Intelligent detection and early warning method and system for quality safety of edible agricultural products

By establishing a correlation model and in-batch calibration parameters, the shortcomings of multi-source data calibration and conflict sample identification in the quality and safety supervision of edible agricultural products have been addressed, achieving the accuracy of sample comparability and disposal scope, and improving the reliability and intelligence of testing.

CN122264630APending Publication Date: 2026-06-23SHENZHEN LAIBO BIOTECHNOLOGY CO LTD
0 Cites 0 Cited by

Patent Information

Application Number
CN202610477254.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-13
Publication Date
2026-06-23

AI Technical Summary

Technical Problem

Existing food safety supervision schemes for edible agricultural products have shortcomings in terms of unified calibration of multi-source data, identification of conflicting samples, and accurate generation of disposal scope, leading to problems such as misjudgment of samples within a batch, inaccurate identification of conflicting samples, and imprecise disposal scope.

Method used

By establishing a correlation model, batch anchor samples are identified and intra-batch calibration parameters are generated. Image data, detection data, and environmental time-series data are calibrated to generate cross-modal consistency residuals. The risk propagation relationship is calculated by combining the correlation model, and the preceding parameters are corrected in reverse through the verification results, thereby improving the comparability of samples and the accuracy of the disposal scope.

Benefits of technology

It improves the comparability of multi-source data for samples in the same batch, enhances the accuracy of identifying conflicting samples and the precision of the chain-like handling scope, and forms a closed-loop update mechanism from detection and judgment to feedback correction, thereby improving the reliability and intelligence level of food safety testing.

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

Abstract

The invention relates to the technical field of edible agricultural product quality safety supervision, in particular to an edible agricultural product quality safety intelligent detection and early warning method and system integrating Internet of Things perception, multi-source data acquisition, intelligent detection, risk identification, risk early warning, automatic tracing and closed-loop supervision. According to the scheme, the incidence relation model is firstly established, then batch anchor point samples are determined, in-batch calibration parameters are generated, image data, detection data and environment time sequence data are calibrated, cross-modal consistency residual errors are generated, shunting judgment is completed, then the risk propagation relation is generated, the chain type processing range is determined, and the processing task is triggered. And finally, performing model correction according to a subsequent recheck result, thereby improving the comparability of multi-source data, the conflict recognition accuracy and the handling precision.
Need to check novelty before this filing date? Find Prior Art