Rösch Petra, Harz Michaela, Schmitt Michael, Peschke Klaus-Dieter, Ronneberger Olaf, Burkhardt Hans, Motzkus Hans-Walter, Lankers Markus, Hofer Stefan, Thiele Hans, Popp Jürgen
Institut für Physikalische Chemie, Friedrich-Schiller-Universität Jena, Helmholtzweg 4, D-07743 Jena, Germany.
Appl Environ Microbiol. 2005 Mar;71(3):1626-37. doi: 10.1128/AEM.71.3.1626-1637.2005.
Microorganisms, such as bacteria, which might be present as contamination inside an industrial food or pharmaceutical clean room process need to be identified on short time scales in order to minimize possible health hazards as well as production downtimes causing financial deficits. Here we describe the first results of single-particle micro-Raman measurements in combination with a classification method, the so-called support vector machine technique, allowing for a fast, reliable, and nondestructive online identification method for single bacteria.
诸如细菌之类的微生物，可能作为污染物存在于工业食品或制药洁净室生产过程中，需要在短时间内进行识别，以尽量减少可能的健康危害以及导致财务赤字的生产停机时间。在此，我们描述了单颗粒显微拉曼测量结合一种分类方法（即所谓的支持向量机技术）的初步结果，该方法可实现对单个细菌的快速、可靠且无损的在线识别。
