Method for constructing global temperature compensation model for thermal oxidation rapeseed oil quality detection based on ultrasonic diagnosis technology

Abstract

The invention belongs to the technical field of edible vegetable oil quality analysis, and discloses a construction method of a global temperature compensation model for thermal oxidation rapeseed oil quality detection based on an ultrasonic diagnosis technology. The invention aims to solve the problem that the environment temperature change can influence the sound wave pulse signal when the rapeseed oil quality is detected by utilizing an ultrasonic diagnosis technology. According to the method, ultrasonic data parameters and physicochemical data parameters at each integer temperature within the temperature range of 22-32 DEG C are integrated, and a correlation model is constructed through a partial least squares PLSR or a random forest method RF, so that the correlation model is adapted to a small number of samples required by the method; meanwhile, a training set, an internal verification set and an external verification set are introduced to perform multiple verification and evaluation on the correlation model, and the prediction performance and stability of the correlation model are ensured through multiple model optimization, so that a quality index prediction value output by the model is ensured to be closer to an actual quality index, and the accuracy and effectiveness of detection data are ensured.

Description

Technical Field

[0001] The invention belongs to the technical field of edible vegetable oil quality analysis, and in particular, relates to a method for constructing a global temperature compensation model for thermal oxidation rapeseed oil quality detection based on ultrasonic diagnostic technology. Background Art

[0002] As a device specially used for testing edible oil, the ultrasonic pulse echo system realizes the detection function by receiving and transmitting specific pulse electrical signals. The device has many significant advantages in the field of edible oil detection, including its rapid analysis capability, which can complete the detection and analysis of edible oil related parameters in a short time; it has non-invasive characteristics, and will not damage the internal structure and properties of edible oil during the detection process, ensuring that the integrity and quality of edible oil are not affected; it has high sensitivity. It can accurately perceive small changes and potential problems in edible oil, effectively improving the accuracy of detection; and low operating costs during the detection process. The pulse echo system mainly consists of 6 parts: pulse transceiver, oscilloscope, ultrasonic probe, sample stage, temperature control device and computer.

[0003] In an ultrasonic probe, its metal structure will be affected by the disordered changes in ambient temperature, which will directly or indirectly act on the sensor, causing the parameter characteristics of the sensor signal to change. Specifically, when the temperature changes by 1°C, the change in the ultrasonic sound velocity is about 3.1-3.6m / s. Under laboratory conditions, because the environment is in a constant temperature state, ultrasonic technology can be used to measure small volume samples. However, when performing measurement operations in an industrial environment, this measurement scheme will encounter huge obstacles. In view of this, in order to ensure the accuracy and effectiveness of the measurement, it is necessary to use appropriate methods to compensate for the impact of temperature on the ultrasonic signal.

[0004] Temperature compensation methods can be mainly divided into two categories: hardware compensation and software compensation. As for hardware compensation, due to the limitations of the internal space of the power transformer, its production cost is relatively high, and it faces many restrictions in actual engineering applications. The software compensation method has the advantages of high accuracy and low cost, and has become the main form of temperature compensation. It should be noted that the mechanism of the influence of temperature on the error of acoustic signal detection is complex. How to construct a suitable temperature compensation model to achieve high-precision compensation is one of the key issues in this research field, and it is also the difficulty. Summary of the invention

[0005] The purpose of the present invention is to provide a method for constructing a global temperature compensation model for thermal oxidation rapeseed oil quality detection based on ultrasonic diagnostic technology, aiming to solve the problem that ambient temperature changes will affect the acoustic pulse signal when using ultrasonic diagnostic technology to detect rapeseed oil quality.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The method for constructing a global temperature compensation model for thermally oxidized rapeseed oil quality detection based on ultrasonic diagnostic technology is characterized by comprising the following steps:

[0008] S1, under each integer temperature condition in the range of 22-32°C, collect ultrasonic data and physical and chemical data of rapeseed oil after thermal oxidation, integrate all collected ultrasonic data as independent variable X, integrate all collected physical and chemical data quality indicators as dependent variable Y, and use partial least squares method PLSR or random forest method RF to establish the association model between X and Y;

[0009] S2, sort out the data set containing independent variables X and dependent variables Y, and mark the samples as (x 1 ,y 1 ), (x 2 ,y 2 ),…,(x i ,y i ), where x i represents the temperature and ultrasonic data parameters of the i-th sample, y i Represents the physical and chemical data quality index parameter of the i-th sample; each time, one sample is selected as the validation set, and the remaining samples are used as the training set. The model training and validation process is carried out i times in total. In each iteration, the prediction error or goodness of fit index is calculated, and finally the results of all iterations are comprehensively evaluated;

[0010] S3, randomly collecting ultrasonic data of thermally oxidized rapeseed oil under a temperature range of 22-32°C, inputting the collected ultrasonic data into the model, and verifying the accuracy of the model by comparing the quality index prediction value of the model with the actual quality index measurement value;

[0011] S4, at room temperature, randomly collect ultrasonic data of thermally oxidized rapeseed oil, and input the collected ultrasonic data into the model, and verify the accuracy of the model by comparing the quality index prediction value of the model with the actual quality index measurement value.

