How to identify the cause of fat and oil oxidation

Abstract

To provide a simpler method for identifying the cause of fat oxidation using a near-infrared spectroscopic analysis.SOLUTION: Provided is a method for identifying the cause of fat oxidation, including: a step in which the near-infrared spectroscopic spectrum of the fat being tested is measured; a step in which the content of lipid hydroperoxide derived from the radical oxidation and / or lipid hydroperoxide derived from singlet oxygen oxidation in the fat being tested is quantified from near-infrared spectroscopic spectrum data obtained in a partial wavenumber region of a wavenumber range measured in the above step, on the basis of an analytical curve having been preliminarily created using the near-infrared spectroscopic spectrum; and a step in which the cause of fat oxidation is identified from the quantification result.SELECTED DRAWING: None

Description

[Technical Field]

[0001] The present invention relates to a method for identifying the cause of oxidation of fats and oils. [Background technology]

[0002] It is known that fats and oils are oxidized by heat, light, etc., and that oxidation of fats and oils leads to a deterioration in the quality of products containing the fats and oils. Since antioxidant measures vary depending on the cause of oxidation, it is important for quality control to identify not only the degree of oxidation of fats and oils but also the cause of oxidation.

[0003] A method for identifying the cause of oxidation by detailed isomer analysis of lipid hydroperoxides using LC-MS / MS has been reported (Non-Patent Document 1). However, this method requires complicated operations and laboratory-level facilities and equipment, and has issues such as long analysis times and environmental impact due to the use of organic solvents.

[0004] Furthermore, near-infrared spectroscopy (NIR), which is widely used for non-destructive analysis of food, is widely used to evaluate the oxidation of vegetable oils, such as their acid value and peroxide value (Patent Documents 1 and 2), but there have been no examples of its application to investigating the causes of oxidation. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Publication No. 2018-205226 [Patent Document 2] Japanese Patent Application Laid-Open No. 2015-232528 [Non-patent literature]

[0006] [Non-Patent Document 1] NPJ Science of Food, 2 (2018) doi:10.1038 / s41538-017-0009-x Summary of the Invention [Problem to be solved by the invention]

[0007] An object of the present invention is to provide a simpler method for identifying the cause of fat and oil oxidation using near-infrared spectroscopy. [Means for solving the problem]

[0008] In order to solve the above problems, the inventors have conducted extensive research and found that lipid hydroperoxides can be quantified by using near-infrared spectroscopy (NIR). The present invention was completed based on these findings and includes the following broad aspects. [Section 1] A method for identifying the cause of fat or oil oxidation, comprising: Measuring the near-infrared spectrum of the test oil or fat; A step of quantifying the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the test oil or fat from near-infrared spectroscopic data obtained in a part of the wavenumber range measured in the step based on a calibration curve prepared in advance using near-infrared spectroscopic spectra; A step of identifying the cause of oxidation of fats and oils from the quantification results; A method comprising: [Section 2] The calibration curve is Measuring near-infrared spectra of a plurality of oil and fat standard samples having different degrees of oxidation; Quantifying the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the oil and fat standard sample; A step of preparing a calibration curve from near-infrared spectroscopic data obtained in all or part of the wavenumber range of the measured wavenumber and the quantified content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation; Item 1, wherein the compound is obtained by a method comprising the steps of: [Section 3] The wave number region is Measuring near-infrared spectra of a plurality of oil and fat standard samples having different degrees of oxidation; analyzing the near-infrared spectral data obtained in all or part of the wavenumber range of the measured wavenumber by principal component analysis; determining a wavenumber region based on the analysis results; Item 3. The method according to Item 1 or 2, wherein the concentration is determined by a method comprising: [Section 4] The wave number region is 5500 to 4500 cm -1 and / or 7500-6000 cm -1 Item 4. The method according to any one of Items 1 to 3, wherein [Section 5] A program executed on a computer, Measuring the near-infrared spectrum of the test oil; Based on a calibration curve prepared in advance using the near-infrared spectroscopy spectrum, the near-infrared spectroscopy spectrum data obtained in all or part of the wavenumber range measured in the above step is used to quantify the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the test oils and fats; Identifying the cause of oxidation of fats and oils from the quantification results; A program for identifying the cause of fat and oil oxidation, characterized by causing the computer to execute the above. [Section 6] Regarding the creation of the calibration curve, Measuring near-infrared spectra of a plurality of oil and fat standard samples having different degrees of oxidation; Quantifying the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the oil and fat standard sample; A step of creating a calibration curve from near-infrared spectroscopic data obtained in all or part of the wavenumber range of the measured wavenumber range and the quantified content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation; Item 6. The program for identifying the cause of fat and oil oxidation according to Item 5, wherein the program is executed by the computer. [Section 7] The wave number region is Measuring near-infrared spectra of a plurality of oil and fat standard samples having different degrees of oxidation; analyzing near-infrared spectral data obtained in all or part of the measured wavenumber range by principal component analysis; determining a wavenumber domain based on the analysis results; Item 7. The program for identifying the cause of fat and oil oxidation according to Item 5 or 6, characterized in that the program is determined by causing the computer to execute the above. [Section 8] A measurement unit for measuring the near-infrared spectrum of the test oil or fat; Based on a calibration curve prepared in advance using near-infrared spectroscopy, Measuring part A calculation unit that quantifies the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the test oil or fat from near-infrared spectroscopic data obtained in all or part of the wavenumber range measured in an evaluation unit that identifies the cause of oxidation of fats and oils from the quantification results; An analytical device comprising: [Section 9] In the wave number region, a measurement unit for measuring near-infrared spectra of a plurality of oil and fat standard samples having different degrees of oxidation; an analysis unit that analyzes the near-infrared spectrum data obtained in all or part of the wavenumber range of the measured wavenumber by principal component analysis; an evaluation unit that determines a wavenumber range based on the analysis results; Item 9. The analytical device according to item 8, further comprising a mechanism for determining [Effects of the Invention]

[0009] According to the present invention, a simpler method for identifying the cause of fat or oil oxidation can be provided. [Brief explanation of the drawings]

