Reagent for rapidly detecting aureomycin and rapid aureomycin detection method

Abstract

The invention relates to the technical field of nano materials and analysis and detection, in particular to a reagent for rapidly detecting aureomycin and a rapid aureomycin detection method. After the 3-mercaptopropionic acid modified AgInS2 quantum dots are added into aureomycin, the fluorescence intensity and color of the AgInS2 QDs are changed due to electrostatic interaction and band gap transition, so that a fluorescence colorimetric sensor is constructed to realize ultra-sensitive detection of the aureomycin. In order to realize on-site detection of aureomycin, a portable device equipped with a smart phone and an AgInS2 QDs sensor integration are also designed. A cloud server data analysis system based on a machine learning algorithm is integrated into the smart phone, so that color data collection, correction, explanation and display are facilitated. According to the invention, a user-friendly field detection solution is provided for aureomycin detection by utilizing the functions of capturing and processing fluorescence color signals of a modern smart phone.

Description

Technical Field

[0001] The present invention relates to the technical field of nano material preparation and chemical analysis detection, and in particular to a reagent for rapid detection of chlortetracycline and a rapid detection method of chlortetracycline. Background Art

[0002] Chlortetracycline (CTC) is one of the most widely used tetracycline antibiotics in humans, livestock and aquaculture worldwide. It is favored for its low price, significant efficacy and broad spectrum. However, due to the lack of awareness of the hazards of veterinary drug residues by some livestock and poultry farmers, they abuse drugs in pursuit of economic benefits, resulting in an increasingly serious problem of chlortetracycline residues in animal-derived foods. Long-term intake of food containing chlortetracycline residues will seriously threaten human health and produce toxic effects such as allergic reactions, liver damage and bacterial resistance. Faced with this severe situation, many countries have clearly defined the maximum residue limits of antibiotics in food. Therefore, in order to ensure food safety, it is imperative to develop a rapid and accurate chlortetracycline detection method.

[0003] There are many methods for detecting chlortetracycline that have been reported, including high performance liquid chromatography (HPLC), liquid chromatography-mass spectrometry (LC-MS), electrochemical method and enzyme-linked immunosorbent assay (ELISA). However, these methods have the defects of long detection time, complex pre-treatment, high analysis cost, need for professional operators and low sensitivity. In recent years, fluorescent sensors have attracted much attention due to their advantages such as simple operation, fast speed, low detection cost, rapid response and good selectivity. However, existing fluorescent sensing methods usually require the aid of instruments, making it difficult to achieve sensitive detection on site. Therefore, there is an urgent need to develop a portable, sensitive and economical chlortetracycline on-site detection method. Based on the portable characteristics of a portable fluorescent visual sensing platform, the present invention provides a new method for ultra-sensitive detection of chlortetracycline based on a fluorescent visual sensing platform assisted by a machine learning smartphone. Summary of the invention

[0004] In order to solve the above problems existing in the prior art, the object of the present invention is to provide a reagent for rapid detection of chlortetracycline and a rapid detection method of chlortetracycline, which can not only detect chlortetracycline with ultra-sensitive sensitivity, but also realize portable fluorescent visualization on-site detection in complex matrices.

[0005] To achieve the above object, the present invention provides a reagent for rapid detection of chlortetracycline in the first aspect, wherein the reagent is AgInS modified with 3-mercaptopropionic acid. 2 Quantum dot solution.

[0006] The second aspect of the present invention provides a 3-mercaptopropionic acid modified AgInS for rapid detection of chlortetracycline concentration. 2The preparation method of quantum dots comprises: dissolving 3-mercaptopropionic acid in ultrapure water to obtain a 3-mercaptopropionic acid solution, then adding silver ions and indium ions and mixing them thoroughly, and then using an alkali solution to adjust the pH value to 8-9; then injecting a sodium sulfide solution into the solution, stirring at room temperature for a preset time and then heating to react, and after the reaction is completed, centrifuging the obtained solution to remove the precipitate to obtain 3-mercaptopropionic acid modified AgInS 2 Quantum dot solution.

[0007] Furthermore, the molar ratio of the 3-mercaptopropionic acid, silver ions, indium ions, and sodium sulfide is 1:1.55-1.75:8.25-8.45:6.9-7.1;

[0008] The alkali solution is a 0.8-1.2 mol / L NaOH solution; preferably a 1 mol / L NaOH solution;

[0009] The preset stirring time at room temperature is 15-20 minutes; the temperature used for the heating reaction is 95-105°C and the time is 180-200 minutes.