[0012] As a further preferred embodiment of the present technical solution, in step S1, the rapeseed oil is sampled as follows: 600 mL is taken from each of the three rapeseed oil samples and placed in containers respectively, the containers are placed in a water bath and heated to 180±2°C within 30 minutes, and then the constant temperature is maintained for continuous heating for 12 hours; heating is continued for 7 days to obtain a total of 21 rapeseed oil samples.

[0013] As a further preferred embodiment of the present technical solution, an ultrasonic pulse echo system device is used to perform ultrasonic detection on the sampled rapeseed oil sample, wherein the ultrasonic pulse echo system device comprises a computer, a pulse transceiver, an oscilloscope, a water bath, a sample table, an ultrasonic probe, a thermometer probe and a sample holder, and the ultrasonic determination method of the ultrasonic pulse echo system device is:

[0014] S101, verify the accuracy and stability of the ultrasonic pulse echo system device by measuring the speed of sound in distilled water at 26°C;

[0015] S102, filtering the rapeseed oil sample using a sieve, and then slowly pouring the oil sample into a sample container;

[0016] S103, placing the sample stage in a water bath to ensure that the temperature remains constant and controllable during the measurement process;

[0017] S104, immersing the signal transmitting end of the ultrasonic probe and the thermometer probe into the oil sample to be tested, removing bubbles around the ultrasonic probe, and ensuring that the placement position of the thermometer probe does not overlap with the transmission path of the sound wave pulse;

[0018] S105, start the pulse transceiver and the oscilloscope, after the oil sample temperature and the ultrasonic signal are stable, use the computer to collect and save the ultrasonic data in real time, and perform three parallel measurements to ensure the accuracy of the results; obtain ultrasonic spectrum data through the computer, and draw a line graph with time as the horizontal axis and amplitude as the vertical axis to obtain a time domain spectrum, and perform fast Fourier transform on the time domain spectrum to obtain a frequency domain spectrum, and obtain characteristic data of the sound wave through the time domain spectrum and the frequency domain spectrum, including the following ultrasonic data parameters:

[0019] Ultrasonic sound velocity v represents the distance ultrasonic waves propagate per unit time, and its calculation formula is:

[0020]

[0021] Where, v represents the ultrasonic velocity; t 1 and t 0 Respectively represent the appearance time of the first echo and the appearance time of the initial peak; L represents the flight distance of the ultrasound within the time interval;

[0022] The attenuation coefficient α indicates the degree of attenuation of sound waves during propagation, and its calculation formula is:

[0023]

[0024] In the formula, α represents the attenuation coefficient; 1 and A 2 is the maximum amplitude of the first echo and the maximum amplitude of the second echo, and L is the distance between the two echoes;

[0025] The frequency domain spectrum peak value Af refers to the maximum amplitude observed within the frequency spectrum;

[0026] The peak frequency Ff represents the frequency corresponding to the peak of the frequency domain spectrum;

[0027] FFT25, FFT50 and FFT75 represent the minimum frequency values ​​when the total received energy reaches 25%, 50% and 75%, respectively.

[0028] As a further preferred embodiment of the present technical solution, the physical and chemical data of the thermally oxidized rapeseed oil to be collected include the acid value, and the data collection method of the acid value is as follows: 1±0.0001g of the rapeseed oil sample is fully dissolved in 20mL of ether-isopropanol solution; phenolphthalein is used as an indicator and a KOH solution is used to titrate the free fatty acids; when the color turns to light pink, the titration is stopped and maintained for 30s, and a blank titration is performed at the same time;

[0029] The acid value is calculated according to the following formula:

[0030]

[0031] Where AV represents the acid value; v and v 0 represent the volume of KOH solution used to titrate the thermally oxidized oil sample and the blank, respectively; c represents the concentration of the KOH solution; and m represents the weight of the sample.

[0032] As a further preference of the present technical solution, the physical and chemical data of the thermally oxidized rapeseed oil to be collected include iodine value, and the data collection method of the iodine value is as follows: 0.2±0.0001g of rapeseed oil sample is fully dissolved in 20mL of cyclohexane-glacial acetic acid solution; 25mL of Wei's reagent is added, mixed evenly and placed in the dark for reaction for 1h; after the reaction is completed, 20mL of potassium iodide solution and 150mL of water are added; sodium thiosulfate solution is used for titration, and 3 drops of starch solution are added after the yellow color of the liquid disappears, and the titration is continued until the blue color just disappears, and a blank titration is performed at the same time;

[0033] The iodine value is calculated according to the following formula:

[0034]

[0035] Where IV represents the iodine value; v and v 0 represent the volume of sodium thiosulfate solution used to titrate the thermally oxidized oil sample and the blank, respectively; c represents the concentration of the sodium thiosulfate solution; and m represents the weight of the sample.

[0036] As a further preferred embodiment of the present technical solution, the physical and chemical data of the thermally oxidized rapeseed oil to be collected include the content of polar components, and the data collection method of the content of polar components is as follows: 1±0.0001g of rapeseed oil sample is dissolved in a mixture of petroleum ether and ether, and then poured into a silica gel column filled with silica gel, and the non-polar fraction is eluted using the mixture of petroleum ether and ether; at the same time, about 200mL of eluate is collected in a dry 500mL round-bottom flask, and the collected eluate is placed in a rotary evaporator under a 60°C water bath condition and rotary evaporated to near dryness, and then the residue is placed in a vacuum constant temperature drying oven at 40°C and further dried for 20min; after the container is cooled, the flask is accurately weighed;

[0037] The calculation of the polar component content is completed according to the following formula:

[0038]

[0039] Where, TPC represents the content of polar components; m 1 and m 2 represent the weight of the blank flask and the flask containing the polar component, respectively; m represents the weight of the sample.

