Honey walnut kernel raw material two-dimensional quality screening system

Abstract

The invention discloses a honey walnut kernel raw material two-dimensional quality screening system, and relates to the technical field of food quality detection, and the system comprises a raw material reference database module; a raw material two-dimensional detection module; a dynamic parameter calibration module; a multi-dimensional quality determination module; a reference data system of multiple production areas and multiple seasons is established through the raw material reference database module, basic indexes and interface interaction data are synchronously obtained in cooperation with the raw material two-dimensional detection module, and the problem that traditional detection only pays attention to the quality of a single raw material and ignores the combination quality of honey and walnut kernels is solved; meanwhile, the dynamic parameter calibration module calculates the comprehensive quality deviation and the equipment adjustment amount, self-adaptive optimization of detection parameters is achieved, insufficient precision caused by fixed parameters is avoided, and raw material quality abnormity can be recognized from multiple aspects of raw material basic attributes and interface interaction states by constructing a two-dimensional screening system of raw material basic quality and interface combination degree.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of food quality detection, in particular to a double-dimension quality screening system for honey walnut kernel raw materials. BACKGROUND

[0002] As a leisure food with both nutrition and flavor, the quality of honey walnut kernel directly depends on the quality of walnut kernel and honey raw materials and the interface bonding effect of the two. Raw material screening is a key link to ensure product quality. With the improvement of consumers' requirements for food quality and the development of food industry standardization, higher requirements are put forward for the quality control of honey walnut kernel raw materials, which need to cover the basic nutritional properties, safety properties and processing adaptation properties of raw materials. At present, the detection of walnut kernel raw materials in the industry focuses on basic nutritional ingredients such as protein and fat, and attention is paid to indicators such as sugar composition and amylase value of honey. A mature single-point detection technology has been formed, such as near-infrared spectroscopy for rapid detection of nutritional ingredients and chromatography-mass spectrometry for pollutant residue analysis. At the same time, the interface bonding quality of honey and walnut kernel (such as honey penetration depth and demelting rate) has a significant impact on product taste and form stability, and has gradually become an important dimension of raw material screening, promoting the development of raw material quality control from single component detection to multi-dimension comprehensive evaluation.

[0003] However, the traditional honey walnut kernel raw material screening technology has obvious limitations and cannot meet the needs of fine production. On the one hand, traditional detection is mainly aimed at independent detection of single raw material of walnut kernel or honey, without considering the interface bonding quality of the two in the screening system, which leads to problems such as demelting, uneven taste, etc. in the processing process of some raw materials with qualified basic indicators due to poor interface bonding, affecting the quality of the final product. On the other hand, the parameters of traditional detection equipment are mostly fixed settings, which cannot be adjusted adaptively according to the production area and seasonal fluctuations of raw materials, and are prone to detection deviation. Moreover, the quality determination mainly relies on the qualitative judgment of whether a single indicator is qualified or not, lacks comprehensive quantitative evaluation of basic nutrition, interface bonding and safety residues, and cannot fully reflect the overall quality of raw materials. In addition, the traditional traceability system mainly records the source information of raw materials, lacks the whole-chain correlation record of detection data, calibration process and determination results, and the data credibility is difficult to verify. Consumers cannot intuitively obtain the details of raw material quality, which is also not conducive to the traceability and improvement of raw material quality problems by enterprises. SUMMARY

[0004] The purpose of the present application is to make up for the shortcomings of the prior art, and provide a honey walnut kernel raw material double-dimension quality screening system, which is composed of a raw material reference database module, a raw material double-dimension detection module, a dynamic parameter calibration module, a multi-dimension quality judgment module and a result application traceability module. The raw material reference database module collects walnut kernel and honey samples in multiple production areas and multiple seasons, detects and stores various reference values; the raw material double-dimension detection module synchronously detects the basic quality and interface bonding degree data of the new batch of raw materials; the dynamic parameter calibration module adjusts the detection equipment parameters according to the deviation of the reference value and the measured value; the multi-dimension quality judgment module enriches the pollutants by magnetic nanoparticles and calculates the comprehensive score to output the judgment result; the result application traceability module pushes the result to the execution end, and at the same time, the whole process data is included in the block chain and a traceability two-dimensional code with credibility is generated. The system realizes the whole process quality control of honey walnut kernel raw material from detection, calibration, judgment to traceability, and provides complete technical support for raw material quality guarantee.