[0010] [Figure 1] 1 shows the results of principal component analysis of the near-infrared spectrum of rapeseed oil in each wavenumber region in Example 2. A: Range 1 (5500-4500 cm-1). B: Range 2 (6000-5500 cm-1). C: Range 3 (7500-6000 cm-1). D: Range 4 (9500-7500 cm-1). [Figure 2] Principal component analysis results of near-infrared spectra of olive oil in each wavenumber region in Example 2. A: Range 1 (5500-4500 cm-1). B: Range 2 (6000-5500 cm-1). C: Range 3 (7500-6000 cm-1). D: Range 4 (9500-7500 cm-1). [Figure 3] 1 shows the results of partial least squares (PLS) regression analysis of TG 18:1_18:1_18:2;13OOH (lipid hydroperoxide isomer in which the 13th position of linoleic acid is oxidized) in rapeseed oil in Example 3. [Figure 4] 1 shows the results of partial least squares (PLS) regression analysis of TG 18:1_18:1_18:2;12OOH (lipid hydroperoxide isomers in which the 12th position of linoleic acid is oxidized) in rapeseed oil in Example 3. [Figure 5] 1 shows the results of partial least squares (PLS) regression analysis of TG 18:1_18:1_18:2;9OOH (lipid hydroperoxide isomer in which the 9-position of linoleic acid is oxidized) in rapeseed oil in Example 3. [Figure 6] 1 shows the results of partial least squares (PLS) regression analysis of TG 18:1_18:1_18:2;10OOH (lipid hydroperoxide isomers in which the 10-position of linoleic acid is oxidized) in rapeseed oil in Example 3. [Figure 7] 1 shows the results of partial least squares (PLS) regression analysis of TG 18:1_18:1_18:1;10OOH (lipid hydroperoxide isomer in which the 10-position of oleic acid is oxidized) in olive oil in Example 3. [Figure 8]1 shows the results of partial least squares (PLS) regression analysis of TG 18:1_18:1_18:1;11OOH (lipid hydroperoxide isomer in which the 11th position of oleic acid is oxidized) in olive oil in Example 3. [Figure 9] 1 shows the results of partial least squares (PLS) regression analysis of TG 18:1_18:1_18:1;9OOH (lipid hydroperoxide isomer in which the 9-position of oleic acid is oxidized) in olive oil in Example 3. [Figure 10] 1 shows the results of partial least squares (PLS) regression analysis of TG 18:1_18:1_18:1;8OOH (lipid hydroperoxide isomer in which the 8th position of oleic acid is oxidized) in olive oil in Example 3. DETAILED DESCRIPTION OF THE INVENTION

[0011] [How to identify the cause of fat oxidation] In one aspect, the present invention provides a method for identifying the cause of fat or oil oxidation, which is characterized by comprising the following steps (1), (2), and (3): (1) A process of measuring the near-infrared spectrum of the test oil or fat. (2) A process of quantifying the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the test oil or fat from near-infrared spectroscopic data obtained in a partial wavenumber region of the wavenumber range measured in the above process, based on a calibration curve prepared in advance using near-infrared spectroscopic spectra. (3) A process of identifying the cause of oxidation of fats and oils from the quantitative results.

[0012] The method of the present invention may include steps other than the above steps (1), (2), and (3), and the details thereof are not important.

[0013] <Process (1)> In step (1), the near-infrared spectrum of the test oil or fat is measured.

[0014] The test oils and fats used in the method of the present invention are not particularly limited as long as they contain unsaturated fatty acids in their structure, and may be edible oils and fats or industrial oils and fats, but edible oils and fats are preferred. Furthermore, edible oils and fats may be derived from either plants or animals, but plant-derived oils are preferred. Examples of plant-derived edible oils and fats include linseed oil, perilla oil, olive oil, sesame oil, rice bran oil, safflower oil, soybean oil, corn oil, rapeseed oil, palm oil, sunflower oil, grape oil, cottonseed oil, coconut oil, and peanut oil. These oils and fats may be used alone or in combination of two or more.

[0015] The unsaturated fatty acid is not particularly limited, but examples thereof include oleic acid, linoleic acid, α-linolenic acid, arachidonic acid, eicosapentaenoic acid, docosahexaenoic acid, etc., with oleic acid, linoleic acid, and α-linolenic acid being preferred. The fats and oils used in the method of the present invention may contain only one of these unsaturated fatty acids in their structure, or may contain two or more of them in their structure.

[0016] In the present invention, the test oil or fat is optionally subjected to pretreatment and then subjected to near-infrared spectroscopy.

[0017] Pretreatments include, for example, solid-liquid separation, dilution, extraction, etc. For solid-liquid separation, for example, solids are filtered from the test oil or fat using filter paper or a filter, or the solids are separated by leaving it to stand. For dilution and extraction, various solvents can be used.

[0018] While the method for measuring near-infrared spectroscopy is not particularly limited, diffuse reflectance or transmittance is preferred, and it is more preferable to use either method depending on the sample being measured. If the sample is solid, it is preferable to primarily use diffuse reflectance, and if the sample is liquid, it is preferable to primarily use transmittance. However, even in the case of liquids, if the sample is highly colored and does not transmit light well, it is preferable to measure diffuse reflected light. If the sample is a solution, it is preferable to measure transmitted light by adjusting the concentration appropriately. While the measurement cell is not particularly limited, it is preferable to use a cell that is appropriately selected depending on the sample and measurement method. Near-infrared spectroscopy can be measured not only by offline analysis, but also by at-line, online, in-line, non-invasive analysis, etc. Near-infrared spectroscopy can be measured by collecting a sample and measuring it using a near-infrared analyzer in an analysis laboratory, or by bringing a near-infrared analyzer to a production site or warehouse and performing measurements on-site. Furthermore, by incorporating a near-infrared analyzer into a production line, it is possible to continuously measure the near-infrared spectroscopy of the sample being measured.

[0019] A commercially available near-infrared spectrometer can be used to measure the near-infrared spectrum, but one that can measure transmitted light and diffusely reflected light is preferred. Also, depending on the sample being measured, one equipped with a solid measurement module, a liquid measurement module, an optical fiber module, or a solid transmittance measurement module can be used. One equipped with a temperature control function for the measurement cell is more preferred. The spectrum obtained is preferably a Fourier transform spectrum.

[0020] Since the transparency of the measurement sample may change depending on the temperature, it is preferable to measure the near-infrared spectrum at a constant temperature. If the viscosity of the measurement sample is high, it is preferable to heat the measurement cell containing the measurement sample to reduce the viscosity. In the present invention, the measurement temperature is preferably 25 to 40°C, and more preferably 25 to 30°C.

[0021] In addition, in consideration of rapid measurement, the thickness of the measurement cell is preferably thin, for example, 0.5 to 10 mm, preferably 2 to 8 mm.

[0022] The wavenumber range for measuring the near-infrared spectrum may be any range that includes the wavenumber range determined by the method described in the section below (Determination of Wavenumber Range), for example, 12,500 to 4,000 cm -1 is.

[0023] The near-infrared spectral data may be raw spectral data, but it is preferable to use processed raw spectral data. Examples of data processing methods include multi-derivatives such as first, second, and third derivatives, smoothing, spectral subtraction, normalization, MSC correction, and standardization (SNV correction). These processing methods may be used alone or in combination. Among these, multi-derivatives, smoothing, and standardization are preferred.

[0024] <Process (2)> In step (2), based on a calibration curve prepared in advance using near-infrared spectroscopy, the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the test oil or fat is quantified from near-infrared spectroscopy data obtained in a partial wavenumber region of the wavenumber range measured in the previous step.

