A method for detecting boric acid and borate based on smart phone

Abstract

The invention discloses a method for detecting boric acid and borate based on a smart phone, which comprises the following steps: S1, preparing a membrane mixture for detecting boric acid and borate; S2, preparing a membrane mixture for detecting boric acid and borate; S3, drying to form a sensor A and a sensor B in a 2ml centrifuge tube; S4, taking a sample to be tested and placing it in a colorimetric tube, adding water to the scale, filtering with a filter membrane, and obtaining a sample filtrate; S5, preparing a series of boric acid reference solutions, diluting the series of boric acid reference solutions with water, and obtaining a linear series solution; S6, taking 1ml of each linear series solution, 1ml of a blank solution, and 1ml of a sample filtrate, respectively, and placing them in a 2ml self-made centrifuge tube with a sensor A and a sensor B, covering the sensor A, and shaking sufficiently to fully dissolve the sensors B and A, and then using a smart phone to determine the content of boric acid and borate. The method is used to prepare a natural biodegradable sensor, which has a rapid response, a simple analysis process, and a low cost of a detection device.

Description

Technical Field

[0001] The present invention relates to the field of cosmetics detection, and in particular to a method for detecting boric acid and borates based on a smart phone. Background Art

[0002] Boric acid and borates are generally used as preservatives in cosmetics and can be applied to the skin epidermis, but excessive intake or contact with boron may damage the reproductive system or the health of the fetus. If absorbed by broken skin, it will cause poisoning. The safety of cosmetics containing boric acid deserves attention, and the establishment of rapid detection methods provides technical support for the screening of a large number of samples.

[0003] Analytical methods for determining boron include inductively coupled plasma spectroscopy (ICP), atomic absorption spectroscopy (AAS), and spectrophotometry with various color developers. ICP and AAS methods suffer from spectral interference and memory effects, while some color developers required for spectrophotometry are difficult to synthesize, unstable, and sensitive to temperature, pH, or reagent concentration. These instrumental methods also rely on expensive and bulky instruments, have high operating costs, and complex procedures. Therefore, these analytical methods are difficult to use for rapid on-site detection of boron. Moreover, instrumental detection requires high detection skills from the detection personnel, and there are disadvantages such as the need for a special detection laboratory or detection environment. In addition, the detection liquids or dangerous reagents are inconvenient to carry. Summary of the invention

[0004] The purpose of the present invention is to solve the defects of the prior art and provide a method for detecting boric acid and borates based on a smart phone.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A method for detecting boric acid and borates based on a smart phone comprises the following steps:

[0007] S1, preparing a nail film mixture for boric acid and borate detection;

[0008] S2, preparing a membrane mixture for boric acid and borate detection;

[0009] S3, transferring the obtained membrane A mixture and membrane B mixture into centrifuge tubes for drying and cooling to room temperature, forming sensor A after the membrane A mixture is processed and forming sensor B after the membrane B mixture is processed, and storing the cooled sensor A and sensor B in a vacuum or filled with nitrogen;

[0010] S4. Place the sample to be tested in a colorimetric tube, add water to the scale, shake vigorously, mix the sample to be tested and water thoroughly, and filter through a filter membrane to obtain a sample filtrate;

[0011] S5. Prepare a series of boric acid reference solutions, and dilute the series of boric acid reference solutions with water to obtain a linear series of solutions;

[0012] In the specific operation, weigh about 10 mg of boric acid reference substance and place it in a 10 mL volumetric flask, add water to the mark, and obtain 1 mg / mL boric acid reference solution ①, then accurately measure 4 mL of boric acid reference solution ① and place it in a 100 mL volumetric flask, and obtain 40 μg / mL boric acid reference solution ②, accurately measure reference solution ② 0, 0.1, 0.25, 0.5, 1, 2, 4, 6, 8, 10 mL, place it in a 10 mL volumetric flask, and add water to the mark. The concentrations of 0, 0.4, 1, 2, 4, 8, 16, 24, 32, 40 μg / ml linear series solutions are obtained.

