A method for colorimetric detection of residual phorate in rice based on nano-gold catalytic activity

Abstract

The application relates to the field of pesticide residue detection, and discloses a method for colorimetric detection of rogor residues in rice based on nano-gold catalytic activity, which comprises the following steps: mixing a nano-gold solution and a rice extract solution and incubating, so that rogor molecules occupy catalytic active sites; adding a mixture of o-phenylenediamine and hydrogen peroxide to inhibit the catalytic activity of nano-gold, thereby inhibiting the color development reaction of the detection system, and measuring the absorbance value at a fixed wavelength; using a matrix background fingerprint spectrum data set to strip the absorbance deviation characteristics caused by endogenous components, extracting a characteristic absorbance component value representing the inhibition intensity of rogor, and calculating the rogor residue amount. The application realizes fixed wavelength signal projection and matrix characteristic decoupling, eliminates the non-specific interference caused by polysaccharides, polypeptides and alkaloids, enhances the reliability of the extraction of weak target signals under high background noise, and reduces the risk of component loss caused by physical purification.

Description

Technical Field

[0001] This invention relates to a method for colorimetric detection of dimethoate residues in rice based on nano-gold catalytic activity, belonging to the field of pesticide residue detection technology. Background Technology

[0002] Currently, the use of gold nanoparticles to simulate peroxidase activity and catalyze the reaction of o-phenylenediamine with hydrogen peroxide to generate o-phenylenediamine oxide constitutes a widely adopted colorimetric analysis pathway in the industry. By monitoring the absorbance change of the chromogenic product at a wavelength of 450 nm, rapid screening of organophosphorus pesticide components can be achieved, which has the advantages of simple operation and low cost. However, rice samples contain complex matrix components such as polysaccharides, peptides, and endogenous alkaloids. These components are prone to non-specific adsorption on the surface of gold nanoparticles, inducing local pH shifts in the reaction system, resulting in nonlinear broadening or redshift of the plasmon resonance absorption peak. Existing technologies usually rely on adding physical purification steps to reduce matrix background interference. This front-end processing-oriented approach prolongs the operation cycle and carries the risk of unexpected loss of target pesticide molecules during the purification process. At the same time, based on a single wavelength scalar absorbance monitoring method, it is difficult to effectively distinguish the specific inhibition signal generated by the target molecule from the non-specific fluctuation signal generated by the complex matrix in terms of physical principles.

[0003] Existing technical solutions exhibit the following shortcomings in addressing the aforementioned challenges: 1. The detection system has weak resistance to interference from biological matrices, easily leading to false positives; 2. Scalar monitoring logic lacks the dimension to capture the characteristics of spectral response; 3. The time-consuming nature of front-end physical separation restricts the demand for on-site real-time detection. While industry attempts have tried to optimize signal quality by increasing sampling frequency or adjusting reagent ratios, the failure to address the nonlinear mapping relationship between absorbance arrays and matrix effects prevents the mathematical removal of interference signals. Besides hardware-level sensitivity limitations, existing technologies also suffer from deficiencies in software aspects such as identification logic and anti-interference algorithms. For example, the Chinese patent with publication number CN104849268A... The invention patent discloses a reagent and its application for colorimetric detection of omethoate based on a gold nanoparticle probe encapsulated by nucleic acid aptamers. It utilizes the specific binding of nucleic acid aptamers to target molecules to enhance system stability. However, this technology is highly dependent on the charge balance of the system. When facing complex matrices containing high concentrations of polar macromolecules, such as rice extract, matrix components can easily occupy the surface of gold nanoparticles through non-specific competition, leading to the failure of the protective effect and causing false positive aggregation. The signal output of this scheme is limited to the ratio of single-wavelength or dual-wavelength absorbance, lacks in-depth capture of the spectral evolution law, and cannot achieve orthogonal decoupling between matrix characteristic components and target inhibition components at the mathematical level. It is difficult to meet the reliability requirements for extracting weak target signals under high background noise.

[0004] Therefore, how to construct a signal orthogonal decoupling model based on multidimensional spectral response characteristics to achieve effective separation of the matrix component and the target inhibition component of rice extract has become the technical problem to be solved by this invention. Summary of the Invention

