Comparative Assessment of Environmental/Energy Performance under Conventional Labor and Collaborative Robot Scenarios in Greek Viticulture

The viticultural sector is facing a significant maturation phase, dealing with environmental challenges to reduce agrochemical application and energy consumption, while labor shortages are increasing throughout Europe and beyond. Autonomous collaborative robots are an emerging technology and an alternative to the scarcity of human labor in agriculture. Additionally, collaborative robots could provide sustainable solutions to the growing energy demand of the sector due to their skillful precision and continuous labor. This study presents an impact assessment regarding energy consumption and greenhouse gas emissions of collaborative robots in four Greek vineyards implementing a life cycle assessment approach. Eight scenarios were developed in order to assess the annual production of four Vitis vinifera L. cultivars, namely, Asyrtiko, Cabernet Sauvignon, Merlot, and Tempranillo, integrating data from two wineries for 3 consecutive years. For each conventional cultivation scenario, an alternative was developed, substituting conventional viticultural practices with collaborative robots. The results showed that collaborative robots' scenarios could achieve a positive environmental and energy impact compared with conventional strategies. The major reason for lower impacts is fossil fuel consumption and the efficiency of the selected robots, though there are limitations regarding their functionality, lifetime, and production. The alternative scenarios have varying energy demand and environmental impact, potentially impacting agrochemical usage and requiring new policy adjustments, leading to increased complexity and potential controversy in farm management. In this context, this study shows the benefits of collaborative robots intended to replace conventional practices in a number of viticultural operations in order to cope with climate change impacts and excessive energy consumption.