[1] [1] Wang G W, Yang C H, Zhu H Q, et al. State-transition-algorithm-based resolution for overlapping linear sweep voltammetric peaks with high signal ratio［J］. Chemometrics and Intelligent Laboratory Systems, 2016, 151: 61-70.

[2] [2] Tai Ling, Gong Qiaojuan, Sun Hong, et al. Application of water quality monitoring by fluorescence spectrometry［J］. Chinese Journal of Spectroscopy Laboratory, 2011, 28(2): 940-945.

[3] [3] Jin Lanlan, Wang Xiuji, Li Huilai, et al. Progress in inductively coupled plasma mass spectrometry technology and its application in metallurgical analysis［J］. Metallurgical Analysis, 2016, 36(7): 1-14.

[4] [4] Wang G W, Yang C H, Li Y G, et al. Reagent optimization for on-line simultaneous polarographic determination of trace amounts of Cu2+, Cd2+ and Co2+ in the presence of anextremely large excess of Zn2+［J］. Journal of Central South University, 2016, 23(9): 2199-2204.

[5] [5] Tang Bin, Wei Biao, Mao Benjiang, et al. Noise analysis and denoising research on the UV-visible absorption spectroscopy water quality detection system［J］. Laser & Optoelectronics Progress, 2014, 51(4): 043002.

[6] [6] Xu D, Fan W, Lv H Y, et al. Simultaneous determination of traces amounts of cadmium, zinc, and cobalt based on UV-Vis spectrometry combined with wavelength selection and partial least squares regression［J］. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2014, 123: 430-435.

[7] [7] Bai Ling, Ni Yongnian. Simultaneous spectrophotometric determination of trace iron, manganese, copper, zinc, cobalt and nickel by partial least squares method［J］. Chinese Journal of Analysis Laboratory, 2002, 21(1): 39-42.

[8] [8] Li Shuo, Wang Shanqin, Zhang Meiqin. Comparision among principal component regression, partical least squares regression and back propagatiom neural network for prediction of soil nitrogen with visible-near infrared spectroscopy［J］. Acta Optica Sinica, 2012, 32(8): 0830001.

[9] [9] Chen Xiaojing, Wu Di, Yu Jiajia, et al. A new choice method of characteristic wavelength of visible/near infrared spectroscopy［J］. Acta Optica Sinica, 2008, 28(11): 2153-2158.

[10] [10] Peng Haigen, Peng Yunfa, Zhan Ying, et al. Determination of the sugar content of jujube in south Xinjiang by near infrared spectroscopy combined with siPLS methods［J］. Food Science and Technology, 2014, 39(6): 276-279.

[11] [11] Wu Xiaohong, Sun Jun, Wu Bin, et al. Qualitative analysis model of near infrared spectra of pork based on synergy interval partial least squares discriminant analysis［J］. Laser & Optoelectronics Progress, 2015, 52(4): 043003.

[12] [12] Hao Yong, Sun Xudong, Pan Yuanyuan, et al. Detection of firmness and surface color of pear by near infrared spectroscopy based on Monte Carlo uninformative variables elimination method［J］. Spectroscopy and Spectral Analysis, 2011, 31(5): 1225-1229.

[13] [13] Li Jiangbo, Guo Zhiming, Huang Wenqian, et al. Near-infrared spectra combining with CARS and SPA algorithms to screen the variables and samples for quantitatively determining the soluble solids content in strawberry［J］. Spectroscopy and Spectral Analysis, 2015, 35(2): 372-378.

[14] [14] Fu Yuanyuan, Wang Jihua, Yang Guijun, et al. Band depth analysis and partial least square regression based winter wheat biomass estimation using hyperspectral measurements［J］. Spectroscopy and Spectral Analysis, 2013, 32(5): 1315-1319.

[15] [15] Zou Xiaobo, Zhao Jiewen. Methods of characteristic wavelength region and wavelength selection based on genetic algorithm［J］. Acta Optica Sinica, 2007, 27(7): 1316-1321.