A malathion detection card two-dimensional code traceability batch parameter automatic matching method

Abstract

This invention relates to the field of food safety testing technology and discloses an automatic matching method for batch parameters of malathion test cards with QR code traceability. The method includes collecting the dual-matrix Lab color space values ​​of the QR code label paper and NC film in the test card, constructing an aging decay function relationship table and an initial coupling correlation matrix, and encoding an encrypted QR code. During testing, a single frame of original image is acquired to extract real-time chromaticity feature vectors of the dual-matrix region, and the aging feature modulus is calculated by combining it with the initial coupling correlation matrix. Based on the aging feature modulus, the aging decay function relationship table is queried to dynamically correct the initial standard curve parameters and generate a real-time standard curve, thereby outputting the malathion concentration. This invention constructs an intrinsic aging indication mechanism through dual-matrix chromaticity difference, achieving adaptive reconstruction of the standard curve according to the aging state of the test card, ensuring detection accuracy throughout the entire lifecycle.

Description

Technical Field

[0001] This invention relates to the field of food safety testing technology, and more specifically, to a method for automatically matching batch parameters for malathion test card QR code traceability. Background Technology

[0002] Currently, colloidal gold immunochromatography has become the mainstream method for rapid on-site screening of malathion due to its advantages such as simple operation, low cost, and no need for large instruments.

[0003] Chinese patent application CN116067936A discloses a colorimetric / SERS dual-mode batch detection method for malathion and its application. This technical solution utilizes the morphological characteristics of gold nanoparticles to modulate their photogenerated plasmon resonance absorption and resonance scattering, achieving rapid colorimetric screening by observing changes in solution color, and combining this with SERS activity changes for quantitative detection. While this method exhibits high sensitivity and stability in a laboratory environment, in practical field applications, especially for large-scale, decentralized testing needs, it places high demands on sample pretreatment and the testing environment. To achieve end-to-end product information tracking, Chinese patent application CN118886922A discloses a QR code-based product information traceability system. This system records detailed information such as the product's production process and raw material sources using QR code technology, and combines this with encryption algorithms to prevent data tampering, greatly improving traceability efficiency and consumer trust. This technology provides a reference for the information management of testing cards, but most current traceability systems only focus on recording and querying static identity information, failing to fully explore the potential of QR codes in carrying dynamic product performance parameters.

[0004] In existing rapid malathion test strip applications, quantitative distortion is commonly caused by uncontrollable storage environments. When test strips are stored under high temperature and humidity or prolonged suboptimal conditions, their nitrocellulose membranes (NC membranes) exhibit nonspecific yellowing, and colloidal gold particles may slightly aggregate, leading to a darker background and decreased sensitivity. Existing batch matching technologies typically rely solely on QR codes to retrieve factory-fixed standard curves, based on the flawed assumption that the biochemical performance of the test strip remains constant throughout its shelf life. In reality, the immunological activity of antigens and antibodies, as well as the optical properties of materials, undergo nonlinear dynamic decay with the accumulation of "time-temperature integrals." This mismatch between static parameters and dynamic aging is the core reason for false negatives or quantitative deviations in test results. Current technologies lack a mechanism to quantify the current aging level of a single test strip in situ and in real time without increasing the cost of additional chemical indicators or electronic tags. Because of the lack of such an "in-situ self-indicating" reference, the detection system cannot distinguish whether the weakening of the measured signal is caused by low sample concentration or by the aging and failure of the reagent card itself. As a result, the accuracy of rapid on-site detection is severely compromised during terminal storage and circulation, making it difficult to guarantee the reliability of quantitative results. Summary of the Invention

[0005] To overcome the aforementioned shortcomings of existing technologies, this invention provides a method for automatically matching batch parameters for malathion test kits using QR code traceability. By printing an encrypted traceability QR code containing dual-matrix aging characteristics on the test kit, the aging degree of the test kit due to storage environment can be detected in real time using a mobile phone or portable detector, and the standard curve parameters can be automatically corrected. This method effectively solves the quantitative error problem caused by the decline in shelf life of traditional test kits, achieving dynamic and accurate quantification with a "one card, one policy" approach, and significantly improving the accuracy and reliability of on-site food safety testing.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for automatically matching batch parameters for malathion test card QR code traceability, including:

[0008] Lab color space values ​​of the dual-matrix region in the malathion rapid test card were collected, initial standard curve parameters were measured, an aging decay function relationship table and an initial coupling correlation matrix were constructed, an encrypted traceability QR code matrix was generated, and the encrypted traceability QR code matrix was printed on the surface of the malathion rapid test card; the dual-matrix region refers to the QR code label paper substrate region and the NC film blank background region.

[0009] A single-frame original image containing an encrypted traceability QR code matrix and a blank background area of ​​the NC film is acquired. The single-frame original image is processed to extract the real-time chromaticity feature vector of the dual matrix region.

[0010] The aging characteristic modulus is obtained based on the initial coupling correlation matrix and the real-time chromaticity feature vector of the dual matrix region. The initial standard curve parameters are corrected based on the relationship table between the aging characteristic modulus and the aging decay function to generate a real-time standard curve. The real-time malathion concentration value is output based on the real-time standard curve.

[0011] The method for constructing the aging decay function relationship table includes:

[0012] Accelerated aging tests were conducted on the same batch of malathion rapid test cards. The Lab color space values ​​of the QR code label paper substrate area and the Lab color space values ​​of the NC film blank background area were collected at each aging time point, and the dual matrix color difference modulus at each aging time point was calculated.

[0013] The sensitivity attenuation coefficient and noise floor rise compensation value at each aging time point are calculated. The nonlinear mapping relationship between the dual matrix chromaticity difference modulus, sensitivity attenuation coefficient, and noise floor rise compensation value is fitted to generate an aging attenuation function relationship table.

[0014] The method for constructing the initial coupling correlation matrix includes:

[0015] At the time of manufacture of the malathion rapid test card, the initial chromaticity feature vectors of the QR code label paper substrate area and the initial chromaticity feature vectors of the NC film blank background area are measured. The initial chromaticity feature vectors of the QR code label paper substrate area and the initial chromaticity feature vectors of the NC film blank background area are combined to construct an initial coupling correlation matrix.

[0016] The method for generating the encrypted traceability QR code matrix includes:

[0017] The aging decay function relationship table, the initial coupling correlation matrix and the initial standard curve parameters are encrypted and encoded to generate a binary data stream, and the binary data stream is rendered into an encrypted traceability QR code matrix.

[0018] The method for processing a single-frame original image and extracting the real-time chromaticity feature vector of the dual-matrix region includes:

[0019] Geometric correction and homomorphic filtering illumination compensation are performed on a single frame of the original image to generate an illumination homogenized image. Real-time chromaticity feature vectors of the dual-matrix region are extracted from the illumination homogenized image.

[0020] The method for performing geometric correction includes:

[0021] The positioning detection pattern in the encrypted traceability QR code matrix is ​​identified from a single frame of the original image. The perspective transformation matrix is ​​calculated based on the coordinate distortion of the positioning detection pattern in the single frame of the original image. The perspective transformation matrix is ​​then applied to spatially map the single frame of the original image to generate an orthophoto image.

[0022] The method for performing homomorphic filtering illumination compensation includes:

[0023] The orthophoto image is converted to the logarithmic domain. In the logarithmic domain, a high-pass filter is used to separate and suppress the incident light component and enhance the reflectivity component. After exponential transformation, the image is restored to generate a uniformly illuminated image.

[0024] The method for extracting real-time chromaticity feature vectors of dual-matrix regions from an illumination homogenized image includes:

[0025] In the image with uniform illumination, locate the QR code label paper substrate area and the NC film blank background area, calculate the average value of the Lab color space of all pixels in the QR code label paper substrate area and the NC film blank background area respectively, and generate the real-time chromaticity feature vector of the QR code label paper substrate area and the real-time chromaticity feature vector of the NC film blank background area.

[0026] The method for obtaining the aging characteristic modulus includes:

[0027] The aging drift vector of the QR code label paper substrate area is obtained by subtracting the real-time chromaticity feature vector of the QR code label paper substrate area from the initial chromaticity feature vector of the QR code label paper substrate area in the initial coupling correlation matrix; the aging drift vector of the NC film blank background area is obtained by subtracting the real-time chromaticity feature vector of the NC film blank background area from the initial coupling correlation matrix.

[0028] The aging drift vector of the blank background area of ​​the NC film and the aging drift vector of the QR code label paper substrate area are subjected to vector difference operation to construct the dual matrix differential aging drift vector; the Euclidean distance of the dual matrix differential aging drift vector in the Lab color space is calculated to obtain the aging characteristic modulus.

[0029] The initial standard curve parameters include the standard curve slope term and the standard curve intercept term at the time of factory delivery;

[0030] The method for correcting the initial standard curve parameters includes:

[0031] Substitute the aging characteristic modulus into the aging decay function relationship table for interpolation indexing, find the corresponding sensitivity decay coefficient and noise floor rise compensation value, and define them as the mapped sensitivity decay coefficient and the mapped noise floor rise compensation value; use the mapped sensitivity decay coefficient to scale and correct the slope term of the standard curve at the time of factory delivery, and use the mapped noise floor rise compensation value to offset and correct the intercept term of the standard curve at the time of factory delivery.

[0032] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0033] This invention establishes an intrinsic in-situ self-indicating mechanism for aging degree by constructing an encrypted traceability QR code matrix containing initial chromaticity and aging models of the dual-matrix system. This mechanism leverages the material differences in the thermal history response of the test card's components (QR code label paper and NC film). The method quantifies the invisible influence of the storage environment into a visualized dual-matrix chromaticity difference signal. By calculating the aging characteristic modulus between the real-time chromaticity feature vector and the initial coupling correlation matrix, it accurately characterizes the cumulative thermal history and physicochemical performance degradation experienced by the test card. Based on this, the system can perform reverse compensation and dynamic reconstruction of the initial standard curve parameters at the time of manufacture according to the measured aging state, generating a real-time standard curve adapted to the performance state at the current testing moment. This "one card, one policy" parameter adaptive matching strategy effectively solves the technical problem that traditional static calibration methods cannot correct for reagent activity degradation and background signal drift caused by uncontrolled storage. Without requiring additional chemical indicators or environmental sensors, it ensures the robustness and accuracy of quantitative detection results throughout the entire lifecycle of the test card. Attached Figure Description

[0034] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 This is a flowchart of a method for automatically matching batch parameters for malathion test card QR code traceability provided in an embodiment of the present invention;

[0036] Figure 2 This is a schematic diagram of the malathion rapid detection card provided in an embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram of the dual-matrix chromaticity change trajectory provided in an embodiment of the present invention;

[0038] Figure 4 A flowchart illustrating the principle of generating real-time standard curves provided in this embodiment of the invention;

[0039] Figure 5 This is a functional module diagram of an automatic batch parameter matching system for malathion detection card QR code traceability provided in an embodiment of the present invention. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, 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 are within the scope of protection of the present invention.

