LIST OF ACRONYMS . ..... The main factors were spread of people, cattle, towns and roads. Factors that describe natural dairy ..... Average land size (acres). 3. 4.
SDP Collaborative Research Report
A Participatory Rapid Appraisal (PRA) of Farming Systems in Western Kenya Michael Waithaka, Angela Wokabi, Julius Nyangaga, Emily Ouma, Tineke de Wolff, Joseph Biwott, Steven Staal, Meshak Ojowi, Richard Ogidi, Ismael Njarro and Patrick Mudavadi
Report of a PRA of Dairy and Crop Activities in Western Kenya September 2000
Smallholder Dairy (R&D) Project PO Box 30028 Nairobi, Kenya
Ministry of Agriculture and Rural Development Kenya Agricultural Research Institute International Livestock Research Institute Department for International Development-UK (DFID)
This Collaborative Research Report is circulated prior to full peer review to stimulate discussion and comment. Based on that process, its content may be revised
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Acknowledgements Gratitude is expressed to all farmers who participated and contributed to this study. Thanks go the Ministry of Agriculture and Rural Development, KARI and ILRI staff who participated or assisted in carrying out this study. We will always remember Dr. Richard Ogidi (RRC Kisii) who passed away two months after the studies were carried out. He was a considerate, sensitive and dedicated team player. May God rest his soul in peace. This publication is an output from a research project funded by the United Kingdom Department for International Development (DFID) for the benefit of developing countries. The views expressed here are not necessarily those of DFID.
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Table of contents TABLE OF CONTENTS ........................................................................................................ I LIST OF FIGURES ................................................................................................................II LIST OF TABLES ..................................................................................................................II LIST OF ACRONYMS ........................................................................................................ III EXECUTIVE SUMMARY ..................................................................................................... I 1
INTRODUCTION............................................................................................................ 1 1.1 OBJECTIVES ................................................................................................................ 2 1.2 METHODOLOGY .......................................................................................................... 2 1.2.1 Site selection ...................................................................................................... 2 1.2.2 The participants ................................................................................................. 5 1.2.3 Factors appraised .............................................................................................. 6 1.2.4 Tools................................................................................................................... 6
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PRODUCTION SYSTEMS ............................................................................................ 8 2.1 CURRENT PRODUCTION SYSTEMS .............................................................................. 10 2.2 CROP PRODUCTION ................................................................................................... 11 2.3 LIVESTOCK PRODUCTION .......................................................................................... 13 2.3.1 Livestock feeding calendar .............................................................................. 14 2.3.2 Livestock breeding ........................................................................................... 14 2.3.3 Livestock diseases ............................................................................................ 14 2.4 LABOUR PROFILE ...................................................................................................... 15 2.5 FARM AND COMMUNITY RESOURCE MAPS ................................................................. 15 2.6 CONSTRAINTS TO CROP AND LIVESTOCK PRODUCTION .............................................. 16
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MILK MARKETING .................................................................................................... 21 3.1 FORMAL MILK MARKETING ....................................................................................... 21 3.2 INFORMAL MILK MARKETING .................................................................................... 21 3.2.1 Milk bars .......................................................................................................... 22 3.2.2 Mobile milk traders “Hawkers” ...................................................................... 22 3.2.3 Milk wholesalers/distributors .......................................................................... 23 3.3 KENYA DAIRY BOARD .............................................................................................. 25
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SERVICE PROVISION ................................................................................................ 26 4.1 4.2
VETERINARIANS, ANIMAL HEALTH ASSISTANTS AND STOCKISTS ............................ 26 AI SERVICES.............................................................................................................. 26
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CONCLUSIONS ............................................................................................................ 27
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REFERENCES ............................................................................................................... 29
ANNEX 1: MAPPING OF SPATIAL VARIATION IN WESTERN KENYA ................ 30 1. Cattle densities in Western and Nyanza....................................................................... 30 2. Tick borne disease distribution .................................................................................... 30 i
3. Spatial distribution of ethnic groups............................................................................ 30 ANNEX 2 FARM AND COMMUNITY LEVEL RESOURCE MAPS ............................ 35 ANNEX 3 MILK FLOWS TO TOWNS .............................................................................. 43 ANNEX 4. TYPICAL FARM LAYOUTS - CURRENT AND PAST ............................... 44
List of Figures Figure 1 Clustering of similar sub-locations in western and Nyanza provinces........................ 5 Figure 2 Purchase and sales prices (KSh per litre) by site ....................................................... 24 Figure 3 Grade and total cattle densities .................................................................................. 31 Figure 4 Distribution of ticks and reported tick-borne disease cases ...................................... 32 Figure 5 Distribution of ethnic groups in western province .................................................... 33 Figure 6 Distribution of ethnic groups in Nyanza province .................................................... 34 Figure 7 Farm and community resource maps for Kakelo Dudi, Rachuonyo district ............. 35 Figure 8 Farm and community resource maps for Kojwang‟/Katunde, Rachuonyo district ... 36 Figure 9 Farm and community resource maps for Bokiamburi, Nyamira district ................... 37 Figure 10 Farm and community resource maps for Ekerenyo, Nyamira district..................... 38 Figure 11 Farm and community resource maps for Marani, Kisii district............................... 39 Figure 12 Farm and community resource maps for Suneka, Kisii district .............................. 40 Figure 13 Community resource map for Mbihi, Vihiga District ............................................. 41 Figure 14 Community resource map for Kilibwoni, Nandi District ........................................ 42 Figure 15 Milk flow and prices to Nyamira town and Oyugis town ....................................... 43 Figure 16 Milk flow and prices in Bungoma district ............................................................... 44 Figure 17 Typical current farm layout in Suneka, Kisii district .............................................. 45 Figure 18 Typical farm layout in 1980s in Suneka, Kisii district ............................................ 45 Figure 19 Typical current farm layout in Bokiamburi, Nyamira district ................................. 45 Figure 20 Typical farm layout in 1980s in Bokiamburi, Nyamira district .............................. 46 Figure 21 Typical current farm layout in Kojwang/ Katunde, Rachuonyo district ................. 46 Figure 22 Typical farm layout in 1980s in Kojwang/Katunde, Rachuonyo district ................ 46
