The invention relates to a shiny-leaved yellowhorn cultivation regulation and control method, device and equipment based on digital twinning and a medium. The method comprises the steps that spectral signals of shiny-leaved yellowhorn plants are collected in real time through an
optical fiber sensor, and a
nutrient prediction model driven by
machine learning is built in combination with historical data; generating an initial fertilization curve based on the current spectral
signal and a preset fertilization function
database, and driving the intelligent
sprayer to execute precise fertilization; furthermore, a digital twinning technology is utilized to fuse and update a spectral
signal and a shiny-leaved yellowhorn
nutrient absorption model, the influence of different fertilization strategies on
nutrient absorption is dynamically simulated, the element ratio is optimized, and a closed-loop regulation and control scheme is generated. According to the method, the problems of resource waste and yield fluctuation caused by fertilization decision
lag, model stiffness and element
antagonism effect in the traditional technology can be solved through real-time sensing of the
plant nutrient state, dynamic adjustment of the fertilization strategy and multi-element collaborative optimization, and the precision and ecological
economic benefits of shiny-leaved yellowhorn cultivation are remarkably improved.