CN113267464A - Method and device for detecting multi-component heavy metal in edible oil based on near infrared combined colorimetric sensor array - Google Patents
Method and device for detecting multi-component heavy metal in edible oil based on near infrared combined colorimetric sensor array Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3577—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing liquids, e.g. polluted water
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/75—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated
- G01N21/77—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator
- G01N21/78—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator producing a change of colour
Abstract
The invention provides a method and a device for detecting multi-component heavy metal in edible oil based on a near-infrared combined colorimetric sensor array. Firstly, 5, 10, 15, 20-tetra (pentafluorophenyl) porphyrin iron chloride which is sensitive to heavy metal Pb, tetramethoxyphenyl porphyrin cobalt which is sensitive to heavy metal Hg ions and tetraphenylporphyrin iron which is sensitive to both are screened out. Then, two analog color sensor arrays are used for detecting heavy metals to be detected in the multi-component heavy metals in the corn oil. And finally, acquiring the reflection spectrum data of the colorimetric sensor array by using the automatic near-infrared detection device manufactured by the invention, and constructing a content prediction model of the multi-component heavy metal in the edible oil by using a joint interval partial least square ant colony algorithm and a partial least square method. The result shows that the method and the device can directly detect the multi-component heavy metal ions in the edible oil without sample pretreatment, and effectively improve the detection efficiency of workers.
Description
Technical Field
The invention belongs to the technical field of food safety, and particularly relates to a method and a device for detecting multi-component heavy metal in edible oil by combining near infrared with a colorimetric sensor array.
Background
Edible vegetable oil is one of the necessities of daily life of people, and contains unsaturated fatty acid, various vitamins, mineral substances and the like required by human bodies. Therefore, the addition of the edible oil can not only improve the color of dishes, but also has the effects of reducing blood fat and preventing arteriosclerosis. However, edible oils may be contaminated with heavy metals from different sources, such as soil, water and air required for the growth of edible oil raw materials. In addition, it may be introduced during the manufacturing process. The addition of these heavy metals promotes the oxidative degradation of the grease on the one hand; on one hand, heavy metal ions with carcinogenicity and strong toxicity, such as Hg, Cr, Pb, and the like, cannot be degraded once entering the human body, and cause serious harm to the health of the human body. And is particularly sensitive to heavy metal ions, namely Pb and Hg, and is particularly sensitive to the heavy metal ions for infants and teenagers. Hg is a highly toxic heavy metal, and its toxicity is manifested by a variety of symptoms, including liver damage, damage to the central nervous system, and the like. Pb poisoning mainly causes certain damage to the nervous system, blood system, skeletal system, and the like of a human body. Therefore, it is very important to detect heavy metals in edible oil from the viewpoints of health, storage of oil and fat, and the like.
At present, spectroscopic techniques (AS) such AS Atomic Absorption Spectroscopy (AAS), Atomic Emission Spectroscopy (AES), Laser Induced Breakdown Spectroscopy (LIBS) and the like, and biochemical methods such AS enzyme inhibition method, immunoassay method, biosensor method and the like are the most commonly used techniques for measuring trace heavy metals in edible oil. Although the method can carry out effective detection, the operation cost is high, the time is long, and the requirements of quick and real-time monitoring cannot be met. Electrochemical analysis methods including ion selective electrode methods, potential dissolution methods, polarographic analysis methods and the like have the advantages of good accuracy, low cost and the like, but still need sample pretreatment, and have poor accuracy and repeatability.
The colorimetric sensor is a large category of chemical sensors, and is a device or a device capable of sensing substances to be detected and the concentration thereof in the environment, and can convert information related to the types and the concentrations of the substances to be detected into electric signals so as to carry out detection, monitoring and analysis. However, the research of the colorimetric sensor is wide in related area and high in difficulty, belongs to the research field of multidisciplinary intersection, and the development difficulty of the characteristic color-sensitive material is high; the function is single, and one instrument cannot be used for detecting the components of various objects to be detected.
Near infrared spectrum is used as an electromagnetic wave containing a near-infrared (NIR) region, the corresponding wavelength range is 899.20-1724.71nm, the near-infrared spectrum is widely applied to the rapid detection of organic components in solid and liquid, and the near-infrared spectrum is widely applied to the field of analysis of the quality of food and agricultural products, such as fruits, meat, eggs and the like.
