Method for determining odor deterioration and lipid oxidation degree of tilapia during cold storage

Abstract

To provide a method for determining odor of fish, especially odor deterioration and lipid oxidation degree of tilapia during cold storage.SOLUTION: The method includes the steps of: killing fresh tilapia, slicing, washing, mixing and grinding the fish meat to obtain raw materials; extracting lipids from the raw materials; dividing the obtained lipids and storing them under low-temperature conditions, and after storage, measuring the lipid oxidation degree and lipid metabolic data of tilapia at different refrigeration times using lipid metabolomics technology; constructing an odor-related lipid metabolic network and analyzing the lipid oxidation degree and metabolic data at different refrigeration times based on the lipid metabolic network to obtain metabolic markers corresponding to multiple lipids; screening the obtained metabolic markers to obtain evaluation metabolic markers; and analyzing the oxidation degree and metabolic status of multiple lipids based on the evaluation metabolic markers corresponding to multiple lipids.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to the technical field of research into fish odor, and more particularly to a method for determining the degree of odor deterioration and lipid oxidation of tilapia during refrigeration. [Background technology]

[0002] Tilapia is one of the most popular fish species, known for its rapid growth, delicious taste, and diverse nutrient content. Fresh tilapia fish has a high water content and is susceptible to spoilage due to the influence of microorganisms and tissue enzymes. Therefore, it is usually stored at low temperatures. However, with increasing refrigeration time, product quality gradually deteriorates, resulting in the development of odor, which significantly affects the production, processing, and application of tilapia. Research into the odor of tilapia during refrigeration has great application value. Changes in odor are primarily related to volatile compounds, which can be generated through various biochemical processes, such as lipid oxidation, proteolysis, and microbial action. Lipid oxidation, in particular, is widely considered to be the key to forming characteristic odors. Lipid oxidation is a complex reaction primarily involving the oxidation of free fatty acids (FFAs) and the effects of radicals. As important flavor precursors, different types of FFAs also contribute to different product odors. Currently, there is a lack of research related to odor, limiting the assessment and screening of fish quality and odor deterioration. Summary of the Invention

[0003] In order to solve the above technical problems existing in the prior art, the present invention provides a method for determining the degree of odor deterioration and lipid oxidation of tilapia during refrigeration.

[0004] To achieve the above object, the embodiments of the present invention provide the following technical solutions. In a first aspect, in one embodiment of the present invention, there is provided a method for determining the degree of odor deterioration and lipid oxidation of tilapia during refrigeration, comprising: Killing fresh tilapia, taking tilapia slices, washing them, wiping off the surface moisture, and mixing and grinding the fish meat to obtain raw materials; A step of extracting lipids from the fish meat obtained by processing the raw material; The obtained lipid is divided into a plurality of parts and stored under low temperature conditions, each of which is stored for a predetermined refrigeration time. After the storage is completed, the lipid oxidation degree and lipid metabolism data of tilapia with different refrigeration times are measured using lipid metabolomics technology based on LC-MS; By combining the KEGG metabolic pathway and the MetPA database, a lipid metabolic network related to odor was constructed. The lipid metabolic data of tilapia with different refrigeration times was analyzed based on the lipid metabolic network to obtain metabolic markers corresponding to multiple required lipids. The lipid metabolic data includes steps including metabolites and metabolic pathways. Screening the obtained metabolic markers to obtain evaluation metabolic markers, where the screening criteria for metabolic markers are p-value≦0.05 and VIP≧1; Analyzing the oxidation degree and metabolic status of a plurality of lipids based on the evaluation metabolic markers corresponding to the plurality of lipids; A method is provided that includes:

[0005] In a further embodiment of the present invention, the step of killing fresh tilapia, taking tilapia slices, washing, wiping off surface moisture, and mixing and grinding the fish meat to obtain raw materials comprises: Fresh tilapia of approximately the same size and weight were selected and promptly transported to the laboratory in a foam box filled with crushed ice and oxygen. The tilapia were then stunned and killed by physical beating, after which the head and organs were removed, the tilapia slices were taken, washed, the surface moisture was wiped off, and the fish meat was mixed and ground.

