光谱学与光谱分析 |
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Determination of Process Variable pH in Solid-State Fermentation by FT-NIR Spectroscopy and Extreme Learning Machine (ELM) |
LIU Guo-hai, JIANG Hui*, XIAO Xia-hong, ZHANG Dong-juan, MEI Cong-li, DING Yu-han |
School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China |
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Abstract Fourier transform near-infrared (FT-NIR) spectroscopy was attempted to determine pH, which is one of the key process parameters in solid-state fermentation of crop straws. First, near infrared spectra of 140 solid-state fermented product samples were obtained by near infrared spectroscopy system in the wavelength range of 10 000~4 000 cm-1, and then the reference measurement results of pH were achieved by pH meter. Thereafter, the extreme learning machine (ELM) was employed to calibrate model. In the calibration model, the optimal number of PCs and the optimal number of hidden-layer nodes of ELM network were determined by the cross-validation. Experimental results showed that the optimal ELM model was achieved with 10-40-1 topology construction as follows: Rp=0.961 8 and RMSEP=0.104 4 in the prediction set. The research achievement could provide technological basis for the on-line measurement of the process parameters in solid-state fermentation.
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Received: 2011-09-12
Accepted: 2011-11-28
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Corresponding Authors:
JIANG Hui
E-mail: jiangh1118@163.com
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[1] HAN Lu-jia, YAN Qiao-juan, LIU Xiang-yang, et al(韩鲁佳,闫巧娟,刘向阳,等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2002, 18(3): 87. [2] SHAN Gu, LUO Lian, YU Shi-yuan(单 谷,罗 廉,余世袁). Journal of Nanjing Forestry University(南京林业大学学报), 1999, 23(3): 60. [3] Chen Q, Zhao J, Liu M, et al. Journal of Pharmaceutical and Biomedical Analysis, 2008, 46(3): 568. [4] ZHU Wei-xing, JIANG Hui, CHEN Quan-sheng, et al(朱伟兴,江 辉,陈全胜,等). Transactions of the Chinese Society of Agricultural Machinery(农业机械学报), 2010, 41(10): 129. [5] FANG Li-min, LIN Min(方利民,林 敏). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2010, 30(11): 2958. [6] WU Yu-ping, CHEN Ping, LI Ying-jin, et al(吴玉萍,陈 萍,李应金,等). Chinese Journal of Spectroscopy Laboratory(光谱实验室), 2008, 25(3): 465. [7] Soons Z I T A, Streefland M, van Straten G, et al. Chemometrics and Intelligent Laboratory Systems, 2008, 94(2): 166. [8] Ward A J, Hobbs P J, Holliman P J, et al. Bioresource Technology, 2011, 102(5): 4083. [9] Cozzolino D, Kwiatkowski M J, Parker M, et al. Analytica Chimica Acta, 2004, 513(1): 73. [10] Tosi S, Rossi M, Tamburini E, et al. Biotechnology Progress, 2003, 19(6): 1816. [11] McLeod G, Clelland K, Tapp H, et al. Journal of Food Engineering, 2009, 90(2): 300. [12] Cozzolino D, Parker M, Dambergs R G, et al. Biotechnology and Bioengineering, 2006, 95(6): 1101. [13] Huang G B, Zhu Q Y, Siew C K. Neurocomputing, 2006, 70(1-3): 489. |
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