CN112881616A - Electronic nose device for monitoring vehicle-mounted food quality - Google Patents
Electronic nose device for monitoring vehicle-mounted food quality Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 50
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- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 claims description 6
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- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
- G01N33/0031—General constructional details of gas analysers, e.g. portable test equipment concerning the detector comprising two or more sensors, e.g. a sensor array
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
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Abstract
The invention discloses a vehicle-mounted electronic nose device for monitoring the quality of food, which comprises a vehicle-mounted fixing component for fixedly mounting the device, a pipeline filter for filtering gas impurities, a pipeline for realizing gas sampling through air pump control, an air chamber for detecting the components of sampled gas and a control mainboard for controlling gas sampling, acquiring data, processing the data and uploading the data. The electronic nose device can realize detection of nitrogen, sulfuration, alcohols and comprehensive VOC of food volatile gas; compared with the prior art, the device has the advantages of delicate structure, rigid and tough installation mode, high detection sensitivity, and capability of avoiding the damage of vehicle-mounted impact on instruments, and detecting the food quality change by conforming to a multi-parameter mode of 4 sensors; the detection air chamber adopts temperature control to adjust, reduces the influence coefficient of temperature and humidity on the sensor, and provides detection precision.
Description
Technical Field
The invention belongs to the technical field of food quality monitoring, and particularly relates to a vehicle-mounted electronic nose device for monitoring the food quality.
Background
Food production and operation enterprises which are licensed in China can reach 1180 thousands of enterprises, internet food sales are rapidly increased, quality safety awareness of operators is general and weak, limited market supervision resources effectively guarantee food safety and face challenges, a novel monitoring method is urgently needed to be researched to solve the contradiction between insufficient supervision resources and improvement of supervision effect, and an intelligent supervision system and method are developed to provide a technical means for intelligent supervision.
The risk point control and tracing can better guarantee the food safety. The united states has first pursued hazard analysis and key control point management, implemented full process control of the production, processing, transportation, storage links, and also monitored media and network information in real time. The European Union adopts the food safety tracking implemented by a global unified identification system to strictly control and identify the whole process food supply chain. The information inquiry of the producing area, the breeder, the cattle variety and the like of the beef is realized in Japan, and the source tracing is realized through the livestock DNA. The food safety early warning research in China is still in the primary stage, wherein the agricultural department develops the control research on the quality and food safety of agricultural products earlier, and dynamically monitors and warns the production, demand, inventory, import and export and the like of the agricultural products. A food safety data warehouse is established by a food safety monitoring center in Beijing to aim at daily monitoring and analyzing mass data information, and a multi-source dynamic data integrated food safety management informatization environment is initially established.
The big data provides a new technical means for food safety. Developed countries such as the United states and the like utilize big data mining analysis theory and technology, form a multi-level data structure through food classification coding and internet food sales information acquisition, and establish an internet food sales illegal behavior supervision system based on big data. Researches of companies such as Walmart and the like show that the block chain technology greatly shortens the food tracing cost and time; a block chain tracing system is established in companies such as GreenFice and the like, and international enterprises such as IBM, Madelong, Chipotle and the like also provide tracing and anti-counterfeiting applications based on product electronic code information service standards.
The food spoilage can be characterized by the number of florae, the content of components and the like, and can also be indirectly reflected and predicted by detecting the external environmental conditions of the food and the products after metabolism. Technologies such as microbial temperature time labels, enzyme temperature labels, freshness labels and the like are internationally appeared and used for indicating the quality of fresh food, and effective monitoring equipment and monitoring methods are always relatively lacked in the food logistics process of China.