[0006] In a further embodiment of the present invention, the step of extracting lipids from the fish meat obtained by processing the raw material comprises: 5g of homogenized fish meat was placed in a 50mL centrifuge tube, and 15mL of chloroform / methanol containing butylhydroxytoluene at a concentration of 0.01g / 100g was added, where the volume ratio of chloroform / methanol was 2:1; Seal the tube with a plug and centrifuge it twice at 10,000 x g in an ice bath, lasting 10 seconds, 13 seconds, 15 seconds, or 20 seconds. The volume is adjusted to 30 mL, and the mixture is allowed to stand for 45 minutes, 55 minutes, 65 minutes, 65 minutes, or 75 minutes, and then filtered to obtain a first filtrate. Add 0.2 volumes of salt water with a concentration of 0.85 g / 100 g to the first filtrate, and centrifuge at 3000 × g for 10 minutes, 12 minutes, 15 minutes, 17 minutes or 20 minutes. Dry the bottom layer solution under the action of nitrogen gas to obtain a lipid extract. To the first filtrate, 0.2 volumes of saline solution with a concentration of 0.85 g / 100 g is added, and the mixture is centrifuged at 3000×g for 15 minutes. The bottom layer solution is dried under a nitrogen stream to obtain a lipid extract.

[0007] In a further embodiment of the present invention, the obtained lipid is divided into a plurality of portions, stored under low temperature conditions, and each portion is stored for a predetermined refrigeration time. After the storage is completed, the lipid oxidation degree and lipid metabolism data of the tilapia with different refrigeration times are measured by lipid metabolomics technology based on LC-MS. The obtained lipid extract was divided into four portions and stored at 4°C for 0, 3, 9 and 15 days, respectively.

[0008] In a further embodiment of the present invention, the method for testing lipid metabolomics technology comprises: Fill a 2 mL centrifuge tube with 0.5 mL of sample, add 600 μL of methanol containing 4-chloro-L-phenylalanine, and vortex the mixture for 30 seconds, where the 4-chloro-L-phenylalanine has a concentration of 4 ppm and is kept at −20° C.; bead-milling using a tissue grinder containing 100 mg glass beads at 60 Hz for 90 seconds; Centrifuging the sample at 12,000 x g for 10 minutes at 4°C, followed by sonication at ambient temperature for 10 minutes, and then filtering the supernatant through a 0.22 μm membrane to obtain a second filtrate; Putting the second filtrate into a measuring bottle, and then subjecting the second filtrate to liquid chromatography analysis and chromatography treatment; Includes.

[0009] In a further embodiment of the present invention, the step of analyzing the metabolic status of a plurality of lipids based on the evaluating metabolic markers corresponding to the plurality of lipids comprises: Three samples were randomly selected as parallel groups on days 0, 3, 9 and 15, respectively, and the lipid oxidation level and lipid metabolism status of the samples were analyzed.

[0010] In a further embodiment of the invention, the assessed metabolic markers comprise 1-cetyl alcohol, 1-monopalmitic acid ester, 10-heptadecenoic acid, 13-docosenoic acid amide, 5,8,11-eicosatrienoic acid, 7,10,13,16,19-docosapentaenoic acid, 9-octadecenoic acid, 9,12-octadecadienoic acid, arachidonic acid, ethyl 4-ethoxybenzoate, brassinosteroids, dibutyl phthalate, glycerol monostearate, heptadecanoic acid, myristic acid, oleic acid, palmitoleic acid, and palmitic acid.

[0011] The technical means of the present invention have the following beneficial effects: In the present invention, a lipid extract is extracted from tilapia, and the lipid extract is stored in a refrigerated environment for a certain number of days. Then, a lipid metabolic network related to the odor of tilapia is constructed by analysis using lipid metabolomics technology, and evaluation metabolic markers are obtained by screening. The degree of lipid oxidation and deterioration of odor quality are determined based on the content of these markers.

