CN115438754A - Food safety detection method, system and storage medium - Google Patents
Food safety detection method, system and storage medium Download PDFInfo
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Abstract
The application relates to the technical field of food management and control, in particular to a food safety detection method, a system and a storage medium, wherein the method comprises the following steps: obtaining a food to be detected; acquiring a corresponding target detection item according to the type of the food to be detected; detecting the target detection item according to a preset detection standard to obtain a detection result; acquiring an abnormal detection item according to the detection result, and acquiring corresponding processing information according to the abnormal detection item; analyzing the processing information according to preset process indexes to obtain a target process; according to the target process, detection feedback information is obtained, and the food safety detection method, the food safety detection system and the storage medium can improve the detection effect of food.
Description
Technical Field
The application relates to the technical field of food management and control, in particular to a food safety detection method, a food safety detection system and a storage medium.
Background
Food inspection refers to a subject for studying and evaluating food quality and changes thereof, which is based on some basic theories of physics, chemistry and biochemistry and various technologies, and checks the food quality according to revised technical standards to ensure the qualified product quality.
At present, food detection link, some food need detect each manufacturing procedure's semi-manufactured goods and final finished product in food formation process because the detection standard requires, need the manual work to record to unqualified semi-manufactured goods and finished product, because artificial subjective reason, inevitably can have the careless omission in the record process, lead to can't trace back unqualified product, detection effect is not good.
Disclosure of Invention
In order to improve the detection effect of food, the application provides a food safety detection method, a food safety detection system and a storage medium.
In a first aspect, the present application provides a food safety detection method, including the following steps:
obtaining a food to be detected;
acquiring a corresponding target detection item according to the type of the food to be detected;
detecting the target detection item according to a preset detection standard to obtain a detection result;
acquiring an abnormal detection item according to the detection result, and acquiring corresponding processing information according to the abnormal detection item;
analyzing the processing information according to preset process indexes to obtain a target process;
and acquiring detection feedback information according to the target process.
By adopting the technical scheme, the target detection item required to be detected is acquired according to the specific type of the food to be detected, the target detection item is analyzed and detected by combining the preset detection standard, and then the corresponding detection result is acquired, the processing information of the food to be detected is acquired through the abnormal detection item in the detection result, the processing information is further contrasted and analyzed with the corresponding preset process index, and then the target process of the abnormal detection item in the processing information is obtained, and the detection feedback information of the food to be detected is acquired according to the target process, so that the detection effect of the food is improved.
Optionally, the preset detection standard includes a finished product detection standard, the target detection item includes a semi-finished product detection item and a finished product detection item, and detecting the target detection item according to the preset detection standard and acquiring the detection result includes the following steps:
judging whether the finished product detection item meets the finished product detection standard or not;
if the finished product detection item does not meet the finished product detection standard, acquiring the abnormal detection item as the detection result according to the finished product detection item;
and if the finished product detection item meets the preset detection standard, analyzing the semi-finished product detection item to obtain the detection result.
By adopting the technical scheme, the semi-finished product detection items of the food to be detected are detected and analyzed on the basis of the finished product detection items, so that the food detection efficiency is improved.
Optionally, the preset detection standard includes a semi-finished product detection standard, and the analyzing the semi-finished product detection item and obtaining the detection result includes the following steps:
judging whether the semi-finished product detection item meets the semi-finished product detection standard or not;
and if the semi-finished product detection item meets the semi-finished product detection standard, acquiring the abnormal detection item as the detection result according to the semi-finished product detection item.
By adopting the technical scheme, the semi-finished product detection items in the food to be detected are analyzed and judged, so that the problem of the semi-finished product in the unqualified product can be traced conveniently.
Optionally, the processing information includes a target processing procedure, and analyzing the processing information according to a preset procedure index to obtain the target procedure includes the following steps:
judging whether the target machining process accords with the preset process index or not;
and if the target machining process does not meet the preset process index, acquiring a corresponding abnormal process as the target process according to the target machining process.
