Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Quantitative detection method of peanut oil adulteration based on multi-source spectral data fusion

A spectral data and detection method technology, applied in the direction of measuring devices, material analysis through optical means, instruments, etc., can solve problems such as endangering consumers' rights and interests, and achieve reliable detection methods, no need for preprocessing, and high accuracy.

Active Publication Date: 2017-09-29
WUHAN POLYTECHNIC UNIVERSITY
View PDF1 Cites 2 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 oil, and some even mix some waste edible oil into peanut oil in order to seek huge profits, seriously endangering consumption Owner's rights

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 detection method of peanut oil adulteration based on multi-source spectral data fusion
  • Quantitative detection method of peanut oil adulteration based on multi-source spectral data fusion
  • Quantitative detection method of peanut oil adulteration based on multi-source spectral 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 detection method for peanut oil adulteration based on multi-source spectral data fusion, which comprises the following steps: oil sample preparation; spectral collection: respectively collecting Raman spectrograms and near-infrared spectrograms of all adulterated oil samples; Data fusion: fused the preprocessed Raman spectrum and near-infrared spectrum to obtain a fusion spectrum; adulteration quantitative model establishment: extracted characteristic wavelengths from the fusion spectrum, and established peanut oil through a multivariate quantitative correction method Quantitative model of sample adulteration; model validation; analysis of test samples. The quantitative detection method of peanut oil adulteration based on multi-source spectral data fusion provided by the present invention performs data fusion of edible oil spectra of two spectra, which has good complementarity and can more comprehensively reflect the internal characteristic information of edible oil; The detection method is fast and convenient, efficient and non-destructive, without pretreatment, high accuracy and strong 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
Patent Type & Authority Patents(China)
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 Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com