Abstract
Traditionally the agriculture expert's knowledge is descriptive and experimental, therefore, it is difficult to describe it mathematically and subsequently build agriculture Decision Support Systems (DSS). Furthermore, the corresponding data may be in such a raw form that it cannot be used in a DSS. The Agriculture Decision Support System (ADSS) is a 26-month project based on the Agro-met data from 2001 to 2006 of Punjab (the bread-basket of Pakistan), its ADSS-OLAP, i.e. Online Analytical Processing tool ( www.agroict-olap.org) allows for quick analysis of all possible interesting aggregates of the ADSS data by employing drag-drop and mouse-click and is used in this paper to identify the effective pesticide groups related to the mealybug incidence. Pakistan is the world's fifth-largest producer of cotton, but the emergence of the mealybug as a new cotton pest is likely to reduce the cotton yield by 1.3 million bales. The research work reported in this paper is based on the detailed pest-scouting data of 2300+ farmers of District Multan (cotton hub of Pakistan) for the years 2005 and 2006. This paper will also provide guidelines for the design and development of similar complex systems/tools and discusses the issues of agricultural data-quality management, particularly in the field of insect-pest management.
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