Method for Judging Odor Deterioration and Degree of Lipid Oxidation of Tilapia during Refrigeration Period

Abstract

、To provide a method for determining the smell of fish, especially the degree of smell deterioration and lipid oxidation of tilapia during the refrigeration period. 【Solution means】Steps of obtaining raw materials by killing fresh tilapia, taking slices, washing, and mixing and grinding the fish meat; steps of extracting lipids from the raw materials; steps of dividing the obtained lipids, storing them under low-temperature conditions, and measuring the degree of lipid oxidation and lipid metabolism data of tilapia at different refrigeration times by lipid metabolomics technology after the storage ends; steps of constructing a lipid metabolism network related to smell and analyzing the degree of lipid oxidation and metabolism data at different refrigeration times based on the lipid metabolism network to obtain metabolic markers corresponding to a plurality of lipids; steps of screening the obtained metabolic markers to obtain evaluation metabolic markers; steps of analyzing the degree of lipid oxidation and metabolic status of a plurality of lipids based on the evaluation metabolic markers corresponding to the plurality of lipids.

Description

Technical Field

[0001] The present invention relates to the technical field of research on the smell of fish, and particularly to a method for judging the smell deterioration and lipid oxidation degree of tilapia during the refrigeration period.

Background Art

[0002] Tilapia is famous for its fast growth and delicious taste. It contains various nutrients and is one of the most popular fish. Fresh tilapia has a high water content and is easily deteriorated under the influence of microorganisms and tissue enzymes, and is usually stored at low temperature. However, with the increase of refrigeration time, the quality of the product gradually deteriorates, and with the generation of odor, it greatly affects the production, processing and application of tilapia. The research on the smell of tilapia during the refrigeration process has high application value. The change of smell is mainly related to volatile compounds, and these compounds can be generated in many biochemical processes such as lipid oxidation, proteolysis and microbial action. In particular, lipid oxidation is widely considered as the key to form characteristic smell. Lipid oxidation is a complex reaction, mainly related to the oxidation of free fatty acids (FFAs) and the influence of radicals. As an important flavor precursor, the type of FFAs also contributes to the different smells of products. At present, there is a lack of research related to smell, and the judgment and screening of the quality and smell deterioration of fish are limited.

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 judging the smell deterioration and lipid oxidation degree of tilapia during the refrigeration period.

[0004] To achieve the above object, the embodiments of the present invention provide the following technical means. In a first aspect, in an embodiment of the present invention, a method for judging the smell deterioration and lipid oxidation degree of tilapia during the refrigeration period, comprising: Steps to obtain raw materials by killing fresh tilapia, taking tilapia slices, washing them, wiping off the surface moisture, and mixing and grinding the fish meat; Steps to extract lipids from the fish meat obtained by processing the raw materials; Steps to divide the obtained lipids into multiple portions, store them under low-temperature conditions, store each portion for a predetermined refrigeration time, and measure the lipid oxidation degree and lipid metabolism data of tilapia at different refrigeration times by lipid metabolomics technology based on LC-MS after the storage ends; Steps to construct a lipid metabolism network related to smell by combining the KEGG metabolic pathway and the MetPA database, and analyze the lipid metabolism data of tilapia at different refrigeration times based on the lipid metabolism network to obtain metabolic markers corresponding to a plurality of required lipids. Here, the lipid metabolism data includes metabolites and metabolic pathways; Steps to screen the obtained metabolic markers to obtain evaluation metabolic markers. Here, the screening criteria for the metabolic markers are p-value ≤ 0.05 and VIP ≥ 1; Steps to analyze 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 including the above is provided.

[0005] In a further embodiment of the present invention, the steps to obtain raw materials by killing fresh tilapia, taking tilapia slices, washing them, wiping off the surface moisture, and mixing and grinding the fish meat include: Selecting fresh tilapia with substantially the same size and weight, putting them into a foam box, quickly transporting them to the laboratory under the conditions of crushed ice and oxygen filling, then stunning the tilapia by physically hitting, killing them, removing the head and organs, taking tilapia slices, washing them, wiping off the surface moisture, and mixing and grinding the fish meat.

