A method for detecting protein in water body based on smart phone

Abstract

This invention discloses a method for detecting proteins in water using a smartphone, belonging to the field of protein detection technology. The portable detection device based on a smartphone uses a beam splitter to split a laser emitted from a laser pointer into two beams. Then, using the test solution and a reference solution as comparisons, the smartphone is used to capture and identify the RGB values, thereby obtaining the A ratio of the test solution and the reference solution. A linear relationship between different protein concentrations and the A value is established, achieving highly sensitive protein detection. Compared to traditional detection methods, this method offers higher sensitivity and enables on-site detection of water samples.

Description

Technical Field

[0001] This invention relates to the field of protein detection technology in water bodies, and in particular to a method for detecting proteins in water bodies based on a smartphone. Background Technology

[0002] There are many methods for determining protein content, commonly used techniques include the Kjeldahl method, colorimetric methods (such as the biuret method, Lowry method, and Bradford method), and ultraviolet absorption methods. Each method has its advantages and limitations, and the choice of appropriate method depends on the specific needs of the experiment, the required sensitivity, and the characteristics of the sample. The Kjeldahl method is a classic method for determining protein content, indirectly estimating the protein content by measuring the nitrogen content in the sample. This method has high accuracy and good reproducibility, but it is complex to operate and time-consuming.

[0003] Colorimetric methods determine protein content based on color changes produced by the reaction of proteins with specific reagents. Several main methods include: The biuret method utilizes the reaction of peptide bonds in proteins with biuret reagent to form a purple complex with a maximum absorption peak at 540 nm. This method is simple and rapid, but has low sensitivity for low protein concentrations. The Lowry method combines the biuret reaction and the redox reaction of Folin-Ciocalteu reagent, offering higher sensitivity and suitability for detecting trace amounts of protein. However, this method is sensitive to many interfering substances (such as reducing agents and sugars). Ultraviolet absorption methods utilize the natural absorption peak of proteins at 280 nm due to the absorption of aromatic amino acid residues (such as tryptophan and tyrosine). This method is rapid and non-destructive, but requires relatively pure samples and is susceptible to interference from other absorbing substances.

[0004] The Bradford method utilizes the color change of Coomassie Brilliant Blue G-250 dye upon binding to proteins to determine protein content. Coomassie Brilliant Blue dye changes from brownish-red to blue upon binding to protein, and the protein content is calculated by measuring the change in absorbance at 595 nm. The specific steps are as follows: Preparation of a standard curve: Prepare a series of standard solutions using standard proteins of known concentrations (such as bovine serum albumin, BSA). Addition of dye: Add Coomassie Brilliant Blue dye to the standard solutions and the sample solution, mix well, and let stand for a few minutes. Absorbance measurement: Measure the absorbance of each standard solution and sample solution at 595 nm. Protein concentration calculation: Calculate the protein concentration of the sample based on the standard curve. This method is widely used in biochemistry laboratories due to its simplicity, speed, and high sensitivity.

[0005] Although there are many methods for detecting absorbance and they are accurate, most sensors or the precision instruments involved can only be used in relatively harsh laboratory environments, and there is a lack of methods for rapid on-site detection. Summary of the Invention

[0006] To address the technical challenge of on-site protein content detection in existing technologies, this invention provides a smartphone-based method for detecting proteins in water. This invention uses the test liquid and a reference solution as a comparison, and utilizes a smartphone to capture and identify RGB values, thereby obtaining the negative logarithmic value of the G ratio between the test liquid and the reference solution, establishing a linear relationship, and achieving rapid and accurate detection of proteins in water.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0008] On one hand, the present invention provides a portable detection device based on a smartphone, including a laser pointer, a light source reflector, a beam splitter, a reflector, a cuvette, a lid, a laser pointer holder, and a detection box;

[0009] The detection box is provided with an L-shaped partition to divide the detection box into a light mirror area and a sample area; the partition is provided with light-transmitting holes, including a first light-transmitting hole and a second light-transmitting hole.

[0010] The optical mirror area is used to place the light source reflector, beam splitter, and reflector. The laser emitted by the laser pointer illuminates the light source reflector, and the light is reflected by the light source reflector to the beam splitter. The sample area is used to place cuvettes, which include a first cuvette and a second cuvette.

