Citation:
I Mytilinaios, M. Salih, H.K. Schofield and R.J.W. Lambert. Growth curve prediction from optical density data. International Journal of Food Microbiology, Volume 154, Issue 3, 15 March 2012, Pages 169-176.
Abstract:
A fundamental aspect of predictive microbiology is the shape of the microbial
growth curve and many models are used to fit microbial count data, the modified
Gompertz and Baranyi equation being two of the most widely used. Rapid,
automated methods such as turbidimetry have been widely used to obtain growth
parameters, but do not directly give the microbial growth curve. Optical density
(OD) data can be used to obtain the specific growth rate and if used in
conjunction with the known initial inocula, the maximum population data and
knowledge of the microbial number at a predefined OD at a known time then all
the information required for the reconstruction of a standard growth curve can
be obtained.Using multiple initial inocula the times to detection (TTD) at a
given standard OD were obtained from which the specific growth rate was
calculated. The modified logistic, modified Gompertz, 3-phase linear, Baranyi
and the classical logistic model (with or without lag) were fitted to the TTD
data. In all cases the modified logistic and modified Gompertz failed to
reproduce the observed linear plots of the log initial inocula against TTD using
the known parameters (initial inoculum, MPD and growth rate). The 3 phase linear
model (3PLM), Baranyi and classical logistic models fitted the observed data and
were able to reproduce elements of the OD incubation-time curves. Using a
calibration curve relating OD and microbial numbers, the Baranyi equation was
able to reproduce OD data obtained for Listeria monocytogenes at 37 and 30°C as
well as data on the effect of pH (range 7.05 to 3.46) at 30°C.The Baranyi model
was found to be the most capable primary model of those examined (in the absence
of lag it defaults to the classic logistic model). The results suggested that
the modified logistic and the modified Gompertz models should not be used as
Primary models for TTD data as they cannot reproduce the observed dat