Non-destructive testing method for hollowness of tumorous stem mustard

Abstract

The invention discloses a nodule stem mustard hollow nondestructive detection method, which is characterized by comprising the following steps: a, obtaining a detection solution with the density greater than the meat density of nodule stem mustard, placing the detection solution in a vertical cylindrical detection container, and recording the original liquid level height h1 of the detection solution; b, placing and naturally floating the to-be-detected tumorous stem mustard in the detection solution, and obtaining the floating liquid level height h2 of the detection solution at the moment after the tumorous stem mustard is stable; c, integrally pressing the tumorous stem mustard into the detection solution to obtain the submerging liquid level height h3 of the detection solution at the moment; d, calculating the overall density of the stem tumor mustard according to the detection data, wherein the calculation formula is rho stem = rho liquid * (h2-h1) / (h3-h1); and e, judging whether the tumorous stem mustard is hollow or not according to the obtained overall density rho stem of the tumorous stem mustard. The method can realize single-plant or batch nondestructive detection of the hollowness degree of the stem nodule mustard, and has the advantages of convenience in detection, low cost, reliable detection precision and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural product quality detection, and particularly to a non-destructive detection method for hollowness of stem mustard. Background Art

[0002] Stem mustard is a plant of the genus Brassica in the family Brassicaceae, commonly known as green vegetable head or knobby vegetable. It is the main raw material for making pickled mustard tuber and can also be eaten fresh.

[0003] In recent years, the pickled mustard tuber industry has maintained stable growth and the market scale has been continuously expanding. The production of pickled mustard tuber has gradually changed from handicraft to large-scale mechanized production, and the demand for stem mustard has been continuously increasing. Due to factors such as climate, fertilizer, and pests, hollowness often occurs in stem mustard during the growth process. Different types of hollowness have different effects on the quality of stem mustard. Some stem mustard with hollowness not only affects the sensory quality of stem mustard but also poses a safety hazard to stem mustard. More serious hollowness will deteriorate with the extension of the storage period. If it is not detected in time during the food processing process, the rotten and hollow stem mustard will contaminate other raw materials during the production process, causing irreparable losses to the processing technology, reducing the edibility of the food, and causing cost losses to the stem mustard processing factory. Therefore, there is a need to detect whether stem mustard is hollow both in the process of breeding and optimizing the cultivation of stem mustard and during the random inspection of raw materials in actual production.

[0004] At present, the research on the quality of stem mustard mainly focuses on detecting the physical and chemical indexes, sensory indexes, etc. of stem mustard, and there is little research on the detection of hollowness of stem mustard. A texture analyzer is an instrument widely used in the quality detection of food. However, when using a texture analyzer for measurement, it has high requirements for the shape and specifications of the sample. Since the shapes of stem mustard are different and the sizes vary greatly, using a texture analyzer cannot meet the need for measuring its hollowness. The domestic measurement of hollowness of stem mustard still stays at manually measuring with traditional measuring tools such as rulers. This measurement method has certain limitations, is not scientific and systematic, and requires cutting open the stem mustard, so it cannot be measured non-destructively.

[0005] Current scientific researchers' detection and research on the hollowness of fruits and vegetables mainly focus on watermelons, potatoes, etc. Wei Yanjun et al. developed an acoustic system for detecting the hollowness inside watermelons to address the problem of internal hollowness in watermelons. By calculating the sound transmission rate parameter between the signal receiving point and the knocking point, and with the help of the discriminant analysis function in the software, it is analyzed and determined whether there is hollowness inside the watermelon. Cheng Y. et al. used ultrasonic waves to detect the hollowness of potatoes. Two probes were placed on both sides of the potato respectively. Hollow potatoes would cause the ultrasonic waves to reflect multiple times. Finally, the ultrasonic waves of the potato were received by the receiving probe on the other side, amplified by a broadband filter, and then displayed on an oscilloscope. The results showed that hollow potatoes and solid potatoes could be distinguished according to the intensity and fluctuation time of the received signal. Chen Zhaoqing established an internal black heart disease defect detection model for potatoes using visible / near-infrared spectroscopy combined with neural networks to detect internal defects of potatoes, with an accuracy rate of up to 98.2%. Yang Guanghui et al. explored the application of detection technologies such as hyperspectral, near-infrared spectroscopy, machine vision, and ultrasonic waves at home and abroad in the detection of the internal and external quality of potatoes.

[0006] The above-mentioned existing research methods for the hollowness of fruits and vegetables generally use ultrasonic waves or infrared spectroscopy for detection. The corresponding equipment is all costly, and the existing methods are more suitable for the detection of fruits and vegetables with relatively smooth and regular surface shapes, and are not suitable for the detection of stem tumor mustard with irregular surface shapes.

