DOI QR코드

DOI QR Code

수화 시의 형태학적 특징에 따른 건해삼의 등급 분류 시스템 개발

Sea Cucumber (Stichopus japonicus) Grading System Based on Morphological Features during Rehydration Process

  • 이충욱 (강원대학교 농업생명과학대학 식품생명공학전공) ;
  • 윤원병 (강원대학교 농업생명과학대학 식품생명공학전공)
  • Lee, Choong Uk (Department of Food Science and Biotechnology, College of Agricultural and Life Science, Kangwon National University) ;
  • Yoon, Won Byong (Department of Food Science and Biotechnology, College of Agricultural and Life Science, Kangwon National University)
  • 투고 : 2016.11.17
  • 심사 : 2017.02.22
  • 발행 : 2017.03.31

초록

본 연구에서는 건해삼의 수화도에 따른 등급 분류를 확립하고자 하였다. 건해삼은 영상분석을 통하여 건해삼의 길이, 너비, 부피, 겉넓이의 형태학적 특징을 추출하였다. 측정된 data를 이용하여 k-mean clustering을 실시, 95개의 건해삼을 3개의 등급으로 분류하여 $30^{\circ}C$에서 40시간 수화실험을 실시하였다. 건해삼의 k-mean clustering을 실시한 결과 건해삼의 부피와 겉넓이는 건해삼의 등급을 가장 잘 나타낼 수 있는 인자였다. 등급별 수분 함량은 grade1은 71.23%, grade2는 75.60%, grade3는 85.62%를 확인하였다. 본 수화속도의 차이는 등급별 해삼이 동일한 수화 flux를 갖는 것을 고려하였을 때, 해삼의 수화는 겉넓이에 지배적임을 확인할 수 있다. 해삼의 수화는 물의 물질전달을 통해 이루어지며 Fick의 확산법칙에 따라 겉넓이가 커질수록 물질전달 속도가 증가함을 본 연구의 수화실험 결과에서도 확인할 수 있었다. 본 연구에서는 건해삼의 등급을 분류하여 최적의 수분 함량(75%)을 충족하기 위한 등급별 수화시간을 도출하였다. 본 연구에서 도출된 건해삼의 등급판별은 "수화도에 따른 건해삼의 품질 변화"에 대한 추가적인 연구를 통해 등급별 최적의 수화시간의 도출이 가능하다.

Image analysis and k-mean clustering were conducted to develop a grading system of dried sea cucumber (SC) based on rehydration rate. The SC images were obtained by taking pictures in a box under controlled light conditions. The region of interest was extracted to depict the shape of the SC in a 2D graph, and those 2D shapes were rendered to build a 3D model. The results from the image analysis provided the morphological features of the SC, including length, width, surface area, and volume, to obtain the parameters of the k-mean clustering weight. The k-mean clustering classified the SC samples into three different grades. Each SC sample was rehydrated at $30^{\circ}C$ for 40 h. During rehydration, the flux of each grade was analyzed. Our study demonstrates that the mass transfer rate of SC increased as the surface area increased, and the grade of SC was classified based on rehydration rate. This study suggests that the optimal rehydration process for SC can be achieved by applying a suitable grading system.

