Quasi-targeting lipidomics method for identifying cold-pressed camellia oleosa seed oil and leached camellia oleosa seed oil

Abstract

According to the quasi-targeting lipidomics method for identifying the cold-pressed camellia oleosa seed oil and the leached camellia oleosa seed oil, identification of the two processing technologies is associated with the processing process, comprehensive lipid information is obtained through a high-resolution mass spectrum, lipid component structure information in the camellia oleosa seed oil is obtained as much as possible, and the content of lipid components in the camellia oleosa seed oil is calculated. And two types of compounds associated with processing are extracted to identify the cold-pressed camellia oleosa seed oil and the leached camellia oleosa seed oil, so that the identification precision is remarkably improved, and the prediction accuracy can reach 100%.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of oil tea detection, and particularly relates to a pseudo-targeted lipidomics method for identifying cold-pressed oil tea seed oil and solvent-extracted oil tea seed oil. BACKGROUND

[0002] Oil tea seed oil is a kind of edible vegetable oil with high nutritional value and unique flavor. Its processing technology mainly includes cold-pressing method and solvent extraction method. The cold-pressing method directly extracts oil by physical pressing, retains the natural flavor and nutritional components of oil tea seeds, and has low acid value, so that it only needs mild refining (such as degumming and sedimentation), without deep processing such as deacidification, decolorization and deodorization. Therefore, the market price of cold-pressed tea oil is significantly higher than that of solvent-extracted tea oil (about 1.5-2 times). The solvent extraction method uses organic solvents (such as n-hexane) to extract oil, and needs to go through the whole refining process of degumming, deacidification, decolorization and deodorization to remove solvents and impurities. In this process, oil oxidation and hydrolysis are easily induced, leading to the degradation of triglycerides to form diglycerides, monoglycerides and oxidation products. How to identify cold-pressed tea oil and solvent-extracted tea oil is of great significance to the healthy development of the oil tea industry.

[0003] At present, the technologies for identifying cold-pressed tea oil and solvent-extracted tea oil mainly include spectroscopy and chromatography. However, the spectroscopy method has insufficient sensitivity and cannot distinguish tea oil from other high-oleic oils; the gas chromatography method is limited by the detection limit and cannot effectively distinguish the two types of tea oil; although the high-resolution liquid chromatography-mass spectrometry technology can analyze from the aspect of triglycerides, it is easy to misjudge due to the natural differences in the composition of triglycerides in tea oil itself. Existing researches mostly use the determination of hydroxyl value (reflecting the total amount of diglycerides / monoglycerides) and peroxide value (reflecting the oxidation degree) for indirect judgment, but such indexes lack specificity and cannot accurately associate with the processing technology.

[0004] In addition, literature research shows that the refining process of cold-pressed oil tea seed oil is simple, and the fatty acid composition remains basically unchanged; while the solvent-extracted oil tea seed oil undergoes complex chemical changes in the refining process, such as the increase of peroxide value in the decolorization stage, the decrease in the deodorization stage, and the minimum acid value after deacidification but possible rebound in the subsequent process. These differences provide potential basis for distinguishing the two types of oils, but the existing methods have not established an accurate identification system based on specific markers (such as oxidation products or glyceride degradation products).

[0005] In summary, the existing identification methods have problems such as low sensitivity, insufficient specificity or dependence on non-characteristic indicators, which cannot meet the market demand for accurate identification of cold-pressed and solvent-extracted oil tea seed oil. Therefore, it is urgent to develop a high-sensitivity and high-specificity detection method based on process characteristic compounds (such as oxidized oil and diglycerides) to accurately identify the two types of oil tea seed oil, protect the rights and interests of consumers and promote the healthy development of the industry. SUMMARY

[0006] The present invention aims to solve at least one of the above-mentioned technical problems existing in the prior art. To this end, the present invention provides a pseudo-targeted lipidomics method for identifying cold-pressed camellia oil and leached camellia oil. The technical problem to be solved is to associate the identification of the two processing techniques with the processing process, obtain more comprehensive lipid information through high-resolution mass spectrometry, obtain as much lipid component structural information as possible in camellia oil, and extract two types of processing-related compounds to identify cold-pressed camellia oil and leached camellia oil, significantly improving the accuracy of identification.

[0007] A first aspect of the present invention provides a pseudo-targeted lipidomics method for identifying cold-pressed camellia oil and leached camellia oil, comprising the following steps:

[0008] S1: Camellia oil sampling: Prepare cold-pressed camellia oil and extracted camellia oil samples with clear origin and category;

[0009] S2: Sample pretreatment: Weigh 0.1000 g of each sample and dissolve it in 10 mL of mass spectrometry-grade isopropanol. Dilute 10-fold. After the experimental samples are prepared, take an equal amount of each sample and mix them as quality control samples to monitor the stability and repeatability of the instrument and to optimize the UPLC-Q-TOF-MS conditions.

[0010] S3: UPLC-Q-TOF-MS analysis;

[0011] S4: The collected quality control samples were subjected to peak extraction and identification by comparing with the lipid EIEIO database through the software;

[0012] S5: Data statistical analysis: Submit the identified peak table results to the data processing platform for statistical analysis PCA analysis and OPLS-DA analysis to find the differential lipid components.

[0013] S6: Confirmation of differential compound structures: Confirm compound structures by primary and secondary mass spectrometry mass number errors, retention time, and isotope abundance;

[0014] S7: Method validation. The characteristic compounds screened by OPLS-DA were cross-validated 200 times to obtain R2Y and Q2;

[0015] S8: Sample verification.

[0016] The pseudo-targeted lipidomics method for identifying cold-pressed camellia oil and leached camellia oil of the present invention has at least the following beneficial effects:

[0017] The present invention adopts a lipidomics method, using a high-sensitivity, high-coverage high-resolution liquid chromatography-mass spectrometry instrument to collect lipid substance information of camellia oil. Using MSdial in combination with a search of the lipid maps database, more than 200 glyceride lipid compounds in the camellia oil are annotated, providing a material basis for distinguishing cold-pressed camellia oil from hot-pressed camellia oil. Combining the process characteristics of leaching camellia oil and pressing camellia oil, as well as the change patterns of substances reported in the literature, diglycerides and oxidized oils with high content in leached camellia oil are screened as characteristic compounds, establishing a new method for distinguishing leached camellia oil from cold-pressed camellia oil. The ion pair information of the substances identified by this method can be applied to highly popular instruments such as triple quadrupoles, and the method established by the present invention has great practicality.

[0018] The pseudo-targeted lipidomics method for identifying cold-pressed camellia oil and leached camellia oil can achieve a prediction accuracy of 100%.

[0019] According to some embodiments of the present invention, in step S1, there are at least 8 samples of cold-pressed camellia seed oil and 8 samples of leached camellia seed oil.

[0020] According to some embodiments of the present invention, in step S1, the origins of the samples of cold-pressed camellia oil and leached camellia oil include Hunan, Guangxi, Hubei, Jiangxi, Anhui and Guizhou.

[0021] According to some embodiments of the present invention, in step S3, the liquid phase conditions are:

[0022] Phase A: methanol:acetonitrile:water (1:1:1, V / V / V, containing 5 mM ammonium acetate);

[0023] Phase B: isopropanol (with low doses of mass spectrometry grade inorganic salts added);

[0024] The gradient elution program was:

[0025] 0.0~1.0min, 80%A, 20%B;

[0026] 1.0~3.0min, 80%~30%A, 20%~70%B;

[0027] 3.0~13.0min, 30%~2%A, 70%~98%B;

[0028] 13.0~15.0min, 2%A, 98%B;

[0029] 15.0~15.1min, 2%~80%A, 98%~20%B;

[0030] 15.1~17.0min, 80%A, 20%B;

[0031] The flow rate was 0.3 mL / min, the sample plate temperature was 4 °C, the column temperature was 45 °C, and the injection volume was 1 μL.

[0032] According to some embodiments of the present invention, the inorganic salt added to phase B is at least one of ammonium acetate, sodium acetate and lithium acetate.

[0033] According to some embodiments of the present invention, the inorganic salts added to phase B have a concentration range of 0-10 mM for ammonium acetate, and 0-30 μM for sodium acetate and lithium acetate.

[0034] According to some embodiments of the present invention, the ionization temperature of the ion source is one of 500°C, 550°C, 600°C and 650°C.

[0035] The electron kinetic energy (KE) of EAD is one of 10 eV, 11 eV, 12 eV, 13 eV, 14 eV, and 15 eV.

[0036] According to some embodiments of the present invention, the experimental parameters are: ammonium acetate and sodium acetate are added simultaneously, the added inorganic salts are ammonium acetate (5 mM) and sodium acetate (20 microns), the ion source temperature is 600°C, and the electron kinetic energy (KE) of EAD is 13 eV.

[0037] According to some embodiments of the present invention, in step S3, the lipid compounds are chromatographed using an ExionL C (Sciex) ultra-high performance liquid chromatograph using a Phenomen Kinetex C18 (2.1×100 mm, 1.7 μm) liquid chromatography column.

[0038] According to some embodiments of the present invention, in step S3, the high-resolution mass spectrometry conditions are: using a Sciex ZenoTOF™ 7600 high-resolution mass spectrometer to acquire high-resolution mass spectrometry data in information-dependent acquisition (IDA) mode.

[0039] According to some embodiments of the present invention, in step S3, in IDA mode, primary mass spectrometry and secondary mass spectrometry data are collected by data acquisition software (OS3.0, Sciex), ions are automatically selected, and their secondary mass spectrometry information is collected;

[0040] In each cycle, the 20 ions with the strongest response were selected for secondary mass spectrometry scanning. The energy of collision-induced dissociation was 45 eV, and the accumulation time of each secondary mass spectrum was 50 ms.

[0041] According to some embodiments of the present application, in step S3, the EAD conditions are: ion source temperature is set to a value between 500℃ and 650℃, GS1: 50 psi, GS2: 50 psi, CUR: 30 Ppsi, DP: 80 V, ISVF: 6000 V. The electron kinetic energy (KE) is set to a value between 10 eV and 15 eV, and the electron beam current is 6000 nA throughout the study.

[0042] According to some embodiments of the present application, in step S3, the Zeno trap pulse function is enabled, and the Zeno detection threshold is set to 10,000,000 cps.

[0043] In order to maintain the high-quality accuracy of the ZenoTOF 7600 in data collection, the instrument is calibrated every 6 experimental samples using an automatic calibration device system. Each sample is injected 3 times.