[0007] Therefore, how to design a detection method that is convenient, low-cost, and more suitable for the hollowness detection of irregularly shaped fruits and vegetables such as stem tumor mustard has become a problem that needs to be considered and solved by those skilled in the art. Summary of the Invention

[0008] Aiming at the deficiencies of the above-mentioned existing technologies, the technical problem to be solved by the present invention is: how to provide a non-destructive detection method for the hollowness of stem tumor mustard that is convenient to detect, low-cost, and has reliable detection accuracy.

[0009] To solve the above technical problems, the present invention adopts the following technical solutions: A non-destructive detection method for the hollowness of stem tumor mustard, characterized by comprising the following steps: a Obtain a detection solution with a density greater than the density of the flesh of stem tumor mustard and place it in a vertical cylindrical detection container, and record its original liquid level height h1; b Place the stem tumor mustard to be detected into the detection solution and let it float naturally. After stabilization, obtain the floating liquid level height h2 of the detection solution at this time; c Then press the whole stem tumor mustard into the detection solution to obtain the submerged liquid level height h3 of the detection solution at this time; d Calculate the overall density of the stem tumor mustard according to the detection data, and the calculation formula is ρ 茎 =ρ 液 × (h2 - h1) / (h3 - h1); In the formula, ρ 茎 is the overall density of the stem mustard tuber, ρ 液 is the density of the detection solution, h1 is the original liquid level height, h2 is the floating liquid level height after the stem mustard tuber is placed and floats stably in the detection solution, and h3 is the submerged liquid level height when the whole stem mustard tuber is just pressed into the detection solution; e Based on the obtained overall density ρ of the stem mustard tuber 茎 judge whether the stem mustard tuber is hollow.

[0010] In this method, the hollow judgment is based on the overall density of the stem mustard tuber. When the stem mustard tuber has a hollow, its overall density will decrease, and the larger the hollow, the lower the overall density. Since this method uses a vertical cylindrical detection container, in step b, after the stem mustard tuber is placed in the detection solution and stabilizes, it is in a floating state, and its gravity is equal to the buoyancy which is equal to the gravity of the discharged water. Therefore, it can be obtained that the mass of the stem mustard tuber is equal to the mass of the detection solution with the rising liquid level height, that is, m 茎 = ρ 液 × (h2 - h1) × S, where S is the cross-sectional area of the detection container. Then in step c, after the whole stem mustard tuber is pressed into the detection solution, at this time, the volume of the stem mustard tuber is equal to the volume of the discharged water, that is, V 茎 = (h3 - h1) × S, where S is the cross-sectional area of the detection container. Therefore, substituting into the density formula, the overall density formula of the stem mustard tuber can be obtained as ρ 茎 = ρ 液 × (h2 - h1) / (h3 - h1). In this way, this method only needs two height detections to calculate the overall density of the stem mustard tuber and judge whether it is hollow, and has the advantages of convenient detection, low cost, reliable detection accuracy, etc.

[0011] Furthermore, in the e step, the judgment process is to compare the obtained ρ 茎 with a preset threshold density. If it is greater than or equal to the preset threshold density, it is judged as solid, and if it is less than the preset threshold density, it is judged as hollow. The preset threshold density is obtained by taking the average value of the skin-inclusive pulp densities of multiple stem mustard tuber samples, and the multiple stem mustard tuber samples include half of the stem mustard tubers with hollows and half of the solid stem mustard tubers.

[0012] This is because the specific value of the pulp density (including skin) of the stem mustard tuber will vary with individual differences, and this difference is related to factors such as different growth cycles, different growth conditions, and the aging of fruit slices. But overall, the pulp density of the stem mustard tuber shows a gradually decreasing tendency before and after hollowing. Therefore, taking the pulp density obtained from sampling multiple stem mustard tubers with half hollow and half solid as the judgment threshold can better improve the accuracy of the judgment.

[0013] Further, in step e, when counting the density of the flesh with skin of the stem mustard sample, it is obtained by cutting open the stem mustard sample and performing the steps from step a to step d. This facilitates obtaining the density of the flesh with skin of the stem mustard sample. At the same time, both the comparison value and the value to be compared are obtained by the same detection means, which can better reduce the influence of the systematic error brought by the detection means itself on the judgment.

[0014] Further, this method is realized by relying on a non-destructive detection device for hollow stem mustard. The non-destructive detection device for hollow stem mustard includes a vertically cylindrical detection container. The detection container is filled with a detection solution whose density is greater than the density of the flesh of the stem mustard. The upper end of the detection container is provided with a feeding port for adding the stem mustard to be detected. In the middle position at the upper end of the detection container, there is also a telescopic device. The telescopic rod of the telescopic device is vertically downward and is fixed with a horizontally arranged pressing plate at the lower end. A detection solution sensor is arranged on the lower surface of the pressing plate. The detection solution sensor is connected to the control center, and the control center is connected to the telescopic device. The lower end of the detection container is also provided with a liquid outlet for discharging the detection solution and the stem mustard to be detected. A switch gate valve is arranged on the liquid outlet. A liquid level detection device is also arranged on the detection container, and the liquid level detection device is connected to the control center.