[0005] To address the problems mentioned in the background art, the technical solution of the present invention is as follows: A method for colorimetric detection of dimethoate residues in rice based on nano-gold catalytic activity, comprising the following steps: Step 101: Remove the rotten parts from the rice sample to be tested, cut it into 1cm segments, weigh 20g of the sample and place it in a 50mL centrifuge tube, then add PBS solution (pH 7.4) and sonicate for 5min. After standing for 2min, the rice extract to be tested is obtained. Step 102: Prepare a nano-gold solution with simulated peroxidase activity. Mix the nano-gold solution with rice extract at a preset volume ratio and incubate at 30°C. This allows the dimethoate molecules in the rice extract to occupy the catalytic active sites on the nano-gold surface through their active functional groups, thereby constructing a colorimetric reaction system with limited catalytic ability. Step 103: Add pH 4.5 sodium acetate buffer to the system, then add a mixture of o-phenylenediamine and hydrogen peroxide to inhibit the catalytic activity of gold nanoparticles, thereby inhibiting the production of the yellow substance 2,3-dioxyphenazine in the detection system. Use a full-wavelength reader to measure the absorbance of the system after the reaction at a wavelength of 450 nm. Step 104: Retrieve the preset matrix background fingerprint spectral dataset, identify the non-specific absorbance interference features caused by endogenous polysaccharides, peptides and alkaloids in rice in the matrix background fingerprint spectral dataset, correlate and project the multi-wavelength scan absorbance sequence with the non-specific absorbance interference features, remove the absorbance deviation caused by matrix effect, and extract the characteristic absorbance component value that characterizes the specific inhibitory strength of dimethoate molecules. Step 105: Based on the characteristic absorbance component values, match the preset standard calibration curve and calculate and determine the residual amount of dimethoate in the rice sample to be tested.

[0006] Preferably, step 104 specifically includes the following sub-steps: Step 401, projecting the multi-wavelength scan absorbance sequence onto a preset matrix interference signal projection space, calculating the background projection component of the multi-wavelength scan absorbance sequence in the space, the background projection component characterizing the non-specific response caused by polysaccharides, peptides and alkaloids in the extract; Step 402, subtracting the background projection component from the absorbance sequence to obtain the target feature difference signal after removing background interference, and determining the modulus of the target feature difference signal as the feature absorbance component value.

[0007] Preferably, in step 102, the step of preparing the nano-gold solution includes: stirring and heating a 1.0 mM chloroauric acid solution to boiling, and quickly adding a 38.8 mM trisodium citrate solution. After continuously heating and stirring for 15 minutes, the heating is stopped. At this time, the solution color turns wine red and is cooled to room temperature. The above cooling solution is filtered through a 250 nm filter membrane and then placed in a brown reagent bottle and stored at 4°C in the dark.

[0008] Preferably, in step 102, the mixing volume ratio of the nano gold solution to the rice extract is 1:4, the temperature of the incubation environment is maintained at 30°C, and the incubation time is 10 min.

[0009] Preferably, in step 103, the characteristic absorbance value of the reaction system is measured at a wavelength of 450 nm.

[0010] Preferably, in step 103, the final concentration of o-phenylenediamine in the colorimetric reaction system to be tested is 20 mM, and the final concentration of hydrogen peroxide in the colorimetric reaction system to be tested is 400 mM.

[0011] Preferably, the calculation logic for the characteristic absorbance component value M follows the following formula: Where V is the multi-wavelength scan absorbance sequence, and P is the basis orthogonal matrix characterizing the projection space of the matrix interference signal. It is the transpose of a basis orthogonal matrix. This refers to the Euclidean norm operation for vectors.

[0012] Preferably, in step 101, ultrasonic extraction can significantly enhance the penetration and mass transfer of the extract, avoid the degradation of the target pesticide by high temperature, and achieve a higher recovery rate of the target pesticide, which can greatly shorten the pretreatment cycle.

[0013] Preferably, in step 102, the acetate buffer solution is a 10 mM acetate-sodium acetate buffer system.

[0014] Preferably, the matrix background fingerprint spectral dataset is pre-set in the following way: the absorbance response of a group of blank rice samples without dimethoate residue is measured, and the common optical features of the blank rice samples are identified and stored using a principal component extraction algorithm.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. In the colorimetric detection of the catalytic activity of gold nanoparticles, by acquiring spectral array data within a specific wavelength range, this invention transforms the detection signal from a single-dimensional absorbance scalar into a high-dimensional feature vector carrying rich response characteristics. This mechanism can capture the nonlinear broadening and frequency shift of the plasmon resonance absorption peak caused by the complex matrix in rice extract, thereby establishing a recognition basis at the data level to distinguish between the specific inhibitory effect of the target pesticide molecule and the non-specific interference effect of the matrix. This transformation from one-dimensional to multi-dimensional information representation avoids the limitation of traditional single-wavelength detection methods that are prone to false positives when dealing with complex background noise, ensuring that the detection system has sufficient discrimination efficiency in the original data acquisition stage.

[0016] 2. Based on the computer-aided construction of a multidimensional feature response topology map, this invention achieves mathematical-level purification of mixed optical signals. By projecting the real-time acquired feature vectors onto a preset matrix interference principal component space and forcing them to zero, this process can remove background fluctuations caused by polysaccharides, peptides, and endogenous alkaloids in rice extract, thereby extracting the feature component modulus values ​​that reflect the true concentration of dimethoate. This logic constructs an orthogonal decoupled signal processing method, enabling the inhibitory effect of target molecules to be accurately characterized under the condition of eliminating matrix overlap interference, thus improving the detection reliability of the system in complex biochemical backgrounds.