According to the reaction between the specific sensing color-sensitive material and the heavy metal to be detected, the sensor array can be used as a corresponding capture sensor array of heavy metal ions so as to realize quantitative analysis of the heavy metal to be detected. Metalloporphyrin as a special structure containing anions can generate coordination and combination reaction with positive 2-valent heavy metal ions, so that the energy of the metalloporphyrin is changed. This change can be characterized in the spectrum in the near-red range, which is sufficient for analytical detection of heavy metal ions.
Therefore, the method for simply, conveniently and quickly detecting the multi-component heavy metal in the edible oil is found, and has important practical significance for meeting the actual production requirements. Mixing the color sensitive material with heavy metal solution to react, and printing and dyeing the reacted solution on a substrate. And then the spectral data after the reaction of the heavy metal ions and the near infrared spectrum are detected and analyzed, and the rapid analysis of the multi-component heavy metal ions can be realized by combining a corresponding chemometrics method.
Disclosure of Invention
The invention aims to provide a method and a device for detecting multi-component heavy metal in edible oil based on a sensor array and a spectrum technology. The method can realize rapid analysis of multi-component heavy metal ions in the edible oil, and does not need to carry out pretreatment on the sample.
In order to achieve the above object, the technical solution of the present invention includes: the method comprises the steps of screening and optimizing a color-sensitive material with characteristic response, constructing a colorimetric sensor, collecting near infrared spectrum data, establishing a multi-component heavy metal detection model in edible oil, and providing the multi-component heavy metal detection device in the edible oil based on a sensor array and a spectrum technology. The method is suitable for the technical fields of food safety, environmental monitoring and the like.
The method and the device specifically adopt the following technical scheme:
a method for detecting multi-component heavy metals in edible oil based on a near-infrared combined colorimetric sensor array comprises the following steps: 1) screening of color sensitive materials: selecting color-sensitive materials sensitive to heavy metal to be detected respectively, and modifying and optimizing dyes by adopting dimethyl pyridinamine DPA and porous silica nanospheres PSNs with high affinity to heavy metal ions so as to improve the performance of the dyes; 2) construction of a colorimetric sensor: screening out DPA-TPPF2OfeCl @ PSN, DPA-TPPFeCl @ PSN and TPPCo @ PSN to form a 3 x 1 multi-component heavy metal capturing sensor array, a standard sample with the heavy metal to be detected being Pb is detected, and TPPF is utilized2A sensor array made of OfeCl @ PSN, TPPFeCl @ PSN and TPPCo @ PSN dyes is used for detecting a standard sample of Hg as heavy metal to be detected; 3) collecting near infrared spectrum data: the automatic near-infrared detection device manufactured by the invention is used for acquiring the near-infrared spectrum data of the sensor; 4) and (3) establishing a detection model of multi-component heavy metal ions in the edible oil.
Further, in the step 1), 5, 10, 15, 20-tetra (pentafluorophenyl) porphyrin iron chloride TPPF (lithium iron phosphate) sensitive to heavy metal Pb is selected through ultraviolet spectral kinetic analysis, mid-infrared spectral analysis and finally combined test verification2OFeCl, cobalt tetramethoxyphenylporphyrin TPPCo, which is sensitive to the heavy metal Hg ion, and iron tetraphenylporphyrin tppfeci, which is sensitive to both.
Further, in the step 3), the prepared DPA-TPPF2Carrying out mixed reaction on OfeCl @ PSN, DPA-TPPFeCl @ PSN and TPPCo @ PSN dyes and a corn oil sample according to a certain proportion to prepare a colorimetric sensor array; TPPF (thermoplastic vulcanizate)2Carrying out mixed reaction on OfeCl @ PSN, TPPFeCl @ PSN and TPPCo @ PSN dyes and a corn oil sample, and preparing a multi-component heavy metal capturing sensor array so as to realize capturing of target heavy metals in the corn oil without a pretreatment step; then, spectrum data of dye points on the sensor are obtained by using an automatic near-infrared detection device so as to carry out real-time synchronization on multi-component heavy metals in the corn oilThe whole process from sampling to displaying the detection result can be controlled within 5 minutes.
