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Volume 12
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10.3390/foods12030435
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Article

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

by
Mengwei Jiang
1,
Yiting Li
1,
Jin Song
2,
Zhenjie Wang
1,
Li Zhang
3,4,
Lijun Song
3,4,
Bingyao Bai
4,
Kang Tu
1,
Weijie Lan
1,* and
Leiqing Pan
1,5,*
1
College of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China
2
College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210095, China
3
College of Food Science and Technology, Hebei Normal University of Science & Technology, Qinghuangdao 066600, China
4
College of Life Sciences, Tarim University, Alaer 843300, China
5
Sanya Institute of Nanjing Agricultural University, Sanya 572024, China
*
Authors to whom correspondence should be addressed.
Foods 2023, 12(3), 435; https://doi.org/10.3390/foods12030435
Submission received: 22 November 2022 / Revised: 10 January 2023 / Accepted: 12 January 2023 / Published: 17 January 2023
(This article belongs to the Special Issue Applications of Non-destructive Technologies for Food Quality and Safety)
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Abstract

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.
Keywords: winter jujube; black spot disease; hyperspectral imaging; pathogenic process visualization winter jujube; black spot disease; hyperspectral imaging; pathogenic process visualization

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MDPI and ACS Style

Jiang, M.; Li, Y.; Song, J.; Wang, Z.; Zhang, L.; Song, L.; Bai, B.; Tu, K.; Lan, W.; Pan, L. Study on Black Spot Disease Detection and Pathogenic Process Visualization on Winter Jujubes Using Hyperspectral Imaging System. Foods 2023, 12, 435. https://doi.org/10.3390/foods12030435

AMA Style

Jiang M, Li Y, Song J, Wang Z, Zhang L, Song L, Bai B, Tu K, Lan W, Pan L. Study on Black Spot Disease Detection and Pathogenic Process Visualization on Winter Jujubes Using Hyperspectral Imaging System. Foods. 2023; 12(3):435. https://doi.org/10.3390/foods12030435

Chicago/Turabian Style

Jiang, Mengwei, Yiting Li, Jin Song, Zhenjie Wang, Li Zhang, Lijun Song, Bingyao Bai, Kang Tu, Weijie Lan, and Leiqing Pan. 2023. "Study on Black Spot Disease Detection and Pathogenic Process Visualization on Winter Jujubes Using Hyperspectral Imaging System" Foods 12, no. 3: 435. https://doi.org/10.3390/foods12030435

APA Style

Jiang, M., Li, Y., Song, J., Wang, Z., Zhang, L., Song, L., Bai, B., Tu, K., Lan, W., & Pan, L. (2023). Study on Black Spot Disease Detection and Pathogenic Process Visualization on Winter Jujubes Using Hyperspectral Imaging System. Foods, 12(3), 435. https://doi.org/10.3390/foods12030435

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