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Technical Paper 4: Diagnosis and Design Methodology

M. Avila and S. Minae


4.0 Performance objectives
4.1 Introduction
4.2 The agroforestry systems research process
4.3 Macro D&D
4.4 Micro D&D
4.5 Methodological considerations in D&D
4.6 Summary
4.7 Feedback exercises (Find out answers from the text)
4.8 Suggested reading and references


4.0 Performance objectives

Technical Paper 4 is intended to enable you to:

1. Explain three major purposes of the Diagnosis and Design methodology developed by ICRAF and relate its role in alley farming research.

2. Discuss two main features of Agroforestry Systems Research Process and list the various steps involved in carrying out the process.

3. List four main objectives of Macro D & D and describe seven steps in conducting Macro D & D exercise.

4. Specify three main objectives of Micro D & D along with the major steps involved in performing Micro D & D exercise.

5. Recall and describe some important methodological considerations in D & D.

4.1 Introduction

Diagnosis and Design (D&D) is a systematic and objective methodology developed by ICRAF to initiate, monitor, and evaluate agroforestry programs. D&D is based on the philosophy that knowledge of the existing situation (diagnosis) is essential to plan and evaluate (design) meaningful and effective programs in agroforestry research for development. The methodology plays a strategic role in all the phases of the agroforestry research process (Huxley and Wood, undated). It borrows from other methodologies used by research or development agencies, such as baseline surveys and feasibility studies. However, D&D is unique in that it has been specially developed for the following purposes (Raintree, 1987):

· to describe and analyze existing land use systems;
· to design appropriate agroforestry technologies to alleviate those constraints;
· to design appropriate research work, such as trials and funkier surveying.

The basic unit of D&D analysis is the land use system (LUS). The LUS can be defined and analyzed at the level of a country, ecozone, farming system, crop system, or any other unit. The structure and function of any LUS are determined by climatic, physical, biological, technological, economic, social, and political factors. D&D focuses on the interactive effects these factors have on the LUS, and searches for opportunities for improved system development in the LUS.

Within the context of alley farming research, ICRAF's D&D methodology can serve a variety of useful roles. It can, in the first place, provide a justification for alley farming research by demonstrating land use constraints which the system can address (e.g., soil degradation, land scarcity, need for low-input technologies). At the same time, it reminds researchers that alley farming is just one land use system among many, and that other agroforestry or non-agroforestry interventions may be more appropriate in specific cases. Finally, D&D methods can guide researchers as they find ways to adapt alley farming prototypes to local conditions.

D&D can be done at two level's: Macro D&D is a large-scale analysis of an ecozone within a country or a group of countries. For example, ICRAF has conducted collaborative macro D&D exercises with Kenya, Uganda, Rwanda, and Burundi for the bimodal highland ecozone. Macro D&D is important for deciding on national agroforestry research-and extension agenda at-the national level. Micro D&D, in contrast, focuses on one land use system (LUS) within the larger ecozone that has special priority for agroforestry intervention. Micro D&D involves a detailed analysis of households and production systems in the LUS. It leads to guidelines for research that will address the constraints of the prioritized LUS.

4.2 The agroforestry systems research process

The basic objective of ICRAF's agroforestry research is to develop technologies to solve farmers' problems in priority land use systems in specific ecozones. An agroforestry technology should be specified with reference to at least its principal components: MPT species, spatial arrangement, management regimes (i.e., management of the trees and associated components), and performance levels (i.e., technical and socioeconomic criteria). To this end, ICRAF has developed a research process that uses a systems perspective and an interdisciplinary approach. D&D exercises initiate the process, and the design of agroforestry technologies is the pivotal step.

The process is called Agroforestry Systems Research. It is recommended for any D&D program in alley farming or other areas of agroforestry. There are six main steps in the process:

· Macro D&D (national and ecozone level),
· Micro D&D (land use analysis at the production systems level),
· Technology design,
· Component experimentation,
· Technology testing, and
· Technology dissemination and adoption.

The AFNETA/NARS collaborative research program as a whole encompasses all six steps. Individual AFNETA projects, however, would normally be too limited in scope to include a macro D&D exercise. On the other hand, micro D&D methods are useful in a project's pre-experimental stage, and during on-farm experimentation. (The final four steps, which are integral components of the different phases in AFNETA projects, are covered in Volume 1.)

4.3 Macro D&D


4.3.1 Identification of Study Ecozones
4.3.2 Delineation of Land Use Systems
4.3.3 Description of Land Use Systems
4.3.4 Analysis of Land Use Systems Constraints and Potentials
4.3.5 Analysis of Potential Agroforestry Technologies
4.3.6 Definition of Agroforestry Research Needs
4.3.7 Inter-Institutional Coordination


The Objectives of Macro D&D

Macro D&D is an analysis of an ecozone within a country or group of countries. The four main objectives of the Macro D&D are:

· to identify broad issues and problems constraining all the land use systems in a given ecozone;

· to identify and prioritize areas for potential agroforestry interventions;

· to identify research priorities and formulate research programs; and

· to identify needs, opportunities, and mechanisms for inter-institutional collaboration for technology development.

To meet these objectives, macro D&D uses rapid appraisal techniques. It relies heavily on secondary data which are verified and complemented by quick field surveys.

Steps in a Macro D&D Exercise

There are seven steps in macro D&D exercise:

1. Identification of study ecozone,
2. Delineation of land use systems within the ecozone,
3. Description of land Use systems,
4. Analysis of land use system constraints and potentials,
5. Analysis of potential agroforestry technologies,
6. Definition of agroforestry research needs, and
7. Inter-institutional coordination.

We will discuss these one at a time.

4.3.1 Identification of Study Ecozones

The first step in macro D&D is the selection of an ecozone for study. The zone covered in a macro D&D exercise is large, containing significant variations in land characteristics with respect to current Uses and constraints. The choice of the study zone should reflect its biological and socioeconomic importance at the national level based on:

· the zone's contribution to food production and/or income;
· the total population it supports and/or the area it covers;
· the urgency of its constraints;
· the extent of its unexploited potential for production; and
· the level of its development with respect to other areas.

For example, in the case of Eastern and Central Africa, the bimodal highland ecozone seems to be an important study zone. According to Hoekstra (1988), it contains a significant proportion of the area and human population: in Kenya (1590 of area and 50% of population), Uganda (40% and 62%), Rwanda (6290 and 7390), and Burundi (85% and 9090).

Each ecozone contains within it a variety of land use systems (LUSs). Delineation (definition) of the LUSs is the next step in macro D&D

4.3.2 Delineation of Land Use Systems

A land use system (LUS) within an ecozone level can defined as follows: It is a population subgroup in which the features and constraints of the farming systems are sufficiently homogeneous to yield similar results if a given agroforestry technology is introduced into those farming systems. The main guideline for distinguishing land use systems is that each system should display unique constraints and potentials differentiating it from other systems in the ecozone of interest.

