A method for rapidly detecting the ARA content and total oil in fermentation broth

Abstract

The present invention relates to a method for rapidly detecting the content of ARA and total oil in fermentation broth. The method uses near-infrared spectroscopy analysis technology and includes model establishment and sample measurement steps. In both the model establishment and sample measurement steps, sample pretreatment is carried out: the bacteria in the fermentation broth are processed until the water content of the bacteria is less than or equal to 30%, and then placed in a cup body. By carrying out sample pretreatment and improving the detection method in both the model establishment and sample measurement steps of the near-infrared analysis method, the accuracy of the detection results can be significantly improved.

Description

Technical Field

[0001] The present invention relates to the field of analytical chemistry, and particularly to a method for rapidly detecting the content of ARA and total oil in fermentation broth. Background Art

[0002] The detection of the content of ARA and oil content in fermentation broth is a cumbersome task, which requires cumbersome steps such as high-temperature oil extraction, methylation, solvent extraction, and on-machine detection. It takes a long time, consumes a lot of solvents, is not environmentally friendly and has a high cost. Therefore, it is of practical significance to develop a rapid detection method applicable to the ARA fermentation broth system.

[0003] At present, the nuclear magnetic resonance content analyzer uses nuclear magnetic resonance technology and is based on an embedded development platform and digital signal processing technology, and can realize the rapid determination of the oil content rate of oil-containing crops. However, it is difficult to realize the determination of the ARA content, and the applicable detection fields have great limitations.

[0004] Near-infrared analysis technology has the advantages of rapidity, non-destructiveness, high efficiency, low cost, etc., and has a wide range of application fields. It is an organic combination of near-infrared equipment, chemometric software and near-infrared models. Near-infrared technology is a quantitative analysis based on the position and intensity of spectral absorption peaks generated by chemical components in a sample. The key technology for detecting using NIR spectra is to establish a quantitative functional relationship between the two. The basic process includes: first, collect representative samples (whose composition and variation range are close to the samples to be analyzed), use standard chemical methods to determine the chemical components of the samples, then collect the spectral data of the samples, and perform regression calculations on the spectral data and chemical analysis and detection data through chemometric software to determine the functional relationship, and then establish a near-infrared model; when analyzing samples, first scan the samples to be tested, and according to the spectral data of the samples to be tested, the component content of the samples to be tested can be calculated using the established near-infrared model. There is no near-infrared analysis method for detecting ARA in fermentation broth in the existing public technologies, and Mortierella alpina in the ARA fermentation broth is a filamentous bacterial cell, and its morphology is different from that of yeast and algae with regular morphologies such as oval, elliptical, spherical, etc., resulting in difficulty in establishing an accurate model with the spectral data collected by the conventional method for samples of the ARA fermentation broth. Summary of the Invention

[0005] Aiming at the deficiencies existing in the prior art, the present invention provides a method for rapidly detecting the content of ARA and total oil in fermentation broth, and improves the accuracy of detection results through sample pretreatment.

[0006] The present invention provides a method for rapidly detecting the content of ARA and total oil in fermentation broth, which adopts near-infrared spectroscopy analysis technology and includes model establishment and sample measurement steps; sample pretreatment is performed in both the model establishment and sample measurement steps: the bacterial cells in the fermentation broth are processed until the water content of the bacterial cells is less than or equal to 30% and then placed in a cup body.

[0007] Near-infrared technology is an organic combination of near-infrared devices, chemometric software, and near-infrared models. In the existing technology, it is generally believed that the near-infrared model is the core and key to the accurate detection of near-infrared devices. Therefore, in view of the problem that the existing near-infrared methods cannot accurately determine the ARA content in the fermentation broth, the researchers focused on improving the model, that is, trying to find a more suitable functional relationship between the near-infrared spectral data of the sample and the chemical analysis and detection data. However, the present invention takes a different approach and discovers that performing sample pretreatment in both the model establishment and sample measurement steps, that is, treating the bacteria in the fermentation broth until the water content of the bacteria is less than or equal to 30% and placing it in a cup, instead of the traditional plastic bag containing the fermentation broth, can significantly improve the accuracy of the detection results.

