Optimal Fluorescence Waveband Determination for Detecting Defective Cherry Tomatoes Using a Fluorescence Excitation-Emission Matrix

Sensors

In-Suck Baek¹  Moon S. Kim²  Hoosoo Lee¹  Wang-Hee Lee¹ 

[1] Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, Korea; E-Mails:;Environmental Microbiology and Food Safety Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Powder Mill Road, Building #303, BARC-East, Beltsville, MD 20705, USA; E-Mail:

关键词: cherry tomato;    quality sorting;    defect detection;    hyperspectral image;    fluorescence image;   

DOI  :  10.3390/s141121483

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.