Search

CN-121994770-A - Intelligent mapping method for clenbuterol concentration based on Raman scattering space-time dynamic attenuation characteristics

CN121994770ACN 121994770 ACN121994770 ACN 121994770ACN-121994770-A

Abstract

The invention relates to an intelligent mapping method for clenbuterol concentration based on Raman scattering space-time dynamic attenuation characteristics. The method is based on a theoretical model of molecular dynamics and statistical physics, inverts frequency domain spectral information to a time domain coherence function, establishes a clenbuterol molecule free state-cluster state double-pool dynamics model, reveals the internal correlation of concentration and molecule aggregation state and coherence attenuation for the first time, can automatically identify abnormal samples in clenbuterol detection and provide a quality scoring mechanism, has obviously improved sensitivity and measuring range compared with the traditional Raman spectrum detection, reduces the detection limit from 10-50 mug/kg to 0.42 mug/kg, improves 20-100 times, achieves national standard requirements (< 0.5 mug/kg), extends the linear range of measuring range from 1-2 orders of magnitude to 3-4 orders of magnitude (0.5-500 mug/kg), covers trace detection of high-residue full scenes, and can be further extended to detection of other small molecules without depending on specific chemical properties of substances.

Inventors

  • PENG YANKUN
  • Yin Tianzhen
  • LI YONGYU
  • MA ZHENHAO
  • JIA MINGJUAN

Assignees

  • 中国农业大学

Dates

Publication Date
20260508
Application Date
20251211

Claims (10)

  1. 1. An intelligent mapping method for the concentration of clenbuterol based on Raman scattering space-time dynamic attenuation characteristics is characterized by comprising the following steps: step 1, acquiring space-time multi-mode Raman spectrum data of a sample to be detected containing clenbuterol, and constructing a four-dimensional Raman spectrum data tensor Wherein the sample space is maintained By determining the dividing points of the three-dimensional space occupied by the sample, the two are shared Space points, sample measurement time dimension By determining the time duration axis demarcation, co-ordinates Time points, frequency dimensions of sample measurement Is the wave number range of Raman spectrum, co-existing A plurality of pixel points; step 2, for the step 1 obtained Carrying out space heterogeneity quantification on each peak intensity of Raman spectrum at each space point to obtain a variation coefficient By means of Judging the distribution condition of each peak of the Raman spectrum at each spatial point; Step 3, performing autocorrelation function on each time point of single space point Calculating, extracting fluctuation memory time Is a time lag; Step 4, deducting the strong fluorescence background in the Raman spectrum based on the asymmetric weighted least square method to obtain a purified Raman signal Wherein In the case of a raman spectrum, The fluorescence background estimated value after n times of iteration; step 5, for the clenbuterol characteristic Raman peak shape in the purified Raman signal obtained in step 4 Fitting by using a Voigt function, and extracting frequency domain characteristic parameters; Step 6, fitting the fitting peak shape obtained in the step 5 by adopting a clenbuterol free state and cluster attenuation dynamics model, and establishing the cluster degree of the cluster Concentration with clenbuterol Is a relationship equation of (2); Step 7, using the track arc length Unique parameterized clenbuterol concentration ; Step 8, extracting multi-domain features by integrating the results obtained in the steps 2,3 and 7, and constructing feature vectors ; Step 9, time-frequency consistency Spatial representation And time drift Weighting and integrating according to the comprehensive quality score And (5) carrying out comprehensive scoring and uncertainty evaluation on the concentration of the clenbuterol and outputting a final concentration report.
  2. 2. The intelligent mapping method for the concentration of clenbuterol based on Raman scattering space-time dynamic attenuation characteristics is characterized by comprising the following steps of: Introduction of the Hurst index in step 2 To further determine the distribution mode of each peak of the raman spectrum, the formula is as follows: For the step 1 Extracting the peak intensity at specific wave number to form a space intensity sequence Calculating Hurst index by heavy scale range analysis, for length of Calculates the range of the subinterval of (2) And standard deviation of Based on the ratio of the scale law relation By double logarithmic regression Solving the slope to obtain Hurst index 。
  3. 3. The intelligent mapping method of the clenbuterol concentration based on the raman scattering spatiotemporal dynamic decay characteristic as set forth in claim 1, wherein the variation coefficient CV in the step 2 is calculated by the following formulas: For the following Raman spectrum peak intensity measured by each space point The method comprises the following steps: Peak intensity mean value ; Standard deviation of ; Coefficient of variation 。
  4. 4. The intelligent mapping method for the concentration of clenbuterol based on Raman scattering spatiotemporal dynamic decay characteristics as set forth in claim 1, wherein said autocorrelation function in step 3 The method comprises the following steps: time series for a single spatial point There is ; Wherein, the Representing a time average; in order for the time to be delayed in time, Is the intensity variance; the fluctuation memory time Concentration with clenbuterol The following power law scale relationship is established: ; Wherein: Is the reference concentration Characteristic fluctuation time; is a kinetic scale index.
  5. 5. The intelligent mapping method for the concentration of clenbuterol based on the raman scattering spatiotemporal dynamic decay characteristic of claim 1, wherein the algorithm formula of the asymmetric weighted least square method in the step 4 is as follows: ; Wherein: indexing pixel points of the Raman spectrum; Is that The first iteration The weight value of each pixel point; Is at wave number Measuring the intensity of the original Raman spectrum at the position; an estimated value of a fluorescence background baseline to be solved at the wave number is obtained; The method is characterized in that a smoothness regularization coefficient is adopted, the smoothness of a fluorescence baseline is guaranteed by a second derivative term in the method, and a weight updating rule is as follows: If it is Then Otherwise 。
  6. 6. The intelligent mapping method for the concentration of clenbuterol based on the raman scattering spatiotemporal dynamic decay characteristic of claim 1, wherein the fitting in step 5 is performed by using a Voigt function as shown in the following formula: ; the objective function is: ; Wherein, the For the peak amplitude of the wave, In the position of the center of the peak, Is Lorentzian full width at half maximum, Is a Gaussian full width at half maximum; Is the first Standard deviation of data points; as an integral variable, represents the amount of frequency mismatch.
  7. 7. The intelligent mapping method for clenbuterol concentration based on Raman scattering spatiotemporal dynamic attenuation characteristics as claimed in claim 1, wherein the clustering degree in step 6 is as follows Concentration with clenbuterol The relation equation of (2) is: ; Wherein the method comprises the steps of Is the total concentration of clenbuterol molecules in a free state and a clustered state, To memorize the time by the fluctuation described in step 3 The corrected cluster reaction equilibrium constant is shown in the following formula: ; Wherein, the Is a reference equilibrium constant in the environment of standard solution; is the ambient coupling coefficient.
  8. 8. The intelligent mapping method for the concentration of clenbuterol based on the features of Raman scattering spatiotemporal dynamic decay as set forth in claim 1, wherein said using the trajectory arc length s to uniquely parameterize the concentration of clenbuterol in step 7 The following formula is shown: For concentration sequences Corresponding parameter points , wherein, For the total number of standard sample concentration gradients, define For index in the concentration sequence, for the first Concentration points Its track arc length The calculation formula of (2) is as follows: initial conditions: ; Wherein: In order to characterize the decay rate, Peak width or peak intensity; The normalized characteristic value; The normalized characteristic value; to balance the weight coefficients of the two feature dimensions.
  9. 9. The intelligent mapping method of the clenbuterol concentration based on the raman scattering space-time dynamic attenuation characteristics as set forth in claim 8, wherein the step 8 is specifically: The feature vector is constructed as 。
  10. 10. The intelligent mapping method of the clenbuterol concentration based on the raman scattering space-time dynamic attenuation characteristics as set forth in claim 8, wherein the step 9 is specifically: the comprehensive quality score expression is: ; the final concentration report is in the form of: ; in the above formulae: the nominal concentration is obtained by mapping the track arc length s in the step 7; is an inclusion factor; is the uncertainty of the synthesis standard; The standard deviation is measured repeatedly and the method, As the standard deviation introduced by the spatial coefficient of variation, The residual standard deviation is fitted to the model.

Description

Intelligent mapping method for clenbuterol concentration based on Raman scattering space-time dynamic attenuation characteristics Technical Field The invention relates to the field of intersection of Raman spectrum analysis and food safety detection, in particular to an intelligent mapping method for clenbuterol concentration based on Raman scattering space-time dynamic attenuation characteristics. Background Clenbuterol (beta-stimulant compound such as clenbuterol hydrochloride, ractopamine and the like) is a feed additive capable of promoting growth of animal lean meat, but residues of the clenbuterol hydrochloride can cause serious harm to human bodies such as palpitation, muscle tremor and the like, and the clenbuterol hydrochloride is forbidden by the Ming dynasty of China. The establishment of a rapid, accurate and on-site clenbuterol detection method has important significance for guaranteeing food safety. The existing clenbuterol detection method mainly comprises the following steps: (1) The enzyme-linked immunosorbent assay (ELISA) has high false positive rate, is easy to generate cross reaction due to matrix interference in a low concentration range (< 1 mug/kg), has limited antibody specificity and has recognition confusion on beta-stimulant compounds with similar structures, and the method also needs strict temperature and time control, has short detection window period and has limited field application. (2) The liquid chromatography-tandem mass spectrometry (LC-MS/MS) method has the advantages of complex pretreatment process, large reagent consumption, serious matrix effect, high single sample cost, long single detection time consumption, incapability of meeting the field rapid screening requirement, expensive detection equipment and high technical requirements on operators. (3) The traditional Raman spectroscopy method only carries out linear fitting based on single parameters of peak intensity or peak width, so that the detection limit is difficult to break through the bottleneck of 10 mug/kg, the time domain dynamics information of coherent attenuation is not utilized, the condition of uneven distribution of clenbuterol in muscle tissue cannot be reflected by single-point or small-point measurement, the detection repeatability is poor, and the narrow-band Raman peak (half-peak width is about) of the clenbuterol is covered by fluorescent background generated by a large amount of chromophores such as hemoglobin and myoglobin in meat) The relative error of the target signal can reach 30-50%, and the detection result is affected. Raman scattering is essentially a coherent evolution process of the excited state of molecular vibrations, whose frequency domain peak shape is the fourier transform of the time domain coherence function. Whereas the traditional method only analyzes static peak shape in the frequency domain, completely discards the rich kinetic information contained in the time domain coherent attenuation, wherein ① molecules in different aggregation states (monomers, dimers and clusters) have obviously different coherent attenuation timesThis is directly related to concentration, ② coherent decay rate is extremely sensitive to molecular microenvironment (solvation degree, hydrogen bond network, charge distribution) and can be used as a "dynamic fingerprint" of concentration, ③ time domain fluctuation characteristic reflects the time scale of molecular diffusion and concentration fluctuation, and contains concentration information. The prior art ignores these time domain features, which amounts to discarding more than 50% of the effective information dimension. Disclosure of Invention Aiming at the defects existing in the prior art, the invention aims to provide an intelligent mapping method for the concentration of clenbuterol based on the characteristic of Raman scattering space-time dynamic attenuation. The method is based on a theoretical model of molecular dynamics and statistical physics, inverts frequency domain spectral information to a time domain coherence function, establishes a clenbuterol molecule 'free state-cluster state' double-pool dynamics model, reveals the internal correlation of concentration and molecule aggregation state and coherence attenuation for the first time, can automatically identify abnormal samples in clenbuterol detection, provides a quality scoring mechanism, can be further expanded to detection of other small molecules, and does not depend on specific chemical properties of substances. In order to achieve the above purpose, the invention adopts the following technical scheme: an intelligent mapping method for the concentration of clenbuterol based on Raman scattering space-time dynamic attenuation characteristics is characterized by comprising the following steps: step 1, acquiring space-time multi-mode Raman spectrum data of a sample to be detected containing clenbuterol, and constructing a four-dimensional Raman spectrum data tensor Wherein the sam