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December 3, 1992
TARGETING TECHNOLOGY DIFFUSION
THROUGH ON-FARM RESEARCH
Peter E. Hildebrand1
Introduction
With the creation of the Extension Service in the United States in
1914, public agricultural technology diffusion has been thought to
lie in its domain. The research-extension model followed is one in
which universities and experiment stations develop technology and
pass the information to extension which in turn processes it to
create messages for farmer consumption. That the process appeared
to work very well in this country was justification to carry the
model to the Third World following World War II where attempts were
being made to rapidly develop agriculture and the economy in the
more disadvantaged countries.
The process so captivated the international development agencies
that early efforts were designed simply to transfer US technology
to farmers in the Third World. Later, when these efforts largely
failed, the problem was thought to be that technology for temperate
agriculture was not appropriate for tropical agriculture. As a
result, national and international research organizations were
fomented to modify or develop technologies more appropriate to the
climatic conditions of these mainly tropical countries. The Green
Revolution was heralded as proof that this new approach was
working.
Still, by the late 1960s it was becoming obvious that even
technology tailored for tropical climates was not trickling down to
the small, limited resource farmers who had less than the best
physical resources and little or no access to irrigation. A new
approach now called Farming Systems Research-Extension (FSRE), with
heavy emphasis on participation by the these limited resource
farmers, was fomented. Research and technology development have
been relatively successful under this paradigm, but in practice,
most organizations who use it still lack a firm research-extension
institutional link. Even though technology generation and
diffusion are relatively successful, if the activities are carried
out by research institutions, there is often little linkage with
extension institutions. That is, both research and extension
functions are working, but the institutional linkages may not be.
The opposite is also true if the FSRE activities are being carried
out by institutions whose main activity is extension In this case,
linkages back to sources of technology are weak.
1 Professor, Food and Resource Economics Department, University
of Florida, Gainesville, Florida 32611-0240.
This paper is an attempt to achieve two objectives. The first is
to demonstrate the advantages of on-farm research for effectively
enhancing the extension function. The second is to create a
paradigm which can be used by research and extension institutions
in developed as well as developing countries to help make their
efforts more effective. If both research and extension functions
work well in FSRE, there should be clear justification for
institutional collaboration, if not a merger, at least at the field
level.
Historical Perspective: The Progressive Farmer Strategy
For a quarter century following World War II, the conventional
technology generation and diffusion process was patterned on a
progressive farmer strategy. This strategy (Rbling, 1988. p. 68),
in turn, was based on several assumptions. First was the
innovation bias (Rogers, 1983), under which it was assumed that any
innovation resulting from the established research-extension
process was "good", and therefore, should be adopted. Second, it
was assumed that this kind of technology was broadly adaptable and
scale neutral -- anyone who was willing, could adopt it. Third,
diffusion research had shown that diffusions spread within a
"social system" from one decision making unit to the next over time
(R8ling, 1988. p. 65), so any introduced innovation should spread
throughout a community. Fourth, it was also assumed that early and
late adopters, as well as non-adopters were all from the same
"social system" simply because they lived in the same community --
late adopters or non-adopters were thought to be "laggards", and
not interested in "improvement".
It was also noticed from feedback messages (farmer to extension to
research, as well as farmer directly to research) that it was the
"progressive farmers" who were adopting the technology first, if
not exclusively. However, this was not a concern because it was
assumed that the "good" technology would trickle down from these
progressive farmers to those who were less progressive or more
conservative or risk diverse (Figure 1). Indeed, extension used
contacts with progressive farmers as a prime strategy.
As it became obvious that these progressive farmers were becoming
wealthier and larger relative to the other farmers in the
community, this was of little concern. The emerging change in the
nature of farms was supported by the concept that bigger is better.
Often the phrase, "Get big or get out" was heard and repeated.
Small farmers often were considered more of a social problem than
an agricultural problem.