[0005] The present application provides the following technical solutions to solve the above technical problems: a honey walnut kernel raw material double-dimension quality screening system, which comprises:

[0006] The raw material reference database module: collects walnut kernel and honey samples in different production areas and seasons, detects and determines the walnut kernel protein content reference value, the honey fructose content reference value, detects and determines the honey penetration depth reference value and the honey transverse relaxation time reference value by a low-field nuclear magnetic resonance instrument, obtains the honey extraction rate reference value by image recognition, calculates the interface bonding degree comprehensive index reference value, and stores the above reference values in the database, and updates the reference value fluctuation range regularly;

[0007] The raw material double-dimension detection module: detects the new batch of honey walnut kernel raw material, detects and determines the walnut kernel protein actual detection value and the honey fructose actual detection value by a near-infrared spectrometer, detects and determines the actual penetration depth and the actual transverse relaxation time of the honey by a low-field nuclear magnetic resonance instrument, obtains the honey extraction rate by image recognition, and calculates the interface bonding degree comprehensive index actual measurement value;

[0008] The dynamic parameter calibration module: calls the reference value and the measured value, calculates the comprehensive quality deviation value, if the comprehensive quality deviation value exceeds the set threshold, calculates the near-infrared spectral characteristic wavelength adjustment amount, adjusts the detection equipment parameters according to the wavelength adjustment amount, and then re-detects to obtain the calibrated walnut kernel protein content, honey fructose content and interface bonding degree comprehensive index;

[0009] The multi-dimension quality judgment module: enriches the antibiotics in the honey and the pesticide residues in the walnut kernel by magnetic nanoparticles, calculates the enrichment efficiency, if the enrichment efficiency reaches the set standard, obtains the concentration of the enriched pollutants, calculates the comprehensive score, and outputs the quality judgment result according to whether the comprehensive score reaches the qualified threshold;

[0010] The result application tracing module: the judgment result of the multi-dimensional quality judgment module is pushed to the production and procurement execution end, and the core data of each module is entered into the block chain, the tracing data credibility is calculated, the tracing two-dimensional code with credibility is generated, and if the credibility does not reach the set requirement, the feedback is fed back to the raw material benchmark database module to update the database benchmark value.

[0011] Further, the calculation formula of the interface bonding degree comprehensive index benchmark value in the raw material benchmark database module is: , wherein, is the interface bonding degree comprehensive index benchmark value; is the honey penetration depth benchmark value; is the production area adaptation coefficient, the value range is 0.95-1.10; is the seasonal correction factor, the value range is 0.7-1.3; is the honey extraction rate benchmark value; is the honey transverse relaxation time benchmark value.

[0012] Further, the calculation formula of the interface bonding degree comprehensive index measured value in the raw material double-dimensional detection module is: , wherein, is the interface bonding degree comprehensive index measured value; is the actual penetration depth of honey; is the honey penetration depth benchmark value; is the production area adaptation coefficient; is the seasonal correction factor; is the honey extraction rate; is the actual transverse relaxation time of honey; is the honey transverse relaxation time benchmark value.

[0013] Further, the calculation formula of the comprehensive quality deviation value in the dynamic parameter calibration module is: , wherein, is the comprehensive quality deviation value; γ is the deviation weight, the value is 0.5-0.7; is the actual detection value of walnut kernel protein; is the walnut kernel protein content benchmark value; is the actual detection value of honey fructose; is the honey fructose content benchmark value; is the interface bonding degree comprehensive index measured value; the threshold value of the comprehensive quality deviation value is set to 0.1, and when the calibration process is started, and the equipment parameter adjustment log is recorded synchronously in the calibration process.

