Mango shelf-life modelling

Australian mangoes (Mangifera indica) enjoy a high reputation owing to their large size, attractive skin blush, and sweet and juicy taste. Increasing demand in overseas markets, particularly Asian, indicates a great potential for export. However, risks during export such as high storage temperature in air freight or long in-transit times of sea shipments can cause loss of fruit quality and shelf life, and consequently disappoint consumers. Yiru Chen, a horticulturist from the Supply Chain Innovation team at the Department of Agriculture and Fisheries in Queensland Australia, worked with her colleagues on a five-year project aiming to deliver consistently high quality of fresh Australian mangoes into Asian markets. This research sought to improve decision making around export logistics through models predicting shelf-life of two Australian mango cultivars, ‘R2E2’ and ‘Kensington Pride’ (KP). Based on extensive monitoring of commercial shipments, temperature and storage duration matrices were designed to encompass the range of temperature and time conditions encountered in export supply chains. Laboratory-based simulation trials were conducted in three consecutive seasons (2018/19 to 2020/21). Statistical models were trained and validated with split dataset (70 and 30%, respectively) and verified by real-world shipment monitoring data. The results showed that the developed remaining shelf-life prediction models had demonstrated potential to empower supply chain stakeholder decision-making towards supporting consumer satisfaction. Averaged storage temperature decreasing from 17 to 13°C led to a 2.4-day increase in shelf-life of ‘R2E2’. Specific regression models were required to account for differences between cultivars and between harvest times (‘early’ or ‘late’). For ‘R2E2’, shelf-life prediction intervals (PI) at 90% confidence level were ±3.2 days and root mean square errors (RMSE) was 4.1 days. PI and RMSE of ‘KP’ were ±2.8 and 4.8 days, respectively. Dry matter content at harvest as a co-variable did not improve shelf-life predictions for both cultivars. A web-based dashboard and a mobile phone application were developed for model demonstration to the industry. Meanwhile, Yiru is a part-time PhD candidate at the University of Queensland. Her research interests include maintaining postharvest quality of fresh produce along supply chains using predictive modelling approaches and technologies.

Yiru Chen won the ISHS Young Minds Award for the best oral presentation at the International Symposium on Postharvest Technologies to Reduce Food Losses at IHC2022 in France in August 2022.

Yiru Chen, Department of Agriculture and Fisheries, Queensland 4102, Australia, e-mail: Yiru.Chen@daf.qld.gov.au

The article is available in Chronica Horticulturae