Purity detection method and system for blueberry juice production
By dynamically calibrating the detection threshold and using multi-level detection methods, combined with acoustic vibration, near-infrared spectroscopy, photoelectric sensor arrays, and random sampling, the problems of missed detection and high cost and low efficiency in blueberry juice purity detection have been solved, achieving efficient and accurate purity detection.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-02-09
- Publication Date
- 2026-04-03
AI Technical Summary
Existing technologies for testing the purity of blueberry juice suffer from problems such as missed detections, high costs, and low efficiency, especially when testing is performed using expensive equipment after batch sampling.
By dynamically calibrating the detection threshold using orchard harvesting data and processing batch data, and combining acoustic vibration, near-infrared spectroscopy and chromatographic analysis, photoelectric sensor array detection, and random sampling verification, a multi-level purity detection system is constructed.
This improved the accuracy and efficiency of blueberry juice purity testing while reducing testing costs.
Smart Images
Figure CN121783910A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of purity testing, and in particular to a method and system for purity testing in blueberry juice production. Background Technology
[0002] Blueberry juice has many uses in production, such as producing blueberry juice drinks and blueberry-flavored videos. Therefore, it is necessary to test the purity of the blueberry juice used in production.
[0003] In existing technologies, when testing the purity of blueberry juice used in production, a portion is typically selected from a batch of raw blueberry juice and sent to a relevant testing unit for analysis. Chromatography and spectroscopy are commonly used to obtain the final results. However, this method easily misses portions of the raw blueberry juice with purity issues. Furthermore, the subsequent sampling requires expensive equipment for testing, resulting in high costs and very low efficiency, which cannot meet the demands of demanding production processes. Summary of the Invention
[0004] The purpose of this invention is to provide a method and system for purity testing in blueberry juice production, so as to solve the problems mentioned in the background art.
[0005] In a first aspect, this application provides a method for purity detection in blueberry juice production, the method comprising: Obtain orchard harvest data and processing batch data for this batch of blueberry juice; obtain standard parameters for the corresponding batch based on the orchard harvest data and the processing batch data; and dynamically calibrate the detection threshold based on the standard parameters. Sound waves are applied to blueberry juice, and the sound wave resonance frequency data generated by the blueberry juice after being subjected to sound waves are recorded. The juice density and juice viscosity are obtained based on the sound wave resonance frequency data. The first purity parameter is obtained based on the juice density and the juice viscosity. Near-infrared light and chromatographic sampling were applied to blueberry juice to obtain the near-infrared spectrum and high-performance liquid chromatography of the blueberry juice. Based on the near-infrared spectrum and the high-performance liquid chromatography, the component spectrum of the blueberry juice was obtained. Based on the component spectrum, the second purity parameter was obtained. A photoelectric sensor array is installed at the blueberry juice delivery pipe to detect the blueberry characteristic pigments in the blueberry juice in real time, obtain the characteristic pigment parameter value, and obtain the third purity parameter based on the characteristic pigment parameter value. By combining the first purity parameter, the second purity parameter, and the third purity parameter, the final purity of the blueberry juice is obtained. Illegal additives in blueberry juice are obtained, and a specific identification probe for the illegal additives is constructed based on the illegal additives. Random sampling and verification of blueberry juice on the production line are carried out at any time and place within a preset random time period.
[0006] Preferably, the step of obtaining standard parameters for the corresponding batch based on the orchard harvesting data and the processing batch data, and dynamically calibrating the detection threshold based on the standard parameters, specifically includes: Based on the orchard harvest data, the initial fruit data of blueberries at the time of harvest was obtained, and the standard parameters of the fruit were obtained based on the initial fruit data. Based on the processing batch data, the processing procedures, processing standards, and storage standards for blueberries are obtained, and processing standard parameters are generated based on the processing procedures, processing standards, and storage standards. By combining the fruit standard parameters and the processing standard parameters, standard parameters for blueberry fruit in subsequent testing processes are generated; Redundancy is identified in the standard parameters to obtain the detection redundancy in subsequent detection processes, and the detection threshold of subsequent detection steps is dynamically calibrated based on the detection redundancy.