[0010] Furthermore, the volume of the 3-mercaptopropionic acid solution is 24-26 mL, and the concentration is 0.195-0.205 mol / L; the amount of the silver nitrate solution is 0.080-0.085 mmol; and the amount of the indium ion substance is 0.415-0.420 mmol;

[0011] And / or, the concentration of the NaOH solution is 1 mol / L, and the pH value is adjusted to 8-9 by adding the NaOH solution;

[0012] And / or, the volume of the sodium sulfide solution is 1.95-2.05 mL, and the amount of the substance is 0.341-0.359 mmol;

[0013] And / or, the preset stirring time at room temperature is 15-20 min; the temperature used for the heating reaction is 95-105° C. and the time is 180-200 min.

[0014] Furthermore, the 3-mercaptopropionic acid-modified AgInS 2 The morphology of the QDs solution under a transmission electron microscope is a regularly spherical shape with a particle size of 2.63 to 4.66 nm. The strongest emission wavelength is 580 nm, showing bright orange fluorescence.

[0015] The third aspect of the present invention provides a method for rapid detection of chlortetracycline concentration, comprising the following steps:

[0016] The 3-mercaptopropionic acid-modified AgInS 2The QDs solution is mixed with the chlortetracycline solution to be tested for reaction, and the concentration of the chlortetracycline solution to be tested is obtained according to the fluorescence intensity and / or color change;

[0017] The fluorescence intensity is determined by establishing a standard relationship curve between the concentration of the chlortetracycline solution and the degree of fluorescence enhancement; the color change is determined by model comparison or prediction based on machine learning or by comparison through an intelligent terminal.

[0018] Furthermore, the method for establishing the standard relationship curve includes: 2 The QDs solution was diluted to a preset concentration and then mixed with chlortetracycline standard solutions of different concentrations. After the reaction was complete, a standard relationship curve between the concentration of chlortetracycline solution and the degree of fluorescence enhancement was established based on the change in the fluorescence intensity of the corresponding mixed solution and the concentration of chlortetracycline solution.

[0019] The standard relationship curve is as follows:

[0020] F / F 0 =4.8952C CTC +8.5546, R 2 =0.9983

[0021] Where F represents the fluorescence intensity of the solution after adding chlortetracycline, F 0 represents the fluorescence intensity of the solution without adding chlortetracycline, C CTC Indicates the concentration of chlortetracycline solution.

[0022] Preferably, AgInS 2 The dilution factor of the QDs solution was 10 times.

[0023] Preferably, AgInS 2 The volume ratio of QDs solution, chlortetracycline solution and ultrapure water is 1:1:18.

[0024] Furthermore, the chlortetracycline standard solution and AgInS 2 The reaction time of the QDs solution is 200 min, and the concentration range of chloramphenicol in the reaction system is 0.05-5 μmol / L; preferably, the concentration of chloramphenicol solution in the reaction system is 0.05, 0.15, 0.25, 0.35, 0.45, 1, 2, 3, 4, and 5 μmol / L, respectively.

[0025] Preferably, in step 1, in AgInS 2 After adding chlortetracycline solution to the QDs solution, the fluorescence color of the mixed solution changed from orange to pink and finally to blue-purple. The fluorescence intensity at 414nm increased, and the particles were no longer dispersed under a transmission electron microscope, but showed obvious aggregation.

[0026] The method for constructing the model based on machine learning includes:

[0027] The 3-mercaptopropionic acid-modified AgInS 2 The QDs solution was diluted to a preset concentration and then mixed with chloramphenicol standard solutions of different concentrations to obtain a mixed solution. After the reaction was complete, the image information of the mixed solution was collected by taking photos with a camera, and the RGB value digital matrix corresponding to the photo was obtained using MATLAB software. Finally, the RF model was used to associate the RGB values ​​of the pixels in the mixed solution photo with the concentration of the chloramphenicol solution.

[0028] Furthermore, specifically: using Photoshop software, extracting pixel information in the captured image; then, using MATLAB software, extracting the RGB value of each pixel to obtain a corresponding digital matrix; finally, combining the digital matrix with an RF algorithm to construct an RF model that can predict the concentration of chloramphenicol.

[0029] Preferably, the specific operation method is: in the RF model, an original training set is established according to the given RGB values ​​and the corresponding chlortetracycline concentrations, and samples are extracted with replacement from the original training set by autonomous sampling to establish multiple different training subsets, each training subset is used to construct a decision tree model, and when all decision trees are constructed, the RF algorithm obtains the final regression prediction result by averaging or voting the prediction results of each decision tree, and establishes a linear model to achieve the prediction of chlortetracycline concentration.