By adopting the technical scheme, the target processing procedure in the abnormal detection item is analyzed according to the preset procedure index, so that the target processing procedure of the defective product is conveniently acquired.
Optionally, the obtaining, according to the target process, detection feedback information includes the following steps:
acquiring corresponding abnormal food according to the target process;
acquiring production batch information according to the abnormal food;
judging whether the abnormal food is from the same production batch according to the production batch information;
and if the abnormal food is from the same production batch, acquiring a production batch number according to the production batch information, and taking the target process and the production batch number as the detection feedback information.
By adopting the technical scheme, whether the abnormal food is from the same production batch is judged based on the production batch information, and the abnormal food is traced according to the corresponding production batch number, so that the centralized production batch of the abnormal food is conveniently obtained.
Optionally, the obtaining of the detection feedback information according to the target process includes the following steps:
acquiring corresponding abnormal food according to the target process;
acquiring production line information according to the abnormal food;
judging whether the abnormal food is from the same production line according to the production line information;
if the abnormal food comes from the same production line, acquiring a production line number according to the production line information, and taking the target process and the production line number as the detection feedback information;
and if the abnormal food comes from different production lines, acquiring and analyzing the quantity of the abnormal food, and acquiring the detection feedback information.
By adopting the technical scheme, whether the abnormal food is from the same production line is judged based on the production line information, and the production outlet of the abnormal food is traced according to the corresponding production line number, so that the centralized production line of the abnormal food is convenient to obtain.
Optionally, the obtaining and analyzing the number of abnormal foods, and the obtaining the detection feedback information includes the following steps:
acquiring the quantity of the abnormal foods of the same production batch number according to the production batch information;
and selecting the production batch number with the largest number of the abnormal foods as the detection feedback information.
By adopting the technical scheme, the production batch number with the largest number of abnormal foods is recorded and is used as the final test feedback information, so that the production batches of most abnormal foods can be traced.
Optionally, the obtaining and analyzing the number of abnormal foods, and the obtaining the detection feedback information further includes the following steps:
acquiring the quantity of the abnormal food of the same production line number according to the production line information;
and selecting the production line number with the largest number of the abnormal foods as the detection feedback information.
By adopting the technical scheme, the production line number with the largest quantity of abnormal foods is recorded and is used as the final test feedback information, so that the production line of most unqualified products can be traced.
In a second aspect, the present application further provides a food safety detection system, including:
the acquisition module is used for acquiring the food to be detected;
the classification module is used for acquiring a corresponding target detection item according to the type of the food to be detected;
the detection module is used for detecting the target detection item according to a preset detection standard and acquiring a detection result;
the query module is used for acquiring an abnormal detection item according to the detection result, acquiring corresponding processing information according to the abnormal detection item, and analyzing the processing information according to a preset process index to acquire a target process;
and the feedback module is used for acquiring detection feedback information according to the target process.
By adopting the technical scheme, the classification module classifies the food to be detected acquired by the acquisition module, acquires a target detection item to be detected, analyzes the detection target detection item according to a preset detection standard by combining the detection module, further acquires a corresponding detection result, so that the query module can acquire processing information of the food to be detected through an abnormal detection item in the detection result according to the detection result, further performs contrastive analysis on the contrasted processing information and a corresponding preset process index, further acquires a target process of the abnormal detection item in the processing information, and finally the feedback module acquires detection feedback information of the food to be detected according to the target process acquired by the query module, thereby improving the detection effect of the food.
In a third aspect, the present application provides a computer-readable storage medium, in which a computer program is stored, and when the computer program is loaded and executed by a processor, a food safety detection method as described above is adopted.
By adopting the technical scheme, the food safety detection method generates the computer program, the computer program is stored in the computer readable storage medium to be loaded and executed by the processor, and the computer program can be conveniently read and stored through the computer readable storage medium.