[0044] According to some embodiments of the present application, in step S3, data extraction can be performed by the msdial software for peak extraction, peak alignment and peak identification. The quality control sample is selected and imported into the msdial 5.0 software, and the EIEIO database is selected for lipid compound retrieval. The search conditions are: the mass tolerance of the first mass spectrum is set to 0.015 Da, the mass tolerance of the second mass spectrum is set to 0.025 Da, and the retention time tolerance is set to 0.05 min. The retention time, compound name, compound addition form and molecular formula in the data exported from the msdial software are imported into the analytics plug-in of the OS 3.0 software for compound verification, and the peak area of the confirmed compound is extracted for subsequent statistical analysis.

[0045] According to some embodiments of the present application, in step S4, the QC sample collected can be subjected to peak extraction and lipid EIEIO database comparison identification by the MS-DIAL software. The molecular formula, ion addition mode and retention time of each lipid are input into the SCIEX 3.0 software, the software calculates the first accurate mass number, calculates the mass spectrum information of the compound in the sample according to the error of the accurate mass number and the isotope type, and matches the peak time and abundance of the liquid chromatogram.

[0046] According to some embodiments of the present application, in step S4, the rules for qualitative analysis of the identified compounds and identification results are: mass number deviation < 5 ppm; isotope abundance ratio deviation < 20%; secondary spectrum matching score > 70, and the retention time window is set to 0.4 min.

[0047] According to some embodiments of the present invention, in step S5, the identified peak table results can be submitted to the MetaboAnalyst platform for statistical analysis PCA analysis and OPLS-DA analysis to find the differential lipid components therein.

[0048] According to some embodiments of the present invention, the differential lipid composition screening rules are as follows: p value <0.05; foldchange >1.5; VIP value >1.2. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is the TIC diagram of the cold-pressed camellia oil and the extracted camellia oil according to the embodiments of the present invention.

[0050] Figure 2 This is the PCA diagram of the cold-pressed camellia oil and the leached camellia oil according to the embodiment of the present invention.

[0051] Figure 3 This is the OPLS-DA diagram of the cold-pressed camellia oil and the extracted camellia oil according to the embodiment of the present invention.

[0052] Figure 4 This is the VIP diagram of the difference compounds in the examples of the present invention.

[0053] Figure 5 This is a heat map of the different compounds between cold-pressed camellia seed oil and leached camellia seed oil in the examples of the present invention.

[0054] Figure 6 This is one of the mass spectra of the different compounds between cold-pressed camellia seed oil and leached camellia seed oil in an embodiment of the present invention.

[0055] Figure 7 This is the second mass spectrum of the different compounds between cold-pressed camellia seed oil and leached camellia seed oil in an embodiment of the present invention.

[0056] Figure 8 This is the third mass spectrum of the difference compounds between cold-pressed camellia seed oil and leached camellia seed oil in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The following are specific embodiments of the present invention, and the technical solutions of the present invention are further described in conjunction with the embodiments, but the present invention is not limited to these embodiments.

[0058] In a first aspect, some embodiments of the present invention provide a pseudo-targeted lipidomics method for identifying cold-pressed camellia oil and leached camellia oil, comprising the following steps:

[0059] S1: Camellia oil sampling: Prepare cold-pressed camellia oil and extracted camellia oil samples with clear origin and category;

[0060] S2: Sample pretreatment: Weigh 0.1000 g of each sample and dissolve it in 10 mL of mass spectrometry-grade isopropanol. Dilute 10-fold. After the experimental samples are prepared, take an equal amount of each sample and mix them as quality control samples to monitor the stability and repeatability of the instrument and to optimize the UPLC-Q-TOF-MS conditions.

[0061] S3: UPLC-Q-TOF-MS analysis;

[0062] S4: The collected quality control samples were subjected to peak extraction and identification by comparing with the lipid EIEIO database through the software;

[0063] S5: Data statistical analysis: Submit the identified peak table results to the data processing platform for statistical analysis PCA analysis and OPLS-DA analysis to find the differential lipid components.

[0064] S6: Confirmation of differential compound structures: Confirm compound structures by primary and secondary mass spectrometry mass number errors, retention time, and isotope abundance;

[0065] S7: Method validation. The characteristic compounds screened by OPLS-DA were cross-validated 200 times to obtain R2Y and Q2;

[0066] S8: Sample verification.

[0067] It should be noted that the present invention adopts a lipidomics method, using a high-sensitivity, high-coverage high-resolution liquid chromatography-mass spectrometry instrument to collect lipid substance information of camellia oil, and uses MSdial combined with a search of the lipid maps database to annotate more than 200 glyceride lipid compounds in the tea oil, providing a material basis for distinguishing cold-pressed tea oil from hot-pressed tea oil. Combining the process characteristics of leaching camellia oil and pressing camellia oil, as well as the change patterns of substances reported in the literature, diglycerides and oxidized oils with higher contents in leached camellia oil were screened as characteristic compounds, establishing a new method for distinguishing leached tea oil from cold-pressed tea oil. The ion pair information of the substances identified by this method can be applied to highly popular instruments such as triple quadrupoles, and the method established by the present invention has great practicality.

[0068] The pseudo-targeted lipidomics method for identifying cold-pressed camellia oil and leached camellia oil can achieve a prediction accuracy of 100%.

[0069] It should also be noted that the present invention utilizes a high-resolution mass spectrometry data acquisition method, which improves the coverage and resolution of compound identification. This allows for more comprehensive and accurate identification of compounds, a greater number of identified compounds, and more comprehensive structural information, providing sufficient compound information for process identification. Characteristic compounds include compounds with high concentrations, such as DG40:3, DG40:2, DG42:3, DG45:3, and DG30:1, produced during deep refining, as well as compounds such as TG54:3;O, TG52:2;O, and TG52:3;O2, which are significantly less abundant during deodorization. This method can be transferred to a triple quadrupole LC / MS system or one equipped with an evaporative light scattering detector.

