Using simulation models to investigate the cumulative effects of sowing rate, sowing date and cultivar choice on weed competitionAndrew, I. K. S. and Storkey, J. (2017) Using simulation models to investigate the cumulative effects of sowing rate, sowing date and cultivar choice on weed competition. Crop Protection, 95. pp. 109-115. ISSN 0261-2194
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1016/j.cropro.2016.05.002 Abstract/SummaryWith the increasing pressure on crop production from the evolution of herbicide resistance, farmers are increasingly adopting Integrated Weed Management (IWM) strategies to augment their weed control. These include measures to increase the competitiveness of the crop canopy such as increased sowing rate and the use of more competitive cultivars. While there are data on the relative impact of these non-chemical weed control methods assessed in isolation, there is uncertainty about their combined contribution, which may be hindering their adoption. In this article, the INTERCOM simulation model of crop / weed competition was used to examine the combined impact of crop density, sowing date and cultivar choice on the outcomes of competition between wheat (Triticum aestivum) and Alopecurus myosuroides. Alopecurus myosuroides is a problematic weed of cereal crops in North-Western Europe and the primary target for IWM in the UK because it has evolved resistance to a range of herbicides. The model was parameterised for two cultivars with contrasting competitive ability, and simulations run across 10 years at different crop densities and two sowing dates. The results suggest that sowing date, sowing density and cultivar choice largely work in a complementary fashion, allowing enhanced competitive ability against weeds when used in combination. However, the relative benefit of choosing a more competitive cultivar decreases at later sowing dates and higher crop densities. Modelling approaches could be further employed to examine the effectiveness of IWM, reducing the need for more expensive and cumbersome long-term in situ experimentation.
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