CN117422483B - Silkworm cocoon industrial chain tracing method - Google Patents

Silkworm cocoon industrial chain tracing method Download PDF

Info

Publication number
CN117422483B
CN117422483B CN202311746792.2A CN202311746792A CN117422483B CN 117422483 B CN117422483 B CN 117422483B CN 202311746792 A CN202311746792 A CN 202311746792A CN 117422483 B CN117422483 B CN 117422483B
Authority
CN
China
Prior art keywords
cocoon
recording
cocoons
silkworm
culture
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202311746792.2A
Other languages
Chinese (zh)
Other versions
CN117422483A (en
Inventor
范鸿才
冯彬
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Sichuan Zhugan Information Technology Co ltd
Original Assignee
Sichuan Zhugan Information Technology Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Sichuan Zhugan Information Technology Co ltd filed Critical Sichuan Zhugan Information Technology Co ltd
Priority to CN202311746792.2A priority Critical patent/CN117422483B/en
Publication of CN117422483A publication Critical patent/CN117422483A/en
Application granted granted Critical
Publication of CN117422483B publication Critical patent/CN117422483B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/018Certifying business or products
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063Operations research, analysis or management
    • G06Q10/0639Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06395Quality analysis or management
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/08Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/04Manufacturing

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Theoretical Computer Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Marketing (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Development Economics (AREA)
  • Tourism & Hospitality (AREA)
  • Accounting & Taxation (AREA)
  • Educational Administration (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Finance (AREA)
  • Game Theory and Decision Science (AREA)
  • Manufacturing & Machinery (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention relates to the technical field of silkworm cocoon cultivation, in particular to a silkworm cocoon industrial chain tracing method, which comprises the following steps: the mulberry field supervision module is arranged in a plurality of mulberry leaf cultivation areas; the silkworm cocoon breeding monitoring module is arranged in the silkworm cocoon breeding areas and is used for monitoring and recording the growth data of silkworms at each stage; the acquisition modules are arranged at each acquisition base; the storage module is arranged in the regional cocoon storage warehouse; according to the invention, a silkworm cocoon industrial chain traceability system is constructed, full life cycle links of silkworm cocoon production are covered through the mulberry field supervision module, the culture monitoring module, the purchasing module and the storage module, important production parameters of each production link are supervised and recorded, and further when lower quality dry cocoons appear in the later quality spot inspection process, the production links of the whole silkworm cocoons can be comprehensively duplicated or traced through the data recorded in each link, so that adjustment references are provided for the production and culture related to the later silkworm cocoons.

