Method for identifying quality of rapeseed oil

Abstract

The invention discloses a rapeseed oil quality identification method. The method comprises the following steps: acquiring concentration data of processing residual electroactive substances in rapeseed oil by adopting an electrochemical detection method; acquiring oxygen partial pressure, relative humidity, thermodynamic temperature and illumination intensity data of the storage environment; constructing a synergistic effect quantitative model to obtain a synergistic effect coefficient; constructing a nonlinear attenuation acceleration model to obtain a quality attenuation acceleration factor; detecting acid value and peroxide value data; and calculating a comprehensive quality index in combination with a synergistic effect deviation correction mechanism. According to the method, the problem that recessive quality attenuation cannot be captured in the prior art is solved through cross-domain technology fusion, accurate identification is realized, and a reliable scheme is provided for rapeseed oil quality evaluation.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of food detection and electrochemistry technology, and particularly relates to a rapeseed oil quality identification method. BACKGROUND

[0002] As one of the main edible oils in China, the quality of rapeseed oil is directly related to food safety and consumer health. The existing rapeseed oil quality identification methods focus on the detection of static component indicators such as acid value and peroxide value, but ignore the hidden influence of the synergistic effect of processing residual electroactive substances and storage environment on quality. This kind of synergistic effect can accelerate the oxidation and deterioration of rapeseed oil, leading to a sharp decline in quality in the later storage period. However, due to the complex mechanism and difficulty in quantification, the existing technology cannot capture the hidden quality degradation process, and can only make judgments after the deterioration phenomenon appears, which cannot realize early warning and accurate evaluation.

[0003] Based on the above problems, there is an urgent need for an identification method that can quantify the synergistic effect of electroactive substances and environment and accurately represent the dynamic degradation of quality, solving the core problem of the existing technology that is not sensitive to hidden quality changes. SUMMARY

[0004] The purpose of the present application is to solve the problems existing in the prior art, and to propose a rapeseed oil quality identification method, comprising the following steps: S1, using an electrochemical detection method to obtain the concentration data of processing residual electroactive substances in the rapeseed oil sample; S2, collecting the oxygen partial pressure, relative humidity, thermodynamic temperature and light intensity data of the storage environment of the rapeseed oil sample; S3, based on the concentration data of the electroactive substances and the data of the storage environment, a synergistic effect quantification model is constructed, and a synergistic effect coefficient is calculated; S4, based on the synergistic effect coefficient, a nonlinear decay acceleration model is constructed, and a quality decay acceleration factor is calculated; S5, detecting the acid value data and peroxide value data of the rapeseed oil sample; S6, based on the quality decay acceleration factor, the acid value data and the peroxide value data, combined with a synergistic effect deviation correction mechanism, a rapeseed oil comprehensive quality index is calculated, and the rapeseed oil quality identification is completed.

[0005] Preferably, the step S1 further comprises a sample pretreatment step before the step S1, and the sample pretreatment step is: taking 50 mL of rapeseed oil sample, filtering the sample with a 0.45 μm organic phase filter to remove mechanical impurities in the sample; taking 10 mL of the filtered rapeseed oil sample and injecting it into an electrochemical detection cell, and standing for 30 min.

[0006] Preferably, the electrically active substance in step S1 is a phospholipid; the electrochemical detection method in step S1 is realized by a three-electrode system, which includes a working electrode, a reference electrode and a counter electrode; the concentration data in step S1 is obtained by detecting the oxidation peak current of the phospholipid through cyclic voltammetry, and is converted by combining a calibration curve of the oxidation peak current and the concentration of the phospholipid, and the expression of the calibration curve is C = k1·I + k0, wherein C is the molar concentration of the phospholipid, k1 is the slope of the calibration curve, k0 is the intercept of the calibration curve, and I is the oxidation peak current of the phospholipid. ox + k0, wherein C is the molar concentration of the phospholipid, k1 is the slope of the calibration curve, k0 is the intercept of the calibration curve, and I ox is the oxidation peak current of the phospholipid.

[0007] Preferably, the storage environment data in step S2 is collected by a sensor group, which includes an oxygen partial pressure sensor, a humidity sensor, a temperature sensor and an illumination sensor; three groups of storage environment data are continuously obtained during the collection process, and the average value of the three groups of data is taken as the input data of step S3.

[0008] Preferably, the synergistic effect quantification model in step S3 is a trace electrically active substance synergistic effect coefficient model, which is constructed based on the mass action law and the van't Hoff equation, and realizes the quantification of the synergistic effect intensity by combining the concentration data of the electrically active substance, the storage environment data, the phospholipid electrically active characteristic constant, the humidity synergistic correction coefficient and the temperature influence constant.

[0009] Preferably, the non-linear decay acceleration model in step S4 is a quality decay acceleration factor model, which is constructed based on the Arrhenius equation, and realizes the non-linear quantification of the quality decay rate by combining the synergistic effect coefficient, the storage environment data, the reference decay rate, the temperature acceleration coefficient and the illumination sensitivity coefficient.

[0010] Preferably, the synergistic effect deviation correction mechanism in step S6 is a rapeseed oil comprehensive quality index computer mechanism, which realizes the correction of the detection deviation and the quantification of the comprehensive quality by combining the synergistic effect coefficient, the quality decay acceleration factor, the acid value data, the peroxide value data and the synergistic deviation correction coefficient, through the acid value weight coefficient, the decay factor weight coefficient, the peroxide value weight coefficient and the synergistic deviation correction coefficient.

[0011] Preferably, the working electrode of the three-electrode system is a glassy carbon electrode, the reference electrode is an Ag / AgCl electrode, and the counter electrode is a platinum wire electrode; the scanning range of the cyclic voltammetry is-0.2V to 1.0V, and the scanning rate is 50mV / s; the calibration curve is established by the following method: five phospholipid-rapeseed oil standard samples with different molar concentrations are configured, the oxidation peak current of the phospholipid of each standard sample is detected by cyclic voltammetry, the molar concentration of the phospholipid is taken as the abscissa, and the oxidation peak current is taken as the ordinate, and the calibration curve is obtained by linear regression analysis.

[0012] Preferably, the phospholipid electroactive characteristic constant is determined by configuring different known molar concentrations of phospholipid-rapeseed oil standard samples, obtaining the oxidation peak current of each standard sample, combining the standard value of the storage environment data, substituting into the micro-electroactive substance synergism coefficient model, and obtaining the specific value by least square fitting; the humidity synergistic correction coefficient is determined by detecting the synergistic strength of the same phospholipid-rapeseed oil standard sample under different relative humidity conditions, and obtaining the specific value by nonlinear regression fitting based on the corresponding relationship between the detection results and the relative humidity; the temperature influence constant is derived based on the Van't Hoff equation, and the activation energy and gas constant of the phospholipid and oxygen reaction are combined to calculate and determine during the derivation process.

[0013] Preferably, the acid value in step S6 is detected by titration method, and the peroxide value is detected by iodine titration method; the acid value weight coefficient, the decay factor weight coefficient and the peroxide value weight coefficient are determined by analytic hierarchy process, which includes three steps of constructing a quality evaluation index system, constructing a judgment matrix, weight calculation and consistency check; the synergistic deviation correction coefficient is determined by the following method: under different synergistic coefficient conditions, the acid value and peroxide value of the same rapeseed oil sample are detected, the deviation of the detection results and the standard value is compared, and the specific value is obtained by nonlinear regression fitting based on the corresponding relationship between the deviation and the synergistic coefficient; the numerical value of the upper limit of the national standard of the acid value of rapeseed oil is 3 mgKOH / g, and the numerical value of the reference value of the peroxide value of fresh rapeseed oil is 0.4 mmol / kg.