[0011] In the optical mirror area, an entrance hole is provided on the side wall of the detection box. The laser pen fixing tube is used to fix the laser pen on the side wall of the detection box. The laser emitted by the laser pen shines on the light source reflector through the entrance hole, and then reflects on the beam splitter. The beam splitter splits the laser into two beams of equal power and parallel to each other. One beam shines on the first cuvette through the first light-transmitting hole, and the other beam shines on the reflector and, after being reflected by the reflector, shines on the second cuvette through the second light-transmitting hole.

[0012] The lid is located on the top of the detection box, making the detection box a dark chamber; a mobile phone camera shooting hole is opened on the side wall of the detection box corresponding to the middle position of the first cuvette and the second cuvette; a smartphone fixing slot is also provided on the side wall of the detection box where the mobile phone camera shooting hole is located, and the smartphone is placed in the smartphone fixing slot, and the camera is aimed at the mobile phone camera shooting hole to take pictures of the sample area.

[0013] Preferably, a support frame is provided below the laser pointer fixing tube to support the laser pointer fixing tube;

[0014] The bottom of the detection box is provided with two sample slots, namely a first sample slot and a second sample slot. The first sample slot is used to fix the first cuvette, and the second sample slot is used to fix the second cuvette.

[0015] The bottom of the detection box is fixed with three positioning posts, namely the first positioning post, the second positioning post, and the third positioning post, and the top of the positioning posts is threaded. The beam splitter is fixed by a beam splitter optical adjustment frame, the reflector is fixed by a reflector optical adjustment frame, and the light source reflector is fixed by a light source reflector frame. The bottom of the beam splitter optical adjustment frame, the reflector optical adjustment frame, and the light source reflector frame are all provided with internal threads, which cooperate with the threads on the top of the positioning posts to fix the beam splitter optical adjustment frame, the reflector optical adjustment frame, and the light source reflector frame onto the first positioning post, the second positioning post, and the third positioning post, respectively.

[0016] On the other hand, the present invention also provides a method for detecting proteins in water based on a smartphone, including step 1: preparing a protein standard solution;

[0017] Step 2: Mix the protein standard solution with the dye and react at room temperature until the color is stable;

[0018] Step 3: Add the stained protein solution from Step 2 as the sample solution to the portable detection device described above, using distilled water as a reference, turn on the laser pointer of the portable detection device, and then take relevant photos using a smartphone.

[0019] Step 4: Extract the effective area from the photograph and obtain the R, G, and B values ​​for the corresponding areas of the sample solution and the reference solution, and then calculate the A value according to formula (I);

[0020] A = -log(G) 样品 / G 参比) (I);

[0021] Step 5: Take photos of the mixture containing protein standard solutions and dye solutions of different concentrations in sequence, extract the effective regions of each and identify the corresponding R, G, and B values, calculate the A value in each image, and establish a standard working curve with protein concentration as the x-axis and A as the y-axis.

[0022] Step 6: After pretreatment of the water sample to be tested, the corresponding A is determined by analogy with steps 2-4 above, and the protein concentration of the water sample to be tested is calculated by combining the standard working curve.

[0023] Preferably, in step 1, the protein is bovine serum albumin (BSA); step 1 specifically involves preparing protein standard solutions with concentrations of 128 ug / L, 144 ug / L, 160 ug / L, 176 ug / L, 192 ug / L, 208 ug / L, 224 ug / L, and 240 ug / L.

[0024] Furthermore, step 2 specifically involves: mixing 2 mL of protein standard solution with 2 mL of 100 mg / L Coomassie brilliant blue dye, and reacting at room temperature for 5-30 minutes to stabilize the color.

[0025] Furthermore, step 3 specifically involves adding 3 mL of stained protein solution to a 5 mL centrifuge tube, placing it in a portable detection device, using distilled water as a reference, turning on the device's laser pointer, and then taking a picture. Each group is repeated 3 times.

[0026] Furthermore, the laser emitted by the laser pen has a wavelength of 500-550nm.

[0027] Furthermore, in step 4, the image is processed using Matlab software; the effective area is the region of the light column formed by the laser beam passing through the solution in the cuvette.

[0028] Furthermore, in step 6, the water sample to be tested is collected, filtered through a 0.45μm pore size filter membrane syringe, and then the pH of the solution to be tested is adjusted to neutral using hydrochloric acid or sodium hydroxide solution before testing.

