Hélias A, Mirade P-S, Corrieu G
UMR782 Génie et Microbiologie des Procédés Alimentaires, Institut National de la Recherche Agronomique, AgroParisTech, F-78850 Thiverval-Grignon, France.
J Dairy Sci. 2007 Nov;90(11):5324-33. doi: 10.3168/jds.2007-0272.
A model of the mass loss of Camembert-type cheese was established with data obtained from 2 experimental ripening trials carried out in 2 pilot ripening chambers. During these experiments, a cheese was continuously weighed and the relative humidity, temperature, oxygen, and carbon dioxide concentrations in the ripening chamber were recorded online. The aim was to establish a simple but accurate model that would predict cheese mass changes according to available online measurements. The main hypotheses were that 1) the cheese water activity was constant during ripening, 2) the respiratory activity of the microflora played a major role by inducing heat production, combined with important water evaporation, 3) the temperature gradient existing inside the cheese was negligible, and the limiting phenomenon was the convective transfer. The water activity and the specific heat of the cheeses were assessed by offline measurements. The others parameters in the model were obtained from the literature. This dynamic model was built with 2 state variables: the cheese mass and the surface temperature of the cheese. In this way, only the heat transfer coefficient had to be fitted, and it was strongly determined by the airflow characteristics close to the cheeses. Model efficiency was illustrated by comparing the estimated and measured mass and the mass loss rate for the 2 studied runs; the relative errors were less than 1.9 and 3.2% for the mass loss and the mass loss rate, respectively. The dynamic effects of special events, such as room defrosting or changes in chamber relative humidity, were well described by the model, especially in terms of kinetics (mass loss rates).
利用在两个中试成熟室进行的2次实验成熟试验所获得的数据，建立了卡门培尔型奶酪质量损失模型。在这些实验过程中，持续对一块奶酪进行称重，并在线记录成熟室内的相对湿度、温度、氧气和二氧化碳浓度。目的是建立一个简单而准确的模型，该模型能够根据现有的在线测量数据预测奶酪质量变化。主要假设为：1）奶酪的水分活度在成熟过程中保持恒定；2）微生物群落的呼吸活动通过产热以及伴随的大量水分蒸发发挥主要作用；3）奶酪内部存在的温度梯度可忽略不计，限制现象为对流传递。通过离线测量评估奶酪的水分活度和比热容。模型中的其他参数从文献中获取。该动态模型由两个状态变量构建而成：奶酪质量和奶酪表面温度。通过这种方式，只需拟合传热系数，而它主要由奶酪附近的气流特性决定。通过比较两次研究运行中估计质量与测量质量以及质量损失率，说明了模型的有效性；质量损失和质量损失率的相对误差分别小于1.9%和3.2%。该模型很好地描述了特殊事件（如房间除霜或室内相对湿度变化）的动态影响，尤其是在动力学方面（质量损失率）。
