Korean Journal of Agricultural Science (농업과학연구)

Institute of Agricultural Science, CNU (충남대학교 농업과학연구소)
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Study on Quality Factor Measurement for Cherry Tomato using Color Imagery

칼라영상을 이용한 방울토마토 품질 인자 계측에 관한 연구

  • Kim, Dae-Yong (Department of Biosystem Machinery Engineering, Chungnam National University) ;
  • Oh, Hyun-Keun (Department of Biosystem Machinery Engineering, Chungnam National University) ;
  • Lee, Nam-Keun (Department of Biosystem Machinery Engineering, Chungnam National University) ;
  • Kim, Young-Sik (Department of Plant Industry Engineering, Sangmyung University) ;
  • Cho, Byung-Kwan (Department of Biosystem Machinery Engineering, Chungnam National University)
  • 김대용 (충남대학교 농업생명과학대학 바이오시스템 기계공학전공) ;
  • 오현근 (충남대학교 농업생명과학대학 바이오시스템 기계공학전공) ;
  • 이남근 (충남대학교 농업생명과학대학 바이오시스템 기계공학전공) ;
  • 김영식 (상명대학교 산업대학 식물산업공학전공) ;
  • 조병관 (충남대학교 농업생명과학대학 바이오시스템 기계공학전공)
  • Received : 2010.08.20
  • Accepted : 2010.09.17
  • Published : 2010.09.30
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Abstract

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.

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References

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