Article

Development of Prediction Model to Estimate the Storage Days of Tomato Using Transmittance Spectrum

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Abstract

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 samples of different varieties were collected at different harvest time. The samples were taken right after harvest from the field and then were stored in a low-temperature storage room in which room temperature was maintained at . The transmittance spectral data of the tomato samples were measured at three-day intervals for 16 days. The performance of the prediction models was affected by the preprocessing techniques as well as the varieties and harvest time of the tomato. The best model was found when SNV was applied. The accuracy of the best model was 90.2%. It can be concluded that the transmittance spectra are useful information for predicting the period of storage of tomato.

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... 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. ...
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Physiochemical factors for evaluating freshness of apple and tomato
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  • J K Hwang
  • Y J Cho
  • J K Hwang