[0040] As a further preferred embodiment of the present technical solution, the physical and chemical data of the thermally oxidized rapeseed oil to be collected include fatty acids, and the data collection method of the fatty acids includes oil sample pretreatment and fatty acid determination;

[0041] The oil sample pretreatment comprises the following steps: taking 0.1±0.0001 g of rapeseed oil sample after vortex treatment for 2 minutes, placing it in a 10 mL test tube; adding 2 mL of 2% sodium hydroxide methanol solution into the test tube, vortexing for 2 minutes, covering the tube with a stopper and placing it in a water bath at 75±1° C. for 20 minutes; after cooling, adding 1 mL of 15% boron trifluoride methanol solution, vortexing again for 1 minute, covering the tube with a stopper and placing it in a water bath at 75±1° C. for 10 minutes; accurately adding 2 mL of n-heptane , vortex for 2 minutes, add 1mL of saturated sodium chloride aqueous solution, and then let it stand to separate; draw 1mL of the upper n-heptane extraction solution, transfer it to a 10mL test tube, accurately add 4mL of n-heptane, and add about 1g of anhydrous sodium sulfate, vortex for 1min, and let it stand for 5min; draw the upper n-heptane extraction solution, dilute it 10 times with n-heptane as the diluent; take 1mL of the diluted solution, filter the sample solution with a 0.22μL hydrophobic membrane, and collect the filtered solution into a sample injection bottle for detection and analysis;

[0042] The fatty acid determination adopts a gas chromatography-mass spectrometer, comprising the following steps: separation using an HP-5 silica gel capillary column and a 20:1 split mode; using helium as a carrier gas with a flow rate of 1 mL / min, an ion source temperature of 230° C., an injector temperature maintained at 250° C., a column oven temperature initially maintained at 120° C. for 2 min, then increased to 200° C. at 4° C. / min and maintained for 2 min, and finally increased to 240° C. at 3° C. / min and maintained for 2 min; recording a chromatogram by monitoring a total ion chromatogram with an m / z range of 40-440; and calculating the content of a given component i by calculating the percentage of the corresponding peak area to the sum of the peak areas of all components by the following formula:

[0043]

[0044] In the formula, FA i Represents the percentage of a certain fatty acid in the total fatty acids; A Si Represents the sum of the peak areas of each fatty acid methyl ester in the sample; Represents the coefficient of conversion of a fatty acid methyl ester into fatty acids.

[0045] As a further optimization of the present technical solution, in step S1, the normality test and variance homogeneity test are performed on the collected ultrasound data and physical and chemical data, and the data indicators that conform to the normal distribution and pass the variance homogeneity test are subjected to variance analysis to test the significance between groups, and the Turkey test is used for post hoc comparison; the data indicators that do not conform to the normal distribution are subjected to significance analysis using non-parametric tests, and multiple comparisons are performed using Nemenyi tests;

[0046] The collected ultrasound data and physical and chemical data were standardized, and the calculation formula was:

[0047]

[0048] In the formula, x new represents the standardized data, x i represents the i-th data, represents the mean and σ represents the standard deviation.

[0049] As a further optimization of the technical solution, in step S1, a variable importance projection is set to evaluate the contribution of each variable to the model, and data indicators with a variable importance projection score greater than or equal to 5 are selected for subsequent model training to enhance the generalization ability of the model; wherein the calculation formula of the variable importance projection score is:

[0050]

[0051] In the formula, VIP jis the variable importance projection, p is the total number of variables, R is the number of principal components, and w aj is the weight of variable j on the ath principal component, d a is the explained variance of the ath principal component.

[0052] As a further optimization of the technical solution, in steps S2, S3, and S4, based on the root mean square error RMSE, the mean absolute error MAE, and the determination coefficient R 2 Evaluate the performance of the temperature compensation model;

[0053] The method based on the root mean square error RMSE as a measure of the model prediction accuracy is:

[0054]

[0055] Among them, y i and Represent the i-th predicted value and reference value respectively, and n represents the number of data;

[0056] The method based on mean absolute error MAE as a measure of model prediction accuracy is:

[0057]

[0058] Among them, y i and Represent the i-th predicted value and reference value respectively, and n represents the number of data;

[0059] Based on the coefficient of determination R 2 The method to evaluate the accuracy of the model is:

[0060]

[0061] Among them, Y p and Y a Represent the predicted data and reference data respectively. Represents the mean value of the reference data.

