• TABLE OF CONTENTS
HIDE
 Front Cover
 Gender issues in farming systems...
 Reference
 Permission page
 Working together: Gender analysis...
 Perspective on farming systems...
 Reference
 Gender issues in farming systems...
 Reference
 Farmers participation for more...
 Reference
 Permission letter
 Using male research and extension...
 Conclusion
 Reference
 Permission letter
 Office of international agricultural...
 Permission letter
 Genotype-by-environment interaction...
 Reference
 Permission letter
 Synthesis of north florida farming...
 Table of Contents
 Executive summary
 Purpose of synthesis
 What farming systems research and...
 History and social- economic characteristics...
 Farming systems: Clientele and...






Group Title: Farming systems approach to research and extension for small farms : USDAOICD Shortcourse TC 110-20
Title: Farming systems approach to research and extension for small farms
CITATION PAGE IMAGE ZOOMABLE PAGE TEXT
Full Citation
STANDARD VIEW MARC VIEW
Permanent Link: http://ufdc.ufl.edu/UF00056174/00001
 Material Information
Title: Farming systems approach to research and extension for small farms USDAOICD Shortcourse TC 110-20
Alternate Title: USDAOICD Shortcourse TC 110-20
Physical Description: 1 v. (various pagings) : ill., maps ; 28 cm.
Language: English
Creator: University of Florida -- Institute of Food and Agricultural Sciences
Publisher: International Training Division, Institute of Food and Agricultural Sciences, University of Florida
Place of Publication: Gainesville Fla.
Publication Date: 1992
 Subjects
Subject: Agricultural systems   ( lcsh )
Agricultural extension work -- Research -- Florida   ( lcsh )
Agricultural education   ( lcsh )
Genre: government publication (state, provincial, terriorial, dependent)   ( marcgt )
bibliography   ( marcgt )
conference publication   ( marcgt )
non-fiction   ( marcgt )
 Notes
Summary: A set of journal articles on farming systems projects and extension work bound together.
Bibliography: Includes bibliographical references.
Statement of Responsibility: International Training Division, Institute of Food and Agricultural Sciences, University of Florida.
General Note: "July 6 - August 7, 1992."
Funding: Electronic resources created as part of a prototype UF Institutional Repository and Faculty Papers project by the University of Florida.
 Record Information
Bibliographic ID: UF00056174
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: oclc - 70323093

Table of Contents
    Front Cover
        Front Cover 1
        Front Cover 2
    Gender issues in farming systems research and extension
        Page 147- 148
        Page 149
        Page 150- 151
        Page 152-153
        Page 154-155
        Page 156-157
        Page 158-159
        Page 160-161
        Page 162-163
        Page 164-165
    Reference
        Page 166-167
        Page 168-169
    Permission page
        Unnumbered ( 15 )
    Working together: Gender analysis in agriculture
        Page A 1
        Page A 2
        Page A 3 - A 4
        Page A 5 - A 6
        Page A 7 - A 8
        Page A 9 - A 10
        Page A 11 - A 12
        Page A 13 - A 14
        Page A 15 - A 16
        Page A 17 - A 18
        Page A 19 - A 20
        Page A 21 - A 22
        Page A 23
        Page A 24 - A 25
        Page A 26 - A 27
    Perspective on farming systems research and extension (Peter E. Hilderbrand)
        Page B 1
        Characteristics of selected systems ( Robert E. mcdowell and Peter E. hildebrand)
            Page B 2
            Page B 3- B4
            Page B 5 - B 6
            Page B 7 - B 8
            Page B 9 - B 10
            Page B 11 - B 12
    Reference
        Page B 13 - B 14
        Page B 15
        The sondeo: A team rapid survey appraoch (Peter E. Hildebrand)
            Page B 16
            Page B 17 - B 18
            Page B 19 - B 20
            Page B 21 - B 22
            Page B 23- B 24
            Page B 25
        Permission letter
            Unnumbered ( 46 )
    Gender issues in farming systems research and extension
        Page C 1
        Research, recommendation and diffusion domains: A farming systems approach to targeting
            Page C 2
            Page C 3 - C 4
            Page C 5 - C 6
            Page C 7 - C 8
            Page C 8 - C 9
            Page C 10 - C 11
    Reference
        Page C 12 - C 13
        Page C 9
    Farmers participation for more effective research in sustainable agriculture
        Page D 1
        Page D 2
        Page D 3
        Page D 4
        Page D 5
        Page D 6
        Page D 7
        Page D 8
        Page D 9
        Page D 10
        Page D 11
        Page D 12
        Page D 13
        Page D 14
        Page D 15
        Page D 16
        Page D 17
        Page D 18
        Page D 19
        Page D 20
        Page D 21
    Reference
        Page D 22
        Page D 23
        Page D 24
        Page D 25
        Page D 26
        Page D 27
        Page D 28
        Page D 29
        Page D 30
        Page D 31
        Page D 32
        Page D 33
        Page D 34
        Page D 35
        Page D 36
        Page D 37
        Page D 38
    Permission letter
        Unnumbered ( 94 )
    Using male research and extension personnel to target women farmers
        Page E 1
        Page E 2
        Page E 3
        Page E 4
        Page E 5
        Page E 6
        Page E 7
        Page E 8
        Page E 9
        Page E 10
    Conclusion
        Page E 11
    Reference
        Page E 12
        Page E 13
        Page E 14
        Page E 15
        Page E 16
        Page E 17
        Page E 18
        Page E 19
        Page E 20
        Page E 21
        Page E 22
        Page E 23
        Page E 24
        Page E 25
        Page E 26
    Permission letter
        Unnumbered ( 121 )
    Office of international agricultural programs U.S. aid title XII strengthening grant
        Page F 1
        Page F 2
        Page F 3
        Page F 5 - F 6
        Page F 7 - F 8
        Page F 9 - F 10
        Page F 11 - F 12
        Page F 13 - F 14
        Page F 15 - F 16
        Page F 17 - F 18
        Page F 19 - F 20
        Page F 21 - F 22
        Page F 23 - F 24
        Page F 25 - F 26
        Page F 27 - F 28
        Page F 29 - F 30
        Page F 31 - F 32
    Permission letter
        Unnumbered ( 139 )
    Genotype-by-environment interaction and plant breeding
        Page G 1
        Page G 2
        Page G 3
        Page G 4
        Page G 5
        Page G 6
        Page G 7
        Page G 8
        Page G 9
        Page G 10
    Reference
        Page G 11
        Page G 12
        Page G 13
    Permission letter
        Unnumbered ( 153 )
    Synthesis of north florida farming systems project, univeristy of Florida, 1981-1984
        Page H 1
        Page H 2
    Table of Contents
        Page H 3
    Executive summary
        Page i
        Page ii
        Page iii
        Page iv
        Page v
    Purpose of synthesis
        Page 1
    What farming systems research and extension is
        Page 1
        Page 2
        Page 3
    History and social- economic characteristics of suwannee and columbia countries : An overview
        Page 4
        Page 5
        Page 6
        Page 7
    Farming systems: Clientele and problem- oriented research of the FSR/E team
        Page 8
        Historical development ofthe North Florida FSR/E project
            Page 8
            Page 9
            Page 10
            Page 11
        The North florida FSR/E clientele
            Page 12
            Page 13
            Page 14
            Page 15
            Page 16
        Clientele problems and proposed alternatives identified by the team
            Page 17
            Page 18
            Page 19
            Page 20
            Page 21
            Page 22
            Management
                Page 23
            Drought and soil compaction
                Page 24
            Grain crops
                Page 25
            Fertility
                Page 26
            Need for forage crops
                Page 26
            Other alternatives
            Summary
                Page 27
                Page 28
                Page 29
        Discussion of research results
            Page 30
            Page 31
            Page 32
            Page 33
            Page 34
            Page 35
            Page 36
        Numbers of collaborators
            Page 37
            Collaboration: meaning and benefits for farming systems approaches
                Page 37
                Page 38
            Farmer collaborators
                Page 39
                Page 40
                Page 41
        Orangization: Development, problems and proposals
            Page 42
            Administration
                Page 42
                Page 43
                Page 44
                Page 45
                Page 46
            Budgets
                Page 47
                Page 48
            Administrative problems
                Page 49
                Page 50
            Synopsis of 1983 external review
                Page 51
                Page 52
Full Text


Farming Systems Approach
to Research and Extension
for Small Farms

USDA/OICD SHORTCOURSE TC 110-20

July 6 August 7, 1992


sw; *~ i
i ;M E MO'' '1 ~ '


International Training Division
Institute of Food and Agricultural Sqiences
University of Florida


'60--s





























THE FOLLOWING SELECTION
HAS BEEN PRINTED
WITH PERMISSION

DATE: 07/02/92


Author: POTS, SCHMINK & SPRING

Title: Chapter 6 and Chapter 7

Book: GENDER ISSUES IN FARMING SYSTEMS
RESEARCH AND EXTENSION

Volume: No: Pgs: 73-87,149-169 Copyright Year: 1987

Reprinted by Permission of: Westview Press Inc.


THIS MATERIAL MAY NOT BE
REPRODUCED IN ANY MANNER
WITHOUT THE PERMISSION
OF THE COPYRIGHT HOLDER










Gender Issues in Farming Systems
Research and Extension
edited by Susan V. Poats,
Marianne Schmink, and Anita Spring
issues of increasing agricultural productivity for small-scale
and the critical role of women in agriculture are brought together
state-of-the-art book. Based on the 1986 University of Florida
-nce of the same title, this volume includes theoretical and
lological papers as well as case studies examining the topics of
. intra-household dynamics, labor- allocation, and crop and live-
;ystems in agricultural production, research, and extension.

in V. Poats is associate director of the Farming Systems Support
at the University of Florida. Marianne Schmlnk is associate
.or of Latin American studies and was co-director of the Women
cultural Development Program, 1984-1986. Anita Spring is
ite professor of anthropology and associate dean of the College
; and Sciences at the University of Florida and was the director
Women in Agricultural Development Program.