[0014] Technical effects: The present application solves the core problem that the existing technology cannot quantify the implicit quality decay by the cross-field fusion of electrochemical detection and environmental parameter modeling, constructing a synergistic quantitative model, a nonlinear decay acceleration model and a deviation correction mechanism. The technical point directly hits the unbroken pain point of the synergistic effect of electroactive substances and environment, realizes the dynamic and accurate identification of rapeseed oil quality, and provides a reliable basis for quality evaluation. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 A flow chart of the method for identifying the quality of rapeseed oil according to the present application. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0017] The existing technology has the following technical problems: it is difficult to capture the implicit quality decay process of rapeseed oil because the synergistic effect of residual electroactive substances and storage environment cannot be quantified, and it can only be judged after the deterioration phenomenon appears.

[0018] Based on this, please refer to Figure 1 The embodiment provides a rapeseed oil quality identification method, comprising the following steps: S1, an electrochemical detection method is used to obtain the concentration data of the processing residual electroactive substance in the rapeseed oil sample; S2, the oxygen partial pressure, relative humidity, thermodynamic temperature and light intensity data of the rapeseed oil sample storage environment are collected; S3, based on the concentration data of the electroactive substance and the storage environment data, a synergistic action quantification model is constructed, and a synergistic action coefficient is calculated; S4, based on the synergistic action coefficient, a nonlinear decay acceleration model is constructed, and a quality decay acceleration factor is calculated; S5, the acid value and peroxide value data of the rapeseed oil sample are detected; S6, based on the quality decay acceleration factor, acid value data and peroxide value data, combined with a synergistic action deviation correction mechanism, a rapeseed oil comprehensive quality index is calculated, and the rapeseed oil quality identification is completed.

[0019] The implementation of the technical solution needs to strictly follow the step logic and model construction principle, and ensure that the data of each link is reliable and quantitatively accurate. First, the concentration detection of the electroactive substance needs to select a high-precision electrochemical workstation, and a three-electrode system is used to build a detection platform. The working electrode is a glassy carbon electrode and is polished to ensure the surface finish to improve the signal response sensitivity. The reference electrode is an Ag / AgCl electrode, and the counter electrode is a platinum wire electrode. The three form a stable electrochemical detection loop. During detection, the pretreated rapeseed oil sample is injected into the detection cell, and the three electrodes are immersed in the sample. The scanning range is set to-0.2V to 1.0V, and the scanning rate is 50mV / s. This parameter combination can effectively stimulate the redox reaction of phospholipids, produce a characteristic oxidation peak, and record the oxidation peak current through the electrochemical workstation. Then, the molar concentration of phospholipids is calculated according to the pre-constructed calibration curve. The calibration curve needs to be fitted by at least 5 standard samples with different concentrations to ensure the linear correlation and accuracy of the concentration conversion.

[0020] Data acquisition for the storage environment requires a dedicated sensor array. An electrochemical sensor is used, covering a measurement range of 0 to 25 kPa, meeting the detection needs of typical storage environments. A capacitive humidity sensor ensures stable response within a relative humidity range of 10% to 90%. A platinum resistance temperature sensor provides a measurement accuracy of ±0.1 K, and a silicon photodiode sensor is used, adaptable to light intensity ranges from 0 to 10000 lux. During data acquisition, the sensor array should be placed in the center of the rapeseed oil storage environment to ensure data representativeness. Three sets of data should be collected consecutively, with a 10-second interval between each set. The average value is then used as the input data to compensate for the effects of instantaneous fluctuations in environmental parameters.

[0021] The construction of a synergistic effect quantification model is one of the core technical points, and its mathematical expression is: 'in , is the synergistic effect coefficient of trace electroactive substances, and is dimensionless; The characteristic constant of phospholipid electroactivity, with dimensions of ; The molar concentration of phospholipids in rapeseed oil, with dimensions of ; The partial pressure of oxygen in the storage environment, with dimensions of ; This is the humidity co-correction coefficient, which is dimensionless. The relative humidity of the storage environment is dimensionless. Let be the temperature effect constant, with dimensions . ; The thermodynamic temperature of the storage environment, with dimensions of The logical derivation of this formula is based on the law of mass action and the van der Hoff equation. The law of mass action states that the rate of a chemical reaction is directly proportional to the product of the concentrations of the reactants. The oxidation rate of phospholipids and oxygen is affected by the concentrations of both, therefore the molar concentration of phospholipids is introduced. partial pressure with oxygen The product term directly reflects the fundamental contribution of reactant concentration to the concerted effect. The van der Hoff equation reveals the effect of temperature on the equilibrium constant; increased temperature accelerates the oxidation reaction, thereby enhancing the concerted effect. Therefore, an exponential term is introduced. ,in The temperature-dependent constant is the activation energy of the reaction between phospholipids and oxygen. and gas constant It is derived that, Dimensions are To ensure that the exponential terms are dimensionless, the effect of humidity on the synergistic effect is not linear. Experiments have shown that when the relative humidity exceeds 60%, the dispersibility of phospholipids in the oil phase significantly improves, and the synergistic effect intensity increases sharply. Therefore, the following approach is adopted. The term characterizes this nonlinear relationship and is corrected by a humidity-coordinated correction coefficient. Make adjustments. The values ​​were obtained by fitting experimental data under different humidity conditions to ensure accurate quantification of the effect of humidity. Phospholipid electroactivity characteristic constants. Dimensional design for Its function is to offset of Dimensions and of Dimensionality, so that the formula outputs a dimensionless coefficient of synergy. , The value ranges from 0 to 2, with a larger value indicating a stronger synergistic effect.

[0022] The mathematical expression for the nonlinear decay acceleration model is: ,in, The quality degradation acceleration factor has a dimension of 1 / day. The baseline decay rate is expressed in units of 1 / day, specifically at 25°C, without light, and... The inherent decay rate of rapeseed oil; The temperature acceleration coefficient has dimensions of . ; The thermodynamic temperature of the storage environment, with dimensions of ; The light sensitivity coefficient has the following dimensions: ; The light intensity of the storage environment, with dimensions of ; The coefficient representing the synergistic effect of trace electroactive substances is dimensionless. The derivation of this model is based on the Arrhenius equation, which shows that the reaction rate constant has an exponential relationship with temperature; therefore, the coefficient is introduced... The item, where 298.15K is the reference temperature of 25℃, and the temperature acceleration factor is... The dimensions are The values ​​were obtained by fitting experimental data to ensure an accurate characterization of the accelerating effect of temperature on the decay rate. Light intensity. The effect of light intensity on lipid oxidation is related to photon energy. Experiments have shown that the square root of light intensity has a linear relationship with the oxidation rate. Therefore, [the following method was adopted]. Item, light sensitivity coefficient The dimensions are This is used to adjust the weighting of the effect of illumination. Synergistic effect coefficient. It has a catalytic effect on the decay rate, when When the catalytic effect is 0, the formula is as follows: ,at this time That is, the reference decay rate, when As the size increases, the catalytic effect is enhanced. The coefficient design makes The catalytic effect reaches saturation at a certain time to avoid over-amplification and ensure the rationality of the model. The dimension is 1 / day, which directly represents the daily rate of quality decay and is consistent with the actual physical meaning.

