CN114882365A - Intelligent monitoring system for peony grafting - Google Patents
Intelligent monitoring system for peony grafting Download PDFInfo
- Publication number
- CN114882365A CN114882365A CN202210575770.3A CN202210575770A CN114882365A CN 114882365 A CN114882365 A CN 114882365A CN 202210575770 A CN202210575770 A CN 202210575770A CN 114882365 A CN114882365 A CN 114882365A
- Authority
- CN
- China
- Prior art keywords
- peony
- growth
- grafting
- monitoring
- target
- 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.)
- Withdrawn
Links
- 241000736199 Paeonia Species 0.000 title claims abstract description 213
- 235000006484 Paeonia officinalis Nutrition 0.000 title claims abstract description 204
- 238000012544 monitoring process Methods 0.000 title claims abstract description 134
- 230000012010 growth Effects 0.000 claims abstract description 196
- 238000012423 maintenance Methods 0.000 claims abstract description 15
- 238000002360 preparation method Methods 0.000 claims abstract description 13
- 238000012790 confirmation Methods 0.000 claims abstract description 12
- 238000012545 processing Methods 0.000 claims abstract description 10
- 238000003860 storage Methods 0.000 claims description 38
- 230000008859 change Effects 0.000 claims description 24
- 238000005070 sampling Methods 0.000 claims description 14
- 210000002615 epidermis Anatomy 0.000 claims description 11
- 238000012549 training Methods 0.000 claims description 10
- 230000028446 budding cell bud growth Effects 0.000 claims description 9
- 238000000605 extraction Methods 0.000 claims description 9
- 238000004321 preservation Methods 0.000 claims description 9
- 238000010586 diagram Methods 0.000 claims description 7
- 238000007789 sealing Methods 0.000 claims description 4
- 240000005001 Paeonia suffruticosa Species 0.000 claims description 3
- 235000003889 Paeonia suffruticosa Nutrition 0.000 claims description 3
- 238000005520 cutting process Methods 0.000 claims description 3
- 230000000249 desinfective effect Effects 0.000 claims description 3
- 238000001514 detection method Methods 0.000 claims description 3
- 230000001954 sterilising effect Effects 0.000 claims description 3
- 238000000034 method Methods 0.000 abstract description 7
- 230000004083 survival effect Effects 0.000 abstract description 7
- 230000029663 wound healing Effects 0.000 abstract description 5
- 230000002349 favourable effect Effects 0.000 abstract 1
- 230000009286 beneficial effect Effects 0.000 description 11
- 241000196324 Embryophyta Species 0.000 description 6
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000017260 vegetative to reproductive phase transition of meristem Effects 0.000 description 3
- 241000238631 Hexapoda Species 0.000 description 1
- 241000847925 Paeonia ostii Species 0.000 description 1
- 241001106477 Paeoniaceae Species 0.000 description 1
- 241000607479 Yersinia pestis Species 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000009546 growth abnormality Effects 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
- G06V20/188—Vegetation
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
- A01G2/00—Vegetative propagation
- A01G2/30—Grafting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
- G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device
- G06K17/0025—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device the arrangement consisting of a wireless interrogation device in combination with a device for optically marking the record carrier
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Environmental Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Developmental Biology & Embryology (AREA)
- Botany (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Multimedia (AREA)
- Cultivation Of Plants (AREA)
Abstract
The invention provides an intelligent monitoring system for peony grafting, which comprises: the grafting preparation module is used for selecting target scions, processing and classifying the target scions, and storing the target scions at a low temperature; the system comprises a time confirmation module, a grafting notification module and a control module, wherein the time confirmation module is used for monitoring a first growth condition of the peony in real time, and sending the grafting notification to a flower farmer when the peony grows to a first preset state; and the management maintenance module is used for monitoring a second generation condition of the stock in real time after grafting based on the target scion is completed, and judging whether branch and bud removal is required on the stock according to the second generation condition. The method realizes the spring grafting of the peony, is favorable for accelerating the wound healing time of the grafted peony, improves the survival rate and greatly shortens the cultivation time of the peony.
Description
Technical Field
The invention relates to the technical field of grafting management, in particular to an intelligent monitoring system for peony grafting.
Background
Peony is deciduous shrub with strong adaptability, belongs to Paeoniaceae, Paeonia and Paeonia, has colorful patterns, is symbolized by prosperity, prosperity and happiness, and is particularly popular. The grafting is one of the main means of peony propagation, not only can retain excellent characters and improve the ornamental quality and application value of the peony, but also can improve the resistance of the peony and has stronger adaptability to the environment.
The invention provides an intelligent monitoring system capable of carrying out peony grafting in spring. Compared with autumn grafting, the peony grafted and cultivated in spring has the advantages that the wound healing is fast, the survival rate is high, and the cultivation time is greatly shortened. The invention is particularly suitable for cultivating the single tree peony, such as the ten-species brocade peony.
Disclosure of Invention
The invention provides an intelligent monitoring system for peony grafting, which realizes the spring grafting of peony, is beneficial to accelerating the wound healing time of the grafted peony, improves the survival rate and greatly shortens the cultivation time of the peony.
The invention provides an intelligent monitoring system for peony grafting, which comprises:
the grafting preparation module is used for selecting target scions, processing and classifying the target scions, and storing the target scions at a low temperature;
the system comprises a time confirmation module, a grafting notification module and a control module, wherein the time confirmation module is used for monitoring a first growth condition of the peony in real time, and sending the grafting notification to a flower farmer when the peony grows to a first preset state;
and the management maintenance module is used for monitoring a second generation condition of the stock in real time after grafting based on the target scion is completed, and judging whether branch and bud removal is required on the stock according to the second generation condition.
Preferably, the grafting preparation module comprises:
the quality monitoring unit is used for acquiring a current image of the scion to be stored and judging whether the scion to be stored meets the scion storage requirement or not based on the current image;
and the scion storage unit is used for taking the scion to be stored as a target scion when the scion to be stored meets the scion storage requirement, and placing the scion to be stored in a fresh-keeping bag for sealing and storing the scion to a fresh-keeping warehouse at a low temperature after the target scion is processed and classified.
Preferably, the freshness protection package is pasted with a traceability two-dimensional code, and the traceability two-dimensional code comprises the variety and the producing area of the scion and the cutting and storage time;
and simultaneously, before the freshness protection package enters a freshness protection warehouse for low-temperature preservation, sterilizing and disinfecting the freshness protection warehouse.
Preferably, an intelligent monitoring system of tree peony grafting still includes:
the temperature control module is used for setting the storage temperature of the fresh-keeping warehouse and adjusting the storage temperature according to a temperature control instruction;
meanwhile, the temperature control device is also used for setting warning temperature.
Preferably, the grafting preparation module further comprises:
the temperature monitoring unit is used for monitoring the current storage temperature of the fresh-keeping warehouse and sending a temperature too low instruction to the temperature control module when the current storage temperature is lower than a first warning temperature;
and when the current storage temperature is higher than a second warning temperature, sending an over-temperature instruction to the temperature control module.
Preferably, the time confirmation module includes:
the first monitoring unit is used for determining the current growth condition of the peony according to the real-time first monitoring image and taking the current growth condition as a first growth condition;
the judging unit is used for comparing the first generation condition with a first preset state and judging whether the growth of the peony reaches the first preset state;
and the first notification unit is used for sending a grafting notification to a flower farmer when the peony grows to reach a first preset state.
Preferably, the first monitoring unit includes:
the contrast setting subunit is used for acquiring growth images of the peony in each period and generating a peony growth change map based on the generated images;
according to the growth change diagram, obtaining branch changes of the peony, and extracting first growth characteristics of the peony in each period;
establishing a peony growth comparison table according to the first growth characteristics and the growth images of the peony in each period;
the image acquisition subunit is used for dividing the monitored flower field into a plurality of first areas, randomly selecting a plurality of target peonies in each first area, acquiring a current image of the target peonies as a first monitoring image, and acquiring a second growth characteristic of the target peonies based on the first monitoring image;
a growth judging subunit, configured to search the peony growth comparison table according to the second growth characteristic, determine a growth period of the target peony, and judge whether the growth period is a branch and bud growth period;
if the growth period is the branch bud growth period, acquiring a third growth characteristic of the target peony on the peony growth comparison table, comparing the third characteristic with the second characteristic, and determining all new branch positions of the target peony on the first monitoring image according to a comparison result;
acquiring the image lengths of all the new branches on the first monitoring image, respectively determining the actual length of each new branch based on the shooting proportion of the first image, and judging whether the actual length of each new branch is greater than or equal to a preset length;
determining the grafting maturity of the target peony based on a length judgment result, and judging that the target peony meets the grafting requirement when the grafting maturity is greater than a preset standard;
if the growth period is not the branch bud growth period, judging that the target peony does not meet the grafting requirement;
the result determining subunit is used for acquiring growth judgment results of all target peonies and calculating the grafting maturity index of the monitored flower field according to the growth judgment results;
and determining the current growth condition of the monitored peony in the flower field based on the grafting maturity index, and meanwhile sending the current growth condition to a judgment unit as a first growth condition.
Preferably, the management maintenance module includes:
the second monitoring unit is used for carrying out region division on the current monitoring flower field according to the growth characteristics of the peony in the current monitoring flower field after grafting is finished, and extracting a monitoring sample image of a corresponding divided region from a second monitoring image of the grafted peony;
based on the monitoring sample image, really corresponding to the second growth condition of the rootstocks in the area, and judging whether the corresponding area needs to remove the rootstock branch buds or not;
and the second notification unit is used for sending the serial number of the divided area needing to be subjected to branch bud removal to the flower grower when the area needs to be subjected to the branch bud removal of the rootstock.
