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最可能数统计在微生物直接计数中的应用。

Application of most-probable-number statistics to direct enumeration of microorganisms.

机构信息

Water Research Laboratory, Faculty of Food and Environmental Sciences, Hawkesbury Agricultural College, Richmond, New South Wales, Australia 2753.

出版信息

Appl Environ Microbiol. 1987 Jun;53(6):1327-32. doi: 10.1128/aem.53.6.1327-1332.1987.

Abstract

A novel method for rapid determination of total microbial cell numbers was investigated. The method involves the application of most-probable-number estimation statistics to direct microscopic counting of microbial cells by using a particle sizing graticule. Its accuracy and reliability were tested with computer simulations of bacterial cell distributions encountered in ecological studies. Good estimates of cell numbers were obtained when the cell density varied from 3 to 6,000 cells per field, i.e., over 3 orders of magnitude. Low levels of contagion did not markedly influence cell estimates, although high levels, corresponding to discrete scattered microcolonies, did. However, these could be recognized visually. Estimates of cell numbers in Breed smears confirmed its speed and good correlation with the standard quadrat counting technique under real experimental conditions.

摘要

研究了一种快速测定总微生物细胞数量的新方法。该方法将最可能数估计统计应用于通过使用颗粒尺寸网格直接对微生物细胞进行直接显微镜计数。通过对生态研究中遇到的细菌细胞分布的计算机模拟测试了其准确性和可靠性。当细胞密度在每个视野 3 至 6000 个细胞之间变化时,即超过 3 个数量级时,可以获得细胞数量的良好估计值。低水平的传染性不会显著影响细胞估计值,尽管高水平,对应于离散的分散微菌落,会影响。但是,这些可以通过肉眼识别。在实际实验条件下,在 Breed 涂片中的细胞数量估计值证实了它的速度和与标准方格计数技术的良好相关性。

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