Journal of Agronomy and Field Innovations

Rice (Oryza sativa L.) accounts for more than half of the food needs of the world’s population; however climate changes, irregular rainfall, and water scarcity threaten crop yields in the major rice-producing areas. The Digital Twin (DT) technologies that combine synchronized measurements with the dynamic simulation of physical systems create a possibility for climate-smart agriculture, although there is not enough empirical data to prove the effectiveness of DT technologies for rice production. This study was aimed at designing, implementing, and evaluating DT technology for precision rice management, which consists of IoT sensors, UAV, satellite technologies, cloud computing, and crop growth simulation systems at three climate scenarios (normal, delayed monsoon, and drought). The designed system allowed synchronization of soil, canopy, and meteorological data obtained at the field with the computer-based simulation model that provided data about crop growth and demand for water and nutrients in real time. The effectiveness of DT implementation was proved by comparing the performance of the fields with DT technologies with those of conventionally managed fields at the same climatic conditions during two seasons. The Digital Twin platform predicted grain yield with a mean absolute percentage error of six point eight percent and enhanced the efficiency of irrigation water use by twenty-four point three percent compared to the traditional practice. It reduced the application of nitrogen fertilizer by eighteen point six percent without penalizing yields. Moreover, decision-making support measures allowed reducing losses from diseases by twenty-one point four percent in the situation of heat stress. The strength of correlation and regression analyses showed similar results of simulated and real bean phenology and yield traits (r = 0.89-0.95). The results suggest that Digital Twin technology may substantially improve resource efficiency, adaptability to climate changes, and yield reliability in rice cultivation.