[0008] According to the method for rapidly detecting the ARA content and total oil in the fermentation broth provided by the present invention, the bacteria in the fermentation broth are treated to have a water content of 15-25%. This operation can be achieved by combining or separately operating methods such as centrifuging, squeezing, and blotting to dry the water after washing the bacteria. Among them, washing the bacteria is mainly to wash away the attached culture medium components, particles, etc. on the bacteria.

[0009] The present invention studies and discovers that the detection results of treating the bacteria in the fermentation broth to wet bacteria with a water content of 15-25% are more accurate than those of treating them to dry bacteria with a water content of less than 10%. In the present invention, the bacteria in the fermentation broth can be treated into wet bacteria by washing the bacteria and then using methods such as filtration, centrifuging, squeezing, and blotting. If they are to be treated into dry bacteria, a further drying step can be carried out. Among them, washing the bacteria is mainly to wash away the attached culture medium components, particles, etc. on the bacteria.

[0010] According to the method for rapidly detecting the ARA content and total oil in the fermentation broth provided by the present invention, the near-infrared spectrometer used is FT9700, and the cup is a sample cup supporting FT9700.

[0011] The near-infrared device is also related to the near-infrared model. The near-infrared spectrometer used in the present invention is FT9700, and its specific parameters are as follows:

[0012] Light source type: An air-cooled, pre-calibrated, and hot-spot stable tungsten halogen light source is used. Beam splitter: Wide-range multi-coated CaF2.

[0013] Vibration damping device: The optical table is isolated from the chassis, and it has good shock resistance.

[0014] Instrument sealing and drying: The optical table, sample chamber, and detector chamber have independent drying and sealing.

[0015] Resolution: 0.2 - 6.4 nm, at 1390 nm (near-infrared region) or 1 cm -1 to 64 cm -1Adjustable.

[0016] Noise: <15 uAbs (1 minute, RMS).

[0017] Spectral range: 700 - 2500 nm (14300 - 4000 cm -1 )

[0018] Wavelength accuracy: better than 0.028 nm (at 1670 nm); or better than 0.1 cm -1 (at 6000 cm -1 )

[0019] Wavelength repeatability: better than 0.004 nm (at 1390 nm); or better than 0.02 cm -1 (at 7200 cm -1 )

[0020] This model of near-infrared spectrometer is equipped with a sample cell made of sapphire. When the sample to be measured is generally a fermentation broth, those skilled in the art usually use plastic bags for detection. The present invention finds that using this sample cell has a better effect.

[0021] According to the method for rapidly detecting the ARA content and total oil in fermentation broth provided by the present invention, the spectral range of the near-infrared spectrometer is 700 - 2500 nm, and near-infrared spectral data within the said spectral range are selected when establishing the model.

[0022] According to the method for rapidly detecting the ARA content and total oil in fermentation broth provided by the present invention, the establishment of the model includes establishing a one-to-one correspondence between the near-infrared spectral data of the sample and the measured values of the ARA content and the total oil respectively, to obtain a near-infrared model.

[0023] It should be noted that establishing the one-to-one correspondence is actually carried out by fitting through computer software. The Unscrambler modeling software used in the specific implementation manner of the present invention can obtain the near-infrared model when the near-infrared spectral data of the sample and the measured values of the ARA content and the total oil are input into the computer.

[0024] According to the method for rapidly detecting the ARA content and total oil in fermentation broth provided by the present invention, the measured value of the ARA content is obtained based on the existing standard chemical detection method; the measured value of the total oil is obtained based on the nuclear magnetic resonance detection method. In short, both the measured value of the ARA content and the measured value of the total oil are measured by known standard methods.

[0025] According to the method for rapidly detecting the ARA content and total oil in fermentation broth provided by the present invention, in the step of establishing the model, the number of samples is greater than 100. The more the number of samples, the higher the detection accuracy of the model.

[0026] According to the method for rapidly detecting the ARA content and total oil in the fermentation broth provided by the present invention, the standard deviation of prediction of the near-infrared model can be less than 1%, and the correlation coefficient is greater than 0.98.

[0027] The accuracy of the near-infrared model can be referred to the SECV (standard deviation of prediction) and R of the model itself 2 (correlation coefficient). The smaller the SECV and the larger the R 2 , the higher the accuracy of the near-infrared model. The near-infrared model obtained by the present invention has high accuracy.

