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.
Auflage
Sprache
Verlagsort
Verlagsgruppe
Springer International Publishing
Zielgruppe
Illustrationen
60
26 s/w Abbildungen, 60 farbige Abbildungen
XII, 342 p. 86 illus., 60 illus. in color.
Maße
Höhe: 235 mm
Breite: 155 mm
Dicke: 20 mm
Gewicht
ISBN-13
978-3-030-44404-4 (9783030444044)
DOI
10.1007/978-3-030-44402-0
Schweitzer Klassifikation
Guillermo R. Chantre is an Associate Professor and Researcher in Weed Ecology at the Department of Agronomy of Universidad Nacional del Sur and CERZOS/CONICET (National Council of Scientific and Technological Research of Argentina). He specializes in weed ecophysiology, weed management and agricultural decision support systems. He is currently a member of the Advisory Board of the Socio-Technological Development Area for postgraduate scholarship grants at the National Council of Scientific and Technological Research of Argentina. He is also an advisor for technological scientific projects on agricultural systems and also serves as an external reviewer for several SCI journals.
Jose Luis Gonzalez-Andujar is a Senior Researcher at the Spanish Research Council (CSIC) and has research interests in weed ecology and weed management. Currently he is the leader of the Weed Agroecology group and Scientific Director of the International Laboratory on Global Change (LINCGlobal). He is a member of the editorial boards of Weed Research, PLOS ONE and Agronomia y Ambiente, having served in the past as Associated Editor of Communications in Biometry and Crop Science, member of the editorial advisory committees of Biometrics, Biometry Bulletin and Journal of Agricultural, Biological and Environmental Statistics. He was also President of the Spanish Weed Science Society, President and Past-President of the Latin-American Association of Weed Science, President and Vice-President of the Spanish Biometric Society and President of the Spanish Region of the International Biometric Society, Vice-president and Secretary of the Spanish Society of Information Technology in Agriculture and Forestry. He has received national and international awards and recognitions, including Honorary Member of the Weed Science Society of America (WSSA) and an ABULAC award for conservation agriculture.
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 IWMstrategies 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.
