| CHEN Xiaona,SU Rongguo,BAI Ying,SHI Xiaoyong,YANG Rujun. 2014. Discrimination of marine algal taxonomic groups based on fluorescence excitation emission matrix, parallel factor analysis and CHEMTAX. Acta Oceanologica Sinica, 33(12):192－205 |
| Discrimination of marine algal taxonomic groups based on fluorescence excitation emission matrix, parallel factor analysis and CHEMTAX |
| 基于三维荧光光谱-平行因子技术联用的浮游藻化学分类学技术研究 |
| Received:September 14, 2013 Revised:January 09, 2014 |
| DOI：10.1007/s13131-014-0576-5 |
| Key words:CHEMTAX fluorescence excitation-emission matrices in vivo fluorescent components parallel factor analysis phytoplankton |
| 中文关键词: CHEMTAX 三维荧光光谱 活体 荧光成分 平行因子 浮游植物 |
| 基金项目:The National Natural Science Foundation of China under contract Nos 41376106 and 41276069. |
| Author Name | Affiliation | E-mail | | CHEN Xiaona | College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao 266100, China | | | SU Rongguo | College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao 266100, China | surongguo@ouc.edu.cn | | BAI Ying | College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao 266100, China | | | SHI Xiaoyong | College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao 266100, China | | | YANG Rujun | College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao 266100, China | |
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| Abstract: |
| An in vivo three-dimensional fluorescence method for the determination of algae community structure was developed by parallel factor analysis (PARAFAC) and CHEMTAX. The PARAFAC model was applied to fluorescence excitation-emission matrix (EEM) of 60 algae species belonging to five divisions and 11 fluorescent components were identified according to the residual sum of squares and specificity of the composition profiles of fluorescent. By the 11 fluorescent components, the algae species at different growth stages were classified correctly at the division level using Bayesian discriminant analysis (BDA). Then the reference fluorescent component ratio matrix was constructed for CHEMTAX, and the EEM-PARAFAC-CHEMTAX method was developed to differentiate algae taxonomic groups. The correct discrimination ratios (CDRs) when the fluorometric method was used for single-species samples were 100% at the division level, except for Bacillariophyta with a CDR of 95.6%. The CDRs for the mixtures were above 94.0% for the dominant algae species and above 87.0% for the subdominant algae species. However, the CDRs of the subdominant algae species were too low to be unreliable when the relative abundance estimated was less than 15.0%. The fluorometric method was tested using the samples from the Jiaozhou Bay and the mesocosm experiments in the Xiaomai Island Bay in August 2007. The discrimination results of the dominant algae groups agreed with microscopy cell counts, as well as the subdominant algae groups of which the estimated relative abundance was above 15.0%. This technique would be of great aid when low-cost and rapid analysis is needed for samples in a large batch. The fluorometric technique has the ability to correctly identify dominant species with proper abundance both in vivo and in situ. |
| 中文摘要: |
| 利用平行因子 (PARAFAC) 和CHEMTAX发展区分浮游藻群落组成的活体三维荧光分析技术.将PARAFAC分解模型应用于分属5个门60种浮游藻的三维荧光光谱(EEM),通过残差分析和荧光成分谱形分析确定浮游藻EEM由11种荧光成分组成;然后,利用Bayesian判别分析(BDA)表明浮游藻的11个荧光成分的组成具有明显的门类特征性;将获得的11个荧光成分构建适合CHEMTAX要求的浮游藻 “荧光成分比值矩阵”,结合CHEMTAX建立浮游藻荧光识别分析技术(EEM-PARAFAC-CHEMTAX). 对浮游藻样品进行门类水平上的识别分析,对单种藻样品,硅藻的识别正确率是 95.6%,其余藻的识别正确率为100%;对于实验室混合样品,优势藻和次优势藻的平均识别正确率分别高于94.0%和87.0%,然而,当估算的次优势藻的相对含量低于15%时,对次优势藻的识别结果不可靠;对于2007年从胶州湾和小麦岛围隔实验现场采集的水样,优势藻群和相对丰度高于15.0%的次优势藻群的识别结果与镜检结果相一致.此荧光技术可以用于现场大批量浮游藻样品的快速、低成本分析,能够实现浮游植物群落组成的现场识别测定. |
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