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Sensors 2014, 14(4), 7489-7504;

Non-Destructive Quality Evaluation of Pepper (Capsicum annuum L.) Seeds Using LED-Induced Hyperspectral Reflectance Imaging

National Academy of Agricultural Science, Rural Development Administration, 150 Suinro, Gwonseon-gu, Suwon, Gyeonggi-do 441-100, Korea
Environmental Microbiology and Food Safety Laboratory, BARC-East, Agricultural Research Service, US Department of Agriculture, 10300 Baltimore Avenue Beltsville, MD 20705, USA
Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, Korea
Author to whom correspondence should be addressed.
Received: 17 March 2014 / Revised: 21 April 2014 / Accepted: 21 April 2014 / Published: 24 April 2014
(This article belongs to the Section Remote Sensors)
Full-Text   |   PDF [864 KB, uploaded 21 June 2014]


In this study, we developed a viability evaluation method for pepper (Capsicum annuum L.) seeds based on hyperspectral reflectance imaging. The reflectance spectra of pepper seeds in the 400–700 nm range are collected from hyperspectral reflectance images obtained using blue, green, and red LED illumination. A partial least squares–discriminant analysis (PLS-DA) model is developed to classify viable and non-viable seeds. Four spectral ranges generated with four types of LEDs (blue, green, red, and RGB), which were pretreated using various methods, are investigated to develop the classification models. The optimal PLS-DA model based on the standard normal variate for RGB LED illumination (400–700 nm) yields discrimination accuracies of 96.7% and 99.4% for viable seeds and nonviable seeds, respectively. The use of images based on the PLS-DA model with the first-order derivative of a 31.5-nm gap for red LED illumination (600–700 nm) yields 100% discrimination accuracy for both viable and nonviable seeds. The results indicate that a hyperspectral imaging technique based on LED light can be potentially applied to high-quality pepper seed sorting. View Full-Text
Keywords: hyperspectral imaging; pepper seed; quality; PLS-DA; LED hyperspectral imaging; pepper seed; quality; PLS-DA; LED
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Mo, C.; Kim, G.; Lee, K.; Kim, M.S.; Cho, B.-K.; Lim, J.; Kang, S. Non-Destructive Quality Evaluation of Pepper (Capsicum annuum L.) Seeds Using LED-Induced Hyperspectral Reflectance Imaging. Sensors 2014, 14, 7489-7504.

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