European Journal of Sustainable Agroecosystems

Rice (Oryza sativa L.) contributes significantly towards feeding half of the world’s population. Nevertheless, rice production faces various challenges, such as reduced water availability, ineffective nutrient use, and balancing increased yields against sustainability. Digital Twin (DT) technology is one of the potential solutions to the problems above that aggregates various state-of-the-art technologies such as IoT, UAV, and satellite remote sensing, as well as edge and cloud computing, and AI-assisted predictive analytics into one unified real-time monitoring and decision-making system. The article summarizes various peer-reviewed works focused on utilizing DT technology for rice growth monitoring and resource use efficiency (RUE). The findings of the reviewed literature indicate that Internet of Things (IoT) based soil moisture and water level sensors combined with machine learning-assisted irrigation scheduling help significantly reduce irrigation water consumption as compared to traditional flooding irrigation while improving yields. Such machine learning-assisted systems demonstrated their ability to predict rice growth, nitrogen status, and yields with R2 ranging from 0.79 to 0.94. Another advantage of applying edge-computing to agriculture is enhanced speed of data processing and near-real-time data transmission and synchronization. In order to support effective decision-making through digital twin systems, it is essential to synchronize real-world agronomical conditions with digital crop models. The case studies have shown that integrated digital twin technologies that marry sensor data with predictive analytics positively impact water use and nitrogen use efficiency, as well as the consistency of crop yields in rice production systems, compared to traditional rice production practices and systems. At the same time, the review highlights some unresolved issues, including high costs of implementation, limitations of communication infrastructure in rural and smallholder farming practices, model transferability, and inconsistency in utilization figures reported in various studies. The review concludes that the digital twin technology becomes an effective way for the development of produce sustainable rice cultivation practices, and its implementation will result in changes in the agricultural sector mostly at research institutions and large businesses.