CN111638190A - Plant growth monitoring method and plant growth cabinet - Google Patents
Plant growth monitoring method and plant growth cabinet Download PDFInfo
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- CN111638190A CN111638190A CN202010389134.2A CN202010389134A CN111638190A CN 111638190 A CN111638190 A CN 111638190A CN 202010389134 A CN202010389134 A CN 202010389134A CN 111638190 A CN111638190 A CN 111638190A
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- 238000000034 method Methods 0.000 title claims abstract description 33
- 230000008635 plant growth Effects 0.000 title claims abstract description 33
- 238000012544 monitoring process Methods 0.000 title claims abstract description 19
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 33
- 238000002835 absorbance Methods 0.000 claims abstract description 21
- 241000196324 Embryophyta Species 0.000 claims description 176
- 238000013528 artificial neural network Methods 0.000 claims description 10
- 230000008569 process Effects 0.000 claims description 7
- 230000012010 growth Effects 0.000 claims description 5
- 238000010521 absorption reaction Methods 0.000 claims description 4
- 230000003595 spectral effect Effects 0.000 claims description 2
- 235000013311 vegetables Nutrition 0.000 abstract description 14
- 241000208822 Lactuca Species 0.000 description 7
- 235000003228 Lactuca sativa Nutrition 0.000 description 7
- 230000009471 action Effects 0.000 description 3
- 238000013527 convolutional neural network Methods 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 235000013399 edible fruits Nutrition 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000000862 absorption spectrum Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 235000013305 food Nutrition 0.000 description 1
- 235000021384 green leafy vegetables Nutrition 0.000 description 1
- 230000001678 irradiating effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000036651 mood Effects 0.000 description 1
- 230000008092 positive effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000033764 rhythmic process Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
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- 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
- A01G9/00—Cultivation in receptacles, forcing-frames or greenhouses; Edging for beds, lawn or the like
- A01G9/02—Receptacles, e.g. flower-pots or boxes; Glasses for cultivating flowers
Abstract
The application relates to the technical field of planting in general, and particularly relates to a plant growth monitoring method and a plant growth cabinet, wherein the plant growth monitoring method comprises the steps of obtaining plant image information; identifying the plant type according to the image information of the plant; determining an infrared band corresponding to the plant based on an infrared spectrum database; according to the scheme, plant image information is obtained, plant types are determined, the infrared rays corresponding to the plant types and the infrared spectrum wave bands are transmitted to the plants based on the corresponding relation of the plant types and the infrared spectrum wave bands according to the infrared spectrum technology, the absorbance of the obtained plants is determined, the maturity of the plants is determined according to the absorbance of the plants, the identification precision of the maturity of the plants is improved, and the fact that people eat fresh vegetables is guaranteed.
Description
Technical Field
The application relates to the technical field of planting in general, and particularly relates to a plant growth monitoring method and a plant growth cabinet.
Background
Along with the development of the society, the urbanization process of China is accelerated, more and more people are moved to cities from rural areas, although the life of the cities is more convenient, the land resources of the cities are limited, the greening area is small, the plant growth cabinet enables people to plant favorite plants in a limited space, the problems of insufficient land resources, less greening and vegetable eating by people are solved, the mood is joyful, the life quality is improved, the harm of food safety problems to people is reduced, the modern life rhythm is fast, people probably cannot pay attention to the plant growth condition in the plant growth cabinet all the time, the maturity of the plants cannot be accurately identified through naked eyes, the plants are over mature, and the people cannot eat the freshest vegetables.
Disclosure of Invention
In this summary, concepts in a simplified form are introduced that are further described in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
In order to solve the technical problem that the maturity of the plant cannot be accurately identified by naked eyes, the main purpose of the application is to provide a plant growth monitoring method and a plant growth cabinet.
In order to achieve the purpose of the invention, the following technical scheme is adopted in the application:
a plant growth monitoring method comprising:
acquiring plant image information;
identifying the plant type according to the image information of the plant;
determining an infrared band corresponding to the plant based on an infrared spectrum database;
and emitting infrared rays with corresponding wave bands to the plants, and generating the plant maturity state information according to the absorption degree of the plants to the infrared rays.
Further, in an embodiment of the present disclosure, the acquiring the plant image information includes:
and obtaining leaf image information of the plants by photographing.