I.,





*


~~~1


edited by

Susan V Poats, Marianne Schmink,
and Anita Spring




Gender Issues in

Farming Systems Research

and Extension



?,* '


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Westview Snecial Studies in AN: cii.rr q.cir-nce and Pc'~ -'.


I....... ...r... TSRN n0-8133-7399-9 F )












11
Gender, Resource Management and
the Rural Landscape: Implications for
Agroforestry and Farming Systems Research
Dianne E. Rocheleau M.

Agroforestry is a form of land use and management
familiar to millions of farmers and forest-dwellers
throughout the world. Formally, agroforestry is any system
of land use in which woody plants are deliberately com-
bined, in space or over time, on the same land management
unit as herbaceous crops and animals (Lundgren 1982). This
definition applies to a variety of land use systems ranging
from very intensive farming to extensive pastoral systems,
including: bush fallow farming; management of fodder trees
in private or communal grazing lands; planting of trees and
shrubs as live fences on farm boundaries for fuelwood,
small timber, and other useful products; intercropping of
tree cash crops with food, timber, fodder and soil
improving crops; ihtercropping of hedges with grain crops
for leaf mulch; home gardens of all types where trees and
annual crops are mixed; and many other systems where far-
mers and herders combine trees with field crops or animals
(Rocheleau 1986). In many of these systems women are pri-
marily responsible for planting, tending, gathering, har-
vesting, processing, and using woody plants, in addition to
performing their roles in crop and animal production and
consumption within the larger agroforestry system.
Agroforestry systems reflect the prevailing sexual.
division of labor, skill, responsibility, and control
within the larger society. In cases where new systems are
introduced, precedents may be set for the sexual division
of costs and benefits from new classes of plants or types
of work not previously known in the same way. The success
or failure of future research efforts to improve existing
agroforestry systems or to develop new ones will depend
largely on the ability of researchers to serve the social
objectives of diverse groups of rural producers and to
reconcile or accommodate the conflicts between men and
women and between classes of rural clients.




While an overall farming systems approach is an appro-
priate starting point, an effective, equitable approach to
agroforestry requires something more. Among those aspects
that demand a broader approach are the system-wide scope of
the topic, the variable scale of the land units involved
(plot to watershed or community), the variety of clients
and land managers,'the diversity of activities involved,
the combination of production and environmental objectives,
the time factor required for testing and growing trees, and
the relative ignorance of researchers about the past and
current use of woody plants by farmers and herders
(Rocheleau 1986). These characteristics overlap to some
extent with gender and class issues. All of these factors
combined require a more comprehensive and complex approach
than might be needed to deal with gender issues in
crop-based farming systems research and extension (FS/VE).
The problems and opportunities inherent in the gender
division of access to land, labor, cultivated and wild
plants, and products present a special challenge to agro-
foresters. They require specific consideration and pro-
grams not yet part of the mainstream approach to agro-
forestry research and development projects. The implica-
tions of these differences extend to the content of tech-
nology designs and social contracts for management as well
as to the way that research and development is conducted
with women clients. Gender based differences in legal sta-
tus, use of and access to space, type of activities, and
control over labor and resources, all have a direct bearing
on what type of plants can be planted, managed, used and
harvested, in terms of place, person, purpose, and benefit
(Rocheleau 1987b).
Whether or not women are considered apart or as a
distinct client sub-group within the larger population, the
terms of their participation will usually be distinct from
that of men. This is especially true with regard to the
quantity, quality, and terms of access to land. Women's
access to other productive resources (water, draft power,
agrochemicals, labor, information) also differs from men's.
Moreover, women's control over the components (animals,
crops, trees, shrubs, pasture) and the products (food,
fodder, fuel, timber, cash, fiber, medicine) of
agroforestry systems is often subject to rules distinct
from those governing men's actions. All of these
differences are expressed in the existence of men's and
women's separate places and activities, in nested
complementary roles in the same places and activities, or
in sharing of interchangeable roles.
While these differences may limit the scope and nature
of agroforestry technology and project design, there are


also distinct advantages and opportunities for agroforestry
within women's separate domains of space, time, activities,
interests, and skills. Women may also have special know-
ledge, rights, and obligations relating to certain cate-
gories of artifacts (tools), natural objects, and phenomena
(water, fire, plants, animals).
Agroforestry may impose new demands on women clients
such as the need to negotiate new arrangements for use and
management of shared lands, labor, or capital inputs, to
learn new skills, and to observe more careful management of
soil, water, plants, and animals in existing woodland,
cropland, pasture, or boundary lands. Agroforestry may
also validate women's land and tree use rights or owner-
ship, increase production and decrease gathering time, and
reconcile conflicting objectives for shared household or
community plots.
A few project histories (Hoskins 1979; Scott 1980; Wiff
1984; Jain 1984; Fortmann and Rocheleau 1984) and a wealth
of experience in traditional and evolving agroforestry
systems suggest that rural women and agroforestry programs
have much to gain from a well-informed and well-defined
association. Among the explicit gender issues of relevance
to women's participation in agroforestry projects are
women's legal status and access to productive resources,
and the division of space, time, knowledge, and decision-
making.
This heightened awareness of gender issues has surfaced
at a time when agroforesters and social foresters are still
learning to involve the population at large (FAO 1985) and
to think in terms of "clients" rather than "targets." Much
of the action research and organizational experiments
required to find viable rules of tree and land ownership,
as well as access to and management by women, can be nested
within broader programs based on a land user perspective.
A general land user perspective for agroforestry
research and development programs should consider multiple
uses, multiple users, landscape as a major focus in a
larger context of sliding scale analysis and design, and
consideration of indigenous knowledge as science. In
addition to these four conditions for understanding and
serving users' interests, the terms of client participation
must be considered. Treating land users as clients is a
critical ingredient in the successful integration of users'
concerns into analysis, design, and action. "Clients" may
be seen as passive recipients ci services or active paLti-
cipants. Incorporating clients as active participants pro-
duces the best results for development projects and builds
local capabilities for continued agroforestry analysis,
design, and management efforts (Rocheleau 1987b).






An overall land user perspective constitutes a neces-
sary but not quite sufficient condition for serving women's
interests in agroforestry. The explicit acceptance of
women as valid clients in their own right would permit the
broadest participation of women whether or not they are in
households headed by men or heads of their own households,
and are artisans, processors, merchants, smallholders, or
landless laborers.
This is not to say that women's issues should be
absorbed into a single homogenized agenda. There is still
a need to disaggregate information, decisions, and action
to assure reasonable and equitable distribution of land,
trees and their products, and program costs and benefits to
all clients. A land user perspective with equity must deal
with women's relationship to the larger community as well
as with the very real differences between groups of women,
based on class, age, ethnicity, and sources of livelihood.
A brief outline of a land user perspective for agro-
forestry research and development illustrates how it can
serve various women's interests.

A LAND USER PERSPECTIVE FOR EQUITY IN AGROFORESTRY

Multiple Uses

Agroforestry is a land use system, not a commodity. It
can address a wide range of rural people's priorities for
fulfillment of basic needs (Raintree 1983). Agroforestry
practices may apply to cash crops, subsistence crops, ani-
mal production, and gathered products, as well as to farm
infrastructure and to the soil, water, and natural vegeta-
tion on the site. Among the major needs that are affected
by agroforestry are: food, water, fuel, cash income, shel-
ter and infrastructure, savings/investment, and resources
to meet social obligations.
A land user approach to the development and implemen-
tation of agroforestry technologies requires design and
evaluation according to a complex set of criteria that goes
far beyond simple economic cost and benefit.
Considerations of need, preference, and multiple use must
be balanced against available resources, required inputs,
risk, and expected yields.
In rural areas all over the world, women are providers
of a wide range of subsistence goods, including water,
fuel, food, fodder for confined animals, fiber for handi-
crafts and other "minor" products of range, forest and
fallow lands. As such, they have much to gain from
development approaches like agroforestry that incorporate a


wide range of products, services, and concerns beyond cash
crops, livestock, and staple grains.
Beyond their concerns in crop and livestock production,
women's responsibility for household water and energy sup-
plies gives them a special interest in the long term main-
tenance of the natural resource base (soil, water, vegeta-
tion). Researchers must pay specific attention to the
history of resource use and condition, and to potential
improvements in soil conservation, watershed management,
and management of range and forest lands (Rocheleau and
Hoek 1984).

Multiple Users

Any program that purports to serve the majority of
rural people is by definition dealing with a diverse array
of land users, many of whom are women. Even projects spe-
cifically geared to "target groups", such as farmers, will
find that their target group may include non-farming land
users. Farmers also depend on a number of items they do
not produce, such as gathered products. Farmers' liveli-
hoods may be inextricably tied to those of gatherers, pro-
cessors, merchants, artisans, farmworkers, herders, or
forest dwellers.
Within a target group loosely defined as farmers there
may also be several types of actors, often women, who
neither own nor manage the farm. Women and children in
farm households perform such essential operations as paid
and unpaid farm labor, child care, home management, domes-
tic and commercial processing, gathering of goods for farm
household use or sale, and management of livestock and
household gardens. If all women land users are to be fully
served as clients, then agroforestry research and action
must also address gathering, processing, trade and consump-
tion as well as production processes in the farm household
and community system.
For example, agroforestry technology design should con-
sider landless men and women, who tend to depend more
heavily on gathering than the population-at-large in many
farming communities. Whereas wealthier women may gather
more on their own land or have easy access to other lands,
landless people and women small-holders share problems of
insecure access to shared collection areas. A change in
the cropping system, a new chemical herbicide, or a change
in tree species in bush-fallows may have important "side
effects" on gatherers. Agroforestry technologies can be
specifically tailored to maintain or increase the flow of
"by-products" to particular groups, including women.








IAL FODDER


FIGURE 11.1

PANANAO SIERRA, DOMINICAN REPUBLIC

This figure demonstrates the multi-purpose use of land and
trees in Pananao assuming that both men and women are
present in the household. R = responsibility to provide a
product thereof to household; 1 = labor input for estab-
lishment, maintenance or harvest; c = control of resource
or process.


Source: Rocheleau, D. (1987a)


A multiple user approach also allows for separation
between spheres of activity and control between men and
women, between age groups and between classes of house-
holds. "Management" of specific plants or places may be
subdivided between these same groups. Examples abound of
the need for agroforesters to deal with multiple users as
clients even with respect to single tree species. The case
of Pananao in the Central Mountains of the Dominican
Republic (see Figure 11.1) illustrates the multiple and
sometimes conflicting uses of individual palm trees by men
and women. The same tree or parts thereof can be used for
fiber by women, cheap construction wood by men, and animal
feed by men and women.
In Pananao, the distinct division of control and
responsibility over resources and labor extends to spaces
and activities as well as to plar. : or specific products.
Women's processing activities require products from men's
fields, herds, and woodlands. While women control the
processing enterprise, they do not manage source areas of
raw materials. In this community, some cassava bread
enterprises have been severely curtailed by fuelwood short-
ages resulting from rapid conversion of woodlands to
cropland and pasture by men (Rocheleau 1984). Women's
handicraft enterprises also suffered from raw material
shortages when swine fever reduced demand for palm fruit
for hog feed and men felled the palms for cheap building
materials or cash (E. Georges 1983, pers. comm.).
Agroforestry design in such situations clearly requires
consultations with both men and women to design agrofores-
try practices that address the needs of each group, whether
separately or jointly. Agroforestry technologies for mul-
tiple users can accommodate separate, fully shared, or
interlocking (partially shared) use depending on the com-
patibility of both the uses and the users.

THE RURAL LANDSCAPE AS CONTEXT AND FOCUS

The landscape embodies spatially and over time rural
people's ideas of their relation to each other and to the
natural environment. Visible landscape patterns and fea-
tures provide an excellent point of departure for deter-
mining the spatial distribution of men's and women's do-
mains of activity, responsibility, control, and knowledge.
During the past few years, many societies have experienced
dramatic changes in the division of space and activity due
to the introduction of cash cropping, commercial logging,
and other enterprises.
The process of "landscape domestication" in rural areas
presents a challenge for agroforestry design and practice.






While this aspect of rural development has been left in the
gap between natural resource management, farming systems
research, and rural women's programs, it is precisely at
this level that many rural people integrate trees, crops,
and livestock with personal and community needs and objec-
tives. It is also the site of many gender-based land use
conflicts. In many areas women are moving rapidly into
activities and spaces formerly occupied by men, though
often with less security of access to productive resources.
The rural landscape is the drawing board for integrated
agroforestry diagnosis and design beyond the single farm or
the individual plot (Rocheleau and Hoek 1984). Since women
are responsible for collecting water, fuelwood, and other
"off-farm" resources, they have a vested interest in the
planning of the larger landscape. Women's access to off-
farm lands, woodland and water resources, and gathered
products can be better addressed when landscape is fully
integrated into agroforestry analysis and design.
Tenure is inextricably tied to the evolution and design
of landscape, and to the place of women's resources and
interests in the landscape. Land and tree tenure are
particularly important for tree planters and managers,
compared to annual cropping that is more ephemeral or
animal husbandry which is a more mobile enterprise. Where
agroforestry designs apply to several categories of land,
land use, and plants in a complex landscape, then tenure
assumes even greater importance.
Community development cycles (settlement, expansion,
diversification, land use intensification) will determine
in large part the future availability of landscape niches
for women's agroforestry activities at the community level.
Oral history and discussions of possible future scenarios
with women and the community at large may provide some
insights into current trends. The choice of agroforestry
practices and landscape designs appropriate for rural women
requires their involvement from the beginning in whole
community applications as well as in individual farm
planning.
Within the context of landscape planning and design, a
diverse array of agroforestry technologies can address a
wide range of land use and production units. These units
may range from small plots to farms, watersheds, communal
holdings, and public lands. The managers may be men or
women, acting as individuals/households or as whole ethnic
groups, cooperatives, communities, or larger political
units. Land use planning at multiple scales requires an
integrated social and ecological approach to agroforestry
that deals with the division of labor, responsibility,
expertise, control, and interests at the intra-household,


inter-household, and community level. To deal with this
complexity, a user approach in agroforestry research and
development must stratify clients by class, sex, household
composition, and social organization, as it affects access
to resources and spatial patterns of activity and resource
use.
An example from Bhaintan watershed in the Lower
Himalayas, Uttar Pradesh State, India (Raintree et al.
1985) illustrates the role of gender in the interplay
between multiple users and landscape units in analysis of
agroforestry potentials. The landscape sketch (Figure
11.2) shows the distinct division in land use and cover
which is closely related to tenure. There is a pronounced
division of use control, and access to specific landscape
features, based on sex.
The relative share of production (and land use pres-
sure) from a given area also varies by user group (Figure
11.3). In turn, the relative importance of particular
areas to each user group also varies. In this case, the
forest reserve is most heavily used by men, yet it is most
important to poor women in terms of its relative con-
tribution to their livelihood. While women's harvest from
the forest may be "minor" compared to men's timber offtake,
the forest products are-major components of women's total
income. Moreover, poor women's interest in renewable use
and sustained yield may be more compatible with national
and village level objectives for the commons and forest
reserves.
The potential for commercializing minor forest products
versus timber resources in the Himalayan foothills is a
good example of this (Surin and Bhaduri 1980). Women are
already interested and involved in cash enterprises based
on gathering, processing, and retailing of many forest
products, and might be best server by projects to improve
and sustain that activity rather chan by planting new
stands of trees that will not yield products for processing
by women. Since women's enterprises depend largely on
renewable products, this presents an opportunity for an
agroforestry system to serve women-as-gatherers, while
ensuring sustainable, renewable resources.

THE ROLE OF INDIGENOUS KNOWLEDGE

Agroforestry as a "formal" science is in a unique posi-
tion to learn from and to improve upon traditional know-
ledge and practice and to combine forces with indigenous
experimental initiatives (Rocheleau and Raintree 1986).
The relative ignorance of the research community about
.woody plants used by rural people implies a special need























FOR WOMEN


FOR POOR WOMEN


FIGURE 11.2

FAKOT VILLAGE, BHAINTAIN WATERSHED, UTTAR PRADESH, INDIA

R, L, and C have the same meaning as in Figure 11.1.

Source: Rocheleau, D. (1987a)


FIGURE 11.3

SOURCES OF LIVELIHOOD (CASH & KIND) IN FAKOT
(by relative importance to land user).

Source: Rocheleau, D. (1987a)


FOR MEN






for ethnobotanical research to identify promising species
(woody and herbaceous) for agroforestry systems and to
understand what is already known about these plants' inter-
action with soil, animals, other crops, and their uses,
ownership, and management. Within the context of such
initiatives, women's knowledge, skills and interests can
change the content and approach of future agroforestry
research and action programs to serve women and the rural
population at large better.
There is a tremendous depth of indigenous knowledge
about particular traditional agroforestry systems under
very site-secific circumstances (von Maydell 1979;
Fernandes and Nair 1986; Flores Paitan 1985; Brokensha et
al. 1983; Budowski 1983; Okafor 1981; Weber and Hoskins
1983; Clay 1983). Existing knowledge can span the full
range of design and management considerations: site
selection, preparation and management; plant selection
and/or breeding; plant propagation; establishment and
management; plant combinations and spatial arrangements;
plant-soil-water interactions; pest management; techno-
logies for processing and use of products; and market
conditions at local and regional levels. Men's and women's
knowledge of these various aspects of traditional agro-
forestry systems is often quite distinct and may require
separate documentation and discussion (Hoskins 1979).
Existing and potential agroforestry systems include a
particularly diverse array of species, both woody and
herbaceous, many of which are wild or only semi-
domesticated thus far. In cases where agroforestry is not
well developed as such, the local people may still have a
wealth of knowledge about useful plant species, including
source areas of superior parent material, the ecology of
the plant habitat, compatibility with other plants, inter-
action with animals and insects, growth rate, method of
regeneration, and response to variation in site conditions
and management practice. Women and men will often have
distinct skills and knowledge for use of natural vegetation
in forests and rangelands. They may each have different
knowledge about the same plants and places, or their exper-
ience may be divided by species or by ecosystem.
Rural people can also play a key role as consumers in
deciding the criteria for the selection and improvement of
agroforestry germplasm and in judging the likelihood of
domesticating particular species. Women's knowledge as
consumers and processors of many tree products should
figure strongly in any user-focused program of germplasm
selection and improvement (Hoskins 1983).
The incorporation of both men's and women's knowledge,
experience, and experimental initiatives into agroforestry


research plans is illustrated by research on the chitemene
system of shifting cultivation in the miombo woodland of
north east Zambia. The area is rich in examples of indi-
genous knowledge as well as its dynamic application to
technology innovation.
The classic chitemene system involves the felling and
harvest of woody vegetation on a 1-5 hectare plot, followed
by piling and burning the collectL wood from the entire
area on a sub-plot approximately one-fifth of the total
area. The combination of high heat and woody biomass
results in higher soil pH and fertility on the burned plot
(Mansfield 1975). The crop rotation follows a six year
cycle beginning with finger millet, maize, cassava, and
perennial sorghum intercropped with yams, gourds, pumpkin
and cowpea on the periphery or on termite mounds. Ground-
nuts are planted next, followed by cassava maturation and
harvest, and two to four years of bean cultivation (Figure
11.4) after which the plot is left in woody fallow for
several years. Most households maintain at least four
fields in different stages of the cycle so as to produce
the full range of major crops (millet, groundnut, cassava,
and beans) in any one year (Stollen 1983; Vedeld 1981; Haug
1981). The long term effects of this system on soil
fertility vary with the length of the fallow with a trend
toward shorter fallows and sharp declines in site
productivity (Mansfield 1975).
An informal survey of the land users in the vicinity of
the Misamfu Research Station revealed a wealth of informa-
tion and opportunities for collaborative experiments on
farmer-initiated innovations and farmer-defined lines of
research. The survey incorporated a user perspective,
which included consultation with both men and women land
users as clients, consideration of multiple uses, multiple
users, and a sliding scale of analysis from region to plot
with emphasis on landscape features and land use at the
farm and community level. The method and content of these
consultations encouraged people to draw upon and explain
specific items from traditional bodies of knowledge, as
well as their methods and rationale for developing or
adapting new technologies (Huxley et al. 1985; Mattson, in
press).
Several points of information proved to be critical for
the design of new agroforestry technologies for testing on-
farm or on-station and for agroforestry research planning
at the Misamfu station.
First, many farmers are actively engaged in experimen-
tation with mounding as a way of incorporating plant bio-
mass (usually grass, with some tree and shrub parts) into
the soil. The mounding of loose topsoil over plant biomass






































FIGURE 11.4

MISAMFU, N.E. ZAMBIA

This figure shows the Chitemene system in northeast Zambia,
including new practices observed near Misamfu. Note that
women control the millet crop (one of several in the
intercrop rotation.) R, L, and C have the same meaning-as
in Figure 11.1.

Source: Rocheleau, D. (1987a).


has been adapted from the grass mounding technology of a
neighboring savannah group. It is being tried in permanent
or long term plots planted to beans, or beans and cassava,
in women's home gardens planted to beans, cassava, fruits,
vegetables, and specialty crops, and it is used in the
latter part of the cycle on chitemene plots to prolong the
useful life of the plot for bean and/or cassava production
(Huxley et al. 1985; Haug 1981). Second, women's home
gardens are becoming increasingly important for food
production and cash income and are being diversified to
include fruit trees. Some women are experimenting for the
first time with tree planting in such gardens. Mounding,
raised beds, and clean tilled plots are all being tried,
with a tendency toward mounding in the larger gardens.
Women heads of household rely heavily on cassava home
gardens for food production to supplement what they can buy
with wages. For women without male household labor for
chitemene clearing, the home garden, beer making, and
cassava processing are important alternatives to earn cash
to buy food. Most garden experiments reflect a desire to
intensify land use on small plots and to diversify
processing enterprises (Stollen 1983; Huxley et al. 1985).
Two women farmers' experiments were especially note-
worthy. One woman conducted a trial with low level ferti-
lizer application on a clean tilled plot with millet and
cassava, with a partial control (clean tilled, no fertili-
zer). This trial combined the site preparation technique
for monocropped maize with lower fertilizer levels and tra-
ditional chitemene crops. The result was increased millet
yield, with lower cost and less risk than maize. The woman
who conducted the experiment wanted millet for home con-
sumption and beer brewing. Another woman planted soybeans
on clean-tilled plots for soya milk, prompted by a concern
for nutrition and by free seed provided through her daugh-
ter's participation in an urban women's program in the
mining district (Huxley et al. 1985).
Both men and women indicated several important roles of
woodland and fallowland products in the household diet and
economy (both commercial and subsistence). Woodland and
fallow areas are major sources of wild leafy vegetables,
and exclusive sources of mushrooms and caterpillars, that
occur mostly on one tree species, Julbernardia paniculata
(S. Holden, pers. comm.). Caterpillars and wild leafy
vegetables are major sources of protein and both mushrooms
and caterpillars are important sources of cash income for
most households. All three products fall within women's
. domain of responsibility as providers and may be processed
or sold by them. Timber (men's responsibility), fuelwood






(women's responsibility), and wild fruits were also cited
as important woodland products, with supply problems
occurring mainly near towns and old villages (Huxley et al.
1985; Mattson, in press).
Trees play an important part in the land use system,
including those planted or "kept" in home compounds, fal-
lows, and cropland as well as those found in woodland. A
considerable body of knowledge and experience exists with
respect to both indigenous and exotic, wild and domesti-
cated species. Some men had extensive knowledge of exotic )
fruit tree horticulture, including layering and grafting
techniques. Both men and women readily identified their
respective favorite non-domesticated tree species by use,
those species in short supply, and those that they would
consider planting now, or in the future in the event of
limited supplies or access (Huxley et al. 1985). Both men
and women also provided information on site requirements,
potential for management (tolerance to coppicing, pol-
larding), relative growth rates, and relative leafy biomass
production for several species that occur in miombo
woodland succession (Mattson 1985; Huxley et al.1985).
While both men and women knew the miombo woodland ecosystem
well, their experience tended to be diided by species.
In spite of the extent of the surrounding woodlands,
many farmers surveyed were often conscious of relative land
limits based on proximity to markets, rivers, and roads.
Most people were concerned about defining and securing
their land rights prior to the imminent return of the
mining population to their home area. People's decisions
to intensify cropping in place or to expand their cropland
varied mainly with household composition, village develop-
ment cycles, and the quality of the village site and ser-
vices. In many cases people were unwilling to move out and
away into outlying woodlands, and they chose instead to
intensify production.
Many women heads of households and sub-households cited
woodland gathering and home garden intensification as their
best strategies to supplement household food supply and
cash income. As a group they were less able to move into
new woodland areas and they expressed a greater interest in
more intensive use of both woodlands and farmlands.
If national programs are prepared to follow the lead of
rural land users, knowledge of indigenous science and
users' initiatives may alter national agricultural and
rural development policy. Useful information and tech-
niques can best flow from the scientific community to the
rural land users once its known what they already know, and
what else might be most useful to add to their store of
knowledge and tools. A well-informed basis for


agroforestry research and action programs must incorporate
and address women's and men's distinct domains of both
knowledge and concern.

CONCLUSION

Women's interests in agroforestry research and develop-
ment will not be the same everywhere. They will usually be
nested within a larger tangle of conflicting and comple-
mentary relationships between and within rural households.
Whether or not ownership is legally demarcated, most rural
people operate in overlapping domains of access and con-
trol on a variety of resources involving a complex array of
activities and purposes. Technological changes in domains
controlled by men may drastically alter the terms of
access, control, production, and ecological stability on
shared lands and resources, or in women's separate places
and activities. Aside from the differential effects of
technology and land use change on men and women, the inter-
ests of different groups of women may diverge signifi-
cantly. Among the factors that may divide women's
interests are age, class, household composition, ethnic
group, location, and sources of livelihood.
The proposed land user perspective can incorporate
women as one of a number of valid client groups and active
participants in agroforestry research and action programs.
This approach can address women's distinct needs, con-
straints, opportunities, and interests in agroforestry
technology and land use innovations. Since it is based on
a premise of dealing with multiple users and multiple
interests in any given place, the land user perspective
c'an also accommodate both women's relationship to the
larger community and the differences between groups of
women within a given community. This approach combines an
explicit concern for women's interests with a commitment to
address those interests within the larger web of social and
ecological relationships in which they live.

NOTES AND ACKNOWLEDGEMENTS

A similar version of this paper was published in
a book edited by H. Gholz, 1987. Agroforestry: Realities,
Possibilities and Potential. Boston, MA: Martinis Nijhoff,
in the chapter entitled: The User Perspective and the
Agro-forestry Research and Actior Acenda.




REFERENCES


Budowski, G.
1983 An Attempt to Quantify Some Current Agroforestry
Practices in Costa Rica. In Plant Research and
Agroforestry. P. Huxley, ed., pp. 43-62. Nairobi:
ICRAF.
Brokensha, D., B. W. Riley and A.P. Castro
1983 Fuelwood Use in Rural Kenya: Impacts of
Deforestation. Washington, D.C.: USAID.
Clay, J.
1983 A Bibliography of Indigenous Agroforestry
Systems. Draft, unpublished manuscript.
FAO
1985 Tree Growing by Rural People. Review Draft.
Forestry Policy and Planning Series. Rome: FAO.
Fernandes, E.M.C. and P.K.R. Nair
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Tropical Home Gardens. ICRAF Working Paper 38.
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Flores Paitan, S.
1985 Informe Sobre el Papel de Umari en los Sistemas
de Produccion Agroforestal en Fincas de la Poblacion
Indigena y los Mestizos en la Zona de Iquitos.
Manuscript. Peru: University of Iquitos.
Fortmann, L. and D. Rocheleau
1984 Why Agroforestry Needs Women: Four Myths and a
Case Study. Unasylva 36:146.
Haug, R.
1981 Agricultural Crops and Cultivation Methods in
the Northern Province of Zambia. Occasional Paper
1, Dept. of Agricultural Economics: Agricultural
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Hoskins, M.
1979 Women in Forestry for Local Community
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D.C.: USAID Office of Women in Development.
1983 Rural Women, Forest Outputs and Forestry
Projects. Rome: FAO.
Huxley, P.A., D. E. Rocheleau and P.J. Wood
1985 Farming Systems and Agroforestry Research in
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Use Problems and Research Indications. Nairobi:
ICRAF.
Jain, S.
1984 Standing Up for the Trees: Women's Role in the
Chipko Movement. Unasylva 36:146.


Lundgren, B.
1982 Introduction. Agroforestry Systems 1:3-6.
Mansfield, J. E.
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Province, Zambia. Supplementary Report 7. Land
Resources Division, Ministry of Overseas
Development, United Kingdom.
Mattson, L.
1985 Summary Report on Survey of Farm Level Problems,
Needs, Existing Strategies and Knowledge of Miombo
Woodland Species. Misamfu, Zambia: Zambia Ministry
of Agriculture and Water Development SPRP.
n.d. Landscape Analysis of Agroforestry Systems in
Northeast Province. Agricultural University of
Norway, As. (In press).
Maydell, H. von
1979 Agroforestry to Combat Desertification: A Case
Study of the Sahel. In Agroforestry: Proceedings
of the 50th Symposium on Tropical Agriculture, pp.
11-24. Bulletin 303. Amsterdam, The Netherlands:
Department of Agricultural Research, Konink Lijk
Institute voor de Tropen.
Okafor, J. C.
1981 Woody Plants of Nutritional Importance in
Traditional Farming Systems of the Nigerian Humid
Tropics. Ph.D. Dissertation, University of Ibadan,
Nigeria.
Raintree, J. B.
1983 A Diagnostic Approach to Agroforestry Design.
Proceedings of the International Symposium on
Strategies and Designs for Afforestation,
Reforestation and Tree Planting, Hinkeloord,
Wageningen, The Netherlands, Sept. 19-23.
Raintree, J.B., D. Rocheleau, P. Huxley, P. Wood, and F.
Torres
1985 Draft Report on the Joint ICAR/ICRAF Diagnostic
and Design Exercise at the BIhaintan Watershed in.the
Outer Himalayan of Uttar Pradesh. Nairobi: ICRAF.
Rocheleau, D.
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168

1986 Criteria for Re-appraisal and Re-design:
Intra-household and Between Household Aspects of
FSR/E in Three Kenyan Agroforestry Projects. In
Selected Proceedings of the Annual Symposium on
Farming Systems Research and Extension, Oct. 7-14
1984. C.B. Flora and M. Tomacek, eds., pp. 456-502.
Manhattan, KS: Kansas State University.
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Gholz, ed., pp. 59-87. Dordrecht, The Netherlands:
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1980 Forestry Projects and Women. Washington, D.C.:
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Surin, V. and T. Bhaduri
1980 Forest Produce and Forest Dwellers. Proceedings
of the Seminar on the Role of Women in Community
Forestry, Dec. 4-9. Dehra Dun, India: Forest
Research Institute and Colleges.
Vedeld, T.
1981 Social-Economic and Ecological Constraints on
Increased Productivity among Large Circle Chitemene
Cultivation in Zambia. Occasional Paper 2,
As, Norway: Department of Agricultural Economics,
Agricultural University of Norway.


Weber, F. and M. Hoskins
1983 Agroforestry in the Sahel. Blacksburg, VA:
Virginia Polytechnic Institute and State University,
Department of Sociology.
Wiff, M.
1984 Honduras: Women Make a Start in Agroforestry.
Unasylva 36:146.






























THE FOLLOWING SELECTION
HAS BEEN PRINTED
WITH PERMISSION

DATE: 06/25/92


Author: FELDSTEIN & POTS

Title: Chapter 9

Book: WORKING TOGETHER: GENDER ANALYSIS IN
AGRICULTURE

Volul e: No: Pgs: 240-267 Copyright Year: 1990

Reprinted by Pertission of: Kularian Press


THIS MATERIAL MAY NOT BE
REPRODUCED IN ANY MANNER
WITHOUT THE PERMISSION
OF THE COPYRIGHT HOLDER











Working Together
Gender Analysis in Agriculture



Volume 1
Case Studies


Editors

HILARY SIR., ~EL3STEIN
AND SUSAN V. POATS


KUMARAN PRESS




Figure 9-1
Map of Zambia Showing Traditional Recommendation Domains in Central Province


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Zambia: Part 1
Country and Project Background
and Results of Initial Diagnosis


