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Robust och kostnadseffektiv automatisering av mekanisk ogräsbekämpning i ekologisk sockerbetsodling

{Project} Robust och kostnadseffektiv automatisering av mekanisk ogräsbekämpning i ekologisk sockerbetsodling. [Robust and cost-effective automation of mechanical weed control for the cultivation of organically grown sugar beets.] Runs 2003 - 2005. Project Leader(s): Åstrand, Björn and Baerveldt, Albert-Jan, Halmstad University.

Full text not available from this repository.

Online at: http://www.hh.se/staff/bjorn/mech-weed/

Summary

Idag rensas ogräs för hand i KRAV-odlingen. Detta är relativt dyrt och det är svårt att hitta personer som vill utföra detta jobb. För att öka volymen behövs det en automatisering av den mekaniska ogräsbekämpningen i den ekologiska odlingen. Ett pågående forskningsprojekt, som finansieras av Formas och avslutas under 2003, syftar till att utveckla metoder för att kunna styra en maskin så att den kan rensa ogräs mekaniskt på egen hand med hjälp av en kamera som kan skilja mellan plantan och ogräs. Detta forskningsprojekt och dess resultat har rönt stort internationelt intresse. Målet med detta projekt är att uppnå en robust och kostnadseffektiv automatisering av mekanisk ogräsbekämpning för ekologisk odling av sockerbetor.

Summary translation

The world-wide problem of environmental pollution caused by excessive use of herbicides and the increasing cost of chemicals call for alternative methods for crop protection. A potential way to reduce chemicals is to employ precision techniques for various types of agricultural operations so that chemicals can be used where they have an optimal effect at a minimum quantity. It will even be possible in some operations to abandon the use of chemicals and apply other methods, e.g. mechanical weed control. There is political interest in the European Union in increasing the amount of ecologically grown products. The goal is that about 5-10% of the total field area should be processed by organic farming methods by the year 2005. Organic farming is not only a political goal; there is also a push from the market. More and more customers are asking for products that are organically grown. This has led to a problem for companies that need to increase their supplies of organically grown products to meet customer demands. For example, it is difficult to extend the amount of organically grown sugar beets at the present because weed control in the seed line of sugar beets is done by human labour, which implies high costs and difficulties in recruiting workers. The motivation for the work reported here is to reduce the amount of herbicides used for crop protection in agriculture by replacing chemical weed control by mechanical weed control. The elimination of chemical weed control is one of the requirements for a crop’s being "ecologically grown".
Goal
*Development of our previously developed methods for plant recognition for handle in-field and between-field variations, i.e. variations of plant properties (size, shape, color) and weed pressure.
*Research and development of a module for weed control that includes the weeding-tool and a plant identification system. The module could be attached to a row-cultivator or applied on an agricultural robot. A key component is the development of a special designed computer vision system that is cost-effective and powerful enough for the application.
Status
Our algorithms for plant identification has been implemented on a weeding-robot and tested under real field conditions. The method is sufficiently fast and robust for real-time control of intra-row weed-tool performing intra-row cultivation, able to identify 99% of the crops and remove about half of the intra-row weeds.

EPrint Type:Project description
Keywords:plant identification system, in-field and between-field variations, computer vision system
Subjects: Crop husbandry > Weed management
Farming Systems > Buildings and machinery
Research affiliation: Sweden > University of Halmstad
Research funders: Sweden > Swedish Farmers' Foundation for Agricultural Research SLF
Sweden > Swedish Board of Agriculture SJV
Location:Halmstad University
P.O. Box 823   
SE-301 18 Halmstad
bjorn.astrand@ide.hh.se
albert@ide.hh.se
Start Date:1 January 2003
End Date:31 December 2005
Deposited By: Fredriksson, Pelle
ID Code:7720
Deposited On:22 Feb 2008
Last Modified:20 Aug 2009 14:31

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