[0029] The present invention uses a detection box as the outer shell of the device, which on the one hand fixes the position of each component, and on the other hand creates a dark environment for detection to avoid interference from the external environment.

[0030] This invention uses a commercially available laser pointer as a light source. For example, a commercially available laser pointer can emit a beam with a wavelength of 532nm. After passing through three optical lenses—a light source reflector, a beam splitter, and a mirror—it is split into two parallel beams, both perpendicular to the laser pointer, that illuminate the optical lenses. These beams then pass through a light-transmitting hole and illuminate the corresponding cuvette. A camera hole for a mobile phone is provided on the side wall of the detection box, and a smartphone mounting slot is fixed to the outer wall for taking pictures of the sample area. The device has simple internal components, requires no complicated operation, and can be used on-site after simple assembly.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] This invention discloses a portable device based on a smartphone for detecting proteins in water. Using this portable device as a detection apparatus, a standard linear curve for proteins is constructed. The smartphone is used to capture and recognize RGB values, thereby obtaining the linear relationship between different protein concentrations and alpha (A). By testing water samples using this portable device, the protein concentration of the water sample can be determined quickly and accurately. This invention reduces the requirements for actual water sample testing conditions, using actual water samples as the basis for analysis, thus achieving convenient and rapid protein determination in real-world water samples. Attached Figure Description

[0033] Figure 1 This is a perspective view of the portable detection device based on a smartphone according to Embodiment 1 of the present invention;

[0034] Figure 2 The internal structure of the detection box in Embodiment 1 of the present invention Figure 1 ;

[0035] Figure 3 The internal structure of the detection box in Embodiment 1 of the present invention Figure 2 ;

[0036] Figure 4 The internal structure of the detection box in Embodiment 1 of the present invention Figure 3 ;

[0037] Figure 5 The internal structure of the detection box in Embodiment 1 of the present invention Figure 4 ;

[0038] The components include: 1. Beam splitter; 2. Reflector; 3. Cuvette; 3-1 First cuvette; 3-2 Second cuvette; 4. Lid; 5. Light source reflector; 6. Light source reflector holder; 7. Smartphone mounting slot; 8. Smartphone camera shooting hole; 9. Laser pointer mounting tube; 10. Detection box; 11. Divider; 12. Light transmission hole; 12-1 First light transmission hole; 12-2 Second light transmission hole; 13. Entrance hole; 14. Laser pointer; 15. Support frame; 16. Positioning post; 16-1 First positioning post; 16-2 Second positioning post; 17. Sample slot; 17-1 First sample slot; 17-2 Second sample slot; 18. Beam splitter optical adjustment frame; 19. Reflector optical adjustment frame.

[0039] Figure 6 This is a sample area image taken in step 3 of embodiment 2 of the present invention, with the reference on the right and the sample on the left;

[0040] Figure 7 This is a standard working curve of protein concentration versus A value for Example 2;

[0041] Figure 8 This is a map showing the effective area division.

[0042] Figure 9 This is a distribution map of A values ​​in the surrounding area under different protein concentrations;

[0043] Figure 10 For Example 2, protein concentration and A2 = -log(B) 样品 / B 参比 Standard working curve of the value;

[0044] Figure 11 A comparative graph showing the results of determining the protein content of water samples using a standard spectrophotometer and SPSD. Detailed Implementation

[0045] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0046] Unless otherwise specified, all materials and reagents used in this invention are commercially available. The optical lenses used in the portable testing device based on a smartphone in this invention are shown in Table 1 below.

[0047] Table 1

[0048]

[0049] This invention provides a method for detecting proteins in water based on a smartphone, and specific embodiments are as follows.

[0050] Example 1

[0051] A portable detection device (SPSD) based on a smartphone, such as Figure 1-5 It includes a laser pointer 14, a beam splitter 1, a reflector 2, a cuvette 3, a lid 4, a light source reflector 5, a smartphone mounting slot 7, a smartphone camera shooting hole 8, a laser pointer mounting tube 9, and a detection box 10.

[0052] The detection box 10 is provided with an L-shaped partition 11 to divide the detection box 10 into a light mirror area and a sample area; the partition 11 is provided with a light-transmitting hole 12, which includes a first light-transmitting hole 12-1 and a second light-transmitting hole 12-2.

