MODULE 2: TARGETING OF AGRICULTURAL RESEARCH

National FSA TrainingModule 4: Targeting research to respond to stakeholder needs

Module 4Targeting research to respond to stakeholder needs

Objectives

By the end of this module participants will

1. Understand why targeting is essential in agricultural research.

2. Be able to differentiate between 3 levels of targeting: geographical, social and within a household.

3. Be able to use 3 levels of targeting to set priorities for their own research projects in their respective zones.

Content

4.1 Why do we need to target

4.1.1 Introduction

4.1.2 Concepts used in targeting

4.1.3 Levels of targeting

4.2 Geographical zonation

4.2.1 Agro-ecological zones

4.2.2 Farming systems zones

4.2.3 Agro-economic zones

4.3 Social stratification

4.4 Intra-household diversity

4.4.1 Introduction

4.4.2 Gender

4.5 Selecting an intervention area or target group

Module 3 discussed how you can involve stakeholders in agricultural research and how you can assess their research needs. In this module we will discuss how you can target research to respond to stakeholder needs in different agro-ecological zones, farming systems, household categories, or gender. The resources of targeting and its use for research planning will be elaborated. Concepts and definitions, as well as levels of analysis and criteria for classification are presented. We will use some examples of research targeting in the Lake Zone.

4.1 Why do we need to target

4.1.1Introduction

Tanzania is divided into seven mandate zones for agricultural research. The zones cover vast areas, in which a diversity of farmers live. We need to address questions such as where to conduct on-farm research and for which group of farmers and we need to choose to increase the efficiency of research. This is also necessary due to dwindling funds for research. At the same time, all agricultural research conducted in Tanzania should be client-oriented. This means that research has to respond to the needs of clients, which are farmers (primary stakeholders) or their representatives (secondary stakeholders like NGOs, or farmer unions). However, while we plan and implement agricultural research we cannot consider farmers to be a homogeneous undifferentiated mass of people. Every farmer has his or her own particular goal and works under different circumstances from his or her neighbour. The ultimate goal of agricultural research is to identify technologies which farmers will implement. Research cannot identify recommendations for every individual farmer. On the other hand, research has to avoid developing blanket recommendations for the whole of Tanzania, or the whole zone. We have to strike a balance between these two options to make research efforts as cost-effective and efficient as possible to serve a maximum of small-scale farmers with the available research resources.

Targeting is the procedure where we identify and select areas and farmer categories on which research should focus. Targeting is not a goal in itself. Targeting is a tool/procedure used to make research more efficient by aiming research efforts at the relevant clients. Targeting research efforts is therefore as essential as priority setting of researchable issues.

Targeting is done to divide a very heterogeneous farming population into more homogeneous subgroups on the basis of factors that determine the farming systems or livelihood systems. It is not done for its own sake, but in order to identify differences between, and highlight similarities within groups which are significant with regard to the development of agricultural innovations. Targeting is not a one-time exercise conducted at the beginning of the research process, but done throughout on-farm research with various purposes. Since the concept of target groups is used throughout the research process, the way groups are defined may change according to the task at hand. Homogeneity must always be determined relative to the purpose of the intervention. Table 4.1, adapted from Tripp, shows how the concept of targeting farmers is used at different stages in the research process.

Table 4.1Targeting throughout a research activity

Research stagePurpose of targeting

Diagnosis of farmer circumstancesDefine groups with similar circumstances

Identification of priority problemsSpecify which farmers have the same production constraints

Selection and testing of possible solutionsIdentify possible solutions appropriate for specific farmer groups and test them with group members

Develop recommendationsDefine flexible recommendations to address needs and circumstances of different farmer groups

Targeting helps to:

determine in the analysis of demand for innovations whether the significance of the target group justifies the development of an innovation;

analyse whether a potential innovation matches with the requirements of the target groups during the identification of options;

ex-ante analysis of the different target groups will also provide a picture on the degree of adoptability of the technology to be tested;

select appropriate farmers belonging to a relevant target group for participation in the farmer research groups or in on-farm research;

evaluate whether the developed innovation was adopted by its target group or how it was adapted by the target group to its specific conditions.

