scholarly journals User's Guide for SeedCalc: A Decision-Support System for Integrated Pest Management in Slash Pine Seed Orchards

1996 ◽  
Author(s):  
Carl W. Fatzinger ◽  
Wayne N. Dixon
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Integrated Pest Management ◽  
Pest Management ◽  
Support System ◽  
Slash Pine ◽  
Seed Orchards

scholarly journals Information Tecnology Based Decision Support System for Integrated Pest Management on Rice

2021 ◽  
Vol 40 (1) ◽  
pp. 9
Author(s):  
I Nyoman Widiarta
Keyword(s):  
Information Technology ◽  
Decision Support ◽  
Decision Support System ◽  
Integrated Pest Management ◽  
Pest Management ◽  
Support System ◽  
Rice Yield ◽  
Sources Of Information ◽  
Control Techniques ◽  
Pests And Diseases

<p>Pest and disease are important biotic obstacles to increase rice yield and production in Indonesia since adoption of green revolution to increase rice yield. This is partly due to the irrational use of pesticides. This paper is a review on information technology (IT) based decision support system (DSSs) in line to the integrated pest management (IPM) implementation strategy for extensionists and farmers in the fields. IPM integrates compatible control techniques to manage pest populations below the economic injury level. IT based DSSs ultimately needed so that extension workers and farmers can quickly access sources of information about pests and diseases as well as prediction of development and control techniques to implement IPM. Web based DSSs to grow healthy rice plant, pest observation and monitoring, cyber extension to make famers an expert on IPM were available, except on how to identify and utilize natural enemies are still lacking. Indonesia need to develop more IT based DSSs which accessible on web as well as on smartphone and create enabling environment for improving IPM implementation on rice not only by officer but also gradually by farmers it self to control pests and diseases of rice which are still an obstacle in increasing production.</p><p>Keywords: Rice, pest, diseases, integrated pest management, information technology</p><p> </p><p><strong>Abstrak</strong></p><p>SISTEM PENDUKUNG PENGAMBILAN KEPUTUSAN HAMA TERPADU PADA TANAMAN PADI BE RPBEANSGIESNDALIAN TEKNOLOGI INFORMASI</p><p>Sejak inovasi revolusi hijau diintroduksikan di Indonesia, hama dan penyakit tanaman semakin berkembang sehingga menghambat upaya peningkatan produktivitas dan produksi padi. Hal ini antara lain disebabkan oleh penggunaan pestisida yang tidak rasional. Tulisan ini mengulas kesiapan sistem pendukung pengambilan keputusan (SPPK) berbasis teknologi informasi (TI) dalam pengendalian hama terpadu (PHT) oleh penyuluh maupun petani di lapangan. PHT mengintegrasikan berbagai teknik pengendalian hama dan penyakit agar tetap berada di bawah ambang ekonomi. TI diperlukan agar penyuluh dan petani dapat dengan cepat mengakses sumber informasi tentang jenis hama dan penyakit tanaman serta perkiraan perkembangan dan teknik pengendalian untuk penerapan PHT. SPPK berbasis TI yang bertujuan menjadikan tanaman tumbuh sehat, pengamatan dan monitoring perkembangan hama dan penyakit, serta penyuluhan berbasis web sudah tersedia, kecuali identifikasi dan cara pemanfaatan musuh alami. Oleh karena itu perlu dikembangkan SPPK berbasis TI yang dapat diakses melalui web maupun telepon pintar dan menciptakan lingkungan yang memungkinkan untuk meningkatkan implementasi PHT tidak hanya oleh petugas tetapi juga petani secara bertahap dalam upaya mengendalikan hama dan penyakit padi yang masih menjadi kendala dalam peningkatan produksi.</p><p>Kata kunci: Padi, hama, penyakit, pengendalian hama terpadu, teknologi informasi</p>

The white pine weevil in British Columbia: Basis for an integrated pest management system

1995 ◽  
Vol 71 (1) ◽  
pp. 66-73 ◽  
Author(s):  
Rene I. Alfaro ◽  
J. H. Borden ◽  
R. G. Fraser ◽  
A. Yanchuk
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Pest Management ◽  
Support System ◽  
Chemical Control ◽  
Genetic Resistance ◽  
White Pine ◽  
Pissodes Strobi ◽  
Pine Weevil ◽  
White Pine Weevil

Research programs to date in British Columbia on the biology, damage and control of the white pine weevil, Pissodes strobi (Peck), a pest of spruce, Picea spp. and pine, Pinus spp., are reviewed. Significant progress has been made in the areas of genetic resistance, silvicultural and chemical control. An integrated pest management (IPM) system is formulated which combines silviculture-driven and resistance-driven tactics. The system relies on accurate hazard rating of plantation sites and requires continuous monitoring of attack levels and the forecasting of plantation productivity under various IPM tactics through the use of a decision support system. Research needs which would increase effectiveness of the IPM system are reviewed and organized in the context of the plantation productivity cycle. Key words: insect control, Pissodes strobi, IPM, genetic resistance, silvicultural control, chemical control, decision support system

scholarly journals Autonomous Wireless Sensor Networks in an IPM Spatial Decision Support System

Computers ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 43 ◽  
Author(s):  
Mina Petrić ◽  
Jurgen Vandendriessche ◽  
Cedric Marsboom ◽  
Tom Matheussen ◽  
Els Ducheyne ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Decision Support ◽  
Sensor Networks ◽  
Decision Support System ◽  
Pest Management ◽  
Support System ◽  
Wireless Sensor ◽  
Spatial Decision Support System ◽  
Spatial Decision Support ◽  
Remote Areas

Until recently data acquisition in integrated pest management (IPM) relied on manual collection of both pest and environmental data. Autonomous wireless sensor networks (WSN) are providing a way forward by reducing the need for manual offload and maintenance; however, there is still a significant gap in pest management using WSN with most applications failing to provide a low-cost, autonomous monitoring system that can operate in remote areas. In this study, we investigate the feasibility of implementing a reliable, fully independent, low-power WSN that will provide high-resolution, near-real-time input to a spatial decision support system (SDSS), capturing the small-scale heterogeneity needed for intelligent IPM. The WSN hosts a dual-uplink taking advantage of both satellite and terrestrial communication. A set of tests were conducted to assess metrics such as signal strength, data transmission and bandwidth of the SatCom module as well as mesh configuration, energetic autonomy, point to point communication and data loss of the WSN nodes. Finally, we demonstrate the SDSS output from two vector models forced by WSN data from a field site in Belgium. We believe that this system can be a cost-effective solution for intelligent IPM in remote areas where there is no reliable terrestrial connection.

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