[0041] Example 1

[0042] Please see Figure 1 As shown, this embodiment provides a method for automatically matching batch parameters for malathion test card QR code traceability, including:

[0043] Step S10: Collect the Lab color space values ​​of the dual-matrix region in the malathion rapid test card, determine the initial standard curve parameters, construct the aging decay function relationship table and the initial coupling correlation matrix, fuse the aging decay function relationship table, the initial coupling correlation matrix and the initial standard curve parameters to generate an encrypted traceability QR code matrix, and print the encrypted traceability QR code matrix on the surface of the malathion rapid test card; the dual-matrix region refers to the QR code label paper substrate region and the NC film blank background region;

[0044] Specifically, the malathion rapid test card is a biochemical detection device based on the principles of colloidal gold or fluorescence immunochromatography. Its core components include a nitrocellulose membrane (NC membrane), a colloidal gold-labeled antibody pad, a sample pad, an absorbent pad, and a plastic casing. See also... Figure 2 This is a schematic diagram of the malathion rapid test card provided in this application embodiment, showing the distribution of the sample pad, colloidal gold-labeled antibody pad, nitrocellulose membrane (NC membrane), absorbent pad, and encrypted traceability QR code matrix on the malathion rapid test card. The components are arranged sequentially along the fluid chromatography direction, with the detection zone T-line and control zone C-line spaced apart on the nitrocellulose membrane (NC membrane), and the encrypted traceability QR code matrix located at one end of the card. The NC membrane, as the reaction matrix, carries the sites where the antigen-antibody reaction occurs. Specific capture antibodies are immobilized on its surface. When malathion in the sample binds to the colloidal gold-labeled antibody and flows through the NC membrane, it will... Figure 2The detection area (T-line) shown forms a visible colorimetric band, and the colorimetric intensity is negatively correlated with the malathion concentration. The dual-matrix region refers to two specific areas on the malathion rapid test card with different material properties and exhibiting differentiated colorimetric change trajectories during aging: the QR code label paper substrate area is composed of cellulose paper or polymer sticker, serving as... Figure 2 The physical carrier of the encrypted traceability QR code matrix shown in the diagram undergoes an aging process primarily characterized by yellowing due to the slow oxidative degradation of cellulose molecular chains. The blank background area of ​​the NC membrane refers to the background area on the NC membrane where no antibodies are fixed (i.e., the undistributed detection area T-line and quality control area C-line). Its aging process involves not only the rapid oxidative yellowing of the nitrocellulose substrate but also the slight aggregation of colloidal gold particles due to changes in the storage environment, resulting in a hue shift from burgundy to purple. The Lab color space is a device-independent color representation system defined by the International Commission on Illumination (ICI). The L-axis represents luminance, the a-axis represents red-green hue, and the b-axis represents yellow-blue hue. Using the Lab color space for colorimetric characterization can convert color differences perceived by the human eye into quantifiable Euclidean distances, providing a mathematical basis for the aging drift calculation in subsequent step S30.

[0045] The initial standard curve parameters refer to the mathematical mapping relationship between the colorimetric intensity and the malathion concentration obtained by calibration with gradient concentration standard solutions at the time of manufacture of the malathion rapid test card. When a linear equation is used for fitting, the initial standard curve parameters include a slope term and an intercept term, where the slope term reflects the detection sensitivity and the intercept term reflects the background signal intensity. When a four-parameter logical equation is used for fitting, the initial standard curve parameters include the lower asymptote parameter, the slope factor parameter, the inflection point concentration parameter, and the upper asymptote parameter. The lower asymptote parameter reflects the colorimetric intensity limit in the high concentration region, the upper asymptote parameter reflects the background colorimetric intensity at zero concentration, the slope factor parameter reflects the steepness of the standard curve at the inflection point, i.e., the detection sensitivity, and the inflection point concentration parameter reflects the malathion concentration corresponding to the colorimetric intensity reaching the midpoint value of the upper and lower asymptotes. The aging degradation function relationship table is a data mapping table established through accelerated aging experiments. It records the nonlinear correspondence between the modulus of chromaticity difference between the two matrices, the sensitivity attenuation coefficient, and the noise floor increase compensation value. This allows subsequent detection devices to inversely deduce the performance degradation degree of the current malathion rapid test card based on the measured chromaticity drift. The encrypted traceability QR code matrix is ​​a two-dimensional graphic code carrying the aging degradation function relationship table, the initial coupling correlation matrix, and the initial standard curve parameters. After encryption and encoding, it is printed on the surface of the malathion rapid test card, enabling each card to carry its own unique biochemical parameters and aging prediction model.

[0046] Step S10 systematically collects initial chromaticity data of the dual-matrix region at the production end and establishes a quantitative mapping relationship between chromaticity change and performance degradation by combining accelerated aging experiments. These multi-dimensional biochemical parameters are encoded into a QR code in encrypted form, so that each malathion rapid test card carries its own "factory fingerprint data" and "aging prediction model" when it leaves the factory. This technology differs from the existing technology that only stores static identification information such as batch number in QR codes, and breaks through by incorporating dynamic variables of time and material aging into the information carrying scope of QR codes. Since there is an essential difference in material composition between the QR code label paper substrate area and the NC film blank background area, the QR code label paper substrate area is mainly composed of cellulose or polymer, while the NC film blank background area is mainly composed of nitrocellulose and contains residual colloidal gold particles. The two matrices exhibit significant "anisotropy" characteristics in response to the same thermal history. That is, under the same storage conditions, the chromaticity change rate of the NC film blank background area is much faster than that of the QR code label paper substrate area. This differential aging characteristic provides a physical basis for constructing an "endogenous time-temperature indicator". By accurately recording the initial colorimetric state of the two matrices at the time of manufacture, the subsequent testing end can compare the measured colorimetric value with the initial value. The difference in aging rates between the two matrices can be used to accurately quantify the cumulative thermal history experienced by the malathion rapid test card, without relying on external temperature sensors or electronic recording devices. Step S10 completely encapsulates the batch-specific data and aging prediction model from the production end into an encrypted traceability QR code matrix. This allows the subsequent testing end to obtain all the information required for dynamic calibration simply by scanning the QR code printed on the surface of the malathion rapid test card, eliminating the risk of batch parameter mismatch due to human error in traditional operating procedures and achieving closed-loop parameter transfer from the production end to the testing end.

[0047] Further, step S10 includes:

[0048] Step S11: Accelerated aging test is conducted on the same batch of malathion rapid test cards. At each aging time point, the Lab color space values ​​of the QR code label paper substrate area and the Lab color space values ​​of the NC film blank background area are collected respectively. The dual matrix chromaticity difference modulus at each aging time point is calculated. The sensitivity attenuation coefficient and background noise increase compensation value at each aging time point are calculated. The nonlinear mapping relationship between the dual matrix chromaticity difference modulus, the sensitivity attenuation coefficient and the background noise increase compensation value is fitted to generate an aging attenuation function relationship table.

[0049] Specifically, accelerated aging testing is a standardized testing method that simulates the long-term aging process of malathion rapid test cards under natural storage conditions by artificially increasing ambient temperature and humidity. According to the exponential relationship between temperature and chemical reaction rate described by the Arrhenius equation, the oxidative degradation rate of the material accelerates exponentially with each increase in temperature. Therefore, aging effects equivalent to a longer storage time under natural conditions can be obtained in a shorter experimental period. Selecting malathion rapid test cards from the same batch of production as the sample set is to eliminate individual differences caused by factors such as raw material sources and fluctuations in production process parameters between different production batches, ensuring that the aging degradation function table accurately reflects the aging pattern of that specific batch of products. The sample set is placed in an environmental test chamber where temperature and humidity can be precisely controlled, and gradient temperature and humidity conditions are set. For example, the temperature gradient can be set to three levels: room temperature, medium temperature, and high temperature; the humidity can be set to two levels: normal humidity and high humidity, according to the product storage specifications. Different temperature and humidity combinations simulate various storage scenarios that the product may encounter. See also... Figure 3 This is a schematic diagram of the dual-matrix chromaticity change trajectory provided in the embodiments of this application. Figure 3 A coordinate system was established with storage time as the horizontal axis and color change as the vertical axis, illustrating the differentiated color change trends in different matrix areas on the malathion rapid test card as storage time progresses. The color change trajectory lines included in this schematic diagram all start from the manufacturing time.

[0050] At each preset aging time point, the Lab color space values ​​of the QR code label paper substrate area and the NC film blank background area on the malathion rapid test card were measured using a standard photometer. The Lab color space values ​​include the L-axis (L value), the a-axis (a value), and the b-axis (b value). The L-value represents luminance, the a-value represents red-green hue, and the b-value represents yellow-blue hue. A standard photometer is a professional instrument for accurately measuring the color parameters of an object's surface under standard light source illumination. The standard light source typically uses a D65 illuminator to simulate sunlight conditions, ensuring the comparability and repeatability of the measurement results. The color change trajectory of the QR code label paper substrate area is shown below. Figure 3 As indicated by the dashed line marked "slow aging," the typical behavior is as follows: with prolonged aging, the L value slowly decreases, indicating a slight reduction in brightness, while the b value slowly increases, indicating a shift towards yellow. This is a macroscopic manifestation of the oxidative degradation of cellulose molecular chains under thermo-oxidative conditions, producing chromophores. The color change trajectory of the blank background area of ​​the NC membrane is as follows... Figure 3 The solid line marked "rapid aging" indicates the following: a significant decrease in L value indicates a marked reduction in brightness; a rapid increase in b value indicates a rapid shift towards yellow; and a possible change in a value indicates a hue shift from burgundy to purple due to the aggregation of colloidal gold particles. The longitudinal distance of the chromaticity change trajectory in the dual-matrix region at the same storage time point constitutes... Figure 3 The chromaticity difference values ​​shown indicate that the rate of chromaticity change in the blank background area of ​​the NC film is much faster than that in the QR code label paper substrate area. This is because nitrocellulose has higher chemical activity and a faster rate of oxidative degradation compared to ordinary cellulose, and the residual colloidal gold particles are prone to condensation changes under thermal conditions.