[0053] The optical mirror area is used to place the light source reflector 5, the beam splitter 1 and the reflector 2. The laser emitted by the laser pointer 14 illuminates the light source reflector 5 and is reflected by the light source reflector 5 onto the beam splitter 1. The sample area is used to place the cuvette 3, which includes a first cuvette 3-1 and a second cuvette 3-2.

[0054] In the optical mirror area, an entrance hole 13 is provided on the side wall of the detection box 10. The laser pen fixing tube 9 is used to fix the laser pen 14 on the side wall of the detection box 10. The laser emitted by the laser pen 14 shines on the light source reflector 5 through the entrance hole 13, and then reflects to the beam splitter 1. The beam splitter 1 is used to split the laser into two laser beams with similar power and perpendicular to each other. One of the laser beams shines on the first cuvette 3-1 through the first light transmission hole 12-1, and the other laser beam shines on the reflector 2, and after being reflected by the reflector 2, shines on the second cuvette 3-2 through the second light transmission hole 12-2.

[0055] The lid 4 is placed on the top of the detection box 10, making the detection box a darkroom; a mobile phone camera shooting hole 8 is opened on the side wall of the detection box 10 corresponding to the middle position of the first cuvette 3-1 and the second cuvette 3-2; a smartphone fixing slot 7 is also provided on the side wall of the detection box 10 where the mobile phone camera shooting hole 8 is located, and the smartphone is placed in the smartphone fixing slot 7, and the camera is aimed at the mobile phone camera shooting hole 8 to take pictures of the sample area.

[0056] The detection box of this invention is a dark box. A laser pointer fixing tube is used to fix the light source position. Then, a light source reflector, a beam splitter, and a reflector are set up to split the laser into two beams with similar power. These two beams illuminate a first cuvette and a second cuvette, respectively, causing them to emit light synchronously. Then, a mobile phone is used to capture both beams in the same image for subsequent analysis. The internal components of this invention are simple, with no complicated operations, and are easy to assemble.

[0057] Preferably, a support frame 15 is provided below the laser pointer fixing tube 9 to support the laser pointer fixing tube 9; during use, the laser pointer 14 is inserted into the laser pointer fixing tube 9, and the laser emitted by the laser pointer 14 will shine through the entrance hole 13 onto the light source reflector 5.

[0058] Furthermore, the bottom of the detection box 10 is provided with two sample slots 17, namely the first sample slot 17-1 and the second sample slot 17-2. The first sample slot 17-1 is used to fix the first cuvette 3-1, and the second sample slot 17-2 is used to fix the second cuvette 3-2. This facilitates fixing the position of the cuvettes, and the liquid level in the cuvette 3 is higher than the position of the light-transmitting hole 12, ensuring the accuracy of the test results.

[0059] Furthermore, the bottom of the test box 10 is fixed with three positioning posts 16, namely the first positioning post 16-1, the second positioning post 16-2, and the third positioning post 16-3, and the top of the positioning posts 16 is provided with threads; the beam splitter 1 is fixed by the beam splitter optical adjustment frame 18, the reflector 2 is fixed by the reflector optical adjustment frame 19, and the light source reflector 5 is fixed by the light source reflector frame 6; the bottom of the beam splitter optical adjustment frame 18, the reflector optical adjustment frame 19, and the light source reflector frame 6 are all provided with internal threads, which cooperate with the threads on the top of the positioning posts 16 to fix the beam splitter optical adjustment frame 18, the reflector optical adjustment frame 19, and the light source reflector frame 6 onto the first positioning post 16-1, the second positioning post 16-2, and the third positioning post 16-3, respectively; this facilitates the determination of the fixed position of the optical lenses during on-site installation, and after the light source reflector, beam splitter, and reflector are installed, the focal position height of their lenses is consistent with the incident height of the laser pointer, ensuring the accuracy of the test results.

[0060] Example 2

[0061] A smartphone-based method for detecting proteins in water, comprising:

[0062] Step 1: Prepare bovine serum albumin standard solutions with concentrations of 128 ug / L, 144 ug / L, 160 ug / L, 176 ug / L, 192 ug / L, 208 ug / L, 224 ug / L, and 240 ug / L.