[0028] According to the method for rapidly detecting the ARA content and total oil in the fermentation broth provided by the present invention, after performing the sample measurement step, the measured near-infrared spectral data is imported into the established near-infrared model, and the ARA content and total oil of the sample to be measured are obtained through calculation by results plus software.

[0029] For the sample measured by the method for rapidly detecting the ARA content and total oil in the fermentation broth provided by the present invention, the probability that the deviation of the ARA content result is less than 1% can reach 84%, and the probability that the deviation of the oil content result is less than 1% can reach 65%.

[0030] According to the method for rapidly detecting the ARA content and total oil in the fermentation broth provided by the present invention, the fermentation broth is Mortierella alpina fermentation broth.

[0031] The present invention provides a method for rapidly detecting the ARA content and total oil in the fermentation broth. By performing sample pretreatment in both the model establishment and sample measurement steps of the near-infrared analysis method, that is, treating the bacteria in the fermentation broth until the water content of the bacteria is less than or equal to 30% and placing it in a cup instead of the traditional plastic bag containing the fermentation broth, the accuracy of the detection result can be significantly improved. Description of the Drawings

[0032] Figure 1 It is the ARA content model diagram obtained in Example 1;

[0033] Figure 2 It is the total oil model diagram obtained in Example 1;

[0034] Figure 3 It is the ARA content model diagram obtained in Example 2;

[0035] Figure 4 It is the total oil model diagram obtained in Example 2;

[0036] Figure 5 It is the ARA content model diagram obtained in Example 3;

[0037] Figure 6 It is the total oil model diagram obtained in Example 3;

[0038] Figure 7Distribution ratio diagram of ARA content prediction deviation for the method in Example 2;

[0039] Figure 8 Distribution ratio diagram of total oil prediction deviation for the method in Example 2;

[0040] Figure 9 Distribution ratio diagram of ARA content prediction deviation for the method in Example 3;

[0041] Figure 10 Distribution ratio diagram of total oil prediction deviation for the method in Example 3;

[0042] Figure 11 Distribution ratio diagram of ARA content prediction deviation for the method in Example 1;

[0043] Figure 12 Distribution ratio diagram of total oil prediction deviation for the method in Example 1. Detailed implementation manners

[0044] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0045] Unless otherwise specified, the raw materials involved in the embodiments of the present invention can be obtained through commercial channels.

[0046] Example 1

[0047] This example provides a method for rapidly detecting the ARA content and total oil in fermentation broth. The specific steps are as follows:

[0048] 1. Model establishment

[0049] 1.1 Collect ARA fermentation broth samples: The collected samples have compositions similar to the samples to be measured, and the number of samples is 148.

[0050] 1.2 Sample pretreatment: Filter the ARA fermentation broth through gauze to remove the liquid, wash the bacterial cells with tap water, centrifuge at 4000 r / min for 10 minutes, then squeeze out the water until the water content is about 23%, pour the obtained wet bacterial cells into the sample cup of FT9700, and flatten them (no light can be seen through the surface of the sample), and set aside.

[0051] The method for measuring the water content of the wet bacterial cells is as follows: Weigh the mass m1 of the bacterial cells with the water squeezed out, place them in an oven at 105 °C and bake until constant weight, and the mass is m2.

[0052] Water content = (m1 - m2) / m1 * 100%

[0053] 1.3 Near-infrared spectrum data acquisition: Place the sample obtained from the above pretreatment in the detection chamber of the FT9700 instrument for detection, and collect the near-infrared spectrum data within the spectral range of 700 - 2500 nm.

[0054] 1.4 Obtaining the measured value of ARA content: Take a part of the fermentation broth and dry it to obtain the bacterial cells. Weigh about 0.1 g of the bacterial cells and place them in a 5 mL volumetric flask. Add 1 mL of NaOH - CH3OH, shake well, place it in a water bath at 60 °C for 30 min, and take it out and shake well every 7 - 8 minutes. After 30 min, take out the volumetric flask, add 1 mL of BF3 - CH3OH solution, shake well, place it in a water bath at 60 °C for 30 min, and take it out and shake well every 7 - 8 minutes. Take out the treated sample, shake well, cool it to room temperature, add a few milliliters of n - hexane, shake well, let it stand, take the supernatant and filter it through a membrane, and detect it by GC.

