CN112578060A - Method for measuring volatile components of linseed oil and application thereof - Google Patents
Method for measuring volatile components of linseed oil and application thereof Download PDFInfo
- Publication number
- CN112578060A CN112578060A CN202011333156.3A CN202011333156A CN112578060A CN 112578060 A CN112578060 A CN 112578060A CN 202011333156 A CN202011333156 A CN 202011333156A CN 112578060 A CN112578060 A CN 112578060A
- Authority
- CN
- China
- Prior art keywords
- temperature
- oil
- extraction
- linseed oil
- volatile components
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/04—Preparation or injection of sample to be analysed
- G01N30/06—Preparation
- G01N30/08—Preparation using an enricher
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/86—Signal analysis
- G01N30/8675—Evaluation, i.e. decoding of the signal into analytical information
- G01N30/8686—Fingerprinting, e.g. without prior knowledge of the sample components
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/88—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
Landscapes
- Analytical Chemistry (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Library & Information Science (AREA)
- Engineering & Computer Science (AREA)
- Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
Abstract
The invention discloses a method for measuring volatile components of linseed oil and application thereof, wherein the measuring method comprises the steps of enriching volatile components by headspace solid phase micro-extraction, and simultaneously carrying out qualitative or/and quantitative detection by gas chromatography-mass spectrometry; the conditions of headspace solid phase microextraction include: fixing the extraction temperature to be 50-90 ℃, the equilibration time to be 10-50 min, the adsorption time to be 20-60 min, and the desorption time to be: 1-9 min, stirring intensity: 200-600 r/min; the temperature-raising program of the gas chromatograph comprises: keeping the temperature of 36-40 ℃ for 2-5 min, raising the temperature to 100-220 ℃ at 3-5 ℃/min, keeping the temperature for 5-10 min, raising the temperature to 180-220 ℃ at 0-8 ℃/min, and keeping the temperature for 0-10 min. The fingerprint spectrum established by the method can effectively detect the adulteration proportion of more than 10% of peanut oil, sunflower seed oil, sesame oil, more than 20% of corn oil, more than 30% of rapeseed oil and more than 40% of soybean oil, and provides a new and more comprehensive reference basis for linseed oil adulteration identification and quality control.
Description
Technical Field
The invention relates to the technical field of food detection, in particular to a method for determining volatile components of linseed oil and application thereof.
Background
Flax, also known as flax, is one of the ten major oil crops in the world and accounts for the seventh of the total oil production in the world. The total content of unsaturated fatty acid in the linseed oil is up to more than 90%, and the linseed oil contains various functional components such as protein, dietary fiber, phenolic substances and the like, and has positive effect on disease prevention. Flaxseed is reported to have various health functions such as anti-inflammatory effects, prevention of cardiovascular diseases and cancer, reduction of bone resorption rate, anti-depression, etc. In recent decades, linseed oil has become increasingly popular in the global market. Compared with common edible vegetable oil such as soybean oil, peanut oil, corn oil and the like in the market, the price of the linseed oil is generally higher, so that the adulteration of the linseed oil is also a serious problem as with olive oil in western countries.
The fragrance of the linseed oil is one of important factors influencing the sensory characteristics and the quality of the linseed oil, and due to the fact that the linseed oil has unique fragrance components, the authenticity of the linseed oil can be identified by researching the volatile components of the linseed oil. In the prior art, the adulteration identification of volatile components is mostly a method using a gas-phase fingerprint, but the detected components are single, the identified volatile components are few, and the volatile components of the linseed oil are difficult to be detected and identified comprehensively and accurately, so that a detection method is urgently needed to be established, and the volatile components of the linseed oil can be identified more comprehensively.
Disclosure of Invention
The invention mainly solves the technical problem of providing a method for measuring the volatile components of linseed oil and application thereof, wherein the method can detect 58 linseed oil volatile components, and the fingerprint spectrum established by the method is suitable for adulteration identification of 10% of peanut oil, sunflower seed oil, sesame oil, more than 20% of corn oil, more than 30% of rapeseed oil and more than 40% of soybean oil.
In order to solve the technical problems, the invention adopts a technical scheme that:
providing a method for measuring volatile components of linseed oil, and carrying out gas chromatography-mass spectrometry combined detection after volatile components are enriched by adopting headspace solid phase micro-extraction;
the conditions of the headspace solid phase microextraction comprise:
fixing the extraction temperature: 50-90 ℃;
the balance time is as follows: 10-50 min;
adsorption time: 20-60 min;
desorption time: 1-9 min;
stirring strength: 200-600 r/min;
the temperature-raising program of the gas chromatograph comprises the following steps: keeping the temperature of 36-40 ℃ for 2-5 min, raising the temperature to 100-220 ℃ at 3-5 ℃/min, keeping the temperature for 5-10 min, raising the temperature to 180-220 ℃ at 0-8 ℃/min, and keeping the temperature for 0-10 min.