[0063] Step 2: Take 2.5 mL of bovine serum albumin standard solution with a concentration of 128 ug / L, then add 500 uL of Coomassie Brilliant Blue G250 solution (100 mg / L), and make up to 5 mL. Let it stand at room temperature for 5 minutes to allow the color to stabilize.

[0064] Step 3: Add 3 mL of the stained protein solution to a 5 mL centrifuge tube, place it in the portable detection device of Example 1, use distilled water as a reference, turn on the device's laser pointer, and then take a picture. Figure 6 As shown, each group is repeated 3 times; in the portable detection device of Example 1, the laser wavelength emitted by the laser pointer is 532nm;

[0065] Step 4: Extract the effective region from the captured image (the effective excitation region is the area of ​​the light column formed by the laser beam passing through the solution in the cuvette, ensuring that the reference and experimental groups have the same size), and obtain the R, G, and B values ​​for the corresponding regions of the sample solution and the reference solution respectively. Specifically, extract the effective region image, save it to the designated folder, and write the following program using Matlab software:

[0066] I = imread('file location\image name.jpg', 'jpg');

[0067] RGB_mean = mean(mean(I));

[0068] R_mean = RGB_mean(:,:,1);

[0069] G_mean = RGB_mean(:,:,2);

[0070] B_mean = RGB_mean(:,:,3);

[0071] By running the above program, the average RGB value of each effective area image is calculated, which completes the process of converting light signals into electrical signals and finally into digital signals. See Table 2 for specific data.

[0072] Then calculate the value of A according to formula (I), as shown in Table 3;

[0073] A = -log(G) 样品 / G 参比) (I);

[0074] Step 5: Following steps 2-4, take photographs of mixtures containing protein standard solutions and dye solutions of different concentrations (144ug / L, 160ug / L, 176ug / L, 192ug / L, 208ug / L, 224ug / L, 240ug / L), extract the effective regions of each image to identify the corresponding R, G, and B values, and calculate the A value for each image; the results are shown in Table 2-3.

[0075] Table 2

[0076]

[0077] Table 3

[0078]

[0079]

[0080] A standard working curve was constructed with protein concentration on the x-axis and A on the y-axis, as shown in the figure. Figure 7 ;

[0081] Step 6: Collect the water sample to be tested, filter it through a 0.45μm pore size filter membrane syringe, and then adjust the pH of the test solution to neutral using hydrochloric acid or sodium hydroxide solution. Add 500ul of Coomassie Brilliant Blue G250 solution to 2.5mL of the test solution and let it stand for 5min. Add 3mL of the reaction solution to a cuvette and place it in the sample cell of the device. Add 3mL of distilled water to the reference cell. Take a picture with a smartphone, input the picture into the computer program for analysis, extract the RGB values, and then calculate the corresponding A value as 0.19. Combined with the standard working curve, the protein concentration of the water sample to be tested is calculated to be 152ug / L.

[0082] To demonstrate the beneficial effects of the method of the present invention, the inventors also conducted the following experiments.

[0083] 1. Feasibility assessment

[0084] Add 0.5 mL of Coomassie Brilliant Blue G250 solution to 2.5 mL of bovine serum albumin standard solutions with concentrations of 128 μg / L, 144 μg / L, 160 μg / L, 176 μg / L, 192 μg / L, 208 μg / L, 224 μg / L, and 240 μg / L, respectively, and bring the volume to 5 mL. Allow the solution to stand at room temperature for 5 minutes to allow the color to stabilize. Detect the above standard solutions using a standard spectrophotometer and the equipment described in Example 1 of this invention, and establish a standard working curve based on the detection results. Figure 7 Ri of the standard working curve established by the standard spectrophotometer 2 =0.9953, the R-value of the standard working curve established by the method of this invention is 0.9953. 2 =0.9854, which is highly accurate.

[0085] 3. Selection of effective area

[0086] Since the protein determination was obtained indirectly by photographing the cuvettes of the device in Example 1 using a smartphone, the selection of the effective region was crucial. For example... Figure 8 As shown, the captured image is cropped to the entire position of the cuvette, and then divided into two regions for evaluation: the light pillar region (the region formed by the laser beam passing through the solution in the cuvette) and the surrounding region (the region below the liquid surface in the cuvette excluding the light pillar region).