[0006] In a further embodiment of the present invention, the steps to extract lipids from the fish meat obtained by processing the raw materials include the following, that is: Put 50 mL of homogeneous fish meat into a centrifuge tube, and add 15 mL of chloroform / methanol containing 0.01 g / 100 g of butylhydroxytoluene, where the volume ratio of chloroform / methanol is 2:1. Seal the centrifuge tube with a plug, and centrifuge twice in an ice bath at a speed of 10,000×g for 10 seconds, 13 seconds, 15 seconds or 20 seconds. Make up the volume to 30 mL, let it stand for 45 min, 55 min, 65 min, 65 min or 75 min, and then filter to obtain the first filtrate. Add 0.2 times the volume of brine with a concentration of 0.85 g / 100 g to the first filtrate, centrifuge at 3000×g for 10 min, 12 min, 15 min, 17 min or 20 min, and dry the bottom layer solution under a nitrogen stream to obtain a lipid extract. Add 0.2 times the volume of brine with a concentration of 0.85 g / 100 g to the first filtrate, centrifuge at 3000×g for 15 min, and dry the bottom layer solution under a nitrogen stream to obtain a lipid extract.

[0007] In a further embodiment of the present invention, the steps of dividing the obtained lipid into multiple portions, storing it under low temperature conditions, storing it for a predetermined refrigeration time respectively, and measuring the lipid oxidation degree and lipid metabolism data of tilapia at different refrigeration times by lipid metabolomics technology based on LC-MS after the storage are as follows: Include dividing the obtained lipid extract into four portions, storing it under the condition of 4°C, and storing it for 0 days, 3 days, 9 days and 15 days respectively.

[0008] In a further embodiment of the present invention, the test method of lipid metabolomics technology is as follows: Fill 0.5 mL of sample into a 2 mL centrifuge tube, add 600 μL of methanol containing 4-chloro-L-phenylalanine, vortex the mixture for 30 seconds, where the concentration of 4-chloro-L-phenylalanine is 4 ppm and it is kept at -20°C. Use a tissue grinder containing 100 mg of glass beads to grind the beads at 60 Hz for 90 seconds. After centrifuging the sample at 4°C and 12,000×g for 10 minutes, sonicating it for 10 minutes at ambient temperature, and filtering the supernatant through a 0.22-μm membrane to obtain a second filtrate; Placing the second filtrate into a measuring flask, and then performing liquid chromatography analysis and chromatographic processing on the second filtrate; including.

[0009] In a further embodiment of the present invention, the step of analyzing the metabolic states of a plurality of lipids based on evaluation metabolic markers corresponding to the plurality of lipids includes randomly selecting three samples as a parallel group on days 0, 3, 9, and 15 respectively, and analyzing the degree of lipid oxidation and the lipid metabolism status of the samples.

[0010] In a further embodiment of the present invention, the evaluation metabolic markers include 1-cetyl alcohol, 1-monopalmitate, 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, brassinosteroid, dibutyl phthalate, glycerin 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, the lipid extract of tilapia is extracted, the lipid extract is stored in a refrigerated environment for a specific number of days, and then a lipid metabolism network related to the smell of tilapia is constructed by analysis using lipid metabolomics technology, screened to obtain evaluation metabolic markers, and the degree of lipid oxidation and the deterioration of smell quality are judged based on the contents of these markers.

[0012] In the present invention, in order to construct a lipid metabolism network diagram related to smell, associate lipid metabolism with smell deterioration, and determine the deterioration status of smell by screening metabolic markers, the present invention is a method with high research value, and provides new ideas for the control of lipid oxidation and the reduction of the generation of bad smell.

[0013] These aspects or other aspects of the present invention will become clearer and easier to understand by the following examples. As can be understood, the above general description and the following detailed description are merely illustrative and interpretive, and do not limit the present invention.

Brief Description of the Drawings

[0014] To describe the technical means in the embodiments of the present invention or the prior art, the drawings necessary for the description of the embodiments or the prior art will be briefly introduced below. Obviously, 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

Figure 2

Figure 3

Modes for Carrying Out the Invention

[0015] Hereinafter, the technical means in the embodiments of the present invention will be clearly and completely described with reference to the drawings in the embodiments of the present invention. Obviously, the following embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts are included in the protection scope of the present invention.

[0016] The flowcharts shown in the drawings are merely exemplary and do not necessarily include all contents and operations / steps, nor are they necessarily executed 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 circumstances.

[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 explaining specific embodiments. As used in this specification and the appended claims, the singular forms "a", "an", and "the" shall include the plural forms unless the context clearly dictates otherwise.

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

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

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

[0021] In an embodiment of the present invention, the step of S10: Kill fresh tilapia, take tilapia slices, wash them, wipe off the surface moisture, mix the fish meat and grind it to obtain raw materials includes the following. That is, The fresh tilapia was purchased from the Luchaogang Wholesale Seafood Market in the Pudong New Area of Shanghai. Select tilapia with shiny scales, distinct gill filaments, bright red gills, transparent mucus on the body surface and inside the gills, no strange smell, and similar size and weight. Put it in a foam box and quickly transport it to the laboratory under the conditions of crushed ice and oxygen filling. Then, stun the tilapia by physically hitting it, and after killing it, remove the head and organs. Take tilapia slices, wash them, wipe off the surface moisture, mix and break the fish meat, and store it for subsequent experiments.

[0022] S20: Extract lipids from the fish meat obtained by processing the raw materials.

[0023] As shown in Figure 2, in the embodiment of the present invention, the step of S20: extracting lipids from the fish meat obtained by processing the raw materials is as follows: S201: Put 5 g of homogeneous fish meat into a 50 mL centrifuge tube, add 15 mL of chloroform / methanol containing 0.01 g / 100 g of butylhydroxytoluene, where the volume ratio of chloroform / methanol is 2:1. S202: Seal the centrifuge tube with a plug, centrifuge twice in an ice bath at a speed of 10,000×g for 10 seconds, 13 seconds, 15 seconds or 20 seconds. S203: Make up the volume to 30 mL, let it stand for 45 min, 55 min, 65 min, 65 min or 75 min, and then filter to obtain the first filtrate. S204: Add 0.2 times the volume of 0.85 g / 100 g saline to the first filtrate, centrifuge at 3000×g for 10 min, 12 min, 15 min, 17 min or 20 min, and dry the bottom layer solution under the action of a nitrogen stream to obtain a lipid extract. including.

[0024] S30: Divide the obtained lipids into multiple portions, store them under low-temperature conditions, store them for specific refrigeration times respectively, and measure the lipid oxidation degree and lipid metabolism data of tilapia at different refrigeration times by lipid metabolomics technology based on LC-MS after the storage ends.

[0025] Note that LC-MS is a liquid chromatography mass spectrometer. The low temperature condition may be 0°C, 2°C, 4°C, 6°C or 8°C.

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

[0027] In the examples of the present invention, the test method of lipid metabolomics technology is filling 0.5 mL of sample into a 2 mL centrifuge tube, adding 600 μL of methanol containing 4-chloro-L-phenylalanine (4 ppm, maintained at -20°C), and vortexing the mixture for 25 seconds, 28 seconds, 30 seconds, 33 seconds or 35 seconds; grinding with glass beads in a tissue grinder containing 100 mg of glass beads for 80 seconds, 85 seconds, 90 seconds, 95 seconds or 100 seconds under 60 Hz; after centrifuging the sample at 4°C and 12,000×g for 10 minutes, performing ultrasonic treatment at ambient temperature for 7 minutes, 8 minutes, 10 minutes, 12 minutes or 13 minutes, and then filtering the supernatant with a 0.22 μm membrane to obtain a second filtrate; performing LC-MS detection; and including. In LC-MS detection, the second filtrate was placed in a measuring flask. Liquid chromatography analysis was performed using an Ultimate 3000 UHPLC system (Thermo Fisher Scientific) to obtain total ion chromatograms and metabolic data, which were calculated by various analytical methods. Chromatography was carried out using an ACQUITY UPLC (registered trademark) HSS T3 (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. An acetonitrile solution (v / v) of 0.1% formic acid (C) and an aqueous solution (v / v) of 0.1% formic acid (D) were the mobile phases for LC-ESI(+)-MS analysis. The analytes used for LC-ESI(-)-MS analysis were acetonitrile (A) and ammonium formate water (5 mM) (B). Metabolites were detected by mass spectrometry using an ESI ion source and Q Exactive (Thermo Fisher Scientific, USA). Data-dependent MS / MS and synchronous MS1 and MS / MS (full MS-ddMS2 mode) were used for collection. The parameters were as follows: capillary temperature: 325 °C, MS1 range: m / z 100 - 1000, MS1 resolution: 70000 FWHM, number of data-dependent scans per cycle: 10 times, MS / MS resolution: 17500 FWHM, normalized collision energy: 30%.

