Daqu worm detection method and system

Abstract

The invention discloses a method and a system for detecting Daqu worms, which are applied to the technical field of intelligent detection of Daqu worms, and the method comprises the following steps: obtaining a detection yeast block; killing the koji insects of the detection koji blocks until all the koji insects and eggs are killed to form insect-free koji blocks, and taking the detection koji blocks without killing the koji insects as insect-containing koji blocks; putting an insect-free koji block into the first sealing cavity, and putting an insect-containing koji block into the second sealing cavity; monitoring gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity; and calculating the contents of adults, pupae, larvae and eggs in the yeast to be detected according to the gas content data, the temperature data and the air pressure data of the first sealed cavity and the second sealed cavity. The invention provides a brand new koji insect detection scheme, a chemical detection means is not needed, the cost is effectively reduced, and the detection influence caused by seasonal change can be reduced because the detection environment can be kept stable.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent detection of Aspergillus niger, and in particular to a method and system for detecting Aspergillus niger. Background Art

[0002] Koji insects refer to pests that harm the koji used in brewing. The term koji insect is unique to the brewing industry, but the pests involved in this name are not unique to breweries and only harm the koji used in brewing, but are commonly found in nature. In terms of classification, the vast majority of species are harmful insects, and a few species are harmful mites; there are many types of koji insects, and there are more than 20 common species, such as the flat grain beetle, the coffee bean weevil, the yellow-spotted dew-tailed beetle, the medicinal material beetle, etc., which are often the dominant populations with large occurrences and serious damage. Koji blocks that are severely infested with insects are riddled with holes and insect eyes. Not only does the weight of the koji lose a lot, the saccharification power is greatly reduced, and the quality of the wine is affected. At present, the harm caused by koji insects in koji and medicinal materials production is getting worse and worse, and it has become a problem that plagues the liquor industry.

[0003] To control the koji worm, it is necessary to first understand the status of the koji worm in the koji block. The existing technology mostly uses chemical methods to detect the koji worm. For example, the Chinese patent with application number 202211157682.8 discloses the technical field of koji worm activity detection, which specifically relates to a method for judging the activity of koji worms in Daqu based on the content of 1-pentadecaene, comprising the following steps: (1) weighing a Daqu sample, adding an extraction solvent to the Daqu sample for leaching, and obtaining an extract; sending the extract to a gas chromatograph-mass spectrometer to detect the content of 1-pentadecaene; (2) judging the activity of Daqu koji worms according to the content of 1-pentadecaene detected in step (1), which can more accurately judge the activity of koji worms in Daqu samples and greatly shorten the time for detecting the activity of koji worms in Daqu samples. Detection by chemical methods requires chemical-related detection equipment, which is extremely expensive. At the same time, for different seasons, the results of chemical experiments may correspond to different states of koji worms, resulting in inaccurate test results. Summary of the invention

[0004] In order to at least overcome the above-mentioned deficiencies in the prior art, the purpose of the present application is to provide a method and system for detecting Aspergillus niger.

[0005] In a first aspect, an embodiment of the present application provides a method for detecting Aspergillus niger, comprising: Obtaining a test piece of music that meets preset standards from the large music to be tested; the preset standards include shape, volume and quality; Kill the test koji blocks with koji insects until all koji insects and koji eggs are killed to form koji blocks without koji insects, and regard the test koji blocks without koji insects as koji blocks with koji insects; Put the insect-free block into the first sealed cavity, and put the insect-containing block into the second sealed cavity; Monitoring gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity; the gas content data includes oxygen content data and carbon dioxide content data; The contents of adults, pupae, larvae and eggs in the Daqu to be detected are calculated based on the gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity.

[0006] In a possible implementation, killing the aspergillus niger in the detected block until all the aspergillus niger and the eggs thereof are killed to form an aspergillus niger block includes: The test block is subjected to a medium temperature pest control treatment at 45° C. to 55° C. or a pest control treatment using an inert gas to form the insect-free block.

[0007] In a possible implementation, calculating the content of adults, pupae, larvae and eggs in the Daqu to be detected according to the gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity includes: Acquire the gas content data, temperature data and air pressure data of the first sealed cavity when it reaches a first preset time after being sealed as the first time reference data, and acquire the gas content data, temperature data and air pressure data of the first sealed cavity when it reaches a second preset time after being sealed as the second time reference data; the second preset time is longer than the first preset time; Acquire the gas content data, temperature data and air pressure data of the second sealed cavity when it reaches a first preset time after being sealed as the first moment monitoring data, and acquire the gas content data, temperature data and air pressure data of the second sealed cavity when it reaches a second preset time after being sealed as the second moment monitoring data; Calculate the ratio of each data in the monitoring data at the first moment to the corresponding data in the reference data at the first moment as the first moment ratio data, and calculate the ratio of each data in the monitoring data at the second moment to the corresponding data in the reference data at the second moment as the second moment ratio data; The first moment ratio data and the second moment ratio data are input into a preset recognition model, and the content of adults, pupae, larvae and eggs output by the recognition model is obtained; the content of adults, pupae, larvae and eggs is expressed by individuals / kg.

[0008] In a possible implementation, the construction of the recognition model includes: Constructing a plurality of bug-free sample song blocks that meet the preset standards; Using at least one of the sample blocks as a reference sample block, and adding different numbers of adults, pupae, larvae and / or eggs into the sample blocks to form a plurality of comparative sample blocks; The reference sample curved block and a plurality of the comparative sample curved blocks are respectively added to different test sealed cavities, and the gas content data, temperature data and air pressure data of the test sealed cavity where the reference sample curved block is located are monitored as reference data, and the gas content data, temperature data and air pressure data of the test sealed cavity where the comparative sample curved block is located are monitored as comparative data; the container states of the test sealed cavity, the first sealed cavity and the second sealed cavity are the same; the container states include volume, inner cavity shape and light-shielding state; Calculating a first preset duration and a second preset duration according to the comparison data; Obtaining the gas content data, temperature data and air pressure data in the reference data when the first preset time period is reached as the first moment reference data, and obtaining the gas content data, temperature data and air pressure data in the reference data when the second preset time period is reached as the second moment reference data; Acquire the gas content data, temperature data and air pressure data in the comparison data when the first preset time is reached as the first moment comparison data, and acquire the gas content data, temperature data and air pressure data in the comparison data when the second preset time is reached as the second moment comparison data; Calculate the ratio of each data in the comparison data at the first moment to the corresponding data in the reference data at the first moment as the first moment sample data, and calculate the ratio of each data in the comparison data at the second moment to the corresponding data in the reference data at the second moment as the second moment sample data; The sample data at the first moment and the sample data at the second moment are used as input data, and the number of adults, pupae, larvae and / or eggs added corresponding to the comparison data is used as output data to train a neural network model to form the recognition model.

[0009] In a possible implementation manner, calculating the first preset duration and the second preset duration according to the comparison data includes: The oxygen content data in all the comparison data are used to generate an oxygen content curve along the time series, the average value of the time corresponding to the first inflection point of all the oxygen content curves is calculated as the first preset time, and the average value of the time corresponding to when all the oxygen content curves reach stability is calculated as the second preset time.

[0010] In a second aspect, the present application also provides a system for detecting Aspergillus niger, comprising: A preparation unit is configured to obtain a test piece of qu that meets a preset standard from the qu to be tested; the preset standard includes shape, volume and quality; An initialization unit is configured to kill all the insects and eggs of the detected song blocks to form an insect-free song block, and to use the detected song blocks that have not been killed as the song blocks with insects; A test unit, configured to place the insect-free song block into a first sealed cavity, and place the insect-infested song block into a second sealed cavity; A monitoring unit configured to monitor gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity; the gas content data includes oxygen content data and carbon dioxide content data; The calculation unit is configured to calculate the content of adults, pupae, larvae and eggs in the Daqu to be detected based on the gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity.

[0011] In a possible implementation manner, the initialization unit is further configured to: The test block is subjected to a medium temperature pest control treatment at 45° C. to 55° C. or a pest control treatment using an inert gas to form the insect-free block.

[0012] In a possible implementation manner, the computing unit is further configured to: Acquire the gas content data, temperature data and air pressure data of the first sealed cavity when it reaches a first preset time after being sealed as the first time reference data, and acquire the gas content data, temperature data and air pressure data of the first sealed cavity when it reaches a second preset time after being sealed as the second time reference data; the second preset time is longer than the first preset time; Acquire the gas content data, temperature data and air pressure data of the second sealed cavity when it reaches a first preset time after being sealed as the first moment monitoring data, and acquire the gas content data, temperature data and air pressure data of the second sealed cavity when it reaches a second preset time after being sealed as the second moment monitoring data; Calculate the ratio of each data in the monitoring data at the first moment to the corresponding data in the reference data at the first moment as the first moment ratio data, and calculate the ratio of each data in the monitoring data at the second moment to the corresponding data in the reference data at the second moment as the second moment ratio data; The first moment ratio data and the second moment ratio data are input into a preset recognition model, and the content of adults, pupae, larvae and eggs output by the recognition model is obtained; the content of adults, pupae, larvae and eggs is expressed by individuals / kg.

[0013] In a possible implementation, the method further includes a construction unit configured to: Constructing a plurality of bug-free sample song blocks that meet the preset standards; Using at least one of the sample blocks as a reference sample block, and adding different numbers of adults, pupae, larvae and / or eggs into the sample blocks to form a plurality of comparative sample blocks; The reference sample curved block and a plurality of the comparative sample curved blocks are respectively added to different test sealed cavities, and the gas content data, temperature data and air pressure data of the test sealed cavity where the reference sample curved block is located are monitored as reference data, and the gas content data, temperature data and air pressure data of the test sealed cavity where the comparative sample curved block is located are monitored as comparative data; the container states of the test sealed cavity, the first sealed cavity and the second sealed cavity are the same; the container states include volume, inner cavity shape and light-shielding state; Calculating a first preset duration and a second preset duration according to the comparison data; Obtaining the gas content data, temperature data and air pressure data in the reference data when the first preset time period is reached as the first moment reference data, and obtaining the gas content data, temperature data and air pressure data in the reference data when the second preset time period is reached as the second moment reference data; Acquire the gas content data, temperature data and air pressure data in the comparison data when the first preset time is reached as the first moment comparison data, and acquire the gas content data, temperature data and air pressure data in the comparison data when the second preset time is reached as the second moment comparison data; Calculate the ratio of each data in the comparison data at the first moment to the corresponding data in the reference data at the first moment as the first moment sample data, and calculate the ratio of each data in the comparison data at the second moment to the corresponding data in the reference data at the second moment as the second moment sample data; The sample data at the first moment and the sample data at the second moment are used as input data, and the number of adults, pupae, larvae and / or eggs added corresponding to the comparison data is used as output data to train a neural network model to form the recognition model.

[0014] In a possible implementation, the construction unit is further configured to: The oxygen content data in all the comparison data are used to generate an oxygen content curve along the time series, the average value of the time corresponding to the first inflection point of all the oxygen content curves is calculated as the first preset time, and the average value of the time corresponding to when all the oxygen content curves reach stability is calculated as the second preset time.

[0015] Compared with the prior art, the present invention has the following advantages and beneficial effects: The present invention provides a new solution for detecting Aspergillus niger, which does not require chemical detection methods, effectively reduces costs, and because the detection environment can be kept stable, the detection impact caused by seasonal changes can be reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings: Figure 1 This is a schematic diagram of the method steps of an embodiment of the present application. DETAILED DESCRIPTION

[0017] To make the purpose, technical scheme and advantages of the embodiment of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described below in conjunction with the drawings in the embodiment of the present application. It should be understood that the drawings in the present application only serve the purpose of explanation and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn in real proportion. The flowchart used in this application shows the operations implemented according to some embodiments of the embodiment of the present application. It should be understood that the operations of the flowchart can be implemented out of sequence, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art can add one or more other operations to the flowchart under the guidance of the content of the present application, or remove one or more operations from the flowchart.

[0018] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0019] Please refer to Figure 1 , is a flow chart of a method for detecting Aspergillus niger provided in an embodiment of the present invention. Further, the method for detecting Aspergillus niger may specifically include the contents described in the following steps S1 to S5.

[0020] S1: Obtaining a test piece that meets a preset standard from the large piece to be tested; the preset standard includes shape, volume and quality; S2: killing all the insects and eggs of the tested koji blocks to form insect-free koji blocks, and treating the tested koji blocks that have not been killed as koji blocks with insects; S3: placing the insect-free block into the first sealed cavity, and placing the insect-containing block into the second sealed cavity; S4: monitoring the gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity; the gas content data includes oxygen content data and carbon dioxide content data; S5: Calculate the contents of adults, pupae, larvae and eggs in the Daqu to be detected according to the gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity.

[0021] When implementing the embodiment of the present application, a technical solution for detecting yeast worms in koji blocks is adopted which does not require chemical preparations and chemical detection equipment. It is necessary to first obtain the test koji blocks, which need to be prepared based on standardized preset standards. The reason is to facilitate subsequent standardized testing. The standardized contents mainly include shape, volume and mass. Generally speaking, they can be prepared into square brick styles. Since the moisture content of Daqu is very high, the control of shape and quality can ensure that the moisture content of different test koji blocks is basically the same.

[0022] In the embodiment of the present application, in order to detect the specific insect state by detecting the block, it is necessary to avoid the influence of microorganisms in the detection block, so it is necessary to construct a block without insects and a block with insects to correct the detection data, wherein the killing of the worms can be carried out by medium temperature killing and / or carbon dioxide killing with less influence on the worm blocks. When the worm-free block and the worm-containing block are respectively placed in the first sealed cavity and the second sealed cavity with the same shape and volume, the worm-free block will continue to ferment in the first sealed cavity, and when the worm-containing block continues to ferment in the second sealed cavity, the worms will also move to produce corresponding gas changes and temperature changes. At this time, the difference in these data can be used to calculate the content of adults, pupae, larvae and eggs. It should be understood that the first sealed cavity and the second sealed cavity can be sealed glass bottles and protected from light by wrapping black tape, and the cost will be much lower than the chemical monitoring means in the prior art. Through the above technical solution, the present application provides a new worm detection scheme, which does not require the use of chemical detection means, effectively reduces the cost, and because the detection environment can remain stable, the detection impact caused by seasonal changes can be reduced.

[0023] In a possible implementation, killing the aspergillus niger in the detected block until all the aspergillus niger and the eggs thereof are killed to form an aspergillus niger block includes: The test block is subjected to a medium temperature pest control treatment at 45° C. to 55° C. or a pest control treatment using an inert gas to form the insect-free block.

[0024] In a possible implementation, calculating the content of adults, pupae, larvae and eggs in the Daqu to be detected according to the gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity includes: Acquire the gas content data, temperature data and air pressure data of the first sealed cavity when it reaches a first preset time after being sealed as the first time reference data, and acquire the gas content data, temperature data and air pressure data of the first sealed cavity when it reaches a second preset time after being sealed as the second time reference data; the second preset time is longer than the first preset time; Acquire the gas content data, temperature data and air pressure data of the second sealed cavity when it reaches a first preset time after being sealed as the first moment monitoring data, and acquire the gas content data, temperature data and air pressure data of the second sealed cavity when it reaches a second preset time after being sealed as the second moment monitoring data; Calculate the ratio of each data in the monitoring data at the first moment to the corresponding data in the reference data at the first moment as the first moment ratio data, and calculate the ratio of each data in the monitoring data at the second moment to the corresponding data in the reference data at the second moment as the second moment ratio data; The first moment ratio data and the second moment ratio data are input into a preset recognition model, and the content of adults, pupae, larvae and eggs output by the recognition model is obtained; the content of adults, pupae, larvae and eggs is expressed by individuals / kg.

[0025] When implementing the embodiment of the present application, a specific scheme for identifying the content of adults, pupae, larvae and eggs through a pre-trained recognition model is adopted; two time nodes for data sampling are set, namely a first preset time and a second preset time. Since the detection block is detected in a sealed container, after a certain period of time, adults and larvae will begin to die on a large scale due to lack of oxygen, and after a period of time, eggs will also begin to die on a large scale, and pupae will also begin to die; therefore, in the embodiment of the present application, the first preset time represents the time node of large-scale death of adults, and the second preset time represents the time node of large-scale death of adults, larvae and eggs, which will show relatively obvious change characteristics in the gas content data, temperature data and air pressure data, so selecting the data corresponding to these two time nodes for analysis can greatly improve the detection accuracy.

[0026] In the embodiment of the present application, since the microorganisms in the song block will also continuously change the monitoring data, in order to reduce the impact of this factor, the monitoring data of the song block with insects and the monitoring data of the song block without insects are calculated by ratio to generate corresponding data for analysis. The recognition model in the embodiment of the present application can adopt various models that can be used for decision-making, such as neural network models, random forest models, etc.

[0027] In a possible implementation, the construction of the recognition model includes: Constructing a plurality of bug-free sample song blocks that meet the preset standards; Using at least one of the sample blocks as a reference sample block, and adding different numbers of adults, pupae, larvae and / or eggs into the sample blocks to form a plurality of comparative sample blocks; The reference sample curved block and a plurality of the comparative sample curved blocks are respectively added to different test sealed cavities, and the gas content data, temperature data and air pressure data of the test sealed cavity where the reference sample curved block is located are monitored as reference data, and the gas content data, temperature data and air pressure data of the test sealed cavity where the comparative sample curved block is located are monitored as comparative data; the container states of the test sealed cavity, the first sealed cavity and the second sealed cavity are the same; the container states include volume, inner cavity shape and light-shielding state; Calculating a first preset duration and a second preset duration according to the comparison data; Obtaining the gas content data, temperature data and air pressure data in the reference data when the first preset time period is reached as the first moment reference data, and obtaining the gas content data, temperature data and air pressure data in the reference data when the second preset time period is reached as the second moment reference data; Acquire the gas content data, temperature data and air pressure data in the comparison data when the first preset time is reached as the first moment comparison data, and acquire the gas content data, temperature data and air pressure data in the comparison data when the second preset time is reached as the second moment comparison data; Calculate the ratio of each data in the comparison data at the first moment to the corresponding data in the reference data at the first moment as the first moment sample data, and calculate the ratio of each data in the comparison data at the second moment to the corresponding data in the reference data at the second moment as the second moment sample data; The sample data at the first moment and the sample data at the second moment are used as input data, and the number of adults, pupae, larvae and / or eggs added corresponding to the comparison data is used as output data to train a neural network model to form the recognition model.

[0028] When implementing the embodiment of the present application, a neural network model is preferably used to construct the recognition model, in which it is necessary to first construct a plurality of insect-free sample blocks that meet the preset standards described above, and then cultivate the corresponding adults, pupae, larvae and eggs through artificial cultivation to add and form comparative sample blocks; since the test sealed cavity in the embodiment of the present application is relatively cheap, multiple groups of tests can be carried out at the same time to obtain more abundant training samples. It should be understood that the overall state of the test sealed cavity, the first sealed cavity and the second sealed cavity should be kept consistent to ensure the consistency of external conditions during the model training process and the use process, so as to improve the detection accuracy.

[0029] In an embodiment of the present application, the data used for training also uses the first preset time length and the second preset time length, which can be calculated based on the specific situation in the comparison data. By sampling at the corresponding moments of the first preset time length and the second preset time length and calculating the ratio, the corresponding sample data can be better obtained, and then the neural network model can be trained.

[0030] In a possible implementation manner, calculating the first preset duration and the second preset duration according to the comparison data includes: The oxygen content data in all the comparison data are used to generate an oxygen content curve along the time series, the average value of the time corresponding to the first inflection point of all the oxygen content curves is calculated as the first preset time, and the average value of the time corresponding to when all the oxygen content curves reach stability is calculated as the second preset time.

[0031] When the embodiment of the present application is implemented, in obtaining the first preset time length and the second preset time length, the first preset time length corresponds to the state when adults and larvae die on a large scale. In the initial stage of the test process, adults and larvae are relatively active, and their oxygen content will decrease at an accelerated rate. When they die on a large scale, the rate of decrease in oxygen content will slow down. At this time, an inflection point will be formed in the oxygen content curve, and the time length corresponding to the inflection point is the first preset time length. During the test process, after all adults, larvae and eggs die, and pupae also die on a large scale, the oxygen content curve will reach a relatively stable state, and the corresponding time length at this time is the second preset time length.

[0032] Based on the same inventive concept, the present application also provides a detection system for Aspergillus niger, comprising: A preparation unit is configured to obtain a test piece of qu that meets a preset standard from the qu to be tested; the preset standard includes shape, volume and quality; An initialization unit is configured to kill all the insects and eggs of the detected song blocks to form an insect-free song block, and to use the detected song blocks that have not been killed as the song blocks with insects; A test unit, configured to place the insect-free song block into a first sealed cavity, and place the insect-infested song block into a second sealed cavity; A monitoring unit configured to monitor gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity; the gas content data includes oxygen content data and carbon dioxide content data; The calculation unit is configured to calculate the content of adults, pupae, larvae and eggs in the Daqu to be detected based on the gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity.

[0033] In a possible implementation manner, the initialization unit is further configured to: The test block is subjected to a medium temperature pest control treatment at 45° C. to 55° C. or a pest control treatment using an inert gas to form the insect-free block.

[0034] In a possible implementation manner, the computing unit is further configured to: Acquire the gas content data, temperature data and air pressure data of the first sealed cavity when it reaches a first preset time after being sealed as the first time reference data, and acquire the gas content data, temperature data and air pressure data of the first sealed cavity when it reaches a second preset time after being sealed as the second time reference data; the second preset time is longer than the first preset time; Acquire the gas content data, temperature data and air pressure data of the second sealed cavity when it reaches a first preset time after being sealed as the first moment monitoring data, and acquire the gas content data, temperature data and air pressure data of the second sealed cavity when it reaches a second preset time after being sealed as the second moment monitoring data; Calculate the ratio of each data in the monitoring data at the first moment to the corresponding data in the reference data at the first moment as the first moment ratio data, and calculate the ratio of each data in the monitoring data at the second moment to the corresponding data in the reference data at the second moment as the second moment ratio data; The first moment ratio data and the second moment ratio data are input into a preset recognition model, and the content of adults, pupae, larvae and eggs output by the recognition model is obtained; the content of adults, pupae, larvae and eggs is expressed by individuals / kg.

[0035] In a possible implementation, the method further includes a construction unit configured to: Constructing a plurality of bug-free sample song blocks that meet the preset standards; Using at least one of the sample blocks as a reference sample block, and adding different numbers of adults, pupae, larvae and / or eggs into the sample blocks to form a plurality of comparative sample blocks; The reference sample curved block and a plurality of the comparative sample curved blocks are respectively added to different test sealed cavities, and the gas content data, temperature data and air pressure data of the test sealed cavity where the reference sample curved block is located are monitored as reference data, and the gas content data, temperature data and air pressure data of the test sealed cavity where the comparative sample curved block is located are monitored as comparative data; the container states of the test sealed cavity, the first sealed cavity and the second sealed cavity are the same; the container states include volume, inner cavity shape and light-shielding state; Calculating a first preset duration and a second preset duration according to the comparison data; Obtaining the gas content data, temperature data and air pressure data in the reference data when the first preset time period is reached as the first moment reference data, and obtaining the gas content data, temperature data and air pressure data in the reference data when the second preset time period is reached as the second moment reference data; Acquire the gas content data, temperature data and air pressure data in the comparison data when the first preset time is reached as the first moment comparison data, and acquire the gas content data, temperature data and air pressure data in the comparison data when the second preset time is reached as the second moment comparison data; Calculate the ratio of each data in the comparison data at the first moment to the corresponding data in the reference data at the first moment as the first moment sample data, and calculate the ratio of each data in the comparison data at the second moment to the corresponding data in the reference data at the second moment as the second moment sample data; The sample data at the first moment and the sample data at the second moment are used as input data, and the number of adults, pupae, larvae and / or eggs added corresponding to the comparison data is used as output data to train a neural network model to form the recognition model.

[0036] In a possible implementation, the construction unit is further configured to: The oxygen content data in all the comparison data are used to generate an oxygen content curve along the time series, the average value of the time corresponding to the first inflection point of all the oxygen content curves is calculated as the first preset time, and the average value of the time corresponding to when all the oxygen content curves reach stability is calculated as the second preset time.

[0037] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0038] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or it can be an electrical, mechanical or other form of connection.

[0039] The units described as separate components may or may not be physically separated. As units, it is obvious that a person of ordinary skill in the art can realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0040] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0041] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a grid device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program code.

[0042] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for detecting Aspergillus niger, characterized in that: include: Obtaining a test song block that meets a preset standard from the large song to be tested; The preset criteria include shape, volume and mass; Kill the test koji blocks with koji insects until all koji insects and koji eggs are killed to form koji blocks without koji insects, and regard the test koji blocks without koji insects as koji blocks with koji insects; Put the insect-free block into the first sealed cavity, and put the insect-containing block into the second sealed cavity; Monitoring gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity; the gas content data includes oxygen content data and carbon dioxide content data; The contents of adults, pupae, larvae and eggs in the Daqu to be detected are calculated based on the gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity.

2. A method for detecting Aspergillus niger according to claim 1, characterized in that: The test block is subjected to killing of Aspergillus niger insects until all Aspergillus niger insects and insect eggs are killed to form an insect-free Aspergillus niger block, which comprises: The test block is subjected to a medium temperature pest control treatment at 45° C. to 55° C. or a pest control treatment using an inert gas to form the insect-free block.

3. A method for detecting Aspergillus niger according to claim 1, characterized in that: The content of adults, pupae, larvae and eggs in the Daqu to be detected is calculated based on the gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity, including: Acquire the gas content data, temperature data and air pressure data of the first sealed cavity when it reaches a first preset time after being sealed as the first time reference data, and acquire the gas content data, temperature data and air pressure data of the first sealed cavity when it reaches a second preset time after being sealed as the second time reference data; the second preset time is longer than the first preset time; Acquire the gas content data, temperature data and air pressure data of the second sealed cavity when it reaches a first preset time after being sealed as the first moment monitoring data, and acquire the gas content data, temperature data and air pressure data of the second sealed cavity when it reaches a second preset time after being sealed as the second moment monitoring data; Calculate the ratio of each data in the monitoring data at the first moment to the corresponding data in the reference data at the first moment as the first moment ratio data, and calculate the ratio of each data in the monitoring data at the second moment to the corresponding data in the reference data at the second moment as the second moment ratio data; The first moment ratio data and the second moment ratio data are input into a preset recognition model, and the content of adults, pupae, larvae and eggs output by the recognition model is obtained; the content of adults, pupae, larvae and eggs is expressed by individuals / kg.

4. A method for detecting Aspergillus niger according to claim 3, characterized in that: The construction of the recognition model includes: Constructing a plurality of bug-free sample song blocks that meet the preset standards; Using at least one of the sample blocks as a reference sample block, and adding different numbers of adults, pupae, larvae and / or eggs into the sample blocks to form a plurality of comparative sample blocks; The reference sample curved block and a plurality of the comparative sample curved blocks are respectively added to different test sealed cavities, and the gas content data, temperature data and air pressure data of the test sealed cavity where the reference sample curved block is located are monitored as reference data, and the gas content data, temperature data and air pressure data of the test sealed cavity where the comparative sample curved block is located are monitored as comparative data; the container states of the test sealed cavity, the first sealed cavity and the second sealed cavity are the same; the container states include volume, inner cavity shape and light-shielding state; Calculating a first preset duration and a second preset duration according to the comparison data; Obtaining the gas content data, temperature data and air pressure data when the first preset time is reached in the reference data as the first moment reference data, and obtaining the gas content data, temperature data and air pressure data when the second preset time is reached in the reference data as the second moment reference data; Acquire the gas content data, temperature data and air pressure data in the comparison data when the first preset time is reached as the first moment comparison data, and acquire the gas content data, temperature data and air pressure data in the comparison data when the second preset time is reached as the second moment comparison data; Calculate the ratio of each data in the comparison data at the first moment to the corresponding data in the reference data at the first moment as the first moment sample data, and calculate the ratio of each data in the comparison data at the second moment to the corresponding data in the reference data at the second moment as the second moment sample data; The sample data at the first moment and the sample data at the second moment are used as input data, and the number of adults, pupae, larvae and / or eggs added corresponding to the comparison data is used as output data to train a neural network model to form the recognition model.

5. A method for detecting Aspergillus niger according to claim 4, characterized in that: Calculating the first preset duration and the second preset duration according to the comparison data includes: The oxygen content data in all the comparison data are used to generate an oxygen content curve along the time series, the average value of the time corresponding to the first inflection point of all the oxygen content curves is calculated as the first preset time, and the average value of the time corresponding to when all the oxygen content curves reach stability is calculated as the second preset time.

6. A system for detecting the large-scale worm, characterized in that: include: A preparation unit is configured to obtain a test piece of song that meets a preset standard from the large song to be tested; The preset criteria include shape, volume and mass; An initialization unit is configured to kill all the insects and eggs of the detected song blocks to form an insect-free song block, and to use the detected song blocks that have not been killed as the song blocks with insects; A test unit, configured to place the insect-free song block into a first sealed cavity, and place the insect-infested song block into a second sealed cavity; A monitoring unit configured to monitor gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity; the gas content data includes oxygen content data and carbon dioxide content data; The calculation unit is configured to calculate the content of adults, pupae, larvae and eggs in the Daqu to be detected based on the gas content data, temperature data and air pressure data of the first sealed cavity and the second sealed cavity.

7. A detection system for Aspergillus niger according to claim 6, characterized in that: The initialization unit is further configured to: The test block is subjected to a medium temperature pest control treatment at 45° C. to 55° C. or a pest control treatment using an inert gas to form the insect-free block.

8. A detection system for Aspergillus niger according to claim 6, characterized in that: The computing unit is further configured to: Acquire the gas content data, temperature data and air pressure data of the first sealed cavity when it reaches a first preset time after being sealed as the first time reference data, and acquire the gas content data, temperature data and air pressure data of the first sealed cavity when it reaches a second preset time after being sealed as the second time reference data; The second preset duration is greater than the first preset duration; Acquire the gas content data, temperature data and air pressure data of the second sealed cavity when it reaches a first preset time after being sealed as the first moment monitoring data, and acquire the gas content data, temperature data and air pressure data of the second sealed cavity when it reaches a second preset time after being sealed as the second moment monitoring data; Calculate the ratio of each data in the monitoring data at the first moment to the corresponding data in the reference data at the first moment as the first moment ratio data, and calculate the ratio of each data in the monitoring data at the second moment to the corresponding data in the reference data at the second moment as the second moment ratio data; The first moment ratio data and the second moment ratio data are input into a preset recognition model, and the content of adults, pupae, larvae and eggs output by the recognition model is obtained; the content of adults, pupae, larvae and eggs is expressed by individuals / kg.

9. A detection system for Aspergillus niger according to claim 8, characterized in that: Also includes build units, configured to: Constructing a plurality of bug-free sample song blocks that meet the preset standards; Using at least one of the sample blocks as a reference sample block, and adding different numbers of adults, pupae, larvae and / or eggs into the sample blocks to form a plurality of comparative sample blocks; The reference sample curved block and a plurality of the comparative sample curved blocks are respectively added to different test sealed cavities, and the gas content data, temperature data and air pressure data of the test sealed cavity where the reference sample curved block is located are monitored as reference data, and the gas content data, temperature data and air pressure data of the test sealed cavity where the comparative sample curved block is located are monitored as comparative data; the container states of the test sealed cavity, the first sealed cavity and the second sealed cavity are the same; the container states include volume, inner cavity shape and light-shielding state; Calculating a first preset duration and a second preset duration according to the comparison data; Obtaining the gas content data, temperature data and air pressure data when the first preset time is reached in the reference data as the first moment reference data, and obtaining the gas content data, temperature data and air pressure data when the second preset time is reached in the reference data as the second moment reference data; Acquire the gas content data, temperature data and air pressure data in the comparison data when the first preset time is reached as the first moment comparison data, and acquire the gas content data, temperature data and air pressure data in the comparison data when the second preset time is reached as the second moment comparison data; Calculate the ratio of each data in the comparison data at the first moment to the corresponding data in the reference data at the first moment as the first moment sample data, and calculate the ratio of each data in the comparison data at the second moment to the corresponding data in the reference data at the second moment as the second moment sample data; The sample data at the first moment and the sample data at the second moment are used as input data, and the number of adults, pupae, larvae and / or eggs added corresponding to the comparison data is used as output data to train a neural network model to form the recognition model.

10. A detection system for Aspergillus niger according to claim 9, characterized in that: The construction unit is further configured to: The oxygen content data in all the comparison data are used to generate an oxygen content curve along the time series, the average value of the time corresponding to the first inflection point of all the oxygen content curves is calculated as the first preset time, and the average value of the time corresponding to when all the oxygen content curves reach stability is calculated as the second preset time.

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