To sum up, the application comprises the following beneficial technical effects: according to the specific type of the food to be detected, a target detection item needing to be detected is obtained, the target detection item is analyzed and detected by combining a preset detection standard, a corresponding detection result is obtained, the processing information of the food to be detected is obtained through an abnormal detection item in the detection result, the processing information is further compared and analyzed with a corresponding preset process index, a target process of the abnormal detection item in the processing information is obtained, the detection feedback information of the food to be detected is obtained according to the target process, and therefore the detection effect of the food is improved.
Drawings
Fig. 1 is a schematic flow chart of steps S101 to S106 in a food safety detection method according to the present application.
Fig. 2 is a schematic flow chart of steps S201 to S203 in the food safety detection method according to the present application.
Fig. 3 is a schematic flowchart of steps S301 to S302 in the food safety detection method according to the present application.
Fig. 4 is a schematic flowchart of steps S401 to S402 in a food safety detection method according to the present application.
Fig. 5 is a schematic flowchart of steps S501 to S504 in a food safety detection method according to the present application.
Fig. 6 is a schematic flow chart of steps S601 to S605 in the food safety detection method according to the present application.
Fig. 7 is a schematic flow chart illustrating steps S701 to S702 in the food safety inspection method according to the present application.
Fig. 8 is a schematic flowchart of steps S801 to S802 in the food safety detection method according to the present application.
Fig. 9 is a block diagram of a food safety detection system according to the present application.
Description of reference numerals:
1. an acquisition module; 2. a classification module; 3. a detection module; 4. a query module; 5. and a feedback module.
Detailed Description
The present application is described in further detail below with reference to figures 1-9.
The embodiment of the application discloses a food safety detection method, which comprises the following steps of:
s101, obtaining a food to be detected;
s102, acquiring a corresponding target detection item according to the type of the food to be detected;
s103, detecting a target detection item according to a preset detection standard to obtain a detection result;
s104, acquiring an abnormal detection item according to the detection result, and acquiring corresponding processing information according to the abnormal detection item;
s105, analyzing the processing information according to preset process indexes to obtain a target process;
and S106, acquiring detection feedback information according to the target process.
In this embodiment, the target detection items are different according to different types of food to be detected, and the target detection items refer to items that need to be detected by the food to be detected according to related food safety regulations, and can be classified according to food detection: sorting according to the production process sequence, sorting according to the inspection method and sorting according to the inspection purpose;
wherein, the general sequence of the production process sequence classification is as follows: the method comprises the steps of carrying out feeding inspection, wherein inspection objects are purchased raw materials, auxiliary materials, packaging materials and semi-finished products, and the purpose is to prevent unqualified products from entering a warehouse; process (procedure) inspection, wherein an inspection object is a semi-finished product of each procedure in the product forming process, and the purpose is to ensure that unqualified semi-finished products of each procedure do not flow into the condition of the execution of the inspection process procedure of the next procedure; and (4) final (finished product) inspection, wherein the inspection object is comprehensive inspection before finished products are put in storage, the purpose is to ensure that unqualified products do not leave a factory, a qualified certificate is issued for qualified products, and the unqualified products are reworked, repaired, degraded or scrapped.
It should be noted that the semi-finished product refers to an intermediate product which has been subjected to a certain production process and is qualified after inspection, but is not finally manufactured into a finished product, the semi-finished product is divided into a self-made semi-finished product and an outsourcing semi-finished product, and the self-made semi-finished product is a semi-finished product which is produced and processed by an enterprise, is qualified after inspection, is delivered to a semi-finished product warehouse and needs to be processed continuously. The semi-finished food comprises bean curd, soybean milk, raw chaos, raw dumplings, raw noodles, raw steamed bread, etc.
Classifying according to a detection method, performing sensory test, detecting and evaluating the food quality by means of human sensory organ functions and time experience, and performing visual test, olfactory test, auditory test, tactile test and the like; the physical and chemical inspection, which is to detect and evaluate the food quality by physical and chemical means with the help of various instruments and reagents, is divided into a physical inspection method (physical chemical testing instrument test), a chemical inspection method (classical analysis method) and a biological inspection method, wherein the biological inspection method is to measure the performance of food, food additives, packaging and the like which are harmful to the health and safety of human bodies by using instruments, reagents and animals.
