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Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/32857
Full metadata record
DC Field | Value | Language |
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dc.contributor.author | ICAR_CRIDA | en_US |
dc.date.accessioned | 2020-02-25T08:57:25Z | - |
dc.date.available | 2020-02-25T08:57:25Z | - |
dc.date.issued | 2006-01-01 | - |
dc.identifier.citation | Not Available | en_US |
dc.identifier.issn | Not Available | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/32857 | - |
dc.description | Not Available | en_US |
dc.description.abstract | Monitoring for pests is a fundamental fi rst step in creating a proper integrated pest management (IPM) programme. Pests are monitored through a variety of monitor ing tools such as pheromone traps, light traps, coloured sticky traps, pitfall traps and suction traps. The trap capture data serves several purposes: (i) ecological studies (Pathak, 1968; Crummayand Atkinson, 1997; Hirao et al., 2008); (ii) tracking insect migration (Drake et al., 2002); (iii) timing of pest arrivals into agroecosystems (Klueken et al., 2009); (iv) initiating fi eld scouting and sampling procedures; (v) timing of pesticide applications (Lewis, 1981; Merril et al., 2010); (vi) starting date or biofi x for phenology models (Knutson and Muegge, 2010); and (vii) prediction of later generations based on size of earlier generations (Zalucki and Furlong, 2005). Forecast for pests is an important component of the IPM strategy. Early warnings and forecasts based on biophysical methods provide lead time for managing impending pest attacks and can thus minimize crop loss, optimize pest control and reduce the cost of cultivation. Prevailing and anticipated weather information can help in crop planning and scheduling spray and farm operations to maximize crop yields and returns. Computer models have been developed to support various aspects of crop management in general and plant protection in particular and are widely in use in developed countries. A decision support system integrates a user-friendly front end to often complex models, know ledge bases, expert systems and database technologies. Decision support systems have emerged as essential tools to bridge the gap between sciencebased technology and end-users who make day-to-day management decisions. Webbased models and decision support systems are becoming popular and in future may become an abosolute requirement for local, regional/area-wide and international implement ation of IPM systems (Waheed et al., 2003). This chapter undertakes a selective review of published work on insect pest monitoring and forecasting and therefore is neither comprehensive nor exhaustive in its cover age | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | English | en_US |
dc.publisher | ICAR_CRIDA | en_US |
dc.relation.ispartofseries | Not Available; | - |
dc.subject | Pest forecasting,Trends,development,India | en_US |
dc.title | Pest forecasting Trends and development in India | en_US |
dc.title.alternative | Pest forecasting Trends and development in India | en_US |
dc.type | Book | en_US |
dc.publication.projectcode | Not Available | en_US |
dc.publication.journalname | Not Available | en_US |
dc.publication.volumeno | Not Available | en_US |
dc.publication.pagenumber | Not Available | en_US |
dc.publication.divisionUnit | Not Available | en_US |
dc.publication.sourceUrl | Not Available | en_US |
dc.publication.authorAffiliation | ICAR_CRIDA | en_US |
dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
Appears in Collections: | NRM-CRIDA-Publication |
Files in This Item:
File | Description | Size | Format | |
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Pest forecasting Trends and development in India.pdf | 196.93 kB | Adobe PDF | View/Open |
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