[0012] In the present invention, a lipid metabolism network diagram related to odor is constructed, lipid metabolism is associated with odor deterioration, and the state of odor deterioration is determined by screening metabolic markers. Therefore, the present invention is a method with high research value and provides new ideas for controlling lipid oxidation and reducing the occurrence of unpleasant odors.

[0013] These and other aspects of the present invention will be more clearly understood and appreciated by the following examples. It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. [Brief explanation of the drawings]

[0014] In order to describe the embodiments of the present invention or the technical means in the prior art, the following briefly introduces drawings necessary for describing the embodiments or the prior art. It is clear that the following drawings are some embodiments of the present invention, and those skilled in the art can obtain other embodiments based on these drawings without creative efforts. [Figure 1] 1 is a flowchart of a method for determining the degree of odor deterioration and lipid oxidation of tilapia during refrigeration according to an embodiment of the present invention. [Figure 2] 1 is a detailed flowchart of step S20 in a method for determining the degree of odor deterioration and lipid oxidation of tilapia during refrigeration according to an embodiment of the present invention. [Figure 3] FIG. 1 is a diagram of a lipid metabolic network and related metabolic pathways according to one embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0015] The technical means in the embodiments of the present invention will be described clearly and completely below with reference to the drawings in the embodiments of the present invention. It is obvious that the following embodiments are only a part of the embodiments of the present invention, but are not all of the embodiments. Based on the embodiments of the present invention, any other embodiments that can be obtained by those skilled in the art without creative efforts are all included in the protection scope of the present invention.

[0016] The flowcharts shown in the drawings are merely illustrative and do not necessarily include all contents and operations / steps, or are not necessarily performed according to the procedures shown. For example, some operations / steps may be further divided, combined, or partially merged. Therefore, the actual execution procedures may vary depending on the case.

[0017] It should be noted that the terms used in this specification are not intended to limit the present invention, but are used for the purpose of describing specific embodiments. As used in this specification and the appended claims, the singular forms "a," "an," and "the" include the plural forms unless the context clearly dictates otherwise.

[0018] More specifically, the embodiments of the present invention will be further described below with reference to the drawings.

[0019] 1 is a flowchart of a method for determining the degree of odor deterioration and lipid oxidation of tilapia during refrigeration according to an embodiment of the present invention. As shown in FIG. 1, the method for determining the degree of odor deterioration and lipid oxidation of tilapia during refrigeration includes steps S10 to S60.

[0020] S10: Kill the fresh tilapia, take the tilapia slices, wash them, wipe off the surface moisture, mix and grind the fish meat to obtain the raw material.

[0021] In an embodiment of the present invention, the step of S10: killing fresh tilapia, taking tilapia slices, washing them, wiping off the surface moisture, and mixing and grinding the fish meat to obtain raw materials includes the following steps: Fresh tilapia were purchased from the Luchaogang Seafood Wholesale Market in the Pudong New District of Shanghai. Tilapia with shiny scales, clear gill filaments, bright red gills, clear mucus on the body surface and in the gills, no unpleasant odor, and approximately the same size and weight were selected and promptly transported to the laboratory in a foam box filled with crushed ice and oxygen. The tilapia were then physically stunned and killed by beating, after which the heads and organs were removed. The tilapia slices were then taken, washed, wiped dry, and the flesh mixed and broken, and stored for further experiments.

[0022] S20: Lipids are extracted from the fish meat obtained by processing the raw material.