Preferably, the second monitoring unit includes:
the model training subunit is used for acquiring a historical image after peony grafting, constructing a model training set, and training a preset recognition model to obtain a stock recognition model;
the system comprises a sample extraction subunit, a data processing unit and a data processing unit, wherein the sample extraction subunit is used for acquiring the historical growth record of the peony planting of the current monitoring flower field, determining the growth deviation of the current monitoring flower field according to the historical growth record, carrying out second area division on the current monitoring flower field based on the growth deviation, and numbering each second area;
the sample extraction subunit is further used for determining the peony growth speed of each second area based on the historical growth records, and predicting the grafted peony growth condition according to the peony growth speed;
determining the current sampling probability of each second region according to the growth condition of the grafted peony, wherein the sampling probability can change along with the growth time of the grafted peony;
extracting a corresponding number of images from a second monitoring image corresponding to each second area according to the current sampling probability to serve as monitoring sample images;
the sample detection subunit is used for identifying the monitoring sample image based on the stock identification model and marking the stock of the grafted peony;
determining the position of the stock based on a stock marking frame, and acquiring a first color characteristic of the stock;
comparing the first color characteristic with a second color characteristic of the stock before grafting to obtain a color difference, and judging whether the color difference is within the stock epidermis color variation range;
if the color difference is not within the variation range of the stock epidermis color, obtaining a third color feature in a second preset state, judging that branch buds grow on the stock when the third color feature is consistent with the first color feature, and adding a blue label to a monitoring sample image corresponding to the stock;
otherwise, judging that the stock grows abnormally, and adding a red label to a monitoring sample image corresponding to the stock;
if the color difference part is within the variation range of the stock epidermis color, judging that no branch bud grows on the stock, and adding a yellow label to a monitoring sample image corresponding to the stock;
the statistical subunit is used for respectively acquiring the color label adding condition of the monitoring sample image of each second region, determining the growth proportion of the rootstock scion and bud of each second region according to the color label adding condition, and judging that the rootstock scion and bud are required to be removed in the target region when the growth proportion of the target region is greater than a preset removal value;
otherwise, judging that the branch buds of the rootstocks are not required to be removed in the target area temporarily.
Preferably, the management maintenance module further includes:
and the growth recording unit is used for recording the growth change of the grafted peony according to the second monitoring image and generating a grafted peony growth log based on the growth change.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice 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 hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic structural diagram of an intelligent monitoring system for peony grafting according to the present invention;
FIG. 2 is a schematic structural diagram of a grafting preparation module of the intelligent monitoring system for peony grafting;
FIG. 3 is a schematic structural diagram of a time confirmation module of the intelligent monitoring system for peony grafting according to the present invention;
fig. 4 is a schematic structural diagram of a management and maintenance module of the intelligent monitoring system for peony grafting.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example 1:
the invention provides an intelligent monitoring system for peony grafting, as shown in fig. 1, comprising:
the grafting preparation module is used for selecting target scions, processing and classifying the target scions, and storing the target scions at a low temperature;
the system comprises a time confirmation module, a grafting notification module and a control module, wherein the time confirmation module is used for monitoring a first growth condition of the peony in real time, and sending the grafting notification to a flower farmer when the peony grows to a first preset state;
and the management maintenance module is used for monitoring a second generation condition of the stock in real time after grafting based on the target scion is completed, and judging whether branch and bud removal is required on the stock according to the second generation condition.
In the embodiment, the target scion is selected for grafting in the last autumn before grafting and can be stored in a fresh-keeping mode, the scion is collected on a healthy plant which is high in flowering rate, strong in growth potential, close in flowering period and free of diseases and insect pests, and the length of the scion is 12-18 cm.
In this embodiment, the treatment of the scion means that the scion is cut and then wax-sealed.
In this example, the temperature for low-temperature preservation of the scions was 0-2 ℃.
In this embodiment, the first growth condition refers to a growth condition of a peony before grafting as a rootstock; the first preset state means that the current year twig of the peony as the stock grows to 20cm before the flower blooms.
In this embodiment, the second growth state refers to the growth condition of the rootstock after grafting is completed; after grafting, whether the branch buds grow out on the stocks is mainly monitored.
In this embodiment, the rootstock can be selected from paeonia ostii with good plant row or variety peony, and can be planted in one tree or in multiple clusters.
The beneficial effects of the above technical scheme are that: the invention stores and manages the scions selected in the last autumn before grafting through the grafting preparation module, provides a foundation for realizing spring grafting of peony, and realizes intelligent monitoring of grafting time through the time determination module; after grafting is completed, the management and maintenance module monitors the second generation condition of the rootstock in real time, so that rootstock branch buds can be removed in time, the wound healing time of grafted peony is shortened, the survival rate is improved, and the peony cultivation time is greatly shortened.
Example 2:
on the basis of the embodiment 1, the grafting preparation module, as shown in fig. 2, includes:
the quality monitoring unit is used for acquiring a current image of the scion to be stored and judging whether the scion to be stored meets the scion storage requirement or not based on the current image;
and the scion storage unit is used for taking the scion to be stored as a target scion when the scion to be stored meets the scion storage requirement, and placing the scion to be stored in a fresh-keeping bag for sealing and storing the scion to a fresh-keeping warehouse at a low temperature after the target scion is processed and classified.
In this embodiment, the scions to be stored refer to scions that have been cut and have not been treated.
In this embodiment, the storage requirement of the scion means that the stored length of the scion is between 12 cm and 18cm without any damage on the surface.
The beneficial effects of the above technical scheme are that: the invention monitors the quality of the scions before storage, ensures the quality of the stored scions and avoids other scions from being polluted by damaged scions; the activity of the scions can be kept by low-temperature sealing and fresh-keeping storage, and the survival rate of the grafted peony is improved.
Example 3:
on the basis of the embodiment 2, a source tracing two-dimensional code is pasted on the freshness protection package, and the source tracing two-dimensional code comprises the variety and the producing area of the scion, the cutting time and the storage time;
and simultaneously, before the freshness protection package enters a freshness protection warehouse for low-temperature preservation, sterilizing and disinfecting the freshness protection warehouse.
The beneficial effects of the above technical scheme are that: the traceable two-dimensional code is pasted on the freshness protection package, so that the flower grower can know the scion information conveniently; before the freshness protection package enters a freshness protection warehouse for low-temperature preservation, the freshness protection warehouse is sterilized and disinfected, so that a sterile environment is provided for scion storage as far as possible, and scion loss is reduced.
