Herbicide resistance modelling: past, present and future
| Autor: | Martin M. Vila-Aiub, David Thornby, Michael Renton, Roberto Busi, Paul Neve |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Computer science
Evolution Weed Control Population alopecurus-myosuroides Population Dynamics Integration Plant Weeds integration Insecticide Resistance Ciencias Biológicas Computer Herbicide resistance amaranthus-palmeri Genetics Computer Simulation education lolium-rigidum rapid evolution computer education.field_of_study Herbicides Simulation modelling population-dynamics General Medicine Ecología Cropping Systems Biological Evolution Risk analysis (engineering) integrated weed management Insect Science simulating evolution Agronomy and Crop Science glyphosate resistance Simulation CIENCIAS NATURALES Y EXACTAS Herbicide Resistance |
| Popis: | Computer simulation modelling is an essential aid in building an integrated understanding of how different factors interact to affect the evolutionary and population dynamics of herbicide resistance, and thus helps in predicting and managing how agricultural systemswill beaffected. In this review,why computer simulation modelling is such animportant tool and framework for dealingwith herbicide resistance is first discussed. The questions related to herbicide resistance that have been addressed to date using simulation modelling are then explained, and the modelling approaches that have been used are discussed, focusing first on the earlier, more general approaches, and then on some newer, more innovative approaches. How these approaches could be further developed in the future, by drawing on modelling techniques that are already employed in other areas, such as individual-based and spatially explicit modelling approaches, is then considered, aswell as the possibility of better representing genetics, competition and economics, and finally the questions and issues of importance to herbicide resistance research and management that could be addressed using these new approaches are discussed. It is concluded that it is necessary to proceed with cautionwhen increasing the complexity of models by adding newdetails, but,with appropriate care, more detailed models will make it possible to integrate more current knowledge in order better to understand, predict and ultimately manage the evolution of herbicide resistance. Fil: Renton, Michael. University of Western Australia. Australian Herbicide Resistance Initiative and Institute of Agriculture. School of Plant Biology; Australia Fil: Busi, Roberto. University of Western Australia. Australian Herbicide Resistance Initiative and Institute of Agriculture. School of Plant Biology; Australia Fil: Neve, Paul. University of Warwick. School of Life Sciences; Reino Unido Fil: Thornby, David. Queensland Department of Agriculture, Fisheries and Forestry; Australia Fil: Vila Aiub, Martin Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina. University of Western Australia. Australian Herbicide Resistance Initiative and Institute of Agriculture. School of Plant Biology; Australia |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|