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Decision system in agricultural pest management

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Decision system in agricultural pest management/ by Ali Rajabpour, Fatemeh Yarahmadi.
作者:	Rajabpour, Ali.
其他作者:	Yarahmadi, Fatemeh.
出版者:	Singapore :Springer Nature Singapore : : 2024.,
面頁冊數:	xv, 353 p. :ill., digital ;24 cm.
內容註:	Chapter 1 - Introduction -- Chapter 2 - Population components of pests -- Chapter 3 - Monitoring and population density estimation -- Chapter 4 - Population fluctuations and dispersions -- Chapter 5 - Sampling program -- Chapter 6 - Decision-making levels -- Chapter 7 - Temperature-dependent models for predicting poikilotherm pest occurrence -- Chapter 8 - Biodiversity and pest outbreaks -- Chapter 9 - Remote Sensing, Geographic Information System (GIS) and Machine learning in the pest status monitoring.
Contained By:	Springer Nature eBook
標題:	Pests - Integrated control -
電子資源:	https://doi.org/10.1007/978-981-97-1506-0
ISBN:	9789819715060

Decision system in agricultural pest management
Rajabpour, Ali.

Decision system in agricultural pest management[electronic resource] /by Ali Rajabpour, Fatemeh Yarahmadi. - Singapore :Springer Nature Singapore :2024. - xv, 353 p. :ill., digital ;24 cm.

Chapter 1 - Introduction -- Chapter 2 - Population components of pests -- Chapter 3 - Monitoring and population density estimation -- Chapter 4 - Population fluctuations and dispersions -- Chapter 5 - Sampling program -- Chapter 6 - Decision-making levels -- Chapter 7 - Temperature-dependent models for predicting poikilotherm pest occurrence -- Chapter 8 - Biodiversity and pest outbreaks -- Chapter 9 - Remote Sensing, Geographic Information System (GIS) and Machine learning in the pest status monitoring.

This book covers the theoretical and practical aspects of pest population components, explaining the probable reasons for pest density fluctuations and outbreaks in agricultural or other ecosystems. Agricultural pest management is a complex task that involves dealing with a variety of pests, including insects, diseases, and weeds. Decision systems can help farmers navigate this complexity by providing structured approaches to identify, monitor, and control pests. By making informed decisions based on data and models, farmers can reduce unnecessary pesticide applications, minimizing environmental impact and saving costs. This book aids in predicting pest outbreaks using population growth parameters and estimating economic crop losses through critical thresholds, illustrated with simple case studies. Additionally, the book covers image processing, remote sensing monitoring, and other novel methods for monitoring and quickly forecasting pest population outbreaks to develop integrated pest management (IPM) programs. The book is valuable for agricultural and entomological students (graduates and postgraduates), researchers, as well as pest managers and farmers.

ISBN: 9789819715060

Standard No.: 10.1007/978-981-97-1506-0doiSubjects--Topical Terms:

3718395
Pests
--Integrated control

LC Class. No.: SB950

Dewey Class. No.: 632.9

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505 0 $a Chapter 1 - Introduction -- Chapter 2 - Population components of pests -- Chapter 3 - Monitoring and population density estimation -- Chapter 4 - Population fluctuations and dispersions -- Chapter 5 - Sampling program -- Chapter 6 - Decision-making levels -- Chapter 7 - Temperature-dependent models for predicting poikilotherm pest occurrence -- Chapter 8 - Biodiversity and pest outbreaks -- Chapter 9 - Remote Sensing, Geographic Information System (GIS) and Machine learning in the pest status monitoring.
520 $a This book covers the theoretical and practical aspects of pest population components, explaining the probable reasons for pest density fluctuations and outbreaks in agricultural or other ecosystems. Agricultural pest management is a complex task that involves dealing with a variety of pests, including insects, diseases, and weeds. Decision systems can help farmers navigate this complexity by providing structured approaches to identify, monitor, and control pests. By making informed decisions based on data and models, farmers can reduce unnecessary pesticide applications, minimizing environmental impact and saving costs. This book aids in predicting pest outbreaks using population growth parameters and estimating economic crop losses through critical thresholds, illustrated with simple case studies. Additionally, the book covers image processing, remote sensing monitoring, and other novel methods for monitoring and quickly forecasting pest population outbreaks to develop integrated pest management (IPM) programs. The book is valuable for agricultural and entomological students (graduates and postgraduates), researchers, as well as pest managers and farmers.
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