Data mining a new pilot agriculture extension data warehouse

Citation

Abdullah A & Hussain A (2006) Data mining a new pilot agriculture extension data warehouse. Journal of Research and Practice in Information Technology, 38 (3), pp. 229-248. https://www.acs.org.au/__data/assets/pdf_file/0015/15117/JRPIT38.3.229.pdf

Abstract
Pakistan is the world's fifth largest cotton producer. To monitor cotton growth, different government departments and agencies in Pakistan have been recording pest scouting, agriculture and metrological data for decades. Coarse estimates of just the cotton pest scouting data recorded stands at around 1.5 million records, and growing. The primary agro-met data recorded has never been digitized, integrated or standardized to give a complete picture, and hence cannot support decision making. In this paper, a complete life-cycle implementation of a novel Pilot Agriculture Extension Data Warehouse is discussed, followed by data analysis by querying the Data Warehouse and some interesting findings through data mining using an indigenous technique based on the crossing minimization paradigm. Actual cotton pest scouting data of 1,500+ farmers for years 2001 and 2002 for the Multan district was processed and used in the pilot project.

Keywords
Data Warehouse; Data Mining; Decision Support System; Agriculture; Cotton; Pest Scouting

Journal
Journal of Research and Practice in Information Technology: Volume 38, Issue 3