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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
- Source :
- Precision Agriculture. 17:1-17
- Publication Year :
- 2015
- Publisher :
- Springer Science and Business Media LLC, 2015.
-
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 (CropCircleâ„¢) 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.
- Subjects :
- 0106 biological sciences
Hydrology
Integrated pest management
geography
Biomass (ecology)
geography.geographical_feature_category
Cockchafer
biology
k-means clustering
Sampling (statistics)
Forestry
04 agricultural and veterinary sciences
biology.organism_classification
01 natural sciences
Pasture
Population density
Risk mapping
040103 agronomy & agriculture
0401 agriculture, forestry, and fisheries
Environmental science
General Agricultural and Biological Sciences
010606 plant biology & botany
Subjects
Details
- ISSN :
- 15731618 and 13852256
- Volume :
- 17
- Database :
- OpenAIRE
- Journal :
- Precision Agriculture
- Accession number :
- edsair.doi...........30af42a6b12a8fef1fe871901acc7dd4