[0025] The near-infrared spectroscopic data measured in the above step can be applied to a calibration curve obtained by the method described in the following section (Creating a calibration curve) to quantify the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the test oil or fat. For a part of the wavenumber range described above, the wavenumber range determined by the method described in the following section (Determining the wavenumber range) is applied.

[0026] In the present invention, "lipid hydroperoxide" refers to fats and oils containing unsaturated fatty acid oxides substituted with hydroperoxy groups in their structure. "Lipid hydroperoxides derived from radical oxidation" refers to fats and oils containing, among unsaturated fatty acid oxides substituted with hydroperoxy groups, hydroperoxides obtained by the radical oxidation reaction of unsaturated fatty acids in their structure. "Lipid hydroperoxides derived from singlet oxygen oxidation" refers to fats and oils containing, among unsaturated fatty acid oxides substituted with hydroperoxy groups, hydroperoxides obtained by the singlet oxygen oxidation reaction of unsaturated fatty acids in their structure. Oxidation reactions of unsaturated fatty acids proceed by exposure to light, heat, etc., but radical oxidation reactions proceed mainly by heat, while singlet oxygen oxidation reactions proceed mainly by light.

[0027] Examples of unsaturated fatty acid oxides substituted with hydroperoxy groups contained in the structure of lipid hydroperoxides derived from radical oxidation include: Oleic acid (FA 18:1) A molecular species with a hydroperoxy group inserted at the 8th position (FA 18:1;8OOH), A molecular species with a hydroperoxy group inserted at the 9th position (FA 18:1;9OOH), A molecular species with a hydroperoxy group inserted at the 10-position (FA 18:1;10OOH), or A molecular species with a hydroperoxy group inserted at the 11th position (FA 18:1;11OOH), Linoleic acid (FA 18:2) A molecular species with a hydroperoxy group inserted at the 9-position (FA 18:2;9OOH), or A molecular species with a hydroperoxy group inserted at the 13th position (FA 18:2;13OOH), α-linolenic acid (FA 18:3) A molecular species with a hydroperoxy group inserted at the 9th position (FA 18:3;9OOH), A molecular species with a hydroperoxy group inserted at the 12th position (FA 18:3;12OOH), A molecular species with a hydroperoxy group inserted at the 13th position (FA 18:3;13OOH), or A molecular species with a hydroperoxy group inserted at the 16th position (FA 18:3;16OOH), Arachidonic acid (FA 20:4) A molecular species with a hydroperoxy group inserted at the 5-position (FA 20:4;5OOH), A molecular species with a hydroperoxy group inserted at the 8th position (FA 20:4;8OOH), A molecular species with a hydroperoxy group inserted at the 9th position (FA 20:4;9OOH), A molecular species with a hydroperoxy group inserted at the 11th position (FA 20:4;11OOH), A molecular species with a hydroperoxy group inserted at the 12th position (FA 20:4;12OOH), or A molecular species with a hydroperoxy group inserted at the 15th position (FA 20:4;15OOH), Eicosapentaenoic acid (FA 20:5) A molecular species with a hydroperoxy group inserted at the 5-position (FA 20:5;5OOH), A molecular species with a hydroperoxy group inserted at the 8th position (FA 20:5;8OOH), A molecular species with a hydroperoxy group inserted at the 9th position (FA 20:5;9OOH), A molecular species with a hydroperoxy group inserted at the 11th position (FA 20:5;11OOH), A molecular species with a hydroperoxy group inserted at the 12th position (FA 20:5;12OOH), A molecular species with a hydroperoxy group inserted at the 14th position (FA 20:5;14OOH), A molecular species with a hydroperoxy group inserted at the 15th position (FA 20:5;15OOH), or A molecular species with a hydroperoxy group inserted at the 18th position (FA 20:5;18OOH), Docosahexaenoic acid (FA 22:6) A molecular species with a hydroperoxy group inserted at the 4-position (FA 22:6;4OOH), A molecular species with a hydroperoxy group inserted at the 7th position (FA 22:6;7OOH), A molecular species with a hydroperoxy group inserted at the 8th position (FA 22:6;8OOH), A molecular species with a hydroperoxy group inserted at the 10th position (FA 22:6;10OOH), A molecular species with a hydroperoxy group inserted at the 11th position (FA 22:6;11OOH), A molecular species with a hydroperoxy group inserted at the 13th position (FA 22:6;13OOH), A molecular species with a hydroperoxy group inserted at the 14th position (FA 22:6;14OOH), A molecular species with a hydroperoxy group inserted at the 16th position (FA 22:6;16OOH), A molecular species with a hydroperoxy group inserted at the 17th position (FA 22:6;17OOH), or A molecular species with a hydroperoxy group inserted at the 20th position (FA 22:6;20OOH) etc.

[0028] Among these, FA 18:1;8OOH and FA 18:1;11OOH are unsaturated fatty acid oxides specific to radical oxygen oxidation, and therefore, if these unsaturated fatty acid oxides are contained in the structure of the lipid hydroperoxide of the test oil, it can be determined that thermal oxidation is one of the causes of oxidation of the test oil.

