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Proceedings Paper

Comparison of multi- and hyperspectral imaging data of leaf rust infected wheat plants
Author(s): Jonas Franke; Gunter Menz; Erich-Christian Oerke; Uwe Rascher
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Paper Abstract

In the context of precision agriculture, several recent studies have focused on detecting crop stress caused by pathogenic fungi. For this purpose, several sensor systems have been used to develop in-field-detection systems or to test possible applications of remote sensing. The objective of this research was to evaluate the potential of different sensor systems for multitemporal monitoring of leaf rust (puccinia recondita) infected wheat crops, with the aim of early detection of infected stands. A comparison between a hyperspectral (120 spectral bands) and a multispectral (3 spectral bands) imaging system shows the benefits and limitations of each approach. Reflectance data of leaf rust infected and fungicide treated control wheat stand boxes (1sqm each) were collected before and until 17 days after inoculation. Plants were grown under controlled conditions in the greenhouse and measurements were taken under consistent illumination conditions. The results of mixture tuned matched filtering analysis showed the suitability of hyperspectral data for early discrimination of leaf rust infected wheat crops due to their higher spectral sensitivity. Five days after inoculation leaf rust infected leaves were detected, although only slight visual symptoms appeared. A clear discrimination between infected and control stands was possible. Multispectral data showed a higher sensitivity to external factors like illumination conditions, causing poor classification accuracy. Nevertheless, if these factors could get under control, even multispectral data may serve a good indicator for infection severity.

Paper Details

Date Published: 19 October 2005
PDF: 11 pages
Proc. SPIE 5976, Remote Sensing for Agriculture, Ecosystems, and Hydrology VII, 59761D (19 October 2005); doi: 10.1117/12.626531
Show Author Affiliations
Jonas Franke, Ctr. for Remote Sensing of Land Surfaces (Germany)
Gunter Menz, Ctr. for Remote Sensing of Land Surfaces (Germany)
Univ. Bonn (Germany)
Erich-Christian Oerke, Univ. Bonn (Germany)
Uwe Rascher, Research Ctr. Jülich (Germany)

Published in SPIE Proceedings Vol. 5976:
Remote Sensing for Agriculture, Ecosystems, and Hydrology VII
Manfred Owe; Guido D'Urso, Editor(s)

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