In a specific embodiment of the present invention, the conditions of the headspace solid phase microextraction include:
fixing the extraction temperature: 70-80 ℃, preferably 80 ℃;
the balance time is as follows: 20-30 min, preferably 20 min;
adsorption time: 20-40 min, preferably 40 min;
desorption time: 5-9 min, preferably 5 min;
stirring strength: 350-450 r/min, preferably 400 r/min.
Further, the conditions of the headspace solid phase microextraction further comprise an extraction head: 50/30 μm divinylbenzene/carbon molecular sieves/polydimethylsiloxane extracted fiber heads.
Further, the temperature rising program of the gas chromatography-mass spectrum comprises the following steps: keeping at 40 deg.C for 2min, increasing to 220 deg.C at 5 deg.C/min, and keeping for 10 min.
Further, in the gas chromatography-mass spectrometry conditions, the gas chromatography conditions further include one or more of the following i to vi:
i, chromatographic column: polyethylene glycol capillary column;
ii chromatography column model: InertCap pure-wax;
iii column specification: 30 m.times.0.25 mm.times.0.25 μm;
iii split ratio: 48-52: 1, preferably 50: 1;
iv flow rate: 0.5-1.5 mL/min, preferably 1.0 mL/min;
v, sample inlet temperature: 245-255 ℃, preferably 250 ℃;
vi carrier gas: helium gas with a purity of 99.999%.
Further, the gas chromatography-mass spectrometry conditions include one or more of the following i to v:
i ion source temperature: 140-160 ℃, preferably 150 ℃;
ii filament emission current: 190-200 muA, preferably 200 muA;
iii electron energy: 60-75 eV, preferably 70 eV;
iv transmission line temperature: 250 ℃ to 270 ℃, preferably 260 ℃;
v scanning mass range m/z: 30-400 u, preferably 35-350 u.
Further, the volatile component includes aldehydes, acids, alcohols, ketones, esters, alkenes, heterocycles, but is not limited to the above components.
The aldehydes, acids, alcohols, ketones, esters, alkenes and heterocycles are main flavor substances forming the vegetable oil.
In a specific embodiment of the present invention, the volatile component further comprises a qualitative or/and quantitative step after the gas chromatography-mass spectrometry detection according to the above determination method.
The invention also provides a linseed oil volatile component fingerprint spectrum which is constructed by the method.
Further, the application of the fingerprint spectrum in the identification of the adulteration of the vegetable oil is realized.
The invention has the beneficial effects that:
(1) the method provided by the invention has high extraction efficiency, establishes the optimal detection method for the flavor substances of the Qinghai linseed oil, can detect 58 volatile components of 12 aldehydes, 8 acids, 9 alcohols, 2 ketones, 5 esters, 13 alkenes, 3 heterocycles and 6 other substances in the linseed oil, is convenient, rapid and effective, and can detect the quality of the linseed oil more comprehensively.
(2) The fingerprint spectrum established by the method has wide applicability, is suitable for adulteration identification of 10 percent of peanut oil, sunflower seed oil, sesame oil, more than 20 percent of corn oil, more than 30 percent of rapeseed oil and more than 40 percent of soybean oil, and improves the quality control level of products.
(3) By utilizing the measuring method, the volatile components and the relative percentage content of the linseed oil of different varieties and production places can be compared, and a theoretical basis is provided for the quality control of the linseed oil.
Drawings
FIG. 1 shows the effect of stirring rate on extraction efficiency.
FIG. 2 shows the effect of extraction temperature on the extraction performance.
FIG. 3 shows the effect of equilibration time on extraction performance.
FIG. 4 shows the effect of adsorption time on extraction efficiency.
FIG. 5 is a graph showing the effect of desorption time on extraction efficiency.
Fig. 6 is a total ion flow diagram of the volatile components of linseed oil under different temperature rise procedures.
Fig. 7 is a 40 linseed oil sample clustering pedigree chart.
Fig. 8 is a superimposed graph of the volatile components of 40 Qinghai linseed oils.
FIG. 9 shows standard fingerprints of 40 Qinghai linseed oils.
FIG. 10 shows the types of volatile components of different vegetable oils and their relative contents.
FIG. 11 is a spectrum of volatile components of different vegetable oils.
FIG. 12 is a model of similarity between finger prints and different amounts of adulteration of vegetable oil.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are only some embodiments, but not all embodiments, of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In addition to the specific methods, devices, and materials used in the examples, the present invention may be implemented by any methods, devices, and materials similar or equivalent to those described in the examples, in accordance with the knowledge of one skilled in the art and the description of the present invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
All data in the invention are mean values, statistical analysis is carried out on the data by using Microsoft Excel and SPSS 23.0, and origin 2018 is plotted.