[0013] S6. Take 1 ml of each linear series solution, 1 ml of blank solution, and 1 ml of sample filtrate, respectively, and place them in a 2 ml self-made centrifuge tube with sensors A and B, cover with sensor A, allow sensors B and A to fully dissolve, react at room temperature for 60 minutes, and use a smart phone to measure the content of boric acid and borate;

[0014] During the specific operation, 1 ml of each linear series solution (equivalent to 0 μg, 0.4 μg, 1 μg, 2 μg, 4 μg, 8 μg, 16 μg, 20 μg, 28 μg, and 40 μg of boric acid, respectively), 1 ml of blank solution, and 1 ml of sample filtrate were placed in 2 ml self-made centrifuge tubes with sensors A and B, covered with sensor A, and shaken thoroughly to allow sensors B and A to fully dissolve. Then, react for 60 minutes at room temperature (25°C) and measure the content of boric acid and borate with a mobile phone.

[0015] In step S1, the method for preparing the nail film mixture comprises the following steps:

[0016] Weigh 0.5g starch and disperse it in 10ml water. Heat it in a 100℃ water bath with continuous stirring until a clear viscous solution is obtained. After cooling to room temperature, add 0.4g azomethine and 2g vitamin C to 10mL starch solution respectively and stir well to obtain a nail membrane mixture.

[0017] In step S2, the method for preparing the film mixture comprises the following steps:

[0018] Weigh 0.5 g of starch and disperse it in 10 ml of water. Heat it in a 100°C water bath with continuous stirring until a clear viscous solution is obtained. After cooling to room temperature, add 5 g of ammonium acetate and 0.45 g of disodium ethylenediaminetetraacetate to 10 mL of the starch solution and stir well to obtain an ethylene film mixture.

[0019] The starch is one or more of corn starch, pea starch, wheat starch, sweet potato starch, konjac, dextrin, potato starch, and cassava starch, and the starch content ranges from 2.5 to 10%. The processing parameters are: heating temperature, which can be 65-100°C; oven drying or vacuum drying, the temperature is 30-80°C for 1-24h, and the starch solution concentration is 2.5-10%; the addition ratio of ammonium acetate and disodium ethylenediaminetetraacetic acid can be adjusted to ensure that the Ph value is 5.5-7; the amount of methyleneamine and vitamin C can also be adjusted, the content of vitamin C ranges from 2-10%, and the amount of methyleneamine is 0.05-1g.

[0020] The reaction time is 20-110min.

[0021] Furthermore, in S6, the specific steps of the mobile phone measurement are as follows:

[0022] S61: Use a smartphone to build an APP to take a photo of the linear series solution in S6 in a self-built detection device to obtain the R, G, and B values. The software automatically calculates A xtotal Value, calculation formula A Xtotal =A R +A G +A B The concentration of the series of solutions is used as the horizontal axis, A xtotal The value is the ordinate, and the software automatically calculates the correlation coefficient, intercept, and slope;

[0023] S62: Use a smartphone to build an APP to take a photo of the sample solution in S6 in the self-built detection device to obtain the R, G, and B values. The software automatically obtains the corresponding concentration value. After entering the sample weight, the software automatically obtains the content.

[0024] Furthermore, the R, G, and B values ​​are not limited to the conversion of the above formulas, but can also be converted according to the following 7 formulas and a model can be established with the concentration of boric acid:

[0025] 1.I total =I R +I G +I B ;

[0026] 2.|I X -I Xblank | total =|I R -I Rblank |+|I G -I Gblank |+|I B -I Bblank |;

[0027] 3.A X =-|og((I X+I X，b ) / (I X，W -I X，W ));

[0028] 4.A Xtotal =A R +A G +A B ;

[0029] 5.|A X -A Xblank | total =|A R -A Rblank |+|A G -A Gblank |+|A B -A Bblank |;

[0030] 6. Gray = 0.3R + 0.59G + 0.11B;

[0031] 7.A Gray = -log(Gray / Gray blank );

[0032] Among them, I R ,I G ,I B Respectively represent the color intensity values ​​of the three channels of the sample solution RGB; I Rblank , I Gblank ,I Bblank Respectively represent the color intensity values ​​of the background blank of the three channels of the sample solution RGB; X represents R, G, B, then I X Represents the color intensity value of the R, G, and B channels of the sample solution; X blank Can represent R blank , G blank , B blank , then I Xblank Represents the color intensity value of the sample solution R, G, B background blank; A X Represents the absorbance value of the R, G, and B channels of the sample solution, A Xblank Represents the background blank absorbance value of the sample solution R, G, B channels, I X , b=0,I X , W = 255; Gray represents the conversion of the R, G, and B channels of the sample solution into grayscale values; A Gray Represents the absorbance value of the sample solution R, G, and B channels after conversion to grayscale values.