Further, in an embodiment of the present disclosure, identifying a plant type according to the image information of the plant includes:
establishing a plant convolution neural network algorithm model;
inputting the image information of the plant into a plant convolution neural network algorithm model and extracting the characteristics.
Further, in an embodiment of the present disclosure, the plant type is calculated according to the extracted plant characteristics by a formula:
y＝Softmax(fi)
and fi represents the extracted characteristics of each plant type, i is different plant types, wherein i is a natural number, and the classification and identification results are output through a softmax function.
Further, in an embodiment of the present disclosure, the infrared spectrum database includes comparison data of different plant species and infrared spectrum bands.
Further, in an embodiment of the present disclosure, the generating the plant maturity status information includes:
the maturity is set according to the absorbance of the plant.
Further, in an embodiment of the present disclosure, the generating the plant maturity status information comprises:
setting a reminding threshold value according to the maturity of the plant;
and if the plant maturity is greater than or equal to the reminding threshold, reminding a user to process.
Further, in an embodiment of the present disclosure, if the plant maturity is less than the threshold, the plant image information is obtained again at preset time intervals.
A plant growth cabinet comprising:
a cabinet body;
the image collector is used for obtaining the image information of the plants in the growth cabinet;
the control processor is used for determining the plant type according to the image information of the plant and determining the infrared wave band corresponding to the plant based on the corresponding database of the plant type and the infrared spectrum;
the infrared spectrum device emits infrared rays to the plants according to the infrared wave band determined by the control processor;
and the photoelectric converter is used for receiving the infrared rays reflected by the plants, converting the infrared rays into electric signals and sending the electric signals to the control processor, so that the control processor generates maturity information according to the absorbance of the plants.
Further, in an embodiment of the present disclosure, the image collector, the infrared spectrometer, and the photoelectric converter are movably disposed in the cabinet body through a ball screw structure.
Known by the above technical scheme, the advantage and the positive effect of the vegetation monitoring method and vegetation cabinet of this application lie in:
the plant species is identified, the plant growth maturity is determined according to the plant species, the growth of various plants can be monitored, and the maturity identification accuracy is high.
According to the scheme, plant image information is obtained, the plant type is determined, corresponding infrared light is emitted to the plant based on the corresponding relation between the plant type and the infrared spectrum wave band according to the infrared spectrum technology, the absorbance of the plant is obtained, and the maturity of the plant is determined according to the absorbance of the plant.
This scheme still provides a plant growth cabinet, and the maturity that the plant can be monitored to the growth cabinet improves the plant maturity recognition accuracy, guarantees that people eat and use fresh vegetables.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
FIG. 1 is a schematic flow diagram illustrating a method for monitoring plant growth according to an exemplary embodiment.
FIG. 2 is another schematic diagram illustrating a method of monitoring plant growth according to an exemplary embodiment.
FIG. 3 is a table of plant species versus infrared spectral wavelength for a method of plant growth monitoring, according to an exemplary embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application. In this application, the terms "upper", "lower", "inner", "middle", "outer", "front", "rear", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings. These terms are used primarily to better describe the present application and its embodiments, and are not used to limit the indicated devices, elements or components to a particular orientation or to be constructed and operated in a particular orientation. Moreover, some of the above terms may be used to indicate other meanings besides the orientation or positional relationship, for example, the term "on" may also be used to indicate some kind of attachment or connection relationship in some cases. The specific meaning of these terms in this application will be understood by those of ordinary skill in the art as appropriate.
The scheme provides a plant growth detection method and a plant growth cabinet, which are used for monitoring the maturity of vegetable plants, solving the technical problem of low visual identification precision of the maturity of vegetables and ensuring that people eat fresh vegetables.
As shown in fig. 1, the plant growth detection method comprises:
s01: acquiring plant image information;
s02: identifying the plant type according to the plant image information;
s03: determining an infrared band corresponding to the plant based on an infrared spectrum database;
s04: and emitting infrared rays with corresponding wave bands to the plants, and generating plant maturity state information according to the absorption of the plants to the infrared rays.
S05: setting a reminding threshold value according to the plant maturity, and judging whether the plant maturity is greater than the threshold value;
s06: if the maturity of the plant is greater than the reminding threshold, reminding a user to process;
s07: and if the maturity of the plant is smaller than the reminding threshold, acquiring the image information of the plant again at preset time intervals for identification and judgment.