[0030] Furthermore, in the construction of the machine learning-based model, the chlortetracycline standard solution and AgInS 2 The reaction time of the QDs solution is 200 min, and the concentration range of chloramphenicol in the reaction system is 0 to 500 μmol / L; preferably, the concentration of chloramphenicol solution in the reaction system is 0, 0.1, 0.2, 1, 10, 50, 100, 500 μmol / L, respectively.

[0031] Furthermore, the prediction of chlortetracycline concentration by the intelligent terminal includes the following steps:

[0032] Step 1: Building an RGB value conversion program and the RF model described in claim 9 on a smart terminal;

[0033] Step 2: The 3-mercaptopropionic acid-modified AgInS 2The QDs solution is diluted to a preset concentration, and then mixed with the chlortetracycline solution to be tested to obtain a mixed solution. After the reaction is complete, the image information of the mixed solution is collected by taking a photo with an intelligent terminal and converted into RGB values. Then, the intelligent terminal predicts the concentration of the chlortetracycline solution to be tested according to the RGB value of the chlortetracycline solution to be tested based on the RF model described above;

[0034] Preferably, the intelligent terminal is a smart phone or a tablet computer.

[0035] Preferably, specifically: add AgInS into the sample plate 2 QDs and different concentrations of chlortetracycline were mixed evenly. Fluorescence photos were taken with a smartphone and accurately converted into corresponding RGB values ​​through the applet. Subsequently, the extracted RGB values ​​were uploaded to the quantitative detection interface, and the cloud machine learning algorithm (RF model) of the applet automatically provided the predicted value of chlortetracycline concentration based on the input RGB values.

[0036] Compared with the prior art, the present invention has the following advantages:

[0037] 1. 3-Mercaptopropionic acid modified AgInS prepared by the present invention 2 QDs, based on electrostatic interaction and band gap transition, make the mixed solution undergo fluorescence enhancement and color change, which is convenient for constructing AgInS 2 QDs fluorescent colorimetric sensor, thus realizing the visual detection of chlortetracycline. Moreover, the electrostatic interaction shortens the AgInS 2 The distance between QDs and chlortetracycline increases the AgInS 2 Sensitivity of QDs to chlortetracycline.

[0038] 2. Compared with the existing chlortetracycline detection method, the present invention is based on the fluorescence visual sensing platform of machine learning assisted smart phones for ultra-sensitive detection of chlortetracycline, which has the characteristics of low cost, low detection limit, high portability and rich color change. In addition, in order to realize the on-site detection of chlortetracycline, a portable device equipped with a smart phone is integrated into the smart phone with a cloud server data analysis system based on a machine learning algorithm, which is convenient for color data collection, correction, interpretation and display. This innovative method takes advantage of the function of modern smart phones to capture and process fluorescent color signals, thereby providing a user-friendly on-site detection solution for chlortetracycline detection. Compared with other detection methods, the sensor can produce more color intervals, and can achieve more sensitive on-site detection of chlortetracycline after being used in combination with a portable fluorescence visual sensing platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 The AgInS 2Principle and detection diagram of QDs fluorescence sensor.

[0040] Figure 2 AgInS 2 Structural characterization of QDs. (a) Transmission electron microscopy, (b) X-ray photoelectron spectroscopy, (c) X-ray diffraction spectrum, (d) AgInS 2 QDs and AgInS 2 Fourier transform infrared spectrum of QDs+chlortetracycline.

[0041] Figure 3 AgInS 2 QDs quantitatively detect chlortetracycline. (a) AgInS in the presence of different concentrations of chlortetracycline (0.05, 0.15, 0.25, 0.35, 0.45, 1, 2, 3, 4, 5 μM). 2 Fluorescence spectra of QDs solution, (b) fluorescence intensity ratio (F / F 0 ) and the linear relationship between chlortetracycline concentration, (c) CIE chromaticity diagram under the action of different concentrations of chlortetracycline, (d) partially enlarged CIE chromaticity diagram.

[0042] Figure 4 To explore the mechanism of action. 2 QDs (a) and AgInS 2 TEM images of QDs+chlortetracycline (b), (c) AgInS 2 QDs and AgInS 2 Zeta potential of QDs+chlortetracycline, (d) AgInS 2 QDs and AgInS 2 UV-visible absorption and fluorescence spectra of QDs+chlortetracycline.