[0051] The calculation of sensitivity attenuation coefficient and noise floor rise compensation value requires simultaneous performance calibration testing. At the time of manufacture and at various aging time points, the malathion rapid test card is calibrated using malathion standard solutions of varying concentrations. For example, the concentration gradient can be set to four levels: zero, low, medium, and high concentration, covering the linear detection range of the malathion rapid test card. The colorimetric intensity of the detection area (T-line) of the malathion rapid test card at each concentration is measured; the colorimetric intensity can be quantified using grayscale values ​​or reflectance. When using linear regression to fit the functional relationship between color intensity and malathion concentration, the slope and intercept terms of the standard curve at the manufacturing time and each aging time point are obtained. The slope term reflects the magnitude of the color intensity change caused by a unit concentration change, i.e., the detection sensitivity, while the intercept term reflects the background color intensity at zero concentration, i.e., the background noise level. When using a four-parameter logistic regression method to fit the functional relationship between color intensity and malathion concentration, the lower asymptote parameter, slope factor parameter, inflection point concentration parameter, and upper asymptote parameter at the manufacturing time and each aging time point are obtained. The slope factor parameter reflects the detection sensitivity, and the upper asymptote parameter reflects the background noise level. The initial standard curve parameters at the manufacturing time serve as the benchmark for subsequent dynamic correction. For the linear regression method, the slope term S of the standard curve at each aging time point is... t The sensitivity attenuation coefficient K at each aging time point is obtained by comparing the slope term S0 of the standard curve at the factory time with the value of the slope term S0. t This coefficient reflects the degree to which the sensitivity of the malathion rapid detection card is retained relative to its factory state after aging. The value ranges from 0 to 1; a value closer to 1 indicates better sensitivity retention, while a value closer to 0 indicates more severe sensitivity degradation. t represents the pre-set aging time points in the accelerated aging experiment. The intercept term I of the standard curve at each aging time point is... t The difference between the intercept term I0 of the standard curve at the factory time and the value at the time of manufacture is used to obtain the noise floor rise compensation value C at each aging time point. t This compensation value reflects the rise in background signal caused by aging, and is used in subsequent step S33 to correct the standard curve intercept term to eliminate the influence of background noise drift on the quantitative results. For the four-parameter logistic regression method, the slope factor parameter at each aging time point is compared with the slope factor parameter B0 at the factory delivery time to obtain the sensitivity attenuation coefficient K at each aging time point. tThe difference between the upper asymptote parameters at each aging time point and the upper asymptote parameter A0 at the factory delivery time is used to obtain the noise floor rise compensation value C at each aging time point. t .

[0052] Calculating the chromaticity difference modulus between two matrices requires vector operations on the Lab color space values ​​of the QR code label paper substrate area and the blank background area of ​​the NC film at the same aging time point. Let the Lab color space value of the QR code label paper substrate area at a certain aging time point be a vector V. paper(t) The Lab color space value of the blank background area of ​​the NC film is vector V. mem(t) Calculate the vector difference Δ between the two. t =V mem(t) -V paper(t) The vector difference at the factory time is defined as Δ0=V mem(0)- V paper(0) V mem(0) V represents the Lab color space value of the blank background area of ​​the NC film at the time of manufacture. paper(0) The Lab color space value of the QR code label paper substrate area at the time of manufacture is used to calculate Δ. t The change relative to Δ0 is Δ t -Δ0 is used to obtain the aging drift vector. Finally, the Euclidean distance of the aging drift vector in the Lab color space is calculated as the dual-matrix chromaticity difference modulus. The dual-matrix chromaticity difference modulus is calculated using a differential method because: if only the chromaticity change of a single matrix is ​​measured, it is difficult to distinguish whether the change is caused by material aging or by changes in ambient light. However, using the dual-matrix differential method, when the ambient light changes, the chromaticity values ​​of the two matrices will change in the same direction and with the same amplitude. The differential operation can cancel out this "common-mode interference" and retain only the "differential-mode signal" caused by the difference in the aging rates of the two matrices, thereby accurately extracting the characteristic quantity representing the cumulative effect of thermal history.

[0053] Since the aging process of materials typically exhibits nonlinear characteristics, with a rapid initial aging rate followed by a gradual decrease, a nonlinear mapping relationship is established between the dual-matrix chromaticity difference modulus, the sensitivity attenuation coefficient, and the noise floor increase compensation value. Mathematical methods such as polynomial fitting, piecewise linear interpolation, or spline interpolation are used to approximate discrete data points, generating an aging attenuation function relationship table. This table can be stored in a lookup table format, with the independent variable being the discrete values ​​of the dual-matrix chromaticity difference modulus and the dependent variables being the corresponding sensitivity attenuation coefficient and noise floor increase compensation value. In subsequent step S33, the table can be quickly queried using an interpolation index. Step S11 transforms the invisible "time-temperature integral" thermal history into visualized "chromaticity difference" data, establishing a quantitative bridge between physical aging phenomena and chemical activity decay. Accelerated aging experiments are used to pre-obtain aging patterns at the production end, allowing subsequent testing to predict the performance degradation corresponding to different aging degrees without waiting for the natural aging process, thus achieving proactive deployment of aging prediction capabilities. The dual-matrix differential measurement method utilizes the anisotropic characteristics of the responses of two materials to the same thermal history, simplifying the complex multi-factor aging process into a single chromaticity difference modulus index, thus reducing the computational complexity of subsequent detection. The aging decay function relationship table stores the mapping relationship in a discretized format, balancing data storage capacity and query accuracy, making it suitable for encoding into QR code data carriers with limited capacity.

[0054] Step S12: At the time of manufacture of the malathion rapid test card, the initial chromaticity feature vector of the QR code label paper substrate area and the initial chromaticity feature vector of the NC film blank background area are measured. The initial chromaticity feature vector of the QR code label paper substrate area and the initial chromaticity feature vector of the NC film blank background area are combined to construct the initial coupling correlation matrix.

[0055] Specifically, the manufacturing time T0 refers to the specific point in time when the malathion rapid test card has completed all production and assembly processes and is about to enter the packaging and storage stage. At this time, the malathion rapid test card has not yet undergone any storage aging process, and its material state and biochemical activity are at their optimal levels. Initial colorimetric measurements are chosen at T0 rather than at an earlier semi-finished product stage because only after the malathion rapid test card has been fully assembled can the relative positional relationship between the QR code label paper substrate area and the NC film blank background area be finally determined, and the initial colorimetric states of the two substrates in the same microenvironment can be recorded synchronously, providing a spatial reference for subsequent simultaneous acquisition at the testing end. The Lab color space values ​​of the QR code label paper substrate area on the malathion rapid test card at the manufacturing time are collected and defined as the initial colorimetric feature vector of the QR code label paper substrate area. The Lab color space values ​​of the NC film blank background area on the malathion rapid test card at the manufacturing time are also collected and defined as the initial colorimetric feature vector of the NC film blank background area. The initial colorimetric feature vector V of the QR code label paper substrate area... paper(0)It is a three-dimensional vector whose three components are the L value, a value, and b value of the QR code label paper substrate area at the time of manufacture, denoted as V. paper(0) =(L p0 ,a p0 ,b p0 ), where L p0 This refers to the lightness component value of the QR code label paper substrate area in the CIE Lab color space at the time of manufacture, reflecting the brightness and darkness of the paper substrate surface; a p0 This refers to the red and green hue components of the QR code label paper substrate area in the CIE Lab color space at the time of manufacture. Positive values ​​indicate a reddish tint, and negative values ​​indicate a greenish tint. p0 This represents the yellow-blue hue component value of the QR code label paper substrate area in the CIE Lab color space at the time of manufacture. Positive values ​​indicate a yellowish tint, and negative values ​​indicate a bluish tint. The initial chromaticity feature vector V for the blank background area of ​​the NC film. mem(0) Similarly, it is a three-dimensional vector, whose three components are the L value, a value, and b value of the blank background region of the NC film at the time of manufacture, denoted as V. mem(0) =(L m0 ,a m0 ,b m0 ), where L m0 This represents the lightness component value of the blank background area of ​​the NC film in the CIE Lab color space at the time of manufacture, reflecting the brightness and darkness of the NC film surface; a m0 b represents the red and green hue components of the blank background area of ​​the NC film at the time of manufacture in the CIE Lab color space. Positive values ​​indicate a reddish tint, and negative values ​​indicate a greenish tint. m0 This represents the yellow-blue hue component value of the blank background area of ​​the NC film in the CIE Lab color space at the time of manufacture. Positive values ​​indicate a yellowish tint, and negative values ​​indicate a bluish tint. For example, the initial chromaticity feature vector of a typical QR code label paper substrate area may exhibit high brightness and near-neutral gray characteristics, i.e., a high L value, an a value close to zero, and a b value close to zero or slightly yellowish. The initial chromaticity feature vector of a typical blank background area of ​​the NC film may exhibit medium-high brightness and slightly reddish-yellow characteristics, i.e., a medium L value, a slightly positive a value, and a slightly positive b value. This is because the NC film itself is milky white and may contain a small amount of residual colloidal gold particles, giving it a pale wine-red hue.

[0056] The initial coupling correlation matrix M0 is constructed by taking the initial chromaticity feature vector V of the QR code label paper substrate region. paper(0) The initial chromaticity feature vector V of the blank background region of the NC film mem(0) Structured data formed by combining elements. Matrix M0 can be stored in a two-row, three-column format, where the first row stores V. paper(0) The three components (L) p0 ,a p0 ,b p0The second line stores V. mem(0) The three components (L) m0 ,a m0 ,b m0 Alternatively, it can be linearly stored in a six-tuple format as (L p0 ,a p0 ,b p0 ,L m0 ,a m0 ,b m0 The advantages of using matrix format for storage are: the matrix structure can clearly express the correspondence between the two matrices, which facilitates vector subtraction operations on the corresponding components in the subsequent step S31; the matrix format has good scalability, and if more matrix regions or more color channels need to be introduced in the future, only the matrix dimensions need to be expanded without changing the data processing logic.

[0057] Since different batches of malathion rapid test cards may use raw materials from different sources, the paper whiteness of the QR code label substrate area and the background color of the NC film blank background area may vary between batches. If a theoretical value is directly used as the initial benchmark, the deviation between the theoretical value and the actual value will be misjudged as aging drift, leading to systematic errors in the calculation of the aging characteristic modulus in subsequent step S32. However, step S12, by measuring the actual initial colorimetric value of each batch of products, "zeros" the unique material background characteristics of that batch, ensuring that the colorimetric changes observed at the subsequent testing end fully reflect the real drift caused by storage aging, eliminating the interference of batch-to-batch material differences on aging assessment. The initial coupling correlation matrix M0 is encoded into the encrypted traceability QR code matrix in step S13, enabling the batch-specific initial colorimetric information to be transferred to the testing site along with the malathion rapid test card.

[0058] Step S13: Encrypt the aging decay function relationship table, the initial coupling correlation matrix and the initial standard curve parameters to generate a binary data stream. Render the binary data stream into an encrypted traceability QR code matrix and print the encrypted traceability QR code matrix on the malathion rapid detection card at the observation window adjacent to the blank background area of ​​the NC membrane.