[0029] Examples of unsaturated fatty acid oxides substituted with hydroperoxy groups contained in the structure of lipid hydroperoxides derived from singlet oxygen oxidation include: Oleic acid (FA 18:1) A molecular species with a hydroperoxy group inserted at the 9-position (FA 18:1;9OOH), or A molecular species with a hydroperoxy group inserted at the 10th position (FA 18:1;10OOH), Linoleic acid (FA 18:2) A molecular species with a hydroperoxy group inserted at the 9th position (FA 18:2;9OOH), A molecular species with a hydroperoxy group inserted at the 10th position (FA 18:2;10OOH), A molecular species with a hydroperoxy group inserted at the 12th position (FA 18:2;12OOH), or A molecular species with a hydroperoxy group inserted at the 13th position (FA 18:2;13OOH), α-linolenic acid (FA 18:3) A molecular species with a hydroperoxy group inserted at the 9th position (FA 18:3;9OOH), A molecular species with a hydroperoxy group inserted at the 10th position (FA 18:3;9OOH), A molecular species with a hydroperoxy group inserted at the 12th position (FA 18:3;12OOH), A molecular species with a hydroperoxy group inserted at the 13th position (FA 18:3;13OOH), A molecular species with a hydroperoxy group inserted at the 15th position (FA 18:3;15OOH), or A molecular species with a hydroperoxy group inserted at the 16th position (FA 18:3;16OOH), Arachidonic acid (FA 20:4) A molecular species with a hydroperoxy group inserted at the 5-position (FA 20:4;5OOH), A molecular species with a hydroperoxy group inserted at the 6-position (FA 20:4;6OOH), A molecular species with a hydroperoxy group inserted at the 8th position (FA 20:4;8OOH), A molecular species with a hydroperoxy group inserted at the 9th position (FA 20:4;9OOH), A molecular species with a hydroperoxy group inserted at the 11th position (FA 20:4;11OOH), A molecular species with a hydroperoxy group inserted at the 12th position (FA 20:4;12OOH), A molecular species with a hydroperoxy group inserted at the 14th position (FA 20:4;14OOH), or A molecular species with a hydroperoxy group inserted at the 15th position (FA 20:4;15OOH), Eicosapentaenoic acid (FA 20:5) A molecular species with a hydroperoxy group inserted at the 5-position (FA 20:5;5OOH), A molecular species with a hydroperoxy group inserted at the 6-position (FA 20:5;6OOH), A molecular species with a hydroperoxy group inserted at the 8th position (FA 20:5;8OOH), A molecular species with a hydroperoxy group inserted at the 9th position (FA 20:5;9OOH), A molecular species with a hydroperoxy group inserted at the 11th position (FA 20:5;11OOH), A molecular species with a hydroperoxy group inserted at the 12th position (FA 20:5;12OOH), A molecular species with a hydroperoxy group inserted at the 14th position (FA 20:5;14OOH), A molecular species with a hydroperoxy group inserted at the 15th position (FA 20:5;15OOH), A molecular species with a hydroperoxy group inserted at the 17th position (FA 20:5;17OOH), or A molecular species with a hydroperoxy group inserted at the 18th position (FA 20:5;18OOH), Docosahexaenoic acid (FA 22:6) A molecular species with a hydroperoxy group inserted at the 4-position (FA 22:6;4OOH), A molecular species with a hydroperoxy group inserted at the 5-position (FA 22:6;5OOH), A molecular species with a hydroperoxy group inserted at the 7th position (FA 22:6;7OOH), A molecular species with a hydroperoxy group inserted at the 8th position (FA 22:6;8OOH), A molecular species with a hydroperoxy group inserted at the 10th position (FA 22:6;10OOH), A molecular species with a hydroperoxy group inserted at the 11th position (FA 22:6;11OOH), A molecular species with a hydroperoxy group inserted at the 13th position (FA 22:6;13OOH), A molecular species with a hydroperoxy group inserted at the 14th position (FA 22:6;14OOH), A molecular species with a hydroperoxy group inserted at the 16th position (FA 22:6;16OOH), A molecular species with a hydroperoxy group inserted at the 17th position (FA 22:6;17OOH), A molecular species with a hydroperoxy group inserted at the 19th position (FA 22:6;19OOH), or A molecular species with a hydroperoxy group inserted at the 20th position (FA 22:6;20OOH), etc.

[0030] Among these, FA 18:2;10OOH, FA 18:2;12OOH, FA 18:3;10OOH, FA 18:3;15OOH, FA 20:4;6OOH, FA 20:4;14OOH, FA 20:5;6OOH, FA 20:5;17OOH, FA 22:6;5OOH, and FA 22:6;19OOH are unsaturated fatty acid oxides specific to singlet oxygen oxidation. Therefore, if these unsaturated fatty acid oxides are contained in the structure of the lipid hydroperoxide of the test oil, it can be determined that photooxidation is one of the causes of oxidation of the test oil.

[0031] <Process (3)> In step (3), the cause of the oxidation of the fats and oils is identified based on the quantitative results in step (2).

[0032] When lipid hydroperoxides derived from radical oxidation are detected in the test oil, it can be determined that thermal oxidation is progressing. When determining that thermal oxidation is progressing, it is preferable that lipid hydroperoxides derived from radical oxidation are detected at 5 nmol / g or more, more preferably 20 nmol / g or more.

[0033] Furthermore, when lipid hydroperoxides derived from singlet oxygen oxidation are detected in the test oil or fat, it can be determined that photooxidation is progressing. When determining that photooxidation is progressing, it is preferable that lipid hydroperoxides derived from singlet oxygen oxidation are detected at 5 nmol / g or more, and more preferably 20 nmol / g or more.

[0034] Furthermore, if both lipid hydroperoxides derived from radical oxidation and lipid hydroperoxides derived from singlet oxygen oxidation are detected in the test oil or fat, it can be determined that thermal oxidation and photooxidation are progressing.

[0035] When the amount of lipid hydroperoxides derived from radical oxidation is greater than the amount of lipid hydroperoxides derived from singlet oxygen oxidation, it can be determined that thermal oxidation is progressing more than photooxidation, and when the amount of lipid hydroperoxides derived from singlet oxygen oxidation is greater than the amount of lipid hydroperoxides derived from radical oxidation, it can be determined that photooxidation is progressing more than thermal oxidation.

[0036] The method according to the present invention can also be carried out in conjunction with other analytical methods, such as gas chromatography, liquid chromatography such as high performance liquid chromatography or ultra high performance liquid chromatography, mass spectrometry, infrared spectroscopy such as Fourier transform infrared spectroscopy, and nuclear magnetic resonance spectroscopy such as Fourier transform nuclear magnetic resonance spectroscopy.

[0037] (Creating a calibration curve) In the present invention, a calibration curve for quantifying the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in a test oil or fat is prepared based on near-infrared spectroscopic data of the test oil or fat. More specifically, the calibration curve is prepared by a method including the following steps (A) to (C): (A) A process for measuring near-infrared spectra of a plurality of oil and fat standard samples having different degrees of oxidation. (B) A step of quantifying the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the oil and fat standard sample. (C) A step of creating a calibration curve from near-infrared spectroscopic data obtained in all or part of the wavenumber range of the measured wavenumber and the quantified content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation.

[0038] In step (A), near-infrared spectra of a plurality of oil and fat standard samples with different degrees of oxidation are measured.

[0039] A plurality of oil and fat standard samples with different degrees of oxidation are used as the oil and fat standard sample to be subjected to step (A). For example, when rapeseed oil is used as the oil and fat standard sample, the rapeseed oil can be irradiated with light and / or heated, and the amount required for measurement can be sampled and measured over time according to the progress of deterioration, or an amount suitable for measurement can be sampled and stored from the beginning, and the same oil and fat standard sample can be measured over time.

[0040] The plurality of fat and oil standard samples used in step (A) are preferably prepared so that the lipid hydroperoxide content in the test fat and oil, as quantified using the obtained calibration curve, falls within the range of the minimum and maximum values ​​of lipid hydroperoxide contained in the samples. The minimum content of radical oxidation-derived lipid hydroperoxide and / or singlet oxygen oxidation-derived lipid hydroperoxide contained in the fat and oil standard sample is not particularly limited, but is preferably 10 nmol / g or less, and more preferably 1 nmol / g or less. Furthermore, the maximum content of radical oxidation-derived lipid hydroperoxide and / or singlet oxygen oxidation-derived lipid hydroperoxide contained in the fat and oil standard sample is not particularly limited, but is preferably 200 to 2000 nmol / g, and more preferably 500 to 1000 nmol / g.

[0041] The more oil and fat standard samples to be subjected to step (A), the better. To obtain sufficient prediction accuracy, 20 or more samples are preferred, and 50 or more samples are more preferred.