[0070] It should also be noted that the present invention avoids the use of compounds such as triglycerides that are comprehensively affected by factors such as region, variety and processing conditions, and instead adopts two types of compounds such as diglycerides and oxidized glycerides that are related to processing methods as screening targets. The requirement for the number of representative samples is reduced, and the method is more practical.

[0071] It can be understood that the method of the present invention is a direct method. The sample is directly injected without pretreatment, and changes in the injection method will not affect the use of the data.

[0072] It should be noted that the TIC plots for cold-pressed and leached camellia oils are not significantly different, and their glyceride compositions are similar. Furthermore, it is difficult to explain the difference in triglyceride composition between the two groups of samples as being due to different processing techniques. During the processing of cold-pressed camellia oil, moderate refining is generally employed to preserve the oil's active nutrients, such as fat-soluble polyphenols, squalene, and sterols, and deacidification, typically bypassing deodorization, bleaching, and other processes. However, during the processing of leached camellia oil, a full oil refining process, including degumming, deacidification, bleaching, and deodorization, is typically required to remove solvent-extracted phospholipids and harmful solvents. These processes can lead to mild hydrolysis and oxidation of triglycerides. The fatty acids produced by hydrolysis are removed during the deacidification step, while other hydrolysis products, such as diglycerides and monoglycerides, remain. Some oxidation products are removed during the deodorization step. Therefore, combining the process characteristics of cold-pressed camellia oil and leached camellia oil, as well as the substance composition detected by UPLC-Q-TOF-MS, the present invention screened diglycerides and oxidized glycerides with p < 0.05, VIP > 1.2, and |log2FC| > 1 to establish unsupervised PCA models and supervised OPLS-DA models.

[0073] The TIC plots of cold-pressed and leached camellia oils show no significant difference, and their glyceride compositions are similar. Furthermore, the difference in triglyceride composition between the two groups of samples is difficult to explain as being due to different processing techniques. During the processing of cold-pressed camellia oil, moderate refining is generally employed to preserve the oil's active nutrients, such as fat-soluble polyphenols, squalene, and sterols, and deacidification, typically bypassing deodorization, bleaching, and other processes. However, during the processing of leached camellia oil, a full oil refining process, including degumming, deacidification, bleaching, and deodorization, is typically required to remove solvent-extracted phospholipids and harmful solvents. These processes can lead to mild hydrolysis and oxidation of triglycerides. The fatty acids produced by hydrolysis are removed during the deacidification step, while other hydrolysis products, such as diglycerides and monoglycerides, remain. Some oxidation products are removed during the deodorization step. Therefore, combining the process characteristics of cold-pressed camellia oil and leached camellia oil, as well as the composition of substances detected by UPLC-Q-TOF-MS, this paper screened diglycerides and oxidized glycerides (two types of substances, including many substances) with p < 0.05, VIP > 1.2, and |log2FC| > 1 to establish unsupervised PCA models and supervised OPLS-DA models. Based on the clear lipid composition of cold-pressed camellia oil and leached camellia oil, principal component analysis (PCA) was used to intuitively distinguish the differences between the two types of oils. Figure 2 PCA was used to evaluate the regularity and variability of the two PC factors by determining their contribution rates in the two camellia oil lipid components. Figure 2 It can be seen that the contribution rate of PC1 to lipid composition is 42.5%, the contribution rate of PC2 is 18.7%, and the total contribution rate is 61.2%. Figure 2 The mid-range QC samples clustered in a small circle, indicating good instrument stability. Cold-pressed and hot-pressed camellia oils clustered in two clusters, with no overlap or overlap. Furthermore, the two oils were clearly separated in the score plot, indicating significant differences between them. The clustering circle for the extracted camellia oil was smaller, indicating a more concentrated distribution of its characteristic compounds. This is attributed to the fact that the extracted camellia oils undergo the same refining process.

[0074] Supervised OPLS-DA was used for discriminant analysis to maximize the difference and highlight the key variables and potential markers. The leaching and pressing oil tea seed oils were clustered into two categories in the OPLS-DA score plot. The R2Y and Q2 of the OPLS-DA model were 0.987 and 0.984, respectively, indicating that the model had excellent explanatory and predictive capabilities. Due to the high dimensionality and small sample size of the data in this study, the supervised discriminant model was prone to overfitting. After 1000 permutation tests, the R2Y and Q2 of the OPLS-DA model were 0.995 and 0.993, respectively, and p<0.0001, indicating that the model was excellent and did not appear to be overfitted, and could accurately predict cold-pressed and leaching oil tea seed oils.

[0075] It should be noted that the p value, VIP value and FC value represent the significance level of the difference, respectively.

[0076] p>0.05 is significant, and p<0.05 is not significant.

[0077] The VIP (Variable Importance in Projection) value and p value are often used as a basis for screening. Generally, the VIP value is used to determine the most important variables in the PLS-DA (Partial Least Squares Discriminant Analysis) model, and the p value is used to determine the statistical significance of the variables.

[0078] FC (Fold Change) is the fold change. In simple terms, it is the average expression value of glycerides in one group of samples divided by the average expression value of glycerides in another group of samples.

[0079] |log2FC|>1 means FC>2.0 or FC<0.5.