Example 4:
on the basis of embodiment 2, a system for intelligently monitoring peony grafting further comprises:
the temperature control module is used for setting the storage temperature of the fresh-keeping warehouse and adjusting the storage temperature according to a temperature control instruction;
meanwhile, the temperature control device is also used for setting warning temperature.
In this embodiment, the storage temperature is the temperature of the artificially set fresh-keeping warehouse, and is generally 0-2 ℃.
In this embodiment, the temperature control command includes a low temperature command and a low temperature command.
In this embodiment, the warning temperature includes a first warning temperature and a second warning temperature.
The beneficial effects of the above technical scheme are that: the invention manages and controls the temperature of the preservation warehouse, and ensures that the temperature of the preservation warehouse is always kept at the optimal temperature for storing the scions.
Example 5:
on the basis of embodiment 4, as shown in fig. 2, the grafting preparation module further includes:
the temperature monitoring unit is used for monitoring the current storage temperature of the scion storage and preservation warehouse and sending a temperature over-low instruction to the temperature control module when the current storage temperature is lower than a first warning temperature;
and when the current storage temperature is higher than a second warning temperature, sending an over-temperature instruction to the temperature control module.
In this embodiment, the current storage temperature refers to the time temperature in the fresh-keeping warehouse.
In this embodiment, the first warning temperature is a lower temperature limit of the scion storage, and is generally 0 ℃; the second warning temperature is the upper temperature limit of the scion storage, typically 2 ℃.
The beneficial effects of the above technical scheme are that: the invention monitors the current storage temperature of the ear storage and preservation warehouse, and sends a temperature control instruction when the temperature is too high or too low.
Example 6:
on the basis of embodiment 1, the time confirmation module, as shown in fig. 3, includes:
the first monitoring unit is used for determining the current growth condition of the peony according to the real-time first monitoring image and taking the current growth condition as a first growth condition;
the judging unit is used for comparing the first generation condition with a first preset state and judging whether the growth of the peony reaches the first preset state;
and the first notification unit is used for sending a grafting notification to a flower farmer when the peony grows to reach a first preset state.
In this embodiment, the first monitoring image is a peony image before grafting, which is taken as a rootstock.
The beneficial effects of the above technical scheme are as follows: according to the method, the growth condition of the peony before grafting is monitored in real time, and when the growth of the peony reaches a first preset state, a grafting notice is sent to a flower farmer, so that the intelligent monitoring of the grafting time is realized.
Example 7:
on the basis of embodiment 6, the first monitoring unit, as shown in fig. 3, includes:
the contrast setting subunit is used for acquiring growth images of the peony in each period and generating a peony growth change map based on the generated images;
according to the growth change diagram, obtaining branch changes of the peony, and extracting first growth characteristics of the peony in each period;
establishing a peony growth comparison table according to the first growth characteristics and the growth images of the peony in each period;
the image acquisition subunit is used for dividing the monitored flower field into a plurality of areas, randomly selecting a plurality of target peonies in each area, acquiring a current image of the target peonies to serve as a first monitoring image, and acquiring a second growth characteristic of the target peonies based on the first monitoring image;
a growth judging subunit, configured to search the peony growth comparison table according to the second growth characteristic, determine a growth period of the target peony, and judge whether the growth period is a branch and bud growth period;
if the growth period is the branch bud growth period, acquiring a third growth characteristic of the target peony on the peony growth comparison table, comparing the third characteristic with the second characteristic, and determining all new branch positions of the target peony on the first monitoring image according to a comparison result;
acquiring the image lengths of all the new branches on the first monitoring image, respectively determining the actual length of each new branch based on the shooting proportion of the first image, and judging whether the actual length of each new branch is greater than or equal to a preset length;
determining the grafting maturity of the target peony based on a length judgment result, and judging that the target peony meets the grafting requirement when the grafting maturity is greater than a preset standard;
if the growth period is not the branch bud growth period, judging that the target peony does not meet the grafting requirement;
the result determining subunit is used for acquiring growth judgment results of all target peonies and predicting the grafting maturity index of the monitored flower field according to the growth judgment results;
and determining the current growth condition of the monitored peony in the flower field based on the grafting maturity index, and meanwhile sending the current growth condition to a judgment unit as a first growth condition.
In this embodiment, the growth image refers to a peony plant image at each period (e.g., a new branch elongation period, a bud period, a sepal initial period, a leaf period, etc.) in the whole growth cycle of a peony to be used as a grafting stock.
In this embodiment, the peony growth variation graph is an image that can represent plant variation in the whole growth cycle (from the seedling stage to the flowering stage) of peony as a grafting stock.
In this embodiment, the branch change refers to whether a new branch of the peony as the grafting stock grows and the growth length of the branch.
In this embodiment, the first growth characteristic refers to the color change of the surface of the branch and the trunk of the peony plant, the size of the plant, and the shape change of the plant at each period in the whole growth cycle of the peony as the grafting stock.
In this embodiment, the peony growth comparison table refers to a comparison table in which growth images of all periods in the whole growth cycle of the peony correspond to the first growth characteristics one to one.
In this embodiment, the target peony is a peony plant randomly extracted in each area of the monitored flower field.
In this embodiment, the second growth characteristic refers to the epidermis color of the branch and the trunk of the target peony plant, and the size and shape characteristics of the plant.