[0023] The mathematical expression for the synergistic bias correction mechanism is: ,in, The comprehensive quality index of rapeseed oil is dimensionless. This is the acid value weighting coefficient, which is dimensionless. For the measured acid value, the dimensions are: ; This is the upper limit of the national standard for acid value of rapeseed oil, with dimensions of [dimensions missing]. ; , is the attenuation factor weighting coefficient, which is dimensionless; The quality degradation acceleration factor has a dimension of 1 / day. This refers to the number of days rapeseed oil can be stored, measured in days. This is the peroxide value weighting coefficient, and its dimensionless value. The peroxide value of fresh rapeseed oil is a reference value, with dimensions of [dimensions missing]. ; For the actual measurement of peroxide value, the dimensions are: ; This is the coefficient for correction of coordination deviation, and its dimension is dimensionless. The coefficient representing the synergistic effect of trace electroactive substances is dimensionless. This mechanism is constructed based on weighted summation and bias correction theory. First, the acid value weighting coefficient is determined using the analytic hierarchy process (AHP). Attenuation factor weighting coefficient Peroxide value weighting coefficient The sum of the three is 1, ensuring the reasonableness of the weighted summation. Acid value term. middle, The value is 3 mg KOH / g, which is the upper limit of the national standard for rapeseed oil acid value. This item reflects the impact of the current free fatty acid content on quality by comparing the measured acid value with the standard value. The smaller the ratio, the larger the value of this item, and the better the quality. (Decrease trend item) Based on first-order reaction kinetics, quality varies with storage time. It decays exponentially. The product is dimensionless, ensuring the exponent term output is reasonable. Peroxide value term. middle, The peroxide value is 0.4 mmol / kg, which is the reference value for fresh rapeseed oil. This value reflects the current degree of oxidation by comparing the reference value with the measured value. The higher the ratio, the lower the degree of oxidation and the better the quality. (Cooperational bias correction term) To address the detection bias caused by synergistic effects, when When the deviation is minimum, the correction coefficient is 1, and when When the deviation deviates from the value, the correction coefficient is adjusted accordingly to offset the influence of the deviation, The value is obtained by experimental fitting to ensure the accuracy of the correction effect. The output is a dimensionless value of 0 to 100, which intuitively reflects the comprehensive quality.

[0024] The scheme realizes the quantification and dynamic evaluation of implicit quality decay through the cross-disciplinary integration of electrochemical detection and environmental parameter modeling. Each model parameter has a clear theoretical basis and experimental support. The dimension design strictly follows the physical law, ensuring the scientificity and implementability of the technical scheme.

[0025] The prior art has the following technical problems: mechanical impurities in the sample can interfere with the accuracy of the electroactive substance concentration detection, affecting the subsequent model calculation accuracy. Therefore, the step S1 further includes a sample pretreatment step, which is: taking 50 mL of rapeseed oil sample, filtering with 0.45 μm organic phase filter membrane to remove mechanical impurities in the sample, and taking 10 mL of filtered rapeseed oil sample into the electrochemical detection cell and standing for 30 min.

[0027] The implementation of the technical scheme needs to strictly control various operation parameters to ensure the stability of the pretreatment effect. When taking 50 mL of rapeseed oil sample, a calibrated pipette should be used to ensure the accuracy of the sample volume. This volume can ensure the representativeness of the detection, avoid detection deviation caused by too small sample volume, and also avoid sample waste. The selection of the organic phase filter membrane needs to meet two core requirements: the pore size is 0.45 μm, which can accurately trap the mechanical impurities in the rapeseed oil without blocking the phospholipid molecules; the material is organic phase compatible type to avoid chemical reaction between the filter membrane and the rapeseed oil or phospholipid, ensuring that the sample composition is not changed. The filtration process uses vacuum filtration, and the filtration rate is controlled at 5 mL / min to avoid insufficient impurity trapping caused by too fast rate or affecting experimental efficiency caused by too slow rate. After filtration, 10 mL of filtered sample is taken, which accurately matches the volume of the electrochemical detection cell to ensure that the three electrodes can be completely immersed in the sample, and the sample volume is sufficient to cover the electrode reaction area. After being injected into the detection cell, it is left to stand for 30 min. This time length is designed to eliminate bubbles in the sample. Bubbles can cause insufficient contact between the electrode and the sample, affecting the stability and accuracy of the electrochemical signal. The 30 min standing time can ensure that the bubbles float to the liquid surface completely, avoiding interference with the detection process. The standardized operation of the entire pretreatment process provides a pure and stable sample basis for subsequent electroactive substance concentration detection, effectively improving the reliability of the detection data.

[0028] The prior art has the following technical problems: there is a lack of precise detection means for processing residual electroactive substances in rapeseed oil, and reliable concentration data cannot be obtained.

[0029] Therefore, the electroactive substance in step S1 is phospholipid, the electrochemical detection method in step S1 is realized by a three-electrode system, the three-electrode system includes a working electrode, a reference electrode and a counter electrode, the concentration data in step S1 is obtained by detecting the oxidation peak current of phospholipid by cyclic voltammetry, and is converted by combining the calibration curve of the oxidation peak current and the concentration of phospholipid. The expression of the calibration curve is , wherein, is the molar concentration of phospholipid, and the dimension is ; is the slope of the calibration curve, and the dimension is ; is the intercept of the calibration curve, and the dimension is ; is the oxidation peak current of phospholipid, and the dimension is μA.

[0030] The implementation of the technical solution needs to focus on the stability of the detection system and the accuracy of the calibration curve. The electroactive substance is definitely phospholipid, because phospholipid is the most important residual electroactive substance in the degumming process of rapeseed oil, its content is directly related to the processing technology, and it has a significant synergistic catalytic effect on the quality degradation of rapeseed oil. Detecting the concentration of phospholipid can accurately reflect the potential impact of processing residues on quality. The selection of three-electrode system is strictly screened, the working electrode is selected as glassy carbon electrode, the glassy carbon electrode has good electrochemical stability, conductivity and surface reproducibility, after 0.05 mu m alumina powder polishing treatment, the surface roughness is less than 0.1 mu m, which can effectively improve the response sensitivity and repeatability of oxidation peak current; the reference electrode is selected as Ag / AgCl electrode with saturated KCl solution, the electrode has stable electrode potential, the potential drift is less than 0.1 mV / h, which ensures the stability of the potential reference in the detection process; the counter electrode is selected as platinum wire electrode with a diameter of 0.5 mm and a length of 5 mm, which has excellent catalytic performance and can quickly transfer electrons to promote the reaction of the counter electrode and avoid the influence of polarization phenomenon on the detection results. The parameters of cyclic voltammetry are optimized, the scanning range is-0.2V to 1.0V, which can completely cover the redox potential interval of phospholipid, neither missing the oxidation peak due to too narrow scanning range nor introducing irrelevant impurity reaction signals due to too wide range; the scanning rate is 50 mV / s, which balances the signal response intensity and peak clarity, too fast rate will lead to peak current increase but peak shape widening, too slow rate will lead to signal noise increase, and the rate of 50 mV / s makes the oxidation peak shape symmetrical and the peak current stable. The construction of calibration curve needs to follow strict standard process, 5 different molar concentrations of phospholipid-rapeseed oil standard samples are configured, the concentration range is 0.01 mmol / L to 0.1 mmol / L, covering the common content interval of phospholipid in actual rapeseed oil, the same three-electrode system and cyclic voltammetry parameters as sample detection are used to detect the oxidation peak current of each standard sample, 3 groups of peak current data corresponding to each concentration are recorded, and the average value is taken as the characteristic current value of this concentration. The molar concentration of phospholipid is taken as the abscissa, the oxidation peak current is taken as the ordinate, the least square method is used for linear regression analysis, and the calibration curve expression is obtained, the linear correlation coefficient is required to ensure that the linear relationship between concentration and peak current is significant and the conversion error is reduced. When detecting the sample, the oxidation peak current of phospholipid is recorded, which can be accurately converted to the molar concentration of phospholipid in the sample , providing reliable core input data for subsequent synergistic effect quantification model.

[0031] The existing technology has the following technical problems: the accuracy and stability of the storage environment parameter collection are insufficient, which affects the reliability of the subsequent model calculation.

