Browsing by Author "Salih, Magdi"

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    Growth curve prediction from optical density data
    (Elsevier Science B.V., Amsterdam., 2012-03-15T00:00:00Z) Mytilinaios, Ioannis; Salih, Magdi; Schofield, Hannah K.; Lambert, Ronald J. W.
    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
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    Modelling of bacterial growth with shifts in temperature using automated methods with Listeria monocytogenes and Pseudomonas aeruginosa as examples
    (Elsevier Science B.V., Amsterdam., 2012-04-02T00:00:00Z) Salih, Magdi; Mytilinaios, Ioannis; Schofield, Hannah K.; Lambert, Ronald J. W.
    Time to detection (TTD) measurements using turbidometry allow a straightforward method for the measurement of bacterial growth rates under isothermal conditions. Growth rate measurements were carried out for Listeria monocytogenes at 25, 30 and 37°C and for Pseudomonas aeruginosa over the temperature range 25 to 45°C. The classical three-parameter logistic model was rearranged to provide the theoretical foundation for the observed TTD. A model was subsequently developed for the analysis of TTD data from non-isothermal studies based on the Malthusian approximation of the logistic model. The model was able to predict the TTD for cultures of L. monocytogenes or P. aeruginosa undergoing simple temperature shunts (e.g. 25 to 37°C and vice versa), and for a multiple temperature shunt for L. monocytogenes (25-37-25-37°C and 37-25-37-25°C) over a period of 24h. In no case did a temperature shunt induce a
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    Temporal changes in vase water
    (Cranfield University, 2013-02) Salih, Magdi; Lambert, R. J. W.
    This study investigated the influence of flower food on vase water quality with the attempt to correlate this with the flowers’ appearance and microbial growth occurring in the vase water. A mixed bouquet of different cut flowers was used in this study for the first time instead of the common practice in the literature of using a single cut flower or a single cultivar. Different combinations of vase solutions; standard water and reverse osmosis water with or without added flower food were used as initial vase solutions and also as the topping up water. The effect of vase solution’s pH on microbial growth and therefore flowers vase quality was also examined. Moreover the analysis of sugar content of vase water was conducted using HPLC and LC/MS. The analysis of vase water in the Cranfield Health laboratory has shown that: Sugar presumably plays a central role in energy for both microbes and plants but the concentration levels present in flower food seems to have no subsequent effect on the growth or otherwise of the microbes even when diluted with top up water. Water uptake by the flowers is little influenced by the presence of flower food or the microbial population. Flower food reduces the pH of Standard water, but not sufficiently enough to inhibit the growth of common pathogens or spoilage organisms. If microbial growth begins, addition of further flower food in the top-up does not inhibit further growth. If reverse osmosis water (ROW) is used with flower food the initial pH is lower than the pH minimum for all common pathogens and the majority of common spoilage organisms. Topping up with ROW with flower food maintains the low pH environment. If growth is initiated due to the presence of microbes capable of growth in the low pH environment, then growth will continue regardless of topping up solution. Microbial growth in ROW with flower food is confined to acidophilic organisms. Addition of weak acid preservatives such as benzoic acid or sorbic acid could control or prevent the growth of such acidophilics, whilst allowing a pH compatible with the flowers to be maintained.