[0033] Furthermore, the concentrations of the linear series solutions are 0, 0.4, 1, 2, 4, 8, 16, 24, 32, and 40 μg / ml, respectively.

[0034] The beneficial effects of the present invention are as follows: 1. The method prepares a natural biodegradable film, embeds liquid reagents and hazardous reagents in the natural biofilm to form a green colorimetric sensor (sensor A, sensor B), simplifies the boric acid and borate pretreatment steps, has the advantages of rapid response, simple analysis process, low device and instrument cost, and achieves real-time on-site detection;

[0035] 2. This method applies smartphones to the field of cosmetics testing, replacing traditional spectrophotometers. It is faster and more convenient, and can help supervisors without professional testing backgrounds to screen samples. Supervisory departments can quickly identify suspicious samples, which will greatly reduce the burden of testing and make testing more efficient. At the same time, the portable testing method can benefit the general public and is easy to promote.

[0036] 3. This method builds a picture acquisition device with a constant light source and establishes a colorimetric detection and classification algorithm based on an artificial neural network. By using the neural network, discrete data points can be fitted with the functional relationship between the chromaticity value and the concentration value of the sample to be tested, and the content of the sample to be tested can be quickly and accurately determined. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic diagram of the detection process of the present invention;

[0038] Figure 2 This is a schematic diagram of the structure of a centrifuge tube with sensors A and B made by the present invention;

[0039] Figure 3 This is a diagram of the app interface of the colorimetric detection system for a smartphone of the present invention. DETAILED DESCRIPTION

[0040] like Figure 1 As shown, a method for detecting boric acid and borates based on a smartphone comprises the following steps:

[0041] S1, preparing a nail film mixture for boric acid and borate detection;

[0042] S2, preparing a membrane mixture for boric acid and borate detection;

[0043] S3, transfer the obtained membrane A mixture and membrane B mixture to containers (the membrane A mixture is transferred to the flat cover of a 1.5 mL centrifuge tube, and the membrane B mixture is transferred to the bottom of a 1.5 mL centrifuge tube) for drying (45°C oven drying for 16 hours), cool to room temperature, the membrane A mixture is processed to form the A sensor, and the membrane B mixture is processed to form the B sensor, put the cooled centrifuge tubes containing the A and B sensors into bags, and store them in a vacuum or nitrogen atmosphere;

[0044] S4. Take the sample to be tested (talcum powder as an example) and place it in a 10 ml colorimetric tube. Add water to the scale for volume fixation, shake vigorously. After the sample to be tested is fully mixed with water, filter it through a 0.22 μm filter membrane to obtain the sample filtrate;

[0045] S5. Prepare a series of boric acid reference solutions, and dilute the series of boric acid reference solutions with water to obtain a linear series of solutions;

[0046] During specific operation, weigh about 10 mg of boric acid reference substance and place it in a 10 mL volumetric flask. Add water to the scale for volume fixation to obtain a 1 mg / mL boric acid reference solution ①. Then accurately measure 4 mL of boric acid reference solution ① and place it in a 100 mL volumetric flask to obtain a 40 μg / mL boric acid reference solution ②. Accurately measure 0, 0.1, 0.25, 0.5, 1, 2, 4, 6, 8, 10 mL of reference solution ② and place them in a 10 mL volumetric flask. Add water to the scale for volume fixation. Thus, a linear series of solutions with concentrations of 0, 0.4, 1, 2, 4, 8, 16, 24, 32, 40 μg / ml are obtained.