List of Tables Table 1 Cluster means ................................................................................................................ 4 Table 2 Cluster description ........................................................................................................ 4 Table 3 Historical profile of the livestock systems .................................................................... 9 Table 4 Historical profile of crop farming ............................................................................... 10 Table 5 Characteristics of the production system for a typical household .............................. 12 Table 6 Ranking of constraints to crop and livestock production in declining order of importance........................................................................................................................ 18 Table 7 Cooperatives, year of establishment and current milk intake ..................................... 21 Table 8 Ranking of constraints cited by milk traders/farmers ................................................. 24 Table 9 Prices of livestock inputs ............................................................................................ 26
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List of Acronyms ABS ADC AFC CAIS DFCS ECF FMD GIS GMR HPI ICRAF ILRI JSC KARI KCC KDB LDP MOARD NDDP PPE PRA SDP SSC TBD
American Breeders Service Agricultural development Corporation Agricultural Finance Corporation Central artificial insemination Station dairy farmers cooperative societies East Coast Fever foot and mouth disease Geographical Information Systems Guaranteed Minimum Returns Heifer Project International International Centre for Research in Agroforestry International Livestock Research Institute juice (chewing) sugar cane Kenya Agricultural Research Institute Kenya Co-operative Creameries Kenya Dairy Board Livestock development Project Ministry of Agriculture and Rural Development National Dairy Development Programme precipitation over potential evapo-transpiration Participatory Rural Appraisal Smallholder Dairy Research and Development Project sugar, sugar cane tick-borne diseases
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Executive summary Introduction In the second phase of the Smallholder Dairy Research and Development Project (SDP), as well as continuing work in central Kenya, attention will be given to Western Kenya where lessons learnt from the Central and Coast regions of Kenya will be applied. Western Kenya shares a number of features that present an opportunity for smallholder dairy research and development. The climate is favourable for dairy production and average farm sizes are declining rapidly due to increasing population pressure. This study follows a sequential process Geographic Information Systems (GIS) analysis to identify potential sites, participatory rapid appraisals (PRAs) in the selected sites and characterization surveys. Each step informs the design and analysis of next study, building each time a better knowledge and understanding of smallholder agriculture and dairy systems and the constraints and refining the recommendation domains for the pilot interventions to be selected with farmers, market agents, regulators and policy makers. Objectives The PRAs were organised in the districts at the sub-location level by the project management together with the farmers and various stakeholders to:
Appraise the history and development of agricultural production systems
Identify stakeholders and their interests
Learn various farming activities from spatial and temporal points of view
Identify local needs and constraints to the development of dairy farming
Identify milk market outlets, flow patterns and constraints faced in this area
Identify service providers and the constraints faced in their trade
Methodology The PRA studies in Western Kenya were designed to gain information on broad agricultural activities. PRA sites were selected based on features described by the spatial mapping of factors crucial to dairy farming. The main factors were spread of people, cattle, towns and roads. Factors that describe natural dairy potential: rainfall and humidity, altitude, soils and disease risk were also used. To cover as much of the variation in a district, one sub-location was picked from each of the two most dominant clusters. The research team included staff from ILRI, KARI and the Ministry of Agriculture and Rural Development. At each site the PRAs were held with groups of farmers of different ages and gender. Farmer turnout ranged from 20 to 130 (on average 50). A variety of PRA tools were
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used in a flexible and sequential manner, cross-checking at each stage and improving on reliability and participation of the farmers. Evolution of production systems The earliest and most distinctive development was adjudication and demarcation of land from communal ownership to individual holdings in the 1960s and 70s resulting in smaller land sizes per household that could not allow the keeping of large numbers of Zebu cattle. With title deeds, credit became accessible and was mostly used for the establishment of the new high yielding maize hybrids, which were also encouraged by effective marketing through the National Cereals Board. During this same period, government supported services were strengthened through the provision of agricultural field extension workers, establishment of veterinary clinics, and construction of communal dips. Coffee was established as a cash crop in the 1940s, tea from the 1960s and 80s and sugar in the late 70s and only to the Northern districts. Dairy cattle were introduced only in the early 70s through the national AI and purchase of cows from large dairy farms. In many places Kenya Co-operative creameries (KCC) had established dairy co-operatives in the1960s and milk was marketed through these societies well through the 70s. The 1980s were the beginning of a period of poor fortunes for both crops and livestock. Poor quality seeds, unreliable markets, high production costs and further decline in land sizes reduced crop production. In the 90s the government withdrew support from essential services and initiated their provision through private enterprise. Withdrawal of veterinary services impacted negatively on the growth of grade cattle numbers. Current production systems Despite the conspicuous presence of Zebu cattle, crop husbandry dominates agricultural activities in all areas studied except Nandi where grade cattle are more prominent. A typical household has about three to five Zebu cattle and very few cross or grade cattle. The low number of grade animals kept per household and their low productivity is a result of low feed supply, and poor husbandry methods. The prevalence of the Zebus is associated with the cultural practices (dowry payment and prestige) where the number of cattle per household is more valuable than the quantity of milk produced. Tick borne diseases, especially East Coast Fever, are endemic throughout the area. Prevalence of foot and mouth disease (FMD) and lumpy skin disease is associated with uncontrolled movement of livestock into and out of the districts and the presence of Trypanosomosis to wildlife in the forests.
