Quality detection device and method for edible oil production

Abstract

The invention provides a quality detection device and method for edible oil production. The method comprises the following steps: collecting spectral data and peroxide value of each edible oil sample; extracting a frequency doubling absorption peak during stretching vibration of each chemical bond from each spectral data, and performing cross validation on the oxidation process of the edible oil according to all the frequency doubling absorption peaks and all the peroxide values to obtain a plurality of chemical characteristic variables related to oxidation of the edible oil; establishing an oxidation kinetic model of the edible oil according to all the chemical characteristic variables, and predicting the optimal oxygen flow rate of oxidation of the edible oil through the oxidation kinetic model; performing oxidation stability detection on the edible oil, and when the optimal oxygen flow rate is greater than the oxygen flow rate in the oxidation stability detection, correcting the oxidation stability detection result according to the optimal oxygen flow rate to obtain the oxidation induction time of the edible oil. By adopting the scheme of the invention, the detection error caused by the mismatching of the oxygen flow rate in the oxidation stability detection can be eliminated.

Description

Technical Field

[0001] The present application relates to the technical field of food detection, and more specifically, to a quality detection device and method for edible oil production. Background Art

[0002] The production of edible oil is an operation carried out through automated technology, usually including operation links such as pretreatment, extraction, refining, deodorization, and packaging of oilseeds. To ensure the quality of the produced edible oil, quality detection of the produced edible oil is required. Among them, the quality indicators related to edible oil include the smoke point, saponification value, iodine value, oxidation stability, etc. of the edible oil; In the prior art, the oxidation stability of the produced edible oil is detected according to the national standard GB / T 21121 "Determination of Oxidation Stability of Animal and Vegetable Oils". This national standard stipulates that the test is carried out in an oven at 150 ± 3 °C, and the oxygen flow rate is set to be constant at 10 L / h, and the conductivity of the measurement cell is collected through an electrode, and then the oxidation induction time of the edible oil is obtained. However, in actual detection, there are defects in detecting through a constant oxygen flow rate. For example, if the oxygen flow rate is too small, the contact between the edible oil and oxygen is incomplete, and the oxidation induction time is too large. If the oxygen flow rate is too large, too much heat in the oven is brought into the measurement cell by the air flow, resulting in an increase in the temperature of the measurement cell and a decrease in the oven temperature. The temperature deviation of the measurement cell will cause a deviation in the collected conductivity, and at the same time, the temperature deviation of the oven will also cause the measurement result of the oxidation induction time to be too large. Therefore, how to eliminate the detection error caused by the mismatch of the oxygen flow rate in the oxidation stability detection has become a difficult problem faced by the industry. Summary of the Invention

[0003] The present application provides a quality detection device and method for edible oil production, which can eliminate the detection error caused by the mismatch of the oxygen flow rate in the oxidation stability detection.

[0004] In a first aspect, the present application provides a quality detection method for edible oil production, in which a plurality of edible oil samples with different heating durations are prepared from the edible oil of the same batch produced. The quality detection method includes: Scanning each edible oil sample through a spectral sensor to obtain the spectral data of each edible oil sample, and measuring the peroxide value of each edible oil sample through an electrochemical sensor; Extracting the overtone absorption peaks when each chemical bond stretches and vibrates from each spectral data, and cross-verifying the oxidation process of the edible oil according to all the overtone absorption peaks and all the peroxide values to obtain a plurality of chemical characteristic variables related to the oxidation of the edible oil; An oxidation kinetic model of the edible oil is established based on all chemical characteristic variables, and the antioxidant index of the antioxidant in the edible oil is determined through the oxidation kinetic model. The optimal oxygen flow rate for the oxidation of the edible oil is predicted based on the antioxidant index. The oxidation stability of the edible oil is detected. When the optimal oxygen flow rate is greater than the oxygen flow rate in the oxidation stability detection, the result of the oxidation stability detection is corrected according to the optimal oxygen flow rate to obtain the oxidation induction time of the edible oil.

[0005] In some embodiments, extracting the overtone absorption peaks when each chemical bond stretches and vibrates from each spectral data specifically includes: Select a spectral data as the selected spectral data, perform baseline correction on the selected spectral data to obtain a corrected spectrum; Perform peak detection on the corrected spectrum to obtain the overtone absorption peaks when each chemical bond stretches and vibrates in the selected spectral data; Continue to determine the overtone absorption peaks when each chemical bond stretches and vibrates in the remaining spectral data.

[0006] In some embodiments, cross-validating the oxidation process of the edible oil based on all the overtone absorption peaks and all the peroxide values to obtain multiple chemical characteristic variables related to the oxidation of the edible oil specifically includes: Establish multiple simulation models for the oxidation process of the edible oil based on all the overtone absorption peaks and all the peroxide values; Determine the root mean square error of each simulation model; Determine the optimal number of principal factors according to all the root mean square errors; Determine multiple chemical characteristic variables related to the oxidation of the edible oil according to the optimal number of principal factors.