Further, in the step 4), preprocessing the spectral data by using SNV; then, qualitatively distinguishing the multi-component heavy metal sample, and mainly screening a spectrum variable, namely TPPF (transient particle Filter) by using ACO (acid-activated carbon)2899.2cm corresponding to three dye dots of OfeCl, TPPCo and TPPFeCl-1～1153.67cm-1，1242.88cm-1～1468.05cm-1And 1640.40cm-1～1710.4cm-1The wave band is a characteristic wave band of heavy metal to be detected in the corn oil; after integrating the variables, the KNN algorithm is used for carrying out qualitative analysis on the variables, and the quantitative analysis on the multi-component heavy metals is carried out by dividing an optimal spectrum interval by using the SiPLS algorithm and carrying out further variable screening on the optimal interval by combining with the ACO algorithm.
Further, the composition also comprises DPA-TPPF21354.16cm corresponding to dye points of OfeCl @ PSN, DPA-TPPFeCl @ PSN and TPPCo @ PSN-1～1379.88cm-1，915.77cm-1、942.24cm-1And 1389.51cm-1～1581.45cm-1And 914.12cm-1、940.59cm-1And 1640.40cm-1～1710.4cm-1The wave band is the characteristic wave band of heavy metal Pb in the corn oil, and TPPF2910.80cm corresponding to OfeCl @ PSN, TPPFeCl @ PSN and TPPCo @ PSN dyes-1～963.70cm-1、1250.97cm-1～1592.61cm-1，1527.20cm-1～1683.36cm-1，1288.12cm-1～1381.49cm-1、1646.76cm-1～1672.23cm-1The wave band is a characteristic wave band of heavy metal Hg in the corn oil, and finally after variables are integrated, a quantitative analysis model of multi-component heavy metal in the corn oil is constructed by using PLS.
A device for detecting multi-component heavy metals in edible oil based on a near-infrared combined colorimetric sensor array comprises a computer, a spectrometer (2), a USB data line (7), a Y-shaped optical fiber (3), a halogen tungsten lamp light source (1), a motor (4), a roller (6), a sampling table (9), a sampling chamber (5), a fixed table (8) and a fixed support (10);
the computer is connected with the spectrometer (2) by a USB data line (7); the incident end of the Y-shaped optical fiber (3) is connected with a halogen tungsten lamp light source (1); the reflection end of the Y-shaped optical fiber (3) is connected with the portable spectrometer (2); the roller (6), the motor (4) and the sampling platform (9) form a screw rod transmission structure, the motor (4) rotates to enable the roller (6) to rotate along with the screw rod transmission structure so as to convert rotary motion into linear motion, and then the sampling platform (9) is driven to move; the sampling chamber (5) is used for placing a sensor array; the fixing table (8) is used for fixing the reflection probe of the Y-shaped optical fiber (3); the fixed support (10) is used for adjusting the height of the fixed table.
Furthermore, the height of the fixing support (10) can be adjusted, and the maximum distance between the fixing support and the colorimetric sensor can be 10 cm; the sampling chamber (5) is a rectangular groove with the length of 3 multiplied by 1 cm; the fixed platform (8) is a rectangle with the length of 2cm and the height of 0.5cm, and the center is a circular hole with the diameter of 0.2 cm; the diameter of the color sensitive circular spot is 0.2cm, and the color sensitive circular spot completely covers the light spot at the probe end of the Y-shaped optical fiber (3).
The invention has the beneficial effects that: firstly, the 3 kinds of optimized porphyrin dyes have good selectivity and sensitivity to heavy metal ions, and two kinds of sensors are adopted to carry out targeted detection on heavy metals (Pb and Hg) to be detected; secondly, compared with other heavy metal ion detection methods, the method utilizes the optimized color-sensitive material to directly capture the heavy metal ions in the edible oil, so that the step of pretreatment of a sample is omitted, and the efficiency of heavy metal detection in the edible oil is effectively improved; thirdly, the sensor array after reaction is detected by using an automatic near infrared spectrum acquisition device, so that the heavy metal to be detected in the interference heavy metal can be accurately analyzed, and the environmental safety problem in actual production can be monitored in real time;
drawings
Fig. 1 is a schematic view of a 3 × 1 visual sensor array according to the present invention.
