Method and system for dynamically predicting vomitoxin content of wheat in harvesting period

Abstract

The invention provides a method and system for dynamically predicting the vomitoxin content of wheat in the harvesting period, and the method comprises the steps of screening out comprehensive factors suitable for building a prediction model through a particle swarm optimization algorithm based on historical data, and building the prediction model through the comprehensive factors; meanwhile, obtaining a second flowering period and a second harvest period of wheat in the current year through agricultural model prediction based on data in the current year, then obtaining weather forecast based on the second flowering period and the second harvest period, and converting the weather forecast and geographic data into related factors, and finally predicting the vomitoxin content in the wheat harvesting period through the prediction model and related factors. Compared with the prior art, statistical items in the prediction model are more complete, growth data of the current year can be dynamically predicted based on the growth period index, then the prediction model is continuously adjusted and established, and meanwhile, the time overhead screened by the particle swarm optimization algorithm for multi-dimensional and large-batch data has more advantages, and the prediction model established through the multiple linear regression algorithm is higher in precision.

Description

technical field [0001] The invention relates to the field of agricultural prediction, in particular to a method and system for dynamically predicting the content of vomitoxin in wheat harvest period. Background technique [0002] DON pollution in grains is produced in two stages, prenatal and postnatal respectively. With the advancement of science and technology and the continuous improvement of grain storage methods in my country, the occurrence of mycotoxins in grains mainly exists before grain harvesting. Before harvest, due to fungal infection during the growth of food crops in the field, the influence of farming methods and unstable weather conditions, mycotoxins accumulate, and there are large differences between different regions and different years. Therefore, it is very important to predict the content of DON in grains before harvest, so as to implement targeted preventive measures and fundamentally reduce the contamination of DON in grains. [0003] In the prior a...

AI Technical Summary

Problems solved by technology

[0004] In the prior art, there is still a static prediction method that only predicts a single time point, which often leads to inaccurate prediction results

[0005] In the prior art, there is also the problem that the time overhead of the algorithm adopted for multi-dimensional and large-scale data is too large

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