Accordingly, an LUS consists of a distinctive combination of soils, crops, livestock, trees and/or other production systems; it occupies a given unit of land where specific outputs are desired and obtained by a given management unit. Normally the smallest unit of decision-making is the household, but any unit (i.e., clan, communal group, cooperatives or company) that makes management decisions collectively and/or shares intimately in the input/output flows of a system is also considered to be an LUS Unit. Some examples of delineated land use systems are given in Table 1 to clarify the above points.

4.3.3 Description of Land Use Systems

All delineated LUSs are described by specifying the characteristics that are known to affect their current management and performance, and would be expected to affect the introduction of potential agroforestry technologies. These characteristics are outlined below:

I. Title of system
II. Location: administrative and political divisions, with map if available.
III. Ecological characteristics

· Agroecological zone,
· Altitude range (m),
· Topography: slope (gradient),
· Rainfall: total annual, monthly levels, range,
· Number of growing seasons: with months and growing days,
· Soil: type, texture, pH, fertility, etc.,
· Hydrology: river network, water table level, etc., and
· Vegetation: natural and secondary

IV. Socioeconomic characteristics

· Total land area in the LUS (km2 or ha)
· Total population in the LUS,
· Population density: persons/km2,
· Ethnic groups: religion, culture, etc.,
· Tenure system: ownership or user rights for crops pastures, land, trees,
· Farm income: levels and sources, and
· Infrastructure: roads, electricity, commercial centers, etc.

V. Land use characteristics

· Farm size: average, range, distribution,

· Spatial arrangement: location of homestead, crop, livestock, trees,

· Major and minor agricultural production activities: food and cash crops, large and small livestock, trees, etc.,

· Area covered by various components: ha or 90 of total farm; activities,

· Crop production: main crops - land preparation, planting methods/timing, use of manure/ fertilizer/pesticides, weeding, soil conservation, harvesting, level of production, storage, etc.,

· Livestock production: type, herd size, breeds, feed sources and management (tree/zero grazing, etc), type/use of output.,

· Tree production: species, main uses, land use niche, management, and arrangement, etc; traditional and new agroforestry systems (Note arrangement, management, or any data on performance., and

· Production systems interactions: relationship between crops, livestock, trees.

VI. Resources/supporting services

· Labor availability and utilization: family owned, hired, communal, etc.,
· Farm power and equipment used,
· Marketing: markets, marketing charnels, prices, etc.,
· Credit facilities: type available and for what farm activities,
· Extension services: nature and organization of extension services, and
· Local organization: cooperatives, farm organizations, churches.

VII. Development activities and policies

· Review of relevant government policies and strategies, and
· Review of research and development projects, e.g., in agroforestry.

Table 1. Examples of land use systems (LUSs) which have been delineated during macro D&D.

COUNTRY

ECOZONE

LAND USE SYSTEMS IN ECOZONE

1. Zambia

Unimodal upland plateau (Kwesiga and Kamau 1988)

· Shifting cultivation
· Grass mound system (cereal/livestock semi commercial, system practiced in open savannah areas where grass is abundant)
· 'Barotse' agropastoral system in flood plains (an intensive cropping system during the wet season and grazing/crop cultivation in the dry season)
· Maize/cattle mixed system of southern/eastern and central plateau regions
· Maize/small stock system

2. Cameroon

Humid lowland (Djimbe and Raintree, 1988)

· Coffee/household farming systems of plantation workers, found throughout the southern plateau.
· Cocoa/food crop/coffee system found throughout the southern plateau on low fertility Orthic ferralsols

3. Kenya

Bimodal high-lands (Minae and Akyeampong, 1988)

· Tea-based
· Coffee-based
· Maize-based
· Potato-based
· Sugar-based
· Food crop systems

4.3.4 Analysis of Land Use Systems Constraints and Potentials

Each system has to be evaluated for factors that prevent its households from obtaining optimal outputs from the available resources. This step requires analysis of farmers' needs and priorities to see how well these are being met by current performance of the LUSs. The performance gap is evaluated by comparing the present levels of outputs with the biophysical and socioeconomic potential of the resources. For instance, one can compare the range of yields obtained in different LUSs with yields obtained in on-station or on-farm research.

Constraints analysis is based on problems facing households - both present problems and envisaged future problems. Emphasis is put on constraints which agroforestry can address.

To diagnose constraints properly, the research team must understand the relationships between manifested symptoms and causal factors. An example of constraints analysis is given in Table 2.

Because almost every constraint identified has several causal factors and symptoms (effects), the D&D team must have a multi-disciplinary capability. It must be able to interpret the relationships between these factors and the objectives of the household. Furthermore, it must be able to determine what opportunities exist to address the constraints. For this reason, constraint analysis is done concurrently with LUS characterization. For example, if one observes steep slopes in cropland, one can conclude that soil erosion is a likely hazard if nothing is being done to prevent it.

4.3.5 Analysis of Potential Agroforestry Technologies

In this step, potential interventions are identified and assessed for their relevance to the constraints and their likelihood of increasing or sustaining productivity of the LUSs. First, all possible interventions are identified, whether they are from the areas of agronomy, forestry, or agroforestry. For example, low soil fertility could be addressed by various technologies such as fertilizer, livestock manure, green manure from trees or shrubs, crop rotations. Next, each alternative is evaluated for its technical potential and suitability to farmers' resources and capabilities, infrastructure, and support services. A judgement is then made on what interventions seem to have the highest potential. Agroforestry interventions are proposed only when they have a comparative advantage.

If agroforestry seems viable, the list of high-priority constraints will suggest specific options for consideration. For example, a fodder shortage problem could be addressed through these seven agroforestry options:

a. establishment of fodder banks for a cut-and-carry system;
b. improvement of grazing management through live fencing;
c. introduction of fodder trees for browse in grazing lands (e.g., alley grazing);
d. planting of fodder trees with grass in intensive feed gardens;
e. planting of MPT/grass strips along contours in crop land; and
f. establishment of MPT/grass/legume rotations.
g. establishment of alley farming mainly for fodder production

Table 2. An example of constraint analysis in macro D&D: the ease of the coffee-based LUS in Kenya (Minae and Akyeampong, 1988).

Symptom 1:

Inadequate food production and income generation to support the household.

Cause:

Small farm size, dense human population, and long-term settlement.

Symptom 2:

Low crop productivity.

Cause:

Continuous cultivation on steep slopes, soil erosion, insufficient use of manure and inorganic fertilizers, lack of cash to purchase needed inputs.

Symptom 3:

Low livestock productivity.

Cause:

Insufficient availability of feed in dry season, poor organization of milk marketing in some areas of LUS.

Symptom 4:

Fuelwood and building material shortage.

Cause:

Total clearing of indigenous trees except for those of high quality timber.