[0028] S40: By combining the KEGG metabolic pathway and the MetPA database, a lipid metabolism network related to odor was constructed. Based on the lipid metabolism network, the lipid metabolism data of tilapia at different refrigeration times were analyzed to obtain metabolic markers corresponding to multiple necessary lipids. Here, the lipid metabolism data include metabolites and metabolic pathways.

[0029] KEGG is a database that integrates genomic, chemical, and systemic functional information, and each database contains a large amount of useful information. Genomic information is stored in the GENEES database and includes completely and partially sequenced genomic sequences. More advanced functional information is stored in the PATHWAY database and includes information on graphically represented cell biochemical processes, such as metabolism, membrane transport, signal transduction, cell cycle, ortholog-conserved subpathways, etc. Another database of KEGG is LIGAND, which includes information on chemical substances, enzyme molecules, and enzyme reactions. The integrated metabolic pathway query provided by KEGG includes metabolism of carbohydrates, nucleosides, amino acids, etc. and biodegradation of organic substances, annotating not only all possible metabolic pathways but also comprehensively the enzymes catalyzing the reactions at each step, including amino acid sequences, links to the PDB library, etc. KEGG is a powerful tool for in vivo metabolic analysis and metabolic network research, and helps researchers study gene and its expression information as an entire network. MetPA is part of metaboanalysis and is mainly based on KEGG metabolic pathways. The MetPA database identifies metabolic pathways that can be perturbed in the organism and analyzes the metabolic pathways of metabolites through enrichment and topological analysis of metabolic pathways. The related metabolic pathways of differential metabolites can be analyzed using the MetPA database, and the data analysis algorithm adopted is hypergeometric test, and the metabolic pathway topological structure adopts Relative-betweeness Centrality. By combining the KEGG metabolic pathway and MetPA, a lipid metabolic network related to odor is constructed.Input the metabolic marker metabolic spectrum identified by prior screening into the MetPA dialog, select the compound name (metabolite name) in the Input tag, click Submit, select the species, adopt the Hyperleometric Test (hypergeometric distribution test), Pathway Topology Analysis (path topological structure analysis), adopt the Relative-betweeness Centrality (betweenness centrality), then register and perform path model analysis, perform signal path analysis using the KEGG database, and visualize and plot the metabolite pathway using Interactive Pathways Explorer. What makes this method different from other analyses is, first, that the analysis target is different. This study extracts lipid extracts alone for metabolic analysis, which is the first example in this research field, eliminates the interference of other factors, and makes the analysis results more reliable. Second, the metabolic database on which the analysis is based is different. Conventional databases perform analysis based on the KEGG database, but in this study, based on the KEGG database, topological analysis is performed using the MetPA database to identify the metabolic pathways related to this study, and the data and metabolic model are analyzed by hypergeometric verification and Relative-betweeness Centrality, and the metabolic network is visualized and plotted using the visualization pathway online analysis tool of Interactive Pathways Explorer.