[0014] Further, the calculation formula of the near-infrared spectral characteristic wavelength adjustment amount in the dynamic parameter calibration module is: , wherein, is the near-infrared spectrum characteristic wavelength adjustment amount; is the comprehensive quality deviation value; is the near-infrared spectrum wavelength initial angle, taking a value of 50°-70°; while adjusting the wavelength, the scanning number of the near-infrared spectrometer is set to 64 times, and the resolution is set to 4 cm -1 .

[0015] Further, the calculation formula of the trace contaminant synergistic enrichment efficiency in the multi-dimensional quality judgment module is: wherein, is the trace contaminant synergistic enrichment efficiency; is the contaminant concentration before enrichment; is the contaminant concentration after enrichment; is the specific surface area of the magnetic nanoparticles; is the contaminant synergistic adsorption coefficient; is the molar mass of the antibiotic in the honey; is the molar mass of the pesticide residue in the walnut kernel; is the total volume after sample treatment; is the density of the extraction solvent.

[0016] Further, the calculation formula of the multi-dimensional quality comprehensive score in the multi-dimensional quality judgment module is: wherein, is the multi-dimensional quality comprehensive score; is the calibrated walnut kernel protein content; is the walnut kernel protein content reference value; is the calibrated honey fructose content; is the honey fructose content reference value; is the calibrated interface binding degree comprehensive index; is the contaminant risk coefficient; is the contaminant concentration after enrichment; the qualified threshold of the comprehensive score is set to 85, when judged as unqualified, the specific unqualified item is marked and improvement suggestions are generated.

[0017] Further, the calculation formula of the traceability data reliability in the result application traceability module is: wherein, is the traceability data reliability; is the full-process data recorded by the i th node of the blockchain; is the average value of the data recorded by the node; is the number of blockchain nodes, including 5 enterprise nodes and 5 third-party detection nodes; is the maximum value of the corresponding type of data; is the node trust coefficient.

[0018] Further, the walnut kernel sample collected by the raw material reference database module comes from 10 core production areas, 30 samples per production area per quarter, 500g per sample; the honey sample comes from the corresponding production area, 20 samples per production area per quarter, 200g per sample; the database is synchronized to the cloud server through the SSL / TLS1.3 protocol, and the stored data includes sampling time, production area number, detection equipment model and original detection spectrum.

[0019] Further, the determination result pushed by the result application traceability module includes the raw material batch number, detection date, comprehensive score and each single index value; after receiving the result by the production execution end, the honey boiling temperature is adjusted according to the interface combination degree comprehensive index, and after receiving the unqualified result by the procurement execution end, the supplier evaluation process is started; the block chain node data update period is 24 hours, and the abnormal node data checking is performed by a third-party detection institution.

[0020] Compared with the prior art, the honey walnut kernel raw material double-dimension quality screening system has the following beneficial effects:

[0021] I. The present application establishes a multi-production area and multi-season reference data system through the raw material reference database module, synchronously obtains the basic index and interface interaction data through the raw material double-dimension detection module, solves the problem that the traditional detection only focuses on the quality of a single raw material and ignores the combination quality of honey and walnut kernel; at the same time, the dynamic parameter calibration module calculates the comprehensive quality deviation and equipment adjustment amount, realizes the adaptive optimization of the detection parameters, avoids the insufficient precision caused by fixed parameters, and through the construction of the "raw material basic quality + interface combination degree" double-dimension screening system, the raw material quality abnormality can be identified from the aspects of raw material basic properties and interface interaction state, the detection error of the interface combination degree is controlled within a reasonable range, the detection precision can meet the fine screening demand of honey walnut kernel raw material, and the potential risks caused by raw material fluctuation and interaction quality can be covered.

[0022] II. The present application introduces the magnetic nanoparticle synergistic enrichment technology, realizes the weighted evaluation of basic quality, interface combination degree and pollutant residue through the comprehensive score, ensures that the determination result is comprehensive and quantitative, and avoids the one-sidedness of single index determination; at the same time, the result application traceability module integrates the whole process data into the block chain, quantifies the data authenticity and generates a traceability two-dimensional code with credibility, which not only enables the production end to accurately adjust the process according to the determination result and reduce the raw material loss, but also enables consumers to intuitively obtain the whole chain information of raw material screening, and improves the consumer trust.