Example 1 determination of volatile component of linseed oil
1 materials and methods
1.1 materials and reagents
The Qinghai linseed oils of 40 varieties are respectively numbered from S1 to S40 (Table 1) and are prepared by Soxhlet extraction in a laboratory (the feed-liquid ratio is 0.06g/mL, the extraction temperature is 70 ℃, and the extraction time is 8 hours).
TABLE 1 Linseed oil information Table
1.2 instruments and devices
QP 2020 NX GC-MS instrument: shimadzu, Japan; 50/30 μm divinylbenzene/carbon molecular sieve/polydimethylsiloxane (DVB/CAR/PDMS) extraction fiber head, solid phase microextraction handle, SPME dedicated magnetic heating stirring device, 15mL sampling bottle: supelco, USA; JA1003 electronic balance: shanghai Liangping instruments and meters, Inc.
1.3 test conditions
1.3.1 extraction of volatile constituents
The SPME extraction method comprises the following steps:
the 50/30 μm DVB/CAR/PDMS extraction head was placed in the 260 ℃ inlet and aged for 60min until no interference peaks appeared. Accurately weighing 6.0g of Qinghai linseed oil in a 15mL sampling bottle, immediately sealing and pressing the Qinghai linseed oil by using a cover with a polytetrafluoroethylene silica gel spacer after a magnetic stirrer is placed, placing the sampling bottle on a magnetic heating stirrer at 80 ℃, stirring at the speed of 400r/min for 20min to fully balance volatile components of the linseed oil, then penetrating an activated extraction head through the silica gel spacer, pushing out a fiber head, and performing headspace extraction and adsorption for 40 min. And after the gas chromatograph is ready, quickly inserting the extraction head into a GC 250 ℃ sample inlet, pushing out the fiber head, and desorbing for 5 min. The extraction head needs to be placed at a 250 ℃ sample inlet for elution for 10min between every two sample injection analyses so as to ensure the high efficiency of the fiber head.
According to the method, the influence of extraction conditions under different stirring strengths, extraction temperatures, equilibrium times, adsorption times and desorption times on the extraction effect is researched.
1.3.1.1 Effect of agitation intensity on extraction efficiency
Fixing the extraction temperature at 70 ℃, the equilibrium time at 30min, the adsorption time at 40min, and the desorption time at 5min, and examining the influence of the stirring intensity at 200, 300, 400, 500, and 600r/min on the extraction effect of the volatile components of the Qinghai linseed oil.
As can be seen from FIG. 1, the number of peaks and the area of the peaks both increased and decreased as the stirring rate increased from 0 to 800 r/min. With the increase of the stirring speed, the diffusion speed of the substance to be detected in the sample from the liquid phase to the gas phase is accelerated, and the volatility of the volatile matters with low content and low volatility in the linseed oil is increased. When the stirring speed is 400r/min, the number of peaks and the area of the peak reach the maximum value, which indicates that the volatile components in the sample reach the equilibrium state at the stirring speed. The effect of the extraction was rather poor by continuing to increase the stirring rate, probably because the magnetic stirrer was unstable due to too high stirring rate, so 400r/min was chosen as the optimum stirring rate.
1.3.1.2 Effect of extraction temperature on extraction Effect
Fixing the stirring intensity at 400r/min, balancing for 30min, adsorbing for 40min, desorbing for 5min, and comparing the effects of extraction temperatures of 50, 60, 70, 80, and 90 ℃ on the extraction effect of volatile components of Qinghai linseed oil.
As can be seen from FIG. 2, the number of peaks increases with the increase of the extraction temperature, but the peak area begins to decrease after reaching the highest point at the extraction temperature of 80 ℃, and the reason for analyzing the peak area may be that the sample is deteriorated at an excessively high temperature, the fatty acid is decomposed to generate a certain amount of low-molecular oxidation products, and the peak area decreases due to the competition with flavor substances for the headspace. Meanwhile, the headspace solid phase microextraction adsorption process belongs to exothermic reaction, and is not beneficial to the adsorption of volatile components in the sample at an overhigh temperature. Considering comprehensively, 80 ℃ is selected as the optimal extraction temperature.
1.3.1.3 Effect of equilibration time on extraction Effect
Fixing the stirring intensity at 400r/min, extracting temperature at 80 ℃, adsorption time at 40min, desorption time at 5min, and comparing the influence of balance time at 10, 20, 30, 40 and 50min on the extraction effect of the volatile components of the Qinghai linseed oil.
As can be seen from FIG. 3, the volatile species and the peak area tend to increase and decrease within the equilibrium time, which indicates that a certain equilibrium time can release more volatile from the sample, and that at most 57 volatile components are detected in the sample at the equilibrium time of 20min, probably because the release and dissolution of the volatile components are in a dynamic equilibrium process, and the volatile released by further increasing the equilibrium time will re-dissolve, resulting in a decrease in the total amount of volatile, so that the volatile release is maximized and the extraction effect is maximized at the equilibrium time of 20 min.