Note:

Significant interest in this problem has led farmers in one area of LUS to plant Grevillea and Eucalyptus species on their farms. There is a high demand for propagating material for fruit trees, fencing and fuel wood.

Symptom 5:

Labor scarcity for agricultural activities, especially during the coffee harvest season.

Cause:

Higher wage for coffee harvest.

Symptom 6:

Problem of weeds and moisture conservation during the dry season in coffee plots.

Cause:

Lack of labor, scarcity of mulch material.

Each technology must be assessed to determine how it would fit into the existing system. For example, d, e, and g are likely to be suitable for intensive systems where farmers are already practicing zero grazing; f is for semi-intensive systems, while c is probably preferable for farmers who have grazing land.

"Ex-ante" evaluation of a technology is part of technology assessment. It is carried out to determine a technology's potential for adoption. Ex-ante evaluation means the evaluation of the likely impact of a proposed technology before the technology has been introduced. It is based on appropriate assumptions using relevant data from other sources. This requires knowledge of technology management and performance under the specific conditions of the LUS.

4.3.6 Definition of Agroforestry Research Needs

If a proposed technology is well known and some farmers are familiar with its management and requirements, then a recommendation for extension programs can be formulated. On the other hand, if very little is known about the technology, then the D&D team will need to propose research activities. The team should propose a program of research to develop specific components, understand technical relationships, and/or to test/adapt the technology or components. The research will address critical information gaps for designing viable and adoptable technologies.

The proposed research activities will be conducted either on-station or on-farm, depending upon the specific objectives of the research activity (more detailed information is given under micro D&D). Possible activities include:

· literature searches and reviews;
· MPT surveys and local collection of seeds;
· nursery propagation and development of improved nursery techniques;
· MPT screening trials; and
· MPT management trials and/or other technology testing trials.

The team should next carry out a comparative analysis of the research needs for each agroforestry technology for each LUS within an ecozone. This analysis will be the basis for the design of appropriate research programs. Thus the main output of the macro D&D exercise is the definition of a research agenda to develop relevant technologies for the ecozone of interest.

4.3.7 Inter-Institutional Coordination

A macro D&D exercise should initiate an inventory and review of past and present agroforestry research or development programs. For example, the research team in the Kenyan study identified all the national or international institutions with existing research on the prioritized agroforestry technologies. The team classified the existing research according to MPT species being evaluated (Table 3). The results of macro D&D will suggest specific problem areas for complementary research in different institutions and better use of their scientific and physical resources. If several countries are involved, as in the case of a network, macro D&D provides a sound basis for planning inter-institutional collaboration across countries.

In practice, inter-institutional coordination is established even before macro D&D begins, based on institutional interests, programs, and potential contributions from the disciplinary areas essential to agroforestry. In some countries, agroforestry coordinating institutions may already exist, e.g., Ghana, Malawi, and India, where ICRAF has facilitated the creation of coordinating mechanisms.

Basically three types of institutional coordination can be established, namely:

· A steering committee to set policy, review and approve research;

· A technical committee, possibly a subgroup of the steering committee, to coordinate implementation, monitoring and evaluation research programs. For example, the steering committee in Kenya has 15 institutional members while the technical committee has just two members;

· Task forces, i.e., multi-disciplinary teams, to carry out specific assignments such as macro D&D, micro D&D, MPT surveys. Often the same scientists are members of different task forces.

Table 3. Existing Research on Mixed Intercropping/Enriched Fallow for Soil Fertility in Cropland (Minae and Akeampong, 1988)

SPECIES

INSTITUTION

SITE

EVALUATION OF SPECIES

MIXED INTER CROPPING

ENRICHED FALLOW TRIALS

Acacia albida


KREDP


Ngong

x



Wambugu

x



Cajanus cajan




CRSP



Maseno, (Kisumu)


x


Hamisi (Kakamega)


x


Husimbi (Siaya)


x


U. Nairobi Crop Science

Kabete

x



Calliandra calothyrsus

KREDP

Kisii

x


x

Cordia abyssinica

KREDP

Kisii

x



Gliricidia sepium


KREDP

Kisii

x



CRSP

Maseno (Kisumu)




Leucaena leucocephala





KREDP


Kisii

x


x

Kiambunyoro

x x


x x

CRSP



Maseno (Kisumu)



x

Hamisi Kakamega


x


Musimbi (Siaya)



x

Sesbania sesban



CRSP



Maseno


x

x

Hamisi



?

Musimbi



x

CRSP: Collaborative Research Support Project, USAID.
KREDP: Kenya Renewable Energy Development Project, Kenya
X: Means doing research on the topic

Multi-institutional participation in strategic phases of the research, such as D&D exercises, definitely facilitates the integration of individual efforts and the development of coordinated programs.

Promotion of inter-institutional collaboration on alley farming research is a key objective of AFNETA. In 1991, the directors of NARS institutions collaborating in AFNETA projects met to discuss and improve such inter-institutional coordination within their countries. Where National Agroforestry committees already exist, coordination of alley farming research takes place within that framework (AFNETA, 1991).

4.4 Micro D&D


4.4.1 Analysis of Land Use System and Constraints
4.4.2 Design and Evaluation of Agroforestry Technologies
4.4.3 Design and Evaluation of Research Programs


Objectives of Micro D&D

The objectives of micro D&D are similar to those of macro D&D. The major difference is that whereas macro D&D has a broad scope (i.e., an ecozone), micro D&D focuses on detailed analysis of one prioritized LUS. The three main objectives of micro D&D are:

· to describe and analyze an LUS in order to identify its constraints; and
· to design and evaluate agroforestry technologies to address the constraints
· to design and evaluate appropriate research programs aiming to develop these technologies.

The basic principles for achieving these objectives were presented under macro D&D (section 4.3) and are also relevant for micro D&D.

Since resources are inevitably limited, a country, institution or project will have to be selective in deciding which LUSs should be subjected to micro D&D. The choice of the LUS for micro D&D depends on criteria such as:

· political and economic importance of the system,
· technical potentials for improvement of the LUS, and
· scientific expertise and other resources in the national collaborating institutions for carrying out research in the LUS.

Although it is not essential for a macro D&D exercise to precede a micro D&D exercise, the task of prioritizing LUSs, defining the research focus, and defining areas for institutional collaboration will be much easier after macro D&D has been completed.

4.4.1 Analysis of Land Use System and Constraints

This phase of micro D&D aims at:

· prioritizing the needs of the household;
· identifying production constraints (both those that can and cannot be manipulated); and
· assessing potentials for system development.

The basic framework used for this analysis is a farming system, where the decision-making unit is the household. The household usually manages a combination of crop, livestock, and tree production systems, along with other non-agricultural and off-farm activities, to satisfy its basic felt needs of food, cash, fuelwood, building materials, and security. Besides endogenous factors, the farming system is influenced by exogenous factors of a political, social, economic, or technological nature. Understanding the interactions within the farming system and the effects of environment is essential for prioritizing the needs of the household, identifying production constraints, and assessing potentials for system development.

