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Staff Paper Series
TARGETING TECHNOLOGY DIFFUSION THROUGH
COORDINATED ON-FARM RESEARCH'
by
Peter E. Hildebrand2
STAFF PAPER SP93-25
NOVEMBER 1993
FOOD AND RESOURCE ECONOMICS DEPARTMENT
Institute of Food and Agricultural Sciences
University of Florida
Gainesville, Florida 32611
63- /Sj
TARGETING TECHNOLOGY DIFFUSION
THROUGH COORDINATED ON-FARM RESEARCH1
Peter E. Hildebrand2
1 Prepared for presentation at the Association for Farming Systems Research-Extension North American
Symposium on Systems Approaches in North American Agriculture and Natural Resources: Broadening the Scope of
FSRE. University of Florida, Gainesville. October 12-16, 1993.
2 Professor, Food and Resource Economics Department, University of Florida, Gainesville, Florida 32611-0240.
TARGETING TECHNOLOGY DIFFUSION
THROUGH COORDINATED ON-FARM RESEARCH
Peter E. Hildebrand
ABSTRACT
This paper has three objectives. The first is to demonstrate the advantages of coordinated, on-
farm research for effectively enhancing diffusion. The second is to help make farmers'
participation in on-farm research more productive in North America. The third is to create a
paradigm which improves on older models and can be used by research and extension institutions
to help make their efforts more efficient and effective. An historical perspective of the
"progressive farmer" and targeted "categories of farmers" strategies is background. Modified
Stability Analysis (MSA) provides the foundation of an alternative to these strategies. It is
presented based on real-world data from the Brazilian Amazon region. The result of using MSA
and on-farm research is to enable the creation of multiple extension messages tailored to specific
farm field environments and the different criteria farmers may use to evaluate new technology.
Activities conducted under this paradigm mutually benefit farmers, extension personnel and
researchers.
BD5/PSi-EXT
TARGETING TECHNOLOGY DIFFUSION
THROUGH COORDINATED ON-FARM RESEARCH3
Peter E. Hildebrand4
Introduction
With the creation of the Cooperative Extension Service in the United States in 1914, public
agricultural technology diffusion has been within its domain. The research-extension model
followed is one in which the United States Department of Agriculture (USDA), and the Land
Grant universities and their experiment stations develop technology and pass the information to
Extension. In turn, Extension, by various means including on-farm validation and
demonstration, processes it to create extension messages (recommendations) 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 I where attempts were being made
to rapidly develop agriculture and the economies of less advantaged 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. National and international research organizations were
created 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 early 1970s 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 infrastructure such as markets and irrigation. These
account for the large majority of all farmers in most countries. A new approach now called
Farming Systems Research-Extension (FSRE), with heavy emphasis on participation by the these
limited resource farmers, was kindled.5 FSRE was based on a bottom-up approach rather than
top down from the experiment station to extension to farmer. Heavy emphasis was on
participation by the small-scale, limited resource farmers in diagnosis and evaluation of potential
new technologies on their own farms. Coordinated, participatory on-farm technology
3 Prepared for presentation at the Association for Farming Systems Research-Extension North American
Symposium on Systems Approaches in North American Agriculture and Natural Resources: Broadening the Scope of
FSRE. University of Florida, Gainesville. October 12-16, 1993.
4 Professor, Food and Resource Economics Department, University of Florida, Gainesville, Florida 32611-0240.
Constructive comments on an earlier draft are acknowledged from L. Van Crowder, J.K. McDermott and N.G. Ruling.
SSome argue that the extension model tranferred from the United States was very similar to much of what is
now known as FSRE. However, "when we tried to take Extension overseas, we tried to transfer fir and not function"
(J.K. McDermott, personal communication). This was exacerbated by the fact that many research and extension workers in
the receiving countries were not familiar with prevailing agricultural conditions, unlike the early American experience.
development and diffusion has now benefitted from about 20 years of use by FSRE practitioners,
mostly in developing countries. With an increasing interest in farmer participatory research in
North America, it is befitting that this region benefit from the experiences it has financed over
the years in less advantaged countries.
This paper has three objectives. The first is to demonstrate the advantages of coordinated, on-
farm research for effectively enhancing diffusion. The second is to help make farmers'
participation in on-farm research more productive in North America. The third is to create a
paradigm which improves on older models and can be used by research and extension institutions
to help make their efforts more efficient and effective. The discussion starts with a brief review
of extension strategies.
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 innovations spread within a "social system" from
one decision making unit to the next over time (Rl6ing, 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
It became obvious early in the 1970s that "bigger is better" was disastrous for developing
countries where the large majority of farmers were not being served by the progressive farmer,
trickle down strategy. In the less advantaged countries, 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 those 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 was able to show ex post what characteristics were related to
slow or non-adopters (small, poor, little education, etc.), but was unable to provide ex ante
suggestions for effective intervention strategies (R6ling, 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 production environments.