[0055] 1.5 Obtaining the measured value of total oil: Take a part of the fermentation broth and dry it to obtain the bacterial cells. Weigh about 5 g of the bacterial cells in an extraction filter paper tube. After the extraction flask is dried to a constant weight, record its mass. Install the fat extraction device, add 30 mL of anhydrous ether, react for two hours, then blow the ether to dryness with nitrogen, place it in an oven at 105 °C for two hours, take it out, cool it, and weigh it again. Calculate the total oil content according to the mass difference before and after.

[0056] Note that the order of 1.3, 1.4, and 1.5 here can be arbitrarily adjusted.

[0057] 1.6 Model establishment: Input the near-infrared spectrum data and the measured value of ARA content into the computer, and use the Unscrambler software for fitting to obtain the ARA content model (as Figure 1 shown);

[0058] Input the near-infrared spectrum data and the measured value of total oil into the computer, and use the Unscrambler software for fitting to obtain the total oil model (as Figure 2 shown).

[0059] 2. Detection of the sample to be measured

[0060] Take the sample to be measured, perform the pretreatment according to 1.2, and collect the near-infrared spectrum data of the processed sample according to 1.3. Import the collected spectrum data into the above ARA content model and total oil model respectively, and calculate the ARA content and total oil through the results plus software.

[0061] Example 2

[0062] This example provides a method for quickly detecting the ARA content and total oil in the fermentation broth. The specific steps are as follows:

[0063] 1. Model establishment

[0064] 1.1 Collect ARA fermentation broth samples: The number of samples is 270;

[0065] 1.2 Sample pretreatment: Filter the ARA fermentation broth through gauze to remove the liquid, rinse the bacterial cells with tap water, and then dry the moisture until the water content is about 9.8%. Pour the obtained dried bacterial cells into the sample cup of FT9700, flatten them, and set aside;

[0066] 1.3 Near-infrared spectrum data collection: Place the samples obtained from the above pretreatment in the detection chamber of the FT9700 instrument for detection, and collect the near-infrared spectrum data within the spectral range of 700 - 2500 nm;

[0067] 1.4 Obtain the measured value of ARA content: Take a part of the fermentation broth and dry it to obtain bacterial cells. Weigh about 0.1 g of the bacterial cells and place them in a 5 mL volumetric flask. Add 1 mL of NaOH-CH3OH, shake well, and place it in a water bath at 60 °C for 30 min. Take it out and shake well every 7 - 8 minutes. After 30 min, take out the volumetric flask, add 1 mL of BF3-CH3OH solution, shake well, and place it in a water bath at 60 °C for 30 min. Take it out and shake well every 7 - 8 minutes. Take out the treated sample, shake well, cool it to room temperature, add a few milliliters of n-hexane, shake well, let it stand, take the supernatant and filter it through a membrane, and detect it by GC.

[0068] 1.5 Obtain the measured value of total oil: Take a part of the fermentation broth and dry it to obtain bacterial cells. Weigh about 5 g of the bacterial cells in an extraction filter paper tube. Record the mass of the extraction flask after drying it to a constant weight. Install the extraction device, add 30 mL of anhydrous ether, react for two hours, then blow the ether to dryness with nitrogen, place it in an oven at 105 °C for two hours, take it out, cool it, and weigh it again. Calculate the total oil content based on the mass difference before and after.

[0069] Note that the order of 1.3, 1.4, and 1.5 here can be arbitrarily adjusted;

[0070] 1.6 Model establishment: Input the near-infrared spectrum data and the measured value of ARA content into the computer, and use the Unscrambler software for fitting to obtain the ARA content model (as Figure 3 shown);

[0071] Input the near-infrared spectrum data and the measured value of total oil into the computer, and use the Unscrambler software for fitting to obtain the total oil model (as Figure 4 shown).

[0072] 2. Detection of samples to be tested

[0073] Take the sample to be tested, perform pretreatment according to 1.2, collect near-infrared spectral data of the processed sample according to 1.3, import the collected spectral data into the above ARA content model and total oil model respectively, and calculate the ARA content and total oil through results plus software.