Between 1981 and 1984, the Adaptive Research Planning Team (ARPT),
located in the Central Province of Zambia, undertook a number of diag-
nostic surveys in order to understand local farming systems and deter-
mine promising agricultural research opportunities. As the time came to
plan the next season's activities, the team members reviewed what they
knew about the Zambian government's objectives, the characteristics of
the local farming systems, and the farmers' views.



COUNTRY BACKGROUND

Zambia became an independent country on 24 October 1964. It is a
landlocked country, lying on the Great Central African Plateau. It has a
tropical climate and vegetation, with three distinct seasons. Like most
parts of Africa, Zambia has experienced unreliable rainfall conditions
since 1978, characterized by late arrival of rain, a short rainfall season,
and inadequate rainfall. Such conditions particularly hurt small farmers
who depend almost entirely on rains for growing their crops. Small farm-
ers account for most of the maize production, and their drop in produc-
tion, therefore, could not be easily absorbed: It led to drastic food short-
ages, especially for the urban population, and also a drop in the income
of small farmers.
The marketed agricultural production is produced by large-scale
commercial and small-scale commercial and subsistence farmers. The con-
tribution to marketed maize production (the main staple and cash crop)
by small-scale farmers was 46 percent in 1973. It rose to a peak of 70 per-
cent in the 1976 season, and then declined to 60 percent and 46 percent
in 1980 and 1981, respectively.
Zambia is the third-most urbanized country in Africa after Algeria and
South Africa. The rural population is sparsely located in scattered settle-
ments. The normal pattern of rural habitation is in small settlements and
hamlets without any large well-nucleated villages. The uneven population
distribution creates serious problems in providing social services. Women


ZAMBIA
Area 753,000 kn2.
Population 6.44 million (1984 estimate based on 1980 census)
43% urban; growth rate 3.1% per year. Density: 7.5 per km2.
Income GDP, 1975: K 1,584 million; 1982: K 3,564 million.
Exports: copper (88%), agriculture (1%).
Resources Mining (31%); agriculture (10%/).
Elevation 1,000-1,300 m.
Rainfall North: 1,000-1,400 mm; south and east: 600-1,100 mm.
Climate Tropical. November-April: warm, wet season, long rains.
May-August: cool, dry winter season (14' to 30' C).
September-October: hot, dry season.
October: short rains.
Vegetation Woodland savannah.
Currency Kwacha (K). 2.5K U.S. $1 (1984).

CENTRAL PROVINCE-MKUSIII DISTRICT
Population Density: 3 per km2.
Elevation: 1,000-1,200 m.
Rainfall: 800-1,000 mm; predominantly November to April.
Soils: Generally sandy (Sandveldt) soils; pockets of heavier textured
soils, damcbos.



have a very small share of the jobs in the formal sector; only 8 percent of
all employees in 1980 were females. However, in rural areas, women pro-
vide on average 60 percent of the agricultural labor.
According to a 1980 International Labor Organization (ILO) estimate
of basic needs income, about 60 percent of Zambia's households were
considered to have incomes below a basic needs level; of this, 85 percent
were estimated to be living in rural areas. Health services in Zambia are
provided by the government. In 1980 only 15 percent of the total popula-
tion was outside twelve kilometers' reach of a health institution.
Primary schooling has long been compulsory for girls and boys, and
women have been particularly encouraged to participate in adult literacy
classes. Girls constituted 30 percent of secondary entrants and 15 percent
of university students. The school year runs from mid-January to mid-
May, mid-June to mid-August, and mid-September to the beginning of
December.
Zambia is characterized by a diversity of cultures and tribal customs,
with seventy-three tribal languages. Thus there are variations in the gen-
der division of labor, particularly between districts and ecological zones.
Division of labor depends on family structure, traditional and tribal cus-
toms, as well as the occupation of the household members.





PROJECT BACKGROUND

Agricultural Institutions

Prior to the 1980s, the organizational structure of the Ministry of
Agriculture and Water Development (MAWD) in Zambia was characterized
by a top-down flow of information. Both research and extension services
were provided by the Department of Agriculture. However, each branch
had its own substructure which operated independently.
Until 1982, research was coordinated from the central research station
.. it. Makulu in Lusaka and was: arrived out by the regional research sta-
tions and substations. The research was conducted by scientists working
on multidisciplinary commodity research teams, with agricultural assis-
tants in the extension service. The commodities included cereals, tubers,
and oil seeds. There were 230 senior agricultural assistants and 604 agri-
cultural assistants in the extension service. Of the senior agricultural assis-
tants, 18 were women, and of the agricultural assistants, 23 were women.
The agricultural assistants introduced new technologies and information
primarily by selected on-farm demonstrations.
In 1981 the input supply and crop-monitoring functions were shifted
from the parastatal National Agricultural Marketing Board (NAMBOARD)
to the Central Province Cooperative Marketing Union (CPCMU). It was re-
sponsible for the distribution and sale of inputs and the purchase of agri-
cultural produce at government-controlled prices. The Agricultural Fi-
nance Company (AFC), a quasi-government company, was the major
source of credit for small farmers.

Formation of ARPT

In the 1970s a series of government and external evaluations found that the
research structure had problems producing recommendations which could
be rapidly adopted by the majority of Zambia's subsistence and small-scale
commerical farmers. Realizing that almost 80 percent of the county's maize
production (which was the principal food and cash crop) was from small-
scale commercial and traditional, or subsistence, farmers, MAWD officials
sought ways to make research of more relevance to small farmers. One
strategy was to develop a standard unit of land measurement of appropriate
size for small farmers and make recommendations according to that unit.
This led to the establishment of LIMA recommendations. A LIMA is approxi-
mately one-quarter of a hectare (seventy steps by seventy steps), and the
term lima means "to cultivate" in most of the languages spoken in Zambia.
Fertilizer, planting density, and other recommendations were developed per
LIMA for each province. The weakness of the program was that provincial
wide recommendations still were not appropriate for all small farmers.


In 1980, MAWD responded favorably to a request by the Centro In-
ternacional de Mejoramiento de Maiz y Trigo (CIMMYT) East and South-
ern African economics program to demonstrate a set of procedures which
could improve the research program. CIMMYT's demonstration was part
of a larger effort to engage in and introduce on-farm research (OFR) to
the region.1 CIMMYT undertook zoning and problem identification stages
in Central Province. Following these demonstrations, MAWD decided to
reorganize research so that commodity research teams would have a na-
tional focus, and farming systems research and extension (FSR/E) an area
focus. This led to the formation of a new adaptive research planning team
(ARPT) in each province, consisting of at least an economist and an
agronomist. A research extension liaison officer was assigned to each
team. Their explicit objective was to work with subsistence and small-
scale commercial farmers in order to increase productivity and improve
family welfare. An ARPT has been established in each of Zambia's nine
provinces, each supported by a different donorss. Since 1981, the United
States Agency for International Development (USAID) has been working
with CIMMYT and MAWD in Central Province.
The ARPT brought together social and natural scientists who examined
the different farming systems in order to plan and undertake adaptive re-
search programs. The overall objective of the ARPT was to produce recom-
mendations relevant to the needs of Zambia's subsistence and small-scale
commercial producers in the hope of improving the farmers' output and
welfare. The ARPT used the following strategy to reach these objectives:

1. Collect information on the different farming systems in Zambia
which would be used to formulate relevant adaptive and applied
research programs.

2. Undertake adaptive research especially on farmers' fields.

3. Improve the link between research and extension staff, through
the program of on-farm trials.

4. Make information available to relevant institutions, that is, those
dealing with extension, input supply, credit, marketing, etc., and
assist them in preparing projects which would remove particular
institutional and infrastructural problems facing farmers in different
recommendation domains.

The ARPT worked closely with the commodity research teams and
the extension branch. Within this structure, the ARPT supplemented bio-
logical parameters used by the commodity research teams with socioecc-
nomic data to help shape the content of the applied research. The na-
tional FSR/E elfort was coordinated by an ARPT leader in Lusaka, who







also maintained formal linkages with the extension branch and planning
divisions within MAWD. CIMMYT had influenced the form and structure
of FSR/E in Zambia from conception through regional implementation,
and it continued to provide training assistance.

Central Province

The location of the Central Province in relation to the urban markets in
Lusaka and the Copperbelt has given it a comparative advantage for com-
mercial agricultural production, and, in the last decade, commercialization in
the small farm sector has accelerated. As a result, the Central Province ranks
among the most agriculturally productive regions of the country in terms of
the total volume of maize produced and marketed. Since the early seventies,
a few farmers have adopted new crops, particularly cotton, sunflowers, and
soybeans. The latter two crops have been encouraged by government exten-
sion efforts to provide new resources for cooking oil. In recent years, the
National Oil Extraction Board has not been able to buy enough groundnuts
because of their popularity as a snack food. Research, input credit, extension
and marketing services for cotton and soybeans are provided by the Lint
Company of Zambia (l.INTCO). Although maize remained the dominant
starch staple and cash crop in Zambia, the Central Province also had the
largest acreage of sunflowers, beans, groundnuts, sorghum, and millet.
The province has a low rural population density of about three persons
per square kilometer, plateau characteristics with a consistent altitude of one
thousand meters above sea level, and a rainfall period from November to
April, which ha:s a long-term average of eight hundred to one thousand mil-
limeters. Most ot the arta :iidel cultivation has a uniform topography with
sandy (Sandveldt) soils, which are highly acidic, deeply weathered, and of
low fertility. The exceptions are small pockets of heavier textured soils and
low-lying drainage areas (dambos). Dambo areas generally are not cultivated
in the wet season because of their high water table. They are used for dry
and wet season grazing or are fenced for dry season vegetable gardens.
In 1976 there were sixty-six extension camps or extension locations in
Central Province ranging from farmer training centers to school demonstra-
tion centers. There were sixty-eight extension staff each covering an area
of approximately 263 square miles and over one thousand households.

SMkushi District

In the Mkushi District in Central Province, the predominant ethnic groups
are the Lenge, the Swaka, and the Lamba. In recent years, a small number
of migrants have moved in and are cultivating land allocated to them by
village headmen. Most of the family households are headed by men, but
an increasing number of women are now heads of households; the 1969


census shows that 24 percent of households in Mkushi District are female
headed. This is because their husbands have migrated to urban areas for
wage income. Others are widowed, divorced, or never married but have
children. There is little interaction between male heads of households and
female heads of households because of social disapproval of meetings be-
tween married men and unmarried women.
The contribution of women to the economy comes through their
work as small-scale farmers, as managers of their households, and as non-
farm workers. Men do most of the heavy work of field preparation and
share responsibilities such as planting, hoeing, weeding, and harvesting.
Female heads of household undertake the heavy work, hire labor, or get
help from male relatives or neighbors. The work load of women without
husbands or with husbands or relatives away from home has increased
drastically, while their ability to feed their families adequately has been
affected by the shortage of male labor. Poor women put in longer hours
than their wealthier counterparts since they cannot afford to hire labor. In
household management, women undertake food processing and prepara-
tion, cooking, housekeeping, and child care, as well as collect fuel, water,
and feed for domestic animals. This work time is shared with children.
Children start going to school at seven years. School-going children
play an important role in farming households. Upon returning from school,
usually about 1 P.M., children change from their school uniforms and, after a
snack, join their parents with ongoing activities. Girls will usually go to the
wells for water and clean the house and yards. Occasionally they will feed
chickens and other domestic animals. They may grind mealie meal while
cooking relish for dinner. During the agricultural season, after completing
the household work, girls will join their parents in the field. During the dry
season they will visit friends. After their snack, boys will normally join their
parents in the field or take over tending cattle from their fathers. Older boys
also will have responsibility for helping their fathers maintain the fence
around the kraals and for helping to construct family houses.
Women and men are also engaged in nonfarm activities. Women are
active in small-scale trade of food commodities and other household
products. Over 90 percent of sellers in local markets are women. Men are
more active in cash-crop production and sales, while women are involved
in food crop markets. Markets are held frequently in larger villages, partic-
ularly after the harvest, and serve as intervillage exchanges. Usually these
small businesses are self-financing.
In addition to their different labor roles, women and men have differ-
ent access to assets and income and different financial responsibilities. Each
sex earns and controls income from different crops or activities. Women are
frequently responsible for their own and their children's food and clothing.
Men's earnings frequently go toward the purchase of capital items, inputs
and so on, and family expenses such as school fees for the children.




Oxen, used primarily for draft power, are a recent introduction and
are not part of the traditional social system. They are generally owned by
men, though some are owned by women. Men manage oxen for land
preparation and other uses. Women who own oxen have their plowing
done by male relatives or by hiring or exchange arrangements. Some
farmers hire custom oxen or tractor operators for land preparation.
Land is readily available and is allocated by the village headmen.
People do not cultivate all the area allocated to them. Female-headed
households have access to land through the village headmen, and, once
acquired, they can keep it for as long as they want. Generally, married
women who prefer to have their own fields acquire land through their
husbands or relatives; this also applies to junior males and females. In
some instances, these assigned plots are part of the general rotation of
fields farmed by the household.
Inheritance is largely patrilineal. When the head of a household dies,
his or her relatives determine the inheritor, usually a son or nephew, who
inherits the responsibility for caring for any dependents. The cultural view
is that husbands know what is best for the household.
The common dish in Mkushi District consists of nshima accompanied
by relish (a sidedish made with vegetables or meat). Nshima is a thick
porridge made from maize meal, sorghum meal, millet meal, or cassava
meal. The most preferred is made of white maize meal. The common rel-
ishes in Mkushi District are boiled beans, meat or chicken curry, and veg-
etables. Groundnuts are used as a substitute for cooking oil in the prepa-
ration of vegetables. Nshima is eaten during lunch and dinner. In
between meals, snacks such as roasted groundnuts, fruits, and roasted or
boiled green maize are taken. Popular beverages are sorghum beer and
mtnukoyo. Munkoyo is nonalcoholic and is usually made from maize por-
ridge into which the munkoyo root is put, dissolving the porridge into
lumps of porridge and liquid. The mixture is sieved and the liquid drunk.
It is particularly popular during the cultivation season as it can be taken
to the fields. During the food shortage times, nshima is taken at dinner.
During the day families depend on snacks, usually roasted maize and
fruits such as mangoes, bananas, and papaya. A diagram of a typical vil-
lage in the Mkushi District is shown in Figure 9-2.


*ARPT ACTIVITIES

The multidisciplinary USAID and MAWD farming systems research and
extension team in the Central Province was composed of positions for an
agronomist, an agricultural econor-ist, and a research extension liaison of-
ficer, which were filled by cxpat.iates and Zambians. While agronomic
and economic disciplines formed the core of each provincial ARPT, these


Figure 9-2
Diagram of a Typical Village in Mkushi District


Legend
Village headman's house
Independent households
Housing for children and household dependents
Backyard gardens for vegetables
Main field for maize, sorghum, and millet
Roads


Dambo gardens (dry season)
Cattle kraal
Water well (ca. 1.5 km from village)
River or stream
Dambo areas
Village boundary


Notes
1. On the average, main fields are about 1.5 km from the village.
2. Each village has only one kraal for all the cattle in the village.
3. Water wells are located near the rivers although during the wet season
people may use another well close to the village.
4. The village boundary is usually determined by the area tribal chief,
although the grazing grounds are communal for all the farmers in the area.
were supported by a rural sociologist and a nutritionist who functioned on
a national level. Using a farming systems focus, the ARPT identified prob-
lems facing farmers and then concentrated on testing out possible techno-
logical solutions on farmers' fields under the conditions faced by the farm-
ers. The sequence of activities used by the ARPT to understand farmers'
problems and to determine acceptable recommendations is described in
Appendix 9-A. The three initial diagnostic activities were a zoning survey,
an informal survey, and a labor survey.








Zoning Survey


In October 1979, in order to identify different recommendation domains
in the province, a CIMMYT team gathered information by interviewing
field agricultural extension staff about agricultural activities in their areas.
On the basis of this information, the different domains were delineated. A
summary of the distinguishing characteristics of the six traditional recom-
mendation domains (TRDs) as determined by the zoning survey is given
in Table 9-1.
Of the differences that are apparent in Table 9-1, the most notable re-
flect the commercialization of agriculture in the farming systems. The
heavy demand for maize in urban areas, in conjunction with the availabil-
ity of hybrid seed, fertilizer, and credit at the local level, has facilitated the
shift from traditional starch staple crops to commercial production. The
ARPT determined that TRD2 was the poorest area, followed by TRD3. The
ARPT initiated its research trials in TRD2 during the 1980/81 season, and
then proceeded to TRD3.
TRD3 falls largely within Mkushi District and includes an estimated
eight thousand farm households. It had six NAMBOARD buying points
serving some thirteen hundred farmers each. The zoning survey indicated
the following distinctive features:


1. A few farmers in four wards owned cattle, but limited ox-hire was
reported in only three of these. The hoe was the dominant method
of land preparation and the cultivated area was consistently re-
ported as between one and two hectares.

2. Sorghum, the major starch staple, was the dominant crop in the
domain. Finger millet was a secondary starch crop, mainly used for
beer. Most wards mentioned some use of maize. A variety of relish
crops was reported, but vegetables, particularly cabbage and rape,
dominated the western wards and gave way to pumpkin leaves,
beans, and groundnuts in the east. Fish was often caught by the
farmers themselves, and chickens were also widely used.

3. Beer was predominant as a cash source, with temporary labor and
charcoal also getting frequent mention. Cash sources were varied
and small. Maize was sold by a few farmers in three wards, and
local transactions of sorghum were prominent in three others.

4. No hired labor was mentioned in any ward. Four wards reported
input purchases by a few farmers, almost exclusively seed and fer-
tilizers for growing vegetables.


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Informal Survey

The informal survey was conducted 12-21 October 1982. The purpose of
the informal survey was twofold. One objective was to make a sample
survey of the areas to check the characterization of the TRD established in
the zoning survey. The second objective was to gather information to de-
termine the farming systems in use and to help formulate on-farm re-
search trials to overcome production problems. A total of twenty-four ran-
domly selected farmers were interviewed by the ARPT staff in selected
areas within TRD3. The survey work was aided by the close cooperation
of the extension personnel in the areas surveyed. The informal survey in-
volved group meetings with the selected farmers who were informally
asked a variety of questions ranging from agricultural production to social
organization, including how information was transmitted within an area.
According to the informal survey, the characteristics of the small-scale
commercial farmer are as follows:

Main starch tAaple Maize, millets, sorghum, and
cassava
Main inputs purchased Fertilizer, seed, and pesticides
Main source of cash Deliberate production of cash-
crop surplus for sale, and sale
of livestock; some production
of new cash crops (cotton,
sunflowers, etc.)
Power source Hand and one or two pairs of
oxen and oxen hire; possible
tractor hire
Labor hired Family, communal, and casual
Farm size 0.25-5 hectares

Table 9-2 summarizes the crop production of farmers interviewed
during the informal survey; Table 9-3, sources of cash income in addition
to crop sales. Farmers were reluctant to state how much of their produc-
tion was sold or stored. Figure 9-3 shows the pattern of food shortages re-
ported by these farmers.


Labor Use Survey

A supplementary labor survey was undertaken from November 1982 to
October 1983. A detailed questionnaire was administered to ten house-
holds in TRD3 on a daily basis. The analysis of the nine completed sur-
veys was finished in 1984. The survey was supervised by an ARPT
economist, while the questionnaires were administered by an enumerator


stationed in TRD3. The main purpose was to find out the extent of the
labor problems revealed in the informal survey. The survey was also ex-
pected to provide a better understanding of the gender roles. The number
of workers and areas planted to different crops for each of the nine fami-
lies are given in Table 9-4. Three of the families owned trained and un-
trained oxen and one family owned two cows.


FINDINGS FROM THE DIAGNOSTIC ACTIVITIES

Resources for Production

As mentioned earlier, access to land is unlimited. Land is either slashed
and burned (chitimene)2 or stumped (completely cleared). The latter is
preferred for hybrid maize cultivation. However, cleared and stumped


Table 9-2
1981/1982 Crop Production (N=24)

Number of Average ha Average yield/ha
Farmers Cultivated (bags) (kg)

Maize 21 2.2 11.6 1,044
Sunflowers 5 1.2 4.3 215
Cotton 3 1.2 218
Sorghum 2 1.2 11.0 990
Groundnuts 2 0.4 13.4 1,072
Beans 1 0.8 7.3 657
Source: Informal Survey (1982).


Table 9-3
Sources of Income Other Than Crop Sales (N=24)

Number of Number of
Source Farmers Source Farmers
Selling beer 11 Selling groceries
Family remittances 7 Hiring out oxen
Selling vegetables 3 Selling bananas
Selling chicken and eggs 2 Working as a blacksmith 1
Selling fish 2 Working as a painter 1
Baking buns 2 Selling munkoy' 1
Working on other farms 2 Operating a grinding mill I
Selling livestock 1 Making bricks 1
Selling charcoal 1
Source: Informal Survey (1982).








Figure 9-3
Pattern of Food Shortages, TRD3


Number of
I households
Reporting
Food
Shortages


8
7- -
6-
5-
4
3-
2-

0-
Oct Nov Dec


Jan Mar Apr May


land is limited. This is because stumping is labor intensive and is mostly
performed by male labor during February, March, and April. Cultivated
areas usually consist of one or two major blocks of land with small sub-
sidiary plots for groundnuts, beans, sweet potatoes, and other vegetables.
The purchase of hybrid maize seed (SR52 and ZH1) is common; a
limited amount of vegetable and sunflower hybrid seed is also purchased.
Fertilizer is commonly purchased and used. Recommendations for maize
call for two applications: a basal application at planting and a top dress-
ing when plants are about fifty centimeters tall, after about six weeks'
growth. Because most farmers are not knowledgeable about pesticides
and because pesticides are not readily available, their use is limited to
very few farmers. The pesticides used are Gamatox for termites, DDT and
Sevin for aphids, and Solbur and Endosulfan for cotton insects.
Oxen and tractor hiring constitute the major source of draft power.
Frinncrs without oxen have access to them once the oxen owners finish
plowing their land. Almost all the plowing is done by men with teams of
oxen, usually a pair of oxen. If the plowing is done by a female farmer's
rcl.;:ives, she usually will pay Ithem !ack in the form of exchange labor.
However, most female-headcd households depend on hired labor for
plowing, and in such cases payment is usually in the form of cash. Ox-
hire is also used for transporting crops from fields to market.
The bulk of the labor force is provided by household members, sup-
plemented by hired labor during peak labor periods. Payment for hired
labor takes the form of cash, mealie meal, exchange labor, beer, or access
to oxen. Most communal labor hiring is for labor-intensive activities,
weeding and harvesting, and occasionally for land preparation. A typical
communal labor day is concluded with a beer party and food festivities.
People attend the work parties for several reasons-they enjoy a party
and they anticipate their own need for extra labor. A farmer is expected


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to attend communal workdays if called upon by a farmer who attended
his or her workday. Communal labor hiring is appropriately viewed as a
kind of communal self-help scheme for neighboring villages as opposed
to kinship groups, as people are not necessarily related to one another.

Crop Husbandry and Uses
Farmers prefer to eat the traditional maize that is mostly grown by
women in small plots near their houses or in dambos. The traditional
maize is usually eaten green. Most farmers also grow a hybrid SR52,
which has been pushed by the local seed companies. Much of this is sold,
but some is stored for food. NAMBOARD will only accept hybrid maize
because of the inconsistencies in-color of the traditional variety. Farmers
say the hybrid is less sweet when eaten green, but indistinguishable when
made into nshima. The recommended planting period for SR52 is Novem-
ber 15 to December 15, after which it will have a poor start.
Land preparation for all crops starts in September, just before the
short, early rains in October, and continues through the end of December.
The surveys showed that some farmers go on planting cereal crops up to
mid-January. The common method of planting maize is dribbling behind
the plow. The spacing for maize is usually seventy-five centimeters be-
tween rows and twenty-five centimeters between hills with an average of
two seeds per hill. Sorghum, sunflower, and finger millet are commonly
broadcast. Other crops such as groundnuts, pumpkins, beans, and so on,
.re usually planted in hills on tilled land.
For maize and sorghum harvesting begins with stocking, the stacking
of sheaves of grain in the field. The cobs or grain heads are later broken
off by hand. Maize is usually stored in bins or sacks. Sorghum and millet
are stored almost exclusively in bins, while other crops are stored exclu-
sively in sacks. Crop residues are either burnt, incorporated into the soil,
or used as cattle feed. Farmers were reluctant to reveal how much of their
Ipoduction was stored and how much was sold. When asked how they
decided how much to store, men responded, "Mother made a decision
and I sold what was left over."

Institutional Problems
I'.rmers were interviewed about the services provided by agricultural
institutions. They stated that access to credit from the AFC was limited
and very unreliable. Small-scale farmers, who marketed their products to
the provincial cooperative and marketing union, said payment was usu-
ally delayed. The inputs supplied by the cooperative were also customar-
ily late. Further, local extension agents have very limited contact with
farmers; new technology is introduced through selected on-farm demon-
strations, which few female farmers attend.


Labor Use and Time Allocation for Major Crops

Family labor constitutes the major source of labor for farm operations. In
peak labor-demand periods this is supplemented by hired labor. Based on
a seven-hour day, male adults devote 75 percent of their time to farm op-
erations while the other 25 percent is split up between nonfarm activities
and resting. Adult females divide their time between farm operations and
house chores such as cooking, fetching water, fetching fuelwood, and at-
tending to children. Adult females have very little time to rest during the
growing season. School-going children devote only 15 percent of their
time to farm operations; most of the time they attend lessons at school.
From August to October very little goes on; males spend this time relax-
ing, drinking beer, and. socializing. However, females still devote almost
50 percent of their time attending to house chores. Fetching water takes
up most of their time because most of the nearby wells are dry during
this period. Cattle herding is mostly done by male children, while female
children assist their mothers in house chores.

Maize cultivation. Maize is often grown on new land, and land
preparation begins in September. The traditional maize grown in small
plots is planted at the short, early rains in October and is harvested, to eat
green, during January and February. Hybrid maize planting begins in
November. Over one-third of the farmers reported using second genera-
tion maize seed, which they selected from the previous generation of hy-
brid seed. Research indicated this practice resulted in a 30 percent de-
crease in yields.
Basal fertilizer application is begun in December after full emer-
gence. The second fertilizer application is made sometime between Jan-
uary and April. Fertilizer application rates in 1982/83 and 1983/84 were
135 kilograms per hectare for basal fertilizer and 140 kilograms per
hectare for top dressing, down from what was reported in 1981 when the
price of fertilizer was lower. Most farmers reported applying the same rate
of fertilizer to late-planted maize; others applied greater amounts.
Farmers generally weed once, beginning in December and continu-
ing through January and February. Some weeding goes on through April.
A few farmers use pesticides to combat stalkborers and termites, the dom-
inant pests.
Stooking and harvesting hybrid maize begins in May and extends
through July. After the maize is shelled and packed, it is transported to
market, some still being sold in September. During the peak labor period,
*December and January, farmers are forced to forgo optimal maize man-
agement (such as early planting and timely weeding) in order to cultivate
other crops. Late planting, however, also results from the lack of draft
power. Farmers who depend on hired draft power, the majority of whom







are female heads of households, are forced into a situation where they
have to plant late because the common planting practice is dribbling the
seed behind the plough.
Family labor is almost equally distributed for land preparation (after
stumping), but planting and fertilizer applications are mostly carried out by
children. Stooking is mostly a job for the husband or wife, while men
mainly transport the produce from the field. Each family member con-
tributes almost equally toward the total labor distribution for maize, with a
:lightly higher contribution from the head of the household (see Table 9-5).

Jorghum cultivation. .;.1gnum is the second major cash and staple
crop, grown by 67 percent of the farmers. Its primary use is for beer
brewing, though some of it is used for cooking nshima (porridge). A
ninety-kilogram bag of sorghum will produce beer which sells for K 100.
Sorghum is mostly grown by women, and the revenues realized from the
sale of sorghum beer usually are controlled by them. Married women,
however, may consult with their husbands.
Planting and preparing land for sorghum take place at the same time.
Women broadcast the seed while men plow behind them with a team of
oxen. This takes place from mid-November to early December. Four to
five weeks after germination, when the plants are just slightly below
knee-high, women thin out some plants and transplant them into parts of
the field where the density is low; this ensures an even stand. The labor
requirement for planting, therefore, is a summation of the labor for broad-
casting and for transplanting.

Table 9-5
Division of Labor for Hybrid Maize Cultivation (N=9)

I husband Wife Children Ilired Labor Total
hr/ha % hr/ha % hr/ha % hr/ha % hr/ha %
Prep. land 25 33 24 32 26 34 75 10
Plant 26 25 25 24 53 51 104 14
Fertilize 10 23 11 26 21 51 42 6
Weed 70 30 51 22 87 37 28 12 236 32
Stook 23 56 17 42 1 2 41 6
Ilarvest 31 28 27 21 31 28 23 21 112 15
Transport
from field 39 84 2 4 2 4 4 8 47 7
Thresh and
pack 18 24 24 32 32 44 74 10
Total 242 33 181 25 221 30 87 12 731 100
Source AI'T Labor Survey (1982/83).
Note I lours per hectare were calculated at the same rate for women, men, and children.
Percent under Husband, Wife, Children and Hired Labor read across (totalling 100 percent);
percent under Total read down.


It was observed during the survey that sorghum husbandry is very
poor due to labor constraints. The calendar time for sorghum weeding is
the same as that for maize, which is considered a priority crop. In addi-
tion, broadcast method results in random growth so that it is more diffi-
cult to weed. Sorghum is weeded two or three times. Sorghum is often
planted on waste fields without any fertilizer applications. The seed rate
ranges from six to twenty-two kilograms per hectare, though the LIMA
recommendation is for three kilograms per hectare. Farmers select their
seed based on the size of the panicle.
Sorghum grows eight to nine feet tall. As the grain matures, bird scar-
ing is necessary fr6m February (just before cutting and stacking the
sorghum in the fields) through May (when the last of the grain heads are
cut from the dried stalks). Because bird damage contributes to low
sorghum yields, women spend almost twelve hours per day in the fields
scaring away birds. This activity, according to the labor survey, accounts
for well over 52 percent of the total labor expended in growing sorghum.
During this period, women move to the fields for the day and use
temporary shelters. The women's activities away from home include
grinding maize and sorghum, preparing meals, washing clothes, and mak-
ing baskets. In an effort to help their mothers, children sometimes miss
classes at school.
To make beer, sorghum seed is germinated and then fermented for
two or three days. Then it is dried and pounded into flour and made into
a light porridge which is fermented for five to seven days. The light por-
ridge is combined with a freshly made thick porridge of maize and
sorghum and left overnight for further fermentation. The following day it
is sieved so that a thin liquid remains. After another night of fermentation,
the brew is ready for drinking. Local laws allow beer selling only on Fri-
days and Saturdays.

Finger millet cultivation. Finger millet is grown primarily by
women. In December and January the seed is broadcast on flat land and
then raked in. Land is not tilled in the conventional manner. Planting and
raking appear in this report as planting. This activity takes up 25 percent
of the total labor used for finger millet. Since it is grown on new land,
weed infestation is minimal; hence, finger millet is not normally weeded.
Bird scaring (April) and harvesting (May and June) take up most of the
labor expended on finger millet (71 percent). Finger millet is mostly used
for beer brewing and for cooking nsbima.

Relish crops. Groundnuts, sweet potatoes, and beans (bush beans)
are the primary relish crops. Sweet potatoes are mostly grown for home
consumption as snacks and also for sale; the leaves of sweet potatoes are
used as a vegetable, fresh or dry. Pumpkin leaves, too, are used as a veg-





etable, while the pumpkin itself is consumed as a snack, usually in be-
tween meals. Groundnuts are a very important relish crop. Dry nuts are
ground into flour and are traditionally a woman's crop. They are added to
vegetables as an alternative to cooking oil, which is difficult to acquire in
rural areas. Fresh nuts are boiled and eaten as snacks or are roasted if
dry; surpluses are sold for cash. Mt. Makulu Red is the favored nut variety
for cash cropping. Though the price for groundnuts is high on the world
market, the government price is low. Most groundnuts sold are sold pri-
vately though local markets. A persistent problem with groundnuts is
"pops" (empty shells). Pops is usually associated with highly acid soils
and the lack of calcium.
Relish crops are usually grown by women in small backyard gardens
or near main fields or in the dambos. Land preparation is the women's re-
sponsibility for these plots. The average size of fields for these crops is
0.07 hectares, with a range of 0.05 to 0.09 hectares. Most operations are
done with a hoe, and most labor used on these crops is expended on
ridging and weeding. Harvesting groundnuts and sweet potatoes also
tends to take up a lot of time. The harvest of dry groundnuts is in two
stages: the plants are lifted upside down so that the nuts can dry and the
