Crop yield prediction method and system, storage medium and electronic equipment

A crop yield and prediction method technology, applied in the agricultural field, can solve problems such as limited application, numerous calculation parameters, and complex boundary conditions

CN113159439APending Publication Date: 2021-07-23兰州里丰正维智能科技有限公司 +2
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
Publication Date
2021-07-23

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Abstract

The invention relates to the technical field of agriculture, and provides a crop yield prediction method and system, a storage medium and electronic equipment. The method comprises the following steps: acquiring a specific value of each parameter related to the growth of a preset crop; and inputting the specific values of all the parameters into a progressive water-salt embedded neural network model to obtain a predicted value of the yield of the preset crop, wherein the progressive water-salt embedded neural network model comprises two layers of progressive causal relationships. According to the invention, the predicted value of the yield of the preset crop is obtained; the influence of different irrigation amounts and other climate and growth factors under a field straw deep burying condition on water-salt migration of soil and production benefits of the crop can be simulated; and tests show that the progressive water-salt embedded neural network model has relatively high precision, can effectively represent the comprehensive conditions of preset crop growth, namely the double-layer progressive causal relationship among each associated parameter, water and salt content migration in the soil and the yield of the preset crop, captures the internal dependency relationship of each parameter, and can be used for simulating the water and salt migration rule of an irrigated area.
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Description

technical field

[0001] The invention relates to the field of agricultural technology, in particular to a crop yield prediction method, system, storage medium and electronic equipment. Background technique

[0002] Hetao irrigation area is an important grain production base in my country. Due to the sharp decrease in the amount of water diverted from the Yellow River and the imperfect management and utilization of water resources, problems such as secondary soil salinization in irrigated areas and agricultural non-point source pollution have become increasingly serious, restricting the sustainable and healthy development of agriculture in irrigated areas. How to improve saline land, improve efficiency and increase production is the main problem faced by irrigation districts. The distribution of water and salt in saline soil in irrigation areas affects the growth of crops. The study of water and salt migration can provide a theoretical basis for improving efficiency and yield...

Examples

Embodiment Construction

[0045] like figure 1 As shown, a method for predicting crop yield in the embodiment of the present invention comprises the following steps:

[0046] S1. Obtain the specific value of each parameter associated with the growth of the preset crop;

[0047] S2. Input the specific values ​​of all parameters into the progressive water-salt embedding neural network model to obtain the predicted value of the yield of preset crops, wherein the progressive water-salt embedding neural network model is used to simulate all parameters and soil water-salt content The functional relationship between, and the functional relationship between the simulated soil water and salt content and the yield of preset crops.

[0048] The progressive water-salt embedded neural network model includes 2 layers of progressive causality, which is embodied as: using the functional relationship between all parameters and soil water-salt content to obtain the specific value of soil water-salt content, based on th...