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Decision support systems for weed ma...

Chantre, Guillermo R.

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Decision support systems for weed management

Record Type:	Electronic resources : Monograph/item
Title/Author:	Decision support systems for weed management/ edited by Guillermo R. Chantre, Jose L. Gonzalez-Andujar.
other author:	Chantre, Guillermo R.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	xii, 342 p. :ill., digital ;24 cm.
[NT 15003449]:	Section I - MODELLING IN WEED SCIENCE -- Chapter 1 - Mathematical models -- Chapter 2 - Decision Support Systems in Weed Science -- Chapter 3 - Optimization in DSS -- Section II - BIO-ECOLOGICAL MODELS -- Chapter 4 - Population-based models -- Chapter 5 - Weed germination and dormancy models -- Chapter 6 - Field Emergence models -- Chapter 7 - Interference/Competition models -- Chapter 8 - Herbicide resistance modelling -- Section III - ENVIRONMENTAL RISK MODELLING -- Chapter 9 - Theory and practice for environmental risk assessment of weed management systems -- Chapter 10 - Environmental risk indicators for weed management assessment: a case study of ecotoxicity risk using fuzzy logic -- Chapter 11 - DRASTIC GIS-based models: assessing the vulnerability of groundwater resources -- Section IV - WEED MANAGEMENT DECISION SUPPORT SYSTEMS: STUDY CASES -- Chapter 12 - FLORSYS model: How to use a virtual field to evaluate and design IWM strategies at different spatial and temporal scales -- Chapter 13 - Ryegrass Integrated Management (RIM)-based DSS -- Chapter 14 - CPOweeds: DSS for multispecies weed control in cereals crops -- Chapter 15 - AVENA-NET/LOLIUM-NET: DSS for Avena sterilis and Lolium rigidum control in cereal crops -- Chapter 16 - AVESUD: DSS for Avena fatua control in winter cereal crop rotations -- Chapter 17 - DSS Perspectives, Challenges and Future work.
Contained By:	Springer Nature eBook
Subject:	Weeds - Control. -
Online resource:	https://doi.org/10.1007/978-3-030-44402-0
ISBN:	9783030444020

Decision support systems for weed management
Decision support systems for weed management[electronic resource] /edited by Guillermo R. Chantre, Jose L. Gonzalez-Andujar. - Cham :Springer International Publishing :2020. - xii, 342 p. :ill., digital ;24 cm.

Section I - MODELLING IN WEED SCIENCE -- Chapter 1 - Mathematical models -- Chapter 2 - Decision Support Systems in Weed Science -- Chapter 3 - Optimization in DSS -- Section II - BIO-ECOLOGICAL MODELS -- Chapter 4 - Population-based models -- Chapter 5 - Weed germination and dormancy models -- Chapter 6 - Field Emergence models -- Chapter 7 - Interference/Competition models -- Chapter 8 - Herbicide resistance modelling -- Section III - ENVIRONMENTAL RISK MODELLING -- Chapter 9 - Theory and practice for environmental risk assessment of weed management systems -- Chapter 10 - Environmental risk indicators for weed management assessment: a case study of ecotoxicity risk using fuzzy logic -- Chapter 11 - DRASTIC GIS-based models: assessing the vulnerability of groundwater resources -- Section IV - WEED MANAGEMENT DECISION SUPPORT SYSTEMS: STUDY CASES -- Chapter 12 - FLORSYS model: How to use a virtual field to evaluate and design IWM strategies at different spatial and temporal scales -- Chapter 13 - Ryegrass Integrated Management (RIM)-based DSS -- Chapter 14 - CPOweeds: DSS for multispecies weed control in cereals crops -- Chapter 15 - AVENA-NET/LOLIUM-NET: DSS for Avena sterilis and Lolium rigidum control in cereal crops -- Chapter 16 - AVESUD: DSS for Avena fatua control in winter cereal crop rotations -- Chapter 17 - DSS Perspectives, Challenges and Future work.

Weed management Decision Support Systems (DSS) are increasingly important computer-based tools for modern agriculture. Nowadays, extensive agriculture has become highly dependent on external inputs and both economic costs, as well the negative environmental impact of agricultural activities, demands knowledge-based technology for the optimization and protection of non-renewable resources. In this context, weed management strategies should aim to maximize economic profit by preserving and enhancing agricultural systems. Although previous contributions focusing on weed biology and weed management provide valuable insight on many aspects of weed species ecology and practical guides for weed control, no attempts have been made to highlight the forthcoming importance of DSS in weed management. This book is a first attempt to integrate 'concepts and practice' providing a novel guide to the state-of-art of DSS and the future prospects which hopefully would be of interest to higher-level students, academics and professionals in related areas.

ISBN: 9783030444020

Standard No.: 10.1007/978-3-030-44402-0doiSubjects--Topical Terms:

544956
Weeds
--Control.

LC Class. No.: SB611 / .D43 2020

Dewey Class. No.: 632.5

Decision support systems for weed management
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245 0 0 $a Decision support systems for weed management $h [electronic resource] / $c edited by Guillermo R. Chantre, Jose L. Gonzalez-Andujar.
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505 0 $a Section I - MODELLING IN WEED SCIENCE -- Chapter 1 - Mathematical models -- Chapter 2 - Decision Support Systems in Weed Science -- Chapter 3 - Optimization in DSS -- Section II - BIO-ECOLOGICAL MODELS -- Chapter 4 - Population-based models -- Chapter 5 - Weed germination and dormancy models -- Chapter 6 - Field Emergence models -- Chapter 7 - Interference/Competition models -- Chapter 8 - Herbicide resistance modelling -- Section III - ENVIRONMENTAL RISK MODELLING -- Chapter 9 - Theory and practice for environmental risk assessment of weed management systems -- Chapter 10 - Environmental risk indicators for weed management assessment: a case study of ecotoxicity risk using fuzzy logic -- Chapter 11 - DRASTIC GIS-based models: assessing the vulnerability of groundwater resources -- Section IV - WEED MANAGEMENT DECISION SUPPORT SYSTEMS: STUDY CASES -- Chapter 12 - FLORSYS model: How to use a virtual field to evaluate and design IWM strategies at different spatial and temporal scales -- Chapter 13 - Ryegrass Integrated Management (RIM)-based DSS -- Chapter 14 - CPOweeds: DSS for multispecies weed control in cereals crops -- Chapter 15 - AVENA-NET/LOLIUM-NET: DSS for Avena sterilis and Lolium rigidum control in cereal crops -- Chapter 16 - AVESUD: DSS for Avena fatua control in winter cereal crop rotations -- Chapter 17 - DSS Perspectives, Challenges and Future work.
520 $a Weed management Decision Support Systems (DSS) are increasingly important computer-based tools for modern agriculture. Nowadays, extensive agriculture has become highly dependent on external inputs and both economic costs, as well the negative environmental impact of agricultural activities, demands knowledge-based technology for the optimization and protection of non-renewable resources. In this context, weed management strategies should aim to maximize economic profit by preserving and enhancing agricultural systems. Although previous contributions focusing on weed biology and weed management provide valuable insight on many aspects of weed species ecology and practical guides for weed control, no attempts have been made to highlight the forthcoming importance of DSS in weed management. This book is a first attempt to integrate 'concepts and practice' providing a novel guide to the state-of-art of DSS and the future prospects which hopefully would be of interest to higher-level students, academics and professionals in related areas.
650 0 $a Weeds $x Control. $3 544956
650 0 $a Decision support systems. $3 545674
650 1 4 $a Agriculture. $3 518588
650 2 4 $a Monitoring/Environmental Analysis. $3 3135580
650 2 4 $a Computer-Aided Engineering (CAD, CAE) and Design. $3 892568
650 2 4 $a Computational Biology/Bioinformatics. $3 898313
650 2 4 $a Simulation and Modeling. $3 890873
700 1 $a Chantre, Guillermo R. $3 3460781
700 1 $a Gonzalez-Andujar, Jose L. $3 3460782
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856 4 0 $u https://doi.org/10.1007/978-3-030-44402-0
950 $a Biomedical and Life Sciences (SpringerNature-11642)