Ascorbic acid detection method based on RGB colorimetry and gray analysis

Abstract

The invention discloses a dual-mode ascorbic acid (AA) detection method based on RGB colorimetry and gray analysis. The method comprises the following steps: firstly preparing nano-silver sol, then uniformly mixing a certain volume of nano-silver sol, ultrapure water and a glycine-NaOH buffer solution with 0.2 mL of 0.01 mol / L AgNO3 solution, and adding an ascorbic acid standard solution or a solution to be detected; a self-made device combined with a smart phone is used for collecting a reaction system image, and a Tyndall effect average gray value (AG) and a color intensity value (RGB channel value) are extracted as double response signals for quantitative analysis of AA. According to the invention, an intelligent mobile phone RGB colorimetric method and a Tyndall effect gray scale analysis method are combined, rapid and sensitive detection of AA is realized, and the method has the advantages of high reliability, good selectivity, strong portability and the like, is suitable for POCT (point-of-care testing) on-site rapid detection, and is convenient to popularize and use.

Description

Technical Field

[0001] This invention relates to the field of chemical detection of ascorbic acid, specifically to a dual-mode ascorbic acid detection method based on POCT (point-of-care testing) using RGB colorimetry and Tyndall effect grayscale analysis in smartphones. Background Technology

[0002] Ascorbic acid (AA), or vitamin C, is an essential nutrient for the human body, widely involved in metabolic processes. Fruits, vegetables, vitamin C drinks, and vitamin C tablets, which are rich in AA, are the main sources of AA for the human body. AA is chemically unstable and easily decomposes during processing, transportation, and storage. Rapid and accurate detection of AA is of great significance for the food industry, pharmaceutical analysis, and clinical diagnosis.

[0003] Methods for detecting acrylamide (AA) include fluorescence methods, electrochemical methods, high-performance liquid chromatography (HPLC), and Raman spectroscopy. However, these methods generally suffer from limitations such as expensive equipment and time-consuming sample pretreatment. Colorimetric analysis, due to its advantages of intuitive and visible results, simplicity, speed, and low cost, has rapidly developed and become one of the main methods for AA determination. Classical colorimetric analysis typically relies on a spectrophotometer, thus remaining limited to laboratory analysis.

[0004] Compared to traditional spectrophotometers, smartphones, as emerging detection tools, can acquire digital images of samples in real time and extract intensity parameters of the red, green, and blue (RGB) color space through mobile software to quantify sample color, offering advantages such as portability and widespread availability. However, this method still faces several challenges in practical applications: first, the detection results are easily affected by external factors such as ambient lighting conditions and sample background color, resulting in weak anti-interference capabilities; second, the method's sensitivity is limited by the smartphone camera's ability to distinguish subtle color differences; and third, the single output signal mode leads to insufficient reliability of the detection results.

[0005] To address the shortcomings of single-mode colorimetric methods in terms of interference resistance, sensitivity, and reliability, developing dual-mode sensing technologies integrating different detection principles and improving analytical performance through signal complementarity and self-verification mechanisms has become an important strategy. Currently, researchers have constructed dual-mode sensors such as Raman spectroscopy-colorimetry, fluorescence-colorimetry, and electrochemical-colorimetry for AA detection. However, these methods still suffer from drawbacks such as reliance on large, precision instruments, complex fluorescent probe synthesis, and the need to construct additional electrode systems, all of which fail to meet the practical needs of rapid on-site detection in scenarios such as food and pharmaceuticals.

[0006] Therefore, finding a novel complementary signal that is both well-suited to smartphone colorimetry and overcomes its sensitivity and anti-interference limitations is crucial for achieving high-performance auto-analysis (AA) in point-of-care testing (POCT). The Tyndall effect, a classic colloidal light scattering phenomenon, has become a highly sought-after new signal readout mechanism in the POCT field in recent years due to its high sensitivity. This technology not only overcomes the sensitivity bottleneck of color resolution, but its scattering signal can also be accurately quantified by extracting the average grayscale value (AG) using a smartphone. It is unaffected by the sample's background color and requires no expensive instruments, demonstrating good compatibility and complementarity with smartphone colorimetry. Currently, no research has been reported on combining Tyndall effect grayscale analysis with smartphone RGB colorimetry for AA analysis.