FIG. 2 is a diagram of an automatic near infrared spectrum detection device according to the present invention.
FIG. 3 is a discrimination model of a colorimetric sensor array based on a KNN algorithm for a class 4 heavy metal sample.
FIG. 4 is a Si-ACO-PLS detection model of Pb in corn oil with multi-component heavy metals by a nano DPA sensor array.
FIG. 5 is a Si-ACO-PLS detection model of Hg in corn oil with multi-component heavy metals by a nanocrystallization sensor array.
Detailed Description
The technical solutions of the present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments. The invention has universality for detecting multi-component heavy metal in edible oil. The target heavy metal selected by the embodiment has strong toxicity and great harmfulness, namely Hg and Pb, and other types of heavy metals can be carried out by referring to the embodiment; the selected edible oil sample is corn oil; interfering heavy metals are heavy metals common in corn oil: mg (magnesium)2+、Zn2+、Co2+、Na2+And K2+。
Referring to fig. 1, a device for detecting multi-component heavy metals in edible oil based on a near-infrared combined colorimetric sensor array comprises a computer, a spectrometer (2), a USB data line (7), a Y-shaped optical fiber (3), a halogen tungsten lamp light source (1), a motor (4), a roller (6), a sampling table (9), a sampling chamber (5), a fixing table (8) and a fixing support (10); the computer is connected with the spectrometer (2) by a USB data line (7); the incident end of the Y-shaped optical fiber (3) is connected with a halogen tungsten lamp light source (1); the reflection end of the Y-shaped optical fiber (3) is connected with the portable spectrometer (2); the sampling chamber (5) is used for placing a sensor array; the fixing table (8) is used for fixing the reflection probe of the Y-shaped optical fiber (3); the fixed support (10) is used for adjusting the height of the fixed table. The roller (6), the motor (4) and the sampling table (9) form a screw rod transmission structure; the roller path is filled with balls, after the motor is started, the balls inside roll along the roller path and circularly move through the two adjacent roller paths, so that the roller (6) rotates along with the rollers to convert the rotary motion into linear motion, and then the sampling platform (9) is driven to move.
3 color sensitive materials with higher sensitivity and reliability are preferably selected in the implementation example; mixing the color sensitive material with corn oil to capture target heavy metal ions in the color sensitive material; thereafter, the post-reaction solution was spotted at C2Manufacturing a sensor array on the reverse silica gel plate; the automatic near infrared spectrum acquisition device is used for acquiring the spectrum data of the sensor array so as to achieve the purpose of rapid analysis. Detailed description of the inventionThe technical scheme is as follows:
example 1 was carried out: qualitative detection of heavy metals (Pb and Hg) to be detected and interfering heavy metals
A novel qualitative discrimination method for multi-component heavy metal ions comprises the following specific operation steps:
(1) as shown in fig. 1, a 3 × 1 heavy metal capture sensor array is fabricated as follows: (a) 10mg of 5, 10, 15, 20-tetrakis (pentafluorophenyl) porphyrin iron chloride (TPPF) were each accurately weighed2OFeCl), cobalt tetramethoxyphenylporphyrin (TPPCo), iron tetraphenylporphyrin (TPPFeCl), dissolved in dichloromethane and made to volume in a 5mL volumetric flask. Performing ultrasonic treatment for 15min to obtain a solution with the concentration of 2 mg/mL; (b) diluting Pb and Hg by using a dye substrate, diluting the interference heavy metal to 10 times of the concentration of the heavy metal to be detected, and preparing the following 4 types of heavy metal samples to be detected: the method comprises the following steps of (I) blank and 5 interference heavy metal solutions, (II) Pb and Pb +5 interference heavy metal solutions, (III) Hg and Hg +5 interference heavy metal solutions, and (IV) Pb + Hg and Pb + Hg +5 interference heavy metal solutions. Wherein the concentration of the heavy metal solution to be detected is 100ppb of the corn oil specified by China standard, and the concentration of the interfering heavy metal is 1 ppm. Each concentration gradient is made into 20 parallels; (c) mixing the optimized porphyrin dye with the prepared heavy metal solution to be detected according to a certain ratio (1:1) for reaction, and spotting the solution on C by using a 5mm capillary tube after shaking and reacting for 1 minute2In a reverse silica gel plate; (d) when the color sensitive material is volatilized on the silica gel plate until the color sensitive material is stable, the 3 × 1 colorimetric sensor array shown in fig. 1 can be obtained, and the colorimetric sensor array is sealed and stored singly by using a sample bag for later use.
(2) The computer is connected with the spectrometer by a data line, and the spectrometer is connected with the light source by an optical fiber cable. The integration time in the reflective mode was set to 70 milliseconds, the average scan time was 5 and the smoothness was 10. And dark correction and white correction are performed thereon. And then, fixing the optical fiber probe on a fixed table, adjusting the height of the fixed support, and placing the sensor array in a sampling chamber. And (3) starting a motor, and sequentially acquiring the reflection spectrum data of the 3 dye printing points on the colorimetric sensor prepared in the step (1) by using the optical fiber probe, and recording the reflection spectrum data as the spectrum numerical value of the color-sensitive material after the current sample is captured. In addition, to avoid errors, each dye spot was irradiated twice with a fiber optic probe and the final results were averaged twice.
(3) The acquired near infrared spectrum contains noise information, background drift and the like. Therefore, the spectral data extracted from the colorimetric sensor is analyzed by adopting standard normal variate transformation (SNV) to eliminate the influence of surface scattering and optical path length change on the original near infrared spectral data. And selecting spectral variables through an ACO algorithm, and establishing a discrimination model of the 4-class heavy metal sample by using KNN. As a result, when the number of principal components was 12 and the K value was 3, the discrimination rate was optimal, and the recognition rates of the training set and the prediction set were 0.903 and 0.896, respectively. Fig. 3 is a discrimination model diagram of the colorimetric sensor array for the 4-class heavy metal samples.
Example 2 was carried out: quantitative detection of heavy metals (Pb and Hg) to be detected in corn oil under the condition of interfering the existence of heavy metals
A novel quantitative detection method for multi-component heavy metal ions in corn oil comprises the following specific operation steps:
(1) as shown in fig. 1, the sensor array for capturing heavy metal ions is 3 × 1, and is manufactured as follows: (a) weighing three kinds of characteristic color-sensitive dyes (5, 10, 15, 20-tetra (pentafluorophenyl) porphyrin iron chloride (TPPF)2OFeCl), tetramethoxyphenyl cobalt porphyrin (TPPCo), tetraphenyl iron porphyrin (TPPFeCl)), and Porous Silica Nanospheres (PSNs) and Dimethyl Pyridinamide (DPA) are utilized to optimize and modify the dye; (b) the heavy metals to be tested (Pb and Hg) are diluted to a certain concentration gradient (10, 20, 40, 60, 80, 100ppb) by using a dye substrate, and the potential interference heavy metal elements: mg (magnesium)2+、Zn2+、Co2+、Na2+And K2+Was spiked into the corn oil sample and the concentration was set at 200 ppb. Each concentration gradient is made into 20 parallels; (c) the prepared DPA-TPPF2OfeCl @ PSN, DPA-TPPFeCl @ PSN and TPPCo @ PSN dyes are mixed with a prepared standard corn oil sample with heavy metal Pb to be detected according to a certain ratio (1:1) for reaction, and TPPF is added2And carrying out mixed reaction on the OfeCl @ PSN, TPPFeCl @ PSN and TPPCo @ PSN dyes and a prepared standard corn oil sample with Hg as a heavy metal to be detected. After shaking up and reacting for 1 minuteThe solution was spotted using a 5mm capillary onto 3X 1cm of C2In a reverse silica gel plate; (d) when the color sensitive material is volatilized on the silica gel plate until the color sensitive material is stable, the 3 × 1 colorimetric sensor array shown in fig. 1 can be obtained, and the colorimetric sensor array is sealed and stored singly by using a sample bag for later use.
(2) The same as embodiment 1: and (2) qualitative detection of heavy metals (Pb and Hg) to be detected and interfering heavy metals.
FIG. 2 is a diagram of an automatic near infrared spectrum detection device according to the present invention. FIG. 3 is a discrimination model of a colorimetric sensor array based on a KNN algorithm for a class 4 heavy metal sample.
