Decision support system in agriculture

Muhamad Radzali MispanMARDI

radzali@mardi.gov.my

Introduction Decision makers are faced with increasingly stressful

environments – highly competitive, fast-paced, near real-time, overloaded with information, data distributed throughout the enterprise, and multinational in scope.

The combination of the Internet enabling speed and access, and the maturation of artificial intelligence techniques, has led to sophisticated aids to support decision making under these risky and uncertain conditions.

These aids have the potential to improve decision making by suggesting solutions that are better than those made by the human alone.

They are increasingly available in diverse fields from medical diagnosis to traffic control to engineering applications.

Decision Support SystemA Decision Support System (DSS) is an interactive

computer-based system or subsystem intended to help decision makers use communications technologies, data, documents, knowledge and/or models to identify and solve problems, complete decision process tasks, and make decisions.

Decision Support System is a general term for any computer application that enhances a person or group’s ability to make decisions.

These tools improve the performance of decision makers while reducing the time and human resources required for analyzing complex decisions

Spatial decision support system (SDDS)Spatial Decision Support Systems (SDSS) deals with spatial

dimension through digitized geo-referenced spatial databases. Agriculture is essentially a spatial phenomenon which is not

independent of location. GIS is the tool and technology that handles various spatial databases,

This spatial information technology allows to examine and analyze a wider range of agricultural related resources such as soil, weather, hydrology, various socio-economic variables simultaneously and accurately.

Simultaneous examination of these variables in a GIS environment leads to a better understanding of how agricultural systems function and interact over space and time.

This understanding leads to developing stable and sustainable dynamic agricultural technologies.

Agro-ecological zoning and land use optimization

Hardcopy and qualitative

Difficult to maintain/update, exchange and integrate with other data source

Only covers Peninsular Malaysia with limited observation points and durations

Only dealt with land areas below 300 m ASL

Incompatible data format and structures

Limited observation

A new approach in AEZ

but modify according to

local requirements

M

Examples of SDDS

Nutrient mapTreatment map