[0017] 3. By synergistically linking chemical colorimetric mechanisms and multidimensional feature matching logic, the improvement in detection dimensions is transformed into enhanced anti-interference capabilities. This technical approach avoids the process dependence on deep physical purification of rice samples, enabling the system to anchor and quantify weak target signals in the original extract environment. This back-end processing logic replaces and optimizes the front-end physical operations, simplifies the actual operation process, and also reduces the risk of loss of target pesticide components during physical purification. This allows the solution to maintain detection speed while having high robustness to adapt to different rice varieties. Attached Figure Description

[0018] Figure 1 This is a flowchart of the detection process and data processing of the nano-gold catalytic OPD colorimetric method of the present invention; Figure 2 This is a block diagram illustrating the hardware architecture and signal inversion calculation logic of the present invention.

[0019] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0021] A method for colorimetric detection of dimethoate residues in rice based on the catalytic activity of gold nanoparticles includes the following steps: Step 101: Remove the rotten parts from the rice sample to be tested, cut it into 1cm segments, weigh 20g of the sample and place it in a 50mL centrifuge tube, then add PBS solution (pH 7.4) and sonicate for 5min. After standing for 2min, the rice extract to be tested is obtained. Step 102: Prepare a nano-gold solution with simulated peroxidase activity. Mix the nano-gold solution with rice extract at a preset volume ratio and incubate at 30°C. This allows the dimethoate molecules in the rice extract to occupy the catalytic active sites on the nano-gold surface through their active functional groups, thereby constructing a colorimetric reaction system with limited catalytic ability. Step 103: Add pH 4.5 sodium acetate buffer to the system, then add a mixture of o-phenylenediamine and hydrogen peroxide to inhibit the catalytic activity of gold nanoparticles, thereby inhibiting the production of the yellow substance 2,3-dioxyphenazine in the detection system. Use a full-wavelength reader to measure the absorbance of the system after the reaction at a wavelength of 450 nm. Step 104: Retrieve the preset matrix background fingerprint spectral dataset, identify the non-specific absorbance interference features caused by endogenous polysaccharides, peptides and alkaloids in rice in the matrix background fingerprint spectral dataset, correlate and project the multi-wavelength scan absorbance sequence with the non-specific absorbance interference features, remove the absorbance deviation caused by matrix effect, and extract the characteristic absorbance component value that characterizes the specific inhibitory strength of dimethoate molecules. Step 105: Based on the characteristic absorbance component values, match the preset standard calibration curve and calculate and determine the residual amount of dimethoate in the rice sample to be tested.

[0022] Preferably, step 104 specifically includes the following sub-steps: Step 401, projecting the multi-wavelength scan absorbance sequence onto a preset matrix interference signal projection space, calculating the background projection component of the multi-wavelength scan absorbance sequence in the space, the background projection component characterizing the non-specific response caused by polysaccharides, peptides and alkaloids in the extract; Step 402, subtracting the background projection component from the absorbance sequence to obtain the target feature difference signal after removing background interference, and determining the modulus of the target feature difference signal as the feature absorbance component value.

[0023] Preferably, in step 102, the step of preparing the nano-gold solution includes: stirring and heating a 1.0 mM chloroauric acid solution to boiling, and quickly adding a 38.8 mM trisodium citrate solution. After continuously heating and stirring for 15 minutes, the heating is stopped. At this time, the solution color turns wine red and is cooled to room temperature. The above cooling solution is filtered through a 250 nm filter membrane and then placed in a brown reagent bottle and stored at 4°C in the dark.

[0024] Preferably, in step 102, the mixing volume ratio of the nano gold solution to the rice extract is 1:4, the temperature of the incubation environment is maintained at 30°C, and the incubation time is 10 min.

[0025] Preferably, in step 103, the characteristic absorbance value of the reaction system is measured at a wavelength of 450 nm.

[0026] Preferably, in step 103, the final concentration of o-phenylenediamine in the colorimetric reaction system to be tested is 20 mM, and the final concentration of hydrogen peroxide in the colorimetric reaction system to be tested is 400 mM.

[0027] Preferably, the calculation logic for the characteristic absorbance component value M follows the following formula: Where V is the multi-wavelength scan absorbance sequence, and P is the basis orthogonal matrix characterizing the projection space of the matrix interference signal. It is the transpose of a basis orthogonal matrix. This refers to the Euclidean norm operation for vectors.

[0028] Preferably, in step 101, ultrasonic extraction can significantly enhance the penetration and mass transfer of the extract, avoid the degradation of the target pesticide by high temperature, and achieve a higher recovery rate of the target pesticide, which can greatly shorten the pretreatment cycle.

[0029] Preferably, in step 102, the acetate buffer solution is a 10 mM acetate-sodium acetate buffer system.

