Weed Science (2016) 64, 474-485
Louis Longchamps, Bernard Panneton, Robin Reich, Marie-Josée Simard and Gilles D. Leroux (2016)
Spatial pattern of weeds based on multispecies infestation maps created by imagery
Weed Science 64 (3), 474-485
Abstract: Weeds are often spatially aggregated in maize fields, and the level of aggregation varies across and within fields. Several annual weed species are present in maize fields before postemergence herbicide application, and herbicides applied will control several species at a time. The goal of this study was to assess the spatial distribution of multispecies weed infestation in maize fields. Ground-based imagery was used to map weed infestations in rain-fed maize fields. Image segmentation was used to extract weed cover information from geocoded images, and an expert-based threshold of 0.102% weed cover was used to generate maps of weed presence/absence. From 19 site-years, 13 (68%) demonstrated a random spatial distribution, whereas six site-years demonstrated an aggregated spatial pattern of either monocotyledons, dicotyledons, or both groups. The results of this study indicated that monocotyledonous and dicotyledonous weed groups were not spatially segregated, but discriminating these weed groups slightly increased the chances of detecting an aggregated pattern. It was concluded that weeds were not always spatially aggregated in maize fields. These findings emphasize the need for techniques allowing the assessment of weed aggregation prior to conducting site-specific weed management.
(The abstract is excluded from the Creative Commons licence and has been copied with permission by the publisher.)
Link to article at publishers website
Database assignments for author(s): Louis Longchamps, Marie-Josée Simard, Gilles D. Leroux
Research topic(s) for pests/diseases/weeds:
surveys/sampling/distribution