[0023] The other advantages, objects and features of the present application will be set forth in part in the following specification, and in part will be apparent to those skilled in the art from the examination of the following text, or will be learned from the practice of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0025] Figure 1 A honey walnut kernel raw material two-dimensional quality screening system flow chart;

[0026] Figure 2 A device parameter feedback calibration method flow chart of a dynamic parameter calibration module. DETAILED DESCRIPTION

[0027] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined object of the application, the specific embodiments, structures, features and effects according to the present application will be described in detail below in combination with the drawings and preferred embodiments.

[0028] Example one: screening of summer batch of honey walnut kernel raw material

[0029] Start the raw material reference database module, which has stored the protein content reference value of summer walnut kernel in 10 core production areas, the honey fructose content reference value, and the honey penetration depth reference value detected by the low-field nuclear magnetic resonance instrument, the honey transverse relaxation time reference value, the honey extraction rate reference value obtained by image recognition, and the interface bonding degree comprehensive index reference value has been calculated and stored. The calculation formula of the interface bonding degree comprehensive index reference value is: Wherein, is the interface bonding degree comprehensive index reference value; is the honey penetration depth reference value; is the production area adaptation coefficient, the value range is 0.95-1.10; is the seasonal correction factor, the value range is 0.7-1.3; is the honey extraction rate reference value; is the honey transverse relaxation time reference value, the database is kept in cloud synchronization through SSL / TLS1.3 protocol, and has stored the sampling time, production area number, detection device model and original detection spectrum, as shown in Figure 1

[0030] ​The raw material double-dimensional detection module is operated to detect the summer new batch of honey walnut kernel raw materials: the actual detection value of walnut kernel protein and the actual detection value of honey fructose are detected by a near-infrared spectrometer; the actual penetration depth of honey and the actual transverse relaxation time are detected by a low-field nuclear magnetic resonance instrument; the honey extraction rate is obtained by image recognition, and then the interface bonding degree comprehensive index measured value is calculated according to the preset logic calculation interface, and the calculation formula of the interface bonding degree comprehensive index measured value is: , wherein, is the interface bonding degree comprehensive index measured value; is the actual penetration depth of honey; is the honey penetration depth reference value; is the production area adaptation coefficient; is the seasonal correction factor; is the honey extraction rate; is the actual transverse relaxation time of honey; is the honey transverse relaxation time reference value.

[0031] The dynamic parameter calibration module is called, which retrieves the corresponding reference value from the raw material reference database module, compares it with the measured value obtained by the raw material double-dimensional detection module, and calculates the comprehensive quality deviation value, and the calculation formula of the comprehensive quality deviation value is: , wherein, is the comprehensive quality deviation value; is the deviation weight, and the value is 0.5-0.7; is the actual detection value of walnut kernel protein; is the walnut kernel protein content reference value; is the actual detection value of honey fructose; is the honey fructose content reference value; is the interface bonding degree comprehensive index measured value; the threshold value of the comprehensive quality deviation value is set to 0.1. If the comprehensive quality deviation value exceeds the set threshold value, continue to calculate the near-infrared spectrum characteristic wavelength adjustment amount, and the calculation formula of the near-infrared spectrum characteristic wavelength adjustment amount is: , wherein, is the near-infrared spectrum characteristic wavelength adjustment amount; is the comprehensive quality deviation value; is the initial angle of the near-infrared spectrum wavelength, and the value is 50°-70°. According to the adjustment amount, the parameters of the near-infrared spectrometer are adjusted (the scanning number is set to 64 times, and the resolution is set to 4cm-1), and the radio frequency pulse parameters of the low-field nuclear magnetic resonance instrument and the gray threshold value of the industrial camera are also adjusted. After adjustment, re-detect to obtain the calibrated walnut kernel protein content, honey fructose content and interface bonding degree comprehensive index, and the equipment parameter adjustment log is recorded synchronously in the calibration process.