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There are some indications of intensification in all areas with livestock playing an important role as a source of food, income and manure. Most areas produce their own food with much diversification. All areas indicate high market activities with sale of food and cash crops, milk and also for sourcing inputs such as fertilizer and food. Communities have close relationships between farmers with the ministry of agriculture, churches, self-help groups, tea and coffee factories, and the veterinary department. The communities did not have close relationships with stockists, KARI and the Agricultural Finance Corporation. Constraints to crop and livestock production The constraints that were mentioned by most of the 14 farmers‟ groups are: animal diseases, extension services, animal breeding, roads, crop diseases, cost of inputs, water, land size, capital, marketing, quality of inputs, output prices, soil fertility, human diseases, veterinary services, credit, management of dips and livestock feeds. Milk marketing Most marketing is through the informal sector to nearest urban centre. A few farmers‟ cooperative societies are still operational though beset by management problems and competition from milk hawkers. Constraints to milk marketing include seasonal fluctuations in supply, high cost of capital items, lack of organised marketing, high transportation costs, lack of storage facilities and knowledge on milk handling. Conclusions Over time, farmers have been responsive to incentives as shown by rapid increases (decrease) in production of crops and milk when conditions are conducive (not conducive). Most areas in the region have the potential for intensive livestock production due to favourable climatic conditions. Intensification of dairy production would increase the household labour demand and offer alternative sources of income. Western and Nyanza are generally deficient in milk and flows tend towards the major towns. There are opportunities for growth in milk marketing if there‟s improvement in the organization of traders and encouragement by regulatory bodies to trade in larger volumes under hygienic conditions. For SDP, the issues that will have to be addressed will revolve around the huge milk deficit while there is still potential to increase milk production. Immediate issues would be to
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improve our understanding on why the production gap exists and why farmers do not adopt technologies that would increase milk output.
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1
INTRODUCTION
In the second phase of the Smallholder Dairy Research and Development Project (SDP), as well as continuing work in central Kenya, attention will be given to Western Kenya where lessons learnt from the Central and Coast regions of Kenya will be applied. Western Kenya shares a number of features that present an opportunity for smallholder dairy research and development using results of studies that have been done in the other regions. The climate is favourable for dairy production and average farm sizes are declining rapidly due to increasing population pressure. The sequential process to be followed is the national rapid appraisal with its broad description and diagnosis of western Kenya. This will include subsequent sub-regional reviews for each of the mandate areas under Regional Research Centers (RRC) of the Kenya Agricultural Research Institute (KARI), Geographic Information Systems (GIS) analysis to identify potential sites, participatory rapid appraisals (PRAs) in the selected sites and finally the characterization surveys. Each step informs the design and analysis of next study, building each time a better knowledge and understanding of smallholder agriculture and dairy systems and the constraints to, and opportunities for, their improvement, and refining the recommendation domains for the pilot interventions to be selected with our clients: the producers, the market agents, the regulators and the policy makers. These studies of a new area attempt to get a clear picture of the prevailing production systems and in particular the dairy industry and how they have evolved over time. Milk marketing structure is also appraised since it has been learnt from the previous studies that the development of commercial small-scale dairy industry is a function of milk demand and the product delivery systems. Moreover, the very recent but fast changes in milk marketing as a consequence of a liberalised economy have created opportunities for growth in dairy production and milk outlets that have not been adequately studied in these parts of the country. The initial diagnostic surveys of Western Kenya are expected to provide an avenue through which the current status of the dairy industry can be observed and provide a guide for project entry and implementation. These surveys include spatial analysis of secondary data to target site selection, rapid appraisals and farm characterisation studies that will form a major part of the first months of the project's second phase.
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1.1
Objectives
The PRAs were organised in the districts at the sub-locational level by the project management together with the farmers and various stakeholders to:
Appraise the history and development of agricultural production systems (and in particularly the dairy industry) to the state in which they are today
Identify stakeholders and their interests
Learn various farming activities from spatial and temporal points of view
Identify local needs and constraints to the development of dairy farming
Identify the various milk market outlets and flow patterns while studying constraints faced in providing this essential link between producers and consumers
Identify various other service providers and learn the constraints faced in their product delivery
1.2 Methodology The PRA studies in Western Kenya were designed to gain information on broad agricultural activities and dairy farming set-up. A team of researchers and extension workers met with farmers to discuss the evolution of agricultural production systems, movement of resources, services and general constraints. PRA sites were selected based on features described by the spatial mapping of factors crucial to dairy farming. Gaining preliminary insight into both Western and Nyanza Provinces was initiated by secondary data analysis, which served two goals. In the first place, mapping the spread of people, cattle, towns and roads (Annex 1) provides a very general overview of the kind of areas the study will be dealing with. It also provides an initial attempt at targeting research areas with certain characteristics. To identify specific and promising cattle or dairy areas, the relationship between cattle and spatial indicators were used to map differentiation in dairy potential to focus site selection. 1.2.1 Site selection Earlier studies show that a number of factors strongly influence the production and marketing of milk by smallholders. Apart from the individual household characteristics these are human population growth and densities, climate and rainfall and access to urban centers and services (Kiambu Pilot Survey 1997). Population growth and densities retain a dual relationship with dairy, presenting a market and price incentive for intensified production when numbers are high. At the same time, however, pressure on land and resources may leave farmers with little other choice but to intensify, if they have the means. Closely related to population density is dairy market access. Both the Kiambu study and the Other District Survey (1998) show that more intensified systems are