[0042] Typically, the oils and fats used as the oil and fat standard samples are of the same type as the test oils and fats described in the section <Step (1)> (for example, oils and fats produced from the same type of material using the same method).

[0043] The method for obtaining near-infrared spectroscopic data of the oil and fat standard sample in order to obtain a calibration curve can be performed in the same manner as the method for measuring near-infrared spectroscopic data of the test oil and fat described in the section <Step (1)>.

[0044] In step (B), the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the oil and fat standard sample subjected to step (A) is quantified.

[0045] In step (B), the method for quantifying the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation is not particularly limited, but the LC-MS / MS method is preferred.

[0046] When quantifying by LC-MS / MS, first, an analytical sample is prepared by diluting an oil / fat standard sample with an organic solvent. The organic solvent is not particularly limited, but hexane, chloroform, isopropanol, methanol, etc. are preferred. The dilution ratio is preferably 500 to 1000 times. Optionally, an internal standard can be added to the analytical sample. The internal standard can be a lipid hydroperoxide in which some / all of the carbons are C13-labeled, or a lipid hydroperoxide in which some / all of the hydrogens are deuterated.

[0047] The separation column used in the LC-MS / MS method is not particularly limited as long as it can separate lipid hydroperoxide isomers, but a reversed-phase column or a normal-phase column is preferred. The column shape is not particularly limited as long as it can achieve the required separation. The column packing material is not particularly limited, but C8, C18, or silica stationary phase is preferred. The column temperature is not particularly limited as long as it is within a range that is acceptable from the standpoint of column performance and lipid hydroperoxide stability, but 40°C or below is preferred. An example of a column suitable for the present invention is a reversed-phase column (C8, 2 μm, 2.1 × 150 mm; GL Science). While it is preferable to achieve the required separation using a single column, multiple columns of the same or different types may be connected and used as desired.

[0048] The mobile phase used in the LC-MS / MS method is preferably a solvent that can dissolve the oil and fat standard sample and is suitable for LC-MS / MS, such as methanol, isopropanol, hexane, and mixtures thereof.

[0049] The flow rate of the mobile phase is not particularly limited as long as it does not cause any problems in terms of column performance, but is preferably 0.2 to 0.4 mL / min.

[0050] Examples of mass spectrometers used in LC-MS / MS include magnetic sector mass spectrometers, triple quadrupole mass spectrometers, time-of-flight mass spectrometers (TOF-MS), ion trap mass spectrometers, and Fourier transform mass spectrometers. In the present invention, triple quadrupole mass spectrometers are particularly preferred.

[0051] Ionization methods in mass spectrometers include electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), fast atom bombardment (FAB), photoionization (APPI), electron ionization (EI), chemical ionization (CI), field desorption (FD), matrix-assisted laser desorption ionization (MALDI), and sonic ionization (SSI), with ESI being particularly preferred.

[0052] MS / MS is preferably a technique for monitoring product ions obtained by collision-induced dissociation of precursor ions, which can be performed using multiple reaction monitoring (MRM) or selected reaction monitoring (SRM). In the present invention, multiple reaction monitoring (MRM) is preferred.

[0053] In step (B), it is preferable to measure lipid hydroperoxides as sodium adducts, which allows for the analysis of isomers with different substitution positions of hydroperoxides.

[0054] In step (C), a calibration curve is prepared from near-infrared spectroscopic data obtained in all or part of the wavenumber range of the measurement and the quantified lipid hydroperoxide content.

[0055] The calibration curve is prepared by multivariate analysis based on near-infrared spectroscopic data and the quantitative values ​​of the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation. For the multivariate analysis, analytical tools commonly used in chemometrics can be used, and various multivariate tools such as principal component analysis, hierarchical cluster analysis, PLS regression analysis, and discriminant analysis can be suitably used. Among these, PLS regression analysis is preferably used.

[0056] By subjecting the spectral data in the wavenumber region used for analysis and the quantified lipid hydroperoxide content (actually measured lipid hydroperoxide value) to multivariate analysis, factors related to lipid hydroperoxide content can be determined and a regression equation can be obtained. Factors related to lipid hydroperoxide content refer to hypothetical variables that are highly correlated with changes in lipid hydroperoxide content inherent in the spectral data. A calibration curve for predicting lipid hydroperoxide content from spectral data is created using the regression coefficients of these factors.

[0057] (Determination of wavenumber range) The wavenumber range of the near-infrared spectroscopic data used to prepare the calibration curve can be determined by a method including the following steps. (i) A process of measuring near-infrared spectra of multiple oil and fat standard samples with different degrees of oxidation. (ii) A step of analyzing the near-infrared spectroscopic data obtained in all or part of the wavenumber range of the measured wavenumbers by principal component analysis. (iii) determining the wavenumber region based on the analysis results;

[0058] In step (i), near-infrared spectra of a plurality of oil and fat standard samples with different degrees of oxidation can be measured in the same manner as in step (A) described in the above section (Calibration curve).

[0059] In step (ii), the obtained spectral data is analyzed by principal component analysis. The principal component analysis may be performed on the entire wavenumber range in which the near-infrared spectrum is measured, but is preferably performed on a partial wavenumber range. The partial wavenumber range in which the near-infrared spectrum is measured is any partial range included in the wavenumber range in which the near-infrared spectrum is measured. The partial wavenumber range is not particularly limited, but may be 9500 to 4500 cm -1 or a part thereof, and -1 or part thereof, 6000-5500 cm -1 or part thereof, 7500-6000 cm -1 or part thereof, or 9500 to 7500 cm -1 It is more preferable that the difference between the maximum wavenumber and the minimum wavenumber in this wavenumber region is 1000 cm or a part thereof. -1 The wavelength range is preferably a continuous range as described above. Only one wavelength range may be set, or multiple wavelength ranges may be set.

[0060] In step (iii), the wavenumber range used in the present invention is determined based on the analysis results of the principal component analysis. The wavenumber range to be determined based on the analysis results is not particularly limited as long as it is a wavenumber range in which the plurality of thermally oxidized fat and oil standard samples, the plurality of photo-oxidized fat and oil standard samples, and the plurality of thermally oxidized and photo-oxidized fat and oil standard samples can be distinguished by the principal component analysis. -1 and / or 7500-6000 cm -1 It is preferable that:

[0061] [Program for identifying the cause of fat and oil oxidation] In one aspect, the present invention provides a program for identifying the cause of fat or oil oxidation, which is executed by a computer, and is characterized in that the program includes the following steps (1) and (2): (1) A step of measuring the near-infrared spectroscopic spectrum of the test oil or fat. (2) A step of quantifying the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the test oil or fat from near-infrared spectroscopic data obtained in all or part of the wavenumber range measured in the previous step, based on a calibration curve prepared in advance using near-infrared spectroscopic spectra. (3) A step of identifying the cause of oxidation of fats and oils from the quantitative results.

[0062] The above steps (1), (2), and (3) are steps for carrying out step (1), step (2), and step (3) in the section [Method for identifying the cause of oxidation of fats and oils], respectively, and are carried out by the method described in the section [Method for identifying the cause of oxidation of fats and oils].

