The invention discloses an intelligent
crop growth cycle management method and
system, and the method comprises the steps: dividing
dynamic monitoring grids based on the farmland
terrain, laying monitoring points at the vertexes of each grid, and collecting the
soil fertility and environment data; and generating a full farmland
soil fertility index matrix through a spatial interpolation
algorithm. Inputting the matrix, the environment data and the
crop growth period parameters into a pre-training model, and outputting growth
abnormality risk areas and types; driving the unmanned aerial vehicle to get close to the abnormal area to obtain a high-definition image, analyzing the
disease and pest or
nutrition deficiency symptom through an image recognition model, and generating an illness state
verification result; and calling a farming operation
knowledge base according to a
verification result, and generating and executing a targeted operation instruction containing a fertilization /
pesticide application scheme. According to the method, the spatial representation precision of the
soil fertility is improved through dynamic gridding monitoring and interpolation, the
crop risk is predicted in combination with multi-
source data fusion, accurate
pathology recognition is realized by utilizing targeted
verification of the unmanned aerial vehicle, and the utilization efficiency of agricultural resources and the
pest control precision are remarkably improved.