Korean Journal of Plant Resources (한국자원식물학회지)

The Plant Resources Society of Korea (한국자원식물학회)
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Development of Near-Infrared Reflectance Spectroscopy (NIRS) Model for Amylose and Crude Protein Contents Analysis in Rice Germplasm

근적외선 분광광도계를 이용한 벼 유전자원 아밀로스 및 단백질 함량분석을 위한 모델개발

  • Oh, Sejong (National Agrobiodiversity Center National Institute of Agricultural Sciences, RDA) ;
  • Lee, Myung Chul (National Agrobiodiversity Center National Institute of Agricultural Sciences, RDA) ;
  • Choi, Yu Mi (National Agrobiodiversity Center National Institute of Agricultural Sciences, RDA) ;
  • Lee, Sukyeung (National Agrobiodiversity Center National Institute of Agricultural Sciences, RDA) ;
  • Oh, Myeongwon (National Agrobiodiversity Center National Institute of Agricultural Sciences, RDA) ;
  • Ali, Asjad (National Agrobiodiversity Center National Institute of Agricultural Sciences, RDA) ;
  • Chae, Byungsoo (National Agrobiodiversity Center National Institute of Agricultural Sciences, RDA) ;
  • Hyun, Do Yoon (National Agrobiodiversity Center National Institute of Agricultural Sciences, RDA)
  • 오세종 (농촌진흥청 국립농업과학원 농업유전자원센터) ;
  • 이명철 (농촌진흥청 국립농업과학원 농업유전자원센터) ;
  • 최유미 (농촌진흥청 국립농업과학원 농업유전자원센터) ;
  • 이수경 (농촌진흥청 국립농업과학원 농업유전자원센터) ;
  • 오명원 (농촌진흥청 국립농업과학원 농업유전자원센터) ;
  • ;
  • 채병수 (농촌진흥청 국립농업과학원 농업유전자원센터) ;
  • 현도윤 (농촌진흥청 국립농업과학원 농업유전자원센터)
  • Received : 2016.09.13
  • Accepted : 2017.01.02
  • Published : 2017.02.28
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Abstract

The objective of this research was to develop Near-Infrared Reflectance Spectroscopy (NIRS) model for amylose and protein contents analysis of large accessions of rice germplasm. A total of 511 accessions of rice germplasm were obtained from National Agrobiodiversity Center to make calibration equation. The accessions were measured by NIRS for both brown and milled brown rice which was additionally assayed by iodine and Kjeldahl method for amylose and crude protein contents. The range of amylose and protein content in milled brown rice were 6.15-32.25% and 4.72-14.81%, respectively. The correlation coefficient ($R^2$), standard error of calibration (SEC) and slope of brown rice were 0.906, 1.741, 0.995 in amylose and 0.941, 0.276, 1.011 in protein, respectively, whereas $R^2$, SEC and slope of milled brown rice values were 0.956, 1.159, 1.001 in amylose and 0.982, 0.164, 1.003 in protein, respectively. Validation results of this NIRS equation showed a high coefficient determination in prediction for amylose (0.962) and protein (0.986), and also low standard error in prediction (SEP) for amylose (2.349) and protein (0.415). These results suggest that NIRS equation model should be practically applied for determination of amylose and crude protein contents in large accessions of rice germplasm.

본 연구에서는 벼 유전자원의 이화학적 대량 분석체계 구축을 위하여 비파괴 분석 방법 중의 하나인 근적외선 분광분석(NIRS) 예측모델을 개발하고, 미지 시료 적용 시 분석 정확도와 실재 적용가능성을 평가하기 위해 교차 검정과 외부 검정을 수행하였다. NIRS 예측모델 개발을 위해 농업유전자원센터 보유자원 중 511자원을 사용하였고, 그 중 아밀로스 농도 대표자원 200점을 추가 선정하여 보존자원과 증식자원의 아밀로스 및 단백질 성분 변화를 비교하였다. 습식분석 상호비교, t-Test를 통한 통계처리 결과로 볼 때 저장고 보존자원과 증식자원 간의 중대한 이화학적 성질의 변이 현상은 관측되지 않았으므로 NIRS 예측모델 개발에 보존자원을 사용하는 것은 가능할 것으로 판단되었다. 511 자원의 습식분석 결과 아밀로스 농도는 6.15-32.25%, 단백질 농도는 4.72-14.81%였다. 현미와 현미가루의 두 가지 시료 형태에 대한 NIR 스펙트럼을 얻었고 일련의 통계적 처리를 이용하여 NIRS 예측모델을 얻었다. 현미의 $R^2$, SEC, Slope 값은 아밀로스 농도의 경우 0.906, 1.741, 0.995였고, 단백질 농도의 경우 0.941, 0.276, 1.011 이었다. 현미가루의 $R^2$, SEC, Slope 값은 아밀로스 농도의 경우 0.956, 1.159, 1.001이었고, 단백질 농도의 경우 0.982, 0.164, 1.003이었다. 이와 같은 결과로 NIRS 예측모델 개발에는 가루형태의 시료가 효율적임을 알 수 있었다. 아밀로스 농도의 경우 9.62-16.58%의 자원밀도가 상대적으로 낮은 구간에 대한 보완을 위해 추가 200자원의 습식분석, NIRS 측정 수행하였으며, 보완된 최적 NIRS 예측모델의 $R^2$, SEC, Slope 값은 아밀로스 농도의 경우 0.970, 1.010, 1.000 이었고 단백질 농도의 경우 0.983, 0.158, 0.998이었다. 최적 NIRS 예측모델의 미지시료 적용 시 정확도를 평가하기 위해 아밀로스는 132자원, 조단백질은 124자원을 검정자원으로 사용하여 외부 검정과정을 거친 결과 $R^2$, SEP 값은 아밀로스 농도의 경우 0.962, 2.349였고, 단백질 농도의 경우 0.986, 0.415였다. 이상의 결과를 종합해 볼 때 본 연구에서 개발된 NIRS 예측모델은 습식분석방법을 대체하여 벼 유전자원의 아밀로스 및 단백질 농도의 대량 분석에 효율적으로 적용 가능할 것으로 판단된다.

Keywords

References

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