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008			200731s2020 gw a o |||| 0|eng d
020			_a9783030444020
024	7		_a10.1007/978-3-030-44402-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aS494.5.I5 _b2020 EB
245	0	0	_aDecision Support Systems for Weed Management _cedited by Guillermo R. Chantre, José L. González-Andújar
250			_aFirst edition
264		1	_aCham _bImprint: Springer _c2020
264		1	_aCham _bSpringer International Publishing _c2020
300			_a1 recurso en línea (XII, 342 páginas) _b86 ilustraciones, 60 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aArchivo de texto _bPDF
490	0		_aBiomedical and Life Sciences (SpringerNature-11642)
490	0		_aBiomedical and Life Sciences (R0) (SpringerNature-43708)
505	0		_aSection 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			_aWeed 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.
988			_aSpringer_Biomedlife_03082020
650		7	_2embne _aAgricultura _xInnovaciones tecnológicas _9205076
700	1		_aChantre, Guillermo R. _eeditor literario _0(orcid)0000-0002-4424-0204 _1https://orcid.org/0000-0002-4424-0204 _4http://id.loc.gov/vocabulary/relators/edt _9675344
700	1		_aGonzález-Andújar, José L. _eeditor literario _0(orcid)0000-0003-2356-4098 _1https://orcid.org/0000-0003-2356-4098 _4http://id.loc.gov/vocabulary/relators/edt _9675345
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-44402-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b08/2020 _dz _ek _zSI