[0032] The multi-dimensional quality judgment module is started, and the surface modified magnetic nanoparticles are used for enrichment treatment of antibiotics in honey and pesticide residues in walnut kernels. The enrichment operation is carried out in a constant temperature water bath at 30°C with an oscillation speed of 200 r / min. Then the synergistic enrichment efficiency of trace pollutants is calculated. The calculation formula of the synergistic enrichment efficiency of trace pollutants is: wherein, is the synergistic enrichment efficiency of trace pollutants; is the concentration of pollutants before enrichment; is the concentration of pollutants after enrichment; is the specific surface area of magnetic nanoparticles; is the synergistic adsorption coefficient of pollutants; is the molar mass of antibiotics in honey; is the molar mass of pesticide residues in walnut kernels; is the total volume after sample treatment; is the density of the extraction solvent. If the enrichment efficiency reaches the set standard, the concentration of pollutants after enrichment is detected and obtained, and then the multi-dimensional quality comprehensive score is calculated in combination with the calibrated raw material index. The calculation formula of the multi-dimensional quality comprehensive score is: wherein, is the multi-dimensional quality comprehensive score; is the calibrated walnut kernel protein content; is the reference value of walnut kernel protein content; is the calibrated honey fructose content; is the reference value of honey fructose content; is the calibrated interface bonding degree comprehensive index; is the pollutant risk coefficient; is the concentration of pollutants after enrichment; the qualified threshold of the comprehensive score is set to 85, and the quality judgment result is output according to whether the comprehensive score reaches the qualified threshold. If it is judged to be unqualified, the specific unqualified items are marked and improvement suggestions are generated.

[0033] The running result application tracing module pushes the judgment result (including raw material batch number, detection date, comprehensive score and each single index value) of the multi-dimensional quality judgment module to the production execution end and the procurement execution end. The production execution end adjusts the honey boiling temperature according to the interface bonding degree comprehensive index, and the procurement execution end starts the supplier evaluation process if it receives an unqualified result. At the same time, the module enters the core data of the raw material reference database module, the raw material two-dimensional detection module, the dynamic parameter calibration module and the multi-dimensional quality judgment module into the blockchain (including 5 enterprise nodes and 5 third-party detection nodes), calculates the traceability data credibility and generates a traceability two-dimensional code with credibility. The calculation formula of the traceability data credibility is: wherein, is the traceability data credibility; is the number of nodes in the blockchain; Whole-process data recorded by the node; Average value of the data recorded for the node; The number of blockchain nodes, including 5 enterprise nodes and 5 third-party detection nodes; The maximum value of the corresponding type of data; The node trust coefficient, the blockchain data cannot be tampered with after writing, the node data update period is 24 hours, if the traceability data credibility does not meet the set requirements, feedback to the raw material benchmark database module to update the benchmark value, and the abnormal node data is checked by the third-party detection agency.

[0034] In summary, the present embodiment is aimed at the screening scene of summer new batch of honey walnut kernel raw materials, and the five modules of "a honey walnut kernel raw material double-dimension quality screening system" are completely run. First, the stored summer core production area raw material benchmark data is retrieved through the raw material benchmark database module, and then the raw material double-dimension detection module completes the synchronous detection of the basic quality of the new batch of raw materials and the interface combination degree, and obtains the measured value and the interface combination degree comprehensive index measured value. Subsequently, the dynamic parameter calibration module calculates the comprehensive quality deviation value and the near-infrared spectral characteristic wavelength adjustment amount, optimizes the detection equipment parameters and re-detects to obtain the calibrated data. The multi-dimensional quality determination module enriches the pollutants by magnetic nanoparticles, calculates the synergistic enrichment efficiency of trace pollutants, and multi-dimensional quality comprehensive score, and outputs the quality determination result. Finally, the result application tracing module pushes the determination result to the execution end, enters the whole-process data into the blockchain, and generates a traceable two-dimensional code with credibility, realizing the whole-process quality control of summer new batch of raw materials from detection to tracing.