The Need to Change Approaches
Without going into the reasons why the "bigger is better" concept
is not wholly appropriate even for industrial countries, it became
obvious early in the 1970s that it was disastrous for the Third
World where the large majority of farmers were not being served by
the progressive farmer, trickle down strategy. In the Third World,
as opposed to the industrialized countries, little capacity was
available to employ persons forced from agriculture into urban
areas. Employment needed to be maintained and productivity and
income increased on small, resource-poor farms in order for growth
to take place.
The gains made by small farms in the Third World with Green
Revolution technology were made only by small farmers with the best
resource base, a limited minority. And the technology did not even
trickle down from them to other small farmers who did not have the
advantages of the better resource base. As it became apparent that
all farmers in a community were not part of the same "social
system", it was realized that the progressive farmer strategy
coupled with the failed trickle down theory did not work, Figure 2.
Other approaches were needed.
Target Categories
Research on technology diffusion, i.e., diffusion research, was
able to show ex post what characteristics were related to slow or
non-adopters (small, poor, little education, etc.), but were unable
to provide ex ante suggestions for effective intervention
strategies (RBling, 1988. p. 64).
The progressive farmer strategy coupled with the trickle down
concept fails when the farm population is not homogeneous, but
heterogeneous. This, of course, is the usual situation.
"Laggards" and "Innovators", originally considered to be members of
the same social system simply because they lived in the same
community, region or country, are very different farmers, with
different environments for production.
Even though millions of farmers were bypassed because of the use of
the progressive farmer/trickle down philosophy, this strategy, in
a modified form, can be used for "categories of farmers who have
been carefully identified as homogeneous and with innovations which
have been developed to suit the characteristics of those
homogeneous categories" (Rbling, 1988. p. 71), Figure 3.
Ruling (1988, p. 77) uses the term "target categories" which
appears to be a concept similar to a combination of recommendation
and diffusion domains. He uses relevant variables to segment a
heterogeneous population into categories and then designs an
"intervention program content and strategy" relevant for each
category, tests it with representative members of the target
category and then "mounts the intervention so as to cover the
intended target category selectively" (p.77). To the extent that
the intervention is agricultural technology and not diffusion
technique, this strategy approaches current FSRE thinking.
The problem still is, however, that it has been easier to develop
technology that suits the "progressive farmer" than it is to
develop technology that fits within the narrow margins of low
access and resource-poor farmers (Rl1ing, 1988. p. 71). Thus, the
extension message that goes to the different categories of farmers
most often is still one message, developed on experiment stations
and appropriate only for "progressive farmers", those with the best
resource base, Figure 4. Without a means to modify the technology
to suit the resources and environments of the "laggards", the
message cannot result in improved technology for farmers whose
resources and environments do not reflect those found under
experimental conditions on the stations.
MSA as an Alternative to the "Progressive Farmer" and an
improvement to the "Target Categories" Strategies
Modified Stability Analysis or MSA (Hildebrand, 1984) provides a
means of solving the lingering problems associated with developing
and diffusing improved agricultural technologies to all categories
of farmers in any community. In MSA, the whole population of
farmers in a community comprises a research domain. To the extent
that a technology might be appropriate (desired and possible to
use) on any of the farms in the research domain, any farm in the
community can be used as an environment for on-farm testing. This
makes the research process more efficient. Research results from
an on-farm testing program can be used to identify recommendation
domains based on each farmer's environment (both the biophysical
base environment and the socioeconomic modifications to the base)
and on the different farmers' evaluation criteria.
The on-farm program results in multiple extension messages suitable
for well defined environments and evaluation or selection criteria.
Each "target category" can receive a message appropriate to its
conditions, Figure 5.
Table 1 demonstrates the nature of recommendation domains specified
by appropriately designed and analyzed on-farm research conducted
in a series of communities, a research domain, of small farmers in
the Amazon Basin of Brazil (Singh, 1990). A number of biophysical
environments (land type) exist in the area represented by whether
the land was cleared from primary or secondary forest (PF or SF)
and whether it was in first or second year of use (the subscripts).
