A method for detecting quality of raw material for soybean protein production

Abstract

The present application relates to the technical field of soybean protein quality detection, and particularly relates to a soybean protein production raw material quality detection method, comprising the following steps: S1, preparing a to-be-detected solution: adding a phosphate buffer solution to a crushed and homogenized soybean meal sample, performing vortex oscillation, and then performing centrifugal separation, and taking supernatant as the to-be-detected solution; S2, color reaction: vertically immersing a test strip into the to-be-detected solution, controlling the depth of a sample pad of the test strip immersed into the to-be-detected solution to be 2-4 mm, and the liquid level of the to-be-detected solution not to exceed the upper edge of the sample pad, and standing for reaction for 90±5 s; S3, image acquisition: taking out the test strip, and acquiring an RGB digital image of a central region of a color developing zone; and S4, quantitative calculation. The present application realizes rapid, accurate and reproducible detection of the residual amount of sulfur dioxide in soybean meal, has a low detection limit, a wide linear range and strong anti-interference, significantly improves the detection efficiency and accuracy, and is suitable for on-site rapid detection.

Description

Technical Field

[0001] This invention relates to the field of soybean protein quality detection technology, specifically to a method for detecting the quality of soybean protein production raw materials. Background Technology

[0002] Current technologies for detecting sulfur dioxide residues in soybean meal, a raw material for soybean protein production, still face several insurmountable technical bottlenecks, hindering their reliable application in actual production scenarios. These bottlenecks are mainly manifested in the following aspects: 1. The test strip method has poor compatibility with soybean meal matrix, and does not take into account the interference of high protein, fat, phytic acid and other substances in soybean meal. It is prone to false positives, signal quenching, large quantitative deviation, and significantly insufficient sensitivity and repeatability in the low concentration range.

[0003] 2. The colorimetric reaction kinetics are not well controlled, the response is delayed and uncontrollable, the reaction equilibrium time is long, which cannot meet the timeliness requirements of rapid on-site testing, and the batch reproducibility is poor due to the buffering capacity of the sample extract.

[0004] 3. Image quantification lacks standardization, and no equipment color calibration and operation specifications have been established. The detection data of different models and operators have high dispersion, making it difficult to achieve stable quantification.

[0005] 4. The test strip has an unstable structure, uneven color development, poor carrier performance, and lacks film-forming enhancement components, which can easily lead to problems such as swelling and peeling of the color development layer, affecting the accuracy of the test.

[0006] The aforementioned deficiencies mean that existing methods cannot simultaneously address detection sensitivity, anti-interference capabilities, operational consistency, and field applicability, making it difficult to support raw material quality access control for soybean protein production enterprises. Summary of the Invention

[0007] The purpose of this invention is to provide a method for detecting the quality of raw materials for soybean protein production, so as to quickly and accurately detect the residual amount of sulfur dioxide in soybean meal, thereby supporting the raw material quality access control of soybean protein production enterprises.

[0008] To achieve the above-mentioned objectives, the present invention proposes the following technical solution: A method for quality testing of soybean protein production raw materials, used to detect sulfur dioxide residue in soybean meal, includes the following steps: S1. Preparation of test solution: Add phosphate buffer to the pulverized and homogenized soybean meal sample, vortex and centrifuge, and take the supernatant as the test solution. S2, Colorimetric reaction: Immerse the test strip vertically into the test solution, control the depth of the sample pad of the test strip into the test solution to be 2~4mm, and the liquid level of the test solution shall not exceed the upper edge of the sample pad, and let it stand for 90±5s. S3. Image Acquisition: Take out the test strip and acquire the RGB digital image of the central area of ​​the color development zone; S4. Quantitative calculation: Calculate the blue index BI of the RGB digital image, BI=B / (R+G+B), and substitute it into the calibration equation y=0.042x+0.018 to obtain the sulfur dioxide residue x, where the unit of x is mg / kg, y is the BI value, and the correlation coefficient of the calibration equation R²≥0.999. The detection limit for sulfur dioxide residue in soybean meal using the above method is 0.5 mg / kg.

[0009] Preferably, in step S1, the ratio of the pulverized and homogenized soybean meal sample to the phosphate buffer is 1g:10mL, and the phosphate buffer is a sodium dihydrogen phosphate-disodium hydrogen phosphate buffer with a concentration of 0.02mol / L and a pH of 7.0.

[0010] Preferably, in step S1, the vortex oscillation time is 2 minutes.

