In this study, we evaluated the temperature situation during transportation by four major home delivery service providers in Taiwan. Automatic temperature data loggers were used to record the temperature profile during transportation. The obtained data were then simulated with various scenarios to estimate the remaining shelf life and food loss probability by using the Monte Carlo algorithm with 10,000 iterations.