[0007] In some embodiments, establishing the oxidation kinetic model of the edible oil based on all the chemical characteristic variables specifically includes: Obtain all the chemical characteristics of the edible oil, select one chemical characteristic as the selected chemical characteristic, and perform fitting according to all the chemical characteristic variables corresponding to the selected chemical characteristic and the heating duration of all the edible oil samples to obtain the oxidation response of the selected chemical characteristic; Continue to determine the oxidation responses of the remaining chemical characteristics; Determine the oxidation kinetic model of the edible oil according to all the oxidation responses.

[0008] In some embodiments, predicting the optimal oxygen flow rate for the oxidation of the edible oil based on the antioxidant index specifically includes: Obtain the addition amount of the antioxidant in the edible oil; Predict the optimal oxygen flow rate for the oxidation of the edible oil based on the addition amount and the antioxidant index.

[0009] In some embodiments, after detecting the oxidation stability of the edible oil, it further includes: When the optimal oxygen flow rate is equal to the oxygen flow rate in the oxidation stability detection, the result of the oxidation stability detection is not adjusted, and the oxidation induction time of the edible oil is obtained; When the optimal oxygen flow rate is less than the oxygen flow rate in the oxidation stability detection, the result of the oxidation stability detection is corrected by the temperature change of the measuring cell during the detection process, and the oxidation induction time of the edible oil is obtained.

[0010] In some embodiments, the spectral sensor is a near-infrared spectral sensor.

[0011] In a second aspect, the present application provides a quality detection device for edible oil production. The quality detection device for edible oil production includes an oxidation stability detection unit, and the oxidation stability detection unit includes: An acquisition module for scanning each edible oil sample through a spectral sensor to obtain spectral data of each edible oil sample, and measuring the peroxide value of each edible oil sample through an electrochemical sensor; A processing module for extracting the overtone absorption peaks when each chemical bond stretches and vibrates from each spectral data, and performing cross-validation on the oxidation process of the edible oil based on all the overtone absorption peaks and all the peroxide values to obtain a plurality of chemical characteristic variables related to the oxidation of the edible oil; The processing module is further configured to establish an oxidation kinetic model of the edible oil based on all the chemical characteristic variables, determine the antioxidant index of the antioxidant in the edible oil through the oxidation kinetic model, and predict the optimal oxygen flow rate for the oxidation of the edible oil based on the antioxidant index; An execution module for detecting the oxidation stability of the edible oil. When the optimal oxygen flow rate is greater than the oxygen flow rate in the oxidation stability detection, the result of the oxidation stability detection is corrected according to the optimal oxygen flow rate, and the oxidation induction time of the edible oil is obtained.

[0012] In a third aspect, the present application provides a computer device, which includes a memory and a processor. The memory stores code, and the processor is configured to obtain the code and execute the above-mentioned quality detection method for edible oil production.

[0013] In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned quality detection method for edible oil production is implemented.

[0014] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: In the quality detection device and method for edible oil production provided by this application, first, each edible oil sample is scanned by a spectral sensor to obtain the spectral data of each edible oil sample, and the peroxide value of each edible oil sample is measured by an electrochemical sensor; the overtone absorption peaks when each chemical bond stretches and vibrates are extracted from each spectral data, and the oxidation process of the edible oil is cross-validated based on all the overtone absorption peaks and all the peroxide values to obtain a plurality of chemical characteristic variables related to the oxidation of the edible oil; an oxidation kinetic model of the edible oil is established based on all the chemical characteristic variables, the antioxidant index of the antioxidant in the edible oil is determined through the oxidation kinetic model, and the optimal oxygen flow rate for the oxidation of the edible oil is predicted based on the antioxidant index; the oxidation stability of the edible oil is detected, and when the optimal oxygen flow rate is greater than the oxygen flow rate in the oxidation stability detection, the result of the oxidation stability detection is corrected according to the optimal oxygen flow rate to obtain the oxidation induction time of the edible oil.

[0015] It can be seen that this application cross-validates the peroxide values and spectral data of edible oil samples with different heating durations, extracts latent variables (i.e., chemical characteristic variables) related to the oxidation process of edible oil from the spectrum of the edible oil, then models the oxidation process of the edible oil through all the chemical characteristic variables, predicts the minimum oxygen flow rate (i.e., the optimal oxygen flow rate) that can make the edible oil sample react sufficiently, and corrects the result of the oxidation stability detection of the edible oil through the optimal oxygen flow rate to obtain a more accurate oxidation induction time of the edible oil. In summary, adopting the solution of this application can eliminate the detection error caused by the mismatch of the oxygen flow rate in the oxidation stability detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is an exemplary flowchart of a quality detection method for edible oil production according to some embodiments of this application; Figure 2 is an exemplary flowchart of determining chemical characteristic variables according to some embodiments of this application; Figure 3 is a structural diagram of the equipment used for oxidation stability detection according to some embodiments of this application; Figure 4 is a schematic structural diagram of an oxidation stability detection unit according to some embodiments of this application; Figure 5 is a schematic structural diagram of a computer device for implementing the quality detection method for edible oil production according to some embodiments of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] To better understand the technical solution of the present application, the technical solution of the present application will be described in detail below in conjunction with the accompanying drawings of the specification and specific embodiments.