[0011] Preferably, in step S2, the test strip is prepared by impregnating filter paper substrate with a mixed solution containing potassium iodide, soluble starch hydrolyzed by α-amylase, polyvinyl alcohol and citrate buffer, and then drying it. The components of the test strip, per 100 mL of impregnation solution, are: 2.0 g potassium iodide, 3.0 g soluble starch hydrolyzed by α-amylase to an average degree of polymerization (DP) of 12-18, 5.0 g polyvinyl alcohol, and 30 mL citrate buffer. The citrate buffer is a citrate-sodium citrate buffer with a concentration of 0.1 mol / L and a pH of 3.2, the potassium iodide concentration is 0.12 mol / L, and the polyvinyl alcohol concentration is 5% w / v.

[0012] Preferably, the α-amylase hydrolysis conditions are: temperature 60℃, pH 6.0, hydrolysis time 15 min, and enzyme addition amount is 0.8% of starch mass.

[0013] Preferably, the filter paper substrate is Whatman No. 1 qualitative filter paper, the drying temperature is 60°C, and the drying time is 10 min.

[0014] Preferably, in step S4, the calibration equation y=0.042x+0.018 is established using at least 15 batches of independently prepared test strips within the sulfur dioxide concentration range of 0.5-50 mg / kg, and the repeatability RSD within each batch is ≤3.5%.

[0015] Preferably, the test strip has a response time t90 ≤ 45s to 0.5 mg / kg sulfur dioxide and an inter-batch coefficient of variation CV ≤ 3.2%.

[0016] Preferably, in step S3, the RGB image acquisition uses a smartphone camera calibrated with a NIST traceable standard color chart, and the acquisition resolution is not less than 1280×720 pixels.

[0017] Preferably, the suitability of the soybean meal for soybean protein extraction is determined based on the results of sulfur dioxide residue testing; when the sulfur dioxide residue is >10mg / kg, it is determined to be an unqualified raw material and is prohibited from being put into production.

[0018] Compared with the prior art, the present invention has the following technical effects: This method, through a unique detection process and specially designed test strips, overcomes the limitations of existing test strip methods in detecting sulfur dioxide in soybean meal. It achieves rapid, accurate, and reproducible detection of sulfur dioxide residues in soybean meal, featuring low detection limits, wide linear range, and strong anti-interference capabilities. It significantly improves detection efficiency and accuracy, is suitable for rapid on-site testing, and provides strong technical support for the quality control of raw materials for soybean protein production. Attached Figure Description

[0019] Figure 1 This is a process flow diagram of the present invention in Example 1. Detailed Implementation

[0020] To make the technical solution of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0021] Example 1 Its preparation process is as follows Figure 1 As shown, a 1.0 g soybean meal sample was placed in a centrifuge tube, and 10 mL of 0.02 mol / L phosphate buffer (pH 7.0) was added. The sample was vortexed at 2500 rpm for 2 min to ensure complete dissolution and stability of the free sulfite. Subsequently, the sample was centrifuged at 4000 rpm for 10 min, and the supernatant was used as the test solution. This extraction condition effectively releases bound sulfite while inhibiting excessive protein dissolution and fat emulsification, reducing turbidity interference. Specifically, the phosphate buffer was a sodium dihydrogen phosphate-disodium hydrogen phosphate buffer.

[0022] Next, a test strip was prepared by uniformly coating a filter paper substrate with an impregnation solution and then drying it. The impregnation solution contained potassium iodide, soluble starch hydrolyzed by α-amylase, polyvinyl alcohol (PVA), and citrate buffer. The components per 100 mL of impregnation solution were: 2.0 g potassium iodide, 3.0 g soluble starch hydrolyzed by α-amylase to an average degree of polymerization (DP) of 12-18, 5.0 g polyvinyl alcohol, and 30 mL citrate buffer. The citrate buffer was a citrate-sodium citrate buffer with a concentration of 0.1 mol / L and a pH of 3.2. The potassium iodide concentration was 0.12 mol / L, and the polyvinyl alcohol concentration was 5% w / v. The α-amylase hydrolysis conditions were: temperature 60℃, pH 6.0, hydrolysis time 15 min, and the enzyme addition amount was 0.8% of the starch mass. The filter paper substrate was Whatman No. 1 qualitative filter paper, and the drying temperature was 60℃ for 10 min.

