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A note on 'plotless' methods for estimating bacterial cell densities
Authors:D Roser    DB Nedwell  A Gordon
Institution:Department of Biology, University of Essex. Colchester C04 3SQ. UK
Abstract:R oser , D., N edwell , D.B. & G ordon , A. 1984. A note on "plotless" methods for estimating bacterial cell densities. Journal of Applied Bacteriology 56 , 343–347.
'Plotless' techniques for determining population densities have been developed for, and applied to, higher plant populations. They can often be carried out more rapidly than techniques involving total counts of individuals in plots, or quadrants, but such plotless techniques have not been generally applied to the estimation of densities of bacterial cells. Direct microscopical counting of cell numbers in a field of view, an example of a plot-related method, has been traditionally used for micro-bial cell counts. In this study 'plot' and 'plotless' methods on a variety of bacterial samples are compared. Estimates of bacterial cell density were obtained by measuring the distance of cells from a fixed point in a field of view. The values, which were more rapidly obtained, were directly correlated with total cell counts. Although there was some apparent deviation from a perfect 1:1 relationship with total counts, as indicated by a correlation coefficient less than 1.0, there were no significant differences between the replicated counts of bacteria on samples of tissue from the surface of Hypholoma basidiocarps ( P < 0.05). This indicated that the methods of enumeration were comparable. The distance-related estimates could readily be obtained from fields of view with cell densities varying over several orders of magnitude. It was more rapidly applied, particularly at high density, and the method was applicable not only to random cell distributions but also to the non-random distributions encountered when microbial cells aggregated into micro-colonies. The method appears to be particularly well-suited for automated, digitized, direct counting procedures, as well as to estimating bacterial numbers on membrane filters and natural substrates.
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