[0030] S50: Screen the obtained metabolic markers 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 appears when the null hypothesis is true, and it is one parameter for judging the hypothesis test result. The p-value is the significance level calculated based on the actual statistic, and the VIP value is one index for evaluating the importance of variables for the model. It describes the overall contribution of each variable to the model, evaluates the influence intensity and interpretability of the classification and discrimination of each group of samples by the expression pattern of each metabolite, and is useful for discovering differential metabolites with biological significance.)

[0031] Note that variables with VIP values higher than 1 are used as candidate variables for biomarkers. To verify whether there are statistically significant differences in units among the candidate variables found by multivariate statistics, the T-test is used in the experiment. When P < 0.05, it indicates that there is a significant difference. Combine the loading map and the screening of candidate variables, and perform searches, collations, and inferences in databases such as METLIN, KEGG, and PubChem through the mass spectrum information of the compounds represented by these variables to finally determine possible biomarkers. As a result of screening under the above conditions, the following evaluation metabolic markers were obtained, namely, 1-cetyl alcohol, 1-monopalmitate, 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, brassinosteroid, dibutyl phthalate, glycerin monostearate, heptadecanoic acid, myristic acid, oleic acid, palmitoleic acid, palmitic acid.

[0032] S60: Analyze the metabolic states of multiple lipids based on the evaluation metabolic markers corresponding to the multiple lipids.

[0033] In an embodiment of the present invention, S60 for analyzing the metabolic states of a plurality of lipids based on evaluation metabolic markers corresponding to the plurality of lipids is randomly selecting and testing three samples as a parallel group on the 0th day, 3rd day, 9th day, and 15th day respectively, and analyzing the degree of lipid oxidation and the lipid metabolism status of the samples.

[0034] In the present invention, the lipid extract of tilapia is extracted, the lipid extract is stored in a refrigerated environment at 4°C for 15 days, and a lipid metabolism network related to the smell of tilapia is constructed and screened by analysis using lipid metabolomics technology to obtain 18 metabolic markers (including 1-cetyl alcohol, 1-monopalmitate, 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, brassinosteroid, dibutyl phthalate, glycerin monostearate, heptadecanoic acid, myristic acid, oleic acid, palmitoleic acid, palmitic acid), and the degree of lipid oxidation and the deterioration of smell quality are judged according to the contents of these markers.

[0035] In the present invention, a network diagram of the lipid metabolism related to smell is constructed, the lipid metabolism is associated with the smell deterioration, and the deterioration status of the smell is judged by screening the metabolic markers. Therefore, the present invention is a method with high research value and provides new ideas for the control of lipid oxidation and the reduction of the occurrence of bad smell.

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

Table 1

[0037] It should be understood that although the above has been described in a certain order, these steps are not necessarily executed sequentially in the above order. Unless otherwise clearly described in this specification, the execution of these steps is not limited to a strict order, and these steps may be executed in other orders. Also, some steps of this embodiment may include multiple steps or multiple stages, and these steps or stages do not necessarily need to be completed at the same time and can be executed at different times. The execution order of these steps or stages also does not necessarily need to be carried out in sequence and can be executed in sequence or alternately with at least a part of other steps or steps or stages in other steps.

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

[0039] Those skilled in the art should understand that the consideration of any of the above embodiments is merely exemplary and is not intended to suggest that the scope disclosed in the 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 in the above embodiments or different embodiments may be combined, and there are many other changes in different aspects of the above embodiments of the present invention. For the sake of brevity, since they are not provided in detail, it should be understood. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present invention should all be included within the protection scope of the embodiments of the present invention.