[0032] Based on this, the storage environment data in step S2 is collected by a sensor group, which includes an oxygen partial pressure sensor, a humidity sensor, a temperature sensor and an illumination sensor. During the collection process, three groups of storage environment data are continuously obtained, and the average value of the three groups of data is taken as the input data of step S3.

[0033] The implementation of the technical solution needs to pay attention to the standardization of sensor selection and data collection process. Each sensor of the sensor group is selected for the detection requirement of a specific environmental parameter. The oxygen partial pressure sensor is selected as an electrochemical sensor. The detection principle is based on the reduction reaction of oxygen on the electrode surface. The reaction current has a linear relationship with the oxygen partial pressure. The detection range is 0 to 25 kPa. The resolution is 0.01 kPa. The response time is less than 10 s, which can quickly capture the change of oxygen partial pressure. The humidity sensor is selected as a capacitive sensor. Based on the principle that the change of humidity causes the change of capacitance value, the detection range is 10% to 90% relative humidity. The accuracy is ±2% relative humidity. The response time is less than 5 s, which avoids the data distortion caused by the lag of humidity response. The temperature sensor is selected as a platinum resistance PT100. Based on the characteristic that the resistance value of platinum resistance changes with temperature, the detection range is 273.15 K to 333.15 K. The accuracy is ±0.1 K. The resolution is 0.01 K, which can accurately measure the thermodynamic temperature of the storage environment. The illumination sensor is selected as a silicon photodiode sensor. Based on the photoelectric effect, the detection range is 0 to 10000 lux. The resolution is 1 lux. The response time is less than 1 s, which is suitable for the detection of light intensity in different storage scenes indoors and outdoors. The installation position of the sensor group needs to be strictly controlled. It is installed at the center height of the rapeseed oil storage container, which is at least 5 cm away from the container wall, to avoid the influence of the temperature and humidity difference of the container wall on the detection result, and to ensure that the sensor probe is not blocked and fully contacts with the environment. The data collection process is standardized. After starting the sensor group, it is preheated for 30 min to ensure that the sensor enters a stable working state, and then three groups of data are continuously collected with an interval of 10 s. The average value of the three groups of data is calculated by using the arithmetic mean method. If the deviation of a group of data from the other two groups of data exceeds 5%, a group of data is re-collected to replace the abnormal data, and then the average value is calculated to ensure the stability and reliability of the input data. Regular calibration of the sensor group is the key. The oxygen partial pressure sensor is calibrated once a month using standard gas. The humidity sensor is calibrated once a quarter using a standard humidity generator. The temperature sensor is calibrated once every half year using a standard constant temperature tank. The illumination sensor is calibrated once a year using a standard light source. The calibration process records the calibration data and correction coefficient to ensure the long-term stability of the detection accuracy of the sensor.

[0034] The existing technology has the following technical problems: it cannot quantify the synergistic effect strength of the electroactive substance and the storage environment, which leads to the difficulty in characterizing the trigger condition of implicit quality degradation.

[0035] Based on this, the synergistic effect quantification model in step S3 is a trace electroactive substance synergistic effect coefficient model, which is constructed based on the mass action law and the Van't Hoff equation, and the synergistic effect intensity is quantified by the phospholipid electroactive characteristic constant, the humidity synergistic correction coefficient, the temperature influence constant, and the concentration data and storage environment data of the electroactive substance.

[0036] In the specific implementation process, the mathematical expression of the model is: , wherein, is the synergistic effect coefficient of the trace electroactive substance, and the dimension is dimensionless; is the phospholipid electroactive characteristic constant, and the dimension is ; is the molar concentration of phospholipid in rapeseed oil, and the dimension is ; is the oxygen partial pressure of the storage environment, and the dimension is ; is the humidity synergistic correction coefficient, and the dimension is dimensionless; is the relative humidity of the storage environment, and the dimension is dimensionless; is the temperature influence constant, and the dimension is ; is the thermodynamic temperature of the storage environment, and the dimension is .

[0037] The construction of the formula is based on multidisciplinary theory, which ensures the scientificity and rationality of the quantification logic, and the definition, dimension and derivation process of each parameter are clear and explicit, which supports the implementation by the person skilled in the art. From the theoretical basis, the mass action law is the core basis, which indicates that the product of the chemical reaction rate and the reactant concentration is proportional, and the oxidation reaction of phospholipid and oxygen is the key reaction of rapeseed oil quality degradation, and its reaction rate is directly affected by the concentration of phospholipid and the oxygen partial pressure, so the product term of and is introduced in the formula, which directly reflects the basic contribution of the concentration of the two to the synergistic effect, which conforms to the basic law of chemical reaction and ensures the theoretical rationality of the model. The Van't Hoff equation provides the basis for the quantification of temperature influence, which shows that the reaction rate constant increases by about 2 to 4 times for every 10K increase in temperature. Temperature affects the reaction rate by affecting the activation energy, and then affects the synergistic effect intensity, so the exponential term is introduced, wherein is the temperature influence constant, which is derived from the activation energy of the reaction of phospholipid and oxygen and the gas constant , , the gas constant The value of the number 8.314 J / (mol·K) is the activation energy of the reaction between phospholipids and oxygen Generally 30000 J / mol to 50000 J / mol, and therefore The value of the number 3600 K to 6000 K has the dimension , ensuring that the exponential term is dimensionless The dimensionless quantity, the exponential function output is dimensionless, in line with mathematical logic.

[0038] The mechanism of the influence of humidity on synergy is relatively complex, and experimental verification shows that changes in relative humidity will affect the solubility and dispersibility of phospholipids in rapeseed oil. Under low humidity conditions, phospholipid molecules tend to aggregate, and the synergistic effect is weak. Under high humidity conditions, phospholipid molecules are evenly dispersed, and the contact area with oxygen increases, significantly enhancing the synergistic effect. Moreover, this influence is not linear, and when the relative humidity exceeds 60%, the growth rate of the strength of the synergistic effect significantly accelerates, so the term is used to characterize this non-linear relationship, and the humidity synergy correction coefficient is used to adjust the weight of the humidity effect, and its value is determined by experimental fitting. The specific process is as follows: configure a standard sample of phospholipid-rapeseed oil with a fixed concentration, and place it in environments with relative humidity of 20%, 40%, 60%, and 80%, respectively, while keeping the temperature and oxygen partial pressure constant. Detect the synergistic effect, and based on the corresponding relationship between the detection results and the square of the relative humidity, use nonlinear regression fitting to obtain the value of , which is usually in the range of 0.01 to 0.05 and has the dimension of dimensionless, ensuring that is dimensionless and does not affect the overall dimension of the formula.

[0039] Phospholipid electroactive characteristic constant The design of the dimensionally uniform key is dimensionless, and its dimension is The determination of this dimension is based on the need for overall dimensional balance of the formula, The dimension of , The dimension of , and the dimension of the product of the two is , After multiplying with the product, the dimension is dimensionless, and after multiplying with other dimensionless terms, the dimension of is dimensionless, in line with the physical meaning of the synergy coefficient, The value of the number ranges from 0 to 2, indicating no synergy when , and indicating that the synergy has reached saturation when , and this value range is verified by experimental data and can accurately cover the strength interval of the synergy in actual storage scenarios.

[0040] The logical derivation process of the formula is complete, from the theoretical basis to the parameter design, and to the dimensional balance, which is strictly demonstrated. The determination method of each parameter is clear and repeatable. The person skilled in the art can accurately construct the model and calculate the synergistic coefficient according to the above description .

[0041] The prior art has the following technical problems: it cannot characterize the nonlinear decay acceleration effect of temperature and light on the quality of rapeseed oil, making it difficult to dynamically evaluate the quality change.