In this embodiment, the third growth characteristic refers to a growth characteristic of the target peony on the peony growth comparison table corresponding to the growth period.
In this embodiment, the image length refers to the length of a newly grown branch on the first monitoring image; the shooting scale refers to the ratio of the length of the object on the first monitoring graph to the length of the actual object.
In this embodiment, the actual length is obtained by multiplying the image length by the shooting ratio.
In this embodiment, the length determination refers to comparing the actual length of the new branch with a preset length.
In this embodiment, the grafting maturity refers to whether the target peony can be used for grafting, the result is determined by the length determination result, and when the actual length of the new branch is greater than or equal to a preset length (for example, 20cm), the grafting maturity of the target peony is determined.
In this embodiment, the preset standard means that the determined peony which is mature in grafting can be grafted.
In this embodiment, the growth determination means determining whether the target peony meets the grafting requirement.
In this embodiment, the first region is a region obtained by indiscriminately dividing the monitored flower field into a plurality of small blocks of equal area.
In this embodiment, the grafting maturity index refers to the overall grafting maturity of the monitored flower field obtained through calculation according to the grafting maturity of the target peony, and is specifically calculated as follows:
wherein, alpha refers to the grafting maturity index of the monitored flower field; n tableDisplaying the total number of the first areas in the monitored flower field; q i Representing the number of target peony plants meeting the grafting requirement in the ith first region; m 0 The total number of target peony plants in the whole monitored flower field is referred to; m i Expressing the total number of target peony plants in the ith first region; rho represents the equal-area random sampling error, and the value range is (0, 0.1).
In this embodiment, the current growth condition refers to the overall growth condition of the peony serving as the rootstock in the monitored flower field before grafting.
The beneficial effects of the above technical scheme are that: according to the method, a peony growth comparison table is established through the growth images of the peony in each period and the first growth characteristics of the peony in each period, so that the growth period of the target peony can be rapidly confirmed; comparing the actual growth characteristic (namely the second growth characteristic) of the target peony with a third growth characteristic which is obtained by searching on a peony growth comparison table and corresponds to the growth period, quickly positioning the position of a new branch of the target peony, and accelerating the measurement of the length of the new branch; then, the grafting maturity index of the whole monitored flower field is predicted according to the growth judgment results of a plurality of samples (namely the target peony), so that the growth condition of the whole monitored flower field is obtained, the workload of manual monitoring is reduced, and the intelligent management of peony grafting preparation is realized; the monitored flower field is divided into a plurality of first areas in the process of selecting a sample (namely target peony), so that the universality of the sampling range is ensured, and a reliable basis is provided for the prediction of the grafting maturity index of the whole monitored flower field.
Example 8:
on the basis of embodiment 1, as shown in fig. 4, the management maintenance module includes:
the second monitoring unit is used for carrying out region division on the current monitoring flower field according to the growth characteristics of the peony in the current monitoring flower field after grafting is finished, and extracting a monitoring sample image of a corresponding divided region from a second monitoring image of the grafted peony;
based on the monitoring sample image, really corresponding to the second growth condition of the rootstocks in the area, and judging whether the corresponding area needs to remove the rootstock branch buds or not;
and the second notification unit is used for sending the serial number of the divided area needing to be subjected to branch bud removal to the flower grower when the area needs to be subjected to the branch bud removal of the rootstock.
In this embodiment, the growing characteristics mean that the peonies in different positions in the current monitoring flower field are different from each other at the same time, and the peonies in different positions in the current monitoring flower field are different from each other in growth vigor, and usually, the outermost peonies flower earlier than the middle peonies.
In this embodiment, the second monitoring image is a real-time image of grafted peony after grafting is completed.
In this embodiment, the monitoring sample image is a real-time image for confirming the stock production status at a portion extracted from the second monitoring image.
The beneficial effects of the above technical scheme are that: according to the method, the second growth condition of the stock is monitored in real time after grafting is completed, and when the condition that the new branch buds are on the stock is confirmed, the flower grower is informed to remove the branch buds in time, so that the branch buds of the stock can be removed in time, the wound healing time of grafted peony is shortened, the survival rate is improved, and the cultivation time of the peony is greatly shortened.
When the second generation condition of the rootstock is monitored in real time, the region division is carried out on the current monitoring flower field, whether the rootstock branch bud is to be removed is judged by taking the region as a unit, the branch bud cleaning frequency is reduced as much as possible, and the working efficiency of flower growers is improved.
