CN-121994718-A - Method for obtaining crude protein yield of pasture and related equipment

CN121994718ACN 121994718 ACN121994718 ACN 121994718ACN-121994718-A

Abstract

The invention discloses a method for obtaining crude protein yield of pasture and related equipment, relating to the technical field of intelligent livestock and agricultural remote sensing, wherein the method comprises the following steps: multispectral data of a preset area are collected through a multispectral sensor carried by the unmanned aerial vehicle and are preprocessed, and then the earth surface reflectivity of the preset area is obtained. The method comprises the steps of calculating a vegetation nitrogen content index, a vegetation index and a grass yield of a preset area, extracting a topography factor of the preset area based on a digital elevation model of the preset area, inputting the vegetation nitrogen content index, the vegetation index, the grass yield and the topography factor into a learning model after training is completed to obtain a crude protein content of the preset area, and calculating the grass crude protein yield of the preset area according to the grass yield and the crude protein content. The invention establishes a high-precision and strong-robustness quantitative inversion method from unmanned aerial vehicle multispectral data to pasture crude protein yield.

Inventors

ZHAO XINQUAN
ZHAO NA
WANG JUNBANG
MING RU
OuYang Xihuang
WANG XIAOLI
ZHAO LIANG
XU SHIXIAO
ZHANG CHUNHUI
WANG ZHAOQI

Assignees

青海大学

Dates

Publication Date: 20260508
Application Date: 20251210

Claims (10)

1. A method for obtaining crude protein yield of pasture, comprising the steps of: collecting multispectral data of a preset area through a multispectral sensor carried by an unmanned aerial vehicle, wherein the multispectral data comprises a red-edge band; preprocessing the multispectral data; obtaining the earth surface reflectivity of the preset area according to the pretreated multispectral data; Calculating a vegetation nitrogen content index of the preset area based on a red-edge wave band in the pretreated multispectral data; Acquiring a vegetation index of the preset area and a grass yield of the preset area based on the pretreated multispectral data; Extracting a terrain factor of the preset area based on a digital elevation model of the preset area; inputting the vegetation nitrogen content index, the vegetation index, the grass yield and the terrain factors into a training learning model to obtain the crude protein content of the preset area; And calculating the crude protein yield of pasture in the preset area according to the grass yield and the crude protein content.
2. The method for obtaining crude protein yield of pasture as set forth in claim 1, wherein calculating the vegetation nitrogen content index of the preset area based on the red-side band in the pretreated multispectral data comprises: And obtaining the reflectivities of the wave bands with different wavelengths from the red-edge wave bands in the pretreated multispectral data, and calculating the vegetation nitrogen content index of the preset area according to the reflectivities of the wave bands with different wavelengths.
3. The method for obtaining crude protein yield of pasture as set forth in claim 1, wherein said obtaining of said grass yield in said predetermined area comprises: and calculating the grass yield of the preset area by utilizing a light energy utilization rate model based on the pretreated multispectral data.
4. A method for obtaining crude protein yield from pasture according to any of claims 1-3, wherein preprocessing the multispectral data comprises performing space-time alignment, radiometric calibration and atmospheric correction on the multispectral data.
5. The system for obtaining the crude protein yield of the pasture is characterized by comprising a data acquisition module, a data preprocessing module, a ground surface reflectivity acquisition module, a vegetation nitrogen content index acquisition module, a vegetation index yield acquisition module, a topography factor acquisition module, a crude protein content acquisition module and a crude protein yield acquisition module of the pasture; the data acquisition module is used for acquiring multispectral data of a preset area through a multispectral sensor carried by the unmanned aerial vehicle, wherein the multispectral data comprises a red-edge wave band; the data preprocessing module is used for preprocessing the multispectral data; the earth surface reflectivity acquisition module is used for acquiring the earth surface reflectivity of the preset area according to the preprocessed multispectral data; the vegetation nitrogen content index acquisition module is used for calculating the vegetation nitrogen content index of the preset area based on the red-edge wave band in the pretreated multispectral data; The vegetation index grass yield acquisition module is used for acquiring a vegetation index of the preset area and grass yield of the preset area based on the pretreated multispectral data; the topographic factor obtaining module is used for extracting topographic factors of the preset area based on the digital elevation model of the preset area; The crude protein content acquisition module is used for inputting the vegetation nitrogen content index, the vegetation index, the grass yield and the topography factors into a training learning model to obtain the crude protein content of the preset area; the pasture crude protein yield obtaining module is used for calculating the pasture crude protein yield of the preset area according to the grass yield and the crude protein content.
6. The system for obtaining crude protein yield of pasture as set forth in claim 5, wherein said vegetation nitrogen content index obtaining module is specifically configured to obtain reflectances of bands including different wavelengths from red-edge bands in the pretreated multispectral data, and calculate the vegetation nitrogen content index of the preset area according to the reflectances of the bands including different wavelengths.
7. The system of claim 5, wherein the vegetation index yield acquisition module is configured to calculate a yield of the predetermined area based on the pretreated multispectral data and using a light energy utilization model.
8. A system for obtaining crude protein yield from pasture as set forth in any one of claims 5-7 wherein said data preprocessing module is specifically configured for space-time alignment, radiometric calibration and atmospheric correction of multispectral data.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing a method of obtaining coarse protein yield from pasture according to any one of claims 1 to 4 when the computer program is executed.
10. A computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, which when executed by a processor, implements a method for obtaining crude protein yield of pasture according to any one of claims 1 to 4.

