A simple maximum probability resolution algorithm for most probable number analysis using microsoft excel

被引:13
作者
Irwin, P [1 ]
Fortis, L [1 ]
Tu, S [1 ]
机构
[1] USDA ARS, Eastern Reg Res Ctr, Microbial Biophys & Biochem Lab, Wyndmoor, PA 19038 USA
关键词
D O I
10.1111/j.1745-4581.2001.tb00226.x
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Traditional most probable number (MPN) methods are executed using one of two schemes. The direct maximum probability resolution (DMPR) technique involves calculating the binomial probability distribution array, P (= IIi P-i; i dilutions), as a function of cell density (Delta) and finding the value of which corresponds to the maximum in P (the MPN). Alternatively, indirect MPR methods seek the solution to a nonlinear equation, related to Pi, by altering Delta. We describe herein a simple maximum probability resolution (SMPR) method of the second type which involves the repeated calculation (j cycles) of Delta (j+1) by the addition of a term, related to the partial first derivative of P-i, with respect to Delta, to Delta (j) until the MPN (Delta (final)) is reached. Using this SMPR algorithm and comparing our results with a DMPR procedure (n = 5, 10, or 96; 10,000 points per Pi), another indirect computer-based MPR method (n = 10 or 96), or published MPN tables (n = 5) we found that there was agreement to 3-5 significant figures. The SMPR approach also outperformed all other computer-based MPR techniques tested.
引用
收藏
页码:33 / 51
页数:19
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