Nondestructive Measurement of Chemical Compositions in Polished Rice and Brown Rice using NIR Spectra of Hulled Rice acquired in Transmittance and Reflectance Modes

정조 상태에서 투과법과 반사법을 이용한 백미 및 현미 성분의 비파괴 측정

  • Kwon Young-Rip (Jeollabuk-do Agricultural Research and Extension Services) ;
  • Cho Seung-Hyun (Jeollabuk-do Agricultural Research and Extension Services) ;
  • Song Young-Eun (Jeollabuk-do Agricultural Research and Extension Services) ;
  • Lee Jae-Heung (Jeollabuk-do Agricultural Research and Extension Services) ;
  • Cho Chong-Hyeon (Jeollabuk-do Agricultural Research and Extension Services)
  • Published : 2006.09.01

Abstract

The purpose of this study is to measure fundamental data required for the prediction of rice quality and to develop regression models to predict protein, amylose, moisture and fatty acid contents, and Toyo taste meter value (TTMV) of brown and polished rice from hulled rice NIR spectra. NIR spectra of hulled rice measured in transmittance mode (850-1050 nm) and in reflectance mode (400-2500 nm) were used to predicted chemical compositions of brown rice and polished rice. For most chemicals, the transmittance spectra could provide better calibration results than the reflectance ones. Beside the Toyo taste meter value (TTMV), the hulled rice spectra could predict chemical contents with the determination coefficients higher than 0.8. Spectra of hulled rice measured in transmittance mode could be used for the prediction of chemical compositions in brown rice and polished rice precisely. However, taste value of polished rice was a constituent that was hardly to be predicted.

분쇄하지 않은 정조상태에서 현미와 백미의 성분을 측정 할 목적으로 수확 후 정조로부터 스펙트럼을 획득하였고(투과법 : 850-1050 nm, 반사법 : 400-2500 nm) 현미와 백미의 단백질, 아밀로스, 지방산, 수분함량, 식미값의 예측모델을 개발하여 그 정밀도를 비교 검토하기 위해서 일련의 시험을 실시한 결과는 다음과 같다. 투과법으로 정조의 스펙트럼을 수집한 후 현미의 단백질, 아밀로스, 지방산, 수분함량의 검량식을 작성한 결과 0.9001, 0.8321, 0.8077, 0.9553의 결정계수를 나타냈다. 백미의 단백질, 아밀로스, 수분함량, 식미값의 검량식을 작성한 결과 0.8255, 0.8559, 0.8226, 0.3421의 결정계수를 나타냈다. 반사법으로 정조의 스펙트럼을 수집한 후 현미의 단백질, 아밀로스, 지방산, 수분함량의 검량식을 작성한 결과 0.8286, 0.7705, 0.9094, 0.9694의 결정계수를 나타냈다. 백미의 단백질, 아밀로스, 수분함량, 식미값의 검량식을 작성한 결과 0.7904, 0.7679, 0.8435, 0.4881의 결정계수를 나타냈다. 이상의 결과에 의해서 단백질, 아밀로스, 지방산, 수분함량은 실용적인 결정계수를 얻었으나, 식미값은 결정계수가 너무 낮아 계속적인 연구가 필요하다고 판단하였다.

Keywords

References

  1. Abrams, S. M., J. S. Shenk, M. O. Westerhaus, and F. E. Barton. 1987. Determination of forage quality by near infrared reflectance spectroscopy : Efficiency of broadbased calibration equations. J. Diary Sci. 70 : 806-813 https://doi.org/10.3168/jds.S0022-0302(87)80077-2
  2. Clarke, M. A., E. R. Arias, and C. McDonald-Lewis. 1992. Near infra-red analysis in the sugarcane factory. Sugary Azucar. pres. at Ruspam Commun. Inc. USA
  3. Han C. S. and M. Y. Natsuga. 1996. Development of a constituent prediction model of domestic rice using near infrared reflectance analyzer( 1) -Constituent prediction model of brown and milled rice- J. Korean Soc Agric. Machin. 21(2) : 198-207
  4. Han C. S., K. S. Yon, and J. R. Warashina. 1998. Development of a constituent prediction model of domestic rice using near infrared reflectance analyzer (II) -Prediction of brown and milled rice protein content and brown rice yield from undried paddy- J. Korean Soc. Agric, Machin. 23(3), 253-258
  5. Hymowitz, T., J. W. Dudley. F. I. Collins, and C. M. Brown. 1974. Estimation of protein and oil concentration in com, soybean, and oat seed by near infrared light reflectance. Crop Sci. 14 : 713-715 https://doi.org/10.2135/cropsci1974.0011183X001400050031x
  6. Ishima, T., H. Taira, and K. Mikoshiba. 1974. Effects of nitrogenous fertilizer and protein content in milled rice on organoleptic quality of cooked rice. Rep. Nat. Food Res. Inst. 29 : 9-15
  7. Kim J. M., B. K. Min, and C. H. Choi. 1997. Development of rice milling ratio by visible/Near-infrared spectroscopy. J. Korean Soc. Agric, Machin. 22(1) : 333-342
  8. Kim J. M .. C. H. Choi. B. K. Min. and J. H. Kim. 1998. Development of prediction model for moisture and protein content of single kernel rice using spectroscopy. J. Korean Soc. Agric. Machin. 23(1) : 49-56
  9. Kwon Y. R., M. H. Baek, D. C. Choi, J. S. Choi, and Y. G. Choi. 2005. Determination of calibration curve for total nitrogen contents analysis in fresh rice leaf using the visible and near infrared spectroscopy system. Korean J. Crop Sci. 50 : 394-399
  10. Marshall, W. E. and J. I. Wadsworth. 1993. Degree of Milling. Rice Science and Technology. Marcel Dekker, Inc. New York 139-176
  11. Marten, G. C., J. L. Halgerson, and J. H. Cherney. 1983. Quality prediction of small grain forage by near infrared reflectance spectroscopy. Crop Sci. 23 : 94-96 https://doi.org/10.2135/cropsci1983.0011183X002300010027x
  12. Park, K. H., Pyun, C. H. and Han, J. P. 2004, Development of a digital chlorophyll meter II. Manufacturing of digital chlorophyll meter. Korean J. Crop Sci. 49 : 198-199
  13. Rubenthaler, G. L. and B. L. Bruinsma 1979. Lysine estimation in cereals by near infrared reflectance. Crop Sci. 19 : 1039-1042
  14. Shenk, J. S., I. Landa, M. R. Hoover, and H. O. Westerhaus. 1981. Description and evalution of a near infrared reflectance spectro-computer for forage and grain analysis. Crop Sci. 21 : 355-358 https://doi.org/10.2135/cropsci1981.0011183X002100030001x
  15. Son J. R., J. H. Kim, J. I. Lee, Y. H. Youn, and J. K. Kim, H. G. Hwang, and H. P. Moon. 2002. Trend and further research of rice quality evaluation. Korean J. Crop Sci. 47(s) : 33-54
  16. Williams, P. C., H. M. Corderiro, and M. F. T. Harnden. 1991. Analysis of oat bran products by near infrared reflectance spectroscopy. Cereal Foods World 36 : 571-574