Title: Global research challenges
Full Citation
Permanent Link: http://ufdc.ufl.edu/UF00082715/00001
 Material Information
Title: Global research challenges including small holders in rural development
Physical Description: Book
Creator: Hildebrand, Peter E.
Publisher: Peter E. Hildebrand
 Record Information
Bibliographic ID: UF00082715
Volume ID: VID00001
Source Institution: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: oclc - 213486204

Table of Contents
        Page 1
        Page 2
        Page 3
        Page 4
        Page 5
        Page 6
        Page 7
        Page 8
        Page 9
        Page 10
        Page 11
Full Text


Peter E. Hildebrand2


Agricultural research has been "globalized" since at least the 1960s when the
International Agricultural Research Center system was inaugurated, the Green Revolution
emerged, and the agricultural researchers and administrators from the foundations,
universities, USAID, the IARCs, and some national agricultural research programs began
globetrotting. In the 1970s, multiple cropping research, as an example, became
international, if not global, in scope. By 1972 in Central America it involved an IARC
(IRRI), a regional research organization (CATIE), a national agricultural research
institute (CENTA in El Salvador), and a U.S. university (Florida). And at least in El
Salvador, this work was also multidisciplinary. It was also during this period of time that
the term "farming systems" began to be applied by the globetrotters to activities around
the world, including Guatemala and Colombia. These were all multidisciplinary
activities oriented specifically toward small holders. Also in the 1970s, animals began to
be incorporated into what were previously crop-biased "farming systems."

Despite this long history of a globalized research effort, a number of factors exist that
have made ineffective our quest to include small holders in rural development. Chief
among these is their great diversity. We tend to work where we can see broadly
adoptable results and these efforts are supported by industry. Land is not necessarily the
most limiting resource on small farms, yet we tend to look mostly at "yield" increasing
technology measured in output per unit land area. "Our" crops are not necessarily the
priority crops of the farmers, yet relatively little effort has been put in minor crops and in
livestock. Average farms do not exist, yet we frequently work with averages. Thus our
technology tends not to be appropriate for the poorer half of the population and they are
not able to benefit from existing rural development efforts.

But small farms are not going away. Even though as a percent of the population, rural
numbers are decreasing, farm populations in most countries in Latin America are still
increasing. Therefore, it is time to take the challenge of including them in rural
development. We need to work with the diversity that is both a characteristic of these
small farms and a critical need of their livelihood systems. A multidisciplinary
methodology that is broadly adaptable, but that conserves this diversity and can lead to
different technologies for diverse groups of the poorest farmers is described in the paper.

Keywords: Diversity, limited resources, multidisciplinary, participatory

Invited keynote address at the 1t Henry A. Wallace Inter-American Scientific Conference on
Globalization of Agricultural Research. CATIE, Turrialba, Costa Rica February 25-27, 2002.
2 Professor, Food and Resource Economics Department, University of Florida, Gainesville FL 32611-0240.


Peter E. Hildebrand2

Agricultural research has been "globalized" since at least the 1960s when the
International Agricultural Research Center system was inaugurated, the Green Revolution
emerged, and agricultural researchers and administrators from the foundations,
universities, USAID, the IARCs, and some national agricultural research programs began
globetrotting. In the 1970s I had foundation directors, university presidents, USAID
officers and IARC scientists in my field plots in El Salvador and Guatemala. In 1972,
Richard Bradfield, a Rockefeller Foundation scientist from IRRI in the Philippines who
had started working with multiple cropping, came to see our field plots in El Salvador on
his way to visit the CATIE multiple cropping experiments in Costa Rica. In the
Agricultural Economics Department of CENTA, we were already orienting our work
toward practical applications for small holders and his visit inspired us to begin what
became the national multicultivos program for CENTA. Multiple cropping research had
become international, if not global, in scope. It involved an IARC, a regional research
organization, a national agricultural research institute, and a U.S. university (Florida).
And at least in El Salvador, this work was also multidisciplinary.