[0023] Among them, short-chain starch with a DP of 12-18 more readily forms a stable blue-violet complex with iodine and responds rapidly to the release of small-molecule SO2; polyvinyl alcohol acts as a film-forming enhancer, improving the mechanical strength and wetting uniformity of the reaction layer; and citrate buffer rapidly releases H+ after the test paper comes into contact with the test solution. + This creates a localized acidic environment (pH≈3.2) within the microporous structure of the test paper, promoting the conversion of sulfite into SO2 gas, which then immediately reacts with I3. - Redox reaction occurs: SO3 2- +2H + →SO2↑+H2O SO2 + I2 + 2H2O → H2SO4 + 2HI This triggers the iodine-starch colorimetric reaction.

[0024] Immerse the test strip vertically into the test solution, ensuring the sample pad is submerged to a depth of 3 mm. Allow it to stand for 90 ± 5 seconds to allow the acidification, diffusion, reaction, and color development processes to complete. Immediately after the reaction, remove the test strip and gently tap it to remove excess liquid, preventing lateral diffusion that could blur the color development area.

[0025] Subsequently, an RGB image of the central area of ​​the color development zone on the test strip was captured using a smartphone camera (with a resolution of no less than 1280×720 pixels) calibrated with a NIST traceable standard color chart under a D65 standard illuminant and an illuminance of 800-1200 lux, to ensure that the color data is consistent across devices.

[0026] Finally, the blue index BI=B / (R+G+B) of the RGB digital image is calculated, and the BI value is substituted into the pre-calibrated linear calibration equation y=0.042x+0.018 (where y is the BI value and x is the SO2 concentration in mg / kg) to inversely determine the residual amount of sulfur dioxide in the sample to be tested.

[0027] Experimental verification showed that the method achieved a detection limit of 0.5 mg / kg for sulfur dioxide residue in soybean meal, with a linear range of 0.5-50 mg / kg (R²>0.99), an inter-batch coefficient of variation (CV) ≤3.2% (n=5 batches, 30 results per batch), and a relative standard deviation (RSD) ≤3.5% for repeated determinations. In actual soybean meal samples with protein content as high as 50%, fat content as high as 20%, and the presence of phytic acid, the spiked recovery rate remained at 96.2%-102.4%, demonstrating excellent anti-interference performance and detection stability.

[0028] Example 2 This embodiment focuses on the technical specifications and color correction strategies for the RGB image acquisition process. A smartphone is fixed inside a light-shielding box, with the lens facing the test strip placement area. The background is a neutral gray card, and the light source is an LED panel simulating D65 daylight, with the illuminance adjusted to 1000 lux ± 10% using a digital illuminance meter. Before each test, the phone's camera is calibrated using a NIST traceable standard color chart (containing 24 color patches). The ColorGrab app (version 5.0 or later) is used to automatically identify reference color values ​​and establish a device-side color response correction matrix. During acquisition, only a 300×300 pixel area at the center of the test strip's color display area is analyzed to eliminate the influence of edge unevenness. After white balance adjustment, the R, G, and B channel grayscale values ​​are extracted from the acquired image, and the blueness index BI = B / (R+G+B) is calculated. This parameter design has inherent normalization characteristics, effectively offsetting overall absorbance changes caused by fluctuations in light intensity and sample turbidity. For example, when the test liquid is slightly turbid, resulting in a decrease in overall transmitted light, R, G, and B decrease simultaneously, but the ratio BI remains stable. Experimental comparisons show that the BI difference between uncalibrated devices can reach ±8%, while after correction by this scheme, it is reduced to within ±1.2%, greatly improving the data comparability of multi-terminal collaborative detection.

[0029] Example 3 This embodiment details the construction process and accuracy verification of the quantitative calculation. The calibration equation y = 0.042x + 0.018 was obtained through calibration with a series of standard solutions. Specifically, a standard SO2 stock solution (1000 mg / L) was prepared and serially diluted to simulated soybean meal extracts of 0.5, 2, 5, 10, 20, and 50 mg / kg. These were processed and tested according to the method in Example 1, with each concentration repeated six times, and the average BI value was recorded. A linear regression was performed with BI as the ordinate (y) and SO2 concentration as the abscissa (x), yielding the above equation (R² = 0.9987). This algorithm is more robust than traditional single-channel methods (such as using only the B value) or the difference method (BRG). Further testing showed that even when the red-green channel increased due to the yellowish ambient light, the BI still accurately reflected the true blueness change. When the calculated SO2 concentration is >10mg / kg, the sample is marked as "unqualified" and the sample number, testing time, operator and other information are recorded. This can realize closed-loop management from testing to production access, effectively supporting the construction of a quality and safety control system for soybean protein products.

