Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/20450
Title: Risk mapping of redheaded cockchafer ('Adoryphorus couloni') (Burmeister) infestations using a combination of novel k-means clustering and on-the-go plant and soil sensing technologies
Contributor(s): Cosby, Amy  (author); Falzon, Gregory  (author)orcid ; Trotter, M  (author); Stanley, John  (author); Powell, Kevin  (author); Lamb, David  (author)
Publication Date: 2016
DOI: 10.1007/s11119-015-9403-z
Handle Link: https://hdl.handle.net/1959.11/20450
Abstract: The ability to identify areas of pasture that are more likely to support damaging levels of the soil-borne, redheaded cockchafer ('Adoryphorus couloni') (Burmeister) (RHC) would allow farmers to target expensive control measures. This study explored soil properties, measured via electromagnetic surveys (EM38), pasture biomass via active optical sensors (CropCircle™) and topography via GPS elevation survey as potential indicators of RHC population density. A combination of these variables was used to produce risk maps with an accuracy of 88% at predicting likely RHC density-categories on a dairy property in the Gippsland region of Victoria, Australia. This risk mapping protocol could be used to improve sampling programs and direct site-specific pest management.
Publication Type: Journal Article
Source of Publication: Precision Agriculture, 17(1), p. 1-17
Publisher: Springer New York LLC
Place of Publication: United States of America
ISSN: 1573-1618
1385-2256
Field of Research (FOR): 070308 Crop and Pasture Protection (Pests, Diseases and Weeds)
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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Appears in Collections:Journal Article
School of Science and Technology

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