The Green Revolution, with its roots even before this time, was widely heralded, but
slowly it was recognized that it was not benefiting many of the world's small farmers,
including most of those on marginal lands, and particularly those with very limited
resources. In the 1970s, new efforts to provide for the 'poorest of the poor' became
common. It was slowly being realized that more than agronomy was required to find
technologies that the poorest of the poor farmers could utilize and benefit from. In El
Salvador, the multiple cropping program was headquartered in agricultural economics.
Perhaps because of the farm management orientation in this department, our multiple
cropping was oriented from the beginning to work under poor farm conditions as opposed
to the work at IRRI and CATIE, which were more focused on the scientific interactions
of different species. In 1973 we established our first on-farm trial even as we were still
experimenting with new ideas on the station.

In El Salvador there was intense pressure on the land because of the high population
density. Farms were small but there was relatively abundant labor. Seed and chemical
inputs were generally available, and in the specific area where we were working
(Zapotitni), there was irrigation. We were looking at ways to help farmers produce more
cash crops on their limited land without decreasing the amount of maize and beans. By
late 1973 we began to be visited by extension agents, small farmers and even some of the
wealthy farmers. In December alone, 100 small farmers visited our plots. It was

2 Invited keynote address at the 1" Henry A. Wallace Inter-American Scientific Conference on
Globalization of Agricultural Research. CATIE, Turrialba, Costa Rica February 25-27, 2002.
2 Professor, Food and Resource Economics and Director of International Programs, Institute of Food and
Agricultural Sciences, University of Florida, Gainesville FL 32611-0240. peh@ufl.edu

interesting to note that after looking over what we were doing, the small farmers often
said that if they could do it, they would not need more land. The wealthy farmers often
said that if the small farmers could do what we were doing they wouldn't need more of
the wealthy farmers' land.

The multicultivos project created a lot of excitement. We were visited in January 1974 by
the President of the Agricultural Development Bank (Banco de Fomento Agropecuario)
of El Salvador, the Director General of CENTA and the Sub-secretary (vice minister) of
the Ministry of Agriculture. Farmers also continued to visit in groups. In March our
visitors to the multicultivos included the Minister of Agriculture and his Sub-secretary,
the Director General of CENTA, the commanding Colonel of the Cavalry who was
interested in putting his soldiers to work producing some of their own food, the Director
of Planning of the Ministry of Agriculture, the owners of a food processing company, a
large number of farmers from many areas of the country, some extension agents, and a
group of managers from cotton farms who were interested in ways their workers might be
able to produce more of their own food. In April, among other visitors, was a group of
reporters for radio, TV, newspapers and magazines. As a result of their visit there were
five articles on the multicultivos in the newspapers, and reports on both radio and TV.
We were also visited by the Board of Directors of the Agrarian Reform Institute who
were interested in the implications of this intensive system on the amount of land small
farmers might need and the potential income they might be able to expect. It was
obvious that research directly focusing on the conditions and needs of small farmers was
seen as unique and potentially very beneficial for the country. By 1976 there were nearly
600 on-farm trials of the multicultivos technology throughout the country.

Beginning in 1974 in ICTA in Guatemala where I had gone, we added anthropologists to
the mix of agronomists and economists in the "Rural Socioeconomics" unit and increased
our efforts at working for the small farmers. This was when the Sondeo (Hildebrand
1981) methodology was formulated and where we began keeping records with the small
farmers (Hildebrand 1982). Rather than study the "adoption" of technology to find the
characteristics of farmers were "innovative" and "early adopters" (Rogers) and thus
worth working with, we assessed the acceptability of the technology for the conditions
and capabilities of the small farmers. We were more concerned about why some farmers
were unwilling or unable to adopt the new technologies being promoted by ICTA. What
were the characteristics of the technology that made it unacceptable to the small farmers
who were the clients? We were looking at the farm as a whole unit, not just at one crop
at a time.