[0062] Compared with the prior art, the present invention has the following beneficial effects:

[0063] The present invention establishes a temperature compensation model for ultrasonic detection of thermally oxidized rapeseed oil based on a global temperature compensation method, which integrates ultrasonic data parameters and physical and chemical data parameters at various integer temperatures within the temperature range of 22-32°C, and constructs an association model through a partial least squares method PLSR or a random forest method RF, so that it is adapted to the smaller number of samples required by the present invention. At the same time, a training set, an internal validation set and an external validation set are introduced to perform multiple validation and evaluation on the association model, and multiple model optimizations are performed to ensure the prediction performance and stability of the association model, ensure that the quality index prediction value output by the model is closer to the actual quality index, and ensure the accuracy and validity of the detection data. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0065] Figure 1 It is a schematic diagram of the construction process of the global temperature compensation model in the present invention;

[0066] Figure 2 A schematic diagram of the construction of the global temperature compensation model in the present invention;

[0067] Figure 3 It is a schematic structural diagram of the ultrasonic pulse echo system device adopted by the present invention;

[0068] Figure 4 A schematic diagram of the steps of an ultrasonic measurement method of an ultrasonic pulse echo system device adopted by the present invention;

[0069] Figure 5 A schematic diagram of a time domain spectrum obtained in a certain embodiment of the present invention;

[0070] Figure 6 It is a schematic diagram of a frequency domain spectrum obtained in a certain embodiment of the present invention. DETAILED DESCRIPTION

[0071] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0072] Example 1

[0073] like Figure 1 and Figure 2The method for constructing a global temperature compensation model for thermal oxidation rapeseed oil quality detection based on ultrasonic diagnostic technology includes the following steps:

[0074] S1, under each integer temperature condition in the range of 22-32°C, collect ultrasonic data and physical and chemical data of rapeseed oil after thermal oxidation, integrate all collected ultrasonic data as independent variable X, integrate all collected physical and chemical data quality indicators as dependent variable Y, and use partial least squares method PLSR or random forest method RF to establish the association model between X and Y;

[0075] S2, sort out the data set containing independent variables X and dependent variables Y, and mark the samples as (x 1 ,y 1 ), (x 2 ,y 2 ),…,(x i ,y i ), where x i represents the temperature and ultrasonic data parameters of the i-th sample, y i Represents the physical and chemical data quality index parameter of the i-th sample; each time, one sample is selected as the validation set, and the remaining samples are used as the training set. The model training and validation process is carried out i times in total. In each iteration, the prediction error or goodness of fit index is calculated, and finally the results of all iterations are comprehensively evaluated;

[0076] Since the number of samples in the present invention is small, the above steps are suitable for using the leave-one-out crossover method to evaluate the model performance, which enables each sample to be used as a test set separately, making full use of all data for training and testing, ensuring the wide applicability of the model, and providing an unbiased model performance estimate;

[0077] S3, randomly collecting ultrasonic data of thermally oxidized rapeseed oil under a temperature range of 22-32°C, inputting the collected ultrasonic data into the model, and verifying the accuracy of the model by comparing the quality index prediction value of the model with the actual quality index measurement value;

[0078] The above steps introduce an internal validation set for internal testing, which performs random sampling with replacement in the original sample set to train and validate the model multiple times, so that it can not only test the repeatability of the model, but also prevent the model from overfitting and overestimating the performance of the model;

[0079] S4, randomly collecting ultrasonic data of thermally oxidized rapeseed oil at room temperature, and inputting the collected ultrasonic data into the model, and verifying the accuracy of the model by comparing the quality index prediction value of the model with the actual quality index measurement value;

[0080] The above steps introduce an external validation set for external testing. It predicts data different from the original sample set to evaluate the performance and robustness of the model when facing unknown data. It can also test whether the model overfits the training data, which is conducive to verifying the robustness and credibility of the model.

[0081] More specifically, in step S1, the rapeseed oil is sampled as follows: 600 mL is taken from each of the three rapeseed oil samples and placed in containers respectively; the containers are placed in a water bath and heated to 180±2°C within 30 minutes, and then the constant temperature is maintained for continuous heating for 12 hours; heating is continued for 7 days to obtain a total of 21 rapeseed oil samples; it should be noted that after the heating is completed each day, the oil temperature needs to be cooled naturally to room temperature, and before the ultrasonic data and physical and chemical data of the rapeseed oil samples are measured, the collected rapeseed oil samples need to be stored at -4°C and protected from light.

[0082] In this embodiment, an ultrasonic pulse echo system is used to perform ultrasonic testing on the sampled rapeseed oil sample. Figure 3 As shown, the ultrasonic pulse echo system device includes a computer, a pulse transceiver, an oscilloscope, a water bath, a sample table, an ultrasonic probe, a thermometer probe and a sample holder. Since the specific assembly structure of the device is a prior art, it will not be described in detail here. The ultrasonic measurement method of the ultrasonic pulse echo system device is:

[0083] S101, verify the accuracy and stability of the ultrasonic pulse echo system device by measuring the speed of sound in distilled water at 26°C;

[0084] S102, filtering the rapeseed oil sample using a sieve, and then slowly pouring the oil sample into a sample container;

[0085] S103, placing the sample stage in a water bath to ensure that the temperature remains constant and controllable during the measurement process;

[0086] S104, immersing the signal transmitting end of the ultrasonic probe and the thermometer probe into the oil sample to be tested, removing bubbles around the ultrasonic probe, and ensuring that the placement position of the thermometer probe does not overlap with the transmission path of the sound wave pulse;

[0087] S105, start the pulse transceiver and the oscilloscope, after the oil sample temperature and the ultrasonic signal are stable, use the computer to collect and save the ultrasonic data in real time, and perform three parallel measurements to ensure the accuracy of the results; obtain ultrasonic spectrum data through the computer, and draw a line graph with time as the horizontal axis and amplitude as the vertical axis to obtain a time domain spectrum, and perform fast Fourier transform on the time domain spectrum to obtain a frequency domain spectrum, and obtain characteristic data of the sound wave through the time domain spectrum and the frequency domain spectrum, including the following ultrasonic data parameters:

[0088] Ultrasonic sound velocity v represents the distance ultrasonic waves propagate per unit time, and its calculation formula is:

[0089]

[0090] Where, v represents the ultrasonic velocity; t 1 and t 0 Respectively represent the appearance time of the first echo and the appearance time of the initial peak; L represents the flight distance of the ultrasound within the time interval;

[0091] The attenuation coefficient α indicates the degree of attenuation of sound waves during propagation, and its calculation formula is:

[0092]

[0093] In the formula, α represents the attenuation coefficient; 1 and A 2 is the maximum amplitude of the first echo and the maximum amplitude of the second echo, and L is the distance between the two echoes;

[0094] The frequency domain spectrum peak value Af refers to the maximum amplitude observed within the frequency spectrum;

[0095] The peak frequency Ff represents the frequency corresponding to the peak of the frequency domain spectrum;

[0096] FFT25, FFT50 and FFT75 represent the minimum frequency values ​​when the total received energy reaches 25%, 50% and 75%, respectively.

[0097] In this embodiment, the physical and chemical data of the thermally oxidized rapeseed oil collected in step S1 include acid value, iodine value, polar component content and fatty acids.

[0098] Specifically, the data collection method of the acid value is as follows: 1±0.0001 g of rapeseed oil sample is fully dissolved in 20 mL of ether-isopropanol solution; free fatty acids are titrated with KOH solution using phenolphthalein as an indicator; titration is stopped when the color turns to light pink, and maintained for 30 seconds, while blank titration is performed;

[0099] The acid value is calculated according to the following formula:

[0100]

[0101] Where AV represents the acid value; v and v 0 represent the volume of KOH solution used to titrate the thermally oxidized oil sample and the blank, respectively; c represents the concentration of the KOH solution; and m represents the weight of the sample.

[0102] The data collection method of the iodine value is as follows: 0.2±0.0001g of rapeseed oil sample is fully dissolved in 20mL of cyclohexane-glacial acetic acid solution; 25mL of Wei's reagent is added, mixed evenly and placed in the dark for reaction for 1h; after the reaction is completed, 20mL of potassium iodide solution and 150mL of water are added; sodium thiosulfate solution is used for titration, and 3 drops of starch solution are added after the yellow color of the liquid disappears, and the titration is continued until the blue color just disappears, and blank titration is performed at the same time;

[0103] The iodine value is calculated according to the following formula:

[0104]

[0105] Where IV represents the iodine value; v and v 0 represent the volume of sodium thiosulfate solution used to titrate the thermally oxidized oil sample and the blank, respectively; c represents the concentration of the sodium thiosulfate solution; and m represents the weight of the sample.

[0106] The data collection method of the polar component content is as follows: 1±0.0001g of rapeseed oil sample is dissolved in a mixture of petroleum ether and ether, and then the mixture is poured into a silica gel column filled with silica gel, and the non-polar fraction is eluted using the mixture of petroleum ether and ether; at the same time, about 200mL of eluate is collected in a dry 500mL round-bottom flask, and the collected eluate is placed in a rotary evaporator under a 60°C water bath condition and rotary evaporated to near dryness, and then the residue is placed in a vacuum constant temperature drying oven at 40°C and further dried for 20min; after the container is cooled, the flask is accurately weighed;

[0107] The calculation of the polar component content is completed according to the following formula:

[0108]

[0109] Where, TPC represents the content of polar components; m 1 and m 2 represent the weight of the blank flask and the flask containing the polar component, respectively; m represents the weight of the sample.

[0110] The fatty acid data collection method includes oil sample pretreatment and fatty acid determination;

[0111] The oil sample pretreatment comprises the following steps: taking 0.1±0.0001 g of rapeseed oil sample after vortex treatment for 2 minutes, placing it in a 10 mL test tube; adding 2 mL of 2% sodium hydroxide methanol solution into the test tube, vortexing for 2 minutes, covering the tube with a stopper and placing it in a water bath at 75±1° C. for 20 minutes; after cooling, adding 1 mL of 15% boron trifluoride methanol solution, vortexing again for 1 minute, covering the tube with a stopper and placing it in a water bath at 75±1° C. for 10 minutes; accurately adding 2 mL of n-heptane , vortex for 2 minutes, add 1mL of saturated sodium chloride aqueous solution, and then let it stand to separate; draw 1mL of the upper n-heptane extraction solution, transfer it to a 10mL test tube, accurately add 4mL of n-heptane, and add about 1g of anhydrous sodium sulfate, vortex for 1min, and let it stand for 5min; draw the upper n-heptane extraction solution, dilute it 10 times with n-heptane as the diluent; take 1mL of the diluted solution, filter the sample solution with a 0.22μL hydrophobic membrane, and collect the filtered solution into a sample injection bottle for detection and analysis;

[0112] The fatty acid determination adopts PerkinElmer Clarus SQ8 gas chromatography-mass spectrometry, comprising the following steps: separation using HP-5 silica gel capillary column and 20:1 split mode; using helium as carrier gas, the flow rate is 1 mL / min, the ion source temperature is 230° C., the injector temperature is maintained at 250° C., the column oven temperature is initially maintained at 120° C. for 2 min, then increased to 200° C. at 4° C. / min and maintained for 2 min, and finally increased to 240° C. at 3° C. / min and maintained for 2 min; recording the chromatogram by monitoring the total ion chromatogram with an m / z range of 40-440; and calculating the content of a given component i by calculating the percentage of the corresponding peak area to the sum of the peak areas of all components by the following formula:

[0113]

[0114] In the formula, FA i Represents the percentage of a certain fatty acid in the total fatty acids; A Si Represents the sum of the peak areas of each fatty acid methyl ester in the sample; Represents the coefficient of conversion of a fatty acid methyl ester into fatty acids.