[0023] As shown in FIG. 2, in an embodiment of the present invention, the step of S20: extracting lipids from fish meat obtained by processing raw materials includes: S201: 5g of homogenized fish meat is placed in a 50mL centrifuge tube, and 15mL of chloroform / methanol containing butylhydroxytoluene at a concentration of 0.01g / 100g is added, where the volume ratio of chloroform / methanol is 2:1; S202: Seal the centrifuge tube with a plug and centrifuge it twice at a speed of 10,000 × g in an ice bath, lasting for 10 seconds, 13 seconds, 15 seconds or 20 seconds; S203: Adjusting the volume to 30 mL, leaving it for 45 minutes, 55 minutes, 65 minutes, 65 minutes or 75 minutes, and then filtering to obtain a first filtrate; S204: Add 0.2 times the volume of the first filtrate to a salt solution having a concentration of 0.85 g / 100 g, and centrifuge at 3000 × g for 10 minutes, 12 minutes, 15 minutes, 17 minutes or 20 minutes, and dry the bottom layer solution under the action of nitrogen gas to obtain a lipid extract; Includes.

[0024] S30: The obtained lipids are divided into several portions and stored under low-temperature conditions, each for a specific refrigeration time. After storage, the lipid oxidation degree and lipid metabolism data of tilapia with different refrigeration times are measured using LC-MS-based lipid metabolomics technology.

[0025] LC-MS stands for liquid chromatograph mass spectrometer. The low temperature condition may be 0°C, 2°C, 4°C, 6°C, or 8°C.

[0026] The step of S30: dividing the obtained lipid into a plurality of parts, storing them under low-temperature conditions, and storing each part for a specific refrigeration time, and measuring the degree of lipid oxidation and lipid metabolism data of tilapia with different refrigeration times by LC-MS-based lipid metabolomics technology after storage is completed. The obtained lipid extract was divided into four portions and stored at 4°C for 0, 3, 9 and 15 days, respectively.

[0027] In an embodiment of the present invention, the lipid metabolomics technology testing method includes: Filling a 2 mL centrifuge tube with 0.5 mL of sample, adding 600 μL of methanol containing 4-chloro-L-phenylalanine (4 ppm, kept at −20° C.), and vortexing the mixture for 25 seconds, 28 seconds, 30 seconds, 33 seconds, or 35 seconds; Grinding the tissue with a 100 mg glass bead-containing tissue grinder at 60 Hz for 80 seconds, 85 seconds, 90 seconds, 95 seconds, or 100 seconds; Centrifuging the sample at 12,000×g for 10 minutes at 4° C., followed by sonication at ambient temperature for 7, 8, 10, 12, or 13 minutes, and then filtering the supernatant through a 0.22 μm membrane to obtain a second filtrate; performing LC-MS detection; Includes. For LC-MS detection, the second filtrate was placed in a measuring vial. Liquid chromatography analysis was performed using an Ultimate 3000U HPLC system (Thermo Fisher Scientific), and total ion chromatograms and metabolic data were acquired and calculated using various analytical methods. Chromatography was performed using an ACQUITY UPLC® HSST3 (150 × 2.1 mm, 1.8 μm) (Waters, Milford, MA, USA). The column was maintained at 40 °C. The injection volume and flow rate were calibrated to 2 μL and 0.25 mL / min, respectively. A 0.1% formic acid solution in acetonitrile (v / v) (C) and a 0.1% formic acid solution in water (v / v) (D) were used as the mobile phases for LC-ESI(+)-MS analysis. The analytes used for LC-ESI(-)-MS analysis were acetonitrile (A) and aqueous ammonium formate (5 mM) (B). Metabolites were detected by mass spectrometry using an ESI ion source and a QExactive (ThermoFisher Scientific, USA). Data-dependent MS / MS and synchronized MS1 and MS / MS (all MS-ddMS2 modes) were used for acquisition. The parameters were capillary temperature: 325 °C, MS1 range: m / z 100–1000, MS1 resolution: 70,000 FWHM, number of data-dependent scans per cycle: 10, MS / MS resolution: 17,500 FWHM, and normalized collision energy: 30%.

[0028] S40: Combining the KEGG metabolic pathway and the MetPA database, we constructed a lipid metabolic network related to odor. Based on this network, we analyzed lipid metabolic data of tilapia samples stored for different periods of time and obtained metabolic markers corresponding to the required lipids. The lipid metabolic data included metabolites and metabolic pathways.

