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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Publications at this Location » Publication #310210
Title: Optimal fluorescence waveband determination for detecting defect cherry tomatoes using fluorescence excitation-emission matrix

Author
item BAEK, INSUCK - Chungnam National University
item Kim, Moon
item LEE, HOONSOO - Chungnam National University
item CHO, BYOUNG-KWAN - Chungnam National University

Submitted to: Sensors
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/15/2014
Publication Date: 11/1/2014
Citation: Baek, I., Kim, M.S., Lee, H., Cho, B. 2014. Optimal fluorescence waveband determination for detecting defect cherry tomatoes using fluorescence excitation-emission matrix. Sensors. 14:21483-21496.

Interpretive Summary: Spectral imaging technologies can provide a rapid means to evaluate quality and safety attributes of produce. Both fluorescence excitation and emission chracterisitics of cherry tomatoes were investigated to determine the optimal wavelengths for discrimination of normal and defective (cracked) cherry tomatoes. The optimal excitation wavelength was 410 nm and the major emission wavelengths were 506 nm and 688 nm for detecting defect areas. The resultant multispectral fluorescence imaging method using these wavelengths demonstrated the detection of defective cherry tomatoes with >98% accuracy. This research provides insightful information to agricultural engineers who are developing nondestructive fruit sorting technologies and is beneficial to produce production and processing industries.

Technical Abstract: A multi-spectral fluorescence imaging technique was used to detect defect 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 defect cherry tomatoes with >98% accuracy. Multi-spectral fluorescence imaging has potential utility in non-destructive quality sorting of cherry tomatoes.