Possas Arícia, Bonilla-Luque Olga María, Valero Antonio
Department of Food Science and Technology, University of Córdoba, Agri-Food Campus of International Excellence ceiA3, Campus Rabanales s/n, Crta. Madrid-Cádiz km 396A, 14014 Córdoba, Spain.
Foods. 2021 Feb 7;10(2):355. doi: 10.3390/foods10020355.
Cheeses are traditional products widely consumed throughout the world that have been frequently implicated in foodborne outbreaks. Predictive microbiology models are relevant tools to estimate microbial behavior in these products. The objective of this study was to conduct a review on the available modeling approaches developed in cheeses, and to identify the main microbial targets of concern and the factors affecting microbial behavior in these products. has been identified as the main hazard evaluated in modelling studies. The pH, a, lactic acid concentration and temperature have been the main factors contemplated as independent variables in models. Other aspects such as the use of raw or pasteurized milk, starter cultures, and factors inherent to the contaminating pathogen have also been evaluated. In general, depending on the production process, storage conditions, and physicochemical characteristics, microorganisms can grow or die-off in cheeses. The classical two-step modeling has been the most common approach performed to develop predictive models. Other modeling approaches, including microbial interaction, growth boundary, response surface methodology, and neural networks, have also been performed. Validated models have been integrated into user-friendly software tools to be used to obtain estimates of microbial behavior in a quick and easy manner. Future studies should investigate the fate of other target bacterial pathogens, such as spore-forming bacteria, and the dynamic character of the production process of cheeses, among other aspects. The information compiled in this study helps to deepen the knowledge on the predictive microbiology field in the context of cheese production and storage.
奶酪是全球广泛消费的传统产品，常与食源性疾病暴发有关。预测微生物学模型是估计这些产品中微生物行为的相关工具。本研究的目的是对奶酪中已开发的现有建模方法进行综述，并确定主要关注的微生物目标以及影响这些产品中微生物行为的因素。已确定为建模研究中评估的主要危害。pH值、a值、乳酸浓度和温度一直是模型中作为自变量考虑的主要因素。其他方面，如生牛奶或巴氏杀菌牛奶的使用、发酵剂培养物以及污染病原体固有的因素也已得到评估。一般来说，根据生产过程、储存条件和理化特性，微生物在奶酪中可能生长或死亡。经典的两步建模是开发预测模型最常用的方法。其他建模方法，包括微生物相互作用、生长边界、响应面方法和神经网络，也已被采用。经过验证的模型已被集成到用户友好的软件工具中，以便快速、轻松地获得微生物行为的估计值。未来的研究应调查其他目标细菌病原体的命运，如产芽孢细菌，以及奶酪生产过程的动态特性等其他方面。本研究汇编的信息有助于加深在奶酪生产和储存背景下对预测微生物学领域的认识。
