Title: Adaptability analysis for diverse environments
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 Material Information
Title: Adaptability analysis for diverse environments
Physical Description: 11 leaves. : ill. ; 28 cm.
Language: English
Creator: Hildebrand, Peter E.
Russell, John T.
Donor: unknown ( endowment ) ( endowment )
Publication Date: 1994
Copyright Date: 1994
 Subjects
Subject: Agriculture -- Research -- Methodology   ( lcsh )
Agriculture -- Research -- On-farm -- Methodology   ( lcsh )
Genre: bibliography   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
non-fiction   ( marcgt )
 Notes
Statement of Responsibility: P.E. Hildebrand and J.T. Russell.
Bibliography: Includes bibliographical references (leaf 6).
General Note: Typescript.
General Note: Caption title.
General Note: "Prepared for presentation at the American Society of Agronomy Meetings, Seattle, Washington, Nov. 13-18, 1994."
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Bibliographic ID: UF00094283
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 - 434023166

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ADAPTABILITY ANALYSIS FOR
DIVERSE ENVIRONMENTS 1

P.E. Hildebrand and J.T. Russell2


The challenge of making small-farm agriculture more efficient i dificut, especially because it depends
on improving production from a large number of farms operating under a wide range of conditions,
constraints and objectives. The task is shared by many people, including farmers, policy makers and
academics, but an important part of the burden falls on agricultural reearcher and extension agents.
(Tripp, 1991, p. 3)

The Challenge

Worldwide, agricultural technology development is facing greater challenges.

World concerns with heavy use of inorganic chemicals associated with broadly
adaptable technologies force farmers and other agricultural researchers to look for
other means to improve productivity.

Farms and farmers are highly diverse, and whether commercial or subsistence,
farmers are facing ever-increasing economic stresses.

Potential alternative technologies are often quite location- and environment-specific
and may be more difficult to generate.

Budgets for agricultural research and technology diffusion are also becoming much
tighter.

For farmers, the technology challenge is to find new, useful, and tested technologies that
work for them under their conditions.

For public, private and non-governmental organizations, the technology challenge is to make
recommendations, specific to widely varying biophysical environments and socioeconomic
situations, both efficiently and economically and for as many conditions as possible.

Thus, with an increasingly difficult challenge and confronted with decreasing funding,
researchers, extension workers and farmers must search for more efficient and effective
means of finding new, acceptable technologies for diverse environments and socioeconomic
situations.



SPrepared for presentation at the American Society of Agronomy Meetings, Seattle, Washington, Nov. 13 18, 1994.

2 Professor and Visiting Professor, respectively, Pood and Resource Economics Department, Univerity of Florida,
Gainesville, FL 32611-0240.











Approaches

One approach being used with commercial farmers is to help them improve their own
experimental methods, so research they conduct on their own farms, based on accepted
experimental methods and a number of replications, provides more reliable results
(Rzewnicki et al., 1988; Illinois Sustainable Agriculture Network, 1992; Frantzen, 1992;
Rosmann, 1994).

This approach can provide farmers with information on responses to new technologies that
they are especially interested in and under their own specific conditions, but it must be
repeated over a number of years before farmers can have a reasonable assessment of its
performance over varying climatic conditions (Stucker and Hicks, 1992).

An alternative, and potentially much more efficient approach for farmers with similar
interests but with different situations, is to collaborate by selecting a common set of
treatments to be applied on their own farms and under their own management systems, each
applying a single replication, and then pooling the results for analysis and interpretation.

An effective procedure for design, analysis and interpretation of this kind of collaborative
technology development is the use of Adaptability Analysis (Hildebrand and Russell, 1994).

Adaptability Analysis is a new name applied to a procedure that many already know:
Modified Stability Analysis (Hildebrand, 1984). We have chosen to change the name
because of the confusion surrounding the concept of stability embedded in the older name.
The procedure, as we use it, is not related to stability but rather to adaptability of
technologies to different environments and socioeconomic conditions.

Adaptability Analysis has the potential not only to provide reliable results in fewer years for
the specific conditions of each collaborating farmer, but also to provide information that can
be extrapolated to a much wider number of farmers than just those participating in the trial.

Thus, it is more efficient and economic because:

Participating farmers manage fewer research plots,

Farmers contribute resources to collective research efforts,

Collaborating farmers obtain reliable results in fewer years, and

Returns for collaborating extension and research organizations are enhanced.


We use two examples to illustrate the procedure.










