Dicotyledon Weed Quantification Algorithm for Selective Herbicide Application in Maize Crops.
The stricter legislation within the European Union for the regulation of herbicides that are prone to leaching causes a greater economic burden on the agricultural industry through taxation. Owing to the increased economic burden, research in reducing herbicide usage has been prompted. High-resolution images from digital cameras support the studying of plant characteristics. These images can also be utilized to analyze shape and texture characteristics for weed identification. Instead of detecting weed patches, weed density can be estimated at a sub-patch level, through which even the identification of a single plant is possible. The aim of this study is to adapt the monocot and dicot coverage ratio vision (MoDiCoVi) algorithm to estimate dicotyledon leaf cover, perform grid spraying in real time, and present initial results in terms of potential herbicide savings in maize. The authors designed and executed an automated, large-scale field trial supported by the Armadillo autonomous tool carrier robot. The field trial consisted of 299 maize plots. Half of the plots (parcels) were planned with additional seeded weeds; the other half were planned with naturally occurring weeds. The in-situ evaluation showed that, compared to conventional broadcast spraying, the proposed method can reduce herbicide usage by 65% without measurable loss in biological effect.
Department of Engineering, Aarhus University, 8000 Aarhus, Denmark. msl@eng.au.dk.
Morten Stigaard
MS
Laursen
Department of Engineering, Aarhus University, 8000 Aarhus, Denmark. rnj@eng.au.dk.
Rasmus Nyholm
RN
Jørgensen
The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, 5230 Odense, Denmark. hemi@mmmi.sdu.dk.
Henrik Skov
HS
Midtiby
The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, 5230 Odense, Denmark. kjen@mmmi.sdu.dk.
Kjeld
K
Jensen
AGROINTELLI, 8200 Aarhus, Denmark. mpc@agrointelli.com.
Martin Peter
MP
Christiansen
Danish Technological Institute, Robot Technology, 5230 Odense, Denmark. tmg@teknologisk.dk.
Thomas Mosgaard
TM
Giselsson
Department of Agroecology-Crop Health, Aarhus University, 4200 Slagelse, Denmark. anmo@agro.au.dk.
Anders Krogh
AK
Mortensen
Department of Agroecology-Crop Health, Aarhus University, 4200 Slagelse, Denmark. pkj@agro.au.dk.
Peter Kryger
PK
Jensen
D000383:Agriculture; D000465:Algorithms; D018556:Crops, Agricultural / Q000737:chemistry; D006540:Herbicides / Q000032:analysis*; D018515:Plant Leaves / Q000737:chemistry; D003313:Zea mays / Q000737:chemistry
D006540:Herbicides
grid sprayer; herbicide reduction; monocot and dicot coverage ratio vision (MoDiCoVi); site specific; sprayer boom; weed crop discrimination