[0018] Refer to Figure 1 , which is an exemplary flowchart of a quality inspection method for edible oil production according to some embodiments of the present application. The quality inspection method 100 for edible oil production mainly includes the following steps: In step 101, each edible oil sample is scanned by a spectral sensor to obtain the spectral data of each edible oil sample, and the peroxide value of each edible oil sample is measured by an electrochemical sensor.

[0019] In some embodiments, before scanning each edible oil sample by a spectral sensor, it further includes: preparing multiple edible oil samples with different heating durations from the edible oil produced in the same batch.

[0020] Specifically, preparing multiple edible oil samples with different heating durations from the produced edible oil can be achieved in the following manner: extracting multiple portions of the same volume of edible oil from the produced edible oil, heating the extracted edible oil at a predetermined temperature for different durations in an outdoor environment, and naturally cooling the heated edible oil to room temperature (i.e., 25 degrees Celsius). Each portion of the cooled edible oil is used as an edible oil sample. Among them, the same volume can be preset according to actual needs. For example, in the present application, the same volume is preset to 10 ml. The predetermined temperature is set according to the detection temperature specified in the national standard for oxidation stability detection. In GB / T 21121 "Animal and Vegetable Fats and Oils - Determination of Oxidation Stability", it is specified that the detection is carried out at 150 ± 10 degrees Celsius. Therefore, the predetermined temperature in the present application can be preset to 150 degrees Celsius. The different heating durations can be preset according to actual needs. For example, in the present application, a value is taken every 5 hours between 0 and 90 hours as the heating duration, that is, 19 samples are prepared, and the heating durations are 0 hour, 5 hours, 10 hours, 15 hours, 20 hours, 25 hours, 30 hours, 35 hours, 40 hours, 45 hours, 50 hours, 55 hours, 60 hours, 65 hours, 70 hours, 75 hours, 80 hours, 85 hours, and 90 hours.

[0021] In specific implementation, each edible oil sample is scanned by a spectral sensor, and the spectral data of each edible oil sample can be obtained in the following manner: select an edible oil sample as the selected sample, extract 2 ml of the edible oil from the selected sample and place it in a sample tube, preset it for 2 minutes at 55 °C, collect the spectrogram of the selected sample in a transmission manner through the spectral sensor, and take the averaged result as the spectral data of the selected sample. Among them, the spectral scanning range is set to 10000~4000 (cm^-1), the resolution is set to 8 (cm^-1), and the number of scans is set to 32 times. In other embodiments, the spectral data of the edible oil sample can also be collected by other existing technologies, which is not limited here.

[0022] It should be noted that in this application, the spectral sensor is a Fourier transform near-infrared spectrometer.

[0023] In addition, it should be noted that in this application, the electrochemical sensor is a peroxide value detector. As a preferred embodiment, the peroxide value of each edible oil sample can be measured by the electrochemical sensor in the following manner: extract 2 ml of the edible oil from each edible oil sample as the test oil, measure the peroxide value of each test oil by the peroxide value detector, and take the peroxide values of the respective test oils as the peroxide values of the corresponding edible oil samples.

[0024] In step 102, the overtone absorption peaks during the stretching vibration of each chemical bond are extracted from each spectral data, and the oxidation process of the edible oil is cross-validated based on all the overtone absorption peaks and all the peroxide values to obtain a plurality of chemical characteristic variables related to the oxidation of the edible oil.

[0025] In some embodiments, the overtone absorption peaks during the stretching vibration of each chemical bond can be extracted from each spectral data by the following steps: Select a spectral data as the selected spectral data, perform baseline correction on the selected spectral data to obtain a corrected spectrum; Perform peak detection on the corrected spectrum to obtain the overtone absorption peaks during the stretching vibration of each chemical bond in the selected spectral data; Continue to determine the overtone absorption peaks during the stretching vibration of each chemical bond in the remaining spectral data.

[0026] In specific implementation, performing baseline correction on the selected spectral data to obtain a corrected spectrum can be achieved in the following manner: the selected spectral data can be input into the omnic software, and the selected spectral data is baseline-corrected through the automatic baseline correction function in the omnic software, and the data after baseline correction is used as the corrected spectrum.

