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Method for detecting fat content distribution in peanuts based on hyperspectral imaging technology

A technology of hyperspectral imaging and fat content, which is applied in the direction of color/spectral characteristic measurement, etc., can solve the problems of detecting the distribution of peanut fat content, achieve the effect of improving resolution and sensitivity, and eliminating interference

Active Publication Date: 2018-02-16
INST OF AGRO FOOD SCI & TECH CHINESE ACADEMY OF AGRI SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the research mainly focuses on the purity of seeds. So far, there is no report on the detection of peanut fat content distribution by hyperspectral imaging technology at home and abroad.

Method used

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  • Method for detecting fat content distribution in peanuts based on hyperspectral imaging technology
  • Method for detecting fat content distribution in peanuts based on hyperspectral imaging technology
  • Method for detecting fat content distribution in peanuts based on hyperspectral imaging technology

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Embodiment 1

[0066] The present embodiment provides a method for establishing a quantitative model of fat content distribution in peanuts based on hyperspectral imaging technology, the method comprising the following steps:

[0067] 1.1 Collect 120 varieties of peanut samples mainly planted in my country's main planting provinces in 2012, 2013 and 2014, select 30 complete peanut kernels from each variety, and use a hyperspectral instrument to simultaneously scan each pixel point in the peanut sample at each wavelength The image information, the spectral wavelength range is 900-1700nm, the scanning method is line scanning, repeated 3 times, and the average value of the hyperspectral images scanned for 3 times is taken. The original hyperspectral 3D image of the peanut sample was obtained. Before each scan, collect a full white calibration image I white and all-black calibration image I dark .

[0068] 1.2 After correcting and deleting the background of the original hyperspectral three-dim...

Embodiment 2

[0089] The present embodiment provides a method for detecting fat content distribution in peanuts based on hyperspectral imaging technology, the method comprising the following steps:

[0090] 1) Collect the spectral images of the peanut samples to be tested at the following characteristic wavelengths: 931nm, 941nm, 964nm, 1143nm, 1157nm, 1317nm, 1400nm, 1434nm, 1658nm, 1661nm, 1668nm, 1678nm;

[0091] Specific process: Take another 6 peanut varieties, use the hyperspectral instrument to obtain the original hyperspectral three-dimensional image of the peanut sample in the same way as in Example 1; then use the same method as in Example 1 to extract the average spectrum of the peanut sample image; The average spectrum of the images of the 6 peanut samples was preprocessed by the second derivative combined with the standard normal variable transformation; finally the spectral reflectance values ​​of the 6 peanut samples at the above characteristic wavelengths were obtained.

[0...

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Abstract

The invention provides a method for detecting fat content distribution in peanuts based on hyperspectral imaging technology, comprising: collecting spectral images of peanut samples at characteristic wavelengths, and inputting preprocessed spectral reflectance values ​​at characteristic wavelengths into peanut fat content distribution quantification The model was used to obtain the fat content distribution of peanut samples. The present invention also provides a method for establishing a quantitative model of fat content distribution in peanuts, which includes collecting peanut hyperspectral images and measuring their fat content using conventional methods; the hyperspectral images are subjected to image correction and background deletion, and the average spectrum is extracted; The average spectrum of the spectral image is the independent variable, and the fat content is the dependent variable to establish a mathematical model of the full-band fat content. On this basis, the regression coefficient is used to determine the characteristic wavelength, and the quantitative model is established and verified. The invention is quick and easy, has high efficiency, does not destroy samples, does not use any chemical reagents, has accurate measurement results, and realizes visualization of peanut fat content.

Description

technical field [0001] The invention relates to a method for detecting fat content in peanuts, in particular to a method for detecting fat content distribution in peanuts based on hyperspectral imaging technology. Background technique [0002] In 2013, my country's peanut production was 16.97 million tons, ranking first in the world. Peanuts contain a lot of nutrients, of which the fat content is as high as 38% to 60%. The vast majority of peanuts produced in my country are used for processing peanut oil. Therefore, the level of fat content in peanuts directly affects the income of farmers and the benefits of enterprises. Traditional methods for the determination of fat in peanuts include: Soxhlet extraction and acid hydrolysis, but these methods have disadvantages such as slow analysis speed, cumbersome operation steps, high cost and strong destructiveness, and the use of reagents pollute the environment. Therefore, it is urgent to find a fast, non-destructive method to ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N21/25
Inventor 王强刘红芝于宏威石爱民刘丽胡晖林伟静瑞哈曼米兹比瑞
Owner INST OF AGRO FOOD SCI & TECH CHINESE ACADEMY OF AGRI SCI
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