nuts are hand-harvested a week or so later. Fresh nuts are dug directly
from the ground. Groundnuts are planted from October through January.
The harvest of the first plantings begins in February and continues
through June. Groundnuts are stored in August. Sweet potatoes and other
relish crops are planted January through March. Some cabbage and rape
are planted in May.
Beans are grown by women ii pure stands or are intercropped with
,-.c; female-controlled relish crol.s such as pumpkins and groundnuts.
Beans are in great demand bringing as much as K 100 for a fifty-pound
bag on the informal market. The local varieties of beans produce a mixed
crop when sown. White or sugar beans are kept for home consumption;
red beans are sold in town. Beans have several plantings throughout the
rainy season, the first in December. Successive plantings are harvested
from April through July.
The hours of labor required for different activities for different crops
per hectare and per average area planted are indicated in Tables 9-6 and
9-7. Appendix 9-B provides information on the prices, costs, and stan-
dards used by the ARPT in the economic analysis of on-farm trials. After
reviewing these surveys, the ARPT team worked to characterize the farm-
ing system, to identify the major constraints and opportunities, and to
plan its research activities for TRD3 for the coming season.


STUDY QUESTIONS

1. Why were the ARPTs created and what are their overall objectives?

2. What were the objectives of the ARPT activities in TRI3?

3. What are the activities of men and women in agricultural house-
holds and when are they done throughout the year?

4. What are the resources of men and women and what benefits do
they derive from their productive activities? From other activities?

5. What are the primary constraints facing farmers in TRD3 and what
are their causes?

6. For two of these problem areas, suggest solutions which might be
tested and criteria for evaluating such tests.

7. Design an on-farm trial based on one of the solutions proposed.
(optional)


NOTES
1. In 1980, when CIMMYT proposed to demonstrate these procedures in Zambia,
farming systems research and extension (FSR/E), as it is known today, was just
being recognized. There was great diversity in terminology and procedures among
the many early practitioners. The CIMMYT economics program operating out of
Nairobi, Kenya, was conducting what it called on-farm research. Most of CIMMIYT's
on-farm research at this time focused on maize, one of the key commodities of the
organization headquartered in Mexico. In Zambia, FSR/E was initially called on-f.irim
research or adaptive research, but by the mid-1980s, the term FSI/E was gaining ac-
ceptance. In this case, the generic term FSR/E is used for consistency among the
different case studies in the volume.
2. "Chitimene" is slash-and burn shifting cultivation. All growth is cut down and lhe
field burned before cultivation. After the fertility of a field drops, a new field is
opened by the same method.


REFERENCES
Adaptive Research Planning Team. 1982. Report of an Informal Survey of Farmers in
Traditional Recommendation Domain #3 of the Mkushi District, Central Province.
Kabwe, Zambia.

-- 1983. Final Report of the Formal Survey in Traditional Recommendation Domain *5
of Kabwe Rural District, Central Province. Kabwe, Zambia.

-- 1984. Central Province ARPT Annual Report, 1 July 1983 to 30 June 198i. Kabwe,
Zambia.

--- 1985. Central Province ARPT Annual Report, 1 July 1984 to 30 June 1985. Kabwe.
Zambia.


--- n.d. Central Province Trial Progiam: 1981/85 Crop Cycle.















Table 9-6
Crop Labor Activities in Person Hours Per Hectare (N=9)

Prep. Thresh Scare
Landa Plant Fertilize Weed Stook Harvest Transp.b and Pack Birds Shell Total

Hybrid maize 75 104 42 236 41 112 47 74 731
Sorgh.. 60 98 361 701 17 1,345 2,582
(1,237)c
Finger millet 147 19 397 563
Beans 184 499 888 358 433 2,363
Sweet potatoes 851 665 421 1,938
Groundnuts 113 1,600 963 2,676
Source: ARPT Labor Survey (1982/83)
'The labor requirement for land preparation is an average between ox and hand cultivation.
bTransportation of produce from fields and, in a few cases, to marketing depot.
CNumber in parentheses is total labor requirement less bird scaring.


Table 9-7
Crop Labor Activities in Person Hours Per Average Area Planted (N-9)a

Crop per Prep. Thresh Scare
Avg. Size Landa Plant Fertilize Weed Stook Harvest Transp. b and Pack Birds Shell Total

Hybrid maize 92b 127 51 288 50 137 57 90 892
(1.22 ha)
Sorghum 47 76 282 547 13 1,049 2,014
(0.78 ha) (965)d
Finger millet 19 3 52 74
(0.13 ha)
Beans 11 30 53 22 26 142
(0.06 ha)
Sweet potatoes 43 33 21 97
(0.05 ha)
Groundnuts 9 128 77 214
(0.08 ha)
Source: ARPT Labor Survey (1982/83)
aAreas from Table 9-4.
0The labor requirement for land preparation is an average between ox and hand cultivation.
CTransporation of produce from fields and. in a few cases, to marketing depot.
'Number in parentheses is total labor requirement less bird scaring.





- n.d. Central Province Trial Program: 1985/86 Crop Cycle.

Burlisher, Mary E., and Nadine R. Horenstein. 1985. Sex Roles in the Nigerian Tiv Farm
fHosehold. Women's Roles and Gender Differences in Development: Cases for Plan-
ners, no. 2. West Hartford, Conn.: Kumarian Press.

Central Statistics Office. 1984. Zambia Country Profile, 1984. Lusaka, Zambia.

Chambers, Robert. 1980. Rapid Rural Appraisal: Rationale and Repertoire. IDS Discussion
Paper 155. Brighton, U.K.: Institute of Development Studies.

Collinson, Michael P. 1979. Demonstrations of an Interdisciplinary Approach to Planning
Adaptive Research Programmes. Report no. 4. Deriving Recommendation Domains for
the Central Province, Zambia. Ministry of Agriculture and Water Development in asso-
ciation with CIMMYT, East African Economics Programme.

Selling, Martin. 1981. Rapid Rural Appraisal as a Tool for Project Identification. Experience
with the Rapid Rural Appraisal Method in Mkushi District, Central Province, Zambia.
Paper prepared for the United Nations Development Programme and the Food and
Agriculture Organization of the United Nations. Kabwe, Zambia.

Harms, A. G. 1982. Development of the Farming System in Western Part of Mkushi District:
Results and Prognosis from the Informal Survey. A Discussion Paper. Kabwe, Zambia:
Adaptive Research Planning Team.

- 1983. "Are Small Scale Farmers Getting a Fair Share of Fertilizer?" A Discussion
Paper. Kabwe, Zambia: Adaptive Research Planning Team.

Iludgens, Robert E. 1984. Subregional Issues in the Implementation of Farming Systems Re-
search and Extension Methodology, A Case Study in Zambia. Paper presented at the
198.4 Farming Systems Research Symposium. Manhattan, Kansas: Kansas State University.

1988. A Diagnostic Survey of Female Headed Households in the Central Province of
Zambia. In Gender Issues in Farming Systems Research and Extension, edited by Susan
V. Poats, Marianne Schmink, and Anita Spring. Boulder: Westview Press.

International Labour Organization Office (ILO). 1981. Basic Needs in an Economyv Under Pres-
sure. ILO/JASPA Basic Needs Mission to Zambia. Addis Ababa, Ethiopia: ILO/JASPA.

Kaplan, 1. ed. 1979. Zambia A Country Study. Washington, D.C.: American University.

Kean, S A., and W. M. Chibasa. 1982. Institutionalizing Farming Systems Research in Zam-
bia. Discussion Paper. Lusaka, Zambia: Ministry of Agriculture and Water Develop-
nent.

Overholt, Catherine, Mary I. Anderson, Kathleen Cloud, and James E. Austin, eds. 1985.
Gender Roles in DlevelomenIt lProjects: A Case Book West Hartford, Conn.: Kumarian
Press.

Shanner, W. W., D. F. Plilip, and L. Schlimhl. 1982. Farming Systems Research and LDvelop-
ment, Guidelinesfior Developing Countries. Boulder: Westview Press.

Tripp, R. n.d. Data Collection, Site Selection, and Farmer Participation in On-Farm Experi-
mentation. CIMMYT Economics Programme Working Paper 8214.


Appendix 9-A: Activities for Understanding

Farmers' Problems in Order to Produce

Acceptable Recommendations


Activity Objective Participants Duration


Zoning Group farmers by their
farming activities into
different farming systems.
Survey Study the constraints of each
farming system to
understand the farmers'
problems and identify
potential for development.
Research Formulate a program of
priorities applied and adaptive
research which aims to
solve the most important
technological problems
identified in the farming
system.
On-farm Test, and, if necessary,
trials modify the possible research
solutions on farmers' fields
under realistic conditions
until acceptable solutions
are found. The trials are
conducted on 3-10 farms
within the target area.
On-farm Information about
tests technological components
or packages which are
successful in on-farm trials
are extended by various
means, on-farm tests/
demonstrations, still within
the target area. The level of
adoption is monitored.
Recommen- Technological components
nation or packages which are
release adopted by the majority of
the farmers within the target
area are released and
extended to farmers
throughout the farming
system.


ARPT staff interview
extension workers and
community leaders
ARPT staff interview
farmers using extension
workers as enumerators


ARPT staff with com-
modity and specialist
research team staff plus
provincial ARPT
committee members


ARPT staff with the trial
assistant provided from
extension branch


3-6 months


3-9 months




2-3 months







2+ years


Research extension liaison 1-2 years
officer with camp level
extension workers







ARPT staff, CSRT staff, and
provincial ARPT
committee members


Source: ARIT Annual Report (1984/84).









Appendix 9-B: Prices, Costs, and
Standards in Mkushi District



Price/Quantitya
Fertilizers
Urea (46%N) 26.75/50 kg
TSP (44% P 0) 28.45/50 kg
KCL (60% K) 23.75/50 kg
"X" compound (20-10-5-10) 26.75/50 kg
"'D" compound (10-20-10-i0) 26.75/50 kg
limestonee 5.80/100 kg
Transport cost 1.00/bag
Seeds
SR52 maize seed 76.00/50 kg; K 17.10/10 kg
MN752 maize seed 86.00/50 kg; K 19.10/10 kg
ZSV-1 sorghum seed 42.61/50 kg; K 10.25/10 kg
CCA75 sunflower seed 47.60/50 kg; K 11.25/5 kg
Carioca bean seed 5.00/kg (est.)
Local bean seed 2.00/kg
I herbicides
Gramoxone (5 1) 12.65/1
Primagram (5 1) 23.50/1
Gesapriin (5 1) 12.10/1
Roundup (5 1) 53.90/1
Custom rates
Land preparation by hired oxen 67.25/ha
Land preparation by hired tractor 75.00/ha
Transport to or from depot 5.00/trip

Continued on next page


Appendix 9-B, continued

Price/Quantity" PD/hab
Labor requirement standards
land preparation with oxen II
Planting maize (separate operation) 15
Planting maize (behind plow) 3
Weeding maize with hoe 34
Harvesting maize 16
Stooking maize 6
Shelling maize 11
Fertilizer application
Basal on surface 6
Basal at root level 8
Top dressing (covered) 8
Top dressing (uncovered) 6
Basal broadcast 6
Lime application 6
Insecticide application
Spraying liquid 1
Banding granules 6
Depreciation on knapsack sprayer 14.50/ha
Opportunity cost of labor
During maize planting 7.50/P1)
Ordinary labor 1.50/PD
Output prices
Maize 23.32/90 kg
Sunflower 27.88/50 kg
Sorghum 26.90/90 kg
Edible beans 1.50/kg
Groundnuts 33.64/80 kg
alrices in kwacha.
bone person-day (PD) is eqial to seven person-hours.




Perspectives on
FARMING
SYSTEMS
RESEARCH
and
EXTENSION
Edited by Peter E. Hildebrand


Lynne Rienner Publishers Boulder, Colorado







CHARACTERISTICS OF SELECTED SYSTEMS
Robert E. McDowell and Peter E. Hildebrand

The objective of this section is to direct attention to
various levels of integration of crops and animals and portray
the infrastructural dependence, within selected systems. Eleven
systems are identified for Asia, Latin America, and Africa, and
each system is discussed in terms of some of the physical
constraints of the region, e.g., climate, soils, elevation, crops
and cropping systems, the role of animals, and the panel's
assessment of the prospects for expansion of benefits derived
from animals.
A standard format was used for ease in comparisons. The box
identified as "Market," represents all off-farm activities and
resources (except land); hence it includes products sold or labor
going off the farm as well as purchased inputs and household
items. The "household" is the core of the farm unit. In pre-
paring the models of the systems, labor use, sources of human
food, household income, animal feed, and the roles of animals.
were the main focus. The solid arrows (-- depict strong flows
or linkages (e.g., more than 20 percent of total income arises
from the sales of crops, animals, or household-processed
products). Broken arrows (- are used when sales of crops
or animals contributed less than 20 percent of household income,
the interchange among functions was intermittent, or there was no
routine pattern identifiable (Figure 2.3). Family labor applied
on the farm was identified, but off-farm employment or the amount
of hired labor was not quantified except generally and is
indicated by broken or solid arrows.
For most products there is a Jir-ci. relation to market.
absent in cases where little is told or when the household
changes the characteristics of the product before sale (e.g.,
wool to yarn, milk to cheese, or manure to dung cakes).
Household modification is shown by solid arrows from crop or
animal products to household to market. Even though all crops
require some processing, a distinction was made only when the
household modified or changed an already marketable product.
Fuel is extremely important on small farms. Gathering of
wood or other materials often constitutes a significant expen-
diture of labor, or may represent an important source of income.
In each system, the major fuel sources are identified.
The models presented are by no means all-inclusive. Hun-
dreds of models would be needed to characterize all small-farm
systems. However, through an appreciation of the "interaction
effects," the rationale of the "whole system" on small farms can
be better understood and serve to explain why a single phase of
technology, such a new variety of maize, may be rejected by small
farmers.


CROPS/ANIMAL SYSTEMS IN ASIA

Swidden System

The swidden system (Figure 2.3) is employed on 30 to 40 per-
cent of all land in tropical Asia (Harwood and Price 1976). It


.---



































Figure 2.3. Swidden farming system in Asia,shifting agriculture
low integration of crops and animals (animals free-
roving or tethered)


centers around dispersed settlements employing slash-and-burn
technology. A family or household cultivates approximately 2
hectares per year using manual labor. The main implements are
hoe and dibble stick. Plant residues are usually left in the
fields for mulch. Each family has pigs and chickens without
controlled management (scavengers); thus there is no systematic
recycling of nutrients, although some manure may be retrieved for
certain crops around the household. After two to four years of
cropping, there follows an extended fallow period. There is
little animal/crop competition since the fields are ordinarily
several hundred meters or more from the village. Fuel is a
relatively minor problem in this system because of low population
densities and the presence of forest or fallow.
Farm infrastructure is low, i.e., few capital inputs and
services are rendered from outside the village. Mutual as-
sistance within the village is the main source of aid. There is
no systematic plan for sale of livestock nor identifiable pattern
of service use for animals. Most sales of animals are for
emergency needs, with the greater proportion being consumed to


celebrate cultural/religious events (De Boer and Weisblat 1978).
The soils are generally marginal in fertility and on moderate to
steep slopes; thereby serious problems often arise with erosion.
Wildlife from forest fallow areas often prey on crops or even on
the small animals.
The system has several assets. The usually low population
pressures permit long-term fallow. Diversified cropping is
already widely practiced; therefore, soil conservation procedures
should be acceptable. The constant shortage of labor slows
expansion of cultivation and thereby risks of erosion. On the
other hand, the system has se ious liabilities, such as po'-r
access to markets and inadequate power for tillage or transport.
Increasing land pressure due to population growth and expansion
of permanent ranching and timber harvest are causing the fallow
system to break down in many areas (Harwood 1978).
The opportunities for positive change are good. Returns
from crops and environmental stability could be improved through
the use of perennial crops, bunded paddies, terraces, and planned
grazing areas in order that buffalo or cattle could be in-
corporated into the system. Use of large ruminants would improve
the opportunity to accumulate capital. These changes would
require development of technology and guidance. To achieve these
steps will necessitate a shift in attitude on the part of
policymakers, most of whom see the swidden system as it is now
practiced as wasteful and making little contribution to agri-
cultural production.

Humid-upland System

The upland system (Figure 2.4) is widespread over the humid
tropics of Asia. There are well-developed farmsteads with
permanent, cleared fields but with no bunding and no irrigation.
The major crops are rice, maize, cassava, wheat, kenaf, sorghum,
and beans. Most households have small numbers of several species
of animals, with swine and poultry dominating. Following these
in popularity are cattle and buffalo. Sheep and goat numbers are
normally low. Where tall-growing crops (maize and sorghum) are
cultivated, cattle are kept to utilize crop residues. In rice
areas buffalo predominate. Frequently, one or two buffalo or
cattle are kept for use in land preparation and to provide
transport for crops, crop residues, and to some extent members of
the family. Swine are tethered or penned, and cattle or buffalo
are tethered at night in order that manures can be collected and
to avoid theft. The manures are frequently composted with crop
residues. Poultry are usually free-roving.
Fuel is not yet a severe problem in many of the humid-upland
systems but is becoming increasingly so as more and more forests
are cleared.
The farm infrastructure is variable, developed for some
areas but extremely limited for others. Land tenure and social
services are also variable. Many upland areas are distant from
markets.
The land ranges from rolling hills to steep slopes. The
soils have moderate fertility, and in general drainage is good.
Erosion hazards are classed as moderate. The rainfall is sea-
sonal and erratic within the rainy season, thus periods of



































Figure 2.4 Humid-upland farming system in Asia, permanent crop-
ping, moderateintegration of crops and animals (ani-
mals tethered or herded)


moisture stress are frequent.
Among the assets of this system are some possibility for
multiple cropping, excellent potential for crop/ animal inte-
gration, good potential for small-holder dairying with crop
rotation, and feasibility of cooperative production and mar-
keting. Rice is milled at the village level; therefore, rice
bran and other by-products are available for supplementary
feeding of animals. Some of the current limitations to increased
output are inadequate or absent credit and animal health
services, insufficient power for tillage (Duff 1978), and limited
access to markets. In addition, farms are often so geo-
graphically fragmented that much potential for grazing is lost.
Considering the assets and liabilities, the potential appears
good for change through increased cropping intensity, especially
of fodder crops for animal feeding; increased animal holdings in
order that farmers could have scheduled outputs for marketing;
expanded farm infrastructure; extended use of draft power; and
larger milk supplies.
With time, the upland areas of Asia promise to meet a rising
demand for milk and meat through greater crop/animal inte-
gration.
Integration on small farms will minimize the need for feed


concentrates in animal production, and there is some potential
for on-farm self-sufficiency in power gasoholl, biogas, and
animal draft) based on conversion of sweet potatoes and cassava.

Lowland Rice System

The lowland rice system (Figure 2.5) is characteristic of
traditional small-farm operations in the river valleys, first and
second terraces, and coastal areas of Asia, including southern
China. These areas have at least three months of rainfall above
200 mm and a dry season of two to six months. Length of dry
season is a major factor in feeding animals. The areas are
tropical (frost free). Population density is high for both
humans and animals. Rice is the major crop, followed in
importance by garden vegetables and food legume crops. The usi
of fertilizer and manures assures high crop yields. Rice is
milled in the villages; therefore, rice bran and other
by-products are available. Rice bran has a good level of crude
protein (12 to 15 percent) and a significant amount of oil or
fat; hence, rice culture/livestock integration adds to the
intensification of this farming system (Maner 1978).
Animals provide income and manure as well as fuel in south
Asia (Figure 2.5). The major species are cattle, buffalo
(swamp-type or carabao), swine, chickens, ducks, and geese. The
bovines are kept to utilize crop residues and to supply manure
and power for tillage and transport. Old draft animals are sold
for meat. Rice by-products and cut grass are utilized for swine
feeding. The pigs are sold for additional income. The ducks and
geese feed on grains lost during harvest and on insects and weeds
in and around the irrigation canals. Most of the eggs and meat
from chickens, ducks and geese are consumed within the household
or in the immediate community. The farms are small and
fragmented, which makes for difficult control of grazing animals.
As a result, the larger livestock are confined and hand-fed,
which permits collection of manures. Another reason for teth-
ering or confinement is security, as theft of animals is a
problem. Animals, especially the buffalo, are a strong feature
of the cultural system (ritual)(Barnett 1978).
Because of high population pressures, no land is available
for producing fuel. The high rate of use of manures on crops
also precludes this as a source of fuel. Hence, in this system,
the primary source of fuel is kerosene purchased at the market.
The assets of the lowland systems are numerous. Multiple
cropping can be expanded to reduce dependence on a single crop
(Riley 1978). Farmers are experienced in the care of an- imals.
Labor for use in livestock production is plentiful during long
periods. Irrigation serves to reduce risks in cropping; thus
farm capital is relatively easy to accumulate on the farms.
There are certain restrictions to expansion of crop and
livestock production. For example, the nutritive value of straw
of the new, high-yielding varieties of rice is lower than in the
traditional varieties (McDowell 1978). The low feeding value of
straw may require supplementary feed for draft animals or their
work efficiency will be low. Multiple cropping reduces the
amount of grasses and weeds traditionally cut and fed to animals.



























Soff farm:


Figure 2.5. Lowland rice system in Asia, permanent cropping,
high integration of crops and animals (animals con-
fined)


Irrigation and multicropping may increase the value of
labor to such an extent that interest in livestock will decline
(Harwood 1978). Increased use of pesticides and herbicides in
multicropping may limit fish and duck production in rice paddies.
Increased mechanized harvesting may cause shifting of rice
milling away from the villages. This may stimulate development
of large commercial livestock operations which could monopolize
markets.
On the whole, the intensity and efficiency of crop/livestock
(nonruminants) production are higher on small farms in the
lowlands rice system than in any other system described in this
report (Maner 1978). Even so, there is good potential for
change. For example, fertilizer costs could be reduced by
cropping of legumes on residual moisture in rice paddies. The
legumes would complement low-quality rice straws for livestock
feeding (Javier 1978). Other approaches which could be used to
bring about institutional change include:

1. Securing land tenure to encourage accumulation of animals.

2. Introducing long-term technology for animal production, e.g.,


Figure 2.6. Central American highlands, permanent cropping, high-
level integration of crops and animals (animals herd-
ed or confined)


use of forage legumes.

3. Adopting a multidisciplinary approach to maximize farm
income.

4. Supplying market assistance to small-scale swine, chicken,
and duck producers in order to overcome the high unit cost
of marketing small numbers of animals.

5. Offering credit and extension services on a year-round basis.


CENTRAL AMERICAN HIGHLANDS SYSTEMS

There are a number of common features of the traditional
farming systems of the highland regions (>1,000 m elevation) of
Central America (Figure 2.6). The highlands have an annual
rainfall of 1,200 to 2,000 mm, most of which falls from April to
November. The rainfall and temperature conditions allow the
choice of alternative food- and cash-crop enterprises. Fluc-
tuations in temperature (two to six months of frost, depending on
elevation) often restrict or inhibit maximizing the utilization






of the precipitation. In general, soil fertility is not
limiting, but topography is.
Areas cultivated per family are usually small (1 to 2 ha),
with cultivation done by hand or animal power. Maize is the
primary crop, but because local varieties need nine months or
more to reach maturity, the maize is intercropped with two to
five other crops. Some diversified farms practice rotations.
Livestock on a typical farm might consist of one or two
pigs, four to five sheep (in higher areas), and one cow. In
addition, there would be approximately one horse per three farms.
Except during the dry or cold seasons, animals are tethered to
avoid crop damage. Women and children are involved in both
livestock and cropping enterprises. Men often work off-farm to
supplement incomes, and the women and children must carry on the
major tasks (Hildebrand 1978). There are many landless laborers
in the highlands. Many of them farm small plots through an
arrangement with a landholder and in return will then provide him
with labor.
Because of poor roads and/or distance to market, fertilizer
costs are high, thus recycling of nutrients through composting is
important to the system. Many farms have a "compost pit" where
animal manures and crop residues are mixed. Materials are
frequently gathered from off the farms to increase the amount of
compost. Livestock feed sources are largely from unfarmed areas
(fallow, forests, or communal grazing) and cut forages, e.g.,
maize leaves. Terraces are used to reduce erosion and to
conserve water in a number of areas. Grass areas on the slopes
of the terraces are a source of livestock feed. Wool from the
sheep is of poor quality; nevertheless, it is used to weave
clothing and handicrafts, which are sold (Fitzhugh 1978). Pigs
are marketed at 9 to 12 months. Milk is used mainly for home
consumption or made into cheese. Calves born on the farm are
kept to maturity (4.5 to 5 years) before sale. Livestock may
play only a minor role in family nutrition, as the primary foods
are maize and beans. There is a high degree of interdependence
between farm families and their livestock, especially since
recycling of animal and crop wastes is such a major aspect of the
system (Diaz 1978).
With increasing population pressures and the resulting
deforestation, fuel is becoming a more severe problem.
Lack of capital, size of farm, limited access to additional
land, and tenure status are all constraints in the highlands
system. Since manual labor is the basis for most farm op-
erations, seasonal availability of labor also becomes a
constraint (Hildebrand 1978). Distance from market and lack of
adequate access roads will limit ability to sell fresh products
like milk. Meat production and wool are less dependent on
infrastructure.
There is some potential for further diversification in the
highland system if maize yields could be increased. Expansion of
crop production would provide opportunities for additional
livestock production. Training in shearing and preservation of
wool would improve quality and increase sales.


Figure 2.7. Land use of small farm typical of western highlands
of Guatemala


SPECIFIC SMALL-FARM EXAMPLE

The objective of this section is to further illustrate
"linkages" or "events" at the farm level in order to increase
awareness of the complexity of a small-farm system. The farm
under discussion is in an area near Quezaltenango in the western
highlands of Guatemala where the Instituto de Ciencia y
Tecnologia Agricolas (ICTA) is conducting extensive investi-
gations on small farms.
The farm is larger than average in the Guatemala highlands;
it has 5.25 ha, of which 0.35 ha are in grass and forest.
Although all types of livestock are not represented, the farm has
been chosen as an example because the relationships among the
market, household, crops, and livestock well demonstrate the
complexities of life on a small farm. Dogs have not been
included in previous models, but are included here because the
family considers the dog as having a strong role in the culture,
and in addition, dogs are used to derive income. Puppies are
sold, and they do consume a significant part of the food produced
on the farm. The bee is the other animal found on the farm that
has not been mentioned before; although bees are not too common
as a farm enterprise, some farms in all areas of Guatemala do
have them.
The main crops are maize, a type of bean locally called
piloy ( Phaseolus coccineous ), wheat, and potatoes. Produced in
smaller amounts are fava or European broad beans, locally called
haba ( Vicia faba ); fruits, vegetables, and medicinal herbs for
teas or medicines. The primary livestock enterprises are cattle
for milk, swine, and chickens. One-fourth of the farm surrounds
the house (Figure 2.7), and the rest is scattered in various
parcels. Two-thirds of the land is owned and one-third is rented
from relatives. Land rent is half the value of the crop after




IMAE | WHAT
|STOVERl STRAW

MAME
STOVER



Anm



CATRE


I LATMWE
0] f CKS





SW R-


Figure 2.8. Family living quarters and animal keeping facil-
ilities on farm in western highlands of Guatemala
(See farmstead and fruit in Figure 2.7)


deducting all costs. On the farmer's own land, he produces 75
percent of the maize, beans, and fava, 80 percent of the
wheat, and 63 percent of the potatoes. Only 30 percent of the
forest and grasslands are owned by him. On the land surrounding
the house, including some forest land, a portion of all the crops
cultivated are represented. The farmstead (Figure 2.8) contains
several sheds for livestock and for forage and wood storage (both
firewood and lumber). One bedroom of the house doubles as a
weaving room for making sweaters, and another bedroom doubles as
a carpentry shop.
The distribution of labor, sale of products, purchases and
sources of food for the Guatemala highland farm are shown in
Figure 2.9. The farmer works 75 percent of the time on the farm
and 25 percent off the farm. His wife works half time on the
farm and half time off the farm. This latter situation is also
not very typical of the region. Of the seven children, two work
off the farm full time and are not counted in the farm picture,
although they do consume eggs and send some money home. The
other five, who are in school, work on weekends making sweaters
and furniture.
About 80 percent of the labor for the crops comes from off
the farm. Of the family labor, most of it (43 percent) is used
in the various activities within the household, including gath-
ering firewood, about 20 percent is expended on animals, and
12 percent on the crops. Excluding the two children who work
full time off the farm, about 25 percent of the family labor is
used off the farm.
The family at present has three cows, of which one or two
are in production at one time. A small proportion of the milk is
sold, but most of it comes into the household, where 10 percent
is consumed fresh and the rest is used to make cheese and whey.
Of the cheese, 20 percent is consumed in the household and 80


Figure 2.9. Distribution of labor, income (sales of products or
off-farm labor), and purchases from exogenous
sources for small crop/livestock farm in western
highlands of Guatemala (Numbers are percent of
total of that item )

percent is sold. Small amounts of whey are sold and consumed,
but most is used to feed the pigs (60 percent) and the dogs (35
percent). All the cream removed from the milk is consumed in the
household.
There is usually one sow that has a litter of six to eight
pigs at approximately six-month intervals. Two of the pigs are
kept on the farm for fattening, while the rest are sold in the
market or to other farmers at the time of weaning. The only meat
produced for the household from two pigs is 2 to 3 kg each six
months when the fat pigs are sold and butchered. This amount
represents 3 percent of the total pork produced on the farm and
about 10 percent of the pork meat consumed by the family.
The family maintains both laying hens and young chickens.






All the old hens are sold for meat, and 58 percent of the young
chickens are sold when they weign 1 to 2 kg. The feathers from
chickens killed on the farm are used to make artificial flowers
as a household industry (20 percent) or composted to make
fertilizer (80 percent).
Maize is the basic food staple of the family diet, and 20
percent of the wheat is consumed. (Most of the wheat grown in
the highlands is marketed, but some is consumed in this
particular area.) Of the maize produced, 40 percent is fed to
the pigs, 20 percent to the chickens, 10 percent to the dogs, 19
percent is consumed in the household, 10 percent is sold at the
end of the year when there is surplus, and 1 percent is used for
seed. The maize stover is fed to the cattle. The parts rejected
by the cattle (lower part of the stalks) is mixed with manure to
produce compost. The same procedure is followed with the wheat
straw. Potato vines are fed to livestock unless they were
fumigated shortly before harvest, in which case they are left for
incorporation into the soil.
Of the vegetables, a wild turnip that grows as a weed in the
maize (recently mixed with broccoli, which is allowed to reseed
itself) is sold, consumed or fed to the animals. It is sold for
human consumption and consumed id the house when the leaves are
young but fed to the livestock when the leaves are older.
Recently, a small garden patch was established with cabbage,
cauliflower, carrots, and radishes, of which half is consumed and
half is sold.
Besides providing deciduous and other fruit, the fruit
orchard also provides herbs for medicines, which account for 25
percent of the medicine used by the family.
The forest (including the grasslands) provides leaf mulch,
half of which is used for compost on the farm and the other half
as payment for gathering the mulch. The forest also provides
firewood and pinecones for fuel and raw materials for making
implement handles and lumber. The lumber, which is sawed by
off-farm labor, was used for building the house, and is used for
constructing sheds, furniture, and boxes for seed potatoes.
In addition to purchasing candles as a source of light, the
family buys ocote, which is a special pitch-pine kindling used
for starting fires. They buy cloth to make about 50 percent of
their clothes and purchase the other half ready-made. Wool yarn
is also bought for making sweaters, of which 7 percent is used
for family needs and the rest sold. Food items wnich are
purchased include tomatoes, garlic, onions, peppers, beans
(Phaseolus vulgaris), coffee, sugar, chocolate, riceflour,
oatmeal, cooking oil, lard, noodles, etc.
Even though sone piloy (beans) is produced on the farm,
yields are presently insufficient for food needs. Bush beans
(Phaseolus vulgaris) are being tested as a means of decreasing
dependence on purchase.
The farm operation described is a very complex system. A
wide variety of activities are carried on to maximize resource
utilization and reduce risks. Due to the tedious balance of the
system, interventions intended to produce change must be
carefully evaluated; otherwise serious imbalances will be cre-
ated.


REFERENCES

M.L. Barnett. 1978. Livestock, rice and culture. Paper
presented at Bellagio Conference, reprint available from
The Rockefeller Foundation.

A.J. De Boer and A. Weisblat. 1978. Livestock component of
small-farm systems in South and Southeast Asia. Paper
presented at Bellagio Conference; reprint available from
The Rockefeller Foundation.
H. Diaz. 1978. Integrating an animal component into an agri-
cultural development project. Paper presented at Bellagio
Conference, reprint available from The Rockefeller
Foundation.

B. Duff. 1978. The potential for mechanization in small-farm
production systems. Paper presented at Bellagio
Conference; reprint available from The Rockefeller
Foundation.

P.A. Fitzhugh. 1978. Role of sheep and goats in small-farm
systems. Paper presented at Bellagio Conference; reprint
available from The Rockefeller Foundation.

R.R. Harwood. 1978. Cropping systems in the Asian humid trop-
ics. Paper presented at Bellagio Conference, reprint
available from The Rockefeller Foundation.

R.R. Harwood and F.C. Price. 1976. Multiple cropping in trop-
ical Asia. In Multiple cropping, R.I. Papendick et al.,
eds. Madison, Wisc.: American Society of Agronomy.

P.E. Hildebrand. 1978. Motivating small farmers to accept
change. Paper presented at Bellagio Conference; reprint
available from The Rockefeller Foundation.

E.Q. Javier. 1978. Integration of forages into small farming
systems. Paper presented at Bellaglo Conference; reprint
available from The Rockefeller Foundation.

J.H. Maner. 1978. Nonruminants for small-farm systems. Paper
presented at Bellagio Conference; reprint available from
The Rockefeller Foundation.

R.R. McDowell. 1978. Are we prepared to help small farmers in
developing countries? J. Animal Sci. 47:1184-1194.

J.J. Riley. 1978. Land, water, and man as determinants in
small-farm production systems. Paper presented at
Bellagio Conference; reprint available from The Rockefeller
Foundation.









THE SONDEO: A TEAM RAPID SURVEY APPROACH
Peter E. Hildebrand


Several characteristics are critical to an efficient and
functioning multidisciplinary effort: first, those concerned must
be well trained in their own field; secondly, they need a working
understanding of -- and must not be afraid to make contributions
in -- one or more other fields. Team members must not feel the
need to defend themselves and their field from intrusion by
others. Working together, all members of the team should view
the final product as a joint effort in which all have par-
ticipated and for which all are equally responsible. That means
that each must be satisfied with the product, given the goals of
the team, and be willing and able to defend it.
Perhaps the most critical characteristic required to achieve
success in a multidisciplinary team is this identification with a
single product in which all participate. The product can be
complex and involve a number of facets, but it should result from
