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Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases
Hyperspectral imaging (HSI) offers high potential as a non-invasive diagnostic tool for disease detection. In this paper leaf characteristics and spectral reflectance of sugar beet leaves diseased with Cercospora leaf spot, powdery mildew and leaf rust at different development stages were connected....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3274483/ https://www.ncbi.nlm.nih.gov/pubmed/22273513 http://dx.doi.org/10.1186/1746-4811-8-3 |
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author | Mahlein, Anne-Katrin Steiner, Ulrike Hillnhütter, Christian Dehne, Heinz-Wilhelm Oerke, Erich-Christian |
author_facet | Mahlein, Anne-Katrin Steiner, Ulrike Hillnhütter, Christian Dehne, Heinz-Wilhelm Oerke, Erich-Christian |
author_sort | Mahlein, Anne-Katrin |
collection | PubMed |
description | Hyperspectral imaging (HSI) offers high potential as a non-invasive diagnostic tool for disease detection. In this paper leaf characteristics and spectral reflectance of sugar beet leaves diseased with Cercospora leaf spot, powdery mildew and leaf rust at different development stages were connected. Light microscopy was used to describe the morphological changes in the host tissue due to pathogen colonisation. Under controlled conditions a hyperspectral imaging line scanning spectrometer (ImSpector V10E) with a spectral resolution of 2.8 nm from 400 to 1000 nm and a spatial resolution of 0.19 mm was used for continuous screening and monitoring of disease symptoms during pathogenesis. A pixel-wise mapping of spectral reflectance in the visible and near-infrared range enabled the detection and detailed description of diseased tissue on the leaf level. Leaf structure was linked to leaf spectral reflectance patterns. Depending on the interaction with the host tissue, the pathogens caused disease-specific spectral signatures. The influence of the pathogens on leaf reflectance was a function of the developmental stage of the disease and of the subarea of the symptoms. Spectral reflectance in combination with Spectral Angle Mapper classification allowed for the differentiation of mature symptoms into zones displaying all ontogenetic stages from young to mature symptoms. Due to a pixel-wise extraction of pure spectral signatures a better understanding of changes in leaf reflectance caused by plant diseases was achieved using HSI. This technology considerably improves the sensitivity and specificity of hyperspectrometry in proximal sensing of plant diseases. |
format | Online Article Text |
id | pubmed-3274483 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-32744832012-02-08 Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases Mahlein, Anne-Katrin Steiner, Ulrike Hillnhütter, Christian Dehne, Heinz-Wilhelm Oerke, Erich-Christian Plant Methods Methodology Hyperspectral imaging (HSI) offers high potential as a non-invasive diagnostic tool for disease detection. In this paper leaf characteristics and spectral reflectance of sugar beet leaves diseased with Cercospora leaf spot, powdery mildew and leaf rust at different development stages were connected. Light microscopy was used to describe the morphological changes in the host tissue due to pathogen colonisation. Under controlled conditions a hyperspectral imaging line scanning spectrometer (ImSpector V10E) with a spectral resolution of 2.8 nm from 400 to 1000 nm and a spatial resolution of 0.19 mm was used for continuous screening and monitoring of disease symptoms during pathogenesis. A pixel-wise mapping of spectral reflectance in the visible and near-infrared range enabled the detection and detailed description of diseased tissue on the leaf level. Leaf structure was linked to leaf spectral reflectance patterns. Depending on the interaction with the host tissue, the pathogens caused disease-specific spectral signatures. The influence of the pathogens on leaf reflectance was a function of the developmental stage of the disease and of the subarea of the symptoms. Spectral reflectance in combination with Spectral Angle Mapper classification allowed for the differentiation of mature symptoms into zones displaying all ontogenetic stages from young to mature symptoms. Due to a pixel-wise extraction of pure spectral signatures a better understanding of changes in leaf reflectance caused by plant diseases was achieved using HSI. This technology considerably improves the sensitivity and specificity of hyperspectrometry in proximal sensing of plant diseases. BioMed Central 2012-01-24 /pmc/articles/PMC3274483/ /pubmed/22273513 http://dx.doi.org/10.1186/1746-4811-8-3 Text en Copyright ©2012 Mahlein et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methodology Mahlein, Anne-Katrin Steiner, Ulrike Hillnhütter, Christian Dehne, Heinz-Wilhelm Oerke, Erich-Christian Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases |
title | Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases |
title_full | Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases |
title_fullStr | Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases |
title_full_unstemmed | Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases |
title_short | Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases |
title_sort | hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3274483/ https://www.ncbi.nlm.nih.gov/pubmed/22273513 http://dx.doi.org/10.1186/1746-4811-8-3 |
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