[0047] S6. As Figure 2 shown, respectively take 1 ml of each linear series solution, 1 ml of the blank solution, and 1 ml of the sample filtrate, and place them in a 2 ml self-made centrifuge tube with sensors A and B. Cover sensor A and shake vigorously. After sensors B and A are fully dissolved, at room temperature, react for 60 min, and use a smartphone to measure the content of boric acid and borate;

[0048] During specific operation, respectively take 1 ml of each linear series solution (respectively equivalent to 0 μg, 0.4 μg, 1 μg, 2 μg, 4 μg, 8 μg, 16 μg, 20 μg, 28 μg, 40 μg of boric acid), 1 ml of the blank solution, and 1 ml of the sample filtrate, and place them in a 2 ml self-made centrifuge tube with sensors A and B. Cover sensor A and shake vigorously. After sensors B and A are fully dissolved, at room temperature (25 °C), react for 60 min, and use a mobile phone to measure the content of boric acid and borate.

[0049] Furthermore, in the above S1, the preparation method of the A-film mixture includes the following steps:

[0050] Weigh 0.5 g of starch and disperse it in 10 ml of water. Continuously stir and heat it in a water bath at 100 °C until a clear viscous solution is obtained. After cooling to room temperature, add 0.4 g of azomethine-H and 2 g of vitamin C to the 10 mL starch solution, and stir evenly to obtain the A-film mixture.

[0051] Furthermore, in the above S2, the preparation method of the B-film mixture includes the following steps:

[0052] Weigh 0.5 g of starch and disperse it in 10 ml of water. Heat it in a 100°C water bath with continuous stirring until a clear viscous solution is obtained. After cooling to room temperature, add 5 g of ammonium acetate and 0.45 g of disodium ethylenediaminetetraacetate to 10 mL of the starch solution and stir well to obtain an ethylene film mixture.

[0053] The starch is one or more of corn starch, pea starch, wheat starch, sweet potato starch, konjac, dextrin, potato starch, and cassava starch, and the starch content ranges from 2.5 to 10%. The processing parameters are: heating temperature, which can be 65-100°C; oven drying or vacuum drying, the temperature is 30-80°C for 1-24h, the starch solution concentration is 2.5-10%; the addition ratio of ammonium acetate and disodium ethylenediaminetetraacetic acid can be adjusted to ensure that the Ph value is 5.5-7; the amount of methyleneamine and vitamin C can also be adjusted, the content of vitamin C ranges from 2-10%, the amount of methyleneamine is 0.05-1g, and the reaction time is 20-110min.

[0054] In this embodiment, the chemical principle of the methyl amine mixture is that boron forms a yellow complex with methyleneamine-H, and its color is linearly related to the concentration of boron within a certain range. Methyleneamine is easily oxidized and unstable, and the role of ascorbic acid is to protect the imine group in methyleneamine-H and prevent it from oxidation.

[0055] The principle of the ethylene film mixture: The role of encapsulating ammonium acetate and disodium ethylenediaminetetraacetate in starch is to adjust the Ph value of the sample solution. When the pH of the buffer solution is between 6.0 and 7.0, the color reaction is more complete. At pH 7.0, the maximum absorbance appears, and the absorbance value is most stable at pH 6.0-6.5.

[0056] By using starch wrapping, methyleneamine-H and ascorbic acid are wrapped in a membrane, and ammonium acetate and disodium ethylenediaminetetraacetate are wrapped in a membrane. This solves the problem of reagent carrying, and starch is degradable, soluble, and does not pollute the environment.

[0057] Furthermore, in S6, the specific steps of the mobile phone measurement are as follows:

[0058] S61: Use a smartphone to build an APP to take a photo of the linear series solution in S6 in a self-built detection device to obtain the R, G, and B values. The software automatically calculates A xtotal Value, calculation formula A Xtotal =A R +A G +A B The concentration of the series of solutions is used as the horizontal axis, A xtotal The value is the ordinate, and the software automatically calculates the correlation coefficient, intercept, and slope;

[0059] S62: Use a smartphone to build an APP to take a photo of the sample solution in S6 in the self-built detection device to obtain the R, G, and B values. The software automatically obtains the corresponding concentration value. After entering the sample weight, the software automatically obtains the content.

[0060] Furthermore, the R, G, and B values ​​can be converted according to the following seven formulas and a model is established with the concentration of boric acid:

[0061] 1.I total =I R +I G +I B ;

[0062] 2.|I X -I Xblank | total =|I R -I Rblank |+|I G -I Gblank |+|I B -I Bblank |;

[0063] 3.A X = -log((I X +I X，b ) / (I X，W -I X，W ));

[0064] 4.A Xtotal =A R +A G +A B ;

[0065] 5.|A X -A Xblank | total =|A R -A Rblank |+|A G -A Gblank |+|A B -A Bblank |;

[0066] 6. Gray = 0.3R + 0.59G + 0.11B;

[0067] 7.A Gray = -log(Gray / Gray blank );

[0068] Among them, I R ,I G ,I B Respectively represent the color intensity values ​​of the three channels of the sample solution RGB; I Rblank , IGblank ,I Bblank Respectively represent the color intensity values ​​of the background blank of the three channels of the sample solution RGB; X represents R, G, B, then I X Represents the color intensity value of the R, G, and B channels of the sample solution; X blank Can represent R blank , G blank , B blank , then I Xblank Represents the color intensity value of the sample solution R, G, B background blank; A X Represents the absorbance value of the R, G, and B channels of the sample solution, A Xblank Represents the background blank absorbance value of the sample solution R, G, B channels, I X , b=0,I X , W = 255; Gray represents the conversion of the R, G, and B channels of the sample solution into grayscale values; A Gray Represents the absorbance value of the sample solution R, G, B channels after conversion to grayscale values. The results are shown in the following table. When the concentration exceeds 40μg / ml, it is not linear.

[0069] Analysis of RGB color space and grayscale color space characteristics

[0070]

[0071]

[0072] From the above table, we can see that A B , A xtotal , A B -A Bblank ,|A x -A xblank | total The correlation coefficient of , is greater than 0.99. The color of this experiment is mainly yellow, which is most affected by the B channel. At the same time, the G channel also has some changes. Considering the linear correlation coefficient, the B channel calculation model, which has a greater impact on the color, is considered. The joint effect of the RGB channels is also considered, and the A channel is selected. B , A B -A Bblank , A xtotal , |A x -A xblank | total Four models were quantified.

[0073] It should be noted that RGB and grayscale values ​​are simple and widely used color spaces. They are the most widely used color systems at present, which are the three basic colors of red (R), green (G), and blue (B) mixed in different degrees to form different colors. Quantification can also be achieved using three color space models, namely CMYK, HSV, and CIELAB.

[0074] Analysis of the characteristics of three color spaces: CMYK, HSV, and CIELAB

[0075]

[0076] Spike recovery test of three concentrations: high, medium and low:

[0077] In order to verify the accuracy and reliability of this method, 0.1g (accurate to 0.0001g) of talcum powder was weighed into a 10mL stoppered colorimetric tube, and 0.05mL, 0.2mL and 0.6mL of 400μg / mL boric acid spiked solution① were accurately added, that is, three levels of samples with addition levels of 2, 8 and 24μg were added to the talcum powder sample, and water was added to the scale. The mixture was shaken vigorously for 3min and filtered. The primary filtrate was discarded and the subsequent filtrate was taken as the test solution. The recovery rate and RSD% are shown in the table below.

[0078] Results of spike recovery tests for high, medium and low concentrations

[0079]

[0080] Because A xtotal The recovery rate at the low concentration point is better. Finally, A is selected in the APP software. xtotal The model is quantified.

[0081] This detection method is compared with the existing UV method, and the results are shown in the following table:

[0082]

[0083] Furthermore, it should be noted that the development of a colorimetric detection system based on a smartphone (a smartphone self-built APP) requires that after taking the basic picture, A is selected according to the applicability of different color models. xtotal Model of model.

[0084] When using the smartphone to build the APP, first use the smartphone to take a picture of the standard solution and extract the R, G, and B values ​​of the colorimetric area of ​​the colorimetric tube in the image, and then convert the RGB values ​​into A xtotal The relationship between the value and the concentration is established, and the steps are as follows:

[0085] The first step is to obtain the average RGB value of the shooting area. After taking the basic picture, take the center point of the shooting area as the origin, and take the vertical and horizontal coordinates of ±5 to obtain a rectangle with a total of 100 pixels. Take the average RGB value to get AverR, AverG, and AverB.