Bean Systems in Costa Rica

The first example comes from work Bellows did in Costa Rica (Bellows, 1992; Bellows, et
al., 1994). As part of an integrated study, an on-farm trial was conducted in nine
environments during the second growing season of 1990. This trial compared the traditional
bean production system (tapado), in which bean seed was broadcast into standing fallow
which was then cut down, with four introduced systems involving planting in rows (espeque).
Without going into detail because of time constraints, the four espeque systems were: 1)
land cleared manually (BARE), 2) natural residue mulching (MULCH), 3) mulching with
Gliricidia sepium (G SEP), and 4) land clearing residues placed in horizontal windows (W
ROW).

This particular trial was designed by the researcher in consultation with the farmers, so it
does not represent a true collaborative effort of a group of farmers. Nevertheless, the results
provide a useful example of the kinds of information that can be obtained from collaboration
with common treatments.

In Adaptability Analysis individual treatment yields are regressed on the mean treatment
yields (usually kg ha-1) at each location. The mean treatment yields provide a measure of the
quality of the environment at that location for the production of the crop (or other product)
being evaluated. This measure becomes an environmental index, EI, shown in Figure 1.

In the higher-yielding environments, land cleared manually (BARE) appears to yield more
than all other treatments. In the lower-yielding environments, G SEP or W ROW appeared
to yield more than the other treatments. In all environments, the traditional system, tapado,
yielded less than all espeque systems.

Of critical importance in interpreting these results is the characterization of the higher-
yielding and lower-yielding environments. It is clear from Figure 1 that the higher-yielding
environments correspond to fields which had been fallowed three or more years. These
environments also correspond to yields in the tapado system of more than 500 kg ha1. If a
farmer has access to such fields, and an appropriate criterion is kg ha~', then the bare field
system should be recommended. If only fields with fewer than three years of fallow are
available, where yields in the tapado system are probably less than 500 kg ha-1, then either
W ROW or G SEP treatments will provide the greatest yield.

Because the espeque systems use a full complement of fertilizers and pesticides compared
with the tapado system in which only a molluscacide is occasionally used, different results
are obtained when the criterion of kg $' of total cost is used, Figure 2. This criterion is
more appropriate to the small-scale bean farmers in Costa Rica (for whom cash is a scarcer
resource than land) than is kg ha1. Comparing the three treatments for which costs were
available shows that when farmers have access to land fallowed at least three years, (and for
which the anticipated yield of the tapado system would be > 500 kg ha'1) the tapado system
will be preferred and none of the espeque systems should be recommended. In land fallowed










less than three years, the natural mulch espeque system could be recommended. In no cases,
using the criterion of kg $', would the high-yielding BARE treatment be recommended to
farmers with scarce cash resources.


Table 1. Preliminary recommendations (extension messages) from bean
system on-farm trial, Costa Rica


Previous years in fallow
Criterion <3 3 or more

kg ha'- Gliricidia mulch Manual clearing
agronomicc) or
Windrows


kg $-' Natural Mulch Tapado
(small farmer)


Results from this trial should be considered preliminary because 1) there were only nine
environments and only three with three or more years in fallow, and 2) the range of Els is
small relative to the overall mean El (ratio < 1).


Dairy Systems in New York

A second example is from a dairy farm system trial in New York (Toomer and Emmick,
1989). In 1989, the New York Soil Conservation Service initiated a study to evaluate the
economic impact of changing to intensive pasturing systems on 15 New York dairy farms.
Before and after data were obtained from dairy producers who had recently developed
intensive pasturing systems and were reducing their use of confined feeding with harvested
feeds. The environmental index, EI, is based on fat-corrected (3.5%) milk production per
cow, a common dairy criterion.

Per cow milk production increased on those farms with low per cow production prior to the
change, but remained constant on the highest producing farms, Figure 3 (taken from
Hildebrand and Russell, 1994). Contrary to expectations, the high producing farms were not
using much pasture after the change, and still were relying on harvested feed. Cost per
animal decreased over all environments, Figure 4, and because production increased in most
environments, cost per CWT of milk decreased, Figure 5. Lowest costs per CWT of milk
were in the mid range environments, corresponding to the use of from about one to two acres
of pasture per animal after the change. Thus, heavy dependence on harvested feeds in










confinement with only about one-half acre of pasture per cow results in high production per
cow (Figure 3), but the use of one to two acres of pasture and a corresponding reduction in
harvested feed can lower cost of production per CWT of milk (Figure 5). The choice
depends on the goals of the individual farmers.