[0059] Specifically, the process of encrypting and encoding the aging attenuation function relation table, the initial coupling correlation matrix M0, and the initial standard curve parameters to generate a binary data stream involves three links: data serialization, data compression, and data encryption. Data serialization is the process of converting various different types of data structures into a byte sequence of a unified format. The aging attenuation function relation table is a discrete mapping table structure, the initial coupling correlation matrix M0 is a numerical matrix structure, and the initial standard curve parameters are equation parameter structures. The three need to be converted into a continuous binary byte stream according to the predefined field order and data type. Data compression uses a lossless compression algorithm to streamline the volume of the serialized byte stream. Since there is an upper limit to the data capacity of the two-dimensional code, compression processing can carry more valid information within a limited symbol space while ensuring the complete restoration of information. Data encryption uses a symmetric encryption or asymmetric encryption algorithm to securely process the compressed byte stream, preventing the two-dimensional code information from being interpreted or tampered with by unauthorized parties, protecting the core technical parameters of the manufacturer from being obtained reversely, and ensuring that the data read by the detection end has not been maliciously modified.

[0060] The process of rendering the binary data stream into an encrypted traceability two-dimensional code matrix follows the two-dimensional code encoding standard. Exemplarily, international common two-dimensional code standards such as QR Code or Data Matrix can be adopted. The two-dimensional code encoding process includes steps such as data analysis, error correction encoding, masking processing, and matrix generation: Data analysis determines the optimal encoding mode to improve data storage efficiency; Error correction encoding uses the Reed-Solomon error correction algorithm to add redundant check symbols to the data, enabling the two-dimensional code to be correctly decoded even in the case of partial smudging or occlusion. The high fault tolerance error correction level can adapt to the wear and pollution scenarios that the malathion rapid detection card may encounter during actual use; Masking processing applies a specific masking pattern to the two-dimensional code matrix to optimize the distribution uniformity of light and dark modules and improve the success rate of scanning and recognition; Matrix generation fills the final data codewords and error correction codewords into the data area of the two-dimensional code, and adds positioning detection patterns, timing patterns, and format information areas to form a complete encrypted traceability two-dimensional code matrix pattern. The positioning detection pattern is a "square inside a square" pattern located at the three corners of the two-dimensional code, which is used to identify the boundary of the two-dimensional code and determine the coordinate system direction in step S21, providing a reference anchor point for geometric correction.

[0061] The encrypted traceability QR code matrix is ​​printed on the malathion rapid test card, adjacent to the observation window of the blank background area of ​​the NC film. This close proximity ensures that the QR code label substrate area and the NC film blank background area are within the same field of view of the detector's camera. In step S21, when acquiring a single frame of the original image, both areas can be captured simultaneously, avoiding measurement errors caused by changes in lighting conditions over time when acquiring two separate frames. This close proximity also ensures that the QR code label substrate area and the NC film blank background area are in the same ambient light field. In step S22, when performing homomorphic filtering for lighting compensation, both areas are affected by the same light component, and the differential operation can effectively cancel common-mode lighting interference. The printing position is chosen near the observation window, rather than on the edge or back of the malathion rapid test card, to ensure that the QR code and the NC film experience identical microenvironmental conditions during storage, including local temperature, humidity, and gas atmosphere. This ensures a high degree of synchronization in the aging process of the QR code label substrate area and the NC film blank background area, so that the color difference between the two matrices only reflects the inherent difference in the aging rates of the two materials, rather than local differences in environmental conditions.

[0062] Step S13 completes the solidification and transfer of production-end data to the physical carrier, so that the aging decay function relationship table, the initial coupling correlation matrix M0, and the initial standard curve parameters no longer depend on external databases or network connections, but are instead bound to the physical malathion rapid test card in the form of a visually readable graphic code. This "data-on-card" technical architecture allows the detector to obtain all calibration parameters by scanning the QR code without needing to be connected to the network in testing scenarios with insufficient network signal coverage, achieving complete offline testing functionality. In large-scale food safety inspection tasks, each malathion rapid test card carries its own unique parameters, eliminating the need for testing personnel to check batch numbers one by one or manually replace the matching identification cards, greatly simplifying the operation process and reducing the risk of batch mixing due to human error. The encrypted encoding method prevents the leakage of core biochemical parameters, protects the manufacturer's intellectual property rights, and ensures the legal validity and traceability of the test data.

[0063] Step S10 utilizes the anisotropic characteristics of the response of two different materials—the substrate area of ​​the QR code label and the blank background area of ​​the NC film—to the same thermal history on the malathion rapid test card. This upgrades the QR code label, originally used only for identification, into a reference matrix for an intrinsic time-temperature indicator. This eliminates the need for additional chemical color-changing indicators or electronic temperature recording chips on the malathion rapid test card, enabling the detection of abnormal storage conditions. This method does not increase the material cost or manufacturing complexity of the malathion rapid test card; it can be achieved simply by adding a colorimetric measurement process and expanding the QR code data capacity at the production end, demonstrating good engineering feasibility and economic efficiency. Step S10 upgrades the "static batch parameters" to a "dynamic aging model," simultaneously encoding the "performance at the time of manufacture" and the "storage degradation law" into the QR code. This allows the detector to not only obtain the factory standard curve of the malathion rapid test card after scanning the QR code but also to correct the curve in real time based on the measured aging degree, adapting to the objective fact that the performance of the malathion rapid test card dynamically changes throughout its entire life cycle. The implementation of step S10 enables each malathion rapid test card to have self-description capabilities, carrying all the prior knowledge required to interpret its current state. This breaks the technical path dependence of existing technologies where the detector relies on external databases or matching identification cards to obtain batch parameters. It transforms batch parameter matching from "manual operation driven" to "image scanning driven," fundamentally eliminating the risk of batch mixing due to operator negligence. It also transforms the standard curve from "fixed at the factory" to "reconstructed at the time of detection," fundamentally eliminating the risk of calibration failure due to improper storage.

[0064] Step S20: Acquire a single-frame original image containing the encrypted traceability QR code matrix and the blank background area of ​​the NC film; perform geometric correction and homomorphic filtering illumination compensation on the single-frame original image to generate an illumination homogenized image; extract the real-time chromaticity feature vector of the dual matrix region from the illumination homogenized image.

[0065] Specifically, step S20 enables real-time sensing of the current status of the malathion rapid detection card at the detection end. A single-frame raw image refers to the raw pixel matrix acquired by the detector's camera within a single exposure cycle without any digital processing. Single-frame acquisition is used instead of continuous multi-frame acquisition because: in actual testing scenarios, the malathion rapid detection card may be held by the operator or placed on an unstable support surface. During multi-frame acquisition, the card may experience slight displacement, leading to deviations in the spatial correspondence between different frames. Single-frame acquisition ensures that the encrypted traceability QR code matrix and the NC film blank background area are recorded at the same instant under the same lighting conditions, providing a time-synchronized data basis for the vector difference operations in subsequent steps S31 and S32. The real-time chromaticity feature vector of the dual-matrix region refers to the three-dimensional coordinate representation of the QR code label paper substrate area and the NC film blank background area at the current detection time t* in the Lab color space, forming a time-axis correspondence with the initial chromaticity feature vector acquired at the factory time in step S12. In practical applications, the rapid detection card for malathion faces several image acquisition interferences, including: surface bending and tilting caused by placing the card on a soft aluminum foil packaging bag; uneven distribution of ambient lighting; specular reflections from the camera's supplementary light on the smooth sticker surface; and color response deviations due to differences in hardware between different detectors. Step S20 eliminates the impact of spatial distortion on pixel sampling density through geometric correction and eliminates the interference of illumination components on color measurement through homomorphic filtering. This ensures that the dual-matrix real-time chromaticity feature vector extracted from the homogenized illumination image accurately reflects the aging state of the material itself, rather than being a mixed signal superimposed with environmental interference. The printing position design of the encrypted traceability QR code matrix in step S20 and step S10 is coordinated: in step S13, the encrypted traceability QR code matrix is ​​printed at the position of the observation window adjacent to the blank background area of ​​the NC film, so that the QR code label paper substrate area and the blank background area of ​​the NC film are within the same field of view in the single frame original image in step S21. There is no need to collect images of the two areas separately and then stitch them together for registration, which fundamentally avoids the changes in lighting conditions and time interval errors that may be introduced by multiple acquisitions.

[0066] Further, step S20 includes:

[0067] Step S21: Acquire a single-frame original image containing the encrypted traceability QR code matrix and the blank background area of ​​the NC film; identify the positioning detection pattern in the encrypted traceability QR code matrix from the single-frame original image; calculate the perspective transformation matrix based on the coordinate distortion of the positioning detection pattern in the single-frame original image; apply the perspective transformation matrix to perform spatial mapping on the single-frame original image to generate an orthophoto image.

[0068] Specifically, the detector uses a camera module to acquire single-frame raw images. The camera module includes an image sensor, a lens assembly, and a supplementary lighting source. The image sensor is typically CMOS or CCD type, and the lens assembly's field of view must cover the entire range of the encrypted traceability QR code matrix and the blank background area of ​​the NC film on the malathion rapid detection card. When acquiring a single-frame raw image, the detector's control system triggers the image sensor to perform a single exposure, and the supplementary lighting source is simultaneously illuminated during the exposure to enhance the image signal-to-noise ratio. The positioning detection pattern is a pattern structure with a fixed shape and proportion defined in the encrypted traceability QR code standard. In the QR Code standard, it is represented by nested square patterns located at the three corners of the QR code matrix, with the width ratio of its black and white modules exhibiting a fixed numerical sequence relationship. The process of identifying the positioning detection pattern includes: converting the single-frame raw image to grayscale; using an adaptive threshold binarization method to convert the grayscale image into a black and white binary image; searching for candidate regions in the binary image that satisfy the characteristic proportion relationship of the positioning detection pattern; verifying the candidate regions using geometric features to eliminate false detections; and finally determining the center coordinates of the three positioning detection patterns. The coordinate distortion of the positioning detection pattern in a single frame of the original image refers to the fact that when the malathion rapid detection card is tilted relative to the optical axis of the camera, the three positioning detection patterns that were originally arranged in a square are projected onto the imaging plane as irregular quadrilaterals that are not squares. The relative distance and included angle between the three positioning detection patterns change. This distortion reflects the attitude deviation of the card in three-dimensional space.