[0074] Example 3

[0075] This example provides a method for quickly detecting the ARA content and total oil in fermentation broth, and the specific steps are as follows:

[0076] 1. Model establishment

[0077] 1.1 Collect ARA fermentation broth samples: The number of samples is 290;

[0078] 1.2 Sample pretreatment: Filter the ARA fermentation broth through gauze to remove the liquid, rinse the bacterial cells with tap water, and then dry the moisture to a water content of about 9.5% (the same drying treatment method as in Example 2). Seal the obtained dry bacterial cells with a plastic bag and store for later use;

[0079] 1.3 Near-infrared spectral data collection: Place the sample obtained from the above pretreatment in the detection chamber of the FT9700 instrument for detection, and collect near-infrared spectral data in the spectral range of 700 - 2500 nm;

[0080] 1.4 Obtain the measured value of ARA content: Take a part of the fermentation broth and dry it to obtain bacterial cells. Weigh about 0.1 g of the bacterial cells and place them in a 5 mL volumetric flask. Add 1 mL of NaOH-CH3OH and shake well. Place it in a 60 °C water bath for 30 min, and take it out and shake well every 7 - 8 minutes. After 30 min, take out the volumetric flask, add 1 mL of BF3-CH3OH solution, shake well, and place it in a 60 °C water bath for 30 min, and take it out and shake well every 7 - 8 minutes. Take out the treated sample, shake well, cool it to room temperature, add a few milliliters of n-hexane, shake well, let it stand, take the supernatant and filter it through a membrane, and detect it by GC.

[0081] 1.5 Obtain the measured value of total oil: Take a part of the fermentation broth and dry it to obtain bacterial cells. Weigh about 5 g of the bacterial cells and place them in an extraction filter paper tube. Record the mass of the extraction flask after drying to a constant weight. Install the extraction device, add 30 mL of anhydrous ether, react for two hours, then blow the ether to dry by nitrogen, place it in an oven at 105 °C for two hours, take it out, cool it, and weigh it again. Calculate the total oil content according to the mass difference before and after.

[0082] Note that the order of 1.3, 1.4, and 1.5 here can be arbitrarily swapped.

[0083] 1.6 Model establishment: Enter the near-infrared spectral data and the measured value of ARA content into the computer, and use Unscrambler software for fitting to obtain the ARA content model (such as Figure 5as shown);

[0084] Input the near-infrared spectral data and the measured total oil values into the computer, and use Unscrambler software for fitting to obtain the total oil model (as Figure 6 shown).

[0085] 2. Detection of samples to be measured

[0086] Take the samples to be measured, perform pretreatment according to 1.2, collect near-infrared spectral data on the processed samples according to 1.3, import the collected spectral data into the above ARA content model and total oil model respectively, and calculate the ARA content and total oil through results plus software.

[0087] Model parameters

[0088] The model parameters in Examples 1-3 are statistically shown as follows:

[0089] Table 1

[0090]

[0091] It can be seen from the above results that near-infrared spectra have a high linear correlation with the total oil and ARA of dry bacterial cells and wet bacterial cells (R 2 > 0.95), and the accuracy of the detection results (the smaller the SECV, the better) from high to low is wet bacterial cells in cups > dry bacterial cells in cups > dry bacterial cells in bags.

[0092] Blind sample verification

[0093] Perform blind sample verification on the methods in Examples 1-3. There are a total of 49 samples. Now, the near-infrared prediction results and the detection results by the standard method are statistically shown as follows:

[0094] Table 2

[0095]

[0096]

[0097] To more intuitively understand the deviation situation of blind sample prediction, the deviation is divided into <0.5, 0.5 - 1.0, 1.0 - 1.5, 1.5 - 2.0, >2.0, a total of 5 levels, and the proportions in 49 samples are statistically shown as Figures 7 - 12 shown.

[0098] From the above results, it can be seen that the parameters of the wet cell model are better than those of the dry cell cup model. In the blind sample verification, for the model established with wet cells, the ARA prediction deviation of 84% of the blind samples is within 1%, and the total oil deviation of 65% of the blind samples is within 1%, which is better than the verification results of the dry cell cup model where the ARA prediction deviation of 77% of the blind samples is within 1% and the total oil deviation of 63% of the blind samples is within 1%.

