To ensure continuous innovations, food industries need tools which enable to predict physical-properties of food during a change of process or recipe. In this work, a thermodynamic model is suggested to predict pH and water activity of pork meat in presence of different additives such as salts or organic acids used in food industry. The predictions of pH and aw are satisfactory in a wide prediction domain, with a good accuracy. In add, a neural network mimetic of thermodynamic model is developed in order to facilitate the use of thermodynamic model and reduce calculation time.

中文翻译：

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用热力学模型预测猪肉的pH和aw：新进展

为了确保持续创新，食品工业需要能够在过程或配方更改期间预测食品物理特性的工具。在这项工作中，提出了一种热力学模型来预测在食品工业中使用的各种添加剂（例如盐或有机酸）存在下猪肉的pH值和水活度。在很宽的预测范围内，pH和aw的预测结果令人满意，且准确性很高。另外，开发了神经网络模拟热力学模型，以促进热力学模型的使用并减少计算时间。