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首页> 外文期刊>Talanta: The International Journal of Pure and Applied Analytical Chemistry >Detection of spoilage associated bacteria using Raman-microspectroscopy combined with multivariate statistical analysis
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Detection of spoilage associated bacteria using Raman-microspectroscopy combined with multivariate statistical analysis

机译:使用拉曼微型光谱进行腐败相关细菌的检测与多变量统计分析相结合

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摘要

Raman-Microspectroscopy with subsequent chemometric evaluation was used for the rapid and non-destructive differentiation of seven important spoilage related microorganisms, namely Brochothrix thermosphacta DSM 20171, Pseudomonas Jiuorescens DSM 4358, Pseudomonas fiuorescens DSM 50090, Micrococcus luteus, Escherichia coli HB101, Escherichia coil TOP10 and Bacillus thuringiensis israelensis DSM 5724. Therefore fast collected spectra directly from rapid surface blots without any pretreatments like purification or singulation steps were used. To estimate and classify the Raman-spectroscopic data at genera and strain level an adequate preprocessing together with a subsequent chemometric evaluation consisting of principal component analysis and discriminant analysis was used. Thereby, importance was attached to a balanced data set, as this makes the multivariate analysis of the data significantly more resilient and meaningful. The analysis showed that the differentiation of spoilage related microorganisms on genera and strain level was successful and the classification of independent test data showed only an error rate of 3.5%.
机译:随后的化学计量评估的拉曼微型光谱学用于七个重要腐败相关的微生物的快速和无损分化,即Brochothrix Thermosphotta DSM 20171,Pseudomonas jiuorescens DSM 4358,Pseudomonas Fiuorescens DSM 50090,Microcococus Luteus,大肠杆菌HB101,大肠杆菌线圈Top10和芽孢杆菌以色列的以色列人DSM 5724.因此,使用快速收集的光谱从快速表面印迹,没有使用纯化或分泌步骤的任何预处理。为了估计和分类属的拉曼光谱数据和应变水平,使用与由主成分分析和判别分析组成的随后的化学计量评估一起进行足够的预处理。由此,将重要性附加到平衡数据集,因为这使得数据的多变量分析明显更具弹性和有意义的。分析表明,腐败相关微生物对白身和应变水平的分化成功,独立测试数据的分类仅显示了3.5%的错误率。

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