[0069] The perspective transformation matrix is ​​calculated based on the principles of projective geometry, utilizing the correspondence between the actual coordinates of three localized probe figures in a single frame of the original image and their standard coordinates under ideal orthographic conditions. Let the center coordinates of the three localized probe figures in the single frame of the original image be P1, P2, and P3, respectively, and their corresponding standard coordinates under ideal orthographic conditions be P1', P2', and P3', respectively. The perspective transformation matrix H is a 3x3 homogeneous transformation matrix satisfying the mapping relationship P' = H × P, where P is the homogeneous representation of the original coordinates, and P' is the homogeneous representation of the transformed coordinates. The perspective transformation matrix H is solved using a direct linear transformation method, a well-known technique in computer vision. This method obtains the matrix element values ​​by constructing a system of linear equations containing the known coordinates of corresponding points and solving for the least-squares solution. Since the three positioning detection patterns of the QR code provide three pairs of corresponding points, and the solution of the perspective transformation matrix theoretically requires at least four pairs of corresponding points, the fourth corner point of the QR code matrix is ​​introduced as a supplementary constraint in step S21. The position of this corner point can be deduced from the position of the three positioning detection patterns based on the version information and module size of the QR code.

[0070] The process of spatially mapping a single-frame original image using a perspective transformation matrix employs an inverse mapping method: for each target pixel coordinate in the orthographic projection image, its corresponding source coordinate in the single-frame original image is calculated using the inverse of the perspective transformation matrix. Then, bilinear interpolation is used to calculate the color value of the target pixel from its four neighboring pixels around the source coordinate. An orthographic projection image refers to an ideal state where, after perspective correction, the surface of the malathion rapid detection card is strictly parallel to the imaging plane, with uniform imaging proportions at all points on the card, eliminating the perspective effect of near-large and far-small caused by card tilt. Generating an orthographic projection image ensures that the number of pixels per unit physical area is equal when extracting the chromaticity values ​​of the QR code label paper substrate area and the NC film blank background area in subsequent step S23. This avoids statistical bias caused by uneven sampling density due to perspective distortion, where pixel weights on one side are higher than on the other. Step S13 uses a standard QR code with a built-in positioning and detection graphic structure, which is directly reused in step S21 as a reference anchor point for geometric correction. This eliminates the need for additional printing of dedicated correction marks on the malathion rapid detection card, achieving functional reuse and structural simplification.

[0071] Step S22: Convert the orthophoto image to the logarithmic domain, use a high-pass filter to separate and suppress the incident light component in the logarithmic domain, enhance the reflectivity component, and restore it by exponential transformation to generate an illumination homogenized image.

[0072] Specifically, homomorphic filtering is a frequency domain filtering technique based on an image imaging physics model. Its theoretical basis lies in the fact that the grayscale value of each pixel in an image can be decomposed into the product of the incident light component and the reflectivity component. The incident light component represents the distribution of ambient light intensity illuminating the object's surface, while the reflectivity component represents the optical reflection characteristics of the object's surface material itself. In the image acquisition scenario of a malathion rapid detection card, the incident light component exhibits a spatially uneven distribution due to the influence of the detector's supplementary lighting angle, stray ambient light intrusion, and changes in the card's surface curvature. This manifests as some areas being brighter than others in the image. The reflectivity component, determined by the material optical properties of the QR code label paper substrate and the blank background of the NC film, is the target information to be extracted in step S20. Homomorphic filtering transforms a multiplicative relationship into an additive one, enabling the incident light component and the reflectivity component to be separated and processed in the frequency domain.

[0073] The specific operation for converting an orthographic projection image to the logarithmic domain is as follows: Take the natural logarithm of the grayscale value or color channel value of each pixel in the orthographic projection image to generate a logarithmic domain image. Let the original value of a pixel in the orthographic projection image be f(x,y), where x and y are the spatial coordinates of the pixel. Then f(x,y) = i(x,y) × r(x,y), where i(x,y) is the incident light component and r(x,y) is the reflectivity component. Taking the natural logarithm of both sides yields ln[f(x,y)] = ln[i(x,y)] + ln[r(x,y)], converting the multiplicative relationship into an additive relationship. The incident light component i(x,y) typically exhibits slow spatial variation characteristics, representing a low-frequency signal; the reflectivity component r(x,y) contains detailed information such as surface texture and boundaries, representing a high-frequency signal. In the logarithmic domain, the difference in the spectral characteristics of the incident light component and the reflectivity component allows them to be separated through frequency domain filtering.

[0074] The process of processing logarithmic domain images using a high-pass filter includes: performing a two-dimensional Fourier transform on the logarithmic domain image to convert the image from the spatial domain to the frequency domain; designing the transfer function of the high-pass filter, which attenuates low-frequency components while enhancing high-frequency components; multiplying the transfer function of the high-pass filter with the spectrum of the logarithmic domain image to achieve frequency domain filtering; and performing a two-dimensional inverse Fourier transform on the filtered spectrum to obtain the filtered logarithmic domain image. The high-pass filter design employs well-known filter types such as Butterworth high-pass filters or Gaussian high-pass filters. The cutoff frequency of the filter determines the separation boundary between the incident light component and the reflectivity component. The selection of the cutoff frequency needs to balance the illumination suppression effect with the degree of detail preservation: a cutoff frequency that is too low will result in some incident light components remaining, and the elimination of illumination inhomogeneity will be incomplete; a cutoff frequency that is too high will lead to the false suppression of low-frequency components in the reflectivity component, and the color uniformity of the color patch areas will be impaired. The method for determining the cutoff frequency is as follows: process standard test images containing known color patches under different cutoff frequency parameters, and select the cutoff frequency that minimizes the deviation between the color measurement value of the color patch area and the standard value as the working parameter.

[0075] The process of restoration via exponential transformation is as follows: Each pixel value in the filtered logarithmic domain image is subjected to an exponential operation, mapping it back from the logarithmic domain to the linear domain, generating a uniformly illuminated image. The exponential transformation is the inverse operation of the logarithmic transformation. Through this transformation, the reflectivity component information retained after filtering is restored to pixel values ​​directly corresponding to the optical properties of the object's surface material. In the uniformly illuminated image, the brightness differences caused by the uneven distribution of incident light are significantly reduced. The QR code label paper substrate area and the blank background area of ​​the NC film exhibit pixel value distributions close to the true material color, no longer dominated by ambient lighting conditions. Step S22 achieves hardware and software decoupling of image acquisition: regardless of the power and angle of the detector's supplementary light, and regardless of whether the detection site is an indoor fluorescent lighting environment or an outdoor natural light environment, the uniformly illuminated image after homomorphic filtering can reflect the reflectivity characteristics of the material itself, making the chromaticity feature vector extracted in the subsequent step S23 comparable across devices and scenes. Step S22 eliminates the interference of specular reflection spots generated by the camera's supplementary light on the smooth sticker surface: specular reflection spots manifest as saturated or abnormally high pixel values ​​in local areas of the image, appearing as locally extremely high values ​​in the logarithmic domain. High-pass filtering suppresses these as low-frequency incident light anomalies, allowing the pixel values ​​in the spot area to revert to the mean of the surrounding normal area, thus avoiding contamination of colorimetric measurements by the spot. Step S21 eliminates spatial geometric distortion, ensuring uniform pixel sampling density in the QR code label paper substrate area and the NC film blank background area in the homogenized illumination image; Step S22 eliminates illumination intensity distortion, ensuring that the pixel values ​​in both areas reflect only the material reflectivity rather than the incident light intensity. The combined effect of these two steps allows the colorimetric feature vector extracted from the homogenized illumination image in step S23 to be freed from the constraints of acquisition conditions, making it comparable to the initial colorimetric feature vector acquired under standard laboratory conditions in step S12.

[0076] Step S23: Decode the encrypted traceability QR code matrix in the illumination homogenization image to restore the aging attenuation function relationship table, the initial coupling correlation matrix, and the initial standard curve parameters; locate the QR code label paper substrate area and the NC film blank background area in the illumination homogenization image, calculate the average Lab color space value of all pixels in the QR code label paper substrate area and the NC film blank background area respectively, and generate the real-time chromaticity feature vector of the QR code label paper substrate area and the real-time chromaticity feature vector of the NC film blank background area.

[0077] Specifically, the decoding process of the encrypted traceability QR code matrix in the illumination homogenization image follows the QR code standard decoding process, including three stages: codeword extraction, error correction decoding, and data decryption. Codeword extraction involves identifying the data region of the encrypted traceability QR code matrix from the illumination homogenization image, determining the module grid based on the positioning detection pattern and timing pattern, sampling the pixel value of each module position and determining whether it is a black or white module, and converting the module sequence into a binary codeword sequence. Error correction decoding uses the Reed-Solomon error correction algorithm to detect and correct errors in the codeword sequence. This algorithm can recover the original data even if some codewords are damaged or misread. Data decryption uses a decryption algorithm paired with the encryption algorithm in step S13 to decrypt the error-corrected data stream and restore the plaintext data. The restored data includes an aging decay function relationship table, an initial coupling correlation matrix M0, and initial standard curve parameters. The initial coupling correlation matrix contains the initial chromaticity feature vector of the QR code label paper substrate area and the initial chromaticity feature vector of the NC film blank background area, providing subtraction data for calculating the aging drift vector in step S31.

[0078] The process of locating the QR code label paper substrate area and the NC film blank background area in the uniformly illuminated image is achieved using edge detection and region segmentation techniques. The location of the QR code label paper substrate area is based on the geometric position of the encrypted traceability QR code matrix: the boundary coordinates of the encrypted traceability QR code matrix have been determined during the decoding process, and the QR code label paper substrate area is the blank edge area of ​​the label paper surrounding the encrypted traceability QR code matrix. This is obtained by expanding the boundary of the encrypted traceability QR code matrix outwards by a certain distance and excluding the area occupied by the QR code pattern itself. The location of the NC film blank background area is based on the structural layout of the malathion rapid detection card: since the encrypted traceability QR code matrix is ​​printed adjacent to the observation window of the NC film blank background area in step S13, the NC film blank background area can be located by shifting a preset distance in a preset direction using the encrypted traceability QR code matrix as a reference in the uniformly illuminated image. The edge detection algorithm uses known methods such as Canny edge detection or Sobel edge detection to identify the boundary contour of the NC film observation window. Within the contour, a blank background area far from the detection area and quality control area is selected as the sampling range of the NC film blank background area.