1.3.1.4 Effect of adsorption time on extraction efficiency
Fixing the stirring intensity at 400r/min, extracting temperature at 80 ℃, balancing time at 20min, desorbing time at 5min, and comparing the influence of the adsorption time at 20, 30, 40, 50 and 60min on the extraction effect of the volatile components of the Qinghai linseed oil.
As can be seen from FIG. 4, the number of peaks and the peak area both increased during the adsorption time of 20-40 min, and reached the maximum at 40min, whereas the number of peaks and the peak area started to decrease slowly as the adsorption time was extended. The method is characterized in that the detectable aroma components in the sample are increased and the peak area is increased along with the prolonging of the extraction time in a certain time, but the target substances adsorbed on the extraction head can be resolved again due to the overlong extraction time, so that the extraction amount is reduced, and the optimal extraction time is 40min in comprehensive consideration.
1.3.1.5 Effect of desorption time on extraction Effect
After the volatile components in the sample are completely adsorbed on the extraction head, the extraction head is inserted into a GC sample inlet at 250 ℃ for desorption.
As can be seen from FIG. 5, the species and peak area of the volatile matter are in an ascending trend within 1-5 min of desorption time, which indicates that the volatile matter cannot be completely desorbed from the extraction head due to too short time, which affects the accuracy of the detection result and also pollutes the next sample; but the temperature tends to be flat after 5min, which indicates that the target is basically completely desorbed when the desorption time is 5min, the desorption time is too long, and the service life of the extraction head is shortened when the extraction head is in a high-temperature environment for a long time, so that 5min is selected as the optimal extraction time.
1.3.2 GC-MS analysis conditions
Chromatographic conditions are as follows: InertCap pure-wax column (30m × 0.25mm, 0.25 μm);
temperature-raising program A: maintaining the initial temperature at 36 deg.C for 5min, heating to 100 deg.C at 3 deg.C/min, maintaining for 5min, heating to 180 deg.C at 8 deg.C/min, and maintaining for 10 min;
temperature-raising program B: the initial temperature is 40 deg.C, the temperature is kept for 2min, and the temperature is raised to 220 deg.C at 5 deg.C/min, and the temperature is kept for 10 min.
The carrier gas is high-purity helium (99.999%), the flow rate of the chromatographic column is 1.0mL/min, the split ratio is 50.0, and the temperature of the injection port is 250 ℃.
Mass spectrum conditions: an electron ionization source; the ion source temperature is 150 ℃; the filament emits current of 200 muA; electron energy 70 eV; the transmission line temperature is 260 ℃; the scanning mass range m/z is 35-350 u.
Qualitative and quantitative: and (3) carrying out GC-MS analysis on the sample, searching each compound by using an NIST 14 standard spectrum library, comparing the compound with a standard spectrogram to obtain a qualitative result, and quantifying the compound by adopting a peak area normalization method.
A. Result of comparing separation effects of two temperature-rising programs B
As shown in FIG. 6, the temperature of each target was raised under the condition of the temperature raising program A, B, the whole temperature raising process was about 50min, and both programs could separate the targets well in this time period, and since the temperature raising rate of the program B was faster, the target peaked almost completely before 38min, and the target peaked at higher temperature, the obtained peak pattern was ideal. In addition, the final target in procedure a gave a lower overall peak height than procedure B because it peaked at a lower temperature. In conclusion, temperature ramp B works better than temperature ramp A.
1.3.3 analysis of volatile Components of Linum usitatissimum oil
Enriching volatile components in 40 batches of linseed oil samples according to the optimal extraction condition of 1.3.1, obtaining 40 Qinghai linseed oil volatile component identification types, relative contents (table 2) and gas chromatograms by combining the optimal analysis condition of GC-MS in 1.3.2, introducing chromatographic signals into a traditional Chinese medicine chromatographic fingerprint similarity evaluation system (2004A) to obtain original spectra of 40 sample oils, establishing a reference spectrum, and obtaining a reference fingerprint R through multipoint correction and automatic matching.
TABLE 2 linseed oil volatile ingredient classifications
As can be seen from table 2, 58 volatile components were identified in 40 linseed oil samples, including 12 aldehydes, 8 acids, 9 alcohols, 2 ketones, 5 esters, 13 alkenes, 3 heterocycles, 6 other species. The aldehyde volatile components are more in types and relatively high in percentage content, and the aldehyde compounds have a dominant effect on the flavor of the Qinghai linseed oil due to the low flavor threshold value. The relative percentage content of the alcohols and the esters is low, and the threshold values of the alcohols and the esters are high, so that the linseed oil flavor is low in contribution.