[0080] Principle Component Analysis (PCA) is a traditional statistical method. After being introduced into the field of machine learning, it is usually considered as a special unsupervised learning algorithm. It can preprocess complex or multivariate data to reduce secondary variables, so as to facilitate further mathematical modeling and statistical model training using the reduced primary variables, so PCA is also called Principal Variable Analysis.

[0081] In combination with the first aspect, in some embodiments of the present application, in step S1, the samples of cold-pressed and leaching oil tea seed oils are at least 8 samples each.

[0082] In combination with the first aspect, in some embodiments of the present invention, in step S1, the origins of the samples of cold-pressed camellia oil and leached camellia oil include Hunan, Guangxi, Hubei, Jiangxi, Anhui and Guizhou.

[0083] In combination with the first aspect, in some embodiments of the present invention, in step S3, the liquid phase conditions are:

[0084] Phase A: methanol:acetonitrile:water (1:1:1, V / V / V, containing 5 mM ammonium acetate);

[0085] Phase B: isopropanol (with low doses of mass spectrometry grade inorganic salts added);

[0086] The gradient elution program was:

[0087] 0.0~1.0min, 80%A, 20%B;

[0088] 1.0~3.0min, 80%~30%A, 20%~70%B;

[0089] 3.0~13.0min, 30%~2%A, 70%~98%B;

[0090] 13.0~15.0min, 2%A, 98%B;

[0091] 15.0~15.1min, 2%~80%A, 98%~20%B;

[0092] 15.1~17.0min, 80%A, 20%B;

[0093] The flow rate was 0.3 mL / min, the sample plate temperature was 4 °C, the column temperature was 45 °C, and the injection volume was 1 μL.

[0094] In combination with the first aspect, in some embodiments of the present invention, the inorganic salt added to phase B is at least one of ammonium acetate, sodium acetate and lithium acetate.

[0095] In combination with the first aspect, in some embodiments of the present invention, the inorganic salt added to phase B has a concentration range of 0-10 mM for ammonium acetate, and 0-30 μM for sodium acetate and lithium acetate.

[0096] In combination with the first aspect, in some embodiments of the present invention, the ionization temperature of the ion source refers to a temperature among 500°C, 550°C, 600°C and 650°C.

[0097] The electron kinetic energy (KE) of EAD is one of 10 eV, 11 eV, 12 eV, 13 eV, 14 eV, and 15 eV.

[0098] In combination with the first aspect, in some embodiments of the present invention, the experimental parameters are: ammonium acetate and sodium acetate are added at the same time, the added inorganic salt is ammonium acetate (5mM), sodium acetate is (20 microns), the ion source temperature is 600°C, and the electron kinetic energy (KE) of EAD is 13eV.

[0099] In combination with the first aspect, in some embodiments of the present invention, in step S3, the lipid compounds are chromatographed using an ExionL C (Sciex) ultra-high performance liquid chromatograph using a Phenomen Kinetex C18 (2.1×100 mm, 1.7 μm) liquid chromatography column.

[0100] In combination with the first aspect, in some embodiments of the present invention, in step S3, the high-resolution mass spectrometry conditions are: using a Sciex Zeno TOF™ 7600 high-resolution mass spectrometer to acquire high-resolution mass spectrometry data in information-dependent acquisition (IDA) mode.

[0101] In combination with the first aspect, in some embodiments of the present invention, in step S3, in IDA mode, primary mass spectrum and secondary mass spectrum data are collected by data acquisition software (OS3.0, Sciex), ions are automatically selected and their secondary mass spectrum information is collected;

[0102] In each cycle, the 20 ions with the strongest response were selected for secondary mass spectrometry scanning. The energy of collision-induced dissociation was 45 eV, and the accumulation time of each secondary mass spectrum was 50 ms.

[0103] In conjunction with the first aspect, in some embodiments of the present invention, in step S3, the EAD conditions are as follows: the ion source temperature is set to a value between 500°C and 650°C, GS1: 50 psi, GS2: 50 psi, CUR: 30 Ppsi, DP: 80 V, and ISVF: 6000 V. Throughout the study, the electron kinetic energy (KE) is set to a value between 10 eV and 15 eV, and the electron beam current is 6000 nA.

[0104] In combination with the first aspect, in some embodiments of the present invention, in step S3, the Zeno trap pulse function is enabled, and the Zeno detection threshold is set to 10,000,000 cps.

[0105] To maintain high mass accuracy during data acquisition, the ZenoTOF7600 was calibrated using an automated calibration system every six experimental samples. Each sample was injected three times.

[0106] In conjunction with the first aspect, in some embodiments of the present invention, in step S3, data extraction can use MSDial software for peak extraction, peak alignment, and peak identification. Quality control samples are selected and imported into MSDial 5.0 software, and the EIEIO database is selected for lipid compound search. The search conditions are as follows: the primary mass spectrometry mass tolerance is set to 0.015 Da, the secondary mass spectrometry mass tolerance is set to 0.025 Da, and the retention time tolerance is set to 0.05 min. The retention time, compound name, compound adduct form, and molecular formula in the data exported from MSDial software are imported into the analytics plug-in of OS 3.0 software for compound verification, and the peak area of ​​the confirmed compound is extracted for subsequent statistical analysis.

