Detecting Green Mold Pathogens on Lemons Using Hyperspectral Images
1
Public Safety Research Center, Konyang University, Nonsan 32992, Korea
2
Department of Civil Engineering, Konyang University, Nonsan 32992, Korea
3
Department of Bio-IT Engineering, Konyang University, Nonsan 32992, Korea
4
Linguistics for Sciences Department, Chernivtsi University, 58012 Chernivtsi, Ukraine
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(4), 1209; https://doi.org/10.3390/app10041209
Received: 19 December 2019 / Revised: 30 January 2020 / Accepted: 6 February 2020 / Published: 11 February 2020
(This article belongs to the Special Issue Intelligent Processing on Image and Optical Information)
Hyperspectral images in the spectral wavelength range of 500 nm to 650 nm are used to detect green mold pathogens, which are parasitic on the surface of lemons. The images reveal that the spectral range of 500 nm to 560 nm is appropriate for detecting the early stage of development of the pathogen in the lemon, because the spectral intensity is proportional to the infection degree. Within the range, it was found that the dominant spectral wavelengths of the fresh lemon and the green mold pathogen are 580 nm and 550 nm, respectively, with the 550 nm being the most sensitive in detecting the pathogen with spectral imaging. The spectral intensity ratio of the infected lemon to the fresh one in the spectral range of 500 nm to 560 nm increases with the increasing degree of the infection. Therefore, the ratio can be used to effectively estimate the degree of lemons infecting by the green mold pathogens. It also shows that the sudden decrease of the spectral intensity corresponding to the dominant spectral wavelength of the fresh lemon, together with the neighboring spectral wavelengths can be used to classify fresh and contaminated lemons. The spectral intensity ratio of discriminating the fresh lemon from the infected one is calculated as 1.15.
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Keywords:
healthy and infected lemons; Hyperspectral image; Penicillium digitatum pathogen; lemon skin; dominant spectral wavelength; spectral intensity ratio
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MDPI and ACS Style
Vashpanov, Y.; Heo, G.; Kim, Y.; Venkel, T.; Son, J.-Y. Detecting Green Mold Pathogens on Lemons Using Hyperspectral Images. Appl. Sci. 2020, 10, 1209.
AMA Style
Vashpanov Y, Heo G, Kim Y, Venkel T, Son J-Y. Detecting Green Mold Pathogens on Lemons Using Hyperspectral Images. Applied Sciences. 2020; 10(4):1209.
Chicago/Turabian StyleVashpanov, Yuriy; Heo, Gwanghee; Kim, Yongsuk; Venkel, Tetiana; Son, Jung-Young. 2020. "Detecting Green Mold Pathogens on Lemons Using Hyperspectral Images" Appl. Sci. 10, no. 4: 1209.
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