[0115] It should be noted that, for those skilled in the art, other physical and chemical data of thermally oxidized rapeseed oil can be appropriately measured to further improve and optimize the established temperature compensation model, such as viscosity, density, etc.

[0116] Specifically, a digital viscometer is used to measure the viscosity of rapeseed oil. The specific measurement method includes the following steps: slowly pour 110 mL of rapeseed oil sample into a round flat-bottomed container with a diameter of about 60 mm, take the rotor equipped with the container, adjust the rotor speed to 30 rpm / min, and then slowly rotate it into the instrument in a counterclockwise direction; operate the lifting block to rotate it so that the rotor can be immersed in the oil sample to be tested at a slower speed until the groove scale line on the rotor is on the same horizontal line as the oil sample to be tested; calibrate the level of the instrument again, and test the viscosity of the oil sample, and repeat this test operation three times for each oil sample.

[0117] The density of the rapeseed oil sample is determined by a liquid density measuring instrument. The specific determination method includes the following steps: controlling the measurement temperature at about 25°C, first placing the hook in the middle position of the density meter, and returning to zero after the data is stable; using the hook to hook the glass weight and hang it in the middle position of the density meter, and pressing the measurement key after the glass weight is stable; taking more than 50mL of rapeseed oil sample and slowly pouring it into a glass beaker, and again hanging the glass weight in the middle position of the density meter; removing the bubbles around the glass weight, ensuring that the oil sample can completely immerse the glass weight and the weight has no contact with the inner wall of the beaker, clicking the measurement button to start the measurement program, and recording the density value displayed by the density meter, and repeating the measurement three times.

[0118] Furthermore, in step S1, the acquired ultrasound data and physical and chemical data are subjected to normality test and variance homogeneity test, and the data indicators that conform to the normal distribution and pass the variance homogeneity test are subjected to variance analysis to test the significance between groups, and the Turkey test is used for post hoc comparison; the data indicators that do not conform to the normal distribution are subjected to significance analysis using non-parametric test, and multiple comparisons are performed using Nemenyi test;

[0119] The acquired ultrasound data and physical and chemical data were standardized, and the calculation formula was:

[0120]

[0121] In the formula, x new represents the standardized data, x i represents the i-th data, represents the mean and σ represents the standard deviation.

[0122] Furthermore, in step S1, the variable importance projection is set to evaluate the contribution of each variable to the model, and data indicators with variable importance projection scores greater than or equal to 5 are selected for subsequent model training to enhance the generalization ability of the model; wherein the calculation formula of the variable importance projection score is:

[0123]

[0124] In the formula, VIP j is the variable importance projection, p is the total number of variables, R is the number of principal components, and w aj is the weight of variable j on the ath principal component, d a is the explained variance of the ath principal component.

[0125] Furthermore, in steps S2, S3, and S4, based on the root mean square error RMSE, the mean absolute error MAE, and the determination coefficient R 2 Evaluate the performance of the temperature compensation model;

[0126] The method based on the root mean square error RMSE as a measure of the model prediction accuracy is:

[0127]

[0128] Among them, y i and Represent the i-th predicted value and reference value respectively, and n represents the number of data;

[0129] The method based on mean absolute error MAE as a measure of model prediction accuracy is:

[0130]

[0131] Among them, y i and Represent the i-th predicted value and reference value respectively, and n represents the number of data;

[0132] Based on the coefficient of determination R 2 The method to evaluate the accuracy of the model is:

[0133]

[0134] Among them, Y p and Y a Represent the predicted data and reference data respectively. Represents the mean value of the reference data.

[0135] After the evaluation, you can visually evaluate the predictive performance of the model by plotting a comparison chart of the predicted values ​​and the true values. If you are not satisfied with the predictive performance of the model, you can optimize the model by adjusting the number of principal components, reselecting variables, or further preprocessing the data.

[0136] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for constructing a global temperature compensation model for thermally oxidized rapeseed oil quality detection based on ultrasonic diagnostic technology, characterized in that: The following steps are involved: S1, under each integer temperature condition in the range of 22-32°C, collect ultrasonic data and physical and chemical data of rapeseed oil after thermal oxidation, integrate all collected ultrasonic data as independent variable X, integrate all collected physical and chemical data quality indicators as dependent variable Y, and use partial least squares method PLSR or random forest method RF to establish the association model between X and Y; S2, sort out the data set containing independent variables X and dependent variables Y, and mark the samples as (x1, y1), (x2, y2), ..., (x i ,y i ), where x i represents the temperature and ultrasonic data parameters of the i-th sample, y i represents the quality index parameter of the physical and chemical data of the i-th sample; Each time, one sample is selected as the validation set, and the remaining samples are used as the training set. The model training and validation process is performed i times in total. In each iteration, the prediction error or goodness of fit index is calculated, and finally the results of all iterations are comprehensively evaluated; S3, randomly collecting ultrasonic data of thermally oxidized rapeseed oil under a temperature range of 22-32°C, inputting the collected ultrasonic data into the model, and verifying the accuracy of the model by comparing the quality index prediction value of the model with the actual quality index measurement value; S4, at room temperature, randomly collect ultrasonic data of thermally oxidized rapeseed oil, and input the collected ultrasonic data into the model, and verify the accuracy of the model by comparing the quality index prediction value of the model with the actual quality index measurement value.