The micro D&D research team, therefore, will want to quantify resources, management, and yield of each component of the farming systems, including characteristics and priorities of the household. (More information on farming systems analysis is presented in Volume I and in Technical Paper 5.)

One component of the farming system analyzed by the team is agroforestry technology and MPTs used by farmers. A brief example of the use of MPTs is presented in Table 4, taken from the Zambian D&D exercise. This initial description is usually followed up by special studies to fine-tune the researchers' understanding of the existing systems.

Table 4: Indigenous trees and their uses as identified by farmers (Ngugi, 1988)

TREE SPECIES


CHARACTERISTICS

USES

Crown

Stem

Flowering/Seeds

Fodder

Timber

Fuelwood

Medicinal

PSEUDOLACHYNOSTYLIS MAPROUNEIFOLIA
Local (Nyanja)
name: Msolo
Family:Euphoribiacea

Light conical or rounded

Short boled or shrub

Flowers: July - Dec.
Fruits ripen June -October
Seeds collected from ground

Leaves

Joinery

x

x

DIPLORHYNCHUS CONDYLOCARPON
Local (Nyanja)
name: Mtowa
Family: Apocynaceae

Light, narrow semi-deciduous

Multistemmed shrub or tree

Flowers: August-Nov.
Fruits ripen June-August
up to 11 m tail

Leaves

Live fence poles, curving

x

x

DIOSPYROS KIRKII
Local (Nyanja)
names: Mkulo, mchenjakulo
Family: Ebenaceae

Evergreen or semi-ever shrub or tree

More or teas cylindrical may be crooked

Flowers: Sept.-Dec.
Fruiting: July-Oct.
Edible fruit

Leaves pods

-

-

-

AZELIA QUANZESIS
Local (Nyanja)
name: Mpapa, Mupapa or Mkolando
Family: Caeaalpiaioideae

Heavy branches forming a crown leafless from 3 days to 3 weeks

Cylindrical

Flowering: July-Nov.
Fruits : maturing a year later, pods, contain 6-10 seeds
Seeds eaten by birds animals, insects hence hard to find on the ground

x

very valuable timber

x

x

ALBIZIA ADIANTHIFOLIA
Local (Nyanja)
name: Mtanga
Family: Mimosoideae

Light crown semi-deciduous


Flowers Sept.-Oct.
Pods mature a year later contain 8-12 seeds

x

-

-

x

FICUS SPP
Family: Moraceae

Varies from large spreading to small crowns

Variable

Fruits edible

x

-

x

x

The Zambian case also provides an example of constraint analysis. The micro D&D analysis of a low-input maize/livestock farming system in the unimodal upland plateau of Zambia looked at the causes of insufficient cash and food supply. A large number of factors combined to produce these problems, including factors related to physical resources (animals, oxen, labor), management practices (poor technology, land preparation, and planning, low or no use of input use, burning of crop residues, animal diseases), low yields (fallow land, cropland and livestock), and exogenous factors (health, markets, village structure).

Another micro D&D exercise analyzed the coffee-based farming system in the bimodal highland ecozone of Kenya. The team identified the critical constraints of each production system (livestock, crop, and wood production), defined the causes of each constraint, and proposed a corresponding role for agroforestry to address each constraint (Table 5). The research team subsequently identified suitable agroforestry technologies for every potentially exploitable niche in the farming system (Table 6).

The constraints analysis aspect of micro D&D is well suited for planning the initial stages of research. However, later stages of research may require a re-assessment or a more precise measurement of some of these constraints.

4.4.2 Design and Evaluation of Agroforestry Technologies

The word design here refers to the act of combining various innovations into a technology and specifying the techniques to test the technology. Accordingly, the design and evaluation objective of micro D&D focuses mainly on:

· technology specification, and
· ex-ante evaluation of technology.

Technology specification

For any type of production system, whether crop, livestock or agroforestry, a technology can be defined as a "package" of husbandry practices and inputs which is specified in terms of:

· the farming systems/households it is targeted to;
· its components and resource requirements;
· the management and implementation regimes to be followed by the farmers; and
· the estimation of real benefits and costs to the farmers under favorable and unfavorable conditions.

Table 5. Summary of LUS constraints with identified agroforestry potential, Kenya (Minae, 1988).

Constraint

Cause

Proposed AF Role

1. Livestock Production



1.1. Low quality fodder (low protein)

1.1.1 Lack of leguminous component in fodder production

1.1.1.1 Introduce fodder MPTS

1.2 Low quantity fodder during the dry season

1.2.1 Inadequate land allocated to fodder production

1.2.1.1 Introduce fodder MPTS to be harvested for leaves and pods during dry season

2. Crop production



2.1 Inadequate application of fertilizer/manure

2.1.1 Lack of cash to purchase term inputs


2.1.2 Insufficient production of manure due to limited livestock and or biomass

2.1.2.1 Increase biomass converted to brown manure through animal fodder from MPTS

2.2 Under exploitation of agricultural potential

2.2.1 Lack of technologies to optimise available, resources

2.2.1.1 Increase the tree (fruits) production on the farm

2.2.1.2 Improve present MPTS/crop combination

2.3 Poor management of soil/ water resources

2.3.1 Lack of appropriate management options

2.3.1.1 Incorporate MPTS component in soil conservation practices

2.3.2 Insufficient labour


3. Wood production



3.1 Insufficient land area to plant MPTS

3.1.1 Low competitiveness of trees with other enterprises

3.1.1.1 introduce/increase more productive, better quality timber/fuelwood MPT production activities

3.2 Poor management of existing MPTS

3.2.1 Lack of knowledge/skills in tree production/management

3.2.1.1 Improve knowhow/management of present MPTS

Table 6: Potential agroforestry technologies based on niches (Minae, 1988),

NICHES

POTENTIAL OF INTERVENTIONS

ROLE OF TREES

1. Homegarden

1.1 Multistrata homegarden

1.1.1 fruits
1.1.2 timber/fuelwood

1.2 Mixed cropping

1.2.1 fruits
1.2.2 industrial tree products

2. Food crops

2.1 Mixed cropping

2.1.1 fruits
2.1.2 timber/fuelwood
2.1.3 honey

2.2 Hedgerow intercropping

2.2.1 soil conservation/fodder
2.2.2 soil conservation/fertility
2.2.3 soil conservation/fuelwood

2.3 Contour hedgerow on grass strips

2.3.1 soil conservation/fodder
2.3.2 soil conservation/fertility
2.3.3 soil conservation/fuelwood

3. Coffee plot

3.1 Mixed cropping

3.1.1 fruits
3.1.2 shade?