4.1.2Concepts used in targeting

The following terms are frequently used in literature on targeting:

Recommendation domain: (CIMMYT) A group of roughly homogeneous farmers with similar circumstances for whom we can make more or less the same recommendation. Recommendation domains may be defined in terms of both natural factors (e.g. rainfall) and economic factors (e.g. farm size). (Byerlee et al. in Mettrick, 1993). A domain is a group of farmers rather than a geographical area. Hence it is not be confused with an agro-ecological zone. The formation of recommendation domains is a gradual and fluid process. They are defined in a preliminary fashion in the early stages of diagnosis and take on their final form when recommendations are ready for dissemination. (Mettrick, 1993)

Target group: a rather homogeneous group of farmers or farming households regarding their problems and potentials, considering agro-ecological as well as socio-economic factors.

Agro-ecological zone: zones defined by the physical and biological characteristics of geographical area.

Farming system zone: a geographical area where a certain farming system is prevailing. This system is a result of an interaction between cultural, agro-biological and socio-economic factors and the households priorities and resource endowments.

Household category: a group of households that has the same value of a certain characteristic, e.g. resource base of the household gives the categories wealthy, average and poor. Regarding the sex of the head of the household we distinguish female headed and male headed households.

Household: a group of people living together sharing family or marital ties and sharing the same stove for cooking. Individual members of a household, depending on their gender, age and relation to the head of the household, differ in access to assets (tangible such as resources and stores) and have different capabilities.

Intra-household differences: a household is not a homogeneous group of people, but rather a complex system in which tasks, resources and benefits are not equally shared among its members. Gender specific constraints and opportunities for male and female members of a household will determine in how far they participate in and share benefits from research. Gender: this refers to those aspects of men and women that have been socially determined. It refers to the roles, responsibilities, characteristics, attitudes and beliefs about/towards women and men. These roles vary within and between cultures. Sex refers to the biological state of being male or female. In research we use the term "sex" only to disaggregate data on the basis of responses from males and females.4.1.3Levels of targeting

Before planning interventions (e.g. research) the scale of analysis or level of aggregation should be well defined. Lower level scales aggregate or merge into a higher level scale, thus reducing precision but increasing the extent. For example, two farming systems may merge into one agro-ecological zone or three household categories can be defined within one farming system.

The scale of analysis or level of aggregation defines the extent of the proposed intervention and depends on goals and availability of data and information. For example, interventions, such as import subsidies or wages of civil servants are relevant at the national level and not at the international level; blanket fertiliser recommendations are relevant at the agro-ecological zone and not at national level; recommended crop varieties are relevant at the farming system zone and not at agro-ecological zone level etc.

Traditionally, the Farming Systems Approach has given strong emphasis to targeting of recommendation domains. In practice this has often led to agro-ecological zonation, which is relatively time and development neutral. Later, during the 1980s, more emphasis was given to farming system zonation, elaboration of farmer typologies, identification of producer groups, and gender differentials.In general we distinguish three different levels of targeting. These will be discussed in 4.2, 4.3 and 4.4:

1. Geographical zonation: In general geographical zonation combines geographic information with either physical, biological or socio-economic data. A few examples are:

a. If the zonation uses just physical and biological characteristics, and qualities of the various natural land units: agro-ecological zonation

b. If zones are dynamic units that are uniform with respect to the farming conditions that determine crop and animal production: farming system zones

c. If zones use income distribution patterns,

2. Social stratification

3. Intra-household diversity

Criteria to distinguish uniform clusters differ between targets should be defined from case to case, depending on the goals of targeting and the local circumstances. Box 6.1 gives an example of the targeting process in the Lake Zone.

Box 4.1

Targeting process in the Lake Zone

4.2Geographical zonation

4.2.1Agro-ecological zones

The overall goal of an efficient research system is to develop location specific recommendations that are socially and economically acceptable to farmers and can be reproduced over a larger target area. A prerequisite for this would be some form of focused zoning of the target area. Agro-ecological or indicative zoning (Bagarama, 1995; Enserink and Kaitaba, 1996; Sombroek and Eger, 1997) divides land on the basis of physical and biological characteristics, and qualities of the various natural land units (climate, soils, terrain forms, land cover and to a large extent its water resources). An agro-ecological zonation defines zones which are uniform with respect to physical and biological conditions that determine crop and animal production. Research carried out within the zone is relevant to all geographical parts of the zone. Examples of criteria for agro-ecological zonation are:

Climate

Rainfall (total annual amount, distribution, duration, incidence of drought)

Parent material

Soils (nutrient supply, texture, structure, drainage, slope, depth, salinity)