[0087] Add 0.5 mL of Coomassie Brilliant Blue G250 solution to 2.5 mL of bovine serum albumin standard solutions with concentrations of 128 μg / L, 144 μg / L, 160 μg / L, 176 μg / L, 192 μg / L, 208 μg / L, 224 μg / L, and 240 μg / L, respectively, and bring the volume to 5 mL. Allow the solution to stand at room temperature for 5 minutes to allow the color to stabilize. Take 3 mL of the stained protein solution and photograph it using the equipment described in Example 1. The reference solution is 3 mL of distilled water. Calculate the correlation A value between the two regions and establish a curve showing the relationship between concentration and A value. The working curve for the light column region is shown in [Figure 1]. Figure 7 Surrounding areas such as Figure 9 The standard curve obtained from the light pillar region, as the effective area, showed a good linear relationship, but the data from the surrounding areas did not show a clear linear relationship. In conclusion, selecting the light pillar region as the effective area for subsequent measurements is reasonable.

[0088] 4. Selection of RGB channels

[0089] In Example 2, 3 mL of a mixture of bovine serum albumin solutions with concentrations of 128, 144, 160, 176, 192, 208, 224, and 240 μg / L and Coomassie Brilliant Blue G-250 solution was sequentially poured into cuvettes and placed in the left sample cell of a smartphone-based portable detection device; 3 mL of distilled water was used as a reference in the right sample cell. Each concentration was measured three times, and three photos were taken. The effective regions were cropped and the RGB average values ​​were obtained, as shown in Table 2.

[0090] As shown in Table 2, since the R value of each photo remains essentially unchanged, the obtained RGB values ​​are mapped one-to-one with the corresponding reference RGB values, and A1 = -log(G 样品 / G 参比 A2 = -log(B) 样品 / B 参比 The concentration was then compared with the A value to establish a standard working curve. The results are shown in Table 4. Figure 7 and Figure 10 .

[0091] Table 4

[0092]

[0093] Depend on Figure 10 It can be seen that there is a certain linear relationship between the G ratio and the R / B ratio of protein solutions of different concentrations, but no obvious linear relationship. Therefore, when measuring proteins in smartphone-based portable detection devices, the G channel can be used as the detection channel to establish linearity. Furthermore, the linear curve established using the G channel has the following linear equation: y = -0.0015x + 0.42, R... 2=0.9854. This indicates that establishing a linear curve for RhB through the G channel will be more sensitive and accurate.

[0094] 6. Accuracy Evaluation

[0095] Water samples were collected from rivers within the school grounds, surrounding areas, and other locations, totaling six samples. These samples were measured using a standard spectrophotometer and the equipment described in Example 1, with each sample measured three times. The results from the equipment described in Example 1 were used... Figure 7 The final result is derived from the linear fitting curve. This will be used... Figure 7 The method for converting the final turbidity from the linear fitting curve is denoted as the SPSD measurement result, as shown in Table 5.

[0096] Table 5

[0097]

[0098] As shown in Table 5, for the same water sample, the detection results using the standard spectrophotometer and the SPSD detection results of this invention are not significantly different. The ratio of the results measured by both methods for the same water sample is calculated as follows: Figure 11 As shown. By Figure 11 It can be seen that the ratio of the turbidity result of the water sample measured by the device in Example 1 to the result measured by the turbidity meter is controlled within 0.93-1.10, which is close to 1.000. This indicates that the difference between the two measurement results is small, confirming that the results of the water turbidity measurement by the smartphone-assisted portable detection device are reliable.

[0099] In summary, this invention utilizes a portable detection device to perform simple photographic processing, and the corresponding protein concentration can be obtained by calculating the A value. The device of this invention is simple, can realize on-site detection of water samples, and has high detection accuracy.