The Rural Socioeconomics unit also had its own on-farm trials and, again, these were
visited by many of the "rural development" globetrotters. It was during this period of
time that the term "farming systems" began to be applied by the globetrotters to our
activities and to the activities of two other agricultural economists, David Norman in
Nigeria and Mike Collinson in Tanzania, as well as to other activities such as the DRI
projects in Colombia in which Hubert Zandstra, among others was involved. These were
all multidisciplinary activities oriented specifically toward small holders. Also in the

1970s, animals began to be incorporated into what were previously crop-biased "farming
systems" (McDowell and Hildebrand).

By 1980, "farming systems" programs were being created in many developing countries,
and in 1982 the Farming Systems Support Project, FSSP, was created at the University of
Florida by USAID. Its purpose was to provide technical assistance, training and
networking for its widely scattered farming systems projects in Africa, Asia and Latin
America. "Farming Systems" was the golden buzzword during the 1980s. But many of
those projects were not based on farming systems methodology nor oriented specifically
toward small holders. USAID gradually became disenchanted with farming systems. A
new buzzword began to emerge sustainable and it began to be substituted for the
words farming systems in project titles. The bureaucracy ignored the fact that
"sustainable" technology or "sustainable" agriculture were states of being and that
"farming systems" as the term was being used was a methodology. It was even more
curious that farming systems methodology was necessary in proposed sustainable
projects in order to get approved.

Gender became incorporated in farming systems methodologies in an important way in
the mid 1980s partly as a result of a conference held at the University of Florida in 1986
(Poats et al., 1988). This conference brought together the Women in Development and
the Farming Systems communities from around the world. The emphasis was not on the
potential confrontation of "Why aren't women taken into account?" but rather on "How
to better take gender into account" in agricultural and rural development activities.
Gender as a concern has persevered.

The new buzzword is "participation." It was thought that previous efforts at reaching
small holders were not being as effective as anticipated because the stakeholders the
small farmers were not sufficiently being taken into account (Chambers). One
frequently referenced successful participation project is that of Jackie Ashby's work with
bean breeding at CIAT. But more purist participation projects tend to wander away from
agricultural technology development and into such things as potable water, schools,
roads, etc., so have not been popular with agricultural research organizations, national or

Constraints to including small holders

As promising as each of these new waves of rural development practices seemed to be at
the time, they still often failed to reach most of the world's poorest farmers. A number of
factors exist that have made ineffective our quest to include small holders in rural
development. Chief among these is their great diversity. Even in areas where we used to
define "homogeneous systems" (Hildebrand, 1981) or "recommendation domains"
(Byerlee et al. 1982) we now know that there is also tremendous diversity among
households because of the composition making up those households. Our scientific and
professional baggage is another.

Land is the most limiting resource on small farms3

To many of us, increased production means increasing the amount of product produced
per unit land area, because arable land is a globally limited resource. Thus we tend to
look at technologies that increase yield per unit land area even if they require other
resources such as more female or male labor or cash that many small holders have little
of. Examples using cash include mechanization, inorganic fertilizer or pesticides. Yet, if
we measured the productivity (yield) of any of these in terms of product per unit of cash,
it might well be lower than what the farmers are already doing. Because labor, cash or
seed are often more limiting than land on small-scale, family farms, we first need to
consider increasing the productivity of these resources. Increased productivity of land
may follow. In crops like potatoes or beans which are staple foods and can readily be
sold, yet somewhat difficult to store under rustic conditions, amount of seed can be much
more limiting than land. In Narifio, Colombia, a well-known minifundio area, farmers
planted potatoes in low densities to maximize the productivity of each potato planted
even though it reduced yield per unit land area. When they ran out of seed, that was what
determined the size of the field. Even on those very small farms, seed was the limiting
resource for potatoes, not land (Andrew 1970). In the Pakistani Punjab in the 1960s,
farmers with limited water, spread it out on as much land as possible to maximize the
productivity of the water. This, of course, reduced the yield of the crop per unit land
area. But if they had increased the per ha application of water, it would have reduced the
productivity of the water, resulting in less product. (Andrew and Hildebrand 1982).