Using SPSS 23.0 software, clustering analysis was performed on 40 samples of linseed oil from the Qinghai province by using intergroup connection, and a clustering pedigree map (see fig. 7) consisting of the volatile components of linseed oil from the Qinghai province was obtained using the squared euclidean distance as a metric.
As can be seen from fig. 7, the 40 samples of Qinghai linseed oil can be better distinguished by cluster analysis. The Euclidean distance can represent the similarity of the samples, and the smaller the Euclidean distance is, the higher the similarity of the samples is, the samples can be classified into one class. When the distance is 20, all samples can be grouped into two main types, S-35 is a single type, and the rest samples are one type; when the distance between classes is 10, linseed oil samples can be grouped into three categories, S-35 is one category, S-22, S-37, S-39 and S-40 can be classified into one category, and the other 35 samples are grouped into one category, which shows that the volatile components of different linseed oil samples can be obviously distinguished through cluster analysis.
The combination of the S-35 and the table 2 shows that the types of volatile components are few, so that the relative percentage content of the alkane and the heterocycle is obviously higher than that of other samples, and the difference between the alkane and the heterocycle is large; the S-22, S-37, S-39 and S-404 samples have higher relative percentage of aldehyde substances, and thus are independently grouped into one type. The analysis reason may be that the content of linoleic acid and linoleic acid in the sample is higher, and the content of aldehyde substances is higher than that of other varieties because the aldehyde substances are usually generated by oxidizing the linoleic acid and the linolenic acid.
The determination method of the invention can be used for identifying the proportion of different adulterated oil seeds.
Example 2 construction of volatile component fingerprint of Qinghai linseed oil
1. Analyzing the chromatogram of the volatile components of 40 linseed oils in Qinghai by using a traditional Chinese medicine chromatogram fingerprint similarity evaluation system to obtain a fingerprint superposition map of S1-S40 (figure 8).
As can be seen from fig. 8, the fingerprint has the following characteristics: (1) a peak area of 1-10 min, less peaks and lower relative content; (2) in the 11-26.5 min peak area, the chromatographic peak in the area is denser than other time peaks, and the chromatographic peak is mainly composed of aldehydes and hydrocarbons, wherein the aldehydes and hydrocarbons comprise trans-2, 4-heptadienal with the highest content, and the trans-2, 4-heptadienal is a main fingerprint area of volatile components of the linseed oil; (3) and in the peak area of 27-35 min, the number of peaks is small, the relative content is low, and a small amount of acid compounds are included.
Through analysis and comparison of 40 Qinghai linseed oil volatile component total ion flow graphs, the fact that the separation condition of chromatographic peaks, the peak area is large and the number of peaks is large in S19 samples is found, therefore, S19 is used as a reference graph and combined with a chromatographic peak matching result of similarity software, peaks 1-18 with retention time within 7-35 min are selected as a common peak, except peaks 1, 3, 7, 8, 9, 11, 13, 16 and 18, and other peaks are relatively small in contribution to the fingerprint, but stably exist among different samples to form a secondary feature of the fingerprint, and therefore the Qinghai linseed oil volatile component fingerprint, namely the standard fingerprint is established (figure 9).
The measured fingerprint of the Qinghai linseed oil sample is compared with the standard fingerprint, the similarity is calculated by adopting an included angle cosine method, and the result is shown in table 3. As can be seen from table 3, although the similarity of 40 batches of linseed oil samples is different to a certain extent, the similarity of 70% of the samples is greater than 0.8, which indicates that although the linseed oil is different in production place, variety and acquisition route, the volatile components still have certain stability, so that the constructed GC-MS standard fingerprint can relatively comprehensively represent the information of the volatile components of the Qinghai linseed oil, and is favorable for comprehensive and accurate evaluation and research of the quality of the volatile components of the linseed oil.
Table 340 linseed oil fingerprint similarity
2. Adulteration model establishment
Designing a blending model of blending vegetable oil with the gradient of 10%, 20%, 30%, 40% and 50% into linseed oil, wherein the vegetable oil is rapeseed oil, soybean oil, sunflower seed oil, peanut oil, corn oil, sesame oil and the like:
the extraction method of rapeseed oil, soybean oil, peanut oil, sunflower seed oil, corn oil and sesame oil in the embodiment 1 is used for enriching the volatile matters of six kinds of vegetable oil, and after sample injection, GC-MS detection and analysis are carried out on the volatile components in each sample, and the main volatile components and the relative percentage content are shown in figure 10.
