Microbial behavior, modeling

Predictive microbiology using growth models should be implemented in order to follow the microbial behavior in fruit osmotically dehydrated/ impregnated and to compute their shelf life as a function of process variables, such as concentration of osmotic medium, initial contamination of the solution, and fruit storage temperature. 

In order to reliably calculate microbial behavior, predictive microbiology requires a reliable combination of mathematical and statistical considerations (Roberts, 1995). It is, however, often inappropriate to extrapolate mathematical models used in different applications. In Table 10.1 the differences between mathematical characterization of bacterial growth in food microbiology and mathematical modeling techniques used in biotechnology are stipulated. 

Microbiologists have developed ways to model microbial growth and, using assumptions related to the expected behavior of organisms under different environmental conditions, these models are then coupled with dose-response models with the result that risks (responses) can be estimated, given a certain degree of knowledge about initial microbe counts and the environmental conditions (related... 

These linear kinetic models and diffusion models of skin absorption kinetics have a number of features in common they are subject to similar constraints and have a similar theoretical basis. The kinetic models, however, are more versatile and are potentially powerful predictive tools used to simulate various aspects of percutaneous absorption. Techniques for simulating multiple-dose behavior evaporation, cutaneous metabolism, microbial degradation, and other surface-loss processes dermal risk assessment transdermal drug delivery and vehicle effects have all been described. Recently, more sophisticated approaches involving physiologically relevant perfusion-limited models for simulating skin absorption pharmacokinetics have been described. These advanced models provide the conceptual framework from which experiments may be designed to simultaneously assess the role of the cutaneous vasculature and cutaneous metabolism in percutaneous absorption. 

Although it is impossible to describe all microbial interactions in the GI tract, some information has been discovered about the interactions of LAB supplementation and the impact on the GI tract microflora and inhibition of food-borne pathogens. We know that the carbohydrate concentration of a diet fed to an animal is changed as it passes through the GI tract, making an in vitro model inadequate to predict the behavior of LAB in a live animal (Fuller, 1992). Model systems have been developed but may not exactly... 

The oscillatory behavior of pore-water profiles near the interface can be accounted for by the different temperature dependence of microbial and macrofaunal activity that control production (consumption) and biogenic transport processes respectively. A non-steady-state model is used to show this is the case. 

From this understanding of the behavior of the SOC pool, models such as Rothamsted (Jenkinson and Rayner, 1977) and Century (Parton et ai, 1993) have been developed that allow results from regional validation studies to be extrapolated to the global scale (Schimel et al, 1994). Such models divide the SOC pool up into three to five pools with turnover times ranging from years to thousands of years, and the sizes of the.se pools for a given. soil texture are determined by climate-driven interactions between plant carbon inputs, nutrients, microbial respiration, and leaching of DOC (Fig. 2). In some cases, the.se models have been tested... 

Testing Using the Umbilical Cord as a Model for Mucous Membranes. The topography, moisture level, microbial ecology, and surface temperature of mucous surfaces are quite different from those of skin. It would, therefore, be safe to assume that the behavior of microbial pathogens on mucous membranes may also be different from that on skin. Each of these differences may also influence the germicidal activity of an antiseptic applied to mucous membranes. 

Microorganisms have a complex cell envelope structure. Their surfaces charge and their hydrophobicity cannot be predicted, only experimentally determined [131]. Several microorganisms are not hydrophobic enough to be floated. They need collectors, similar to ore flotation. In cultivation media proteins which adsorb on the cell surface act as collectors. The interrelationship between cell envelope and proteins caimot be predicted, only experimentally evaluated. The accumulation of cells on the bubble surface depends not only on the properties of the interface, proteins and cells, but on the bubble size and velocity as well [132]. On account of this complex interrelationship between several parameters, prediction of flotation performance of microbial cells based on physicochemical fundamentals is not possible. Therefore, only empirical relationships are known which cannot be generalized. Based on the large amount of information collected in recent years, mathematical models have been developed for the calculation of the behavior of protein solutions and particular microbial cells. They hold true only for systems (e.g. BSA solutions and particular yeast strains) which are used for their evaluation. In spite of this, several recommendations for protein and microbial cell flotation can be made. 

According to Fig. 2.3, microbial cells suspended in the liquid phase of the bioreactor are treated as black boxes this does not mean that they are neglected. Their macroscopic behavior, manifested in the changes of the concentrations in the liquid phase, is taken into consideration. As a consequence of this approach, the bioreactor itself is not treated as a black box. The core of the formal macroapproach is that formal analogies are used (see Sect. 2.4.3). The utility of the principle of simplification can also be demonstrated in the case of modeling the dynamics of bioprocesses (see Sects. 3.5.3 and 5.7). 

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