Decision Support Systems in Agriculture: Some Successes and a Bright Future - Efficient Decision Support Systems: Practice and Challenges from Current to Future - page 301

6.2.1 Goal
Develop an expert system comprised of multiple experts dealing with complex agricultural
problems.
6.2.2 Objectives
Capture the knowledge of various scientists working with the papaya ( Carica papaya )
tropical fruit.
6.2.3 Implementing language
Prolog declarative language. Arity Prolog®.
6.2.4 Successes
The Propa decision-aid illustrated that it was possible for a group of experts from various
disciplines to assess a case of a papaya problem and sort out which expert would be the
primary expert to solve the problem. This was achieved through the use of a monitor and
blackboard system that evaluated the interaction between the experts and the person with
the papaya problem information. Each expert was assigned a dynamic relevancy factor
which represented the success of their interaction with the papaya problem information.
The disciplines brought together for the problem-solving session included experts in 1)
Insect pests, 2) Nutrient management, 3) Disease identification, and 4) General management
and good practice (Itoga et al., 1990).
Propa was able to show the user images of the various insects to assist and confirm their
identification, which greatly assisted the insect expert's diagnosis and recommendation
process.
6.2.5 Disadvantages
Test runs of the final system with users indicated that they were often overwhelmed with
the number of technical questions that were asked of them by the group of experts. Many
users were not prepared to answer dozens of questions about the detailed appearance of the
plant and thus could not respond to the experts. When users could not respond to the
expert's questions the experts were no longer able to proceed with a diagnosis.
6.3 PDSS (phosphorus decision support system)
The PDSS system development began in 1990 (Yost et al., 1992a).
6.3.1 Goal
Capture the knowledge, including both successful practice and the supporting scientific
knowledge associated with the Diagnosis, Prediction, Economic Analysis, and
Recommendations associated with managing nutrient phosphorus (P) in tropical food
production systems.
6.3.2 Objectives
Capture a P management structure in a computer software decision-aid that would improve
the management of the nutrient P.