[0043] Figure 5 To explore the mechanism of action. 2 QDs (a) and AgInS 2 Fluorescence spectra of QDs+chlortetracycline (c), AgInS 2 QDs (b) and AgInS 2 QDs+chlortetracycline (d) (αhv) 1 / 2 Graph showing the variation of hv.

[0044] Figure 6 (a) Fluorescence photos of AgInS2 QDs in the presence of different concentrations of chloramphenicol (0-500μM) (3 sets of parallel), (b) RF algorithm analysis results of fluorescence photo RGB values ​​and chloramphenicol concentrations (0-500μM).

[0045] Figure 7In the figure, (a) physical picture of the components of the portable sensing platform, (b) the use process of the portable sensing platform.

[0046] Figure 8 Images of different concentrations of chlortetracycline taken for the portable sensing platform. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0048] The invention provides a reagent for rapid detection of chlortetracycline and a rapid detection method of chlortetracycline. Based on electrostatic interaction and band gap transition, the mixed solution undergoes fluorescence enhancement and color change, thereby constructing an AgInS 2 QDs fluorescence colorimetric sensor. In this process, the concentration of chlortetracycline solution is directly related to the change of fluorescence enhancement and fluorescence color of the solution. As the concentration of chlortetracycline increases, the fluorescence intensity of the solution gradually increases, and the fluorescence color gradually changes from orange to pink, purple, and blue. Based on the above principles, the present invention can achieve the following purposes: (1) Measure the degree of fluorescence enhancement by a fluorescence spectrophotometer, and establish a linear equation to predict the concentration of chlortetracycline in a complex matrix; (2) By extracting the RGB value of the solution fluorescence color and combining the RF model to realize the visualization concentration prediction of chlortetracycline in a complex matrix; (3) By using the portable fluorescence sensing platform developed by us to take fluorescent photos, the applet extracts the RGB value of the solution fluorescence color and uploads it to the cloud, and the cloud algorithm calculates to realize the prediction of chlortetracycline concentration.

[0049] The method for ultra-sensitive detection of chlortetracycline based on a fluorescence visual sensing platform assisted by a smartphone using machine learning of the present invention will be described in detail below through specific examples.

[0050] In the following examples: the chlortetracycline solution is prepared by adding chlortetracycline hydrochloride to ultrapure water.

[0051] A reagent for rapid detection of chlortetracycline and a rapid detection method of chlortetracycline, comprising the following steps:

[0052] Step (1): 3-Mercaptopropionic acid modified AgInS 2 Synthesis of QDs

[0053] 3-Mercaptopropionic acid (MPA) was dissolved in 25 mL of ultrapure water to obtain a 0.2 M 3-mercaptopropionic acid solution, and then 0.083 mmol of silver nitrate and 0.417 mmol of indium ion (indium chloride) were added and mixed evenly. The pH of the resulting solution was adjusted to 8.5 with 1 M sodium hydroxide. Subsequently, 2 mL of 0.35 mmol of Na 2 S was quickly injected into the solution, stirred at room temperature for 15 min, and heated at 100 °C for 3 h to obtain AgInS 2 The resulting solution was centrifuged to remove the precipitate and stored in a refrigerator at 4°C for later use. Finally, AgInS with orange fluorescence under 365nm UV light was obtained. 2 QDs solution, the maximum fluorescence emission wavelength is at 580nm.

[0054] The prepared AgInS 2 QDs were scanned by transmission electron microscopy, and the resulting TEM images were shown in Figure 2 As shown in a, the prepared AgInS 2 The QDs morphology is close to spherical particles, with good dispersion and a lattice fringe width of 0.32nm. 2 QDs were subjected to XRD characterization to analyze their crystal structure. Figure 2 As shown in c, the XRD peaks at 2θ = 26.7°, 44.8°, and 52.3° correspond to AgInS 2 The (112), (204) and (312) crystal planes of the QDs tetragonal crystals are consistent with the crystal planes of the standard card JCPDS25-1330. 2 The Fourier transform infrared spectra of QDs are shown in Figure 2 As shown in d. 3400cm -1 The broad vibration peak at 2900 cm-1 corresponds to the -OH stretching vibration. -1 The band at is attributed to -CH 2 Extension vibration. 1565cm -1 and 1385cm -1 The two absorption bands at 2570cm -1 There is no vibration band corresponding to the -SH group at , which indicates that the thiol covalent bond may be broken, indicating that MPA successfully modifies AgInS through the covalent bond between thiol and metal cation. 2 QDs. Figure 4 As shown in middle d, under the excitation of 340nm, AgInS 2 The fluorescence spectrum of QDs shows an emission peak at 580nm, and there is no obvious absorption peak in the UV spectrum.