[0029] KEGG is an integrated database of genomic, chemical, and system function information, each containing a wealth of useful information. Genomic information is stored in the GENEES database, including complete and partial genome sequences. More advanced functional information is stored in the PATHWAY database, which contains graphed cellular biochemical processes, such as metabolism, membrane transport, signal transduction, cell cycle, and cognate conservative subpathways. Another KEGG database is LIGAND, which contains information on chemicals, enzyme molecules, and enzymatic reactions. KEGG's integrated metabolic pathway queries include the metabolism of carbohydrates, nucleosides, amino acids, and other substances, as well as the biodegradation of organic compounds. They provide comprehensive annotations of all possible metabolic pathways, as well as the enzymes catalyzing each step, including amino acid sequences and PDB library links. KEGG is a powerful tool for in vivo metabolic analysis and metabolic network research, helping researchers study genes and their expression information as a holistic network. MetPA is a part of metaboanalysis and is primarily based on KEGG metabolic pathways. The MetPA database uses metabolic pathway enrichment and topology analysis to identify metabolic pathways that may be affected by biological disturbances and analyze metabolic pathways of metabolites. The MetPA database can be used to analyze the related metabolic pathways of differential metabolites. The data analysis algorithm used is the hypergeometric test, and the metabolic pathway topology structure employs relative-betweenness centrality. By combining KEGG metabolic pathways with MetPA, a lipid metabolic network related to odor can be constructed.The metabolic marker spectra identified through screening are entered into the MetPA dialog, the compound name is selected in the Input tag, and then Submit is clicked. The species is then selected, and the hypergeometric distribution test, pathway topology analysis, and relative-betweenness centrality are applied. The data are then registered and a path model analysis is performed. Signal path analysis is performed using the KEGG database, and the metabolic pathways are visualized and plotted using the Interactive Pathways Explorer. This method differs from other analyses in that, first, the target of analysis is different. This study is the first in this field to perform metabolic analysis using lipid extracts alone, eliminating interference from other factors and resulting in more reliable analytical results. Second, the metabolic database on which the analysis is based is different. Conventional databases are analyzed based on the KEGG database, but in this study, topological analysis is performed using the MetPA database based on the KEGG database to identify the metabolic pathways related to this study, and the data and metabolic model are analyzed using hypergeometric validation and relative-betweenness centrality, and the metabolic network is visualized and plotted using the Interactive Pathways Explorer visualization pathway online analysis tool.

[0030] S50: The obtained metabolic markers are screened to obtain evaluation metabolic markers. Here, the screening criteria for metabolic markers are p-value≦0.05 and VIP≧1. (The p-value is the probability that a result more extreme than the obtained sample observation result will appear if the null hypothesis is true, and is a parameter for determining the hypothesis test result. The p-value is a significance level calculated based on actual statistics, and the VIP value is an index for evaluating the importance of variables to the model. It describes the overall contribution of each variable to the model, evaluates the strength of influence and interpretability on the classification and discrimination of each group sample based on the expression pattern of each metabolite, and is useful for discovering differential metabolites with biological significance.)

[0031] Variables with a VIP value greater than 1 are considered candidate biomarkers. A T-test is used to verify whether the candidate variables found through multidimensional statistics have statistically significant differences in units, with a P value of <0.05 indicating a significant difference. By combining the weight map and screening of candidate variables, and using the mass spectral information of compounds represented by these variables, search, matching, and inference are performed in databases such as METLIN, KEGG, and PubChem to ultimately identify potential biomarkers. As a result of screening under the above conditions, the following metabolic markers were obtained: 1-cetyl alcohol, 1-monopalmitic acid ester, 10-heptadecenoic acid, 13-docosenoic acid amide, 5,8,11-eicosatrienoic acid, 7,10,13,16,19-docosapentaenoic acid, 9-octadecenoic acid, 9,12-octadecadienoic acid, arachidonic acid, ethyl 4-ethoxybenzoate, brassinosteroids, dibutyl phthalate, glycerin monostearate, heptadecanoic acid, myristic acid, oleic acid, palmitoleic acid, and palmitic acid.

