Fluorescent probe signal calibration method and system for rapid detection of multiple residues in complex matrix

Abstract

The invention provides a fluorescence probe signal calibration method and system for rapid detection of multiple residues in a complex matrix, and the method comprises the steps: collecting a fluorescence signal of a to-be-detected sample, and analyzing the original concentration, the fluorescence average lifetime and the fluorescence peak emission wavelength of the to-be-detected sample from the fluorescence signal; calculating a life deviation between the fluorescence average life and a preset reference life, and a wavelength deviation between the fluorescence peak emission wavelength and a preset reference wavelength; calculating to obtain a signal fidelity index based on the life deviation and the wavelength deviation; according to a preset threshold interval in which the signal fidelity index falls, a corresponding calibration strategy is determined, and the calibration strategy is one of non-calibration, calibration execution or invalid marking; and when the calibration strategy is to execute calibration, calculating a total calibration factor based on the life deviation and the wavelength deviation, calibrating the original concentration by using the total calibration factor, and outputting the calibrated concentration.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of signal processing and calibration for analytical detection, and particularly relates to a fluorescence probe signal calibration method and system for rapid detection of multiple residues in a complex matrix. BACKGROUND

[0002] With the wide application of biomimetic enzyme fluorescent probes in the field of rapid detection, they have become the core technology support for food quality and safety screening, environmental pollutant monitoring, etc. due to their advantages of high sensitivity, specificity and rapid response. From pesticide residue detection in tea, fruits and vegetables, to on-site screening of harmful pollutants in water and soil, this kind of probe technology is gradually replacing traditional detection methods to meet the urgent needs of grassroots supervision and on-site rapid analysis. However, the complexity of the actual detection environment far exceeds the ideal conditions in the laboratory. Proteins, lipids and natural pigments (such as chlorophyll and carotenoids) in food matrix, humic acid and heavy metal ions in environmental samples, and reducing substances in biological samples will all interact with biomimetic enzyme fluorescent probes, causing significant interference with the detection signal.

[0003] Such matrix interference is not a single effect, but a combined effect caused by multiple physical and chemical processes. For example, polyphenols in plant-derived samples may change the conformation of the probe through non-specific binding, causing a shift in the fluorescence emission wavelength. Heavy metal ions in environmental water samples can easily cause fluorescence quenching, reducing signal intensity. Natural pigments in food can produce background fluorescence, causing spectral overlap with probe signals, and even exacerbating signal distortion through fluorescence resonance energy transfer (FRET) mechanism. More challenging is that these interferences often exist simultaneously and superimpose on each other, making the change in fluorescence signal no longer simply reflect the target concentration, but a comprehensive result mixed with multiple matrix effects, thus breaking the traditional detection logic that relies on the linear relationship between signal and concentration.

[0004] To address the above problems, the industry has developed various conventional calibration strategies, but all have obvious technical limitations. The most common approach is to calibrate based on a single fluorescence intensity parameter, by comparing the intensity difference between the blank control and the sample to correct the results. However, this method cannot distinguish whether the signal change is due to fluctuations in target concentration, background fluorescence overlap or quenching effect, and is prone to misjudgment. Another common solution is to use a fixed calibration coefficient for compensation, by pre-determining the interference level of a specific matrix to establish a calibration library. However, the matrix composition of actual samples varies greatly, even for the same type of food, different varieties, origins or processing methods can lead to significant differences in interference components, making it impossible for the fixed coefficient to adapt to the dynamic interference scenario, and almost losing its calibration value in unknown matrices.

[0005] In recent years, some improved methods attempt to introduce a single dimension of signal parameters to assist calibration, such as distinguishing quenching-induced signal attenuation by fluorescence lifetime, or avoiding the absorption interference of pigments by using near-infrared spectroscopy, but these methods still cannot break through the "single parameter limitation": the former cannot cope with the intensity shift caused by background fluorescence, and the latter is completely ineffective for non-pigment interference (such as protein adsorption, ion quenching). More importantly, the existing technology generally lacks the ability to accurately identify the type of interference, and cannot quantify the contribution weight of different physical and chemical processes to the signal, resulting in the calibration behavior being reduced to "blind compensation". In complex samples with significant matrix effects, the relative error of the detection results often exceeds the acceptable range, seriously restricting the practical application value of the biomimetic enzyme fluorescent probe technology.

[0006] Therefore, how to break through the inherent defects of traditional calibration methods, realize the accurate identification and dynamic adaptation of multiple interferences in complex matrix, and establish a signal calibration system that can match the actual detection scene, has become a key bottleneck for promoting the biomimetic enzyme fluorescent probe technology to scale application, and is also a core technical problem urgently needed to be solved in the field. SUMMARY

[0007] In view of the defects and deficiencies of the prior art, the present application provides a fluorescent probe signal calibration method and system for rapid detection of multiple residues in complex matrix, aiming to solve the technical problems of fluorescence detection signal distortion caused by complex interference in complex matrix and the difficulty of accurate adaptation of conventional calibration methods.

[0008] The method first collects the fluorescence signal of the to-be-tested sample, and resolves two types of key fluorescence physical parameters, i.e., an original concentration, a fluorescence average lifetime and a fluorescence peak emission wavelength from the fluorescence signal; then, a lifetime deviation of the fluorescence average lifetime from a preset reference lifetime and a wavelength deviation of the fluorescence peak emission wavelength from a preset reference wavelength are calculated; a weighted sum is performed based on the square of the ratio of the two types of deviations to the corresponding reference values, and a signal fidelity index is obtained by combining a preset reference value, and the index is boundary processed to ensure that it is in a reasonable interval, and the index can quantitatively reflect the degree of signal interference; then, a calibration strategy is determined according to the preset threshold interval (including a high-confidence threshold and a calibration lower limit threshold) into which the signal fidelity index falls, and the calibration strategy is specifically that the signal is not calibrated when the signal confidence is extremely high, the calibration is performed when the signal is moderately distorted, and the signal is marked as invalid when the signal is severely distorted, wherein the high-confidence threshold is determined based on the signal fidelity index distribution statistics of the non-interference standard sample, the calibration lower limit threshold is determined in combination with the relative error after calibration, and a preset minimum tolerance is used when the thresholds are compared to ensure numerical stability; when the calibration is performed, the wavelength deviation is multiplied by a preset wavelength calibration coefficient, the lifetime deviation is multiplied by a preset lifetime calibration coefficient, and then the two types of calibration values are added to obtain a total calibration factor, the wavelength calibration coefficient is calibrated by adding an interference substance that only affects the wavelength in the standard sample and performing linear regression, and the lifetime calibration coefficient is calibrated by adding an interference substance that only affects the lifetime, and finally the calibration is completed based on the correlation between the original concentration and the total calibration factor and the calibrated concentration is output.

[0009] The system corresponds to the above method and is provided with a signal acquisition module, a deviation calculation module, a fidelity index module, a calibration strategy module and a concentration calibration module, and can be further integrated with an in-situ isolation sensing unit, which is provided with an in-situ isolation micro-reactor model containing an interface film characteristic permeability coefficient and an interference substance repulsion coefficient, and can establish a mapping relationship between the external sample concentration and the effective concentration in the micro-reactor to reduce the influence of the interference substance from the physical layer. In addition, the present application also provides a computer device and a non-transitory computer readable storage medium for implementing the above method, which are matched by a hardware carrier and software storage to ensure that the calibration method can be stably implemented.

[0010] The present application breaks through the limitation of traditional single parameter calibration by using the technical architecture of "two-dimensional fluorescence parameter acquisition-signal fidelity quantitative evaluation-hierarchical closed-loop calibration-physical isolation cooperation", realizes accurate identification and directional compensation of complex interference in complex matrix, and significantly improves the accuracy and reliability of multi-residue rapid detection.

[0011] The technical scheme specifically adopted by the present application to solve the technical problems is:

[0012] A fluorescence probe signal calibration method for multi-residue rapid detection in a complex matrix, comprising:

[0013] Collecting a fluorescence signal of a to-be-tested sample, and resolving original concentration, fluorescence average lifetime and fluorescence peak emission wavelength of the to-be-tested sample from the fluorescence signal;

[0014] Calculating lifetime deviation of the fluorescence average lifetime from a preset reference lifetime, and wavelength deviation of the fluorescence peak emission wavelength from a preset reference wavelength;

[0015] Based on the lifetime deviation and the wavelength deviation, a signal fidelity index is calculated;

[0016] According to the preset threshold interval into which the signal fidelity index falls, a corresponding calibration strategy is determined, the calibration strategy being one of no calibration, performing calibration or marking invalid;

[0017] When the calibration strategy is performing calibration, a total calibration factor is calculated based on the lifetime deviation and the wavelength deviation, the original concentration is calibrated by using the total calibration factor, and a calibrated concentration is output.

[0018] Further, when the fluorescence signal is collected, a time-dependent single photon counting technique is used to obtain the fluorescence average lifetime and the fluorescence peak emission wavelength, and the original concentration is resolved based on the fluorescence intensity signal obtained by a high-sensitivity fluorescence detector; the lifetime deviation is the difference between the fluorescence average lifetime and a preset reference lifetime, and the wavelength deviation is the difference between the fluorescence peak emission wavelength and a preset reference wavelength.

[0019] Further, the method for calculating the signal fidelity index based on the lifetime deviation and the wavelength deviation specifically comprises: squaring the ratio of the wavelength deviation to a preset reference wavelength to obtain a wavelength normalized square deviation; squaring the ratio of the lifetime deviation to a preset reference lifetime to obtain a lifetime normalized square deviation; performing weighted summation on the two kinds of normalized square deviations to generate a weighted deviation sum; subtracting the weighted deviation sum from a preset reference value 1 to obtain the signal fidelity index; after the signal fidelity index is calculated, if it is greater than 1, it is adjusted to 1, and if it is less than 0, it is adjusted to 0, so that the index is in the interval of 0-1.

[0020] Further, the preset threshold interval includes a high-confidence threshold and a correction lower limit threshold, wherein: when the signal fidelity index is not less than the high-confidence threshold, the calibration strategy is no calibration; when the signal fidelity index is not less than the correction lower limit threshold and is less than the high-confidence threshold, the calibration strategy is performing calibration; when the signal fidelity index is less than the correction lower limit threshold, the calibration strategy is marking invalid; the high-confidence threshold is determined based on the distribution statistics of the signal fidelity index of an undisturbed standard sample, the correction lower limit threshold is determined based on whether the relative error after calibration exceeds a preset range, and a preset minimum tolerance is used for threshold comparison to ensure numerical stability.

[0021] Further, the method for calculating the total calibration factor based on the lifetime deviation and the wavelength deviation specifically comprises: multiplying the wavelength deviation by a preset wavelength calibration coefficient to obtain a wavelength calibration value, multiplying the lifetime deviation by a preset lifetime calibration coefficient to obtain a lifetime calibration value, and adding the two calibration values to obtain the total calibration factor; the wavelength calibration coefficient is determined by linear regression of the normalized concentration deviation and the normalized wavelength deviation through adding an interference substance that only causes the emission wavelength of the fluorescence peak to shift in the standard sample, and the lifetime calibration coefficient is determined by linear regression through adding an interference substance that only affects the average lifetime of the fluorescence in the standard sample; when the original concentration is calibrated using the total calibration factor, the calibrated concentration is calculated based on the correlation between the original concentration and the total calibration factor.

[0022] Further, the method is applied to an in-situ isolation sensing system of a preset in-situ isolation micro-reactor model, the in-situ isolation micro-reactor model including a characteristic permeability coefficient of an interfacial membrane to a target substance and a rejection coefficient of the interfacial membrane to a plurality of main interference substances in a sample, for establishing a mapping relationship between an external sample concentration and an effective concentration inside the micro-reactor to reduce the influence of the interference substances.

[0023] And a fluorescence probe signal calibration system for rapid detection of multiple residues in a complex matrix, comprising:

[0024] A signal acquisition module is configured to acquire a fluorescence signal of a sample to be tested, and analyze the original concentration, the average lifetime of fluorescence, and the emission wavelength of the fluorescence peak of the sample to be tested from the fluorescence signal.

[0025] A deviation calculation module is configured to calculate a lifetime deviation between the average lifetime of fluorescence and a preset reference lifetime, and a wavelength deviation between the emission wavelength of the fluorescence peak and a preset reference wavelength.

[0026] A fidelity index module is configured to calculate a signal fidelity index based on the lifetime deviation and the wavelength deviation.

[0027] A calibration strategy module is configured to determine a corresponding calibration strategy according to a preset threshold interval in which the signal fidelity index falls, the calibration strategy being one of no calibration, performing calibration, or invalidation.

[0028] A concentration calibration module is configured to, when the calibration strategy is performing calibration, calculate a total calibration factor based on the lifetime deviation and the wavelength deviation, calibrate the original concentration using the total calibration factor, and output a calibrated concentration.

[0029] Further, the in-situ isolation sensing unit is further included, and the in-situ isolation sensing unit is preset with an in-situ isolation micro-reactor model, the in-situ isolation micro-reactor model includes a characteristic permeability coefficient of an interface film to the target and a rejection coefficient of the interface film to a plurality of main interferents in a sample, and is used to establish a mapping relationship between an external sample concentration and an effective concentration in the micro-reactor to reduce the influence of the interferents on the fluorescence signal.

[0030] Also, a computer device includes a memory, a processor, and a computer program stored on the memory, and the processor implements the method as described above when executing the computer program.

[0031] A non-transitory computer-readable storage medium has a computer program stored thereon, and the computer program is executed by a processor to implement the method as described above.

[0032] Compared with the prior art, the present application and its preferred schemes at least include the following beneficial effects:

[0033] Compared with the prior art, the present application and its preferred schemes at least include the following beneficial effects:

[0034] The present application breaks through the limitation of traditional calibration methods relying on a single fluorescence intensity parameter, and through synchronous acquisition and analysis of two specific fluorescence physical dimension parameters, i.e., fluorescence average lifetime and fluorescence peak emission wavelength, combined with bias calculation and signal fidelity index evaluation, can quantitatively identify complex interference caused by quenching, background fluorescence and other different physical and chemical processes, and no longer relies on a single signal change to judge the target concentration, thereby providing a reliable interference distinguishing basis for subsequent accurate calibration and avoiding the blindness of traditional calibration methods due to the inability to distinguish interference types.

[0035] A hierarchical closed-loop calibration strategy is constructed, and differential calibration operations are performed according to the threshold interval (highly credible, moderately distorted, and severely distorted) of the signal fidelity index: no calibration is performed for scenes with high signal credibility to avoid introducing additional errors; targeted calibration is started for moderately distorted scenes to ensure correction effectiveness; and invalidity is marked for severely distorted scenes to prompt sample processing requirements. This intelligent decision mechanism effectively prevents the problems of “over-calibration” or “insufficient calibration” in traditional fixed coefficient calibration or unified calibration mode, thereby improving the robustness of the detection system.

[0036] When performing calibration, the calculation of the total calibration factor is not based on a general compensation value, but is based on the fluorescence average lifetime bias and the fluorescence peak emission wavelength bias, and is respectively combined with the preset calibration coefficient calibrated by specific interferents for weighted summation, so that the influence of different types of interference on the detection signal can be compensated in a targeted manner, the complex interference can be accurately decomposed and corrected, and the accuracy of the detection result in a complex matrix is further improved.

[0037] By combining the signal calibration method with the in-situ isolation sensing system, a double anti-interference system of "physical isolation + signal calibration" is formed: the in-situ isolation micro-reactor model reduces the interference of interference substances into the sensing area from the physical layer by means of the characteristic permeability coefficient of the interface film and the exclusion coefficient of the interference substances, and purifies the micro-environment for detection; the signal self-adaptive calibration logic accurately corrects the residual interference that penetrates the physical barrier, and the two work together, compared with the single dependence on signal calibration or physical isolation technology, which significantly enhances the anti-interference ability of the system to complex matrix.

[0038] The corresponding fluorescence probe system of the calibration method is provided, and the computer equipment and non-transient computer readable storage medium for realizing the method are provided, through the integrated design of the functional modules and the matching of the software and hardware carriers, it is ensured that the calibration method can be stably executed, and the problem that the technical scheme only stays at the theoretical level and is difficult to be practically applied is avoided, and an operable complete technical scheme is provided for the multi-residue rapid detection scene. BRIEF DESCRIPTION OF DRAWINGS

[0039] The application will be further described in detail below in combination with the drawings and specific embodiments:

[0040] Figure 1 is a flow chart of the method implemented by the embodiment of the application.

[0041] Figure 2 is a system structure diagram of the embodiment of the application. DETAILED DESCRIPTION

[0042] In order to make the features and advantages of the application more obvious and easy to understand, the following examples are specifically described as follows:

[0043] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in the specification have the same meaning as understood by those skilled in the art to which the present application belongs.

[0044] It should be noted that the terms used herein are only for the purpose of describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form, and in addition, it should be understood that when the terms "comprise" and / or "include" are used in the specification, they indicate the presence of a feature, step, operation, device, component and / or combination thereof.

[0045] To solve the problems in the prior art, the application provides a fluorescent probe signal calibration scheme for rapid detection of multiple residues in a complex matrix, and a corresponding biomimetic enzyme fluorescent probe system for rapid detection of multiple residues and a construction method thereof, which breaks through the limitation of traditional dependence on single fluorescence intensity and innovatively synchronously analyzes two physical dimensions of average lifetime and peak emission wavelength of a fluorescent signal; the core lies in collecting original concentration, fluorescent lifetime and wavelength of a to-be-detected sample, and calculating directional deviation of the original concentration, the fluorescent lifetime and the wavelength from preset reference values; in combination with the deviation, signal fidelity is quantitatively evaluated by a signal fidelity model, and a signal fidelity index is solved; finally, the index is used to determine a total calibration factor by adopting a hierarchical closed-loop calibration strategy, and the original concentration is adaptively closed-loop calibrated; the method can deeply understand and correct complex interference caused by quenching, background fluorescence and the like, and provides a decision basis for realizing accurate and reliable rapid detection.

[0046] Please refer to Figure 1 , first, the most core scheme process of the application is provided, that is, a fluorescent probe signal calibration method for rapid detection of multiple residues in a complex matrix, comprising:

[0047] The fluorescent signal of the to-be-detected sample is collected, and the original concentration, the fluorescent average lifetime and the fluorescent peak emission wavelength of the to-be-detected sample are analyzed from the fluorescent signal;

[0048] The lifetime deviation of the fluorescent average lifetime from a preset reference lifetime and the wavelength deviation of the fluorescent peak emission wavelength from a preset reference wavelength are calculated;

[0049] Based on the lifetime deviation and the wavelength deviation, a signal fidelity index is calculated;

[0050] According to a preset threshold interval into which the signal fidelity index falls, a corresponding calibration strategy is determined, the calibration strategy being one of no calibration, performing calibration or marking invalid;

[0051] When the calibration strategy is performing calibration, a total calibration factor is calculated based on the lifetime deviation and the wavelength deviation, the original concentration is calibrated by using the total calibration factor, and a calibrated concentration is output.

[0052] On this basis, in order to make the purpose, technical scheme and advantages of the application more clear, the following will further introduce the specific implementation scheme, design and construction of the application in combination with several specific embodiments:

[0053] Embodiment 1

[0054] The embodiment provides a biomimetic enzyme fluorescent probe construction scheme for rapid detection of multiple residues, comprising:

[0055] The original concentration, the average lifetime and the peak emission wavelength of the fluorescent signal of the to-be-detected sample are collected;

[0056] Based on the average lifetime collected and the preset reference lifetime, the lifetime orientation deviation is determined;

[0057] Based on the collected peak emission wavelength and the preset reference wavelength, the wavelength orientation deviation is determined;

[0058] By combining lifetime orientation deviation and wavelength orientation deviation, the signal fidelity index is calculated through signal fidelity model prediction.

[0059] Based on the signal fidelity index, lifetime orientation deviation, and wavelength orientation deviation, and in response to a preset correction threshold, the total calibration factor is determined through a hierarchical closed-loop calibration strategy.

[0060] By combining the original concentration and the total calibration factor, the calibrated concentration is output through adaptive closed-loop calibration logic based on sensor signals.

[0061] This invention provides an adaptive calibration method for biomimetic enzyme fluorescent probe signals for rapid detection of multiple residues. This method constructs a complete adaptive closed-loop calibration process, aiming to solve the problem of detection signal distortion caused by complex matrix interference. This method constitutes a technical closed loop from signal acquisition, distortion assessment, graded calibration to final concentration output.

[0062] In a specific implementation scenario, such as detecting pesticide residues in fruit and vegetable juices, the execution flow of this method is as follows:

[0063] The raw signal of the sample to be tested is collected, and the raw concentration is calculated. The original concentration here This refers to the target concentration calculated directly based on raw signals such as fluorescence intensity before any calibration; simultaneously, using time-correlated single-photon counting technology, two key signal characteristic dimensions are acquired: the average lifetime of the fluorescence signal. and peak emission wavelength .

[0064] Based on the collected average lifespan and preset reference lifespan Determine lifetime orientation deviation Based on the collected peak emission wavelength and the preset reference wavelength Determine wavelength orientation deviation Reference lifespan here With reference wavelength The reference value in the reference signal database is previously established by measuring a series of standard samples in an ideal buffer solution without any interference, and the purpose is to provide a vector basis with clear physical meaning for subsequent signal quality evaluation and accurate calibration; combined with the lifetime directional deviation and the wavelength directional deviation, the signal fidelity index is calculated by signal fidelity model prediction ; the signal fidelity index here is a real-time quantitative evaluation of the purity or reliability of the current detection signal; according to the signal fidelity index , the lifetime directional deviation and the wavelength directional deviation, and in response to the preset correction threshold, the total calibration factor is determined by the hierarchical closed-loop calibration strategy; the total calibration factor here is a calibration amount triggered by the signal fidelity index and driven by the specific lifetime directional deviation and the wavelength directional deviation; combined with the original concentration and the total calibration factor , the calibrated concentration is output by the self-adaptive closed-loop calibration logic of the sensing signal, and the calculation logic is .

[0065] The present application realizes the self-adaptive calibration of the detection signal by constructing a complete closed loop from multi-dimensional signal acquisition, fidelity evaluation, hierarchical calibration to concentration output; compared with the method of relying on single signal intensity or using fixed coefficient for calibration in the prior art, the present application can identify and quantify the complex interference caused by different sources such as quenching and background fluorescence in real time and dynamically, and take differentiated calibration strategies according to the reliability of the signal, greatly improving the accuracy and reliability of the detection result in complex matrix.

[0066] Embodiment 2:

[0067] On the basis of the above embodiments, the present embodiment provides a specific design of signal fidelity model prediction, including:

[0068] Based on the wavelength directional deviation and the reference wavelength, the wavelength normalized square deviation is calculated;

[0069] Based on the lifetime directional deviation and the reference lifetime, the lifetime normalized square deviation is calculated;

[0070] The weighted deviation sum is generated by weighted sum of the wavelength normalized square deviation and the lifetime normalized square deviation;

[0071] The signal fidelity index is obtained by subtracting the weighted deviation sum from the preset reference value 1.

[0072] The embodiment is a specific implementation of the signal fidelity model prediction of embodiment 1, which aims to provide an accurate and robust mathematical model for calculating the signal fidelity index The model is constructed by borrowing the concept of distance measurement in multi-dimensional space, and the deviation of the real-time measured signal feature points from the reference points in the normalized feature space is taken as the measure of signal distortion.

[0073] The specific calculation process of the model is as follows: based on the wavelength directional deviation and the reference wavelength, the wavelength normalized square deviation is calculated; the normalization process aims to eliminate the dimensional influence of different wavelength ranges, so that the wavelength deviations of different detection items are comparable; the square processing aims to amplify the effect of deviation and make it always positive; similarly, based on the life directional deviation and the reference life, the life normalized square deviation is calculated; the weighted sum of the wavelength normalized square deviation and the life normalized square deviation is calculated to generate the weighted deviation sum:

[0074]

[0075] wherein, and are two dimensionless weight coefficients, which are used to adjust the contribution of the two-dimensional deviation in the final evaluation according to the sensitivity difference of the probe system to different types of interference, and satisfy ; the two weight coefficients are not arbitrarily set, but are determined by multivariate linear regression analysis on a calibration data set containing multiple known types and concentrations of interferents, so as to quantify the relative influence of wavelength and life change on the accuracy of concentration measurement.

[0076] The specific determination steps are as follows: prepare at least 20 groups of standard samples containing different types and concentration gradient interferents, and the true concentration of each group of samples is known; measure the , and of each group of samples, calculate the normalized concentration deviation , the normalized wavelength deviation and the normalized life deviation ; establish a multivariate linear regression model , and solve the coefficients and using the least square method; normalize the regression coefficients to obtain and , and ensure ; verify the goodness of fit of the regression model Should be greater than 0.85, otherwise need to increase the sample size or optimize the experimental conditions to recalibrate.

[0077] Subtract the weighted deviation from the preset reference value 1 to obtain the signal fidelity index The final mathematical expression is:

[0078]

[0079] On the basis of the basic signal fidelity model concept defined in embodiment 1, this embodiment provides a specific implementation based on the normalized Euclidean distance idea; the model eliminates the influence of dimension and deviation direction through normalization and square processing, making the evaluation more objective; by introducing the calibratable weight coefficient And The model is flexible and can be optimized according to specific application scenarios.

[0080] To ensure the physical meaning of And the effectiveness of the subsequent hierarchical calibration strategy, the boundary processing is performed on the calculation result: when the calculated Value is greater than 1, it is truncated to 1, indicating that the signal quality exceeds the expectation and is still processed as a high-quality signal; when the calculated Value is less than 0, it is truncated to 0, indicating that the signal is severely distorted and will be determined as invalid in the subsequent hierarchical calibration strategy; after boundary processing, Strictly between 0 and 1, providing a highly reliable and quantitatively accurate decision basis for the subsequent hierarchical calibration strategy.

[0081] Embodiment 3:

[0082] On the basis of the above embodiments, this embodiment provides a specific design of the hierarchical closed-loop calibration strategy, including:

[0083] In response to the signal fidelity index being greater than or equal to a preset high-confidence threshold, the total calibration factor is determined to be zero;

[0084] In response to the signal fidelity index being less than the high-confidence threshold and greater than or equal to a preset correction lower threshold, the total calibration factor is composed of the weighted sum of the wavelength directional deviation and the lifetime directional deviation;

[0085] In response to the signal fidelity index being less than the correction lower threshold, an invalid identification is output.

[0086] This embodiment is a specific implementation of the hierarchical closed-loop calibration strategy of embodiment 1, and its purpose is to establish an intelligent decision logic to avoid uniform calibration of all signals, thereby improving the accuracy of calibration and the reliability of the results; the strategy is based on the signal fidelity index Performing different operations in different intervals.

[0087] The execution logic of this strategy involves two key preset thresholds: high-confidence threshold and correction lower limit threshold ; the values of these two thresholds are not empirically set, but are determined by statistical analysis of a large number of historical experimental data containing different interference levels; specifically, the determination method of high-confidence threshold is to select at least 30 groups of standard samples without interference, calculate the distribution of signal fidelity index , and take the 95% confidence lower limit of the distribution as , the typical numerical range is 0.85-0.95; the determination method of correction lower limit threshold is to prepare a series of samples with known interference concentrations, calculate their values and relative errors after calibration respectively, when the relative error exceeds the preset acceptable range, the corresponding value is , the typical numerical range is 0.50-0.65.

[0088] For example, high-confidence threshold can be set as the confidence lower limit covering 95% of the distribution of standard samples without interference , to ensure that statistical normal system fluctuations are not misjudged as interference; correction lower limit threshold can be set as the value when the prediction error of the calibration model starts to exceed the preset acceptable range such as 10%, and below this value it is considered that the signal distortion cannot be reliably corrected.

[0089] In response to the signal fidelity index being greater than or equal to the preset high-confidence threshold, that is, when , the system determines that the current signal quality is extremely high and almost not interfered, and determines the total calibration factor as zero, that is ; in response to the signal fidelity index being less than the high-confidence threshold and greater than or equal to the preset correction lower limit threshold, that is, when , the system determines that the signal has been moderately interfered and needs to be calibrated, and the total calibration factor is composed of the weighted sum of wavelength directional deviation and lifetime directional deviation; in response to the signal fidelity index being less than the correction lower limit threshold, that is, when , the system determines that the signal has been severely distorted, and outputs an invalid identifier and prompts the user to take sample pretreatment measures.

[0090] In actual implementation, considering the precision problem of floating-point number operation, a small tolerance value is set for threshold comparison: when , it is considered that It falls into the high confidence interval; when At that time, it is considered The tolerance is included in the correction interval; this tolerance processing ensures the numerical stability of the algorithm.

[0091] This embodiment introduces a hierarchical calibration logic, elevating the calibration process from a single calculation step to an intelligent decision-making process. It achieves an intelligent response of no calibration for high reliability, fine calibration for moderate distortion, and early warning for severe contamination, greatly enhancing the robustness of the system and effectively preventing erroneous calibration.

[0092] Example 4:

[0093] Based on the above embodiments, this embodiment provides a specific design for constructing a total calibration factor by weighting the wavelength orientation deviation and lifetime orientation deviation, including:

[0094] Multiply the wavelength orientation deviation by the preset wavelength calibration coefficient to obtain the wavelength calibration value;

[0095] Multiply the lifetime orientation deviation by the preset lifetime calibration coefficient to obtain the lifetime calibration value;

[0096] The total calibration factor is obtained by adding the wavelength calibration value to the lifetime calibration value.

[0097] This embodiment is based on Embodiment 3, in the correction area. The specific implementation of the technical feature of the total calibration factor consisting of the weighted sum of wavelength orientation deviation and lifetime orientation deviation aims to provide a calibration factor calculation method that can trace the source and accurately eliminate different types of interference.

[0098] Multiplying the wavelength orientation deviation by a preset wavelength calibration coefficient yields the wavelength calibration value; here, the wavelength calibration coefficient... It is a dimensionless parameter determined through calibration experiments; the calibration method is as follows: Add interfering substances, such as background fluorescent agents, that primarily cause wavelength shift to the standard sample, and set a series of concentration gradients; the normalized concentration deviation is then measured... Deviation from normalized wavelength A linear regression analysis is performed on the relationship between them, and the slope of the resulting straight line is... Similarly, the lifetime orientation deviation is multiplied by a preset lifetime calibration coefficient to obtain the lifetime calibration value; here, the lifetime calibration coefficient is... The calibration process and Similarly, the difference lies in the addition of interfering substances that primarily affect fluorescence lifetime, such as quenchers; the total calibration factor is obtained by adding the wavelength calibration value to the lifetime calibration value. The final mathematical expression is:

[0099]

[0100] wherein the model assumes that the measurement bias effects caused by different physicochemical processes are linearly independent, and the total calibration factor can be first-order approximated by the weighted sum of each bias component; the embodiment proposes a calculation formula, which is innovative in that the calibration is no longer based on the general signal distortion, but on the directional bias with clear physical traceability; by introducing decoupled calibration coefficients and the calibration model can distinguish and compensate for the measurement bias caused by different physicochemical processes; for example, when quenching and background fluorescence coexist, the model can accurately calculate the total calibration direction and amplitude according to the respective bias size and calibration coefficient, achieving precise and directional calibration of the composite interference.

[0101] Embodiment 5:

[0102] Based on the above embodiments, the embodiment provides a specific design of the method applied to an in-situ isolation sensing system, and the system presets an in-situ isolation micro-reactor model.

[0103] The in-situ isolation micro-reactor model is used to establish a mathematical relationship between the external sample concentration and the effective concentration inside the micro-reactor.

[0104] The in-situ isolation micro-reactor model comprises:

[0105] a characteristic permeability coefficient of the interface film to the target substance;

[0106] a rejection coefficient of the interface film to multiple main interference substances in the sample;

[0107] wherein the internal effective concentration is determined by the external sample concentration, the characteristic permeability coefficient, and the concentrations and rejection coefficients of all main interference substances.

[0108] The embodiment describes the application of the aforementioned signal adaptive calibration method to a specific physical system, namely an in-situ isolation sensing system; the application of the method is based on a designed sensing microenvironment; for this purpose, the system presets an in-situ isolation micro-reactor model.

[0109] The purpose of the in-situ isolation micro-reactor model is to pre-process and quantify the fundamental influence of matrix interference on target detection from the dimensions of physical layer and mathematical model; the core of the model is to construct an intelligent response interface film on the sensing surface of the probe, forming a micro-reactor, so as to realize in-situ isolation of the target analyte and most of the interference substances at the molecular level; the model is used to establish a mathematical relationship between the external sample concentration and the effective concentration inside the micro-reactor .

[0110] The in-situ isolation micro-reactor model materializes its core components, and its mathematical expression is inspired by the competitive inhibition model of enzyme reactions in biochemistry:

[0111]

[0112] wherein, refers to the effective concentration of the target substance that can actually react with the biomimetic enzyme probe inside the micro-reactor; refers to the actual concentration of the target substance in the original sample to be tested, which can be obtained by standard analysis methods; is the characteristic permeability coefficient of the interface film to the target substance, which is a dimensionless parameter, and is calibrated by using non-interfering pure target substance standard solution for penetration experiment, representing the maximum transport efficiency of the interface film to the target analyte; is the rejection coefficient of the interface film to the th main interferent in the sample, with a unit of , which is determined by competitive penetration experiment in a solution containing a single interferent, reflecting the inhibition intensity of the specific interferent to the transport of the target substance; refers to the concentration of the th main interferent in the sample, and its type and concentration range are obtained by pre-analysis in the design stage through standard analysis methods such as high-performance liquid chromatography-mass spectrometry.

[0113] The model is based on the following physical assumptions and applicable conditions: the transport of the interface film to the target substance and the interferent follows the passive diffusion mechanism, complying with Fick's first law; there are competitive binding sites for the interferent and the target substance at the membrane interface, and the binding of the interferent reduces the effective permeability of the target substance; the system is in a steady state, i.e. the concentration gradient inside and outside the membrane is constant; the model is applicable to the case where the concentration of the interferent does not exceed the saturation concentration of the membrane, when the concentration of a certain interferent is extremely high, a modified Langmuir adsorption model should be used; the model assumes that the inhibition effects of each interferent are independent and can be linearly superimposed, which is true in most actual samples, but for special systems with synergistic interference effects, cross terms need to be introduced for correction.

[0114] Combining the signal calibration logic with the physical isolation model, a dual anti-interference system of physical isolation and signal correction is constructed; the in-situ isolation micro-reactor at the physical level serves as the first line of defense, purifying the sensing micro-environment from the source; the signal self-adaptive closed-loop calibration logic at the mathematical level serves as the second line of defense, accurately identifying and correcting the signal distortion caused by residual interference that has penetrated the physical barrier; this combination of software and hardware design produces a synergistic anti-interference ability, which significantly surpasses any single method.

[0115] Example 6:

[0116] Based on the above embodiments, this embodiment provides a specific design scheme for evaluating the anti-interference capability of the in-situ isolated sensing system using a composite evaluation model of probe system detection performance:

[0117] The evaluation model introduces an isolation synergy factor to characterize the performance leap brought about by the in-situ isolated sensing system. The value of the isolation synergy factor is determined by the microscopic physical characteristics of the in-situ isolated microreactor.

[0118] After constructing the in-situ isolation sensing system, to quantitatively evaluate its superior anti-interference capability, this embodiment further introduces a composite evaluation model for probe system detection performance. This evaluation model is mainly used in the system design and optimization stages, and specific application scenarios include: in the research and development stage, comparing the isolation synergy factors of different interface film materials. Values ​​guide the selection and optimization of membrane materials; during the system validation phase, measurements are used to... The evaluation assesses whether the overall system performance meets the design specifications; during the quality control phase, the performance of standard samples is measured periodically. The value is used to monitor whether the system performance is stable. This evaluation model does not participate in the real-time calibration calculation in the daily testing process, but serves as a macro-level evaluation tool for system performance. Its purpose is to break the limitation of the separation between sensitivity and robustness in traditional evaluation and establish a single indicator that can comprehensively reflect the synergistic improvement of the two.

[0119] The core innovation of this evaluation model lies in the introduction of an isolation synergy factor. This is used to macroscopically and quantitatively characterize the performance leap brought about by in-situ isolated sensing systems; isolation synergy factor. The value is directly determined by the microscopic physical properties of the in-situ isolated microreactor, that is, by the permeability of the interfacial membrane to the target analyte. and repulsion of interfering substances Jointly determined; its inherent logical relationship can be expressed as better isolation performance, i.e., higher... and This will lead to The value approaches 0; for conventional probes that do not possess the isolation structure of this invention, its The value approaches 1.

[0120] The mathematical expression for this performance composite evaluation model is:

[0121]

[0122] in, The performance synergy index is a dimensionless comprehensive index. The higher the value, the stronger the anti-interference capability of the probe system while maintaining high sensitivity. The ideal signal-to-noise ratio is measured in a pure buffer solution without any interference, representing the theoretical upper limit of the performance of the probe system; The matrix interference coefficient is a dimensionless parameter between 0 and 1, which quantifies the inherent interference strength of a specific sample matrix, and its value is classified and assigned according to the complexity of the sample to be measured; The isolation synergy factor is a physical quantity that represents the inhibition ability of the isolation system to the matrix interference, The greater the value, the better the isolation effect and the stronger the inhibition of interference; for a traditional probe without the isolation structure of the present application, Tends to 0, at which time The model degenerates to The performance decreases linearly with the interference; for a system with good isolation performance, The value is relatively large, typically in the range of 2-5, at which time Significantly reduced, so that even at a larger Value, Still remains small, so that Remains at a high level.

[0123] In specific implementation, its exact value is measured by experiments in a variety of known interference coefficient Matrices, and the experimental data points Are nonlinearly fitted, the fitting function is And the value of Is obtained by least squares method; the goodness of fit Should be greater than 0.90 to ensure the reliability of the model.

[0124] The physical reasonableness of the model is that when There is no interference, i.e. , which conforms to the ideal case; when And , i.e. extremely strong interference and no isolation, , which conforms to the complete failure case; when Increases, the value of Significantly improves under the same interference level, quantitatively reflecting the performance transition brought by isolation.

[0125] The evaluation model provides a new scientific method for quantitatively evaluating the comprehensive performance of the probe system; through the core parameter of isolation synergy factor It directly links the microscopic film material properties , With the macroscopic system anti-interference performance For the first time; it not only proves that the system of the present application is superior to the traditional system, but also can be used as a research and development tool to quantitatively compare the The value is used to guide and optimize the design of in-situ isolated microreactors.

[0126] Example 7:

[0127] Please see Figure 2 Based on the method design of the above embodiments, this embodiment further provides a systematic implementation scheme, including:

[0128] The signal acquisition module is used to acquire the original concentration of the sample to be tested, the average lifetime of the fluorescence signal, and the peak emission wavelength.

[0129] The deviation determination module is used to determine the lifetime orientation deviation and wavelength orientation deviation based on the acquired average lifetime and peak emission wavelength, combined with the preset reference lifetime and reference wavelength.

[0130] The fidelity index calculation module is used to calculate the signal fidelity index by combining lifetime orientation deviation and wavelength orientation deviation.

[0131] The calibration factor determination module is used to determine the total calibration factor based on the signal fidelity index, lifetime orientation deviation, and wavelength orientation deviation, and in response to a preset correction threshold.

[0132] The concentration output module is used to combine the original concentration with the total calibration factor to output the calibrated concentration.

[0133] The system provided in this embodiment of the invention is a physical carrier for implementing the above-described method, and integrates multiple functional modules that work together to achieve high-precision adaptive detection.

[0134] The system includes a signal acquisition module, a deviation determination module, a fidelity index calculation module, a calibration factor determination module, and a concentration output module.

[0135] The signal acquisition module consists of a high-sensitivity fluorescence detector and a time-correlated single-photon counting controller. It is responsible for performing optical measurements on the sample and resolving the data to calculate the original concentration. Required fluorescence intensity, average lifetime of fluorescence signal and peak emission wavelength .

[0136] The deviation determination module has a built-in reference lifespan. and reference wavelength The reference database receives signals from the signal acquisition module. and The lifetime orientation deviation and wavelength orientation deviation are determined by performing subtraction operations.

[0137] The fidelity index calculation module is a core processor in which a signal fidelity model algorithm is solidified, takes the lifetime directional deviation and the wavelength directional deviation as inputs, and calls preset weight coefficients and to calculate the signal fidelity index .

[0138] The calibration factor determination module is also implemented in the core processor, and a hierarchical closed-loop calibration strategy and a total calibration factor calculation formula are embedded in the core processor, and the total calibration factor is determined according to the signal fidelity index , and in response to a preset high-trust threshold and a correction lower threshold . .

[0139] The concentration output module receives the original concentration and the total calibration factor , performs a final calibration operation , and outputs the calibrated concentration to a display interface or a data recording system.

[0140] The present application provides a highly integrated and automated detection system; by solidifying complex calibration algorithms and decision logic into different functional modules, full-process automation from sample measurement to result output is achieved; compared with traditional equipment that requires manual interpretation of spectra and manual data correction, the present system can provide real-time, objective and intelligently calibrated detection results, significantly improving detection efficiency and result reliability, and is particularly suitable for on-site rapid detection and other application scenarios.

[0141] Compared with the prior art, the present application has the following beneficial effects:

[0142] 1. The limitations of traditional single fluorescence intensity are broken through, and a signal fidelity model is constructed by synchronously analyzing two additional physical dimensions of fluorescence lifetime and peak emission wavelength; the model can evaluate the reliability of the detection signal in real time and quantitatively, and deeply understand the complex interference caused by different physical and chemical processes such as quenching and background fluorescence, providing a reliable decision basis for subsequent accurate calibration;

[0143] 2. Based on the signal fidelity index, the present application establishes an intelligent hierarchical closed-loop calibration strategy; the strategy can take differentiated measures according to the degree of signal distortion: high-quality signals are not calibrated to avoid introducing errors; fine calibration is started for moderately distorted signals; and a warning prompt is issued for severely contaminated signals; this intelligent decision mechanism greatly improves the robustness of the system and effectively prevents the occurrence of false calibration;

[0144] 3. When calibration is needed, the total calibration factor of the present application is not a general compensation value, but is calculated by weighting the life deviation and the wavelength deviation combined with respective independent calibration coefficients; these calibration coefficients are obtained by introducing the calibration experiment of specific types of interferents, so that the calibration can be traced to specific physical interference sources, thereby realizing the accurate identification and directional compensation of multiple interferences in complex matrices;

[0145] 4. The present application combines intelligent signal calibration algorithm with physical sensing system of in-situ isolated microreactor; physical isolation as the first line of defense purifies the sensing microenvironment from the source, greatly reducing the influence of interferents; signal self-adaptive calibration logic as the second line of defense accurately corrects the residual interference that penetrates the physical barrier; this dual anti-interference design of software and hardware produces a synergistic effect, significantly improving the accuracy and reliability of detection in complex samples.

[0146] Based on the same inventive concept, the present application also provides a computer device, which comprises one or more processors and a memory for storing one or more computer programs; the program comprises program instructions, and the processor is configured to execute the program instructions stored in the memory. The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is used to implement one or more instructions, and is specifically used to load and execute one or more instructions in the computer storage medium to realize the above-mentioned method.

[0147] It should be further noted that based on the same inventive concept, the present application also provides a computer storage medium, which stores a computer program, and the computer program is run by a processor to execute the above method. The storage medium can adopt any combination of one or more computer readable media. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, infrared, or semiconductor system, device or apparatus, or any combination of the above. More specific examples (non-exhaustive list) of the computer readable storage medium include: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or apparatus.

[0148] It should be noted that unless otherwise defined, technical or scientific terms used in the present application should be understood as having the common meaning in the field of the present application to those having ordinary skill in the art. The terms "first", "second" and similar terms used in the present application do not denote any order, quantity or importance, but are only used to distinguish different components. The terms "include" or "contain" and similar terms mean that the elements or objects before the terms cover the elements or objects listed after the terms and their equivalents, and do not exclude other elements or objects. The terms "connected" or "connected" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to represent relative positional relationships, and when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0149] The above is only the preferred embodiment of the present application, and is not intended to limit the other forms of the present application. Any skilled person in the art can modify or change the above disclosed technical content to equivalent embodiments. However, any simple modification, equivalent change and modification of the above embodiments without departing from the technical solution of the present application, and according to the technical essence of the present application, still belongs to the protection scope of the technical solution of the present application.

[0150] The present application is not limited to the above best mode, and anyone can derive other various forms of a fluorescent probe signal calibration method and system for rapid detection of multiple residues in complex matrices under the inspiration of the present application. Any equivalent changes and modifications made within the scope of the present application should be included in the scope of the present application.

Claims

1. A method for calibrating fluorescent probe signals for rapid detection of multiple residues in complex matrices, characterized in that, include: The fluorescence signal of the sample to be tested is collected, and the original concentration, average fluorescence lifetime and fluorescence peak emission wavelength of the sample are extracted from it. Calculate the lifetime deviation between the average fluorescence lifetime and the preset reference lifetime, and the wavelength deviation between the peak fluorescence emission wavelength and the preset reference wavelength; Based on the lifetime deviation and wavelength deviation, the signal fidelity index is calculated. Based on the preset threshold range into which the signal fidelity index falls, a corresponding calibration strategy is determined, wherein the calibration strategy is one of no calibration, performing calibration, or marking as invalid. When the calibration strategy is to perform calibration, a total calibration factor is calculated based on the lifetime deviation and wavelength deviation, and the original concentration is calibrated using the total calibration factor to output the calibrated concentration.

2. The fluorescent probe signal calibration method for rapid detection of multiple residues in complex matrices according to claim 1, characterized in that: When acquiring the fluorescence signal, time-correlated single-photon counting technology is used to obtain the average fluorescence lifetime and the peak emission wavelength of fluorescence. The original concentration is obtained by analyzing the fluorescence intensity signal acquired by the high-sensitivity fluorescence detector. The lifetime deviation is the difference between the average fluorescence lifetime and the preset reference lifetime, and the wavelength deviation is the difference between the peak emission wavelength of fluorescence and the preset reference wavelength.

3. The fluorescent probe signal calibration method for rapid detection of multiple residues in complex matrices according to claim 1, characterized in that: The method for calculating the signal fidelity index based on the lifetime deviation and wavelength deviation specifically includes: squaring the ratio of the wavelength deviation to a preset reference wavelength to obtain a wavelength normalized squared deviation; squaring the ratio of the lifetime deviation to a preset reference lifetime to obtain a lifetime normalized squared deviation; weighting and summing the two normalized squared deviations to generate a weighted deviation sum; subtracting the weighted deviation sum from a preset reference value of 1 to obtain the signal fidelity index; after calculating the signal fidelity index, if it is greater than 1, adjusting it to 1, and if it is less than 0, adjusting it to 0, so that the index is in the 0-1 range.

4. The fluorescent probe signal calibration method for rapid detection of multiple residues in complex matrices according to claim 1, characterized in that: The preset threshold range includes a high confidence threshold and a lower correction threshold, wherein: when the signal fidelity index is not lower than the high confidence threshold, the calibration strategy is no calibration; when the signal fidelity index is not lower than the lower correction threshold but lower than the high confidence threshold, the calibration strategy is to perform calibration; when the signal fidelity index is lower than the lower correction threshold, the calibration strategy is to mark it as invalid; the high confidence threshold is determined based on the statistical distribution of the signal fidelity index of interference-free standard samples, and the lower correction threshold is determined based on whether the relative error after calibration exceeds a preset range, and a preset minimum tolerance judgment is used when comparing thresholds to ensure numerical stability.

5. The fluorescent probe signal calibration method for rapid detection of multiple residues in complex matrices according to claim 1, characterized in that: The method for calculating the total calibration factor based on the lifetime deviation and wavelength deviation specifically includes: multiplying the wavelength deviation by a preset wavelength calibration coefficient to obtain a wavelength calibration value, multiplying the lifetime deviation by a preset lifetime calibration coefficient to obtain a lifetime calibration value, and adding the two calibration values ​​to obtain the total calibration factor; the wavelength calibration coefficient is determined by adding an interfering substance that only causes a shift in the fluorescence peak emission wavelength to the standard sample and performing linear regression on the normalized concentration deviation and the normalized wavelength deviation; the lifetime calibration coefficient is determined by adding an interfering substance that only affects the average fluorescence lifetime to the standard sample and performing linear regression in the same way; when calibrating the original concentration using the total calibration factor, the calibrated concentration is calculated based on the correlation between the original concentration and the total calibration factor.

6. The fluorescent probe signal calibration method for rapid detection of multiple residues in complex matrices according to claim 1, characterized in that: The method is applied to an in-situ isolation sensing system based on a pre-defined in-situ isolation microreactor model. The in-situ isolation microreactor model includes the characteristic permeability coefficient of the interface membrane to the target analyte and the repulsion coefficient of various major interfering substances in the sample. This model is used to establish a mapping relationship between the external sample concentration and the effective concentration inside the microreactor in order to reduce the influence of interfering substances.

7. A fluorescent probe signal calibration system for rapid detection of multiple residues in complex matrices, characterized in that, include: The signal acquisition module is used to acquire the fluorescence signal of the sample to be tested and to extract the original concentration, average fluorescence lifetime and fluorescence peak emission wavelength of the sample to be tested. The deviation calculation module is used to calculate the lifetime deviation between the average fluorescence lifetime and the preset reference lifetime, and the wavelength deviation between the fluorescence peak emission wavelength and the preset reference wavelength. The fidelity index module is used to calculate the signal fidelity index based on the lifetime deviation and wavelength deviation. The calibration strategy module is used to determine the corresponding calibration strategy based on the preset threshold range into which the signal fidelity index falls. The calibration strategy is one of no calibration, performing calibration, or marking as invalid. The concentration calibration module is used to calculate the total calibration factor based on the lifetime deviation and wavelength deviation when the calibration strategy is to perform calibration, and to calibrate the original concentration using the total calibration factor, and output the calibrated concentration.

8. A fluorescent probe signal calibration system for rapid detection of multiple residues in complex matrices according to claim 7, characterized in that: It also includes an in-situ isolation sensing unit, which is based on an in-situ isolation microreactor model. The in-situ isolation microreactor model includes the characteristic permeability coefficient of the interface membrane to the target and the repulsion coefficient of various major interfering substances in the sample. It is used to establish a mapping relationship between the external sample concentration and the effective concentration inside the microreactor to reduce the influence of interfering substances on the fluorescence signal.

9. A computer device, characterized in that, It includes a processor and a memory, the memory storing a computer program, and the processor, when executing the computer program, implements the method of any one of claims 1-6.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-6.

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