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Study on Black Spot Disease Detection and Pathogenic Process Visualization on Winter Jujubes Using Hyperspectral Imaging System

In this work, the potential of a hyperspectral imaging (HSI) system for the detection of black spot disease on winter jujubes infected by Alternaria alternata during postharvest storage was investigated. The HSI images were acquired using two systems in the visible and near-infrared (Vis-NIR, 400–10...

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Autores principales: Jiang, Mengwei, Li, Yiting, Song, Jin, Wang, Zhenjie, Zhang, Li, Song, Lijun, Bai, Bingyao, Tu, Kang, Lan, Weijie, Pan, Leiqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9914266/
https://www.ncbi.nlm.nih.gov/pubmed/36765962
http://dx.doi.org/10.3390/foods12030435
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author Jiang, Mengwei
Li, Yiting
Song, Jin
Wang, Zhenjie
Zhang, Li
Song, Lijun
Bai, Bingyao
Tu, Kang
Lan, Weijie
Pan, Leiqing
author_facet Jiang, Mengwei
Li, Yiting
Song, Jin
Wang, Zhenjie
Zhang, Li
Song, Lijun
Bai, Bingyao
Tu, Kang
Lan, Weijie
Pan, Leiqing
author_sort Jiang, Mengwei
collection PubMed
description In this work, the potential of a hyperspectral imaging (HSI) system for the detection of black spot disease on winter jujubes infected by Alternaria alternata during postharvest storage was investigated. The HSI images were acquired using two systems in the visible and near-infrared (Vis-NIR, 400–1000 nm) and short-wave infrared (SWIR, 1000–2000 nm) spectral regions. Meanwhile, the change of physical (peel color, weight loss) and chemical parameters (soluble solids content, chlorophyll) and the microstructure of winter jujubes during the pathogenic process were measured. The results showed the spectral reflectance of jujubes in both the Vis-NIR and SWIR wavelength ranges presented an overall downtrend during the infection. Partial least squares discriminant models (PLS-DA) based on the HSI spectra in Vis-NIR and SWIR regions of jujubes both gave satisfactory discrimination accuracy for the disease detection, with classification rates of over 92.31% and 91.03%, respectively. Principal component analysis (PCA) was carried out on the HSI images of jujubes to visualize their infected areas during the pathogenic process. The first principal component of the HSI spectra in the Vis-NIR region could highlight the diseased areas of the infected jujubes. Consequently, Vis-NIR HSI and NIR HSI techniques had the potential to detect the black spot disease on winter jujubes during the postharvest storage, and the Vis-NIR HSI spectral information could visualize the diseased areas of jujubes during the pathogenic process.
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spelling pubmed-99142662023-02-11 Study on Black Spot Disease Detection and Pathogenic Process Visualization on Winter Jujubes Using Hyperspectral Imaging System Jiang, Mengwei Li, Yiting Song, Jin Wang, Zhenjie Zhang, Li Song, Lijun Bai, Bingyao Tu, Kang Lan, Weijie Pan, Leiqing Foods Article In this work, the potential of a hyperspectral imaging (HSI) system for the detection of black spot disease on winter jujubes infected by Alternaria alternata during postharvest storage was investigated. The HSI images were acquired using two systems in the visible and near-infrared (Vis-NIR, 400–1000 nm) and short-wave infrared (SWIR, 1000–2000 nm) spectral regions. Meanwhile, the change of physical (peel color, weight loss) and chemical parameters (soluble solids content, chlorophyll) and the microstructure of winter jujubes during the pathogenic process were measured. The results showed the spectral reflectance of jujubes in both the Vis-NIR and SWIR wavelength ranges presented an overall downtrend during the infection. Partial least squares discriminant models (PLS-DA) based on the HSI spectra in Vis-NIR and SWIR regions of jujubes both gave satisfactory discrimination accuracy for the disease detection, with classification rates of over 92.31% and 91.03%, respectively. Principal component analysis (PCA) was carried out on the HSI images of jujubes to visualize their infected areas during the pathogenic process. The first principal component of the HSI spectra in the Vis-NIR region could highlight the diseased areas of the infected jujubes. Consequently, Vis-NIR HSI and NIR HSI techniques had the potential to detect the black spot disease on winter jujubes during the postharvest storage, and the Vis-NIR HSI spectral information could visualize the diseased areas of jujubes during the pathogenic process. MDPI 2023-01-17 /pmc/articles/PMC9914266/ /pubmed/36765962 http://dx.doi.org/10.3390/foods12030435 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Jiang, Mengwei
Li, Yiting
Song, Jin
Wang, Zhenjie
Zhang, Li
Song, Lijun
Bai, Bingyao
Tu, Kang
Lan, Weijie
Pan, Leiqing
Study on Black Spot Disease Detection and Pathogenic Process Visualization on Winter Jujubes Using Hyperspectral Imaging System
title Study on Black Spot Disease Detection and Pathogenic Process Visualization on Winter Jujubes Using Hyperspectral Imaging System
title_full Study on Black Spot Disease Detection and Pathogenic Process Visualization on Winter Jujubes Using Hyperspectral Imaging System
title_fullStr Study on Black Spot Disease Detection and Pathogenic Process Visualization on Winter Jujubes Using Hyperspectral Imaging System
title_full_unstemmed Study on Black Spot Disease Detection and Pathogenic Process Visualization on Winter Jujubes Using Hyperspectral Imaging System
title_short Study on Black Spot Disease Detection and Pathogenic Process Visualization on Winter Jujubes Using Hyperspectral Imaging System
title_sort study on black spot disease detection and pathogenic process visualization on winter jujubes using hyperspectral imaging system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9914266/
https://www.ncbi.nlm.nih.gov/pubmed/36765962
http://dx.doi.org/10.3390/foods12030435
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