Although the number of farms (environments) included in this trial was more adequate than
the previous bean example, the relative homogeneity of the environments still limited the
range which was sampled. The ratio of the El range (based on CWT of milk/cow/year) to
the overall mean El is only slightly over 0.5. Based on our analysis of many data sets, we
posit that this ratio should be at least 1:1, implying that a much more heterogeneous sample
of farms should have been incorporated in this trial.

Summary

To use Adaptability Analysis, a set of common treatments must be installed on each
environment. One of the treatments should be the current practice of each collaborating
farmer so there is a basis of comparison. Individual farmers do not need to replicate the
common set of treatments on their own farms but can if analysis of treatment responses on
their own farms is of interest to them. Environments can be separate fields on a farm as
well as separate farms, or they can be whole farm systems as in the case of the dairy trial in
New York. The differences in management among farmers create differences in environment
and do not need to be controlled. The environments included in the trial should vary as
widely as possible. The number of environments that need to be included will vary
depending on a number of factors, but 15 to 20 should be adequate in most cases.

If the range and distribution of yields of the current practices approximates what would be
expected for the diverse environments over a period of years, the relationships among the
treatments should be stable if the trial is repeated or the results verified in a trial a second
year. The wider the range and the better the distribution of these yields, the more a set of
environments within a single year can substitute for multiple years.

Collaboration among farmers, by deciding on a common set of treatments, can improve both
efficiency and effectiveness of on-farm research by providing farmers useful and, tested
technologies in a relatively short period of time and with fewer of their own resources than if
they were to do the research on their own. Public, private and non-governmental
organizations working in technology development also benefit because they are able to make
recommendations for many more farmers than just those with whom they are working.










REFERENCES

Bellows, B.C. 1992. Sustainability of bean (Phaseolus Vulgaris L.) farming on steep lands
in Costa Rica: an agronomic and socioeconomic assessment. Ph.D. diss. Univ. of Florida,
Gainesville.

Bellows, B.C., P.E. Hildebrand, and D.H. Hubbell. 1994. Sustainability of bean
production systems on steep lands in Costa Rica. Agricultural Systems (accepted).

Frantzen, T.J. 1992. Farmer-first research methods: a success story from Iowa. p 12-15.
In Participatory on-farm research and education for agricultural sustainability. Proc.
Conference Univ. of llinois, July 30 August 1, 1992.

Hildebrand, P.E. 1984. Modified stability analysis of farmer managed, on-farm trials.
Agronomy Journal 76:271-274.

Hildebrand, P.E. and J.T. Russell. 1994. Adaptability analysis. Draft.

Illinois Sustainable Agriculture Network. 1992. 1992 on-farm participatory research
program. University of Illinois, Urbana.

Rosmann, R.L. 1994. Farmer initiated on-farm research. Amer. J. Alt. Agri. 9:34-37.

Rzewnicki, P.E., R. Thompson, G.W. Lesoing, R.W. Elmore, C.A. Francis, A.M.
Parkhurst, and R.S. Moomaw. 1988. On-farm experiment designs and implications for
locating research sites. Amer. J. Alt. Agr. 3:168-173.

Stucker, R.E. and D.H. Hicks. 1992. Some aspects of design and interpretation of row-
crop on-farm research. p 129-151. In Participatory on-farm research and education for
agricultural sustainability. Proc. Conference Univ. of Illinois, July 30 August 1, 1992.

Toomer, L. and D.L. Emmick. 1989. The economics of intensive grazing on fifteen dairy
farms in New York state 1989. Soil Conservation Service, Syracuse, N.Y.

Tripp, R. 1991. Planned change in farming systems: progress in on-farm research. John
Wiley and Sons, New York.


W07/a94













1,300 o I4
BARE
1,200 11- 1- s
MULCH / 3.5
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1,000- TAP" ' .* 3
** * 0
0 *
900 ww *- .51

800 z
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400
0.5
300

200 I I 0
500 600 700 800 900 1000
ENVIRONMENTAL INDEX, El


Figure 1. Bean yield (kg ha"1) response of four espeque treatments and tapado to
environment on steep land in Costa Rica.












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BARE YRS
5 B3.5
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3.5 mmm-
TAP 3


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ENVIRONMENTAL INDEX, El



Figure 2. Bean response (kg $-' total cost) of two espeque treatments and tapado to
environment on steep land in Costa Rica.












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ENVIRONMENTAL INDEX,


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Figure 3. Response of per cow milk production to environment before and after change
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Figure 4. Cost per animal before and after change, New York dairy systems.






























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Figure 5. Cost per CWT milk before and after change, New York dairy systems.


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