the joint effort of the whole team and not contain strictly iden-
tifiable parts attributable to individual team members. Failures
of multidisciplinary efforts in agricultural institutions fre-
quently result because teams are organized as committees that
meet occasionally to "coordinate" efforts, but in which the crop
work is left to the agronomists, the survey to the an-
thropologists, and the desks to the economists. In these cases
there is not a single identified product but, rather, several
products or reports purported to be concerned with the same
problem.


THE SONDEO: A TEAM RAPID SURVEY APPROACH

The Sondeo is a modified survey technique developed by the
Guatemalan Institute of Agricultural Science and Technology
(ICTA) as a response to budget restrictions time requirements,
and the other methodology utilized, to augment information in a
region where agricultural technology generation and promotion is
being initiated.
In order to understand the methodology, it is first
necessary to understand how ICTA is organized at the regional
level. Each of the regions in which the Institute functions has
a Regional Director who is the representative of the Director
General of the Institute and of the Technical Director. Within
the region, each area in which work is being carried out is in
the charge of a "sub-regional delegate," a technician who has a
minimum amount of administrative responsibilities. All the tech-
nicians, from whatever discipline or program, who work in the
area are responsible to him. This multidisciplinary team is
usually comprised of some or all of the following: plant
breeders, pathologists, a socioeconomist, and approximately four
general agronomists who are the Technology Testing Team. This
group, backed up by the national coordinators of programs (corn,
beans, etc.) and support disciplines (socioeconomics, soil
management) are responsible for orienting and conducting the




smell) experiment station in the area, farm trials, tests by
farmers of promising technology, evaluation of the acceptability
of the technology tested by farmers, and economic production or
farm records maintained by farmers with the help of the
technicians. In order to provide the original orientation to the
team, the Sondeo, or reconnaissance survey, is conducted by
members of the Techology Testing Team who are going to work in
the area, sometimes personnel from an appropriate program, and a
team from socioeconomics comprised of one or more of the
following: anthropologists, sociologists, economists, agri-
cultural economists and/or engineers. Usually, there are five
people from socioeconomics and five from the Technology Testing
Team who form a ten-man Sondeo team for an area. The
purpose of the Sondeo is to provide the information required to
orient the work of the technology generating team. The cropping
or farming systems are described, the agro-economic situation of
the farmers is determined, and the restrictions they face are
defined, so that any proposed modifications of their present
technology are appropriate to their conditions. If ICTA is to
work in an area that is not previously defined, such as by the
bounds of a land settlement or an irrigation project, one of the
objectives of the Sondeo is to delimit the area.
As well as delimiting the area of this homogeneous system,
the tasks of the Sondeo team are to discover what agro-
socioeconomic conditions all the farmers who use the system have
in common and then to identify which are the most important in
determining the present system and therefore would be the most
important to consider in any modifications to be made by the team
in the future. Finally, the end purpose of the Sondeo is to
orient the first year's work in farm trials and variety
selection. It also serves to locate future collaborators for the
farm trials and for the farm record projects.
Because the farm trials are conducted under farm
conditions, during the first year they provide an additional
learning process about the conditions that affect the farmers and
are invaluable in acquainting the technicians with the realities
of farming in the area. The farm records which are also
initiated in the first year -- provide quantifiable technical and
cost information on the technology being used by the farmers. At
the end of the first year's work, then, the technicians have not
only been farming under the conditions of the farmers in the
area, but they also have the information from the farm record
project. For this reason, it is not necessary to obtain
quL~ntifiable information in the Sondeo, which is not a benchmark
study. Quantifiable information for impact evaluation in the
area is available from farm records which increase in value each
year.


THE SONDEO PROCEDURE

The primary purpose of the Sondeo, then, is to acquaint the
technicians with the area in which they are going to work.
becausee quantifiable information is not needed, the Sondeo can be

94


questionnaires are used; so farmers are interviewed in an
informal manner that does not alienate them. At the same time,
the use of a multidisciplinary team serves to provide information
from many different points of view simultaneously. Depending on
the size, complexity, and accessibility of the area, the Sondeo
should be completed in from 6 to 10 days at a minimum of cost.
Areas of from 40 to 50 km2 have been studied in this period of
time. The following is a description of the methodology for a
six-day operation.

Day 1
The first day is spent in a general reconnaissance of the
area by the whole team as a unit. The team must make a prelim-
inary determination of the most important cropping or farming
system that will serve as the key system, become acquainted in
general terms with the area, and begin to search out the limits
to the homogeneous system. Following each discussion with a
farmer, the group meets out of sight of the farmer to discuss
each one's interpretation of the interview. In this way, each
team member begins to become acquainted with how the others
think. Interviews with farmers (or other people in the area)
should be very general .and wide-ranging because the team is
exploring and searching for an unknown number of unknown
elements. (This does not imply, of course, that the interviews
lack orientation.) The contribution or point of view of each
discipline is critical throughout the Sondeo, because the team
does not know beforehand what type of problems or restrictions
may be encountered. The more disciplines that are brought to
bear on the situation, the greater is the probability of
encountering the factors that are, in fact, the most critical to
the farmers of the area. It has been established that these
restrictions can be agro-climatic, economic or socio-cultural.
Hence, all disciplines make equal contributions to the Sondeo.

Day 2
The interviewing and general reconnaissance of the first day
serve to guide the work of the second day. Teams are made up of
pairs: one agronomist or animal scientist from the Technology
Testing Team and one person from socioeconomics who work together
in the interviews. The five teams scatter throughout the area
and meet again either after the first half-day (for small areas
or areas with good access roads) or day (for larger areas or
where access is difficult and more time is required for travel).
Each member of each team discusses what was learned during the
interviews, and tentative hypotheses are formed to help explain
the situation in the area. Any information concerning the limits
of the area is also discussed to help in its delimitation. The
tentative hypotheses or doubts raised during the discussion serve
as guides to the following interview sessions. During the team
discussions, each of the members learns how interpretations from
other points of view can be important in understanding the
problems of the farmers of the region.
Following the discussion, the team pairs are changed to
maximize interdisciplinary interaction and minimize interviewer








bias, and they return to the field guided by the previous
discussion. Once again, following the half-day's or day's in-
terviews, the group meets to discuss the findings.
The importance of these discussions following a series of
interviews cannot be overstressed. Together, the group begins to
understand the relationships encountered in the region, delimits
the zone, and starts to define the type of research that is going
to be necessary to help improve the technology of the farmers.
Other problems such as marketing -- are also discussed and, if
solutions are required, relevant entities can be notified. It is
important to understand the effect that these other limitations
will have, if not corrected, on the type of technology to be
developed, so that they can be taken into account in the
generation process.
During the second day there should be a notable convergence
of opinion and a corresponding narrowing of interview topics. In
this way, more depth can be acquired in following days on the
topics of increasing interest.

Day 3
This is a repeat of the second day and includes a change in
the makeup of the teams after each discussion. A minimum of four
interviews/discussion cycles is necessary to complete this part
of the Sondeo. If the area is not too complex, these cycles
should be adequate. Of course, if the area is so large that a
full day of interviewing is required between each discussion
session, then four full days are required for this part of the
Sondeo.

Day 4
Before the teams return to the field for more interviews on
the fourth day, each member is assigned a portion or section of
the report that is to be written. Then, knowing for the first
time for what topic each will be responsible, the teams,
regrouped in the fifth combination, return to the field for more
interviewing. For smaller areas, this also is a half-day. In
the other half-day, and following another discussion session, the
group begins to write the report of the Sondeo. All members
should be working at the same location so that they can circulate
freely and discuss points with each other. For example, an
agronomist who was assigned the section on maize technology may
have been discussing a key point with an anthropologist and need
to refresh his memory about what a particular farmer said. In
this manner the interaction among the disciplines continues.

Day 5
As the technicians are writing the report, they invariably
encounter points for which neither they nor others in the group
have answers. The only remedy is to return to the field on the
morning of the fifth day to fill in the gaps found the day
before. A half-day can be devoted to this activity, together
with finishing the writing of the main body of the report.
In the afternoon of this day, each team member reads his
section of the report to the group for discussion, editing and
approval. The sections should be read in the order in which they
will appear in the report. As a group, the team should approve


and/or modify what is presented.

Day 6
The report is read once again and, following the reading of
each section, conclusions are drawn and recorded. When this is
finished, the conclusions are read once again for approval, and
specific recommendations are then made and recorded, both for the
team who will be working in the area and for any other agencies
that should be involved in the general development process of the
zone.
The product of the sixth day is a single report generated
and authored by the entire multidisciplinary team that should be
supported by all of the members. Furthermore, after par-
ticipating in a team effort for six days, each member should be
able to defend all the points of view discussed, the conclusions
drawn, and the recommendations made.


THE REPORT

To a certain extent, the report of the Sondeo is of sec-
ondary value because it has been written by the same team that
will be working in the area. Most of its value lies in the fact
that they have written it. By forcing the team members into a
situation where many different points of view have to be taken
into consideration and coalesced, the horizons of all will have
been greatly amplified. Further, the report can serve as
orientation for nonparticipants, such as the Regional Director or
the Technical Director, in discussing the merits of various
courses of action. However, it is also obvious that the report
will appear to be one written by ten different persons in a
hurry, which is exactly what it isl It is not a benchmark study
with quantifiable data that can be used in the future for project
evaluation; rather, it is a working document to orient the
research program and it served one basic function in just being
written.


CONCLUDING REMARKS

The disciplinary specialty of each member of the Sondeo team
is not critical so long as there are several disciplines
represented, and, if the Sondeo is in agriculture, a significant
number of them are agriculturalists, at least some of whom who
will be working in the area in the future. The discipline of
coordinators of Sondeos is probably not critical, either, if they
are persons with a broad capability, an understanding of
agriculture (if it is an agricultural Sondeo), and experience in
surveying and survey technique. However, the coordinators must
have a high degree of multidisciplinary tolerance and be able to
interact with all the other disciplines represented on the team.
The coordinators, in a sense, are orchestra directors who
must assure that everyone contributes to the tune and that, in
the final product, all are in harmony. They must control the
group and maintain discipline. They arbitrate differences,
create enthusiasm, extract hypotheses and thoughts from each





participant, and ultimately will be the ones who coalesce the
product into the final form. It is perhaps not essential that
they have prior experience in a Sondeo, but it would certainly
improve their efficiency if they had.


SELECTED REFERENCES

Chinchilla, Maria E. Condiciones agro-socioeconomicas de una
zona maicera-horticola de Guatemala. Trabajo presentado en
la XXV Reunion Anual del P3OMCA, Tegucigalpa, Honduras, 19-
23 de Marzo, 1979.

Hildebrand, P. Motivating small farmers to accept change.
Paper prepared for presentation at the Conference on
Integrated Crop and Animal Production to Optimize Resource
Utilization on Small Farms in Developing Countries. The
Rockefeller Foundation Conference Center, Bellagio, Italy,
18-23 October, 1978, ICTA, Guatemala.

Hildebrand, P.E. Summary of the Sondeo methodology used by
ICTA, ICTA, Guatemala, 1979.


COMPARING INFORMAL AND FORMAL SURVEYS
Steven C. Franzel


Farming systems practitioners generally make use of two
types of surveys -- informal and formal. The objectives of
informal surveys, also called sondeos, rapid-reconnaissance
surveys, or exploratory surveys, are to develop a rapid
understanding of farmer circumstances through direct, informal
interaction between researchers and farmers. Informal surveys
have four distinguishing characteristics. First, farmer inter-
views are conducted by researchers themselves, not by
enumerators, as in formal surveys. Second, interviews are
essentially unstructured and semidirected, with emphasis on
dialogue and probing for information. Questionnaires are never
used; however some researchers use topic guidelines so as to
ensure that they cover all relevant topics on a given subject
(Collinson 1982). Third, informal random and purposive sampling
procedures are used instead of formal random sampling from a
sample frame. Fourth, in an informal survey, the data collection
process is dynamic, that is, researchers evaluate the data
collected and reformulate data needs on a daily basis (Honadle
1982). In a formal survey, reformulating data needs requires
changing the questionnaire or adding a new questionnaire; this
cannot be done on a frequent basis. Informal surveys are
generally conducted over a period of one week to two months
during the growing season.
The objectives of a formal survey may be quite diverse to
verify hypotheses developed during an informal survey, to
quantify parameters critical to developing the understanding of
the system, or to measure resource stocks and flows. In a formal

98


survey, a questionnaire is administered by enumerators to a
random sample of farmers. Formal surveys may involve single
visits to farmers or frequent visits over a period of a growing
season, a calendar year, or longer. Since questioning is
standardized and sampling is random, data are subject to
statistical testing procedures.
Most farming systems researchers use a combination of the
two types of surveys; a few use one type exclusively. khat
appears clear, however, is that the role of the informal survey
in farming systems and farm management investigations in
developing countries has increased in importance in recent years,
relative to the formal survey. In the past, the informal survey
was generally considered to be a "pre-survey," that is, a
preliminary task to complete before starting a formal survey. In
fact, its primary function was to contribute to more effective
planning and execution of the formal surveys. In recent years,
however, same farming systems researchers have begun to place
greater emphasis on the informal survey. For example, Collinson
(1982) calls the informal survey the "pivotal" procedure in the
diagnosis of farming systems. Hildebrand (1981) claims that
well-managed informal surveys can generate the information
necessary for identifying principal farmer problems and planning
experimentation to solve these problems.
Indeed, many FSR/E practitioners have found the informal
survey to be an extremely useful tool for diagnosing farming
systems (Hildebrand 1991; Rhoades, 1982; Byerlee and Collinson
1980). The principal advantages are (1) its low cost and rapid
turnaround, (2) the emphasis placed on direct researcher-farmer
teamwork, (3) its sequential, iterative data collection procedure
in which data are evaluated and data needs are reformulated on a
daily basis, (4) its facilition of interdisciplinary interaction,
and (5) its conduciveness to collection of data concerning
farmers' values, opinions, and objectives.
However, informal surveys have important disadvantages as
well, which may render data inaccurate. First, the sample of
farmers interviewed may not be representative of the group
researchers wish to characterize. Second, since questioning is
not standardized, it may not be possible to generalize across the
farmers interviewed. Thus Shaner, Philipp, and Schmehl (1982)
warn that in analysis of results from informal surveys, sta-
tistical testing is not possible, summarization is difficult, and
the reliability of conclusions is subject to question.


RESEARCH PROBLEM

Because both informal and formal surveys have particular
strengths and weaknesses, many researchers use both approaches in
their investigations. For example, CIMMYT advocates a two-stage
procedure an informal survey followed by a formal survey. The
principal objective of the formal survey is to verify, using
appropriate statistical tests, the impressions developed during
the informal survey.
However, given the acute scarcity of research resources in
developing countries, the formal survey is too expensive and
time-consuming an exercise if it serves only to confirm informal

99






survey findings. Little work has been done to formally compare
the information and implications for research from informal
surveys with those of the ensuing formal survey for the same
group of farmers. Indeed, if the formal survey exercise does not
lead to significant improvements in the accuracy of information
and the design of experiments appropriate for farmers, one can
argue that it is superfluous.
In this paper, we examine the utility of conducting a formal
survey by comparing the data and the proposed experimental
program developed in an informal survey with those developed from
an ensuing formal survey in the same area. The utility of
carrying out a formal survey, in addition to an informal survey,
is evaluated by:

1. Comparing the data obtained with those obtained in the
informal survey, using a systematic rating system to measure the
degree of closeness.

2. Assessing the implications that the formal survey re-
sults have on changing or refining the proposed research and
extension program planned following the informal survey.

In addition, we examine some of the sources of inaccuracy in
the informal survey findings in order to make recommendations for
conducting more effective informal surveys in future exercises.


CONCLUSIONS

In summary, it appears that the contribution of the formal
survey to developing an understanding of the farming systems and
an experimental program for Middle Kirinyaga were rather
marginal, relative to its costs. The formal survey involved
approximately four months of the researchers' time and
istantial costs in transpol c, hiring and training of enu-
merators, computer and manual data analysis, paper, and
photocopying. However, there were relatively few refinements
made in the experimental program following the formal survey and,
in fact, most of the changes were not due to information gained
in the formal survey. Rather, they were due to:

1. Incidental refinements and additions which researchers
informally discovered, such as the potential of coffee husks.
This lends support to conducting a more thorough informal survey,
or carrying out more frequent informal surveys in the same area,
rather than mounting a formal survey.

2. A deliberate acceptance of lower accuracy in some as-
jects of informal survey method and analysis, likely due to the
fact that the researchers knew that a formal survey would be
carried out and thus more precise information would be obtained.
The effort to measure plant population reflects this.

It is important to emphasize the danger in overgeneralizing
from our conclusion that a formal survey was not really
~.octhwhile. Certainly, different methods are appropriate for


different sets of circumstances. For example, Middle Kirinyaga
has several features that make it relatively easy for re-
searchers to develop an understanding of farming systems without
a formal survey. First, the cropping system, composed almost
exclusively of maize and beans, is less complex in many senses
than cropping systems in other areas. Second, farmers and local
officials were exceptionally cooperative. Third, farmers' fields
are generally all located at their homestead, making it fairly
easy to estimate farm size and generalize about field
characteristics.
On the other hand, one can also argue that Middle Kirinyaga
has several features that make it more difficult than other areas
to study. This lends support to the position that if a formal
survey is not useful in Middle Kirinyaga, it will not be useful
in most other areas. First, farmers have two cropping seasons
per year. This in effect doubles the quantity of information
needed about cropping practices. Second, two recommendation
domains co-exist in the area and it is often difficult to
ascertain the relative numbers in each and the characteristics
that distinguish them. Third, there appears to be much variation
in how certain operations are performed, e.g., land preparation
and planting. Furthermore, it should also be noted that the
inclusion of the repertory grid and hierarchical decision-tree
methods for developing the understanding of farmer decisions in
the informal survey made the survey more effective than it
otherwise would have been.
Overall, the data in this paper support the hypothesis that
the informal survey is an effective and sufficient method for
developing an understanding of farming systems and planning
experimental programs for farmers. It also suggests that a
formal survey may be replaced by (1) a slightly longer and more
carefully managed informal survey than would otherwise be
conducted, or (2) two or more informal surveys. However, it
could also be argued that even if this is so, a very brief,
focused formal survey may be important for verifying selected
findings of the informal survey, quantifying a few important
variables, providing a cross-check for the informal survey, and
lending greater credibility to the diagnostic exercise.


REFERENCES

Byerlee, D., M. Collinson, et al. 1980. Planning technologies
appropriate for farmers: concepts and procedures. Interna-
tional Maize and Wheat Improvement Center (CIMMYT), Mexico.

Caldwell, John. 1983. Issues in the integration of the
household in farming systems research and development. Paper
presented at the Family Systems and Farming Systems
Conference, Virginia Tech., Blacksburg, Virginia.

Collinson, M.P. 1980. The use of farming systems research for
understanding small farmers and improving relevancy in
adaptive experimentation. Paper presented at Second
Symposium on Intercropping for Semi-arid Areas, University of
Dar es Salaam, Morogoro, Tanzania.






Collinson, M.P. 1982. Farming systems research in Eastern
Africa: the experience of CIMMYT and some national
agricultural research services: 1976-81. Michigan State
University International Development Paper No. 3. East
Lansing, Michigan.

Dillon, J.L. 1976. The economics of systems research.
Agricultural Systems, 1:1:5-22.

Franzel, Steven, 1983. Planning an adaptive production research
program for small farmers: a case study of farming systems
research in Kirinyaga District, Kenya.

Franzel, Steven. 1984. Modeling farmers' decisions in a farming
systems research exercise: the adoption of an improved maize
variety in Kirinyaga District, Kenya. Human Organization
43:3, Washington D.C.

Franzel, Steven, and Njogu Njery. 1982. Informal survey report
on two farmer recommendation domains in Middle Kirinyaga.
CIMMYT Eastern Africa Economics Program, Nairobi, Kenya.

Gilbert, E.H., D. Norman, and F. Winch. 1980. Farming systems
research: a critical appraisal. MSU Rural Development Paper
No. 6. East Lansing, Michigan.

Hildebrand, P.E. 1981. Motivating small farmers, scientists and
technicians to accept change. Agricultural Administration
8:375-83.

Honadle, George. 1982. Rapid reconnaissance for development
administration: mapping and moulding organizational
landscapes. World Development, 10:8, London.

Johnson, G.L. 1981. Small farms in a changing world. Paper
presented at Farming Systems Reseach Symposium, Kansas State
University, Manhattan, Kansas.

Rhoades, R.E. 1982. The art of the informal agricultural
survey. International Potato Center. Lima, Peru.

Shaner, W.W., P.F. Philipp, and W.R. Schmehl. 1982. Farming
systems research and development: guidelines for developing
countries. Westview Press. Boulder, Colorado.


102































THE FOLLOWING SELECTION
HAS BEEN PRINTED
WITH PERMISSION

DATE: 07/02/92


Author: POTS, SCMINK & SPRING

Title: Chapter 6 and Chapter 7

Book: GENDER ISSUES IN FARMING SYSTEMS
RESEARCH AND EXTENSION

Volume: No: Pgs: 73-87,149-169 Copyright Year: 1987

Reprinted by Permission of: Westview Press Inc


THIS MATERIAL MAY NOT BE
REPRODUCED IN ANY MANNER
WITHOUT THE PERMISSION
OF THE COPYRIGHT HOLDER











Published in cooperation with the
Women in Agricultural Development Program,
University of Florida


Gender Issues
in Farming Systems
Research and Extension


EDITED BY
Susan V. Poats, Marianne Schmink,
and Anita Spring



















Westview Press
BOULDER & LONDON











6
Research, Recommendation and
Diffusion Domains: A Farming Systems
Approach to Targeting
Peter Wotowiec, Jr., Susan V. Poats, and Peter E. Hildebrand

TARGETING FARMING SYSTEMS ACTIVITIES:
HOMOGENIZING VARIABILITY?
Inherent in the farming systems approach is the recog-
nition of the variability of the complex circumstances
farmers face while managing farms that are comprised of
inter-related crop, animal, household, and off-farm
enterprises. Diversity in farming systems must be
recognized in developing appropriate technologies for the
farmers that manage those systems. However, it is not
practical to conduct research tailored specifically to a
few individual farmers. Targeting entails the grouping
together of similar clientele so efforts can be suffi-
ciently focused. Although the concept of targeting might
seem contrary to the recognition of heterogeneity among
farms, it is an essential component of the farming systems
approach. When Farming Systems Research and Extension
(FSR/E) practitioners target a group of farming systems as
relatively homogeneous based on a few simple factors, the
existing variability among farms is often not sufficiently
considered. How can FSR/E teams define and target homo-
geneous groups of farming systems without losing sight of
the heterogeneity among them? Farming systems practi-
tioners take different positions on this issue (Cornick and
Alberti 1985).
One perspective stresses the early definition of homo-
geneous groups of farmers using the recommendation domain
concept to guide subsequent research activities. Collinson
(1979, 1980), Gilbert et al. (1980), and Franzel (1985)
advocate ex ante delineation of recommendation domains
based on secondary data and preliminary surveys, followed
by a formal survey to refine the domain boundaries. Both
Collinson and Franzel describe a technique of defining
recommendation domains through interviews with extension
agents and local authorities before actually initiating
activities with farmers. Early definition of






recommendation domains is usually based upon a few
relatively easily identifiable factors such as soil type,
agroecological zones, crop type, and management (Harrington
and Tripp 1985). These authors note the importance of
continuing the refinement of domain boundaries throughout
the sequence of on-farm adaptive research, but the subse-
quent reassessment of recommendation domains is often not
vigorously pursued.
A more recent view states that grouping farming systems
should not take place until the researchers have an ade-
quate understanding of the variability inherent in local
farming systems, usually not accomplished early in the work
in an area. Cornick and Alberti argue that recommendation
domains established early are frequently poorly conceived
and lead to a premature assumption of homogeneity. The
failure to consider potential variability from factors such
as long-term climate induced trends in cropping patterns,
household decision-making and labor allocation, or rela-
tionships between on- and off-farm activities, may bias
subsequent technology development. For example, Cornick
and Alberti (1985:1) note:

...the roles of women and children that can be critical
factors in the development and subsequent adoption of
technologies are often explicitly excluded from consi-
deration in recommendation domains. This occurs because
the usual time frame for development of recommendation
domains is inadequate to the task of understanding intra-
household dynamics and the importance they hold in the
system.

In particular, socioeconomic factors are often not
fully integrated into domains defined early, either because
of the longer period of time necessary to gather this
information, or because of the absence of trained social
scientists as part of farming systems teams. One area
often poorly covered in early definitions of domains is the
different agricultural roles of men and women. Proceeding
with on-farm research and other activities on the basis of
a hastily achieved assumption of homogeneity could result
in inefficient subsequent research and the promotion of
solutions that are not appropriate to farmers (Cornick and
Alberti 1985:25) or technologies that may favor some
farmers (male) while causing disadvantages for others
(female).
In this paper the issue of variability versus
homogeneity in the targeting of farming systems research
and extension activities is explored. After a brief review


of targeting in FSR/E using recommendation domains, prob-
lems in the conventional use domains in FSR/E are described
in an attempt to bring together the two differing view-
points and to begin to resolve the question. The refined
concept of targeting allows for better inclusion of gender
variables in the definition of domains.

OVERVIEW OF TARGETING AND RECOMMENDATION DOMAINS

Targeting for Efficiency and Social Equity

FSR/E must differentiate between various potential
farmer-client groups and determine the particular needs of
each, if technologies are to be developed that clearly meet
those needs (Byerlee and Hesse de Polanco 1982). Most
literature on the subject of targeting in farming systems
has stressed the increase in efficiency of FSR/E activities
made possible through focusing upon specific, relatively
homogeneous farmer groups.
Efficiency in allocation of research resources is
essential if a program is to reach and benefit a maximum
number of farmers. By focusing scarce resources upon
roughly similar groups of farmers, research programs are
able to carry out investigations on a selected number of
representative farms and later can transfer the findings to
the comparable situations faced by other farmers.
Targeting is also important in justifying the farming
systems approach to institutional policy makers who are
concerned about social equity in the distribution of
resulting benefits. Farming systems practitioners use tar-
geting concepts to assist them in making decisions which
increase the likelihood of an optimal distribution of
research results among the members of a community.

Conventional Concept of Recommendation Domains

The concept of "recommendation domains" has been widely
used in targeting farming systems research since Perrin et
al. (1976) first introduced the idea. It is described and
defined by.Byerlee et al. (1980:899) in the following
manner:

... a recommendation domain (RD) is a group of farmers
with roughly similar practices and circumstances for
whom a given recommendation will be broadly appropri-
ate. It is a stratification of farmers, not area:
farmers, not fields, make decisions on technology.







Socioeconomic criteria may be just as important as
agroclimatic variables in delineating domains. Thus
resulting domains are often not amenable to geographi-
cal mapping because farmers of different domains may be
interspersed in a given area.

Using this definition, neighboring farm households
might be placed in different recommendation domains because
of differences in availability of family labor. In socie-
ties where women cultivate different crops than those of
the men, female farmers could comprise a recommendation
domain separate from male farmers even if they are from the
same household.

Expanding Upon the Definition of Recommendation Domain

Perrin et al. (1976) originally conceived of the notion
of recommendation domains as an aid to researchers for
targeting the development of technologies to specific
audiences. The concept has been expanded since then to
include a number of additional situations and purposes.
Some of the most common applications of recommendation
domains include the following gleaned from current
literature on the topic:

(1) making policy decisions;
(2) identifying priority issues for research;
(3) specifying clientele for developing recommenda-
tions;
(4) selecting representative sites and farmer-
cooperators;
(5) focusing analysis of surveys and on-farm trials;
(6) orienting extensionists to groups of similar
farmers;
(7) transferring adapted technology to appropriate
farmers; and,
(8) enhancing equitable distribution of FSR/E benefits.

As Harrington and Tripp (1985) point out, the domain
concept is vital to every stage of the on-farm research
process. However, it is apparent from reviewing the
literature on the subject that the definition of "recommen-
dation domain" not only changes at each stage, but also
varies according to the individual who applies it as well
as to the end result. The wide variability among farmers
and farms, and the dynamic nature of the farming systems
development sequence, contribute to the confusion that


exists among FSR/E practitioners as to the general meaning,
and use of the term recommendation domain.

On-Farm Variability and Conventional Recommendation Domaii.

The emphasis by Byerlee et al. (1980) upon "farmers,
not fields" as the sole basis for the delineation of rec'
mendation domains is not always warranted because of the
variability found in some field situations. Cornick and
Alberti (1985) cite the case of farmers in the community
Quimiaq in the mountains of Ecuador who manage different
cropping patterns in different agro-ecological zones, a
product of altitude, temperature, and rainfall variation o,,
the mountain slopes. Not only does each farm cross agro-
ecological zones, but the cropping patterns found in each
field vary greatly from year to year. For example, depend
ing upon a farmer's perception of trends and yearly change:
in climatic conditions, bean or fava bean intercrops will
be assigned to maize fields located at varying elevations
along the slope.
Gender and intra-household variables are often
neglected in the process of defining a recommendation
domain because of the relatively more difficult and time:
consuming task of collecting and analyzing data on these;
variables. Existing information on gender and household
variables often offers few useful insights for defining
recommendation domains when compared to the secondary dat;
available on agroecological characteristics. In additic,i,
the gender and household data that may exist may be unob-
.tainable locally. Nevertheless, superficial understanding;
of these variables or the transfer of erroneous assumptio.
without continued investigation can hamper design and deli
very of appropriate technology.

Refining the Concept of Domains

The argument here is that the issue of targeting in
FSR/E has become confusing because the definition of the
term "recommendation domain" has been stretched to cover
too many situations and too many different purposes. Fat:
ing systems practitioners must develop a common understan)cI
ing of how the use and definition of "domains" change as
the farming systems sequence progresses from initial chat-
acterization through proi. ter.t .Lgnosis, testing, adj ..(
tion, evaluation, and finally, to the delivery of the new
technology to farmers.
It is essential to account for the heterogeneity in
farming systems, even while delineating relatively





homogeneous groups. Refinement and expansion of the use of
domains in targeting will enable researchers to distinguish
applications of the domain concept, while still recognizing
the diversity among farm households and farming systems.
This can be accomplished by recognizing a problem focus
in the definition of the domains, by tying the changing
concept of domain more closely to the farming systems
sequence, and by stressing a greater inclusion of socio-
economic considerations into the targeting process. The
refinements outlined below are a sharpening of focus not a
changing of terminology, that will lead to increased
utility of this method of targeting in the field.
Any of the three types of domains described below may
be defined within specific geographic boundaries for ease
in conceptualization, but it is imperative to realize that
domains do not necessarily include all the area within the
boundaries prescribed. Because domains are based upon a
specified problem focus and upon socioeconomic considera-
tions in addition to the more geographically mappable fac-
tors of climate, altitude, and soil, they are actually
interspersed intermittently in a discontinuous pattern
throughout a geographic area.
The examples here will emphasize gender as a key factor
in delineating domains; other factors, such as class,
