KOREAN JOURNAL OF CROP SCIENCE (한국작물학회지)

The Korean Society of Crop Science (한국작물학회)
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Statistical Analysis of Protein Content in Wheat Germplasm Based on Near-infrared Reflectance Spectroscopy

밀 유전자원의 근적외선분광분석 예측모델에 의한 단백질 함량 변이분석

  • Oh, Sejong (National Agrobiodiversity Center, National Institute of Agricultural Sciences, RDA) ;
  • Choi, Yu Mi (National Agrobiodiversity Center, National Institute of Agricultural Sciences, RDA) ;
  • Yoon, Hyemyeong (National Agrobiodiversity Center, National Institute of Agricultural Sciences, RDA) ;
  • Lee, Sukyeung (National Agrobiodiversity Center, National Institute of Agricultural Sciences, RDA) ;
  • Yoo, Eunae (National Agrobiodiversity Center, National Institute of Agricultural Sciences, RDA) ;
  • Hyun, Do Yoon (National Agrobiodiversity Center, National Institute of Agricultural Sciences, RDA) ;
  • Shin, Myoung-Jae (National Agrobiodiversity Center, National Institute of Agricultural Sciences, RDA) ;
  • Lee, Myung Chul (National Agrobiodiversity Center, National Institute of Agricultural Sciences, RDA) ;
  • Chae, Byungsoo (National Agrobiodiversity Center, National Institute of Agricultural Sciences, RDA)
  • 오세종 (농촌진흥청 국립농업과학원 농업유전자원센터) ;
  • 최유미 (농촌진흥청 국립농업과학원 농업유전자원센터) ;
  • 윤혜명 (농촌진흥청 국립농업과학원 농업유전자원센터) ;
  • 이수경 (농촌진흥청 국립농업과학원 농업유전자원센터) ;
  • 유은애 (농촌진흥청 국립농업과학원 농업유전자원센터) ;
  • 현도윤 (농촌진흥청 국립농업과학원 농업유전자원센터) ;
  • 신명재 (농촌진흥청 국립농업과학원 농업유전자원센터) ;
  • 이명철 (농촌진흥청 국립농업과학원 농업유전자원센터) ;
  • 채병수 (농촌진흥청 국립농업과학원 농업유전자원센터)
  • Received : 2019.09.19
  • Accepted : 2019.10.22
  • Published : 2019.12.31
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Abstract

A near-infrared reflectance spectroscopy (NIRS) prediction model was set to establish a rapid analysis system of wheat germplasm and provide statistical information on the characteristics of protein contents. The variability index value (VIV) of calibration resources was 0.80, the average protein content was 13.2%, and the content range was from 7.0% to 13.2%. After measuring the near-infrared spectra of calibration resources, the NIRS prediction model was developed through a regression analysis between protein content and spectra data, and then optimized by excluding outliers. The standard error of calibration, R2, and the slope of the optimized model were 0.132, 0.997, and 1.000 respectively, and those of external validation results were 0.994, 0.191, and 1.013, respectively. Based on these results, a developed NIRS model could be applied to the rapid analysis of protein in wheat. The distribution of NIRS protein content of 6,794 resources were analyzed using a normal distribution analysis. The VIV was 0.79, the average protein was 12.1%, and the content range of resources accounting for 42.1% and 68% of the total accessions were 10-13% and 9.5-14.6%, respectively. The composition of total resources was classified into breeding line (3,128), landrace (2,705), and variety (961). The VIV in breeding line was 0.80, the protein average was 11.8%, and the contents of 68% of total resources ranged from 9.2% to 14.5%. The VIV in landrace was 0.76, the protein average was 12.1%, and the content range of resources of 68% of total accessions was 9.8-14.4%. The VIV in variety was 0.80, the protein average was 12.8%, and the accessions representing 68% of total resources ranged from 10.2% to 15.4%. These results should be helpful to the related experts of wheat breeding.

본 연구는 근적외선 분광분석기(NIRS) 예측모델을 설정하여 유전자원 대량분석 체계를 확립하고 그에 따른 국내 외 밀 자원의 단백질 함량에 관한 기초 정보를 제공하고자 하였다. 1. 농업유전자원센터에 보유하고 있는 20,000여 자원 중 1,798자원을 검량 자원으로 선발하였다. 검량자원의 NIR 스펙트럼을 측정하였고, 단백질 함량 습식분석 데이터 입력 등 일련의 통계적 처리 과정을 거쳐 NIRS 예측모델을 설정했다. 검량 자원의 다양성 지수는 0.80이었고, 습식 분석법에 의한 단백질 평균은 13.2%, 함량 구간은 7.0-20.8%였다. 최적화된 NIRS 모델의 R2, SEC, Slope은 0.997, 0.132, 1.000이었다. 300자원을 사용하여 외부 검정 과정을 실시하였고 R2, SEP, Slope은 0.994, 0.191, 1.013이었다. 최적화된 NIRS 모델과 외부검정 결과의 통계치가 상호 유사하였고, 1에 가까운 R2와 Slope 값, 낮은 SEC와 SEP 값을 볼 때 본 연구에서 설정한 NIRS 모델은 습식 분석법을 대체하여 밀 자원의 단백질 함량 분석에 적용 가능할 것으로 판단되었다. 2. 국내외 수집된 밀 6,794자원의 NIRS 단백질 함량 측정값을 정규분포로 작성하여 특성을 파악했다. 자원의 다양성 지수는 0.79, 단백질 평균은 12.1%, 전체 자원의 임의구간 42.1% 단백질 함량자원 범위는 10-13%이었으며, 68.0%를 차지하는 자원들의 단백질 함량 범위는 9.5-14.7%였다. 3. 전체 6,794자원의 품종 집단 구성은 육성계통 3,128자원, 재래종 2,705자원, 육성품종 961자원이었다. 육성계통 자원의 다양성 지수는 0.80, 단백질 평균은 11.8%, 전체 자원의 68%를 차지하는 자원들의 함량 범위는 9.2-14.5%였다. 재래종 자원의 다양성 지수는 0.76, 단백질 평균은 12.1%, 전체 자원의 68.0%를 차지하는 자원들의 함량 범위는 9.8-14.4%였다. 육성품종 자원의 다양성 지수는 0.80, 단백질 평균은 12.8%, 전체 자원의 68.0%를 차지하는 자원들의 함량 범위는 10.2-15.4%였다. 재래종 자원은 가장 낮은 다양성 지수를 나타냈고, 육성계통과 육성품종은 동일한 다양성 지수를 나타냈다. 육성계통은 가장 낮은 단백질 평균을 나타냈고, 육성품종은 가장 높은 단백질 평균을 나타냈다.

Keywords

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