[0007] Preferably, the steps of recording the sound wave resonance frequency data generated when blueberry juice is exposed to sound waves, obtaining the juice density and viscosity based on the sound wave resonance frequency data, and obtaining the first purity parameter based on the juice density and the juice viscosity are as follows: Record the liquid oscillation data generated by blueberry juice after being subjected to sound wave vibration, and extract the sound wave resonance frequency data and liquid oscillation decay rate of blueberry juice based on the liquid oscillation data; Based on the acoustic resonant frequency data, the liquid mass distribution parameters of blueberry juice are obtained, and the juice density is obtained based on the liquid mass distribution parameters. The internal friction consumption parameter of blueberry juice is obtained based on the liquid oscillation decay rate, and the juice viscosity is obtained based on the internal friction consumption parameter. By combining the juice density and the juice viscosity, blueberry liquid parameters are obtained. These blueberry liquid parameters are then compared with preset blueberry standard parameters to obtain the comparison difference. Based on this comparison difference, a first purity parameter is generated.
[0008] Preferably, the step of obtaining the component spectrum of blueberry juice based on the near-infrared spectroscopy and the high-performance liquid chromatography, and obtaining the second purity parameter based on the component spectrum, specifically includes: Based on the high performance liquid chromatography, chromatographic signals are extracted from the high performance liquid chromatography to obtain a chromatogram; Identify the baseline of the chromatogram, perform a smooth fit on the baseline to obtain the target baseline, and integrate based on the target baseline to obtain the chromatographic integral; Based on the chromatographic integral, qualitative and quantitative analyses were performed on the blueberry juice, and the parameters of the first active ingredient were output. Based on the near-infrared spectrum, multivariate scattering correction is performed on the near-infrared spectrum to obtain a standard near-infrared spectrum; Characteristic peaks are identified in the near-infrared spectrum to obtain the functional group absorption region, and the data of the functional group absorption region is reduced in dimensionality to obtain the main component information; Based on the information on the main components, qualitative and quantitative analyses were performed on the blueberry juice, and parameters of the second effective component were output. The first effective component parameter and the second effective component parameter are cross-validated to generate a second purity parameter.
[0009] Preferably, the step of setting up a photoelectric sensor array at the blueberry juice delivery pipe to detect the blueberry characteristic pigments in the blueberry juice in real time, obtaining characteristic pigment parameter values, and obtaining a third purity parameter based on the characteristic pigment parameter values is as follows: A photoelectric sensor array is installed at the blueberry juice delivery pipe. The photoelectric sensor array is located on one side of the delivery pipe and emits a target light of a preset specific wavelength into the blueberry juice inside the delivery pipe. Obtain target pigments with blueberry characteristics present in blueberry fruits, and construct pigment optical filters based on the target pigments; Based on the target light and the pigment optical filter, the blueberry juice in the conveying pipe is identified to obtain the blueberry characteristic pigments and irrelevant pigments of the blueberry juice. The ratio between the characteristic pigments and irrelevant pigments of blueberries is extracted, and a third purity parameter is generated based on the ratio data.
[0010] Preferably, the step of obtaining illegal additives to blueberry juice and constructing a specific identification probe for the illegal additives specifically includes: Obtain data on additives in commercially available blueberry juice and the additive restriction standards for blueberry juice used in production; The data on additives was filtered according to the additive restriction standards to identify illegal additives that might be added to blueberry juice used in production. Identify the additive component data for each of the illegal additives, and obtain specific identification data based on the additive component data; Based on the specific identification data, a specific identification probe is constructed to identify the illegal additives.
[0011] Preferably, the step of randomly sampling and verifying blueberry juice on the production line at any time and place within a preset random time period is as follows: A maximum sampling interval and a minimum sampling interval are preset. The time period between the minimum sampling interval and the maximum sampling interval is extracted and marked as the target sampling time interval. After the previous sampling inspection is completed, a random sampling time point is selected within the target sampling time interval to obtain the random sampling time point. Obtain the transportation method and transportation area of blueberry juice within the factory, and determine the location and collection method of blueberry juice based on the transportation method and transportation area; After the previous sampling inspection is completed, a random location is selected within the existing area according to the collection method to obtain the random sampling location; Blueberry juice was randomly sampled and verified based on the random sampling time point and the random sampling location.
