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A novel approach to estimating the competitive ability of Cirsium arvense in cereals using unmanned aerial vehicle imagery
Authors:J Rasmussen  J Nielsen
Institution:Department of Plant and Environmental Sciences, University of Copenhagen, Taastrup, Denmark
Abstract:Eight experiments were carried out in Denmark to determine the yield loss of spring barley due to Cirsium arvense in farmers' fields and to suggest and evaluate a novel approach for quantifying C. arvense infestation in large plots. Literature about the competitive ability of C. arvense is old, scattered and inconclusive, and existing models for estimating crop yield loss are based on data from North America. This study showed that C. arvense coverage could be quantified from unmanned aerial vehicle imagery using a manual image analysis procedure. This gave similar results as scoring the coverage. Yield loss of spring barley due to C. arvense infestation assessed at harvest was given by Y = 100·(1?exp(?0.00170·X)) where Y is the percentage of crop yield loss and X is the percentage of C. arvense coverage. The yield loss was much lower than estimates from models that have been developed in North America. It is speculated that the main reason for this is the later emergence of C. arvense than the crop due to lower soil temperatures in spring. Grain moisture increased linearly with C. arvense coverage: M = 0.0310·X where M is the proportional (%) increase in grain moisture and X is the proportion (%) of C. arvense coverage. Automated image analysis procedures are needed to estimate C. arvense coverage on field scales, and further experiments are needed to reveal whether the low competitive ability of C. arvense found in this study is representative for Northern Europe.
Keywords:site-specific weed management  economic threshold  perennial weeds  unmanned aerial vehicles  UAS  image analysis  UAV
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