Digital Twins: A novel traceability concept for post-harvest handling

Abstract

Digital Twins are a novel approach to systems engineering that can help control complex environments and interface humans with them. This is achieved by digitally mirroring a physical asset to provide historical data, monitoring, and predictions of future states. While there are a few applications of Digital Twins to agriculture, none exist for post-harvest grain handling. However, there have been past attempts at integrating computer assistance in grain quality, called expert systems. These systems were largely abandoned due to their inability to keep operators in the loop and the inadequacy of sensors available during the time of expert systems research. By utilizing Digital Twins and modern post-harvest sensors, operators can be provided with a digital representation of inventory and the quality of grain as it moves throughout a facility. This virtual representation also presents a unique opportunity to enhance market traceability. This review focuses on (1) expert systems, their history, and limitations, (2) the history of Digital Twins and their applicability to grain storage and handling, (3) unit operations and the sensors that are common to grain handling facilities, (4) mathematical and computer models to simulate grain handling operations, and (5) a conceptualization of post-harvest Digital Twins, which identifies research gaps where critical questions should be answered if Digital Twins technology is to be considered a logical contender for traceability of commodities post-harvest.