[0035] Example two: winter cross-region honey walnut kernel raw material screening

[0036] The raw material benchmark database module is opened, which stores the walnut kernel protein content benchmark value, honey fructose content benchmark value, and honey penetration depth benchmark value detected by a low-field nuclear magnetic resonance instrument, honey transverse relaxation time benchmark value, and honey extraction rate benchmark value obtained by image recognition in 10 core production areas in winter. The calculation and storage of the interface combination degree comprehensive index benchmark value have been completed, and the calculation formula of the interface combination degree comprehensive index benchmark value is: The database is synchronized with the cloud through SSL / TLS1.3 protocol, and the storage information covers sampling time, production area number, detection equipment model and original detection spectrum.

[0037] Run the raw material double-dimensional detection module to detect the new batch of honey walnut kernel raw materials in winter across production areas (such as purchasing walnut kernels from production area A and honey from production area B): use the near-infrared spectrometer to detect the actual detection value of walnut kernel protein and the actual detection value of honey fructose; use the low-field nuclear magnetic resonance instrument to detect the actual penetration depth and actual transverse relaxation time of honey; use image recognition to obtain the honey loss rate, and then calculate the actual value of the interface combination degree comprehensive index according to the preset rules, and the calculation formula of the actual value of the interface combination degree comprehensive index is: Before detection, the walnut kernel sample is treated with deionized water cleaning and draining (to ensure that the water content is ≤8%), and the honey sample is diluted to 50% concentration for unified detection standard.

[0038] Start the dynamic parameter calibration module, and call the corresponding reference values of walnut kernels from production area A and honey from production area B in winter from the raw material reference database module, compare them with the actual values obtained by the raw material double-dimensional detection module, and calculate the comprehensive quality deviation value, the calculation formula of the comprehensive quality deviation value is: If the comprehensive quality deviation value exceeds the set threshold value (0.1), calculate the near-infrared spectrum characteristic wavelength adjustment amount, the calculation formula of the near-infrared spectrum characteristic wavelength adjustment amount is: According to the adjustment amount, adjust the near-infrared spectrometer parameters (set the scanning times to 64 times and the resolution to 4 cm-1), and at the same time, adjust the low-field nuclear magnetic resonance instrument and industrial camera parameters, and after adjustment, re-detect to obtain the calibrated walnut kernel protein content, honey fructose content and interface combination degree comprehensive index, and record the changes of the equipment parameters during the calibration process, as shown in Figure 2 .

[0039] Run the multi-dimensional quality judgment module, use surface-modified magnetic nanoparticles to enrich antibiotics in honey and pesticide residues in walnut kernels, calculate the synergistic enrichment efficiency of trace pollutants after enrichment, and the calculation formula of the synergistic enrichment efficiency of trace pollutants is: If the enrichment efficiency meets the set standard, detect the concentration of pollutants after enrichment, calculate the multi-dimensional quality comprehensive score combined with the calibrated raw material indicators, and the calculation formula of the multi-dimensional quality comprehensive score is: According to whether the comprehensive score reaches the qualified threshold of 8 points, output the quality judgment result, and mark the problem item and generate improvement suggestions when it is unqualified.

[0040] Start the result application traceability module, push the judgment result to the production execution end and the procurement execution end, the production execution end adjusts the honey boiling process parameters according to the interface combination degree comprehensive index, and the procurement execution end evaluates the production area adaptability according to the judgment result of the cross-production area raw materials. At the same time, record the core data of each module into the blockchain, calculate the traceability data credibility and generate a traceability two-dimensional code with credibility, and the calculation formula of the traceability data credibility is: , the blockchain node data is updated for 24 hours, if the traceability data is not up to standard, feedback to the raw material benchmark database module to update the benchmark value, and the abnormal node data is checked by a third-party detection agency.

