Cargando…

Development and Evaluation of a New Spectral Disease Index to Detect Wheat Fusarium Head Blight Using Hyperspectral Imaging

Fusarium head blight (FHB) is a major disease threatening worldwide wheat production. FHB is a short cycle disease and is highly destructive under conducive environments. To provide technical support for the rapid detection of the FHB disease, we proposed to develop a new Fusarium disease index (FDI...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Dongyan, Wang, Qian, Lin, Fenfang, Yin, Xun, Gu, Chunyan, Qiao, Hongbo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219049/
https://www.ncbi.nlm.nih.gov/pubmed/32316216
http://dx.doi.org/10.3390/s20082260
_version_ 1783532918184869888
author Zhang, Dongyan
Wang, Qian
Lin, Fenfang
Yin, Xun
Gu, Chunyan
Qiao, Hongbo
author_facet Zhang, Dongyan
Wang, Qian
Lin, Fenfang
Yin, Xun
Gu, Chunyan
Qiao, Hongbo
author_sort Zhang, Dongyan
collection PubMed
description Fusarium head blight (FHB) is a major disease threatening worldwide wheat production. FHB is a short cycle disease and is highly destructive under conducive environments. To provide technical support for the rapid detection of the FHB disease, we proposed to develop a new Fusarium disease index (FDI) based on the spectral data of 374–1050 nm. This study was conducted through the analysis of reflectance spectral data of healthy and diseased wheat ears at the flowering and filling stages by hyperspectral imaging technology and the random forest method. The characteristic wavelengths selected were 570 nm and 678 nm for the late flowering stage, 565 nm and 661 nm for the early filling stage, 560 nm and 663 nm for the combined stage (combining both flowering and filling stages) by random forest. FDI at each stage was derived from the wavebands of each corresponding stage. Compared with other 16 existing spectral indices, FDI demonstrated a stronger ability to determine the severity of the FHB disease. Its determination coefficients (R(2)) values exceeded 0.90 and the RMSEs were less than 0.08 in the models for each stage. Furthermore, the model for the combined stage performed better when used at single growth stage, but its effect was weaker than that of the models for the two individual growth stages. Therefore, using FDI can provide a new tool to detect the FHB disease at different growth stages in wheat.
format Online
Article
Text
id pubmed-7219049
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-72190492020-05-22 Development and Evaluation of a New Spectral Disease Index to Detect Wheat Fusarium Head Blight Using Hyperspectral Imaging Zhang, Dongyan Wang, Qian Lin, Fenfang Yin, Xun Gu, Chunyan Qiao, Hongbo Sensors (Basel) Article Fusarium head blight (FHB) is a major disease threatening worldwide wheat production. FHB is a short cycle disease and is highly destructive under conducive environments. To provide technical support for the rapid detection of the FHB disease, we proposed to develop a new Fusarium disease index (FDI) based on the spectral data of 374–1050 nm. This study was conducted through the analysis of reflectance spectral data of healthy and diseased wheat ears at the flowering and filling stages by hyperspectral imaging technology and the random forest method. The characteristic wavelengths selected were 570 nm and 678 nm for the late flowering stage, 565 nm and 661 nm for the early filling stage, 560 nm and 663 nm for the combined stage (combining both flowering and filling stages) by random forest. FDI at each stage was derived from the wavebands of each corresponding stage. Compared with other 16 existing spectral indices, FDI demonstrated a stronger ability to determine the severity of the FHB disease. Its determination coefficients (R(2)) values exceeded 0.90 and the RMSEs were less than 0.08 in the models for each stage. Furthermore, the model for the combined stage performed better when used at single growth stage, but its effect was weaker than that of the models for the two individual growth stages. Therefore, using FDI can provide a new tool to detect the FHB disease at different growth stages in wheat. MDPI 2020-04-16 /pmc/articles/PMC7219049/ /pubmed/32316216 http://dx.doi.org/10.3390/s20082260 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Dongyan
Wang, Qian
Lin, Fenfang
Yin, Xun
Gu, Chunyan
Qiao, Hongbo
Development and Evaluation of a New Spectral Disease Index to Detect Wheat Fusarium Head Blight Using Hyperspectral Imaging
title Development and Evaluation of a New Spectral Disease Index to Detect Wheat Fusarium Head Blight Using Hyperspectral Imaging
title_full Development and Evaluation of a New Spectral Disease Index to Detect Wheat Fusarium Head Blight Using Hyperspectral Imaging
title_fullStr Development and Evaluation of a New Spectral Disease Index to Detect Wheat Fusarium Head Blight Using Hyperspectral Imaging
title_full_unstemmed Development and Evaluation of a New Spectral Disease Index to Detect Wheat Fusarium Head Blight Using Hyperspectral Imaging
title_short Development and Evaluation of a New Spectral Disease Index to Detect Wheat Fusarium Head Blight Using Hyperspectral Imaging
title_sort development and evaluation of a new spectral disease index to detect wheat fusarium head blight using hyperspectral imaging
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219049/
https://www.ncbi.nlm.nih.gov/pubmed/32316216
http://dx.doi.org/10.3390/s20082260
work_keys_str_mv AT zhangdongyan developmentandevaluationofanewspectraldiseaseindextodetectwheatfusariumheadblightusinghyperspectralimaging
AT wangqian developmentandevaluationofanewspectraldiseaseindextodetectwheatfusariumheadblightusinghyperspectralimaging
AT linfenfang developmentandevaluationofanewspectraldiseaseindextodetectwheatfusariumheadblightusinghyperspectralimaging
AT yinxun developmentandevaluationofanewspectraldiseaseindextodetectwheatfusariumheadblightusinghyperspectralimaging
AT guchunyan developmentandevaluationofanewspectraldiseaseindextodetectwheatfusariumheadblightusinghyperspectralimaging
AT qiaohongbo developmentandevaluationofanewspectraldiseaseindextodetectwheatfusariumheadblightusinghyperspectralimaging