Soil data processing method and system combined with demand analysis

By detecting soil and seed characteristic parameters and combining integrated soil adjustment prediction and error compensation, the soil adjustment scheme is optimized, which solves the problem that existing soil management methods lack precise consideration and achieves high efficiency and accuracy in soil adjustment.

CN121766533APending Publication Date: 2026-03-31LUAN MINGFENG AGRICULTURAL SCIENCE & TECHNOLOGY DEVELOPMENT CO LTD
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Patent Information

Application Number
CN202511978662.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-25
Publication Date
2026-03-31

AI Technical Summary

Technical Problem

Existing soil management methods lack precise consideration of the differences in the needs of different crops and systematic predictive optimization methods, resulting in low soil adjustment efficiency and difficulty in ensuring the accuracy and effectiveness of the adjustment results.

Method used

By detecting soil and seed characteristic parameters of the target land, and combining integrated soil adjustment prediction and sample error compensation, the soil adjustment scheme is optimized to meet the needs of seed growth. The systematized processing adopts basic detection module, adjustment prediction module, error compensation module and adjustment optimization module.

Benefits of technology

It achieves precise matching of seed needs, improves the pertinence and effectiveness of soil conditioning, and ensures healthy seed growth.

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Abstract

The invention relates to a demand analysis-combined soil data processing method and system, and relates to the field of data processing, and the method comprises the steps: detecting target land soil characteristic parameters and target seed demand parameters, randomly configuring a soil adjustment scheme, carrying out the integrated prediction, and carrying out the error compensation based on a data sample occurrence rate and a historical adjustment error rate. Finally, an optimal soil adjustment scheme is obtained according to optimization of the soil nutrient fitness and the soil gap fitness, the technical problem that a soil management adjustment method lacks accurate consideration of different crop demand differences and systematic prediction and optimization means is solved, and the purposes that seed demands can be accurately matched, and the adjustment accuracy is improved are achieved. And the pertinence and effectiveness of soil adjustment are improved.
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