As can be seen from fig. 10, aldehydes and acids are detected in six vegetable oils, and the aldehydes have high relative percentage content in each sample oil, and abundant aldehydes are mainly generated by oxidation of fatty acids such as linoleic acid, linolenic acid, and the like, and have fragrance such as fat, fruit flavor, and the like, wherein the aldehydes in rapeseed oil, soybean oil, and sunflower seed oil account for 48.38% -54.53% of the total content. Alcohols, ketones, esters, heterocycles have not been detected in all vegetable oils. The soybean oil contains no alcohol substances, the ketoester substances are not detected in the sunflower seed oil and the corn oil, and the content of the ketoester substances in other vegetable oils is lower, wherein the relative percentage content is 0.65-4.34. The heterocyclic substances have the highest content of peanut oil and sesame oil, and the content of the heterocyclic substances is 2-4 times that of other vegetable oil.
Therefore, when the linseed oil is mixed with the vegetable oil, the types and relative percentage contents of volatile components in the mixed linseed oil can be regularly increased and decreased along with the change of the mixing amount.
3. Qinghai linseed oil adulteration identification based on fingerprint spectrum
The standard fingerprint of the linseed oil is compared with the other six vegetable oil fingerprints, and the figure 11 shows. Similarity evaluation software is used for calculating the similarity between different vegetable oils and linseed oil so as to test the effect of the constructed Qinghai linseed oil volatility fingerprint spectrum on distinguishing linseed oil from other vegetable oils, and the result is shown in table 4.
TABLE 4 Standard fingerprint similarity of different vegetable oils and linseed oils
As can be seen from table 4, the similarity between the fingerprints of the six different vegetable oils and the standard fingerprint of the linseed oil is small, the similarity between the fingerprints of the rapeseed oil, the sunflower seed oil and the linseed oil is only 0.036 and 0.077, the similarity between the fingerprint of the other vegetable oil samples and the standard fingerprint of the linseed oil is less than 0.3, and the results of the similarity are obviously different from that of the linseed oil, so that feasibility is provided for the adulteration identification research of the linseed oil.
The types and relative percentage contents of volatile components of 30 samples doped with different proportions of rapeseed oil, soybean oil, peanut oil, sunflower seed oil, corn oil and sesame oil are measured, similarity of the linseed oil doped with different proportions of oil relative to pure linseed oil is calculated by utilizing similarity evaluation software, a adulteration model is established, and the result is shown in figure 12.
As can be seen from fig. 12, the more the other vegetable oils in the linseed oil are adulterated, the smaller the similarity of the fingerprint is, and the two are in a linear decreasing curve, and the linear equation is shown in table 5. The adulteration amount is calculated through the linear equation of the adulteration model, and compared with the actual adulteration amount, the relative error is calculated, and the result is shown in the table 6.
TABLE 5 fingerprint similarity and adulteration model curve equation
TABLE 6 fingerprint similarity and relative error of adulterated linseed oil
As can be seen from Table 6, the average value of the relative error of the adulteration amount in the rapeseed oil adulteration model is 8.651%, and the rapeseed oil adulteration model is suitable for the adulteration detection of the rapeseed oil with the adulteration amount of more than 30%; the relative error average value of the adulteration amount in the soybean oil adulteration model is 12.987%, and when the average relative error of the adulteration amount in the range of 40-50% is 3.420%, the identification effect is good; the average relative errors of the adulteration amounts in the peanut oil adulteration model, the sunflower seed oil adulteration model and the sesame oil adulteration model are 2.061%, 0.666% and 0.453% respectively, so that excellent detection effects can be achieved, and the adulteration detection method is suitable for the adulteration detection with the adulteration ratio of more than 10%; the average relative error of the adulteration amount in the corn oil adulteration model is 4.750 percent, the corn oil with the adulteration ratio of more than 20 percent has good detection effect, and when the adulteration amount reaches 30 percent, the detection effect is excellent.
In conclusion, the method has good extraction effect, the GC-MS is used for detecting 58 volatile components contained in the Qinghai linseed oil sample, the separation and identification effects are good, and meanwhile, the lower similarity indicates that the volatile components of the linseed oil are greatly different from those of other 6 plant oils. The adulteration model established on the basis is suitable for adulteration identification of 10% of peanut oil, sunflower seed oil, sesame oil, more than 20% of corn oil, more than 30% of rapeseed oil and more than 40% of soybean oil, and provides a theoretical basis for linseed oil adulteration identification and quality control.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. A method for measuring the volatile components of linseed oil is characterized in that headspace solid phase micro-extraction is adopted to enrich the volatile components, and then gas chromatography-mass spectrometry combined detection is carried out;
the conditions of the headspace solid phase microextraction comprise:
fixing the extraction temperature: 50-90 ℃;
the balance time is as follows: 10-50 min;
adsorption time: 20-60 min;
desorption time: 1-9 min;
stirring strength: 200-600 r/min;
the temperature-raising program of the gas chromatograph comprises the following steps: keeping the temperature of 36-40 ℃ for 2-5 min, raising the temperature to 100-220 ℃ at 3-5 ℃/min, keeping the temperature for 5-10 min, raising the temperature to 180-220 ℃ at 0-8 ℃/min, and keeping the temperature for 0-10 min.