Even though millions of farmers were bypassed because of the progressive farmer/trickle down
philosophy, a modification of this strategy 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" (R61ing, 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 the recommendation and diffusion domain concepts used in FSRE (Wotowiec
et al., 1988). 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 (R61ing, 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 for solving the
lingering problems associated with developing and diffusing improved agricultural technologies
to all categories of farmers in any community. In MSA, a wide range of farmers and their fields
in a community or region can be part of a single research domain. To the extent that a
technology might be appropriate (desired and possible to use) on any of the farms or fields in
the research domain, any field on any farm in the domain 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 the environment in
each field (both the biophysical base environment and the socioeconomic modifications to the
base) and on the different farmers' evaluation criteria.
A critical element in the design of an on-farm trial to make it amenable to analysis by MSA is
that each environment (field) have the same set of treatments, or at least a common set of two
or more treatments. In projects such as those in the Illinois Sustainable Agriculture Network,
if groups of farmers could agree on a common set of treatments, the resulting design would be
amenable to MSA. Individual farmers could still include their own specialized treatment, in
addition to the common set if they wanted additional information. For purposes of MSA, it is
not necessary to replicate treatments within an environment. If farmers want to replicate, then
treatment averages within an environment can be used for the MSA. However, it is more
important for purposes of MSA to have more environments than more replications within
environments. With a large number of cooperators involved in a single year, it may not be
necessary to wait two or more years before having definitive results (Stucker and Hicks, 1992;
Stroup et al., 1993).
A cooperative on-farm research program designed in this way results in multiple extension
messages suitable for well defined environments and different evaluation or selection criteria.
Each "target category" can receive a message appropriate to its conditions, Figure 5. An
example from Brazil will be used to illustrate the potential of MSA in this kind of a program.
Table 1 demonstrates the nature of recommendation domains specified by appropriately designed
and analyzed on-farm maize fertility 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. Four treatments were included:
the farmers' local practice (FP), which had essentially no, or very low levels of
fertilization;
a "full dose" of triple super phosphate (TSP);
chicken manure (CM) plus a half dose of TSP; and
processed city waste (PCW) from Manaus, plus a half dose of TSP.
Two criteria represent 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 $-' of cash cost is a common criterion used by
resource-poor, small farmers. Other criteria also could be included.
The result of using MSA and on-farm research is to enable the creation of multiple extension
(recommendation) messages tailored to specific field environments and the different criteria
which farmers may use to evaluate new technology, Figure 6. Farmers with fields 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 the technology recommended for maize,
Rio Preto da Eva, Amazonas, Brazil, based on environmental factors and evaluation criteria.
Land Type Evaluation criterion
Mg ha-1 kg $-
PFI TSP FP
SFi CM FP
PF2 CM CM
SF2 CM CM
WL CM
Source: Singh, 1990
In the demonstration/verification trials, extension agents can assess with the farmers the kind of
field 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, effective and productive farmer-participatory, 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. Because it results in recommendations for specific kinds of field environments and
criteria relevant to individual farmers, it should also make more productive the time and
resources invested by farmers in on-farm research.
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.
Stroup, W.W., P.E. Hildebrand and C.A. Francis. 1993. Farmer participation for more
effective research in sustainable agriculture. In: Technologies for sustainable agriculture in the
tropics. American Society of Agronomy, Special Publication, Madison. In press.
Stucker, R.E. and D.H. Hicks. 1992. Some aspects of design and interpretation of row-crop
on-farm research. In: Proceedings of a conference on Participatory on-farm research and
education for agricultural sustainability. University of Illinois at Urbana-Champaign. July 30-
August 1, 1992.
Wotowiec, P., S.V. Poats and P.E. Hildebrand. 1988. Research, recommendation and
diffusion domains: a farming systems approach to targeting. In: Poats, S.V., M. Schmink and
A. Spring. Gender issues in farming systems research and extension. Westview Press. Boulder
and London.
BDO/FR-EXr
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.
Extension
message
"Laggards"
Number of Farmers
i :::A::i: B NHigh
Level of Adoption Low
None
A8/FIGO2.DRW
Figure 3. Diffusion to Categories of Farmers.
"Laggards"
Number of Farmers
A8SFIG03.DRW
Figure 5.
Extension
from One
Messages for Multiple Environments
Coordinated On-Farm Trial
Extension
I
On-Farm
Research
cm
UJ
O
4-
0
o
..J
Number of Farmers
A8/FIGO5.DRW
* -
Figure 6. Extension Messages for Multiple Environments
and Several Evaluation Criteria with MSA
Population
of Farms
........... ".s
............:.cl.r..............
FP
FP ___
Not recommended
................ :...; ..'i.:f~ 72~~
F P
.. . .....
........ ....... .. . .... ..
2: .......... ...........
.. . .. .. .. .
.. . . . ss a i ,
..................;... ............~: ...... ....
.. .. .. .. .. .. . .. ...... ..
No ecmene
Multiple
Criteria
Mg/ha
kg/$
Mg/ha
kg/$
Mg/ha
kg/$
kg/$
Mg/ha
kg/$
On-Farm
Research-Extension
in
Multiple Environments
PF1
SF,
PF2
SF
WL
Level of Adoption High
I INone
A8/FGO6.DRW
SF,
PF2
SF,
WL
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