[0042] Therefore, the nonlinear decay acceleration model in step S4 is a quality decay acceleration factor model, which is constructed based on the Arrhenius equation. The nonlinear quantification of the quality decay rate is realized by the reference decay rate, the temperature acceleration coefficient, the light sensitivity coefficient, and the synergistic coefficient and the storage environment data.

[0043] In the specific implementation process, the mathematical expression of the model is , wherein is the quality decay acceleration factor, with a dimension of 1 / day; is the reference decay rate, with a dimension of 1 / day, specifically the inherent decay rate of rapeseed oil at 25℃, without light, and is the inherent decay rate of rapeseed oil at 25℃, without light, and is the temperature acceleration coefficient, with a dimension of ; is the thermodynamic temperature of the storage environment, with a dimension of ; is the light sensitivity coefficient, with a dimension of ; is the light intensity of the storage environment, with a dimension of ; is the synergistic coefficient of trace electroactive substances, with a dimension of dimensionless.

[0044] The construction of the formula combines chemical kinetics and experimental verification data, has sufficient theoretical basis, is fully disclosed, and the physical meaning, dimension, and derivation process of each parameter are clear, ensuring that the person skilled in the art can implement it. The core theoretical basis is the Arrhenius equation, which is a classic formula describing the relationship between reaction rate constant and temperature, indicating that the reaction rate constant increases exponentially with temperature. The decay of rapeseed oil quality is essentially a first-order reaction of oil oxidation, and its decay rate conforms to the Arrhenius equation rule. Therefore, the term is introduced, where 298.15K is the reference temperature of 25℃, which is the common food storage reference temperature, facilitating data comparison, and the dimension of the temperature acceleration coefficient is , the value of which is determined by experimental fitting, the specific process being: select fresh rapeseed oil samples, respectively in constant temperature environments of 283.15 K, 293.15 K, 303.15 K, 313.15 K, 323.15 K, keep other conditions unchanged, regularly detect quality indicators, calculate the decay rate constant at different temperatures, based on the exponential relationship between the rate constant and temperature, the value of is fitted to be , usually in the range of 0.03 to 0.051 / K, ensuring accurate characterization of the accelerating effect of temperature on the decay rate.

[0045] The effect of light on the quality decay of rapeseed oil is due to the action of photon energy, which can excite the electron transition of oil molecules and accelerate the oxidation reaction. Experimental verification shows that the light intensity is linearly related to the square root of the decay rate, because the transfer of photon energy is proportional to the square root of the light intensity, so the term is used in the formula, and the light sensitivity coefficient has a dimension of , the value of which is determined by experiment, the specific process being: select fresh rapeseed oil samples, respectively in light environments of 1000 lux, 3000 lux, 5000 lux, 7000 lux, 9000 lux, keep temperature, oxygen partial pressure and other conditions unchanged, regularly detect quality indicators, calculate the decay rate constant at different light intensities, based on the linear relationship between the rate constant and the square root of the light intensity, the value of is fitted to be , usually in the range of 0.001 to 0.0031 / lux 0 5 , ensuring the accuracy of the quantification of light effects.

[0046] The catalytic effect of the synergistic coefficient on the decay rate is realized through the term , this design is based on catalytic reaction kinetics, when , the catalytic effect is 0, , at this time , i.e. the reference decay rate, , which is the inherent decay rate of rapeseed oil at 25°C, no light and , is determined by experiment, usually in the range of 0.002 to 0.0051 / day, and has a dimension of 1 / day, when increases, the catalytic effect gradually increases, , the coefficient design makes , at this time , the catalytic effect reaches a reasonable interval, avoiding excessive amplification of the catalytic effect when is too large, ensuring the reasonableness of the model, the determination of this coefficient is verified by multiple experiments, which can accurately reflect the catalytic relationship between and the decay rate. ​

[0047] The dimensional balance of the formula is strictly verified, The dimension of is 1 / day, and both the exponential term and the logarithmic term are dimensionless, so The dimension of is 1 / day, which is consistent with the physical meaning of the quality decay acceleration factor, that is, the rate of daily quality decay, and the dimension design conforms to the physical law, ensuring the rationality of the calculation result. The logical derivation process of the entire formula starts from the theoretical model, optimizes the parameters combined with experimental data, forms a complete quantification system, and the determination method of each parameter is repeatable. The skilled person in the art can accurately construct the model and calculate to obtain , which fully meets the requirements of Article 26, paragraph 4 of the Patent Law.

[0048] The prior art has the following technical problems: the synergistic effect will cause deviation in the detection of static quality indicators, affecting the accuracy of comprehensive quality evaluation. Therefore, the synergistic effect deviation correction mechanism described in step S6 is a rapeseed oil comprehensive quality index computer mechanism, which realizes the correction of detection deviation and the quantification of comprehensive quality by combining the quality decay acceleration factor, acid value data, peroxide value data, and synergistic effect coefficient through the acid value weight coefficient, decay factor weight coefficient, peroxide value weight coefficient, and synergistic deviation correction coefficient.

[0050] In the specific implementation process, the mathematical expression of the mechanism is , wherein is the rapeseed oil comprehensive quality index, and the dimension is dimensionless; is the acid value weight coefficient, and the dimension is dimensionless; is the measured acid value, and the dimension is ; is the upper limit of the national standard of rapeseed oil acid value, and the dimension is ; is the decay factor weight coefficient, and the dimension is dimensionless; is the quality decay acceleration factor, and the dimension is 1 / day; is the storage days of rapeseed oil, and the dimension is days; is the peroxide value weight coefficient, and the dimension is dimensionless; is the reference value of the peroxide value of fresh rapeseed oil, and the dimension is ; is the measured peroxide value, and the dimension is ; is the synergistic deviation correction coefficient, and the dimension is dimensionless; is the synergistic effect coefficient of trace electroactive substances, and the dimension is dimensionless.

[0051] The formula is constructed based on multi-index evaluation theory and deviation correction theory, and has sufficient theoretical basis, clear definition, dimension and derivation process of each parameter, and full disclosure; can support the implementation of the skilled person in the art, and provides sufficient specification support for the claims. The core design idea is to integrate static quality indicators and dynamic attenuation trend, and correct the detection deviation caused by synergistic effect, so as to realize accurate quantification of comprehensive quality.

[0052] The static quality indicators include acid value and peroxide value. The acid value reflects the content of free fatty acid in rapeseed oil, and is an important indicator for measuring oil rancidity. The peroxide value reflects the content of primary oxidation products of oil, and directly reflects the degree of oxidation. Both of them are national standard indicators for rapeseed oil quality evaluation, and have clear detection methods and standard values. The acid value term is is the measured acid value, and the dimension is , is the upper limit of the national standard of rapeseed oil acid value, and the value is 3 mgKOH / g, which has the same dimension as , so is dimensionless, The value range of is 0 to 1, and the larger the value is, the lower the acid value is, and the better the quality is. The peroxide value term is is the measured peroxide value, and the dimension is , is the reference value of fresh rapeseed oil peroxide value, and the value is 0.4 mmol / kg, which has the same dimension as , so is dimensionless, and the value range is 0 to 1. The larger the value is, the lower the peroxide value is, the lighter the oxidation degree is, and the better the quality is.

[0053] The dynamic attenuation trend term is Based on the first-order reaction kinetics, the quality attenuation of rapeseed oil conforms to the first-order reaction law, that is, the quality is exponentially attenuated with the storage time, is the quality attenuation acceleration factor, and the dimension is 1 / day, is the storage time, and the dimension is day, so is a dimensionless quantity, which ensures the reasonable output of the exponential term, and the value range is 0 to 1. The larger the value is, the more gentle the attenuation trend is, and the better the quality is maintained. This design integrates the dynamic attenuation process into the comprehensive quality evaluation, which makes up for the shortcomings of the prior art which only focuses on static indicators, and can more comprehensively reflect the quality state of rapeseed oil.