[0007] Furthermore, constructing a complete system suitable for rapid on-site detection and the green and simple preparation of stable nanoparticles are also important technical prerequisites. Green tea is rich in natural components such as tea polyphenols and tea polysaccharides, which can be used as green reducing agents and stabilizers to replace traditional chemical reagents such as NaBH4 and citric acid in the synthesis of nanoparticles. This plant reduction preparation method based on green tea extract does not require soaking glassware in aqua regia, nor does it require post-processing modification of the prepared nanoparticles; it is simple to operate and environmentally friendly. Summary of the Invention

[0008] The purpose of this invention is to provide a dual-mode ascorbic acid detection method based on RGB colorimetry and grayscale analysis. This method uses green tea extract as a reducing agent and stabilizer to prepare silver nanoparticles. By utilizing the seed-induced growth mechanism, the AA concentration is converted into changes in the color (RGB signal) and Tyndall scattering intensity (grayscale signal) of the reaction system. It can simultaneously apply the Tyndall effect grayscale method and the smartphone RGB colorimetry method for AA analysis. The two methods can be used individually or simultaneously and mutually verified to improve the reliability of the analysis results.

[0009] To achieve the above objectives, the present invention adopts the following technical solution:

[0010] A dual-mode ascorbic acid detection method based on RGB colorimetry and grayscale analysis, characterized by the following steps:

[0011] Step 1: Preparation of nano-silver sol: Tea extract was mixed evenly with NaOH solution, and then AgNO3 solution was added. The mixture was reacted at room temperature for 10 min to obtain nano-silver sol. The reaction ratio was 1 mL tea extract (1%, v / v) to 0.25 mL 0.1 mol / L NaOH solution to 1 mL 1 mmol / L AgNO3 solution. The tea extract was prepared by adding 0.4 g tea leaves to 30 mL ultrapure water, stirring at room temperature for 30 min, centrifuging, and collecting the supernatant.

[0012] Step 2: Construction of the standard curve: Mix 50 µL of silver nanoparticle sol, 1.25 mL of ultrapure water, 0.5 mL of 0.1 mol / L pH 8.8 glycine-NaOH buffer solution, and 0.2 mL of 0.01 mol / L AgNO3 solution thoroughly. Add 0.5 mL of ascorbic acid standard solutions of different concentrations, where the concentration range of the ascorbic acid standard solutions is 0~85 µg / mL. After reacting at room temperature for 10 min, acquire images of the reaction system and extract the ∑RGB and AG values ​​of the captured images. The ∑RGB value is the sum of the R, G, and B channel values ​​of the image (colorimetric signal), and the AG value is the average gray value of the image (scattering signal). Plot a standard curve with ascorbic acid concentration as the abscissa and AG value and Δ∑RGB value as the ordinate, where Δ∑RGB is the difference between the ∑RGB values ​​of an ascorbic acid concentration of 0 and a certain concentration of ascorbic acid standard solution.

[0013] Step 3: Determination of the test sample: Mix 50 µL of silver nanoparticle sol, 1.25 mL of ultrapure water, 0.5 mL of 0.1 mol / L pH 8.8 glycine-NaOH buffer solution, and 0.2 mL of 0.01 mol / L AgNO3 solution thoroughly. Add 0.5 mL of the test solution and react at room temperature for 10 min. Acquire an image of the reaction system and extract the ∑RGB and AG values ​​from the captured images to calculate the Δ∑RGB value. Substitute the Δ∑RGB and AG values ​​of the test solution into the corresponding standard curve equation plotted in Step 2 to calculate the concentration of ascorbic acid in the test solution.

[0014] In a preferred embodiment of the present invention, the detection can be performed solely based on the AG signal or the Δ∑RGB signal, or it can be performed in conjunction with both AG and Δ∑RGB signals.

[0015] The present invention has the following beneficial effects:

[0016] 1. Green and environmentally friendly, easy to operate: Nano-silver sol (AgNPs) is synthesized in a green way through plant reduction and used to construct an ascorbic acid (AA) colorimetric sensing platform. No complicated modification is required and no additional colorimetric substrate is needed. It is environmentally friendly and easy to operate.

[0017] 2. Dual-mode complementarity and high reliability: By combining the RGB colorimetric method of smartphones with the Tyndall effect grayscale method, and verifying the scattering-colorimetric dual signals, the anti-interference ability and reliability of AA detection are effectively improved. It can be used to detect AA in commercially available beverages and vitamin C tablets.

[0018] 3. High sensitivity: The detection limits of both the Tyndall effect grayscale method and the smartphone colorimetric method are lower than those of the traditional absorbance spectrophotometry method.

[0019] 4. High portability: The method only requires a smartphone to complete the synchronous acquisition and analysis of scattering and colorimetric dual signals. It is simple to operate, low in cost, and highly portable, and has good application prospects in the POCT field. Attached Figure Description

[0020] Figure 1 The following are schematic diagrams of the preparation process of AgNPs for dual-mode detection of AA: (a) is the preparation process of silver nanoparticle sol, and (b) is the dual-mode detection process.

[0021] Figure 2 The device is a self-made dual-mode detection device, (a) using the RGB colorimetric method of a smartphone and (b) using the Dahl effect grayscale method.