[0032] S60: Analyzing the metabolic status of a plurality of lipids based on the evaluated metabolic markers corresponding to the plurality of lipids.

[0033] In an embodiment of the present invention, the step of analyzing the metabolic status of a plurality of lipids based on the evaluating metabolic markers corresponding to the plurality of lipids (S60) includes: Three samples were randomly selected as parallel groups on days 0, 3, 9 and 15, respectively, to analyze the lipid oxidation level and lipid metabolism status of the samples.

[0034] In this study, lipid extracts were extracted from tilapia and stored in a refrigerated environment at 4°C for 15 days. A lipid metabolic network associated with tilapia odor was constructed using lipid metabolomics analysis. Eighteen metabolic markers were then screened (including 1-cetyl alcohol, 1-monopalmitic acid ester, 10-heptadecenoic acid, 13-docosenoic acid amide, 5,8,11-eicosatrienoic acid, 7,10,13,16,19-docosapentaenoic acid, 9-octadecenoic acid, 9,12-octadecadienoic acid, arachidonic acid, 4-ethoxybenzoic acid ethyl ester, brassinosteroids, dibutyl phthalate, glycerol monostearate, heptadecanoic acid, myristic acid, oleic acid, palmitoleic acid, and palmitic acid). The levels of these markers were used to assess the degree of lipid oxidation and deterioration of odor quality.

[0035] In the present invention, a lipid metabolism network diagram related to odor is constructed, lipid metabolism is associated with odor deterioration, and the state of odor deterioration is determined by screening metabolic markers. Therefore, the present invention is a method with high research value and provides new ideas for controlling lipid oxidation and reducing the occurrence of unpleasant odors.

[0036] Table 1: Metabolic markers identified by lipid metabolomics analysis [Table 1]

[0037] It should be understood that although the above is described in a certain order, the steps are not necessarily performed sequentially in the above order. Unless explicitly stated otherwise in this specification, the execution of the steps is not limited to a strict order, and the steps may be performed in other orders. In addition, some steps in this embodiment may include multiple steps or multiple stages, and these steps or stages do not necessarily have to be completed at the same time but can be performed at different times. The order in which these steps or stages are performed does not necessarily have to be sequential, and they can be performed sequentially or alternately with other steps or at least some of the steps or stages in other steps.

[0038] As used herein, it should be understood that the singular form "one" is intended to include the plural form unless the context clearly supports otherwise. It should be further understood that "and / or," as used herein, means including any and all possible combinations of one or more of the associated listed items. The example numbers disclosed in the above examples of the present invention are for illustrative purposes only and do not indicate the relative merits of the examples.

[0039] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to suggest that the scope of the disclosed embodiments of the present invention (including the scope of the claims) is limited to these examples. Under the concept of the embodiments of the present invention, the technical features of the above embodiments or different embodiments may be combined. In addition, there are many other variations in different aspects of the above embodiments of the present invention, which are not provided in detail for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the embodiments of the present invention should be included within the protection scope of the embodiments of the present invention.

Claims

1. A method for determining the degree of odor deterioration and lipid oxidation of tilapia during refrigeration, Killing fresh tilapia, taking tilapia slices, washing them, wiping off the surface moisture, and mixing and grinding the fish meat to obtain raw materials; A step of extracting lipids from the fish meat obtained by processing the raw material; The obtained lipid is divided into a plurality of portions and stored under low temperature conditions, each portion being stored for a predetermined refrigeration time. After the storage is completed, the lipid oxidation degree and lipid metabolism data of the tilapia with different refrigeration times are measured by lipid metabolomics technology based on LC-MS; By combining the KEGG metabolic pathway and the MetPA database, a lipid metabolic network related to odor is constructed, and the lipid metabolic data of tilapia with different refrigeration times is analyzed based on the lipid metabolic network to obtain metabolic markers corresponding to multiple required lipids, where the lipid metabolic data includes metabolites and metabolic pathways; Screening the obtained metabolic markers to obtain evaluation metabolic markers, where the screening criteria for metabolic markers are p-value≦0.05 and VIP≧1; Analyzing the metabolic status of a plurality of lipids based on the evaluated metabolic markers corresponding to the plurality of lipids; A method comprising:

