Information Technology Reference
In-Depth Information
Fahmuddin Agus, Doctoral student, N. Carolina State University, and Centre for Soil and
Agroclimate Research and Development, Bogor, Indonesia. Tom Dierolf, Senior Scientist,
formerly of the Heifer International and International Consultant
Dan Gill, Doctoral student, N. Carolina State University.
Michael Wade, Senior Scientist, N. Carolina State University
Richard Kablan, Senior Research Associate, Department of Tropical Plant and Soil Science,
University of Hawai`i at Manoa, Honolulu, Hawai`i
This study was was made possible by the generous support of the American people through
the United States Agency for Development, International Development, under the terms of
Award No. LAG-G-00-97-00002-00. The opinions expressed herein are those of the authors
and do not necessarily reflect the views of the U.S. Agency for International Development.
6.11 Abstract
The application of Information Technology to agricultural knowledge in the form of
decision-support systems and decision-aids has already been successful and offers great
promise of more success in the future. This chapter will discuss the complex characteristics
of agricultural information and the challenges it presents to society and to Information
Technology (IT) to capture, organize, and disseminate this knowledge. Successes resulting
from the application of IT to agricultural knowledge are discussed. The challenging
characteristics of agricultural knowledge are that it is 1) Highly experiential and highly
situational, 2) Characterized by outcomes and results that are risky, uncertain, with many
events minimally predictable, 3) Interdisciplinary in nature, ranging from social sciences to
biology, chemistry, physics, and mathematics. That this knowledge has been an
extraordinary challenge for IT to capture is well-known and it is not surprising that new
methods, structures, and systems continue to be required to capture the information.
Agricultural knowledge remains in a much earlier more descriptive stage of development,
where personal observation and personal experience play a primary role in understanding
agriculture and attempts to control or manage it. It is the thesis of this chapter that
information technology can play a role in moving agriculture along to a more advanced
stage of development by recognizing consistent trends, patterns, rules of the trade, rules of
thumb and building upon such knowledge. Meta-analysis of the state of agricultural
knowledge should be encouraged as being helpful to the process. The understanding of the
causes of risk and uncertainty is relatively recent as are the benefits from systems studies
conducted at a relatively high level of abstraction. Some examples include the identification
of “tipping points” and their recognition in fragile ecosystems. Other aspects of the
mathematics of catastrophe theory seem to offer benefits of perspective and overview of
complex systems such as agriculture. The highly interdisciplinary nature of the knowledge,
while involving virtually the full range of human knowledge systems, goes well beyond the
scope of traditional biological, physical, and chemical disciplines. Of particular note is the
importance of social sciences in the understanding and in attempts to control and manage
real agricultural systems. As indicated, the need for decision-support systems to consider
the human element in observing, capturing, and delivering management expertise is well
known and several examples have been given. Preliminary exploratory decision-aids are
discussed and the results of the development effort are chronicled in this chapter. One
example depicts the capture for knowledge associated with the management of acid soils,
developed in the SE US, Central America, and South America, and enable its transfer and
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