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Remote sensing to detect plant stress induced by Heterodera schachtii and Rhizoctonia solani in sugar beet fields
Authors:C Hillnhütter  A-K MahleinRA Sikora  E-C Oerke
Institution:Institute of Crop Science and Resource Conservation (INRES), Phytomedicine, Rheinische-Friedrich-Wilhelms-Universität Bonn, Nussallee 9, 53115 Bonn, Germany
Abstract:The characteristically clustered occurrence and low level of mobility of Heterodera schachtii and Rhizoctonia solani in the soil and the induction of stress symptoms in the sugar beet canopy make them ideal targets for site-specific arrangements with precision agriculture tools. A field site infested with H. schachtii and R. solani was investigated in 2009 with near-range and aerial hyperspectral sensors during the growing season. At 31 sample points ground truth data for incidence and severity of the two organisms were collected and geo-referenced. Spectral vegetation indices computed from reflectance measurements obtained from two flight campaigns (AISA, 17th of June; HyMap, 28th of August) and the near-range spectroradiometers were significantly correlated (P < 0.01) with symptoms caused by the nematode or Rhizoctonia crown and root rot. A supervised classification with Spectral Angle Mapper of leaf symptoms induced by the organisms resulted in a classification accuracy of 72 and 64% for the AISA and HyMap data, respectively. The results demonstrated that remote sensing in combination with geographic information system technologies can be used effectively for the detection and mapping of symptoms caused by beet cyst nematode and Rhizoctonia crown and root rot.
Keywords:BCN  beet cyst nematode  GIS  geographic information system  GS  growth stage  IDW  inverse distance weighting  NDVI  normalized differenced vegetation index  RCRR  Rhizoctonia crown and root rot  ROI  region of interest  SAM  Spectral Angle Mapper  SVIs  spectral vegetation indices  Pf  final nematode population  Pi  initial nematode population
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