Multi-element crop disease and insect pest monitoring and early warning method based on big data

Abstract

The invention provides a multi-element crop disease and insect pest monitoring and early warning method based on big data. According to the multi-element crop disease and insect pest monitoring and early warning method based on big data, reported data is subjected to standard classification, such as successive data reporting, weekly report data reporting, lamp trapping data reporting and grass adult trapping data reporting, so that the difficulty of subsequent data statistical analysis is reduced; the crop pest monitoring pre-system performs statistical analysis on local pest data uploaded by plant protection stations of all cities and counties of the whole province, and performs distribution by using a comprehensive analysis and prediction method to obtain the occurrence probability of the pest; and a unified data format is formulated to realize unified uploading of each plant protection station in the whole province. According to the multi-element crop disease and insect pest monitoring and early warning method based on big data, a reliable basis is provided for a manager to make a scientific decision, and the problems of manpower and material resource waste, incomplete monitoring, lack of accuracy of early warning and the like caused by traditional disease and insect pest monitoring are reduced.

Description

technical field [0001] The invention relates to the field of crop quality safety, in particular to a method for monitoring and early warning of multiple crop diseases and insect pests based on big data. Background technique [0002] People depend on food, and pests and diseases are unavoidable in agricultural production, but agricultural growers rely too much on chemical pesticides, which has caused serious troubles to the agricultural environment and crop safety. The outdated concept of pest control should strengthen the monitoring and early warning of pests and diseases, further understand the occurrence of pests, and accelerate the transformation of chemical control to green control. However, traditional pest monitoring relies on manpower, which has low efficiency and poor accuracy, and cannot meet the actual work needs of modern agricultural pest monitoring and early warning. Using the pest monitoring system to carry out automated and intelligent remote real-time monitor...

AI Technical Summary

Problems solved by technology

However, traditional pest monitoring relies on manpower, which has low efficiency and poor accuracy, and cannot meet the actual work needs of modern agricultural pest monitoring and early warning. Using the pest monitoring system to carry out automated and intelligent remote real-time monitoring of pests can be used for green crop prevention and control. Do a good job in monitoring and effectively improve the level and effect of pest monitoring and early warning

[0003] The effect of pest control depends to a large extent on the effectiveness of pest monitoring. Traditional pest monitoring generally involves setting up a fixed point in the field. The monitored data needs to be collected by a special person every day, which is very inconvenient. It is convenient, and at the same time, the real-time performance is relatively poor; and with the advancement of science and technology, there are many means of monitoring pests and diseases, but most of them are lacking in data. Precise early warning of possible pests and diseases in the future, and the general early warning technology lacks a clear classification of pests and diseases, and there are many plant protection stations in various places, and when uploading a lot of data, it is easy to cause the data to be disorderly and close, resulting in difficulties in data statistics, which cannot be achieved. Scientific monitoring and early warning effect

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