[0063] The calibration curve in step (2) above can be created by having a computer execute the following steps (A), (B), and (C). (A) A step of measuring near-infrared spectra of a plurality of oil and fat standard samples with different degrees of oxidation. (B) A step of quantifying the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the oil and fat standard sample. (C) A step of creating a calibration curve from near-infrared spectroscopic data obtained in all or part of the wavenumber range of the measured wavenumber and the quantified content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation.

[0064] The above steps (A), (B), and (C) are steps for carrying out step (A), step (B), and step (C) in the section [Method for identifying the cause of oxidation of fats and oils], respectively, and are carried out by the method described in the section [Method for identifying the cause of oxidation of fats and oils].

[0065] The wavenumber range in the above step (2) and step (C) can be determined by having a computer execute the following steps (i), (ii), and (iii). (i) A step of measuring near-infrared spectra of a plurality of oil and fat standard samples having different degrees of oxidation. (ii) A step of analyzing the near-infrared spectroscopic data obtained in all or part of the wavenumber range of the measured wavenumbers by principal component analysis. (iii) determining the wavenumber domain based on the analysis results;

[0066] The above steps (i), (ii), and (iii) are steps for carrying out step (i), step (ii), and step (iii) in the section [Method for identifying the cause of oxidation of fats and oils], respectively, and are carried out by the method described in the section [Method for identifying the cause of oxidation of fats and oils].

[0067] [Analyzer] In one aspect, the present invention provides an analytical device capable of identifying the cause of oxidation of fats and oils, characterized in that the analytical device includes the following: (1) a measurement unit, (2) a calculation unit, and (3) an evaluation unit. (1) A measurement unit for measuring the near-infrared spectrum of the test oil. (2) Based on a calibration curve prepared in advance using near-infrared spectroscopy, Measuring part A calculation unit that quantifies the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the test oil or fat from near-infrared spectroscopic data obtained in all or part of the wavenumber range measured in the method. (3) An evaluation unit that identifies the cause of oxidation of fats and oils from the quantitative results.

[0068] The above (1) measurement unit, (2) calculation unit, and (3) evaluation unit are parts that respectively perform step (1), step (2), and step (3) in the section [Method for identifying the cause of oxidation of fats and oils], and are capable of performing the steps described in the section [Method for identifying the cause of oxidation of fats and oils].

[0069] The analytical device of the present invention may further include a mechanism for determining the wavenumber range in the calculation unit (2). In this case, the analytical device is characterized by further including the following (i) measurement unit, (ii) analysis unit, and (iii) evaluation unit. (i) A measurement unit for measuring near-infrared spectra of multiple oil and fat standard samples with different degrees of oxidation. (ii) An analysis unit that analyzes the near-infrared spectroscopic data obtained in all or part of the wavenumber range of the measured wavenumber by principal component analysis. (iii) An evaluation unit that determines the wavenumber range based on the analysis results.

[0070] The above (i) measurement unit, (ii) analysis unit, and (iii) evaluation unit are parts that respectively perform step (i), step (ii), and step (iii) in the section [Method for identifying the cause of oxidation of fats and oils], and are capable of performing the steps described in the section [Method for identifying the cause of oxidation of fats and oils]. [Example]

[0071] The present invention will be explained in more detail using Production Examples and Examples, but the present invention is not limited to these Examples.

[0072] <Example 1> Preparation of oil and fat standard samples 1. Oxidation of rapeseed oil (photo-oxidation) Twenty-four 10-mL test tubes were prepared, each containing 4 mL of commercially available rapeseed oil. After oxygen was sealed in, the tubes were capped with a 25-mm septum. Each sample (24 tubes) was oxidized under photooxidation conditions (4°C, 15,000 lux). A 1 mL sample was taken for NIR measurement (see "3. Near-Infrared Spectroscopy Measurement" below) and a 0.1 mL sample was taken for LC-MS / MS analysis (see "4. LC-MS / MS Analysis" below) at 0, 1, 2, 4, 6, 8, 24, 30, 48, 3, 4 days, 7, 8, 9, 10, 11, 14, 16, 18, 21, 23, 25, 28, and 30 days after the start of oxidation.

[0073] (thermal oxidation) Twenty-four 10-mL test tubes were prepared, each containing 4 mL of commercially available rapeseed oil. After oxygen was sealed in, the tubes were capped with a 25-mm septum. Each sample (24 tubes) was then oxidized under thermal oxidation conditions (40°C, dark). A 1-mL sample was taken for NIR measurement (see "3. Near-Infrared Spectroscopy Measurement" below) and a 0.1-mL sample was taken for LC-MS / MS analysis (see "4. LC-MS / MS Analysis" below) at 0, 1, 2, 4, 6, 8, 24, 30, 48, 3, 48, 7, 8, 9, 10, 11, 14, 16, 18, 21, 23, 25, 28, and 30 days after the start of oxidation.

[0074] (Photo-oxidation and thermal oxidation) Twenty-four 10-mL test tubes were prepared, each containing 4 mL of commercially available rapeseed oil. After oxygen was sealed in, the tubes were capped with a 25-mm septum. Each sample (24 tubes) was then oxidized under photooxidation and thermal oxidation conditions (40°C, 15,000 lux). A 1 mL sample was taken for NIR measurement (see "3. Near-Infrared Spectroscopy Measurement" below) and a 0.1 mL sample was taken for LC-MS / MS analysis (see "4. LC-MS / MS Analysis" below) at 0, 1, 2, 4, 6, 8, 24, 30, 48, 3, 4 days, 7, 8, 9, 10, 11, 14, 16, 18, 21, 23, 25, 28, and 30 days after the start of oxidation.

[0075] (Store in a dark place) Twenty-four 10-mL test tubes containing 4 mL of commercially available rapeseed oil were prepared. After oxygen was sealed in each tube, the tubes were capped with a 25-mm septum. Each sample (24 tubes) was then stored in the dark. 1 mL of each sample was sampled for NIR measurement (see "3. Near-Infrared Spectroscopy Measurement" below) and 0.1 mL for LC-MS / MS analysis (see "4. LC-MS / MS Analysis" below) at 0, 1, 2, 4, 6, 8, 24, 30, 48, 3, 48, 7, 8, 9, 10, 11, 14, 16, 18, 21, 23, 25, 28, and 30 days after storage.

[0076] 2. Oxidation of olive oil (photo-oxidation) Twenty-four 10-mL test tubes were prepared, each containing 4 mL of commercially available olive oil. After oxygen was sealed in, the tubes were capped with a 25-mm septum. Each sample was then oxidized under photooxidation conditions (4°C, 15,000 lux). A 1 mL sample was taken for NIR analysis (see "3. Near-Infrared Spectroscopy Measurements" below) and a 0.1 mL sample was taken for LC-MS / MS analysis (see "4. LC-MS / MS Analysis" below) at 0, 1, 2, 4, 6, 8, 24, 30, 48, 3, 4 days, 7, 8, 9, 10, 11, 14, 16, 18, 21, 23, 25, 28, and 30 days after the start of oxidation.

