A - Papers appearing in refereed journals
Bagavathiannan, M. V., Beckie, H. J., Chantre, G. R., Gonzalez-Andujar, J. L., Leon, R. G., Neve, P., Poggio, S. L., Schutte, B. J., Somerville, G., Werle, R. and Van Acker, R. 2020. Simulation Models on the Ecology and Management of Arable Weeds: Structure, Quantitative Insights, and Applications. Agronomy. 10, p. 1611. https://doi.org/10.3390/agronomy10101611
Authors | Bagavathiannan, M. V., Beckie, H. J., Chantre, G. R., Gonzalez-Andujar, J. L., Leon, R. G., Neve, P., Poggio, S. L., Schutte, B. J., Somerville, G., Werle, R. and Van Acker, R. |
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Abstract | In weed science and management, models are important and can be used to betterunderstand what has occurred in management scenarios, to predict what will happen and to evaluatethe outcomes of control methods. To-date, perspectives on and the understanding of weed modelshave been disjointed, especially in terms of how they have been applied to advance weed scienceand management. This paper presents a general overview of the nature and application of a fullrange of simulation models on the ecology, biology, and management of arable weeds, and howthey have been used to provide insights and directions for decision making when long-term weedpopulation trajectories are impractical to be determined using field experimentation. While researchon weed biology and ecology has gained momentum over the past four decades, especially for specieswith high risk for herbicide resistance evolution, knowledge gaps still exist for several life cycleparameters for many agriculturally important weed species. More research efforts should be investedin filling these knowledge gaps, which will lead to better models and ultimately better inform weedmanagement decision making |
Keywords | Weed seedling emergence; Geneflow; Crop-weed competition; Weed population dynamics; Herbicide resistance; Decision-support tools; Predictive models |
Year of Publication | 2020 |
Journal | Agronomy |
Journal citation | 10, p. 1611 |
Digital Object Identifier (DOI) | https://doi.org/10.3390/agronomy10101611 |
Open access | Published as ‘gold’ (paid) open access |
Funder | Biotechnology and Biological Sciences Research Council |
Global Challenges Research Fund (UKRI) | |
Funder project or code | BB/S014683/1 |
Publisher's version | |
Output status | Published |
Publication dates | |
Online | 21 Oct 2020 |
Publication process dates | |
Accepted | 14 Oct 2020 |
ISSN | 2073-4395 |
Publisher | MDPI |
Permalink - https://repository.rothamsted.ac.uk/item/98272/simulation-models-on-the-ecology-and-management-of-arable-weeds-structure-quantitative-insights-and-applications