[0086] The second step is to convert the corrected RGB value into absorbance value. The third step is to establish a suitable color algorithm model for each calculation parameter value based on the experimental model determined in the previous experiment. According to the previous steps, A Xtotal , A R , A G , A B Parameters such as I R , I G , I B are the R, G, and B values ​​of the colorimetric tube’s color development area, and A R =-lg(I R / 255), A G =-lg(I G / 255), A B =-lg(I B / 255), A Xtotal =A R +A G +A B ; A xtotal The relationship between the value and the concentration is established to establish the linear regression model parameters. The fourth step is to calculate the sample concentration value. After taking the sample picture, the sample concentration value is calculated according to the existing linear regression parameters.

[0087] The fifth step is to build a colorimetric detection system app interface based on a smartphone. The colorimetric detection system app interface is shown in the figure below: Figure 3 shown.

[0088] When the software is running, first click the "Take Basic Picture" button to start the camera function of the mobile phone. After taking the picture, click the "Get Corrected RGB Value" button to get the absorbance value of the current picture. After entering the concentration data in the "Please Enter Concentration Value" input box, click the "Generate Linear Regression Data" button, and then click the "Calculate Linear Regression Value" button to generate the intercept and slope parameters of the linear regression. Finally, click the "Take Sample Picture" button, get the absorbance value of the sample picture, then enter the sample weight, click the "Get Sample Content Value" button, and calculate the sample content.

[0089] In summary, this method develops natural biodegradable film, embeds liquid reagents and hazardous reagents in natural biological film to make green colorimetric sensors (sensor A and sensor B), simplifies the pretreatment steps of boric acid and borate, and integrates the concept of innovation, coordination, green, openness and sharing into the field of inspection and testing. It has the advantages of rapid response, simple analysis process, low cost of detection device, and real-time on-site detection.

[0090] This method applies smartphones to the field of cosmetics testing, replacing traditional spectrophotometers. It is faster and more convenient, and can help supervisors without professional testing backgrounds to screen samples. Regulatory authorities can quickly identify suspicious samples, which will greatly reduce the burden of testing and make testing more efficient. At the same time, the portable testing method can benefit the general public and is easy to promote.

[0091] This method builds a picture acquisition device with a constant light source, establishes a colorimetric detection classification algorithm based on an artificial neural network, and uses the neural network to fit the functional relationship between the chromaticity value and the concentration value of the sample to be tested at discrete data points, thereby quickly and accurately determining the content of the sample to be tested.

[0092] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for detecting boric acid and borate based on a smartphone. It is characterized in that The steps include: S1, preparing a nail film mixture for boric acid and borate detection; S2, preparing a membrane mixture for boric acid and borate detection; S3, transferring the obtained membrane A mixture and membrane B mixture into centrifuge tubes for drying and cooling to room temperature, the membrane A mixture is processed to form the sensor A, and the membrane B mixture is processed to form the sensor B, and the centrifuge tubes with the sensors A and B after cooling are vacuumed or filled with nitrogen for storage; S4. Place the sample to be tested in a colorimetric tube, add water to the scale, shake vigorously, mix the sample to be tested and water thoroughly, and filter through a filter membrane to obtain a sample filtrate; S5. Prepare a series of boric acid reference solutions, and dilute the series of boric acid reference solutions with water to obtain a linear series of solutions; S6. Take 1 ml of each linear series solution, 1 ml of blank solution, and 1 ml of sample filtrate, and place them in a 2 ml self-made centrifuge tube with sensors A and B. Cover with sensor A and shake thoroughly to allow sensors B and A to fully dissolve. Then react for 60 minutes at room temperature and use a smart phone to determine the boric acid and borate content.

2. The method for detecting boric acid and borates based on a smart phone according to claim 1, It is characterized in that In S1, the method for preparing the nail membrane mixture comprises the following steps: Weigh 0.5g of starch and disperse it in 10ml of water. Heat it in a 100℃ water bath with continuous stirring until a clear viscous solution is obtained. After cooling to room temperature, add 0.4g of azomethine and 2g of vitamin C to 10mL of starch solution and stir well to obtain a nail membrane mixture.