education, language use, or food preferences, could also be
used.

Research Domains: Targeting for Variability

A "research domain" is a problem-focused environmental
(agro-ecological and socioeconomic) range throughout which
it is expected that hypothesized solutions to a defined
problem could have potential applicability and therefore
should be tested. Research domains are determined during
the initiation of research activities, largely by consider-
ation of biophysical (agro-ecological) factors, with some
attention to socioeconomic and gender issues.

Recommendation Domains: Targeting for Homogeneity

Research domains are comprised of one or more agro-
socioeconomic "recommendation domains", that are tenta-
tively defined based upon the response of a specific tech-
nology to the actual agro-socioeconomic conditions foumd on
farms. A "recommendation domain" is a group of farmers (or
farmers and their fields) with a common problem for whom a
tested solution meets their biophysical and socioeconomic
requirements for adoption.


In the Ecuadorian case cited by Cornick and Alberti,
recommendation domains would be based not only upon farm
households, but also upon their separate fields that are
not contiguous but widely dispersed in location and alti-
tude. Each household might fall into several recommenda-
tion domains depending upon: (1) where their fields are
located along the agroecological gradient of the mountain-
side; (2) the climate-related crop management decisions
made for each of those fields; and, (3) the particular
problem solutions to be tested.
Other examples from West Africa demonstrate how gender
can be used to differentiate recommendation domains. In
many areas, men and women have separate fields, often
inherited from their same sex parent, that are not managed
communally by the household. Women traditionally grow rice
on their lands while men produce upland crops such as
groundnuts or sorghum on their own fields. In this system,
fields managed by a household pertain to different recom-
mendation domains depending upon both the cropping system
and the gender of the farmer manager. In one area of the
Ivory Coast, men plant yams in a cleared field. Women will
often care for the yam plants by weeding them while they
plant their vegetable crops in the space between the yam
plants. In this system, fields are neither men's nor
women's, nor would entire -ields fall into a single
problem-focused recommendation domain. Rather, domains
would be determined by crops and their managers, male or
female, and contain pieces of many fields.
Recommendation domains are seen as tentative in nature
throughout the on-farm adaptive research process. Recom-
mendation domains are initially hypothesized by the FSR/E
team on the basis of on-farm exploratory and refinement
trials, information collected through directed surveys, and
subsequent on-farm verification trials. Over time, as more
information is gathered, the recommendation domains are
refined and redefined to closer approach reality.

Diffusion Domains: Targeting for Communication

"Diffusion domains" are interpersonal communication
networks through which newly acquired knowledge of agri-
cultural technologies naturally flows (Hildebrand 1985).
Informal flow of information through a community grapevii.
is substantial (Rogers 1983). From farmer to farmer,
neighbor to neighbor, store operator to patron, information
about new ideas moves through a farming community. Aware-
ness of a new technology being verified in on-farm trials







takes place among farmers and their families who are not
directly involved in the on-farm research.
A farming systems team can enhance the informational
effect of on-farm research activities in a community. By
understanding the local communication networks in an area,
the FSR/E team can strategically locate on-farm verifica-
tion trials in each diffusion domain to enhance the diffu-
sion of information about a new technology among potential
users. This ensures a broader, more equitable distribution
of information because it has the potential of reaching
farmers who are difficult to reach through conventional
extension methods and who rely greatly upon localized
interpersonal communication to acquire information.
Frequently, information about new technologies
developed in agricultural programs tends to be communicated
only through male information networks. In some societies
information about technologies is diffused only slowly, if
at all, from men to women even within a household. Female
farmers are clearly disadvantaged in learning about new
technologies if they cannot participate in male-oriented
dissemination programs. Definition and use of diffusion
domains in the FSR/E testing process allows practitioners
to recognize and plan for the fact that men and women often
have different communication networks. For example, if men
gather and exchange information about agricultural
technology at certain locales (cooperatives, local seed and
feed stores, bars) where women are usually not permitted by
custom to enter, women may effectively be excluded from the
process of dissemination.
FIELD USE OF THE DOMAIN CONCEPT

In practice, farming systems teams work in a project
area located on the basis of geographical and political
considerations rather than with biological conditions or
socioeconomic concerns. Within a project area, project
focus can be based on a specific priority commodity common-
ly produced by farmers in the area or may be based on
socioeconomic considerations such as an emphasis upon small
farmers or women farmers. The farming systems team working
in the area may have responsibility for determining project
focus. Seldom will the team have input into defining the
project area. Even though it is of great importance in
targeting farming systems efforts, the process of selecting
the project area and project focus lies beyond the scope of
this paper. This discussion will commence with subsequent
stages of the targeting process. For the sake of brevity
and clarity, a relatively simple example will be used.


A Case of Targeting in the Farming Systems Approach

The following example is drawn from farming systems
activities in Central America (Ruano 1977; Hildebrand and
Cardona 1977; Reiche Caal et al. 1976). Although based on
actual experiences and cases, some liberty has been taken
with its portrayal here to shr i hor, this refined concept
domains might have been advantageously applied.
A farming systems team from the national research
institute composed of three agricultural technicians, one
economist, and one anthropologist (all men) was assigned to
a certain hilly section of the country. In accordance with
national agricultural production objectives, the team's
mandate was to work on improving the production of basic
grains among small, resource-limited farmers in the project
area (a commodity and socioeconomic based project focus).
Initial informal reconnaissance of the area and a
review of secondary information revealed that the area was
comprised of relatively flat, fertile lands in the valley
bottoms and poorer, rocky soils on the slopes. The larger,
fertile farms in the valley bottoms were owned by wealthier
farmers who were able to employ mechanization in their
cultivation systems. Tractors were used in their mono-
cultural stands of maize and short, improved sorghum
varieties. In contrast, the hillsides were largely devoted
to small farmer cultivation, with farms averaging about 3.5
hectares. Sorghum and maize were interplanted using mostly
traditional, taller sorghum varieties. A few farmers
employed bullocks and plows on their farms, but most
cultivated their crops by hand.
Unfortunately, little secondary information existed
concerning the socioeconomic conditions of the area.
However, generally for this region, people say that men
plant and tend the crops while women manage the household,
food processing and preparation, and the marketing. Little
was known about the role of women in production. The team
assumed that this was generally true for the project area.
The team did not at this point have any female members.
In keeping with their project focus, the team decided
their attention should be targeted on the smaller hillside
farmers and farms. A sondeo (Hildebrand 1982), or diag-
nostic survey, conducted in the hillside region revealed
that farmers in the hillside areas used similar systems of
intercropping maize and sorghum. They complained that the
scarcity and irregularity of rainfall had made maize cul-
tivation an increasingly risky endeavor. Farmers were
unable to grow enough maize to meet their consumption





needs. Only the male heads of households were targeted for
the sondeo.
Since irregular rainfall frequently caused the failure
of the maize crop, the more drought-tolerant sorghum was
being grown to supplement it. However, farmers expressed a
dislike for eating sorghum and indicated they only grew it
to sell for animal feed, using the proceeds to purchase
maize. In this sense, substituting cultivation of sorghum
for maize reduced the risk of crop failure yet provided for
the household subsistence needs.
Sorghum production in the area was higher per unit
planted than maize, but still below production levels
achieved elsewhere in similar environments with improved
varieties. As one facet of their farming systems program,
the team hypothesized that selected improved sorghum vari-
eties within the traditional cropping system could lead to
a partial solution to the identified production problem.
Based on these findings, the team considered the hill-
side maize and sorghum farmers and their fields, with
declining maize yields as a single "research domain"
(problem-focused, agroecological range). A series of
exploratory trials were designed for placement throughout
the research domain.
At harvest, the team collected production data as well
as information on farmer opinions about the new varieties.
Even though the new, earlier varieties performed well on
all test sites, there were sharp differences among farmers
as to their acceptability. Some farmers were planning to
keep seed and plant the new varieties again the following
season. Others were quite disinterested in the varieties,
but their reasons were unclear to the team. Based on far-
mer evaluations, the team partitioned the "research domain"
into two groups of farmers; those interested in planting
the sorghums again and those not interested. The former
group became a tentative "recommendation domain" and more
precisely refined trials were designed to continue testing
the varieties under farm conditions, while further deter-
mining the reasons for the farmers' acceptance of the new
sorghums. For the other group, more information was needed
by the team to determine why the new sorghums were unac-
ceptable. Thus, this group continued to constitute a
"research domain."
Information had been collected to characterize the
farming systems of the area while monitoring the explora-
tory trials. Continuous contact of the team members with
farmers during this period had yielded much additional
socioeconomic information not apparent from the initial


sondeo activity. All hillside farmers and their farming
systems no longer appeared alike.
Some farmers at slightly lower elevations had soils
with better water retention characteristics than other
farmers on higher slopes. These farmers could plant mi,
with a greater assurance of obtaining a harvest than th<
at higher locations with poorer soils. Through additional.
directed interviews, it was found that lower elevation
farmers tended to grow sorghum primarily as a cash crop:
Because of their favored soil conditions, they possessed
enough cash from crop sales to ensure a continuous supply
of maize in the household. These farmers did not consuim.
sorghum.
Over time the team came to realize that even though
most people claimed they did not eat sorghum, many were
actually using it as a substitute for maize. The team
hypothesized that sorghum consumption increased among les;
well-off households farming the poorer, higher elevation
fields. It was apparent that farmers of this group also
were not interested in the new higher yielding sorghums.
As one aspect of their attempt to resolve this seeming
contradiction, the team initiated informal surveys with
women of the households within this group. Unfortunately,
owing to socio-cultural and linguistic barriers, the male
team members were unable to obtain adequate information.
This was corrected by temporarily adding a female
social scientist from the institute headquarters to the
team to conduct the interviews. She found that these
families did consume sorghum, although they had not always
done so. Decreasing maize harvests and lack of resources
for the purchase of maize had forced them to consume sor-
ghum. Women interviewed indicated that consumption of sor-
ghum implied a certain social degradation, a "shame" in the
eyes of neighbors. In many cases, a farmer whose family
consumed sorghum was considered a poor provider. To the
casual observer, sorghum consumption was not apparent among
the farmers; but as the team moved deeper into the com-
munity, they found that sorghum was an important part of
the diet among families lacking maize.
Further study of sorghum preparation, cooking and
taste preferences revealed that sorghum, like maize, is
primarily eaten in the form of tortillas, either prepared
with maize or alone. Women said some of the new varieties
tasted bitter and were not fit for consumption. One of the
new varieties was not bitter-tasting, but due to purple
glumes, it left telltale dark spots when made into tor-
tilllas. Although the purple glumes could be removed after
many washings, this was an unacceptable alternative for







most families because of a scarcity of readily available
water in the higher elevation areas of the research domain.
Using this information, the team partitioned the
original research domain into two "recommendation domains."
For the earlier tentatively defined recommendation domain,
consisting of farmers who produced sorghum destined for the
animal feed market, on-farm testing of the previously
introduced new sorghum varieties was continued. For the
second recommendation domain, composed of relatively poorer
farmers producing sorghum for home consumption under less
favored soil conditions, the team recommended that the
research institute acquire or develop varieties with less
coloring and no bitter taste that could then be tested
on-farm with the farmers in this group.
Through this experience the FSR/E team and the research
institute began to realize that while women were not
directly involved in sorghum production, they did have con-
siderable influence in making cropping decisions that
affect household concerns such as consumption. Newly cog-
nizant of the need for an augmented social perspective in
their development activities, the team began a second phase
of on-farm experimentation targeted towards the two sep-
arate recommendation domains.
At the same time, they began to work with local exten-
sion personnel to study the flow of agricultural informa-
tion among the farmers and households ip the region. Rec-
ognizing the role that household consumption preferences
play in the adoption or rejection of sorghum technologies,
female team members and interviewers were added to the
farming systems program to ensure a balanced gender
perspective.
Among the many local information pathways, it was found
that women exchanged much information about sorghum and
other agricultural crops with other women at the weekly
markets. Among men, interpersonal communication concerning
farming and crops took place on Sundays when farmers from
the surrounding countryside congregated in the town plaza
to converse and visit. By the close of the second season
of farming systems activities, the team had tentatively
defined several local "diffusion domains" based on gender,
religious affiliation, locality groups, and other factors.
On-farm trials and extension efforts were managed to ensure
information flow to each diffusion domain.
CONCLUSION

This greatly simplified case provides an example of how
the refined domain concept allows grouping of roughly


homogeneous farmers while not losing sight of the
heterogeneity inherent among them. This conception of
domains is not a static one, but one that recognizes the
changing nature of the targeting process as a result of
on-going information gathering through surveys, participate!
observation, and on-farm experimentation. Maintaining a
flexible determination of domains allows for a greater
understanding of the diversity of local farming systems, or
the rationale behind the behavior of farmers, and of the
effect of gender and social factors upon the local practice
of agriculture.


REFERENCES

Byerlee, D., M. Collinson, et al.
1980 Planning Technologies Appropriate to Farmers:
Concepts and Procedures. Mexico: CIMMYT.
Byerlee, D. and E. Hesse de Polanco
1982 The Rate and Sequence of Adoption of Cereal
Technologies: The Case of Rainfed Barley in the
Mexican Altiplano. Mexico: CIMMYT.
Collinson, M. P.
1979 Deriving recommendation domains for Central
province, Zambia. Report no. 4. Nairobi, Kenya:
CIMMYUT.
1980 A Farming Systems Contribution to Improved
Relevancy in Agricultural Research: Concepts and
Procedures and Their Promotion by CIMMYT in Eastern
Africa. Nairobi, Kenya: CIMMYT East Africa
Economics Program.
Cornick, T. and A. Alberti
1985 Recommendation Domains Reconsidered. Paper
presented at the 1985 Farming Systems Research and
Methodology Symposi im. Manhattan, KS: Kansas State
University.
Franzel, S.
1985 Evaluating a Method for Defining Recommendation
Domains: A Case Study from Kenya. Paper presented
at the 1985 Farming Systems Research and Methodology
Symposium. Manhattan, KS: Kansas State University.
Gilbert, E. H., D.W. Norman and F.E. Winch
1980 Farming Systems Research: A Critical Appraisal.
Michigan Sate University Rural Development Paper No.
6. East Lansing, MI: Michigan State University.
Harrington, L. W. and R. Tripp
1985 Recommendation Domains: A Framework for
On-Farm Research Working Paper 02/84. Mexico:
CIMMYT.





Hildebrand, P.E.
1982 Combining Disciplines in Rapid Appraisal: The
Sondeo Approach. Agricultural Administration 8:
423-432.
1985 On-Farm Research: Organized Community
Adaptation, Learning and Diffusion for Efficient
Agricultural Technology Innovation. Farming Systems
Support Project Newsletter 3:4:6-7.
Hildebrand, P.E. and D. Cardona
1977 Sistemas de Cultivos de Ladera para Pequenos y
Medianos Agricultores: La Barranca. Guatemala:
ICTA.
Perrin, R. K., D. L. Winkelmann, E. R. Moscardi and J. R.
Anderson
1976 From Agronomic Data to Farmer Recommendations:
An Economics Training Manual. Mexico: CIMMYT.
Reiche Caal, E.C., P. E. Hildebrand, S. R. Ruano and J. Wyld
1976 El Pequeno Agricultor y Sus Sistemas de Cultivos
en Ladera. Guatemala: ICTA.
Rogers, E.M.
1983 Diffusion of Innovations. New York, NY: Free
Press.
Ruano, S.R.
1977 El Uso del Sorgo para Consumo Humano: Caracter-
isticas y Limitaciones. Guatemala: ICTA.


7
Incorporating Women into
Monitoring and Evaluation in
Farming Systems Research and Extension

Jonice Louden

OVERVIEW OF FARMING SYSTEMS RESEARCH AND EXTENSION

During the past few decade;, a number of programs
designed and financed by national and international agen-
cies tried to improve the productivity of rural popula-
tions. Among the strategies adopted were the "Green Revo-
lution," extension, research and development, credit, irri-
gation, and soil conservation. While these innovations
have made technological advances, a number of limitations
have also been detected. The plant breeding breakthroughs
of the "Green Revolution" of the 1960s, that produced high-
yielding grain varieties favored more progressive farmers.
Most of this research concentrated largely on plantations
and export crops and provided little technical assistance
to the small farmer.
The strategy employed by extension services took
results generated on research stations to the farmer.
Implicit in this approach was the assumption that farmers
have inadequate knowledge about agriculture and must depend
on information from professional groups. Farmers often
rejected advice based on what they perceived as "book
learning" rather than practical experience about farming.
Due to the limited success of the extension approach, it
was imperative that new strategies be employed to improve
agricultural production and to correct the food deficit
situation now becoming acute in most developing countries.
The farming systems approach was introduced during the
1970s to work more effectively with the problem of
increased agricultural production through improved techno-
logy. Farming Systems Research and Extension (FSR/E) aims
at improving the effectiveness of national research and
extension services in generating and disseminating techno-
logies appropriate to farmers. A farming system may be
broadly defined as the way in which a farm family manages
the resources it controls to meet its objectives within a
particular ecological, social and economic setting.


wV






















Farmer Participation for More Effective Research
in Sustainable Agriculture

by

Walter W. Stroup', Peter E. Hildebrand2
and Charles A. Francis3


Staff Paper SP91-32


September, 1991


Staff papers are circulated without formal review by the Food and Resource Economics
Department. This paper, a chapter for the proposed American Society of Agronomy Special
Publication: "Technologies for Sustainable Agriculture in the Tropics", is being circulated for
review and comments. Contents are the sole responsibility of the authors.
123


1 Associate Professor, Department of Biometry, University of Nebraska-Lincoln

2 Professor, Food and Resource Economics Department, University of Florida

3 Professor, Department of Agronomy University of Nebraska-Lincoln


Senior authorship not assigned









ABSTRACT


Farmers have conducted their own research from before plants and animals were domesticated.
However, with the advent of scientifically based agriculture their influence on technology
development waned. Farming systems research-extension (FSRE) methodology was a response to
a concern that Green Revolution technology was bypassing many small, resource-poor farmers in
the Third World. Based on the FSRE-generated concepts of domains (research, recommendation
and diffusion), the unique nature of on-farm research, and its demands on statistical analysis are
examined. On-farm trials differ from on-station trials in two important ways: 1) the objectives are
usually different, and 2) the variablity of on-farm data is more complex and must be addressed with
greater sophistication. Four analysis of variance (ANOVA) models for on-farm research data are
examined and the relationship of ANOVA to modified stability analysis (MSA) is discussed. Means
of incorporating larger farms (both developed and developing countries) into an organized research
and extension effort are examined. Finally, the integration of large and small farms into a combined
research and extension effort is discussed.











FARMER PARTICIPATION FOR MORE EFFECTIVE RESEARCH
IN SUSTAINABLE AGRICULTURE


If developing countries are to meet national food needs and alleviate rural poverty,
millions of small farmers must become active participants in the agricultural
research and development process (Whyte and Boynton, 1983).


Most crops and many predominant agricultural production systems are the result of
empirical research, or trial and error, by generations of farmers working the land. Neolithic farmers
knew much about 1500 different plant species used for food and. medicine (Braidwood, 1967).
Vestiges of their traditional subsistence systems still exist in many regions (Francis, 1986b). With
the advent of scientifically based agriculture following World War II, however, farmers' influence on
technology development became less and less.

In the late 1960s and early 1970s, the international development community began to see
a need to reach the many small, resource-poor farmers who were being by-passed by the Green
Revolution. Whyte and Boynton (1983) argued that this meant 1) an increased emphasis upon on-
farm research, 2) greater interdisciplinary collaboration, 3) agricultural bureaucracies that are more
responsive to the interests and needs of small farmers, and 4) small farmers should no longer be
treated simply as passive recipients of what the experts decide is good for them.

To respond to this new clientele, a methodology was needed to efficiently find
environment-specific technologies for large numbers of such farmers. This methodology had to not
only reach farmers in widely varying and often difficult situations who lack the resources required
to dominate the environment, but also:

speed up the technology development, evaluation, delivery and adoption process,
and

efficiently use scarce institutional resources (those human, physical, and financial
resources of national agricultural research and extension services in developing
countries.

In order to accomplish these needs, the methodology required an integrated, multidisciplinary
approach that incorporated farmers, researchers and extension personnel.

Internationally, over the last 20 years, this "real world" or on-farm research for large
numbers of farmers has come to be called Farming Systems Research and Extension (FSRE). In the
broadest sense FSRE involves

rapid diagnosis of farm problems by multidisciplinary teams to provide the basis for

adaptive and descriptive biophysical on-farm research which is supported by

socioeconomic research on-farm and in the farm community,

S controlled biophysical research in laboratories and on-station, and

simultaneous dissemination and diffusion of results.

By incorporating farmers from the beginning of technology development from problem
diagnosis, through adaptation and evaluation FSRE methodology reduces the incidence of










research results that perform poorly on farms (Figure 1), or the rejection on-station of technologies
which might have performed well on farms but were never released (Figure 2).

As methods have developed over time, FSRE is not limited to small farms. Indeed, efficiency in the
use of research resources is enhanced by incorporating farmers from multiple environments. In this
chapter, methods for incorporating large numbers of limited resource farmers into on-farm research
are discussed. Later in the chapter, means of including larger, more commercial farms is covered.


CONCEPTS AND METHODS

Diagnosis

Using FSRE methods, farm problems are diagnosed by rapid rural appraisal procedures
(Chambers, 1981) or sondeos (Hildebrand, 1981), that incorporate farmers as active participants
working with multidisciplinary research and extension teams. These methods are flexible and may
or may not use formal questionnaires in the process. Problems encountered are elaborated and
prioritized for research by several methods including those proposed by Tripp and Woolley (1989)
from CIMMYT and CIAT.

Research domains

An earlier concept that sought homogeneous groups of farms (Hildebrand, 1981; Norman,
1980) has been modified to incorporate the concept of a research domain (Wotoweic, et al., 1988)
which recognizes the fact that farms and farmers are highly variable and targets this variability.
Often research domains are chosen based on biophysical characteristics although they may be
chosen politically. Research domains ideally contain a wide range of environments that are
incorporated as early as possible in the technology screening process. Environments in this context
can be associated with farms, fields or even portions of fields. The use of socioeconomic
considerations in the choice of environments within the research domain enhances efficiency in
technology development and evaluation.

To comprehend a research domain, compare the environment for producing tobacco in the
field on the small, resource-poor farm in north Florida shown in Photo 1 with the environment for
raising tobacco in the field on a larger farm, in the same area, but which has enough resources that
it can dominate the environment to a much greater extent, shown in Photo 2 and to the
environment for raising tobacco on an experiment station, also in the same area, where it is grown
with few limitations, allowing most environmental factors to be dominated, Photo 3.

All of these environments can be considered part of the same research domain and be
incorporated simultaneously into an integrated technology development, evaluation and diffusion
process for tobacco in north. Florida. The nature of on-farm research in research domains is
exploratory, to answer the questions WHAT and WHERE, not why and when. Diverse
environments, such as those shown in north Florida, enhance the exploratory nature of on-farm
research in research domains.

Recommendation domains

In a research domain, an integrated, multidisciplinary research and extension team conducts
both biophysical and socioeconomic on-farm research and analyzes the results to 1) characterize
the biophysical environments associated with each location, 2) elicit farmers' evaluation criteria
with respect to the technology being evaluated, and 3) define recommendation domains. A













recommendation domain is a unique combination of these environmental characteristics and
evaluation criteria.

Recommendation domains, then, are one or more subsets of a research domain which
target for homoaeneitv of 1) natural and farmer-created biophysical environments, and 2) farmers'
evaluation criteria for the technology being evaluated. Also modified from previous thinking that
recommendation domains pertained to whole farms (Byerlee, et al., 1982), or cropping or farming
systems (Hildebrand, 1981) are that these logically can refer as well to individual fields on a farm,
or even different locations in the same field. The most important concept is to consider
recommendation domains as environments whose biophysical and socioeconomic characteristics
can be identified.

The nature of on-farm research in recommendation domains is validation, to confirm
answers as to 1) how each alternative (treatment) will respond, and 2) where each alternative is
best, as well as to refine the characterization of the recommendation domains and farmer
evaluation criteria. At this stage, the number of treatments in on-farm trials is limited. Extension
personnel can play an increasingly important role by expanding coverage for evaluation and
enhancing exposure (diffusion) of the technology.

Diffusion domains

Diffusion domains are informal interpersonal communication networks through which newly
acquired knowledge of agricultural technology normally flows. Knowledge of these networks is
important in helping research and extension personnel Ic'ate on-farm trials to target for
communication.

The challenge of diagnosis and identification of these several domains is complicated by
how information is collected, analyzed, and evaluated from on-farm trials. We need to clearly
identify where research results can be applied, how broad the recommendations can be, and for
whom these new technologies are appropriate. To be credible for farmers as well as rigorous from
a statistical point of view, results from on-farm research must be analyzed and evaluated according
to valid statistical methods.


ANALYTIC VERSUS ENUMERATIVE STATISTICAL METHODS

Over the past several decades, procedures for the design and analysis of experiments have
been developed and utilized very effectively in agricultural research. Many of these procedures
have become so institutionalized that it is easy to lose sight of the fact.that they are only specific
applications of statistical theory to specific experimental conditions namely, those of the
agricultural experiment station.

Are the requirements of on-farm trials identical to those of experiment station trials? There
is no good reason to expect they should be. In fact, on-farm trials differ from their on-station
counterparts in two very significant ways: 1) the objectives are typically quite different; and 2) the
variability of the data in an on-farm trial is typically more complex and must be addressed with
greater sophistication than is normally required for an on-station trial.

How do the objectives of on-farm trials differ from on-station research? How does this in
turn affect decisions regarding appropriate statistical methodology? Although probably not obvious
to agricultural researchers, on-farm trials have many statistical similarities to quality improvement
experimentation in manufacturing.. Deming (1953, 1975), the statistician whose contributions to










quality in Japanese industry are legendary, distinguishes between two approaches to statistical
analysis: enumerative and analytic. From Deming (1975):

Enumerative. "The action to be taken on the frame depends purely on estimates or
complete counts of one or more specific populations of the frame. The aim of the statistical study
in an enumerative problem is descriptive." Virtually all classical statistical procedures t-tests, F-
tests, analysis of variance (ANOVA), standard confidence intervals are enumerative in nature.

Analytic. "In which action will be taken on the process or cause-system that produced the
frame studied, the aim being to improve the practice in the future." Only statistical procedures
which involve prediction rather than estimation or hypothesis testing are analytic in nature.

Deming (1975) puts it another way: "A 100 percent sample in an enumerative problem
provides the complete answer to the problem posed for an enumerative problem. In contrast, a
100 percent sample of a group of patients, or of a section of land, or of last week's product,
industrial or agricultural, is still inconclusive in an analytic problem. This point, though fundamental
in statistical information for business, has escaped many writers."

Clearly, most on-farm trials have analytic rather than enumerative objectives. Thus, the
literal application of enumerative statistical procedures, many of which form the core of statistical
tradition in agricultural research, is not appropriate for most on-farm trials. For example, the
analysis of variance (ANOVA) can be very useful for interpreting data from on-farm trials.
However, traditional ANOVA places much emphasis on hypothesis testing and significance levels.
These are important in enumerz. ve studies, but essentially irrelevant to analytic studies, where the
emphasis is on prediction and taking action.

Ad hoc statistical procedures are common in analytic studies. While many of these
procedures can be validly criticized using enumerative statistical arguments, these criticisms often
miss the point. Analytic studies are usually conducted with less prior knowledge of and control
over experimental conditions. The choice is frequently between no knowledge and useful, if
imperfect knowledge; conditions of optimality characteristic of enumerative statistical procedures
are simply not an option. Analytic studies typically sacrifice control over variability for a broadened
research domain. This does not make them incorrect or invalid, it just means that the researcher
must understand the trade-offs and choose statistical methods accordingly.

The complex variability in on-farm trials often troubles those trained in traditional statistical
methods for agricultural research. In statistical jargon, these methods are examples of "ordinary
least squares'; their main virtue is that they are easy relativelyy) to do without a computer, which
was a vital consideration in the 1920s and 1930s when they were developed. Their main
drawbacks are the rigid structure and narrow, frequently unrealistic assumptions required of the
data to permit legitimate interpretation. Since on-farm trials rarely satisfy these assumptions, many
have concluded falsely that they are somehow "statistically improper." In truth, traditional
methods simply cannot accommodate the complexity of on-farm trials.

'Ordinary least squares" theory has long since been supplanted by more versatile methods,
mixed linear model methods (or "mixed model methods" as they will be referred to here) being of
particular importance to on-farm trials. The virtue of mixed model methods is their flexibility; their
drawback is that they generally require a computer. Thus, while mixed model theory has been
around for nearly a half century, it did not become practical to use until the 1970s in developed
countries and the 1980s in most developing countries.. By then, more traditional methods were so
deeply entrenched in statistics courses, on experiment stations, and in agricultural research journals
that substantial re-education has either been required or, more correctly, is still required.














Recently, there has been a great deal of interest in applications of mixed model theory in
agriculture. Henderson (1975) developed best linear unbiased predictors (or BLUPs) as an
alternative to more enumerative-type estimators. Perceived at first as an ad hoc procedure, Harville
(1976) put BLUP on sound theoretical footing. A regional publication of the southern Research and
Information Exchange Group in statistics (Southern Regional Bulletin, 1989) contained several
examples of mixed model applications in agriculture. This publication also contained articles by
McLean (1989) and Stroup (1989a) describing mixed model theory and methods.

In the following section, mixed linear models appropriate for on-farm trials are discussed.
These models superficially resemble models used to evaluate on-station data. The goal of this
section is to show how to use mixed model theory to understand the distinction between the
various assumptions that can be made about these models, their effect on the resulting analysis,
and their implications for the on-farm researcher. The larger objective is to empower the on-farm
researcher with a relevant statistical perspective so that design and analysis choices appropriate to
on-farm trials can be made.


THE "TYPICAL" ON-FARM TRIAL

On-farm trials are conducted in a variety of ways, but most have a common basic structure.
The following is a generic description of the essential elements:

Suppose a number of treatments, V, are to be evaluated. Each treatment is observed at F
different farms where the specific biophysical and socioeconomic characteristics of the specific site
on the farm will be characterized.. At.each farm site, each treatment is "replicated" R times the
word "replicated" appears in quotes here because, as will become apparent later in this discussion,
multiple observations on treatments within a farm site may not be true replications. Note that the
term "farm", to be designated in what follows by the letter "F" is generic. The term more
specifically should be interpreted as "environment". In specific trials, "field', "location", "village",
etc. may apply equally.

Schematically, this trial can be represented as in Figure 1. As a starting point for analysis
of this trial, the following mathematical model can be used:

y, = y + f, + r(f), + v + vik + S*, (1)

where y, is the observation on the j replication of the i* farm for the k* treatment,
p is the overall mean,
f, is the effect of the i* farm,
r(f), is the effect of the j* replication in the i* farm,
v, is the effect of the k" treatment,
vf, is the interaction between the il farm and k' treatment, and
e, is residual variation not accounted for by the above effects.

