Regional agricultural product over-standard probability prediction and error analysis method

Abstract

The invention relates to a regional agricultural product standard exceeding probability prediction and error analysis method, and the method comprises the steps: dividing a research region into different sub-regions through the existing soil monitoring information and agricultural product monitoring information of the research region, and carrying out the iterative precise calculation in the sub-regions, thereby improving the accuracy and applicability of an agricultural product risk prediction model, and improving the prediction precision. While the accuracy is greatly improved, the on-site sampling workload can be greatly reduced, and data support is provided for producing area environment early warning work.

Description

technical field [0001] The invention belongs to the technical field of agricultural environment, and in particular relates to a method for predicting and analyzing the probability of exceeding the standard of regional agricultural products. Background technique [0002] The pollution of agricultural products in my country is serious year by year. It is of great significance to analyze the main causes, clarify the key links, and propose corresponding countermeasures to control the risk of excessive heavy metals in agricultural products. Excessive heavy metals in agricultural products have the characteristics of high risk uncertainty, complex influencing factors, and different accumulation physiological mechanisms. However, the current risk prediction methods are relatively single and the accuracy of the results is low. In addition, the safety of agricultural products is closely related to soil quality, but the current monitoring of soil and agricultural products is not system...

AI Technical Summary

Problems solved by technology

Excessive heavy metals in agricultural products have the characteristics of high risk uncertainty, complex influencing factors, and different accumulation physiological mechanisms. However, the current risk prediction methods are relatively single and the accuracy of the results is low.

In addition, the safety of agricultural products is closely related to soil quality, but the current monitoring of soil and agricultural products is not systematic and the data availability is low, and there are few studies on the response relationship between agricultural products and soil heavy metal content

[0003] CN113020232A, on the basis of encrypted point distribution detection results, conducts preliminary unit division of the target area, further partitions according to the pollution characteristics of each unit, selects corresponding restoration and treatment measures, and carries out tracking evaluation and dynamic adjustment of the treatment effect; CN112883137A discloses a safe place of origin of agricultural products Encrypted investigation and safety early warning methods, including multi-stage and multi-process processes such as calculation of the probability of exceeding the standard of agricultural products, encrypted investigation, classified early warning, and early warning response; the above-mentioned technologies all involve the method of encrypted point distribution, which does not involve the calculation of detection data based on the main cause of change. In order to obtain the point representative area of ​​the encrypted point, the effect of representing the characteristics of the research area is low

[0004] The main problems of the above-mentioned technical methods are: (1) The comprehensive utilization of soil and agricultural product monitoring data is low; (2) The risk prediction work of agricultural products is rarely carried out and the technology is single, with low accuracy and poor applicability; (3) The workload of risk prediction and the consumption of funds and time are large

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