3. The method for detecting boric acid and borates based on a smart phone according to claim 2, It is characterized in that In S2, the method for preparing the membrane mixture comprises the following steps: Weigh 0.5 g of starch and disperse it in 10 ml of water. Heat it in a 100°C water bath with continuous stirring until a clear viscous solution is obtained. After cooling to room temperature, add 5 g of ammonium acetate and 0.45 g of disodium ethylenediaminetetraacetate to 10 mL of the starch solution and stir well to obtain an ethylene film mixture.

4. The method for detecting boric acid and borates based on a smart phone according to claim 3, It is characterized in that The starch is one or more of corn starch, pea starch, wheat starch, sweet potato starch, konjac, dextrin, potato starch and tapioca starch.

5. A method for detecting boric acid and borate based on a smart phone according to claim 3 It is characterized in that In the S6, the specific steps of the mobile phone determination are as follows: S61: Use a smartphone to build an APP to take a photo of the linear series solution in S6 in a self-built detection device to obtain the R, G, and B values. The software automatically calculates A xtotal Value, calculation formula A Xtotal =A R +A G +A B The concentration of the linear series solution is used as the horizontal axis, A xtotal The value is the ordinate, and the software automatically calculates the correlation coefficient, intercept, and slope; S62: Use a smartphone to build an APP to take a photo of the sample solution in S6 in the self-built detection device to obtain the R, G, and B values. The software automatically obtains the corresponding concentration value. After entering the sample weight, the software automatically obtains the content.

6. The method for detecting boric acid and borates based on a smart phone according to claim 5, It is characterized in that The R, G, and B values ​​were converted according to the following seven formulas and a model was established with the concentration of boric acid: I total =I R +I G +I B ; |I X -I Xblank | total =|I R -I Rblank |+|I G -I Gblank |+|I B -I Bblank |; A X =-log((I X +I X，b ) / (I X，W -I X，W )); A Xtotal =A R +A G +A B ; |A X -A Xblank | total =|A R -A Rblank |+|A G -A Gblank |+|A B -A Bblank |; Gray=0.3R+0.59G+0.11B; A Gray =-log(Gray / Gray blank ); Among them, I R ,I G ,I B Respectively represent the color intensity values ​​of the three channels of the sample solution RGB; I Rblank ,I Gblank ,I Bblank Respectively represent the color intensity values ​​of the background blank of the three channels of the sample solution RGB; X represents R, G, B, then I X Represents the color intensity value of the R, G, and B channels of the sample solution; X blank Can represent R blank , G blank , B blank , then I Xblank Represents the color intensity value of the sample solution R, G, B background blank; A X Represents the absorbance value of the R, G, and B channels of the sample solution, A Xblank Represents the background blank absorbance value of the sample solution R, G, and B channels, I X , b=0,I X , W = 255; Gray represents the conversion of the R, G, and B channels of the sample solution into grayscale values; A Gray Represents the absorbance value of the sample solution R, G, and B channels after conversion to grayscale values; At the same time, the three color spaces of CMYK, HSV, and CIELAB can be used for conversion, and a model can be established with the concentration of boric acid.

7. The method for detecting boric acid and borates based on a smart phone according to claim 1, It is characterized in that The concentrations of the linear series solutions are 0, 0.4, 1, 2, 4, 8, 16, 24, 32, and 40 μg / ml, respectively.

8. A method for detecting boric acid and borates based on a smart phone according to claim 2 or 3, It is characterized in that The starch solution content ranges from 2.5% to 10%.

9. The method for detecting boric acid and borates based on a smart phone according to claim 3, It is characterized in that After the ammonium acetate and disodium ethylenediaminetetraacetate are added to the starch solution, the Ph value is 5.5-7.

10. The method for detecting boric acid and borates based on a smart phone according to claim 2, It is characterized in that After methyleneamine and vitamin C are added to the starch solution, the content of vitamin C ranges from 2 to 10%.

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