Rahardjo Yovita S P, Tramper Johannes, Rinzema Arjen
Wageningen Centre for Food Sciences, P.O. Box 557, 6700 AN Wageningen, The Netherlands.
Biotechnol Adv. 2006 Mar-Apr;24(2):161-79. doi: 10.1016/j.biotechadv.2005.09.002. Epub 2005 Nov 2.
Solid-state fermentation (SSF) is accompanied inevitably by development of concentration and temperature gradients within the substrate particles and microbial biofilms. These gradients are needed for driving the transport of substrates and products. In addition, concentration gradients have been suggested to be crucial for obtaining the characteristics that define the products of SSF; nevertheless, gradients are also known to result in reduced productivity and unwanted side reactions. Solid-state fermentations are generally batch processes and this further complicates their understanding as conditions change with time. Mathematical models are therefore needed for improving the understanding of SSF processes and allowing their manipulation to achieve the desired outcomes. Existing models of SSF processes describe coupled substrate conversion and diffusion and the consequent microbial growth. Existing models disregard many of the significant phenomena that are known to influence SSF. As a result, available models cannot explain the generation of the numerous products that form during any SSF process and the outcome of the process in terms of the characteristics of the final product. This review critically evaluates the proposed models and their experimental validation. In addition, important issues that need to be resolved for improved modeling of SSF are discussed.
固态发酵（SSF）不可避免地伴随着底物颗粒和微生物生物膜内浓度和温度梯度的形成。这些梯度对于驱动底物和产物的运输是必需的。此外，有人认为浓度梯度对于获得定义固态发酵产物的特性至关重要；然而，梯度也会导致生产率降低和产生不必要的副反应。固态发酵通常是间歇过程，随着时间的推移条件会发生变化，这使得对其理解更加复杂。因此，需要数学模型来增进对固态发酵过程的理解，并通过控制这些过程来实现预期的结果。现有的固态发酵过程模型描述了底物转化与扩散以及随之而来的微生物生长之间的耦合关系。现有模型忽略了许多已知会影响固态发酵的重要现象。因此，现有的模型无法根据最终产物的特性解释在任何固态发酵过程中形成的众多产物的产生以及该过程的结果。本综述对所提出的模型及其实验验证进行了批判性评估。此外，还讨论了为改进固态发酵建模需要解决的重要问题。
