CN112213363A - Method for judging mushroom drying stage based on gas sensor - Google Patents
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Abstract
The invention relates to a method for distinguishing a mushroom drying stage based on a gas sensor, which comprises the steps of sample preparation, detection information acquisition, mode recognition and judgment model construction, and belongs to the technical field of agricultural product detection. According to the invention, the odor information of the mushrooms at different drying times is obtained by adopting an array consisting of 6 metal oxide type gas sensors, and the drying stage of the mushrooms is judged rapidly, nondestructively and accurately through the established discrimination model. The invention can be used for monitoring the drying process of the lentinus edodes, prevents the deterioration of the quality of the lentinus edodes caused by incomplete drying or prevents the nutrition loss and energy waste caused by excessive drying, and saves the labor and time.
Description
Technical Field
The invention relates to a method for judging a mushroom drying stage based on a metal oxide type gas sensor, and belongs to the technical field of agricultural product detection.
Background
Lentinus edodes (Lentinus edodes) is the second major edible fungus in the world and is rich in amino acids, minerals, polysaccharides and other nutritional ingredients. Fresh mushrooms are extremely high in water content and vigorous in metabolism, and can soften brown stain in a short time after being picked, so that the commodity value is lost. Therefore, after the mushrooms are picked, a proper preservation method is selected to prolong the shelf life, and dehydration and drying are one of the important processes in the storage and processing of the mushrooms, so that the growth of microorganisms and the metabolic activity of sporocarp per se are inhibited by removing water. The hot air drying is the most common method in the processing of the shiitake mushrooms at present, the equipment is simple to operate and low in cost, and the fragrance of the shiitake mushrooms is favorably emitted in the drying process.
Drying not only changes the moisture content of the mushrooms, but also affects its flavor, nutrition and palatability. Fresh mushroom has light smell, sporophore is subjected to enzymatic and non-enzymatic reactions during drying to generate smell similar to that of garlic and rotten eggs, and Maillard reaction at the later stage of drying enhances the generation of fried flavor accompanied with light burnt smell. Meanwhile, a special volatile flavor substance of the dried mushroom, namely a sulfur-containing heterocyclic compound, is generated, particularly 1, 2, 3, 5, 6-pentasulfur heterocyclic heptane (shiitake essence), so that the obvious difference of the flavor characteristics of the dried and fresh shiitake mushrooms is caused.
The gas sensor array is a set consisting of a plurality of gas sensors with cross sensitivity, and can quickly and directly acquire the integral flavor information of the shiitake mushroom sample. The characteristic that the sensor can generate different responses to different volatile substances is utilized, the gas input information is converted into an electric signal, and a response spectrum of the gas is formed, so that different characteristic aromas are distinguished. Gas sensors can be classified into metal oxide semiconductor sensors, chemical capacitance type sensors, mass type gas sensors, electric potential type sensors, thermoelectric type sensors, etc. according to their operation principle, and the most widely used metal oxide sensor is currently the metal oxide sensor. The kit has the advantages of small volume, low cost, long working time and the like, has extremely high sensitivity and low detection limit, and can be directly used for detecting volatile substances in food.
The flavor change of the mushrooms is often closely related to the internal quality thereof, however, the drying conditions are difficult to control in the actual production, and the instability of the drying process is easy to generate inferior products and simultaneously accompanies the unpleasant smell. For the mushroom, the characteristic smell is an important index for evaluating the quality of the mushroom. Therefore, in order to ensure the quality of the end product of the mushroom, the gas sensor is used for collecting the odor information of the mushroom in different drying times, and the change of the aroma components of the mushroom is essential to be monitored in the drying process.
Disclosure of Invention
1. The invention aims to provide a novel method.
The invention aims to provide a method for judging the drying stage of lentinus edodes based on a metal oxide type gas sensor, which utilizes the gas sensor to obtain the odor information of the lentinus edodes in different drying times, quickly and nondestructively judges the drying stage of the lentinus edodes and prevents the nutrition loss and energy waste caused by the deterioration or excessive drying of the lentinus edodes due to incomplete drying.
