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An Imagery-Based Weed Cover Threshold Established Using Expert Knowledge

Published online by Cambridge University Press:  20 January 2017

Louis Longchamps ,
Bernard Panneton ,
Marie-Josée Simard  and
Gilles D. Leroux
Louis Longchamps*
Affiliation:
Department de Phytologie, Université Laval, Québec, Canada
Bernard Panneton
Affiliation:
Agriculture and Agri-Food Canada, Horticulture Research and Development Centre, Saint-Jean-sur-Richelieu, Canada
Marie-Josée Simard
Affiliation:
Agriculture and Agri-Food Canada, Soils and Crops Research and Development Center, Québec, Canada
Gilles D. Leroux
Affiliation:
Department de Phytologie, Université Laval, Québec, Canada
*
Corresponding author's E-mail: [email protected]
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Abstract

The implementation of site-specific weed management requires information about weed cover and decision support systems to determine weed cover thresholds and concomitant herbicide rates. Although it is possible to create accurate weed cover maps over large areas, weed cover thresholds have generally been evaluated using tedious weed density counts. To bridge this gap between weed cover obtained by machine vision and the concept of economic threshold, crop advisers specializing in weed scouting were asked to evaluate over 2,500 weed cover images (2 m by 3 m) and determine if a given image would require herbicide application or not. Using the area under the “receiver operating characteristic” curve method, an optimal weed cover threshold was established. The derived economic thresholds ranged from 0.06 to 0.31% weed cover contingent on the level of tolerance of the expert adviser. Although this threshold seems low, it is comparable with economic threshold values based on weed density.

Keywords

Economic thresholdimageryreceiver operating characteristicsite-specific weed management
Type
Weed Management
Information
Weed Science , Volume 62 , Issue 1 , March 2014 , pp. 177 - 185
Copyright
Copyright © Weed Science Society of America 

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