Abstract
Digitalization has impacted agricultural and food production systems, and makes application of technologies and advanced data processing techniques in agricultural field possible. Digital farming aims to use available information from agricultural assets to solve several existing challenges for addressing food security, climate protection, and resource management. However, the agricultural sector is complex, dynamic, and requires sophisticated management systems. The digital approaches are expected to provide more optimization and further decision-making supports. Digital twin in agriculture is a virtual representation of a farm with great potential for enhancing productivity and efficiency while declining energy usage and losses. This review describes the state-of-the-art of digital twin concepts along with different digital technologies and techniques in agricultural contexts. It presents a general framework of digital twins in soil, irrigation, robotics, farm machineries, and food post-harvest processing in agricultural field. Data recording, modeling including artificial intelligence, big data, simulation, analysis, prediction, and communication aspects (e.g., Internet of Things, wireless technologies) of digital twin in agriculture are discussed. Digital twin systems can support farmers as a next generation of digitalization paradigm by continuous and real-time monitoring of physical world (farm) and updating the state of virtual world.
Highlights
One of the main global challenges is how to ensure food security for the world’s growing population whilst ensuring long-term sustainable development
One of the main features of digitalization in agriculture is the introduction of innovative Information and Communication Technology (ICT), Internet of Things (IoT), big data analytics and interpretation techniques, machine learning and Artificial Intelligence (AI)
There are different types of digital farming paradigms in the literature that could be used in digital twin concepts as the generation of digitalization in the agricultural field
Summary
One of the main global challenges is how to ensure food security for the world’s growing population whilst ensuring long-term sustainable development. Data acquisition and analysis in digital farming by means of smart technologies are supporting complex decision-making approaches [8,9] They enhance final productivity, reduce costs, and optimize the decision-making process. An alternative technology which has been recently introduced to the smart farming is edge-computing that enables computation at the edge of the network [17] It helps to reduce network load and supports real-time data processing in agricultural fields. Cyber-physical systems have been introduced through smart farming systems to develop hardware and software, improve adaptability, and safety and security of computer-based algorithms and systems [18] It enables adaptability, practicality, security, and safety of collected information in agricultural field e.g., climate, irrigation, soil, nutrition, and yield for better management.
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