Claims

1. A method for determining the odor deterioration and lipid oxidation degree of tilapia during the refrigeration period, comprising: killing fresh tilapia, taking tilapia slices, washing them, wiping off the surface moisture, and obtaining fish meat by mixing the raw materials and grinding; extracting lipids from the fish meat obtained by processing the raw materials; dividing the obtained lipids into a plurality of portions, storing them under low-temperature conditions, storing them for a predetermined refrigeration time respectively, and measuring the lipid oxidation degree and lipid metabolism data of tilapia at different refrigeration times by lipid metabolomics technology based on LC-MS after the storage ends; constructing a lipid metabolism network related to odor by combining the KEGG metabolic pathway and the MetPA database, and analyzing the lipid metabolism data of tilapia at different refrigeration times based on the lipid metabolism network to obtain metabolic markers corresponding to a plurality of required lipids, wherein the lipid metabolism data includes metabolites and metabolic pathways; screening the obtained metabolic markers to obtain evaluation metabolic markers, wherein the screening criteria for the metabolic markers are p-value ≤ 0.05 and VIP ≥ 1; analyzing the metabolic states of a plurality of lipids based on the evaluation metabolic markers corresponding to the plurality of lipids; and the step of killing fresh tilapia, taking tilapia slices, washing them, wiping off the surface moisture, and obtaining fish meat by mixing the raw materials and grinding includes: selecting fresh tilapia with substantially the same size and weight, putting it into a foam box, transporting it to the laboratory quickly under the condition of crushed ice and oxygen filling, then stunning the tilapia by physically hitting it, after killing, removing the head and organs, taking tilapia slices, washing them, wiping off the surface moisture, and then mixing and grinding, characterized by the method.

2. The step of extracting lipids from the fish meat obtained by processing the raw materials includes: putting 5 g of homogeneous fish meat into a 50 mL centrifuge tube, adding 15 mL of chloroform / methanol containing 0.01 g / 100 g of butylhydroxytoluene, wherein the volume ratio of chloroform / methanol is 2:1; sealing the centrifuge tube with a plug, centrifuging twice at a speed of 10,000×g in an ice bath for 10 seconds, 13 seconds, 15 seconds or 20 seconds; A step of making up the volume to 30 mL, allowing to stand for 45 min, 55 min, 65 min, 65 min or 75 min, and then filtering to obtain a first filtrate; A step of adding 0.2 times the volume of brine with a concentration of 0.85 g / 100 g to the first filtrate, centrifuging at 3000×g for 10 min, 12 min, 15 min, 17 min or 20 min, and drying the bottom layer solution under the action of a nitrogen stream to obtain a lipid extract; The method according to claim 1, characterized by comprising the above steps.

3. The step of dividing the obtained lipid into a plurality of portions, storing them under low temperature conditions, storing them for a predetermined refrigeration time respectively, and measuring the lipid oxidation degree and lipid metabolism data of tilapia at different refrigeration times by lipid metabolomics technology based on LC-MS after the storage is completed, The method according to claim 1, characterized by comprising dividing the obtained lipid extract into four portions, storing them under the condition of 4°C, and storing them for 0 days, 3 days, 9 days and 15 days respectively.

4. The test method of lipid metabolomics technology is Filling 0.5 mL of sample into a 2 mL centrifuge tube, adding 600 μL of methanol containing 4-chloro-L-phenylalanine, vortexing the mixture for 30 seconds, where the concentration of 4-chloro-L-phenylalanine is 4 ppm and it is kept at -20°C; A step of pulverizing at 60 Hz for 90 seconds using a tissue grinder containing 100 mg of glass beads; After centrifuging the sample at 4°C and 12,000×g for 10 minutes, performing ultrasonic treatment at ambient temperature for 10 minutes, and then filtering the supernatant with a 0.22 μm membrane to obtain a second filtrate; Putting the second filtrate into a measuring flask, and then performing liquid chromatography analysis and chromatography processing on the second filtrate; The method according to claim 1, characterized by comprising the above steps.

5. The step of analyzing the metabolic states of a plurality of lipids based on evaluation metabolic markers corresponding to the plurality of lipids The method according to claim 1, characterized by comprising randomly selecting three samples as a parallel group on the 0th day, 3rd day, 9th day and 15th day respectively, and analyzing the lipid oxidation degree and lipid metabolism status of the samples.

6. The method according to claim 1, wherein the evaluation metabolite marker comprises 1-cetyl alcohol, 1-monopalmitate, 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, brassinosteroid, dibutyl phthalate, glycerin monostearate, heptadecanoic acid, myristic acid, oleic acid, palmitoleic acid, and palmitic acid.

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