[0107] In conjunction with the first aspect, in some embodiments of the present invention, in step S4, the collected QC samples can be subjected to peak extraction and identification by comparison with the lipid EIEIO database using MS-DIAL software. The molecular formula, ion adduction mode, and retention time of each lipid are input into SCIEX3.0 software, which calculates the primary accurate mass. Based on the error between the accurate mass and isotope type, the mass spectrum information of the compound in the sample is calculated, and the peak time and abundance of the liquid chromatogram are matched.

[0108] In combination with the first aspect, in some embodiments of the present invention, in step S4, the rules for extracting and identifying the compounds and qualitative analysis of the identification results are: mass number deviation <5ppm; isotope abundance ratio deviation <20%; secondary spectrum matching score >70, and the retention time window is set to 0.4min.

[0109] In combination with the first aspect, in some embodiments of the present invention, in step S5, the identified peak table results can be submitted to the MetaboAnalyst platform for statistical analysis PCA analysis and OPLS-DA analysis to find the differential lipid components therein.

[0110] In combination with the first aspect, in some embodiments of the present invention, the differential lipid composition screening rules are as follows: p value <0.05; fold change >1.5; VIP value >1.2.

[0111] The following will clearly and completely describe the concept and technical effects of the present invention in conjunction with the embodiments to fully understand the purpose, features and effects of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, other embodiments obtained by those skilled in the art without creative work are all within the scope of protection of the present invention.

[0112] In the description of the present invention, reference to terms such as "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the exemplary expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0113] Unless otherwise specified, "room temperature" in the present invention means 25°C±5°C.

[0114] Unless otherwise specified, “about” in the present invention means that the allowable error is within ±2%.

[0115] If the specific conditions are not specified in the examples, the experiments were carried out under conventional conditions or those recommended by the manufacturer. All reagents or instruments used, if the manufacturer is not specified, are commercially available conventional products.

[0116] Example

[0117] Identify cold-pressed camellia oil and extracted camellia oil by the following steps:

[0118] S1: Camellia oil sampling: 7 samples of cold-pressed camellia oil and 7 samples of leached camellia oil with clear origin and category were purchased from JD.com. The origins were Hunan, Guangxi, Zhejiang, Anhui and other camellia producing areas.

[0119] S2: Sample pretreatment: Weigh 0.1000 g of each sample and dissolve it in 10 mL of mass spectrometry-grade isopropanol as the mobile phase, dilute 10-fold. After the experimental sample preparation is completed, take an equal amount of each sample and mix them as quality control samples to monitor the stability and repeatability of the instrument and to optimize the UPLC-Q-TOF-MS conditions;

[0120] S3: UPLC-Q-TOF-MS analysis;

[0121] S4: The collected quality control samples were subjected to peak extraction and identification by comparing with the lipid EIEIO database through the software;

[0122] S5: Data statistical analysis: Submit the identified peak table results to the data processing platform for statistical analysis PCA analysis and OPLS-DA analysis to find the differential lipid components.

[0123] S6: Confirmation of differential compound structures: Confirm compound structures by primary and secondary mass spectrometry mass number errors, retention time, and isotope abundance;

[0124] S7: Method validation. The characteristic compounds screened by OPLS-DA were cross-validated 200 times to obtain R2Y and Q2;

[0125] S8: Sample verification.

[0126] In step S3:

[0127] The liquid phase conditions are:

[0128] Phase A: methanol:acetonitrile:water (1:1:1, V / V / V, containing 5 mM ammonium acetate);

[0129] Phase B: isopropanol (added with low-dose mass spectrometry-grade inorganic salt sodium acetate 20 μM);

[0130] The gradient elution program was:

[0131] 0.0~1.0min, 80%A, 20%B;

[0132] 1.0~3.0min, 80%~30%A, 20%~70%B;

[0133] 3.0~13.0min, 30%~2%A, 70%~98%B;

[0134] 13.0~15.0min, 2%A, 98%B;

[0135] 15.0~15.1min, 2%~80%A, 98%~20%B;

[0136] 15.1~17.0min, 80%A, 20%B;

[0137] The flow rate was 0.3 mL / min, the sample plate temperature was 4 °C, the column temperature was 45 °C, and the injection volume was 1 μL.

[0138] The ionization temperature of the ion source is 600°C.

[0139] The electron kinetic energy (KE) of EAD is 13 eV.

[0140] The lipid compounds were chromatographed on a Phenomen Kinetex C18 (2.1×100 mm, 1.7 μm) liquid chromatography column using an ExionL C (Sciex) ultra-high performance liquid chromatograph.

[0141] High-resolution mass spectrometry conditions were as follows: Sciex Zeno TOF™ 7600 high-resolution mass spectrometer was used to acquire high-resolution mass spectrometry data in information-dependent acquisition (IDA) mode.

[0142] In IDA mode, primary and secondary mass spectrometric data were collected by data acquisition software (OS3.0, Sciex), which automatically selected ions and collected their secondary mass spectrometric information;

[0143] In each cycle, the 20 ions with the strongest response were selected for secondary mass spectrometry scanning. The energy of collision-induced dissociation was 45 eV, and the accumulation time of each secondary mass spectrum was 50 ms.

[0144] AD conditions were: ion source temperature set between 500°C and 650°C, GS1: 50 psi, GS2: 50 psi, CUR: 30 Ppsi, DP: 80 V, and ISVF: 6000 V. Throughout the study, the electron kinetic energy (KE) was set between 10 eV and 15 eV, and the electron beam current was 6000 nA.

[0145] The Zeno Trap Pulse feature is enabled, and the Zeno detection threshold is set to 10,000,000cps.

