Method, device and storage medium for detecting antioxidant activity of oat seeds

Abstract

The present invention discloses a method, device and storage medium for detecting the antioxidant activity of oat seeds, and relates to the technical field of antioxidant activity detection. The method for detecting the antioxidant activity of oat seeds comprises the following steps: average humidity fluctuation detection; humidity control analysis; seed grinding and antioxidant activity detection. The present invention detects the average humidity fluctuation of oat seeds and determines whether to perform seed grinding and antioxidant activity detection. If seed grinding and antioxidant activity detection are not performed, humidity control analysis is performed and it is determined whether to perform humidity control optimization. If seed grinding and antioxidant activity detection are performed, qualified antioxidant activity detection data is obtained, thereby improving the accuracy of oat seed humidity control analysis and achieving the effect of improving the accuracy of oat seed antioxidant activity detection, solving the problem in the prior art that oat seed antioxidant activity detection does not fully consider seed humidity.

Description

Technical Field

[0001] The present invention relates to the technical field of antioxidant activity detection, and in particular to a method, device and storage medium for detecting the antioxidant activity of oat seeds. Background Art

[0002] Oat seeds are a source of natural antioxidants, and their antioxidant active ingredients are complex and diverse, including avenanthramides, flavonoids, vitamin E, etc. When oat seeds are in a high humidity environment, the antioxidant components inside them easily react with water molecules, leading to decomposition or inactivation. For example, antioxidant components such as avenanthramides, flavonoids and vitamin E may undergo structural changes due to the action of water molecules in a high humidity environment, thereby reducing their antioxidant activity.

[0003] Existing methods are mainly based on electronic humidity controllers, which automatically adjust humidity through electronic components, and PID control algorithms, which achieve precise control of the humidity environment during the antioxidant activity detection of oat seeds through the synergistic effect of the three parts of proportion, integration and differentiation.

[0004] For example, the invention patent application with publication number CN116429990A discloses a method and device for detecting the antioxidant activity of oat seeds based on cellulase, comprising: crushing a plurality of oat seeds of different types into an oat powder set, performing cellulose hydrolysis on each oat powder in the oat powder set using cellulase to obtain an oat hydrolyzate set, performing spectral imaging on the oat hydrolyzate set to obtain an oat spectrum atlas; performing sugar, ketone and phenol detection on each oat hydrolyzate in the oat hydrolyzate set to obtain an oat component parameter set, performing antioxidant detection on the oat hydrolyzate set using a free radical scavenging method to obtain an antioxidant data set; training an antioxidant activity model using the oat spectrum atlas and the oat component parameter set to obtain an antioxidant analysis model; and analyzing the antioxidant activity of the oat seeds to be tested using the antioxidant analysis model.

[0005] For example, the invention patent publication number CN114705673B discloses a method for rapid colorimetric analysis of total antioxidant capacity based on MnCo@CNCs-like enzyme activity and its application. The method involves preparing a core-shell MnCo@CNCs-like enzyme material. The material is then incubated in a sodium acetate-acetate buffer solution containing varying concentrations of AA using its oxidase-like activity. The chromogenic substrate TMB is then added to the solution for reaction. The absorbance value A at a wavelength of 652 nm is recorded, and the linear relationship between the AA concentration and the absorbance difference ΔA is determined. AA is used as a model antioxidant compound, and TAC is characterized using mM / LAA.

[0006] However, in the process of implementing the technical solutions of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the existing technology, oat seeds, as a source of natural antioxidants, have complex and diverse antioxidant active ingredients. Humidity is also one of the important factors affecting the antioxidant activity of oat seeds. When oat seeds are in a high humidity environment, the antioxidant components inside them easily react with water molecules, leading to decomposition or inactivation. In some areas, due to the humid climate or frequent rainfall, the humidity conditions of oat seeds may be inaccurately controlled, resulting in the oat seed antioxidant activity test not fully considering the issue of seed humidity. Summary of the Invention

[0008] The embodiments of the present application provide a method, device and storage medium for detecting the antioxidant activity of oat seeds, thereby solving the problem that the antioxidant activity detection of oat seeds in the prior art does not fully consider the seed moisture content, and achieving more accurate antioxidant activity detection of oat seeds.

[0009] An embodiment of the present application provides a method for detecting the antioxidant activity of oat seeds, comprising the following steps: performing an average humidity fluctuation detection on oat seeds, and determining whether to perform seed grinding and antioxidant activity detection; if seed grinding and antioxidant activity detection are not performed, performing a humidity control analysis based on the obtained oat seed humidity optimization data, and determining whether to perform humidity control optimization; if seed grinding and antioxidant activity detection are performed, obtaining qualified antioxidant activity detection data.

[0010] An embodiment of the present application provides an antioxidant activity detection device for oat seeds, comprising an average humidity fluctuation detection module, a humidity control analysis module, and a seed grinding and antioxidant activity detection module: wherein the average humidity fluctuation detection module is used to perform average humidity fluctuation detection on oat seeds and determine whether to perform seed grinding and antioxidant activity detection; the humidity control analysis module is used to perform humidity control analysis based on acquired oat seed humidity optimization data if seed grinding and antioxidant activity detection are not performed, and determine whether to perform humidity control optimization; the seed grinding and antioxidant activity detection module is used to obtain qualified antioxidant activity detection data if seed grinding and antioxidant activity detection are performed.

[0011] An embodiment of the present application provides a computer-readable storage medium for storing a program, which, when executed by a processor, implements a method for detecting the antioxidant activity of oat seeds.

[0012] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0013] 1. By detecting the average humidity fluctuation of oat seeds and determining whether to perform seed grinding and antioxidant activity testing, if seed grinding and antioxidant activity testing are not performed, humidity control analysis is performed based on the obtained oat seed humidity optimization data to determine whether to perform humidity control optimization; if seed grinding and antioxidant activity testing are performed, qualified antioxidant activity test data is obtained, thereby improving the accuracy of oat seed humidity control analysis and further achieving more accurate oat seed antioxidant activity testing, effectively solving the problem that the antioxidant activity testing of oat seeds in the existing technology does not fully consider seed humidity.

[0014] 2. After coupling the humidity uniformity data group, a weighted operation is performed with the preset humidity uniformity weight to obtain the humidity distribution uniformity value. Then, after coupling the humidity fluctuation qualified data group, a weighted operation and negative correlation processing are performed with the preset humidity fluctuation weight to obtain the humidity fluctuation qualified value, thereby achieving an improvement in the reliability of humidity control optimization, and then achieving an improvement in the accuracy of humidity control optimization.

[0015] 3. By grinding and testing the antioxidant activity of qualified oat seeds, then monitoring the absorbance change value and comparing it with the preset absorbance change range, and finally obtaining qualified antioxidant activity test data, the reliability of the antioxidant activity test of oat seeds is improved, and then the effectiveness of the antioxidant activity test of oat seeds is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flow chart of a method for detecting the antioxidant activity of oat seeds provided in an embodiment of the present application;

[0017] Figure 2 This is a schematic structural diagram of a device for detecting the antioxidant activity of oat seeds provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] The embodiments of the present application solve the problem that the antioxidant activity detection of oat seeds in the prior art does not fully consider seed moisture by providing a method, device and storage medium for detecting the antioxidant activity of oat seeds. By detecting the average humidity fluctuation of oat seeds and judging whether to perform seed grinding and antioxidant activity detection, when the average humidity fluctuation value of the oat seeds is greater than the preset humidity fluctuation value, humidity control analysis is performed and it is judged whether to perform humidity control optimization. When the average humidity fluctuation value of the oat seeds is not greater than the preset humidity fluctuation value, seed grinding and antioxidant activity detection are performed to obtain qualified antioxidant activity detection data, thereby achieving more accurate antioxidant activity detection of oat seeds.

[0019] The technical solution in the embodiment of the present application is to solve the problem that the above-mentioned oat seed antioxidant activity detection does not fully consider the seed moisture. The overall idea is as follows:

[0020] By detecting the average humidity fluctuation of oat seeds and determining whether to perform seed grinding and antioxidant activity testing, if seed grinding and antioxidant activity testing are not performed, humidity control analysis is performed based on the obtained oat seed humidity optimization data to determine whether to perform humidity control optimization, and if seed grinding and antioxidant activity testing are performed, qualified antioxidant activity test data is obtained, thereby achieving the effect of improving the accuracy of oat seed humidity control analysis and improving the accuracy of oat seed antioxidant activity testing.

[0021] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0022] like Figure 1 As shown, it is a flow chart of a method for detecting the antioxidant activity of oat seeds provided in an embodiment of the present application, and the method includes the following steps: average humidity fluctuation detection: performing average humidity fluctuation detection on oat seeds, and determining whether to perform seed grinding and antioxidant activity detection; humidity control analysis: if seed grinding and antioxidant activity detection are not performed, performing humidity control analysis based on the obtained oat seed humidity optimization data, and determining whether to perform humidity control optimization; seed grinding and antioxidant activity detection: if seed grinding and antioxidant activity detection are performed, obtaining qualified antioxidant activity detection data.

[0023] It's important to understand that the antioxidant components within oat seeds are complex and diverse, including phenols, flavonoids, and other compounds with antioxidant activity. However, these components are extremely sensitive to humidity. The higher the humidity in the environment in which oat seeds are stored, the more likely the antioxidant components within them are to interact with water molecules, leading to decomposition or inactivation, thereby reducing their antioxidant activity. Therefore, strict control of oat seed humidity is crucial to maintaining their antioxidant activity.

[0024] In this embodiment, when the average humidity fluctuation of the monitored oat seeds is greater than a preset average humidity fluctuation, a humidity control analysis is performed; otherwise, it indicates that the oat seed sample has passed the initial screening and seed grinding and antioxidant activity testing are directly performed. A humidity distribution uniformity value and a humidity distribution difference value are obtained by performing the humidity control analysis, and the wind speed adjustment factor of the preset air circulation device is dynamically set based on the humidity distribution difference value. A humidity fluctuation qualified value and a humidity fluctuation qualified difference value are obtained by performing the humidity control analysis, and the dehumidification time adjustment factor of the preset dehumidification device is dynamically set based on the humidity fluctuation qualified difference value. An absorbance change value is obtained by performing the grinding process and antioxidant activity testing. When the absorbance change value is within the preset absorbance change range, qualified antioxidant activity test data of the corresponding oat seeds is obtained (tested by the DPPH free radical scavenging method to obtain, for example, free radical scavenging rate, total phenol content, total flavonoid content, etc.). The average humidity fluctuation detection, humidity control analysis, and seed grinding and antioxidant activity testing are interconnected and work together to help improve the reliability of the antioxidant activity test data of the oat seeds, thereby achieving more accurate antioxidant activity testing of the oat seeds.

[0025] Furthermore, the specific process of conducting an average moisture fluctuation test on oat seeds and determining whether to perform seed grinding and antioxidant activity testing is as follows: obtaining the average moisture fluctuation value of oat seeds within a preset first time period; performing a primary screening of oat seed samples based on the average moisture fluctuation value of oat seeds; the specific process of the primary screening is as follows: determining whether the average moisture fluctuation value of oat seeds is greater than the preset moisture fluctuation value; when the average moisture fluctuation value of oat seeds is not greater than the preset moisture fluctuation value, it indicates that the oat seed sample has passed the primary screening, and seed grinding and antioxidant activity testing are performed; when the average moisture fluctuation value of oat seeds is greater than the preset moisture fluctuation value, it indicates that the oat seed sample has failed the primary screening, and humidity control analysis is performed; the average moisture fluctuation value of oat seeds is represented by the absolute value of the corresponding difference between the initial average moisture value and the final average moisture value of the oat seed sample within the preset first time period; the humidity control analysis includes humidity distribution uniformity analysis and humidity fluctuation qualification analysis.

[0026] It should be added that the oat seed moisture optimization data includes a moisture uniformity data group and a moisture fluctuation qualified data group; the moisture uniformity data group is used to reflect the quantitative data of the comprehensive influence of the moisture distribution uniformity parameter and the preset moisture distribution uniformity parameter on the moisture distribution uniformity of the oat seeds; the humidity fluctuation qualified data group represents the quantitative data of the comprehensive influence of the humidity fluctuation parameter and the preset humidity fluctuation parameter on the moisture fluctuation qualified situation of the oat seeds; the moisture uniformity data group includes uniformity-humidity change evaluation value, uniformity-seed moisture content evaluation value, uniformity-hydrolysis evaluation value, uniformity-moisture absorption evaluation value; moisture distribution uniformity The uniformity parameters include the average value of the humidity gradient, the average value of the humidity change rate, the final oat seed moisture content, the average value of the hydrolysis rate, and the average value of the seed moisture absorption time; the preset humidity distribution uniformity parameters include the preset average value of the humidity gradient, the preset average value of the humidity change rate, the preset oat seed moisture content, the preset average value of the hydrolysis rate, the preset average value of the seed moisture absorption time, the preset humidity uniformity weight, and the preset humidity uniformity analysis weight group; the preset humidity uniformity analysis weight group includes the preset gradient-humidity change weight value, the preset gradient-hydrolysis weight value, the preset gradient-seed moisture weight value, and the preset gradient-moisture absorption weight value.

[0027] The units of the average humidity gradient and the preset average humidity gradient are both %RH / m, the units of the average humidity change rate and the preset average humidity change rate are both %RH / h, the final oat seed moisture content and the preset oat seed moisture content are both unitless, the units of the average hydrolysis rate and the preset average hydrolysis rate are both mol / (L*s), and the units of the average seed moisture absorption time and the preset average seed moisture absorption time are both min.

[0028] The humidity of the unqualified oat seeds at a preset location within a preset second time period is monitored using a hygrometer. The humidity difference between adjacent preset locations and the distance difference between the adjacent preset locations are compared, and the average of the results is used as the average humidity gradient. The humidity of the unqualified oat seeds at the initial and final states within the preset second time period is monitored using a hygrometer, and the absolute value of the difference and the average of the ratio corresponding to the preset second time period are used as the average humidity change rate. The moisture content of the unqualified oat seeds at the final state within the preset second time period is monitored using a moisture meter (such as a halogen moisture meter), which is the final oat seed moisture content. The electrical conductivity of a preset number of unqualified oat seeds within the preset second time period is monitored using electrodes (when the moisture or other ionizable substances in the oat seeds change, their electrical conductivity will also change accordingly). The absolute value of the difference and the average of the ratio corresponding to the preset second time period are used as the average hydrolysis rate. The time required for the unqualified oat seeds to reach a preset moisture content within the preset second time period is monitored using a moisture meter and a timer, and the average of the difference is used as the average seed moisture absorption time.

[0029] The qualified data group of humidity fluctuation includes fluctuation-moisture content fluctuation reflection, fluctuation-evaporation rate reflection value, fluctuation-humidity difference reflection value, and fluctuation-moisture content reflection value; humidity fluctuation parameters include the second humidity fluctuation average value, seed moisture content fluctuation value, water evaporation rate average value, humidity difference value, and final oat seed moisture content; the second humidity fluctuation average value is represented by the absolute value of the corresponding difference between the initial average humidity value and the final average humidity value of the unqualified oat seeds in the preset second time period; unqualified oat seeds indicate that the oat seed humidity fluctuation average value is greater than the oat seed sample corresponding to the preset humidity fluctuation average value; the preset humidity fluctuation parameters include the preset humidity fluctuation average value, the preset moisture content fluctuation value, the preset water evaporation rate average value, the preset humidity difference value, the preset oat seed moisture content, the preset humidity fluctuation weight The preset humidity fluctuation analysis weight group is composed of the preset moisture content fluctuation weight, the preset evaporation rate weight, the preset humidity difference weight, and the preset moisture content weight. The preset humidity uniformity weight is used to reflect the degree of influence of the humidity uniformity data group on the humidity distribution uniformity value within the preset second time period. The preset humidity uniformity analysis weight group is used to reflect the degree of influence of the humidity distribution uniformity parameter on the humidity uniformity data group within the preset second time period. The preset humidity fluctuation weight is used to reflect the degree of influence of the humidity fluctuation qualified data group on the humidity fluctuation qualified value within the preset second time period. The preset humidity fluctuation analysis weight group is used to reflect the degree of influence of the humidity fluctuation parameter on the humidity fluctuation qualified data group within the preset second time period. Humidity control optimization includes humidity distribution uniformity optimization and humidity fluctuation qualified optimization. The humidity fluctuation qualified data group and the humidity uniformity data group are both greater than 0.

[0030] The units of the second humidity fluctuation average value and the preset humidity fluctuation average value are both %RH, the seed moisture content fluctuation value and the preset moisture content fluctuation value have no units, the units of the water evaporation rate average value and the preset water evaporation rate average value are both mg / min, and the units of the humidity difference value and the preset humidity difference value are both %RH.

[0031] The initial average humidity value and the final average humidity value of the unqualified oat seeds in the preset second time period are monitored by a hygrometer, and the absolute value of the difference is used as the second humidity fluctuation average value; the moisture content of the unqualified oat seeds in the preset second time period is monitored by a moisture meter (such as a halogen moisture meter), and the difference between the maximum and minimum values ​​is used as the seed moisture content fluctuation value; the mass change (the difference between the final mass and the initial mass) of the unqualified oat seeds in the preset second time period is monitored by a timer and a balance (such as a laboratory 1 / 10,000 balance), and a ratio operation is performed with the corresponding preset second time period, and the average value of the results is used as the moisture evaporation rate average value; the humidity of the unqualified oat seeds in the preset second time period is monitored by a hygrometer, and the difference between the maximum and minimum values ​​is used as the humidity difference value.

[0032] In this embodiment, the aforementioned database is a method for detecting the antioxidant activity of oat seeds provided in an embodiment of the present application, which is used to store various set data means, preset oat seed moisture content, etc., wherein the various numerical values ​​are directly set by technical personnel; for example, the preset evaluation parameters include the preset humidity gradient average value, the preset humidity change rate average value, the preset oat seed moisture content, the preset hydrolysis rate average value, the preset moisture absorption time average value, the preset humidity fluctuation average value, the preset moisture evaporation rate average value, and the preset humidity difference value; the preset evaluation historical data include humidity gradient, humidity change rate, moisture content, hydrolysis rate, moisture absorption time, oat seed humidity fluctuation average value, moisture evaporation rate, and humidity difference value; the preset evaluation parameters are represented by the average value of the preset evaluation historical data of the corresponding historical time period.

[0033] By conducting an initial screening of oat seed samples and performing humidity control analysis on oat seed samples that fail the initial screening, it is helpful to achieve precise control of the humidity environment for antioxidant activity testing, help reduce the impact of humidity fluctuations on seed quality, and thus achieve the effect of improving the accuracy of antioxidant activity testing in oat seeds.

[0034] Furthermore, the specific process of humidity distribution uniformity analysis is as follows: first, a convergence degree analysis is performed on the preset humidity gradient average value and the humidity gradient average value, and then a convergence degree analysis is performed on the preset humidity change rate average value and the humidity change rate average value, and then a weighted operation is performed on the preset gradient-humidity change weight value to obtain a uniformity-humidity change evaluation value; the uniformity-humidity change evaluation value is used to reflect the joint effect of the preset second time period humidity gradient average value and the humidity change rate average value on the uniformity of oat seed moisture distribution; first, a convergence degree analysis is performed on the preset humidity gradient average value and the humidity gradient average value, and then a convergence degree analysis is performed on the preset oat seed moisture content and the final oat seed moisture content, and then a weighted operation is performed on the preset gradient-seed moisture weight value to obtain a uniformity-seed moisture evaluation value; the uniformity-humidity change evaluation value is used to reflect the joint effect of the preset second time period humidity gradient average value and the final oat seed moisture content on the uniformity of oat seed moisture distribution; first, a convergence degree analysis is performed on the preset humidity gradient average value and the humidity gradient average value, and then a preset hydrolysis After the convergence degree analysis of the rate average value and the hydrolysis rate average value, a weighted operation is performed in combination with the preset gradient-hydrolysis weight value to obtain the uniformity-hydrolysis evaluation value; the uniformity-humidity change evaluation value is used to reflect the joint effect of the humidity gradient average value and the hydrolysis rate average value in the preset second time period on the uniformity of the moisture distribution of the oat seeds; after the convergence degree analysis of the preset humidity gradient average value and the humidity gradient average value, and then the convergence degree analysis of the seed moisture absorption time average value and the preset seed moisture absorption time average value, a weighted operation is performed in combination with the preset gradient-moisture absorption weight value to obtain the uniformity-moisture absorption evaluation value; the uniformity-humidity change evaluation value is used to reflect the joint effect of the humidity gradient average value and the seed moisture absorption time average value in the preset second time period on the uniformity of the moisture distribution of the oat seeds; after the humidity uniformity data group is coupled, a weighted operation is performed with the preset humidity uniformity weight to obtain the humidity distribution uniformity value; the humidity distribution uniformity value is used to reflect the joint influence of the humidity distribution uniformity parameter of the preset second time period and the preset humidity distribution uniformity parameter on the uniformity of the moisture distribution of the oat seeds.

[0035] The humidity distribution uniformity value is obtained by the following method:

[0036] ;

[0037] Where, Indicates the moisture distribution uniformity value of unqualified oat seeds in the sth preset second time period, , s represents the number of the preset second time period, k represents the total number of preset second time periods, represents the uniformity-humidity change evaluation value of unqualified oat seeds in the sth preset second time period, Indicates the uniformity-seed moisture evaluation value of unqualified oat seeds in the sth preset second time period, represents the uniformity-hydrolysis evaluation value of unqualified oat seeds in the sth preset second time period, It represents the uniformity-moisture absorption evaluation value of unqualified oat seeds in the sth preset second time period, Indicates the preset humidity uniformity weight.

[0038] Specifically, the expression of uniformity-humidity change evaluation value is: , where Indicates the preset gradient-humidity change weight value, represents the average moisture gradient of unqualified oat seeds in the sth preset second time period, Indicates the preset humidity gradient average value, represents the average value of the moisture change rate of unqualified oat seeds in the sth preset second time period, Indicates the preset average value of humidity change rate.

[0039] The expression of uniformity-seed moisture evaluation value is , where Indicates the preset gradient-seed moisture weight value, represents the final moisture content of unqualified oat seeds in the sth preset second time period, Indicates the preset oat seed moisture content.

[0040] The expression of the homogeneity-hydrolysis evaluation value is , where Represents the preset gradient-hydrolysis weight value, represents the average hydrolysis rate of unqualified oat seeds in the sth preset second time period, Indicates the preset average value of hydrolysis rate.

[0041] The expression of uniformity-moisture absorption evaluation value is , where Indicates the preset gradient-hygroscopic weight value, It represents the average moisture absorption time of unqualified oat seeds in the sth preset second time period. Indicates the average value of the preset seed moisture absorption time.

[0042] In this embodiment, the moisture uniformity value is analyzed in conjunction with the moisture uniformity data set. A larger uniformity-humidity change assessment value indicates a stronger combined effect of the average moisture gradient and the average moisture change rate on the moisture uniformity of the oat seeds, resulting in a larger moisture uniformity value. A larger uniformity-humidity change assessment value indicates a stronger combined effect of the average moisture gradient and the final oat seed moisture content on the moisture uniformity of the oat seeds, resulting in a larger moisture uniformity value. A larger uniformity-humidity change assessment value indicates a stronger combined effect of the average moisture gradient and the average hydrolysis rate on the moisture uniformity of the oat seeds, resulting in a larger moisture uniformity value. A larger uniformity-humidity change assessment value indicates a stronger combined effect of the average moisture gradient and the average seed moisture absorption time on the moisture uniformity of the oat seeds, resulting in a larger moisture uniformity value. In summary, the moisture uniformity data set is directly proportional to the moisture uniformity value.

[0043] The humidity distribution uniformity parameters in this embodiment do not exist independently but are interrelated and require comprehensive analysis. A larger average humidity gradient may cause some oat seeds to be in a higher humidity environment, which will directly affect the moisture content of the final oat seeds and result in a higher moisture content in the final oat seeds. A larger humidity gradient may cause the hydrolysis reaction to be faster, leading to accelerated decomposition of substances in the seeds, which in turn leads to a larger average hydrolysis rate. A faster average humidity change rate may lead to a higher probability of seed moisture content change, which in turn affects the moisture content of the final oat seeds. A higher moisture content in the final oat seeds may accelerate the hydrolysis reaction, produce more decomposition products, and result in a higher average hydrolysis rate. A longer average seed moisture absorption time means that the moisture inside the oat seeds has more time to be evenly distributed, which in turn affects the humidity distribution uniformity value and results in a higher humidity distribution uniformity value. By analyzing the comprehensive influence of the parameters, an accurate assessment of the moisture distribution uniformity of the oat seeds in the preset second time period is achieved, thereby achieving the effect of improving the accuracy of the antioxidant activity detection of oat seeds.

[0044] Among them, this embodiment provides two mapping groups obtained from the database, and each contains a mapping set. The mapping relationship in the mapping set can be a one-to-one correspondence or a many-to-one relationship. One group is used to reflect the mapping relationship between the humidity uniformity data group and the corresponding preset humidity uniformity weight, and one group is used to reflect the mapping relationship between the humidity distribution uniformity parameter and the corresponding preset humidity uniformity analysis weight group; by inputting the real-time humidity uniformity data group into the mapping group, the corresponding preset humidity uniformity weight can be obtained, and by inputting the real-time humidity distribution uniformity parameter into the mapping group, the corresponding preset humidity uniformity analysis weight group can be obtained; for example, the weight value range is 0-1.

[0045] Furthermore, the specific process of optimizing the humidity distribution uniformity is as follows: ST1, sending a prompt to the preset personnel to turn on the preset air circulation device, and monitoring the humidity distribution uniformity value during the preset air supply time period; ST2, performing humidity distribution algorithm control based on the humidity distribution uniformity value; ST3, sending a dynamic humidity distribution adjustment prompt to the preset air circulation device based on the humidity distribution difference value and the humidity distribution control signal, and stopping execution when the humidity distribution difference value is not greater than the preset humidity distribution difference value obtained from the database, and the average value of the oat seed humidity fluctuation is not greater than the preset humidity fluctuation average value; the humidity distribution algorithm control represents obtaining the humidity distribution uniformity value and the corresponding target value, as well as the humidity distribution control signal based on the PID (Proportion, Integral, Differential) control algorithm; the humidity distribution difference value is represented by the difference between the humidity distribution uniformity value and the corresponding target value (only considering the case where the humidity distribution uniformity value is greater than the corresponding target value); the dynamic humidity distribution adjustment represents sending a prompt to the preset personnel to set the adjustment multiple of the wind speed of the preset air circulation device.

[0046] In this embodiment, the preset humidity distribution difference value is represented by the average of humidity distribution difference values ​​over a historical time period. When a prompt to dynamically adjust the humidity distribution is received, the wind speed of a preset air circulation device (e.g., a fan) is dynamically set. For example, when the humidity distribution difference value exceeds a preset multiple (typically 2) of the preset humidity distribution difference value, the wind speed of the preset air circulation device is set to exceed a preset multiple (typically 2) of a preset wind speed threshold. The preset wind speed threshold is represented by the average of the wind speeds of the preset air circulation device within the preset storage space over the historical time period. When oat seeds are exposed to high humidity, antioxidant components are easily reacted with water molecules, resulting in decomposition or inactivation. Precisely controlling the uniformity of humidity distribution helps protect the antioxidant components within the oat seeds and maintain their antioxidant activity, thereby enabling more accurate antioxidant activity testing of oat seeds.

[0047] Furthermore, the specific process of humidity fluctuation qualification analysis is as follows: after performing a proportion analysis on the second humidity fluctuation average value and the preset humidity fluctuation average value, a humidity fluctuation reflection value is obtained; after performing a proportion analysis on the seed moisture content fluctuation value and the preset moisture content fluctuation value, a weighted operation is performed on the humidity fluctuation reflection value, the preset moisture content fluctuation weight and the preset humidity fluctuation comprehensive weight to obtain a fluctuation-moisture content fluctuation reflection value; the fluctuation-moisture content fluctuation reflection value is used to reflect the comprehensive effect of the second humidity fluctuation average value and the seed moisture content fluctuation value on the humidity fluctuation qualification of the oat seeds in the preset second time period; after performing a proportion analysis on the water evaporation rate average value and the preset water evaporation rate average value, a weighted operation is performed on the preset evaporation rate weight and the preset evaporation rate weight and the preset humidity fluctuation comprehensive weight to obtain a fluctuation-evaporation rate reflection value; the fluctuation-evaporation rate reflection value is used to reflect the comprehensive effect of the second humidity fluctuation average value and the water evaporation rate average value on the humidity fluctuation qualification of the oat seeds in the preset second time period; the humidity difference value and the preset After the humidity difference value is analyzed for the proportion, a weighted operation is performed on the results of the proportion analysis of the preset humidity difference weight and the preset humidity difference weight and the preset humidity fluctuation comprehensive weight to obtain the fluctuation-humidity difference reflection value; the fluctuation-humidity difference reflection value is used to reflect the comprehensive effect of the second humidity fluctuation average value and the humidity difference value in the preset second time period on the qualified situation of the humidity fluctuation of the oat seeds; after the proportion analysis of the final oat seed moisture content and the preset oat seed moisture content, a weighted operation is performed on the results of the proportion analysis of the preset moisture weight and the preset moisture weight and the preset humidity fluctuation comprehensive weight to obtain the fluctuation-moisture reflection value; the fluctuation-humidity difference reflection value is used to reflect the comprehensive effect of the second humidity fluctuation average value and the final oat seed moisture content in the preset second time period on the qualified situation of the humidity fluctuation of the oat seeds; after coupling processing of the humidity fluctuation qualified data group, a weighted operation and negative correlation processing are performed with the preset humidity fluctuation weight to obtain the humidity fluctuation qualified value; the humidity fluctuation qualified value is used to reflect the influence of the humidity fluctuation parameter and the preset humidity fluctuation parameter on the qualified situation of the humidity fluctuation of the oat seeds.

[0048] The qualified value of humidity fluctuation is obtained by the following method:

[0049] ;

[0050] Where, Indicates the qualified value of humidity fluctuation of unqualified oat seeds in the sth preset second time period, , s represents the number of the preset second time period, k represents the total number of preset second time periods, It represents the fluctuation of unqualified oat seeds in the sth preset second time period - the moisture content fluctuation reflection value, represents the fluctuation-evaporation rate reflection value of unqualified oat seeds in the sth preset second time period, It represents the fluctuation-humidity difference reflection value of unqualified oat seeds in the sth preset second time period, It represents the fluctuation-water reflection value of unqualified oat seeds in the sth preset second time period, represents the preset humidity fluctuation weight, and e represents a natural constant.

[0051] Specifically, the expression of the fluctuation-water content fluctuation reflection value is: , where Indicates the preset moisture content fluctuation weight, Indicates the moisture content fluctuation value of unqualified oat seeds in the sth preset second time period, Indicates the preset moisture content fluctuation value.

[0052] The expression of the fluctuation-evaporation rate reflection value is: , where represents the preset evaporation rate weight, represents the average water evaporation rate of unqualified oat seeds in the sth preset second time period, Indicates the preset average value of water evaporation rate.

[0053] The expression of the fluctuation-humidity difference reflection value is: , where Indicates the preset humidity difference weight, Indicates the humidity difference value of unqualified oat seeds in the sth preset second time period, Indicates the preset humidity difference value.

[0054] The expression of the fluctuation-water reflection value is , where Indicates the preset water weight, represents the final moisture content of unqualified oat seeds in the sth preset second time period, Indicates the preset humidity difference value, Indicates the preset oat seed moisture content.

[0055] In the above formula It represents the humidity fluctuation reflection value of unqualified oat seeds in the sth preset second time period. The specific expression is: , h represents the preset humidity fluctuation comprehensive weight, the specific expression is , represents the second humidity fluctuation average value of unqualified oat seeds in the sth preset second time period, It represents the preset average value of humidity fluctuation, and h represents the preset comprehensive weight of humidity fluctuation.

[0056] This example analyzes the humidity fluctuation qualified data set to obtain a humidity fluctuation qualified value. In this example, the range of the humidity fluctuation qualified value is greater than 1 to expand the allowable fluctuation range of the humidity fluctuation qualified value data. A larger fluctuation-moisture content fluctuation reflection value indicates a stronger combined effect of the second humidity fluctuation average value and the seed moisture content fluctuation value on the oat seed humidity fluctuation qualified condition, resulting in a smaller humidity fluctuation qualified value. A larger fluctuation-evaporation rate reflection value indicates a stronger combined effect of the second humidity fluctuation average value and the water evaporation rate average value on the oat seed humidity fluctuation qualified condition, resulting in a smaller humidity fluctuation qualified value. A larger fluctuation-humidity difference reflection value indicates a stronger combined effect of the second humidity fluctuation average value and the humidity difference value on the oat seed humidity fluctuation qualified condition, resulting in a smaller humidity fluctuation qualified value. A larger fluctuation-moisture content reflection value indicates a stronger combined effect of the second humidity fluctuation average value and the final oat seed moisture content on the oat seed humidity fluctuation qualified condition, resulting in a smaller humidity fluctuation qualified value. In summary, the humidity fluctuation qualified data set and the humidity fluctuation qualified value are negatively correlated.

[0057] In this embodiment, the humidity fluctuation parameters do not exist independently, but are interrelated and require comprehensive analysis. The larger the second humidity fluctuation average value, the more likely it is that the moisture distribution inside the seed is uneven, which in turn causes a larger fluctuation in the seed moisture content; the larger the average value of the water evaporation rate, the faster the rate of moisture loss from the surface of the oat seed, which may cause the surface of the seed to dry quickly while the internal moisture has no time to diffuse, resulting in uneven humidity distribution, which in turn affects the second humidity fluctuation average value, resulting in a larger second humidity fluctuation average value; the larger the seed moisture content fluctuation value, the faster the moisture loss inside the seed, which in turn causes a larger seed moisture content fluctuation value; the larger the humidity difference value, the greater the humidity difference of the oat seeds, and the water lost by the oat seeds may be different, which in turn affects the final oat seed moisture content; by analyzing the comprehensive influence between the parameters, an accurate assessment of the qualified situation of the humidity fluctuation of the oat seeds in the preset second time period is achieved, thereby achieving a more accurate detection of the antioxidant activity of the oat seeds.

[0058] Among them, this embodiment provides two mapping groups obtained from the database, and each contains a mapping set. The mapping relationship in the mapping set can be a one-to-one correspondence or a many-to-one relationship. One group is used to reflect the mapping relationship between the humidity fluctuation qualified data group and the corresponding preset humidity fluctuation weight, and one group is used to reflect the mapping relationship between the humidity fluctuation parameters and the corresponding preset humidity fluctuation analysis weight group; by inputting the real-time humidity fluctuation qualified data group into the mapping group, the corresponding preset humidity fluctuation weight can be obtained, and by inputting the real-time humidity fluctuation parameters into the mapping group, the corresponding preset humidity fluctuation analysis weight group can be obtained; for example, the weight value range is 0-1.

[0059] Furthermore, the specific process of humidity fluctuation qualification optimization is as follows: the first step is to send a prompt to the preset personnel to turn on the preset dehumidification equipment, and monitor the humidity fluctuation qualification value during the preset dehumidification time period; the second step is to perform humidity fluctuation qualification algorithm control based on the humidity fluctuation qualification value; the third step is to send a dynamic adjustment humidity fluctuation prompt to the preset dehumidification equipment based on the humidity fluctuation qualification difference value and the humidity fluctuation control signal. When the monitored humidity fluctuation qualification difference value is not greater than the preset humidity fluctuation qualification difference value obtained from the database, and the average humidity fluctuation value of the oat seeds is not greater than the preset humidity fluctuation average value, the execution is stopped; the humidity fluctuation qualification algorithm control represents obtaining the humidity fluctuation qualification value and the corresponding target value, as well as the humidity fluctuation control signal based on the PID control algorithm; the humidity fluctuation qualification difference value is represented by the absolute value of the difference between the humidity fluctuation qualification value and the corresponding target value; the dynamic adjustment humidity fluctuation represents sending a prompt to the preset personnel to set the adjustment multiple of the dehumidification time of the preset dehumidification equipment.

[0060] In this embodiment, the preset humidity fluctuation qualified difference value is represented by the average value of the humidity fluctuation qualified difference values ​​in the historical time period; when a dynamic humidity fluctuation adjustment prompt is received, the dehumidification time of the preset dehumidification device (such as a dehumidification duct) is dynamically set. For example, when the humidity fluctuation qualified difference value is greater than a preset multiple (generally 2 times) of the preset humidity fluctuation qualified difference value, the dehumidification time of the preset dehumidification device is set to be greater than a preset multiple (generally 2 times) of the preset dehumidification time threshold, and the preset dehumidification time threshold is represented by the average value of the dehumidification time of the preset dehumidification device in the preset storage space in the historical time period; the antioxidant active ingredients in oat seeds are extremely sensitive to humidity conditions, and a high humidity environment may cause these ingredients to decompose or inactivate. Areas with humid climates or frequent rainfall may cause inaccurate control of the humidity conditions of oat seeds, thereby affecting the accuracy of the antioxidant activity test results. By precisely controlling humidity fluctuations, it can be ensured that the oat seeds are always within an appropriate humidity range during storage, thereby effectively protecting the antioxidant active ingredients inside them, thereby achieving more accurate oat seed antioxidant activity detection.

[0061] Furthermore, the specific process of obtaining qualified antioxidant activity test data is as follows: grinding qualified oat seeds and performing antioxidant activity testing; monitoring the initial absorbance and final absorbance within a preset third time period to obtain an absorbance change value; comparing the absorbance change value with a preset absorbance change range obtained from a database to obtain qualified antioxidant activity test data; qualified antioxidant activity test data represents antioxidant activity test data corresponding to qualified oat seeds whose average humidity fluctuation value of the oat seeds is not greater than the preset humidity fluctuation average value, and whose absorbance change value is within the preset absorbance change range; the absorbance change value is represented by the absolute value corresponding to the difference between the initial absorbance and the final absorbance; qualified oat seeds represent oat seed samples whose average humidity fluctuation value of the oat seeds is not greater than the preset humidity fluctuation average value; antioxidant activity detection represents detection by DPPH (1,1-Diphenyl-2-picrylhydrazyl radical, 1,1-diphenyl-2-trinitrophenylhydrazine) free radical scavenging method.

[0062] It should be added that, Figure 2 As shown, it is a structural diagram of an antioxidant activity detection device for oat seeds provided in an embodiment of the present application. An antioxidant activity detection device for oat seeds provided in an embodiment of the present application includes an average humidity fluctuation detection module, a humidity control analysis module and a seed grinding and antioxidant activity detection module: wherein the average humidity fluctuation detection module is used to detect the average humidity fluctuation of oat seeds and determine whether to perform seed grinding and antioxidant activity detection; the humidity control analysis module is used to perform humidity control analysis based on the acquired oat seed humidity optimization data if seed grinding and antioxidant activity detection are not performed, and determine whether to perform humidity control optimization; the seed grinding and antioxidant activity detection module is used to obtain qualified antioxidant activity detection data if seed grinding and antioxidant activity detection are performed.

[0063] Among them, an embodiment of the present application also provides a computer-readable storage medium for storing a program, which, when executed by a processor, implements a method for detecting the antioxidant activity of oat seeds.

[0064] In this embodiment, the preset absorbance change range is set in advance by a preset personnel; by comparing the absorbance change value with the preset absorbance change range, oat seed samples with qualified antioxidant activity can be screened out (the average value of the humidity fluctuation of the oat seeds is not greater than the preset humidity fluctuation average value, and the absorbance change value is within the preset absorbance change range). Qualified oat seeds); through humidity control and precise quantification of antioxidant activity, it helps to reduce the deviation of the antioxidant activity test results of oat seeds caused by high humidity environment, thereby achieving the effect of improving the accuracy of the antioxidant activity test of oat seeds.

[0065] In summary, the embodiment of the present application detects the average humidity fluctuation of oat seeds and determines whether to perform seed grinding and antioxidant activity testing. If seed grinding and antioxidant activity testing are not performed, humidity control analysis is performed based on the obtained oat seed humidity optimization data to determine whether to perform humidity control optimization. If seed grinding and antioxidant activity testing are performed, qualified antioxidant activity testing data is obtained, thereby improving the accuracy of oat seed humidity control analysis, and further achieving more accurate oat seed antioxidant activity testing, effectively solving the problem that the oat seed antioxidant activity testing in the prior art does not fully consider seed humidity.

[0066] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0067] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0068] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0069] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0070] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0071] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A method for detecting the antioxidant activity of oat seeds, characterized in that: The following steps are involved: Conduct oat seed average moisture fluctuation tests and determine whether to proceed with seed grinding and antioxidant activity testing; If seed grinding and antioxidant activity testing are not performed, humidity control analysis is performed based on the obtained oat seed humidity optimization data to determine whether humidity control optimization is performed; If seed grinding and antioxidant activity testing are performed, qualified antioxidant activity test data will be obtained; The specific process of detecting the average humidity fluctuation of oat seeds and determining whether to perform seed grinding and antioxidant activity testing is as follows: Obtaining an average value of humidity fluctuation of the oat seeds within a preset first time period, and determining whether the average value of humidity fluctuation of the oat seeds is greater than a preset average value of humidity fluctuation; When the average value of the humidity fluctuation of the oat seeds is not greater than the preset average value of the humidity fluctuation, it indicates that the oat seed sample has passed the initial screening and the seed grinding and antioxidant activity test are carried out; When the average value of humidity fluctuation of oat seeds is greater than the preset average value of humidity fluctuation, it indicates that the oat seed sample fails the initial screening and humidity control analysis is performed; The humidity control analysis includes humidity distribution uniformity analysis and humidity fluctuation qualification analysis.

2. The method for detecting the antioxidant activity of oat seeds according to claim 1, wherein: The oat seed moisture optimization data includes a moisture uniformity data group and a moisture fluctuation qualified data group; The moisture uniformity data set is used to quantify the comprehensive impact of the moisture distribution uniformity parameter and the preset moisture distribution uniformity parameter on the moisture distribution uniformity of oat seeds, specifically including uniformity-humidity change evaluation value, uniformity-seed moisture evaluation value, uniformity-hydrolysis evaluation value, and uniformity-moisture absorption evaluation value; The humidity fluctuation qualified data group represents quantitative data of the comprehensive impact of the humidity fluctuation parameter and the preset humidity fluctuation parameter on the qualified situation of the humidity fluctuation of the oat seeds, specifically including the fluctuation-moisture content fluctuation reflection value, the fluctuation-evaporation rate reflection value, the fluctuation-humidity difference reflection value, and the fluctuation-moisture content reflection value; The moisture distribution uniformity parameters include the average value of the moisture gradient, the average value of the moisture change rate, the final oat seed moisture content, the average value of the hydrolysis rate, and the average value of the seed moisture absorption time; The humidity fluctuation parameters include the second humidity fluctuation average value, the seed moisture content fluctuation value, the water evaporation rate average value, the humidity difference value, and the final oat seed moisture content; The humidity control optimization includes humidity distribution uniformity optimization and humidity fluctuation eligibility optimization.

3. The method for detecting the antioxidant activity of oat seeds according to claim 1, wherein: The specific process of the humidity distribution uniformity analysis is as follows: First, the preset humidity gradient average and humidity gradient average are analyzed for their degree of convergence, and then the preset humidity change rate average and humidity change rate average are analyzed for their degree of convergence. Then, a weighted operation is performed on the preset gradient-humidity change weight value to obtain a uniformity-humidity change evaluation value, which is used to reflect the combined effect of the preset humidity gradient average and humidity change rate average in the second time period on the uniformity of the moisture distribution of the oat seeds; After first performing a convergence analysis on the preset humidity gradient average and the humidity gradient average, and then performing a convergence analysis on the preset oat seed moisture content and the final oat seed moisture content, a weighted operation is performed on the preset gradient-seed moisture content weight value to obtain a uniformity-seed moisture content assessment value, which is used to reflect the combined effect of the preset humidity gradient average and the final oat seed moisture content in the second time period on the uniformity of the oat seed moisture distribution; After first performing a convergence analysis on the preset humidity gradient average and the humidity gradient average, and then performing a convergence analysis on the preset hydrolysis rate average and the hydrolysis rate average, a weighted operation is performed on the preset gradient-hydrolysis weight value to obtain a uniformity-hydrolysis evaluation value, which is used to reflect the combined effect of the humidity gradient average and the hydrolysis rate average in the preset second time period on the uniformity of the moisture distribution of the oat seeds; After first analyzing the degree of convergence of the preset humidity gradient average and the humidity gradient average, and then analyzing the degree of convergence of the seed moisture absorption time average and the preset seed moisture absorption time average, a weighted operation is performed on the preset gradient-moisture absorption weight value to obtain a uniformity-moisture absorption evaluation value, which is used to reflect the combined effect of the preset second time period humidity gradient average and seed moisture absorption time average on the uniformity of oat seed moisture distribution; After coupling processing of the humidity uniformity data group, a weighted operation is performed with the preset humidity uniformity weight to obtain a humidity distribution uniformity value, which is used to reflect the influence of the humidity distribution uniformity parameter of the preset second time period and the preset humidity distribution uniformity parameter on the humidity distribution uniformity of oat seeds.

4. The method for detecting the antioxidant activity of oat seeds according to claim 2, wherein: The specific process of optimizing the humidity distribution uniformity is as follows: ST1, sends a reminder to the preset personnel to turn on the preset air circulation device, and monitors the humidity distribution uniformity value during the preset air supply time period; ST2, humidity distribution algorithm control based on humidity distribution uniformity value; ST3, based on the humidity distribution difference value and the humidity distribution control signal, a dynamic humidity distribution adjustment prompt is sent to the preset air circulation device. When the humidity distribution difference value is not greater than the preset humidity distribution difference value obtained from the database, and the average humidity fluctuation value of the oat seeds is not greater than the preset humidity fluctuation average value, the execution is stopped.

5. The method for detecting the antioxidant activity of oat seeds according to claim 1, wherein: The specific process of the humidity fluctuation qualification analysis is as follows: Performing a proportion analysis on the second humidity fluctuation average value and the preset humidity fluctuation average value to obtain a humidity fluctuation reflection value; After performing a proportion analysis on the seed moisture content fluctuation value and the preset moisture content fluctuation value, a weighted calculation is performed on the results of the proportion analysis based on the humidity fluctuation reflection value, the preset moisture content fluctuation weight, and the preset humidity fluctuation comprehensive weight to obtain a fluctuation-moisture content fluctuation reflection value, which is used to reflect the comprehensive effect of the second humidity fluctuation average value and the seed moisture content fluctuation value on the qualified condition of the oat seed moisture fluctuation within the preset second time period; After analyzing the proportion of the average water evaporation rate and the preset average water evaporation rate, a weighted calculation is performed on the results of the proportion analysis based on the preset evaporation rate weight and the preset evaporation rate weight and the preset humidity fluctuation comprehensive weight to obtain a fluctuation-evaporation rate reflection value, which is used to reflect the comprehensive effect of the second humidity fluctuation average value and the water evaporation rate average value on the qualified humidity fluctuation of the oat seeds within the preset second time period; After performing a proportion analysis on the humidity difference value and the preset humidity difference value, a weighted operation is performed on the results of the proportion analysis based on the preset humidity difference weight and the preset humidity difference weight and the preset humidity fluctuation comprehensive weight to obtain a fluctuation-humidity difference reflection value, which is used to reflect the comprehensive effect of the second humidity fluctuation average value and the humidity difference value on the qualified humidity fluctuation of the oat seeds in the preset second time period; After performing a proportion analysis on the final oat seed moisture content and the preset oat seed moisture content, a weighted calculation is performed on the results of the proportion analysis based on the preset moisture weight and the preset moisture weight and the preset humidity fluctuation comprehensive weight to obtain a fluctuation-moisture reflection value, which is used to reflect the comprehensive effect of the second humidity fluctuation average value and the final oat seed moisture content on the qualified status of the oat seed humidity fluctuation within the preset second time period; After coupling processing of the humidity fluctuation qualified data group, weighted operation and negative correlation processing are performed with the preset humidity fluctuation weight to obtain the humidity fluctuation qualified value, which is used to reflect the joint influence of the humidity fluctuation parameter and the preset humidity fluctuation parameter on the humidity fluctuation qualified situation of oat seeds.

6. The method for detecting the antioxidant activity of oat seeds according to claim 2, wherein: The specific process of humidity fluctuation eligibility optimization is as follows: The first step is to send a reminder to the preset personnel to turn on the preset dehumidification equipment, and monitor the humidity fluctuation qualified value during the preset dehumidification time period; The second step is to perform humidity fluctuation qualification algorithm control based on the humidity fluctuation qualified value; The third step is to send a dynamic humidity fluctuation adjustment prompt to the preset dehumidification device based on the humidity fluctuation qualified difference value and the humidity fluctuation control signal. When the monitored humidity fluctuation qualified difference value is not greater than the preset humidity fluctuation qualified difference value obtained from the database, and the average humidity fluctuation value of the oat seeds is not greater than the preset humidity fluctuation average value, the execution is stopped; The humidity fluctuation qualification algorithm control means obtaining a humidity fluctuation qualification value and a corresponding target value, as well as a humidity fluctuation control signal based on a PID control algorithm.

7. The method for detecting the antioxidant activity of oat seeds according to claim 1, wherein: The specific process of obtaining qualified antioxidant activity test data is as follows: Grinding and antioxidant activity testing of qualified oat seeds; Monitoring the initial absorbance and the final absorbance within a preset third time period to obtain an absorbance change value; Comparing the absorbance change value with the preset absorbance change range obtained from the database to obtain qualified antioxidant activity test data; The qualified antioxidant activity test data represents the antioxidant activity test data corresponding to qualified oat seeds whose humidity fluctuation average value is not greater than a preset humidity fluctuation average value and whose absorbance change value is within a preset absorbance change range.

8. A device for detecting the antioxidant activity of oat seeds, using the method for detecting the antioxidant activity of oat seeds according to any one of claims 1 to 7, characterized in that: It includes average humidity fluctuation detection module, humidity control analysis module and seed grinding and antioxidant activity detection module: The average humidity fluctuation detection module is used to detect the average humidity fluctuation of oat seeds and determine whether to perform seed grinding and antioxidant activity testing; The humidity control analysis module is used to perform humidity control analysis based on the acquired oat seed humidity optimization data if seed grinding and antioxidant activity testing are not performed, and determine whether to perform humidity control optimization; The seed grinding and antioxidant activity detection module is used to obtain qualified antioxidant activity detection data if seed grinding and antioxidant activity detection are performed.

9. A computer-readable storage medium for storing a program, wherein when the program is executed by a processor, the method for detecting the antioxidant activity of oat seeds according to any one of claims 1 to 7 is implemented.

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