The invention relates to the technical field of smart
agriculture, and discloses a smart
agriculture comprehensive
management system integrated with
big data analysis, which is characterized in that an in-vivo physiological
probe array applies micro stimulation to a key sample
plant, collects a biopotential
signal, extracts a stimulation response feature signature, and realizes early and accurate diagnosis of a
crop stress state; taking the diagnosis result as a
ground truth value, dynamically calibrating a
remote sensing-physiological state mapping model, and applying the model to global
remote sensing data to generate a high-precision stress diagnosis
distribution diagram; generating a variable operation prescription based on the distribution map and instructing the intelligent agricultural
machine to execute; after operation, the
system collects a
recovery phase potential
signal to extract a
recovery phase feature signature, and closed-loop adaptive updating is carried out on a
decision model for generating a prescription. According to the method, internal physiological information of crops can be directly obtained, diagnosis
hysteresis is overcome, the accuracy of large-range diagnosis is remarkably improved, a decision
closed loop with learning ability is constructed, and
adaptive optimization of management is realized.