[0030] Preferably, the matrix background fingerprint spectral dataset is pre-set in the following way: the absorbance response of a group of blank rice samples without dimethoate residue is measured, and the common optical features of the blank rice samples are identified and stored using a principal component extraction algorithm.

[0031] Example 1: In the case of high-throughput on-site screening of newly harvested rice from multiple production areas, the content distribution of endogenous polysaccharides, polypeptides, and alkaloids in rice varies drastically due to different varieties and planting environments. The complex matrix composed of these polar and non-polar macromolecules accumulates during the extraction process and competes with the target analyte, dimethoate, for non-specific adsorption. When a colorimetric reaction is initiated by o-phenylenediamine and hydrogen peroxide, the non-specific encapsulation of the matrix components on the surface of the gold nanoparticles and the resulting local pH shift cause unpredictable nonlinear broadening and redshift of the plasmon resonance absorption peak of the reaction system. This matrix effect-induced broadband absorbance abnormal fluctuation covers the specific inhibition signal generated by trace amounts of dimethoate molecules occupying the catalytic active sites of the gold nanoparticles. This makes it impossible for the single-wavelength absorbance measurement mode to separate the true concentration characteristics of the target pesticide molecules from the high-dimensional matrix noise background, resulting in false positives in the final output detection results.

[0032] To address the aforementioned challenges, this technical solution involves removing rotten parts from the rice sample, cutting it into 1cm segments, and weighing 20g of the sample into a 50mL centrifuge tube. PBS solution (pH 7.4) is then added, and the sample is ultrasonically extracted for 5min. After standing for 2min, the rice extract is obtained. A 1.0mM chloroauric acid solution is stirred and heated to boiling, and a 38.8mM trisodium citrate solution is quickly added. Heating and stirring are continued for 15min, after which heating is stopped. The solution turns wine-red and is cooled to room temperature. The cooled solution is filtered through a 250nm filter membrane and placed in a brown reagent bottle to prepare a nano-gold solution with simulated peroxidase activity. This solution is mixed with the rice extract at a 1:4 volume ratio and incubated at 30℃ for 10min, allowing the dimethoate molecules in the rice extract to occupy the nanoparticles through their active functional groups. The catalytically active sites on the surface of gold nanoparticles were used to construct a colorimetric reaction system with limited catalytic activity. After preparing a gold nanoparticle solution with simulated peroxidase activity, the surface morphology and particle size distribution of the obtained product were characterized by transmission electron microscopy. The results showed that the gold nanoparticles exhibited a spherical symmetrical morphology with an average particle size in the range of 13 nm to 18 nm. The system had a plasmon resonance absorption peak at a wavelength of 450 nm. The surface zeta potential of the gold nanoparticle solution was measured using a potentiometer, and its value was distributed in the range of -35.8 mV to -45.2 mV. The charge density in this specific range maintained the thermodynamic stability of the colloidal particles in rice extract containing endogenous organic acid components through electrostatic repulsion, preventing non-specific aggregation that would lead to physical masking of the catalytically active sites. This established a surface physical environment in which dimethoate molecules specifically bind and inhibit catalytic activity.

[0033] Rice extract and gold nanoparticle solution were mixed and incubated at 30℃ for 10 min, with the pH of the system controlled at 4.5. Utilizing the affinity of the sulfur-phosphorus bonds in dimethoate molecules for atoms on the gold nanoparticle surface, dimethoate molecules occupied catalytically active sites on the gold nanoparticle surface, forming an inhibitory state against simulated peroxidase activity. During incubation, the zeta potential of the gold nanoparticle solution surface was measured using a potentiometer. When the potential was between -38.5 mV and -42.0 mV and the average particle size was 15.5 nm, electrostatic repulsion was generated using a specific charge density to antagonize the colloidal aggregation induced by endogenous organic acids in rice, keeping the dimethoate molecules in a thermodynamically stable range and providing a stable environment for limited catalytic activity. A pH 4.5 sodium acetate buffer was added to the system, followed by a mixture of 20 mM o-phenylenediamine and 400 mM hydrogen peroxide. The liquid inhibits the catalytic activity of gold nanoparticles, thereby suppressing the formation of the yellow substance 2,3-dioxyphenazine in the detection system. The absorbance of the system after the reaction is measured at 450 nm using a spectrophotometer. A preset matrix background fingerprint spectral dataset is retrieved to identify non-specific absorbance interference features caused by endogenous polysaccharides, peptides, and alkaloids from rice. The multi-wavelength scan absorbance sequence is projected onto a preset matrix interference signal projection space, and the background projection component of the multi-wavelength scan absorbance sequence in the space is calculated. The background projection component is subtracted from the multi-wavelength scan absorbance sequence to obtain the target feature difference signal after removing background interference. The modulus of the target feature difference signal is determined as the feature absorbance component value. The calculation logic of this feature absorbance component value follows the following formula: Where M is the characteristic absorbance component value, V is the multi-wavelength scan absorbance sequence, and P is the basis orthogonal matrix characterizing the projection space of the matrix interference signal. It is the transpose of a basis orthogonal matrix. The Euclidean norm operation is performed on the vector; the residual amount of dimethoate in the rice sample to be tested is calculated and determined based on the characteristic absorbance component value matched with the preset standard calibration curve. This multidimensional spectral array projection decoupling operation directly isolates the absorbance deviation characteristics caused by polysaccharides and alkaloids, and eliminates the influence of matrix overlap interference on the characterization of the inhibitory effect of target molecules.