Description

Method for obtaining crude protein yield of pasture and related equipment Technical Field The invention relates to the technical field of intelligent livestock and agricultural remote sensing, in particular to a method for obtaining crude protein yield of pasture and related equipment. Background In traditional alpine grassland grazing management and bearing capacity evaluation, the actual nutritional requirements of herbivores are difficult to accurately reflect by evaluating the bearing potential only according to the grassland grass amount, so that the actual livestock carrying potential of the grassland is difficult to scientifically reveal. The management measures are often left in rough control of the quantity of pastures, but cannot meet the requirements of modern animal husbandry on nutrition fine management, and particularly for ecologically vulnerable areas such as Qinghai-Tibet plateau, the improvement of the quality of the grassland animal husbandry must be realized on the basis of meeting the basic nutrition requirements of livestock, so that the cultivation efficiency and benefit are improved, and a method capable of synchronously quantifying the nutritional quality supply capability of the grassland is needed. To improve the scientificity of the evaluation, the prior art has attempted to incorporate livestock maintenance requirements and pasture nutritional quality to evaluate the bearing potential based on the edible pasture bearing potential. Technically, satellite remote sensing such as MODIS, sentinel-2 is used to monitor vegetation conditions over a wide range. Still further, the vegetation nitrogen content index developed based on the Sentinel-2 data provides a potential tool for regional scale assessment of pasture nutritional quality. Meanwhile, the unmanned aerial vehicle remote sensing platform is introduced into the field of grassland monitoring due to the advantages of flexibility and high resolution, is mainly used for estimating biomass, and tries to overcome the limitation of satellite remote sensing on space-time resolution. However, there are significant limitations to the prior art systems. Traditional bearing capacity assessment is based on dry matter yield, and spatial heterogeneity of pasture nutrition quality cannot be fully considered, so that fine management decision of 'grazing by quality' cannot be supported. Satellite remote sensing has a wide coverage range, but has lower spatial resolution, the revisiting period is limited by weather, and detailed features of small-scale spot block distribution of alpine grasslands are difficult to characterize. Although the index of vegetation nitrogen content based on Sentinel-2 has been developed, its spatial resolution of 10-20 meters is still significantly inadequate and is susceptible to frequent clouds in plateau areas. Although the unmanned aerial vehicle platform solves the bottleneck of partial data acquisition, the existing application is concentrated on biomass estimation in a plurality of isolation ways, and a complete and business-operable technical system integrating accurate inversion of pasture nutrition quality, synchronous measurement and calculation of grass yield and integral calculation of nutrition bearing capacity is not formed. Therefore, aiming at the defects of the prior art in the aspects of evaluation precision, technical integration level and pasture level applicability, a new technical scheme is urgently needed to be developed so as to realize quick, accurate and integrated evaluation of the nutrient output capability of the pasture in the alpine grassland and provide direct and reliable technical support for the fine pasture management with the nutrient requirement as the core. Disclosure of Invention The invention aims to solve the technical problems of the prior art, and particularly provides a method for obtaining the crude protein yield of pasture and related equipment, which comprises the following steps: 1) In a first aspect, the invention provides a method for obtaining crude protein yield of pasture, which comprises the following specific technical scheme: The method comprises the steps of collecting multispectral data of a preset area through a multispectral sensor carried by an unmanned aerial vehicle, preprocessing the multispectral data, obtaining the surface reflectivity of the preset area according to the preprocessed multispectral data, calculating the vegetation nitrogen content index of the preset area based on the red-sided wave band in the preprocessed multispectral data, obtaining the vegetation index of the preset area and the grass yield of the preset area based on the preprocessed multispectral data, extracting the topography factors of the preset area based on a digital elevation model of the preset area, inputting the vegetation nitrogen content index, the vegetation index, the grass yield and the topography factors into a learning model which is trained to obtain the crude