[0022] Figure 3 The following are characterization spectra of AgNPs: (a) UV-Vis spectrum, (b) TEM image (inset shows particle size distribution), (c) high-resolution transmission electron microscopy (HRTEM) image, and (d) FT-IR spectrum.

[0023] Figure 4 The diagram shows the optimization of preparation conditions for AgNPs, including: (a) optimization of green tea extract volume fraction, (b) optimization of NaOH solution concentration, (c) optimization of preparation temperature, and (d) optimization of preparation time.

[0024] Figure 5 The following are spectra related to the feasibility of dual-mode colorimetric detection of AA, including: (a) spectrophotometric detection, (b) Tyndall effect grayscale method, (c) smartphone RGB colorimetric method, and (d) TEM characterization of AgNPs after the addition of AA.

[0025] Figure 6 Selectivity correlation spectrum for AA detection; including: (a) spectrophotometry, (b) Tyndall effect grayscale method, (c) smartphone RGB colorimetry; from left to right: water, glycine, glutamic acid, lysine, Mg 2+ Citric acid, Na + glucose, K + Aspartic acid, sucrose, and amino acids;

[0026] Figure 7 The graph shows the effect of AgNO3 concentration on AA detection; where: (a) spectrophotometric detection, (b) Tyndall effect grayscale method, and (c) smartphone RGB colorimetric method.

[0027] Figure 8 The graph shows the effect of pH on AA detection; where: (a) spectrophotometry, (b) Tyndall effect grayscale method, and (c) smartphone RGB colorimetry.

[0028] Figure 9 The graph shows the effect of incubation time on AA detection; where: (a) spectrophotometric detection, (b) Tyndall effect grayscale method, and (c) smartphone RGB colorimetric method.

[0029] Figure 10 To evaluate the analytical performance of the dual-mode colorimetric analysis AA method, the following graphs are provided: (a) absorption curves of the system after adding different concentrations of AA; (b) standard curve of spectrophotometry at 416 nm; (c) standard curve with AG value as the ordinate in the Tyndall effect; and (d) standard curve with Δ∑RGB value of smartphone as the ordinate. Detailed Implementation

[0030] The present invention will now be described in detail with reference to specific embodiments and accompanying drawings.

[0031] Example 1: Construction of a dual-mode system for smartphone RGB colorimetry and Tyndall effect grayscale analysis

[0032] 1.1 Reagents and Instruments

[0033] Citric acid, sodium citrate, AgNO3, MgSO4, K2CO3, and AA were purchased from Tianjin Damao Chemical Reagent Factory; glucose, sucrose, glycine, glutamic acid, lysine, and aspartic acid were purchased from Shanghai Aladdin Biochemical Technology Co., Ltd.; all reagents were of analytical grade, and the experimental water was ultrapure water. Green tea (pre-Qingming tender buds), originating from Xinyang, Henan; Vitamin C tablets (AA labeled content 100 mg / tablet), from Northeast Pharmaceutical Group Shenyang First Pharmaceutical Co., Ltd.; and a sports drink (AA labeled content 200 µg / mL), purchased from a local supermarket.

[0034] UV-2600 UV-Vis spectrophotometer, Shanghai Tianmei Scientific Instruments Co., Ltd.; JEM-2010 FEF-JEOL transmission electron microscope, NEC Corporation; TENSOR-37 Fourier transform infrared spectrometer, Bruker Scientific Instruments GmbH, Germany; Nova 7 5G smartphone, Huawei Technologies Co., Ltd.; SS-10 red laser pointer (wavelength 635 nm, output power 2 mW), HP China Ltd.; QZ-037 LED tube, Linhai Zhongyuan Electronic Technology Co., Ltd.; 24-well plate, Wuxi Nester Biotechnology Co., Ltd.

[0035] 1.2 Experimental Procedure

[0036] 1.2.1 Design of Dual-Mode Detection Device

[0037] This invention designs and constructs a dual-mode optical detection device based on a smartphone, combining scattering and colorimetry. The smartphone RGB colorimetric detection device is as follows... Figure 2As shown in Figure a, the device is a sealed dark chamber with a camera window for taking pictures on top. Two LED tubes are fixed at the bottom of the chamber as light sources to avoid interference from external light. The 24-well plate containing the samples is placed above the light source, and the smartphone is fixed at the opening on the top of the chamber, maintaining a vertical distance of 43 cm between the camera and the well plate. All sample images were acquired in the smartphone's "professional mode" with the following parameters: ISO 100, resolution 2 MP, and shutter speed 1 / 1000 s. The images were imported into the smartphone's built-in "Color Collect" software (version 2.7.0), and the R, G, and B channel intensity values ​​were extracted. The sum of the three channel intensities (∑RGB) was used as the quantitative colorimetric signal.

