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Method for building triticum aestivum leaf dry weight quantitative model based on continuous wavelet analysis

A quantitative model and wavelet analysis technology, applied in the re-radiation of electromagnetic waves, radio wave measurement systems, measurement devices, etc., can solve the problems of the optimal scale of the optimal generating function and the lack of clear determinism of the sensitive band, and achieve accuracy and stability. Good results

Active Publication Date: 2017-05-31
NANJING AGRICULTURAL UNIVERSITY
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Problems solved by technology

At present, Mexican Hat is the most widely used, but whether Mexican Hat is the best wavelet function for hyperspectral information extraction remains to be studied; in addition, how to determine the appropriate scale and sensitive band of the optimal parent function has not been solved yet. clear conclusion

Method used

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  • Method for building triticum aestivum leaf dry weight quantitative model based on continuous wavelet analysis
  • Method for building triticum aestivum leaf dry weight quantitative model based on continuous wavelet analysis
  • Method for building triticum aestivum leaf dry weight quantitative model based on continuous wavelet analysis

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Embodiment Construction

[0043] The technical solutions of the present invention will be further described in detail below in conjunction with specific drawings and embodiments.

[0044] The present invention has carried out the different nitrogen fertilizers of 10 varieties of 8 ecological points and the wheat field experiment of different densities altogether for 7 consecutive years, and concrete test design is as follows table 1.

[0045] Table 1 The detailed field test information table of test data collection

[0046]

[0047]

[0048] A method for establishing a quantitative model of wheat leaf dry weight based on continuous wavelet analysis, the specific steps are as follows:

[0049] Step (1), select sampling plot, obtain wheat canopy hyperspectral reflectance, wheat leaf dry weight;

[0050] Obtaining the hyperspectral reflectance of the wheat canopy: the spectral measurement is carried out on a sunny day with no clouds, no wind or a slight breeze, and the measurement time is from 10:0...

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Abstract

The invention discloses a canopy hyper-spectral triticum aestivum leaf dry weight monitoring method based on continuous wavelet analysis. The method comprises the following steps: selecting sampling plots, acquiring the triticum aestivum canopy hyper-spectral reflectance, and measuring the triticum aestivum leaf dry weight, wherein the sampling plots are selected from different test points, are of different varieties, different nitrogen levels and different planting density, and are from different years; carrying out continuous wavelet transform on the acquired triticum aestivum canopy hyper-spectral reflectance data to get a wavelet coefficient under a specific wavelength and a specific scale; using the wavelet coefficient to analyze the quantitative relation between triticum aestivum leaf dry weight and wavelet coefficient, screening out an optimal wavelet function sensitive to triticum aestivum leaf dry weight and a characteristic value corresponding to the optimal wavelet function, and building a triticum aestivum leaf dry weight quantitative model based on continuous wavelet analysis; and using independent triticum aestivum test data to assess the reliability and applicability of the quantitative model, and using a determination coefficient R<2> and relative root mean square error RRMSE between predicted and observed values to evaluate the quantitative model.

Description

technical field [0001] The invention relates to a monitoring method for dry weight of wheat leaves, in particular to a method for establishing a quantitative model of dry weight of wheat leaves based on continuous wavelet analysis. Background technique [0002] Wheat is one of the most important food crops in the world. 35% to 40% of the world's population takes wheat as a staple food. my country's annual wheat output is about 100 million tons, accounting for 22% of the country's total grain output and 20% of the world's total wheat output. [0003] Leaf dry weight is a parameter to measure whether the leaf layer structure of vegetation is good, and it plays an important role in material production and yield formation. The real-time, fast and non-destructive monitoring of crop leaf dry weight using hyperspectral remote sensing technology is a hot issue in information agriculture. Although previous studies have done a lot of research on the dry weight of aboveground parts ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S17/89
CPCG01S17/89
Inventor 姚霞朱艳程涛司海洋田永超马吉锋张羽邱小雷王雪曹卫星
Owner NANJING AGRICULTURAL UNIVERSITY
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