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Method for detection of oleic acid content distribution in peanut based on hyperspectral imaging technology

A hyperspectral imaging and hyperspectral technology, applied in the measurement of color/spectral characteristics, etc., can solve the problems of detecting peanut oleic acid, and achieve the effect of increasing the difference, improving the robustness and prediction ability

Active Publication Date: 2018-06-26
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 the seeds. So far, there has been no report on the detection of the content distribution of peanut oleic acid by hyperspectral imaging technology at home and abroad.

Method used

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  • Method for detection of oleic acid content distribution in peanut based on hyperspectral imaging technology
  • Method for detection of oleic acid content distribution in peanut based on hyperspectral imaging technology
  • Method for detection of oleic acid content distribution in peanut based on hyperspectral imaging technology

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Embodiment 1

[0068] The present embodiment provides a method for establishing a quantitative model of oleic acid content distribution in peanuts based on hyperspectral imaging technology, the method comprising the following steps:

[0069] 1.1 Collect 96 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 of the peanut sample was repeated three times, and the average value of the three scanned hyperspectral images was taken to obtain the original hyperspectral three-dimensional image of the peanut sample. Before each scan, collect a full white calibration image I white and all-black calibration image I dark .

[0070] 1.2 After correcting and deleting the background of the original hyperspectral three-dimensional image of the above-mentioned peanut...

Embodiment 2

[0094] The present embodiment provides a method for detecting oleic acid content distribution in peanuts based on hyperspectral imaging technology, the method comprising the following steps:

[0095] 1) Collect the spectral images of the peanut samples to be tested at the following characteristic wavelengths: 901nm, 980nm, 1064nm, 1147nm, 1230nm, 1313nm, 1397nm, 1480nm, 1564nm, 1648nm;

[0096] Specific process: take another single peanut variety, obtain the original hyperspectral three-dimensional image of the peanut sample with a hyperspectral instrument 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 peanut sample image of the variety is preprocessed by centering, mean variance, and standard normal variable transformation; finally, the spectral image of the peanut sample at the above-mentioned characteristic wavelengths is obtained.

[0097] 2) Input the spectra...

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Abstract

The invention provides a method for detecting oleic acid content distribution in peanuts based on a hyperspectral imaging technology. The method includes the steps that a spectral image, at the characteristic wavelength, of a peanut sample is collected, a spectral reflectance value obtained after preprocessing the characteristic wavelength is input into a peanut oleic acid content distribution quantitative model, and then oleic acid content distribution of the peanut sample is obtained. The invention further provides a method for establishing the peanut oleic acid content distribution quantitative model. The method includes the steps that a hyperspectral image of the peanuts is collected, and the oleic acid content of the peanuts is determined through a conventional method; image correction and background deletion are performed on the hyperspectral image, and the average spectrum is extracted; with the preprocessed average spectrum as an independent variable and the oleic acid content as a dependent variable, a full-wave band oleic acid content regression model is established, on this basis, the characteristic wavelength is determined through the regression coefficient, and the quantitative model is established and verified. The methods are rapid, easy and convenient to implement and efficient, no damage is caused to the sample, no chemical reagent is used, the determination result is accurate, and the oleic acid content of the peanuts is visualized.

Description

technical field [0001] The invention relates to a method for detecting oleic acid content in peanuts, in particular to a method for detecting oleic acid 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. Most of the peanuts produced in my country are used to process peanut oil, which contains a large amount of monounsaturated fatty acids and polyunsaturated fatty acids, of which the content of oleic acid is as high as 35% to 72%. The level of oleic acid content in peanuts directly affects the quality and shelf life of peanut oil, and indirectly affects the benefits of enterprises. Traditional methods for the determination of oleic acid in peanuts include: acetyl chloride-methanol methyl esterification method and ammonia water-ethanol extraction method, but these methods have disadvantages such as slow analysis speed, cumbersome op...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N21/25
Inventor 王强石爱民瑞哈曼米兹比瑞于宏威刘红芝刘丽胡晖巩阿娜
Owner INST OF AGRO FOOD SCI & TECH CHINESE ACADEMY OF AGRI SCI
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