At present, the main food shelf life identification methods at home and abroad comprise a sensory evaluation method, a physicochemical index and microbial index evaluation method, a near infrared spectrum detection method and a bionic electronic nose identification method. The sensory evaluation method can intuitively reflect the sensory requirements of consumers on food, but the method is time-consuming and labor-consuming, has high requirements on evaluators, and the evaluation result is easy to be interfered by subjective factors and cannot meet the requirement of shelf detection of large-batch food. Although the physicochemical index and microbial index evaluation method overcomes the interference of subjective factors, the method is complex to operate, slow in detection speed and requires manual participation in the whole process. In addition, the physicochemical index and microbial index of food in storage are affected by raw materials, initial bacteria, processing technology, storage and transportation environment, and the like, and the physicochemical index and microbial index method can only roughly judge the shelf life of food. Due to mutual shielding caused by mass storage of foods and limitation of a field angle, the near infrared spectrum detection method is likely to have omission, and the phenomenon of foreign matters in the same spectrum is also an important element relative sense organ evaluation method, a physicochemical index and a microorganism index evaluation method which influence the accuracy of the near infrared spectrum detection method, so that the electronic nose identification method greatly reduces the labor intensity, improves the detection efficiency and is more intelligent; the relative near infrared spectrum detection method is not influenced by the limit of the food visual field angle and the mutual shielding between foods. Therefore, the electronic nose is more suitable for identifying food shelf information, has wide application prospect, and along with the development of the electronic nose technology and the improvement of the manufacturing process of the gas sensor, more and more high-precision gas sensors are applied to solving the problem of classification and identification.
The literature [ LI H, CHEN Q S, ZHAO J W, et al. non-destructive evaluation of porous fresh using adaptive electronic nose (E-nose) base on a colorimetric sensor array [ J ]. Analytical Methods,2014,6(16):6271-6277] proposes to use a colorimetric sensor array to manufacture an electronic nose to measure pork freshness and to establish a linear discriminant analysis model (LDA) and a forward multilayer artificial neural network model (BP-ANN), wherein the accuracy of the 2 models is 97.5% and 100%, respectively.
The document [ Yang, Guo and Jiang, Wang and Zhang, etc. ] shows that the electronic nose is used to measure and refrigerate the pork samples at different time and before the frozen storage, the odor data difference is obvious and the accuracy of the established neural network prediction model is high.
The literature [ Wangming, Gaofan, Zhang Junyu and the like, an intelligent electronic nose-based refrigerator refrigerated food freshness in-situ detection technology [ J ] a sensing technology report, 2019,32(2):161 plus 166] proposes that the electronic nose is used for detecting the freshness of food stored in a refrigerator refrigerated chamber (4 ℃), a mode recognition algorithm is used for distinguishing freshness, sub-freshness and putrefaction of the food, and an experimental conclusion shows that the electronic nose is used for obtaining the odor change of the food, so that the technology can be used for detecting the freshness of the food in the refrigerator in real time.
With the continuous development of the gas sensor technology, artificial intelligence is rapidly developed, people have more and more extensive application scenes of electronic nose equipment, and algorithm technology in an electronic nose system is concerned more and more, for example, the electronic nose system recognizes the freshness of fruits and vegetables and detects cold-chain logistics, warehouse storage and other complex environments from the detection of the electronic nose system in the traditional simple environment.
Disclosure of Invention
In view of the above, the invention provides a vehicle-mounted electronic nose device for monitoring food quality, which can realize whole-process gas monitoring on the food quality in the food logistics process.
A vehicle-mounted electronic nose device for monitoring the quality of food comprises a device shell, wherein a detection gas sampling pipeline, a detection gas chamber, a gas pipeline filter, a gas pump and a control main board are arranged in the device shell, a gas inlet of the detection gas sampling pipeline is led out of the shell, a gas outlet of the detection gas sampling pipeline is communicated with the detection gas chamber, and the detection gas sampling pipeline is driven by the gas pump to realize sampling of food volatile gas in a carriage; the gas pipeline filter is arranged on one side, close to the gas inlet, of the detection gas sampling pipeline and is used for filtering gas impurities in the pipeline; a monitoring sensor of related gas is arranged in the detection gas chamber and is used for detecting the components of the sampled gas; the control mainboard is connected with the monitoring sensor and is used for being responsible for gas sampling control, data acquisition, data processing and data uploading.
Furthermore, a vehicle-mounted fixing component is arranged on the device shell and used for vehicle-mounted fixed installation of the electronic nose device, and the requirements of rigidity and toughness of vehicle-mounted installation of the device can be met.
Further, aiming at the volatilization change of the nitrogen-containing gas in the food deterioration process, an ammonia gas monitoring sensor is arranged in the detection gas chamber, and the monitoring range is 0-100 ppm.
Further, aiming at the volatilization change of sulfide gas in the food deterioration process, a hydrogen sulfide gas monitoring sensor is arranged in the detection gas chamber, and the monitoring range is 0-50 ppm.
Further, an alcohol gas monitoring sensor is installed in the detection air chamber aiming at the volatilization change of alcohol gas in the food deterioration process, and the monitoring range is 0-500 ppm.
Furthermore, aiming at the volatilization change of the comprehensive organic gases in the food deterioration process, a VOC (volatile organic compounds) gas monitoring sensor is arranged in the detection air chamber, and the monitoring range is 10-100 ppm.
Furthermore, an air heater and a humidifier are installed in the detection air chamber, and the heater and the humidifier are subjected to temperature control adjustment (the temperature is controlled within the range of 0-60 ℃) through the control main board, so that the influence of the temperature and the humidity on the accuracy of the sensor is reduced.
Further, the control mainboard uploads the detection result to the upper computer in a RS485 serial port communication mode after completing the collection and processing of gas data.
Furthermore, for any type of gas monitoring sensor, the components of the sampled gas in the gas chamber are detected through array distribution to generate a steady-state response resistance value as a sensing signal, and the sensing signal is filtered by a Kalman filter based on a sensor response correction model and then provided to a control mainboard; the control main board preprocesses the filtered sensing signals, namely, a differential algorithm is adopted to extract a characteristic gas response value, then the response value is calibrated according to the characteristic gas response value and the variation thereof and in combination with the temperature and the humidity in the air chamber, and finally the calibrated characteristic gas response value is normalized and guided into a pre-trained BP neural network model so as to identify the freshness and the shelf life of the current food.
The electronic nose device can realize detection of nitrogen, sulfuration, alcohols and comprehensive VOC of food volatile gas. Compared with the prior art, the device has the advantages of delicate structure, rigid and tough installation mode, high detection sensitivity, and capability of avoiding the damage of vehicle-mounted impact on instruments, and detecting the food quality change by conforming to a multi-parameter mode of 4 sensors; the detection air chamber adopts temperature control to adjust, reduces the influence coefficient of temperature and humidity on the sensor, and provides detection precision.
Drawings
Fig. 1 is a schematic structural view of an electronic nose device of the present invention.
Fig. 2 is a schematic view of a detection process of the electronic nose device of the present invention.
In fig. 1: the device comprises a shell, a gas sampling pipeline, a gas detection chamber, a gas pipeline filter, a gas pump, a control mainboard and a vehicle-mounted fixing component, wherein the shell is 1, the gas detection sampling pipeline is 2, the gas detection chamber is 3, the gas pipeline filter is 4, the gas pump is 5, the control mainboard is 6, and the vehicle-mounted fixing component is 7.
Detailed Description
In order to more specifically describe the present invention, the following detailed description is provided for the technical solution of the present invention with reference to the accompanying drawings and the specific embodiments.
As shown in fig. 1, the vehicle-mounted electronic nose device for monitoring food quality of the present invention comprises a housing 1, a detection gas sampling pipeline 2, a detection gas chamber 3, a gas pipeline filter 4, a gas pump 5 and a control mainboard 6 are installed in the housing 1, a gas inlet of the detection gas sampling pipeline 2 is led out of the housing 1, a gas outlet is communicated with the detection gas chamber 3, and the detection gas sampling pipeline 2 is driven by the gas pump 5 to realize sampling of food volatile gas; the gas pipeline filter 4 is arranged on the side, close to the gas inlet, of the detection gas sampling pipeline 2 and is used for filtering gas impurities in the pipeline; a monitoring sensor of related gas is arranged in the detection gas chamber 3 and is used for carrying out component detection on the sampled gas; the control main board 6 is connected with the monitoring sensor and is used for gas sampling control, data acquisition, data processing and data uploading.
And a vehicle-mounted fixing component 7 is further arranged on the shell 1 and used for vehicle-mounted fixed mounting of the electronic nose device, and the requirements on the rigidity and toughness of vehicle-mounted mounting of instruments can be met.
Aiming at the volatilization change of nitrogen-containing gas in the food deterioration process, an ammonia gas monitoring sensor is arranged in the detection gas chamber 3, and the monitoring range is 0-100 ppm; aiming at the volatilization change of sulfide gas in the food deterioration process, a hydrogen sulfide gas monitoring sensor is arranged in the detection gas chamber 3, and the monitoring range is 0-50 ppm; aiming at the volatilization change of alcohol gas in the food deterioration process, an alcohol gas monitoring sensor is arranged in the detection gas chamber 3, and the monitoring range is 0-500 ppm; aiming at the volatilization change of comprehensive organic gases in the food deterioration process, a VOC gas monitoring sensor is arranged in the detection gas chamber 3, and the monitoring range is 10-100 ppm.
An air heater and a humidifier are installed in the detection air chamber 3, and the heater and the humidifier are subjected to temperature control adjustment (the temperature is controlled within the range of 0-60 ℃) through the control main board 6, so that the influence of the temperature and the humidity on the accuracy of the sensor is reduced. The control mainboard 6 finishes the collection and the processing of gas data and uploads the detection result to the upper computer in the form of RS485 serial port communication.
As shown in figure 2, for the gas emitted by the food in the carriage, the device firstly utilizes the air pump to suck the gas into the air chamber, realizes the sampling of the volatile gas of the food in the carriage, and simultaneously utilizes the array sensor to sample the volatile gas in real timeSteady state response resistance R generated by gas emitted by food in containerijBased on a traditional sensor response correction model Kalman filter, filtering the sensor signal to suppress noise; then, data preprocessing is carried out on the sensor data after denoising, and a difference algorithm is adopted to extract a sensor response value Xij＝Rij–R0Wherein R is0Is the base resistance value of the sensor itself; further according to the sensor response value XijAmount of change Δ X ofijWhether the set range is reached or not to determine the accurate response value XijThe feedback regulation is carried out by combining feedback data with a heater and a humidifier in a control main board control air chamber; finally, the sensor response value X is calculatedijAnd carrying out normalization processing, and importing the trained BP neural network model for calculation so as to identify the freshness and shelf life of the current food material.
We now perform experimental operations on the electronic nose device of the present invention to describe in detail the overall detection process:
1. sample pretreatment
The sample taken in the experiment is fresh pork ham which is purchased from Jiaxing market Fengqian vegetable market and killed in the morning, and is brought back by a portable refrigerator and ice blocks. After purchase, the product is washed by ice water for several times, peeled, degreased, drained, cut into blocks, placed in a culture dish with the sterilization of 90mm, and then placed in a thermostat with the temperature of 4 ℃ (refrigeration condition), the temperature of 25 ℃ (normal temperature condition) and the temperature of 37 ℃ (extreme condition) for storage.
2. Electronic nose for detecting pork quality
Samples stored at 4 ℃ were measured for 6d, 1 time per day; samples stored at 25 ℃ were measured 1 time every 4 hours and 6 times; the samples stored at 37 ℃ were measured 1 time and 6 times every 2 hours. And when the measuring time reaches a point, taking out 50g of the weighed sample from the thermostat, filling the sample into a sample bottle which is washed clean in advance, detecting by using an electronic nose, recording data for 3min, and washing the samples for 5 min.
TVB-N, detection of microorganisms
The measurement of volatile basic nitrogen is carried out according to a semi-trace nitrogen determination method in the national standard (GB/T5009.44-2016), and the measurement value is carried out according to GB2707-2008 fresh (frozen) livestock meat volatilityThe freshness of each sample is judged according to the basic nitrogen index (TVB-N value (mg/100g) < 15). The determination of the total number of microbial colonies is carried out according to the national standard (GB/T4789.2-2016), the total number of microbial colonies exceeds 106Indicating sample spoilage.
Research shows that when the total number of bacterial colonies is less than or equal to 6lg cfu/g, the meat keeps good fresh state, when the total number of bacteria of the meat in storage reaches about 7lg cfu/g, peculiar smell is generated, when the total number of bacteria of the meat reaches 8lg cfu/g, the meat surface is sticky, and the meat is completely putrefactive and becomes completely unacceptable. When the content of TVB-N is less than or equal to 15mg/100g, the meat keeps a first-grade fresh state; if the protein in the pulp is continuously decomposed, the TVB-N content is continuously increased, and the pulp is changed into sub-fresh pulp with the content less than or equal to 25mg/100 g. When the content of TVB-N is more than or equal to 25mg/100g, obvious rancid odor can be smelled. Therefore, we define pork freshness as shown in table 1:
TABLE 1
4. Dynamic monitoring of pork spoilage process
During the storage process of pork, volatile components change along with the change of storage time. Sensory analysis shows that under different storage temperature conditions, with the increase of storage days, the color of the pork is changed from glossy, even red, milky fat gradually changes into low glossiness, even dark red, green surface, gradually reduced toughness, changed odor from no odor into peculiar smell, and even pungent and stink at high temperature.
Carrying out electronic nose detection on pork under 3 different storage temperatures, and detecting the total bacterial count and the content of volatile basic nitrogen to obtain the relationship between the electronic nose output signal, the total bacterial count, the volatile basic nitrogen and the pork storage time of each sample, wherein the specific data are as follows:
monitoring data at 4 deg.C
| MP3B | MP702 | MP502 | MP7110 | Temperature of | Humidity | Total number of colonies | TVBN | |
| Day one | 11.67773 | 7.593206 | 84.65725 | 27.79015 | 31.97 | 55.66 | 4.08 | 7.91 |
| The next day | 10.10665 | 5.095237 | 51.35212 | 15.43151 | 33.27 | 50.02 | 4.67 | 10.23 |
| The third day | 9.143888 | 2.31964 | 39.0493 | 14.893 | 30.39 | 51.4 | 5.77 | 14.67 |
| The fourth day | 7.88451 | 1.109462 | 21.86728 | 10.90138 | 29.16 | 57.82 | 6.46 | 20.34 |
| The fifth day | 6.226421 | 1.476896 | 23.16624 | 10.3748 | 28.74 | 57.64 | 6.48 | 27.35 |
| Day six | 6.080435 | 1.03748 | 19.04344 | 10.3748 | 31.06 | 55.02 | 8.34 | 31.11 |
25 ℃ State monitoring data
| MP3B | MP702 | MP502 | MP7110 | Temperature of | Humidity | Total number of colonies | TVBN | |
| 0h | 14.68944 | 11.12891 | 170.2497 | 27.97208 | 31.71 | 56.13 | 4.05 | 8.43 |
| 4h | 14.98586 | 10.57834 | 150.6121 | 38.13336 | 31.25 | 68.52 | 4.89 | 12.23 |
| 8h | 9.957726 | 6.945194 | 97.9767 | 25.98987 | 31.26 | 68.33 | 5.89 | 14.12 |
| 12h | 8.93109 | 4.865483 | 80.025 | 23.40935 | 30.54 | 69.13 | 6.34 | 18.23 |
| 16h | 7.898848 | 1.607878 | 33.61212 | 17.90368 | 30.68 | 68.52 | 7.78 | 27.78 |
| 20h | 7.62706 | 1.03748 | 14.96656 | 12.61819 | 31.15 | 66.6 | 8.78 | 33.78 |
37 ℃ State monitoring data
| MP3B | MP702 | MP502 | MP7110 | Temperature of | Humidity | Total number of colonies | TVBN | |
| 0h | 14.68944 | 11.12891 | 170.2497 | 27.97208 | 31.71 | 56.13 | 4.05 | 8.43 |
| 4h | 14.98586 | 10.57834 | 150.6121 | 38.13336 | 31.25 | 68.52 | 4.89 | 12.23 |
| 8h | 9.957726 | 6.945194 | 97.9767 | 25.98987 | 31.26 | 68.33 | 5.89 | 14.12 |
| 12h | 8.93109 | 4.865483 | 80.025 | 23.40935 | 30.54 | 69.13 | 6.34 | 18.23 |
| 16h | 7.898848 | 1.607878 | 33.61212 | 17.90368 | 30.68 | 68.52 | 7.78 | 27.78 |
| 20h | 7.62706 | 1.03748 | 14.96656 | 12.61819 | 31.15 | 66.6 | 8.78 | 33.78 |
The foregoing description of the embodiments is provided to enable one of ordinary skill in the art to make and use the invention, and it is to be understood that other modifications of the embodiments, and the generic principles defined herein may be applied to other embodiments without the use of inventive faculty, as will be readily apparent to those skilled in the art. Therefore, the present invention is not limited to the above embodiments, and those skilled in the art should make improvements and modifications to the present invention based on the disclosure of the present invention within the protection scope of the present invention.
Claims (9)
1. The utility model provides an electron nose device of vehicular food quality monitoring, includes the device casing, its characterized in that: a detection gas sampling pipeline, a detection gas chamber, a gas pipeline filter, a gas pump and a control main board are arranged in the device shell, a gas inlet of the detection gas sampling pipeline is led out of the shell, a gas outlet of the detection gas sampling pipeline is communicated with the detection gas chamber, and the detection gas sampling pipeline is driven by the gas pump to realize sampling of food volatile gas; the gas pipeline filter is arranged on one side, close to the gas inlet, of the detection gas sampling pipeline and is used for filtering gas impurities in the pipeline; a monitoring sensor of related gas is arranged in the detection gas chamber and is used for detecting the components of the sampled gas; the control mainboard is connected with the monitoring sensor and is used for being responsible for gas sampling control, data acquisition, data processing and data uploading.
2. The electronic nose device of claim 1, wherein: the device shell is provided with a vehicle-mounted fixing component for vehicle-mounted fixed installation of the electronic nose device, and the rigidity and toughness requirements of vehicle-mounted installation of the device can be met.
3. The electronic nose device of claim 1, wherein: aiming at the volatilization change of nitrogen-containing gas in the food deterioration process, an ammonia gas monitoring sensor is arranged in the detection gas chamber, and the monitoring range is 0-100 ppm.
4. The electronic nose device of claim 1, wherein: aiming at the volatilization change of sulfide gas in the food deterioration process, a hydrogen sulfide gas monitoring sensor is arranged in the detection gas chamber, and the monitoring range is 0-50 ppm.
5. The electronic nose device of claim 1, wherein: aiming at the volatilization change of alcohol gas in the food deterioration process, an alcohol gas monitoring sensor is arranged in the detection gas chamber, and the monitoring range is 0-500 ppm.
6. The electronic nose device of claim 1, wherein: aiming at the comprehensive organic gas volatilization change in the food deterioration process, a VOC gas monitoring sensor is arranged in the detection gas chamber, and the monitoring range is 10-100 ppm.
7. The electronic nose device of claim 1, wherein: an air heater and a humidifier are installed in the detection air chamber, and the heater and the humidifier are subjected to temperature control adjustment through the control main board, so that the influence of the temperature and the humidity on the precision of the sensor is reduced.
8. The electronic nose device of claim 1, wherein: and the control mainboard uploads the detection result to the upper computer in a RS485 serial port communication mode after completing the acquisition and processing of gas data.
9. The electronic nose device of claim 1, wherein: for any type of gas monitoring sensor, the components of the sampled gas in the gas chamber are detected through array distribution to generate a steady-state response resistance value as a sensing signal, and the sensing signal is filtered through a Kalman filter based on a sensor response correction model and then provided to a control mainboard; the control main board preprocesses the filtered sensing signals, namely, a differential algorithm is adopted to extract a characteristic gas response value, then the response value is calibrated according to the characteristic gas response value and the variation thereof and in combination with the temperature and the humidity in the air chamber, and finally the calibrated characteristic gas response value is normalized and guided into a pre-trained BP neural network model so as to identify the freshness and the shelf life of the current food.
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