Example 9:
on the basis of embodiment 8, the second monitoring unit, as shown in fig. 4, includes:
the model training subunit is used for acquiring a historical image after peony grafting, constructing a model training set, and training a preset recognition model to obtain a stock recognition model;
the system comprises a sample extraction subunit, a data processing unit and a data processing unit, wherein the sample extraction subunit is used for acquiring the historical growth record of the peony planting of the current monitoring flower field, determining the growth deviation of the current monitoring flower field according to the historical growth record, carrying out second area division on the current monitoring flower field based on the growth deviation, and numbering each second area;
the sample extraction subunit is further used for determining the peony growth speed of each second area based on the historical growth records, and predicting the grafted peony growth condition according to the peony growth speed;
determining the current sampling probability of each second region according to the growth condition of the grafted peony, wherein the sampling probability can change along with the growth time of the grafted peony;
extracting a corresponding number of images from a second monitoring image corresponding to each second area according to the current sampling probability to serve as monitoring sample images;
the sample detection subunit is used for identifying the monitoring sample image based on the stock identification model and marking the stock of the grafted peony;
determining the position of the stock based on a stock marking frame, and acquiring a first color characteristic of the stock;
comparing the first color characteristic with a second color characteristic of the stock before grafting to obtain a color difference, and judging whether the color difference is within the stock epidermis color variation range;
if the color difference is not within the stock epidermis color change range, obtaining a third color characteristic in a second preset state, judging that a branch bud grows on the stock when the third color characteristic is consistent with the first color characteristic, and adding a blue label to a monitoring sample image corresponding to the stock;
otherwise, judging that the stock grows abnormally, and adding a red label to a monitoring sample image corresponding to the stock;
if the color difference part is within the variation range of the stock epidermis color, judging that no branch bud grows on the stock, and adding a yellow label to a monitoring sample image corresponding to the stock;
the statistical subunit is used for respectively acquiring the color label adding condition of the monitoring sample image of each second region, determining the growth proportion of the rootstock branch bud of each second region according to the color label adding condition, and judging that the rootstock branch bud needs to be removed in the target region when the growth proportion of the target region is larger than a preset removal value;
otherwise, judging that the rootstock branch buds do not need to be removed in the target area temporarily.
In this embodiment, the rootstock identification model is suitable for identifying the rootstock on the grafted peony.
In this embodiment, the historical growth record is a record of the growth of previously planted peony in the currently monitored flower field.
In this embodiment, the grafted peony is completed by grafting the peony.
In this embodiment, the growth deviation means that the peony growth conditions at different positions of the same flowery field are different due to illumination, moisture and wind, and the positions with the same growth conditions are divided into the same region, which is the second region, so that the areas of the different second regions are not necessarily the same.
In this embodiment, the growth rate of peony refers to the growth rate of peony planted before the current monitoring field.
In this embodiment, the growth condition of the grafted peony refers to the growth condition of the grafted peony at different positions in the current monitoring field.
In this embodiment, the current sampling probability refers to a proportion of each region to the total number of samples under the current growth condition, and the faster the growth speed of the branches in a certain region is, the greater the current sampling probability is, and the sampling probability can change along with the growth time of the grafted peony.
In this embodiment, the stock marking frame is a rectangular frame for positioning the position of the grafted peony stock by the stock identification model.
In this embodiment, the first color feature refers to a color feature of the surface of the grafted peony rootstock after grafting is completed; the second color characteristic refers to the color characteristic of the surface of the rootstock before grafting, and the color comprises the color of the section of the rootstock.
In the embodiment, the color difference refers to the difference of the surface color of the rootstock before and after grafting, for example, the rootstock is bright green due to the growth of new branch buds.
In this embodiment, the color change range of the rootstock epidermis means the color change before no new shoot grows on the rootstock. For example, from dark brown to light brown to dark green.
In this embodiment, the second preset state refers to that a new branch bud grows on the rootstock; the third color characteristic refers to the condition of the color formation on the surface of the stock when new branch buds grow on the stock.
In this embodiment, the color labels include a blue label, a red label, and a yellow label, all of which are added to the monitoring sample image. The blue label is added when the branch buds grow on the corresponding rootstocks on the monitoring sample image; the red label is added when the corresponding rootstock growth abnormality (for example, death of grafted peony) on the sample image is monitored; the yellow label is added when no branch bud grows on the corresponding rootstock on the monitoring sample image.
In this embodiment, the growth ratio refers to the ratio of rootstock to bud in different second regions of the currently monitored paddy field, and is specifically calculated as follows:
wherein, beta j Expressing the growth proportion of the jth second region; y is j Indicating the number of blue labels of the jth second area; x j The number of yellow labels of the jth second area is represented; z j Indicating the number of red labels of the jth second area; mu represents the system deviation of the system in the second area division, and takes the value of (0, 0.1).
In this embodiment, the target region is a second region for determining whether the branch bud of the rootstock needs to be removed.
In this embodiment, the preset removal value refers to a minimum growth ratio value of a certain region that is manually set and needs to remove rootstock branch buds.
The beneficial effects of the above technical scheme are that: according to the method, a stock identification model is obtained through training, the position of a stock of the grafted peony is quickly identified, then whether new branch buds grow out on the stock is confirmed through verification of the surface color of the stock, finally, the growth proportion of each area is confirmed according to the divided areas, so that whether the branch buds of the stock need to be removed in each area is respectively determined, the intelligent management of grafting maintenance is realized, meanwhile, the areas are divided according to growth deviation in the maintenance monitoring process, and the management of the currently monitored flower field is more orderly and scientific. The method has the advantages that the branch and bud of the stock can be removed in time, the grafting survival rate is improved, the removal times are reduced, the workload of flower growers is reduced, and the working efficiency in the grafting maintenance stage is improved.
Example 10:
on the basis of embodiment 8, as shown in fig. 4, the management maintenance module further includes:
and the growth recording unit is used for recording the growth change of the grafted peony according to the second monitoring image and generating a grafted peony growth log based on the growth change.