[0055] Step (2): AgInS 2 Quantitative Analysis of Chlortetracycline by Fluorescence Spectroscopy Using QDs Fluorescence Sensor

[0056] (1) Quantitative detection of chlortetracycline by fluorescence spectroscopy

[0057] The AgInS obtained in step (1) diluted 10 times was placed in an EP tube. 2 50 μL of QDs and 50 μL of chlortetracycline solutions of different concentrations were mixed, and ultrapure water was added to keep the total volume of the system at 1 mL to obtain a mixed solution that interacts with chlortetracycline solutions of different concentrations (the concentration of chlortetracycline in the system is 0.05, 0.15, 0.25, 0.35, 0.45, 1, 2, 3, 4, 5 μmol / L). After reacting for 200 minutes, the fluorescence spectrum data of the mixed solution was collected at room temperature and normal pressure. A standard curve for detecting chlortetracycline was established based on the concentration of chlortetracycline solution and the degree of fluorescence enhancement of the corresponding mixed solution. Figure 3 As shown in a, with the increase of chlortetracycline concentration in the system (0-5.00×10 -6 mol / L), the fluorescence intensity at 414 nm gradually increased. Figure 3 In b, it is shown that at 5.00×10 -8 Up to 5.00×10 -6 mol / L range, the fluorescence intensity of the system (F / F 0 ) showed a good linear relationship with the concentration of chlortetracycline, and the standard curve was F / F 0 =4.8952C CTC +8.5546(R 2 =0.9983), where F represents the fluorescence intensity of the solution after adding chlortetracycline, F 0 The fluorescence intensity of the solution without chlortetracycline was expressed as follows: LOD = 3σ / k, and the detection limit (LOD) of chlortetracycline was calculated to be 1.97 nmol / L, where k is F / F 0 The slope of the standard curve related to the concentration of chlortetracycline, σ is the standard deviation of the blank signal. As shown in Table 1, compared with other literature, the detection limit of the sensor system developed in the present invention is lower. More importantly, Figure 3 Medium c and Figure 3 As shown in (d), based on AgInS 2 The QDs-based sensor exhibited a rich color shift (from orange to blue) and remarkable linearity.

[0058] Table 1 Comparison of the present invention and existing CTC residual detection methods

[0059]

[0060] The literature information corresponding to the 5 prior arts in Table 1 is as follows:

[0061] [1]Z.W.Lu,S.R.Chen,M.T.Chen,H.Ma,T.K.Wang,T.Liu,J.J.Yin,M.M.Sun,C.Wu,G.H.Su,X.X.Dai,X.X.Wang,Y.Y.Wang,H.D.Yin,X.G.Zhou,Y.Z.Shen,H.B.Rao,Trichromatic ratiometric fluorescent sensor based on machine learning andsmartphone for visual and portable monitoring of tetracycline antibiotics,Chem.Eng.J.454(2023)140492.

[0062] [2]L.Yu,H.X.Chen,J.Yue,X.F.Chen,M.T.Sun,H.Tan,A.M.Asiri,K.A.Alamry,X.K.Wang,S.H.Wang,Metal–Organic Framework Enhances Aggregation-InducedFluorescence of Chlortetracycline and the Application for Detection,Anal.Chem.91(9)(2019)5913-5921.

[0063] [3]H.Moon,C.Lee,W.Lee,J.Kim,H.Chae,Stability of Quantum Dots,QuantumDot Films,and Quantum Dot Light-Emitting Diodes for Display Applications,Adv.Mater.31(34)(2019)1804294.

