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利用衰减全反射傅里叶变换红外光谱法鉴别泰国呵叻府盐渍土中分离出的蓝藻菌株。

Discrimination of cyanobacterial strains isolated from saline soils in Nakhon Ratchasima, Thailand using attenuated total reflectance FTIR spectroscopy.

机构信息

School of Biology, Suranaree University of Technology, Nakhon Ratchasima, Thailand.

出版信息

J Biophotonics. 2010 Aug;3(8-9):534-41. doi: 10.1002/jbio.201000017.

Abstract

A method was developed whereby high quality FTIR spectra could be rapidly acquired from soil-borne filamentous cyanobacteria using ATR FTIR spectroscopy. Spectra of all strains displayed bands typical of those previously reported for microalgae and water-borne cyanobacteria, with each strain having a unique spectral profile. Most variation between strains occurred in the C-O stretching and the amide regions. Soft Independent Modelling by Class Analogy (SIMCA) was used to classify the strains with an accuracy of better than 93%, with best classification results using the spectral region from 1800-950 cm(-1). Despite this spectral region undergoing substantial changes, particularly in amide and C-O stretching bands, as cultures progressed through the early-, mid- to late-exponential growth phases, classification accuracy was still good (approximately 80%) with data from all growth phases combined. These results indicate that ATR/FTIR spectroscopy combined with chemometric classification methods constitute a rapid, reproducible, and potentially automated approach to classifying soil-borne filamentous cyanobacteria.

摘要

建立了一种方法,使用衰减全反射傅里叶变换红外光谱(ATR FTIR 光谱)可以快速获得土壤丝状蓝藻的高质量 FTIR 光谱。所有菌株的光谱均显示出先前报道的微藻和水栖蓝藻的典型谱带,每个菌株都有独特的光谱特征。菌株间的大多数差异发生在 C-O 伸缩和酰胺区域。使用软独立建模分类分析(SIMCA)对菌株进行分类,准确率超过 93%,使用光谱区域为 1800-950 cm(-1) 时分类效果最佳。尽管该光谱区域发生了很大变化,特别是在酰胺和 C-O 伸缩带中,但当培养物经历早期、中期到晚期指数生长阶段时,结合所有生长阶段的数据,分类准确率仍然很高(约 80%)。这些结果表明,ATR/FTIR 光谱结合化学计量分类方法是一种快速、可重复且具有潜在自动化的分类土壤丝状蓝藻的方法。

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