Isothermal germination curves, sigmoid and nonsigmoid, can be described by a variety of models reminiscent of growth models. Two of these, which are consistent with the percent of germinated spores being initially zero, were selected: one, Weibullian (or "stretched exponential"), for more or less symmetric curves, and the other, introduced by Dantigny's group, for asymmetric curves (P. Dantigny, S. P.-M. Nanguy, D. Judet-Correia, and M. Bensoussan, Int. J. Food Microbiol. 146:176 -181, 2011). These static models were converted into differential rate models to simulate dynamic germination patterns, which passed a test for consistency. In principle, these and similar models, if validated experimentally, could be used to predict dynamic germination from isothermal data. The procedures to generate both isothermal and dynamic germination curves have been automated and posted as freeware on the Internet in the form of interactive Wolfram demonstrations. A fully stochastic model of individual and small groups of spores, developed in parallel, shows that when the germination probability is constant from the start, the germination curve is nonsigmoid. It becomes sigmoid if the probability monotonically rises from zero. If the probability rate function rises and then falls, the germination reaches an asymptotic level determined by the peak's location and height. As the number of individual spores rises, the germination curve of their assemblies becomes smoother. It also becomes more deterministic and can be described by the empirical phenomenological models.T he germination of Bacillus and Clostridium endospores can play an important role in food safety and, as in the case of anthrax, in bioterrorism and public health as well. But germination can also influence health promotion, as in the case of supplementing food with probiotic bacilli (1). It is no wonder, therefore, that the biochemical and biophysical mechanisms of bacterial spore germination and its kinetics have been intensively studied (2-6). Fungal spore germination can play an important role in food production (notably in blue cheeses) and spoilage but also in skin and other human diseases. Thus, the mechanisms of yeast and mold spore germination, and their kinetics, have also been extensively studied (7,8). Although microbial cell division and spore germination are distinct physiological phenomena, their time scales can be about the same. The two processes' kinetics may also have superficial similarities. When the percentage (or fraction of) germinated microbial spores is plotted versus time, the typical result is a sigmoid curve, which resembles the isothermal growth curve of microbial cells in a closed habitat prior to the onset of mortality. It has therefore been tempting to use microbial growth models, notably the Gompertz model (see below), to describe isothermal germination curves and extend their application to dynamic conditions such as fluctuating temperatures.The main objectives of this work were as follows: (i) to develop a mathematical method to con...