[0015] In this way, during detection, first rely on the liquid level detection device to obtain the original liquid level height h1 in the detection container. Then add the stem mustard to be detected into the detection container from the feeding port. After it reaches a stable floating state, rely on the liquid level detection device to obtain the floating liquid level height h2 in the detection container. Then control the telescopic rod of the telescopic device to press down, and press the stem mustard completely into the detection solution. Stop when the detection solution sensor touches the detection solution signal. At this time, the lower surface of the pressing plate just touches the liquid surface. At this time, rely on the liquid level detection device to obtain the submerged liquid level height h3 in the detection container. Then the control center calculates the overall density ρ of the stem mustard through the formula ρ 液 =ρ 茎 ×(h2 - h1) / (h3 - h1). 液 Then the overall density ρ of the stem mustard can be calculated. 茎 Furthermore, it can be judged whether the stem mustard is hollow through this density value. Therefore, this device can realize the rapid detection of whether the stem mustard is hollow and has the characteristics of convenient and reliable detection. During specific implementation, the size of this device can be flexibly adjusted according to needs. When used for detecting the breeding quality of stem mustard, the size can be set smaller to realize the detection of a single stem mustard plant at a time and judge whether a single stem mustard plant is hollow. When used for sampling detection of stem mustard raw materials for making pickled mustard tuber, the size can be set larger, which can realize the one-time batch detection of a batch of samples (from several kilograms to more than a dozen kilograms) and judge whether the raw materials of this batch meet the corresponding hollowness requirements as a whole.

[0016] Furthermore, the edge of the pressing plate is located at the position adjacent to the inner wall of the detection container, which can better press down the stem mustard and prevent it from showing through the gap between the edge of the pressing plate and the detection container.

[0017] Furthermore, the detection solution sensor is arranged at the edge position of the lower surface of the pressing plate, which can prevent the detection container sensor from contacting the stem mustard when the pressing plate is pressed down, thus affecting the detection effect.

[0018] Furthermore, the feeding port is obliquely bypass-connected to the upper side wall of the detection container, which makes the feeding of the stem mustard not interfere with the pressing plate and is more convenient.

[0019] Furthermore, the telescopic device is realized by a telescopic electric cylinder. The telescopic electric cylinder works on the principle of a lead screw and nut, and has the advantages of stable and reliable telescopic control.

[0020] Furthermore, the liquid outlet is bypass-connected to one side of the lower end of the detection container, and a liquid receiving container is also arranged below and outside the liquid outlet, which makes it more convenient to discharge the stem mustard and the detection solution after detection.

[0021] Furthermore, a liquid leakage basket is arranged above the liquid receiving container at the liquid outlet. In this way, the stem mustard can be caught by the liquid leakage basket and the solution can leak down, which is convenient for taking away the stem mustard.

[0022] Furthermore, a liquid return pump is arranged in the liquid receiving container, and the liquid return pump is connected to the upper part of the detection container through a liquid return pipeline, which is convenient for realizing the recycling of the detection solution.

[0023] Furthermore, the liquid level detection device is a capacitive liquid level sensor installed on the side wall of the detection container, and the detection container is made of non-metallic material. The capacitive liquid level sensor is a mature non-contact liquid level sensor. Its measurement accuracy of the liquid surface position is reliable and it does not contact the solution, which can better avoid interfering with the detection process. The detection container made of non-metallic material can better ensure the detection effect of the sensor.

[0024] Furthermore, the detection solution is brine, preferably brine with a salt content of 1.1978 g / mL.

[0025] This is because if the specific gravity of the detection solution is too light, the difference between h3 and h2 will be small, and if it is too heavy, the difference between h2 and h1 will be small, both of which will lead to a decrease in detection accuracy. Through the correlation coefficient test calculation, when the detection solution is brine, preferably brine with a salt content of 1.1978 g / mL, the correlation coefficient between the test data and the hollow volume is the highest, which is most conducive to improving the detection accuracy.

[0026] Further, a hollow volume detection module for Brassica juncea var. tumida is also provided in the control center. A multiple regression model for hollow volume detection is preset in the hollow volume detection module for Brassica juncea var. tumida. The multiple regression model for hollow volume detection uses the overall density ρ of the detected Brassica juncea var. tumida 茎 and the liquid level height difference (h3 - h2) as two regression variables, and its regression model equation is y = 200.0 - 0.3314x1 - 211.5x2, with the correlation coefficient R 2 being 0.9750, y being the hollow volume, x1 being the liquid level height difference (x1 = h3 - h2), and x2 being the density of Brassica juncea var. tumida (x2 = ρ 茎 ).

