Practicability of TTI application to yogurt quality prediction in plausible scenarios of a distribution system with temperature variations.

Yogurt has high temperature sensitivity, resulting in the temperature variations from production to consumption. Cooling capacity of cold chain facilities and product storage height are regarded as factors contributing to temperature variations in this study. To find an effective method to monitor temperature history of every yogurt product, three measurements were used: the set point of a cold chamber, a data logger, and a time-temperature integrator (TTI). The mean measured yogurt quality factor (acidity, °T) of 30 samples was 92.1 °T, and predicted values were 91.8 °T from the set point, 93.3 °T from the data logger, and 92.4 °T from the TTI. In terms of individual prediction, the SSE of the TTI showed the smallest difference (5.76) followed by 81.5 of the set point and 118.9 of the data logger. Thus, the TTI showed the best performance and can be used to monitor the time-temperature history of yogurt in the cold chain system.