Altitude

Landscape

Vegetation

Biology (pest, disease, weed incidence)

4.2.2Farming system zones

The objective of farming system zonation is to define dynamic units that are uniform with respect to the farming conditions that determine crop and animal production. Research carried out within the farming system is relevant to all farms in this farming system zone. Examples of criteria for farming system zonation are:

Agro-ecological features

Demographic features (population density, ethnic composition, mobility)

Household and farm characteristics (household size and composition, access to resources, acreage, livestock ownership)

Livestock herd size and composition

Type of cultivation, major food and cash crops, cultivation practices

Livestock management practices

Energy use and production

Off-farm activities

Constraints and opportunities

The identification of these zones needs data from primary and secondary stakeholders. The following steps are usually part of the zonation exercise:

Compilation of existing data

Field visits to major farming systems

Observations on farming system parameters

Interviews with farmers and other stakeholders

Checking boundaries of farming systems by using a GPS

Cartography and description of farming systems

For example, the Lake Zone has been sub-divided into 13 Farming System Zones (defined as agro-ecological zones with a particular dominant farming system) (Enserink and Kaitaba, 1996). Out of these, eight were given priority for research interventions. Although not perfect yet, zoning has helped to reduce research time and other costs e.g. transport, considerably. Clustering of all research in farmer research groups (FRGS) has helped to foster closer supervision and better management of trials. It has also helped strengthen field-level linkages with farmers, local extension agents and commodity researchers (see Box 4.2). See also Annex 2 for an example of FSZ in the Northern Zone and how they are defined.

Box 4.2

Farming Systems Zonation in the Lake Zone

Source: Enserink and Kaitaba, 1996

4.2.3Agro-economic zones

Rural livelihoods are becoming increasingly diversified as far as their economic opportunities are concerned. An increasing numbers of members of rural households find jobs outside the agricultural sector; an increasing number of different crops is grown; market oriented cash crop production is increasing with increased marketing of traditional food crops; traditional activities such as livestock keeping are becoming increasingly commercial. A major obstacle to livelihood development of poor households in developing countries is access to markets for their products and cash. Market opportunities and competitiveness to a large extend influence household decision-making. To assist poor rural households in detecting new opportunities a Market Opportunity Analysis (MOAS) may be useful (Meerendonk et al., 1997). This analysis assesses the feasibility of a product or activity for a specific market for a specific producer group. What may be attractive to one household or region may be unattractive to another. Using data that the MOAS creates we can create a map of potential economic opportunities for different zones. Research can than assist households in optimising resources used.

Examples of information required for developing such maps are:

Population density

Consumption patterns and purchasing power

Infrastructure

Access to markets

Farm gate prices

Market prices

Household income and expenditure patterns

Even though information in Tanzania is available on demography, natural environment, agronomy, etc., household income and expenditure data are not abundant. In such conditions research can use estimates or indicators for economic potential as they were used in the Lake Zone study in 1997 (Meerendonk et al., 1997). These could be:

Population density: An indicator of agricultural and economic potential of a region as human beings are the producers and consumers of goods and services, consequently economic activity will concentrate in those areas where most people are located.

Purchasing power: An indicator of a region's economic potential due to it's impact on the marketability of products and services as its impact on opportunities for investment and accumulation.The resulting agro-economic zones can than be used to target research on specific opportunities that were identified (see Box 4.3).

Box 4.3

Agro-economic zones in the Lake Zone of Tanzania

Source: Meerendonk et al., 1997

4.3Social stratificationRural societies are not homogeneous. They are composed of different household categories with specific constraints and contrasting interests. Targeting is a tool to identify groups of households with similar socio-economic and cultural features. The objective of household categorisation is to define household categories that are uniform with respect to the goals and availability of resources that determine crop and animal production. Research carried out with one household category is relevant to all households belonging to that category. In the Lake Zone, for example, full-time small-scale farmers are the target group of the institute. This implies that absentee landlords in Kagera Region (land-owners who do not live on their land but other people take care of their land) are not considered a target group for Lake Zone research (see Box 4.2).

Social stratification enables research to (KIT et. al., forthcoming: 71):

Assess the significance of household categories and select target categories for research and extension.

Discuss constraints and potential solutions with farmers who have similar socio-economic and cultural conditions.

Analyse whether a potential innovation matches with the requirements of the target category.