"Our" crops are the priority crops

We also tend to put priority only on the animal, crop or crops in which we are interested,
forgetting that the farmer must allocate resources among all the activities and needs of the
household. Ignoring the seasonal needs of farmers can lead to inappropriate
technologies. For instance, early (short season) crops usually have lower yields than later
(longer season) crops. Yet farmers grow them to provide food or cash at a time when
they are needed even if they yield less. Also, "late" planting is often the result of a
difference between our priorities and those of the farmers. The farmer may put a higher
priority on a different crop than the one in which we are interested so plants the other one
first and ours later than we "know" is optimal.

We need to see results

We tend to define "results" in different ways. Researchers usually define results as
statistically significant differences among treatments. If our trials do not produce
statistically significant differences, we do not see "results." This leads to tight control of
non-test variables in experiments to reduce unexplained variance, thus increasing the
probability of achieving statistically significant differences among test treatments. When

3 Parts of the following are from a previous paper presented at the Workshop on No-till Farming in South
Asia's Rice-Wheat System: Experiences from the Rice-Wheat Consortium and the USA, 21 February 2002,
Ohio State University.

this practice is followed in on-farm trials, it creates an artificially superior environment
that the farmer is unable to provide over time on a field basis (Hildebrand and Russell).
Another method of helping assure statistically significant results is to have higher yields,
to achieving a lower coefficient of variance, thus increasing the probability of significant
differences among treatments. In on-farm trials this leads to selecting the best farms or
the best fields or even the best spots in fields on which to conduct trials. The DG of one
national agricultural research organization for which I worked said, "Pete, if you work on
those hillsides (where the small farms were) you won't get any response." By response,
he meant results as measured by statistically significant differences.

But results also are measured by breadth of adoption. Whether it is a cultivar, another
input or a cultivation practice, broader adoption is always better than limited adoption.
This is also appreciated by industry. A limited number of broadly adoptable products is
better than a larger number of narrowly applicable items. This leads us toward practices
and materials that require the modification of the field environment so that they can be
productive, similar to what is done in experiments.4 This practice has been very effective
in areas such as the corn belt of the United States. It can also be effective in flooded rice
paddies. But most small farmers with limited resources cannot modify the highly diverse
environments of their farms and fields to suit the requirements of new technologies.

Looking for results can also lead us into working with the "innovators" or "early
adopters" as Rogers (1962) would call them. These inevitably are the farmers with more
resources, those who have the time to devote to meetings and in working with us, and
those who can accept risk of experimentation. But orienting our work toward them so we
can see "results" also leads us to those who are best able to modify their environments to
meet the requirements of the technology. They inevitably are not the poorest of the poor
small farmers.

Average farms do not exist

An "average" farm household in an area might have 1.2 adult males, 1.4 adult females,
1.7 adolescent males, 0.6 adolescent females and 2.4 children. It would probably have
more land than at least half of the households in the area. It could have from 0.4 to 1.6
cattle or horses. Other averages could be added, but nowhere could such a farm
household be found. Yet we inevitably tend to use averages when we discuss yields,
farm size, available resources or capabilities to adopt new technologies. We ignore the
fact that somewhere around half of the farms do not achieve the average yield, nor are
that large, nor have other resources or capabilities to adopt new technologies. And
technology mostly is not scale neutral. It is not the size of the field nor farm, but the
resources that small farms do not have compared with large farms that make the
difference. I once heard the research dean of a U.S. Land Grant university declare,
"Certainly our technology works on small farms as well as large ones. We test it on
small plots, don't we?"

4 Conway, p. 39, expresses a similar concern in a slightly different way.

Small farms are not going away.

Although the percentage of people living in rural, as opposed to urban areas is declining,
in many countries the number of people living in rural areas and the agricultural
population continues to increase. In Central America, between 1970 and 2000, the
agricultural population increased by 2.6 million people (FAO). In Guatemala, there are
as many people in agriculture now as there were total people in the country in 1970.
Although there are no statistics that I know of, the majority of these people have to be
living on small farms. This could be as many as 400,000 new small farms in Central
America over this 30-year period.

