Abstract
The paper discusses development of the smart digital twin of plant (SDTP) as an intelligent cyber-physical system that includes an open knowledge base and a multi-agent subsystem for planning and discrete-event modeling of plant growth and development, as well as forecasting crop parameters based on the knowledge of agronomists, which can be supplemented with sensors and plant growth management mechanisms. SDTP functions should provide continuous adaptive adjustment of the plant development plan for each specific field, depending on the changes in external conditions, so that the discrepancy between each digital crop models and the real crops is minimal. SDTP is designed to systematize and formalize expert empirical data of agronomists on the stages of plant growth and development and yield forecast. Currently, SDTP is implemented as a web service that integrates various data sources from the fields and plants, and provides users with a possibility to track the state of real plants, predict and simulate plant condition.
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