[0064] [4] L. Yu, HXChen, J. Yue,

[0065] [5] CCLong, SCLiu,

[0066] (2) AgInS 2 Study on the mechanism of QDs fluorescence sensor

[0067] Figure 4 A and Figure 4 The transmission electron microscopy results in (b) show that the prepared AgInS 2 QDs were well dispersed. However, after adding chlortetracycline, AgInS 2 The QDs showed a tendency to aggregate, and the average diameter increased from 3.71 nm to 4.62 nm. This aggregation phenomenon may be due to the chlorine atoms in chlortetracycline and AgInS 2 The p-π conjugation between QDs is caused by Figure 4 As shown in c, AgInS 2 The Zeta potential of QDs was initially -45.65 mV and changed to -20.53 mV after the addition of chlortetracycline. 2 The Zeta potential of QDs increases, which may be due to the 2 The negative charge associated with the carboxyl groups of QDs was neutralized by the -OH groups of chlortetracycline. This change indicates that the electrostatic interaction shortens the AgInS 2The distance between QDs and chlortetracycline increases the AgInS 2 QDs are sensitive to chlortetracycline. Figure 2 As shown in (d), for AgInS 2 QDs and AgInS 2 The comparison of Fourier transform infrared spectra of QDs+chlortetracycline revealed that AgInS 2 3400cm of QDs -1 、1565cm -1 and 1385cm -1 The vibration peak at did not move significantly after the addition of chlortetracycline. This indicates that in AgInS 2 No new functional groups were generated during the binding of QDs to chlortetracycline. Figure 4 In AgInS 2 The addition of chlortetracycline to the QDs solution resulted in the 2 The absorption peak of QDs changes, which indicates that the conjugated structure of the system has changed. The band gap is the difference between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO). Figure 5 As shown in b and d, the UV-visible diffuse reflectance spectrum was analyzed to determine the AgInS 2 The energy level difference between LUMO and HOMO of QDs before and after adding chlortetracycline. Figure 5 As shown in a and c, after adding chlortetracycline, AgInS 2 The original fluorescence peak of QDs did not change, but a new fluorescence peak appeared at 414nm. The original energy band gap hardly changed, but a new energy band gap of 4.53eV was added. This may be that the energy band gap was split and part of it underwent transition. 2 The band gap transition caused by surface defects of QDs plays a role in regulating the fluorescence properties of QDs. Therefore, we infer that the sensing mechanism of chlortetracycline detection involves electrostatic interaction and band gap transition.

[0068] Step (3): Quantitative detection of chlortetracycline by fluorescence visual sensing

[0069] Further development of AgInS 2 The fluorescence visual sensing technology of QDs was used to explore its applicability in detecting chlortetracycline in complex samples. The specific operation was as follows: the AgInS obtained by diluting 10 times in step (1) was placed in a 96-well plate. 2200 μL of QDs and 200 μL of chlortetracycline solutions of different concentrations were mixed to obtain mixed solutions that interacted with chlortetracycline solutions of different concentrations (chlortetracycline concentrations were 0, 0.1, 0.2, 1, 10, 50, 100, and 500 μmol / L). After reacting for 200 min, a camera was used to capture fluorescent photos of the mixed solution at room temperature and atmospheric pressure. Figure 6 As shown in a, with the increase of chlortetracycline concentration (0-5000×10 -7 mol / L) gradually increased, and AgInS could be observed by naked eyes under UV light. 2 QDs showed obvious fluorescence color changes from orange to pink, purple, and blue.

[0070] The present invention uses MATLAB software to convert different concentrations of chlortetracycline (0-5000×10 -7 mol / L) was converted into RGB (red, green, blue) color values. Then, the random forest (RF) algorithm was applied for quantitative analysis. The specific process is as follows:

[0071] First, the collected fluorescence images were imported into PS, and 10px×10px pixels (30 groups of parallels) were extracted for each concentration. Then, with the assistance of MATLAB software, each 10px×10px image was converted into a matrix of 300 (RGB)×30 (parallel samples). Finally, we converted the images of 8 different concentrations into a matrix of 300 (RGB)×240 (samples). In order to establish the best quantitative model, the RGB data of 240 samples of 8 different concentrations were randomly divided into 168 training samples and 72 prediction samples. At this time, the Ntree and leaf number of the RF model were 150 and 7, respectively. The coefficient of determination R 2 c and R 2 p is used to evaluate the correlation between the predicted concentration and the actual concentration in the training set and the prediction set, respectively. Generally speaking, R 2 c. R 2 p and R 2 The closer it is to 1, the better the prediction effect of the model. RMSE (root mean square error) measures the deviation between the predicted value and the true value. It is sensitive to outliers in the data. The root mean square error (RMSEC) and root mean square prediction error (RMSEP) of the training set and the prediction set are used to evaluate the accuracy of the quantitative model. Generally speaking, the smaller the RMSEC and RMSEP, the better the accuracy of the model. Table 2 lists the prediction results, showing that the R2c of the training set is 1.0000 and the RMSEC is 4.58. The R2p of the prediction set is 0.9999 and the RMSEP is 17.33.