It is time to take the challenge

Over this same 30 year period, even after realizing that Green Revolution technology has
had a very limited effect on limited resource farmers on marginal lands, we have avoided
the challenge of working with the great biophysical and socioeconomic diversity in which
the world's small farmers struggle to survive. Perhaps we thought small farms would go
away. "Get bigger or get out." Perhaps we thought that our technology was scale neutral
and that it was just a matter of trickling down to the late adopters and laggards that were
the small farmers who did not adopt it. Perhaps we thought that average farms
represented all farms. Perhaps we feel we have to work where we can easily measure
results the way we are traditionally accustomed to do. Perhaps we are convinced that
land is the most limiting resource on small farms and that yield is measured only per unit
land area. Perhaps we have forgotten, or do not know that farmers have many priorities
and theirs may not coincide with ours.

Not all farms will adopt new technology

For whatever reasons, over this period of time, only a small fraction of our research and
technology development efforts have been oriented directly and adequately at
intensification of the still increasing numbers of small-scale, family farms with limited or
marginal resources. For forty years we have been convinced by Everett M. Rogers
(Diffusion of Innovations, 1962) that many farmers are slow adopters or even laggards or
non-adopters of new technological innovations. Because we believe our technology is
good we believe what Rogers tells us. We lean toward working with the "innovators" or
"early adopters" who are those who are most apt to adopt our technology. We feel it is
not our fault that some farmers do not adopt what we think is good technology.
Furthermore, it is not our fault that some farmers do not have access to credit nor the cash
resources to acquire our good technology or that it is not available in local markets. We
know that it takes time for the benefits of our technology to be understood and for
farmers to be "motivated" to adopt it (Hildebrand 1980). As a result, the research
impacts the relatively small number of larger farmers, or those small farmers in better
environments or with more resources, Figure 1, but does little or nothing for the very
large number of limited resource farmers at the bottom of the pyramid. We have taken
the easy road of asking those farmers with sufficient resources to change the environment
to suit the technology. Now it is time to accept the challenge of creating technology to

suit the diverse biophysical and socioeconomic environments of most of the world's
small farmers.

Higher More


Environmental 7Resources

Lower Less
Lower No. of Farmers Less

Figure 1. Farm resource diversity and relative numbers of farmers. (Hildebrand

Agricultural intensification on small farms
To effectively help intensify highly diverse small farm agriculture it is necessary to
comprehend the livelihood systems of these small farmers. A livelihood system is
comprised of all the on- and off-farm activities available to farmers in an area from which
they can select their strategies to survive and thrive. This includes not only all the crops
and livestock they raise, but different ways or times of raising them. Besides production
activities, it is also important to understand reproduction and community activities as
well because they also use scarce farm resources. Production activities are those that
result in the production of goods such as food (for consumption or sale), or cash.
Farming, fishing, carpentry, cottage industry, migrant work, paid labor, civil service, etc.
can be considered production activities whether on or off the farm. Reproduction
activities are those like maintenance and care of the family unit that result in the survival
and succession of the family or household. Meal preparation, hauling water or fuel,
childcare, laundry, house cleaning, re-roofing, house building (for family), or caring for
elderly or disabled are among reproduction activities. Community activities are more
difficult to quantify in terms of inputs and outputs, however they play a key role in
understanding how households and communities function. Community activities might
include: attending or organizing meetings; forming or participating in women's groups,
men's groups, children's groups, or producer groups; acting as part of a village or

community council; household food sharing; or the like. Seasonality of activities and
periods of cash or labor scarcities are important to understand as well as which of the
household members is involved in each activity.

Different households do not all adopt the same strategies. Livelihood strategies are a
function of the characteristics of the households such as wealth, sex of the household
head, relative age of the household and household composition (sex, age and relationship
of household members). Even though all households in a livelihood system have access
to all activities, the constraints and resources reflected in these characteristics cause the
members to choose different subsets of the activities as strategies. To effectively help all
these diverse households intensify production, it is critical to assess the capabilities of
each type of household in order to mold the technology to the needs and constraints of
each type.

