Raman characteristic spectrum peak extraction method based on improved principal assembly analysis

A principal component analysis and extraction method technology, applied in the field of Raman characteristic peak extraction based on improved principal component analysis, can solve the problems of too many features, complex models, and low robustness, and achieve high accuracy and accuracy The effect of high rate and fast classification speed

Active Publication Date: 2020-01-10
ZHEJIANG UNIV
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Problems solved by technology

[0005] Aiming at the disadvantages of low robustness or too many features and complex models in the previous feature extraction methods, the present invention proposes a Raman feature spectrum peak extraction method based on improved principal component analysis

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  • Raman characteristic spectrum peak extraction method based on improved principal assembly analysis
  • Raman characteristic spectrum peak extraction method based on improved principal assembly analysis
  • Raman characteristic spectrum peak extraction method based on improved principal assembly analysis

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Embodiment Construction

[0035] The present invention will be further described below in conjunction with drawings and embodiments.

[0036] Such as figure 1 Shown, embodiment of the present invention and its implementation process are as follows:

[0037] In this example, three types of samples are mainly distinguished. They are adulterated minced meat samples mixed with equal mass and minced meat samples of pure beef and pure pork respectively. The source of meat is vacuum-packed fresh pork and beef tenderloin slaughtered in the same batch (slaughtered and processed according to standards and passed the inspection by the health and quarantine department, after 24 hours of acid discharge). Before the experiment, the meat was taken out of the freezer, placed in room temperature water to thaw, and then air-dried to remove the obvious fat and connective tissue in the sample. Mix the quality of pork and beef, put them into the meat grinder and stir twice, each time for 30s, to obtain adulterated mince...

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Abstract

The invention discloses a Raman characteristic spectrum peak extraction method based on improved principal assembly analysis. The method comprises the following steps of collecting Raman spectrum dataof the surfaces of pork and beef samples by a confocal microscopic Raman spectrometer; preprocessing the Raman spectrum data, performing principal component analysis, establishing a principal component load scatter diagram, analyzing and extracting scatter point characteristics of the principal component load scatter diagram, and screening a Raman characteristic spectrum peak according to the scatter point characteristics. The method extracts the Raman characteristic spectrum peaks of the beef and the pork and substitutes the Raman characteristic spectrum peaks into a classifier for classification, so that higher accuracy rate is achieved, and the classification speed is high.

Description

technical field [0001] The invention relates to a method for extracting spectral features of biological tissues, in particular to a method for extracting Raman characteristic spectrum peaks based on improved principal component analysis. Background technique [0002] Raman spectroscopy is a spectral analysis technique based on the Raman scattering effect. It has the advantages of strong spectral interpretation, rich information, and simple pre-processing. It is widely used in materials, biology, and food safety. Each specific functional group or group in the Raman spectrum will produce different characteristic peaks due to its different vibration structure. For a substance with a complex compound composition, its Raman spectrum signal consists of multiple spectral peaks. When performing quantitative and qualitative analysis of the spectrum, accurately extracting the Raman characteristic peaks of the sample can reduce the complexity of the model and improve the generalizatio...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/65
CPCG01N21/65G01N33/12G01N2201/1293
Inventor 饶秀勤张延宁高迎旺张小敏王怡田林洋洋应义斌
Owner ZHEJIANG UNIV
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