Description

Silkworm cocoon industrial chain tracing method
Technical Field
The invention relates to the technical field of silkworm cocoon cultivation, in particular to a silkworm cocoon industrial chain tracing method.
Background
At present, silkworm cocoon cultivation is scattered, mainly single farmers cultivate the silkworm cocoons, silkworm merchants regularly acquire qualified silkworm cocoons in corresponding cultivation areas and then return the silkworm cocoons to be processed into dry cocoons for storage, but with popularization of intelligent agriculture and intervention of intelligent equipment, the traditional cultivation mode is low in efficiency, large-scale silkworm cocoon cultivation becomes trend, and accordingly large-scale management problems are increasingly prominent, especially when low-quality dry cocoons are detected in a storage warehouse in a sampling manner, a complex plate is needed or cultivation data corresponding to the dry cocoons are traced, and therefore a tracing management system suitable for a full-production industrial chain of the silkworm cocoons is needed.
Disclosure of Invention
The invention aims to provide a cocoon industrial chain tracing system and a method thereof so as to solve the problems. In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
in a first aspect, the present application provides a cocoon industrial chain tracing system, including: the mulberry field supervision module is arranged in the plurality of mulberry leaf cultivation areas and is used for monitoring and recording the harvest date, quality grade, distributed silkworm cocoon cultivation areas and corresponding farmer information of the mulberry leaves; the silkworm cocoon breeding monitoring module is arranged in the silkworm cocoon breeding areas and is used for monitoring and recording the growth data of silkworms at each stage; the purchasing module is arranged at each purchasing base and is used for purchasing mature cocoons and recording cocoon cultivation areas corresponding to each frame of cocoons; the storage module is arranged in the regional silkworm cocoon storage warehouse and is used for drying, storing and recording silkworm cocoons of different purchasing bases.
Optionally, the mulberry field supervision module includes a plurality of harvesting cycle identification units, a farmer responsibility area supervision unit and a mulberry She Pinzhi evaluation unit, wherein the harvesting cycle identification units are used for supervising and recording interval cycles of mulberry leaf harvesting, and the farmer responsibility area supervision unit is used for recording responsibility areas corresponding to each farmer in the corresponding mulberry leaf cultivation park.
Optionally, the breeding monitoring module comprises a hatching chamber detection unit, a co-breeding chamber detection unit, a silkworm house detection unit and a seed preservation chamber detection unit, wherein the hatching chamber detection unit is used for detecting and recording the temperature and humidity, sunlight intensity and sunlight duration in the hatching chamber, the co-breeding chamber detection unit is used for adjusting and recording the temperature and humidity of the growth environment of the young silkworms in the co-breeding chamber, the supply quantity of the mulberry leaves and the corresponding production area and quality grade of each batch of the mulberry leaves, the silkworm house detection unit is used for detecting the temperature and humidity in the silkworm house, the supply quantity of the mulberry leaves and the corresponding production area and quality grade of each batch of the mulberry leaves, and the seed preservation chamber detection unit is used for recording the temperature and humidity in the seed preservation chamber.
Optionally, the purchasing module comprises an instrument evaluation unit, a weighing recording unit and a settlement unit, wherein the instrument evaluation unit is used for evaluating the quality grade of the cocoons and recording the farmer information and the cocoon quality grade corresponding to each frame of cocoons, the weighing recording unit is used for recording the quality data of each frame of cocoons, and the settlement unit is used for recording the purchasing price corresponding to each frame of cocoons.
Optionally, the storage module comprises a drying detection unit, a drying detection unit and a storage position recording unit, wherein the drying detection unit is used for detecting and recording the drying temperature and the drying time of each frame of cocoons, the drying detection unit is used for recording the temperature and the humidity of a drying area, the drying time and the drying area, and the storage position recording unit is used for recording the storage area of the dried cocoons.
In a second aspect, the present application provides a method for tracing a cocoon industrial chain, the method comprising:
when abnormal dry cocoons are detected in a sampling mode, a plurality of corresponding first associated cocoon baskets are found based on the dry cocoon accommodating basket corresponding to the first abnormal dry cocoons, and the mapping relation between the first associated cocoon baskets and the dry cocoon accommodating basket is constructed by a airing detection unit when the dry cocoons in the first associated cocoon baskets are collected to the dry cocoon accommodating basket after the completion of the airing of the cocoons;
the corresponding cocoon quality grades are called in an instrument evaluation unit in the purchasing module based on the marks corresponding to the dry cocoon accommodating basket, and the cocoon frames with the cocoon quality grades lower than the second quality grades are marked as first abnormal cocoon frames;
collecting a culture area corresponding to a first abnormal cocoon frame, and marking the cocoon frame corresponding to the cocoons purchased in the same batch as the first abnormal cocoon frame as a second cocoon frame;
invoking a second cocoon quality rating corresponding to the second cocoon frame, and calculating fluctuation parameters and average quality ratings of a plurality of the second cocoon quality ratings;
when any one of the fluctuation parameters and the average quality ratings exceeds a preset threshold value, collecting historical culture data corresponding to a first culture area, and sending the historical culture data to an anomaly analysis model, wherein the anomaly analysis model is a BP neural network model trained based on a large number of historical culture data and corresponding silkworm cocoon quality mapping relations, the historical culture data comprises historical operation parameters of a plurality of functional rooms, and the operation parameters comprise temperature and humidity, sunlight duration, sunlight intensity, historical weather, mulberry leaf supply frequency and mulberry leaf culture areas for supplying mulberry leaves;
and analyzing abnormal culture sub-data based on the abnormal analysis model, and adjusting culture parameters of corresponding functional chambers of the corresponding cocoon culture areas based on the abnormal culture sub-data.
In a third aspect, the present application further provides a cocoon industrial chain tracing apparatus, including:
a memory for storing a computer program;
and the processor is used for realizing the steps of the cocoon industrial chain tracing method when executing the computer program.
In a fourth aspect, the present application further provides a readable storage medium, where a computer program is stored, where the computer program, when executed by a processor, implements the steps of the above-mentioned cocoon-based industrial chain tracing method.
The beneficial effects of the invention are as follows:
according to the invention, a silkworm cocoon industrial chain traceability system is constructed, full life cycle links of silkworm cocoon production are covered through the mulberry field supervision module, the culture monitoring module, the purchasing module and the storage module, important production parameters of each production link are supervised and recorded, and further when lower quality dry cocoons appear in the later quality spot inspection process, the production links of the whole silkworm cocoons can be comprehensively duplicated or traced through the data recorded in each link, so that adjustment references are provided for the production and culture related to the later silkworm cocoons.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the embodiments of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of a structure of a cocoon industrial chain tracing system according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a method for tracing a cocoon industrial chain according to an embodiment of the invention;
fig. 3 is a schematic diagram of a structure of a cocoon industrial chain tracing device according to an embodiment of the invention.
The marks in the figure: 800. cocoon industry chain tracing equipment; 801. a processor; 802. a memory; 803. a multimedia component; 804. an I/O interface; 805. a communication component.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.
Example 1: the embodiment provides a silk cocoon industrial chain traceability system, which comprises:
the mulberry field supervision module is arranged in the plurality of mulberry leaf cultivation areas and is used for monitoring and recording the harvest date, quality grade, distributed silkworm cocoon cultivation areas and corresponding farmer information of the mulberry leaves;
the silkworm cocoon breeding monitoring module is arranged in the silkworm cocoon breeding areas and is used for monitoring and recording the growth data of silkworms at each stage;
the purchasing module is arranged at each purchasing base and is used for purchasing mature cocoons and recording cocoon cultivation areas corresponding to each frame of cocoons;
the storage module is arranged in the regional silkworm cocoon storage warehouse and is used for drying, storing and recording silkworm cocoons of different purchasing bases.
Secondly, in this embodiment, the mulberry field supervision module includes a plurality of harvesting cycle identification units, a farmer responsibility area supervision unit and a mulberry She Pinzhi evaluation unit, where the harvesting cycle identification units are used for supervising and recording interval periods of harvesting of mulberry leaves, and the farmer responsibility area supervision unit is used for recording responsibility areas corresponding to each farmer in the corresponding mulberry leaf cultivation garden.
Secondly, in this embodiment, the culture monitoring module includes a detecting unit of a hatching chamber, a detecting unit of a co-breeding chamber, a detecting unit of a silkworm house and a detecting unit of a seed retaining chamber, wherein the detecting unit of the hatching chamber is used for detecting and recording the temperature and humidity, the sunlight intensity and the sunlight duration in the hatching chamber, the detecting unit of the co-breeding chamber is used for adjusting and recording the temperature and humidity of the growing environment of the young silkworms in the co-breeding chamber, the supply amount of the mulberry leaves and the corresponding producing area and quality grade of each batch of the mulberry leaves, the detecting unit of the silkworm house is used for detecting the temperature and humidity in the silkworm house, the supply amount of the mulberry leaves and the corresponding producing area and quality grade of each batch of the mulberry leaves, and the detecting unit of the seed retaining chamber is used for recording the temperature and the humidity in the seed retaining chamber.
Secondly, in this embodiment, the purchase module includes an appearance evaluation unit, a weighing recording unit and a settlement unit, where the appearance evaluation unit is used to evaluate the quality grade of cocoons and record the farmer information and the quality grade of cocoons corresponding to each frame of cocoons, the weighing recording unit is used to record the quality data of each frame of cocoons, and the settlement unit is used to record the purchase price corresponding to each frame of cocoons.
Secondly, in this embodiment, the storage module includes stoving detecting element, sunning detecting element and storage position record unit, stoving detecting element is used for detecting and recording the stoving temperature and the stoving duration of every frame silk cocoon, and sunning detecting element is used for recording the humiture, the sunning duration and the sunning region in sunning region, storage position record unit is used for recording the storage region of dry cocoon.
According to the embodiment, the whole life cycle links of cocoon production are covered through the mulberry field supervision module, the culture monitoring module, the purchasing module and the storage module, important production parameters of each production link are supervised and recorded, and further when lower quality dry cocoons appear in the later quality spot inspection process, the whole production links of the cocoons can be comprehensively coiled or traced through the recorded data of each link, and adjustment references are provided for production and culture related to the later cocoons.
Example 2: the embodiment is based on embodiment 1, and is used for providing a cocoon industrial chain tracing method, which comprises a step S1, a step S2, a step S3, a step S4, a step S5 and a step S6.
Step S1, when abnormal dry cocoons are detected in a sampling way, a plurality of corresponding first associated cocoon baskets are found based on the dry cocoon accommodating basket corresponding to the first abnormal dry cocoons, and the mapping relation between the plurality of first associated cocoon baskets and the dry cocoon accommodating basket is constructed by a airing detection unit when the dry cocoons in the plurality of first associated cocoon baskets are collected into the dry cocoon accommodating basket after the completion of the airing of the cocoons;
step S2, corresponding cocoon quality ratings are called in an instrument evaluation unit in the purchasing module based on the marks corresponding to the dry cocoon accommodating basket, and cocoon frames with the cocoon quality ratings lower than the second quality grades are marked as first abnormal cocoon frames, generally speaking, the quality of the cocoons is divided into a plurality of grades in the industry, and corresponding evaluation standards are all the prior art, and the embodiment is not explained;
s3, collecting a culture area corresponding to a first abnormal cocoon frame, and marking the cocoon frame corresponding to cocoons purchased in the same batch as the first abnormal cocoon frame as a second cocoon frame;
s4, calling a second cocoon quality rating corresponding to the second cocoon frame, and calculating fluctuation parameters and average quality ratings of a plurality of second cocoon quality ratings;
s5, under the condition that any one of the fluctuation parameters and the average quality ratings exceeds a preset threshold, collecting historical culture data corresponding to a first culture area, and sending the historical culture data to an anomaly analysis model, wherein the anomaly analysis model is a BP neural network model which is obtained by training based on a large number of historical culture data and corresponding silkworm cocoon quality mapping relations, the historical culture data comprises historical operation parameters of a plurality of functional rooms, and the operation parameters comprise temperature and humidity, sunlight duration, sunlight intensity, historical weather, mulberry leaf supply frequency and mulberry leaf culture areas for supplying mulberry leaves;
and S6, analyzing abnormal culture sub-data based on the abnormal analysis model, and adjusting culture parameters of corresponding functional chambers of the corresponding cocoon culture areas based on the abnormal culture sub-data.
Example 3: corresponding to the above method embodiment, a cocoon industrial chain tracing device is further provided in this embodiment, and a cocoon industrial chain tracing device described below and a cocoon industrial chain tracing method described above may be referred to correspondingly.
Fig. 3 is a block diagram of a cocoon industry chain traceability device 800, according to an exemplary embodiment. As shown in fig. 3, the cocoon industrial chain traceability device 800 may include: a processor 801, a memory 802. The cocoon industrial chain traceability device 800 may also include one or more of a multimedia component 803, an I/O interface 804, and a communication component 805.
The processor 801 is configured to control the overall operation of the cocoon industrial chain tracing apparatus 800, so as to complete all or part of the steps in the cocoon industrial chain tracing method. The memory 802 is used to store various types of data to support the operation of the cocoon industrial chain traceability device 800, such data may include, for example, instructions for any application or method operating on the cocoon industrial chain traceability device 800, as well as application related data such as contact data, messages, pictures, audio, video, and the like. The Memory 802 may be implemented by any type or combination of volatile or non-volatile Memory devices, such as static random access Memory (Static Random Access Memory, SRAM for short), electrically erasable programmable Read-Only Memory (ElectricallyErasable Programmable Read-Only Memory, EEPROM for short), erasable programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM for short), programmable Read-Only Memory (Programmable Read-Only Memory, PROM for short), read-Only Memory (ROM for short), magnetic Memory, flash Memory, magnetic disk, or optical disk. The multimedia component 803 may include a screen and an audio component. Wherein the screen may be, for example, a touch screen, the audio component being for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in the memory 802 or transmitted through the communication component 805. The audio assembly further comprises at least one speaker for outputting audio signals. The I/O interface 804 provides an interface between the processor 801 and other interface modules, which may be a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 805 is configured to perform wired or wireless communication between the cocoon industrial chain tracing apparatus 800 and other apparatuses. Wireless communication, such as Wi-Fi, bluetooth, near field communication (Near FieldCommunication, NFC for short), 2G, 3G or 4G, or a combination of one or more thereof, the respective communication component 805 may thus comprise: wi-Fi module, bluetooth module, NFC module.
In an exemplary embodiment, the cocoon industrial chain tracing apparatus 800 may be implemented by one or more application specific integrated circuits (Application Specific Integrated Circuit, abbreviated as ASIC), digital signal processor (DigitalSignal Processor, abbreviated as DSP), digital signal processing apparatus (Digital Signal Processing Device, abbreviated as DSPD), programmable logic device (ProgrammableLogic Device, abbreviated as PLD), field programmable gate array (Field Programmable Gate Array, abbreviated as FPGA), controller, microcontroller, microprocessor, or other electronic components for performing the cocoon industrial chain tracing method described above.
In another exemplary embodiment, there is also provided a computer readable storage medium including program instructions which, when executed by a processor, implement the steps of the cocoon industrial chain tracing method described above. For example, the computer readable storage medium may be the memory 802 including the program instructions described above, which are executable by the processor 801 of the cocoon industrial chain tracing apparatus 800 to perform the cocoon industrial chain tracing method described above.
Example 4: corresponding to the above method embodiment, a readable storage medium is further provided in this embodiment, and a readable storage medium described below and a cocoon industry chain tracing method described above may be referred to correspondingly.
A readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the cocoon industrial chain tracing method of the above method embodiment.
The readable storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, and the like.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.

Claims (5)

1. The cocoon industrial chain tracing method is suitable for a cocoon industrial chain tracing system, and the system comprises the following steps: the mulberry field supervision module is arranged in the plurality of mulberry leaf cultivation areas and is used for monitoring and recording the harvest date, quality grade, distributed silkworm cocoon cultivation areas and corresponding farmer information of the mulberry leaves; the silkworm cocoon breeding monitoring module is arranged in the silkworm cocoon breeding areas and is used for monitoring and recording the growth data of silkworms at each stage; the purchasing module is arranged at each purchasing base and is used for purchasing mature cocoons and recording cocoon cultivation areas corresponding to each frame of cocoons; the storage module is arranged in the regional cocoon storage warehouse and is used for drying, storing and recording cocoons of different purchasing bases; characterized in that the method comprises:
when abnormal dry cocoons are detected in a sampling mode, a plurality of corresponding first associated cocoon baskets are found based on the dry cocoon accommodating basket corresponding to the first abnormal dry cocoons, and the mapping relation between the first associated cocoon baskets and the dry cocoon accommodating basket is constructed by an airing detection unit when the dry cocoons in the first associated cocoon baskets are collected into the dry cocoon accommodating basket after the completion of the airing of the cocoons;
the corresponding cocoon quality grades are called in an instrument evaluation unit in the purchasing module based on the marks corresponding to the dry cocoon accommodating basket, and the cocoon frames with the cocoon quality grades lower than the second quality grades are marked as first abnormal cocoon frames;
collecting a culture area corresponding to a first abnormal cocoon frame, and marking the cocoon frame corresponding to the cocoons purchased in the same batch as the first abnormal cocoon frame as a second cocoon frame;
invoking a second cocoon quality rating corresponding to the second cocoon frame, and calculating fluctuation parameters and average quality ratings of a plurality of the second cocoon quality ratings;
when any one of the fluctuation parameters and the average quality ratings exceeds a preset threshold value, collecting historical culture data corresponding to a first culture area, and sending the historical culture data to an anomaly analysis model, wherein the anomaly analysis model is a BP neural network model trained based on a large number of historical culture data and corresponding silkworm cocoon quality mapping relations, the historical culture data comprises historical operation parameters of a plurality of functional rooms, and the operation parameters comprise temperature and humidity, sunlight duration, sunlight intensity, historical weather, mulberry leaf supply frequency and mulberry leaf culture areas for supplying mulberry leaves;
and analyzing abnormal culture sub-data based on the abnormal analysis model, and adjusting culture parameters of corresponding functional chambers of the corresponding cocoon culture areas based on the abnormal culture sub-data.
2. The method for tracing silkworm cocoon industrial chains according to claim 1, wherein the mulberry field supervision module comprises a plurality of harvesting cycle identification units, a farmer responsibility area supervision unit and a mulberry She Pinzhi evaluation unit, wherein the harvesting cycle identification units are used for supervising and recording interval cycles of mulberry leaf harvesting, and the farmer responsibility area supervision unit is used for recording responsibility areas corresponding to each farmer in the corresponding mulberry leaf cultivation garden.
3. The method for tracing the silkworm cocoon industrial chain according to claim 2, wherein the breeding monitoring module comprises a hatching chamber detection unit, a co-cultivation chamber detection unit, a large silkworm room detection unit and a seed preservation chamber detection unit, wherein the hatching chamber detection unit is used for detecting and recording the temperature and humidity, sunlight intensity and sunlight duration in the hatching chamber, the co-cultivation chamber detection unit is used for adjusting and recording the temperature and humidity of the growing environment of the young silkworms in the co-cultivation chamber, the supply amount of mulberry leaves and the corresponding production area and quality grade of each batch of mulberry leaves, the large silkworm room detection unit is used for detecting the temperature and humidity in the large silkworm room, the supply amount of mulberry leaves and the corresponding production area and quality grade of each batch of mulberry leaves, and the seed preservation chamber detection unit is used for recording the temperature and humidity in the seed preservation chamber.
4. The method for tracing a cocoon industrial chain according to claim 3, wherein the purchasing module comprises an instrument evaluation unit, a weighing recording unit and a settlement unit, wherein the instrument evaluation unit is used for evaluating the quality grade of cocoons and recording farmer information and cocoon quality grade corresponding to each frame of cocoons, the weighing recording unit is used for recording the quality data of each frame of cocoons, and the settlement unit is used for recording purchasing price corresponding to each frame of cocoons.
5. The method for tracing a silkworm cocoon industrial chain according to claim 4, wherein the storage module comprises a drying detection unit, a drying detection unit and a storage position recording unit, the drying detection unit is used for detecting and recording the drying temperature and drying time of each frame of silkworm cocoons, the drying detection unit is used for recording the temperature and humidity of a drying area, the drying time and the drying area, and the storage position recording unit is used for recording the storage area of the dried cocoons.
CN202311746792.2A 2023-12-19 2023-12-19 Silkworm cocoon industrial chain tracing method Active CN117422483B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311746792.2A CN117422483B (en) 2023-12-19 2023-12-19 Silkworm cocoon industrial chain tracing method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311746792.2A CN117422483B (en) 2023-12-19 2023-12-19 Silkworm cocoon industrial chain tracing method

Publications (2)

Publication Number Publication Date
CN117422483A CN117422483A (en) 2024-01-19
CN117422483B true CN117422483B (en) 2024-03-19

Family

ID=89530693

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202311746792.2A Active CN117422483B (en) 2023-12-19 2023-12-19 Silkworm cocoon industrial chain tracing method

Country Status (1)

Country Link
CN (1) CN117422483B (en)

Citations (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5478990A (en) * 1993-10-14 1995-12-26 Coleman Environmental Systems, Inc. Method for tracking the production history of food products
CN101162512A (en) * 2006-10-11 2008-04-16 北京农业信息技术研究中心 Aquiculture product quality safety whole processingmanagement and retroactive method and system
CN101840538A (en) * 2010-03-31 2010-09-22 华南理工大学 Aquatic product supply chain traceability system based on RFID and bar code technology and method thereof
CN104115756A (en) * 2014-07-29 2014-10-29 丁志强 Method for breeding beef cattle and mutton sheep standardly on large scale through photovoltaic facilities
CN104751367A (en) * 2013-12-31 2015-07-01 南京理工大学常熟研究院有限公司 System for sensing, controlling and tracking breeding quality of breeding pigs in pig farm in whole process
CN106665511A (en) * 2017-02-20 2017-05-17 嵊州陌桑高科股份有限公司 Silkworm breeding method based on combined type silkworm breeding frame
CN107545363A (en) * 2017-08-23 2018-01-05 青岛联海兴业信息科技有限公司 One kind cultivation plateform system and cultural method
CN110597167A (en) * 2019-09-02 2019-12-20 重庆中控欧玛仪表研究院有限公司 Silkworm breeding monitoring system
CN112837074A (en) * 2021-01-26 2021-05-25 云南云创智慧科技有限公司 Poultry breeding meat growth traceability monitoring method, system and platform
CN114897544A (en) * 2022-05-25 2022-08-12 贵州财经大学 Traceability management system based on agricultural product planting
CN114998046A (en) * 2022-06-17 2022-09-02 贵州东彩供应链科技有限公司 Traceability system based on livestock breeding supply chain
CN115439789A (en) * 2022-09-13 2022-12-06 四川省农业科学院蚕业研究所 Intelligent identification method and identification system for life state of silkworm
CN115669617A (en) * 2022-10-31 2023-02-03 四川省农业机械研究设计院 Intelligent silkworm rearing environment control system driven by Internet of things
CN117057822A (en) * 2023-08-22 2023-11-14 成都蓉桑里现代农业发展有限公司 Silkworm cocoon purchasing supervision method
CN117192985A (en) * 2023-09-11 2023-12-08 成都主干智慧云信息技术有限公司 Silkworm breeding control method based on big data

Patent Citations (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5478990A (en) * 1993-10-14 1995-12-26 Coleman Environmental Systems, Inc. Method for tracking the production history of food products
CN101162512A (en) * 2006-10-11 2008-04-16 北京农业信息技术研究中心 Aquiculture product quality safety whole processingmanagement and retroactive method and system
CN101840538A (en) * 2010-03-31 2010-09-22 华南理工大学 Aquatic product supply chain traceability system based on RFID and bar code technology and method thereof
CN104751367A (en) * 2013-12-31 2015-07-01 南京理工大学常熟研究院有限公司 System for sensing, controlling and tracking breeding quality of breeding pigs in pig farm in whole process
CN104115756A (en) * 2014-07-29 2014-10-29 丁志强 Method for breeding beef cattle and mutton sheep standardly on large scale through photovoltaic facilities
CN106665511A (en) * 2017-02-20 2017-05-17 嵊州陌桑高科股份有限公司 Silkworm breeding method based on combined type silkworm breeding frame
CN107545363A (en) * 2017-08-23 2018-01-05 青岛联海兴业信息科技有限公司 One kind cultivation plateform system and cultural method
CN110597167A (en) * 2019-09-02 2019-12-20 重庆中控欧玛仪表研究院有限公司 Silkworm breeding monitoring system
CN112837074A (en) * 2021-01-26 2021-05-25 云南云创智慧科技有限公司 Poultry breeding meat growth traceability monitoring method, system and platform
CN114897544A (en) * 2022-05-25 2022-08-12 贵州财经大学 Traceability management system based on agricultural product planting
CN114998046A (en) * 2022-06-17 2022-09-02 贵州东彩供应链科技有限公司 Traceability system based on livestock breeding supply chain
CN115439789A (en) * 2022-09-13 2022-12-06 四川省农业科学院蚕业研究所 Intelligent identification method and identification system for life state of silkworm
CN115669617A (en) * 2022-10-31 2023-02-03 四川省农业机械研究设计院 Intelligent silkworm rearing environment control system driven by Internet of things
CN117057822A (en) * 2023-08-22 2023-11-14 成都蓉桑里现代农业发展有限公司 Silkworm cocoon purchasing supervision method
CN117192985A (en) * 2023-09-11 2023-12-08 成都主干智慧云信息技术有限公司 Silkworm breeding control method based on big data

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
四川省蚕业信息化发展的思考;史宏科;《四川蚕业》;20230915;第51卷(第03期);8-10 *
基于移动物联网终端的蚕桑安全追溯系统研究;茅海军等;《丝绸》;20120620;第49卷(第06期);46-49 *
鲜茧交易中测定茧层率抽样方法的优化;邹凤竹;孙春光;黄慧明;张世友;孙烨林;;山东农业大学学报(自然科学版);20100615(02);221-224 *

Also Published As

Publication number Publication date
CN117422483A (en) 2024-01-19

Similar Documents

Publication Publication Date Title
Zapata et al. Predicting key phenological stages for 17 grapevine cultivars (Vitis vinifera L.)
CN108133380A (en) The source tracing method of food security
JP6551943B2 (en) Growth management device, growth management method, and program
EP3937098A1 (en) Crop yield amount prediction program and cultivation environment assessment program
CN111460990A (en) Big data-based alpine pastoral area grassland insect pest monitoring and early warning system and method
CN102150582A (en) Intelligent cultivation system of sunlight greenhouse
CN107609078A (en) Growing state survey model update method, sensor, server and system
CN111754045A (en) Prediction system based on fruit tree growth
KR20210109575A (en) Information processing devices and information processing systems
JP2021128756A (en) Futures Trading Information Display Program
CN117422483B (en) Silkworm cocoon industrial chain tracing method
CN108607106B (en) Automatic disinfection method and system for greenhouse
CN114723118A (en) Insect pest early warning system based on Internet of things
CN117057822A (en) Silkworm cocoon purchasing supervision method
CN208027393U (en) Quality Tracing of Agricultural Product system and supervisory systems
CN117315915A (en) Crop planting supervision system based on remote sensing data monitoring
KR102355211B1 (en) Cultivation monitoring system
CN113010529A (en) Crop management method and device based on knowledge graph
CN116186392A (en) Citrus variety planting recommendation method and device, terminal equipment and storage medium
Nurmansyah et al. Novel inflorescence architecture in gamma radiation-induced faba bean mutant populations
Wickramaarachchi et al. Real-time greenhouse environmental conditions optimization using neural network and image processing
US20230385703A1 (en) High-resolution environmental sensor imputation using machine learning
WO2021152585A1 (en) Screening system for abiotic stress mitigation in plants
Mamatha et al. Remotely monitored web based smart hydroponics system for crop yield prediction using IoT
Sheel et al. IoT based disease monitoring system for apple orchardin Himachal pradesh

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant