Forestry seedling raising seedling disease and insect pest early warning system based on digital twinning

By implanting microdialysis probes, deploying micro thermocouple arrays and microbial fuel cells in seedlings, a multi-scale coupled model was constructed, which solved the problems of accuracy and timeliness in seedling disease and pest early warning in existing technologies, and realized early warning and probabilistic time prediction of seedling diseases and pests.

CN122223933APending Publication Date: 2026-06-16聊城市林业发展中心
View PDF 3 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
聊城市林业发展中心
Filing Date
2026-03-17
Publication Date
2026-06-16

AI Technical Summary

⚠Technical Problem

Existing technologies lack the ability to continuously, in situ, and with high precision collect and analyze endogenous physiological signals of individual seedlings in forestry seedling cultivation. This results in early warning of pests and diseases relying on empirical maps, lacking clear physiological indicators and causal explanations, thus limiting the accuracy and timeliness of early warnings.

⚗Method used

By implanting microdialysis probes into the main trunk of seedlings to collect xylem sap signal molecules, deploying micro thermocouple arrays on the leaf surface to measure temperature fluctuations, and deploying microbial fuel cells in the rhizosphere soil to monitor microbial metabolic currents, a multi-scale coupled model is constructed to simulate physiological and ecological states, and combined with nonlinear dynamic analysis for early warning of diseases and pests.

🎯Benefits of technology

It enables early warning of seedling diseases and pests, quantifies the deviation between the actual state and the theoretical model, identifies the chaotic state of the system and predicts the probability and timing of disease and pest occurrence, outputs forward-looking early warning signals, and improves the accuracy and timeliness of early warning.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN122223933A_ABST
    Figure CN122223933A_ABST
Patent Text Reader

Abstract

The application relates to the technical field of digital twinning, and particularly provides a forestry seedling raising seedling disease and pest early warning system based on digital twinning, which comprises a seedling endogenous signal acquisition subsystem for synchronously collecting concentration time series data, temperature fluctuation curves and current change original signals, amplifying and filtering the original signals, and then extracting energy features of each frequency band through wavelet packet decomposition to form actual feature vectors representing physiological and ecological states of the seedlings; an ecological coupling model construction subsystem is used for performing element-by-element difference on the actual feature vectors and theoretical state vectors to obtain a deviation vector; a nonlinear dynamics analysis subsystem is used for calculating Lyapunov exponents and correlation dimensions of the deviation vector, judging whether the system enters a chaotic state, and comparing with a feature library before a historical disease and pest outbreak to identify a risk level of a current state. The application realizes integration from real-time monitoring, virtual simulation to advanced prediction.
Need to check novelty before this filing date? Find Prior Art