[0041] In summary, the present embodiment focuses on the screening of winter cross-region honey walnut kernel raw materials, relying on a "honey walnut kernel raw material double-dimension quality screening system" to carry out screening work. First, open the raw material benchmark database module and retrieve the winter cross-region (A production area walnut kernel, B production area honey) raw material benchmark data. The raw material double-dimension detection module completes the cross-region raw material basic quality and interface bonding degree detection after pretreatment of the sample, calculates the interface bonding degree comprehensive index measured value. The dynamic parameter calibration module compares the cross-region benchmark value and the measured value, calculates the comprehensive quality deviation value, and if it exceeds the threshold, adjusts the equipment parameters and re-detects to obtain the calibration data. The multi-dimensional quality judgment module enriches pollutants by magnetic nanoparticles, calculates the synergistic enrichment efficiency of trace pollutants and the comprehensive score, and outputs the judgment result. The result application tracking module pushes the result to the execution end, assists in production process adjustment and production area adaptability evaluation, at the same time, the data is entered into the blockchain to generate a traceability two-dimensional code, effectively solving the quality screening and traceability problem of winter cross-region raw materials.

[0042] The above is only a preferred embodiment of the present application, and does not limit the present application in any form. Although the present application has been disclosed as above, it is not intended to limit the present application. Any person skilled in the art can make some changes or modifications to the above disclosed technical content without departing from the scope of the present application, and any brief introduction, modification, equivalent change and modification of the above embodiments made according to the technical essence of the present application are still within the scope of the present application.

Claims

1. A honey and walnut kernel raw material two-dimensional quality screening system, characterized in that, The system comprises: The raw material reference database module: collect walnut kernel and honey samples from different production areas and seasons, detect and determine the walnut kernel protein content reference value, honey fructose content reference value, detect and determine the honey penetration depth reference value and honey transverse relaxation time reference value by low-field nuclear magnetic resonance instrument, obtain the honey extraction rate reference value by image recognition, calculate the interface binding degree comprehensive index reference value, and store the above reference values to the database, and update the reference value fluctuation range regularly; The raw material double-dimension detection module: detects new batches of honey walnut kernel raw materials, detects and determines the actual detection values of walnut kernel protein and honey fructose by near-infrared spectrometer, detects and determines the actual penetration depth and actual transverse relaxation time of honey by low-field nuclear magnetic resonance instrument, obtains the honey extraction rate by image recognition, and calculates the actual measurement value of the interface binding degree comprehensive index; The dynamic parameter calibration module: calls the reference value and the measured value, calculates the comprehensive quality deviation value, if the comprehensive quality deviation value exceeds the set threshold, calculates the near-infrared spectrum characteristic wavelength adjustment amount, adjusts the detection equipment parameters after the wavelength adjustment amount, and re-detects to obtain the calibrated walnut kernel protein content, honey fructose content and interface binding degree comprehensive index; The multi-dimensional quality judgment module: uses magnetic nanoparticles to enrich antibiotics in honey and pesticides in walnut kernel, calculates the enrichment efficiency, if the enrichment efficiency reaches the set standard, obtains the concentration of pollutants after enrichment, calculates the comprehensive score, and outputs the quality judgment result according to whether the comprehensive score reaches the qualified threshold; The result application tracing module: pushes the judgment result of the multi-dimensional quality judgment module to the production and procurement execution end, and at the same time, the core data of each module is input into the block chain, the tracing data credibility is calculated, the tracing two-dimensional code with credibility is generated, and if the credibility does not reach the set requirement, the database reference value is updated to the raw material reference database module.

2. A honey and walnut kernel raw material two-dimensional quality screening system according to claim 1, characterized in that, The calculation formula of the interface bonding degree comprehensive index benchmark value in the raw material benchmark database module is: Wherein, is the interface bonding degree comprehensive index benchmark value; is the honey penetration depth benchmark value; is the production area adaptation coefficient, the value range is 0.95-1.10; is the seasonal correction factor, the value range is 0.7-1.3; is the honey extraction rate benchmark value; is the honey transverse relaxation time benchmark value.

3. A honey and walnut kernel raw material two-dimensional quality screening system according to claim 1, characterized in that, The calculation formula of the interface bonding degree comprehensive index measured value in the raw material double-dimensional detection module is: Wherein, is the interface bonding degree comprehensive index measured value; is the actual penetration depth of honey; is the honey penetration depth reference value; is the production area adaptation coefficient; is the seasonal correction factor; is the honey extraction rate; is the actual transverse relaxation time of honey; is the honey transverse relaxation time reference value.