[0027] The multiple regression model for hollow volume detection is because the size of the hollow volume of Brassica juncea var. tumida is related to two detectable parameter factors, namely the overall density ρ of Brassica juncea var. tumida 茎 and the liquid level height difference (h3 - h2). Therefore, these two parameters are selected as regression variables to establish a regression model. The establishment process includes the following steps.

[0028] 1) Multiple (the applicant used 430 effective sample points) hollow Brassica juncea var. tumida were selected as effective samples, and the density ρ of the sample Brassica juncea var. tumida 茎 and the liquid level height difference (h3 - h2) before and after the Brassica juncea var. tumida was pressed into the detection liquid were successively detected using a non-destructive detection device for the hollow of Brassica juncea var. tumida 2) Then, the Brassica juncea var. tumida was cut in half to expose its hollow position and placed into the detection solution. After stabilization, the liquid level height h4 at this time was recorded. Then, the pressing plate was controlled to extend downward to press the two halves of the cut Brassica juncea var. tumida completely into the detection solution. When the detection solution sensor detected the detection solution signal, it stopped, and the liquid level height h5 at this time was obtained. According to the formula {(h3 - h2) - (h5 - h4)} × S, where S is the cross-sectional area of the detection container, the hollow volume of the Brassica juncea var. tumida can be calculated 3) After obtaining multiple effective samples according to steps 1 - 2, a relationship model between the hollow volume and the density of Brassica juncea var. tumida was established, y = 2.8E + 5x 密 2 -5.7E + 5x 密 +2.8E + 5, with the correlation coefficient R 2 being 0.9294, y being the hollow volume, and x 密 being the density of Brassica juncea var. tumida Then, a relationship model between the hollow volume and the liquid level height difference was established, y = 0.0099x 2 +0.1186x - 0.9209, with the correlation coefficient R 2 being 0.9229, y being the hollow volume, and x being the liquid level height difference (h3 - h2) On this basis, multiple regression analysis is carried out to establish a multiple regression model for detecting the hollow volume.

[0029] In this way, after presetting the multiple regression model for detecting the hollow volume in the hollow volume detection module of the stem mustard in the control center, the specific hollow volume size can be directly obtained by substituting the detected liquid level height and stem mustard density data into the model, and the specific detection and judgment of the hollow degree of the stem mustard can be quickly realized.

[0030] Therefore, the present invention is researched and invented in view of the problems of consuming manpower and material resources, cumbersome operation, low detection efficiency, etc. in the detection of the hollowness of stem mustard. It can solve the economic losses and food safety problems caused by the inability of merchants to well judge the hollowness of stem mustard during the large-scale mechanized production of pickled mustard tuber, and can also control the quality of fresh edible stem mustard, thereby reducing the cost losses caused by pickled mustard tuber processing plants, improving the utilization rate and edible value of stem mustard, and thus accelerating the development of the stem mustard and its processed product industries. It can also provide help for testing the hollowness during the breeding and selection process of stem mustard.

[0031] Specifically, the present invention has the following advantages and positive effects. The present invention completely avoids the physical damage to the sample caused by traditional puncture detection, maintains the integrity of the stem mustard, and can still be used for processing or sales after detection, which is especially suitable for scenarios that require retaining samples such as breeding research and quality grading. The single detection cycle of this device is short, it supports continuous automatic detection, the embedded system automatically completes data acquisition, calculation and result output, and the modular structure is convenient for maintenance and function expansion. This device combines the buoyancy principle with modern sensing technology and intelligent control, has significant technological innovation and practical value in the field of agricultural quality inspection, and is especially suitable for use by stem mustard processing enterprises, agricultural scientific research institutions and quality supervision departments. Its comprehensive performance is significantly better than existing detection methods such as the specific gravity method and image analysis method.

[0032] To sum up, the present invention can realize single-plant or batch non-destructive detection of the hollow degree of stem mustard, and has the advantages of convenient detection, low cost, reliable detection accuracy, etc. Description of the Drawings

[0033] Figure 1 It is a schematic structural diagram of the non-destructive detection device for the hollowness of stem mustard used in the embodiment of the present invention.

[0034] Figure 2 In Embodiment 1 of the present invention, two major parameter factors are obtained by testing under the conditions of detection solutions of different materials, that is, the liquid level height difference (h3 - h2) before and after the stem mustard is pressed into the detection liquid, and the density ρ of the stem mustard 茎 The correlation coefficient relationship table between each and the hollow volume.

[0035] Figure 3This is the test data table of some samples actually detected by the applicant in Embodiment 2 of the present invention.

[0036] Figure 4 In Embodiment 2 of the present invention, the non-linear relationship model diagram between the hollow volume and the density of stem mustard is established.

[0037] Figure 5 In Embodiment 2 of the present invention, the non-linear relationship model diagram between the hollow volume and the liquid level height difference is established.

[0038] Figure 6 In Embodiment 2 of the present invention, the multiple regression model diagram between the hollow volume, the liquid level height difference and the density of stem mustard is established. Detailed implementation manners

[0039] The present invention will be further described in detail below in conjunction with the specific implementation manners.

[0040] Embodiment 1: A non-destructive detection method for the hollowness of stem mustard, characterized in that it includes the following steps: a. Place a detection solution with a density greater than the density of the flesh of stem mustard in a vertical cylindrical detection container, and record its original liquid level height h1; b. Place the stem mustard to be detected into the detection solution and let it float naturally. After stabilization, obtain the floating liquid level height h2 of the detection solution at this time; c. Then press the whole stem mustard into the detection solution to obtain the submerged liquid level height h3 of the detection solution at this time; d. Calculate the overall density of the stem mustard according to the detection data. The calculation formula is ρ 茎 =ρ 液 ×(h2 - h1) / (h3 - h1); In the formula, ρ 茎 is the overall density of the stem mustard, ρ 液 is the density of the detection solution, h1 is the original liquid level height, h2 is the floating liquid level height after the stem mustard is placed in the detection solution and stabilized, and h3 is the submerged liquid level height when the whole stem mustard is just pressed into the detection solution; e. Judge whether the stem mustard is hollow according to the obtained overall density ρ 茎 of the stem mustard.

[0041] In this method, the hollowness judgment is based on the overall density of the stem mustard. When the stem mustard has hollowness, its overall density will decrease, and the greater the hollowness, the lower the overall density. Since this method uses a vertical cylindrical detection container, in step b, after the stem mustard is placed in the detection solution and stabilized, it is in a floating state, and its gravity is equal to the buoyancy and equal to the gravity of the discharged water. Therefore, it can be obtained that the mass of the stem mustard is equal to the mass of the detection solution with the rising liquid level height, that is, m 茎 =ρ 液× (h2 - h1) × S, where S is the cross-sectional area of the detection container. Then in step c, after the whole stem mustard tuber is pressed into the detection solution, the volume of the stem mustard tuber at this time is equal to the volume of the discharged water, that is, V 茎 = (h3 - h1) × S, where S is the cross-sectional area of the detection container. Therefore, substituting into the density formula, the overall density formula of the stem mustard tuber can be obtained as ρ 茎 = ρ 液 × (h2 - h1) / (h3 - h1). In this way, this method only needs two height detections to calculate the overall density of the stem mustard tuber and determine whether it is hollow, with the advantages of convenient detection, low cost, and reliable detection accuracy, etc.

[0042] In this embodiment, in the e step, the judgment process is to compare the obtained ρ 茎 with the preset threshold density. If it is greater than or equal to the preset threshold density, it is judged as solid; if it is less than the preset threshold density, it is judged as hollow. The preset threshold density is obtained by taking the average of the skin-included pulp densities of multiple stem mustard tuber samples, and the multiple stem mustard tuber samples include half of the stem mustard tubers with hollowness and half of the solid stem mustard tubers.

[0043] This is because the specific value of the pulp density (including skin) of the stem mustard tuber will vary with individual differences, and this difference is related to factors such as different growth cycles, different growth conditions, and the aging of the fruit slices. But overall, the pulp density of the stem mustard tuber shows a tendency of gradually decreasing before and after hollowness. Therefore, taking the pulp density obtained by sampling multiple stem mustard tubers with half hollowness and half solid as the judgment threshold can better improve the accuracy of judgment.

[0044] In this embodiment, in the e step, when counting the skin-included pulp density of the stem mustard tuber sample, it is obtained by performing the steps from step a to step d after cutting the stem mustard tuber sample open. This is convenient for obtaining the skin-included pulp density of the stem mustard tuber sample, and at the same time, both the comparison value and the value to be compared are obtained by the same detection means, which can better reduce the influence of the systematic error brought by the detection means itself on the judgment.

[0045] In this embodiment, this method is realized by relying on a non-destructive detection device for stem mustard tuber hollowness. See Figure 1, the hollow non-destructive detection device for stem mustard includes a vertically cylindrical detection container 1 filled with a detection solution whose density is greater than that of the stem mustard flesh. At the upper end of the detection container 1, there is a feeding port 2 for adding the stem mustard to be detected. In the middle position at the upper end of the detection container 1, there is also a telescopic device 3. The telescopic rod of the telescopic device 3 is vertically downward and fixedly connected with a horizontally arranged pressing plate 4 at the lower end. On the lower surface of the pressing plate 4, there is a detection solution sensor 5. The detection solution sensor 5 is connected to a control center 6, and the control center 6 is connected to the telescopic device 3. At the lower end of the detection container 1, there is also a liquid outlet 7 for discharging the detection solution and the stem mustard to be detected. A switch gate valve 8 is arranged on the liquid outlet 7. A liquid level detection device 9 is also arranged on the detection container, and the liquid level detection device 9 is connected to the control center 6.

[0046] In this way, during detection, first rely on the liquid level detection device to obtain the original liquid level height h1 in the detection container. Then add the stem mustard to be detected into the detection container from the feeding port. After it reaches a stable floating state, rely on the liquid level detection device to obtain the floating liquid level height h2 in the detection container. Then control the telescopic rod of the telescopic device to press down, completely press the stem mustard into the detection solution downward, and stop after the detection solution sensor contacts the detection solution signal. At this time, the lower surface of the pressing plate just contacts the liquid surface. At this time, rely on the liquid level detection device to obtain the submerged liquid level height h3 in the detection container. Then the control center calculates the overall density ρ of the stem mustard according to the density ρ of the detection solution input in advance 液 , and then through the formula ρ 茎 = ρ 液 × (h2 - h1) / (h3 - h1) to calculate the overall density ρ of the stem mustard 茎 . Furthermore, it can be judged whether the stem mustard is hollow through this density value. Therefore, this device can realize the rapid detection of whether the stem mustard is hollow and has the characteristics of convenient and reliable detection. During specific implementation, the size of this device can be flexibly adjusted according to needs. When used for detecting the breeding quality of stem mustard, the size can be set smaller to realize the detection of a single stem mustard per time and judge whether a single stem mustard is hollow. When used for sampling detection of stem mustard raw materials for pickled mustard production, the size can be set larger to realize the one-time batch detection of a batch of samples (from several kilograms to more than a dozen kilograms) and judge whether the raw materials of this batch meet the corresponding hollowness requirements as a whole.

[0047] Among them, the edge of the pressing plate 4 is located at the adjacent position of the inner wall of the detection container. It can better press down the stem mustard and prevent it from exposing from the gap between the edge of the pressing plate and the detection container.

[0048] Among them, the detection solution sensor 5 is arranged at the edge position of the lower surface of the pressing plate 4. In this way, it can be avoided that the detection container sensor contacts the stem mustard when the pressing plate is pressed down, which affects the detection effect. During implementation, the detection solution sensor is preferably a conductive contact, which is more suitable for contact detection of brine solution.

[0049] Among them, the dosing port 2 is obliquely bypass-connected and arranged on the upper side wall of the detection container 1. This makes the dosing of the stem mustard not interfere with the pressing plate, which is more convenient.

[0050] Among them, the telescopic device 3 is realized by using a telescopic electric cylinder. The telescopic electric cylinder adopts the transmission principle of a lead screw and nut, and has the advantages of stable and reliable telescopic control.

[0051] Among them, the liquid outlet 7 is bypass-connected to one side of the lower end of the detection container 1, and a liquid receiving container 10 is also arranged below and outside the liquid outlet 7. This is more convenient for the discharge of the stem mustard and the detection solution after detection.

[0052] Among them, a liquid leakage basket 11 is also arranged at the liquid outlet above the liquid receiving container 10. In this way, the stem mustard can be caught by the liquid leakage basket and the solution can leak down, which is convenient for taking away the stem mustard.

[0053] Among them, a liquid return pump 12 is arranged in the liquid receiving container, and the liquid return pump 12 is connected to the upper part of the detection container 1 through a liquid return pipe 13. This is convenient for realizing the recycling of the detection solution.

[0054] Among them, the liquid level detection device is a capacitive liquid level sensor installed on the side wall of the detection container, and the detection container is made of a non-metallic material. The capacitive liquid level sensor is a mature non-contact liquid level sensor. Its measurement accuracy of the liquid level position is reliable and it does not contact the solution, which can better avoid interfering with the detection process. The detection container made of a non-metallic material can better ensure the detection effect of the sensor.

[0055] Among them, the detection solution uses brine. When implemented, brine with a salt content of 1.1978 g / mL is preferably used.

[0056] This is because if the specific gravity of the detection solution is too light, the difference between h3 and h2 will be small, and if it is too heavy, the difference between h2 and h1 will be small, both of which will lead to a decrease in detection accuracy. Through the correlation coefficient test calculation, the calculation results are shown in Figure 2 From Figure 2 the table shown, it can be seen that the test solutions with different densities have an impact on the correlation coefficient of the model and have an impact on the test accuracy and accuracy. After multiple tests and data analysis, using brine with a density of 1.1978 g / mL as the test solution, the correlation coefficient between the hollow volume of the stem mustard and the density of the stem mustard and the height difference between the immersed liquid level and the floating liquid level (h3 - h2) is the highest. Selecting this solution as the detection solution is most conducive to improving the detection accuracy.

[0057] Embodiment 2. The difference between this Embodiment 2 and Embodiment 1 lies in the implementation manner of step e (the rest is the same as Embodiment 1). In this Embodiment 2, the implementation manner of step e is realized by relying on the hollow volume detection module set in the control center and can obtain the specific hollow volume of the stem mustard tuber.

[0058] Specifically, in this embodiment, a hollow volume detection module for stem mustard tuber is further set in the control center. A multiple regression model for hollow volume detection is preset in the hollow volume detection module for stem mustard tuber. The multiple regression model for hollow volume detection uses the overall density ρ of the stem mustard tuber obtained by detection 茎 and the liquid level height difference (h3 - h2) as two regression variables, and its regression model equation is y = 200.0 - 0.3314x1 - 211.5x2, and the correlation coefficient R 2 is 0.9750, y is the hollow volume, x1 is the liquid level height difference (x1 = h3 - h2), and x2 is the density of the stem mustard tuber (x2 = ρ 茎 ).

[0059] The multiple regression model for hollow volume detection is because the size of the hollow volume of the stem mustard tuber is related to two detectable parameter factors, the overall density ρ of the stem mustard tuber 茎 and the liquid level height difference (h3 - h2). Therefore, these two parameters are selected as regression variables to establish a regression model. The establishment process includes the following steps.

[0060] 1) Select multiple (the applicant used 430 effective sample points) hollow stem mustard tubers as effective samples, and use the non-destructive detection device for the hollow of the stem mustard tuber to sequentially detect the density ρ of the sample stem mustard tuber 茎 and the liquid level height difference (h3 - h2) before and after the stem mustard tuber is pressed into the detection liquid; Figure 3 It is a partial sample test data table actually detected by the applicant.

[0061] 2) Then cut the stem mustard tuber in half to expose its hollow position and place it in the detection solution. After stabilization, record the liquid level height h4 at this time. Then control the pressing plate to extend downward to press the two halves of the cut stem mustard tuber completely into the detection solution. Stop when the detection solution sensor touches the detection solution signal, and obtain the liquid level height h5 at this time. According to the formula {(h3 - h2) - (h5 - h4)} × S, where S is the cross-sectional area of the detection container, the hollow volume of the stem mustard tuber can be calculated; 3) After obtaining multiple effective samples according to steps 1 - 2, establish a relationship model between the hollow volume and the density of the stem mustard tuber, y = 2.8E + 5x 密 2 -5.7E + 5x 密 +2.8E + 5, and the correlation coefficient R 2is 0.9294, y is the hollow volume, x 密 is the density of stem mustard tuber, and the regression model diagram is as Figure 4 shown; Then, establish a relationship model between the hollow volume and the liquid level height difference, y = 0.0099x 2 + 0.1186x - 0.9209, and the correlation coefficient R 2 is 0.9229, y is the hollow volume, and x is the liquid level height difference (h3 - h2). The regression model diagram is as Figure 5 shown; On this basis, perform multiple regression analysis to establish a multiple regression model for detecting the hollow volume as shown in Figure 6 shown.

[0062] In this way, after presetting the multiple regression model for detecting the hollow volume of stem mustard tuber in the hollow volume detection module in the control center, the specific hollow volume size can be directly obtained by substituting the detected liquid level height and stem mustard tuber density data into the model, and the specific detection and judgment of the hollowness of stem mustard tuber can be quickly realized.

[0063] Therefore, the present invention is researched and invented in view of the problems such as labor and material consumption, cumbersome operation, and low detection efficiency in the hollow detection of stem mustard tuber. It can solve the economic losses and food safety problems caused by the inability of merchants to well judge the hollowness of stem mustard tuber during the large-scale mechanized production of pickled mustard tuber, and can also control the quality of fresh edible stem mustard tuber, thereby reducing the cost losses caused by pickled mustard tuber processing plants, improving the utilization rate and edible value of stem mustard tuber, and thus accelerating the development of the industries of stem mustard tuber and its processed products. It can also provide help for testing hollowness during the breeding and selection process of stem mustard tuber.

[0064] Specifically, the present invention has the following advantages and positive effects. The present invention completely avoids the physical damage to the sample caused by traditional puncture detection, maintains the integrity of the stem mustard tuber, and can still be used for processing or sales after detection, which is particularly suitable for scenarios such as breeding research and quality grading that require retaining samples. The single detection cycle of this device is short, it supports continuous automated detection, the embedded system automatically completes data acquisition, calculation, and result output, and the modular structure is convenient for maintenance and function expansion. This device combines the buoyancy principle with modern sensing technology and intelligent control, has significant technological innovation and practical value in the field of agricultural quality inspection, and is particularly suitable for use by stem mustard tuber processing enterprises, agricultural scientific research institutions, and quality supervision departments. Its comprehensive performance is significantly better than existing detection methods such as the specific gravity method and image analysis method.

Claims

1. A method for non-destructive detection of hollowness in stem mustard, characterized in that, Including the following steps: a. Place a detection solution with a density greater than the density of the fleshy part of the stem mustard tuber into a vertical cylindrical detection container, and record its original liquid level height h1; b. Place the stem mustard tuber to be detected into the detection solution and let it float naturally. After stabilization, obtain the floating liquid level height h2 of the detection solution at this time; c. Then press the whole stem mustard tuber into the detection solution to obtain the submerged liquid level height h3 of the detection solution at this time; d Calculate the overall density of stem mustard according to the detection data, and the calculation formula is ρ 茎 =ρ 液 × (h2 - h1) / (h3 - h1); In the formula, ρ 茎 is the overall density of the stem mustard tuber, ρ 液 is the density of the detection solution, h1 is the original liquid level height, h2 is the floating liquid level height after the stem mustard tuber is placed and floats stably in the detection solution, and h3 is the submerged liquid level height when the whole stem mustard tuber is just pressed into the detection solution; eAccording to the obtained overall density ρ of the stem mustard 茎 Judge whether the stem mustard is hollow.

2. The hollow non-destructive detection method for stem mustard as described in claim 1, characterized in that, In step e, the judgment process is to compare the obtained ρ 茎 with a preset threshold density. If it is greater than or equal to the preset threshold density, it is judged as solid; if it is less than the preset threshold density, it is judged as hollow. The preset threshold density is obtained by taking the average of the densities of the skin-containing pulp of multiple stem mustard samples, and the multiple stem mustard samples include half of the stem mustard with hollow and half of the solid stem mustard.

3. The hollow non-destructive detection method for stem mustard as described in claim 2, wherein In the e step, when counting the density of the fleshy part with skin of the stem mustard tuber sample, it is obtained by performing the steps from a to d after cutting the stem mustard tuber sample open.

4. The hollow non-destructive detection method for stem mustard according to claim 1, characterized in that, This method is realized by relying on a non-destructive hollow detection device for stem mustard tuber. The non-destructive hollow detection device for stem mustard tuber includes a vertical cylindrical detection container. The detection container is filled with a detection solution with a density greater than the density of the fleshy part of the stem mustard tuber. An adding port for adding the stem mustard tuber to be detected is arranged at the upper end of the detection container. A telescopic device is also arranged at the middle position of the upper end of the detection container. The telescopic rod of the telescopic device is vertically downward and a horizontally arranged pressing plate is fixed at the lower end. A detection solution sensor is arranged on the lower surface of the pressing plate. The detection solution sensor is connected to the control center, and the control center is connected to the telescopic device. A liquid outlet for discharging the detection solution and the stem mustard tuber to be detected is also arranged at the lower end of the detection container. A switch gate valve is arranged on the liquid outlet. A liquid level detection device is also arranged on the detection container. The liquid level detection device is connected to the control center.

5. The hollow non-destructive detection method for stem mustard according to claim 4, wherein, The edge of the pressing plate is located at the adjacent position of the inner wall of the detection container.

6. The method for non-destructive detection of hollow stems of stem mustard as described in claim 4, wherein, The detection solution sensor is arranged at the edge position of the lower surface of the pressing plate.

7. The hollow non-destructive detection method for stem mustard as claimed in claim 4, wherein, The adding port is obliquely and bypass-connected to the side wall at the upper end of the detection container.

8. The hollow non-destructive detection method for stem mustard according to claim 4, characterized in that, The telescopic device adopts a telescopic electric cylinder.

9. The hollow non-destructive detection method of stem mustard as described in claim 4, characterized in that, The liquid outlet is bypass-connected to one side at the lower end of the detection container, and a liquid receiving container is also arranged below and outside the liquid outlet; A liquid leakage basket located above the liquid receiving container is also arranged on the liquid outlet; A liquid return pump is arranged in the liquid receiving container, and the liquid return pump is connected to the upper part of the detection container through a liquid return pipeline; The liquid level detection device is a capacitive liquid level sensor installed on the side wall of the detection container, and the detection container is made of a non-metallic material; The detection solution adopts brine.

10. The hollow non-destructive detection method for stem mustard as described in claim 4, characterized in that, A hollow volume detection module for stem mustard is also provided in the control center. A multiple regression model for hollow volume detection is preset in the hollow volume detection module for stem mustard. The multiple regression model for hollow volume detection uses the overall density ρ of the detected stem mustard 茎 and the liquid level height difference (h3 - h2) as two regression variables. The regression model equation is y = 200.0 - 0.3314x1 - 211.5x2, and the correlation coefficient R 2 is 0.9750. y is the hollow volume, x1 is the liquid level height difference (x1 = h3 - h2), and x2 is the density of stem mustard (x2 = ρ 茎 ).

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