The analysis of variance (ANOVA) implied by this model has the following general form:










SOURCE OF VARIATION degrees of freedom

FARM F F-1
REP(FARM) R(F) F(R-1)
TREATMENT V V-1
FARM X TREATMENT V x F (F-1)(V-1)
RESIDUAL resid F(R-1)(V-1)

TOTAL FRV 1

This ANOVA has several possible interpretations, depending on the specific objectives of a
given on-farm trial and how the effects in the model are defined as a consequence. In order to
make appropriate use of this ANOVA table, the researcher must be clear about the objectives of
the trial and the nature of the effects being observed. Some useful definitions follow.

Population of inference: The set of elements (e.g. farms) to which the results of the study
are to be applied. this is similar to the concept of a research domain.

Prediction space: Applications of study results from on-farm trials often take the form of
recommendations. Recommendations are based on the predicted behavior of the treatments, either
for the entire population or for various sub-populations. The set of elements (e.g. farms or
environments) to which a prediction is intended to be applicable is called the prediction space. This
is similar to the concept of a recommendation domain.

Random.and Fixed. Effects:..Effects inrthe-study treatments, farms, replicationss" can be
considered as fixed or random depending on 1) how they are chosen and 2) what prediction space
is appropriate to the objectives of the study. An effect is considered fixed if the levels of a
particular factor are chosen deliberately in advance of the study. In this case identical levels would
be used again were the study to be repeated based on the same prior knowledge, and prediction is
limited to only those levels actually represented in the study. Typically, treatments such as tillage
methods or fertilizer levels in a variety trial would be considered fixed effects. An effect is
considered random if the levels actually observed in the study result from a random sample of a
larger population identical levels in a repeat of the study would be exceedingly unlikely.
Prediction in this case is intended to apply to the population of which the levels observed are only -
representatives. The most blatant example of a random effect would be the effect of "replication"
or of residual variation. Many effects are not clearly fixed or random the effect of farm site or
environment, for example. Whether an effect is fixed or random has a major impact on the
analysis, as will be demonstrated below.

Most statistical methods texts, e.g. Steel and Torrie (1980) or Snedecor and Cochran
(1980), contain discussions of fixed and random effects. Many texts on the design or planning of
experiments discuss the population of inference, e.g. Cox (1958) or Mead (1988). The reader is
referred to these texts for more detail.

IMPACT OF FIXED OR RANDOM EFFECTS ON ANOVA

In the ANOVA for the on-farm trial given above, it is usually fairly clear that "treatments"
are fixed effects and replicationss" are random. Farms, however, are not so easily categorized.
Different farms may have been selected quite intentionally based on certain criteria: size, income,
technology level, soil type, climatic characteristics, etc. Or they may have been selected at
random from a target population. Actually, these are extremes; usually, farms are selected using a
combination of fixed and random effect tactics.- That is, a spectrum of-defined conditions must be













represented, but some form of random sampling is done within each condition. Essentially, this
amounts to stratified random sampling.

It follows that farms are not easily categorized as fixed or random. Usually, in fact, the
"correct" analysis of the on-farm trial will involve some compromise between the analysis with
farm as a fixed effect and the analysis with farms as random. Before examining this
"compromise," it is instructive to look at the appropriate analyses with farms strictly fixed or
strictly random.

If farms are fixed, then the only random components of model (1) are r(f)l, and eijk. Denote
the variance of r(f),, by o,2 and the variance of elk by a2. Then the expected values of the mean
squares of the ANOVA are as follows:

SOURCE OF VARIATION EXPECTED MEAN SQUARE .

F a2 + FVr,2 +RV0,
R(F) oa + FV,2
V o + FR0,,
VxF o2 + R0,
residual a2

where 0,, 0,, and 0, denote variation attributable to the fixed effects fi, vk, and vfik,
respectively.

If farms are random, then the components f, and-vfl from model (1) are also random.
Denote their variances by o,2 and o2, respectively. Then the expected mean squares are:

SOURCE OF VARIATION EXPECTED MEAN SQUARE

F 4a + Roa2+ Vo2, + RVo,2
R(F) oa + Vo
V a2 + Roa2 + FR,,
Vx F o + R',2
residual a2

These two ANOVA tables imply very different approaches to inference. When farms are
fixed, the data analyst's first concern must be the farm by treatment interaction (V x F), the
magnitude of which is assessed by the F-ratio MS(V x F)/MS(resid). If this F-ratio indicates the
existence of interaction, then effort must be focused on understanding its nature. Even if the
interaction F-ratio appears to be negligible, the data analyst would do well to partition MS(V x F)
into meaningful components, e.g. using contrasts, since important interactions often are masked by
the large number of degrees of freedom associated with the V x F effect (see Snedecor and
Cochran (1980), pp. 304-307).

When farms are considered fixed, the treatment main effect is of interest only if the
interaction effects are negligible, i.e. if it is clear that the same relationships among treatment
means appear to hold for every farm in the population of inference. This is generally not true, but
if it is then the treatment main effect can be evaluated using the F-ratio MS(V)/MS(resid).

When farms are considered random, then test of farm by treatment interaction, which uses
the same F-ratio as above, has a far different interpretation. Specifically, it means that differences
amongetreatments vary at random by farm. This is quite.distinct.from thefixed effect case, in










which interaction implies that relative differences among treatments are affected by systematic,
identifiable and repeatable farm characteristics (i.e. the characteristics that motivated the choice of
the farms in the first place). In fact, the test for interaction is not particularly interesting if farms
are random: if o, is not greater than zero, then the assumption of random farms is probably
defective. Of interest is the treatment main effect. This is evaluated using the F-ratio MS(V)/MS(V
x F). Its purpose is to verify that differences among treatment means, substantial and consistent
enough to be seen through the population of inference, over and above random differences among
treatment by farm, actually exist.

To summarize, if farms are fixed, the F-ratio of primary interest is that for the V x F
interaction, MS(V x F)/MS(resid), or, if the V x F interaction is negligible then the V main effect is
assessed by MS(V)/MS(resid). If farms are random, the V x F test is of little intrinsic interest
(except to verify the validity of the assumptions); of primary interest is the V main effect, which in
this case has an F-ratio MS(V)/MS(V x F).

In on-farms trials as they are actually conducted, farms are rarely purely fixed or purely
random effects. The above ANOVAs, therefore, are useful as academic exercises to illustrate
issues the farming systems researcher needs to understand, but neither, unmodified, is likely to be
of much use in practice.

PARTITIONING THE FARM BY TREATMENT INTERACTION

In most on-farm trials, the population of inference includes a set of "types of
environments," that the researcher wants to be represented. In the extreme fixed effects case, the
number of typeswould be F, and. thus only.one environment per type would be observed. In the
extreme random effects case, there-would be exactly one type of environment. (or so little would be
known about the environments that typing could not be done prior to conducting the trial) and F
randomly sampled environments per type. Usually on-farm researchers would reject either extreme;
a more realistic design would be to randomly sample a number of environments from each of the
several types of in the population.

If the types of "farms" are very well defined, model (1) could be modified as follows:

yi, = p + t + f(t), + r(tf),i + v, + vt, + vf(t),, + e,, (2)

where t, is the effect of farm type,
f(t), is the effect of farm within type,
vtv is the farm type by treatment interaction,
and other terms follow by extension from model (1).

In model (2) type and treatment would be considered fixed, farm and replication random,
and analysis would proceed accordingly based on the.following ANOVA:

SOURCE OF VARIATION f EXPECTED MEAN SQUARE

T T-1 o2 + Roa2+ Voa2 + RVoaf, + FRV0,
Fm T(F-1) o2 + Roa + Va,2 + RVo
R(TF) TF(R-1) oa + Vo,2
V V-1 e + Ro,2 + TFR9,
VxT (T-1)(V-1) oa + Ro, + FR,,
V x F(T) T(V-1)(F-1) o + Ro
residual TF(R-1)(V-1) o2













The type by treatment (V x T) interaction would be of initial primary interest. Its F-ratio is
MS[V x T]/MS[V x F(T)].

As before, partitioning MSIV x TI into meaningful contrasts would be strongly advisable.
For example, suppose the farm types are:

1. higher rainfall, mechanized
2. higher rainfall, non-mechanized
3. lower rainfall, mechanized
4. lower rainfall, non-mechanized

and the treatments are:

1. standard variety, no fertilizer
2. standard variety, with fertilizer
3. resistant variety, no fertilizer
4. resistant variety, with fertilizer

The type main effect could be partitioned into rainfall and mechanization main effects and a
rainfall by mechanization interaction. The treatment main effect could be partitioned into variety
and fertilizer main effects and a variety by fertilizer interaction. Then the interaction of any of the
three type effects with any of the three treatment effects could be evaluated. For example, a
rainfall by variety effect could be examined to see if the resistant variety is equally advantageous at
lower and higher rainfall. In the unusual case that type by treatment interactions are negligible, the
-treatment mainr.effect, could be tested using MS[V]/MS[V x F(T)].

Predicted performance of treatments for particular farm types can be obtained using
confidence intervals for the treatment x farm type means. Care should be taken to base the
confidence interval on the correct standard error. Most statistical software packages are poorly
suited to work with mixed linear models such as model (2) without special attention. For a
complete discussion of this issue, see McLean (1989) and Stroup (1989a). Predicted performance
of specific farms within a given farm type for a particular.treatment can be obtained by calculating
best linear unbiased predictors (Henderson, 1975). These are not the same as usual sample
means. Again, see McLean (1989) and Stroup (1989a and 1989b) for a full discussion of best
linear unbiased prediction.

STABILITY ANALYSIS

A special case of the above analysis occurs when "environmental types" and their potential
interactions with treatment are not well understood prior to conducting the on-farm trial. In such
cases, the researcher makes an attempt to represent as wide a spectrum of types as possible
within the'population of inference.but a "clean' partition of the variability among environments into
types and environments within types may not be possible. Indeed, one objective of the research
may be to provide insight concerning which environments favor or disfavor certain treatments and
what features are common to these environments. Various forms of "stability analysis" are
important examples of this approach.

Excellent review articles on stability analysis are available (see Freeman (1973), Hill (1975),
Westcott (1985)). Hildebrand (1984) has adapted the approach for on-farm trials and its use is
demonstrated in the following section. This discussion will be restricted to pointing out its relation
to model (2) above. In Hildebrand's modified stability analysis (MSA), an index for a given
environment (El) is defined as the mean response over all treatments at that farm site. A linear










regression over Els is obtained for each treatment and used as a basis for determining
"recommendation domains," a notion loosely similar (but not identical) to the mixed model concept
of prediction space. In terms of ANOVA, this could be expressed by modifying model (2):

Yiik = p + fi + r(f)i, + v + Bk(ElI) + vfk + eik (3)

where El, is the index of the i" environment, and
Bk is the linear regression coefficient for the k* treatment.

In essence, El in model (3) replaces type in model (2). Also, f, in model (3) is equivalent to
t, + f(t),, in model (2) and vfk in model (3) is equivalent to vf(t),ii in model (2). Since environment
(represented by "F") aside from El, is a random effect, the ANOVA is:

SOURCE OF VARIATION df EXPECTED MEAN SQUARE

F F-1 a2 + Ra,2 + Voaf + RVa,2
R(F) F(R-1) oa + Voa
V V-1 a2 + Ra,2 + FR0,
V x El V-1 a2 + Ro'2 + FR0e
VxF (V-1)(F-2) a2 + Rao
residual F(V-1)(R-1) a2

Equality of the Bk can be tested using MS[V x Ell/MSIV x Fl. A "significant" F-ratio would
imply that treatments respond unequally to El (and thus to whatever environmental types +he El
imply). This would in. turn provide formal justification for predicting that different treatments are
optimal for various "recommendation domains."

There is no reason why the use of environmental indices need be limited to linear
regression. For example, model (3) can easily be extended to

yw = + f, + r(f), + vk + Ik(EI,) + Bk(ElI)2 + vf + elik, (4)

where S,, is the linear regression coefficient for the kd1 treatment, and
Snk is the quadratic regression coefficient for the k" treatment.

The ANOVA for model (4) would be identical to the ANOVA for model (3) except that an
additional line for V x El2 (or V x El x El) with V-1 degrees of freedom would appear immediately
after V x El and the remaining V x F term would have (V-1)(F-3) degrees of freedom.

The F-ratio MSIV x E12]/MSIV x F1 tests the equality of quadratic regression over El for the
various treatments. Pictorially, this can be visualized as in Figure 4. Note that the quadratic
regressions are quite different for the treatments, although their linear components are similar.
Several authors have noted the limitations of linear-only regression over El, e.g. Westcott (1985).
However, model (4) should make it clear that this restriction is unnecessary. Indeed, model (4) can
be extended to more complex forms of regression over El.

If there is only one "replication" per farm (a discussion of the advantages and
disadvantages of this appears below) then the R(F) and residual terms in the ANOVA have no
degrees of freedom and the result is the following simplified form:













SOURCE OF VARIATION df EXPECTED MEAN SQUARE

F F-1 ao + Va,2
V V-1 o2 + Fo,
V x El V-1 o,'2 + Fog
V x E2 V-1 ao 2 + F0E,
V x F (now the residual) (V-1)(F-3) ao2

Note that this has no impact on the F-ratio used.

The use of El in stability analysis has been widely criticized because the independent
variable El is in fact a function of the dependent variable. Westcott (1985) makes a case for
greater use of independently determined "environmental variables.' He also notes that
"environmental measurements are very seldom available." Theoretical objections aside, the on-
farm researcher often has but two alternatives: using El or being unable to make useful
recommendations within a reasonable period of time. And, as McCullagh and Nelder (1989) point
out, "A first, though at first sight, not a very helpful principle, is that all models are wrong; some,
though, are more useful than others and we should seek those." Critics often point to the
weaknesses in formal statistical properties of analysis using El. These difficulties clearly exist;
however, a more compelling point is that the researcher often has the El as the ONLY objective
guide to environmental quality. These criticisms would be severe problems if formal, definitive
statistical inference were the objective. It is not. The more important use of this type of analysis
is to obtain preliminary insight regarding the consistency of treatment performance, which fields,
farms or groups of farms appear *o be troublesome, what recommendations appear to be
reasonable etc. This.sort of analysisis. always a starting point, never an end in itself.

For the researcher to make the jump from finding a significant El x treatment interaction
from a model such as (3) or (4) to associating El with predictable future environments or
"recommendation domains" and making reliable treatment recommendations for them obviously
requires a great deal of thought and care (and involves, to a large extent, non-statistical questions,
i.e. why are some El low and others high). Predicted treatment performance for farms included in
the trial can be made using well known best linear unbiased prediction methods. The Els have no
intrinsic meaning, so predictions for fields or farms not included in the trial are only as good as the
researcher's ability to predict which fields or farms will be in which recommendation domain. The
on-farm trial will not by itself generate data suitable for this purpose.

AN IMPORTANT NOTE ON DESIGNING ON-FARM TRIALS

Note that neither MS[R(FT)] nor MS[residl are ever used in the analysis of the "usual" on-
farm trial, i.e. one described by some variation on model (2). The appropriate denominator term for
all tests of interest is MS[V x F(T)1. Why is this important? Both MStR(FT)] and MS[residl require
that R, the number of replicationss" per farm, be at least two. However, neither of these terms
has any role in the analysis of the standard on-farm trial. What would happen if only one
replication per farm were observed? Neither. MS[R(FT)1 nor MS[residl could be calculated.
However, since neither term plays any role in the analysis, this is no real disadvantage.

It IS important to have as many farms per type as possible. This maximizes the degrees of
freedom for MS[V x F)]; since this is the denominator term for all F-ratios of interest, this will
maximize power and, consequently, the usable information available. Thus, it is the FARM that is
the true replication in an on-farm trial, not the "replication" within a farm (hence the motivation for
the quotation marksl). This is important because on-farm researchers often have been advised to
replicate within a farm, even for example in Hildebrand and Poey (1985)1 From an ANOVA










viewpoint, we now know this is clearly erroneous advice. Moreover, it is wasteful: the researcher
would be better off observing more farms. Even worse, it abuses the hospitality of the farmer
donating the space for the research to be conducted; the farmer should not have any more land out
of ordinary production than absolutely necessary.

To repeat, in most on-farm trials, the number of farms observed should be maximized.
Replication within a farm should not ordinarily be necessary and is usually wasteful. The only
exception is for the purely "farms as fixed effect" case of model (1), an unlikely, though not
unheard of, on-farm trial design.

MODIFIED STABILITY ANALYSIS

One method for managing research in such different environments as those shown above in
north Florida is with "stability analysis", modified to provide a positive rather than a negative
interpretation to treatment by environment interaction (Hildebrand 1990). Figure 3 shows
hypothetical results of three varieties (as an example of three alternative technologies) that have
been tested over an appropriately wide range of environments. In this hypothetical case, all three
have the same overall mean yield and deviations from regression, s2d, = 0. The linear regression
coefficients are 1.5, 1.0 and 0.5 for varieties A, B and C, respectively. In the absence of other
disqualifying characteristics, variety B (the most generally adaptable according to Finlay and
Wilkinson (1963), or the most stable according to Eberhart and Russell (1966)) would be selected
based on the value of the regression coefficient. The argument against variety A is that because it
has a coefficient much higher than unity, it is too sensitive to environmental change and does
poorly in pnor environments. Variety C, because it has a coefficient much lower than unity, is
unable to.exploit.high-yielding environments-Therefree.variety. B, which is not superior in any
environment, is chosen as the best of the three.

Notice that the argument against variety A with a high coefficient, moves from right to left
or toward low environments (it does poorly in poor environments). The opposite is true of the
argument against variety C with a low coefficient, which moves from left to right or toward high
environments (it is unable to exploit good environments). These are negative interpretations which
lead to the selection of variety B, Figure 5.'

If the emphasis regarding varieties with a high regression coefficient were toward, rather
than away from the best environments (which variety can exploit the better environments?), variety
A would be selected. Likewise, if for varieties with a low coefficient, emphasis were toward
(rather than away from) the poorer environments (which variety can maintain yield even in poorer
environments?), variety C would be selected, Figure 6. The difference is not one of analytical
procedure, but of a positive rather than a negative philosophy, goal and/or attitude toward
technology selection.

The result of using this approach with modified stability analysis (Hildebrand, 1984) is to
describe recommendation domains within.which specific technologies excel (recommend variety A
for the better environments and variety C for the poorer environments, in the above example,
rather than variety B for all environments).

Numbers of locations (environments)

Following models (3) and (4), the number of environments required for estimation of
treatment by environment response in research domains and verification in recommendation
domains is not excessive. In order to have at least 20 degrees of freedom in the error term, and
allowing for estimation of both linear and quadratic responses as in. model (4), if 8 treatments are













included in the trial, such as might be used in an exploratory trial in a research domain, 6
environments is an adequate number. For 4 treatments, 10 environments would be required, and
in a verification trial with only two treatments (the recommended treatment and the farmer check,
for example) 23 environments is adequate. These suggestions, of course, are approximate. The
appropriate number of environments is a function of the variance and the required sensitivity all
case-by-case situations.

Numbers of years

Experience has indicated that if three conditions are met, the estimates of environment by
treatment response stabilize in one year. These conditions are:

1. The range of environmental indices (El) should be at least as great as the mean of the
indices.

2. The range of environmental indices should approximate what would normally be
expected over a period of years.

3. The distribution of environments should be reasonably uniform from good to poor.

However, it should be remembered that at least two years of data will be available for
estimates if both an exploratory trial (in a research domain) and a validation trial (in a
recommendation domain) are carried out prior to making firm recommendations. Also, preliminary
data often are available from on-station trials, conducted over previous years, as the technology is
being developed..Thetreatments.that.are common from among these current and previous trials
can be combined in a single MSA. The data from previous years can also help to verify whether
the range of environments included in a current trial is adequate.


RECENT EXAMPLE

Singh (1990) reports on recent research conducted near Manaus, Brazil, that illustrates
many of these concepts. The on-farm portion of his research was conducted in two small farming
communities in the municipality of Rio Preto da Eva, Amazonas, Brazil, where the government was
initiating a small watershed management program. The Brazilian national agricultural research
institution (EMBRAPA) has a mandate to develop appropriate technology for different farming
conditions in this relatively inaccessible area. Also collaborating in the research were EMATER
(extension) and SEPA, the state development planning entity, TROPSOILS, and the University of
Florida.

Secondary information regarding indigenous farming practices of the area.were collected
from published sources. A-rapid appraisal of the area' was conducted with a multidisciplinary team
of persons from EMBRAPA, SEPA and EMATER who visited the area on three different occasions.
Farmers' knowledge of indigenous technology, agronomic practices, and land types being used
were recorded. An extensive soil sampling program was carried out to understand soil physical and
chemical characteristics and relate them to farmers' rationale for assigning a particular cropping
pattern to a given land type.

Three treatments, based on previous on-station research, were selected for comparison
with farmers' practices (FP) for growing maize (Zea mayS L) and cowpea (Viona unguiculata).
Only results from the cowpea are reported here. All three treatments with amendments received K
(60 kg ha'- broadcast. Processed city waste (PCW), chicken manure (CM)-and triple super









phosphate (TSP) were applied in 25 cm bands. The cowpea variety IPEAN V-69 was planted in
rows 60 cm apart. Plot size varied from 100-200 square meters. Land preparation and planting
methods consisted of clearing the area by slash and burn, followed by manual land preparation and
planting with sticks.

The project area is inhabited by subsistence farmers who clear land from primary forest (PF)
or secondary forest (SF) and farm it up to three years before abandoning it as waste land (WL).
Cowpea trials were established on 13 locations. Eight were replicated and five were not. Yield
results, averaged across replications where appropriate, and the environmental index for each
location are shown in Table 1. Analysis of variance using the model (4) with R = 1 is shown in
Table 2.

For the criterion Mg ha'', the response of the four treatments to environment, using
modified stability analysis, is shown in Figure 7. It is clear that amendments are needed to
maximize per ha yield from these soils. In the poorer environments (El< 1.32) CM produces the
best results, and in the better environments (El> 1.32) TSP is best.

The biophysical characteristics of the better and poorer environments closely follows the
nature of the land being used. That is, the better environments (El> 1.32) are all land taken from
PF and in first or second year of use and SF in first year of use. All other categories (PF3, SF,, SF3,
WL) are in the poorer environments. For farmers whose evaluation criterion is to maximize Mg ha"',
the research domain can be divided into two recommendation domains. For farmers with PF, and
PF,, the recommendation is to use TSP. Farmers in all other cases should use CM.

Figures 8.and: 9-show.the. MSA resultsifor thealternate evaluation criterion of kg per dollar
of cash cost (kg/$CC), a criterion usually of great-importance to farmers in this area who have little
cash to spend for agricultural inputs. Figure 8 shows that for the better environments (here
El> 1.25, but covering the same soil situations) FP is by far the best practice of those tested. In
the first or second year out of primary forest, none of the other tested treatments would be
acceptable to farmers for whom cash is very scarce and therefore need to maximize kg/$CC. For
any other soil situation, however, either TSP or CM could be recommended even if the farmers had
to use scarce cash to purchase the amendments.

The use of Figure 9 narrows the choice somewhat in the poorer environments. CM
produces very stable results compared to TSP which could result in fewer kg/$CC than FP. This
leads to the recommendation of CM as the best choice of those treatments tested in cases where
farmers use, or are forced by circumstances to use fields more than one year out of secondary
forest or two years out of primary forest.


FOCUS ON INDIVIDUAL FARMERS. FARMS. AND FIELDS IN COMMERCIAL AGRICULTURE

Farmers, themselves, continually fine-tune their systems to the specific resource-and
infrastructure conditions in which the farm and family are found. In addition to the crop varieties
mentioned earlier, a number of innovations in farm equipment originated with producers. Perhaps
the agricultural machinery industry has been the sector most active in capturing the experience of
farmers and putting this into commercial practices. Many of the current tillage, planting, and
harvesting units have reached their present form through farmer modification of what was on the
market, and then tested and adopted by industry for the next generation of commercial units. The
ridge tillage planters and cultivators are currently going through this phase of farmer modification.
A number of cropping system innovations likewise originated with farmers. Annual windbreaks
have been proven useful.to reduce transpiration in crops between thewindbreaks, and perennial













windbreaks used to break the wind and trap moisture as snow in the Northern Great Plains.
Alternating strips of different species, such as maize and soybean, have been used by a number of
farmers in the Western Corn Belt. Although there is a growing body of technical research on
experiment stations to validate and quantify the effects of these practices, many of them in fact
originated with farmers in the region. What has been difficult is the rationalization of different
methods used by farmers to test their systems, and those used by scientists trained in a different
research paradigm.

In many respects, on-farm research has a great deal in common with industrial statistical
process control. In manufacturing, products are designed in the lab, then prototypes are produced
and evaluated under "real world conditions." During the latter phase, problems are identified when
typical workers, rather than research engineers, attempt to produce the product and when
prospective consumers attempt to use the product. Invariably, they find ways to "break" the
product that would never occur to lab workers. So it is with agricultural research. The experiment
station or greenhouse can be thought of as the agronomic lab. The function of on-farm trials is
identical in agriculture to "real world" testing in manufacturing. Real farmers will surface problems
not encountered by experiment station workers; the research process is not complete until this is
done.



DESIGNS FOR RESEARCH ON COMMERCIAL FARMS

In a recent symposium of the American Society of Agronomy in San Antonio, there were
many presentations about.howwresearch is being.conducted on,farms.. The examples appeared to
fall into one of two categories. First was the replicated trial with relatively small plots in which the
university researcher developed an agenda, designed treatments and plots in the field, collected
most of the data and interpreted the results. The farmer was a participant in providing land and
some cultural operations during the season, but was not an active part of the planning or the
evaluation process. This role for the farmer meets most of the reasons for locating plots on farms
as listed by Lockeretz (1987).

In contrast, a second approach was essentially an extension of the farming systems
Sresearch/extension philosophy and method (Hildebrand and Poey, 1985), where farmers were
primary participants in the setting of a research agenda, search for relevant treatments, layout and
implementation of the trial, and interpretation and use of results. The latter approach provides an
environment in which the methodologies given by Taylor (1990) for on-farm research can be
implemented: use of multidisciplinary research teams (including the farmer), whole-farm analysis of
results where appropriate, design of long-term plots and treatments, and synthetic as well as
analytical approaches to use of data. In the United States, the former approach has been favored
by researchers from land grant universities, while the-latter has been part of the agenda.of farmer
groups and other non-profit organizations. The proponents of each approach find it difficult to
communicate at times with others who do not share their definitions of what constitutes research,
since each group has a relatively clear mind set of what is meant by "on-farm research", while in
fact these definitions are quite divergent.

When a university trained scientist uses the term "research", there is an assumption of an
explicit and testable hypothesis, replicated treatments in a randomized pattern in a standard design,
homogeneity of variances among treatments, control of experimental conditions, and relative
uniformity of the experimental area or some blocking pattern to handle variation in the field.
These are the normal assumptions connected with the analysis of variance, and although they are
not always strictly, adhered to we.often: make. the assumption that they are being met. Saying that










"standard statistical procedures were followed" implies all of the above even if the researcher (or
farmer) did not really understand the statistical thinking very well.

Many of these criteria are not recognized nor understood by most farmers. They prefer
trials that are fairly close to the home farm or under similar conditions or both, that have plots large
enough to use commercial equipment, that show visible differences among treatments, that can
reduce costs or increase profits, or that solve a constraint that was already perceived on their farm
or in the area (Francis, 1986a). In the real world we encounter comparisons from one year to the
next, from one field to another, from one farm to a neighbor's, or among strips in a field that have
different treatments (eg. varieties or hybrids) with no replication. Although these comparisons do
not meet the criteria recognized by the scientist to qualify as credible or valid research, the results
are no less meaningful to many farmers. We do find that careful explanation in an extension
meeting of some of the criteria used by researchers, for example replication and randomization of
treatments, leads to a fairly quick understanding of the need for these methods and the importance
for repeatability of the experience.

Are these two definitions of "research" mutually exclusive, or is there some middle ground
where farmer creativity, land, and resources can be utilized for credible on-farm research? Over the
past several years, there has been substantial work on large plots with few treatments, replication
and randomization, and standard statistical analysis. Long strip designs used to compare two or
three treatments were described by Thompson (1990), and are currently being used by a number of
the members of the Practical Farmers of Iowa, among other groups. Rzewnicki et al. (1988)
summarized these trials from Iowa as well as some from farms and from experiment stations in
Nebraska. With plots that ranged from 200 to 1200 feet long by four to eight rows wide and three
to six replications, per treatment they.foundicoefficients of variation from less-than 1.0 to about 10
percent; the CVs-were frequently less than five percent. Practical researchers who are familiar
with the variation in most field experiments find these levels very acceptable.

How is it possible that such large plots have low CVs? Although we are only now testing
these hypotheses by comparing large and small plots from the same field (Shapiro et al., 1989,
1990), it appears that a long and narrow plot goes across a range of variability in the field. A plot
located adjacent with the same dimensions crosses the same gradient, and at any one point there
is relatively less difference between the strips than there is across the gradient in each long plot.
Thus the potential exists for planting contrasting treatments side by side, allowing use of full sized
commercial equipment and having a highly visible comparison, while still meeting the requirements
of replication and randomization. This would appear to be one option for an individual farmer to
collect credible data for one site in one year. and use standard statistical techniques such as
analysis of variance, t-test, or paired comparisons to evaluate the trials. In one set of comparisons,
the Clay County Corn Growers in Nebraska planted maize hybrids in unreplicated strip plots in four
areas in the county, with similar conditions and the same hybrids in each test. Analyzed with
farms as replications, there were CVs from three-to four percent over the five years of the tests
(Rzewnicki et al., 1988). This opens the possibilities for individuals or groups of farmers to work in
a cooperative research network and to develop-a credible set of comparisons for.use by them and.
by others. Each farmer becomes a part of the research and extension network, since these plots
are used for field tours and the data for extension meetings before the next planting season.

Results from these large replicated or unreplicated trials in Nebraska represent one approach
that can be taken by farmers in a highly mechanized, large farm situation. It is a challenge to the
practical researcher or applied extension person to explain the basic characteristics of the trials,
and to- work directly with farmers in developing the research agenda.
















INTERPRETATION AND EXTRAPOLATION OF RESULTS

The zone across which such results can be applied depends on how many sites were used
for the trials, the soil and climatic characteristics of the sites, whether similar results could be
expected from other sites in the region, and how credible or repeatable the results are from the
experiments. Several dimensions of this question have been discussed above. In statistical terms,
the potential for application of results across a range of environments depends on the significance
of the specific technology by environment.interaction. An example is the testing of hybrids across
locations, and measuring the genotype by location interaction. When this is low, it is relatively
easy to recommend one or a few hybrids across a wide area; when the interaction is large, there is
a high degree of site specificity and need for unique choices for different locations.

It is important to consider the effects of replications, years, and locations in contributing to.
the value of results. Increasing number of locations and environments had little effect beyond
about eight on the magnitude of the standard error of a genotype mean (Saeed et al., 1984).
Increasing number of years from one to two substantially reduced the standard error of the mean,
while adding an additional year had minimal effect. Likewise, increasing number of replications has
little effect on the standard error. The influence of additional locations or environments is much
greater than either adding years or replications to an experiment in order to reduce the variance of
a mean, thus increasing the potential for detecting statistical differences among treatments in the
experiment. Although it is less expensive to add replications in a single location, this is relatively
ineffective in increasing the potential to detect differences. This is consistent with the above