[0079] The process of calculating the average Lab color space value of all pixels in the QR code label paper substrate area and the NC film blank background area includes two steps: color space conversion and statistical calculation. Illumination homogenization images are typically stored in RGB color space and need to be converted to Lab color space for chromaticity characterization. The RGB to Lab color space conversion follows the standard conversion procedure defined by the International Commission on Illumination (ICI): first, RGB values ​​are converted to XYZ tristimulus values, and then XYZ values ​​are converted to Lab values. During the conversion process, a reference white point needs to be specified to ensure color consistency between different devices; the reference white point is usually selected from the coordinates corresponding to the D65 standard light source. For all pixels in the QR code label paper substrate area, the arithmetic mean of their L, a, and b values ​​is calculated to obtain the real-time chromaticity feature vector V of the QR code label paper substrate area. paper(t*)= (L pt* ,a pt* ,b pt* ), L pt* a represents the brightness value of the QR code label paper substrate area at the current moment. pt* b represents the red-green hue value of the QR code label paper substrate area at the current moment. pt* The value of yellow-blue tint in the QR code label paper substrate area at the current moment is used as an example. Similarly, for all pixels within the blank background area of ​​the NC film, the arithmetic mean of the L, a, and b values ​​is calculated to obtain the real-time chromaticity feature vector V for the blank background area of ​​the NC film. mem(t*) =(L mt* ,a mt* ,b mt* ), L mt* a represents the brightness value of the blank background area of ​​the NC film at the current moment. mt* b represents the red-green hue value of the blank background region of the NC membrane at the current moment. mt* This represents the yellow-blue hue value of the blank background area of ​​the NC film at the current moment. The average value of all pixels in the area is used instead of single-point sampling because: there may be microscopic inhomogeneities on the material surface or image sensor noise, and the results of single-point sampling are greatly affected by random factors, while the regional average value can effectively smooth out random fluctuations and improve the repeatability and stability of colorimetric measurements.

[0080] Step S23 successfully obtained all the dynamic variables and static references required to calculate the degree of aging: the dynamic variable is the real-time chromaticity feature vector V of the QR code label paper substrate area at the current detection time t*. paper(t*) Real-time chromaticity feature vector V of the blank background region of the NC film mem(t*) The static reference is the V contained in the initial coupling correlation matrix M0 at the time of manufacture. paper(0) and V mem(0)These data all come from the processing results of the same illumination homogenized image, ensuring that dynamic variables and static references underwent the same geometric correction and illumination compensation processing during acquisition, eliminating systematic errors that may be introduced due to differences in processing procedures. Step S20 ensures that the QR code label paper substrate area and the NC film blank background area are imaged at the same time and under the same illumination conditions through single-frame acquisition, eliminating illumination fluctuations and card displacement errors that may be introduced by multiple acquisitions within time intervals; perspective transformation correction eliminates geometric distortion caused by card tilt, ensuring that the pixel sampling density of the two areas is uniform; homomorphic filtering eliminates the interference of uneven ambient illumination and local reflective spots on colorimetric measurements, so that the extracted colorimetric values ​​reflect the aging state of the material itself rather than changes in acquisition conditions. Step S20 standardizes the complex and variable image acquisition conditions in actual detection scenarios, making the colorimetric data acquired in uncontrolled environments such as remote farmers' markets and fields comparable to the initial colorimetric data acquired at the production end under standard laboratory conditions, laying a data quality foundation for the reverse inference of aging degree in the subsequent step S30. The implementation of step S20 frees the detector from dependence on auxiliary equipment such as fixed testing stations and standard light source boxes. Operators can handheld malathion rapid test cards to complete scanning under any lighting conditions, greatly expanding the scope of application of the detector and improving the convenience and mobility of on-site rapid testing. Step S20 successfully transmits the production-end data encoded in the encrypted traceability QR code matrix in step S10 to the testing end, realizing an information closed loop between the production end and the testing end. This allows each malathion rapid test card to autonomously acquire and analyze all the data required for aging status assessment without a network connection.

[0081] Step S30: Obtain the aging characteristic modulus based on the initial coupling correlation matrix and the real-time chromaticity feature vector of the dual matrix region; modify the initial standard curve parameters based on the relationship table between the aging characteristic modulus and the aging decay function to generate a real-time standard curve; and output the real-time malathion concentration value based on the real-time standard curve.

[0082] Specifically, step S30 uses vector operations to convert the invisible thermal history experienced by the malathion rapid test card during storage into a quantifiable aging characteristic modulus. This allows for the reverse deduction of the performance degradation of the malathion rapid test card at the current moment, and the dynamic reconstruction of a real-time standard curve adapted to the current aging state. The dual-matrix differential aging drift vector is a three-dimensional vector in the Lab color space formed by the difference between the aging drift vector of the NC film blank background area and the aging drift vector of the QR code label paper substrate area. It characterizes the difference in colorimetric change caused by the difference in aging rate between two different material matrices after experiencing the same storage environment. The aging characteristic modulus is obtained from the dual-matrix differential aging drift vector. The aging characteristic modulus is the Euclidean distance of the dual-matrix differential aging drift vector in the Lab color space. Its value monotonically increases with the cumulative thermal history experienced by the malathion rapid test card. A larger aging characteristic modulus indicates a longer thermal history or higher storage temperature, resulting in more severe performance degradation. The real-time standard curve refers to the detection curve obtained after dynamically correcting the parameters of the initial standard curve based on the current aging characteristic modulus. Compared with the initial standard curve at the time of manufacture, the slope term of the real-time standard curve is adjusted by scaling the sensitivity attenuation coefficient to adapt to the decrease in color rendering ability, and the intercept term is adjusted by offsetting the noise floor increase compensation value to adapt to the increase in background signal.

[0083] The reason for using dual-matrix differential measurement instead of single-matrix absolute measurement in step S30 is that if only the color change of the blank background area of ​​the NC film is measured to assess the degree of aging, it is impossible to distinguish whether the color change is caused by the actual aging of the material or by the change of the ambient light conditions. For example, when the light at the test site is dim, the measured L value of the blank background area of ​​the NC film will be systematically lower. If this lower value is mistakenly regarded as a decrease in brightness caused by aging, the degree of aging will be overestimated and the standard curve will be overcorrected, resulting in an overestimation of the quantitative result. However, when using the dual-matrix differential method, the QR code label paper substrate area and the blank background area of ​​the NC film are simultaneously acquired in the same uniformized light image. Both are affected by the same ambient light. When the light is dim, the L values ​​of both areas will be lower at the same time. The differential operation can cancel this common-mode interference and retain only the differential-mode signal caused by the inherent difference in the aging rates of the two materials, thereby accurately extracting the aging characteristic modulus that represents the cumulative effect of the real thermal history. The aging decay function relationship table established in step S30 and step S10 forms a reverse mapping relationship: In step S11, a nonlinear mapping relationship between the dual matrix chromaticity difference modulus, sensitivity decay coefficient, and noise floor rise compensation value is established in the forward direction through accelerated aging experiments at the production end. In step S30, the mapping relationship is inversely indexed at the detection end through the measured aging characteristic modulus to obtain the current performance decay parameters. This symmetrical structure of forward modeling and reverse deduction enables the aging law obtained in advance at the production end to be effectively reused at the detection end.

[0084] Further, see Figure 4 Step S30 includes:

[0085] Step S31: Subtract the real-time chromaticity feature vector of the QR code label paper substrate area from the initial chromaticity feature vector of the QR code label paper substrate area in the initial coupling correlation matrix to obtain the aging drift vector of the QR code label paper substrate area; Subtract the real-time chromaticity feature vector of the NC film blank background area from the initial coupling correlation matrix to obtain the aging drift vector of the NC film blank background area.

[0086] Specifically, the aging drift vector ΔV of the QR code label paper substrate area paper The calculation process is as follows: subtract the initial chromaticity feature vector of the QR code label paper substrate area from the real-time chromaticity feature vector of the QR code label paper substrate area to obtain the aging drift vector ΔV of the QR code label paper substrate area. paper =V paper(t*) -V paper(0) =(L pt* -L p0 ,a pt* -a p0 ,b pt* -b p0 )=(ΔL p ,Δa p ,Δb p ), where ΔL p Δa represents the change in brightness of the QR code label paper substrate area from the time of manufacture to the current inspection time. p Δb represents the change in red-green tint of the QR code label paper substrate area from the time of manufacture to the current inspection time. p This represents the change in yellow-blue tint of the QR code label paper substrate area from the time of manufacture to the current inspection moment. The aging drift vector ΔV of the NC film blank background area. mem The calculation process uses the same vector subtraction operation: subtract the real-time chromaticity feature vector of the NC film blank background region from the initial chromaticity feature vector of the NC film blank background region to obtain the aging drift vector ΔV of the NC film blank background region. mem =(ΔL m ,Δa m ,Δb m ), where ΔL m Δa represents the change in brightness of the blank background area of ​​the NC film from the time of manufacture to the current testing time. m Δb represents the change in red-green tint of the blank background area of ​​the NC membrane from the time of manufacture to the current testing time. m This indicates the change in yellow-blue tint of the blank background area of ​​the NC membrane from the time of manufacture to the current testing time.

[0087] Vector subtraction compares the current chromaticity state with the initial chromaticity state at the time of manufacture, extracting the increment of chromaticity change caused by storage aging, thus eliminating the interference of the material's inherent background color on aging assessment. The QR code label paper substrate area is mainly made of cellulose paper or polymer sticker material, and its aging process is primarily affected by the oxidative degradation of cellulose molecular chains under thermo-oxidative conditions, macroscopically manifested as: ΔL p Typically negative but with a small absolute value, Δa indicates a slight decrease in brightness; p The change was not significant; Δb p Typically positive but with a small absolute value, indicating a slow shift towards the yellow direction. The blank background area of ​​the NC membrane is mainly composed of nitrocellulose and contains residual colloidal gold particles. Its aging process is affected by both the rapid oxidative degradation of nitrocellulose and the thermally induced aggregation of colloidal gold particles, macroscopically manifested as: ΔL m Typically, a negative value with a large absolute value indicates a significant decrease in brightness; Δa m The hue may change, indicating a shift from burgundy to purple due to the aggregation of colloidal gold particles; Δb m Typically, a positive value with a large absolute value indicates a rapid shift towards the yellow direction. The significant difference in aging rates between the two materials results in ΔV mem The growth rate of the modulus is much faster than that of ΔV. paper This differential aging characteristic is the physical basis for constructing the dual-matrix differential aging drift vector in step S32. The reason for using vector subtraction instead of directly using real-time chromaticity values ​​in step S31 is that different production batches of malathion rapid test cards may use raw materials from different sources, and there may be batch-to-batch differences in the whiteness of the QR code label paper and the background color of the NC film. If the degree of aging is directly assessed using real-time chromaticity values, the material background differences between batches will be misjudged as aging drift, resulting in a lack of comparability in the aging assessment results of different batches of products. However, by using vector subtraction to zero out the initial chromaticity value as a benchmark, the aging drift vector only reflects the increment of chromaticity change from the time of manufacture to the current time, eliminating the interference of material background differences between batches, so that different batches of products have similar aging drift vector magnitudes after experiencing the same storage conditions for the same period of time.

[0088] Step S32: Perform vector difference operation on the aging drift vector of the blank background area of ​​the NC film and the aging drift vector of the QR code label paper substrate area to construct the dual matrix differential aging drift vector; calculate the Euclidean distance of the dual matrix differential aging drift vector in the Lab color space to obtain the aging characteristic modulus.

