Sang-Ryong Suh's scientific contributions

Publications (2)

Article
This study was carried out to find a useful method to predict hardness of tomato using optical spectrum data. Optical spectrum of reflectance and transmittance data were collected processed by 9 kind of preprocessing methods-normalizations of mean, maximum and range, SNV (standard normal variate), MSC (multiplicative scatter correction), the first...
Article
The goal of this study was to develop prediction models to estimate the storage days of tomato. The transmittance spectral data measured on tomato were preprocessed through normalization, SNV, Savitzky-Golay, and Norris Gap and then were used to build the prediction models using partial least square (PLS) method. For the experiments, the tomato sam...

Citations

... 수집한 분광 자료는 측정범위 하단에 있어 잡음 혼입 정도 가 심하여 486~1100 nm 범위의 자료만을 사용하였다. 이러 한 분광 자료를 이용하여 배의 당도를 예측하기 위한 모형 개발은 분광자료를 이용한 농산물의 내부품질 예측에 많이 사용(Hwang et al., 2000; Lee et al., 2001; Zude et al., 2006; Kim and Suh, 2008; Moghimi et al., 2010; Kim et al., 2010) 하는 다변량 분석방법인 부분최소제곱회귀법(partial least squares regression, PLSR)을 사용하였다. 이러한 당도 예측용 PSLR 모형 개발에 있어 각 분광자료 에 대한 전처리가 요구되며 적합(당도 예측성능이 우수)한 전처리를 구하는 것은 당도 예측모형 개발의 매우 중요한 과 정이다. ...
... It is known that NIR spectra possess complex and overlapping absorption bands, so that mathematical procedures are needed for turning the spectra into meaningful information. Therefore, a multivariate analysis method is commonly used for the analysis of data sets with more than one variable because it is capable of describing how the measured spectral features are related to the property of interest [32,33]. Until now, some multivariate techniques, such as partial least-squares regression (PLSR), principal component regression (PCR), and multiple linear regression (MLR), are commonly used to extract quantitative and qualitative information from NIR spectra [34,35]. ...