2. The method for constructing a global temperature compensation model according to claim 1, characterized in that: In step S1, the rapeseed oil is sampled as follows: 600 mL is taken from each of the three rapeseed oil samples and placed in containers respectively; the containers are placed in a water bath and heated to 180±2° C. within 30 minutes; then the constant temperature is maintained for continuous heating for 12 hours; heating is continued for 7 days to obtain a total of 21 rapeseed oil samples.

3. The method for constructing a global temperature compensation model according to claim 2, characterized in that: The ultrasonic pulse echo system device is used to perform ultrasonic detection on the sampled rapeseed oil sample. The ultrasonic pulse echo system device includes a computer, a pulse transceiver, an oscilloscope, a water bath, a sample table, an ultrasonic probe, a thermometer probe and a sample holder. The ultrasonic determination method of the ultrasonic pulse echo system device is: S101, verify the accuracy and stability of the ultrasonic pulse echo system device by measuring the speed of sound in distilled water at 26°C; S102, filtering the rapeseed oil sample using a sieve, and then slowly pouring the oil sample into a sample container; S103, placing the sample stage in a water bath to ensure that the temperature remains constant and controllable during the measurement process; S104, immersing the signal transmitting end of the ultrasonic probe and the thermometer probe into the oil sample to be tested, removing bubbles around the ultrasonic probe, and ensuring that the placement position of the thermometer probe does not overlap with the transmission path of the sound wave pulse; S105, start the pulse transceiver and the oscilloscope, after the oil sample temperature and the ultrasonic signal are stable, use the computer to collect and save the ultrasonic data in real time, and perform three parallel measurements to ensure the accuracy of the results; obtain ultrasonic spectrum data through the computer, and draw a line graph with time as the horizontal axis and amplitude as the vertical axis to obtain a time domain spectrum, and perform fast Fourier transform on the time domain spectrum to obtain a frequency domain spectrum, and obtain characteristic data of the sound wave through the time domain spectrum and the frequency domain spectrum, including the following ultrasonic data parameters: Ultrasonic sound velocity v represents the distance ultrasonic waves propagate per unit time, and its calculation formula is: Wherein, v represents the ultrasonic velocity; t1 and t0 represent the appearance time of the first echo and the appearance time of the initial peak respectively; L represents the flight distance of the ultrasonic wave in the time interval; The attenuation coefficient α indicates the degree of attenuation of sound waves during propagation, and its calculation formula is: Where α represents the attenuation coefficient; A1 and A2 are the maximum amplitude of the first echo and the maximum amplitude of the second echo, and L is the distance between the two echoes; The frequency domain spectrum peak value Af refers to the maximum amplitude observed within the frequency spectrum; The peak frequency Ff represents the frequency corresponding to the peak of the frequency domain spectrum; FFT25, FFT50 and FFT75 represent the minimum frequency values ​​when the total received energy reaches 25%, 50% and 75%, respectively.

4. The method for constructing a global temperature compensation model according to claim 2, characterized in that: The physical and chemical data of the thermally oxidized rapeseed oil to be collected include the acid value, and the data collection method of the acid value is as follows: 1±0.0001 g of the rapeseed oil sample is fully dissolved in 20 mL of ether-isopropanol solution; Using phenolphthalein as an indicator, titrate the free fatty acids with KOH solution; stop titrating when the color turns light pink, maintain for 30 seconds, and perform a blank titration at the same time; The acid value is calculated according to the following formula: Wherein, AV represents the acid value; v and v0 represent the volume of KOH solution used to titrate the thermally oxidized oil sample and the blank, respectively; c represents the concentration of the KOH solution; and m represents the weight of the sample.

5. The method for constructing a global temperature compensation model according to claim 2, characterized in that: The physical and chemical data of the thermally oxidized rapeseed oil to be collected include iodine value, and the data collection method of the iodine value is as follows: 0.2±0.0001g of rapeseed oil sample is fully dissolved in 20mL of cyclohexane-glacial acetic acid solution; 25mL of Wei's reagent is added, mixed evenly and placed in the dark for reaction for 1h; after the reaction is completed, 20mL of potassium iodide solution and 150mL of water are added; sodium thiosulfate solution is used for titration, and 3 drops of starch solution are added after the yellow color of the liquid disappears, and the titration is continued until the blue color just disappears, and blank titration is performed at the same time; The iodine value is calculated according to the following formula: Wherein, IV represents the iodine value; v and v0 represent the volumes of the sodium thiosulfate solution used to titrate the thermally oxidized oil sample and the blank, respectively; c represents the concentration of the sodium thiosulfate solution; and m represents the weight of the sample.

