Method for detecting illegal cooking oil

A detection method and technology for waste oil, which are applied in the direction of analysis using nuclear magnetic resonance, can solve problems such as inaccurate detection, and achieve the effects of high repeatability, simple operation, good repeatability and stability

Active Publication Date: 2012-10-03
XIAMEN UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The ICP-MS method can detect almost all elements in edible oil at the same time, and the sensitivity is relatively high. At the same time, it solves the problem of inaccurate detection of edible oil samples with low waste oil content.

Method used

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  • Method for detecting illegal cooking oil
  • Method for detecting illegal cooking oil

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0039] Measure 300 μL of peanut oil into an NMR tube, add a deuterated solvent to obtain the sample to be tested. The hydrogen spectrum was collected by a high-field NMR spectrometer such as Figure 5 and carbon spectra such as Image 6 , after obtaining the spectrum, first compare as figure 2 Characteristic fingerprint peaks in the chemical shift range of 33.0 to 35.0ppm; compare as image 3 The characteristic fingerprint peaks in the range of chemical shift 150.0 to 190.0ppm; compare as Figure 4 Characteristic fingerprint peaks in the chemical shift range from 40.0 to 80.0 ppm. Judging by the fingerprint peak is normal. At the same time, the original data can be exported, and the software developed by ourselves can be used to calculate the specific composition, saturation, relative acidity and relative oxidation of fatty acids. The results are shown in Table 1. figure 1 Give the waste oil judged by the difference of the total hydrogen number of saturated fatty acids. ...

Embodiment 2

[0043] Measure 300 μL of olive oil into an NMR tube, add a deuterated solvent, and obtain the sample to be tested. The hydrogen spectrum was collected by a high-field NMR spectrometer such as Figure 5 and carbon spectra such as Image 6 . After obtaining the spectrum, first compare as figure 2 Characteristic fingerprint peaks in the chemical shift range of 33.0 to 35.0ppm; compare as image 3The characteristic fingerprint peaks in the range of chemical shift 150.0 to 190.0ppm; compare as Figure 4 Characteristic fingerprint peaks in the chemical shift range from 40.0 to 80.0 ppm. Judging by the fingerprint peak is normal. At the same time, the original data can be exported, and the software developed by ourselves can be used to calculate the specific composition and saturation, relative acidity and relative oxidation of fatty acids. The results are shown in Table 2.

[0044] Table 2

[0045]

Embodiment 3

[0047] Measure 300 μL of soybean oil into an NMR tube, add a deuterated solvent, and obtain the sample to be tested. The hydrogen spectrum was collected by a high-field NMR spectrometer such as Figure 5 and carbon spectra such as Image 6 , after obtaining the spectrum, first compare as figure 2 Characteristic fingerprint peaks in the chemical shift range of 33.0 to 35.0ppm; compare as image 3 The characteristic fingerprint peaks in the range of chemical shift 150.0 to 190.0ppm; compare as Figure 4 Characteristic fingerprint peaks in the chemical shift range from 40.0 to 80.0 ppm. Judging by the fingerprint peak is normal. At the same time, the original data can be exported, and the software developed by ourselves can be used to calculate the specific composition, saturation, relative acidity and relative oxidation of fatty acids. The results are shown in Table 3.

[0048] table 3

[0049]

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Abstract

The invention discloses a method for detecting illegal cooking oil and relates to the method for detecting fat. The method comprises the steps of: sampling, weighing a liquid oil sample to be measured, dissolving the liquid oil sample by a deuterated solvent, transferring the solution to a nuclear magnetic tube, and collecting hydrogen spectrum and carbon spectrum data of the sample through a high-field nuclear magnetic resonance spectrometer; analyzing data, leading out a nuclear magnetic spectrogram, judging normal edible oil and drainage oil by comparison of a specific fingerprint area, and refining the illegal oil just the same as the fingerprint area; distinguishing by concrete fatty acid constituents, carrying out aggregate analysis on concrete data of total hydrogen quantity of saturated fatty acids, concrete content of various fatty acids, relative content of oxide and relative content of free acid in different edible oil obtained by data analysis, analyzing the spectrogram by a stoichiometry method to obtain a result, collecting the spectrogram of an oil product by NMR (nuclear magnetic resonance), and then comprehensively distinguishing the illegal cooking oil according to each constituent in the oil product by a plurality of indexes.

Description

technical field [0001] The invention relates to a method for detecting grease, in particular to a method for detecting waste oil. Background technique [0002] Waste oil generally refers to all kinds of low-quality oils that exist in daily life, such as recycled cooking oil, repeatedly used frying oil, etc. Long-term consumption of waste oil may induce cancer and is extremely harmful to the human body. In recent years, waste oil or waste oil mixed with edible oil has appeared all over the country and flowed back into the edible oil market, which has aroused great concern from the government and the whole society. Since the processing technology of catering waste oil is quite mature, it is extremely important to find a fast and effective identification and monitoring method to increase the supervision of relevant departments to ensure the safety of edible oil and the health of the people. [0003] At present, there is no uniform standard for the detection of waste oil in Chi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N24/08
Inventor 黄慧英胡友恒杨朝勇蔡剑怀林东海许一婷曾碧榕
Owner XIAMEN UNIV
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