The Role of Auto-Harvester in Enhancing the Efficiency of the Australian Mango Value Chain

The growing reduction in overtime-driven manual labour is an imminent threat to the profitability and overall sustainability of the agri-food industry, including the Australian mango industry. Specifically, picking and packing operations during harvesting contribute almost 50% or more of the total variable cost of production. The adoption of cost-efficient automation technologies in the harvesting of high-value tree fruits, therefore, becomes essential. However, it faces the challenges of capital investment, reliable equipment performance, compatibility to heterogenous planting systems in the different orchard environments, and in-house upskilling and capability development. Recently it has been projected that the use of mango auto-harvesters [MAH] achieves greater performance accuracy through detection and fruit load estimation and reduces the cost of production. The aim of this project is to investigate the performance parameters that an auto-harvester must achieve to replace human labour and the technological requirements for its adoption by the industry. Using a qualitative research approach, this study presents data from respondents representing more than 40% of the Australian fresh mango production, and more than 200 farmer members’ insights. The findings have provided unique theoretical, economic, and social contributions that filled a clear research gap. From a theoretical standpoint, this research will advance the understanding of factors like behavioural, competitive pressure, and sustainability-driven, besides commercial, and operational ones that can potentially expedite the adoption rate of the auto-harvester. The study establishes that the “3 As” of labour (namely, affordability, availability, and assurance) must be addressed with a holistic appreciation of all the stakeholders in the industry. The researcher has identified efficiency parameters and break-even thresholds for growers (categorized under large, medium, and small), that will increase the uptake rate to replace human labour. An interactive simulating tool has been developed to get a “go” or “no-go” capital investment decision, bespoke to the grower’s size, scale, current labour costs and complexity of operation. From an economic perspective, the adoption of auto-harvester technology can augment the growth of the Australian mango industry, contributing to the national GDP. Based on historical data trend, a model has been developed with extrapolated revenue and wages, to predict the gross profit margin outlook in 2030. Other things being the same, overdependence on manual labour could lead to a drop in the gross profit margin by 5.4%. Socially, the upskilling, international trade, and yield-enhanced growth of the mango industry will improve the eating experience, create more job opportunities, and improve the socio-economic conditions of the people related to the mango growers’ community. This research contributes to the Sustainable Development Goals (SDGs) 1,2, 8, and 9, stipulated by the United Nations.