[0054] The weight coefficient is , , ​​The determination adopts the analytic hierarchy process, which is a scientific method commonly used in multi-index evaluation and can objectively allocate the weight of each index. The specific process is as follows: constructing a quality evaluation index system, the target layer is the comprehensive quality of rapeseed oil, and the criterion layer is acid value, attenuation trend and peroxide value; constructing a judgment matrix, inviting five experts in the field of food detection to compare the importance of each criterion layer index pairwise, and assigning values by using the 1-9 scale method; calculating the weight vector and performing consistency check, when the consistency check index , it indicates that the judgment matrix has consistency and the weight allocation is reasonable, and finally the values of , , are obtained, usually ranges from 0.3 to 0.4, ranges from 0.4 to 0.5, ranges from 0.1 to 0.2, all of which are dimensionless, and ensures the rationality of weighted summation.

[0055] The synergistic deviation correction term is the core to solve the detection deviation problem. It is found through experiments that the synergistic coefficient has an influence on the detection results of acid value and peroxide value, and when , the deviation is the smallest, and the deviation gradually increases as deviates from this value, therefore is used to represent the degree of deviation, and the value of the synergistic deviation correction coefficient is determined through experimental fitting. The specific process is as follows: selecting a standard rapeseed oil sample, the standard values of acid value and peroxide value of which are known, detecting the acid value and peroxide value of the sample under different values, calculating the deviation between the detection results and the standard values, and based on the corresponding relationship between the deviation and , the value of is obtained through nonlinear regression fitting, usually ranging from 0.1 to 0.2, and being dimensionless, which ensures that the correction term is dimensionless and does not affect the overall dimension of the formula.

[0056] The dimension balance design of the formula is reasonable, and 100 is the normalization coefficient, making the output range of be 0 to 100, dimensionless, which is convenient for intuitive understanding, each term in the weighted summation part is dimensionless, and after being divided by , it is still dimensionless, and the correction term is also dimensionless, therefore the overall dimension of is dimensionless, which conforms to the physical meaning of the comprehensive quality index. The logical derivation process of the entire formula forms a complete system from index selection, weight allocation, dynamic trend quantification to deviation correction, and the determination method of each parameter is scientific and repeatable. The person skilled in the art can accurately calculate , realize the accurate evaluation of comprehensive quality.

[0057] The prior art has the following technical problems: the electrode type of the three-electrode system and the parameter setting of the cyclic voltammetry are not clear, the calibration curve is not standardized, and the accuracy of the detection of the phospholipid concentration is affected.

[0058] Therefore, the working electrode of the three-electrode system is a glassy carbon electrode, the reference electrode is an Ag / AgCl electrode, the counter electrode is a platinum wire electrode, the scanning range of the cyclic voltammetry is-0.2V to 1.0V, the scanning rate is 50mV / s, and the calibration curve is established by the following method: 5 phospholipid-rapeseed oil standard samples with different molar concentrations are configured, the cyclic voltammetry is used to detect the phospholipid oxidation peak current of each standard sample, the molar concentration of the phospholipid is taken as the abscissa, and the oxidation peak current is taken as the ordinate, and the calibration curve is obtained by linear regression analysis.

[0059] The implementation of the technical scheme needs to strictly standardize each operation detail to ensure the stability of the detection system and the accuracy of the calibration curve. The electrode selection of the three-electrode system is verified by multiple experiments, the working electrode is a glassy carbon electrode with a diameter of 3mm, the surface treatment process of the glassy carbon electrode is standardized, first, 1.0μm aluminum oxide powder is used to roughen on a polishing cloth, then 0.05μm aluminum oxide powder is used for fine polishing, until the electrode surface presents mirror gloss, then the glassy carbon electrode is ultrasonically cleaned with anhydrous ethanol and deionized water for 5min to remove the residual polishing powder and impurities on the surface, and finally the glassy carbon electrode is cyclically scanned in a 0.5mol / L H2SO4 solution, the scanning range is-0.2V to 1.0V, and the scanning rate is 50mV / s, until the cyclic voltammetry curve is stable, and the electrochemical activity of the electrode surface is consistent. The reference electrode is a saturated KCl solution Ag / AgCl electrode, before use, it is necessary to check whether the salt bridge is unobstructed to ensure that the electrode potential is stable; the counter electrode is a platinum wire electrode with a diameter of 0.5mm and a length of 5mm, the surface of the platinum wire is electrochemically polished to improve the catalytic activity; the installation position of the three electrodes needs to be fixed, the distance between the working electrode and the counter electrode is 5mm, and the distance between the reference electrode and the working electrode is 2mm, to avoid the potential drop caused by the large electrode distance or the mutual interference caused by the small electrode distance.

[0060] The parameters of cyclic voltammetry are set through system optimization, the scanning range is -0.2V to 1.0V, which is determined based on the redox characteristics of phospholipids, the oxidation potential of phospholipids is about 0.6V, and the reduction potential is about -0.1V, the scanning range can completely capture the oxidation peak and reduction peak of phospholipids, and will not include the redox signals of other irrelevant components in rapeseed oil; the scanning rate is 50mV / s, the selection of the rate takes into account the peak current intensity and peak shape resolution, too fast scanning rate will lead to peak current increase but peak shape widening, oxidation peak and other impurity peaks are difficult to distinguish, too slow scanning rate will lead to peak current decrease and signal noise increase, the rate of 50mV / s makes the oxidation peak shape of phospholipids sharp and symmetrical, and the peak current is stable, which is convenient for accurate reading.

[0061] The construction of the calibration curve is the key to concentration conversion, which needs to follow a strict standard process, the standard sample is configured by weight method, the phospholipid standard is accurately weighed, rapeseed oil is used as solvent, and 5 standard samples with different molar concentrations are configured, the concentrations are 0.01mmol / L, 0.03mmol / L, 0.05mmol / L, 0.07mmol / L and 0.1mmol / L, which covers the common content range of phospholipids in actual rapeseed oil, ensuring the applicability of the calibration curve. The detection of standard sample needs to use the same three-electrode system, cyclic voltammetry parameters and environmental conditions as sample detection, each standard sample is detected for 3 times, the oxidation peak current of each detection is recorded, and the average value is taken as the characteristic current value corresponding to the concentration, the oxidation peak current is read by peak height method, and the vertex current value of the oxidation peak is read based on the baseline, to ensure the consistency of reading method. Linear regression analysis is adopted for data processing, the molar concentration of phospholipids is taken as the abscissa, and the oxidation peak current is taken as the ordinate, the least square method is used to fit the calibration curve, the linear correlation coefficient , the absolute value of intercept is less than 0.001mmol / L, and the relative standard deviation of slope is less than 5%, to ensure that the linear relationship of the calibration curve is significant, and the conversion error is within the allowable range. The effective period of the calibration curve is 3 months, if the electrode is replaced or the detection environment changes during the period, the calibration curve needs to be reconstructed to ensure the accuracy of concentration conversion.

[0062] The prior art has the following technical problems: the determination method of the key parameters in the micro-electroactive substance synergistic coefficient model is not clear, which affects the accuracy of model calculation.

[0063] Based on this, the phospholipid electroactive characteristic constant is determined by the following manner: configuring different known molar concentrations of phospholipid-rapeseed oil standard samples, obtaining the oxidation peak current of each standard sample by using the detection method, combining the standard value of the storage environment data, substituting into the micro-electroactive substance synergistic coefficient model, and fitting to obtain the specific value by the least square method; the humidity synergistic correction coefficient is determined by the following manner: under different relative humidity conditions, the synergistic effect intensity of the same phospholipid-rapeseed oil standard sample is detected, based on the corresponding relationship between the detection result and the relative humidity, and the specific value is obtained by nonlinear regression fitting; the temperature influence constant is derived based on the Van't Hoff equation, and the activation energy of the reaction of phospholipid and oxygen and the gas constant are combined to calculate and determine during the derivation process.

[0064] The implementation of the technical solution needs to focus on the scientificity and repeatability of parameter determination, and ensure that the value of each key parameter is accurate and reliable. The determination of the phospholipid electroactive characteristic constant needs to be fitted by experiments of multiple concentration standard samples, and the configuration of the standard samples is consistent with that of the standard samples for constructing the calibration curve, the concentration range is 0.01 mmol / L to 0.1 mmol / L, and there are 5 concentration points, and the standard value of the storage environment data is set as: oxygen partial pressure 21 kPa, relative humidity 50%, and thermodynamic temperature 298.15 K, which simulates the typical conditions of the conventional storage environment, and ensures the universality of parameter fitting. By using the electrochemical detection method, the oxidation peak current of each standard sample is obtained, and the phospholipid molar concentration is converted by combining the calibration curve, then , the standard value of the storage environment data is substituted into the micro-electroactive substance synergistic coefficient model, and the corresponding synergistic effect intensity of each standard sample is determined by independent experiments, the synergistic effect intensity is determined by using the differential scanning calorimetry method, and the heat release rate of the oxidation reaction is characterized, based on the corresponding relationship between the determined synergistic effect intensity and the model calculation value, the least square method is used to fit to obtain the specific value of , and the initial values of and are fixed to 0.03 and 4800 K respectively during the fitting process, and after the fitting is completed, the relative error between the model calculation value and the experimental determination value is required to be less than 5%, and the accuracy of is ensured.

[0065] The humidity synergistic correction coefficient The determination of the constant needs to be determined through experiments under different humidity conditions. The phospholipid-rapeseed oil standard sample with a concentration of 0.05 mmol / L is selected, which is an intermediate concentration and has good representativeness. The other parameters of the storage environment data are set as follows: oxygen partial pressure 21 kPa, thermodynamic temperature 298.15 K, and relative humidity set to 20%, 40%, 60%, and 80% in four gradients, covering the common humidity range. Under each humidity condition, the synergistic effect intensity is determined by differential scanning calorimetry, and , the storage environment data are substituted into the model, and the values of and are fixed. Based on the corresponding relationship between the synergistic effect intensity and the relative humidity square, the specific value of is obtained by nonlinear regression fitting. The exponential function is selected for the fitting model, and the determination coefficient of the fitting curve is required to ensure that can accurately represent the nonlinear effect of humidity.

[0066] The determination of the temperature influence constant is based on the Van't Hoff equation. The expression of the Van't Hoff equation is , where is the reaction enthalpy change. For the oxidation reaction of phospholipids and oxygen, can be determined by differential scanning calorimetry, and the usual range is -30 kJ / mol to -50 kJ / mol, with a negative sign indicating an exothermic reaction. The gas constant , based on the derivation of the Van't Hoff equation, , since is negative, the value of is positive, usually ranging from 3600 K to 6000 K. During the derivation process, the reaction equilibrium constant at different temperatures needs to be determined through experiments to verify the value of . Three different temperatures: 288.15 K, 298.15 K, and 308.15 K are selected to determine the reaction equilibrium constant at each temperature, and the average value of is calculated by substituting the Van't Hoff equation to ensure the reliability of the derivation result. The determination process of each parameter records detailed experimental data, including standard sample configuration data, detection data, and fitting curve, to ensure the traceability and repeatability of the parameter values and provide support for the accuracy of the model calculation.

[0067] The existing technology has the following technical problems: the detection method of the static basic quality index is not clear, the determination method of the weight coefficient and the synergistic deviation correction coefficient is not standardized, and the accuracy of the comprehensive quality index calculation is affected.

[0068] Based on this, the acid value in step S6 is detected by titration method, and the peroxide value is detected by iodometric method; the weight coefficient of acid value, the weight coefficient of attenuation factor and the weight coefficient of peroxide value are determined by analytic hierarchy process, which includes three steps of constructing quality evaluation index system, constructing judgment matrix, weight calculation and consistency test; the synergistic deviation correction coefficient is determined by the following method: under the condition of different synergistic coefficients, the acid value and peroxide value of the same rapeseed oil sample are detected, the deviation of the detection results and the standard value is compared, based on the corresponding relationship between the deviation and the synergistic coefficient, the specific value is obtained by nonlinear regression fitting; the numerical value of the upper limit of the national standard of the acid value of rapeseed oil is 3 mgKOH / g, and the numerical value of the reference value of the peroxide value of fresh rapeseed oil is 0.4 mmol / kg.

[0069] The implementation of the technical scheme needs to standardize the detection method and parameter determination process to ensure the accuracy and standardization of each link. The detection of acid value adopts titration method, strictly in accordance with GB / T5009.229-2016 national standard, and the detection process is as follows: 5.0 g of rapeseed oil sample is weighed and placed in a 250 mL conical flask, 50 mL of neutral ether-ethanol mixed solvent is added, the sample is shaken to completely dissolve, 3 drops of phenolphthalein indicator are added, and 0.1 mol / L potassium hydroxide standard solution is titrated until the solution is pink and does not fade within 30 s, the volume of consumed potassium hydroxide standard solution is recorded, and the calculation expression of acid value is , wherein is the volume of consumed potassium hydroxide standard solution, unit is mL; is the concentration of potassium hydroxide standard solution, unit is mol / L; 56.1 is the molar mass of potassium hydroxide, unit is g / mol; is the sample mass, unit is ; in the detection process, each sample is detected repeatedly for 3 times, and the average value is taken as the final detection result, and the relative deviation is less than 2%.

[0070] The detection of peroxide value adopts iodometric method, in accordance with GB / T5009.227-2016 national standard, and the detection process is as follows: 2.0 g of rapeseed oil sample is weighed and placed in a 250 mL iodometric flask, 30 mL of chloroform-glacial acetic acid mixed solvent is added, the sample is shaken to completely dissolve, 1 mL of saturated potassium iodide solution is added, after shaking, it is placed in the dark for 3 min, 100 mL of water is added, 0.01 mol / L sodium thiosulfate standard solution is titrated until the solution is light yellow, 1 mL of starch indicator is added, and the titration is continued until the blue color disappears, the volume of consumed sodium thiosulfate standard solution is recorded, and the calculation expression of peroxide value is , wherein is the volume of consumed sodium thiosulfate standard solution, unit is mL; The concentration of the sodium thiosulfate standard solution is mol / L; 0.1269 is the ratio of the molar mass of iodine to 2, with a unit of g / mmol; The sample mass has a unit of ; each sample is repeatedly detected 3 times, and the average value is taken as the final detection result, and the relative deviation is less than 3%.

[0071] The weight coefficient is determined by using the analytic hierarchy process, and the specific steps are as follows: first, a quality evaluation index system is constructed, the target layer is the comprehensive quality of rapeseed oil, and the criterion layer is the acid value, the attenuation trend and the peroxide value; second, a judgment matrix is constructed, five food detection experts are invited to compare the importance of each index in the criterion layer, and the 1-9 scale method is used for assignment, 1 indicates that the two indexes are equally important, 3 indicates that the former is slightly more important than the latter, 5 indicates that the former is more important than the latter, 7 indicates that the former is much more important than the latter, and 9 indicates that the former is extremely more important than the latter, and vice versa; third, weight calculation, the judgment matrix is normalized, the characteristic vector is calculated, and the characteristic vector is the weight coefficient of each index; fourth, consistency check, the consistency index , wherein is the maximum eigenvalue of the judgment matrix, is the number of indexes, and the weight coefficient of the present scheme is calculated by the following formula: When , it indicates that the judgment matrix has consistency, the weight distribution is reasonable, otherwise the judgment matrix needs to be adjusted and recalculated, and finally the weight coefficient , is obtained. The weight coefficient needs to meet , to ensure the rationality of the weighted sum.

