Giudici Paolo, Baiano Antonietta, Chiari Paola, De Vero Luciana, Ghanbarzadeh Babak, Falcone Pasquale Massimiliano
Department of Life Sciences, University of Modena and Reggio Emilia, 42122 Reggio Emilia, Italy.
Dipartimento di Scienze Agrarie, Alimenti, Risorse Naturali e Ingegneria, University of Foggia, 71122 Foggia, Italy.
Foods. 2021 Feb 4;10(2):334. doi: 10.3390/foods10020334.
This study deals with the mathematical modeling of crystallization kinetics occurring during batch production of the ice cream. The temperature decrease was recorded in-situ through a computerized wireless system. A robust pattern-recognition algorithm of the experimental cooling curves was developed to determine the initial freezing point. The theoretical freezing point was used to calibrate the whole time-temperature profile. Finally, a modified Gompertz's function was used to describe the main steps of crystallization kinetics. Derivative analysis of the Gompertz's function allowed to determine the time-temperature physical markers of dynamic nucleation, ice crystal growth and air whipping. Composition and freezing properties were used as input variables in multivariate analysis to classification purposes of the ice cream mixtures as a function of their ability to produce high-quality ice cream. The numerical analysis of the whole cooling curve was used to build predictive models of the ice cream quality indices.
本研究涉及冰淇淋批量生产过程中发生的结晶动力学的数学建模。通过计算机化无线系统现场记录温度下降情况。开发了一种稳健的实验冷却曲线模式识别算法来确定初始冰点。理论冰点用于校准整个时间-温度曲线。最后,使用修正的冈珀茨函数来描述结晶动力学的主要步骤。对冈珀茨函数的导数分析能够确定动态成核、冰晶生长和空气搅拌的时间-温度物理标记。在多变量分析中,将成分和冷冻特性用作输入变量,以便根据冰淇淋混合物生产高质量冰淇淋的能力对其进行分类。对整个冷却曲线的数值分析用于建立冰淇淋质量指标的预测模型。