[0099] Comparative Example 1

[0100] This comparative example provides a method for rapidly detecting the ARA content and total oil in fermentation broth, and the specific steps are as follows:

[0101] 1. Model establishment

[0102] 1.1 Collect ARA fermentation broth samples: Pour the samples into the sample cups of FT9700;

[0103] 1.2 Near-infrared spectral data acquisition: Place the collected samples in the detection chamber of the FT9700 instrument for detection, and collect near-infrared spectral data within the spectral range of 700 - 2500 nm;

[0104] 1.3 Obtain the measured value of ARA content: Take a part of the fermentation broth and dry it to obtain the cells. Weigh about 0.1 g of the cells and place them in a 5 mL volumetric flask. Add 1 mL of NaOH - CH3OH, shake well, place it in a water bath at 60 °C for 30 min, and take it out and shake well every 7 - 8 minutes. After 30 min, take out the volumetric flask, add 1 mL of BF3 - CH3OH solution, shake well, place it in a water bath at 60 °C for 30 min, and take it out and shake well every 7 - 8 minutes. Take out the treated sample, shake well, cool it to room temperature, add a few milliliters of n-hexane, shake well, let it stand, take the supernatant and filter it through a membrane, and detect it by GC.

[0105] 1.4 Obtain the measured value of total oil: Take a part of the fermentation broth and dry it to obtain the cells. Weigh about 5 g of the cells in an extraction filter paper tube. After the extraction flask is dried to a constant weight, record its mass. Install the extraction device, add 30 mL of anhydrous ether, react for two hours, then blow the ether to dry by nitrogen, place it in an oven at 105 °C for two hours, take it out, cool it, and weigh it again. Calculate the total oil content according to the mass difference before and after.

[0106] Note that the order of 1.2, 1.3, and 1.4 here can be arbitrarily adjusted.

[0107] 1.5 Model establishment: Enter the near-infrared spectral data and the measured value of ARA content into the computer, and use Unscrambler software for fitting to obtain the ARA content model;

[0108] Enter the near-infrared spectral data and the measured value of total oil into the computer, and use Unscrambler software for fitting to obtain the total oil model.

[0109] 2. Detection of the sample to be measured

[0110] Take the sample to be measured, pour it into the sample cup of FT9700, collect the near-infrared spectral data according to 1.2, and import the collected spectral data into the above ARA content model and total oil model respectively. The ARA content and total oil are obtained through the calculation of the results plus software.

[0111] The model obtained in Comparative Example 1 was used for sample verification, and large data deviations and unstable data occurred. The specific details are as follows:

[0112] Table 3

[0113]

[0114] Although the present invention has been described in detail with general descriptions and specific embodiments above, based on the present invention, some modifications or improvements can be made, which are obvious to those skilled in the art. Therefore, these modifications or improvements made without departing from the spirit of the present invention all fall within the scope of protection required by the present invention.

Claims

1. A method for rapidly detecting the ARA content and total oil in fermentation broth, characterized in that, Adopt near-infrared spectroscopy analysis technology, including model establishment and sample measurement steps; In both the model establishment and sample measurement steps, sample pretreatment is carried out: the bacteria in the fermentation broth are processed until the water content of the bacteria is 15-25% and then placed in a cup body; The spectral range of the near-infrared spectrometer is 700-2500 nm, and the near-infrared spectral data within the said spectral range are selected when establishing the model; The said model establishment includes establishing a one-to-one correspondence between the near-infrared spectral data of the sample and the measured values of ARA content and total oil measured values respectively to obtain a near-infrared model; The said fermentation broth is Mortierella alpina fermentation broth.

2. The method for rapidly detecting the ARA content and total oil in the fermentation broth according to claim 1, wherein The near-infrared spectrometer adopted is FT9700, and the said cup body is a sample cup supporting FT9700.

3. The method for rapidly detecting the ARA content and total oil in the fermentation broth according to claim 2, characterized in that The measured value of ARA content is obtained based on the existing standard chemical detection method; And / or, the measured value of total oil is obtained based on the nuclear magnetic resonance detection method.

4. The method for rapidly detecting the ARA content and total oil in the fermentation broth according to claim 3, characterized in that, The number of the said samples is greater than 100.

5. The method for rapidly detecting the ARA content and total oil in the fermentation broth according to claim 4, wherein, After carrying out the said sample measurement step, the measured near-infrared spectral data are imported into the established near-infrared model, and the ARA content and total oil of the sample to be measured are calculated by results plus software.

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