[0100] The above description is a preferred embodiment of the present invention. For those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for detecting proteins in water based on a smartphone, characterized in that, include: Step 1: Prepare protein standard solutions; Step 2: Mix 2 mL of protein standard solution with 2 mL of Coomassie brilliant blue dye and react at room temperature for 5-30 minutes to stabilize the color; Step 3: Add the stained protein solution from Step 2 as the sample solution to the portable detection device, using distilled water as a reference. Turn on the laser pointer of the portable detection device and then take relevant photos using a smartphone; the laser wavelength emitted by the laser pointer is 500-550nm. Step 4: Extract the effective area from the photograph and obtain the R, G, and B values ​​for the corresponding areas of the sample solution and the reference solution, and then calculate the A value according to formula (I); A=-log(G 样品 / G 参比 )(I); Step 5: Take photos of the mixture containing protein standard solutions and dye solutions of different concentrations in sequence, extract the effective regions of each and identify the corresponding R, G, and B values, calculate the A value in each image, and establish a standard working curve with protein concentration as the x-axis and A as the y-axis. Step 6: After pretreatment of the water sample to be tested, the corresponding A is determined by analogy with steps 3-4 above, and the protein concentration of the water sample to be tested is calculated by combining the standard working curve.

2. The detection method according to claim 1, characterized in that, In step 1, the protein is bovine serum albumin (BSA).

3. The detection method according to claim 2, characterized in that, Step 1 specifically involves preparing protein standard solutions with concentrations of 128 ug / L, 144 ug / L, 160 ug / L, 176 ug / L, 192 ug / L, 208 ug / L, 224 ug / L, and 240 ug / L.

4. The detection method according to claim 1, characterized in that, Step 3 specifically involves adding 3 mL of stained protein solution to a 5 mL cuvette, placing it in a portable detection device, using distilled water as a reference, turning on the device's laser pointer, and then taking a picture. Each group is repeated 3 times.

5. The detection method according to claim 1, characterized in that, In step 4, the image is processed using Matlab software; the effective area is the region of the light column formed by the laser beam passing through the solution in the cuvette.

6. The detection method according to claim 1, characterized in that, In step 6, the water sample to be tested is collected, filtered through a 0.45μm pore size filter membrane syringe, and then the pH of the solution to be tested is adjusted to neutral using hydrochloric acid or sodium hydroxide solution before testing.

7. The detection method according to claim 1, characterized in that, In step 3, the portable detection device includes a laser pointer, a light source reflector, a beam splitter, a reflector, a cuvette, a lid, a laser pointer holder, and a detection box. The detection box is provided with a partition for dividing the detection box into a light mirror area and a sample area; the partition is provided with light-transmitting holes, including a first light-transmitting hole and a second light-transmitting hole. The optical mirror area is used to place the light source reflector, beam splitter, and reflector. The laser emitted by the laser pointer illuminates the light source reflector, and the light is reflected by the light source reflector to the beam splitter. The sample area is used to place cuvettes, which include a first cuvette and a second cuvette. In the optical mirror area, an entrance hole is provided on the side wall of the detection box. The laser pen fixing tube is used to fix the laser pen on the side wall of the detection box. The laser emitted by the laser pen shines on the light source reflector through the entrance hole, and then reflects on the beam splitter. The beam splitter splits the laser into two beams of equal power and parallel to each other. One beam shines on the first cuvette through the first light-transmitting hole, and the other beam shines on the reflector and, after being reflected by the reflector, shines on the second cuvette through the second light-transmitting hole. The cover is positioned on top of the detection box, thus creating a dark chamber within the detection box; A camera hole for a mobile phone is provided on the side wall of the detection box corresponding to the position between the first cuvette and the second cuvette; a smartphone fixing slot is also provided on the side wall of the detection box where the camera hole is located, and the smartphone is placed in the smartphone fixing slot, and the camera is aimed at the camera hole to take pictures of the sample area.

8. The detection method according to claim 7, characterized in that, A support frame is provided below the laser pointer fixing tube to support the laser pointer fixing tube; The bottom of the detection box is provided with two sample slots, namely a first sample slot and a second sample slot. The first sample slot is used to fix the first cuvette, and the second sample slot is used to fix the second cuvette. The bottom of the detection box is fixed with three positioning posts, namely the first positioning post, the second positioning post, and the third positioning post, and the top of the positioning posts is threaded. The beam splitter is fixed by a beam splitter optical adjustment frame, the reflector is fixed by a reflector optical adjustment frame, and the light source reflector is fixed by a light source reflector frame. The bottom of the beam splitter optical adjustment frame, the reflector optical adjustment frame, and the light source reflector frame are all provided with internal threads, which cooperate with the threads on the top of the positioning posts to fix the beam splitter optical adjustment frame, the reflector optical adjustment frame, and the light source reflector frame onto the first positioning post, the second positioning post, and the third positioning post, respectively.

Images