Decision Support Systems in Agriculture: Some Successes and a Bright Future - Efficient Decision Support Systems: Practice and Challenges from Current to Future - page 310

Economic Analysis, and Recommendation) identifies major components in the decision-
making process and helps the user step through the process.
Developing a tool that predicts actual quantities of fertilizer needed given specified data
illustrates that multiple disciplines can contribute to solutions in a systematic, synergistic
way provided a common language is used. Is it true that computer-based knowledge
systems can better accommodate and use multiple disciplines than humans?
A structure was proposed that enabled a monitor to guide and organize a multidisciplinary
search to solve an unidentified problem in papaya problem diagnosis.
The calculation of propagated error in the prediction of fertilizer quantity at approximately
50% illustrates that despite attempts to achieve highly precise estimates in agronomic
research, the results need improvement to better support economic and environmental
objectives. The calculation of propagated error identified the variables most contributing to
error. These variables became objectives for research to improve prediction accuracy and
precision.
Conducting research to produce a knowledge module provided a clear, stimulating
objective and resulted in high quality, problem-driven, and yet rewarding research.
The meta-analysis of the decision-making process and surveys of the users resulted in the
identification of knowledge gaps that, in turn, resulted in numerous educational
opportunities for young scientists. They conducted their research knowing that the results of
their work would fill a gap in a working knowledge-base. The following scientists
completed dissertations and Ph.D. degrees during this work (Gill, 1988; Evensen 1989; Agus
1997); Deenik, 2000; Diarra et al., 2004; Dierolf et al., 1999; Nilawonk et al., 2008; Sipaseuth et
al., 2007; Yampracha et al., 2005).
6.4 NuMaSS (nutrient management support system)
The NuMaSS Project was designed to join the individually developed decision-aids ADSS
and PDSS, with a new system to be adapted from a nitrogen decision-aid (Osmond et al.,
2000).
6.4.1 Goal
The NuMaSS Project was developed to integrate and disseminate decision-aid tools that
diagnose soil nutrient constraints and select appropriate management practices for location-
specific conditions. The strategy was to develop globally applicable, largely computer-
assisted, integrated decision-aids that could both diagnose and prescribe appropriate
solutions to soil nutrient constraints.
6.4.2 Objectives
The Project had three objectives 1) Improve the diagnosis and recommendations for soil
acidity and nutrient problems. 2) Develop an integrated computerized knowledge-base, and
3) Develop auxiliary tools resulting from the integrated knowledge-base to assist producers
to diagnose and solve soil acidity and nutrient constraints.
6.4.3 Implementing language
The rapid application development package Delphi ® , which was a Pascal-based
development environment.