discussion on need for a large number of locations or environments for testing, and the relatively
smaller need for replication in one site. The concept of single replications and a large number of
locations is-a cornerstone. of. current commerciathybrid. testing, strategies (Bradley et al., 1 9b8).
The efficiency of this procedure-inma testing- program has recently been described (Dofing and
Francis, 1990). Replication at one site does improve the precision of measurement at that site in
that year. But with multilocational (multiple environment) on-farm testing, the relevant variance is
that among locations or environments. Therefore, multiple replications at one location contribute
little to the potential extrapolation from that. site to others, or to other years.

The challenge for the individual farmer is to decide what information really applies to his or
her site, given the abundance of results from trials that are available from industry, university, or
private sources. The better a farmer is able to characterize the farm and the individual fields, and
the better the description of the conditions under which data were collected in other sites, the
easier it will be to decide which data or recommendations are relevant. This is a practical way of
defining recommendation domains, a topic already explored. The best place to look for relevant
data is within the same recommendation domain as that where the field is located. It should be
apparent that these domains are not defined only by geographical location, by soil type, or by any
single factor. Likewise, it is possible that a single farm may encompass several domains. It is
important to understand the concept, and to use this information to best access the most
appropriate data. before making production technology decisions.


PARTICIPATORY MODEL FOR RESEARCH AND EXTENSION

On-farm research trials and demonstrations for extension purposes have long been a staple
component of comprehensive investigation and development programs in agriculture. Some of the
reasons have been described above. There are even more compelling reasons today why research
with individual farmers and groups of producers makes sense (Francis et al., 1990). There are
limited research and extension budgets, with an increasing focus of federal funds in the U.S. on
basic work at the expense of applied research. This is a trend that is being followed by national














research programs around the world, as scientists become better prepared for basic investigations
and the glamour of genetic engineering and high technology solutions pervades the scientific
community. In contrast to the range of ecological situations where farmers produce crops, the
research establishments have relatively few experiment stations. Much of the research performed
on these stations is reductionist in nature, with limited regard for the incorporation of new
innovations into the total farming system. For these reasons, there is comparative advantage to
conducting at least some of the research in a wider array of sites with collaborating farmers.

Another compelling reason for working directly with individual farmers and groups relates-to
distance from the controlled research site to the farm where results will be applied. This "distance"
may take several forms (Francis et al., 1990). Geographic space in miles or kilometers from one
site to another is the most commonly used measure of distance. Farmers are willing to travel
certain distances to visit other sites, depending on culture and infrastructure (Rzewnicki, 1991).
More important, perhaps, is the "ecological distance" from one site to another. For example, a low
lying area with poor drainage and heavy soils may be a very short physical distance from a well
drained, lighter soil on a hillside, yet the soil conditions, appropriate cultural practices, and crops or
varieties that are appropriate may be quite distinct. Finally, there may be "conceptual" or
"psychological distances" between researcher and farmer, based on differences in education or
experience, and these need to be bridged in order to effect a working partnership and a fully
participatory system of research and extension. On- farm activities among people who have
mutual respect for each others' talents and potentials to contribute can help to overcome these
social distances.

The potentials of a participatory network of farmers and rese"-chers can perhaps best be
illustrated through use of an example, Th&eunique contributions of the farmer in the total research
process is highlighted. -A number of additional examples, especially in farmer contributions to ideas
for weed management, were recently summarized by Francis and Doll (1991).

Maize yield response to nitrogen in croo rotations. In order to study the effect of nitrogen
applications on maize yields in continuous maize and sorghum compared to rotation of these
cereals in Nebraska, a network of about thirty farmers was established to work with a project of
the University of Nebraska. There has been great concern about the energy costs of this input in
maize production, as well as potential for nitrate contamination of ground water supplies that are
frequently used for human and animal consumption. Supported in part through a grant from the
Nebraska Energy Office, a university technician established contact with a number of farmers,
many of whom were members of the Nebraska Sustainable Agriculture Society. All were interested
in more efficient use of nitrogen, and in finding ways to quantify the effects of a cereal-legume
rotation on response to this important nutrient.

In cooperation with farmers, fields and experimental sites were chosen, soil samples were
taken, and lab test results discussed. Together the team determined realistic yield goals and
developed nitrogen budgets considering all sources of this major nutrient. Each farmer thus derived
a conservative but optimum level of nitrogen for the. coming season. In most fields this N rate and
a one-half rate were included, and in some fields a zero rate as well. On many fields these
treatments were applied in replicated strips across the entire field. For the years 1988, 1989, and
1990 there was a predicted yield response to rates of 80 to 150 pounds N/acre, although the
actual economic optima were lower in most fields (Franzluebbers, 1991). Following soybean,
sweet clover, or alfalfa there was no economic response to applied nitrogen by either maiza or
sorghum under rainfed conditions. In irrigated fields, there was no economic response of maize
yields to nitrogen if the maize followed alfalfa. The conclusions from this three-year project, as
interpreted by farmers and project personnel, was that nitrogen generally is over applied under
many conditions in Nebraska.













Statistical analysis followed the standard procedures described above in model (1). Where
replicated treatments were present, the analysis and comparison were conducted on each farm. In
a number of cases there was a single replication per farm, and these results were pooled with the
replicated sites using a single mean per treatment per location, and locations used as replications.
Regression analysis was used to compare the response of cereal yields to applied nitrogen in
rotation compared to continuous culture. Grain yield response in maize and sorghum to applied
nitrogen was measured at 29 sites with continuous cropping and at .57 sites in rotation with
legumes and small grains. Continuous maize responded to nitrogen up to about 80 kg N/ha, the
maximum level' in the trials. Maize and sorghum following small. grains or legumes showed only a.
modest response in some cases, not statistically significant, and not economically sound because
the cost of nitrogen plus application was not offset by the increase in yield. This type of analysis
is useful for grouping results of like treatments across sites.

To reach more farmers with this information, eight meetings were scheduled jointly by the
Sustainable Agriculture Society and Nebraska-Extension in early 1990. The objectives of the trials
and methods were described, tables or figures presented, and the meeting turned over to farmers
to interpret the data and derive results. A lively discussion ensued about results from the trials and
how to apply them to specific fields. The university staff present were valuable as resource
people, helping to explain why or why not crops were responding in specific situations. But the
farmers were deriving their own recommendations, and the extension specialists were able to
empower the producers to make these decisions. During the next summer of 1990, many of the
trial fields were used for field tours and discussions on site. Farmers were in charge of describing
what happened. These are both examples of participatory extension practices.


Should the farmer put more confidence- in results.from his or her own field trial, or from the
aggregate analysis across sites? It is usually appealing to have one's own data from a field on the
farm, where the cultural practices are known and the results appear to uniquely fit that farm.
Whether these are. the best data to use to predict next year's results depends on the similarity of
cultural practices, hybrids, and soil conditions across the range of sites, and how likely those sites
represent the potential range of possible rainfall events that may occur over a number of years.
Since rainfall is the most limiting factor in most Nebraska sites each year in rainfed crop culture, it
is possible that the mean performance over several similar sites will be a better predictor of next
year's situation than the results from the single farm. We are seeking data and a method to
analyze this situation. The decision by an individual farmer at the moment is a judgement call, and
the best that we can do is to provide tools to help improve that judgement.


RESEARCH-EXTENSION AGENDA: LARGE AND SMALL FARMERS

The approach and examples presented in this chapter illustrate the potential of an emerging
paradigm, or shift in patterns of research and extension activities. This applies to both large and
small farmers. Efficient research of the type being discussed here depends on recognition and full
representation of the research domain or inference space. Scientists need to recognize that on-
station trials are useful for research and development, but limited for surfacing knowledge about
production realities. Both large and small farmers need to recognize that they represent these
realities, and in a major way can contribute to their identification and solution.

Once the inference space is well understood, it is possible to follow with carefully designed
activities to solve the problems associated with the primary constraints to sustainable production
using resources and information from both large and small farms. Data gathered in-situ is critical,
and on-farm trials- that include the widest possible variety of farms are essential. Failure to include











this range of environments can result in compromised research (bad for the scientist) that may
produce flawed information and incorrect production decisions (bad for farmers). The need for
many environments and a wide range of participants should be clear.

Large-scale farmers often have the resources to contribute to the research process, and can
easily grasp the relevance of self-generated information to their own operations. Using the
principles described above, their efforts can be more productive if combined across locations, and
at times combined with data from small-scale farm trials. A wide coalition of farmers, researchers,.
and extension specialists can, bring together the resources needed to broaden the range of
environments over which results can be collected. If large farmers are incorporated into a
technology evaluation network with small farmers, the length of time required for testing can be
reduced because environments (locations) can substitute substantially for years. This can lead to
greater efficiency in use of scarce resources, both from farmers and the government. It may well
be possible for many of the larger farmers, in conjunction with the national research and extension
organizations, to pick up costs associated with on-farm research that will benefit them, and at the
same time enhance the development of technology for all farmers.

The role of the research and extension specialists in this system needs to be clearly
recognized. The upgrading of farmer participation and input into the research process does not
devalue the scientists' role, but rather expands their capacity to recognize and work with real world
problems that limit production and the range of solutions that may be available to solve them. The
role of research specialists can, in fact, become more focused on describing the "why" behind
questions in agriculture, ecology, biology and sustainability. The role of extension specialists can
be to catalyze the exchange of information among a number of credible and relevant sources. The
research process. can.be a rigorousstatistical.exercise, and.it is possible to determine where results
can be applied in the appropriate recommendation domains.

Assumptions about roles of different players, cooperation among farmers and scientists,
relevance of information from various sources, and ultimate objectives of the systems need to be
recast. This is the paradigm shift described above. Many agricultural infrastructures are set up
with good intentions, but fail to produce anticipated results due to inadequate communication,
limited scientific literacy among specialists and farmers, and a strained relationship between those
who develop theoretical knowledge and those who focus on practical application. This is a
problem in both developing and developed countries. The farming systems paradigm, and
especially the on-farm research approaches described here can offer enormous potential that will
benefit national agricultural infrastructure as well as sustainable agricultural production systems.


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21

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Table 1.


Cowpea yield (Mg/ha) across environments,
Rio Preto da Eva, Amazonas, Brazil, 1989


LOCATION FP PCW TSP CM El

8 0.10 0.20 1.30 1.65 0.81
13 0.00 0.00 1.30 2.00 0.82
6 0.15 0.50 1.35 1.35 0.84
9 0.20 0.40 1.20 1.70 0.88
2 0.50 0.65 1.10 1.50 0.94
5 0.15 0.50 2.10 2.05 1.20
4 0.60 1.20 1.60 2.25 1.41
1 0.70 0.90 2.30 1.80 1.42
11 1.20 1.50 2.20 1.90 1.70
12 1.50 1.80 2.10 1.70 1.78
3 1.45 1.95 2.50 1.90 1.95
10 2.20 1.90 2.60 1. .0 2.02
7 1.70 1.65 2.65 2.15 2.04


Source: Singh (1990).








25

Table 2. ANOVA, Cowpea response to environment,
Manaus, 1990


SOURCE OF VARIATION df MEAN SQUARE Pr > F

Location 12 0.9470 0.0001
Treatment 3 3.8127 0.0001
Env*Trt 3 0.9923 0.0001
Env*Env*TrT 3 0.1266 0.1840
Residual 30 0.0736






















REJECTED, NO
FURTHER TESTING


PERFORM POORLY
ON FARMS


Figure 1. Possible results of on-station testing.


EVALUATION























Law;rj~'~ui~ mu~u*-~~Fs~-;II;


MAY HAVE P
WELL ON


REJECT
FURTHER






PERFORMED
FARMS I


Figure 2. Possible results of on-station testing.


S CTED FOR
IER TESTING


ED, NO
TESTING


SELE
FOURTH


---IYl.;~ac.--~Z .---=~YPU9--~.-~~II-C~*-L~Y--i~-T~.~






















FARM 1


FARM F


Figure 3. Representation of a typical on-farm trial.












23

22

21

20

19

18

17

16

15

14

13

12

11

10


1 2 3 4 5 6 7


Figure 4. Illustration of treatment by environment interaction.
















6
A


5 B


4. C



S 3










0
1/

0 I I I I

0 1 2 3 4 5 6

ENVIRONMENTAL INDEX, El


Figure 5. Hypothetical results of variety testing over range of environments.













6
A

5 B



4 C




01

2





10


0 1 2 3 4 5 6

ENVIRONMENTAL INDEX, El



Figure 6. Negative interpretation of the response of varieties to environment resulting in choice
of variety B for "broad adaptation".







































0 1 2 3 4 5

ENVIRONMENTAL INDEX, El



Figure 7. Positive interpretation of the response of varieties to environment resulting in a choice
of variety A for the better environments and of variety C for the poorer environments.
























1


0.5


0 i
0.8


1 1.2 1.4 1.6 1.8 2

ENVIRONMENTAL INDEX, El


WL SF, SF, PF, SF, PF2 PF

LAND CLASSES

Figure 8. Cowpea response (MG/HA) of four treatments to environment,
Manaus, Brazil 1990 (Singh)



























30'1-


FP.



TSP



S........... .. .... CM




,,....----- ---"" Pcw


1 1.2


1.8


2 2.2


ENVIRONMENTAL INDEX, El


WL SF3 SF, PF3 SF PF PF,

LAND CLASSES



Figure 9. Cowpea response (KG/SCC) of four treatments to environment
Manaus, Brazil, 1990 (Singh)














50

: 1I -


60 a I I





Uz
S / / I
I 80


C, I
8I''

90 / I
I *4
ZI


90
TSP I\

100 I '
-10 -5 0 5 10 15 21

Kg/$CC


Figure 10. Stability of three treatments in cowpea for poor environments
Manaus, Brazil, 1990 (Singh)



























Photo 1




























Po 2-
PhotoPhoto 1





^ ^c fc ^ ^ ^ ^ ^^ ^ ^ ^ ^ '5 ^ '^*'y? K ^ SY






3


Photo 3


rs~t












r._
r-r~-~--~-~ ~- .-
r-































THE FOLLOWING SELECTION
HAS BEEN PRINTED
WITH PERMISSION

DATE: 07/01/92


Author: CB. FLOR--EDITOR

Title: 1 ARTICLE

Journal: NO. 9/ FARMING SYSTEMS RESEARCH PAPER

Volume: No: Pgs: Copyright Year: 1986

Reprinted by Permission of: Kansas State Univ.-Library


THIS MATERIAL MAY NOT BE
REPRODUCED IN ANY MANNER
WITHOUT THE PERMISSION
OF THE COPYRIGHT HOLDER









Proceedings of the Kansas State University 1985 Farming Systems Research Symposium.
No. 8 (in press)


USING MALE RESEARCH AND EXTENSION PERSONNEL TO TARGET WOMEN FARMERS


Anita Spring
University of Florida



A group of people en route to the FSR Conference met a
child with a wagon load of puppies. One of them asked
where the child was taking the puppies and the child
answered that the puppies were going to be given to the
commodity researchers (this was a sophisticated child).
The next day, after the conference had started, the
participants were en route to lunch and they came across
the same child again. One of the participants introduced
the child to some people who hadn't been there the day
before and asked the same question about the fate of the
puppies. This time the child said the puppies were
being taken to the farming systems researchers. The
participants pointed out that only yesterday the child
said the puppies were going to commodity researchers.
"But," the child replied, "yesterday, the puppies didn't
have their eyes open."


INTRODUCTION

To many FSR proponents, commodity-oriented scientists do not focus on the
whole farming system and therefore do not have their eyes open. They cannot
appreciate the complexities of small farm management and smallholder needs and
problems. This is analagous to the way those involved in farming systems
research and extension (FSR/E) feel about the lack of appreciation and
consideration of gender issues and intrahousehold dynamics amongst FSR&E
practitioners. Those who ignore these issues do not have their eyes open.
Farming systems researchers did not invent the fact that farmers have to deal
with a multitude of environmental, familial, infrastructural, and other
factors, so that a focus on a single commodity might not remedy the problems
of the farming system. So too, researchers who consider women's role in
agriculture did not invent the sexual division of labor, the semiautonomous
nature of different family members, the differential access to land, labor,
and capital, or the fact that women are becoming more involved in the
smallholder sector in some developing countries because of extensive male
migration (Chaney and Lewis, 1980; Gladwin et al.; Dixon, 1982).

Evidence is accumulating that technology transfer is frequently hindered when
intrahousehold dynamics are not taken into account (see for example Rogers,
1979; McKee, 1984). Often, technologies are ill-suited or only partially
adopted because the resource base in terms of personnel, capital, land, and
equipment is inappropriate or inadequately understood. A consideration of
intrahousehold labor allocations and decision-making shows that in many places
female family members will have to provide the labor and will either make or
be involved in the decision as to whether or not to adopt the technology. In
addition, labor, access to resources, and remuneration are not consolidated in
one neat family unit everywhere in the world, but often are dispersed among










individuals who are in diverse age and sex categories. A failure to look at
who does what farm operations, who makes which decisions, and who receives the
remuneration, and makes further investments, will affect the practice of
FSR/E. For example, a higher yielding variety might require more labor in
managing, harvesting, processing, and storing the cereal especially in
synchronously maturing varieties (Ferguson and Horn, 1985; McKee, 1984) or a
livestock intervention might target one group of producers at the expense of
another. For example, in a case from Senegal, men made decisions about the
planting of cereal crops, but women contributed much of the labor for the
crop's weeding, harvesting, and processing. Women made decisions about
legume, vegetable, and condiment crops. If women did the extra work for the
new variety of cereal crop, they had less time for the crops that they
managed. In livestock production male farmers favored livestock interventions
that "would increase live-weight and quality of stock" because size and number
were determinants of wealth. But, women controlled the milk allocation and
sale of milk products and "would gain most from interventions-which increased
calf survival or ...permitted an increase in the number of animals under
current land or labor constraints" (McKee, 1984:598-599).

There are specific methodologies needed to understand intrahousehold variables
within the FSR/E process (McKee, 1984). 'In the pre-diagnostic stage, the
ethnographic literature that provides information on the household's division
of labor, decision-making, and allocation of resources must be reviewed for
specific recommendation domains. In the diagnostic stage, the types of
household and the types of representative farmers need to be considered. For
example, in areas where there are many households headed by women, as in the
case of much of Africa and the Caribbean, it is necessary to include such
households in the sample and to ask if their resources and needs are the same
as or different from the households headed by men. Socioeconomic and
agronomic variables have to be assessed in terms of various household members
in the different types of households. The interventions have to be geared to
the needs of the types of households and the constituent members. In the
technology design stage, it is necessary to make sure that the researchers do
not use incorrect assumptions about gender; McKee suggests the input of female
scientists and field workers, but this is not always possible or even a
guarantee tht gender issues will be considered. There is no reason why both
male and female scientists, who have their eyes open, cannot work on the
problem. In the testing stage McKee says that one must monitor "how the farm
household actually copes with the reallocation of resources required by the
new requirements" (McKee, 1984:602). In the final extension stage, McKee
argues that it is important "to involve women farmers and farm workers, as
well as female extension agents, in diffusing technologies for crops and tasks
in which women predominate" (McKee, 1984:602).

The major thrust of this paper is that men as well as women agricultural
researchers and extensionists have to become involved and have to target
farmers of both genders. The argument here first considers the gender-related
characteristics of extension services and how these characteristics affect
reaching a variety of farmers, especially women. Then a case study from
Malawi shows that women are important in agriculture but tend to be neglected
in extension services and in the practice of FSR/E. In order to study and
correct the problem, the results of two sets of trials are considered here.
In one analysis, the results of using men and women farmers in the sample
shows differences in recommendation domains. In another, mechanisms by which
the male staff can work with women farmers are discerned. Based on the















lessons learned the paper concludes with a mechanism whereby the male
extensionists were legitimate and mandated to work with female farmers.


CHARACTERISTICS OF EXTENSION SERVICES

Usually it is the male extension personnel who work with farming systems
researchers to locate, interview, select trial cooperators, and target
disseminators. The number of male extension workers far exceeds the number of
women who receive training and who are employed as extensionists in most
places. Many writers comment on the paucity of female extension workers
compared with male ones (Jiggins, 1984; Berger et al., 1984; Staudt, 1975-76,
1978; Fresco, 1984). The data show that worldwide (including North America
and Europe) only 19% of the agricultural extension staff members are women.
The average number of female extensionists for Africa is 3%, for Latin America
and the Caribbean it is 14%, and for Asia and Oceania the figure is 23%. Only
in the Philippines are 40% of the staff members female. Table 1 gives the
figures as of 1981 for these regions. Berger et al. (1984) estimate that of
extensionists specially designated as agriculturalists, 41% do home economics
rather than agriculture. Tables 2 and 3 show the number of men and women
trained in two countries where women are critical in agricultural production:
Malawi in Africa and Nepal in Asia. These tables show that women
extensionists also are to be found in the bottom education tier and that their
training is much shorter than the training for men. A consequence of this is
that women extensionists often are not regarded as professionally competent in
their knowledge of field crops and of livestock as men. What is not evident
in the tables is that female workers are often pressured to work in home
economics programs rather than to work in the agricultural programs for which
they were trained. The contacts of female workers with male farmers tend to
be limited; concomitantly, the male extensionists tend to deal with male
farmers rather than with all farmers (Jiggins, 1984, Part 3:16). Whereas it
is often the case that only a small proportion of farmers are reached by the
extension service in any case, there is no reason to restrict extension to
only male farmers.

In the extension service itself, male personnel hold a variety of positions,
including decision-making ones that affect programs and policies. The female
extensionists, with the exception of a few supervisors, usually are
concentrated in the lower ranks. Often male workers are given the tasks of
offering concrete agricultural services either through the training and visit
system or through other regimes, while the female workers are supposed to form
women's groups for small scale income generation activities. Most extension
services in developing countries were modeled after the systems in North
America and Western Europe during the colonial period with men providing
agricultural information to male farmers and women providing home economics
and nutrition information to women (Mead, 1976; Berger et al., 1984).
Ironically, home economics programs in the developed countries have changed a
great deal since the late 1800s and have become relevant to the needs of
American farm women today, focusing on such topics as human development,
consumer education, household finances, and marketing. By contrast, the
teaching of domestic science in Africa is mostly focused on sewing,
embriodery, recipes, and basic hygiene/nutrition. Coupled with this is the
notion that there is better communication between members of the-same sex than
between members of the opposite sex. Sometimes these notions are strongly
stated in terms of tradition or cultural constraints and operationalized so










that only women are slated to work with women and only men are slated to work
with men. The paucity of women in agricultural service assures that rural
women will remain uncontacted and unassisted in terms of mainstream
agricultural training and services. Although it is probably true that many
people prefer to learn or to work with people of their same sex, coeducational
programs have worked in a large portion of the world. Berger et al. remark
that "since very little empirical work has been done in this area, there is
really no basis on which to judge the relative effectiveness of men and women
agents in assisting women farmers" (1984:54).

The Integrated Cereals Project in Nepal funded by USAID studied women's
contribution to agriculture in four areas of the country and queried how women
farmers could most effectively be reached (Shrestha et al., 1984). In this
case because of women's important role in the agricultural system, it was
"posited that unless new information, methods, and techniques are made
available to women, major potential change agents in the agricultural labor
force are being by-passed" (Shrestha et al., 1984:6). When questioned, the
women farmers said they did most of the agricultural work (79%) and more than
a third (35%) of the decision-making (Table 4). The female extensionists
agreed with the female farmers but the male extensionists thought women did
only some of the work and were not involved in decision-making. The male
workers were therefore "unlikely to perceive female farmers as important
recipients of extension information" (Shrestha et al., 1984:29) and this
undoubtedly constrained their contacts with women. Concomitantly, female
farmers did not think of themselves as recipients of extension information.
However, there were contacts by male extension agents to family members as
reported by female farmers. The data showed that three fourths of the male
extensionists did talk with women but only sporadically (about only 16% of
their contacts are women); and one fourth never contacted women (Table 5).
Female farmers were asked if they would visit male and female extensionists.
Table 6 shows that almost all the women farmers said they would seek out a
female extensionist and would go to their homes for advice, a common practice
of male farmers towards male extensionists. Fewer would ask a male
extensionist or visit their houses. Yet, in the areas where fewer women would.
contact the male extensionists, male extensionists had visited the women. This
case illustrates that people prefer to work with people of the same gender,
but in practice farmers work with those who have the knowledge, power, and
access to resources. It should also be mentioned that only 2.5% of all
extension workers in Nepal are female, so the possibility of having a woman
agent nearby is remote.

Because of the polarization of the extension service in many places, there is
little or no way to account for the variety of real situations and to take
into account the needs of the various household members. Some households may
share resources well and have a division of labor that is complementary.
There are households where husbands may preempt resources that other household
members helped to generate. In some households both husband and wife are full
time farmers; in others the husband may be absent and may or may not send
remittances while the wife does the farming; in still others a woman will have
no male labor or support; in some households only the husband will farm or the
wife is a part-time assistant. These varieties of intrahousehold dynamics and
access to services and resources by different family members have to be
considered in the design of technology testing and dissemination.

Part of the reason that it is difficult to reach the women in the practice of













FSR/E is that researchers make use of the extension and research services as
they are already set up in the host country. Farming systems researchers
accept the bias of the system either because they do not recognize it as such
and/or because it coincides with their own. In recent years there has been a
reexamination of the assumptions behind the sexual segregation in extension
and research programs. In a number of places, the policies have become
non-discriminatory so that technically women farmers can apply for credit or
they can be part of FSR/E programs, although in practice the number of
participants is low (Delancy, 1984). The question to be asked is what would
happen if the equation were changed and if extension and research programs in
practice were geared to all farmers regardless of sex. This might even entail
new procedures to target and reach the neglected farmers rather than the
standard procedure of assuming that one method works for all. A case study
from Malawi examines the problem of relying on male extensionists in FSR/E and
reports on some methods that were undertaken to change extension and FSR
procedures in order to reach female as well as male farmers.


CASE STUDY FROM MALAWI

Between 1981 and 1983, I directed an agricultural development project funded
by the Office of Women in Development and housed within the Ministry of
Agriculture in Malawi (Spring, 1985). The Women in Agricultural Development
Project (WIADP) was of national scope and its aims were multifaceted: to
research women's and men's roles in smallholder farming to use farming
systems research to ascertain smallholder, and especially women's needs; to
disaggregate agricultural data by sex; to work with extension and research
units to target women as well as men farmers; to evaluate women's programs;
and to orient policy makers to consider women farmers in agricultural
programs. Primary and secondary research by the WIADP showed the
contributions by gender for various commodities (Clark 1975; Spring, Smith and
Kayuni, 1983b). Women indeed did form the bulk of the agriculturalists in the
rural areas. They spent as much time on their farm work as on their domestic
work. Approximately one third of the households in the country were headed by
women, but in some areas as many as 45% of the households were female headed.
Women were taking over more of the management of family farms. This was true
not only in households that they headed, but in married households because of
male out migration for wage labor in cities and in the agricultural estate
sector. Women were involved in a variety of cropping patterns from mixed
subsistence to cash crops. They grew maize, groundnuts, rice, cassava,
tobacco, cotton, coffee, and tea. They worked on both food and cash crops
doing many of the operations such as spraying cotton and planting tobacco
seedlings that were commonly believed to be done by men only (Clark, 1975).
In fact, farm operations were differential by sex in some areas and in some
households, while in other places and households they were not. The so called
standard sexual division of labor where men prepared the land and women
planted, weeded, and harvested had given way to expediency in many places
(Spring, Smith and Kayuni, 1983b). The adult who was home on the farm did the
operations and in many cases this meant that the women were doing the work and
making the farm decisions. Women were involved in all aspects of farming
including land clearing, plowing, applying fertilizer, crop protection, etc.,
either routinely or when male labor was unavailable. Women in many areas were
involved in the care of livestock, especially of small ruminants and poultry.
Free ranging cattle were mostly owned by men and cared for by boys and men,
but as the animals were brought into the village for fattening in










stall-feeding projects, their care fell to women (Spring, 1986a).

Agricultural development projects increased the amount of time in hours per
day and in days per month that both men and women had to work (Clark, 1975).
The agricultural services provided by integrated development and localized
projects that included such services as training, input, and credit programs,
and agricultural extension mostly by-passed women. For many households this
meant that the efficiency of their farming was reduced. There were some women
who were able to participate in development programs in order to increase
their productivity. There were some male extensionists who included women
farmers with the male farmers they targeted for training, credit and visits
(Spring, Smith and Kayuni, 1983b).

The WIADP documented the delivery of agricultural extension services to men
and to women in a variety of ways. First, the WIADP analyzed the extension
survey that was part of a large national multi-instrument survey conducted by
the Ministry of Agriculture and financed by the World Bank. Second, the WIADP
interviewed and observed extension personnel in the field in terms of the way
they worked with clients. Third, the WIADP conducted FSR/E surveys and trials
and studied the ways the extension personnel were utilized to identify and to
work with farmers. Fourth, meetings and interviews were held with the staff
and management of agricultural projects who supervised extension and research
efforts to examine their procedures.

The results from the national s: :vey (The National Sample Survey of
Agriculture or NSSA) showed that farmers' contact with extension workers in
terms of personal and field visits, attendance at group meetings and
demonstrations, and participation in training courses were differential by sex
(Table 7). The data showed that contact with extension workers was the major
source of advice for both men and women farmers, but that men received more
personal visits and more advice than women. Group meetings tended to reach
more farmers than personal visits, but men were the primary participants.
Relatively few farmers of either sex viewed extension demonstrations, but more
men than women learned from this method. Field visits reached even fewer
women and the WIADP observed that many male extensionists simply dismissed the
women working in the fields while they concentrated on the men.

The WIADP disaggregated the NSSA data into three categories: male household
heads, female household heads, and wives of the male household heads. The
data showed that men received more services than women and often wives
received more services than female household heads. The data also showed that
very few wives received agricultural information from their husbands. The
presumed transfer of technology from husbands to wives and from men to women
in the household did not take place. The assumption that if men are trained
or assisted that other family members learned or were assisted was not
confirmed by the data (Spring, Smith and Kayuni, 1983b).

In terms of the practice of FSR/E surveys and trials it was the uncommon
situation where women farmers were contacted by reconnaissance or survey teams
or where they were part of the recommendations domains discerned. There was a
tendency for the host country and expatriate researchers to ignore the women
in the fields during rapid reconnaissance surveys. When production and social
scientists relied on the extension workers, which they often did, the
extension workers tended to take them to interview and work with the men. In
terms of on-farm farmer managed trials, only male cooperators were selected.




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