[0012] Secondly, this application provides a purity detection system for blueberry juice production, the system comprising: Standard calibration module: used to acquire orchard harvest data and processing batch data of this batch of blueberry juice, obtain standard parameters for the corresponding batch based on the orchard harvest data and the processing batch data, and dynamically calibrate the detection threshold based on the standard parameters; Liquid detection module: used to apply sound wave vibration to blueberry juice, record the sound wave resonance frequency data generated after the blueberry juice is subjected to sound waves, obtain the juice density and juice viscosity based on the sound wave resonance frequency data, and obtain the first purity parameter based on the juice density and juice viscosity; Component detection module: used to apply near-infrared light and chromatographic sampling to blueberry juice to obtain the near-infrared spectrum and high-performance liquid chromatography of blueberry juice, to obtain the component spectrum of blueberry juice based on the near-infrared spectrum and the high-performance liquid chromatography, and to obtain the second purity parameter based on the component spectrum; Pigment detection module: Used to set up a photoelectric sensor array at the blueberry juice delivery pipeline to detect the blueberry characteristic pigments in the blueberry juice in real time, obtain the characteristic pigment parameter value, and obtain the third purity parameter based on the characteristic pigment parameter value; Comprehensive verification module: used to combine the first purity parameter, the second purity parameter and the third purity parameter to obtain the final detected purity of blueberry juice; Random sampling module: used to detect illegal additives in blueberry juice, construct a specific identification probe for the illegal additives, and conduct random sampling and verification of blueberry juice on the production line at any time and place within a preset random time period.
[0013] In summary, this application includes at least one of the following beneficial technical effects: By collecting orchard harvesting data and processing batch data for blueberry juice, standard parameters for each batch of blueberries are obtained. These standard parameters are then used to dynamically calibrate the detection thresholds for each subsequent testing step. Sonic vibrations are applied to the blueberry juice to identify its density and viscosity, yielding a first purity parameter. Near-infrared spectroscopy and high-performance liquid chromatography are collected to identify the component profiles, yielding a second purity parameter. A photoelectric sensor array is then used to identify the characteristic pigments of blueberries, yielding a third purity parameter. Combining these three purity parameters yields the final purity of the blueberry juice. Furthermore, the system identifies potential illegal additives that may be added to commercially available blueberry juice. A specific identification probe is constructed to detect these illegal additives, and random sampling of blueberry juice within the factory is performed at any time and place during preset random time periods. This improves the accuracy and efficiency of blueberry juice purity testing while reducing testing costs. Attached Figure Description
[0014] Figure 1 This is a flowchart illustrating the steps of a method for purity testing in blueberry juice production provided in an embodiment of this application. Figure 2 This is a block diagram of a purity detection system for blueberry juice production provided in an embodiment of this application.
[0015] Explanation of reference numerals in the attached diagram: 1. Standard calibration module; 2. Liquid detection module; 3. Component detection module; 4. Pigment detection module; 5. Comprehensive verification module; 6. Random sampling module. Detailed Implementation
[0016] The following is in conjunction with the appendix Figures 1-2 This application will be described in further detail, but the embodiments of the present invention are not limited thereto.
[0017] This application discloses a method and system for purity testing in blueberry juice production.
[0018] This embodiment relates to a purity detection method for blueberry juice production, the method comprising: S100: Obtain orchard harvesting data and processing batch data for this batch of blueberry juice, obtain the standard parameters for the corresponding batch based on the orchard harvesting data and processing batch data, and dynamically calibrate the detection threshold based on the standard parameters; S200: Apply sound wave vibration to blueberry juice, record the sound wave resonance frequency data generated after the blueberry juice is subjected to sound waves, obtain the juice density and juice viscosity based on the sound wave resonance frequency data, and obtain the first purity parameter based on the juice density and juice viscosity. S300: Apply near-infrared light and chromatographic sampling to blueberry juice to obtain the near-infrared spectrum and high-performance liquid chromatography of blueberry juice. Based on the near-infrared spectrum and high-performance liquid chromatography, obtain the component spectrum of blueberry juice. Based on the component spectrum, obtain the second purity parameter. S400: A photoelectric sensor array is set at the blueberry juice conveying pipeline to detect the blueberry characteristic pigments in the blueberry juice in real time, obtain the characteristic pigment parameter value, and obtain the third purity parameter based on the characteristic pigment parameter value. S500: The final purity of blueberry juice is obtained by combining the first purity parameter, the second purity parameter, and the third purity parameter. S600: Identify illegal additives in blueberry juice, construct a specific identification probe for illegal additives based on the illegal additives, and conduct random sampling and verification of blueberry juice on the production line at any time and place within a preset random time period.
[0019] The steps for obtaining standard parameters for corresponding batches based on orchard harvesting data and processing batch data, and then dynamically calibrating the detection threshold based on these standard parameters, are as follows: Based on the orchard harvest data, the initial fruit data of blueberries at the time of harvest was obtained, and the standard parameters of the fruit were obtained based on the initial fruit data. Based on the processing batch data, the processing procedures, processing standards, and storage standards for blueberries are obtained, and processing standard parameters are generated based on the processing procedures, processing standards, and storage standards. By combining the standard parameters of the fruit and the standard parameters of the processing, standard parameters for blueberry fruit in subsequent testing processes are generated; Redundancy is identified in the standard parameters to obtain the detection redundancy in the subsequent testing process. The detection threshold of the subsequent testing process is then dynamically calibrated based on the detection redundancy.