[0030] Example 4 The technical features in different embodiments can be combined and used together without conflict. For example, the test strip formulation in Embodiment 1 can be applied to the image acquisition system of Embodiment 3, and combined with the quantitative calculation process of Embodiment 4, to form a complete on-site rapid testing solution. Alternatively, the pretreatment conditions of Embodiment 1 and the threshold determination logic of Embodiment 4 can be integrated into a portable detector to develop an intelligent raw material access control system. All combinations can achieve efficient, accurate, and reproducible detection of sulfur dioxide residues in soybean meal, meeting the quality control requirements in industrial production scenarios.

[0031] The embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for detecting the quality of raw materials used in soybean protein production, for detecting the residual amount of sulfur dioxide in soybean meal, characterized in that, Includes the following steps: S1. Preparation of test solution: Add phosphate buffer to the pulverized and homogenized soybean meal sample, vortex and centrifuge, and take the supernatant as the test solution. S2, Colorimetric reaction: Immerse the test strip vertically into the test solution, control the depth of the sample pad of the test strip into the test solution to be 2~4mm, and the liquid level of the test solution shall not exceed the upper edge of the sample pad, and let it stand for 90±5s. S3. Image Acquisition: Take out the test strip and acquire the RGB digital image of the central area of ​​the color development zone; S4. Quantitative calculation: Calculate the blue index BI of the RGB digital image, BI=B / (R+G+B), and substitute it into the calibration equation y=0.042x+0.018 to obtain the sulfur dioxide residue x, where the unit of x is mg / kg, y is the BI value, and the correlation coefficient of the calibration equation R²≥0.

999. The detection limit for sulfur dioxide residue in soybean meal using the above method is 0.5 mg / kg.

2. The method according to claim 1, characterized in that, In step S1, the ratio of the pulverized and homogenized soybean meal sample to the phosphate buffer is 1g:10mL. The phosphate buffer is a sodium dihydrogen phosphate-disodium hydrogen phosphate buffer with a concentration of 0.02mol / L and a pH of 7.

0.

3. The method according to claim 1, characterized in that, In step S1, the vortex oscillation time is 2 minutes.

4. The method according to claim 1, characterized in that, In step S2, the test strip is prepared by impregnating filter paper substrate with a mixed solution containing potassium iodide, soluble starch hydrolyzed by α-amylase, polyvinyl alcohol and citrate buffer, and then drying it. The components of the test strip, per 100 mL of impregnation solution, are: 2.0 g potassium iodide, 3.0 g soluble starch hydrolyzed by α-amylase to an average degree of polymerization (DP) of 12-18, 5.0 g polyvinyl alcohol, and 30 mL citrate buffer. The citrate buffer is a citrate-sodium citrate buffer with a concentration of 0.1 mol / L and a pH of 3.2, the potassium iodide concentration is 0.12 mol / L, and the polyvinyl alcohol concentration is 5% w / v.

5. The method according to claim 4, characterized in that, The α-amylase hydrolysis conditions are: temperature 60℃, pH 6.0, hydrolysis time 15 min, and enzyme addition amount is 0.8% of starch mass.

6. The method according to claim 4, characterized in that, The filter paper substrate is Whatman No. 1 qualitative filter paper, and the drying temperature is 60℃, and the drying time is 10min.

7. The method according to claim 1, characterized in that, In step S4, the calibration equation y=0.042x+0.018 is established using at least 15 batches of independently prepared test strips within the sulfur dioxide concentration range of 0.5-50 mg / kg, and the repeatability RSD within each batch is ≤3.5%.

8. The method according to claim 7, characterized in that, The response time t of the test strip to 0.5 mg / kg sulfur dioxide is... 90 ≤45s, inter-batch coefficient of variation (CV) ≤3.2%.

9. The method according to claim 1, characterized in that, In step S3, the RGB image acquisition uses a smartphone camera calibrated with a NIST traceable standard color chart, with an acquisition resolution of no less than 1280×720 pixels.

10. The method according to claim 1, characterized in that, The suitability of soybean meal for soybean protein extraction is determined based on the results of sulfur dioxide residue testing. When the sulfur dioxide residue is >10mg / kg, it is deemed an unqualified raw material and is prohibited from being used in production.

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