[0089] Specifically, the dual-matrix differential aging drift vector D ariny The construction process is as follows: the aging drift vector ΔV of the blank background region of the NC film obtained in step S31 is... memThe aging drift vector ΔV of the QR code label paper substrate area paper Perform vector difference operations to obtain D ariny =ΔV mem -ΔV paper The physical meaning of vector difference operation lies in extracting the color change difference between two material matrices caused by differences in aging rates, thus eliminating interference from environmental factors experienced by both. For example, assuming the malathion rapid detection card is in a dimly lit environment during detection, the homomorphic filtering in step S22, although light compensation has been performed, may still have residual errors, leading to ΔL... m and ΔL p All shift towards the negative direction, at which point ΔL m -ΔL p The differential operation can cancel out the common-mode offset, retaining only the differential-mode brightness change caused by the faster aging rate of the NC film compared to the QR code label paper; similarly, if there is slight contamination on the surface of the malathion rapid test card, causing an overall color shift, the differential operation can also cancel out this common-mode contamination interference.

[0090] The aging characteristic modulus |D| is calculated using the Euclidean distance formula in the Lab color space: The Euclidean distance is used as the representation of the aging characteristic modulus because: Euclidean distance is the standard measure of the perceptual difference between two color points in the Lab color space, and it has a good correspondence with the human eye's perception of color differences; Euclidean distance is non-negative and symmetric, ensuring that the aging characteristic modulus is always a non-negative real number and is not affected by the order of vector subtraction; Euclidean distance integrates the changes of the three color channels into a single scalar value, which is convenient for interpolation indexing and numerical comparison in subsequent step S33. The value of the aging characteristic modulus |D| increases monotonically with the accumulation of thermal history experienced by the malathion rapid test card. This monotonically increasing characteristic stems from the inherent difference in the aging rates of the two materials: since the aging rate of the blank background area of ​​the NC film is much faster than that of the QR code label paper substrate area, as the storage time increases or the storage temperature rises, ΔV mem The growth rate is always greater than ΔV paper This leads to the difference vector D ariny The modulus length continues to increase, and the aging characteristic modulus |D| shows a monotonically increasing trend.

[0091] Step S32 employs a dual-matrix differential measurement method instead of a single-matrix absolute measurement method because: single-matrix absolute measurement cannot distinguish the superimposed effects of actual material aging and environmental interference factors, while the dual-matrix differential method uses the QR code label paper substrate area as an intrinsic reference matrix, which undergoes the same storage environment as the blank background area of ​​the NC film on the same malathion rapid test card. The difference results between the two only reflect the difference in color change caused by the inherent difference in the material aging rate, thus offsetting common-mode interference factors such as changes in ambient light, overall contamination, and measurement system drift. Step S32 utilizes the material properties differences of existing components on the malathion rapid test card to construct an intrinsic time-temperature indicator, eliminating the need to add additional chemical color-changing indicators or electronic temperature recording chips to the malathion rapid test card, without increasing product cost or process complexity. The thermal history experienced by the malathion rapid test card can be perceived solely through image analysis, achieving a "zero-cost incremental" in-situ self-indication function for aging degree. The aging characteristic modulus calculated in step S32 and the dual-matrix chromaticity difference modulus established in step S11 are calculated in the same way. Both are the Euclidean distance of the dual-matrix differential aging drift vector in the Lab color space. The two are mathematically equivalent, so that the aging characteristic modulus calculated by the detection end can be directly substituted into the aging decay function relationship table established by the production end in step S33 for interpolation index lookup.

[0092] Step S33: Substitute the aging characteristic modulus into the aging decay function relationship table for interpolation indexing, find the corresponding sensitivity decay coefficient and noise floor rise compensation value, and define them as the mapped sensitivity decay coefficient and the mapped noise floor rise compensation value; use the mapped sensitivity decay coefficient to scale and correct the slope term of the standard curve at the time of factory delivery in the initial standard curve parameters, and use the mapped noise floor rise compensation value to offset and correct the intercept term of the standard curve at the time of factory delivery in the initial standard curve parameters, and generate a real-time standard curve; measure the real-time color intensity of the detection area of ​​the malathion rapid test card, substitute the real-time color intensity into the real-time standard curve, calculate and output the real-time malathion concentration value.

[0093] Specifically, the aging attenuation function relationship table is a data mapping table established in step S11 through accelerated aging experiments and encoded in the encrypted traceability QR code matrix. The independent variable of the table is the discrete value sequence of the dual matrix chromaticity difference modulus, and the dependent variables are the corresponding sensitivity attenuation coefficient and noise floor rise compensation value. The aging characteristic modulus |D| calculated in step S32 is used as the query key value to index the aging attenuation function relationship table: if |D| is exactly equal to a certain discrete value in the table, the sensitivity attenuation coefficient and noise floor rise compensation value corresponding to that value are directly read; if |D| falls between two adjacent discrete values, the corresponding sensitivity attenuation coefficient and noise floor rise compensation value are calculated using a linear interpolation method based on the distance ratio between |D| and the two adjacent values. The queried sensitivity attenuation coefficient is defined as the mapped sensitivity attenuation coefficient K. t* Its value ranges from 0 to 1, K t* A value closer to one indicates better sensitivity retention and less aging of the malathion rapid test card. t* The closer the value is to zero, the more severe the sensitivity degradation and the greater the aging. The noise floor rise compensation value obtained from the query is defined as the mapped noise floor rise compensation value C. t* Its value is a non-negative real number, C t* The higher the value, the more significant the rise in background signal due to aging.

[0094] Using the mapping sensitivity attenuation coefficient K t* The process of scaling and correcting the standard curve slope term at the factory time in the initial standard curve parameters is as follows: extract the standard curve slope term S0 at the factory time from the initial standard curve parameters obtained by decoding in step S23, and multiply it by the mapping sensitivity attenuation coefficient K. t* The corrected real-time standard curve slope term S is obtained. t* =K t* ×S0. The technical consideration for using multiplicative scaling is that sensitivity decay manifests as a proportional decrease in the change in color intensity caused by a unit change in malathion concentration. If a unit change in concentration at the time of manufacture causes a change in color intensity of S0 units, then after aging, a unit change in concentration will only cause a change in color intensity of K. t* ×S0 units, the multiplication operation accurately reflects this proportional attenuation relationship. The mapping noise floor is raised to compensate for the value C. t* The process of offset correction for the standard curve intercept term at the factory time in the initial standard curve parameters is as follows: extract the standard curve intercept term I0 at the factory time from the initial standard curve parameters, and add the mapping noise floor rise compensation value C to it. t* The corrected real-time standard curve intercept term I is obtained. t* =I0+C t*The additive offset is used because: the increase in background noise is manifested as an increase in the background color intensity at zero concentration, which is added to the original level. The additive operation accurately reflects this incremental superposition relationship.

[0095] The process of generating a real-time standard curve is as follows: The slope term S of the corrected real-time standard curve is... t* and real-time standard curve intercept term I t* Substituting the values ​​into the standard curve equation, a real-time standard curve adapted to the current aging state is generated. For example, if the initial standard curve uses a linear equation, the standard curve equation at the factory setting is: Color intensity = S0 × Malathion concentration + I0. The real-time standard curve equation after dynamic correction is: Color intensity = S t* ×Malathion concentration + I t* If the initial standard curve adopts a four-parameter logical equation form, then the standard curve at the factory setting is jointly determined by four parameters: the lower asymptote parameter D0, the slope factor parameter B0, the inflection point concentration parameter C0, and the upper asymptote parameter A0. The parameters of the real-time standard curve after dynamic correction are adjusted according to the following rules: multiply the slope factor parameter B0 at the factory setting by the sensitivity attenuation coefficient K. t The corrected slope factor parameters are obtained; the noise floor increase compensation value C is added to the upper asymptote parameter A0 at the factory setting. t The corrected upper asymptote parameters are obtained; the lower asymptote parameters D0 at the factory setting are then added to the noise floor increase compensation value C. t The corrected lower asymptote parameter D is obtained. t* To compensate for the overall signal baseline drift caused by aging; divide the inflection point concentration parameter C0 at the time of manufacture by the sensitivity attenuation coefficient K. t The corrected inflection point concentration parameter was obtained to compensate for the impact of decreased sensitivity on the midpoint of the detection range. Using the four corrected parameters, a real-time standard curve equation was constructed to convert the measured colorimetric intensity into malathion concentration values. The change in the real-time standard curve compared to the initial standard curve is as follows: the slope term is multiplied by a K term less than 1. t* The value decreases, and the curve becomes flatter, reflecting that the rapid detection card for malathion becomes less sensitive to the same concentration of malathion after aging; the intercept term is affected by the addition of a positive value C. t* As the concentration increases, the curve shifts upwards overall, reflecting the increase in color intensity reading at zero concentration due to the rise in background signal after aging.

[0096] The process of measuring the real-time colorimetric intensity of the detection area of ​​the malathion rapid test card is as follows: The location of the detection area of ​​the malathion rapid test card is positioned in the illumination homogenization image generated in step S22. The detection area refers to the T-line region on the NC membrane where specific capture antibodies are immobilized. When malathion in the sample binds to the colloidal gold-labeled antibody and flows through this region, a visible colorimetric band is formed. The colorimetric intensity of this region is quantified using grayscale value or reflectance and denoted as the real-time colorimetric intensity Y. The process of substituting the real-time colorimetric intensity into the real-time standard curve to calculate the malathion concentration value is as follows: Based on the inverse function form of the real-time standard curve equation, the malathion concentration value X is deduced from the real-time colorimetric intensity Y. The calculated malathion concentration value is the real-time malathion concentration value, which is the final output result of step S30.

[0097] The significance of using a "dynamic degradation correction" strategy in step S33 instead of directly using the initial standard curve is that: during storage, the malathion rapid test card experiences a decrease in colorimetric ability and an increase in background signal due to material aging. If the high-sensitivity initial standard curve from the factory is continued for quantitative calculation, the same measured colorimetric intensity will be converted into a lower malathion concentration value, leading to false negative results where samples that actually exceed the standard are misjudged as acceptable. However, through the dynamic degradation correction in step S33, the system actively reduces the slope of the real-time standard curve and increases the intercept, acknowledging the objective fact that the colorimetric ability of the current malathion rapid test card has weakened and the background has deepened. This ensures that the same measured colorimetric intensity is converted into a value closer to the true concentration, effectively avoiding the risk of false negatives. Step S30 achieves in-situ self-indication of the aging degree of the malathion rapid test card and dynamic reconstruction of the standard curve. By performing vector subtraction in step S31, the chromaticity state at the current time is compared with that at the time of manufacture, and the incremental change in chromaticity caused by storage aging is extracted, eliminating the interference of material background differences between batches. By performing vector difference in step S32, the inherent difference in aging rates of the two materials is used to construct a dual-matrix differential aging drift vector, which cancels out common-mode interference factors such as changes in ambient light, and accurately extracts the differential-mode signal representing the true thermal history. By performing interpolation indexing and curve correction in step S33, the aging characteristic modulus is inversely mapped to a performance degradation parameter, and the slope and intercept of the standard curve are dynamically adjusted accordingly to generate a real-time standard curve that adapts to the current aging state. Step S30 enables the malathion rapid test card to guarantee detection accuracy throughout its entire lifecycle: regardless of whether the malathion rapid test card is a brand new card or an old card nearing its expiration date, and regardless of whether it has undergone normal storage or abnormal high-temperature storage, the system can automatically identify its current performance status through measured aging characteristic modulus and adjust the standard curve used for quantitative calculation accordingly, so that malathion rapid test cards with different aging levels can provide accurate quantitative results. Step S30 converts the color change information of the existing components on the malathion rapid test card into quantifiable aging indicators. It does not rely on external temperature sensors to record storage temperature history, electronic tags to record storage time history, or network queries of product storage trajectory databases. It only needs to use a single frame image acquired by the detector at the time of detection to complete the aging degree assessment and dynamic curve correction, realizing an intelligent detection closed loop of aging self-sensing and parameter self-adaptation.

[0098] Example 2

[0099] This embodiment, based on Embodiment 1, provides an automatic batch parameter matching system for malathion detection card QR code traceability, such as... Figure 5 As shown, it includes:

[0100] The parameter construction and encoding module is used to collect Lab color space values ​​of the dual-matrix region in the malathion rapid test card, determine the initial standard curve parameters, construct the aging decay function relationship table and the initial coupling correlation matrix, generate the encrypted traceability QR code matrix, and print the encrypted traceability QR code matrix on the surface of the malathion rapid test card; the dual-matrix region refers to the QR code label paper substrate region and the NC film blank background region.

[0101] Image acquisition and extraction module: used to acquire a single frame of original image containing the encrypted traceability QR code matrix and the blank background area of ​​the NC film, process the single frame of original image, and extract the real-time chromaticity feature vector of the dual matrix region;

[0102] Curve reconstruction output module: The aging characteristic modulus is obtained based on the initial coupling correlation matrix and the real-time chromaticity feature vector of the dual matrix region. The initial standard curve parameters are corrected based on the relationship table between the aging characteristic modulus and the aging decay function to generate a real-time standard curve. The real-time malathion concentration value is output based on the real-time standard curve.

[0103] Furthermore, in the parameter construction encoding module, the method for constructing the aging decay function relationship table includes:

[0104] Accelerated aging tests were conducted on the same batch of malathion rapid test cards. The Lab color space values ​​of the QR code label paper substrate area and the Lab color space values ​​of the NC film blank background area were collected at each aging time point, and the dual matrix color difference modulus at each aging time point was calculated.

[0105] The sensitivity attenuation coefficient and noise floor rise compensation value at each aging time point are calculated. The nonlinear mapping relationship between the dual matrix chromaticity difference modulus, sensitivity attenuation coefficient, and noise floor rise compensation value is fitted to generate an aging attenuation function relationship table.

[0106] The method for constructing the initial coupling correlation matrix includes:

[0107] At the time of manufacture of the malathion rapid test card, the initial chromaticity feature vectors of the QR code label paper substrate area and the initial chromaticity feature vectors of the NC film blank background area are measured. The initial chromaticity feature vectors of the QR code label paper substrate area and the initial chromaticity feature vectors of the NC film blank background area are combined to construct an initial coupling correlation matrix.

[0108] Furthermore, in the image acquisition and extraction module, the method for processing a single-frame original image and extracting the real-time chromaticity feature vector of the dual-matrix region includes:

[0109] Geometric correction and homomorphic filtering illumination compensation are performed on a single frame of the original image to generate an illumination homogenized image. Real-time chromaticity feature vectors of the dual-matrix region are extracted from the illumination homogenized image.

[0110] The method for performing geometric correction includes:

[0111] The positioning detection pattern in the encrypted traceability QR code matrix is ​​identified from a single frame of the original image. The perspective transformation matrix is ​​calculated based on the coordinate distortion of the positioning detection pattern in the single frame of the original image. The perspective transformation matrix is ​​then applied to spatially map the single frame of the original image to generate an orthophoto image.

[0112] The method for performing homomorphic filtering illumination compensation includes:

[0113] The orthophoto image is converted to the logarithmic domain. In the logarithmic domain, a high-pass filter is used to separate and suppress the incident light component and enhance the reflectivity component. After exponential transformation, the image is restored to generate a uniformly illuminated image.

[0114] The methods and systems of this application may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the method is for illustrative purposes only, and the steps of the method of this application are not limited to the order specifically described above, unless otherwise specifically stated.

[0115] In addition, the parts of the technical solutions provided in the embodiments of this application that are consistent with the implementation principles of the corresponding technical solutions in the prior art have not been described in detail, so as to avoid excessive elaboration.

[0116] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the invention. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for automatically matching the two-dimensional code traceability batch parameters of malathion detection cards, characterized in that, The method includes: Lab color space values ​​of the dual-matrix region in the malathion rapid test card were collected, initial standard curve parameters were measured, an aging decay function relationship table and an initial coupling correlation matrix were constructed, an encrypted traceability QR code matrix was generated, and the encrypted traceability QR code matrix was printed on the surface of the malathion rapid test card; the dual-matrix region refers to the QR code label paper substrate region and the NC film blank background region. A single-frame original image containing an encrypted traceability QR code matrix and a blank background area of ​​the NC film is acquired. The single-frame original image is processed to extract the real-time chromaticity feature vector of the dual matrix region. The aging characteristic modulus is obtained based on the initial coupling correlation matrix and the real-time chromaticity feature vector of the dual matrix region. The initial standard curve parameters are corrected based on the relationship table between the aging characteristic modulus and the aging decay function to generate a real-time standard curve. The real-time malathion concentration value is output based on the real-time standard curve.

2. The method for automatically matching batch parameters using QR code traceability on malathion detection cards according to claim 1, characterized in that, The method for constructing the aging decay function relationship table includes: Accelerated aging tests were conducted on the same batch of malathion rapid test cards. The Lab color space values ​​of the QR code label paper substrate area and the Lab color space values ​​of the NC film blank background area were collected at each aging time point, and the dual matrix color difference modulus at each aging time point was calculated. The sensitivity attenuation coefficient and noise floor rise compensation value at each aging time point are calculated. The nonlinear mapping relationship between the dual matrix chromaticity difference modulus, sensitivity attenuation coefficient, and noise floor rise compensation value is fitted to generate an aging attenuation function relationship table.

3. The method for automatically matching batch parameters using QR code traceability on malathion detection cards according to claim 2, characterized in that, The method for constructing the initial coupling correlation matrix includes: At the time of manufacture of the malathion rapid test card, the initial chromaticity feature vectors of the QR code label paper substrate area and the initial chromaticity feature vectors of the NC film blank background area are measured. The initial chromaticity feature vectors of the QR code label paper substrate area and the initial chromaticity feature vectors of the NC film blank background area are combined to construct an initial coupling correlation matrix.

4. The method for automatically matching batch parameters of a malathion test card QR code traceability system according to claim 3, characterized in that, The method for generating the encrypted traceability QR code matrix includes: The aging decay function relationship table, the initial coupling correlation matrix and the initial standard curve parameters are encrypted and encoded to generate a binary data stream, and the binary data stream is rendered into an encrypted traceability QR code matrix.

5. The method for automatically matching batch parameters of malathion test card QR code traceability according to claim 4, characterized in that, The method for processing a single-frame original image and extracting the real-time chromaticity feature vector of the dual-matrix region includes: Geometric correction and homomorphic filtering illumination compensation are performed on a single frame of the original image to generate an illumination homogenized image. Real-time chromaticity feature vectors of the dual-matrix region are extracted from the illumination homogenized image.

6. The method for automatically matching batch parameters of a malathion test card QR code traceability system according to claim 5, characterized in that, The method for performing geometric correction includes: The positioning detection pattern in the encrypted traceability QR code matrix is ​​identified from a single frame of the original image. The perspective transformation matrix is ​​calculated based on the coordinate distortion of the positioning detection pattern in the single frame of the original image. The perspective transformation matrix is ​​then applied to spatially map the single frame of the original image to generate an orthophoto image.

7. The method for automatically matching batch parameters of a malathion test card QR code traceability system according to claim 6, characterized in that, The method for performing homomorphic filtering illumination compensation includes: The orthophoto image is converted to the logarithmic domain. In the logarithmic domain, a high-pass filter is used to separate and suppress the incident light component and enhance the reflectivity component. After exponential transformation, the image is restored to generate a uniformly illuminated image.

8. The method for automatically matching batch parameters of a malathion test card QR code traceability system according to claim 7, characterized in that, The method for extracting real-time chromaticity feature vectors of dual-matrix regions from an illumination homogenized image includes: In the image with uniform illumination, locate the QR code label paper substrate area and the NC film blank background area, calculate the average value of the Lab color space of all pixels in the QR code label paper substrate area and the NC film blank background area respectively, and generate the real-time chromaticity feature vector of the QR code label paper substrate area and the real-time chromaticity feature vector of the NC film blank background area.

9. The method for automatically matching batch parameters of a malathion test card QR code traceability system according to claim 8, characterized in that, The method for obtaining the aging characteristic modulus includes: The aging drift vector of the QR code label paper substrate area is obtained by subtracting the real-time chromaticity feature vector of the QR code label paper substrate area from the initial chromaticity feature vector of the QR code label paper substrate area in the initial coupling correlation matrix; the aging drift vector of the NC film blank background area is obtained by subtracting the real-time chromaticity feature vector of the NC film blank background area from the initial coupling correlation matrix. The aging drift vector of the blank background area of ​​the NC film and the aging drift vector of the QR code label paper substrate area are subjected to vector difference operation to construct the dual matrix differential aging drift vector; the Euclidean distance of the dual matrix differential aging drift vector in the Lab color space is calculated to obtain the aging characteristic modulus.

10. The method for automatically matching batch parameters of a malathion test card QR code traceability system according to claim 9, characterized in that, The initial standard curve parameters include the standard curve slope term and the standard curve intercept term at the time of factory delivery; The method for correcting the initial standard curve parameters includes: Substitute the aging characteristic modulus into the aging decay function relationship table for interpolation indexing, find the corresponding sensitivity decay coefficient and noise floor rise compensation value, and define them as the mapped sensitivity decay coefficient and the mapped noise floor rise compensation value. The slope term of the standard curve at the time of factory departure is scaled and corrected using the mapping sensitivity attenuation coefficient, and the intercept term of the standard curve at the time of factory departure is offset and corrected using the mapping noise floor rise compensation value.

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