• 한국산학기술학회논문지
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• 제13권3호
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• pp.1319-1324
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• 2012

토마토는 여러 가지 다른 숙성 단계에서 수확될 수 있다. 토마토의 숙성 상태를 판단하기 위해 토마토 과육을 HPLC로 분석한 여러 가지 화합물과 토마토 RGB 이미지를 ICA로 분석한 독립성분간의 관계를 분석하였다. 여러 토마토 화합물중 품질에 가장 영향을 많이 미치는 라이코펜과 토마토 RGB 이미지의 독립성분간의 부분최소제곱 $Q^2$ 값이 0.92로 매우 높음을 알 수 있었다. 그리고 라이코펜에 대응되는 독립성분을 토마토 RGB 이미지에 적용하여 픽셀 면적을 구한 것과 단순이진 이미지로 구해진 이미지의 픽셀 면적간의 비교를 제시하여 독립성분의 유효성을 제시하였다. 독립성분을 반영한 토마토 이미지를 통해 토마토의 숙성 상태를 보여주는 것이 가능하며, ICA 독립성분을 이용한 농축이미지 생성을 통해 토마토의 색상이 좋지 않거나 라이코펜과 같은 주요 성분이 없게 된 토마토를 분류해 내는 것이 가능해진다.

• 농업과학연구
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• 제37권2호
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• pp.303-308
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• 2010

Surface color is the most important quality factor for the grade evaluation of cherry tomato. Color is one of the representative indicators for the maturity which is closely related to the internal quality of cherry tomato, such as firmness, sugar content, and acidity. This study was carried out to investigate the relationship between surface color and internal quality of cherry tomatoes harvested from both hydroponic and soil culture at different ripening stages. To calculate the color values of cherry tomatoes an automatic color imaging system was constructed. A specially designed image processing algorithm for the color measurement was developed. The color values of L*, a*, b* were calculated from the initial color values of RGB and then compared with the internal quality. Statistical analyses indicated that the internal quality was more highly correlated with the surface color than size of cherry tomatoes. Color image features were also investigated to detect external damage of cherry tomatoes. The value of (R value - R mean value)/R mean value was the most effective image feature for the detection of damaged areas on the surface of cherry tomatoes. The results of this study demonstrated the feasibility of color sorting process as an alternative of the conventional drum type size sorting system for cherry tomato industry.

• Journal of Biosystems Engineering
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• 제35권6호
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• pp.450-457
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• 2010

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.