Journal of Biosystems Engineering

  • 제35권6호
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  • Pages.450-457
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  • 2010
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  • 1738-1266(pISSN)
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  • 2234-1862(eISSN)
한국농업기계학회 (Korean Society for Agricultural Machinery)
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가시광 및 근적외선 분광기법을 이용한 방울토마토의 내부품질 예측에 관한 연구

Study on Prediction of Internal Quality of Cherry Tomato using Vis/NIR Spectroscopy

  • Kim, Dae-Yong (Dept. of Biosystems Machinery Engineering, Chungnam National University) ;
  • Cho, Byoung-Kwan (Dept. of Biosystems Machinery Engineering, Chungnam National University) ;
  • Mo, Chang-Yeun (National Academy of Agricultural Science, RDA) ;
  • Kim, Young-Sik (Dept. Plant Industry Engineering, Sangmyung University)
  • 투고 : 2010.11.05
  • 심사 : 2010.11.30
  • 발행 : 2010.12.25
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초록

Although cherry tomato is one of major vegetables consumed in fresh vegetable market, the quality grading method is mostly dependant on size measurement using drum shape sorting machines. Using Visible/Near-infrared spectroscopy, apparatus to be able to acquire transmittance spectrum data was made and used to estimate firmness, sugar content, and acidity of cherry tomatoes grown at hydroponic and soil culture. Partial least square (PLS) models were performed to predict firmness, sugar content, and acidity for the acquired transmittance spectra. To enhance accuracy of the PLS models, several preprocessing methods were carried out, such as normalization, multiplicative scatter correction (MSC), standard normal variate (SNV), and derivatives, etc. The coefficient of determination ($R^2_p$) and standard error of prediction (SEP) for the prediction of firmness, sugar, and acidity of cherry tomatoes from green to red ripening stages were 0.859 and 1.899 kgf, with a preprocessing of normalization, 0.790 and $0.434^{\circ}Brix$ with a preprocessing of the 1st derivative of Savitzky Golay, and 0.518 and 0.229% with a preprocessing normalization, respectively.

키워드

참고문헌

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피인용 문헌

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  2. Development of On-line Sorting System for Detection of Infected Seed Potatoes Using Visible Near-Infrared Transmittance Spectral Technique vol.35, pp.1, 2015, https://doi.org/10.7779/JKSNT.2015.35.1.1
  3. Non-destructive quality prediction of truss tomatoes using hyperspectral reflectance imagery vol.39, pp.3, 2012, https://doi.org/10.7744/cnujas.2012.39.3.413
  4. Rapid monitoring of the fermentation process for Korean traditional rice wine ‘Makgeolli’ using FT-NIR spectroscopy vol.73, 2015, https://doi.org/10.1016/j.infrared.2015.09.007
  5. On-line fresh-cut lettuce quality measurement system using hyperspectral imaging vol.156, 2017, https://doi.org/10.1016/j.biosystemseng.2017.01.005
  6. Applications of Discrete Wavelet Analysis for Predicting Internal Quality of Cherry Tomatoes using VIS/NIR Spectroscopy vol.38, pp.1, 2013, https://doi.org/10.5307/JBE.2013.38.1.048