KSBB Journal

The Korean Society for Biotechnology and Bioengineering (한국생물공학회)
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Chemometric Analysis of 2D Fluorescence Spectra for Monitoring and Modeling of Fermentation Processes

생물공정 모니터링 및 모델링을 위한 2차원 형광스펙트럼의 다변량 분석

  • Kang Tae-Hyoung (Department of Industrial Engineering, Research Center for Biophotonics, Chonnam National University) ;
  • Sohn Ok-Jae (Department of Material Chemical and Biochemical Engineering, BioProcess Technology Lab., Research Center for Biophotonics, Chonnam National University) ;
  • Kim Chun-Kwang (Department of Material Chemical and Biochemical Engineering, BioProcess Technology Lab., Chonnam National University) ;
  • Chung Sang-Wook (Department of Industrial Engineering, Research Center for Biophotonics, Chonnam National University) ;
  • Rhee Jong-Il (School of Applied Chemical Engineering, BioProcess Technology Lab., Research Center for Biophotonics, Chonnam National University)
  • 강태형 (전남대학교 공과대학 산업공학과, 바이오 광기반기술개발사업단) ;
  • 손옥재 (전남대학교 공과대학 물질.생물화공과, 생물공정기술연구실, 바이오 광기반기술개발사업단) ;
  • 김춘광 (전남대학교 공과대학 물질.생물화공과, 생물공정기술연구실) ;
  • 정상욱 (전남대학교 공과대학 산업공학과, 바이오 광기반기술개발사업단) ;
  • 이종일 (전남대학교 공과대학 응용화공학부, 생물공정기술연구실, 바이오 광기반기술개발사업단)
  • Published : 2006.02.01
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Abstract

2D spectrofluorometer produces many spectral data during fermentation processes. The fluorescence spectra are analyzed using chemometric methods such as principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLS). Analysis of the spectral data by PCA results in scores and loadings that are visualized in score-loading plots and used to monitor a few fermentation processes by S. cerevisae and recombinant E. coli. Two chemometric models were established to analyze the correlation between fluorescence spectra and process variables using PCR and PLS, and PLS was found to show slightly better calibration and prediction performance than PCR.

본 연구에서는 2차원 형광스펙트럼의 PCA 분석을 통하여 발효 공정을 모니터링하고 PCR과 PLS과 같은 다변량 분석기법을 이용하여 공정을 모델링하였다. 재조합 대장균 E. coli 와 효모 S.cerevisiae의 발효 공정 중에 얻어진 많은 양의 2차원 형광스펙트럼 자료는 우선 PCA를 통해 축소된다. 그리고 PCA에서 주성분점수와 적재 산점도는 발효 공정의 정성적 경향을 묘사하기 위해 사용되었다. 또한, PCR과 PLS는 2차원 형광스펙트럼의 분석을 위해 사용되었으며 PLS모델이 보정과 예측 능력에서 PCR모델보다 조금 더 우수한 성능을 나타냈다. 따라서 2차원 형광스펙트럼 자료를 이용하여 생물공정을 모델링 하고자 할 때는 PCR 방법보다는 PLS 방법을 사용하는 것이 유리할 것이다.

Keywords

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