不同傅里叶近红外仪器间(积分球漫反射测量)的模型传递及误差分析

doi:10.3964/j.issn.1000-0593(2019)03-0964-05

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Abstract Model transfer is a key common technical problem in the near infrared spectral analysis technology. By seeking feasible mathematical methods between the two instruments that have the same working principle, we can make the model which was set up on one instrument be applied to another one. In this paper, with 150 flue-cured tobaccos as test samples, with two Bruker MPA near infrared spectrometer and one Thermo Antaris near infrared spectrometer as the research object. We obtained spectral data by integrating sphere diffuse reflectance. Processed and analyzed the spectral data by using the first derivative and standard normal variate (SNV) transformation, and calculated the value of residual error between different instruments, first moment, signal probability density and maximum signal to noise ratio(SNR) and so on. Also, we established mathematical model of total sugar content by partial least squares (PLS) to test the effect of model transfer. The results showed that first derivative could reduce the first moment and transfer the deviation between different instruments into the standard Gaussian distribution, but at the same time, it could also put SNR down. SNV could also reduce the first moment and even could do better than first derivative, and it could increase SNR significantly, but SNR could not transfer the deviation into standard Gaussian distribution, which would need other ways to make up for it. The combination method of the first derivative and SNV can retain the advantages of both, and make up for the disadvantages of individual treatment, and it can settle the model transfer problem caused by different instrument types and different using time between different instruments that work in the principle of Fourier, which is based on the integrating sphere diffuse reflectance. This method is an ideal model transfer method without the prototype.

Key words：Model transfer; First-order derivative; Standard normal variate

Received: 2016-03-08 Accepted: 2017-01-05

ZTFLH:

O657.3

Corresponding Authors: LI Jun-hui E-mail: caunir@cau.edu.cn

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https://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2019)03-0964-05 OR https://www.gpxygpfx.com/EN/Y2019/V39/I03/964

[1] YAN Yan-lu, ZHAO Long-lian, HAN Dong-hai, et al(严衍禄，赵龙莲，韩东海，等). Foundation and Application of NIR Spectra Analysis(近红外光谱分析基础与应用). Beijing: China Light Industry Press(北京：中国轻工业出版社), 2005. 13.
[2] YAN Yan-lu(严衍禄). The Principle, Technique and Application of NIR Spectra Analysis(近红外光谱分析的原理、技术与应用). Beijing: China Light Industry Press(北京：中国轻工业出版社), 2013. 35.
[3] JI Na-yu, HAN Dong-hai(吉纳玉, 韩东海). Journal of Food Safety & Quality(食品安全质量检测学报), 2014(3).
[4] Wang Yongdong, Velramp David J, Kowalski Bruce R. Anal. Chem., 1991, 63 2750.
[5] Shenk J S, Wes terhaus M O. U. S. Patent: 4866644, Sept. 12, 1989.
[6] Blank Thomas B, Brown Steven D. Anal. Chem., 1996, 68(17): 2987.
[7] Goodacre Royston, Timmins Eadaoin M, Jones Alun, et al. Analytica Chimica Acta, 1997, 348(1-3): 511.
[8] Kirsten E K, Robert E M, Susan L R. Chemometrics and Intelligent Laboratory Systems，2008, 92: 33.
[9] Roychoudhury P，O’Kennedy R，McNeil B，et al. Analytica Chimica Acta, 2007, 590(1): 110.
[10] Tan H W, Brown S D. Journal of Chemometrics, 2002, 16(5): 228.
[11] YANG Hui-hua, ZHANG Xiao-feng, CHU Xiao-li(杨辉华，张晓峰，褚小立). Chinese Journal of Analytical Chemistry(分析化学), 2014，(9): 1229.
[12] SHI Xin-zhen，WANG Zhi-guo，CHEN Zeng-ping(史新珍，王志国，陈增平). Chinese Journal of Analytical Chemistry(分析化学), 2014, (11): 1673.
[13] LIANG Yi-zeng, YU Ru-qin(梁逸曾, 俞汝勤). Analytical Chemsitry Manul (10)—Stoichiometry(分析化学手册(10)—化学计量学). Beijng: Chemical Industry Press(北京: 化工出版社), 2001.
[14] CHU Xiao-li, YUAN Hong-fu, LU Wan-zhen(褚小立, 袁洪福, 陆婉珍). Progress in Chemistry(化学进展), 2004, 16(4): 528.
[15] Papoulis A. Probability, Random Variables, Stochastic Processes, 2nd ed. New York: McGraw-Hill, 1984.