(3) The acquired near infrared spectrum contains noise information, background drift and the like. Therefore, the spectral data extracted from the colorimetric sensor is analyzed by adopting standard normal variate transformation (SNV) to eliminate the influence of surface scattering and optical path length change on the original near infrared spectral data. The spectral variables of the 3 dyes were initially screened using the SiPLS algorithm. And integrating the screened variables, further selecting spectral variables through ACO, and establishing a prediction model of the content of heavy metals Hg and Pb in the corn oil by utilizing a PLS algorithm. Finally, DPA-TPPF in the presence of interfering heavy metals2And a sensor array consisting of OfeCl @ PSN, DPA-TPPFeCl @ PSN and TPPCo @ PSN dyes is used for detecting the heavy metal Pb in the corn oil. The number of intervals is 10, 18 and 20, and the combined interval is [10,11 ]]、[1,11,14,15]、[1,11,14,18]Then, the optimal spectral intervals are obtained respectively. After variable integration, under the ACO-PLS algorithm, the predicted correlation coefficient reaches 0.9896, and the predicted root mean square error is 0.2491; TPPF2When a sensor array consisting of OfeCl @ PSN, TPPFeCl @ PSN and TPPCo @ PSN dyes detects heavy metal Hg in corn oil, the combined intervals are [1,6,8 and 11 ] at intervals of 13, 20 and 20]、[12,16,19]、[1,10,12,19]The optimal spectral interval is obtained. The correlation coefficient and root mean square error for the prediction set were 0.9752 and 0.3844, respectively. The model effect is better. FIG. 4 is a Si-ACO-PLS detection model of a nano DPA sensor array for Pb in corn oil containing multiple heavy metals. FIG. 5 shows a Si-ACO-PLS detection model of Hg in corn oil of multi-component heavy metals by a nanocrystallization sensor array.
Claims (7)
1. A method for detecting multi-component heavy metals in edible oil based on a near-infrared combined colorimetric sensor array is characterized by comprising the following steps: 1) screening of color sensitive materials: selecting color-sensitive materials sensitive to heavy metal to be detected respectively, and modifying and optimizing dyes by adopting dimethyl pyridinamine DPA and porous silica nanospheres PSNs with high affinity to heavy metal ions so as to improve the performance of the dyes; 2) construction of a colorimetric sensor: screening out DPA-TPPF2OfeCl @ PSN, DPA-TPPFeCl @ PSN and TPPCo @ PSN to form a 3 x 1 multi-component heavy metal capturing sensor array, a standard sample with the heavy metal to be detected being Pb is detected, and TPPF is utilized2A sensor array made of OfeCl @ PSN, TPPFeCl @ PSN and TPPCo @ PSN dyes is used for detecting a standard sample of Hg as heavy metal to be detected; 3) collecting near infrared spectrum data: the automatic near-infrared detection device manufactured by the invention is used for acquiring the near-infrared spectrum data of the sensor; 4) and (3) establishing a detection model of multi-component heavy metal ions in the edible oil.
2. The method for rapidly detecting the multi-component heavy metal in the edible oil based on the near-infrared combined sensor technology as claimed in claim 1, wherein in the step 1), 5, 10, 15, 20-tetra (pentafluorophenyl) porphyrin iron chloride TPPF sensitive to heavy metal Pb is selected through ultraviolet spectral dynamics analysis, mid-infrared spectral analysis and finally combined test verification2OFeCl, cobalt tetramethoxyphenylporphyrin TPPCo, which is sensitive to the heavy metal Hg ion, and iron tetraphenylporphyrin tppfeci, which is sensitive to both.
3. The method for rapidly detecting the multi-component heavy metals in the edible oil based on the near infrared combined sensor technology as claimed in claim 1, wherein in the step 3), the prepared DPA-TPPF is used2Carrying out mixed reaction on OfeCl @ PSN, DPA-TPPFeCl @ PSN and TPPCo @ PSN dyes and a corn oil sample according to a certain proportion to prepare a colorimetric sensor array; TPPF (thermoplastic vulcanizate)2OfeCl @ PSN, TPPFeCl @ PSN and TPPCo @ PSN dyes are mixed with a corn oil sample for reaction, and multi-component heavy metal capturing sensor is preparedAn array of devices to capture the target heavy metals in the corn oil without a pretreatment step; and then, acquiring spectral data of dye points on the sensor by using an automatic near-infrared detection device so as to synchronously monitor multi-component heavy metal in the corn oil in real time, wherein the whole process from sampling to displaying the detection result can be controlled within 5 minutes.