Determine the potential adoptability of an innovation.

Select farmers belonging to relevant target categories for participation in farmer research groups and participatory technology testing.

Evaluate test results with farmers of a specific category.

Verify adoption of a recommendation among farmers belonging to a target household category.Households adopt technologies depending on their resources, management levels, knowledge etc. Obvious examples are cattle ownership and access to fertile land. Less obvious are the various management levels e.g. soil fertility management. Knowledge levels equally determine to which category a farm household belongs. Examples of criteria for household categorisation are:

Age, ethnic origin and religion

Household size and composition

Consumers and labour force

Farm size and quality of the land (soil fertility, irrigation etc.)

Livestock, herd size

Availability of animal traction and means of mechanisation

Land use intensity (crops, animals, practices, yields)

Cropping patterns, herd composition

Off-farm activities

Production and income

Goals and priorities

Tools that have proven useful in the classification of households are wealth ranking (see Module 7) and a formal survey. Steps could be as follows:

Discuss criteria for household differentiation with key-informants. Start with indicators of wealth or living standard and discuss the causes of differences between households.

Discuss and describe the various categories with the key-informants in order to achieve consensus about the number of categories in the community and their designation (e.g. low-resource and high-resource households).

Assess the proportional importance of each category by using a (complete) list of households in the village. Take a random sample of households and ask the (group of) key-informants to categorise each household.

Interview farmers per category on household composition, means of production, productive activities, productive results and key constraints. Use appropriate interview techniques and tools to involve all group members in the discussions, such as matrix ranking and pairwise comparison of constraints (see Module 7).

Discuss with farmers potential solutions to their constraints and specific activities, as well as the key-actors, to test or apply these potential solutions.

What has not yet been taken into account in the above mentioned classifications, is the management aspect: how do farmer manage their resources for agricultural production. This aspect is the most difficult to capture, but it is as important as the access to and control over resources. In the Lake Zone, during a PRA on integrated soil fertility management, farmers were classified according to the way they managed the fertility of their soils (Kajiru et al, 1996). In general, there was a close relation between the access to resources and the degree of management (the more resources, the better the management of the soil fertility). However, in one village it was found that a group of resource wealthy farmers were bad managers because of lack of education, as was explained by the villagers.

Box 4.4

Farmer categorisation in the Lake Zone of Tanzania

4.4Intra-household diversity

4.4.1Introduction

The household is a co-residential unit, comprising persons who are usually related by family or marital ties. It is sometimes referred to as a group of people who share the same cooking stove. It is also a socially recognised unit and a productive unit. Although a household is referred to as a unit, it is by no means a homogeneous unit. Within a household individuals have different positions based on gender, age and inter-generational relations which are reflected in e.g. patterns of authority, division and control of labour, and access to and control over resources and benefits. Household members have shared, as well as different (and sometimes opposing) interests. The roles of household members other than the male head of the household are frequently ignored. Adult women, junior men and women, and children bring specific skills, resources and priorities to farm production. To ignore them is to ignore half or more of the system in which decisions about farming are made.

While doing research it is essential to take these intra-household dynamics into account. When addressing the wrong intra-household target group or excluding an intra-household target group, this leads to incomplete identification of researchable needs, priority setting, inadequate training of farmers in new technologies and a blocked dissemination of the innovation. There are ample examples that illustrate this point: training male heads of households in oxen-weeding whereas normally the work is done by young men (age criterion); improving varieties of crops grown by women without involving them in the assessment of preferred characteristics of the varieties (gender). See also Box 4.5.

Box 4.5Influence of gender on adoption of maize technologies in Mbeya Region

Source: Mwangi et al., 1999: 65

The major factors that determine ones position within a household (and thus ones interests but also the impact of new technologies for a person) are gender and age/inter-generational relations. In many households more than 1 or 2 generations live together: husband/wife, their children and their grandchildren. Often, the father/male head is the main decision-maker whereas children and grandchildren carry out the work. An activity profile as used in the Harvard Analytical Framework (see Module 7) provides information which household members should be included in on-farm experimentation, in diagnostics, in farmers assessments etc. During a PRA in Kahama District, Lake Zone, it was found that young men did not want to invest all their money/earnings in the purchase of cattle. They wanted to have cash money throughout the year and therefore were much more interested in investing their money in income-generating activities like small shops. Their fathers still preferred to invest their income only in cattle (Kajiru et al., 1997).4.4.2Gender

The position and opportunities for women and men in a society is not so much the result of biological differences but of differences that have been socially determined. This is what is meant in the word gender. Gender refers to those aspects of women and men that have been socially determined. It is defined as a socio-cultural construct that refers to the roles, responsibilities, characteristics, attitudes and beliefs about/towards women and men. These roles are defined, supported and reinforced by societal structures and institutions. The process of socialisation takes place in a specific society, in a specific time and place. As a result of gender characteristics, women and men have different experiences in life, different perspectives, priorities and opportunities. Sex refers to the biological state of being male or female.

The socialisation process of girls or boys, men or women, in any society creates specific gender roles. This is not the same as sex roles. An example of a sex role is the capacity of women to give birth. This is a biological role that men cannot fill. In contrast gender roles are roles which society assigns to women or men. For instance, in some parts of the world, women are given responsibility for tasks such as cooking, preserving food or storing seed. These tasks are not done by women all around the world. Men, on the other hand, are given social roles such as hunting or taking care of livestock but, again, these gender roles are not universal. Our society and biology both have an impact on what we can do or should do as men or women. The difference is that biology does not change, society does. Therefore our sex roles may remain the same but our gender roles can and do change. Gender roles are learned and vary within and between cultures. Gender roles can change over time due to changes in culture, education, technology, economic conditions or a sudden crisis like war or famine.

Gender roles define what a society considers to be appropriate for a man or a woman, reflecting a division of labour (Joldersma and Musyoki, 1999; CCIC et al., 1991; Moser et al., 1998):

Productive role: Work that is done by both men and women for pay in cash or kind. This includes all agricultural activities such as planting, weeding, harvesting, grazing animals and cutting grass, trading such as selling cassava cakes, employment or self-employment, and services.

Reproductive role: Work that is required to maintain and reproduce the labour force, i.e. the household. This includes child bearing, cooking, collecting firewood, collecting water, repairing the house, looking after children or elder people, attending the health clinic.

Community roles: Voluntary activities that contribute to the welfare, development or political organisation of the community such as participation in groups, funerals, meetings.

The above is our basis to improve research targeting within a household. To do so we use a concept that is called gender analysis. Gender analysis starts with the recognition that the household is not a homogeneous group of people, but rather a complex system in which tasks, resources and benefits are not equally shared among its members. Gender analysis is an organised approach (qualitative and quantitative) to understand how women and men, female and male household members, relate to each other in terms of roles and responsibilities, access and control over resources and benefits (see Box 4.6 for an example), their needs and priorities. Gender analysis is an instrument to target research and development with the objective to improve the efficiency and effectiveness of research, and to create a more equal development of women and men in society.

Box 4.6

Access to and control over land in Tanzania

Source: Country Gender Profile, www.worldbank.org/gender, 1999

Gender analysis aims to:

Identify the major gender differentials of the target groups in a given community or field of activity (e.g. agriculture, forestry, water)

Identify gender specific constraints and opportunities for female and male members of the household or community to participate in and share benefits from research and extension activities (see Box 4.7)

Identify possible strategies or measures to overcome the constraints.

Recognise different effects or impact of research and extension activities on female and male members of the target group.

Box 4.7

Effect of gender differentials on afforestation in Shinyanga Region

Source: Otsyina and Rosenberg, 1999

Gender analysis is relevant in all phases of agricultural research and development, be it planning, experimentation, evaluation, dissemination, or adoption/impact assessment. Major tools for analysing gender relations such as the Harvard Analytical Framework and the Gender Analysis Matrix will be discussed in Module 7.

4.5Selecting an intervention area or target group

In addition to the criteria given in the previous chapters, there are a number of logistical criteria that should be considered when selecting intervention zones:

1. Distance: the nearest by intervention area should be chosen to reduce transport costs, but the intervention area should still represent the further away areas.

2. Accessibility: the roads to the intervention area should be all-weather roads in order to allow scientists to visit the farmers all year round. Areas not accessible by cars should be avoided.

3. Farmer representation: priority should be given to zones where NGOs or other organisations represent (groups of) farmers. These organisations increase the change of adoption and may co-fund research. Linkage with extension for day to day monitoring of trials with farmers is essential. Presence of qualified extension staff is therefore a precondition for selecting an intervention area.