4. Napier plot

4.1 Hedgerow intercropping

4.1.1 fodder
4.1.2 fuelwood/poles

4.2 Mixed cropping

4.2.1 poles/fuelwood/timber

5. Internal boundaries

5.1 Row of MPTs

5.1.1 fruits
5.1.2 timber/fuelwood

5.2 Multistorey hedgerow of MPTs

5.2.1 fodder
5.2.2 poles/fuelwood
5.2.3 soil fertility

6. External boundaries

6.1 Multistorey/ Hedgerow of MPTs

6.1.1 timber/fuelwood-top storey
6.1.2 poles - Midstorey
6.1.3 fodder-lower storey
6.1.4 fuelwood - lower storey
6.1.5 fertility - lower storey

6.2 Row of MPTs

6.2.1 timber/fuelwood
6.2.2 fruits

6.3 Double hedge/row

6.3.1 timber/firewood-outer row
6.3.2 fodder - inner hedge

7. Valley bottoa?

7.1 Mixed cropping

7.1.1 fruits

8. River banks

8.1 Row of trees

8.1.1 fodder
8.1.2 poles

In other words, technology specification should provide sufficient detail to permit technical feasibility analysis, socioeconomic analysis, and assessment by farmers. An example of technology specification in the process of designing MPT hedgerows for napier plots in the coffee-based system in Kenya is given in Table 7.

In the course of technology design, several outcomes can be derived depending on the particular decisions and assumptions made by the team at each juncture, especially with respect to target levels of performance desired, management possibilities of the farmers, and endogenous and exogenous conditions of the farming systems. Developing realistic future scenarios in the above areas is an essential part of the technology design exercise.

Technology specification demands a lot from the D&D team. It raises a large number of specific questions requiring knowledge of the farming systems and scientific expertise. It demands the intuition to integrate fragmented pieces of information. If the questions raised cannot be resolved to the satisfaction of the team, then specific priorities for research (farm or community studies, experiments) have to be established. For example, the team in a Ugandan D&D study prioritized research areas for each technology that was being designed (Table 8).

Because agroforestry is a new science, there is a dearth of technical information on most components. For examples, information on the biophysical productivity of MPTs under different arrangements and management regimes is known only for a few species in selected environments. Similarly, not much is known about utilization and timing of MPT outputs for crop and livestock productivity in alley farming. Successful technology design requires adequate research experience.

The D&D team may design several technologies to address constraints of the farming system, in terms of the number of innovations, management requirements, and performance levels. For example, one technology may comprise small incremental changes, another quite radical changes relative to the practices of the farmers, and still another could be an "optimal" design of a technology that is absolutely new to the farmers.

Table 7. An example of technology specification from a micro D&D exercise in Kenya.

Objective:

To increase biomass productivity/quality of fodder for milk production (3 livestock units) by introducing high protein fodder MPTs in existing napier of the coffee-based LUS.

Land niche:

In napier plot with average size of 0.5 ha per farm.

Arrangement:

Napier is currently established under 1 x 0.5 m spacing; MPT hedgerow will be introduced at 0.5 x 4 m, replacing one row of napier.

Components:

Non-woody species is napier grass (Pennisetum purpureum, common varieties are Bana and F. camerona); proposed MPT species is Leucaena leucocephala (K8); other species may be better but management and yield unknown.

Management of rapier:

Similar to the management of farmers: Establishment: cuttings at onset of rains; Manure: 1 bucket at planting, small amounts of fertilizer after that; Age at 1st cutting: 6 months; Frequency of cutting: every 6-8 weeks (1 m height).

Management of MPT:

Propagation by seedling (6 mos before napier during long rains); Age at 1st cutting: 1 year; Height of cutting: 0.5 m; Frequency of cutting: 3 times/year Manure: proposed 0.5 bucket at planting; Weeding: 2 times/year or as often as necessary.

Required Inputs:

Similar to the existing fodder plots; Manure at establishment; Labor at establishment, for weeding and for regular harvesting.

Anticipated output:

Yield of napier not known exactly but farmers require about 0.5 ha/LUS depending upon management and age of rapier, research results in the area suggest that 0.2 ha well managed can support I cow producing an average of 2500 litres milk per lactation (Karanja, 1986). Yield of Leucaena in napier could be from 1.5-2.5 tons DM/ha; a cow would require about 6.25 kg DM/day (2.5% of live weight); MPT N-fixing capacity should directly benefit napier.

Table 8: SUMMARY OF PROPOSED RESEARCH (Source: Okorio and Hoekstra, 1988).

Type of research

TECHNOLOGY

Hedgerow intercropping

Grass/shrub strips

Upperstorey trees

Fruit trees

1. Literature search & international seed acquisition

x

x

x

x

2. MPT identification survey

x

x

x

x

3. Local collection of seeds

x

x

x

x

4. Nursery propagation

x

x

x

x

5. MPT selection trials

-

-

x

x

6. Technology development trials

-

-

x

x

7. Prototype trials

x

x



8. Extension research

x

x



Note

x

= Areas for immediate research

-

= Areas not requiring a lot of research


= Areas where research will follow after the immediate research areas

Ex-ante evaluation of technology

Once a technology has been specified in its main components, it becomes possible to carry out an ex-ante evaluation based on data from relevant situations. Ex-ante evaluation is simply the analysis of its probable impacts and implications. This analysis looks at benefits and conflicts or problems likely to arise at the levels of:

· farming system, with respect to household division of tasks and benefits, on-and off-farm activities, and resource use schedules;

· community or-village, with respect to obligations, organizations, management, and regional or catchment-level systems; and

· region or catchment area, with respect to land tenure, market incentives, credit and extension agencies.

The ex-ante analysis should use indicators that are relevant to farmers, in addition to those which researchers and extensionists may consider relevant to their technical domains. It should assess the production potential and technical feasibility of the technology. There are four essential types of analysis involved in ex-ante evaluation, namely:

· Economic viability: benefit/cost ratio; net returns to land/labor/cash; risk and sensitivity analysis.

· Sustainability: analysis of the technology's capacity to meet objectives in short -and long-terms; also, analysis of expected changes and requirements related to soils, water, vegetation, management, and commercial input/output streams.

· Farmer acceptability: comparability analysis with respect to resources and management; also, social analysis with respect to defined rules and responsibilities within household obligations, tenurial conditions, etc. It is essential to analyze who in the household makes decisions on the resources required, who has to do the work, and who will receive the benefit accruing from proposed changes.

· Adoption potential: analysis of technology impacts in terms of number of farmers, regional development priorities, tenure rights, institutional and infrastructural support systems, etc. (Macro D&D also plays a key role here.)

It is logical to expect that the larger and more complex the technology, the more demanding is the ex-ante analysis. During the design process, the team should interact with typical households of the target system and with extension and development agents, particularly in relation to the following topics:

· priority problems being addressed and expected performance levels of the technology;
· endogenous factors and constraints to successful adoption;
· resource and management requirements for effective establishment (transitional analysis); and
· expected benefits, and impacts on farmers' objectives.