[0077] (thermal oxidation) Twenty-four 10-mL test tubes were prepared, each containing 4 mL of commercially available olive oil. After oxygen was introduced into the tubes, the tubes were capped with 25-mm septa. Each tube was then oxidized under thermal oxidation conditions (40°C, dark). A 1 mL sample was taken for NIR analysis (see "3. Near-Infrared Spectroscopy Measurements" below) and a 0.1 mL sample was taken for LC-MS / MS analysis (see "4. LC-MS / MS Analysis" below) at 0, 1, 2, 4, 6, 8, 24, 30, 48, 3, 48, 7, 8, 9, 10, 11, 14, 16, 18, 21, 23, 25, 28, and 30 days after the start of oxidation.

[0078] (Photo-oxidation and thermal oxidation) Twenty-four 10-mL test tubes were prepared, each containing 4 mL of commercially available olive oil. After oxygen was introduced into the tubes, the tubes were capped with a 25-mm septum. Each tube was then oxidized under photo- and thermal-oxidation conditions (40°C, 15,000 lux). A 1 mL sample was taken for NIR analysis (see "3. Near-Infrared Spectroscopy Measurements" below) and a 0.1 mL sample was taken for LC-MS / MS analysis (see "4. LC-MS / MS Analysis" below) at 0, 1, 2, 4, 6, 8, 24, 30, 48, 3, 4 days, 7, 8, 9, 10, 11, 14, 16, 18, 21, 23, 25, 28, and 30 days after the start of oxidation.

[0079] (Store in a dark place) Twenty-four 10-mL test tubes were prepared, each containing 4 mL of commercially available olive oil. After purging, the tubes were sealed with a 25-mm septum. Each tube was then stored in the dark. After 0 hours, 1 hour, 2 hours, 4 hours, 6 hours, 8 hours, 24 hours, 30 hours, 48 ​​hours, 3 days, 4 days, 7 days, 8 days, 9 days, 10 days, 11 days, 14 days, 16 days, 18 days, 21 days, 23 days, 25 days, 28 days, and 30 days, 1 mL of each sample was used for NIR analysis (see "3. Near-Infrared Spectroscopy Measurement" below) and 0.1 mL for LC-MS / MS analysis (see "4. LC-MS / MS Analysis" below).

[0080] 3. Near-infrared spectroscopy measurement 1 mL of each sample from "1. Oxidation of rapeseed oil" and "2. Oxidation of olive oil" above was placed in an 8 mm vial (6.6 mm id vial, Bruker Optics) and measured at 12500–4000 cm -1 Near-infrared spectroscopy in the 1000 MHz region was measured at room temperature using an FT-NIR (MPA, Bruker Optics) under the following measurement conditions: All samples were analyzed twice. Measurement mode: Transmittance mode Spectral resolution: 8 cm -1 Spectral integration count: 128 scans

[0081] 4.LC-MS / MS analysis Each sample from "1. Oxidation of rapeseed oil" and "2. Oxidation of olive oil" above was diluted 10-fold with chloroform:isopropanol (1:9) and then further diluted 50-fold with isopropanol:methanol (1:1). 2 μL of this solution was analyzed by LC-MS / MS. HPLC was performed using a Shimadzu LC system including a vacuum degasser, pump, and autosampler (Shimadzu Corporation). Mass spectrometry was performed using a 4000 QTRAP mass spectrometer (AB SCIEX). HPLC conditions were: column oven temperature 40 °C, solvent A (methanol) and solvent B (isopropanol), and separation was performed on a reversed-phase column (C8, 2 μm, 2.1 × 150 mm; GL Science). Gradient conditions are shown in Table 1. The column eluate was mixed with a post-column solvent (methanol containing 2 mM sodium acetate, 0.01 mL / min) and subjected to mass spectrometry. Mass spectrometry was performed in multiple reaction monitoring (MRM) mode to detect each lipid hydroperoxide isomer. The detected lipid hydroperoxide isomers are as follows. The MRM conditions are shown in Table 2, and the electrospray ionization conditions are shown in Table 3. The concentration of each lipid hydroperoxide was calculated using the corresponding external standard curve (0.01 pmol-10 pmol).

[0082] <Detected lipid hydroperoxide isomers> Rapeseed oil: TG 18:1_18:1_18:2 (Dioleoyl-linoleoyl-glycerol) is a molecular species formed by oxidation of linoleic acid TG 18:1_18:1_18:2;9OOH: a molecular species in which the 9th position of linoleic acid is oxidized TG 18:1_18:1_18:2;10OOH: A molecular species in which the 10th position of linoleic acid is oxidized TG 18:1_18:1_18:2;12OOH: A molecular species in which the 12th position of linoleic acid is oxidized TG 18:1_18:1_18:2;13OOH: A molecular species in which the 13th position of linoleic acid is oxidized Olive oil: TG 18:1_18:1_18:1 (Trioleoylglycerol), a molecular species in which one oleic acid is oxidized TG 18:1_18:1_18:1;8OOH: A molecular species in which the 8th position of oleic acid is oxidized TG 18:1_18:1_18:1;9OOH: A molecular species in which the 9th position of oleic acid is oxidized TG 18:1_18:1_18:1;10OOH: A molecular species in which the 10th position of oleic acid is oxidized TG 18:1_18:1_18:1;11OOH: A molecular species in which the 11th position of oleic acid is oxidized

[0083] [Table 1]

[0084] [Table 2]

[0085] [Table 3]

[0086] Example 2: Determination of wavenumber range The near-infrared spectrum obtained in Example 1 was analyzed using the Unscrambler (ver. 11: CAMO AS) software program. -1 The absorbance spectrum in the region was second-order differentiated using Salvizky-Golay smoothing (17 points). Then, to identify the wavenumber region in which differences in the causes of fat oxidation can be distinguished, the near-infrared spectral region was divided into four regions (Range 1: 5500-4500 cm -1 , Range 2: 6000-5500 cm -1 , Range 3: 7500-6000 cm -1, Range 4: 9500-7500 cm -1 ) and performed principal component analysis (PCA) of the spectra in each wavenumber region. The results are shown in Figures 1 and 2. From these results, it was found that both rapeseed oil and olive oil had a spectrum in Range 1: 5500-4500 cm -1 , Range 3: 7500-6000 cm -1 It was found that it is possible to distinguish between the causes of fat oxidation in the wavenumber range.