키워드

참고문헌

  1. Cui FX, Xue CH, Li ZJ, Zhang YQ, Dong P, Fu XY, Gao X. 2007. Characterization and subunit composition of collagen from the body wall of sea cucumber Stichopus japonicus. Food Chem 100: 1120-1125. https://doi.org/10.1016/j.foodchem.2005.11.019
  2. Gianasi BL, Hamel JF, Mercier A. 2016. Experimental test of optimal holding conditions for live transport of temperate sea cucumbers. Fish Res 174: 298-308. https://doi.org/10.1016/j.fishres.2015.11.004
  3. Duan X, Zhang M, Mujumdar AS. 2007. Study on a combination drying technique of sea cucumber. Drying Technol 25: 2011-2019. https://doi.org/10.1080/07373930701728497
  4. Fukunaga T, Matsumoto M, Murakami T, Hatae K. 2004. Effects of soaking conditions on the texture of dried sea cucumber. Fish Sci 70: 319-325. https://doi.org/10.1111/j.1444-2906.2003.00807.x
  5. Kim NG, Hong YK, Lee DG, Cho SH, Koh KC, Bahn SH, Hwang H, Yoon WB. 2013. Development of an image analysis system to evaluate the freshness of eggs. Food Eng Prog 17: 76-83.
  6. Matas J, Kittler J. 1995. Spatial and feature space clustering: applications in image analysis. Proceedings of the 6th International Conference on Computer Analysis of Images and Patterns. Prague, Czech Republic. p 162-173.
  7. Hartigan JA. 1975. Clustering algorithms (probability & mathematical statistics). 1st ed. John Wiley & Sons, New York, NY, USA. p 162-173.
  8. Dutta MK, Sengar N, Minhas N, Sarkar B, Goon A, Banerjee K. 2016. Image processing based classification of grapes after pesticide exposure. LWT-Food Sci Technol 72: 368-376. https://doi.org/10.1016/j.lwt.2016.05.002
  9. Zhang L, Huang X, Miao S, Zeng S, Zhang Y, Zheng B. 2016. Influence of ultrasound on the rehydration of dried sea cucumber (Stichopus japonicus). J Food Eng 178: 203-211. https://doi.org/10.1016/j.jfoodeng.2016.01.024
  10. Zhang Y, Hou H, Fan Y, Zhang F, Li B, Xue C. 2016. Effect of moisture status on the stability of thermal gels from the body wall of sea cucumbers (Apostichopus japonicus). LWT -Food Sci Technol 74: 294-302. https://doi.org/10.1016/j.lwt.2016.07.058
  11. Liming X, Yanchao Z. 2010. Automated strawberry grading system based on image processing. Comput Electron Agric 71: S32-S39. https://doi.org/10.1016/j.compag.2009.09.013
  12. Donis-Gonzalez IR, Guyer DE. 2016. Classification of processing asparagus sections using color images. Comput Electron Agric 127: 236-241. https://doi.org/10.1016/j.compag.2016.06.018
  13. Xing J, Saeys W, De Baerdemaeker J. 2007. Combination of chemometric tools and image processing for bruise detection on apples. Comput Electron Agric 56: 1-13. https://doi.org/10.1016/j.compag.2006.12.002
  14. Moon JH, Yoon WB. 2016. Size dependence of the salting process for dry salted sea cucumber (Stichopus japonicus). J Food Eng 170: 170-178. https://doi.org/10.1016/j.jfoodeng.2015.09.028
  15. Bae W, Roh SW. 2005. A study on K-means clustering. CSAM 12: 497-508. https://doi.org/10.5351/CKSS.2005.12.2.497
  16. Mirzaie A, Mohammadi T. 2012. Effect of ultrasonic waves on flux enhancement in microfiltration of milk. J Food Eng 108: 77-86. https://doi.org/10.1016/j.jfoodeng.2011.07.026
  17. Hong YK, Uhm JT, Yoon WB. 2014. Using numerical analysis to develop and evaluate the method of high temperature sous-vide to soften carrot texture in different-sized packages. J Food Sci 79: E546-E561. https://doi.org/10.1111/1750-3841.12427

피인용 문헌

  1. Sous-vide가열과 열탕가열 조건에 따른 콩나물 머리와 줄기의 조직감 변화에 관한 연구 vol.61, pp.3, 2017, https://doi.org/10.3839/jabc.2018.032
  2. 장기 저장 중 저장 온도와 습도에 따른 해품 콩의 콩나물 가공적성 연구 vol.63, pp.1, 2017, https://doi.org/10.3839/jabc.2020.001
  3. Rapid Production of Dried Sea Cucumber (Stichopus japonicus) Using Infrared Assisted Freeze Drying (IRAFD) vol.24, pp.4, 2020, https://doi.org/10.13050/foodengprog.2020.24.4.292