The ex-ante analysis is not confined only to micro D&D but extends into the later technology testing phases as well.

4.4.3 Design and Evaluation of Research Programs

There are four types of scientific research, namely:

· basic research which is designed to generate new knowledge or understanding;
· strategic research to solve specific research problems;
· applied research to create new technology; and
· adaptive research to adjust technology to the specific needs of a particular set of biophysical or socioeconomic conditions.

It is generally recognized that these are part of a continuum in the technology development process, and that productive research requires an integrated and complementary research strategy consisting of on-station research (OSR) and on-farm research (OFR). OSR consists mainly of basic and applied research; it must be able to offer technical components, information and support to the OFR activities. OFR complements but does not substitute for OSR. OFR provides feedback for setting OSR priorities, and adapting technologies or components coming out of OSR. In the case of agroforestry, where basic and applied research is not well developed and where farmers have more experience than scientists with management of technologies, OFR may have a stronger role to play in the research strategy, including applied research.

Research Design Criteria

A technology comprises a number of components. Experiments are designed to develop the technical components and to understand relationships among them. As discussed previously, agroforestry technology must be specified at least in its principal components, namely, MPT species, spatial arrangement, management regimes, and performance levels. Different types of trials are conducted to achieve these specifications. Within the ICRAF D&D scheme, the three general categories of agroforestry trials are:

· General MPTs screening trials,
· MPTs technology screening trials, and
· MPTs management trials.

This general scheme is similar to AFNETA's classification of alley farming research projects into four broad types, namely:

· MPT screening and evaluation,
· Alley farming management trials,
· Livestock integration trials, and
· On-farm research and socioeconomic assessment.

While all D&D teams have a mandate to design a program of research, the scope of their proposals may vary. For example, the Ugandan team proposed four relevant agroforestry technologies (e.g., alley farming, fruit trees), and then specified a set of up to eight different research needs for each technology (e.g. literature review, MPT screening) (Table 8). Another proposal emphasized the chronological sequencing of research activities during a five-year program (Table 9). A more detailed research program attempted to identify specific objectives, factors/treatments, and assessments for several types of proposed research (Table 10). Table 11 presents an example of a summary of an experimental station protocol. It is expected that any D&D exercise will provide sufficient understanding of the farmers' environment and production systems for design the types research programs exemplified in these tables. To achevie this, it may be necessary for the D&D teams to carry out multi-visit surveys and interactions with land Users and to review scientific secondary information.

Table 9: CHRONOLOGICAL SEQUENCE OF RESEARCH STEPS (After Ngugi, 1988).


1987 - 88

1988 - 89

1989 - 90

1990 - 91

1991 - 92

Literature review end International germplasm acquisition

------------------------------------------------------------------------------

Ethnobotanical survey Cattle feeding practices survey

--------

PROPAGATION STUDIES

------------------------------------------------------------------------------

MPT SELECTION TRIALS

--------------------------------------------------------------------------

ALLEY CROPPING

Establishment/Trials and Management


Prototype Trials/Extension Research

-------------

LIVING FENCES

Establishment/Management Trials

--------------------------------------------------------------

Prototype Trials/Extension Research

----------------------------------------------

FODDER BANKS



Establishment Trials

--------------------------------------------------------------------------

Phenology/Field Screening Trials

--------------------------------------------------------------

Management Trials

------------------------------

Prototype Trials/Extension Research


BOUNDARY PLANTINGS

Establishment/Management Trials

--------------------------------------------------------------

Prototype Trials/Extension Research

--------------------------

FRUIT TREES

Phenology/Establishment Trials

--------------------------------------------------------------------------

Prototype Trails/ Extension Research

-----------------------------------------------------------------------

Table 10. Multistorey MPT hedgerow on boundary planting (fuelwood/timber/poles), Kenya (Minae. 1988).

Type of Research

Objectives

Factors (Treatments)

Assessments

A. Species selection
Design RCB
Duration > 5 years

To determine suitable MPT for boundary planting for production of fuelwood/ timber/poles to identity ecological adoptation/provenances

MPT species
Upper storey
- Grevillea robusta
- Grevillea glaucar
- Casuarina equisitifolia
- Croton megalocarpus
- Markhamia lutea
- Cassia siamea
- Pinus pania
- Alnus Patala
- Eucalyptus ssp.
Understorey
- Calliandra calothyrsus
-Leucaena diversifolia
- Leucaena leucocephala
-Sesbania grandiflora

For upper storey:
Survival rates
Growth rates
Woody biomass production
Morphology - canopy
(size and density)
For understorey:
Fodder biomass
Tolerance to shading
Nutritive value
Woody biomass survival
Growth rates

B. Management trials
Design
- Randomized complete block for on-station trials
- Either randomized complete block or incomplete block for on-sum trials

- To determine suitable MPTs for boundary planting
- To determine the best establishment and management methods
- To evaluate the effect of time of harvesting

Spacing arrangements within the hedge
- Time of first harvesting
- Distance of crop from boundary
- Frequency of pruning/pollarding

- Tree growth (height and diameter)
- Tree canopy cover (diameter)
- Crop yield
- Interval from boundary
- Tree percent survival/initial after 2 years old
- Coppicing and pollarding/pruning characteristics
- Observation on morphology

C. Technology testing trials
Design
- Randomized complete block for on-station trials
- Either randomized complete or incomplete block for on-farm trials
Duration 3 years

- Researcher and farmer evaluation of boundary pluming under term conditions

- Application of various management techniques
- Species combination

- Labour input for establishment and management
- Interactive effects on adjacent crops and soil
- Farmer evaluation of yield and value of harvesting products

D. Extension research
Design to be determined
Duration done concurrently with prototype trials

- To evaluate the impact of the technology on farm overall performance


- Farmers acceptability

Table. 11. On-Station Experiment No. 2 KEN/88 (Personal communication, G.B. Singh, 1988)

Title

- Fooder production potential of different MPTs and grass combinations on the field bunds

Location

- Maseno (Kenya)

Date of "art and duration

- April, 1988, for 4 years

Objectives

i) to determine the fodder yield of Napier grass and Sesbania sesban, Calliandra calothyrsus MPT species and their combinations,

ii) to determine the effect of trees and grass raised on field bunds on the yield of associated crops.

Treatments T1: Leucaena leucocephala - Melinda Forest Station, Blize

T2: Sesbania sesban - Kakamega, Kenya
T3: Calliandra calothyrsus - KFSC:Guatemala
T4: Napier grass - vet. farm, Maseno, Kenya
T5: T1 + T4
T6: T2 + T4
T7: T2 + T4

Experimental design

- RDB with 4 replications

Experimental details

i) Field bund is constructed across the slope for planting trees and grass;

ii) Each bund plot is of 4 x 1 m dimension. Grass is to be planted on the upper side and trees on the lower side of the bund

iii) Where tree and grass are to be planted together, the grass will be planted only after the establishment of the trees;

iv) In between two bunds bean crop GLP-2 (Rose-coco) will be planted in the first year and in the second year maize will be cropped. The bean and maize crops are fertilised as per local recommendations. The plot, including cropped area, will be on both sides of the bund;

v) Distance between two rows on the bund will be 50 cm and within the row, plants will be at 25 cm.