[0087] Example 3: Preparation of a calibration curve A partial least squares (PLS) regression analysis was performed based on the near-infrared spectroscopy results and the LC-MS / MS analysis results in Example 1 to create a calibration curve. Here, in Example 2, it was revealed that it was possible to distinguish between the causes of fat and oil oxidation in the wavenumber range of Range 1: 5500-4500 cm. -1 and Range 3: 7500-6000 cm -1 The second derivative spectra of the lipid hydroperoxides were used as explanatory variables, and the lipid hydroperoxide concentration quantified by LC-MS / MS analysis was used as the objective variable. The accuracy of the prediction model was evaluated by cross-validation using the coefficient of determination (R 2 The accuracy was confirmed by the root mean square error (RMSEC). The results are shown in Figures 3 to 10. These results demonstrate that the calibration curves created have high prediction accuracy.

[0088] In rapeseed oil, TG 18:1, 18:1, 18:2;10OOH and TG 18:1, 18:1, 18:2;12OOH are lipid hydroperoxides specific to singlet oxygen oxidation. Therefore, if TG 18:1, 18:1, 18:2;10OOH and TG 18:1, 18:1, 18:2;12OOH are detected in the rapeseed oil test sample, it can be determined that photooxidation is progressing. Since TG 18:1, 18:1, 18:2;9OOH and TG 18:1, 18:1, 18:2;13OOH are lipid hydroperoxides produced by both radical oxidation and photooxidation. If TG 18:1, 18:1, 18:2;9OOH and TG 18:1, 18:1, 18:2;13OOH are detected in the rapeseed oil test sample, but TG 18:1, 18:1, 18:2;10OOH and TG 18:1, 18:1, 18:2;12OOH are not detected, it can be determined that only thermal oxidation is occurring. Furthermore, if any of TG 18:1_18:1_18:2;10OOH, TG 18:1_18:1_18:2;12OOH, TG 18:1_18:1_18:2;9OOH, and TG 18:1_18:1_18:2;13OOH is detected in the rapeseed oil test oil, it can be determined that both thermal oxidation and photooxidation are progressing, and the content of each lipid hydroperoxide can also be used to determine the degree of photooxidation and thermal oxidation in the rapeseed oil test oil.

[0089] In olive oil, TG 18:1, 18:1, 18:1;8OOH and TG 18:1, 18:1, 18:1;11OOH are lipid hydroperoxides specific to radical oxidation. Therefore, if TG 18:1, 18:1, 18:1;8OOH and TG 18:1, 18:1, 18:1;11OOH are detected in the olive oil test sample, it can be determined that thermal oxidation is progressing. TG 18:1, 18:1, 18:1;9OOH and TG 18:1, 18:1, 18:1;10OOH are lipid hydroperoxides produced by both radical oxidation and photooxidation. Therefore, if 18:1, 18:1, 18:1;9OOH and TG 18:1, 18:1, 18:1;10OOH are detected in the olive oil test sample, but TG 18:1, 18:1, 18:1;8OOH and TG 18:1, 18:1, 18:1;11OOH are not detected, it can be determined that only photooxidation is occurring. If any of TG 18:1_18:1_18:1;8OOH, 18:1_18:1_18:11OH, TG 18:1_18:1_18:1;9OOH, and TG 18:1_18:1_18:1;10OOH are detected in the olive oil test oil, it can be determined that both thermal oxidation and photooxidation are progressing, and the content of each lipid hydroperoxide can also be used to determine the degree of photooxidation and thermal oxidation in the olive oil test oil.

[0090] In this example, rapeseed oil and olive oil were used as examples, but taking into consideration the above results and common technical knowledge (for example, the findings described in (S. Kato et al. npj Sci. Food, 2:1, 2018)), it is clear that similar judgments can be made for other oils and fats.

Claims

1. A method for identifying the cause of fat or oil oxidation, comprising: Measuring the near-infrared spectrum of the test oil or fat; A step of quantifying the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the test oil or fat from near-infrared spectroscopic data obtained in a part of the wavenumber range measured in the step based on a calibration curve prepared in advance using near-infrared spectroscopic spectra; A step of identifying the cause of oxidation of fats and oils from the quantification results; A method comprising:

2. The calibration curve is Measuring near-infrared spectra of a plurality of oil and fat standard samples having different degrees of oxidation; Quantifying the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the oil and fat standard sample; A step of preparing a calibration curve from near-infrared spectroscopic data obtained in all or part of the wavenumber range of the measured wavenumber and the quantified content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation; 2. The method of claim 1, wherein the method is obtained by a method comprising:

3. The wave number region is Measuring near-infrared spectra of a plurality of oil and fat standard samples having different degrees of oxidation; analyzing the near-infrared spectral data obtained in all or part of the wavenumber range of the measured wavenumber by principal component analysis; determining a wavenumber region based on the analysis results; The method according to claim 1 or 2, wherein the temperature is determined by a method comprising:

4. The wave number region is 5500 to 4500 cm -1 and / or 7500 to 6000 cm -1 The method according to any one of claims 1 to 3, wherein

5. A program executed on a computer, Measuring the near-infrared spectrum of the test oil; Based on a calibration curve prepared in advance using the near-infrared spectroscopy spectrum, the near-infrared spectroscopy spectrum data obtained in all or part of the wavenumber range measured in the above step is used to quantify the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the test oils and fats; Identifying the cause of oxidation of fats and oils from the quantification results; A program for identifying the cause of fat and oil oxidation, characterized by causing the computer to execute the above.

6. Regarding the creation of the calibration curve, Measuring near-infrared spectra of a plurality of oil and fat standard samples having different degrees of oxidation; Quantifying the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the oil and fat standard sample; A step of creating a calibration curve from near-infrared spectroscopic data obtained in all or part of the wavenumber range of the measured wavenumber range and the quantified content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation; The program for identifying the cause of fat and oil oxidation according to claim 5, wherein the program causes the computer to execute the above steps.

7. The wave number region is Measuring near-infrared spectra of a plurality of oil and fat standard samples having different degrees of oxidation; analyzing near-infrared spectral data obtained in all or part of the measured wavenumber range by principal component analysis; determining a wavenumber domain based on the analysis results; The program for identifying the cause of fat and oil oxidation according to claim 5 or 6, characterized in that the program is determined by causing the computer to execute the above.

8. A measurement unit for measuring the near-infrared spectrum of the test oil or fat; A calculation unit that quantifies the content of lipid hydroperoxides derived from radical oxidation and / or lipid hydroperoxides derived from singlet oxygen oxidation in the test oil or fat from near-infrared spectroscopic data obtained in all or part of the wavenumber range measured in the measurement unit based on a calibration curve prepared in advance using the near-infrared spectroscopic spectrum; an evaluation unit that identifies the cause of oxidation of fats and oils from the quantification results; An analytical device comprising:

9. In the wave number region, A measurement unit that measures near-infrared spectra of a plurality of oil and fat standard samples with different degrees of oxidation; an analysis unit that analyzes near-infrared spectrum data obtained in all or part of the wavenumber range of the measured wavenumber by principal component analysis; an evaluation unit that determines a wavenumber range based on the analysis results; The analytical device of claim 8 , further comprising a mechanism for determining by:

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