[0020] In application, taking a batch of blueberries harvested in the spring of 2023 from a certain blueberry orchard as an example, according to the orchard's harvest data, the initial fruit data for this batch of blueberries at the time of harvest included an average fruit diameter of 1.5 cm, a sugar content of 12%, and an acidity of 0.8%. Based on these initial fruit data, the standard parameters for the resulting fruit are: fruit diameter 1.5 cm, sugar content 12%, and acidity 0.8%. Meanwhile, according to the processing batch data, the processing steps for this batch of blueberries included washing, crushing, pressing, and filtering. The processing standards were: washing water temperature controlled at 25 degrees Celsius, crushing time not exceeding 10 minutes, and pressing pressure of 0.5 MPa; the storage standard was: storage at 4 degrees Celsius for no more than 48 hours. Based on the processing steps, processing standards, and storage standards, the standard processing parameters are: washing temperature 25 degrees Celsius, crushing time 10 minutes, pressing pressure 0.5 MPa, storage temperature 4 degrees Celsius, and storage time 48 hours. Combining standard parameters for the fruit and processing, the standard parameters for subsequent blueberry testing were determined as follows: fruit diameter 1.5 cm, sugar content 12%, acidity 0.8%, washing temperature 25°C, crushing time 10 minutes, pressing pressure 0.5 MPa, storage temperature 4°C, and storage time 48 hours. Redundancy identification of these standard parameters revealed potential redundancy in washing temperature and storage time. Fluctuations in washing temperature within 2°C do not affect purity, and storage time within 48 hours has minimal impact on composition. Based on these redundancies, the testing thresholds for subsequent testing processes were dynamically calibrated, relaxing the washing temperature threshold to 23-27°C and the storage time threshold to no more than 50 hours.
[0021] The steps for recording the sound wave resonance frequency data generated when blueberry juice is exposed to sound waves, obtaining the juice density and viscosity based on the sound wave resonance frequency data, and obtaining the first purity parameter based on the juice density and viscosity are as follows: Record the liquid oscillation data generated by blueberry juice after being subjected to sound wave vibration, and extract the sound wave resonance frequency data and liquid oscillation decay rate of blueberry juice based on the liquid oscillation data; Based on the acoustic resonant frequency data, the liquid mass distribution parameters of blueberry juice are obtained, and the juice density is obtained based on the liquid mass distribution parameters. The internal friction loss parameters of blueberry juice are obtained based on the liquid oscillation decay rate, and the juice viscosity is obtained based on the internal friction loss parameters. By combining the juice density and juice viscosity, the blueberry liquid parameters are obtained. The blueberry liquid parameters are compared with the preset blueberry standard parameters to obtain the comparison difference. The first purity parameter is generated based on the comparison difference.
[0022] In this application, taking a testing step on a blueberry juice production line as an example, sound waves are applied to the blueberry juice at a frequency of 1000 Hz, and the liquid oscillation data generated by the sound waves is recorded. The oscillation data is collected by sensors, and the sound wave resonance frequency is extracted to be 950 Hz, with a liquid oscillation decay rate of 0.2 units per second. Based on the sound wave resonance frequency of 950 Hz, the liquid mass distribution parameter of the blueberry juice is calculated to be 1200 kg / m³, further yielding a juice density of 1.2 g / cm³. Based on the liquid oscillation decay rate of 0.2 units per second, the internal friction loss parameter of the blueberry juice is calculated to be 0.15 units, further yielding a juice viscosity of 1.5 mPa·s. Combining the juice density of 1.2 g / cm³ and the juice viscosity of 1.5 mPa·s, the blueberry liquid parameters are calculated to be a density of 1.2 and a viscosity of 1.5. The liquid blueberry parameters were compared with the preset standard blueberry parameters of density 1.15 and viscosity 1.2, resulting in a density difference of 0.05 and a viscosity difference of 0.3. Based on these differences, a first purity parameter was generated. A density difference of 0.05 corresponds to a 2% reduction in purity, and a viscosity difference of 0.3 corresponds to a 5% reduction in purity. The final first purity parameter was 93%.