Observations to be recorded

i) Survival of trees and grass after establishment;
ii) Monthly height and diameter observations till the cutting for fodder starts;
iii) Fodder yield from grass and trees;
iv) Estimation for fodder quality (crude protein, crude fibres, etc)

4.5 Methodological considerations in D&D


4.5.1 Research Team
4.5.2 Research Domains and Recommendation Domains
4.5.3 Data Collection Methods
4.5.4 Analytical Methods and the Role of Farmers
4.5.5 Logistical and Operational Aspect


4.5.1 Research Team

The nature of agroforestry systems suggests the need to set up multi-disciplinary and multi-institutional teams to achieve the objectives of D&D. For macro D&D, efforts should made to form teams comprising:

1) biophysical scientists from the fields of soils, crops, climate, livestock, and forestry, and
2) social scientists from the fields of agricultural economics, rural sociology, or anthropology

These scientists should have experience in research and extension. For micro D&D and follow-up studies, the expertise and composition of the team are based on the prioritized LUS, its identified constraints, and the specific objectives of the study. Normally teams implementing macro and micro D&Ds should consist of 5-10 members. The minimum of 5 members allows for a multi-disciplinary range and inter-institutional representation, while the maximum of 10 avoids management problems.

Team leadership is critical for successful D&D implementation. In the first instance, the leader should have experience with, and an appreciation for, the conceptual framework and "tools" used by both biological scientists and social scientists. Interaction should be focused on the objectives of the D&D exercise, and on the specific contributions which can be made by each discipline to the overall research strategy. An objective D&D strategy is the key to bringing disciplines to work together to address the problems of the farmer in an integrated manner.

Care should be taken to provide an effective interface between the D&D exercise and the planning and implementation of technology development research. It is essential that the scientists who will implement the experimental program participate in the D&D teams, or at least that those who carry out the D&Ds participate in the design of the experimental programs.

4.5.2 Research Domains and Recommendation Domains

Defining the target land use system or farming system is probably the most crucial step in the Agroforestry Systems Research process. The problem is that unless researchers have developed the technology and know how to manage it, what requirements it has and exactly what it can do, they do not have a solid basis to define an appropriate recommendation domain. For this reason, it is better in the preliminary stages of technology design to speak of a "research domain" until there is sufficient understanding of the technology to determine precisely where it can fit. Accordingly, the research team should always be concerned about whether and how technology development is modifying the original research domain.

Precise definition of the target system is also important for the reason that every farming system or household is somewhat different. Some customizing or fine-tuning of technology is required for each case; this is what occurs in the adoption process However, in research the objective should be to develop and give priority to the technology or technologies with the widest possible application and greatest impact, so that research resources can yield good returns. Thus the definition of research domains should strike a wise balance: not too general so as to be useless as a guide to research, nor too specific so as to apply only to a small number of farms or households.

The research team can assess the effect of its work on the research domain by answering the following questions:

· Which LUSs are most affected by the problem under investigation?

· Which systems can benefit (one hopes the majority) and to what extent can they benefit from the technologies being developed?

· What are the major conditioning and determinant factors, endogenous or exogenous to the farming system, for technology management and performance?

· What are the expected benefits and impacts of technology adoption?

The concept of research domain is a tool to facilitate and expedite the task of focusing on these key questions. If the team can answer them adequately, the concept has served its purpose.

4.5.3 Data Collection Methods

The D&D methodology employs several data collection methods appropriate to its specific objectives. Each method has its own strengths, weaknesses, degree of reliability of collected data, and resource requirements (Table 12). For example, the informal survey is fairly effective for identifying constraints, designing technology, promoting interdisciplinary interactions, and contributing to research planning, but the reliability of the data is not up to the standard of other methods. An informal survey also requires the most input from senior scientists, but its implementation is the quickest with minimum logistical and computer requirements. This offers a definite advantage if the research team does not have access to computer facilities.

D&D exercises should generate a minimum of raw data, a maximum of useful information, and in a timely matter. For this reason, the preliminary D&D work will take a rapid appraisal approach using secondary information surveys. D&D work at later stages in the research and development process will use methods that make a maximum contribution within the limits of available human and physical resources.

4.5.4 Analytical Methods and the Role of Farmers

The major decisions in the D&D analysis are derived using interactive and heuristic methods, with the principal actors being the D&D team and the farmers/households. This interaction should be based on solid information, consultation with development agents and policy-makers, and a commitment to arrive at logical conclusions in the process.

To ensure effective participation in discussions, all participants must show mutual respect and accept that each can make a valuable contribution. This should be reflected in observance of the following guidelines of behavior:

· understand a point from the other's perspective,
· criticize constructively, admit if wrong, stress the positive,
· reason - don't argue,
· explain thoroughly,
· offer helpful suggestions, and
· avoid snap judgements.

Table 12: CRITERIA TO SELECT D&D METHODS.

CRITERIA

METHODS

Secondary information

Key informants

Informal survey

Formal survey

Multi-visit survey

Technical monitoring

Case studies

OBJECTIVES









LUS description

1

3

3

1





Recommendation domain

1

3


2





Constraints identification


3

2


1

3



Technology design and evaluation



2


1

3



Research design and evaluation



3


1

2



Scientists' interact/on



1



2

3


Farmers' participation



2


1


3


Extensionists' participation


1

2


3

3


RELIABILITY (TYPE OF DATA)









Sectoral/Village

1

3


2





Household priorities, needs, etc.



1


1


3


Biophys. & S-Econ resources

2



1

3




Management:

Crops



3

1

1




Livestock



3

1

1




Trees




1

1

3



Performance:

Crops



3


2

1



Livestock



3


2

1



Trees



3


2

1


RESOURCES (COST)









Time/speed

1

2

3






Human resources

1


1

3





Logistic (ven., comp. etc.)

1

1

3





However, this does not mean that participants should accept everything said; there is a need to challenge, seek clarification, and discover the root causes of disagreements or conflicts. In this respect, the farmers should be treated as equal participants.

4.5.5 Logistical and Operational Aspect

For macro D&D, the total staff time required from planning to conclusion is estimated to be roughly 3 months. An approximate breakdown of the work schedule could be as follows:

· planning the study and orientation of the entire team - from 2 to 3 days;
· review and synthesis of secondary information - from 2 to 3 weeks;
· field work - from 2 to 3 weeks depending on the geographical size of the ecozone;
· final analysis and reporting - from 1 to 1.5 months.

The review work and report preparation do not require participation of the whole team; two members could do these with occasional assistance from the others. Computer support is not essential except, perhaps, for word processing.

