CN111141862B - Method for detecting butyric acid in feed - Google Patents
Method for detecting butyric acid in feed Download PDFInfo
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- CN111141862B CN111141862B CN201911404025.7A CN201911404025A CN111141862B CN 111141862 B CN111141862 B CN 111141862B CN 201911404025 A CN201911404025 A CN 201911404025A CN 111141862 B CN111141862 B CN 111141862B
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Abstract
The invention relates to the technical field of feed detection, in particular to a method for detecting butyric acid in feed, which comprises the following steps: s10: acquiring standard liquid data and a plurality of groups of different data of samples to be detected; s20: generating a model training message according to the standard liquid data and the data of the plurality of samples to be detected; s30: according to the model training message, obtaining a detection result corresponding to each sample data to be detected, and setting a butyric acid detection model according to the detection result; s40: and if the butyric acid detection message is obtained, obtaining the butyric acid detection model, obtaining sample data to be detected from the butyric acid detection message, and inputting the sample data to be detected into the butyric acid detection model to obtain a butyric acid detection result. The method has the effect of improving the efficiency of detecting the butyric acid in the feed while ensuring the precision of detecting the butyric acid in the feed.
Description
Technical Field
The invention relates to the technical field of feed detection, in particular to a method for detecting butyric acid in feed.
Background
At present, people can use the feed to raise pets at home or livestock. Because butyric acid functions to synthesize the short chain fatty acids found in milk fat, butyrate is converted in the epithelial tissues of the animal body to ketone bodies, which are incompletely oxidized butyric acid products including acetoacetate, p-hydroxybutyrate, and acetone. p-hydroxybutyric acid is used efficiently to synthesize milk fat. Butyric acid has a high energy value and also has the possibility of synthesizing lactose, and thus, butyric acid is added to the feed.
In the existing feed, the addition amount of butyric acid is related to regulations, so the content of the butyric acid in the feed is detected before the feed is put. The detection standard can be referred to in appendix A 'high performance liquid chromatography for measuring the content of butyric acid' in 'Q/ISTNX 49-2019 mixed feed additive feeding flavor substance butyric acid'.
The above prior art solutions have the following drawbacks: in this standard, the content of the added reagent in the detection method is not clear, so that the result of the detection is inaccurate, and the detection effect is influenced.
Disclosure of Invention
The invention aims to provide a method for detecting butyric acid in feed, which can improve the efficiency of detecting butyric acid in feed while ensuring the accuracy of detecting butyric acid in feed.
The above object of the present invention is achieved by the following technical solutions:
a method for detecting butyric acid in feed comprises the following steps:
s10: acquiring standard liquid data and a plurality of groups of different data of samples to be detected;
s20: generating a model training message according to the standard liquid data and the data of the plurality of samples to be detected;
s30: obtaining a detection result corresponding to each sample data to be detected according to the model training message, and setting a butyric acid detection model according to the detection result;
s40: and if the butyric acid detection message is obtained, obtaining the butyric acid detection model, obtaining sample data to be detected from the butyric acid detection message, and inputting the sample data to be detected into the butyric acid detection model to obtain a butyric acid detection result.
By adopting the technical scheme, the butyric acid detection model is preset, so that the butyric acid detection model with accurate dosage can be directly used when butyric acid is actually required to be detected, the precision of butyric acid detection in the feed can be further ensured, and the detection efficiency can be improved; through setting up the sample data of waiting to examine of different groups, can make statistics of the testing result that the sample data of waiting to examine of different groups obtained, can guarantee the precision and the success rate that the butyric acid detection model that obtains detects butyric acid in the fodder.
The invention is further configured to: before step S10, the method for detecting butyric acid in feed further comprises:
s11: acquiring preparation raw material data of the sample to be detected;
s12: and setting a plurality of groups of mass parts corresponding to each preparation raw material data according to the preparation raw material data to obtain a plurality of groups of different data of the sample to be tested.
Through adopting above-mentioned technical scheme, through setting up the preparation raw materials data of different mass fractions, can obtain the preparation raw materials of the different sample of waiting to examine of a plurality of groups mass fraction, and then richened the sample data of waiting to examine, can make statistics of the preparation raw materials data of different mass fractions for the butyric acid detection model that follow-up obtained is more accurate.
The invention is further configured to: step S20 includes:
s21: acquiring the quantity of the data of the sample to be detected, and setting the same quantity of the standard solution data according to the quantity;
s22: and generating the model training message after corresponding each group of the standard solution data and one group of the sample data to be tested.
By adopting the technical scheme, the butyric acid detection model can be obtained by counting the corresponding reaction result after each group of standard solution data corresponds to the corresponding sample data to be detected by generating the model training message.
The invention is further configured to: the step S30 includes:
s31: according to the model training message, after each group of standard liquid data reacts with the standard liquid corresponding to a group of the sample data to be detected and the sample liquid to be detected, obtaining a corresponding detection result;
s32: and after the detection result is subjected to statistical analysis, selecting the data of the sample to be detected, which corresponds to the best butyric acid content in the detection result, and setting the butyric acid detection model.
By adopting the technical scheme, the content of the butyric acid can be better detected from the feed by the obtained butyric acid detection model through carrying out statistical analysis on the detection result.
The invention is further configured to: the step S40 includes:
s41: triggering a sample preparation message to be detected according to the butyric acid detection model, wherein the sample preparation message to be detected comprises sample amount data to be detected and additive amount data;
s42: and obtaining the butyric acid detection result after testing according to the data of the sample amount to be tested and the data of the additive amount.
By adopting the technical scheme, when the actual feed is detected for butyric acid, the butyric acid detection model can be conveniently used for detecting the butyric acid in the feed by triggering the preparation message of the sample to be detected.
The second aim of the invention is realized by the following technical scheme:
a butyric acid detection device in feed, the butyric acid detection device in feed comprising:
the test group acquisition module is used for acquiring standard liquid data and a plurality of groups of different data of samples to be tested;
the message triggering module is used for generating a model training message according to the standard liquid data and the data of the plurality of samples to be detected;
the model setting module is used for acquiring a detection result corresponding to each sample data to be detected according to the model training message and setting a butyric acid detection model according to the detection result;
and the detection module is used for acquiring the butyric acid detection model if the butyric acid detection message is acquired, acquiring sample data to be detected from the butyric acid detection message, and inputting the sample data to be detected to the butyric acid detection model to obtain a butyric acid detection result.
By adopting the technical scheme, the butyric acid detection model is preset, so that the butyric acid detection model with accurate dosage can be directly used when butyric acid is actually required to be detected, the precision of butyric acid detection in the feed can be further ensured, and the efficiency during detection can be improved; through setting up the sample data of waiting to examine of different groups, can make statistics of the testing result that the sample data of waiting to examine of different groups obtained, can guarantee the precision and the success rate that the butyric acid detection model that obtains detects butyric acid in the fodder.
The third object of the invention is realized by the following technical scheme:
a computer device comprising a memory, a processor and a computer program stored in said memory and executable on said processor, said processor implementing the steps of the method for detecting butyric acid in a feedstuff as described above when executing said computer program.
The fourth object of the invention is realized by the following technical scheme:
a computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out the steps of the above-mentioned method for detecting butyric acid in a feedstuff.
In summary, the beneficial technical effects of the invention are as follows:
1. by presetting the butyric acid detection model, the butyric acid detection model with accurate dosage can be directly used when butyric acid is actually required to be detected, so that the precision of butyric acid detection in the feed can be ensured, and the efficiency of detection can be improved; through setting up the sample data of waiting to examine of different groups, can make statistics of the testing result that the sample data of waiting to examine of different groups obtained, can guarantee the precision and the success rate that the butyric acid detection model that obtains detects butyric acid in the fodder.
Drawings
FIG. 1 is a flow chart of a method for detecting butyric acid in feed according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating the implementation of step S10 in the method for detecting butyric acid in feedstuff according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating the implementation of step S20 in the method for detecting butyric acid in feedstuff according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating the implementation of step S30 in the method for detecting butyric acid in feedstuff according to an embodiment of the present invention;
FIG. 5 is a test pattern of test 1 in one embodiment of the present invention;
FIG. 6 is a test pattern of experiment 1 in an example of the present invention;
FIG. 7 is a test pattern of experiment 2 in an example of the present invention;
FIG. 8 is a test pattern of trial 2 according to an embodiment of the present invention;
FIG. 9 is a test pattern of trial 3 according to an embodiment of the present invention;
FIG. 10 is a test pattern of experiment 3 in an example of the present invention;
FIG. 11 is a test pattern of test 4 in one embodiment of the present invention;
FIG. 12 is a test pattern of experiment 4 in an example of the present invention;
FIG. 13 is a test pattern of test 5 in an embodiment of the present invention;
FIG. 14 is a test spectrum of test 5 in one embodiment of the present invention;
FIG. 15 is a test pattern of test 6 in an example of the present invention;
FIG. 16 is a test pattern of test 6 in an example of the present invention;
FIG. 17 is a test pattern of test 7 in an example of the present invention;
FIG. 18 is a test pattern of test 7 in an example of the present invention;
FIG. 19 is a test pattern of experiment 8 in an example of the present invention;
FIG. 20 is a test pattern of trial 8 according to an embodiment of the present invention;
FIG. 21 is a flowchart illustrating the implementation of step S40 in the method for detecting butyric acid in feedstuff according to an embodiment of the present invention;
FIG. 22 is a schematic block diagram of a butyric acid detection device in feed according to an embodiment of the present invention;
FIG. 23 is a schematic diagram of a computing device in accordance with an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
The first embodiment is as follows:
in one embodiment, as shown in fig. 1, the invention discloses a method for detecting butyric acid in feed, which specifically comprises the following steps:
s10: and acquiring standard liquid data and a plurality of groups of different data of samples to be detected.
In this example, the standard solution data refers to a standard butyric acid solution against which the test sample is compared. The data of the sample to be tested means data of a reagent of the sample for testing the content of butyric acid.
Specifically, the data of the standard solution is obtained according to the record in the Q/ISTNX 49-2019 mixed feed additive aromatic substance butyric acid for feeding, and the corresponding standard solution is prepared, namely, 0.05g (accurate to 0.0001 g) of butyric acid standard is weighed and placed in a 10mL volumetric flask, dissolved and diluted to scales by methanol, and filtered by a 0.45 mu m filter membrane after being fully shaken up, so that the standard stock solution with the concentration of 5000 mu g/mL is obtained. Diluting the standard stock solution with water to prepare standard solutions with butyric acid concentrations of 500. Mu.g/mL, 1000. Mu.g/mL, 2000. Mu.g/mL, 3000. Mu.g/mL and 4000. Mu.g/mL respectively.
Further, the raw material for preparing the data of the sample to be tested is obtained by referring to the content recorded in the 'Q/ISTNX 49-2019 mixed type feed additive aromatic substance butyric acid for feeding', and a plurality of groups of different data of the sample to be tested are set by setting different mass parts. It can be understood that the different data of the samples to be tested are specifically the same raw materials, but the data of each group of samples to be tested are different in parts by mass.
S20: and generating a model training message according to the standard liquid data and the data of the plurality of samples to be tested.
In the present embodiment, the model training message refers to a message for training a model for testing the content of butyric acid in the feedstuff.
Specifically, a group of sample data to be tested is respectively corresponding to a standard solution data, and then a corresponding model training message is generated for each group of sample data to be tested, so as to train out a specific detection model of raw materials with a certain mass fraction.
S30: and acquiring a detection result corresponding to the data of each sample to be detected according to the model training message, and setting a butyric acid detection model according to the detection result.
In the present embodiment, the butyric acid detection model refers to a model for detecting the content of butyric acid in the feed.
Specifically, the corresponding solutions to be detected are prepared one by one according to the data of the samples to be detected, each group of solutions to be detected is compared with the standard solution to obtain the corresponding detection result, and the mass fraction of the raw material of the sample to be detected with the clearest butyric acid content expression is obtained according to the detection result and is used as the butyric acid detection model.
S40: and if the butyric acid detection message is obtained, obtaining a butyric acid detection model, obtaining sample data to be detected from the butyric acid detection message, and inputting the sample data to be detected into the butyric acid detection model to obtain a butyric acid detection result.
In the present embodiment, the butyric acid detection message refers to a message specifically detecting the content of butyric acid in the feed.
Specifically, when the content of butyric acid in the feed needs to be detected actually, the butyric acid detection model is obtained from the database in which the butyric acid detection model is stored. Further, a corresponding sample to be detected is prepared according to corresponding sample data to be detected in the butyric acid detection model, and then a detection result of butyric acid is obtained according to a detection mode, such as a chromatogram, in the butyric acid detection model.
In the embodiment, by presetting the butyric acid detection model, the butyric acid detection model with accurate dosage can be directly used when butyric acid is actually required to be detected, so that the precision of butyric acid detection in the feed can be ensured, and the detection efficiency can be improved; through setting up the sample data of waiting to examine of different groups, can make statistics of the testing result that the sample data of waiting to examine of different groups obtained, can guarantee the precision and the success rate that the butyric acid detection model that obtains detects butyric acid in the fodder.
In an embodiment, as shown in fig. 2, before step S10, the method for detecting butyric acid in feedstuff further includes:
s11: and acquiring preparation raw material data of the sample to be detected.
In this example, the preparation raw material data refers to a preparation raw material for preparing the sample to be tested.
Specifically, the preparation raw material data is obtained from the 'Q/ISTNX 49-2019 mixed feed additive feeding flavor substance butyric acid'. Wherein, the preparation raw material data comprises: a product to be detected, methanol and hydrochloric acid.
S12: and according to the preparation raw material data, setting a plurality of groups of parts by mass corresponding to each preparation raw material data to obtain a plurality of groups of different data of the sample to be tested.
Specifically, according to the preparation raw material data, a plurality of groups of quality parts corresponding to each preparation raw material data are set, and a plurality of groups of to-be-tested sample data with different quality parts are obtained.
In an embodiment, as shown in fig. 3, in step S20, a model training message is generated according to the standard solution data and the data of the plurality of samples to be tested, which specifically includes the following steps:
s21: and acquiring the quantity of the data of the sample to be detected, and setting the same quantity of standard solution data according to the quantity.
Specifically, according to the number of data of the sample to be tested, a corresponding number of standard solutions are set according to the number for comparison with each group of samples to be tested.
S22: and generating a model training message after corresponding each group of standard liquid data with a group of sample data to be tested.
Specifically, after each group of standard solution data corresponds to a group of sample data to be tested, a model training message is generated.
In an embodiment, as shown in fig. 4, in step S30, that is, according to the model training message, the detection result corresponding to each sample data to be tested is obtained, and the butyric acid detection model is set according to the detection result, which specifically includes the following steps:
s31: and according to the model training information, obtaining a corresponding detection result after each group of standard liquid data, the standard liquid corresponding to the corresponding group of sample data to be detected and the sample liquid to be detected react.
Specifically, a corresponding solution to be tested is prepared based on each set of data of the sample to be tested, and corresponding tests are performed, for example:
sample 1: weighing 0.2g of sample to be detected, adding 50mL of methanol, adding 0.1mL of hydrochloric acid, performing ultrasonic treatment for 10min, adjusting the pH value to be consistent with that of a standard sample, filtering supernate through a 0.45-micrometer filter membrane, and taking filtrate as solution to be detected. The test pattern is shown as follows: fig. 5 and 6.
Sample 2: weighing 0.2g of sample to be detected, adding about 25mL of methanol, carrying out ultrasonic treatment for 10min, fixing the volume to 50mL by using the methanol, taking supernatant, and filtering through a 0.45um filter membrane to obtain filtrate as solution to be detected. The test pattern is shown as follows: fig. 7 and 8.
Sample 3: weighing 0.2g of sample to be detected, adding about 25mL of methanol, adding 0.1mL of hydrochloric acid, performing ultrasonic treatment for 10min, adjusting the pH to be consistent with that of a standard sample, metering volume to 50mL by using methanol, taking supernatant, and filtering by using a 0.45-micrometer filter membrane to obtain filtrate as solution to be detected. The test pattern is shown as follows: fig. 9 and 10.
Sample 4: weighing 0.2g of sample to be detected, adding about 25mL of methanol, adding 0.2mL of hydrochloric acid, performing ultrasonic treatment for 10min, adjusting the pH to be consistent with that of a standard sample, metering volume to 50mL by using methanol, taking supernatant, and filtering by using a 0.45-micrometer filter membrane to obtain filtrate as solution to be detected. The test pattern is shown as follows: fig. 11 and 12.
Sample 5: weighing 0.2g of sample to be detected, adding about 25mL of methanol, adding 0.3mL of hydrochloric acid, performing ultrasonic treatment for 10min, adjusting the pH to be consistent with that of a standard sample, metering volume to 50mL by using methanol, taking supernatant, and filtering by using a 0.45-micrometer filter membrane to obtain filtrate as solution to be detected. The test pattern is shown as follows: fig. 13 and 14.
Sample 6: weighing 0.2g of sample to be detected, adding about 25mL of methanol, adding 0.4mL of hydrochloric acid, performing ultrasonic treatment for 10min, adjusting the pH to be consistent with that of a standard sample, metering volume to 50mL by using methanol, taking supernatant, and filtering by using a 0.45-micrometer filter membrane to obtain filtrate as solution to be detected. The test pattern is shown as follows: fig. 15 and 16.
Sample No. 7: weighing 0.2g of sample to be detected, adding about 25mL of methanol, adding 0.5mL of hydrochloric acid, performing ultrasonic treatment for 10min, adjusting the pH to be consistent with that of a standard sample, metering volume to 50mL by using methanol, taking supernatant, and filtering by using a 0.45-micrometer filter membrane to obtain filtrate as solution to be detected. The test map is shown as follows: fig. 17 and 18.
Sample 8: weighing 0.2g of sample to be detected, adding about 25mL of methanol, adding 1mL of hydrochloric acid, performing ultrasonic treatment for 10min, adjusting the pH value to be consistent with that of a standard sample, using the methanol to fix the volume to 50mL, taking supernatant, filtering through a 0.45um filter membrane, and taking filtrate as solution to be detected. The test pattern is shown as follows: fig. 19 and 20.
S32: and after the detection result is subjected to statistical analysis, selecting the data of the sample to be detected, which corresponds to the best butyric acid content in the detection result, and setting a butyric acid detection model.
Specifically, the test patterns of each group of samples are combined, and the results of the samples 1, 2 and 3 are statistically not significantly different; the results of samples 4, 5, 6, 7 and 8 showed a large difference. According to the analysis of the experimental results, the results of the amounts of the hydrochloric acid added and the hydrochloric acid added are not very different, the results of the amounts of the hydrochloric acid added by more than 0.2mL are very different, the addition amount of the hydrochloric acid in the pretreatment is subjected to supplementary description, and otherwise, the results are greatly different. The hydrochloric acid added in an amount of more than 0.2mL may cause the result of the test to be unqualified, so the butyric acid detection model is set to be that the hydrochloric acid added in an amount of less than 0.2mL.
In an embodiment, as shown in fig. 21, in step S40, that is, if a butyric acid detection message is obtained, obtaining a butyric acid detection model, obtaining sample data to be detected from the butyric acid detection message, and inputting the sample data to be detected to the butyric acid detection model to obtain a butyric acid detection result, specifically, the method includes the following steps:
s41: and triggering a sample preparation message to be detected according to the butyric acid detection model, wherein the sample preparation message to be detected comprises sample amount data to be detected and additive amount data.
Specifically, when the butyric acid in the feed is actually required to be detected, the preparation message of the sample to be detected is triggered according to the butyric acid detection model.
S42: and obtaining a butyric acid detection result after testing according to the data of the amount of the sample to be tested and the data of the amount of the additive.
Specifically, after corresponding sample data is prepared according to the sample amount data to be detected and the additive amount data, a chromatogram is adopted, and a corresponding butyric acid detection result is laterally output.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by functions and internal logic of the process, and should not limit the implementation process of the embodiments of the present invention in any way.
The second embodiment:
in one embodiment, a device for detecting butyric acid in feed is provided, and the device for detecting butyric acid in feed corresponds to the method for detecting butyric acid in feed in the above embodiment one by one. As shown in fig. 22, the device for detecting butyric acid in feedstuff comprises a test group acquisition module 10, a message trigger module 20, a model setting module 30 and a detection module 40. The functional modules are explained in detail as follows:
the test group acquisition module 10 is used for acquiring standard liquid data and a plurality of groups of different data of samples to be tested;
the message triggering module 20 is used for generating a model training message according to the standard liquid data and the data of the plurality of samples to be detected;
the model setting module 30 is used for acquiring a detection result corresponding to each sample data to be detected according to the model training message and setting a butyric acid detection model according to the detection result;
the detection module 40 is configured to, if a butyric acid detection message is obtained, obtain a butyric acid detection model, obtain sample data to be detected from the butyric acid detection message, and input the sample data to be detected to the butyric acid detection model to obtain a butyric acid detection result.
Preferably, the butyric acid detection device in the feed further comprises:
the first raw material preparation module 11 is used for acquiring preparation raw material data of the sample to be detected;
the second raw material preparation module 12 is configured to set a plurality of groups of quality parts corresponding to each preparation raw material data according to the preparation raw material data, so as to obtain a plurality of groups of to-be-inspected sample data with different quality parts.
Preferably, the message triggering module 20 includes:
the setting submodule 21 is used for acquiring the number of the data of the sample to be detected and setting the same number of standard solution data according to the number;
and the message triggering submodule 22 is used for generating a model training message after each group of standard liquid data corresponds to a group of sample data to be tested.
Preferably, the model setting module 30 includes:
the test submodule 31 is used for obtaining a corresponding detection result after each group of standard liquid data, the standard liquid corresponding to a group of sample data to be detected and the sample liquid to be detected react according to the model training information;
and the statistic submodule 32 is used for selecting the data of the sample to be detected, which corresponds to the best butyric acid content in the detection result, to set a butyric acid detection model after the detection result is subjected to statistic analysis.
Preferably, the detection module 40 comprises:
the preparation submodule 41 is used for triggering a preparation message of the sample to be detected according to the butyric acid detection model, wherein the preparation message of the sample to be detected comprises data of the amount of the sample to be detected and data of the amount of the additive;
and the testing submodule 42 is used for obtaining a butyric acid detection result after testing according to the data of the sample amount to be tested and the data of the additive amount.
For the specific limitation of the butyric acid detection device in the feed, reference may be made to the above limitation on the butyric acid detection method in the feed, and details thereof are not repeated herein. All or part of each module in the butyric acid detection device in the feed can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
Example three:
in one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 23. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and the computer program to run on the non-volatile storage medium. The database of the computer device is used for storing the butyric acid detection model. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method for detecting butyric acid in feed.
In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
s10: acquiring standard liquid data and a plurality of groups of different data of samples to be detected;
s20: generating a model training message according to the standard liquid data and the data of a plurality of samples to be detected;
s30: according to the model training message, obtaining a detection result corresponding to each sample data to be detected, and setting a butyric acid detection model according to the detection result;
s40: and if the butyric acid detection message is obtained, obtaining a butyric acid detection model, obtaining sample data to be detected from the butyric acid detection message, and inputting the sample data to be detected into the butyric acid detection model to obtain a butyric acid detection result.
Example four:
in one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, performs the steps of:
s10: acquiring standard liquid data and a plurality of groups of different data of samples to be detected;
s20: generating a model training message according to the standard liquid data and the data of a plurality of samples to be detected;
s30: acquiring a detection result corresponding to the data of each sample to be detected according to the model training message, and setting a butyric acid detection model according to the detection result;
s40: and if the butyric acid detection message is obtained, obtaining a butyric acid detection model, obtaining sample data to be detected from the butyric acid detection message, and inputting the sample data to be detected into the butyric acid detection model to obtain a butyric acid detection result.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It should be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional units and modules is only used for illustration, and in practical applications, the above function distribution may be performed by different functional units and modules as needed, that is, the internal structure of the apparatus may be divided into different functional units or modules to perform all or part of the above described functions.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (4)
1. The method for detecting butyric acid in the feed is characterized by comprising the following steps of:
s11: acquiring preparation raw material data of sample data to be detected;
s12: setting a plurality of groups of mass parts corresponding to each preparation raw material data according to the preparation raw material data to obtain a plurality of groups of different data of the sample to be tested;
s10: obtaining standard liquid data and a plurality of groups of different data of the sample to be detected;
s20: generating a model training message according to the standard solution data and the data of the plurality of samples to be tested, wherein the step S20 comprises the following steps:
s21: acquiring the quantity of the data of the sample to be detected, and setting the same quantity of the standard solution data according to the quantity;
s22: generating the model training message after corresponding each group of the standard solution data to a group of the sample data to be tested;
s30: according to the model training message, obtaining a detection result corresponding to each sample data to be detected, and setting a butyric acid detection model according to the detection result, wherein the step S30 comprises the following steps:
s31: according to the model training message, after each group of standard liquid data and the standard liquid corresponding to a group of the sample data to be detected and the sample liquid to be detected react, obtaining the corresponding detection result;
s32: after the detection result is subjected to statistical analysis, selecting the data of the sample to be detected corresponding to the best butyric acid content in the detection result, and setting the butyric acid detection model;
s40: if a butyric acid detection message is obtained, obtaining the butyric acid detection model, obtaining sample data to be detected from the butyric acid detection message, inputting the sample data to be detected into the butyric acid detection model, and obtaining a butyric acid detection result, wherein the step S40 comprises:
s41: triggering a sample preparation message to be detected according to the butyric acid detection model, wherein the sample preparation message to be detected comprises sample amount data to be detected and additive amount data;
s42: and obtaining the butyric acid detection result after testing according to the data of the amount of the sample to be detected and the data of the amount of the additive.
2. The utility model provides a butyric acid detection device in fodder, its characterized in that butyric acid detection device in fodder includes:
the first raw material preparation module is used for acquiring preparation raw material data of the sample to be detected;
the second raw material preparation module is used for setting a plurality of groups of mass parts corresponding to each preparation raw material data according to the preparation raw material data to obtain a plurality of groups of different sample data to be tested;
the test group acquisition module is used for acquiring standard liquid data and a plurality of groups of different data of the sample to be tested;
the message triggering module is used for generating a model training message according to the standard liquid data and the data of the plurality of samples to be detected, and comprises:
the setting submodule is used for acquiring the number of the data of the sample to be detected and setting the same number of the data of the standard solution according to the number;
the message triggering submodule is used for generating the model training message after each group of the standard solution data corresponds to one group of the sample data to be tested;
the model setting module is used for acquiring a detection result corresponding to each sample data to be tested according to the model training message and setting a butyric acid detection model according to the detection result, and the model setting module comprises:
the test submodule is used for obtaining a corresponding detection result after each group of standard liquid data, the standard liquid corresponding to a group of sample data to be detected and the sample liquid to be detected react according to the model training information;
the statistic submodule is used for selecting sample data to be detected corresponding to the best content of butyric acid in the detection result and setting a butyric acid detection model after the detection result is subjected to statistic analysis;
the detection module is used for acquiring the butyric acid detection model if butyric acid detection information is acquired, acquiring sample data to be detected from the butyric acid detection information, and inputting the sample data to be detected into the butyric acid detection model to obtain a butyric acid detection result, and comprises:
the preparation submodule is used for triggering preparation information of the sample to be detected according to the butyric acid detection model, wherein the preparation information of the sample to be detected comprises data of the sample amount to be detected and data of the additive amount;
and the test submodule is used for obtaining a butyric acid detection result after testing according to the data of the sample amount to be tested and the data of the additive amount.
3. A computer device comprising a memory, a processor and a computer program stored in said memory and executable on said processor, wherein said processor when executing said computer program performs the steps of the method for detecting butyric acid in a feed according to claim 1.
4. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method for detecting butyric acid in a feedstuff according to claim 1.
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