WL symbolizes land cleared by bulldozer when the communities were
established and is essentially waste land. Two criteria represent
the several which might be relevant in the area. The criterion Mg
ha'1 is more often used by researchers and extension personnel than
by farmers. When cash is a scarce resource, as is the case in
these communities, kg $' is a common criterion used by resource-
poor, small farmers. Other criteria could also be included.
The result of using MSA and on-farm research is to create multiple
extension messages tailored to specific farm environments and the
different criteria which farmers may use to evaluate new
technology, Figure 6. Farmers from all the environments included
in on-farm research in a research domain can benefit from this kind
of a research-extension program. Following the first year's
research program, extension demonstration trials (which also can
serve the purpose of verification trials for research and farmer
purposes) can be set up so that individual farmers can evaluate the
specific recommendations against their current practices. Farmers,
extension personnel and researchers all benefit from this
additional effort.
Table 1. Summary of the recommendation domains and specific
technology recommended, based on the data for maize in Amazonas,
Brazil (Singh, 1990).
Land Type
PFi SF1 PF2 SF2 WL
Criterion
Mg ha1 TSP CM CM CM CM
kg $- FP FP CM CM None
In the demonstration/verification trials, extension agents can
assess with the farmers the kind of environment in which the
farmers will be using the technology and the way the farmers will
evaluate results. This provides the extension agents with the
information to choose among the recommendations specified by
environment and evaluation criterion as shown in Table 1 and Figure
6. The same process can be used for broader diffusion of the
specific technology recommendations in the extension program.
Summary
On-farm research appropriately designed for Modified Stability
Analysis can provide the framework for an efficient and effective
research-extension program. Activities conducted under this
paradigm mutually benefit farmers, extension personnel and
researchers. This paradigm should effectively fill the "missing
linkage" between research and extension and make the programs of
both research and extension institutions more efficient.
References
Hildebrand, P.E. 1984. Modified stability analysis of farmer
managed, on-farm trials. Agronomy Journal, 76:271-274.
Rogers, E.M. 1983. Diffusion of innovations. Third Edition. The
Free Press. New York.
Ruling, N.G. 1988. Extension science: information systems in
agricultural development. Cambridge. New York.
Singh, B.K. 1990. Sustaining crop phosphorus nutrition of highly
leached oxisols of the Amazon Basin of Brazil through use of
organic amendments. Unpublished PhD Dissertation, University of
Florida, Gainesville.
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Figure 1. Theory of Technology Trickle-Down
from Progressive Farmers.
Extension
message
"Laggards"
Number of Farmers
A8/FIG01.DRW
Figure 2. Limited Technology Trickle-Down
from Progressive Farmers.
.._ .Extensi
"Progressive" messa
farmers
Jjil: ^iill:
"Laggards"
Number of Farmers
High
Level of Adoption Low
El None
A8/FIGO2.DRW
ion
goe I
Diffusion to Categories of Farmers.
Extension
message
"Laggards"
Number of Farmers
A8/FIGO3.DRW
Figure 3.
Figure 4.
Developing an Extension Message from
an Experiment Station.
Message Experiment
SStation
One Extension Message
to Multiple Categories
Number of Farmers
A -io ^ ^sHigh
Level of Adoption HiLowgh
rl None
A8/FIG04.DRW
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Figure 5. Developing Multiple Extension Messages
from On-Farm Trials.
Extension On-Farm
Si Research
* *
Number of Farmers
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Figure 6.
Extension Messages for Multiple Environments
and Several Evaluation Criteria with MSA
Population
of Farms
Multiple
Criteria
S Mg/ha
kg/$
Mg/ha
Mg/ha
kg/$
S Mg/ha
kg/$
Mg/ha
kg/$
On-Farm
Research-Extension
in
Multiple Environments
PF1
SF,
PF2
SF,
WL
Level of Adoption
PF,
SF,
PF
2
SF,
WL
High
None
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