4. The method for rapidly detecting the multi-component heavy metal in the edible oil based on the near-infrared combined sensor technology according to claim 1, wherein in the step 4), SNV is used for preprocessing spectral data; then, qualitatively distinguishing the multi-component heavy metal sample, and mainly screening a spectrum variable, namely TPPF (transient particle Filter) by using ACO (acid-activated carbon)2899.2cm corresponding to three dye dots of OfeCl, TPPCo and TPPFeCl-1～1153.67cm-1，1242.88cm-1～1468.05cm-1And 1640.40cm-1～1710.4cm-1The wave band is a characteristic wave band of heavy metal to be detected in the corn oil; after integrating the variables, the KNN algorithm is used for carrying out qualitative analysis on the variables, and the quantitative analysis on the multi-component heavy metals is carried out by dividing an optimal spectrum interval by using the SiPLS algorithm and carrying out further variable screening on the optimal interval by combining with the ACO algorithm.
5. The method for rapidly detecting the multi-component heavy metals in the edible oil based on the near infrared combined sensor technology as claimed in claim 4, further comprising DPA-TPPF21354.16cm corresponding to dye points of OfeCl @ PSN, DPA-TPPFeCl @ PSN and TPPCo @ PSN-1～1379.88cm-1，915.77cm-1、942.24cm-1And 1389.51cm-1～1581.45cm-1And 914.12cm-1、940.59cm-1And 1640.40cm-1～1710.4cm-1The wave band is the characteristic wave band of heavy metal Pb in the corn oil, and TPPF2910.80cm corresponding to OfeCl @ PSN, TPPFeCl @ PSN and TPPCo @ PSN dyes-1～963.70cm-1、1250.97cm-1～1592.61cm-1，1527.20cm-1～1683.36cm-1，1288.12cm-1～1381.49cm-1、1646.76cm-1～1672.23cm-1The wave band is a characteristic wave band of heavy metal Hg in the corn oil, and finally after variables are integrated, a quantitative analysis model of multi-component heavy metal in the corn oil is constructed by using PLS.
6. A device for detecting multi-component heavy metals in edible oil based on a near-infrared combined colorimetric sensor array is characterized by comprising a computer, a spectrometer (2), a USB data line (7), a Y-shaped optical fiber (3), a halogen tungsten lamp light source (1), a motor (4), a roller (6), a sampling table (9), a sampling chamber (5), a fixing table (8) and a fixing support (10);
the computer is connected with the spectrometer (2) by a USB data line (7); the incident end of the Y-shaped optical fiber (3) is connected with a halogen tungsten lamp light source (1); the reflection end of the Y-shaped optical fiber (3) is connected with the portable spectrometer (2); the roller (6), the motor (4) and the sampling platform (9) form a screw rod transmission structure, the motor (4) rotates to enable the roller (6) to rotate along with the screw rod transmission structure so as to convert rotary motion into linear motion, and then the sampling platform (9) is driven to move; the sampling chamber (5) is used for placing a sensor array; the fixing table (8) is used for fixing the reflection probe of the Y-shaped optical fiber (3); the fixed support (10) is used for adjusting the height of the fixed table.
7. The device for detecting the multi-component heavy metal in the edible oil based on the near infrared combined colorimetric sensor array according to claim 6, wherein the height of the fixing support (10) can be adjusted, and the distance between the fixing support and the colorimetric sensor is 10cm at most; the sampling chamber (5) is a rectangular groove with the length of 3 multiplied by 1 cm; the fixed platform (8) is a rectangle with the length of 2cm and the height of 0.5cm, and the center is a circular hole with the diameter of 0.2 cm; the diameter of the color sensitive circular spot is 0.2cm, and the color sensitive circular spot completely covers the light spot at the probe end of the Y-shaped optical fiber (3).
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