[0027] It should be noted that in this application, the calibrated spectrum is the spectral data after baseline correction.

[0028] In specific implementation, peak detection is performed on the calibrated spectrum to obtain the overtone absorption peaks when each chemical bond stretches and vibrates in the selected spectral data, which can be achieved by the following method, that is: First, input the selected spectral data into the omnic software, and mark the overtone absorption peaks when each chemical bond stretches and vibrates and the peak areas of each overtone absorption peak through the peak marking function in the omnic software.

[0029] It should be noted that in this application, the overtone absorption peak refers to the absorption peak that appears at an integer multiple of the fundamental frequency of the chemical bond stretching vibration in the spectral data, which reflects the harmonic effect of molecular vibration. In edible oil, the spectrum usually has strong absorption peaks at 4500 - 4770, 5680, 5800, 7087, 7197, and 8271 (cm^-1). Among them, the absorption peak at 4500 - 4770 (cm^-1) reflects the combination frequency of the stretching vibrations of carbon-hydrogen bonds and carbon-oxygen bonds, the absorption peaks at 5680 and 5800 (cm^-1) reflect the first overtone of the stretching vibrations of carbon-hydrogen bonds of methylene, methylene group, and alkenyl groups used in the production of edible oil in the edible oil, the absorption peaks at 7087 and 7197 (cm^-1) reflect the multiple absorption of hydroxyl groups, and the absorption peak at 8271 (cm^-1) reflects the second overtone of the stretching vibration of carbon-hydrogen bonds in aliphatic hydrocarbons.

[0030] In some embodiments, referring to Figure 2 , this figure is an exemplary flowchart for determining chemical characteristic variables according to some embodiments of this application. In this application, cross-validation is performed on the oxidation process of the edible oil based on all overtone absorption peaks and all peroxide values, and multiple chemical characteristic variables related to the oxidation of the edible oil can be obtained by the following steps: In step 1021, multiple simulation models of the edible oil oxidation process are established based on all overtone absorption peaks and all peroxide values; In step 1022, the root mean square error of each simulation model is determined; In step 1023, the optimal number of principal factors is determined according to all root mean square errors; In step 1024, multiple chemical characteristic variables related to the oxidation of the edible oil are determined according to the optimal number of principal factors.

[0031] In specific implementation, multiple simulation models of the edible oil oxidation process can be established based on all the overtone absorption peaks and all the peroxide values in the following manner: First, standardize the peak areas of all the overtone absorption peaks and all the peroxide values. Then, construct multiple simulation models of the edible oil oxidation process through the leave-one-out cross-validation in the prior art. Among them, the dependent variables in all the simulation models are the peak areas of the respective overtone absorption peaks, and the independent variables are the peroxide values. The number of main factors is all integers between 1 and n, where n can be set according to actual needs. For example, in this application, n is set to 10.

[0032] It should be noted that the simulation model in this application is a least-squares model for simulating the edible oil oxidation process.

[0033] In specific implementation, the root mean square error of each simulation model can be determined in the following manner: Calculate the root mean square error of cross-validation of each simulation model, and use the obtained root mean square errors of cross-validation as the root mean square errors of the respective simulation models.

[0034] It should be noted that the root mean square error in this application is a parameter value for measuring the deviation degree between the predicted value and the actual value of the simulation model. The larger the root mean square error, the greater the deviation between the predicted value and the actual value of the simulation model; the smaller the root mean square error, the smaller the deviation between the predicted value and the actual value of the simulation model.

[0035] In specific implementation, the optimal number of main factors can be determined based on all the root mean square errors in the following manner: Arrange all the root mean square errors in ascending order according to the corresponding number of main factors. Subsequently, use the number of main factors when the root mean square error first appears at a minimum value as the optimal number of main factors.

[0036] It should be noted that the optimal number of main factors in this application refers to the number of main factors when the model has the best prediction ability and avoids overfitting during the model construction process.

[0037] In specific implementation, determining multiple chemical characteristic variables related to the oxidation of the edible oil according to the optimal number of principal factors can be achieved in the following manner, i.e., by using the NIPALS algorithm (Nonlinear Iterative Partial Least Squares) in the prior art to iteratively fit the peak areas of all overtone absorption peaks and all peroxide values. During the fitting process, the number of principal factors is the optimal number of principal factors, the independent variable is the peak area of the overtone absorption peak, and the dependent variable is the peroxide value. All the principal factors obtained by fitting are used as chemical characteristic variables related to the oxidation of the edible oil. Among them, k weight vectors are obtained during the fitting process, each weight vector corresponds to a chemical characteristic of the edible oil, and each chemical characteristic corresponds to a chemical characteristic variable in the spectral data of each edible oil sample, that is, there are k chemical characteristics in total, and each chemical characteristic has N chemical characteristic variables. k is the optimal number of principal factors, and N is the number of edible oil samples.

