• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Optical engineering >Detection and discrimination of microorganisms on various substrates with quantum cascade laser spectroscopy
【24h】

Detection and discrimination of microorganisms on various substrates with quantum cascade laser spectroscopy

机译：量子级联激光光谱法检测和鉴别各种基质上的微生物

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Investigations focusing on devising rapid and accurate methods for developing signatures for microorganisms that could be used as biological warfare agents' detection, identification, and discrimination have recently increased significantly. Quantum cascade laser (QCL)-based spectroscopic systems have revolutionized many areas of defense and security including this area of research. In this contribution, infrared spectroscopy detection based on QCL was used to obtain the mid-infrared (MIR) spectral signatures of Bacillus thuringiensis, Escherichia coli, and Staphylococcus epidermidis. These bacteria were used as microorganisms that simulate biothreats (biosimulants) very truthfully. The experiments were conducted in reflection mode with biosimulants deposited on various substrates including cardboard, glass, travel bags, wood, and stainless steel. Chemometrics multivariate statistical routines, such as principal component analysis regression and partial least squares coupled to discriminant analysis, were used to analyze the MIR spectra. Overall, the investigated infrared vibrational techniques were useful for detecting target microorganisms on the studied substrates, and the multivariate data analysis techniques proved to be very efficient for classifying the bacteria and discriminating them in the presence of highly IR-interfering media.
机译：最近，致力于设计快速，准确的方法来开发可用于生物战剂的检测，识别和区分的微生物特征的研究已经大大增加。基于量子级联激光（QCL）的光谱系统彻底改变了国防和安全领域的许多领域，包括这一领域的研究。在此贡献中，基于QCL的红外光谱检测用于获得苏云金芽孢杆菌，大肠杆菌和表皮葡萄球菌的中红外（MIR）光谱特征。这些细菌被用作能够真实地模拟生物威胁（生物模拟物）的微生物。实验以反射模式进行，生物模拟物沉积在各种基材上，包括纸板，玻璃，旅行袋，木材和不锈钢。使用化学计量学的多元统计程序，例如主成分分析回归和偏最小二乘与判别分析，来分析MIR光谱。总体而言，所研究的红外振动技术可用于检测所研究基质上的目标微生物，而多元数据分析技术被证明对细菌进行分类并在存在强烈红外干扰的介质下对其进行区分非常有效。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号