|Appears in Collections:||Computing Science and Mathematics Book Chapters and Sections|
|Peer Review Status:||Refereed|
|Title:||Analysis of pesticide application practices using an intelligent Agriculture Decision Support System (ADSS)|
|Citation:||Abdullah A, Hussain A & Barnawi A (2012) Analysis of pesticide application practices using an intelligent Agriculture Decision Support System (ADSS). In: Zhang H, Hussain A, Liu D, Wang Z (ed.). Advances in Brain Inspired Cognitive Systems: 5th International Conference, BICS 2012, Shenyang, China, July 11-14, 2012. Proceedings. Lecture Notes in Computer Science, 7366, Berlin Heidelberg: Springer, pp. 382-391.|
|Series/Report no.:||Lecture Notes in Computer Science, 7366|
|Abstract:||Pesticides are used for controlling pests, but at the same time they have impacts on the environment as well as the product itself. Although cotton covers 2.5% of the world's cultivated land yet uses 16% of the world's insecticides, more than any other single major crop . Pakistan is the world's fourth largest cotton producer and a major pesticide consumer. Numerous state run organizations have been monitoring the cotton crop for decades through pest-scouting, agriculture surveys and meteorological data-gatherings. This non-digitized, dirty and non-standardized data is of little use for strategic analysis and decision support. An advanced intelligent Agriculture Decision Support System (ADSS) is employed in an attempt to harness the semantic power of that data, by closely connecting visualization and data mining to each other in order to better realize the cognitive aspects of data mining. In this paper, we discuss the critical issue of handling data anomalies of pest scouting data for the six year period: 2001-2006. Using the ADSS it was found that the pesticides were not sprayed based on the pests crossing the critical population threshold, but were instead based on centuries old traditional agricultural significance of the weekday (Monday), thus resulting in non optimized pesticide usage, that can potentially reduce yield.|
|Rights:||The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.|
|Analysis of pesticide application practices.pdf||314.93 kB||Adobe PDF||Under Permanent Embargo Request a copy|
Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact firstname.lastname@example.org providing details and we will remove the Work from public display in STORRE and investigate your claim.