[0023] The composition spectrum of blueberry juice was obtained based on near-infrared spectroscopy and high-performance liquid chromatography. The specific steps for obtaining the second purity parameter based on the composition spectrum are as follows: Based on high performance liquid chromatography (HPLC), chromatographic signals are extracted from HPLC to obtain chromatograms; Identify the baseline of the chromatogram, perform a smooth fit on the baseline to obtain the target baseline, and integrate based on the target baseline to obtain the chromatographic integral; Based on chromatographic integration, qualitative and quantitative analyses were performed on blueberry juice, and the parameters of the first active ingredient were output. Based on near-infrared spectroscopy, multivariate scattering correction is performed on the near-infrared spectrum to obtain a standard near-infrared spectrum; Characteristic peaks were identified in the near-infrared spectrum to obtain the functional group absorption region, and the data of the functional group absorption region was reduced in dimensionality to obtain the main component information; Based on the information of the main components, qualitative and quantitative analyses were performed on blueberry juice, and the parameters of the second effective component were output. The first and second effective component parameters are cross-validated to generate a second purity parameter.
[0024] In this application, taking a blueberry juice sample as an example, near-infrared light and chromatographic sampling were applied to the sample to obtain near-infrared spectral and high-performance liquid chromatography (HPLC) data. Based on the HPLC data, chromatographic signal extraction was performed to obtain a chromatogram, which showed multiple peaks, with the highest peak corresponding to a retention time of 5 minutes. The baseline of the chromatogram was identified, with an initial baseline value of 100 units. Through smoothing and fitting, a target baseline of 98 units was obtained. Integrating based on the target baseline yielded a chromatographic integral of 1500 units. Based on the chromatographic integral of 1500 units, qualitative analysis of the blueberry juice was performed, identifying anthocyanins, vitamin C, and sugars as the main components. Quantitative analysis revealed anthocyanin content of 50 mg / L, vitamin C content of 30 mg / L, and sugar content of 10 g / L. The first effective component parameters were output as anthocyanin 50 mg / L, vitamin C 30 mg / L, and sugars 10 g / L. Based on the near-infrared spectral data, multivariate scattering correction was performed to obtain a standard near-infrared spectrum, which showed a characteristic peak at a wavelength of 800 nm. Characteristic peaks were identified in the near-infrared spectrum, revealing hydroxyl and carboxyl absorption regions. Dimensionality reduction was used to extract the main components, identifying anthocyanins and organic acids. Qualitative analysis confirmed the presence of anthocyanins and organic acids, while quantitative analysis yielded an anthocyanin content of 48 mg / L and an organic acid content of 5 mg / L. The second effective component parameters were then calculated as 48 mg / L for anthocyanins and 5 mg / L for organic acids. Cross-validation of the first and second effective component parameters showed a 2 mg / L difference in anthocyanin content, within acceptable error range. Other components remained consistent, resulting in a second purity parameter of 95%.
[0025] A photoelectric sensor array is installed at the blueberry juice delivery pipeline to detect the characteristic pigments of blueberries in real time, obtain the characteristic pigment parameter values, and derive the third purity parameter based on the characteristic pigment parameter values. The specific steps are as follows: A photoelectric sensor array is installed at the blueberry juice delivery pipe. The photoelectric sensor array is located on one side of the delivery pipe and emits a target light of a preset specific wavelength into the blueberry juice inside the delivery pipe. Obtain target pigments with blueberry characteristics present in blueberry fruits, and construct pigment optical filters based on the target pigments; Based on the target light and the pigment optical filter, the pigments in the blueberry juice in the delivery pipe are identified to obtain the characteristic blueberry pigments and irrelevant pigments of the blueberry juice. Extract the ratio between the characteristic pigments and irrelevant pigments of blueberries, and generate a third purity parameter based on the ratio data.
[0026] In this application, taking a blueberry juice production line conveyor pipe as an example, a photoelectric sensor array containing 10 sensor units is installed on one side of the conveyor pipe. Target light with a specific wavelength of 550 nanometers is emitted into the blueberry juice within the conveyor pipe; the light penetrates the juice and is received by the sensors. Target pigments characteristic of blueberries, including anthocyanins and carotenoids, are identified within the blueberries. A pigment optical filter is constructed based on these target pigments, designed to allow light with a wavelength of 550 nanometers to pass through while filtering out other irrelevant wavelengths. Based on the target light and the pigment optical filter, pigment identification is performed on the blueberry juice within the conveyor pipe. The light intensity received by the sensor is 80 units; the signal intensity of the identified blueberry characteristic pigment is 60 units, and the signal intensity of irrelevant pigments is 20 units. The ratio between the blueberry characteristic pigment and the irrelevant pigment is extracted; the ratio is 60:20, or 3:1. A third purity parameter is generated based on this ratio data. A ratio of 3 corresponds to a purity of 90%, and a ratio of 2 corresponds to a purity of 80%. The calculated third purity parameter is 90%.