But this sounds like anthropology. And everyone knows that anthropologists take years
to do their ethnographic studies in remote villages and then don't really want anyone or
anything to change "their" village. This is no longer the case. Many anthropologists
with solid agricultural backgrounds are productive members of multidisciplinary teams.
Also, many agronomists now have solid anthropological training. Incorporating these
kinds of scientists in teams working to intensify diverse small farm agriculture is highly
productive. Economists (heaven forbid!) with agronomic and/or anthropological training
can also be useful members of the team.

Modeling small-scale, limited-resource family farm livelihood systems, such as by
ethnographic linear programming (Bastidas; Breuer; Cabrera; Grier; Gough; Kaya; Kaya
et al.; Litow; Mudhara; Pomeroy; Sullivan; Thangata), is one effective way to integrate
crop, animal, anthropologic and economic knowledge gained through farmer
participation to help predict which households may be able to adopt different kinds of
new technologies even prior to their being offered to farmers in the community.5 These
models help us understand the kinds of technologies that are needed by the different types
of households in an area and thus can guide innovative thought into unique approaches to
agricultural intensification that can help even the poorest kinds of small farm households
survive and thrive.

Figure 2 represents a highly efficient and very effective methodology for incorporating
these different kinds of scientists in a participatory process with farmers that incorporates
diversity, both in problem or constraint assessment and in recommendations. With the
availability of laptop computers, it is now feasible for modelers to work in the field with
farmers in the process of creating, validating and using their models. When these models
are validated (adequately simulate the existing livelihood system), alternatives can be
pre-tested in the models, even while on-farm trials are being conducted, both to help
researchers better understand how the alternatives would fit into the strategies of the
different kinds of households, and to help characterize the recommendation domains for

5 See Hazell and Norton for details on linear programming. See Hildebrand, 2001, for details on
ethnographic linear programming. For examples of ethnographic linear programming see the other authors
listed above.

which the technologies are appropriate. The results of the on-farm trials and knowledge
gained from continuous contact with the farmers can be used to improve the ethnographic
linear programming models which should constantly be modified to make them even
more useful.

Figure 2. Schematic representation of the methodology for ex-ante evaluation of
potential technology, infrastructure or policy changes. (based on Bastidas, 2001)

It can be done

Miniaturizations of computer hardware, and advances in software have generated the
potential to create and use sophisticated models in the field while working with farmers
in their diverse environments in a participatory, ethnographic mode. We know these
methods work. Now is the time to put them all to work together. This will require
concerted, multidisciplinary efforts and the will to shed many approaches to which we
tend to cling. The remaining challenge is for research and extension personnel,
infrastructure managers and politicians to become innovative in their search for
technologies, infrastructure and policies specifically oriented to the still increasing
number of highly diverse, small-scale, limited resource, family farms in many countries
of the world including those in Latin America and the Caribbean.

Success (reaching poor farmers) will not be achieved either by applying modem science and
technology, on the one hand, or by implementing economic and social reform on the other, but
through a combination of these that is innovative and imaginative. (Conway p. 42).


American Society of Agronomy. 1976. Multiple cropping. ASA Special Publication
Number 27. Madison.

Bastidas, E.P. 2001. Assessing potential response to changes in the livelihood system of
diverse, limited-resource farm households in Carchi, Ecuador: modeling livelihood
strategies using participatory methods and linear programming. PhD dissertation, Food
and Resource Economics, University of Florida.

Breuer, N.E. 2000. The role of medicinal plants in rural Paraguayan livelihoods. M.A.
thesis, Latin American Studies, University of Florida.

Byerlee, D., L. Harrington and D.L. Winkelman. 1982. Farming systems research
strategy and technology design. American Journal of Agricultural Economics 64:899-

Cabrera, V.E. 1999. Farm problems, solutions, and extension programs for small
farmers in Caiiete, Lima, Peru. M.S. thesis, Agricultural Education and Communication,
Farming Systems Concentration, University of Florida.