Steps S06 and S07 select one of them to be performed.
Specifically, a plant convolution neural network algorithm model is established, image information of the plant is transmitted to the plant convolution neural network algorithm model, characteristic information in the plant image is extracted according to the plant convolution neural network algorithm model, and the extracted plant characteristics are used for classification, and the method comprises the following steps:
y＝Softmax(fi) i＝0,1,···n
in the above formula, fi represents the extracted features of each plant type, i is different plant types, and the classification and identification results are output through the softmax function.
When i is equal to 1, the plant is represented as a first type plant, f1 represents the plant characteristics of the first type plant extracted by the plant convolutional neural network algorithm model, and y represents the type of plant to which the recognition result belongs.
The method is characterized in that the plant type identification and infrared spectrum detection maturity are combined, and infrared rays are emitted corresponding to the plant type.
The infrared spectrum technology is that molecules selectively absorb infrared rays with certain wavelengths to cause the transition of vibration energy level and rotation energy level in the molecules, and the infrared absorption spectrum of a substance can be obtained by detecting the absorption condition of the infrared rays.
FIG. 3 is a table of infrared spectra of a portion of a plant species; the infrared spectrum database comprises comparison data of plant species and infrared spectrum bands, the absorbance of the plant is determined according to the infrared spectrum technology, and the maturity of the plant is determined according to the absorbance.
The method comprises the steps of obtaining leaf image information of plants in a photographing mode, transmitting the leaf image information of the plants to a plant convolutional neural network algorithm model, obtaining the types of the plants by using a formula, determining infrared ray wave bands corresponding to the plants based on an infrared spectrum database, emitting infrared rays of corresponding wave bands to the plants, setting the maturity according to the absorbance of the plants, determining the absorbance of the plants to the infrared rays, and generating plant maturity state information.
The scheme is used for preparing edible stem and leaf vegetables, and leaves of plants are irradiated by infrared rays.
The method comprises the steps of firstly obtaining image information of a plant, extracting the color, texture, shape and other characteristics of lettuce leaves according to a plant convolution neural network algorithm model, determining the plant to be lettuce according to a formula, determining the infrared spectrum of the lettuce in a 500nm-800nm wave band through an infrared spectrum database, irradiating the lettuce leaves by adopting infrared rays in the 500nm-800nm wave band to obtain the absorbance of the lettuce leaves, and obtaining the maturity of the lettuce according to the relation between the absorbance and the maturity.
It should be noted that, in the present embodiment, the corresponding relationship between the absorbance and the maturity of different plants may be preset, and the maturity range of a plant may be defined as-1 to 1, when the maturity is 0, the plant is completely mature, when the maturity is-0.9, the plant is mature by 90%, and so on, when the maturity is 0.2, the plant is more than 20% of the complete maturity.
When the plants are green vegetables, firstly acquiring image information of the plants, extracting leaf color, texture characteristics and shapes of the green vegetables according to a plant convolution neural network algorithm model, determining that the plants are the green vegetables according to a formula, and determining that the infrared spectrum of the green vegetables is in a 800nm-1000nm wave band through an infrared spectrum database, so that the green vegetables are irradiated by infrared rays in the 800nm-1000nm wave band, then acquiring the absorbance of the green vegetables, and obtaining the maturity of the lettuce according to the relation between the absorbance and the maturity.
In the scheme, a reminding threshold value is set according to the maturity of the plant, if the maturity of the plant is greater than or equal to the threshold value, a user is reminded of processing, and if the maturity of the plant is smaller than the threshold value, the image information of the plant is acquired again at intervals of preset time. It is also contemplated that the time may be set to one day, two days, or three days.
This scheme still provides a vegetation cabinet, includes:
a cabinet body;
the image collector is used for obtaining the image information of the plants in the growth cabinet;
the control processor is used for determining the plant type according to the image information of the plant and determining the infrared wave band corresponding to the plant based on the corresponding database of the plant type and the infrared spectrum;
the infrared spectrum device emits infrared rays to the plants according to the infrared wave band determined by the control processor;
and the photoelectric converter is used for receiving the infrared rays reflected by the plants, converting the infrared rays into electric signals and sending the electric signals to the control processor, so that the control processor generates maturity information according to the absorbance of the plants.
The image collector, the infrared spectrometer and the photoelectric converter are movably arranged in the cabinet body through ball screw structures respectively.