4. Cluster: research intervention areas should be clustered as much as possible, not only to reduce costs but also to create interdisciplinary. Researchers of different disciplines will be working with the same farmers leading to jointly executed programmes.Once farming systems zones and target groups have been identified in a particular area this should be used to prioritise zones and groups for research interventions. There are no objective criteria for assessing the importance of a particular system or a particular group. This means that research needs to develop a policy that explicitly states criteria for selection of priority farming systems and priority target groups in a given mandate area. This policy is related to the objectives of a particular research institute. If for example the objective is poverty alleviation, stakeholders and research should agree on the research policy and as a consequence at which farming systems and target groups the research efforts should be targeted. Farming systems zonation often results in the production of a map. However, research should use this map effectively as a planning tool.

Once target areas and target groups have been research will then be carried out in a limited number of sites, representing a zone, system or group. To increase research impact, efforts should be made to diffuse the available results to the relevant population. Criteria for scaling up have to be considered before starting a research activity or intervention (see also Module 6 and Module 17).

Once zones, systems and groups are identified for research management purposes, research and extension become familiar with them through their use and application in planning. It should be avoided to change the target definitions often. Nevertheless, all systems and groups are dynamic and change over time. Continuous data collection is necessary to fine-tune the target definitions and adjust for changes.

The above described concept of recommendation domains or targeting is useful where technologies are tailored for specific client groups. However, if researchers are developing different technology options and offering a range of potential technologies then the precise definition of the recommendation domain/target group becomes less important. Nonetheless, researchers still have to ensure that the basket of technologies which is offered is appropriate to the circumstances of the farmers whom they are trying to reach. Recommendation domains are used solely for more efficient research targeting or recommendations. Short cuts have been developed that do not require a very precise definition of recommendation domains:

Farmer Research Groups (by including different farmer (see Module 5)

Flexible and conditional formulation of recommendations (see Module 14)

Exercises

Exercise 1:

Identify research topics that are relevant at the following levels of analysis:

Level of analysisRelevant research topics

National

Agro-ecological zone

Farming system zone

Household category

Intra-household groups

Exercise 2:

Discuss criteria for agro-ecological zonation of your research zone and prepare a preliminary map indicating zones and their boundaries.

Exercise 3:

Discuss criteria for farming system zonation of your research zone and prepare a preliminary map indicating farming systems and their boundaries.

Exercise 4:

Do you distinguish different household categories within your zone in your own work? List these household categories for each discipline in your group.

Exercise 5:

1. Analyse to what extent your latest released technology has influenced the gender roles within the household. What are the implications for further research and development?

2. Are there specific technologies, or topics of research that are of interest to your research institute which require attention to gender analysis?

3. What is the justification for gender analysis in the topics or areas that you have specified?

4. Based on this analysis are there topics or issues of relatively low or high priority with respect to carrying out gender analysis?

Exercise 6:

Combine the results of exercises 2, 3, 4 and 5. Link these results to the objectives of research in your respective zone. What are priority zones and groups for research interventions?

References

FSR (1990). Diagnostic survey of Bukoba District. Formal Survey. Tanzania/Netherlands Farming Systems Research Project, lake Zone. Working paper no.5. ARI Maruku, Bukoba. Royal Tropical Institute, Amsterdam, The Netherlands.

Joldersma, Rita and Samule Musyoki (1999). Gender Analysis Tools: user guide for application in agricultural research and extension. Draft. 27 pp.

KIT, IER, DRD (forthcoming). A Guide to Demand-Driven Agricultural Research: the Client Oriented Research Management Approach. Part 1

Meerendonk, J.C.M., J.M. Mafuru and J. Nkuba (1997). Agro-economic zones and market opportunities for livelihoods in the Lake Zone, Tanzania. Royal Tropical Institute, Amsterdam, The Netherlands.

Mettrick, H. (1993). Development oriented research in agriculture: an ICRA textbook. The International Centre for development-oriented Research in Agriculture, Wageningen, The Netherlands.

Moser, Caroline O.N., Annika Tornqvist and Bernice van Bronkhorst (1998). Mainstreaming Gender and Development in the World Bank: progress and recommendations. Environmentally and socially sustainable development series. The World Bank, Washington, U.S.A. 38 pp.

Mwangi, Wilfred, Hugo Verkuijl and Shekania Bisanda (1999). Gender differentials in adoption of improved maize production technologies in Mbeya Region of the southern highlands of Tanzania. In: EASSRR, Vol. XV, No.2, June 1999: 66-77.

