AbstractIn‐transit quality loss and wastage of perishables, during cold chain export, is a critical issue faced globally. Owing to increasing population, reducing food wastages by enhancing the efficacy of supply chain is imperative to meet the increasing demand. This paper presents a virtual cold chain‐based approach to model quality loss of horticultural produce prior to actual logistics operations. It is a combination of different models for predicting the temperature heterogeneity among the perishables, its related quality decay and remaining shelf‐life. An innovative simulation‐based approach is also presented which predicts the temperature of perishables inside a domain based upon its storage conditions, at a reduced computational expense. The proposed approach is demonstrated for Indian mango cold chain export. The simulation results are validated with an experimental setup, using mangoes and a standard refrigerated (reefer) container. Different metrices shows a RMSE and MAPE of 0.8 K and 10.02%, respectively. The calculated remaining quality is also found to be in accordance with experimental findings. The results report uneven air circulation and hence, heterogeneity in temperature distribution of about 3–4 K after 15 days of sea transport. This induces variations in remaining quality and shelf‐life among the mangoes placed at different locations. The maximum variation in quality is found to be 19% at 25th day of export at a location near the door of the reefer. The export transit time should be less than or equal to 26 days, to avoid spoilage, as it is the minimum shelf life of mangoes inside the container under given conditions.Practical applicationsThis study is concerned with managing the loss in quality and wastage of perishables, during cold chain export. Predicting the storage temperature, prior to actual logistics operations, can aid the decision makers in appropriate planning of export mode so as to minimize the loss and wastage during real export process. A virtual or simulation‐based approach is proposed to analyze the cooling behavior of individual mangoes and hence predict the evolution of its various quality attributes, passing through different stages of the cold chain. To illustrate this approach, a case study of Indian mango export is presented.