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Hyperspectral and Thermal Imaging of Oilseed Rape (Brassica napus) Response to Fungal Species of the Genus Alternaria

In this paper, thermal (8-13 µm) and hyperspectral imaging in visible and near infrared (VNIR) and short wavelength infrared (SWIR) ranges were used to elaborate a method of early detection of biotic stresses caused by fungal species belonging to the genus Alternaria that were host (Alternaria alter...

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Autores principales: Baranowski, Piotr, Jedryczka, Malgorzata, Mazurek, Wojciech, Babula-Skowronska, Danuta, Siedliska, Anna, Kaczmarek, Joanna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4380467/
https://www.ncbi.nlm.nih.gov/pubmed/25826369
http://dx.doi.org/10.1371/journal.pone.0122913
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author Baranowski, Piotr
Jedryczka, Malgorzata
Mazurek, Wojciech
Babula-Skowronska, Danuta
Siedliska, Anna
Kaczmarek, Joanna
author_facet Baranowski, Piotr
Jedryczka, Malgorzata
Mazurek, Wojciech
Babula-Skowronska, Danuta
Siedliska, Anna
Kaczmarek, Joanna
author_sort Baranowski, Piotr
collection PubMed
description In this paper, thermal (8-13 µm) and hyperspectral imaging in visible and near infrared (VNIR) and short wavelength infrared (SWIR) ranges were used to elaborate a method of early detection of biotic stresses caused by fungal species belonging to the genus Alternaria that were host (Alternaria alternata, Alternaria brassicae, and Alternaria brassicicola) and non-host (Alternaria dauci) pathogens to oilseed rape (Brassica napus L.). The measurements of disease severity for chosen dates after inoculation were compared to temperature distributions on infected leaves and to averaged reflectance characteristics. Statistical analysis revealed that leaf temperature distributions on particular days after inoculation and respective spectral characteristics, especially in the SWIR range (1000-2500 nm), significantly differed for the leaves inoculated with A. dauci from the other species of Alternaria as well as from leaves of non-treated plants. The significant differences in leaf temperature of the studied Alternaria species were observed in various stages of infection development. The classification experiments were performed on the hyperspectral data of the leaf surfaces to distinguish days after inoculation and Alternaria species. The second-derivative transformation of the spectral data together with back-propagation neural networks (BNNs) appeared to be the best combination for classification of days after inoculation (prediction accuracy 90.5%) and Alternaria species (prediction accuracy 80.5%).
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spelling pubmed-43804672015-04-09 Hyperspectral and Thermal Imaging of Oilseed Rape (Brassica napus) Response to Fungal Species of the Genus Alternaria Baranowski, Piotr Jedryczka, Malgorzata Mazurek, Wojciech Babula-Skowronska, Danuta Siedliska, Anna Kaczmarek, Joanna PLoS One Research Article In this paper, thermal (8-13 µm) and hyperspectral imaging in visible and near infrared (VNIR) and short wavelength infrared (SWIR) ranges were used to elaborate a method of early detection of biotic stresses caused by fungal species belonging to the genus Alternaria that were host (Alternaria alternata, Alternaria brassicae, and Alternaria brassicicola) and non-host (Alternaria dauci) pathogens to oilseed rape (Brassica napus L.). The measurements of disease severity for chosen dates after inoculation were compared to temperature distributions on infected leaves and to averaged reflectance characteristics. Statistical analysis revealed that leaf temperature distributions on particular days after inoculation and respective spectral characteristics, especially in the SWIR range (1000-2500 nm), significantly differed for the leaves inoculated with A. dauci from the other species of Alternaria as well as from leaves of non-treated plants. The significant differences in leaf temperature of the studied Alternaria species were observed in various stages of infection development. The classification experiments were performed on the hyperspectral data of the leaf surfaces to distinguish days after inoculation and Alternaria species. The second-derivative transformation of the spectral data together with back-propagation neural networks (BNNs) appeared to be the best combination for classification of days after inoculation (prediction accuracy 90.5%) and Alternaria species (prediction accuracy 80.5%). Public Library of Science 2015-03-31 /pmc/articles/PMC4380467/ /pubmed/25826369 http://dx.doi.org/10.1371/journal.pone.0122913 Text en © 2015 Baranowski et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Baranowski, Piotr
Jedryczka, Malgorzata
Mazurek, Wojciech
Babula-Skowronska, Danuta
Siedliska, Anna
Kaczmarek, Joanna
Hyperspectral and Thermal Imaging of Oilseed Rape (Brassica napus) Response to Fungal Species of the Genus Alternaria
title Hyperspectral and Thermal Imaging of Oilseed Rape (Brassica napus) Response to Fungal Species of the Genus Alternaria
title_full Hyperspectral and Thermal Imaging of Oilseed Rape (Brassica napus) Response to Fungal Species of the Genus Alternaria
title_fullStr Hyperspectral and Thermal Imaging of Oilseed Rape (Brassica napus) Response to Fungal Species of the Genus Alternaria
title_full_unstemmed Hyperspectral and Thermal Imaging of Oilseed Rape (Brassica napus) Response to Fungal Species of the Genus Alternaria
title_short Hyperspectral and Thermal Imaging of Oilseed Rape (Brassica napus) Response to Fungal Species of the Genus Alternaria
title_sort hyperspectral and thermal imaging of oilseed rape (brassica napus) response to fungal species of the genus alternaria
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4380467/
https://www.ncbi.nlm.nih.gov/pubmed/25826369
http://dx.doi.org/10.1371/journal.pone.0122913
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