Otsyina, Joyce A. and Diana Rosenberg (1999). Rural Development and Women: What are the best approaches to communicating information? In: Gender and Development Vol.7, No.2, July 1999: 45-55.

Overholt, Catherine, Mary B. Anderson, Kathleen Cloud and James E. Austin (1985). A Case Book: Gender roles in development projects. Kumarian Press.

Schaap, Mirjam (1998). Reference Guide for Gender Responsiveness in Project-Cycle Management, with specific reference to FAO Trust Fund Projects. Working Paper 1/98, FAO Representation Nepal.

Further reading

Development Assistance Committee (1998). DAC Source Book on Concepts and Approaches linked to Gender Equality. OECD, Paris. 80 pp.

OECD Development Assistance Committee (1998). DAC Source Book on Concepts and Approaches Linked to Gender Equality. OECD/OCDE, Paris. 80 pp.

Web resources

BRIDGE (briefing on development and gender): www.ids.ac.uk/bridgeFAO Socioeconomic and Gender Analysis Programme (SEAGA): www.fao.orgSouthern African Development Community (SADC) - Gender Website: www.sadc.int/genderAnnex 1:Case study from Kagera Region and ARI- Maruku

Source: de Steenhuijsen Piters and Ndege, 1996

1. More about agro-ecological zonation

One of the elements of the ARI Maruku approach is that we try to adapt our research to the specific conditions of production. For that purpose we need an agro-ecological zonation. An agro-ecological zone is a geographical unit in which the conditions for crop-and livestock production are more or less the same. Various criteria were used to define agro-ecological zones in Kagera Region. These were: parent material and soils, rainfall, landscape and altitude, population density and dominant land use types. We finally defined the following zones in Kagera Region:

Zone I: Intensive banana based farming system, covers most of Bukoba and Muleba Districts. It is a medium to high rainfall zone and population densities are high. The altitude varies according to the distribution of ridges and plans. The cultivated area per household is small (average 1 ha). Fishing is an important economic activity besides crop production.

The zone can be divided into three sub-zones. Soils in Zone 1A and 1B are formed on Bukoba sandstone, while those in Zone 1C are based on the Karagwe-Ankolean System. Annual rainfall is very high in Zone 1A (above 2000mm/year) and declines to 800mm in Zone 1C. The high rainfall causes very important leaching of soil nutrients in Zone 1A, which seriously reduces soil fertility. High soil phosphorus contents and disturbed action-balances are other characteristics of this sub-zone, which negatively affect crop production, especially of bananas.

Zone II: Semi-intensive banana based farming system covers the ridges in Karagwe and Ngara Districts. It is a medium high rainfall zone and population densities are moderate. The altitude ranges between 1400 and 2000m asl. Soils are formed by the Karagwe-Ankolean System and have good physical properties, as well as moderate chemical fertility.

The zone can be divided into two sub-zones. Zone IIA corresponds to Karagwe District where the cultivated area per household is large (average 2 ha). These farmers produce a surplus of banana, coffee and beans. Zone IIB corresponds to Ngara District where households cultivate on the average only I ha and are hardly self-sufficient. The difference between these two sub-zones is mainly due to cultural and historical factors and cannot be explained by bio-physical properties or land availability.

Zone III: Extensive annual crop production covers the south-eastern part of Ngara and most parts of Biharamulo Districts. Altitude is low (average 1200-masl). Population densities are low. The landscape is undulating and altitude is relatively low. Fishing is of local importance, especially on Ukerewe Islands.

Zone IV: Extensive livestock production covers the eastem part of Karagwe District and the western parts of Bukoba and Muleba Districts. Rainfall is low to medium (800mm/year) and the altitude is relatively low. Population densities are very low.

Zone V: Game and forest reserves cover important parts of central Kagera Region, as well as some spots in northern parts of Karagwe and Bukoba Districts. Rainfall is medium to low. The zone is mainly limited to low altitude, alluvial planes. No economic activities are undertaken besides some hunting and tourism.

2. More about target groups

A target group is a group of farmers with similar circumstances for whom we can make more or less the recommendation. It is important to understand the groups from the society because then you know better who are you clients. During our analysis of target groups in Bukoba, we used criteria which farmers can use themselves for classification. The groups we identified are:

1. Absentee land lords

Land owners who do not live on their land;

Land has the value of investment and extra security to them.