[0146] To maintain high mass accuracy during data acquisition, the ZenoTOF 7600 was calibrated using an automated calibration system every six experimental samples. Each sample was injected three times.

[0147] Data extraction can be performed using MSDial software for peak extraction, alignment, and identification. Quality control samples were imported into MSDial 5.0 software, and lipid compound searches were performed using the EIEIO database with a primary mass spectrometry tolerance of 0.015 Da, a secondary mass spectrometry tolerance of 0.025 Da, and a retention time tolerance of 0.05 min. Retention times, compound names, adduct forms, and molecular formulas from the MSDial data were imported into the Analytics plugin of OS 3.0 software for compound verification. Peak areas of the confirmed compounds were extracted for subsequent statistical analysis.

[0148] The collected QC samples were peak extracted and identified using MS-DIAL software, along with comparisons to the lipid EIEIO database. The molecular formula, ion adduction pattern, and retention time of each lipid were entered into SCIEX 3.0 software, which calculated the primary accurate mass. Based on the error between the accurate mass and isotope type, the mass spectrometric information for the compound in the sample was calculated, and the peak time and abundance from the liquid chromatogram were matched.

[0149] The rules for qualitative analysis of the extracted identified compounds and the identification results are: mass number deviation <5ppm; isotope abundance ratio deviation <20%; secondary spectrum matching score >70, and the retention time window is set to 0.4min.

[0150] The identified peak table results were submitted to the MetaboAnalyst platform for statistical analysis, PCA analysis and OPLS-DA analysis to find the differential lipid components.

[0151] The screening rules for differential lipid components were as follows: p value < 0.05; fold change > 1.5; VIP value > 1.2.

[0152] Table 1 is a summary of the mass spectrometry information of different compounds in cold-pressed camellia oil and leached camellia oil according to the embodiments of the present invention.

[0153] Table 1

[0154]

[0155]

[0156] Table 1 lists the characteristic compounds recommended by the present invention for identifying pressed and leached camellia seed oils, including their molecular formulas, retention times, adduct forms, primary and secondary mass spectra, as well as response intensities and primary mass spectral errors. The high response intensities and detailed primary and secondary mass spectrometric data indicate that the compounds can be transferred to triple quadrupole instruments for widespread application.

[0157] Figure 1 The TIC plots for cold-pressed and leached camellia oils from an example of the present invention are shown. The LC elution procedure takes 17 minutes. The TIC plots for the cold-pressed and leached camellia oils show no significant differences in peak elution time or abundance between the two groups, necessitating analysis of the abundance of each glyceride molecule.

[0158] Figure 2 The PCA diagram of cold-pressed camellia oil and leached camellia oil in the embodiment of the present invention is shown in Figure 2. The results show that the TIC curves of the QC samples completely overlap, indicating that the instrument has good stability. The PCA analysis of the lipid components of 8 leached camellia oils and 8 cold-pressed camellia oils shows the following results: Figure 2 As can be seen from the score plot, the QC samples are clustered in a small area, further indicating good instrument stability and good sample data quality. All sample data points are within the 95% confidence interval, and the two groups of sample projections can be clearly separated, indicating significant differences between cold-pressed and leached camellia oils. The data within the two groups are evenly distributed along the PC2 axis, indicating some differences within the groups and representative sample selection. The variance contributions of PC1 and PC2 are 42.5% and 18.7%, respectively, for a cumulative variance contribution of 61.2%.

[0159] Figure 3 This is the OPLS-DA diagram of the cold-pressed camellia oil and the extracted camellia oil according to the embodiment of the present invention. Figure 4It is the VIP diagram of differential compounds. Supervised OPLS-DA was used for discriminant analysis to maximize the differences and highlight key variables and potential markers. Extracted camellia oil and pressed camellia oil clustered into two categories on the OPLS-DA score diagram. The R2Y of the OPLS-DA model is 0.987, Q2 is 0.984, indicating that the explanatory and predictive abilities of the model are excellent. Due to the high dimensionality and small sample size of the data in this study, supervised discriminant models are prone to overfitting. After 1000 permutation tests, the OPLS-DA model had an R2Y of 0.995, a Q2 of 0.993, and p<0.0001. Figure 6 , indicating that the model is excellent without overfitting and can accurately predict cold-pressed camellia oil and leached camellia oil.

[0160] Figure 5 This is a heat map of the difference in compounds between the cold-pressed camellia oil and the leached camellia oil according to an embodiment of the present invention. As can be seen from the heat map, there are obvious differences between the pressed camellia oil and the leached camellia oil. The diglyceride (DG) content in the leached camellia oil is significantly increased, the content of partially oxidized triglycerides is increased, and the content of partially oxidized triglycerides is decreased. The decreased content of oxidized triglycerides is higher in natural camellia oil, and the increased content of oxidized oils is lower in natural camellia oil. Combined with the analysis of the processing technology, the deep refining process goes through the links of degumming, deacidification, decolorization and deodorization. The first three steps will cause the oil to hydrolyze and oxidize, and the oxidized oil will be removed in the deodorization link. Oil hydrolysis produces fatty acids and diglycerides, and oil deodorization reduces the content of oxidized oils. However, because the oxidized oils TG50:1;O, TG54:3;O, TG50:2;O, and TG52:3;O2 are present at high concentrations in natural camellia oil, their removal results in a decrease in content. Other oxidized oils are present at lower concentrations in natural camellia oil, and their removal during processing results in an increase in content. Pressed camellia oil uses a moderately refined process, generally undergoing only degumming and a shorter deodorization period than deep refining.

[0161] Figure 6 to Figure 8 The following is a mass spectrum of differential compounds in cold-pressed camellia oil and leached camellia oil from an example of the present invention. From the XIC graphs of these characteristic compounds, it can be seen that the content of these compounds is far above the detection limit, thus proving the accuracy of this method in annotating characteristic compounds.

[0162] Table 2 shows the predictive ability of the OPLS-DA model.

[0163] Table 2

[0164]

[0165] Hunan Chunxiang Agroforestry Technology Co., Ltd. provided 6 batches of leaching oil-tea camellia seed oil samples, and 6 pressed oil-tea camellia seed oil samples were pressed in the laboratory by using a small-scale pressing equipment to verify the established OPLS-DA model, and the accuracy of the calibration set and the validation set of the model reached 100%, indicating that the method for identifying leaching oil-tea camellia seed oil and pressed oil-tea camellia seed oil by using process-related substances is effective.

[0166] The application is described in detail above in combination with the embodiments, but the application is not limited to the above-described embodiments, and various changes can be made within the knowledge range possessed by those skilled in the art without departing from the purpose of the application.

Claims

1. A pseudo-targeted lipidomics method for identifying cold-pressed camellia oil and leached camellia oil, characterized in that: The following steps are involved: S1: Camellia oil sampling: Prepare cold-pressed camellia oil and extracted camellia oil samples with clear origin and category; S2: Sample pretreatment: Weigh 0.1000 g of each sample and dissolve it in 10 mL of mass spectrometry-grade isopropanol. Dilute 10-fold. After the experimental samples are prepared, take an equal amount of each sample and mix them as quality control samples to monitor the stability and repeatability of the instrument and to optimize the UPLC-Q-TOF-MS conditions. S3: UPLC-Q-TOF-MS analysis; S4: The collected quality control samples were subjected to peak extraction and identification by comparing with the lipid EIEIO database through the software; S5: Data statistical analysis: Submit the identified peak table results to the data processing platform for statistical analysis PCA analysis and OPLS-DA analysis to find the differential lipid components; S6: Confirmation of differential compound structures: Confirm compound structures by primary and secondary mass spectrometry mass number errors, retention time, and isotope abundance; S7: Method validation: The characteristic compounds screened by OPLS-DA were cross-validated 200 times to obtain R2Y and Q2; S8: Sample verification.

2. The targeted lipidomics method according to claim 1, wherein In step S1, there are at least 8 samples of cold-pressed camellia oil and 8 samples of extracted camellia oil.

3. The targeted lipidomics method according to claim 1, wherein In step S3, the liquid phase conditions are: phase A: methanol:acetonitrile:water (1:1:1, V / V / V, containing 5 mM ammonium acetate); Phase B: isopropyl alcohol; The gradient elution program was: 0.0~1.0min, 80%A, 20%B; 1.0~3.0min, 80%~30%A, 20%~70%B; 3.0~13.0min, 30%~2%A, 70%~98%B; 13.0~15.0min, 2%A, 98%B; 15.0~15.1min, 2%~80%A, 98%~20%B; 15.1~17.0min, 80%A, 20%B; The flow rate was 0.3 mL / min, the sample plate temperature was 4 °C, the column temperature was 45 °C, and the injection volume was 1 μL.

4. The targeted lipidomics method according to claim 1, wherein In step S3, the lipid compounds were chromatographed using an ExionL C (Sciex) ultra-high performance liquid chromatograph using a Phenomen Kinetex C18 (2.1×100 mm, 1.7 μm) liquid chromatography column.

5. The targeted lipidomics method according to claim 1, wherein In step S3, the high-resolution mass spectrometry conditions are as follows: using a Sciex Zeno TOF™ 7600 high-resolution mass spectrometer to acquire high-resolution mass spectrometry data in information-dependent acquisition (IDA) mode.

6. The targeted lipidomics method according to claim 1, wherein In step S3, in IDA mode, primary mass spectrometry and secondary mass spectrometry data were collected by data acquisition software (OS3.0, Sciex), which automatically selected ions and collected their secondary mass spectrometry information; In each cycle, the 20 ions with the strongest response were selected for secondary mass spectrometry scanning. The energy of collision-induced dissociation was 45 eV, and the accumulation time of each secondary mass spectrum was 50 ms.

7. The targeted lipidomics method according to claim 1, wherein In step S3, the EAD conditions are as follows: the ion source temperature is set to a value between 500°C and 650°C, GS1: 50psi, GS2: 50psi, CUR: 30Ppsi, DP: 80V, ISVF: 6000V, the electron kinetic energy (KE) is set to a value between 10eV and 15eV during the entire study process, and the electron beam current is 6000nA.

8. The targeted lipidomics method according to claim 1, wherein In step S4, the rules for the qualitative analysis of the extracted identified compounds and the identification results are: mass number deviation <5 ppm, isotope abundance ratio deviation <20%.

9. The targeted lipidomics method according to claim 1, wherein In step S4, the rules for extracting the identified compounds and the qualitative analysis of the identification results also include: a secondary spectrum matching score > 70, and a retention time window set to 0.4 min.

10. The targeted lipidomics method according to claim 1, wherein In step S5, the screening rules for differential lipid components are: p value < 0.05; fold change > 1.5; VIP value > 1.2.

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