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mainly found in highly populated areas and close to urban centers, which provide market outlets and good milk prices that act as an incentive to produce. Since the timing of milk delivery and collection is critical, particularly in a smallholder African setting where cooling systems are rarely available, distance to markets and available infrastructure are of prime importance to smallholder farmers. Of course, infrastructure and distances do not only influence market access, they also affect the availability of veterinary and artificial and insemination services. Hence, general accessibility is an important factor where dairy is concerned. Apart from factors related to market access and infrastructure, factors that describe natural dairy potential are rainfall and humidity, altitude, soils and disease risk. Given the use of crossbred animals and associated susceptibility of imported breeds, disease challenge plays an important role in farmer choice of production systems. Tick-borne diseases present a serious threat to the whole dairy system as a number of them cause heavy mortality losses (Staal et.al. 1999). However, due to data limitations, only those factors for which GIS coverages could be made available within a reasonable time span were used in the initial stratification procedure. These turned out to be mean household density and climatic potential per sub location and mean access to the nearest urban center: o Population data were derived from the 1989 census. Since the survey will focus on households and their practices, household densities have been given preference over population densities as an input for patterns of spatial differentiation. o Annual PPE (precipitation over potential evapo-transpiration) proved to be a useful indicator for climate related factors. It combines elevation, rainfall and temperature data into one measure of overall humidity. A PPE value of 1 indicates that the amount of rain falling is similar to the amount lost through evapo-transpiration (crop production can only be carried out when PPE is greater than 0.5) o The layer for access to urban centers was created by ICRAF and estimates the travel time to the nearest urban center (with population density greater than 2,500 persons per square kilometre) in hours. A major setback was that this layer for access to urban centers proved to be insignificant in almost all analyses tried. The layer is quite crude and does not take into account that different areas are serviced by different road types (and thus show tremendous variations in travel
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time). However it proved to be quite useful for a general insight into distance to markets and spatial spread of densely populated areas. Mapping spatial differentiation To facilitate sampling in the seven selected districts (Bungoma, Kakamega, Vihiga, Nandi, Rachuonyo, Kisii and Nyamira) the challenge was to come up with groups of sub-locations that ranked similarly on combinations of these dairy related factors. According to Carter 1996, there are two ways in which to create these spatial stratifications. In the first, unique combinations of specific characteristics or value ranges are identified by mapping each factor involved and physically overlaying each map. In the second, statistical models of the relations between variables are constructed which might involve simple correlations, principle component analysis and cluster analysis (Carter 1996). For this characterisation effort we chose cluster analysis. With only three significant data layers available it seemed the most logical thing to do, since both principle component analysis and simple correlations seek to reduce the initial number of variables to serve as input for clustering. SAS software generated six clusters which portray quite some difference between the various sub-locations. The clusters all range somewhere between the highly urbanized and the remote and sparsely populated (Table 1 and Table 2) Based on these clusters it is possible to voice expectations on the presence and level of dairying, e.g., in sub-locations with high market access, high population densities and resulting low land holdings and a high PPE, chances are considerable that dairy will be present: farmers will be either lured or forced into intensification under these circumstances. Table 1 Cluster means Cluster number. 1 (x1) 2 (x15) 3 (x155) 4 (x106) 5 (x238) 6 (x154)
Mean household density
Mean access
Mean PPE
0 497 53 174 61 75
5 hrs 0.2 hrs 2 hrs 0.6 hrs 0.8 hrs 1 hr
1.07 0.91 0.95 1.07 0.85 1.15
(low) (high) (low) (medium) (low) (low)
(poor) (high) (poor) (good) (reasonable) (reasonable)
(high) (reasonable) (reasonable) (high) (lower) (high)
Table 2 Cluster description Cluster 1 2 3 4 5 6
Description Mt Elgon Highly urbanised sub-locations (municipalities) Remote, sparsely populated areas High potential areas (not too many households, good access and climatic potential) Lower density areas with good access but lower climatic potential Similar to 5 but with very high climatic potential
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To cover as much of the variation in a districts as possible, one sublocation was picked from each of the two most dominant clusters. Thus the PRAs were carried out in Navakholo and Central Kabras in Kakamega, Kilibwoni and Mutwot in Nandi, Nangili and Temberera in Bungoma, Mbihi and Gisambai in Vihiga, Kakelo Dudi and Kojwang Katunde in Rachuonyo, Marani and Suneka in Kisii and Bokiamburi and Ekerenyo in Nyamira. Figure 1 Clustering of similar sub-locations in western and Nyanza provinces
1.2.2 The participants The research team included staff from ILRI, KARI and the Ministry of Agriculture. At each site the PRAs were held with farmers from within the area. The farmers were mixed in age, gender even farmers who did not keep livestock. For each site there were 6 to 5 researchers and the farmer turnout ranged from 20 to 130, but on average 50. The farmers gathered at each pre-arranged location from around 10 am and the discussions went on till around 5 pm.
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The market PRAs were conducted alongside the farmer PRA. In many places it was not very possible to have the milk marketers gather as a group for an effective PRA and the research team conducted semi-structured interviews. This method was also used for the service providers (veterinary, feed stockists, extension personnel from the Ministry, AI service providers both private and Government employees). Although the objectives of the study were covered as arranged it was felt that the time allocated was not adequate for an in-depth PRA using all the appropriate tools. 1.2.3 Factors appraised Diverse PRA tools were to use to gain more insight in: 1. Production systems 2. Condition and circumstances 3. Prioritisation of constraints and opportunities from activities 1 and 2 4. Milk marketing 5. Service provision For a start, the research team split into two groups and carried out trial PRAs in the two sites in Kakamega districts and compared notes on the outcomes. Later, one group handled Vihiga, Bungoma and Nandi districts and the other Kisii, Nyamira and Rachuonyo districts. The two groups met at the end of each week to review progress and prepare a report on information gathered. 1.2.4 Tools The PRAs sought to actively involve farmers in appraisal, analysis and prioritisation of local issues. This was done through listening, capturing local knowledge and encouraging partnership. The interviews with farmers were conducted in groups. A variety of different PRA tools were used in a flexible and sequential manner crosschecking with different methods at each stage to improve on reliability and to involve more people in the planning process. The actual sequence of methods used in each PRA site broadly followed a similar pattern in each site:
Time line and trend analysis, to visualise the historical changes in the area: farmers drew on a manila sheet the typical farm in their areas in the 1970s, 80s, 90s and currently. Emphasis was placed in identifying land size, crops grown and their relative areas as well as livestock types and their numbers (Annex 4, Table 3 and Table 4).
