Monitoring analysis system and method for potato breeding

Through multimodal data collection and spatiotemporal causal modeling, combined with three-dimensional phenotypic analysis and whole genome association, the problems of insufficient detection of latent diseases and delayed warning of genetic degeneration in potato breeding have been solved, precise breeding and early risk identification have been achieved, and breeding efficiency and yield have been improved.

CN120823876APending Publication Date: 2025-10-21ECONOMIC CROP RES INST OF HEILONGJIANG ACAD OF AGRI SCI
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Patent Information

Application Number
CN202510921275.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-04
Publication Date
2025-10-21

AI Technical Summary

Technical Problem

In existing potato breeding technologies, traditional visible light imaging technology cannot identify latent diseases, and multispectral imaging and gene expression data are not integrated, resulting in insufficient disease detection, lack of temporal correlation between environmental parameters and gene expression, and delayed warning of species degeneration.

Method used

A multimodal data acquisition module is used to obtain greenhouse environmental parameters, multispectral imaging data and leaf metabolite concentrations. A dynamic association model between environmental fluctuations and gene expression is constructed through the spatiotemporal causal modeling module. A multimodal risk index is generated and adaptive environmental regulation is triggered. Combined with three-dimensional phenotypic analysis and whole genome association analysis, degradation early warning is achieved.

Benefits of technology

It significantly improves the accuracy of potato breeding monitoring and the timeliness of early warning, identifies degradation risks in advance and dynamically adjusts greenhouse parameters, reduces the cost of blind planting adjustments, improves starch accumulation efficiency, reduces virus detection rates and increases yields.

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Abstract

The invention discloses a monitoring analysis system and method for potato breeding, and relates to the technical field of agricultural information technology and intelligent breeding, and the system comprises a multi-modal data acquisition module which is configured to synchronously obtain greenhouse environment parameters, potato plant multispectral imaging data and leaf metabolite concentration data; and the space-time causal modeling module is connected to the multi-modal data acquisition module, and is used for constructing a dynamic correlation model among environmental fluctuation, gene expression and phenotypic characteristics, and deducing and quantifying the genetic effect of the environmental abnormal event based on anti-fact intervention. According to the monitoring analysis system and method for potato breeding, through multi-modal data fusion and space-time causal modeling, the accuracy and early warning timeliness of potato breeding monitoring are improved, the limitation of traditional visible light imaging is broken through, and the incubation period disease recognition accuracy is improved compared with a traditional method.
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