2. The technical scheme is as follows.
A method for distinguishing the drying stage of lentinus edodes based on a gas sensor (the research technical route is shown in figure 1), which utilizes the gas sensor to obtain the odor information emitted by the dried lentinus edodes after different time to determine the drying stage of the lentinus edodes, and is characterized in that the distinguishing method comprises the following steps:
(1) sample preparation: spreading (one layer) 400g of fresh Lentinus Edodes (with moisture content of wet base of about 88%) with uniform size (canopy radius of about 2.5cm) in a 65 deg.C electric heating constant temperature air blast drying oven (volume of 105L), and drying for 8h to obtain drying end point (moisture content of wet base of about 13%);
(2) collecting detection information: an array of 6 metal oxide type gas sensors was used, MQ-136, S1, sensitive to hydrogen sulfide with a sensitivity of 1-200 ppm; TGS2602, S2, is sensitive to organic volatile substances with a sensitivity of 1-30 ppm; MQ-138, namely S3, is sensitive to volatile substances such as alcohol, aldehyde, ketone and the like, and the sensitivity is 5-500 ppm; TGS2620, namely S4, is sensitive to organic solvents such as ethanol and the like, and the sensitivity is 50-5000 ppm; MQ-2, namely S5, is sensitive to substances such as liquefied gas, propane, hydrogen and the like, and the sensitivity is 300-10000 ppm; TGS2610, namely S6, is sensitive to alkanes, and the sensitivity is 500-10000 ppm; the gas sensor is an independently developed electronic nose system, the system is subjected to gas washing before sample detection, the time is 5min, the sample detection time is 60S, the sample interval gas washing time is 100S, the response value S of the gas sensor is the ratio (G/G0) of the resistance G of the sensor after contacting with sample volatile matters and the resistance G0 of the sensor after contacting with clean air, and the average value of the response values of 58 th to 60 th S of each sensor is extracted as a characteristic value;
(3) constructing a pattern recognition and discrimination model: modeling the extracted characteristic values by adopting a support vector machine model (SVM-C), and then constructing four support vector machine modules distinguished in the drying stage by utilizing an LIBSVM software package: SVM1, SVM2, SVM3, SVM 4; the response values S1-S6 of 6 metal oxide gas sensors are sequentially substituted into the support vector machine modules for judging the four drying stages: SVM1, SVM2, SVM3, SVM4, the modules performing the discrimination of the four drying phases in a sequential relationship: fresh mushrooms are dried in the early stage, the middle stage and the later stage.
3. The invention has the advantages.
According to the method for judging the mushroom drying stage based on the metal oxide type gas sensor, the judging process is only 1 minute, the accuracy rate can reach 95%, and the method is rapid and accurate; the sample pretreatment is simple, and the lentinus edodes is not damaged; the judgment model is established by adopting 240 shiitake mushroom samples, so that the model is extremely high in stability, repeatability and applicability; the weighing operation at the drying end point is avoided, and the labor and the time are saved; the quality deterioration phenomenon generated in the drying process is monitored and early warned in time, so that more serious economic loss is avoided.
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FIG. 1: technical route map
FIG. 2: the gas sensor is used for detecting response graphs of mushrooms in different drying stages, wherein (a) the detection response graph of fresh mushrooms, (b) the detection response graph of mushrooms at the early stage of drying, (c) the detection response graph of mushrooms at the middle stage of drying, and (d) the detection response graph of mushrooms at the later stage of drying
FIG. 3: PCA analysis chart of shiitake mushroom response values at different drying stages
FIG. 4: shiitake mushroom drying stage modeling result based on SVM-C discrimination mode
Detailed Description
A method for distinguishing a mushroom drying stage based on a gas sensor comprises the following specific implementation modes:
1. test materials
Selecting fresh Lentinus Edodes with uniform size (canopy radius of about 2.5cm) and intact fruiting body, trimming stem to length of about 1.0cm, cleaning, and wiping to remove surface water. 400g of mushroom samples are spread (one layer) and dried in an electrothermal constant-temperature air blast drying oven at 65 ℃ until the drying end point is reached (the moisture content of a wet base is less than 13 percent), and the drying end point is reached after the moisture content of the wet base is measured for 8 hours.
2. Testing instrument
The model of the used electric heating constant temperature air-blast drying oven is DGG-9123A, Shanghai Senxin experiment instrument Co., Ltd; the electronic nose is independently developed and comprises 6 metal oxide type sensors, namely MQ-136, namely S1, and is sensitive to hydrogen sulfide, and the sensitivity is 1-200 ppm; TGS2602, S2, is sensitive to organic volatile substances with a sensitivity of 1-30 ppm; MQ-138, namely S3, is sensitive to volatile substances such as alcohol, aldehyde, ketone and the like, and the sensitivity is 5-500 ppm; TGS2620, namely S4, is sensitive to organic solvents such as ethanol and the like, and the sensitivity is 50-5000 ppm; MQ-2, namely S5, is sensitive to substances such as liquefied gas, propane, hydrogen and the like, and the sensitivity is 300-10000 ppm; TGS2610, S6, is sensitive to alkanes with a sensitivity of 500-10000 ppm.
3. Sorting of drying stages
The drying process of the mushroom is divided into four stages according to the moisture content of the wet base, namely fresh mushroom (the moisture content of the wet base is 88%), the early stage of drying (the moisture content of the wet base is 75-88%), the middle stage of drying (the moisture content of the wet base is 50-75%) and the later stage of drying (the moisture content of the wet base is 13-50%).
4. Collecting detection signals
Placing single shiitake mushroom samples in different drying stages in a 250ml beaker, covering tin foil paper on the cup mouth, placing in a headspace at room temperature (25 ℃) and sealing for 7min to ensure that the smell of the shiitake mushroom is fully emitted and the shiitake mushroom samples reach balance, and then starting detection. 60 shiitake mushroom samples were taken for each drying stage. The sample detection time was 60s and the sample interval purge time was 100 s. The response value S of the gas sensor is determined by the resistance G of the sensor after contacting the sample volatile matter and the resistance G of the sensor after contacting the clean air0Ratio of (G/G)0) And extracting a response value (an average value of 58 th to 60 th s) when the sensor signal tends to be stable as a characteristic stable value for subsequent analysis.
5. Construction of pattern recognition and discrimination model
And (4) selecting a support vector machine discrimination algorithm (SVM-C) to establish a model in the drying stage. The total mushroom samples were as follows 3: 1, randomly dividing the model into a model set and a verification set, wherein 180 samples of the model set and 60 samples of the verification set are obtained. And the characteristic stable value of each sensor is used as an input variable, the corresponding drying stage label is used as an output variable, and the performance of the sensor is evaluated through the accuracy of the model. Four support vector machine modules for drying stage discrimination are constructed by using an LIBSVM software package: SVM1, SVM2, SVM3, SVM 4; the response values S1-S6 of 6 metal oxide gas sensors are sequentially substituted into the support vector machine modules for judging the four drying stages: SVM1, SVM2, SVM3, SVM4, the modules performing the discrimination of the four drying phases in a sequential relationship: fresh mushrooms are dried in the early stage, the middle stage and the later stage.
6. Response analysis of gas sensor to lentinus edodes smells in different drying stages
As shown in FIG. 2, the gas sensor detection response chart of Lentinus edodes at different drying stages has abscissa as detection time and ordinate as response value of each sensor, and the deviation of the value from the base line value of 1 represents the gas concentration detected by the sensor. FIG. 2a is a response signal diagram of fresh mushrooms, and the response values of all sensors are low, which shows that the fresh mushrooms are very light in smell. FIG. 2b is a graph of response signals of mushroom at the early stage of drying, wherein S1, S3 and S2 are three sensors with the highest response values, which reach about 1.5, and S6, S4 and S5 are the next, and the response values also reach about 1.25. Indicating that the dried mushroom has changed significantly in odor. Fig. 2c is a response signal diagram of the mushroom in the middle drying period, the response values of the sensors are improved in different amplitudes, wherein the response value of S2 is the highest and reaches about 2.7; the response values of S3 and S1 are slightly lower than S2 and reach about 2.3; the response values of the three sensors S4, S5 and S6 are still relatively close to each other, about 1.5. At this time, the stage with the highest response value of the mushrooms indicates that the mushrooms in the middle stage of drying are the most intense in smell. FIG. 2d is a graph of the response signal of the dried mushroom, and the response value of S2 falls back to about 1.5; the response values of other 5 sensors are reduced compared with the middle drying period and the early drying period, and the response values of the sensors S1, S6 and S5 are closer.
7. Principal component analysis of gas sensor detection signal
As shown in FIG. 3, the PCA analysis chart of the response values of shiitake mushrooms in different drying stages shows that the contribution rates of the first principal component (PC1) and the second principal component (PC2) are 83.49% and 9.55%, respectively, and the total contribution rate is 93.04%, which can explain most information of the original data. It can be seen from fig. 3 that the data points of the different drying stages are dispersed along the first and second main components, and the shiitake mushroom samples of the respective different drying stages can be successfully distinguished.
8. Effect of mushroom drying stage discrimination model
As shown in FIG. 4, the results of the lentinus edodes drying stage discrimination model established based on SVM-C show that the accuracy rates of the modeling set and the prediction set respectively reach 95.56% and 93.33%, the overall accuracy rate reaches 95%, and the discrimination effect is good. When the method is applied, the mushroom sample at any drying stage is taken, and after the signals are collected in the step 4, the model can give a recognition result within 1 minute.
Claims (2)
1. A method for distinguishing a mushroom drying stage based on a gas sensor is characterized by comprising the following steps:
(1) sample preparation: spreading (one layer) 400g of fresh Lentinus Edodes (with moisture content of wet base of about 88%) with uniform size (canopy radius of about 2.5cm) in a 65 deg.C electric heating constant temperature air blast drying oven (volume of 105L), and drying for 8h to obtain drying end point (moisture content of wet base of about 13%);
(2) collecting detection information: an array of 6 metal oxide type gas sensors was used, MQ-136, S1, sensitive to hydrogen sulfide with a sensitivity of 1-200 ppm; TGS2602, S2, is sensitive to organic volatile substances with a sensitivity of 1-30 ppm; MQ-138, namely S3, is sensitive to volatile substances such as alcohol, aldehyde, ketone and the like, and the sensitivity is 5-500 ppm; TGS2620, namely S4, is sensitive to organic solvents such as ethanol and the like, and the sensitivity is 50-5000 ppm; MQ-2, namely S5, is sensitive to substances such as liquefied gas, propane, hydrogen and the like, and the sensitivity is 300-10000 ppm; TGS2610, namely S6, is sensitive to alkanes, and the sensitivity is 500-10000 ppm; the gas sensor is an independently researched and developed electronic nose system, the system is subjected to gas washing before sample detection, the time is 5min, the sample detection time is 60S, the sample interval gas washing time is 100S, and the response value S of the gas sensor is obtained according to the resistance G of the sensor after the sensor is contacted with sample volatile matters and the resistance G of the sensor after the sensor is contacted with clean air0Ratio of (G/G)0) Extracting the average value of response values of 58 th to 60 th s of each sensor as a characteristic value;
(3) constructing a pattern recognition and discrimination model: modeling the extracted characteristic values by using a Support vector machine (SVM-C), and then constructing four Support vector machine modules for drying stage judgment by using an LIBSVM software package: SVM1, SVM2, SVM3, SVM 4; the response values S1-S6 of 6 metal oxide gas sensors are sequentially substituted into the support vector machine modules for judging the four drying stages: SVM1, SVM2, SVM3, SVM4, the modules performing the discrimination of the four drying phases in a sequential relationship: fresh mushrooms are dried in the early stage, the middle stage and the later stage.
2. The method as claimed in claim 1, wherein the gas sensor is used to obtain the odor information of dried shiitake mushrooms at different time to determine the drying stage of shiitake mushrooms.
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