H
Hoonsoo Lee
Researcher at Chungbuk National University
Publications - 62
Citations - 1503
Hoonsoo Lee is an academic researcher from Chungbuk National University. The author has contributed to research in topics: Hyperspectral imaging & Multispectral image. The author has an hindex of 18, co-authored 62 publications receiving 1013 citations. Previous affiliations of Hoonsoo Lee include United States Department of Agriculture & Agricultural Research Service.
Papers
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Journal ArticleDOI
A review of vibrational spectroscopic techniques for the detection of food authenticity and adulteration
TL;DR: Vibrational spectroscopic techniques have potential to fulfill the industrial need for food quality and authenticity analysis, however, still requires measurement accessories and dynamic chemomatric analytical methods for modern food inspection.
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Hyperspectral near-infrared imaging for the detection of physical damages of pear
Wang-Hee Lee,Moon S. Kim,Hoonsoo Lee,Stephen R. Delwiche,Hanhong Bae,Dae-Yong Kim,Byoung-Kwan Cho +6 more
TL;DR: In this paper, a hyperspectral imaging with beyond NIR range of 950-1650 nm was investigated for detecting bruise damages underneath the pear skin, which has never been examined in the past.
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Rapid assessment of corn seed viability using short wave infrared line-scan hyperspectral imaging and chemometrics
Collins Wakholi,Lalit Mohan Kandpal,Hoonsoo Lee,Hyungjin Bae,Eunsoo Park,Moon S. Kim,Changyeun Mo,Wang-Hee Lee,Byoung-Kwan Cho +8 more
TL;DR: In this article, three classification models, linear discriminant analysis (LDA), partial least squares discriminant analyses (PLS-DA), and support vector machines (SVM), coupled with some pre-processing methods, were tested to determine the most suitable among them.
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Determination of the total volatile basic nitrogen (TVB-N) content in pork meat using hyperspectral fluorescence imaging
TL;DR: In this article, the authors used hyperspectral fluorescence imaging techniques to determine TVB-N contents in pork meat and developed prediction algorithms based on partial least squares analysis and least squares support vector machines (LS-SVM).
Journal ArticleDOI
Prediction of crude protein and oil content of soybeans using Raman spectroscopy
Hoonsoo Lee,Byoung-Kwan Cho,Moon S. Kim,Wang-Hee Lee,Jagdish Tewari,Hanhong Bae,Soo-In Sohn,Hee-Youn Chi +7 more
TL;DR: In this paper, the authors developed an optimal prediction model for determining the protein and oil contents of soybeans using a dispersive Raman spectroscopy method, which can be used to measure a variety of food components rapidly and non-destructively without supervision from experts once the instrument has been calibrated.