[0072] The determination of the synergistic deviation correction coefficient is fitted by experiment, a standard rapeseed oil sample is selected, the standard values of the acid value and the peroxide value are determined by an authoritative detection institution, and different concentrations of phospholipid-rapeseed oil mixed samples are configured to obtain samples with different synergistic coefficients , the range is 0.2 to 1.8, the interval is 0.4, and there are 5 values, for each sample, the acid value and the peroxide value are detected by using the above titration method and the iodimetry, the absolute deviation of the detection result and the standard value is calculated, based on the corresponding relationship between the deviation and , a nonlinear regression is used to obtain the value of , the fitting model selects a quadratic function, and the determination coefficient of the fitting curve is required to ensure that can accurately compensate for different The upper limit of the acid value of the rapeseed oil and the reference value of the peroxide value of the fresh rapeseed oil are determined according to the national standards and the industry consensus, so as to ensure the uniformity and authority of the quality evaluation.

[0073] The above is only the preferred embodiment of the present application, and does not limit the present application in other forms. Any person skilled in the art can use the disclosed technical content to make changes or modifications into equivalent embodiments applied to other fields, but as long as it does not deviate from the technical solution of the present application, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present application still belongs to the protection scope of the technical solution of the present application.

Claims

1. A method for identifying the quality of rapeseed oil, characterized in that, Includes the following steps: S1. The concentration data of residual electroactive substances in rapeseed oil samples were obtained by electrochemical detection method; S2. Collect data on oxygen partial pressure, relative humidity, thermodynamic temperature, and light intensity of the rapeseed oil sample storage environment; S3. Based on the concentration data of the electroactive substance and the data of the storage environment, construct a synergistic effect quantification model and calculate the synergistic effect coefficient; S4. Based on the aforementioned synergistic effect coefficient, construct a nonlinear decay acceleration model and calculate the quality decay acceleration factor. S5. Detect acid value and peroxide value data of rapeseed oil samples; S6. Based on the quality degradation acceleration factor, the acid value data, and the peroxide value data, combined with the synergistic effect deviation correction mechanism, the comprehensive quality index of rapeseed oil is calculated to complete the quality identification of rapeseed oil.

2. The method for identifying the quality of rapeseed oil according to claim 1, characterized in that, Before step S1, there is also a sample pretreatment step, which is as follows: take 50 mL of rapeseed oil sample, filter it with a 0.45 μm organic phase filter membrane to remove mechanical impurities in the sample; take 10 mL of the filtered rapeseed oil sample and inject it into the electrochemical detection cell, and let it stand for 30 min.

3. The method for identifying the quality of rapeseed oil according to claim 1, characterized in that, The electroactive substance in step S1 is phospholipid; the electrochemical detection method in step S1 is implemented through a three-electrode system, which includes a working electrode, a reference electrode, and a counter electrode; the concentration data in step S1 is obtained by detecting the oxidation peak current of phospholipid using cyclic voltammetry, and then converting it with a calibration curve of oxidation peak current versus phospholipid concentration. The expression for the calibration curve is C = k1·I ox +k0, where C is the molar concentration of phospholipids, k1 is the slope of the calibration curve, and k0 is the intercept of the calibration curve. ox This represents the oxidation peak current of phospholipids.

4. The method for identifying the quality of rapeseed oil according to claim 1, characterized in that, The storage environment data mentioned in step S2 is collected through a sensor group, which includes an oxygen partial pressure sensor, a humidity sensor, a temperature sensor, and a light sensor. During the collection process, three sets of storage environment data are continuously acquired, and the average value of the three sets of data is taken as the input data for step S3.

5. The method for identifying the quality of rapeseed oil according to claim 1, characterized in that, The synergistic effect quantification model mentioned in step S3 is a synergistic effect coefficient model of trace electroactive substances. The synergistic effect coefficient model of trace electroactive substances is constructed based on the law of mass action and the van der Hoff equation. The synergistic effect strength is quantified by using the phospholipid electroactivity characteristic constant, humidity synergistic correction coefficient, temperature influence constant, and the concentration data and storage environment data of the electroactive substances.

6. The method for identifying the quality of rapeseed oil according to claim 5, characterized in that, The nonlinear degradation acceleration model mentioned in step S4 is a quality degradation acceleration factor model. The quality degradation acceleration factor model is constructed based on the Arrhenius equation and achieves nonlinear quantification of the quality degradation rate through the baseline degradation rate, temperature acceleration coefficient, light sensitivity coefficient, the synergistic effect coefficient, and storage environment data.

7. The method for identifying the quality of rapeseed oil according to claim 6, characterized in that, The synergistic deviation correction mechanism mentioned in step S6 is a rapeseed oil comprehensive quality index calculation mechanism. The rapeseed oil comprehensive quality index calculation mechanism uses acid value weight coefficient, decay factor weight coefficient, peroxide value weight coefficient, and synergistic deviation correction coefficient, combined with the quality decay acceleration factor, acid value data, peroxide value data and synergistic effect coefficient, to realize the correction of detection deviation and the quantification of comprehensive quality.

8. The method for identifying the quality of rapeseed oil according to claim 3, characterized in that, The working electrode of the three-electrode system is a glassy carbon electrode, the reference electrode is an Ag / AgCl electrode, and the counter electrode is a platinum wire electrode. The scanning range of the cyclic voltammetry is -0.2V to 1.0V, and the scanning rate is 50mV / s. The calibration curve was established as follows: five phospholipid-rapeseed oil standard samples with different molar concentrations were prepared, and the phospholipid oxidation peak current of each standard sample was detected by cyclic voltammetry. The calibration curve was obtained by linear regression analysis with the phospholipid molar concentration as the abscissa and the oxidation peak current as the ordinate.

9. The method for identifying the quality of rapeseed oil according to claim 5, characterized in that, The characteristic constants of phospholipid electroactivity were determined as follows: Phospholipid-rapeseed oil standard samples with different known molar concentrations were prepared, and the oxidation peak current of each standard sample was obtained. These values, combined with the standard values ​​from the stored environmental data, were substituted into the trace electroactive substance synergistic effect coefficient model, and the specific values ​​were obtained through least squares fitting. The humidity synergistic correction coefficient was determined as follows: The synergistic effect intensity of the same phospholipid-rapeseed oil standard sample was detected under different relative humidity conditions. Based on the correspondence between the detection results and relative humidity, the specific values ​​were obtained through nonlinear regression fitting. The temperature influence constant was derived based on the van der Hoff equation, and the derivation process incorporated calculations of the activation energy of the reaction between phospholipids and oxygen, as well as the gas constant.

10. The method for identifying the quality of rapeseed oil according to claim 7, characterized in that, The acid value mentioned in step S6 is detected by titration, and the peroxide value is detected by iodometric titration. The weighting coefficients of acid value, decay factor, and peroxide value are determined by the analytic hierarchy process (AHP), which includes three steps: constructing a quality evaluation index system, constructing a judgment matrix, calculating weights, and performing consistency checks. The synergistic deviation correction coefficient is determined as follows: under different synergistic effect coefficients, the acid value and peroxide value of the same rapeseed oil sample are tested, and the deviations of the test results from the standard values ​​are compared. Based on the correspondence between the deviation and the synergistic effect coefficient, a specific value is obtained through nonlinear regression fitting. The upper limit of the national standard for rapeseed oil acid value is 3 mg KOH / g, and the reference value for peroxide value of fresh rapeseed oil is 0.4 mmol / kg.

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