Clustering pests of rice using self organizing map

• Main Authors: Md. Sap, Mohd. Noor, Hasan, Shafaatunnur
• Format: Article
• Language: English
• Published: Penerbit UTM Press 2008
• Subjects: QA76 Computer software
• Online Access: http://eprints.utm.my/id/eprint/10755/1/MohdNoorMdSap2008_ClusteringPestsOfRiceUsingSelf.pdf; http://eprints.utm.my/id/eprint/10755/
• Institution: Universiti Teknologi Malaysia

Rice, Oryza sativa, also called paddy rice, common rice, lowland and upland.rice. This food grain is produced at least 95 countries around the globe, with China producing 36% of the world's production in 1999, followed by India at 21%, Indonesia at 8%, Bangladesh and Vietnam each producing about 5%. The United States produced about 1.5% of the world's accounts for about 15% of the annual world exports of rice. However the Modern agriculture is influenced by both the pressure for increased productivity and increased stresses caused by plant pests. Geographical Information Systems and Global Positioning Systems are currently being used for variable rate application of pesticides, herbicide and fertilizers in Precision Agriculture applications, but the comparatively lesserused tools of Neural Network can be of additional value in integrated pest management practices. This study details spatial analysis and clustering using Neural Network based on Kohonen Self Organizing map (SOM) as applied to integrated agricultural rice pest management in Malaysia.