2. The steps to obtain raw materials are to kill fresh tilapia, take tilapia slices, wash them, wipe off the surface moisture, mix and grind the fish meat, The method according to claim 1, characterized in that it comprises: selecting fresh tilapia of approximately the same size and weight, transporting them quickly to the laboratory in a foam box under crushed ice and oxygen-filled conditions, then physically striking and killing the tilapia, removing the head and organs, taking tilapia slices, washing them, wiping off the surface moisture, and mixing and grinding the fish meat.

3. The step of extracting lipids from the fish meat obtained by processing the raw material includes: 5 g of homogenized fish meat is placed in a 50 mL centrifuge tube, and 15 mL of chloroform / methanol containing butylhydroxytoluene at a concentration of 0.01 g / 100 g is added, where the volume ratio of chloroform / methanol is 2:1; Seal the tube with a plug and centrifuge twice in an ice bath at 10,000 x g for 10 seconds, 13 seconds, 15 seconds or 20 seconds; adjusting the volume to 30 mL, allowing the solution to stand for 45 minutes, 55 minutes, 65 minutes, 65 minutes, or 75 minutes, and then filtering the solution to obtain a first filtrate; Add 0.2 volumes of salt water with a concentration of 0.85 g / 100 g to the first filtrate, and centrifuge at 3000 × g for 10 minutes, 12 minutes, 15 minutes, 17 minutes or 20 minutes, and dry the bottom layer solution under the action of nitrogen gas to obtain a lipid extract; 2. The method of claim 1, comprising:

4. The obtained lipid is divided into a plurality of parts, stored under low temperature conditions, each of which is stored for a predetermined refrigeration time, and after the storage is completed, the lipid oxidation degree and lipid metabolism data of the tilapia with different refrigeration times are measured by lipid metabolomics technology based on LC-MS.

2. The method according to claim 1, characterized in that the obtained lipid extract is divided into four portions and stored at 4°C for 0 days, 3 days, 9 days and 15 days, respectively.

5. The lipid metabolomics technology testing method is Loading 0.5 mL of sample into a 2 mL centrifuge tube, adding 600 μL of methanol containing 4-chloro-L-phenylalanine, and vortexing the mixture for 30 seconds, wherein the 4-chloro-L-phenylalanine has a concentration of 4 ppm and is kept at −20° C.; grinding using a tissue grinder containing 100 mg glass beads at 60 Hz for 90 seconds; Centrifuging the sample at 12,000×g for 10 minutes at 4° C., followed by sonication at ambient temperature for 10 minutes, and then filtering the supernatant through a 0.22 μm membrane to obtain a second filtrate; Putting the second filtrate into a measuring bottle, and then subjecting the second filtrate to liquid chromatography analysis and chromatography treatment; 2. The method of claim 1, comprising:

6. The step of analyzing the metabolic status of the plurality of lipids based on the evaluated metabolic markers corresponding to the plurality of lipids includes: The method of claim 1, characterized in that it comprises randomly selecting three samples as parallel groups on days 0, 3, 9 and 15, respectively, and analyzing the degree of lipid oxidation and lipid metabolic status of the samples.

7. 2. The method of claim 1, wherein the metabolic markers evaluated include 1-cetyl alcohol, 1-monopalmitic acid ester, 10-heptadecenoic acid, 13-docosenoic acid amide, 5,8,11-eicosatrienoic acid, 7,10,13,16,19-docosapentaenoic acid, 9-octadecenoic acid, 9,12-octadecadienoic acid, arachidonic acid, ethyl 4-ethoxybenzoate, brassinosteroids, dibutyl phthalate, glycerol monostearate, heptadecanoic acid, myristic acid, oleic acid, palmitoleic acid, and palmitic acid.

Images