[0038] Tyndall effect grayscale detection device, such as Figure 2 As shown in b, the main body is a closed dark box (15.5 cm × 14 cm × 3.2 cm), which can effectively shield against ambient light interference. Openings are located on the front wall, top, and right side of the dark box for securing a smartphone, placing a glass sample vial (1 cm radius), and mounting a laser pointer. The center of the top opening is 6 cm from the phone window on the front wall and 3.5 cm from the laser pointer's entrance on the right side. During detection, the laser pointer illuminates the center of the sample vial vertically from the right side, exciting the Tyndall scattering light path. The smartphone captures the scattered image through the front window. All image capture parameters were set as follows: ISO 200, shutter speed 1 / 200 s, and white balance mode: cloudy. ImageJ software was used to crop a fixed area (300 × 250 pixels) at the center of the scattered light path, and the AG value was extracted as the quantitative scattering signal.

[0039] 1.2.2 Preparation of AgNPs from Green Tea Extract

[0040] Weigh 0.4 g of tea leaves, add 30 mL of ultrapure water, stir at room temperature for 30 min, centrifuge at 6000 r / min for 10 min, and collect the supernatant, which is the green tea extract. Dilute it with ultrapure water to different volume fractions for later use. Mix 1 mL of green tea extract (100%, v / v) with 0.25 mL of 0.1 mol / L NaOH solution, add 1 mL of 1 mmol / L AgNO3 solution, and react at room temperature for 10 min to obtain AgNPs sol.

[0041] 1.2.3 Optimization of AgNPs Preparation Conditions

[0042] In the preparation of AgNPs, the volume fraction of green tea extract (0.1%~3%, v / v), NaOH solution concentration (0.02~0.3mol / L), preparation temperature (20~100℃) and preparation time (0~12 min) were optimized to select the best preparation conditions.

[0043] 1.2.4 Feasibility of Dual-Mode Colorimetric Analysis (AA)

[0044] 50 µL of AgNPs, 1.25 mL of ultrapure water, 0.5 mL of 0.1 mol / L pH 8.8 glycine-NaOH buffer, and 0.2 mL of 0.01 mol / L AgNO3 solution were mixed thoroughly, and then 0.5 mL of AA solutions of different concentrations (0, 20, and 50 µg / mL) were added respectively. The mixture was incubated at room temperature for 10 min, and the color change was observed. The absorption spectrum was scanned using a spectrophotometer, and the ∑RGB and AG values ​​were extracted using the aforementioned dual-mode detection device.

[0045] 1.2.5 Dual-mode colorimetric analysis of AA selectivity

[0046] To investigate the selectivity of the two-mode colorimetric analysis AA method, the study examined Mg... 2+ K + Na + Ca 2+ The effects of common interfering substances such as glucose, sucrose, citric acid, glutamic acid, glycine, and lysine on the detection of amino acids (AA) were investigated. The above interfering substances were replaced with 500 µg / mL of each AA, and experiments were conducted according to the method described in 1.2.4.

[0047] 1.2.6 Optimization of Detection Conditions

[0048] When detecting AA using the dual-mode colorimetric method, the final concentration of AgNO3 solution (0~2.4 mmol / L), buffer pH (7.0~9.0), and incubation time (0~40 min) were investigated to determine the optimal detection conditions.

[0049] 1.2.7 Performance Evaluation of Dual-Mode Colorimetric Analysis

[0050] The analytical performance of the method was evaluated under optimal conditions: 50 µL of AgNPs, 1.25 mL of ultrapure water, 0.5 mL of 0.1 mol / L pH 8.8 buffer, and 0.2 mL of 0.01 mol / L AgNO3 solution were mixed thoroughly, and then 0.5 mL of AA solutions of different concentrations (0–85 µg / mL) were added. The mixture was incubated at room temperature for 10 min, and the A values ​​were recorded. 416 (i.e., absorbance at 416 nm), ∑RGB and AG values.

[0051] Plotting AA concentration on the x-axis, and then using A... 416 Using AG value and Δ∑RGB (difference between blank control and sample ∑RGB) as the ordinate, plot the standard curve and calculate the detection limit according to formula (1).

[0052] Detection limit = 3σ / k (1)

[0053] In the formula: σ is the standard deviation of the blank signal; k is the slope of the standard curve.

[0054] 2. Experimental Results

[0055] 2.1 Feasibility of AgNPs Preparation

[0056] like Figure 3 As shown in Figure a, when only green tea extract is used, the system is nearly colorless, while the AgNPs sol prepared from it is dark in color, turning yellow upon dilution, and exhibiting a distinct surface plasmon resonance absorption peak at 405 nm. (Transmission electron microscopy) Figure 3 (b) The results showed that the silver nanoparticles were spherical and well dispersed, with an average particle size of approximately 2.69 nm and a lattice spacing of 0.235 nm. Figure 3 c), which is the Ag(111) crystal plane.