Conway, G. 1997. The doubly green revolution. Cornell University Press, Ithaca.

FAOSTAT Agricultural Data. http://apps.fao.org/page/collections?subset=agriculture

Grier, C.E. 2002. Potential Impact of Improved Fallows on Small Farm Livelihoods,
Eastern Province, Zambia. M.S. thesis, Food and Resource Economics, University of

Gough, A.E. 2002. The Starter Pack Program in Malawi: Implications for Household
Food Security. M.S. thesis, Agricultural Education and Communication, Farming
Systems Concentration, University of Florida.

Hazell, P.B.R. and R.D. Norton, 1986. Mathematical programming for economic
analysis. Macmillan, New York.

Hildebrand, P.E. 1979. The ICTA farm record project with small farmers: four years of
experience. ICTA, Guatemala.6

Hildebrand, P.E. 1980. Motivating small farmers, scientists and technicians to accept
change. Agricultural Administration 8:375-383.

Hildebrand, P.E. 1981. Combining disciplines in rapid appraisal: The sondeo approach.
Agricultural Administration 8:423-432.

6 Also pp. 309-314 In: Shaner, W.W., Philipp, P.F. and W.R. Schmehl. 1982. Farming systems research
and development: guidelines for developing countries. Westview Press, Boulder.

Hildebrand, P.E. 1993. Targeting technology diffusion through coordinated on-farm
research. Presented at the Association for Farming Systems Research-Extension North
American Symposium on Systems Approaches in North American Agriculture and
Natural Resources: Broadening the Scope-ofFSRE. University of Florida.

Hildebrand, P.E. 2001. Ethnographic linear programming: limited-resource, family-farm
household models. Class handout. AEB 5167, Economic analysis in small farm
livelihood systems. Food and Resource Economics Department, University of Florida.

Kaya, B. 2000. Soil fertility regeneration through improved fallow systems in southern
Mali. PhD dissertation, Forest Resources and Conservation, University of Florida.

Kaya, B., P.E. Hildebrand and P.K. Nair. 2000. Modeling changes in farming systems
with adoption of improved fallows in southern Mali. Agricultural Systems 66: 51-68.

Litow, P.A. 2000. Food security and household livelihood strategies in the Maya
Biosphere Reserve: The importance ofmilpa in the community ofUaxactin, Pet6n,
Guatemala. M.S. thesis, Agricultural Education and Communication, Farming Systems
Concentration, University of Florida.

McDowell, R.E. and P.E. Hildebrand. 1980. Integrated crop and animal production:
Making the most of resources available to small farms in developing countries. A
Bellagio conference. The Rockefeller Foundation, New York.

Mudhara, M. 2002. Assessing the livelihood system of diverse smallholder farm
households: potential adoption of improved fallows in Zimbabwe. PhD dissertation,
Food and Resource Economics, University of Florida.

Pomeroy, C. 2000. An evaluation of a crop diversification project for low resource
hillside farmers in the Dominican Republic. M.S. thesis, Agricultural Education and
Communication, Farming Systems Concentration, University of Florida.

Poats, S.V., M. Schmink and A. Spring. 1988. Gender issues in farming systems
research and extension. Westview Press, Boulder.

Rogers, E.M. 1962. Diffusion of innovations. The Free Press, A Division of Macmillan
Publishing Co, Inc. New York.

Sullivan A.J. 2000. Decoding diversity: mitigating household stress. M.S. thesis,
Agricultural Education and Communication, Farming Systems Concentration, University
of Florida.

Thangata, P. 2002. The potential for agroforestry adoption and carbon sequestration in
smallholder agroecosystems of Malawi: an ethnographic linear programming approach.
PhD dissertation, Interdisciplinary Ecology, Natural Resources and Environment,
University of Florida.

University of Florida Home Page
© 2004 - 2010 University of Florida George A. Smathers Libraries.
All rights reserved.

Acceptable Use, Copyright, and Disclaimer Statement
Last updated October 10, 2010 - - mvs