Refrigerated transport and storage of mango fruit are essential to maintain quality, reduce food waste and the associated embodied energy losses. Refrigeration is also key to enable successful transcontinental export to distant markets. To minimize the environmental impact of the cold chain and to optimize logistics, a better knowledge of the fruit quality evolution within individual shipments would be extremely valueable. For this purpose, a digital fruit twin is developed, based on mechanistic modeling. This digital twin simulates the thermal behavior of mango fruit throughout the cold chain, based on the measured environmental temperature conditions, namely the air temperature in the vicinity of the fruit. At the same time, the evolution of associated quality attributes, due to enzymatically-driven, temperature-dependent biochemical degradation reactions, is quantified. Also, a biophysical counterpart of real mango fruit – an innovative fruit simulator sensing device – was developed and used for model validation of fruit pulp temperatures. We identified – in-silico – the impact of the unique delivery air temperature history and cold chain length on fruit quality evolution for actual maritime vs. airfreight transport pathways. Digital twins were found to provide complementary insights in the thermophysical behavior of fruit, particularly in supply chains of very perishable species, and for storage at low airflow rates. Such mechanistic modeling enabled to understand, record, and predict where temperature-dependent fruit quality loss occurs in each supply chain. In that way, digital twins can help to improve refrigeration processes and logistics to reduce food losses, thereby making the refrigerated supply chain greener.