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Hyperspectral inversion method for content of chlorophyll in apple leaves based on SVR (support vector regression) algorithm

A chlorophyll content, hyperspectral technology, applied in the field of agriculture, can solve the problem of less research on fruit trees

Inactive Publication Date: 2017-02-22
NORTHWEST A & F UNIV
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Problems solved by technology

In recent years, most studies on the relationship between hyperspectral and chlorophyll content have focused on rice, corn, wheat and other food crops, and relatively few studies on fruit trees

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  • Hyperspectral inversion method for content of chlorophyll in apple leaves based on SVR (support vector regression) algorithm
  • Hyperspectral inversion method for content of chlorophyll in apple leaves based on SVR (support vector regression) algorithm
  • Hyperspectral inversion method for content of chlorophyll in apple leaves based on SVR (support vector regression) algorithm

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Embodiment Construction

[0016] The technical solution of the present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0017] 1 Materials and methods

[0018] 1.1 Experimental design

[0019] The experimental site is located in Zhaozhai Village, Xinglin Town, Fufeng County, Shaanxi Province (108°00′45"E, 34°22′12"N). The samples were collected on April 27, 2015, when the apple trees were in the early growth stage, and the leaves were affected by The influence of other factors such as diseases is small, and the spectrum of leaves can better reflect the chlorophyll status. Monitoring the chlorophyll content of apple leaves at this time can provide a certain reference for the application of nitrogen fertilizer during the growth of fruit trees. Collect red Fuji apple leaves and use fresh-keeping Keep the bag sealed and bring it back to the laboratory for processing.

[0020] 1.2 Determination of leaf spectrum

[0021] Spectral...

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Abstract

The present invention discloses a hyperspectral inversion method for the content of chlorophyll in apple leaves based on an SVR (support vector regression) algorithm. In order to realize the hyperspectral inversion of the content of chlorophyll in the apple leaves, the correlation between various spectral parameters and measured SPAD (soil and plant analyzer development) values is analyzed, normalized spectral parameter values and SPAD values are subjected to polynomial regression and SVR, determination coefficients of an SVR inversion model adopting a normalized differential vegetation index as a variable in modeling and model detection are 0.7410 and 0.8914 respectively, root-mean-square errors are 0.1332 and 0.1256 respectively, and higher precision and good prediction capacity are realized. Compared with polynomial regression, SVR has a better inversion effect and can be used as an optimal algorithm for hyperspectral inversion of chlorophyll.

Description

technical field [0001] The invention belongs to the technical field of agriculture, and in particular relates to a hyperspectral inversion method for chlorophyll content of apple leaves based on an SVR algorithm. Background technique [0002] Chlorophyll concentration is an important indicator reflecting the photosynthetic ability and growth status of plants. Since there is a good correlation between chlorophyll and leaf nitrogen content, which can characterize the nutritional status of plants, chlorophyll concentration is also an indicator of plant nutritional stress. It can be seen that it is of great application value to quickly and accurately measure the chlorophyll content of plant leaves. HORLER et al. studied the correlation between leaf chlorophyll concentration and reflectance spectrum, and pointed out the value of red edge measurement for the evaluation of chlorophyll status; CURRAN and FILELLA pointed out that the position and shape of red edge can be used as inf...

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Application Information

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IPC IPC(8): G01N21/25
CPCG01N21/25
Inventor 常庆瑞刘京李粉玲
Owner NORTHWEST A & F UNIV
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