Resource and social map, to identify resources, occupations and means of livelihood: here farmers depicted on manila sheets the flow of inputs into the farm and outputs from the
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farm. They would also show movement within the farm between crops and livestock (Annex 2).
Seasonal analysis, focussing on temporal information pertaining to cropping, land and labour use: using manila paper, farmers would draw the months of a year at the bottom and then indicate with lines or symbols the frequency of occurrence of events for a given crop, e.g., planting, weeding to harvesting. After all crops and livestock were covered a labour profile was drawn depicting monthly requirements through the year (Table 5 and Annex 3).
Scoring and ranking of constraints and opportunities: based on a list of say constraints that the farmers would give, they were asked to compare two at a time and state which was more severe compared to the other. The number of times a constraint would be repeated formed the scored and these were ranked to show order of importance (Table 6 and Table 8).
Visualisation was used to encourage active participation of farmers in the group interviews.
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2 Production Systems The farmers gave an account of various events that have shaped the current scenarios in the areas (Table 3 and Table 4). The earliest most notable event that has impacted greatly on agricultural systems in this area is the adjudication and demarcation of land from communal ownership to individual holdings with title. This took place in the 60s in most places though it was reported as early as 1957 in Mutwot and as late as 1970 in Kilibwoni, both in Nandi district. This resulted in smaller land sizes per household that could not allow the keeping of large numbers of the local Zebu cattle reported as high as 100 per household in the 60s in Kakamega (west Bunyala), though the average appears to have been 30 to 40, especially for the Southern districts. During this same period, government supported services were strengthened through the provision of agricultural field extension workers, establishment of Veterinary clinics, and construction of communal dips. Credit facilities such as guaranteed minimum returns (GMR) loans were made available through Agricultural Finance Corporation (AFC). These were made possible by the use of land title deeds as collateral. It seems that the credit was mostly used in the establishment of crops, especially the newly introduced high yielding maize hybrids which was encouraged by effective marketing through the National Cereals Board. The high grain yield, taste preference and ease with which maize could be produced and processed resulted in diminishing attention in the production of indigenous sorghum and finger millet especially in the 70s and 80s. However, in Rachuonyo, better hybrids of sorghum (Serena and Seredo) were introduced in 1982 and their production has been on the increase. Although coffee as a cash crop appears to have been established much earlier than 1960 (in Marani, farmers mention the existence of their co-operative society in 1940), tea was only introduced in Nandi (Kilibwoni) in 1961 and in Rachuonyo as late as 1980. Sugar, sugarcane (SSC) only came in the late 1970s and only to the Northern districts of Kakamega and Bungoma. These crops competed for land other crops and with livestock putting pressure on large local zebu cattle sheep and goat populations and indirectly encouraging the build up of grade cows. Dairy cattle were introduced only in the early 70s through the national AI and purchase of cows from larger Agricultural development Corporation (ADC) dairy farms in Kitale. Farmers in Kakamega (west Bunyala) and Rachuonyo obtained Napier grass from Kakamega research station at about the same time. The availability of the Government supported services for livestock helped sustain a relatively high grade cattle population during the 1970s (an average three to four per household then as compared to one to two now). However, grade cattle population in Kakamega and Rachuonyo, suddenly dwindled due to what farmers described as diseases outbreaks and inability to feed them. In a few places Kenya Cooperative creameries (KCC) had established dairy co-operatives in the1960s
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and milk was marketed through these societies well through the 70s. However, administrative problems associated with non-payment of loans saw their collapse at the end of this period. The 1980s were the beginning of a period of poor fortunes for both crops and livestock. In Nandi, armyworm infestations and maize smut seriously affected crop yields. Growing ineffectiveness of government services resulted in dairy cattle populations dropping to almost nil in Rachuonyo. Maize production was also affected by poor quality seeds, unreliable market (cereals board was not purchasing farmers' produce), high production costs and further decline in land sizes. In the 90s the government withdrew support from essential services and initiated their provision through private enterprise. Dips were left to farmer committees, Veterinary and AI services were left in the hands of private providers. The floundering efficiency of this new approach has negatively affected agricultural production and farmers have not yet readjusted to these developments. These changes and the continuing subdivision of farmland have impacted negatively on agricultural. Table 3 Historical profile of the livestock systems PERIOD 1960s
1970s
1980s
Event; activity Land adjudication: Nandi (Mutwot,Kilibwoni), Bungoma, Kakamega (west Bunyala, central Kabras) Sahiwals and crosses introduced: Nandi (Kilibwoni) Grade cattle introduced and increased in number till the 80s: Nandi (Kilibwoni) AI started: Kakamega (central Kabras) GMR loans provided for dairy production: Kakamega (central Kabras) Government supported services availed: meat inspection, hides and skins bandas introduced. Dips started: Vihiga (Gisambai) Kakamega and Malava dairy Coops started: Kakamega (central Kabras) Zero-grazing started: Kakamega (central Kabras) Friesian cattle obtained from Kitale ADC: Kakamega (west Bunyala) Napier grass from Kakamega KARI: Kakamega (west Bunyala) Co-operatives increase: Vihiga (Gisambai) AI started: Nandi (Kilibwoni) Grade cattle introduced but many died from TBDs: Rachuonyo (west Karachuonyo) Dairy production started to drop to the lowest level it is today: Rachuonyo (west Karachuonyo) Kakamega and Malava dairy co-operatives collapsed from unpaid loans Grade cattle introduced in Kakamega (central Kabras) and Bungoma Introduction of Ayrshire bulls after construction of cattle dips: Nandi (Kilibwoni) GMR loans stopped: Nandi (Mutwot) Grade cattle introduced but many died from diseases. Number of grade cattle increased due to availability of government supported AI services and organised milk marketing through KCC: Nyamira (Nyamira) Tea introduced: Rachuonyo (W/Karachuonyo) ECF outbreak affects cattle populations: Kakamega (west Bunyala) Dairy production encouraged through Finland supported Rural Dairy Project: Rachuonyo (west Karachuonyo) AI started: Bungoma Seasonal credit introduced: Nandi (Mutwot)
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1990s
Populations of local cattle declined because of their low milk production, low milk prices and small land sizes: Kakamega (central Kabras) Government AI and veterinary services declined: Rachuonyo (west Karachuonyo) Dips handed over to farmer management committees: Kakamega (west Bunyala) Government withdraws from provision of veterinary, AI and extension services. Dips cease to operate: Kakamega (central Kabras)
Table 4 Historical profile of crop farming PERIOD 1960s
1970s
1980s
1990s
Event; activity Land adjudication: Nandi (Mutwot), Bungoma, Kakamega (west Bunyala, central Kabras) Tea planting started: Nandi (Kilibwoni) Coffee 'forced' on farmers, production increases: Rachuonyo (west Karachuonyo) Sorghum varieties grown: local brown ('Andino) and red (Ochuti); production high: Rachuonyo (west Karachuonyo) Credit facilities availed: Nandi (Kilibwoni) Agricultural extension established, readily available: Nandi (Mutwot) Maize production increased with introduction of better hybrids: Nandi (Kilibwoni) Co-operatives increased: Vihiga (Gisambai) Land adjudication: Nandi (Kilibwoni), Rachuonyo (west Karachuonyo) Improved sugarcane (SSC) introduced: Kakamega (west Bunyala) Tea introduced: Kakamega (central Kabras) GMR loans availed, boosted maize production: Kakamega (central Kabras), Nandi (Mutwot) GMR loans stopped in 1978: Nandi (Mutwot) Sugarcane planting, overproduction and marketing problems: Kakamega (central Kabras) West Sugar Company starts buying cane: Kakamega (central Kabras) Seasonal credit introduced: Nandi (Mutwot) Army worm infestation and maize smut: Kakamega (west Bunyala) Sorghum hybrid varieties introduced: Rachuonyo (west Karachuonyo) Number of co-operatives decreased: Vihiga (Gisambai) Slump in coffee prices, crop uprooted and replaced by maize and bananas: Rachuonyo (west Karachuonyo) Cassava and maize diseases increase: Kakamega (west Bunyala)
2.1 Current production systems Despite the obvious presence of indigenous livestock, crop husbandry dominates agricultural activities in all areas studied except Nandi district where dairy is relatively more prominent. Table 5 shows the basic comparisons across the districts studied. Land size per household is low ranging from one to four acres in Kisii, Nyamira, Vihiga and Kakamega. Households in Bungoma, Rachuonyo and Nandi have larger acreage (over 10 acres). Leasing of land is common, especially in Kakamega where it is rented at Kshs 1,000 per acre per year. Typical farms practice mixed farming, combining cash and food crops with livestock production. The main cash crops are coffee, tea, sugar cane for sugar production (SSC) and juice sugar cane for chewing (JSC), and pineapples. The main food crops are maize, beans and sweet potatoes. Others food crops include bananas, cassava, finger - millet, sorghum, groundnuts, vegetables and arrowroots. Surplus food crops are also sold for cash.
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The main livestock types are cattle (pure breeds or grade, local Zebu and crosses), poultry (exotic and local chicken), sheep, goats and donkeys. The livestock are fed on natural pastures, Napier grass, banana stems, sweet potato vines, vegetable waste, sugar cane leaves and tops, maize stover and shrubs. Cattle are mainly grazed though there is increasing confinement by tethering, zero-grazing or semi-grazing systems. Use of concentrates was not high and was said to be common in the dry season when pastures and fodders are in short supply.
2.2 Crop production In Kakamega, Bungoma, Vihiga and Rachuonyo, maize, beans, bananas, and sorghum are the main food crops while sugar sugar cane (SSC) and coffee are the main cash crops. Others are cassava, bambara nuts, ground nuts, simsim, though their production has been on the decline over the years. In Kisii and Nyamira and Vihiga maize, beans, bananas, millet and sorghum are the main food crops while coffee and tea are the main cash crops. In all the places beans are intercropped in maize. On a very low scale in the regions there are sweet potatoes, pumpkin, indigenous vegetables and arrowroots. Juice sugar cane (JSC) is grown in Kisii and Nyamira as a food and as a cash crop. Wheat was mentioned in Nyamira, but on small plots. However, it appears to be a very recent addition in the farms and is gaining popularity. Sorghum and finger millet in the region is gradually being replaced by maize which is less laborious to grow, process and is preferred increasing for consumption. Most farming activities in the region follow the rainfall pattern that is bimodal with the long rains occurring from April to June and the short from August to October. The dry season spreads from November to February. Since the short rains are not heavy and not much happens in this season in many parts. Kakamega has one long rainy season from mid March to August while in Kisii and Nyamira, there is rainfall every month of the year, the least being in January and July, the highest in April and May. In those areas and Vihiga a second crop of maize and beans is grown during the short rains.
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Table 5 Characteristics of the production system for a typical household Sites and Districts Kakamega Navakholo
Average land size (acres)
Nandi
C. Kabras
Kilibwoni
3
4
15
< 10
6
0
Crosses
3
5
Grade cattle
1
5
Bungoma
Mutwot
30
Nangili
Vihiga
Tembelela
Mbihi
Gisambi 0.5 – 0.9
4-5
Rachuonyo
Kisii
Kakelo
Kojwang
Dudi
Katunde
Marani
Nyamira
Suneka
Bokia-
Ekerenyo
mburi
2
5
2
1
2
1
5
5
10
2
5
2
1
3
3
3
1
0
0
2
5
3
2
5
0
2
2
1
1
50
10
50
10
20
5
10
10
0
0
20
10
100
5
8
20
3
5
3
4
Maize Beans Fruits Coffee Tea Millet Sorghum Napier
Maize Beans Cotton Sorghum Cassava Sweet potato Groundnuts Napier
Maize Beans Sugar cane Cotton Ground nuts Napier Fingermillet Sorghum Sweet potatoes Cassava
Maize Beans Coffee Tea Bananas Napier Vegetables
Maize Coffee Tea Banana Sugar cane Finger millet Napier Vegetables Groundnuts Sweet potatoes
Maize Coffee Tea Banana Finger millet Napier Vegetables
Maize Coffee Tea Bananas Napier Vegetables Pineapple Sweet potatoes
Livestock Zebu cattle
Indigenous poultry
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Exotic poultry Shoats
95% of the total inhabitants) no secondary ethnic group was recorded. Most areas proved to be quite consistent especially Kisii and Nyamira. In all other areas, secondary ethnic groups were recorded, with Nandi harboring the largest number of other ethnic groups apart from the predominant Kalenjin.
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Figure 3 Grade and total cattle densities
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Figure 4 Distribution of ticks and reported tick-borne disease cases
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Figure 5 Distribution of ethnic groups in western province
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Figure 6 Distribution of ethnic groups in Nyanza province
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Annex 2 Farm and Community level Resource maps Figure 7 Farm and community resource maps for Kakelo Dudi, Rachuonyo district
OUTPUTS INPUTS
Milk
Awach DFCS
Homestead
labour
cows
Neighbour
Napier grass
Bananas Market
maize manure Cassava Sugar cane tops
Sugar cane
groundnuts
Beans
Trees
AI
Ministry of Agriculture
Church
Schools
Kakelo Dudi community Sowako Support Health dispensary
Group
Water Department
NGOs,(CARE, RED CROSS) Electricity
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Figure 8 Farm and community resource maps for Kojwang’/Katunde, Rachuonyo district
OUTPUTS INPUTS
Homestead
cows
Milk (Ksh 15 per Treetop)
cowshed Firewood
trees
fruits Ksh 25 per gorogoro
maize
Market
manure finger millet Ksh 5 per piece
sweet potatoes
groundnuts Ksh 50 per gorogoro
Beans Ksh 5 per bundle
vegetables
Telecommunications
Agriculture
CARE
Education Church
Provincial Administration Homa Hills
Health
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Veterinary services
Figure 9 Farm and community resource maps for Bokiamburi, Nyamira district
OUTPUTS INPUTS Firewood
Homestead Cows Fertiliser/agro - chemials
Milk (Ksh 20 per Lt)
Manure
Nyangoko coffee factory
Coffee
Neighbours
Napier grass Neighbours
Labour Maize
fertiliser, cash Sanganyi Tea factory
Tea
Local Mkt.
Timber Trees
Stockist AI KARI KTDA Dispensary
Nyambomisi Farmers Cooperative Society
Bokiamburi
Schools
Agricultural Extension Veterinary Department
Provincial Administration Miruka Market
NGOs (HPI)
Water Dept.
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Figure 10 Farm and community resource maps for Ekerenyo, Nyamira district
OUTPUTS
INPUTS Homestead Cows
Maize stover
Milk Ksh 12 per treetop
Hotels
Manure Fertiliser/agro - chemicals Bisembe FCS
Napier (Ksh 50 per headload)
Coffee
Maize Neighbours
Sugar cane fertiliser Sanganyi Tea factory
Tea Local Mkt. Napier grass
Pasture
Timber
Trees
Fertiliser/seeds
AI (Nyamira) Fisheries Water Department KTDA Churches
Schools
Coffee factory
Forestry (Ekerenyo)
Tombe Ikonge
Agricultural Extension
Veterinary Department Provincial Administrati on.
Dispensary Local markets
NGOs
KARI
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Figure 11 Farm and community resource maps for Marani, Kisii district
OUTPUTS
INPUTS Homestead Cows Manure Coffee factory
Coffee
Bananas
Neighbours
fertiliser
KISII Town
Beans
Agro chemicals
Tea
Tea factory Local Mkt.
Maize
Vegetables
Napier
Local healer
Neighbour
Bull LDP
Marani MANGA Marani Bull (Local) Agricultural and Veterinary Department AI Services
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Figure 12 Farm and community resource maps for Suneka, Kisii district INPUTS
OUTPUTS Homestead cow
Vet drugs, dairy feeds
manure Ksh 10/Kg
Iyabe coffee factory
coffee Milk
manure
napier
maize
Seeds and fertiliser
Ksh 20-35/gorogoro
Ksh 60-70/gorogoro
Finger millet
Sugar cane
Ksh 5-7/cane
vegetables
sorghum
Ksh 25-40/gorogoro
groundnuts
trees
Ksh 80-150/charcoal
KARI Dairy cows
Cattle dips
Markets Health services Extension services
COMMUNITY
Roads
Provincial Administration Schools
Veterinary Services
Water
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Local market
Figure 13 Community resource map for Mbihi, Vihiga District
AFC
Provincial Administration Veterinary Department
Education
MBIHI
Ministry of Agriculture
Health
Church
Markets
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Figure 14 Community resource map for Kilibwoni, Nandi District
Water supply
Electricity Provincial Administra tion
Kosirai
Health services
School Communi cation (Roads)
Extension services
Credit Services Veterinary services
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Annex 3 Milk flows to towns Figure 15 Milk flow and prices to Nyamira town and Oyugis town Nyachogochogo (Ksh 13/Lt)
Etono (Ksh 20/Lt)
Marindi 5 Km
1 Km Foot 3 Km
10 Km Gesure (Ksh 20/Lt)
Mabundu (Ksh 20/Lt)
Tinga (Ksh 13/Lt)
Bike
Nyameru (Ksh 20/Lt)
3 Km 3 Km (foot)
Nyamira Town (Ksh 20/Lt)
0.5 Km Foot Nyabite (Ksh 20/Lt)
1 Km 4 Km Nyangoso Kioge
Milk Purchase, sales areas and quantity flows in Kamuma sub-location, Rachuonyo district
Kojwach sub-location
2 Km(Foot/Bike)
East Kamagak location
5-6 Lts Foot 3Km (15Lts)
Kokwanyo location 7Km (14-16Lts)
Matatu/Bike Ksh 30/Lt
Kakelo Dudi subloc.
Matatu/Bike Kamuma sub-location
Kadongo Centre 4 Km 35 Lts
Ringa Market traders
8Km 20-30Lt Oyugis town
Ksh 30-32/Lt Ksh 30-32/Lt
Awach Dairy society
Kisii
Kisumu 7Km (7-10Lts) Kakelo Kamroth sub-location
Mawego Market
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Figure 16 Milk flow and prices in Bungoma district
TURBO Ksh.18 300 lts
SOI KSh. 17 150 lts 9.30 a.m. 60 Km 12 p.m. Fresh KSh 26
KITALE Cherangani Ksh.17 1200lts 5.30 a.m.
110 Km 2.00 p.m. Fresh KSh. 28 Mala Ksh. 30
150 Km 11.30 a.m. Fresh KSh. 32 Mala KSh. 26
BUNGOMA TOWN
30 Km Fresh KSh. 26 Mala KSh. 40 100lts Fresh KSh 30
SIRISIA KSh. 20 9.00 a.m.
KANDUYI KSh. 24 120lts 7.30 a.m.
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Annex 4. Typical farm layouts - current and past Figure 17 Typical current farm layout in Suneka, Kisii district Homestead (1/2 acre) Trees (1/8 acres) Tea (1/4 acre)
Maize/Beans (1 acre)
Ground nuts (1/4 acre)
Sweet potatoes/cassa va (1/8 acre)
Grazing ground (1/4 acre)
Tomatoes (1/8 acre) Sugar cane (1/2 acre) Napier (1/4 acre)
Cattle shed (1/8 acre) Sugar cane (1/2 acre)
Bananas (1/4 acre)
Vegetables (1/4 acre)
Figure 18 Typical farm layout in 1980s in Suneka, Kisii district Homestead (2 acre) Coffee (1.5 acre)
Maize/Beans (4 acre)
Sorghum (0.2 Acre)
Sweet potatoes (1 acre)
Grazing ground (2 acre) Thatch grass (2 Ground acres) nuts (1 acre)
Finger millet (0.5 acre)
Sugar Cane (4.5 acres) Napier (3 acre)
Bananas (2 acre)
Figure 19 Typical current farm layout in Bokiamburi, Nyamira district Homestead (1/4 acre) Tea (1/2 acre)
Maize/Beans (1 acre)
Bananas (1/2 acre)
Sweet potatoes (1/8 acre)
Trees (1/8 acre)
Grazing ground (1/8 acre) Ground nuts (1/8 acre) Finger millet (1/4 acre)
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Coffee (1/4 acre) Sugar cane (1/16 Napier acre) (1/4 acre) Vegetables (1/16 acre)
Figure 20 Typical farm layout in 1980s in Bokiamburi, Nyamira district Homestead (3/4 acre) Trees (1/8 acre) Bananas Maize/Beans (1/4 acre) (1 acre) Sweet potatoes (1/4 acre) Irish potatoes (1/4 acre) Sugar cane(1/4 acre)
Grazing ground (1/2 acre) Pyrethrum (1/2 acre) Ground nuts (1/2 acre)
Coffee (1/2 acre) Tea (1 acre) Napier (1/4 acre)
Vegetables (1/2 acre)
Finger millet (1/2 acre)
Figure 21 Typical current farm layout in Kojwang/ Katunde, Rachuonyo district Homestead (1/2 acre) (inclusive of fruits/trees) Cotton (1 acre)
Maize/Beans (1 acre)
Grazing ground (1/2 acre)
Fallow
Sugar cane
Sorghum Ground (Var: nuts Seredo/Serina/Gopari/Ochuti (1/2 acre) ) (1 Acre) Sweet Tobacco Finger potatoes/cassa (1/2 acre) millet va (1/8 acre) (1/8 acre)
Napier (1/4 acre) Vegetables (1/4 acre)
Figure 22 Typical farm layout in 1980s in Kojwang/Katunde, Rachuonyo district Homestead (1/2 acre) (inclusive of fruits/trees) Cotton (2 acre)
Maize/Beans (1 acre)
Sorghum (Seredo/Serina/Gopari/Och uti) (1 Acre) Sweet potatoes (1/4 acre)
Grazing ground (1/2 acre)
Fallow
Groundnuts (1/2 acre)
Napier (1/4 acre)
Vegetables (1/2 acre)
Finger millet (1/4 acre)
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