2. The assay of claim 1, wherein the conditions of the headspace solid phase microextraction comprise:
fixing the extraction temperature: 70-80 ℃, preferably 80 ℃;
the balance time is as follows: 20-30 min, preferably 20 min;
adsorption time: 20-40 min, preferably 40 min;
desorption time: 5-9 min, preferably 5 min;
stirring strength: 350-450 r/min, preferably 400 r/min.
3. The assay of claim 1, wherein the conditions of the headspace solid phase microextraction further comprise an extraction head: 50/30 μm divinylbenzene/carbon molecular sieves/polydimethylsiloxane extracted fiber heads.
4. The assay method of claim 1, wherein the temperature-increasing procedure of gas chromatography-mass spectrometry comprises: keeping at 40 deg.C for 2min, increasing to 220 deg.C at 5 deg.C/min, and keeping for 10 min.
5. An assay according to claim 1 or 4 wherein the gas chromatography-mass spectrometry conditions further comprise one or more of i to vi:
i, chromatographic column: polyethylene glycol capillary column;
ii chromatography column model: InertCap pure-wax;
iii column specification: 30 m.times.0.25 mm.times.0.25 μm;
iii split ratio: 48-52: 1, preferably 50: 1;
iv flow rate: 0.5-1.5 mL/min, preferably 1.0 mL/min;
v, sample inlet temperature: 245-255 ℃, preferably 250 ℃;
vi carrier gas: helium gas with a purity of 99.999%.
6. An assay as claimed in claim 1 wherein the gas chromatography-mass spectrometry conditions comprise one or more of the following i to v:
i ion source temperature: 140-160 ℃, preferably 150 ℃;
ii filament emission current: 190-200 muA, preferably 200 muA;
iii electron energy: 60-75 eV, preferably 70 eV;
iv transmission line temperature: 250 ℃ to 270 ℃, preferably 260 ℃;
v scanning mass range m/z: 30-400 u, preferably 35-350 u.
7. The method of claim 1, wherein the volatile component comprises an aldehyde, an acid, an alcohol, a ketone, an ester, an alkane, or a heterocycle.
8. The assay according to any one of claims 1 to 7, wherein the volatile component is further characterized by a qualitative or/and quantitative step after the GC-MS detection.
9. A linseed oil volatile component fingerprint constructed by the method of any one of claims 1 to 8.
10. Use of the fingerprint of claim 9 for the identification of adulteration of vegetable oil.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011333156.3A CN112578060A (en) | 2020-11-25 | 2020-11-25 | Method for measuring volatile components of linseed oil and application thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011333156.3A CN112578060A (en) | 2020-11-25 | 2020-11-25 | Method for measuring volatile components of linseed oil and application thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112578060A true CN112578060A (en) | 2021-03-30 |
Family
ID=75123211
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011333156.3A Pending CN112578060A (en) | 2020-11-25 | 2020-11-25 | Method for measuring volatile components of linseed oil and application thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112578060A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114076806A (en) * | 2021-10-28 | 2022-02-22 | 青海大学 | Fingerprint spectrum detection method of linseed oil and application thereof |
| CN114088837A (en) * | 2021-11-22 | 2022-02-25 | 青海大学 | Linseed oil adulteration detection method based on triglyceride fingerprint spectrum and application thereof |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101398412A (en) * | 2008-11-04 | 2009-04-01 | 河北大学 | Gas-chromatography fingerprinting for rapidly identifying edible oil |
| US20140208825A1 (en) * | 2012-08-03 | 2014-07-31 | Conocophillips Company | Petroleum-fluid property prediction from gas chromatographic analysis of rock extracts or fluid samples |
| CN104458991A (en) * | 2014-12-12 | 2015-03-25 | 广东省农业科学院蚕业与农产品加工研究所 | Detection method for volatile flavor substance of edible vegetable oil |
| CN106526031A (en) * | 2016-12-23 | 2017-03-22 | 山东鲁花集团有限公司 | Method for distinguishing adulterated peanut oil |
| CN106770796A (en) * | 2017-01-25 | 2017-05-31 | 青岛市食品药品检验研究院 | The method that static headspace-GC-MS combination determines ready-mixed oil harmonic proportion |
| CN109001361A (en) * | 2018-10-09 | 2018-12-14 | 南京财经大学 | A method of detection rapeseed oil flavor substance |
-
2020
- 2020-11-25 CN CN202011333156.3A patent/CN112578060A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101398412A (en) * | 2008-11-04 | 2009-04-01 | 河北大学 | Gas-chromatography fingerprinting for rapidly identifying edible oil |
| US20140208825A1 (en) * | 2012-08-03 | 2014-07-31 | Conocophillips Company | Petroleum-fluid property prediction from gas chromatographic analysis of rock extracts or fluid samples |
| CN104458991A (en) * | 2014-12-12 | 2015-03-25 | 广东省农业科学院蚕业与农产品加工研究所 | Detection method for volatile flavor substance of edible vegetable oil |
| CN106526031A (en) * | 2016-12-23 | 2017-03-22 | 山东鲁花集团有限公司 | Method for distinguishing adulterated peanut oil |
| CN106770796A (en) * | 2017-01-25 | 2017-05-31 | 青岛市食品药品检验研究院 | The method that static headspace-GC-MS combination determines ready-mixed oil harmonic proportion |
| CN109001361A (en) * | 2018-10-09 | 2018-12-14 | 南京财经大学 | A method of detection rapeseed oil flavor substance |
Non-Patent Citations (4)
| Title |
|---|
| 吴翠蓉 等: "SPME-GC-MS测定山茶油掺假", 《江苏农业科学》 * |
| 孙亚娟 等: "杏仁油挥发性成分指纹图谱的构建及掺伪定量检测方法研究", 《食品工业科技》 * |
| 王李平 等: "花生油挥发性风味物质SPME-GC/MS指纹图谱的研究", 《食品工业》 * |
| 魏长庆 等: "新疆亚麻籽油香气指纹图谱的构建与研究", 《中国粮油学报》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114076806A (en) * | 2021-10-28 | 2022-02-22 | 青海大学 | Fingerprint spectrum detection method of linseed oil and application thereof |
| CN114088837A (en) * | 2021-11-22 | 2022-02-25 | 青海大学 | Linseed oil adulteration detection method based on triglyceride fingerprint spectrum and application thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Arbulu et al. | Untargeted metabolomic analysis using liquid chromatography quadrupole time-of-flight mass spectrometry for non-volatile profiling of wines | |
| Risticevic et al. | Solid phase microextraction coupled with comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry for high-resolution metabolite profiling in apples: Implementation of structured separations for optimization of sample preparation procedure in complex samples | |
| Kovačevič et al. | Determination and verification of hop varieties by analysis of essential oils | |
| CN112578060A (en) | Method for measuring volatile components of linseed oil and application thereof | |
| Mateus et al. | Characterization of the volatile fraction emitted by Pinus spp. by one-and two-dimensional chromatographic techniques with mass spectrometric detection | |
| CN111220763B (en) | Application of high-content DSM as characteristic marker of linden honey | |
| CN103675127A (en) | Method for distinguishing flavor substance in edible mushroom through combination of headspace gas chromatography-mass spectrometer and electronic nose | |
| Di et al. | Application of headspace solid‐phase microextraction (HS‐SPME) and comprehensive two‐dimensional gas chromatography (GC× GC) for the chemical profiling of volatile oils in complex herbal mixtures | |
| CN112595786A (en) | Quantitative detection method for volatile flavor substances in fermented grains | |
| CN107085051A (en) | A kind of construction method and discrimination method of Huanghua Pear redwood seeds finger-print | |
| CN111366647A (en) | Method for detecting volatile components of cabbage leaves by combining headspace solid phase microextraction with gas chromatography-mass spectrometry | |
| CN110596255A (en) | Method for detecting volatile components of tomatoes and products thereof | |
| CN112710765A (en) | Fingerprint detection method of gardenia medicinal material and application thereof | |
| CN113252812A (en) | Method for analyzing flavor substances of hotpot condiment | |
| CN109187784B (en) | Headspace solid phase microextraction-gas chromatography-mass spectrometry detection and analysis method for sea buckthorn volatile oil component | |
| CN110514757A (en) | A kind of method of Volatile flavor components in fast resolving white wine | |
| Jeleń et al. | Solid phase microextraction for profiling volatile compounds in liquered white wines | |
| CN107589204B (en) | Method for determining anthranilate grape essence in wine by gas chromatography-mass spectrometry | |
| CN115950979A (en) | Method for tracing origin of complex matrix tobacco extract | |
| CN114280196A (en) | Method for distinguishing extra virgin olive oil from other olive oils based on flavor markers | |
| CN112697931B (en) | Application of trifolioside as characteristic marker of lespedeza-pedeza honey | |
| CN109212102B (en) | Method for identifying gardenia oil based on characteristic component gas chromatography-mass spectrum fingerprint | |
| CN112129856B (en) | Method for identifying ellagic acid from gallnut | |
| CN113075318A (en) | Analysis method for chafing dish beef tallow sample in old chafing dish beef tallow production | |
| CN113984940A (en) | Analysis method for high-throughput rapid detection of volatile components of rhododendron lapponicum |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |