Masinde FEO Kauma Ganze 0735 524724

11. Mwandawiro A. M FEO Kambe (Kaloleni) 0735 787629

12. Joseph G. Munga FEO Vitengeni 0736 315424

13. Douglas Kabira FEO Baharini 0723 144327

14. Kalu Kitsao Mwango FEO Matsangoli 0724 804051

15. Peter M. Kogo DAEO Ganze 0726 393081

16. Boniface Mwandogo FEO Bahari 0722 791430


5

17. Nelson Mwadzua Div. Crop Dev Off. Chonyi 0720 846219

18. Ndunda k. Kioko FEO Kaloleni 0733 242090

19. Agnes H. Katana FEO Kaloleni 0734 790397

20. Mary M. Munyazi FEO Kaloleni 0726 318754

21. Elfransiah M. Hare FEO Vitengeni 0723 600419

22. Eunice Mwanyanya FEO Kikambala 0722 448354

23. Pamphil M. Mdighila FEO Vitengeni 0734 963977

24. Juma Nyawa FEO Kaloleni 0723 756223

25. Thomas Dzombo FEO Kaloleni 0726 941061

26. Joseph M. Lewa FEW Chonyi 0722 434398

27. Johnstone A. Dhadho FEO Ribe Loc. 0733 348878

28. Hussen s.O Baya FEO Tsangatsini 0726 820574

29. Nyale K. Nyale FEO Mtsangoni/Yumbo -

30. Boniface M. Karisa FEO Mavueni /Takaungu 0723 859433

31. Peter M. Mburu DAO Kilifdi 0722 872960

LAMU DISTRICT MOA STAFF

Name Position Division Telephone 1. O.K Nyambu Div. Agric. & Env.Officer Amu 0727 048292

2. Elvis M. Mjomba FEO Hindi Loc 0735 744109

3. B.M Chokera FEW Mpeketoni -

4. Elijah M. Rufus Div. Crop Officer Amu 0725 611069

5. S.M Mbeka FEW Mokowe Loc 0727 788264

6. F.K Cheruiyot Div Agric. & Land Dev Off Hindi 0720 283365

7. K.M Mazozo FEW Witu -

8. P.M Njuguna Div. Crop Dev Officer Witu 0735 335544

9. Charles Omondi Div. Env. & Land Dev Off. DAO’s Office 0722 674331

10. Gerald Yawa Div. Crop Dev. Officer Mpeketoni 0735 321353

11. Patrick L. Daiga FEW Dide -

12. S.M Ndaiga DPMEO DAO’s Office 0722 672730

13. Munga P.P. Div. Crop Dev. Off Faza 0723 402599

14. Ali Mwakuphunza DAO Lamu District


6

Tana River District MOA Staff

Name Position Division Telephone 1. Galugalu A. Johana FEO / DAEO Chara -

2. Bakari S. Victor Div. Crop Dev. Officer Garsen 0734 927554

3. John Muteti Kisuna DAEO Kipini 0733 267264

4. Kassin M. Nyambu Div. Env. Land Dev. Off Garsen 0735 636064

5. Jackson C. Mwambao FEO Mwina Unit

6. William N. Garashi Div. Env. & Land Dev. Off Kipini 0721 338050

7. Timothy M. Mwamuye Div. Crop Dev. Officer Kipini 0736 308004

8. Peter M. Igogo DAEO Garsen 0726 393081

9. Anne S. Haruta for DAEO Garsen 0734 151718

10. Martin K. Wekesa DAEO Bura 0735 298958

11. Odari Ngwetuo District Crop Officer Tana River 0735 818216

12. George Mukabi FEO Galole 0736 134378

13. Bunu A. Haji DAO Tana River District

PROVINCIAL ADMINISTRATION STAFF WHO SUPPORTED THE

COCONUT SURVEY PROJECT Ernest Munyi Provincial Commissioner

R. L. Letimalo District Commissioner Mombasa District

B.M Wambua District Commissioner Kilifi District

W.K. Thuku District Commissioner Taita Taveta District

J.R. Matipei District Commissioner Tana River District

N. Ole Lankas District Commissioner Lamu District

M.M. Kangi District Commissioner Kwale District

A.R. Ng’etich (Mrs) District Commissioner Malindi District


7

PARTICIPANTS IN

DRAFT REPORT VALIDATION MEETING HELD ON 2/5/2007 AT CDA

1. W K Mureithi MOA 0734 884962

2. G S Munga KARI 0725 464749

3. Babu S Musa MOA 0722 836373

4. Lilian Hadullo MOA Box 97962 MSA

5. Sam Pande Palm International Box 85784 MSA

6. Zachary Odhiambo CDA/IDM Box 1322 MSA

7. Githende Gachanja IDM 0722 244686

8. Joseph M Njoya Msambweni Dev. Co. Box 87358 MSA

9. Dr. Enoch Mrabu Private Consultancy Box 1202 Kilifi

10. Edward B Kingi Farmer Box 5632 Malindi

11. Luciana Sanzua CDA Box 1322 MSA

12. Jefwa Ngombo GTI Matuga 0722 641884

13. Finyange N Pole KARI, Mtwapa 041 5485842

14. Muli Musinga ABD Consultant Box 49879 NBI

15. Simiyu KD MOA Box 5454 Malindi

16. Dan M Biryah Civic 0727 200111

17. Baetrice M Gambo USAD-KHDP Box 43433 MSA

18. F C Mng’ong’o CDA Box 1322 MSA

19. George Mazuri ABD DANIDA 0724 105520

20. Kennedy Mayende ABD DANIDA 0724 105515

21. Alice Maitha Palm International 0722 480819

22. Morris Mangi ADU Ranching 0723 146353

23. Jim Davies KOCOS K LTD 0722 682018

24. Hubbel M Randu Kilifi co-op Union 0720 806809

25. Baha Nguma CDA Box 1322 MSA

26. Hemed R Mwabudzo CDA Box 1322 MSA

27. Mwango Kazungu CDA 0733 258666

Coconut Census Report.pdf

Documents

coconut production

survey of coconut trees

madafu clusters

wine clusters

makuti clusters

brooms clusters

coconut varieties

mature nuts clusters