[0027] The steps for obtaining illicit additives in blueberry juice and constructing a specific identification probe for these additives are as follows: Obtain data on additives in commercially available blueberry juice and the additive restriction standards for blueberry juice used in production; Data on additives was filtered according to additive restriction standards to identify illegal additives that might be added to blueberry juice used in production. Identify the additive composition data for each illegal additive, and obtain specific identification data based on the additive composition data; Based on specific identification data, a specific identification probe for identifying illegal additives was constructed.
[0028] In this application, taking the additives that may be used in the production of a blueberry juice as an example, data on additives available in commercially available blueberry juices were obtained, including preservatives such as sodium benzoate, sweeteners such as aspartame, and colorants such as carmine. Simultaneously, the additive restriction standards for blueberry juice used in production were obtained. These standards prohibit the use of sodium benzoate and carmine, while allowing the use of aspartame, but with a limit of no more than 0.1%. Based on the additive restriction standards, the data was screened, revealing that sodium benzoate and carmine are the illegal additives that may be added to blueberry juice used in production. The component data of each illegal additive were identified: sodium benzoate consists of benzoic acid and its sodium salt, while carmine consists of an azo compound. Based on this component data, specific identification data was obtained: the characteristic absorption peak of benzoic acid is at a wavelength of 280 nm, and the characteristic absorption peak of azo compounds is at a wavelength of 400 nm. Based on this specific identification data, a specific identification probe was constructed to identify illegal additives. The probe material was selected from photoelectric elements sensitive to wavelengths of 280 nm and 400 nm, and the probe sensitivity was set to 0.01 mg / L. In this way, the probe can quickly identify whether the juice contains sodium benzoate and carmine, and issue an alarm in time.
[0029] The steps for randomly sampling and verifying blueberry juice on the production line at any time and place within a preset random time period are as follows: A maximum sampling interval and a minimum sampling interval are preset. The time interval between the minimum and maximum sampling intervals is extracted and marked as the target sampling time interval. After the previous sampling inspection is completed, a random sampling time point is selected within the target sampling time interval to obtain the random sampling time point. Obtain the transportation methods and areas for blueberry juice within the factory, and determine the location and collection method of blueberry juice based on the transportation methods and areas. After the previous sampling inspection is completed, random locations are selected within the existing area according to the collection method to obtain the random sampling locations; Blueberry juice was randomly sampled and verified based on the random sampling time and location.
[0030] In practice, taking a blueberry juice production line as an example, a maximum sampling interval of 8 hours and a minimum sampling interval of 2 hours are preset. The time period between the minimum and maximum sampling intervals is extracted and marked as the target sampling time interval of 2-8 hours. After the previous sampling is completed, a random time point is selected within the target sampling time interval, and a random number generator determines the random sampling time point to be 4.5 hours. The transportation methods and areas of the blueberry juice within the factory are obtained. The transportation methods include pipeline transportation and tank storage, and the transportation areas include the raw material area, processing area, and finished product area. Based on the transportation methods and areas, the storage areas of the blueberry juice are determined to be the pipelines and tanks in the processing area. The sampling method is to collect samples from the pipeline sampling port or the tank sampling valve. After the previous sampling is completed, a random location is selected within the storage area according to the sampling method. The random sampling location is determined to be the third sampling port of the pipeline in the processing area. Based on the random sampling time point of 4.5 hours and the random sampling location of the third sampling port, blueberry juice was randomly sampled for verification, and 100 ml of sample was taken for testing.
[0031] This invention provides a purity detection system for blueberry juice production, using any one of the purity detection methods for blueberry juice production described above. The system includes the following: Standard calibration module 1: Used to acquire orchard harvest data and processing batch data of this batch of blueberry juice, obtain the standard parameters of the corresponding batch based on the orchard harvest data and processing batch data, and dynamically calibrate the detection threshold based on the standard parameters; Liquid detection module 2: used to apply sound wave vibration to blueberry juice, record the sound wave resonance frequency data generated after the blueberry juice is subjected to sound waves, obtain the juice density and juice viscosity based on the sound wave resonance frequency data, and obtain the first purity parameter based on the juice density and juice viscosity. Component detection module 3: used to apply near-infrared light and chromatographic sampling to blueberry juice to obtain the near-infrared spectrum and high-performance liquid chromatography of blueberry juice. Based on the near-infrared spectrum and high-performance liquid chromatography, the component spectrum of blueberry juice is obtained. Based on the component spectrum, the second purity parameter is obtained. Pigment detection module 4: Used to set up a photoelectric sensor array at the blueberry juice delivery pipe to detect the blueberry characteristic pigments in the blueberry juice in real time, obtain the characteristic pigment parameter value, and obtain the third purity parameter based on the characteristic pigment parameter value. Comprehensive verification module 5: used to combine the first purity parameter, the second purity parameter and the third purity parameter to obtain the final purity of blueberry juice; Random sampling module 6: Used to detect illegal additives in blueberry juice, construct a specific identification probe for illegal additives, and conduct random sampling and verification of blueberry juice on the production line at any time and place within a preset random time period.
