Abstract：Three-dimensional fluorescence of 17 red tide algae species that belong to 13 genera of five divisions was measured by fluorescence excitation-emission matrix spectroscopy. And 2-D wavelet db7 was selected to decompose the spectra at different levels to choose the alternative characteristic spectra. Based on the norm reference spectra constructed by cluster analysis, the linear regression model was solved by particle swarm optimization (PSO) algorithm and the discrimination method was established at the division and genus level. Some samples were tested: for single algal samples, and the correct discrimination ratios (CDRs) were 96.1% and 73.6%, respectively; For simulative mixed algal samples, when the dominance were 60%, 75%, 80% and 90% of the total biomass, the CDRs of the dominant algae were 86.7%, 96.9%, 98.7% and 99.4% with the average relative contents of 62.6%, 72.7%, 76.0% and 81.6%, respectively at the division level. And the CDRs were 51.0%, 68.9%, 72.0%, and 78.8% at the genus level, respectively. For 364 actual mixture samples, the CDRs of the dominant species (75%) were 99.4% at the division level and 75.9% at the genus level . For the particular field samples from mesocosm experiment and corrected from Jiaozhou Bay, results showed that the method can be used to realize the identification of red tide algae population and estimate the relative abundance of different classes, especially between diatoms and dinoflagellates.
段亚丽，苏荣国*，石晓勇，张 翠 . 三维荧光光谱-小波变换-粒子群算法联用快速识别测定浮游藻群落组成方法的研究 [J]. 光谱学与光谱分析, 2012, 32(06): 1562-1569.
DUAN Ya-li, SU Rong-guo*, SHI Xiao-yong, ZHANG Cui. Research on Using 3-D Fluorescence Spectroscopy-Wavelet Transform-PSO for Rapid Discrimination of Compositions of Phytoplankton Population. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32(06): 1562-1569.
[1] Poryvkina L, Babichenko S, Leeben A. Proceedings of EARSeL-SIG-Workshop LIDAR, Dresden/FRG, 2000, 1(1): 224. [2] Yentsch C S, Yentsch C M. Journal of Marine Research, 1979, 37: 471. [3] Boddy L, Wilkins M F, Morris C W, et al. Marine Ecology Progress Series, 2000, 195: 47. [4] Seppala J, Ylostalo P, Kaitala S, et al. Estuar Coast Shelf Science, 2007, 73: 489. [5] Ismael F, Aymerich J P, Aureli S F, et al. Applied Spectroscopy, 2009, 63(6): 716. [6] Bruckman L S, Richardson T L, Swanstrom J A, et al. Applied Spectroscopy, 2012, 66(1): 60. [7] ZHANG Fang, WANG Liang, SU Rong-guo(张 芳，王 良，苏荣国). Chinese Journal of Sensors and Actuators(传感技术学报), 2007, 20(10): 2143. [8] ZHANG Fang, SU Rong-guo, WANG Xiu-lin(张 芳，苏荣国，王修林). Journal of Experimental Marine Biology and Ecology, 2009, 368(1): 37. [9] ZHANG Shan-shan, SU Rong-guo, DUAN Ya-li, et al(张珊珊，苏荣国，段亚丽，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2011, 31(3): 732. [10] Ma Jun, Wang Zhaoyang, Pan Bin, et al. Applied Optics, 2011, 50(16): 2425. [11] WANG Jian-lin, XUE Yao-yu, YU Tao, et al(王建林，薛尧予，于 涛，等). Chinese Journal of Chemical Engineering, 2010, 18(5): 787. [12] LIANG Yan-ming, LIU Ding, REN Hai-peng, et al(梁炎明，刘 丁，任海鹏，等). Chinese Journal of Scientific Instrument(仪器仪表学报), 2010, 31(7): 1441. [13] Zepp R G, Sheldon W N, Moran M A. Marine Chemistry, 2004, 89: 15. [14] HAN Ling, DONG Lian-feng, ZHANG Min, et al(韩 玲，董连凤，张 敏，等). Acta Optica Sinica(光学学报), 2009, 29(12): 3333. [15] Kaitala S，Babichenko S，Poryvkina L, et al. Marine Technology Society, 1994, 28: 50. [16] Babichenko S, Kaiatla S, Leeben A, et al. Jounral of Marine Systems, 1999, 23: 69. [17] Kennedy J, Eberhart R C. Particle Swarm Optmization. Proc. IEEE International Conference on Neural Networks. Australia: IEEE Service Center, 1995, 1942. [18] LIU Dong-yan, SUN Jun, CHEN Hong-tao, et al(刘东艳，孙 军，陈洪涛，等). Journal of Ocean University of Qingdao(青岛海洋大学学报), 2003, 33(3): 366. [19] LI Yan, LI Rui-xiang, WANG Zong-ling, et al(李 艳，李瑞香，王宗灵，等). Advances in Marine Science(海洋科学进展), 2005, 23(3): 328.