[0057] Infrared spectroscopy was used to investigate which components of green tea extract play a role in the synthesis of AgNPs. Figure 3 d). Green tea extract at 3450~3200 cm⁻¹ -1 The broad absorption peaks within the range are attributed to the stretching vibrations of O-H in tea polyphenols and N-H in tea polysaccharides; 2920 cm⁻¹ -1 The absorption peak is due to the C-H stretching vibration; 1637 cm⁻¹ -1 The absorption peak corresponds to the C=O and C=C stretching vibrations of tea polyphenols and tea polysaccharides; 1402 cm⁻¹ -1 The absorption peak corresponds to the C-O stretching vibration of tea polyphenols; 1037 cm⁻¹ -1 The absorption peaks correspond to the stretching vibrations of the C—O—C and C—N chains of tea polysaccharide glycosides. This indicates that green tea extract contains components such as tea polyphenols and tea polysaccharides. Compared to green tea extract, AgNPs are concentrated in the 3450–3200 cm⁻¹ range. -1 There is still a broad absorption peak, but the intensity decreases, while at 2920, 1637, 1402, and 1037 cm⁻¹... -1 The absorption peaks at 1317 and 877 cm⁻¹ almost disappeared, indicating that during the preparation of AgNPs, tea polyphenols and tea polysaccharides were mainly consumed as reducing agents; while at 1317 and 877 cm⁻¹... -1 New absorption peaks appeared at the locations, corresponding to the molecular skeleton vibrations of the aromatic ring and the ==C—H bending vibrations, respectively. This indicates that tea polyphenols, tea polysaccharides, and Ag... + The oxidation products generated after the reaction modify the surface of AgNPs, providing a protective effect and ensuring good dispersibility of the AgNPs. These results confirm the successful preparation of AgNPs from green tea extract.

[0058] 2.2 Optimization of AgNPs preparation conditions

[0059] To construct a high-performance dual-mode AA sensor, the preparation of high-performance AgNPs is crucial. Therefore, the main influencing factors in the AgNPs synthesis process were investigated, including the volume fraction of green tea extract, NaOH concentration, synthesis temperature, and synthesis time. The experimental results are as follows: Figure 4 As shown. Figure 4 a indicates that when the volume fraction of green tea extract is less than 1%, A 405 The concentration of extract increases with increasing content; when the volume fraction is 1%, A... 405 Reaching the maximum value indicates that the AgNPs concentration is highest at this point; while when the volume fraction is higher than 1%, A 405 The slight decrease is likely due to the excessive reducing agent causing the silver nanoparticles to aggregate, thus reducing their dispersibility. Therefore, the volume fraction of green tea extract was chosen to be 1%.

[0060] Under acidic conditions, green tea extract cannot reduce AgNO3 to prepare AgNPs, while alkaline conditions are more conducive to the nucleation and growth of nanoparticles. Therefore, the effect of NaOH concentration on the preparation of AgNPs was investigated. Figure 4 As shown in b, with the increase of NaOH concentration, A 405 The concentration of NaOH initially increases and then levels off; when the concentration is 0.08 mol / L, A... 405 Since the maximum value was reached, 0.08 mol / L was chosen as the optimal NaOH concentration.

[0061] The effect of temperature on AgNPs synthesis is as follows: Figure 4 As shown in c, AgNPs can be successfully prepared in the temperature range of 20~100℃, and A 405 The differences are minor. Considering the simplicity of the experimental procedures, subsequent experiments were all conducted using AgNPs prepared at room temperature.

[0062] The effect of synthesis time on the preparation of AgNPs is as follows: Figure 4 As shown in d, AgNPs are rapidly generated after AgNO3 is mixed with green tea extract, and the concentration of AgNPs increases with time. 405 The sample size initially increased and then remained constant, therefore a preparation time of 10 min was chosen.

[0063] 2.3 Feasibility of dual-mode colorimetric method for detecting AA

[0064] The principle of dual-mode detection of AA is as follows: using AgNPs as seed crystals, under alkaline conditions, AA reduces Ag. + The deposition of elemental silver on the surface of AgNPs leads to an increase in the AgNP particle size, which in turn affects the system's color and... 416 The changes in AG value and ∑RGB are used to achieve a dual-mode quantitative analysis of AA.

[0065] In the control group without added AA, due to the low concentration of seed AgNPs and the lack of AA reduction, Ag... + It cannot be reduced, and the system is nearly colorless; in the control group containing only AA and AgNO3, due to the lack of seed crystals AgNPs, AA reduces Ag. + The homogeneous nucleation rate is extremely slow, making it difficult to generate detectable nanoparticles, and the system is also colorless. These results can be directly determined by naked-eye observation without the need for further testing.

[0066] In the experimental group where AgNPs, AgNO3, and AA were added simultaneously, when the AA concentration was between 20 and 50 µg / mL, the effect of AgNO3 on AA concentration increased. 416 The value increases ( Figure 5 a) The Tyndall effect is simultaneously enhanced, and the AG value increases ( Figure 5 b), the solution color gradually deepens, and the ∑RGB value decreases accordingly ( Figure 5 c). A 416 The consistent trend of changes in AG and ∑RGB values ​​fully confirms that AA can drive the seed-induced growth process of AgNPs, indicating the feasibility of the dual-mode detection method for AA. TEM results ( Figure 5 d) Further, it was shown that the average particle size of AgNPs increased to 31.64 nm after the addition of 50 µg / mL AA, which verified the AA-mediated seed-induced growth mechanism from a morphological perspective.

[0067] The experimental results above demonstrate that the method of using a seed-induced growth-based dual-mode colorimetric sensor for detecting AA is feasible.

[0068] 2.4 Selectivity of AA Detection Using Two-Mode Colorimetric Method

[0069] To investigate the selectivity of the two-mode colorimetric analysis AA method, 500 µg / mL Mg was used. 2+ K + Na + Ca 2+ Common interfering substances such as glucose, sucrose, citric acid, glutamic acid, glycine, and lysine were used to replace 20 µg / mL AA. The experimental results are as follows: Figure 6 As shown. Only with the addition of 20 µg / mL AA did A416 significantly increase ( Figure 6 a); The Tyndall effect is enhanced, and the AG value increases significantly ( Figure 6 b); The system color changed from colorless to light yellow, and the ∑RGB value dropped sharply ( Figure 6 c). The above results indicate that even in the presence of high concentrations of interfering substances (25 times the concentration of AA), the two-mode colorimetric method remains unaffected in the detection of AA, demonstrating good selectivity.

[0070] 2.5 Optimization of AA Detection Conditions

[0071] Factors affecting the detection of AA, such as final AgNO3 concentration (0–2.4 mmol / L), pH (7.0–9.0), and incubation time (0–40 min), were investigated. The experimental results are as follows: Figure 7-9 As shown.

[0072] 2.5.1 Optimization of the final concentration of AgNO3 solution

[0073] AgNO3, used as a silver source, directly affects the amount of silver deposited on the seed crystal surface, thus influencing the intensity of the scattering-colorimetric dual signal. Figure 7 It can be seen that when the final concentration of AgNO3 increases from 0 to 0.8 mmol / L, A 416 As the AG value gradually increases and reaches its peak, the ∑RGB value correspondingly decreases to its lowest point; when the dosage of AgNO3 continues to increase, A 416 Both the AG and ∑RGB values ​​decreased, while the ∑RGB value slightly increased. This is because the reducing agent AA was insufficient, and the excess Ag could not be completely reduced. + This resulted in incomplete growth of the silver shell and uneven nucleation, leading to a weakened signal response. Therefore, subsequent experiments selected a final AgNO3 concentration of 0.8 mmol / L.

[0074] 2.5.2 pH Optimization

[0075] The effect of pH on AA detection, such as Figure 8 As shown, under acidic and neutral conditions, AA has weak reducing power, resulting in insufficient sensitivity of the scattering-colorimetric dual-signal method. This experiment used a glycine-NaOH buffer solution, which not only provides the alkaline environment required for seed growth induction, but also allows glycine molecules to react with Ag. + Coordination effectively inhibits the formation of AgOH or Ag₂O precipitates. At pH 8.8, A… 416 Both the pH and AG values ​​reach their maximum, while the ∑RGB value decreases to its minimum. Further increasing pH will lead to OH-. - If the concentration is too high, even with glycine coordination, precipitation cannot be completely suppressed. Therefore, a glycine-NaOH buffer solution with a pH of 8.8 was ultimately chosen.

[0076] 2.5.3 Incubation Time Optimization

[0077] The effect of incubation time on AA detection was investigated, and the results are as follows: Figure 9 As shown. With increasing incubation time, A 416 The AG value rose rapidly and then stabilized, while the ∑RGB value fell rapidly and then remained essentially unchanged. Therefore, an incubation time of 10 min was chosen.

[0078] 2.6 Method Analysis and Performance Evaluation

[0079] The analytical performance of the AA dual-mode sensor was evaluated under optimal experimental conditions, and the results are as follows: Figure 10 As shown. A 416 AG and Δ∑RGB showed good linear relationships with AA in the ranges of 1~85, 0.1~85, and 0.5~85 µg / mL, respectively, and the corresponding linear equations were A 416 = 0.01932c - 0.0148 (R) 2 = 0.9941), AG = 1.1616c + 8.2080 (R 2 =0.9933) and Δ∑RGB= 5.0112c + 9.1817 (R 2 = 0.9996); the limits of detection (LODs) were 0.66, 0.018, and 0.34 µg / mL, respectively. Compared with spectrophotometry, the LOD of the smartphone RGB colorimetric method was reduced by about 2 times, and the LOD of the Tyndall effect grayscale analysis method was reduced by about 36 times, demonstrating superior sensitivity.

[0080] Table 1 Performance comparison with other AA detection methods

[0081]

[0082] ① Cobalt hydroxyoxide nanosheets; ② Oxygen-coordinated bimetallic iron-copper material in nitrogen-doped carbon nanorods with dual enzyme activity; ③ Silver nanoparticle / single-walled carbon nanotube composite nanozymes; ④ Zirconium-based metal-organic frameworks with phosphatase-mimicking activity. [1]Sep. and Purif. Technol., 2025, 355: 129819; [2] Microchem. J., 2024,201: 110745; [3] Analytical Chemistry, 2020, 48(8): 1041-1049; [4] Sens. Actuators B:Chem., 2018, 256: 512-519; [5] Microchem. J., 2025, 27: 114852; [6] Luminescence, 2020, 35(7): 1084-1091; [7] Food Chem., 2025, 47: 142837.

[0083] Example 2: Actual Sample Testing

[0084] Commercially available sports drinks and vitamin C tablets were used as actual samples for analysis. The sports drinks were appropriately diluted, and the vitamin C tablets were ground and dissolved in ultrapure water to prepare sample solutions with a theoretical background concentration of AA of 5 µg / mL. The accuracy of the method was further verified through spiked recovery experiments. Known concentrations of AA standard solution were added to the above sample solutions to prepare spiked sample solutions, resulting in AA spikes of 1, 20, and 50 µg / mL. The dual-mode analytical method established in this invention was used to detect all sample solutions (including background and three spiking levels). Each sample was measured in triplicate, and the spiked recovery rate and relative standard deviation were calculated.

[0085] Perform the test as follows:

[0086] Step 1: Preparation of nano-silver sol: Tea extract and NaOH solution were mixed evenly, and then AgNO3 solution was added. The mixture was reacted at room temperature for 10 min to obtain nano-silver sol. The reaction ratio was 1 mL tea extract (1%, v / v) to 0.25 mL 0.1 mol / L NaOH solution to 1 mL 1 mmol / L AgNO3 solution. The tea extract was obtained by adding 0.4 g tea leaves to 30 mL ultrapure water, stirring at room temperature for 30 min, centrifuging and collecting the supernatant, and then diluting 1 volume of the supernatant with 99 volume of ultrapure water.

[0087] Step 2: Construction of standard curves: Mix 50 µL of silver nanoparticle sol, 1.25 mL of ultrapure water, 0.5 mL of 0.1 mol / L pH 8.8 glycine-NaOH buffer solution, and 0.2 mL of 0.01 mol / L AgNO3 solution thoroughly. Add 0.5 mL of ascorbic acid standard solutions of different concentrations and react at room temperature for 10 min. Collect images of the reaction system and extract the ∑RGB and AG values ​​of the images. When constructing a standard curve of AG value versus ascorbic acid concentration, the concentration range of the ascorbic acid standard solution is 0.1~85 µg / mL. When constructing a standard curve of Δ∑RGB value versus ascorbic acid concentration, the concentration range of the ascorbic acid standard solution is 0.5~85 µg / mL.

[0088] Step 3: Actual Sample Analysis: Mix 50 µL of silver nanoparticle sol, 1.25 mL of ultrapure water, 0.5 mL of 0.1 mol / L pH 8.8 glycine-NaOH buffer, and 0.2 mL of 0.01 mol / L AgNO3 solution thoroughly. Add 0.5 mL of sample solution (including background and three spiking levels) to each solution. Incubate at room temperature for 10 min. Acquire images of the reaction system and extract the ∑RGB and AG values ​​from the images. Based on the standard curve plotted in Step 2, substitute the measured AG or Δ∑RGB values ​​into the corresponding standard curve equation to calculate the concentration of ascorbic acid in the sample solution. For samples of different concentrations, either the AG signal or the Δ∑RGB signal can be used for analysis, or both methods can be used simultaneously and cross-validated.

[0089] The content of amino acids (AA) in vitamin C tablets and commercially available beverages was determined using this invention, as shown in Table 2. Calculations showed that each sample was measured in triplicate (n=3), with spiked recoveries ranging from 89.0% to 110.0% and RSD < 5%, indicating that this method has good precision and accuracy.

[0090] Table 2. Results of spiked recovery test of AA in VC tablets and sports drinks.

[0091]

[0092] Detected value: mean ± standard deviation

[0093] A novel method for determining ascorbic acid (AA) was successfully developed using a plant reduction method to prepare nano-silver sol (AgNPs). Using AgNPs as seeds and catalysts, a seed-induced growth mechanism was employed to construct a colorimetric sensing platform, eliminating the need for additional substrates and making it environmentally friendly. A new method for AA determination was established by combining smartphone RGB colorimetry with the Tyndall effect grayscale method. Mutual verification using scattering and colorimetric dual signals effectively improved the reliability of AA detection results. The detection limit for AA using the Tyndall effect grayscale method was 0.018 µg / mL, and the detection limit using the smartphone colorimetry method was 0.34 µg / mL, both lower than that of traditional spectrophotometry. This method can be used for the detection of AA in commercially available beverages and vitamin C tablets, with satisfactory spiked recoveries. The method requires only a smartphone for simultaneous acquisition and analysis of scattering and colorimetric dual signals, making it simple to operate, low-cost, and highly portable, showing promising application prospects in the field of point-of-care testing.

Claims

1. A method for detecting ascorbic acid based on RGB colorimetry and grayscale analysis, characterized in that... Includes the following steps: Step 1: Preparation of nano-silver sol: Tea extract was mixed evenly with NaOH solution, and then AgNO3 solution was added. The mixture was reacted at room temperature for 10 min to obtain nano-silver sol. The reaction ratio was 1 mL tea extract to 0.25 mL 0.1 mol / L NaOH solution to 1 mL 1 mmol / L AgNO3 solution. The tea extract was obtained by adding 0.4 g tea leaves to 30 mL ultrapure water, stirring at room temperature for 30 min, centrifuging and collecting the supernatant, and then diluting 1 volume of the supernatant with 99 volumes of ultrapure water. Step 2: Construction of the standard curve: Mix 50 µL of nano silver sol, 1.25 mL of ultrapure water, 0.5 mL of 0.1 mol / L pH 8.8 glycine-NaOH buffer solution, and 0.2 mL of 0.01 mol / L AgNO3 solution thoroughly. Add 0.5 mL of ascorbic acid standard solutions of different concentrations, wherein the concentration range of the ascorbic acid standard solutions is 0~85 µg / mL. After reacting at room temperature for 10 min, acquire images of the reaction system and extract the ∑RGB and / or AG values ​​of the captured images. The ∑RGB is the sum of the R, G, and B channel values ​​of the image, and the AG value is the average gray value of the image. Plot a standard curve with ascorbic acid concentration as the abscissa and AG value and / or Δ∑RGB as the ordinate. The Δ∑RGB is the difference between the ∑RGB values ​​of an ascorbic acid concentration of 0 and a certain concentration of ascorbic acid standard solution. Step 3: Determination of the sample to be tested: Mix 50 µL of nano silver sol, 1.25 mL of ultrapure water, 0.5 mL of 0.1 mol / L pH 8.8 glycine-NaOH buffer, and 0.2 mL of 0.01 mol / L AgNO3 solution thoroughly. Add 0.5 mL of the test solution and react at room temperature for 10 min. Then, acquire an image of the reaction system and extract the ∑RGB and / or AG values ​​of the captured images. Determine the concentration of ascorbic acid in the test solution based on the Δ∑RGB and / or AG values ​​of the test solution and the standard curve from Step 2.

2. The ascorbic acid detection method based on RGB colorimetry and grayscale analysis as described in claim 1, characterized in that, In step 2, only the AG value of the reaction system is extracted, and an ascorbic acid standard solution with a concentration range of 0.1~85 µg / mL is used to plot a standard curve with ascorbic acid concentration as the abscissa and AG value as the ordinate. In step 3, only the AG value of the reaction system of the test solution is extracted, and the concentration of ascorbic acid in the test solution is calculated based on the above AG value standard curve.

3. The ascorbic acid detection method based on RGB colorimetry and grayscale analysis as described in claim 1, characterized in that, In step 2, only the ∑RGB values ​​of the reaction system are extracted, and a standard curve is plotted using an ascorbic acid standard solution with a concentration range of 0.5~85 µg / mL, with the ascorbic acid concentration as the abscissa and the Δ∑RGB value as the ordinate. In step 3, only the ∑RGB values ​​of the reaction system of the test solution are extracted, the Δ∑RGB value is calculated, and the concentration of ascorbic acid in the test solution is calculated based on the above Δ∑RGB value standard curve.

4. The ascorbic acid detection method based on RGB colorimetry and grayscale analysis as described in claim 1, characterized in that, In step 2, the AG and ∑RGB values ​​of the reaction system are extracted simultaneously, and the Δ∑RGB value is calculated. Using an ascorbic acid standard solution with a concentration range of 0.5~85 µg / mL, two standard curves are plotted with ascorbic acid concentration as the abscissa and AG and Δ∑RGB values ​​as the ordinates. In step 3, the AG and ∑RGB values ​​of the reaction system of the test solution are extracted simultaneously, and the Δ∑RGB value is calculated. Quantitative analysis is performed using the two standard curves to calculate the concentration of ascorbic acid in the test solution.

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