[0032] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.
Claims
1. A method for purity testing in blueberry juice production, characterized in that, include: Obtain orchard harvest data and processing batch data for this batch of blueberry juice; obtain standard parameters for the corresponding batch based on the orchard harvest data and the processing batch data; and dynamically calibrate the detection threshold based on the standard parameters. Sound waves are applied to blueberry juice, and the sound wave resonance frequency data generated by the blueberry juice after being subjected to sound waves are recorded. The juice density and juice viscosity are obtained based on the sound wave resonance frequency data. The first purity parameter is obtained based on the juice density and the juice viscosity. Near-infrared light and chromatographic sampling were applied to blueberry juice to obtain the near-infrared spectrum and high-performance liquid chromatography of the blueberry juice. Based on the near-infrared spectrum and the high-performance liquid chromatography, the component spectrum of the blueberry juice was obtained. Based on the component spectrum, the second purity parameter was obtained. A photoelectric sensor array is installed at the blueberry juice delivery pipe to detect the blueberry characteristic pigments in the blueberry juice in real time, obtain the characteristic pigment parameter value, and obtain the third purity parameter based on the characteristic pigment parameter value. By combining the first purity parameter, the second purity parameter, and the third purity parameter, the final purity of the blueberry juice is obtained. Illegal additives in blueberry juice are obtained, and a specific identification probe for the illegal additives is constructed based on the illegal additives. Random sampling and verification of blueberry juice on the production line are carried out at any time and place within a preset random time period.
2. The method for purity detection in blueberry juice production according to claim 1, characterized in that, The steps of obtaining standard parameters for the corresponding batches based on the orchard harvesting data and the processing batch data, and dynamically calibrating the detection threshold based on the standard parameters, are as follows: Based on the orchard harvest data, the initial fruit data of blueberries at the time of harvest was obtained, and the standard parameters of the fruit were obtained based on the initial fruit data. Based on the processing batch data, the processing procedures, processing standards, and storage standards for blueberries are obtained, and processing standard parameters are generated based on the processing procedures, processing standards, and storage standards. By combining the fruit standard parameters and the processing standard parameters, standard parameters for blueberry fruit in subsequent testing processes are generated; Redundancy is identified in the standard parameters to obtain the detection redundancy in subsequent detection processes, and the detection threshold of subsequent detection steps is dynamically calibrated based on the detection redundancy.
3. The method for purity detection in blueberry juice production according to claim 2, characterized in that, The steps of recording the sound wave resonance frequency data generated when blueberry juice is exposed to sound waves, obtaining the juice density and viscosity based on the sound wave resonance frequency data, and obtaining the first purity parameter based on the juice density and viscosity are as follows: Record the liquid oscillation data generated by blueberry juice after being subjected to sound wave vibration, and extract the sound wave resonance frequency data and liquid oscillation decay rate of blueberry juice based on the liquid oscillation data; Based on the acoustic resonant frequency data, the liquid mass distribution parameters of blueberry juice are obtained, and the juice density is obtained based on the liquid mass distribution parameters. The internal friction consumption parameter of blueberry juice is obtained based on the liquid oscillation decay rate, and the juice viscosity is obtained based on the internal friction consumption parameter. By combining the juice density and the juice viscosity, blueberry liquid parameters are obtained. These blueberry liquid parameters are then compared with preset blueberry standard parameters to obtain the comparison difference. Based on this comparison difference, a first purity parameter is generated.
