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Plant Disease Forecasting Systems : Procedure, Application and Prospect / by Dilip Kumar Chakrabarti, Prabhat Mittal

By: Chakrabarti, D. K.(Dilip Kumar), (1948-), autor
Contributor(s): Mittal, Prabhat, autor
Material type: materialTypeLabelE-bookPublisher: Singapore : Springer Nature Singapore , 2023Edition: 1st ed. 2023.Description: 1 recurso en línea.ISBN: 9789819912100.Subject: Patología vegetalOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
1. Historic Plant Disease Epidemics -- 2. Epidemic Factors -- 3. Predicting Variables. 4.Criteria to Develop Forecast -- 5. Modeling of Epidemic Dynamic -- 6. Decision Support Systems (DSSs) -- 7. Expert System -- 8. Geographic Information Systems: Web-Based Disease Forecasting -- 9. Decision Support Systems and Expert Systems: A Comparison -- 10. Forecasting in Changed Climate -- 11. Disease Detection: Imaging Technology and Remote Sensing -- 12. Classical Disease Forecasting Systems.
Summary: This book focus on creating popularity and interest in modeling, derivation of equations for plant disease forecasting or construction and use of Web-based Expert Systems among plant pathologists. This book covers descriptions of many historic plant disease epidemics, various forecasting systems and methods of their construction, instruments required for study of plant disease epidemics, widely used commercial forecasting systems and present global scenario of forecasting. In the human history plant disease epidemics have brought unsurmountable misery many a times. Still breaking out of epidemic in any time in any part of the world is a stark reality. The panic spraying of chemical pesticides is not a panacea. Only the IPM technology may give relief. This technology if backed by the disease forewarning system may yield the desired results. Hence, an in depth understanding of plant disease forecasting system and its successful implementation may bring the global food security. This title provides a useful background for all students, practitioners, and researchers interested in the field of epidemiology, food security and agriculture sciences. .
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería SB731 2023 EB (Browse shelf(Opens below)) Acceso electrónico ebook29022628
Total holds: 0

1. Historic Plant Disease Epidemics -- 2. Epidemic Factors -- 3. Predicting Variables. 4.Criteria to Develop Forecast -- 5. Modeling of Epidemic Dynamic -- 6. Decision Support Systems (DSSs) -- 7. Expert System -- 8. Geographic Information Systems: Web-Based Disease Forecasting -- 9. Decision Support Systems and Expert Systems: A Comparison -- 10. Forecasting in Changed Climate -- 11. Disease Detection: Imaging Technology and Remote Sensing -- 12. Classical Disease Forecasting Systems.

This book focus on creating popularity and interest in modeling, derivation of equations for plant disease forecasting or construction and use of Web-based Expert Systems among plant pathologists. This book covers descriptions of many historic plant disease epidemics, various forecasting systems and methods of their construction, instruments required for study of plant disease epidemics, widely used commercial forecasting systems and present global scenario of forecasting. In the human history plant disease epidemics have brought unsurmountable misery many a times. Still breaking out of epidemic in any time in any part of the world is a stark reality. The panic spraying of chemical pesticides is not a panacea. Only the IPM technology may give relief. This technology if backed by the disease forewarning system may yield the desired results. Hence, an in depth understanding of plant disease forecasting system and its successful implementation may bring the global food security. This title provides a useful background for all students, practitioners, and researchers interested in the field of epidemiology, food security and agriculture sciences. .

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