Driven by the ball screw structure, the image collector, the infrared spectrometer and the photoelectric converter move up and down to better collect the image information of the plants, the image collector collects the image information of the plants and sends the image information to the control processor, the control processor obtains the plant species according to the plant convolution neural network algorithm model, according to the comparison data of the plant species and the infrared spectrum wave band, the infrared spectrum wave band corresponding to the plant is determined, the control processor controls the infrared spectrum device to emit infrared rays to the leaves or the fruits of the plant, when the image is collected, the plant can be photographed in a large area, if plant fruits exist in the image, the fruit is preferentially irradiated with infrared rays, the photoelectric converter receives the infrared rays reflected by the plant, and the signals are converted into electric signals to be sent to a control processor, and the control processor generates maturity information according to the absorbance of the plants.
In the scheme, a plant convolutional neural network algorithm model, comparison data of plant types and infrared spectrum bands and a comparison data table of absorbance and maturity of different plants are prestored in a control processor, the corresponding relation between the absorbance and maturity of different plants is set, the maturity range of the plants can be defined as-1 to 1, when the maturity is 0, the plants are completely mature, when the maturity is-0.9, the plants are mature by 90%, and by analogy, when the maturity is 0.2, the plants are mature by more than 20%.
In this embodiment, still can set up display and siren at the cabinet body, the display is used for showing plant species and maturity, and the person of facilitating the use looks over the ripe state of plant to guarantee that people eat and use fresh vegetables. The plant maturity of 0.2 can be set as the reminding threshold, and when the plant maturity exceeds 0.2, the user is reminded to handle in time.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present invention, which enable those skilled in the art to understand or practice the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for monitoring plant growth, comprising:
acquiring plant image information;
identifying the plant type according to the image information of the plant;
determining an infrared band corresponding to the plant based on an infrared spectrum database;
and emitting infrared rays with corresponding wave bands to the plants, and generating the plant maturity state information according to the absorption degree of the plants to the infrared rays.
2. The plant growth monitoring method according to claim 1, wherein the acquiring plant image information comprises:
and obtaining leaf image information of the plants by photographing.
3. The plant growth monitoring method of claim 1, wherein identifying a plant species from the image information of the plant comprises:
establishing a plant convolution neural network algorithm model;
inputting the image information of the plant into a plant convolution neural network algorithm model and extracting the characteristics.
4. The plant growth monitoring method according to claim 3, wherein the plant species is calculated by the formula according to the extracted plant characteristics:
y＝Softmax(fi)
and fi represents the extracted characteristics of each plant type, i is different plant types, wherein i is a natural number, and the classification and identification results are output through a softmax function.
5. A plant growth monitoring method according to claim 1, wherein the infrared spectra database comprises different plant species versus infrared spectral band control data.
6. The plant growth monitoring method of claim 1, wherein generating plant maturity status information comprises:
the maturity is set according to the absorbance of the plant.
7. The method of claim 1, wherein generating the plant maturity status information comprises:
setting a reminding threshold value according to the maturity of the plant;
and if the plant maturity is greater than or equal to the reminding threshold, reminding a user to process.
8. The plant growth monitoring method according to claim 7, wherein if the plant maturity is less than the threshold, the plant image information is acquired again at a preset time interval.
9. A plant growth cabinet, comprising:
a cabinet body;
the image collector is used for obtaining the image information of the plants in the growth cabinet;
the control processor is used for determining the plant type according to the image information of the plant and determining the infrared wave band corresponding to the plant based on the corresponding database of the plant type and the infrared spectrum;
the infrared spectrum device emits infrared rays to the plants according to the infrared wave band determined by the control processor;
and the photoelectric converter is used for receiving the infrared rays reflected by the plants, converting the infrared rays into electric signals and sending the electric signals to the control processor, so that the control processor generates maturity information according to the absorbance of the plants.
10. The plant growth cabinet according to claim 9, wherein the image collector, the infrared spectrometer and the photoelectric converter are movably disposed in the cabinet body through a ball screw structure.
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| CN113218898A (en) * | 2021-05-06 | 2021-08-06 | 塔里木大学 | Plant disease remote sensing feature extraction method based on spectral analysis |
| CN114973001A (en) * | 2022-06-17 | 2022-08-30 | 东北林业大学 | Wetland plant growth information monitoring method |
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Application publication date: 20200908 |