Quantitative adulteration detection method for peanut oil based on multiple-source spectroscopic data fusion

A technology of spectral data and detection methods, applied in measurement devices, material analysis by optical means, instruments, etc., can solve problems such as harming consumers' rights and interests, and achieve the effect of reliable detection means, strong applicability, and no need for preprocessing

Active Publication Date: 2015-07-29
WUHAN POLYTECHNIC UNIVERSITY
View PDF1 Cites 31 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In real life, some unscrupulous traders adulterate some low-priced edible oils such as soybean oil, cottonseed oil, and corn oil into peanut

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Quantitative adulteration detection method for peanut oil based on multiple-source spectroscopic data fusion
  • Quantitative adulteration detection method for peanut oil based on multiple-source spectroscopic data fusion
  • Quantitative adulteration detection method for peanut oil based on multiple-source spectroscopic data fusion

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] The present invention will be further described in detail below in conjunction with the accompanying drawings, so that those skilled in the art can implement it with reference to the description.

[0028] Such as figure 1 As shown, the present invention provides a peanut oil adulteration quantitative detection method based on multi-source spectral data fusion, comprising the steps of:

[0029] 1) Preparation of oil samples: In several peanut oil samples of equal mass, the same other edible oils were sequentially mixed in different mass ratios of 3% to 95%, to obtain several adulterated oil samples;

[0030] 2) Spectrum acquisition: use Raman spectrometer and near-infrared spectrometer to collect Raman spectrograms and near-infrared spectrograms of all adulterated oil samples in step 1) respectively, wherein, the Raman spectrometer spectrum acquisition process is as follows: The sample tube of the oil sample is placed in an electronic constant temperature water bath and...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a quantitative adulteration detection method for peanut oil based on multiple-source spectroscopic data fusion. The quantitative adulteration detection method comprises the following steps: oil sample preparation; spectrum acquisition: respectively acquiring Raman spectrograms and near-infrared spectrograms of all adulterated oil samples; spectroscopic data fusion: performing data level fusion on the preprocessed Raman spectrograms and the preprocessed near-infrared spectrograms to obtain a fusion spectrogram; quantitative adulteration model establishment: extracting characteristic wavelengths of the fusion spectrogram, and establishing a quantitative peanut oil sample adulteration model through a multivariate quantitative calibration method; model verification: analyzing samples to be detected. The detection method performs data fusion on the edible oil spectrograms of two spectrums, has good complementarity, can reflect the inner characteristic information of edible oil more comprehensively, and is quick, convenient, efficient, non-destructive, free from preprocessing, high in accuracy, and strong in applicability.

Description

technical field [0001] The invention relates to the technical field of rapid detection of oil adulteration, in particular to a quantitative detection method for peanut oil adulteration based on multi-source spectral data fusion. Background technique [0002] Peanut oil is light yellow and transparent, with clear color, fragrant smell and delicious taste. It is a kind of edible oil that is relatively easy to digest. Peanut oil contains more than 80% unsaturated fatty acids (including 41.2% oleic acid and 37.6% linoleic acid). Regular consumption of peanut oil can make cholesterol in the human body be decomposed into bile acids and excreted, thereby reducing the content of cholesterol in blood plasma; Contains sterols, wheat germ phenol, phospholipids, vitamin E, choline and other substances beneficial to the human body. Regular consumption of peanut oil can prevent skin wrinkling and aging, protect blood vessel walls, prevent thrombosis, and help prevent arteriosclerosis and ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G01N21/65G01N21/359
Inventor 郑晓涂斌何东平尹成曾路路彭博陈志沈雄宋志强
Owner WUHAN POLYTECHNIC UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap