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CN-121995018-A - Coffee bean origin tracing method based on detection temperature optimization

CN121995018ACN 121995018 ACN121995018 ACN 121995018ACN-121995018-A

Abstract

The invention discloses a coffee bean origin tracing method based on detection temperature optimization. The method comprises the steps of obtaining coffee bean samples of different producing places and preparing corresponding coffee solutions, uniformly mixing each coffee solution with NaOH solution and analyzing optimal detection temperature, taking the average value of all optimal detection temperatures as global optimal temperature, uniformly mixing the coffee solutions corresponding to each coffee bean sample with the NaOH solution and adjusting the temperature to the global optimal temperature to extract a corresponding characteristic signal set, inputting the characteristic signal set and the producing label of the coffee bean sample into a machine learning model for training to obtain a coffee bean producing place tracing model, preparing the coffee solution corresponding to the coffee bean sample to be tested, uniformly mixing the coffee solution with the NaOH solution and adjusting the temperature to the global optimal temperature, extracting the corresponding characteristic signal set and inputting the coffee bean producing place tracing model, and outputting the producing place of the coffee bean sample to be tested by the coffee bean producing place tracing model. The invention can rapidly and accurately trace the origin of the coffee beans.

Inventors

  • Yong Chengxiang
  • CUI YAWEN
  • HUANG JIPING
  • HUI GUOHUA
  • LIAO YING
  • Bi Deyi
  • WU PENG
  • LU JIANYU
  • SUN ZHAOYI
  • Xia Chengling
  • WU WENXIONG
  • Lan Huiting
  • HUANG YUCHEN
  • ZHANG YUFENG
  • XIAO YUQI

Assignees

  • 浙江农林大学

Dates

Publication Date
20260508
Application Date
20260120

Claims (10)

  1. 1. The coffee bean origin tracing method based on detection temperature optimization is characterized by comprising the following steps of: s1, obtaining coffee bean samples of different producing places, preparing m coffee bean samples of each producing place, and preparing a coffee solution corresponding to each coffee bean sample; s2, uniformly mixing each coffee solution with the NaOH solution to obtain corresponding mixed solutions, analyzing the optimal detection temperature of each mixed solution, and taking the average value of the optimal detection temperatures of all the mixed solutions as the global optimal temperature; S3, uniformly mixing the coffee solution corresponding to each coffee bean sample with the NaOH solution to obtain a corresponding mixed solution, adjusting the temperature of the mixed solution to the global optimal temperature, and extracting a corresponding characteristic signal set; S4, inputting the characteristic signal set and the origin mark of the coffee bean sample into a machine learning model for training to obtain a coffee bean origin tracing model; s5, preparing a coffee solution corresponding to the coffee bean sample to be detected, uniformly mixing the coffee solution with the NaOH solution to obtain a mixed solution, adjusting the temperature of the mixed solution to the global optimal temperature, extracting a corresponding characteristic signal set, inputting the characteristic signal set into a coffee bean origin tracing model, and outputting the origin of the coffee bean sample to be detected by the coffee bean origin tracing model.
  2. 2. The method for tracing the origin of coffee beans based on the optimal detection temperature according to claim 1, wherein the method for analyzing the optimal detection temperature of the mixed solution in the step S2 comprises the following steps: M1, placing the three-electrode sensor in the mixed solution, and regulating the temperature of the mixed solution to Let k=0, Is a preset initial temperature; M2, collecting by cyclic voltammetry to obtain cyclic voltammetry curve of the mixed solution Recording cyclic voltammograms Peak current of (2) ; M3 raising the temperature of the mixed solution to , , Collecting the cyclic voltammetry to obtain the cyclic voltammetry curve of the mixed solution for the temperature step length Recording cyclic voltammograms Peak current of (2) ; M4 calculating the relative Current gain Rate The calculation formula is as follows: ; M5 determining the relative current gain ratio Whether or not it is less than or equal to a preset gain threshold If so, the temperature is increased Ending the optimal detection of the temperature of the mixed solution, otherwise, executing the step M6; M6, judging the temperature Whether or not to be less than the end temperature If yes, let k=k+1 jump to step M3, otherwise, terminate the temperature And ending the process as the optimal detection temperature of the mixed solution.
  3. 3. The method for tracing a coffee bean origin based on detection temperature optimization of claim 2, wherein the initial temperature 20-25 ℃, And the temperature step length Is 2-5 ℃, and the termination temperature is Is 60-80 ℃.
  4. 4. A method for tracing a coffee bean origin based on detection temperature optimization as claimed in claim 2, wherein said gain threshold value The value range of the (C) is 4% -8%.
  5. 5. The method for tracing the origin of coffee beans based on the detection temperature optimization as set forth in claim 1, wherein the calculation formula for taking the average value of the optimal detection temperatures of all the mixed solutions as the global optimal temperature in step S2 is as follows: , Wherein, the For a global optimum temperature, n is the number of origin of the coffee beans, For the optimal detection temperature of the mixed solution corresponding to the jth coffee bean sample in the ith production place, i is more than or equal to 1 and less than or equal to n, and j is more than or equal to 1 and less than or equal to m.
  6. 6. The method for tracing a coffee bean origin based on detection temperature optimization of claim 1, wherein the method for extracting the characteristic signal set corresponding to the coffee bean sample comprises the following steps: n1, placing the three-electrode sensor in a mixed solution which is correspondingly adjusted to the global optimal temperature of the coffee bean sample; N2, dripping v microliter of coffee bean sample corresponding to the coffee solution into the mixed solution every t seconds, dripping g times, collecting the response current of the mixed solution by adopting a timing current method, recording the average response current in t seconds after each dripping of the coffee solution, wherein the average response current in t seconds after the q-th dripping of the coffee solution is ,1≤q≤g; And N3, combining all the recorded average response currents into a characteristic signal set of the coffee bean sample.
  7. 7. The method for tracing the origin of coffee beans based on detection temperature optimization of claim 6, wherein t is 20-100, v is 50-100, and g is 5-20.
  8. 8. The method for tracing the origin of coffee beans based on detection temperature optimization according to claim 1 is characterized in that the method for preparing the coffee solution corresponding to the coffee bean sample comprises the following steps of grinding the coffee bean sample, sieving the ground coffee bean sample with a 80-100-mesh sieve, dissolving the ground coffee bean sample in distilled water at 95 ℃ according to a solid-to-liquid ratio of 1:10 (g/mL), stirring the ground coffee bean sample uniformly, standing the ground coffee sample, and filtering the ground coffee sample to obtain the coffee solution.
  9. 9. The method for tracing the origin of the coffee beans based on the detection temperature optimization of claim 1 is characterized in that the method for uniformly mixing the coffee solution and the NaOH solution to obtain the corresponding mixed solution is that 1mL of the coffee solution and 20mL of the NaOH solution with the concentration of 0.05mol/L are uniformly mixed to obtain the corresponding mixed solution.
  10. 10. The coffee bean origin tracing method based on detection temperature optimization of claim 1, wherein the machine learning model is a random forest model.