The beneficial effects of the above technical scheme are that: according to the second monitoring image, the growth change of the grafted peony is recorded, and data support is provided for feasibility of peony grafting in spring; and generating a grafted peony growth log based on the growth change, and providing a theoretical basis for next peony spring grafting.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. The utility model provides an intelligent monitoring system of tree peony grafting which characterized in that includes:
the grafting preparation module is used for selecting target scions, processing and classifying the target scions, and storing the target scions at a low temperature;
the system comprises a time confirmation module, a grafting notification module and a control module, wherein the time confirmation module is used for monitoring a first growth condition of the peony in real time, and sending the grafting notification to a flower farmer when the peony grows to a first preset state;
and the management maintenance module is used for monitoring a second generation condition of the stock in real time after grafting based on the target scion is completed, and judging whether branch and bud removal is required on the stock according to the second generation condition.
2. The intelligent monitoring system for peony grafting according to claim 1, wherein the grafting preparation module comprises:
the quality monitoring unit is used for acquiring a current image of the scion to be stored and judging whether the scion to be stored meets the scion storage requirement or not based on the current image;
and the scion storage unit is used for taking the scion to be stored as a target scion when the scion to be stored meets the scion storage requirement, and placing the scion to be stored in a fresh-keeping bag for sealing and storing the scion to a fresh-keeping warehouse at a low temperature after the target scion is processed and classified.
3. The intelligent monitoring system for peony grafting according to claim 2, wherein a traceability two-dimensional code is pasted on the freshness protection package, and the traceability two-dimensional code comprises the variety and the producing area of the scion, the cutting time and the storage time;
and simultaneously, before the freshness protection package enters a freshness protection warehouse for low-temperature preservation, sterilizing and disinfecting the freshness protection warehouse.
4. The intelligent monitoring system for peony grafting according to claim 2, further comprising:
the temperature control module is used for setting the storage temperature of the fresh-keeping warehouse and adjusting the storage temperature according to a temperature control instruction;
meanwhile, the temperature control device is also used for setting warning temperature.
5. The intelligent monitoring system for peony grafting according to claim 4, wherein the grafting preparation module further comprises:
the temperature monitoring unit is used for monitoring the current storage temperature of the fresh-keeping warehouse and sending a temperature too low instruction to the temperature control module when the current storage temperature is lower than a first warning temperature;
and when the current storage temperature is higher than a second warning temperature, sending an over-temperature instruction to the temperature control module.
6. The system of claim 1, wherein the time confirmation module comprises:
the first monitoring unit is used for determining the current growth condition of the peony according to the real-time first monitoring image and taking the current growth condition as a first growth condition;
the judging unit is used for comparing the first generation condition with a first preset state and judging whether the growth of the peony reaches the first preset state;
and the first notification unit is used for sending a grafting notification to a flower farmer when the peony grows to reach a first preset state.
7. The intelligent monitoring system for peony grafting as claimed in claim 6, wherein said first monitoring unit comprises:
the contrast setting subunit is used for acquiring growth images of the peony in each period and generating a peony growth change map based on the generated images;
according to the growth change diagram, obtaining branch changes of the peony, and extracting first growth characteristics of the peony in each period;
establishing a peony growth comparison table according to the first growth characteristics and the growth images of the peony in each period;
the image acquisition subunit is used for dividing the monitored flower field into a plurality of first areas, randomly selecting a plurality of target peonies in each first area, acquiring a current image of the target peonies as a first monitoring image, and acquiring a second growth characteristic of the target peonies based on the first monitoring image;
a growth judging subunit, configured to search the peony growth comparison table according to the second growth characteristic, determine a growth period of the target peony, and judge whether the growth period is a branch and bud growth period;
if the growth period is the branch bud growth period, acquiring a third growth characteristic of the target peony on the peony growth comparison table, comparing the third characteristic with the second characteristic, and determining all new branch positions of the target peony on the first monitoring image according to a comparison result;
acquiring the image lengths of all the new branches on the first monitoring image, respectively determining the actual length of each new branch based on the shooting proportion of the first image, and judging whether the actual length of each new branch is greater than or equal to a preset length;
determining the grafting maturity of the target peony based on a length judgment result, and judging that the target peony meets the grafting requirement when the grafting maturity is greater than a preset standard;
if the growth period is not the branch bud growth period, judging that the target peony does not meet the grafting requirement;
the result determining subunit is used for acquiring growth judgment results of all target peonies and calculating the grafting maturity index of the monitored flower field according to the growth judgment results;
and determining the current growth condition of the monitored peony in the flower field based on the grafting maturity index, and meanwhile sending the current growth condition to a judgment unit as a first growth condition.
8. The intelligent monitoring system for peony grafting according to claim 1, wherein the management maintenance module comprises:
the second monitoring unit is used for carrying out region division on the current monitoring flower field according to the growth characteristics of the peony in the current monitoring flower field after grafting is finished, and extracting a monitoring sample image of a corresponding divided region from a second monitoring image of the grafted peony;
based on the monitoring sample image, really corresponding to the second growth condition of the rootstocks in the area, and judging whether the corresponding area needs to remove the rootstock branch buds or not;
and the second notification unit is used for sending the serial number of the divided area needing to be subjected to branch bud removal to the flower grower when the area needs to be subjected to the branch bud removal of the rootstock.
9. The intelligent monitoring system for peony grafting as claimed in claim 8, wherein said second monitoring unit comprises:
the model training subunit is used for acquiring a historical image after peony grafting, constructing a model training set, and training a preset recognition model to obtain a stock recognition model;
the system comprises a sample extraction subunit, a data processing unit and a data processing unit, wherein the sample extraction subunit is used for acquiring the historical growth record of the peony planting of the current monitoring flower field, determining the growth deviation of the current monitoring flower field according to the historical growth record, carrying out second area division on the current monitoring flower field based on the growth deviation, and numbering each second area;
the sample extraction subunit is further used for determining the peony growth speed of each second area based on the historical growth records, and predicting the grafted peony growth condition according to the peony growth speed;
determining the current sampling probability of each second region according to the growth condition of the grafted peony, wherein the sampling probability can change along with the growth time of the grafted peony;
extracting a corresponding number of images from a second monitoring image corresponding to each second area according to the current sampling probability to serve as monitoring sample images;
the sample detection subunit is used for identifying the monitoring sample image based on the stock identification model and marking the stock of the grafted peony;
determining the position of the stock based on a stock marking frame, and acquiring a first color characteristic of the stock;
comparing the first color characteristic with a second color characteristic of the stock before grafting to obtain a color difference, and judging whether the color difference is within the stock epidermis color variation range;
if the color difference is not within the variation range of the stock epidermis color, obtaining a third color feature in a second preset state, judging that branch buds grow on the stock when the third color feature is consistent with the first color feature, and adding a blue label to a monitoring sample image corresponding to the stock;
otherwise, judging that the stock grows abnormally, and adding a red label to a monitoring sample image corresponding to the stock;
if the color difference part is within the variation range of the stock epidermis color, judging that no branch bud grows on the stock, and adding a yellow label to a monitoring sample image corresponding to the stock;
the statistical subunit is used for respectively acquiring the color label adding condition of the monitoring sample image of each second region, determining the growth proportion of the rootstock branch bud of each second region according to the color label adding condition, and judging that the rootstock branch bud needs to be removed in the target region when the growth proportion of the target region is larger than a preset removal value;
otherwise, judging that the branch buds of the rootstocks are not required to be removed in the target area temporarily.
10. The intelligent monitoring system for peony grafting according to claim 8, wherein the management maintenance module further comprises:
and the growth recording unit is used for recording the growth change of the grafted peony according to the second monitoring image and generating a grafted peony growth log based on the growth change.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210575770.3A CN114882365A (en) | 2022-05-24 | 2022-05-24 | Intelligent monitoring system for peony grafting |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210575770.3A CN114882365A (en) | 2022-05-24 | 2022-05-24 | Intelligent monitoring system for peony grafting |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114882365A true CN114882365A (en) | 2022-08-09 |
Family
ID=82677149
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210575770.3A Withdrawn CN114882365A (en) | 2022-05-24 | 2022-05-24 | Intelligent monitoring system for peony grafting |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114882365A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116548195A (en) * | 2023-07-12 | 2023-08-08 | 北京市农林科学院智能装备技术研究中心 | Stock cutting method, device, system, equipment, medium and grafting robot |
-
2022
- 2022-05-24 CN CN202210575770.3A patent/CN114882365A/en not_active Withdrawn
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116548195A (en) * | 2023-07-12 | 2023-08-08 | 北京市农林科学院智能装备技术研究中心 | Stock cutting method, device, system, equipment, medium and grafting robot |
| CN116548195B (en) * | 2023-07-12 | 2023-10-20 | 北京市农林科学院智能装备技术研究中心 | Stock cutting method, device, system, equipment, medium and grafting robot |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP4009441B2 (en) | Crop cultivation evaluation system | |
| CN111507857A (en) | Digital agricultural planting system and method based on Internet of things technology | |
| CN112836623B (en) | Auxiliary method and device for agricultural decision of facility tomatoes | |
| CN111476149A (en) | Plant cultivation control method and system | |
| JP2019170359A (en) | Plant cultivation result prediction system | |
| CN114882365A (en) | Intelligent monitoring system for peony grafting | |
| CN114723118B (en) | Insect pest early warning system based on internet of things | |
| CN114740930A (en) | Intelligent management and control platform system for greenhouse and management and control processing method | |
| CN101536669A (en) | Efficient polymerization method for apple crossbreeding | |
| Ahmad et al. | Evaluation of smart greenhouse monitoring system using raspberry-Pi microcontroller for the production of tomato crop | |
| CN116797601B (en) | Image recognition-based Huashansong growth dynamic monitoring method and system | |
| Elenzano | Smart farming for lowland strawberry (Fragaria x ananassa) production | |
| CN112913497A (en) | Method for measuring cooling capacity required by peach blossom buds under facility conditions | |
| US20230309464A1 (en) | Method and apparatus for automated crop recipe optimization | |
| US8413373B2 (en) | Method of cutting crops | |
| Robinson et al. | Studies in precision crop load management of apple | |
| CN113313374A (en) | Insect density and harmfulness analysis method | |
| Thalwatte et al. | Fully automatic hydroponic cultivation growth system | |
| CN114500603A (en) | Intelligent management system for agricultural greenhouse planting | |
| Delaquis et al. | Cassava rapid stem multiplication tunnel: Operations manual | |
| Noyce et al. | Methods for continual production of grapevine plants grown from green cuttings, with repeated budburst induction, in an environmentally controlled greenhouse | |
| CN108849215A (en) | A kind of grape cultivation method | |
| CN112903677B (en) | Method for rapidly detecting grape flower buds | |
| Xin et al. | Melon Growth Detection Strategy Using Artificial Intellegence in Greenhouse Cultivation | |
| Manfrini et al. | A multi-tool approach for assessing fruit growth, production and plant water status of a pear orchard |
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 | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20220809 |
|
| WW01 | Invention patent application withdrawn after publication |