Classified according to the purpose of the test, production test (seller test): self-delivery inspection, which is to obtain the capability of detecting that the food production license has, or entrust delivery inspection, which is to obtain the license but has no detection capability; acceptance and inspection (buyer inspection): the purpose is to maintain the interests of the user and the customers, ensure the food purchased is qualified, find problems and feed back quality problems in time; third party test (fair test): notarization and authentication are carried out to maintain the benefits of all parties.
Step S103 in this embodiment, according to the classification method for food detection, a target detection item of a food to be detected is detected, and for the attribute of the target detection item matching a corresponding detection method, the detection method for the food is roughly divided into: sensory evaluation, checking whether the food has color abnormality with naked eyes, smelling the food with nose to find whether the food has peculiar smell, trying the taste of the food with mouth, and the like; detecting physical and chemical indexes, namely judging whether the food is qualified or not according to a detection result by using a method of a chemical experiment; and (4) detecting microbial indexes, namely checking whether the number of pathogenic bacteria contained in the food is qualified or not by using a special microbial detection method. And finally, acquiring a corresponding detection result according to the detection method.
Step S104 to step S105 in this embodiment, according to the abnormal detection item in the detection result, processing information for producing the food to be detected is obtained, where the processing information refers to flow information of the food to be detected in the processing production process, and according to the processing information, a target process corresponding to the abnormal detection item is obtained, where the target process refers to a processing process corresponding to the abnormal detection item occurring in the detection process.
Step S106, in this embodiment, according to the obtained target process, the production place and the related processing information of the food to be detected corresponding to the abnormal detection item can be traced back, and the corresponding detection feedback information is obtained, and the specific information of the food to be detected can be traced back through the test feedback information.
In the food safety detection method, a target detection item needing to be detected is acquired according to the specific type of food to be detected, the target detection item is analyzed and detected by combining a preset detection standard, a corresponding detection result is further acquired, processing information of the food to be detected is acquired through an abnormal detection item in the detection result, the comparison processing information and a corresponding preset process index are further subjected to comparison analysis, a target process of the abnormal detection item in the processing information is further acquired, detection feedback information of the food to be detected is acquired according to the target process, and therefore the detection effect of the food is improved.
In one implementation manner of this embodiment, as shown in fig. 2, the preset detection criteria include a finished product detection criterion, the target detection item includes a semi-finished product detection item and a finished product detection item, and step S103 includes the following steps:
s201, judging whether the finished product detection item meets the finished product detection standard;
s202, if the finished product detection item does not accord with the finished product detection standard, acquiring an abnormal detection item as a detection result according to the finished product detection item;
and S203, if the finished product detection item meets the preset detection standard, analyzing the semi-finished product detection item to obtain a detection result.
In practical application, the finished product detection item refers to an item to be detected when food finishes all processing procedures and is put in storage or before leaving a factory, and the finished product detection standard refers to various safety standards required to be met after food processing and manufacturing are finished; the semi-finished product detection item is a detection item carried out on each processing procedure in the product forming process, and aims to ensure that unqualified semi-finished products in each procedure cannot flow into the next procedure, prevent the unqualified semi-finished products from being processed continuously and unqualified in batches, and ensure the normal production order.
For example, one of the inspection standards for ice cream products is a package sealing standard: (1) whether the temperature of a sealing knife of the packaging machine meets the specified requirements or not; (2) whether a resistor of a sealing knife of the packaging machine has a fault or not; (3) whether the longitudinal seals of the packaging films are aligned and deflected or not; (4) whether the packaging film is folded or wrinkled; (5) if the transverse and longitudinal sealing wheels have faults, the packaging film can not be clamped or compressed. The problem of untight seal is caused by detecting the ice cream finished product detection items, the detection items do not accord with the corresponding package sealing standard, and the abnormal detection items with untight seal are used as detection results after the inspection that the transverse and longitudinal sealing wheels have faults and can not clamp or press the packaging film.
The finished product detection items before delivery of the ice cream bar meet the corresponding finished product detection standards, and the semi-finished product detection items of the raw and auxiliary materials such as sugar and edible vegetable oil used in the ice cream bar are further detected and analyzed, so that the semi-finished product detection items of the food to be detected are detected and analyzed on the basis of the finished product detection items of the food to be detected, and the food detection efficiency is improved.
In one implementation manner of this embodiment, as shown in fig. 3, the preset detection criteria includes a semi-finished product detection criteria, and step S203 includes the following steps:
s301, judging whether the semi-finished product detection item meets the semi-finished product detection standard or not;
and S302, if the semi-finished product detection item accords with the semi-finished product detection standard, acquiring an abnormal detection item as a detection result according to the semi-finished product detection item.
In practical application, the semi-finished product inspection standard refers to a safety standard which is required to be met by a semi-finished product in each processing procedure, and the semi-finished product inspection is also called process inspection, and generally comprises three modes of first-piece inspection, itinerant inspection (flow inspection) and finished inspection.
The first piece detection is to detect the first or former products at the beginning of production (working or changing) or after the process factors are adjusted (adjusting process, tool, equipment and the like) so as to find out the system factors in the process as early as possible and prevent the products from being scrapped in batches; the inspection tour, the product quality and processing craft of the relevant process are supervised and detected at certain time interval in the production field by the inspector, the key point of the inspection tour is the key process, the inspector should be familiar with the quality requirement, detection method and processing craft of the process quality control point in the responsible detection range, and whether the processed product meets the requirement specified by the quality requirement detection instruction and is responsible for supervising the process execution condition, and the inspection tour is the special storage and treatment work of the qualified product, unqualified product and waste product after detection; and the completion detection is to comprehensively detect a batch of finished products in one process, and the purpose of the completion detection is to pick out unqualified products and make the qualified products continuously flow into the next process.
For example, finished product detection items of bagged cooked beef all accord with corresponding finished product detection standards, in order to ensure the quality safety of the cooked beef after leaving the factory, the raw beef semi-finished product is further detected, the raw beef semi-finished product to be processed is subjected to sensory, physicochemical and microorganism related detection, and when the total number of bacterial colonies of the raw beef is found not to accord with the corresponding semi-finished product detection standard in the microorganism detection of the raw beef, the abnormal detection item of the total number of the microbial colonies is taken as a detection result, so that the semi-finished product detection item in the food to be detected is judged through analysis, and the problem tracing of the semi-finished product in the unqualified product is facilitated.
In one implementation of this embodiment, as shown in fig. 4, the processing information includes a target processing procedure, and step S105 includes the following steps:
s401, judging whether the target machining process accords with preset process indexes;
s401, if the target machining process does not meet the preset process index, acquiring a corresponding abnormal process as the target process according to the target machining process.
In practical applications, the target processing procedure refers to a processing procedure corresponding to various abnormal detection items appearing in the product in the processing process, the preset procedure index refers to an index which the product should meet in each processing procedure, and the target procedure refers to a specific processing procedure corresponding to the abnormal detection item.
For example, in the detection of raw beef semi-finished products, the target processing procedure for detecting microorganisms does not meet the corresponding standard, and is available according to the relevant safety standard, and the microbial contamination of meat products is probably caused by several reasons: 1. the livestock are sick livestock and sick livestock before slaughtering; 2. the cutting tools, chopping boards and appliances used in the meat processing process are not clean, the disinfection is not in place, and the raw meat and the cooked meat are cross-polluted; 3. bad sanitary condition, mosquito and fly breeding; 4. exposed to air during the production process and polluted by microorganisms in the air. The inspection confirms that due to the fact that cutters, chopping blocks and appliances used in the meat processing process are not clean, disinfection is not in place, and raw and cooked cross contamination is caused, abnormal procedures in the appliance processing link are taken as target procedures, the target processing procedures in the abnormal detection items are analyzed according to preset procedure indexes, and the target processing procedures of defective products are convenient to obtain.
In one implementation of this embodiment, as shown in fig. 5, step S106 includes the following steps:
s501, acquiring corresponding abnormal food according to a target process;
s502, obtaining production batch information according to abnormal food;
s503, judging whether the abnormal food is from the same production batch according to the production batch information;
and S504, if the abnormal food comes from the same production batch, acquiring a production batch number according to the production batch information, and taking the target process and the production batch number as detection feedback information.
In practical applications, the abnormal food refers to a food processed in a target processing procedure, the production lot information refers to factory packaging information such as a production date and a production lot number of the abnormal food, the production lot number includes a production line number of the abnormal food, and the production line number includes a team group number.
For example, 20220722-06-01, wherein 20220722 means the date of production is 2022 year 7 month 22 number, 06 means the production lot number is lot 6, 01 means the group number of class 1. 6 groups of abnormal foods are obtained through the target process, and the production batch information of 20220419-06-01, 20220419-06-01 and 20220419-06-01 is obtained through the abnormal foods, so that the production batch numbers of the 6 groups of abnormal foods are all 06, the batch numbers are all 01, the abnormal foods are all derived from the 6 th batch of the 1 st batch, the 06-01 batches are used as test feedback information, and workers can know that the abnormal foods are mainly concentrated in the 6 th production batch and are produced from the 1 st batch according to the 06-01 batch information, so that whether the abnormal foods are derived from the same production batch is judged based on the production batch information, and the abnormal foods are traced back according to the corresponding production batch numbers, thereby facilitating the concentrated production batch of the abnormal foods.
In one implementation manner of this embodiment, as shown in fig. 6, step S106 further includes the following steps:
s601, acquiring corresponding abnormal food according to the target process;
s602, acquiring production line information according to abnormal food;
s603, judging whether the abnormal food is from the same production line according to the production line information;
s604, if the abnormal food is from the same production line, acquiring a production line number according to the production line information, and taking the target process and the production line number as detection feedback information;
and S605, if the abnormal food comes from different production lines, acquiring and analyzing the quantity of the abnormal food, and acquiring detection feedback information.
In practical use, the line information refers to information on the production line of abnormal food processing, for example, 5 groups of abnormal foods are obtained through a target process, and the corresponding line information is 20220419-01-01, and 20220407-01-01, respectively, wherein 20220419 in 20220419-01 refers to a production line number of 4 months 19 at 2022 years, and 01-01 refers to a production line number of 1 st station in the 1 st line; therefore, the abnormal food is mainly concentrated on the 1 st station of the 1 st assembly line in the processing process, 01-01 is used as detection feedback information, whether the abnormal food is from the same production line or not is judged based on the production line information, and the production place of the abnormal food is traced according to the corresponding production line number, so that the concentrated production line of the abnormal food is convenient to obtain.
In one implementation of this embodiment, as shown in fig. 7, step S605 includes the following steps:
s701, acquiring the quantity of abnormal foods of the same production batch number according to the production batch information;
s702, selecting the production batch number with the largest abnormal food quantity as detection feedback information.
In practical use, 10 sets of abnormal food products are obtained through the target process, and the corresponding production lot numbers are 20220419-01, 20220407-01, 20220419-02, 20220419-03, and 20220419-03, respectively, wherein 20220419-01 refers to a production lot number of 2022 years and 4 months 19, 01 refers to a production lot number of the abnormal food product, and thus, the abnormal food product with the production lot number 01 is 5 sets, the abnormal food product with the production lot number 02 is 3 sets, and the abnormal food product with the production lot number 03 is 2 sets, so that the production lot number 01 is used as test feedback information, so that a worker can know that the abnormal food products appear mainly concentrated on the production lot number 01, and record the production lot number with the largest number of abnormal food products, and can be used as final test feedback information, thereby facilitating the production of most abnormal food products.
In one implementation manner of this embodiment, as shown in fig. 8, step S605 further includes the following steps:
s801, acquiring the number of abnormal foods of the same production line number according to the production line information;
and S802, selecting the production line number with the most abnormal food quantity as detection feedback information.
In practical use, 10 groups of abnormal food products are obtained through a target process, the corresponding production lot numbers are 20220419-01-01, 20220407-01-01, 20220419-01-02, 20220419-01-03 and 20220419-01-03 respectively, wherein in 20220419-01, 20419 refers to No. 4/19 of the delivery date of 2022 years, and 01-01 refers to the production line number of the abnormal food products, and accordingly, the abnormal food products with the production line numbers 01-01 are 5 groups, the abnormal food products with the production line numbers 01-02 are 3 groups, and the abnormal food products with the production line numbers 01-03 are 2 groups, so that the production line numbers 01-01 are used as test feedback information, and accordingly, a worker can be made aware of the abnormal food products mainly focusing on the production line numbers 01-01, the number of the abnormal food products is recorded, and the number of the most abnormal food products is used as final test line number feedback information, thereby being beneficial to the final product tracing.
The application also provides a food safety detection system, as shown in fig. 9, which includes an obtaining module 1, a classifying module 2, a detecting module 3, an inquiring module 4 and a feedback module 5, wherein the obtaining module 1 is used for obtaining food to be detected; the classification module 2 is used for acquiring a corresponding target detection item according to the type of the food to be detected; the detection module 3 is used for detecting a target detection item according to a preset detection standard and acquiring a detection result; the query module 4 is used for acquiring an abnormal detection item according to a detection result, acquiring corresponding processing information according to the abnormal detection item, and analyzing the processing information according to a preset process index to acquire a target process; the feedback module 5 is used for acquiring detection feedback information according to the target process.
The classification module 2 classifies the food to be detected acquired by the acquisition module 1, acquires a target detection item to be detected, analyzes the detected target detection item according to a preset detection standard by combining the detection module 3, further acquires a corresponding detection result, so that the query module 4 acquires processing information of the food to be detected through an abnormal detection item in the detection result according to the detection result, further performs comparison analysis on the comparison processing information and a corresponding preset process index, and further acquires a target process of the abnormal detection item in the processing information, and finally the feedback module 5 acquires detection feedback information of the food to be detected according to the target process acquired by the query module 4, thereby improving the detection effect of the food.
The embodiment of the application also discloses a computer readable storage medium, and the computer readable storage medium stores a computer program, wherein when the computer program is executed by a processor, any one of the food safety detection methods in the above embodiments is adopted.
The computer program may be stored in a computer readable medium, the computer program includes computer program code, the computer program code may be in a source code form, an object code form, an executable file or some intermediate form, and the like, the computer readable medium includes any entity or device capable of carrying the computer program code, a recording medium, a usb disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a Read Only Memory (ROM), a Random Access Memory (RAM), an electrical carrier signal, a telecommunication signal, a software distribution medium, and the like, and the computer readable medium includes but is not limited to the above components.
The food safety detection method in the above embodiments is stored in the computer-readable storage medium through the computer-readable storage medium, and is loaded and executed on the processor, so as to facilitate storage and application of the method.
The above are preferred embodiments of the present application, and the scope of protection of the present application is not limited thereto, so: all equivalent changes made according to the structure, shape and principle of the present application shall be covered by the protection scope of the present application.
Claims (9)
1. A food safety detection method is characterized by comprising the following steps:
obtaining a food to be detected;
acquiring a corresponding target detection item according to the type of the food to be detected;
detecting the target detection item according to a preset detection standard to obtain a detection result;
acquiring an abnormal detection item according to the detection result, and acquiring corresponding processing information according to the abnormal detection item;
analyzing the processing information according to preset process indexes to obtain a target process;
acquiring corresponding abnormal food according to the target process;
acquiring production line information according to the abnormal food;
judging whether the abnormal food is from the same production line or not according to the production line information;
if the abnormal food comes from the same production line, acquiring a production line number according to the production line information, and taking the target process and the production line number as the detection feedback information;
and if the abnormal foods come from different production lines, acquiring and analyzing the quantity of the abnormal foods and acquiring the detection feedback information.
2. The food safety detection method according to claim 1, wherein the preset detection criteria include finished product detection criteria, the target detection item includes semi-finished product detection items and finished product detection items, and the detection of the target detection item according to the preset detection criteria to obtain the detection result includes the following steps:
judging whether the finished product detection item meets the finished product detection standard or not;
if the finished product detection item does not accord with the finished product detection standard, acquiring the abnormal detection item as the detection result according to the finished product detection item;
and if the finished product detection item meets the preset detection standard, analyzing the semi-finished product detection item to obtain the detection result.
3. The food safety detection method according to claim 2, wherein the preset detection standard comprises a semi-finished product detection standard, and the analyzing the semi-finished product detection item to obtain the detection result comprises the following steps:
judging whether the semi-finished product detection item meets the semi-finished product detection standard or not;
and if the semi-finished product detection item meets the semi-finished product detection standard, acquiring the abnormal detection item as the detection result according to the semi-finished product detection item.
4. The food safety detection method according to claim 1, wherein the processing information includes a target processing procedure, and the step of analyzing the processing information according to a preset procedure index to obtain the target procedure includes the steps of:
judging whether the target machining process accords with the preset process index or not;
and if the target machining process does not meet the preset process index, acquiring a corresponding abnormal process as the target process according to the target machining process.
5. The food safety detection method according to claim 1, wherein the step of obtaining detection feedback information according to the target process comprises the following steps:
acquiring corresponding abnormal food according to the target process;
acquiring production batch information according to the abnormal food;
judging whether the abnormal food is from the same production batch according to the production batch information;
and if the abnormal food is from the same production batch, acquiring a production batch number according to the production batch information, and taking the target process and the production batch number as the detection feedback information.
6. The food safety detection method according to claim 5, wherein the step of obtaining and analyzing the abnormal food quantity and obtaining the detection feedback information comprises the following steps:
acquiring the quantity of the abnormal food of the same production batch number according to the production batch information;
and selecting the production batch number with the largest number of the abnormal foods as the detection feedback information.
7. The food safety detection method according to claim 1, wherein the step of obtaining and analyzing the abnormal food quantity and obtaining the detection feedback information further comprises the steps of:
acquiring the number of the abnormal foods of the same production line number according to the production line information;
and selecting the production line number with the most abnormal food quantity as the detection feedback information.
8. A food safety detection system, comprising:
the acquisition module (1) is used for acquiring the food to be detected;
the acquisition module (1) is also used for acquiring corresponding abnormal food according to the target process,
the acquisition module (1) is also used for acquiring production line information according to the abnormal food;
the classification module (2) is used for acquiring a corresponding target detection item according to the type of the food to be detected;
the detection module (3) is used for detecting the target detection item according to a preset detection standard and acquiring a detection result;
the detection module (3) is also used for judging whether the abnormal food is from the same production line according to the production line information;
the query module (4) is used for acquiring an abnormal detection item according to the detection result, acquiring corresponding processing information according to the abnormal detection item, and analyzing the processing information according to a preset process index to acquire a target process;
the feedback module (5) is used for acquiring detection feedback information according to the target process;
if the abnormal food comes from the same production line, the feedback module (5) is also used for acquiring a production line number according to the production line information and taking the target process and the production line number as the detection feedback information;
and if the abnormal foods come from different production lines, the feedback module (5) is also used for acquiring and analyzing the quantity of the abnormal foods and acquiring the detection feedback information.
9. A computer-readable storage medium, in which a computer program is stored, wherein the computer program, when being loaded and executed by a processor, is adapted to carry out a method according to any one of claims 1 to 7.
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Application publication date: 20221206 |