[0038] It should be noted that in this application, the chemical characteristic variable is a comprehensive variable used to reflect the change characteristics of chemical components during the oxidation of the edible oil.

[0039] In step 103, an oxidation kinetic model of the edible oil is established based on all the chemical characteristic variables. The antioxidant index of the antioxidant in the edible oil is determined through the oxidation kinetic model, and the optimal oxygen flow rate for the oxidation of the edible oil is predicted based on the antioxidant index.

[0040] In some embodiments, establishing the oxidation kinetic model of the edible oil based on all the chemical characteristic variables can be achieved through the following steps: Obtain all the chemical characteristics of the edible oil, select one chemical characteristic as the selected chemical characteristic, and fit the chemical characteristic variables corresponding to the selected chemical characteristic and the heating duration of all edible oil samples to obtain the oxidation response of the selected chemical characteristic. Continue to determine the oxidation responses of the remaining chemical characteristics. Determine the oxidation kinetic model of the edible oil based on all the oxidation responses.

[0041] In specific implementation, fitting the chemical characteristic variables corresponding to the selected chemical characteristic and the heating duration of all edible oil samples to obtain the oxidation response of the selected chemical characteristic can be achieved in the following manner, i.e., fitting the chemical characteristic variables corresponding to the selected chemical characteristic in each edible oil sample and the heating duration of each edible oil sample through the least squares algorithm in the prior art, and using the obtained function expression as the oxidation response of the selected chemical characteristic. Among them, the chemical characteristic variable is used as the dependent variable, and the heating duration is used as the independent variable.

[0042] It should be noted that in this application, the oxidation response is a function expression describing the relationship between the chemical feature variables corresponding to a chemical feature in the spectral data and the heating duration.

[0043] In specific implementation, to determine the oxidation kinetic model of the edible oil based on all the oxidation responses, the following method can be adopted, that is: the state space equation composed of the expressions of all the oxidation responses is used as the oxidation kinetic model of the edible oil.

[0044] It should be noted that in this application, the oxidation kinetic model is a state space equation describing the conversion relationship between the spectral data and the heating duration of the edible oil during the oxidation process of the edible oil.

[0045] In some embodiments, to determine the antioxidant index of the antioxidant in the edible oil through the oxidation kinetic model, the following steps can be adopted: Determine the oxidation critical point of each oxidation response in the oxidation kinetic model; Determine the antioxidant index of the antioxidant in the edible oil based on all the oxidation critical points.

[0046] In specific implementation, to determine the oxidation critical point of each oxidation response in the oxidation kinetic model, the following method can be adopted, that is: for each oxidation response, the time point corresponding to the first obvious inflection point in the curve of each oxidation response is respectively used as the oxidation critical point of each oxidation response. For example, the derivative of each oxidation response can be calculated, the calculated derivative is subtracted by 0.5, and the abscissa of the intersection point of each obtained curve and the x-axis is respectively used as the oxidation critical point of each oxidation response.

[0047] It should be noted that in this application, the oxidation critical point is the time point when the chemical feature in the oxidation process of the edible oil changes significantly.

[0048] In specific implementation, to determine the antioxidant index of the antioxidant in the edible oil based on all the oxidation critical points, the following method can be adopted, that is: the average value of all the oxidation critical points is used as the antioxidant index of the antioxidant in the edible oil. Since antioxidants are added to the edible oil, in the initial stage of the oxidation of the edible oil, the chemical features in the edible oil change little. When the antioxidant loses its efficacy, the edible oil begins to oxidize rapidly. At this time, obvious inflection points, that is, oxidation critical points, appear in the oxidation responses of the chemical features in the oxidation kinetic model. This oxidation critical point corresponds to the time point when the antioxidant fails. Therefore, the average value of all the oxidation critical points can be used as a parameter value to measure the antioxidant performance of the antioxidant in the edible oil.

[0049] It should be noted that in this application, the antioxidant index is a parameter value for measuring the antioxidant performance of the antioxidant in the edible oil.

[0050] In some embodiments, predicting the optimal oxygen flow rate for the oxidation of the edible oil based on the antioxidant index can be achieved by the following steps: Obtain the addition amount of the antioxidant in the edible oil; Predict the optimal oxygen flow rate for the oxidation of the edible oil based on the addition amount and the antioxidant index.

[0051] Specifically, obtaining the addition amount of the antioxidant in the edible oil can be achieved in the following way, that is: in the production of edible oil, the addition amount of the antioxidant is usually preset by the production line. Therefore, the addition amount of the antioxidant in the edible oil can be directly obtained.

