Apple tree growth state intelligent identification system

By constructing the internode spindle direction vector sequence and fruit parameters linkage change trends, identifying the growth status of apple trees, solving the problem of identification lag for branch structure and fruit growth mutations in the existing technology, and achieving accurate identification and management of fruit tree growth abnormalities.

CN120495687AActive Publication Date: 2025-08-15子长市果业开发中心
6 Cites 2 Cited by

Patent Information

Application Number
CN202510976199.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-16
Publication Date
2025-08-15
Estimated Expiration
2045-07-16

AI Technical Summary

Technical Problem

The existing apple tree growth status recognition system lacks quantitative analysis of continuous change trends in the direction between branches and nodes and analysis of dynamic timing angle differences, resulting in the inability to accurately identify fruit growth mutations, affecting the advance warning and management of abnormal growth areas of fruit trees.

Method used

The vector sequence of internode spindle direction is constructed, the angle change trend is quantified, and the fruit diameter growth rate and color difference change trend is combined. The growth trajectory sequence is constructed through the three-dimensional vectors of multi-period branch angle growth, diameter growth rate and leaf area index to identify the fruit growth mutation nodes.

Benefits of technology

It improves the accuracy and timeliness of growth abnormality recognition, and supports the accuracy and timeliness of intelligent management of fruit trees.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention relates to the technical field of state recognition, in particular to an apple tree growth state intelligent recognition system which comprises a branch structure recognition module, a direction sequence calculation module, a growth stability judgment module, a fruit trend steering module and a vector trajectory offset module. According to the method, the continuous change characteristics of the branch direction in the time sequence dimension can be identified by constructing the inter-node main axis direction vector sequence and quantifying the change trend of the included angle of the inter-node main axis direction vector sequence, synchronous detection of the fruit diameter growth rate and the color difference change trend is combined, and the reflectivity and morphological symmetry linkage change is introduced as the judgment condition of the trend turning point; according to the method, fruit growth mutation nodes are effectively positioned, a growth trajectory sequence is constructed through multi-period branch angle amplification, diameter growth rate and leaf area index three-dimensional vectors, an individual growth direction offset region is accurately identified, and the precision and timeliness of growth anomaly identification are enhanced. And intelligent fruit tree management implementation based on the linkage relationship between the structure and the fruit parameters is effectively supported.
Need to check novelty before this filing date? Find Prior Art