[0072] Table 2 Chlortetracycline concentration determination results based on RGB images and RF

[0073]

[0074] like Figure 6 As shown in b, in the range of 0-5000×10 -7 In the concentration range of 1.1 mol / L, the predicted concentration of chlortetracycline showed a good linear relationship with the actual concentration, with minimal deviation. These results further prove that the RGB color value combined with the RF algorithm model can predict the concentration of chlortetracycline in animal-derived foods, and the quantitative results are accurate and reliable.

[0075] Step (4): Visual detection of chlortetracycline using a portable smartphone sensing platform

[0076] In order to broaden the application scope of this sensing strategy and make on-site detection simpler and more portable, we have incorporated AgInS 2 QDs were combined with a smartphone-based homemade optical device to develop an instrument-free smart fluorescence visual sensing platform. The optical device was equipped with a 365nm UV lamp with light filtering function and a sample box, which served as both a carrier and a darkroom ( Figure 7 a). It not only eliminates the influence of the distance between the sample and the excitation beam, but also effectively suppresses the interference of the excitation beam and the environment, thereby improving the accuracy and feasibility of on-site monitoring. The cloud server data analysis system based on machine learning algorithm is integrated into the smartphone as a fluorescence color signal reader and substance content analyzer to extract features from the fluorescence image and convert it into RGB to achieve quantitative analysis of chlortetracycline in complex matrices. Taking milk samples as an example, Figure 7 As shown in b, 200 μL AgInS was added to the sample plate. 2 QDs and 200 μL of chlortetracycline of different concentrations were mixed evenly and the reaction was complete. Fluorescence photos were then taken using a smartphone, and the colors of the fluorescence photos were accurately converted into corresponding RGB values. Subsequently, the extracted RGB values ​​were uploaded to the quantitative detection interface, and the predicted values ​​of chlortetracycline concentrations were automatically provided based on the input RGB values. In order to verify the accuracy of the sensing platform, a series of chlortetracycline concentrations (1, 10, 100, and 500 μM) were selected, and three parallel fluorescence photos were taken for each concentration to facilitate the recognition and judgment of the applet. The results are shown in Table 3. The recovery rate ranged from 94.00% to 104.67%, and the RMSEP ranged from 0.04 to 3.48. According to LOD = 3.3σ, σ represents the standard deviation of the blank signal, the LOD of the portable fluorescence sensing platform for chlortetracycline is 0.69×10 -7 mol / L. These results demonstrate that the machine learning-assisted intelligent platform is able to extract color features and detect the concentration of analytes quickly and accurately in a simple and portable manner.

[0077] Table 3 Comparison of predicted and measured values ​​of the milk matrix portable sensing platform

[0078]

[0079]

[0080] In summary, the present invention utilizes 3-mercaptopropionic acid modified AgInS 2 The quantum dots interact with the electrostatic and band gap transition of chlortetracycline, resulting in changes in fluorescence intensity and color, which enables ultrasensitive detection of chlortetracycline. A portable device equipped with a smartphone and AgInS 2 QDs sensor integration. The cloud server data analysis system based on machine learning algorithms is integrated into the smartphone to facilitate color data collection, correction, interpretation and display. This innovative method takes advantage of the ability of modern smartphones to capture and process fluorescent color signals, thereby providing a user-friendly on-site detection solution for chlortetracycline detection. Compared with other detection methods, the sensor can produce more color ranges, and when used in combination with a portable fluorescent visual sensing platform, it can achieve more sensitive on-site detection of chlortetracycline. The method of the present invention has the characteristics of low cost, low detection limit, high portability and high selectivity.

[0081] The above-mentioned embodiments only express the accurate implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present invention. It should be pointed out that, for those of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention patent shall be subject to the attached claims.

Claims

1. A reagent for rapid detection of chlortetracycline, characterized in that: The reagent is a 3-mercaptopropionic acid modified AgInS2 quantum dot solution.

2. A method for preparing a reagent for rapid detection of chlortetracycline according to claim 1, characterized in that: include: 3-Mercaptopropionic acid is dissolved in ultrapure water to obtain a 3-mercaptopropionic acid solution, and then silver ions and indium ions are added and mixed thoroughly, and then the pH value is adjusted to 8-9 with an alkaline solution; sodium sulfide solution is then injected into the solution, and the solution is heated to react after stirring at room temperature for a preset time. After the reaction is completed, the resulting solution is centrifuged to remove the precipitate to obtain a 3-mercaptopropionic acid modified AgInS2 quantum dot solution.