[0052] Specifically, predicting the optimal oxygen flow rate for the oxidation of the edible oil based on the addition amount and the antioxidant index can be achieved in the following way, that is: First, obtain the amount of oxygen consumed when 1 g of the antioxidant is completely oxidized. Then, multiply the consumed amount of oxygen by the addition amount and divide by the antioxidant index, and take the obtained value as the optimal oxygen flow rate for the oxidation of the edible oil. Among them, obtaining the amount of oxygen consumed when 1 g of the antioxidant is completely oxidized can be determined through preliminary experiments. For example, take 1 g of the antioxidant and place it in a closed environment for heating oxidation. The heating temperature is the same as the heating temperature for preparing the edible oil sample in this application, and take the difference in the amount of oxygen in the closed environment before and after heating oxidation as the amount of oxygen consumed when 1 g of the antioxidant is completely oxidized.

[0053] It should be noted that the optimal oxygen flow rate in this application refers to the minimum oxygen flow rate that can make the oxidation rate of the edible oil reach the maximum during the oxidation stability detection.

[0054] In step 104, perform an oxidation stability detection on the edible oil. When the optimal oxygen flow rate is greater than the oxygen flow rate in the oxidation stability detection, correct the result of the oxidation stability detection according to the optimal oxygen flow rate to obtain the oxidation induction time of the edible oil.

[0055] Specifically, performing an oxidation stability detection on the edible oil can be achieved in the following way, that is: perform an oxidation stability detection on the edible oil according to the national standard GB / T 21121 "Animal and Vegetable Fats and Oils - Determination of Oxidation Stability". Among them, the oxygen flow rate in the oxidation stability detection is set to 10 L / h according to the regulations of the national standard GB / T 21121 "Animal and Vegetable Fats and Oils - Determination of Oxidation Stability", and the sample volume used for the oxidation stability detection is G, where G is the preset same volume among the multiple edible oil samples with different heating durations prepared in this application.

[0056] In some embodiments, refer to Figure 3 , this figure is a structural diagram of the equipment used for the oxidation stability detection shown in some embodiments of this application, specifically including: A heating block for heating the sample; An electrode for measuring the conductivity of the measurement cell; A measurement cell for absorbing the gas released by the oxidation of the sample.

[0057] In specific implementation, according to the optimal oxygen flow rate to correct the result of the oxidation stability detection, the oxidation induction time of the edible oil can be obtained by the following method: First, obtain the flow rate of oxygen in the oxidation stability detection and the result of the oxidation stability detection (i.e., the uncorrected oxidation induction time). Then, according to the conversion formula between oxygen flow rate and oxygen concentration and the free radical chain reaction model, it can be inferred that the oxidation reaction rate is proportional to the oxygen flow rate (the oxygen concentration is proportional to the oxygen flow rate, and the oxidation reaction rate is proportional to the oxygen concentration). That is, multiply the ratio of the oxygen flow rate in the oxidation stability detection to the optimal oxygen flow rate by the uncorrected oxidation induction time. Finally, take the result obtained by multiplication as the oxidation induction time of the edible oil.

[0058] In some embodiments, after performing the oxidation stability detection on the edible oil, it further includes: When the optimal oxygen flow rate is equal to the flow rate threshold, do not adjust the result of the oxidation stability detection, and obtain the oxidation induction time of the edible oil; When the optimal oxygen flow rate is less than the preset flow rate threshold, correct the result of the oxidation stability detection by the temperature change of the measurement cell during the detection process, and obtain the oxidation induction time of the edible oil.

[0059] In specific implementation, correcting the result of the oxidation stability detection by the temperature change of the measurement cell during the detection process to obtain the oxidation induction time of the edible oil can be achieved by the following method: The temperature sensor installed in the measurement cell collects the temperature values of the measurement cell during the detection process at a preset sampling interval, and fits all the collected temperature values into a curve by Lagrange interpolation method. Take the fitted curve as the temperature change of the measurement cell during the detection process. Among them, the sampling interval can be set according to actual needs. For example, in this application, the sampling interval is set to 0.5 seconds. Subsequently, obtain the conductivity curve of the oxidation stability detection, convert the conductivity curve to the conductivity curve at the actual temperature through the temperature compensation calculation formula of temperature change and conductivity, and extract the oxidation induction time of the edible oil from the conductivity curve at the actual temperature according to the requirements in the national standard GB / T 21121 "Determination of Oxidation Stability of Animal and Vegetable Oils".

[0060] In addition, on the other hand of this application, in some embodiments, this application provides a quality detection device for edible oil production. The quality detection device for edible oil production includes an oxidation stability detection unit. Refer to Figure 4, This figure is a schematic structural diagram of an oxidation stability detection unit according to some embodiments of the present application. The oxidation stability detection unit 400 includes: a collection module 401, a processing module 402, and an execution module 403, which are described as follows: Collection module 401. In the present application, the collection module 401 is mainly used to scan each edible oil sample through a spectral sensor to obtain the spectral data of each edible oil sample, and measure the peroxide value of each edible oil sample through an electrochemical sensor; Processing module 402. In the present application, the processing module 402 is mainly used to extract the overtone absorption peaks when each chemical bond stretches and vibrates from each spectral data, and perform cross-validation on the oxidation process of the edible oil based on all the overtone absorption peaks and all the peroxide values to obtain a plurality of chemical characteristic variables related to the oxidation of the edible oil; It should be noted that in the present application, the processing module 402 is also used to establish an oxidation kinetic model of the edible oil based on all the chemical characteristic variables, determine the antioxidant index of the antioxidant in the edible oil through the oxidation kinetic model, and predict the optimal oxygen flow rate for the oxidation of the edible oil based on the antioxidant index; Execution module 403. In the present application, the execution module 403 is mainly used to detect the oxidation stability of the edible oil. When the optimal oxygen flow rate is greater than the oxygen flow rate in the oxidation stability detection, the result of the oxidation stability detection is corrected according to the optimal oxygen flow rate to obtain the oxidation induction time of the edible oil.

[0061] In addition, the present application also provides a computer device, which includes a memory and a processor. The memory stores code, and the processor is configured to obtain the code and execute the above quality detection method for edible oil production.

[0062] In some embodiments, refer to Figure 5 , This figure is a schematic structural diagram of a computer device for implementing the quality detection method for edible oil production according to some embodiments of the present application. The quality detection method for edible oil production in the above embodiments can be implemented by Figure 5 the computer device shown. The computer device 500 includes at least one processor 501, a communication bus 502, a memory 503, and at least one communication interface 504.

[0063] The processor 501 can be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).

[0064] The communication bus 502 can be used to transfer information among the above components.

[0065] The memory 503 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 503 can exist independently and be connected to the processor 501 through the communication bus 502. The memory 503 can also be integrated with the processor 501.

[0066] Among them, the memory 503 is used to store the program code for implementing the solution of this application and is controlled by the processor 501 for execution. The processor 501 is used to execute the program code stored in the memory 503. The program code can include one or more software modules. The quality detection method for edible oil production in the above embodiments can be implemented by one or more software modules in the program code in the processor 501 and the memory 503.

[0067] The communication interface 504, using any device such as a transceiver, is used to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0068] In a specific implementation, as an embodiment, the computer device can include multiple processors, and each of these processors can be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, the processor can refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions).

[0069] The above computer device may be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device may be a desktop computer, a laptop computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiments of the present application do not limit the type of the computer device.

[0070] In addition, the present application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above quality detection method for edible oil production.

[0071] In summary, in the quality detection device and method for edible oil production disclosed in the embodiments of the present application, first, each edible oil sample is scanned by a spectral sensor to obtain the spectral data of each edible oil sample, and the peroxide value of each edible oil sample is measured by an electrochemical sensor; the overtone absorption peaks when each chemical bond stretches and vibrates are extracted from each spectral data, and the oxidation process of the edible oil is cross-validated based on all the overtone absorption peaks and all the peroxide values to obtain a plurality of chemical characteristic variables related to the oxidation of the edible oil; an oxidation kinetic model of the edible oil is established based on all the chemical characteristic variables, the antioxidant index of the antioxidant in the edible oil is determined through the oxidation kinetic model, and the optimal oxygen flow rate for the oxidation of the edible oil is predicted based on the antioxidant index; the oxidation stability of the edible oil is detected, and when the optimal oxygen flow rate is greater than the oxygen flow rate in the oxidation stability detection, the result of the oxidation stability detection is corrected according to the optimal oxygen flow rate to obtain the oxidation induction time of the edible oil.

[0072] Thus, it can be seen that the present application cross-validates the peroxide values and spectral data of edible oil samples with different heating durations, extracts the latent variables (i.e., chemical characteristic variables) related to the oxidation process of the edible oil from the spectrum of the edible oil, then models the oxidation process of the edible oil through all the chemical characteristic variables, predicts the minimum oxygen flow rate (i.e., the optimal oxygen flow rate) that can make the edible oil sample react sufficiently, and corrects the result of the oxidation stability detection of the edible oil through the optimal oxygen flow rate to obtain a more accurate oxidation induction time of the edible oil. In summary, by adopting the solution of the present application, the detection error caused by the mismatch of the oxygen flow rate in the oxidation stability detection can be eliminated.

[0073] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present application.

[0074] Obviously, those skilled in the art can make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalent technologies, this application is also intended to include these changes and modifications.

Claims

1. A quality inspection method for edible oil production, characterized in that, Preparing a plurality of edible oil samples with different heating durations from the same batch of edible oil produced, the quality inspection method includes: Scanning each edible oil sample through a spectral sensor to obtain the spectral data of each edible oil sample, and measuring the peroxide value of each edible oil sample through an electrochemical sensor; Extracting the overtone absorption peaks when each chemical bond stretches and vibrates from each spectral data, and cross-verifying the oxidation process of the edible oil based on all the overtone absorption peaks and all the peroxide values to obtain a plurality of chemical characteristic variables related to the oxidation of the edible oil; Establishing an oxidation kinetic model of the edible oil based on all the chemical characteristic variables, determining the antioxidant index of the antioxidant in the edible oil through the oxidation kinetic model, and predicting the optimal oxygen flow rate for the oxidation of the edible oil based on the antioxidant index; Conducting an oxidation stability test on the edible oil. When the optimal oxygen flow rate is greater than the oxygen flow rate in the oxidation stability test, correcting the result of the oxidation stability test according to the optimal oxygen flow rate to obtain the oxidation induction time of the edible oil.

2. The method according to claim 1, characterized in that, Extracting the overtone absorption peaks when each chemical bond stretches and vibrates from each spectral data specifically includes: Selecting one spectral data as the selected spectral data, performing baseline correction on the selected spectral data to obtain a corrected spectrum; Performing peak detection on the corrected spectrum to obtain the overtone absorption peaks when each chemical bond stretches and vibrates in the selected spectral data; Continuing to determine the overtone absorption peaks when each chemical bond stretches and vibrates in the remaining spectral data.

3. The method according to claim 1, wherein Cross-verifying the oxidation process of the edible oil based on all the overtone absorption peaks and all the peroxide values to obtain a plurality of chemical characteristic variables related to the oxidation of the edible oil specifically includes: Establishing a plurality of simulation models for the oxidation process of the edible oil based on all the overtone absorption peaks and all the peroxide values; Determining the root mean square error of each simulation model; Determining the optimal number of principal factors based on all the root mean square errors; Determining a plurality of chemical characteristic variables related to the oxidation of the edible oil according to the optimal number of principal factors.

4. The method according to claim 1, wherein Establishing an oxidation kinetic model of the edible oil based on all the chemical characteristic variables specifically includes: Obtaining all the chemical characteristics of the edible oil, selecting one chemical characteristic as the selected chemical characteristic, and fitting according to all the chemical characteristic variables corresponding to the selected chemical characteristic and the heating duration of all the edible oil samples to obtain the oxidation response of the selected chemical characteristic; Continuing to determine the oxidation responses of the remaining chemical characteristics; Determining the oxidation kinetic model of the edible oil based on all the oxidation responses.

5. The method according to claim 1, characterized in that, Predicting the optimal oxygen flow rate for the oxidation of the edible oil based on the antioxidant index specifically includes: Obtaining the addition amount of the antioxidant in the edible oil; Predicting the optimal oxygen flow rate for the oxidation of the edible oil according to the addition amount and the antioxidant index.

6. The method according to claim 1, characterized in that After conducting the oxidation stability test on the edible oil, it further includes: When the optimal oxygen flow rate is equal to the oxygen flow rate in the oxidation stability test, not adjusting the result of the oxidation stability test to obtain the oxidation induction time of the edible oil; When the optimal oxygen flow rate is less than the oxygen flow rate in the oxidation stability detection, the result of the oxidation stability detection is corrected by detecting the temperature change of the measuring cell during the detection process to obtain the oxidation induction time of the edible oil.

7. The method according to claim 1, wherein The spectral sensor is a near-infrared spectral sensor.

8. A quality inspection device for edible oil production, the quality inspection device for edible oil production includes an oxidation stability detection unit, characterized in that, The oxidation stability detection unit includes: An acquisition module, configured to scan each edible oil sample through a spectral sensor to obtain spectral data of each edible oil sample, and measure the peroxide value of each edible oil sample through an electrochemical sensor; A processing module, configured to extract the overtone absorption peaks when each chemical bond stretches and vibrates from each spectral data, and perform cross-validation on the oxidation process of the edible oil according to all the overtone absorption peaks and all the peroxide values to obtain a plurality of chemical characteristic variables related to the oxidation of the edible oil; The processing module is further configured to establish an oxidation kinetic model of the edible oil according to all the chemical characteristic variables, determine the antioxidant index of the antioxidant in the edible oil through the oxidation kinetic model, and predict the optimal oxygen flow rate for the oxidation of the edible oil based on the antioxidant index; An execution module, configured to perform an oxidation stability detection on the edible oil. When the optimal oxygen flow rate is greater than the oxygen flow rate in the oxidation stability detection, correct the result of the oxidation stability detection according to the optimal oxygen flow rate to obtain the oxidation induction time of the edible oil.

9. A computer device, characterized in that, The computer device includes a memory and a processor. The memory stores code, and the processor is configured to obtain the code and execute the quality detection method for edible oil production according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the quality detection method for edible oil production according to any one of claims 1 to 7.

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