Research on the Robustness Improvement of Calibration Model for Measuring the Contents of Components in Milk by Multidimensional Calibration in Near-Infrared Spectroscopy
PENG Dan1，2,XU Ke-xin1*,SONG Yang1
1. State Key Laboratory of Precision Measuring and Instruments, Tianjin University, Tianjin 300072, China 2. College of Grain Oil and Food Science, Henan University of Technology, Zhengzhou 450052, China
Abstract：A new hybrid algorithm (NOSC-NPLS), the combination of multi-way orthogonal signal correction (N-OSC) algorithm and multi-way partial least squares (N-PLS) algorithm, is proposed. In NOSC-NPLS algorithm, the 3-D spectral matrix was firstly constructed, which is composed of the temperature information and the NIR spectrum. Secondly, the N-OSC algorithm was used as a pretreatment algorithm to remove the interference information irrelevant to analyte in 3-D spectral matrix. Finally, the N-PLS algorithm was applied to develop the calibration model based on the pretreated 3-D transmission spectral matrix and content matrix of major components in milk. In order to evaluate the performances of conventional algorithms and multidimensional calibration algorithms on suppressing the effects of temperature variation, a batch of milk samples at temperature of 25, 30, 35 and 40 ℃ were measured in the wavelength range from 1 100 to 1 700 nm and the experimental results were investigated. It was found that the conventional algorithms, which could not suppress the effects caused by temperature variation, failed to obtain satisfactory results. However, compared with these algorithms, the experimental results showed that the NOSC-NPLS algorithm can effectively eliminate the effects of temperature variation and also can help achieve the analytic models with better prediction ability and robustness.
彭丹1，2,徐可欣1*,宋扬1. 用多维校正法提高近红外牛奶成分校正模型稳健性的研究[J]. 光谱学与光谱分析, 2009, 29(04): 913-917.
PENG Dan1，2,XU Ke-xin1*,SONG Yang1. Research on the Robustness Improvement of Calibration Model for Measuring the Contents of Components in Milk by Multidimensional Calibration in Near-Infrared Spectroscopy. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2009, 29(04): 913-917.
[1] YAN Yan-lu, ZHAO Long-lian, HAN Dong-hai, et al(严衍禄，赵龙莲，韩东海，等). Principle and Application of Near Infrared Spectroscopy(近红外光谱分析基础与应用). Beijing: Light Industry Press of China(北京：中国轻工业出版社), 2005. [2] WANG Li-jie, XU Ke-xin, GUO Jian-ying(王丽杰, 徐可欣, 郭建英). Journal of Optoelectronics·Laser(光电子·激光), 2004, 15(4): 468. [3] Sasic S, Ozaki Y. Appl. Spectrosc., 2000, 54: 1327. [4] Thygesen L G J. J. Near Infrared Spectrosc., 2000, 8: 183. [5] Kamal Y T, Vidi A S. Progress Report, 2000, 3: 2. [6] Hazen K H, Arnold M A, Small G W. Applied Spectroscopy, 1994, 48(4): 477. [7] Florian W, Wm Th Kok, Age K S. Anal. Chem.，1998, 70: 1761. [8] CHU Xiao-li, YUAN Hong-fu, WANG Yan-bin, et al(褚小立, 袁洪福, 王艳斌, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2004, 24(6): 666. [9] ZHANG Jun, CHEN Hua-cai, CHEN Xing-dan(张 军, 陈华才, 陈星旦). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2005, 25(6): 890. [10] Venyaminov S Yu, Prendergast F G. Anal. Biochem., 1997, 248: 234. [11] Fornes V, Chaussidon J. J. Chem. Phys., 1978, 68: 4667. [12] CHANG Min, PENG Dan, XU Ke-xin(常 敏, 彭 丹, 徐可欣). Acta Optica Sinica(光学学报), 2007, 27(6): 1080. [13] http: //www.foodsci.uoguelph.ca/dairyedu/chem.html. [14] Andersson C A, Bro R. Chemometrics and Intelligent Laboratory Systems, 1998，42: 93. [15] Bro R. J. Chemometrios, 1996, 10(1): 47. [16] Peinado A C, van den F Berg, Blanco M, et al. Chemometrics and Intelligent Laboratory Systems, 2006，83: 75.
