Study on the Analysis of the Proportion of Mixed Samples with Near Infrared Spectroscopy and Non-Negative Coefficients Regression
LI Xue-ying1, SHU Ru-xin2, LUAN Li-li1, LI Kai1, YANG Kai2, LI Jun-hui1*, ZHAO Long-lian1, ZHANG Ye-hui1, ZHANG Lu-da3
1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China 2. Technology Center of Shanghai Tobacco (Group) Corporation, Shanghai 200082, China 3. College of Science, China Agricultural University, Beijing 100083, China
Abstract：In the process of practical production, it is important to accurately analyze the proportion of mixed samples with high speed, which plays a great role for quality control and formulation design in food and agricultural processing. Traditional solution is to build statistical model with a large number of representative samples, which is both labor-intensive and time-consuming. In this paper, the proportion of alcohol and acids mixed samples，and their dilute solution mixed samples(used carbon tetrachloride (CCl4) which has no near-infrared absorption characteristics as the solvent medium)，as well as sheet tobacco leaf mixed samples are respectively analyzed by using near infrared spectroscopy, SG smooth and non-negative coefficients regression, which verifies the feasibility of analyzing the proportion of the mixed samples. The results show that, the analytic proportion of transmission spectra of alcohol and acids according to non-negative coefficients regression is closer to actual molar proportion with result error less than 4%. The result of the dilute solution is much better with error less than 4%. The analytic proportion of diffuse reflectance spectra of sheet tobacco leaf according to non-negative coefficients regression is highly accurate with error less than 10%. In the meantime, it has a highly consistency between actual spectra and analytic spectra of mixed samples; and the result of F-test and T-test shows that there is no significant difference between them and the confidence level is 0.01. It has the reliability of analytical proportion in theory. With the spectral data of several pure samples, the proportion of mixed samples can be thus analyzed, which has a good application prospect for quality control and formulation design in food and agricultural processing.
李雪莹1，束茹欣2，栾丽丽1，李 凯1，杨 凯2，李军会1*，赵龙莲1，张晔晖1，张录达3 . 近红外光谱结合非负回归系数回归法(配方回归)解析混合样品的组成比例 [J]. 光谱学与光谱分析, 2016, 36(04): 967-971.
LI Xue-ying1, SHU Ru-xin2, LUAN Li-li1, LI Kai1, YANG Kai2, LI Jun-hui1*, ZHAO Long-lian1, ZHANG Ye-hui1, ZHANG Lu-da3 . Study on the Analysis of the Proportion of Mixed Samples with Near Infrared Spectroscopy and Non-Negative Coefficients Regression. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2016, 36(04): 967-971.
[1] Rinnan A，van den Berg F，Engelsen S B. TrAC-Trends in Analytical Chemistry, 2009，28(10): 1201. [2] Qian G，Wang Z Y. Chemistry-an Asian Journal, 2010，5(5): 1006. [3] 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. [4] Guillarme D，Casetta C，Bicchi C，et al. Journal of Chromatography A, 2010，1217(44): 6882. [5] Bulat FA，Toro-Labbe A，Brinck T，et al. Journal of Molecular Modeling, 2010，16(11): 1679. [6] Gu Haiwei，Pan Zhengzheng，Xi Bowei，et al. Analytica Chimica Acta, 2011, 688(1-2): 57. [7] Martelo-Vidal M J，Vazquez M. CyTA-Journal of Food M, 2015，13(1): 32. [8] Tenorio-Borroto E，Rivas C G P，Chagoyan J C V，et al. Bioorganic & Medicinal Chemistry, 2012，20(20): 6181. [9] Galtier O，Abbas O，Le Dreau Y，et al. Vibrational Spectroscopy, 2011，55(1): 132. [10] Tong Hong，Tang Jun，Zhang Zhengfang. China Condiment, 2014，39(4): 54. [11] Zude M，Pflanz M，Spinelli L，et al. Journal of Food Engineerin, 2011，103(1): 68. [12] Chen X G，Li W W，Wu J D，et al. Materials Research Bulletin, 2012，47(1): 111. [13] Liu W，Wang Z Z，Qing J P，et al. Pharmacognosy Magazine, 2014, 10(40): 441. [14] Tabari H，Sabziparvar A A，Ahmadi M. Meteorology and Atmospheric Physics, 2011，110(3-4): 135. [15] WANG Ju-xiang，LI Hua，XING Zhi-na, et al(王菊香, 李 华, 邢志娜, 等). Chinese Journal of Analytical Chemistry(分析化学), 2011，39(6): 846. [16] Wang Jianguo, Jang Shishang, Wong David Shan-Hill. Control Engineering Practice, 2013, 21(9): 1157. [17] Pan Changchun, Bai Jie, Yang Genke. Journal of Process Control，2012, 22(9): 1637. [18] FANG Kai-tai, HE Shu-dong(方开泰，贺曙东). Mathematica Numerica Sinica(计算数学)，1985, 8: 237. [19] FANG Kai-tai, WANG Dong-qian, WU Guo-fu(方开泰，王东谦，吴国富). Mathematica Numerica Sinica(计算数学)，1982, 2: 57. [20] DONG Han-zhong，ZHANG Xiao-wei(董汉忠, 张小薇). Journal of Computer Applications(计算机应用)，1983, 4: 40.