For micro D&D, the total input of staff time and logistic support is approximately similar. However, a formal survey (i.e., a survey of 5-100 farmers with a semi-structured questionnaire) will normally constitute an important part of the study. Formal surveys require computer capability. In addition, the team may need to allocate relatively more time to the review of relevant agroforestry researcher and extension work to strengthen its analysis.

ICRAF, in collaboration with national institutions, can implement the entire sequence of a macro and micro D&D exercise in about eight months, including a short workshop after each phase to discuss and digest its results. Normally the process takes longer because the research team does not work on a full-time basis. In addition, ICRAF typically does not rush through, since the training objective is a high priority in such exercises - particularly for national scientists who have not been exposed to farming systems or on-farm research.

4.6 Summary

This technical paper has presented Diagnosis and Design (D&D) as a systematic and objective methodology used to initiate, monitor, and evaluate agroforestry research for development. It can be applied at the level of an agroecological zone (macro D&D) or at the level of a specific land use system (micro D&D). Methodological guidelines have been presented to explain how the D&D achieves its basic objectives, which are:

1. Describing and analyzing existing land use systems;
2. Diagnosing their constraints and causal factors;
3. Designing appropriate agroforestry technologies;
4. Designing appropriate research work; and
5. Identifying needs and opportunities for inter-institutional collaboration.

The key methodological considerations for D&D implementation are: the composition of the research team; the definition of research domains and recommendation domains; data collection methods; and logistical and operational aspects.

4.7 Feedback exercises (Find out answers from the text)

1. Match these terms to fill Up the blank spaces in sentences given below:

Terms: Technology, diagnosis, production systems, household, spatial arrangement, land use system, design, systems perspective, performance levels.

i) D and D stands for _________ and _________

ii) The basic unit of D & D analysis is _________ which can be defined at the level of country, ecozone, or household.

iii) The four main components of agroforestry technology are: 1) MPT species 2) _________ 3) _________ management regimes and 4) _________

iv) ICRAF has developed a research process for developing technologies to solve farmer's problems. This research process uses a _________ with an interdisciplinary approach.

v) Macro D & D is an analysis of an ecozone within a country while micro D & D is a detailed analysis of the _________ and _________.

vi) The three main types of screening to judge the potential of MPTs are: 1) general screening 2) _________ trials 3) management trials.

2. Place the following terms associated with the Agroforestry Research Process in their correct order of implementation.

· technology design
· technology testing
· Micro D&D
· Component experimentation
· Macro D&D
· Technology dissemination and adoption.

3. Circle A for agree and DA for disagree.

i) In selecting a study ecozone under macro D&D the single criterion used is the level of development of the ecozone with respect to other areas

A

DA

ii) The criteria for distinguishing one land use system from others vary depending on the factors that influence LUS managements and performance.

A

DA

iii) The delineation of an LUS is a one-time process based on the understanding of biophysical and socioeconomic potentials of the system.

A

DA

iv) Constraint analysis identifies two types of constraints namely modifiable and fixed, but does not explore causative factors.

A

DA

v) Constraint analysis is done concurrently with LUS characterization.

A

DA

4. In what way do macro D&D and micro D&D differ? Tick the correct answer.

i) In their three objectives.
ii) In their scope - macro D&D focuses on the ecozone while micro D&D on the farming system.
iii) In the composition of the multi-disciplinary team.
iv) In basic principles to achieve the three objectives.

5. a) Fill in the blanks. The three components of a research continuum to generate technologies are:

i) ________________________
ii) strategic research
iii) ________________________
iv) ________________________

b) Expand the following abbreviations.

i) LUS ________________________
ii) OSR ________________________
iii) OFR ________________________
iv) MPT ________________________

6. a) What are the two categories of scientists that form the macro D&D team. Which disciplines and subjects are represented in each category?

1) ________________________
2) ________________________

b) Differentiate between research domain and recommendation domain.

________________________
________________________

7. To complete a macro D&D analysis what is the suggested length of time for following stages:

i) ________________________ planning and teem orientation
ii) ________________________ review and synthesis of secondary information
iii) ________________________ field work
iv) ________________________ final analysis and reporting

4.8 Suggested reading and references

AFNETA. 1991. NARS Collaboration in AFNETA Research. Meeting Report Series Nos. 1 & 2. Ibadan, Nigeria: AFNETA.

Atta-Krah, A.N. and P.A. Francis. 1987. The Role of On-farm Trials in the Evaluation of Composite Technologies: The Case of Alley Farming in Southern Nigeria. Agricultural Systems 23 (1987): 133-152.

Djimbe, M. and J.B. Raintree, (eds.). 198X. Agroforestry Potential in the Humid Lowlands of Cameroon. AFRENA Report No. 12. Nairobi: ICRAF.

Hoekstra, D. 1988. Summary of Zonal Agroforestry Potentials and Research across Land Use Systems in the Highlands of Eastern and Central Africa. AFRENA Report No. 15. Nairobi: ICRAF.

Huxley, P.A. and P.J. Wood. undated. Technology and Research Considerations in ICRAF's "Diagnosis and Design" Procedures. ICRAF Working Paper 26, Nairobi.

Karanja, G.M. 1986. Recommendation Guidelines on Forages and Fodder for the Districts of Embu, Kirinyaga, Muranga, Meru and Nyeri. Pubs/3. Embu, Kenya: Embu Agricultural Research Station, P.O. Box 27.

Kwesiga, F. and I.N. Kamau (eds.). 1988. Agroforestry Potential in the Unimodal Upland Plateau of Zambia. AFRENA Report No. 7. Nairobi: ICRAF.

Minae, S. (ed.). 1988. Agroforestry Research Project Proposal for the Coffee-Based System in the Bimodal Highlands, Central and Eastern Provinces, Kenya. AFRENA Report No. 16. Nairobi: ICRAF.

Minae, S. and E. Akyeampong (eds.). Agroforestry Potentials for the Land Use Systems in the Bimodal Highlands of Eastern Africa, Kenya. AFRENA Report No. 3. Nairobi: ICRAF (1988).

Ngugi, D., editor. 1988. Agroforestry Research Project for the Maize-Livestock System in the Unimodal Upland Plateau (Chipata and Katete) in Eastern Province of Zambia. AFRENA Report No. 10. Nairobi: ICRAF.

Okorio, J. and D. Hoekstra, (ed.). 1988. Agroforestry Research Project Proposal for the Kigezi Annual Montane Food Crop System in the Highlands of Uganda. AFRENA Report No. 11. Nairobi: ICRAF.

Raintree, J.B. (ed.). 1987. D&D User's Manual. Nairobi: ICRAF.

Raintree, J.B. and K. Warner. 1986. Agroforestry Pathways for the Intensification of Shifting Cultivation. Agroforestry Systems 4 (1): 39-54.


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