Other people are taking care of their land.

2. Surplus producing households

Have capital for investment

Produce in surplus

Own cattle

Hire labourers

Are full time farmers or involved in trade

Have bibanja of about 2 ha

Have access to services e.g. health, education etc.

3. Self-sufficient household

Produce enough food

Do not produce agricultural surplus

Have not enough capital for investment

Kibanja size is about I ha

Are full time farmers

Have limited access to services

4. Not self sufficient households

Do not produce enough food

Buy food

Kibanja size is about 0.5 ha

Are part time farmers

Have no access to services

5. Care-takers and wage-labourers

Are landless, do not own land

Care-takers live on the land of landlords

Depend on wage-labour

Grow some annual crop to supplement salary

6. Female headed household

Households with female head

They fall under the above mentioned groups.

Landlords cannot be considered to be real farmers. The importance of the remaining groups is estimated for Bukoba:

Surplus producing households

15%

Self sufficient household.30%

Not self sufficient household..

50%

Care-taker households

5%

Female-headed households are very important and are represented in the four groups mentioned above. In Bukoba they count for 25% of all households!

Target groups and research needs are very much linked:

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Target group

Research needs

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Landlords

no clients of research

Surplus producing households

coffee and bananas, large livestock

Self sufficient household

coffee and bananas, small livestock

Not self sufficient household

food crops, small livestock, poultry

Care-takers and wage labourers

annual crops (maize, beans, sweet potato)

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3. More about producer groups

Gender refers to the social relationship in our case of agriculture. It refers to roles, opportunities, responsibilities and constraints of different members of the household in the act of agricultural production. Women contribute a lot to agricultural production. They work on the field, produce crops, and make sure that their family can eat, clean the house, fetch water. In short, they produce and take care of the family.

Because women are involved in crop production, we cannot neglect them. If women grow sweet potato we should not talk to men when we want to test new sweet potato varieties. You are sure to get wrong information by talking to men! The same is true when it comes to crops of men, like coffee. So choose the right gender group when you address a problem.

Gender analysis starts with the recognition that the household is not a homogeneous group of the people. It is rather a complex system itself, in which the division of tasks, allocation of resources and the distribution of benefits are not equally shared among its members. Gender analysis takes into account these differences through targeting of research and extension. Moreover, negative side effects on other groups of people are understood and, if possible, prevented.

For example, if you introduce new coffee varieties and farmers plant more coffee, women may have to spend more time in harvesting the coffee. That is what we call a negative side-effect, because now women have less time for their own crops. The following methods are important for gender analysis:

Access and control profile: The questions are who has access to and control over resources required to undertake an activity and who benefits from it?

Activity profile: The basic questions here is who does what, when and where? The result is a gender distribution of labour and activities.

Gender Analysis Matrix: This is a tool to determine the impact of technology interventions considering factors such as time, labour, resources and culture.

The above mentioned methods are useful in all adaptive research and during all stages, from diagnosis, planning and designing, experimentation and evaluation of the tasted technologies.

4. More about Farmer Research Groups

This approach aims at a good contact between researchers and farmers. FRGs help researchers understand the needs of the farmers and form a platform of discussion. FRG farmers participate in research activities and help researchers to evaluate the results. Research of ARI Maruku is concentrated in villages that represent agro-ecological zones. Until now, three villages were selected in Bukoba District, and three in Karagwe District. In each village there is a Farmer Research Group formed by farmers who are interested in research. Each FRG has a chairman, a secretary and leaders of different trials. Before each season a FRG meeting is called in order to get farmers ideas about the problems which need research. Researchers and extension staff propose experiments and farmers choose and volunteer for experiments they like. They select a trial leader and discuss the planning. During the trial farmers visit each others fields and evaluate the performance of the crops and treatments. This is called farmer assessment. It is the evaluation of the tested technology (by farmers) and see if farmers are able and willing to adopt it or not. This makes farmers to become full partners in the technology development process.

Annex 2:Farming system zonation in the Northern Zone

Name of the farming system:Maasai steppe pastoralism

Legend abbreviation:Pa1

Location:Plains north of Mount Meru and west of Ngorongoro

Towns and wards:Longido, Mogitu, Oldovai

Estimated:..km2

Altitude:1200-1700 masl.

Total annual rainfall: