Optimal Fluorescence Waveband Determination for Detecting Defective Cherry Tomatoes Using a Fluorescence Excitation-Emission Matrix
A multi-spectral fluorescence imaging technique was used to detect defective cherry tomatoes. The fluorescence excitation and emission matrix was used to measure for defects, sound surface and stem areas to determine the optimal fluorescence excitation and emission wavelengths for discrimination. Tw...
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MDPI AG
2014-11-01
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Online Access: | http://www.mdpi.com/1424-8220/14/11/21483 |
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author | In-Suck Baek Moon S. Kim Hoosoo Lee Wang-Hee Lee Byoung-Kwan Cho |
author_facet | In-Suck Baek Moon S. Kim Hoosoo Lee Wang-Hee Lee Byoung-Kwan Cho |
author_sort | In-Suck Baek |
collection | DOAJ |
description | A multi-spectral fluorescence imaging technique was used to detect defective cherry tomatoes. The fluorescence excitation and emission matrix was used to measure for defects, sound surface and stem areas to determine the optimal fluorescence excitation and emission wavelengths for discrimination. Two-way ANOVA revealed the optimal excitation wavelength for detecting defect areas was 410 nm. Principal component analysis (PCA) was applied to the fluorescence emission spectra of all regions at 410 nm excitation to determine the emission wavelengths for defect detection. The major emission wavelengths were 688 nm and 506 nm for the detection. Fluorescence images combined with the determined emission wavebands demonstrated the feasibility of detecting defective cherry tomatoes with >98% accuracy. Multi-spectral fluorescence imaging has potential utility in non-destructive quality sorting of cherry tomatoes. |
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institution | Directory Open Access Journal |
issn | 1424-8220 |
language | English |
last_indexed | 2024-04-13T09:20:38Z |
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spelling | doaj.art-051aaddc89d344e1ac5c916db55883ba2022-12-22T02:52:36ZengMDPI AGSensors1424-82202014-11-011411214832149610.3390/s141121483s141121483Optimal Fluorescence Waveband Determination for Detecting Defective Cherry Tomatoes Using a Fluorescence Excitation-Emission MatrixIn-Suck Baek0Moon S. Kim1Hoosoo Lee2Wang-Hee Lee3Byoung-Kwan Cho4Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, KoreaEnvironmental Microbiology and Food Safety Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Powder Mill Road, Building #303, BARC-East, Beltsville, MD 20705, USADepartment of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, KoreaDepartment of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, KoreaDepartment of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, KoreaA multi-spectral fluorescence imaging technique was used to detect defective cherry tomatoes. The fluorescence excitation and emission matrix was used to measure for defects, sound surface and stem areas to determine the optimal fluorescence excitation and emission wavelengths for discrimination. Two-way ANOVA revealed the optimal excitation wavelength for detecting defect areas was 410 nm. Principal component analysis (PCA) was applied to the fluorescence emission spectra of all regions at 410 nm excitation to determine the emission wavelengths for defect detection. The major emission wavelengths were 688 nm and 506 nm for the detection. Fluorescence images combined with the determined emission wavebands demonstrated the feasibility of detecting defective cherry tomatoes with >98% accuracy. Multi-spectral fluorescence imaging has potential utility in non-destructive quality sorting of cherry tomatoes.http://www.mdpi.com/1424-8220/14/11/21483cherry tomatoquality sortingdefect detectionhyperspectral imagefluorescence image |
spellingShingle | In-Suck Baek Moon S. Kim Hoosoo Lee Wang-Hee Lee Byoung-Kwan Cho Optimal Fluorescence Waveband Determination for Detecting Defective Cherry Tomatoes Using a Fluorescence Excitation-Emission Matrix Sensors cherry tomato quality sorting defect detection hyperspectral image fluorescence image |
title | Optimal Fluorescence Waveband Determination for Detecting Defective Cherry Tomatoes Using a Fluorescence Excitation-Emission Matrix |
title_full | Optimal Fluorescence Waveband Determination for Detecting Defective Cherry Tomatoes Using a Fluorescence Excitation-Emission Matrix |
title_fullStr | Optimal Fluorescence Waveband Determination for Detecting Defective Cherry Tomatoes Using a Fluorescence Excitation-Emission Matrix |
title_full_unstemmed | Optimal Fluorescence Waveband Determination for Detecting Defective Cherry Tomatoes Using a Fluorescence Excitation-Emission Matrix |
title_short | Optimal Fluorescence Waveband Determination for Detecting Defective Cherry Tomatoes Using a Fluorescence Excitation-Emission Matrix |
title_sort | optimal fluorescence waveband determination for detecting defective cherry tomatoes using a fluorescence excitation emission matrix |
topic | cherry tomato quality sorting defect detection hyperspectral image fluorescence image |
url | http://www.mdpi.com/1424-8220/14/11/21483 |
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