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SA4多小波在浮游藻荧光识别测定技术中的应用 被引量:5

Fluorescence Discrimination and Determination Method for Phytoplankton Composition by SA4 Multiwavelet
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摘要 基于SA4多小波函数和浮游藻三维荧光光谱发展了一种浮游藻荧光识别测定技术。首先,采用SA4多小波对我国近海常见的42种优势藻种的三维荧光光谱进行分解,得到不同的尺度分量和小波分量,然后,应用贝叶斯判别原理选择第二、三层尺度分量Ca2,Ca3及二者的联合Ca2-Ca3作为荧光特征光谱分量,通过系统聚类分析得到Ca2,Ca3,Ca2-Ca3标准谱库,在此基础上,利用非负最小二乘法解析的多元线性回归建立识别测定技术。用3种标准谱库对培养的单种浮游藻样品在门、属水平上进行分级识别,表明Ca2标准谱库的识别效果最好:门水平上识别正确率平均为96.1%,属水平上识别正确率平均为87.4%。将该技术用于模拟混合样品及实际混合样品的分析,3种比例下,模拟混合样品的优势藻在门水平上识别正确率范围为91.4%~100%,平均为98.0%,99.4%,99.9%,平均相对含量分别为72.7%,77.1%,86.1%,优势藻在属水平上识别正确率范围23.2%~100%,平均为91.2%,92.5%,93.4%。实际混合样品的优势藻在门水平上的识别正确率范围为60.0%~100%,平均为97.0%,平均相对含量为71.8%,在属水平上识别正确率范围为25.0%~100%,平均为83.1%。将该技术用于麦岛围隔和胶州湾采集样品,在门水平上优势藻的分析结果与镜检结果一致,对于10个单种浮游藻优势度超过75%的样品,7个在属水平上的优势藻分析结果与镜检结果一致。 A fluorescence spectroscopy method for differentiation of phytoplankton classes is developed.SA4 multiwavelet functions are used to decompose the three-dimensional(3D) fluorescence spectra date of 42 phytoplankton species dominant in coastal area of China sea into scale vectors and wavelet vectors,then the Ca2,Ca3 and Ca2-Ca3 vectors are chosen as fluorescence feature spectra by Bayesian discriminant analysis and the three kinds of reference spectra are obtained by application of the systematic cluster to the fluorescence feature spectra,based on which,a fluorescence spectroscopy method is developed by multivariate linear regression resolved by nonnegative least squares.The three kinds of reference spectra are utilized to the samples composed of one phytoplankton species,the results suggest that the Ca2 reference spectra are the strongest: the average correctly discriminating rate are 96.1% at the division level and 87.4% at the genus level.For the simulative mixed samples,the correctly discriminating rate for dominant species ranged from 91.4% to 100%,the average are 98.0%,99.4%,99.9%,the average relative content are 72.7%,77.1%,86.1% at division level,the correctly discriminating rate for dominant species ranged from 23.2% to 100% and the average are 91.2%,92.5%,93.4% at genus level in three different ratios respectively.For the mixed samples in lab,the correctly discriminating rate for dominate species range from 60.0% to 100%,the average is 97.0%,and the average relative content is 71.8% at division level;the correctly discriminating rate for dominate species range from 25.0% to 100%,the average is 83.1% at genus level.For the samples from the mesocosm experiment in Maidao Bay of Qingdao and Jiaozhou Bay,the discriminating results of dominant phytoplankton classes from the fluorescence spectroscopy method are the same as that of microscopic examination at division level,and for the 10 samples with over 75% relative dominance of one phytoplankton species,the dominant species of 7 samples are recognized at genus level.
出处 《中国激光》 EI CAS CSCD 北大核心 2011年第7期240-248,共9页 Chinese Journal of Lasers
基金 国家863计划(2009AA063005) 国家自然科学基金(40976060) 山东省自然科学基金(ZR2009EM001)资助课题
关键词 光谱学 识别测定 SA4多小波 三维荧光光谱 浮游藻 spectroscopy discriminate SA4 multiwavelet three-dimensional fluorescence spectrum phytoplankton
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