3. The preparation method according to claim 2, characterized in that: The molar ratio of 3-mercaptopropionic acid, silver ions, indium ions and sodium sulfide is 1:1.55-1.75:8.25-8.45:6.9-7.1; The alkali solution is a 0.8-1.2 mol / L NaOH solution; The preset stirring time at room temperature is 15-20 minutes; the temperature used for the heating reaction is 95-105°C and the time is 180-200 minutes.

4. The preparation method according to claim 2, characterized in that: The morphology of the 3-mercaptopropionic acid modified AgInS2 QDs solution under a transmission electron microscope is a regular sphere with a particle size of 2.63-4.66 nm and a strongest emission wavelength of 580 nm.

5. A rapid detection method for chlortetracycline concentration, characterized in that: include: Mixing the 3-mercaptopropionic acid-modified AgInS2 QDs solution obtained by the preparation method according to any one of claims 2 to 4 with the chlortetracycline solution to be tested, and obtaining the concentration of the chlortetracycline solution to be tested according to the fluorescence intensity and / or color change; The fluorescence intensity is determined by establishing a standard relationship curve between the concentration of the chlortetracycline solution and the degree of fluorescence enhancement; the color change is determined by model comparison or prediction based on machine learning or by realizing chlortetracycline concentration prediction through an intelligent terminal.

6. The detection method according to claim 5, characterized in that: The method for establishing the standard relationship curve includes: diluting the 3-mercaptopropionic acid modified AgInS2 QDs solution to a preset concentration, and then mixing with chlortetracycline standard solutions of different concentrations, and after the reaction is complete, establishing a standard relationship curve between the concentration of chlortetracycline solution and the degree of fluorescence enhancement according to the concentration of chlortetracycline solution and the degree of change in the fluorescence intensity of the mixed solution corresponding to it; The standard relationship curve is as follows: F / F0=4.8952C CTC +8.5546,R 2 =0.9983 Where F represents the fluorescence intensity of the solution after adding chlortetracycline, F0 represents the fluorescence intensity of the solution without adding chlortetracycline, and C CTC Indicates the concentration of chlortetracycline solution.

7. The detection method according to claim 6, characterized in that: The reaction time of the chloramphenicol standard solution and the AgInS2 QDs solution is 200 min, and the concentration range of chloramphenicol in the reaction system is 0.05-5 μmol / L; preferably, the concentration of chloramphenicol solution in the reaction system is 0.05, 0.15, 0.25, 0.35, 0.45, 1, 2, 3, 4, and 5 μmol / L, respectively.

8. The detection method according to claim 5, characterized in that: The method for constructing the model based on machine learning includes: The 3-mercaptopropionic acid modified AgInS2 QDs solution is diluted to a preset concentration, and then mixed with chloramphenicol standard solutions of different concentrations to obtain a mixed solution. After the reaction is complete, the image information of the mixed solution is collected by taking photos with a camera, and the RGB value digital matrix corresponding to the photo is obtained using MATLAB software. Finally, the RF model is used to associate the RGB values ​​of the pixels in the mixed solution photo with the concentration of the chloramphenicol solution.

9. The detection method according to claim 8, characterized in that: Specifically, the pixel information in the captured image is extracted by using Photoshop software; then, the RGB value of each pixel is extracted by using MATLAB software to obtain the corresponding digital matrix; finally, the digital matrix is ​​combined with the RF algorithm to construct an RF model that can realize the prediction of chlortetracycline concentration; Preferably, the specific operation method is: in the RF model, an original training set is established according to the given RGB values ​​and the corresponding chlortetracycline concentrations, and samples are extracted with replacement from the original training set by autonomous sampling to establish multiple different training subsets, each training subset is used to construct a decision tree model, and when all decision trees are constructed, the RF algorithm obtains the final regression prediction result by averaging or voting the prediction results of each decision tree, and establishes a linear model to achieve the prediction of chlortetracycline concentration.

10. The detection method according to claim 9, characterized in that: The method of realizing chlortetracycline concentration prediction by the intelligent terminal comprises the following steps: Step 1: Building an RGB value conversion program and the RF model described in claim 9 on a smart terminal; Step 2: dilute the 3-mercaptopropionic acid modified AgInS2 QDs solution to a preset concentration, and then mix it with the chlortetracycline solution to be tested to obtain a mixed solution. After the reaction is complete, use a smart terminal to capture image information of the mixed solution and convert it into RGB values. Then, the smart terminal predicts the concentration of the chlortetracycline solution to be tested based on the RGB value of the chlortetracycline solution to be tested based on the RF model of claim 9; Preferably, the intelligent terminal is a smart phone or a tablet computer.

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