6. The method for constructing a global temperature compensation model according to claim 2, characterized in that: The physical and chemical data of the thermally oxidized rapeseed oil to be collected include the content of polar components. The data collection method of the content of polar components is as follows: 1±0.0001g of rapeseed oil sample is dissolved in a mixture of petroleum ether and ether, and then the mixture is poured into a silica gel column filled with silica gel, and the non-polar fraction is eluted using the mixture of petroleum ether and ether; at the same time, about 200mL of eluate is collected in a dry 500mL round-bottom flask, and the collected eluate is placed in a rotary evaporator under a 60°C water bath condition and rotary evaporated to near dryness, and then the residue is placed in a vacuum constant temperature drying oven at 40°C and further dried for 20 minutes; after the container is cooled, the flask is accurately weighed; The calculation of the polar component content is completed according to the following formula: Wherein, TPC represents the content of polar components; m1 and m2 represent the weight of the blank flask and the flask containing polar components, respectively; m represents the weight of the sample.

7. The method for constructing a global temperature compensation model according to claim 2, characterized in that: The physical and chemical data of the thermally oxidized rapeseed oil to be collected include fatty acids, and the data collection method of the fatty acids includes oil sample pretreatment and fatty acid determination; The oil sample pretreatment comprises the following steps: taking 0.1±0.0001 g of rapeseed oil sample after vortex treatment for 2 minutes, placing it in a 10 mL test tube; adding 2 mL of 2% sodium hydroxide methanol solution into the test tube, vortexing for 2 minutes, covering the tube with a stopper and placing it in a water bath at 75±1° C. for 20 minutes; after cooling, adding 1 mL of 15% boron trifluoride methanol solution, vortexing again for 1 minute, covering the tube with a stopper and placing it in a water bath at 75±1° C. for 10 minutes; accurately adding 2 mL of n-heptane , vortex for 2 minutes, add 1mL of saturated sodium chloride aqueous solution, and then let it stand to separate; draw 1mL of the upper n-heptane extraction solution, transfer it to a 10mL test tube, accurately add 4mL of n-heptane, and add about 1g of anhydrous sodium sulfate, vortex for 1min, and let it stand for 5min; draw the upper n-heptane extraction solution, dilute it 10 times with n-heptane as the diluent; take 1mL of the diluted solution, filter the sample solution with a 0.22μL hydrophobic membrane, and collect the filtered solution into a sample injection bottle for detection and analysis; The fatty acid determination adopts a gas chromatography-mass spectrometer, comprising the following steps: separation using an HP-5 silica gel capillary column and a 20:1 split mode; using helium as a carrier gas with a flow rate of 1 mL / min, an ion source temperature of 230° C., an injector temperature maintained at 250° C., a column oven temperature initially maintained at 120° C. for 2 min, then increased to 200° C. at 4° C. / min and maintained for 2 min, and finally increased to 240° C. at 3° C. / min and maintained for 2 min; recording a chromatogram by monitoring a total ion chromatogram with an m / z range of 40-440; and calculating the content of a given component i by calculating the percentage of the corresponding peak area to the sum of the peak areas of all components by the following formula: In the formula, FA i Represents the percentage of a certain fatty acid in the total fatty acids; A Si Represents the sum of the peak areas of each fatty acid methyl ester in the sample; Represents the coefficient of conversion of a fatty acid methyl ester into fatty acids.

8. The method for constructing a global temperature compensation model according to claim 1, characterized in that: In step S1, the collected ultrasound data and physical and chemical data are subjected to normality test and variance homogeneity test, and the data indicators that conform to the normal distribution and pass the variance homogeneity test are subjected to variance analysis to test the significance between groups, and the Turkey test is used for post hoc comparison; Nonparametric tests were used to analyze the significance of data indicators that did not conform to the normal distribution, and Nemenyi test was used for multiple comparisons; The collected ultrasound data and physical and chemical data were standardized, and the calculation formula was: In the formula, x new represents the standardized data, x i represents the i-th data, represents the mean and σ represents the standard deviation.

9. The method for constructing a global temperature compensation model according to claim 1, characterized in that: In step S1, variable importance projection is set to evaluate the contribution of each variable to the model, and data indicators with variable importance projection scores greater than or equal to 5 are selected for subsequent model training to enhance the generalization ability of the model; The calculation formula of the variable importance projection score is: In the formula, VIP j is the variable importance projection, p is the total number of variables, R is the number of principal components, and w aj is the weight of variable j on the ath principal component, d a is the explained variance of the ath principal component.

10. The method for constructing a global temperature compensation model according to claim 1, characterized in that: In steps S2, S3, and S4, based on the root mean square error RMSE, the mean absolute error MAE, and the coefficient of determination R 2 Evaluate the performance of the temperature compensation model; The method based on the root mean square error RMSE as a measure of the model prediction accuracy is: Among them, y i and Represent the i-th predicted value and reference value respectively, and n represents the number of data; The method based on mean absolute error MAE as a measure of model prediction accuracy is: Among them, y i and Represent the i-th predicted value and reference value respectively, and n represents the number of data; Based on the coefficient of determination R 2 The method to evaluate the accuracy of the model is: Among them, Y p and Y a Represent the predicted data and reference data respectively. Represents the mean value of the reference data.

Images