4. The method for purity detection in blueberry juice production according to claim 3, characterized in that, The steps for obtaining the component spectrum of blueberry juice based on the near-infrared spectroscopy and the high-performance liquid chromatography, and for obtaining the second purity parameter based on the component spectrum, are as follows: Based on the high performance liquid chromatography, chromatographic signals are extracted from the high performance liquid chromatography to obtain a chromatogram; Identify the baseline of the chromatogram, perform a smooth fit on the baseline to obtain the target baseline, and integrate based on the target baseline to obtain the chromatographic integral; Based on the chromatographic integral, qualitative and quantitative analyses were performed on the blueberry juice, and the parameters of the first active ingredient were output. Based on the near-infrared spectrum, multivariate scattering correction is performed on the near-infrared spectrum to obtain a standard near-infrared spectrum; Characteristic peaks are identified in the near-infrared spectrum to obtain the functional group absorption region, and the data of the functional group absorption region is reduced in dimensionality to obtain the main component information; Based on the information on the main components, qualitative and quantitative analyses were performed on the blueberry juice, and parameters of the second effective component were output. The first effective component parameter and the second effective component parameter are cross-validated to generate a second purity parameter.
5. The method for purity detection in blueberry juice production according to claim 4, characterized in that, The process of installing a photoelectric sensor array at the blueberry juice delivery pipeline to detect the blueberry characteristic pigments in the blueberry juice in real time, obtaining characteristic pigment parameter values, and then deriving a third purity parameter based on these characteristic pigment parameter values is as follows: A photoelectric sensor array is installed at the blueberry juice delivery pipe. The photoelectric sensor array is located on one side of the delivery pipe and emits a target light of a preset specific wavelength into the blueberry juice inside the delivery pipe. Obtain target pigments with blueberry characteristics present in blueberry fruits, and construct pigment optical filters based on the target pigments; Based on the target light and the pigment optical filter, the blueberry juice in the conveying pipe is identified to obtain the blueberry characteristic pigments and irrelevant pigments of the blueberry juice. The ratio between the characteristic pigments and irrelevant pigments of blueberries is extracted, and a third purity parameter is generated based on the ratio data.
6. The method for purity detection in blueberry juice production according to claim 5, characterized in that, The steps of obtaining illegal additives in blueberry juice and constructing a specific recognition probe for the illegal additives are as follows: Obtain data on additives in commercially available blueberry juice and the additive restriction standards for blueberry juice used in production; The data on additives was filtered according to the additive restriction standards to identify illegal additives that might be added to blueberry juice used in production. Identify the additive component data for each of the illegal additives, and obtain specific identification data based on the additive component data; Based on the specific identification data, a specific identification probe is constructed to identify the illegal additives.
7. The method for purity detection in blueberry juice production according to claim 6, characterized in that, The steps for randomly sampling and verifying blueberry juice on the production line at any time and place within a preset random time period are as follows: A maximum sampling interval and a minimum sampling interval are preset. The time period between the minimum sampling interval and the maximum sampling interval is extracted and marked as the target sampling time interval. After the previous sampling inspection is completed, a random sampling time point is selected within the target sampling time interval to obtain the random sampling time point. Obtain the transportation method and transportation area of blueberry juice within the factory, and determine the location and collection method of blueberry juice based on the transportation method and transportation area; After the previous sampling inspection is completed, a random location is selected within the existing area according to the collection method to obtain the random sampling location; Blueberry juice was randomly sampled and verified based on the random sampling time point and the random sampling location.
8. A purity detection system for blueberry juice production, said system using a purity detection method for blueberry juice production as described in any one of claims 1-7, characterized in that, The system includes: Standard calibration module: used to acquire orchard harvest data and processing batch data of this batch of blueberry juice, obtain standard parameters for the corresponding batch based on the orchard harvest data and the processing batch data, and dynamically calibrate the detection threshold based on the standard parameters; Liquid detection module: used to apply sound wave vibration to blueberry juice, record the sound wave resonance frequency data generated after the blueberry juice is subjected to sound waves, obtain the juice density and juice viscosity based on the sound wave resonance frequency data, and obtain the first purity parameter based on the juice density and juice viscosity; Component detection module: used to apply near-infrared light and chromatographic sampling to blueberry juice to obtain the near-infrared spectrum and high-performance liquid chromatography of blueberry juice, to obtain the component spectrum of blueberry juice based on the near-infrared spectrum and the high-performance liquid chromatography, and to obtain the second purity parameter based on the component spectrum; Pigment detection module: Used to set up a photoelectric sensor array at the blueberry juice delivery pipeline to detect the blueberry characteristic pigments in the blueberry juice in real time, obtain the characteristic pigment parameter value, and obtain the third purity parameter based on the characteristic pigment parameter value; Comprehensive verification module: used to combine the first purity parameter, the second purity parameter and the third purity parameter to obtain the final detected purity of blueberry juice; Random sampling module: used to detect illegal additives in blueberry juice, construct a specific identification probe for the illegal additives, and conduct random sampling and verification of blueberry juice on the production line at any time and place within a preset random time period.