4. A honey and walnut kernel raw material two-dimensional quality screening system according to claim 1, characterized in that, The calculation formula of the comprehensive quality deviation value in the dynamic parameter calibration module is: Wherein, is the comprehensive quality deviation value; is the deviation weight, and the value is 0.5-0.7; is the actual detection value of walnut kernel protein; is the reference value of walnut kernel protein content; is the actual detection value of honey fructose; is the reference value of honey fructose content; is the actual measurement value of the interface bonding degree comprehensive index; the threshold value of the comprehensive quality deviation value is set to 0.1, and when the calibration process is started, and the equipment parameter adjustment log is recorded synchronously in the calibration process.

5. A honey and walnut kernel raw material two-dimensional quality screening system according to claim 1, characterized in that, The calculation formula of the near-infrared spectral characteristic wavelength adjustment amount in the dynamic parameter calibration module is: Wherein, is the near-infrared spectral characteristic wavelength adjustment amount; is the comprehensive quality deviation value; is the near-infrared spectral wavelength initial angle, and the value is 50°-70°; while adjusting the wavelength, the scanning number of the near-infrared spectrometer is set to 64 times, and the resolution is set to 4cm -1 .

6. A honey and walnut kernel raw material two-dimensional quality screening system according to claim 1, characterized in that, The calculation formula of the synergistic enrichment efficiency of trace pollutants in the multi-dimensional quality determination module is: Wherein, is the synergistic enrichment efficiency of trace pollutants; is the concentration of pollutants before enrichment; is the concentration of pollutants after enrichment; is the specific surface area of magnetic nanoparticles; is the synergistic adsorption coefficient of pollutants; is the molar mass of antibiotics in honey; is the molar mass of pesticide residues in walnut kernels; is the total volume after sample treatment; is the density of the extraction solvent.

7. A honey and walnut kernel raw material two-dimensional quality screening system according to claim 1, characterized in that, The calculation formula of the multi-dimensional quality comprehensive score in the multi-dimensional quality determination module is: Wherein, is the multi-dimensional quality comprehensive score; is the calibrated walnut kernel protein content; is the walnut kernel protein content reference value; is the calibrated honey fructose content; is the honey fructose content reference value; is the calibrated interface binding degree comprehensive index; is the pollutant risk coefficient; is the enriched pollutant concentration; the qualified threshold of the comprehensive score is set to 85, when it is determined to be unqualified, the specific unqualified item is marked and improvement suggestions are generated.

8. A honey and walnut kernel raw material two-dimensional quality screening system according to claim 1, characterized in that, The formula for calculating the reliability of traceability data in the traceability module is as follows: ,in, To ensure the reliability of the data; For the first blockchain Each node records the entire process data; Record the average value of the data for this node; This refers to the number of blockchain nodes, including 5 enterprise nodes and 5 third-party testing nodes; The maximum value of the corresponding data type; This represents the node trust coefficient.

9. A honey and walnut kernel raw material two-dimensional quality screening system according to claim 1, characterized in that, The walnut kernel samples collected by the raw material reference database module come from 10 core production areas, 30 samples per production area per quarter, and each sample is 500g; the honey samples come from the corresponding production area, 20 samples per production area per quarter, and each sample is 200g; the database is synchronized to the cloud server through SSL / TLS1.3 protocol, and the stored data includes sampling time, production area number, detection equipment model and original detection spectrum.

10. A honey and walnut kernel raw material two-dimensional quality screening system according to claim 1, characterized in that, The judgment result pushed by the result application tracing module includes raw material batch number, detection date, comprehensive score and each single index value; after receiving the result, the production execution end adjusts the honey boiling temperature according to the interface binding degree comprehensive index, and after receiving the unqualified result, the procurement execution end starts the supplier evaluation process; The block chain node data update period is 24 hours, and the abnormal node data check is performed by a third-party detection institution.

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