[0034] Example 2: In an industrial field screening operation accompanied by power frequency electromagnetic fluctuations and broadband background light scattering interference, a test platform was constructed using a constant-temperature oscillating water bath and an array spectrophotometer with a wavelength resolution of 1 nm. The test subjects included rice extracts with three matrix concentration gradients: low, medium, and high. The concentration gradients were calibrated by setting the solid-liquid mass ratios of pulverized rice and acetonitrile solution to 1:20, 1:10, and 1:5, respectively. A 0.54 mg / kg concentration of dimethoate standard was injected into each gradient extract. The process control parameters, including the incubation time, were also considered. The value of the incubation time is constrained by both the saturation of the binding between the dimethoate molecule and the catalytic active site and the risk of system aggregation caused by complex matrix. When the initial background value of the absorbance of the system caused by endogenous macromolecules in rice is high, in order to suppress matrix non-specific aggregation caused by intensified molecular collisions, the incubation time needs to converge to the lower limit of the defined range. Accordingly, the incubation time is set to 5.5 min for the high matrix gradient extract in this working condition and 14.5 min for the low matrix gradient extract to balance the signal response intensity and colloidal thermodynamic stability.

[0035] Based on the aforementioned concentration gradient, experimental samples were prepared, and control and two out-of-range control groups were simultaneously constructed. The control groups employed the same pretreatment and color development procedures, but omitted multi-wavelength scanning and orthogonal projection algorithms, only reading the single-wavelength absorbance value at 450 nm from the array spectrophotometer. The pH of the first out-of-range control group was adjusted to 3.0, and the pH of the second out-of-range control group was adjusted to 6.5. 3.2 mM o-phenylenediamine and 8.5 mM hydrogen peroxide were added to each group system, driving the array spectrophotometer to acquire transmitted light signals from 400 nm to 550 nm. During acquisition, a driving current was applied to the light source. Gaussian white noise with a signal-to-noise ratio of 20dB is superimposed to simulate power supply ripple interference. The original multi-wavelength scan absorbance sequence of each group at the end of the reaction is extracted and transmitted to the processor to extract the characteristic absorbance component values. The processor performs pre-denoising processing and uses a sliding window with a width of 5 sampling points to perform mean filtering on the 76-dimensional original sequence. The wavelength overlap rate between adjacent sampling points is 80% to filter out hardware transient electrical noise with a bandwidth of less than 4nm. The smoothed 76-dimensional multi-wavelength scan absorbance sequence is projected onto a basis orthogonal matrix space composed of 12 principal component eigenvectors, and the characteristic absorbance component values ​​after removing the background projection component are calculated.

[0036] The experimental results exhibited a nonlinear evolution pattern strongly correlated with the matrix concentration gradient; under low matrix concentration gradients, the inversion concentration output by the control group was 0.56 mg / kg, while that of the experimental group was determined using the formula... The inversion concentration calculated after extracting the characteristic absorbance components was 0.53 mg / kg, both close to the actual injected baseline value of 0.54 mg / kg. When the matrix concentration increased to a high gradient, the single-wavelength measurement signal of the control group was interfered with by the superposition of scattering from polysaccharide and alkaloid macromolecules and the nonlinear rise of the absorption baseline, causing its output inversion concentration to drift to 1.48 mg / kg, exhibiting a false positive amplification phenomenon. Under the same high matrix gradient, the experimental group maintained an output inversion concentration of 0.55 mg / kg because the multi-wavelength scanning absorbance sequence filtered out the background projection component within the preset matrix interference signal projection space, overcoming the signal distortion caused by single-point background fluctuations. For the out-of-range control group The tests revealed the constraint effect of the system's physical boundaries. When the pH value dropped to 3.0, the high concentration of protons neutralized the citrate electrostatic repulsion layer on the surface of the gold nanoparticles, causing irreversible aggregation of the blank system without bound dimethoate molecules, resulting in an abnormal change in the overall transmittance of the system. When the pH value rose to 6.5, the oxidative condensation reaction of o-phenylenediamine was thermodynamically inhibited and attenuated, and the extracted characteristic absorbance component value dropped below the instrument detection limit. The above cross-gradient experimental data confirm that the multidimensional spectral array projection decoupling operation can directly strip away the optical interference of multidimensional non-specific matrix components within the pH working range that preserves the thermodynamic stability of the gold nanoparticles, and quantitatively extract the target molecule inhibition signal mixed in high background noise.

[0037] Example 3: In the initial deployment of a high-throughput field screening system for rice from multiple production areas, the system faced the challenge of unknown matrix interference feature space due to the significant differences in the proportions of endogenous polysaccharides and alkaloids among different rice varieties before performing on-site unknown sample detection. The system controller initiated the matrix background fingerprint library construction and matrix orthogonal matrix extraction procedure in offline mode, selected multiple blank rice samples that did not contain dimethoate but covered the preset production area classification, pulverized the rice samples to be tested, added acetonitrile solution for extraction and centrifugation, and purified the supernatant by passing it through a neutral alumina column. After evaporating the purified liquid to dryness, the residue was redissolved using acetic acid buffer solution to obtain blank rice extract. The blank rice extract was mixed with a nano-gold solution with simulated peroxidase activity at a preset volume ratio, and the system pH was adjusted. The H value was set to 4.0 to 5.5, and incubation was performed at 25°C to 40°C to allow matrix molecules in the blank rice extract to occupy the catalytically active sites on the surface of the gold nanoparticles. Then, o-phenylenediamine and hydrogen peroxide were added to the system. The residual activity on the gold nanoparticle surface induced the oxidation of o-phenylenediamine to generate 2,3-dioxyphenazine. A spectrophotometer was used to scan the system in the 400nm to 550nm band to obtain a multi-wavelength scan absorbance sequence composed of absorbance values ​​at multiple consecutive wavelengths. These multi-wavelength scan absorbance sequences were used as column vectors to construct a high-dimensional initial matrix spectral matrix. The processor calculated the covariance matrix of the initial matrix spectral matrix and performed eigenvalue decomposition on the covariance matrix to extract orthogonal eigenvectors corresponding to each eigenvalue.

[0038] The system sorts orthogonal eigenvectors in descending order of eigenvalues, extracts the leading principal component eigenvectors with a cumulative variance contribution rate of 99%, and concatenates the extracted principal component eigenvectors column-wise to generate a basis orthogonal matrix P representing the projection space of the matrix interference signal, which is then stored in the knowledge base. This calibration process extracts and transforms biological matrix background interference into orthogonal basis vectors of finite dimension, establishing a quantifiable reference benchmark for projection stripping of non-specific absorbance deviations in the real-time detection stage, eliminating blind spots in model building within the underlying logic of the algorithm, and performing offline calibration. Fifty rice samples free of dimethoate residues were collected, including northern japonica rice and southern indica rice. Multi-wavelength scan absorbance sequences of each sample were obtained to construct an initial matrix spectral matrix. The matrix covariance matrix was calculated, and eigenvalue decomposition was performed to extract the corresponding preceding principal component orthogonal eigenvectors. These eigenvectors were then concatenated column-wise, and the cumulative variance contribution rate reached 99%. The resulting orthogonal matrix P, representing the projection space of the matrix interference signal, was used in the projection stripping operation during real-time detection. The characteristic absorbance component M, representing the specific inhibitory strength of dimethoate molecules, was calculated according to the formula... Where V is the multi-wavelength scan absorbance sequence of the sample to be tested, and P is the basis orthogonal matrix. Let P be the transpose of the basis orthogonal matrix. Using the vector Euclidean norm, the calculation process removes the absorbance deviation characteristics caused by matrix effects, and extracts the target molecule suppression signal mixed in high background noise.

[0039] Example 4: In the case of on-site pre-calibration of the target detection equipment, the system initiates the offline calibration process of the standard calibration curve, selects a series of dimethoate standard solutions with an arithmetic gradient, and injects each gradient standard solution into a constant matrix blank extract to construct the corresponding standard test system. Then, nano-gold solution with simulated peroxidase activity, o-phenylenediamine, and hydrogen peroxide are added to each standard test system in sequence. After maintaining a constant ambient temperature and incubating for a preset time, the spectrophotometer is driven to collect the transmitted light signal of each concentration gradient system one by one, and obtain the corresponding multi-wavelength scanning absorbance sequence. Through controlled concentration gradient traversal operation, reference multidimensional optical data covering the full range response interval is obtained.

[0040] The system processor receives multiple sets of multi-wavelength scan absorbance sequences, retrieves the pre-stored basis orthogonal matrix characterizing the projection space of matrix interference signals, and sequentially calculates the background projection component of the absorbance sequence corresponding to each concentration gradient in that space, using the formula... The characteristic absorbance components after removing background interference are extracted, where M is the characteristic absorbance component value, V is the multi-wavelength scan absorbance sequence, and P is the basis orthogonal matrix. It is the transpose of a basis orthogonal matrix. The system performs Euclidean norm operations on vectors. Using the true concentration of the dimethoate standard solution as the independent variable and the corresponding characteristic absorbance component as the dependent variable, it fits a polynomial using the least squares method to generate a standard calibration curve. The model parameters are then stored in the system memory. To ensure analytical accuracy in the low concentration range, a second-order polynomial model is specifically used for fitting, establishing a mathematical mapping relationship between the characteristic absorbance component value and the dimethoate concentration within the range of 0.05 mg / kg to 5.0 mg / kg. The coefficients of the second-order term, the first-order term, and the constant offset term of the fitting equation are determined through regression calculations on eight concentration gradient standard points, requiring the absolute value of the linear correlation coefficient to be greater than 0.999. This directly maps the abstract optical characteristic modulus value to a mass concentration result in mg / kg. This pre-calibration process establishes the mathematical mapping relationship between the optical absorption characteristic modulus value and the target pesticide concentration, providing a quantitative basis for concentration inversion calculations during the real-time detection stage.

[0041] Example 5: In a deployment scenario for high-throughput continuous on-site detection, the diurnal fluctuations in ambient temperature induce irregular drift in the dark current of the spectrophotometer's photoelectric sensor. Simultaneously, the initial matrix turbidity of different batches of rice samples varies. The inherent detection parameter settings cause non-specific physical aggregation of gold nanoparticles in high-turbidity samples during the initial incubation period, thereby disrupting the optical linear response basis of the multi-wavelength scan absorbance sequence. Before loading the rice extract, the system controller initiates a pre-baseline calibration and dynamic mixing procedure, injecting a quantitative amount of acetate-sodium acetate buffer solution into the detection cell as a blank reference, driving the spectrophotometer to collect data from 400 nm to 5 nm. The background dark current absorbance sequence in the 50nm band is stored as a dynamic compensation vector to eliminate zero-point drift parameters introduced by the hardware system during subsequent acquisition of multi-wavelength scan absorbance sequences. The system extracts a quantitative amount of the rice extract to be tested and illuminates it with a 600nm wavelength probe light source to obtain the initial turbidity absorbance parameter characterizing the concentration of physical suspended matter. When the initial turbidity absorbance parameter exceeds the preset critical threshold for colloidal aggregation, the system reconstructs the mixing drive logic of the injection pump in real time based on the initial turbidity absorbance parameter, calculating the target mixing volume ratio of the gold nanoparticle solution to the rice extract. The quantitative determination logic of this target mixing volume ratio follows a formula. ;in, For the target mixing volume ratio, This is the volume adjustment slope coefficient. The initial turbidity absorbance parameters. The base volume ratio constant is the baseline state. Based on the calculated target mixing volume ratio, the system drives the fluid injection pipeline to mix the nano-gold solution with the rice extract to be tested in the correct amount, so that the total ablation in the high turbidity sample environment is maintained within the thermodynamic steady state range.

[0042] To address the differences in initial turbidity of rice extracts from different origins, dynamic ratio adjustments were implemented during the initial incubation period. The absorbance of the initial turbidity of the extracts was measured using a 600nm probe light source. According to the formula Set the mixing volume ratio of the gold nanoparticle solution and the extract. ,in For the target mixing volume ratio, This is the volume adjustment slope coefficient. The initial turbidity absorbance parameter is given. Using the baseline volume ratio constant as a reference, the injection pump drive parameters were adjusted to maintain the total absorptivity within the linear response range of the spectrophotometer under high-turbidity sample conditions. This suppressed non-specific physical aggregation caused by the intensified collisions of high-concentration endogenous macromolecules, thus constructing a stable detection environment. To address the differences in matrix loading of the extract caused by different rice varieties from different origins, when determining the packing dosage of the neutral alumina column, the system initiated a load balancing calibration procedure, selecting the packing mass of neutral alumina in 50mg increments. The average background absorbance deviation of the purified extract in the 400nm to 550nm wavelength range was monitored in real time. When the decrease rate of absorbance deviation caused by increasing the packing mass is less than 5%, the packing mass is determined to be the process saturation dose corresponding to the current sample to be tested. After the reaction system is mixed, it is transferred to the pH adjustment and incubation process. The colorimetric reaction is initiated by adding o-phenylenediamine and hydrogen peroxide so that the spectrophotometer can complete the acquisition of the target absorption signal. The aforementioned dynamic baseline calibration and feedback adjustment linkage mechanism transforms the physical temperature drift error of the spectrophotometer hardware and the initial matrix concentration difference of the biochemical liquid phase sample into a quantitative control compensation parameter, and outputs an anti-agglomeration control strategy independent of external environmental fluctuations and initial physical conditions.

[0043] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0044] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for colorimetric detection of dimethoate residues in rice based on the catalytic activity of gold nanoparticles, characterized in that, Includes the following steps Step 101: Remove the rotten parts from the rice sample to be tested, cut it into 1cm segments, weigh 20g of the sample and place it in a 50mL centrifuge tube, then add PBS solution (pH 7.4) and sonicate for 5min. After standing for 2min, the rice extract to be tested is obtained. Step 102: Prepare a nano-gold solution with simulated peroxidase activity. Mix the nano-gold solution with rice extract at a preset volume ratio and incubate at 30°C. This allows the dimethoate molecules in the rice extract to occupy the catalytic active sites on the nano-gold surface through their active functional groups, thereby constructing a colorimetric reaction system with limited catalytic ability. Step 103: Add pH 4.5 sodium acetate buffer to the system, then add a mixture of o-phenylenediamine and hydrogen peroxide to inhibit the catalytic activity of gold nanoparticles, thereby inhibiting the production of the yellow substance 2,3-dioxyphenazine in the detection system. Use a full-wavelength reader to measure the absorbance of the system after the reaction at a wavelength of 450 nm. Step 104: Retrieve the preset matrix background fingerprint spectral dataset, identify the non-specific absorbance interference features caused by endogenous polysaccharides, peptides and alkaloids in rice in the matrix background fingerprint spectral dataset, correlate and project the multi-wavelength scan absorbance sequence with the non-specific absorbance interference features, remove the absorbance deviation caused by matrix effect, and extract the characteristic absorbance component value that characterizes the specific inhibitory strength of dimethoate molecules. Step 105: Based on the characteristic absorbance component values, match the preset standard calibration curve to calculate and determine the residual amount of dimethoate in the rice sample to be tested.

2. The method for colorimetric detection of dimethoate residues in rice based on nano-gold catalytic activity according to claim 1, characterized in that, Step 104 specifically includes the following sub-steps: Step 401, project the multi-wavelength scan absorbance sequence onto the preset matrix interference signal projection space, calculate the background projection component of the multi-wavelength scan absorbance sequence in the space, and the background projection component characterizes the non-specific response caused by polysaccharides, peptides and alkaloids in the extract. Step 402: Subtract the background projection component from the absorbance sequence to obtain the target feature difference signal after removing background interference, and determine the magnitude of the target feature difference signal as the feature absorbance component value.

3. The method for colorimetric detection of dimethoate residues in rice based on nano-gold catalytic activity according to claim 1, characterized in that, In step 102, the steps for preparing the nano-gold solution include: stirring and heating a 1.0 mM chloroauric acid solution to boiling, and quickly adding a 38.8 mM trisodium citrate solution. After stirring and heating for 15 minutes, the heating is stopped. At this time, the solution color turns wine red and is cooled to room temperature. The above cooling solution is filtered through a 250 nm filter membrane and then placed in a brown reagent bottle and stored at 4°C in the dark.

4. The method for colorimetric detection of dimethoate residues in rice based on nano-gold catalytic activity according to claim 1, characterized in that, In step 102, the volume ratio of the nano-gold solution to the rice extract is 1:4, the temperature of the incubation environment is maintained at 30℃, and the incubation time is 10 min.

5. The method for colorimetric detection of dimethoate residues in rice based on nano-gold catalytic activity according to claim 1, characterized in that, In step 103, the characteristic absorbance value of the reaction system is measured at a wavelength of 450 nm.

6. The method for colorimetric detection of dimethoate residues in rice based on nano-gold catalytic activity according to claim 1, characterized in that, In step 103, the final concentration of o-phenylenediamine in the colorimetric reaction system is 20 mM, and the final concentration of hydrogen peroxide in the colorimetric reaction system is 400 mM.

7. The method for colorimetric detection of dimethoate residues in rice based on nano-gold catalytic activity according to claim 2, characterized in that, The calculation logic for the characteristic absorbance component value M follows the following formula: Where V is the multi-wavelength scan absorbance sequence, and P is the basis orthogonal matrix characterizing the projection space of the matrix interference signal. It is the transpose of a basis orthogonal matrix. This refers to the Euclidean norm operation for vectors.

8. The method for colorimetric detection of dimethoate residues in rice based on nano-gold catalytic activity according to claim 1, characterized in that, In step 101, ultrasonic extraction can significantly enhance the penetration and mass transfer of the extract, avoid the degradation of the target pesticide by high temperature, and achieve a higher recovery rate of the target pesticide, which can greatly shorten the pretreatment cycle.

9. The method for colorimetric detection of dimethoate residues in rice based on nano-gold catalytic activity according to claim 1, characterized in that, In step 102, the acetate buffer solution is a 10 mM acetate-sodium acetate buffer system.

10. The method for colorimetric detection of dimethoate residues in rice based on nano-gold catalytic activity according to claim 2, characterized in that, The matrix background fingerprint spectral dataset was pre-set in the following way: the absorbance response of a set of blank rice samples without dimethoate residue was measured, and the common optical features of the blank rice samples were identified and stored using the principal component extraction algorithm.

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