Journal of Biosystems Engineering

  • 제34권3호
  • /
  • Pages.197-203
  • /
  • 2009
  • /
  • 1738-1266(pISSN)
  • /
  • 2234-1862(eISSN)
한국농업기계학회 (Korean Society for Agricultural Machinery)
권호 표지
DOI QR코드

DOI QR Code

단감의 당도예측모델 개발에 관한 연구

Development of Prediction Models for Nondestructive Measurement of Sugar Content in Sweet Persimmon

  • Son, J.R. (Department of Agricultural Engineering, National Academy of Agricultural Science) ;
  • Lee, K.J. (Department of Agricultural Engineering, National Academy of Agricultural Science) ;
  • Kang, S. (Department of Agricultural Engineering, National Academy of Agricultural Science) ;
  • Kim, G. (Department of Agricultural Engineering, National Academy of Agricultural Science) ;
  • Yang, G.M. (Department of Agricultural Engineering, National Academy of Agricultural Science) ;
  • Mo, C.Y. (Department of Agricultural Engineering, National Academy of Agricultural Science) ;
  • Seo, Y. (Department of Biosystems and Biomaterials Science and Engineering, Seoul National University)
  • 발행 : 2009.06.25
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This study was performed to develop a nondestructive determination technology for sugar content in sweet persimmons, and the main research results included the following. In order to determine sugar content in sweet persimmons, a dual side reflex was adopted, and the study was to measure sugar content using a reflectance spectrum for 2 parts because it was difficult to determine representative sugar content due to a great deviation in sugar content according to the part of sweet persimmons. To predict sugar contents of sweet persimmon, PLSR and PCR models were compared with a few preprocess methods. As a result, PLSR had $R^2$=0.67, SEP=0.42 brix, LV=11, and PCR had $R^2$=0.65, SEP=0.41 brix, PC=16. SNV method was the best among preprocess methods for predicting sugar contents.

키워드

참고문헌

  1. Birth, G. S. 1978. Non destructive quality evaluation of agricultural products-introduction. Journal of Food Protection 41: 48-49 https://doi.org/10.4315/0362-028X-41.1.48
  2. Choi, C. H., K. J. Lee and B. S. Park. 1997. Prediction of soluble solid and firmness in apple using Vis/NIR-infrared spectroscopy. Journal of Biosystems Engineering 22(2): 256-265
  3. Choi. J. S. 2006. Agricultural outlook 2006. Korea Rural Economic Institute, Seoul, Korea
  4. Clark, C. J., V. A. McGlone and R. B. Jordan. 2003. Detection of brownheart in 'Braeburn' apple by transmittance NIR spectroscopy. Postharvest Biology and Technology 28:87-96 https://doi.org/10.1016/S0925-5214(02)00122-9
  5. Coen, T., W. Saeys, H. Ramon and J. De Baerdemaeker. 2006. Optimizing the tuning parameters of least squares support vector machines regression for NIR spectra. Journal of Chemometrics 20:184-192 https://doi.org/10.1002/cem.989
  6. Cozzolino, D., R. G. Dambergs, L. Janik, W. U. Cynkar and M. Gishen. 2006. Analysis of grapes and wine by near infrared spectroscopy. Journal of Near Infrared Spectroscopy 14: 279-289 https://doi.org/10.1255/jnirs.679
  7. Greenshill, C. V. and K. B. Walsh. 2000. A remote acceptance probe and illumination configuration for spectral assessment of internal attributes of intact fruit. Measurement Science Technology 11(12):1674-1684 https://doi.org/10.1088/0957-0233/11/12/304
  8. Kang, C. K. 1999. A historical study on fruits in Korea. Korean Journal of Dietary Culture 5:301-312
  9. Kawano, S. 1994. Non destructive NIR quality evaluation of fruits and vegetables in Japan. NIR news 5(6):10-12
  10. Kim, G., K. Lee, J. Son, D. Choi and S. Kang. 2004. Defect and ripeness inspection of citrus using NIR transmission spectrum. Key Engineering Material 270-273:1018-1013
  11. Kim, I. S. S. K. Jin and C. J. Ha. 2008. Improved quality properties of low-fat meat patties containing sweet persimmon powder during freeze storage. Korean Journal of Food Science Animal Resource 28(2):113-121 https://doi.org/10.5851/kosfa.2008.28.2.113
  12. Kim, J., A. Mowat, P. Poole and N. Kasabov. 2000. Linear and non-linear pattern recognition models for classification of fruit from visible-near infrared spectra. Chemometrics and Intelligent Laboratory Systems 51:201-216 https://doi.org/10.1016/S0169-7439(00)00070-8
  13. Lammertyn, J., B. Nicolai, K. Ooms, V. De Smedt and J. De Baerdemaerker. 1998. Non-destructive measurment of acidity, soluble solids, and firmness of Jonagold apples using NIR spectroscopy. Transaction of the ASAE 41:1089-1094 https://doi.org/10.13031/2013.17238
  14. Martens, H. and T. Naes. 1989. Multivariate Calibration, JOHN WILEY & SONS, Chichester, UK
  15. Naes, T., T. Isaksson, T. Fearn and T. Davies. 2004. A user-friendly guide to multivariate calibration and classification. NIR publications, Charlton, Chichester, UK
  16. Naes, T., K. Kvaal, T. Isaksson and C. Miller. 1993. Artificial neural networks in multivariate calibration. Journal of Near Infrared Spectroscopy 1:1-11 https://doi.org/10.1255/jnirs.1
  17. Son, J. R., K. J. Lee, S. Kang and W. K. Choi. 2008. Quality evaluation of sugar contents for grapes using NIR spectroscopy. Journal of Food Engineering Progress 12(4):263-268
  18. Seo, Y., K. J. Lee and S. H. Noh. 2007. Study for nondestructive detection algorithm development of the internal browning and watercore of fuji apple using VIS/NIR transmittance spectroscopy. Journal of Food Engineering Progress 11(1): 38-44
  19. Vegard, H. B. H. M. Segtnan, I. Tomas and N. Tormod. 2005. Low-cost approaches to robust temperature compensation in near-infrared calibration and prediction situations. Applied Spectroscopy 59(6):816-825 https://doi.org/10.1366/0003702054280586
  20. Wold, S., M. Sjostrom and L. Eriksson. 2001. PLS-regression : a basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems 58:109-130 https://doi.org/10.1016/S0169-7439(01)00155-1
  21. Zude-Sasse, M., I. Truppel. and B. Herold. 2002, An approach to non-destructive apple chlorophyll determination. Postharvest Biology and Technology 25(2):123-133 https://doi.org/10.1016/S0925-5214(01)00173-9

피인용 문헌

  1. Development of non-destructive pungency measurement technique for red-pepper powder produced in different domestic origins vol.39, pp.4, 2012, https://doi.org/10.7744/cnujas.2012.39.4.603