Description

Coffee bean origin tracing method based on detection temperature optimization Technical Field The invention relates to the technical field of food tracing, in particular to a coffee bean origin tracing method based on detection temperature optimization. Background The origin of coffee beans is a key factor influencing the quality and the value of the coffee beans, and the differences of environmental conditions such as climate, soil, altitude and the like of different origins can lead to obvious differences of the coffee in aspects of flavor, ingredients and the like. The current method for tracing the origin of the coffee beans mainly comprises a sensory evaluation method, a spectroscopic analysis method, a chromatographic analysis method, a mass spectrometry method and the like. The sensory evaluation method relies on experience of a professional taster, has strong subjectivity and poor repeatability, is difficult to realize standardized tracing, and has the defects of huge equipment volume, complex operation, long detection period, high cost and the like although the detection precision of the spectral analysis method, the chromatographic analysis method and the mass spectrometry method is high, so that the requirements of low cost and quick tracing cannot be met. Disclosure of Invention The invention aims to solve the technical problems, and provides a coffee bean origin tracing method based on detection temperature optimization, which can rapidly and accurately trace the origin of coffee beans, and is simple to operate and low in cost. In order to solve the problems, the invention is realized by adopting the following technical scheme: the invention discloses a coffee bean origin tracing method based on detection temperature optimization, which comprises the following steps of: s1, obtaining coffee bean samples of different producing places, preparing m coffee bean samples of each producing place, and preparing a coffee solution corresponding to each coffee bean sample; s2, uniformly mixing each coffee solution with the NaOH solution to obtain corresponding mixed solutions, analyzing the optimal detection temperature of each mixed solution, and taking the average value of the optimal detection temperatures of all the mixed solutions as the global optimal temperature; S3, uniformly mixing the coffee solution corresponding to each coffee bean sample with the NaOH solution to obtain a corresponding mixed solution, adjusting the temperature of the mixed solution to the global optimal temperature, and extracting a corresponding characteristic signal set; S4, inputting the characteristic signal set and the origin mark of the coffee bean sample into a machine learning model for training to obtain a coffee bean origin tracing model; s5, preparing a coffee solution corresponding to the coffee bean sample to be detected, uniformly mixing the coffee solution with the NaOH solution to obtain a mixed solution, adjusting the temperature of the mixed solution to the global optimal temperature, extracting a corresponding characteristic signal set, inputting the characteristic signal set into a coffee bean origin tracing model, and outputting the origin of the coffee bean sample to be detected by the coffee bean origin tracing model. Preferably, the method for analyzing the optimal detection temperature of the mixed solution in the step S2 includes the steps of: M1, placing the three-electrode sensor in the mixed solution, and regulating the temperature of the mixed solution to Let k=0,Is a preset initial temperature; M2, collecting by cyclic voltammetry to obtain cyclic voltammetry curve of the mixed solution Recording cyclic voltammogramsPeak current of (2); M3 raising the temperature of the mixed solution to,,Collecting the cyclic voltammetry to obtain the cyclic voltammetry curve of the mixed solution for the temperature step lengthRecording cyclic voltammogramsPeak current of (2); M4 calculating the relative Current gain RateThe calculation formula is as follows: ; M5 determining the relative current gain ratio Whether or not it is less than or equal to a preset gain thresholdIf so, the temperature is increasedEnding the optimal detection of the temperature of the mixed solution, otherwise, executing the step M6; M6, judging the temperature Whether or not to be less than the end temperatureIf yes, let k=k+1 jump to step M3, otherwise, terminate the temperatureAnd ending the process as the optimal detection temperature of the mixed solution. A is a positive integer greater than 1. The temperature rise accelerates the mass transfer rate and the electrode reaction kinetics of the electroactive species in the mixed solution, resulting in an increase in the response current, thereby improving the detection sensitivity. However, the current gain is remarkable when the temperature is increased, but the relative current gain rate caused by the temperature increase is gradually smaller when the temperature reaches a certai