Intelligent culture, identification and analysis system and method for microorganisms

Abstract

The embodiment of the invention relates to and particularly relates to an intelligent microorganism culture, identification and analysis system and an intelligent microorganism culture, identification and analysis method. The system comprises a culture cabinet, the culture cabinet comprises a plurality of culture dishes, a cabinet body, an air conditioner, a controller and a cabinet door, the interior of the cabinet body is divided into a plurality of culture layers through partition plates, each culture layer is provided with a supporting plate, an air inlet, an air outlet, a multicolor illuminating lamp, a camera and an infrared camera, the supporting plates are fixedly connected with the cabinet body, and the air inlet is fixedly connected with the cabinet body. The supporting plate is used for placing a culture dish, the air inlet and the air outlet are formed in the cabinet body and connected with the air conditioner, the air inlet is provided with an air inlet baffle, the air outlet is provided with an air outlet baffle, and the air inlet baffle is provided with an air outlet baffle. The air conditioner, the air inlet baffle, the air outlet baffle, the multicolor illuminating lamp, the camera and the infrared camera are all connected with the controller.

Description

Technical Field

[0001] The multiple embodiments of this specification relate to, specifically, a system and method for intelligent cultivation, identification and analysis of microorganisms. Background Art

[0002] The role of microbial culture identification is to ensure accurate classification and characterization of microorganisms. By identifying specific types of microorganisms, we can better understand the behavior of microorganisms and help deepen our research on microorganisms. In the medical field, microbial culture identification helps to quickly diagnose infectious diseases. In environmental science, it can help assess the health of ecosystems, monitor pollution, and even be used for bioremediation.

[0003] With the continuous advancement of technology, more and more intelligent devices are being integrated into the microbial culture process. For example, the use of automated incubators and shakers can provide a stable and controllable growth environment for microorganisms, while microscope imaging systems and spectrometers can provide in-depth analysis of microorganisms.

[0004] However, although modern technology has effectively improved the accuracy of identification, there is still the possibility of misjudgment, especially when facing new or variant microorganisms. The second is the cost-effectiveness issue. The introduction of high-end equipment and technology is often accompanied by high investment costs, which poses an obstacle to small laboratories or areas with limited resources. To this end, it is necessary to study culture identification technology that can both discover and identify new or variant microorganisms. Summary of the invention

[0005] Multiple embodiments of this specification describe a system and method for intelligent cultivation, identification and analysis of microorganisms.

[0006] In a first aspect, the embodiments of the present specification provide a microbial intelligent culture identification and analysis system, including a culture cabinet, wherein the culture cabinet includes a plurality of culture dishes, a cabinet body, an air conditioner, a controller and a cabinet door, wherein a plurality of culture layers are separated by partitions in the cabinet body, The culture layer is provided with a support plate, an air inlet, an air outlet, a multi-color lighting lamp, a camera, and an infrared camera. The support plate is fixedly connected to the cabinet, and the support plate is used to place the culture dish. The air inlet and the air outlet are arranged on the cabinet, and the air inlet and the air outlet are connected to the air conditioner. The air inlet is provided with an air inlet baffle, and the air outlet is provided with an air outlet baffle. The air conditioner, air inlet baffle, air outlet baffle, multi-color lighting lamp, camera, and infrared camera are all connected to a controller.

[0007] In a second aspect, the embodiments of this specification provide a method for intelligent cultivation and identification analysis of microorganisms, which is applied to the aforementioned intelligent cultivation and identification analysis system of microorganisms. Includes steps: Receiving the temperature setting and the culture time setting of each culture layer, and controlling the air conditioner, the air inlet baffle and the air outlet baffle of the corresponding culture layer according to the temperature setting; When the set culture time is reached, the following steps are performed in a preset detection cycle: Collecting images captured by a plurality of cameras; Identify bacterial plaques and their areas in the culture dish according to the plurality of captured images; identifying the type of bacterial colony based on the image of the bacterial plaque; When the set culture time is reached, a microorganism identification result is generated according to the type of bacterial flora.

[0008] In a third aspect, an embodiment of this specification provides an electronic device, including a processor and a memory; The processor is connected to the memory; The memory is used to store executable program code; The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the method described in any one of the above aspects.

[0009] In a fourth aspect, an embodiment of the present specification provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method described in any of the above aspects.

[0010] In a fifth aspect, an embodiment of this specification provides a computer program product, including a computer program, which implements the method described in any of the above aspects when executed by a processor.

[0011] The beneficial effects brought by the technical solutions provided by some embodiments of this specification include at least: In multiple embodiments of this specification, the provided microbial intelligent culture identification and analysis system can provide a rich culture environment of temperature, light intensity and light color, with a wide range of applications. By setting a culture layer, multiple culture environment settings can be provided. The identification of microbial species is achieved through image recognition, which has the advantages of being fast and efficient. In the case where the colony area is too small, the growth rate is accelerated by actively adjusting the culture environment, and the recognition probability is increased after increasing the colony area. By constructing flora characteristics, the types of microorganisms can be identified through flora characteristics.

[0012] Other features and advantages of the various embodiments of the present specification will be further disclosed in the following detailed description and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of this specification, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0014] Figure 1 Schematic diagram of the microbial intelligent cultivation, identification and analysis system provided in the embodiments of this specification.

[0015] Figure 2 This is a schematic diagram of the system module connections provided in the embodiments of this specification.

[0016] Figure 3 A schematic diagram of an application scenario provided in the embodiments of this specification.

[0017] Figure 4 A schematic diagram of the interactive interface provided in the embodiments of this specification.

[0018] Figure 5 Schematic diagram of the method for intelligent cultivation, identification and analysis of microorganisms provided in the embodiments of this specification.

[0019] Figure 6 A schematic diagram of a method for identifying bacterial species using images provided in an embodiment of this specification.

[0020] Figure 7 A schematic diagram of another method for identifying bacterial species by using images provided in an embodiment of this specification.

[0021] Figure 8 This is a schematic diagram of the change in colony area provided in the examples of this specification.

[0022] Fig. 9 A schematic diagram of another method for identifying bacterial species by using images provided in an embodiment of this specification.

[0023] Fig.10 A schematic diagram of an electronic device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0024] The following is an explanation and description of the technical solutions of the embodiments of this specification in conjunction with the drawings of the embodiments of this specification, but the following embodiments are only preferred embodiments of this specification, not all. Based on the embodiments in the implementation mode, other embodiments obtained by those skilled in the art without creative work are all within the scope of protection of this specification.

[0025] The terms "first", "second", "third", etc. in the description and claims of this specification and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0026] In the following description, terms such as "inside", "outside", "up", "down", "left", "right", etc. that indicate directions or positional relationships are only used to facilitate the description of the embodiments and simplify the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as a limitation of this specification.

[0027] The data involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection of relevant data complies with the relevant laws, regulations and standards of relevant countries and regions.

[0028] Before describing the technical solution in this specification, an introduction is given to the application scenarios and related technologies of the technical solution.

[0029] Microbial culture identification is the process of determining and analyzing microbial species and their characteristics through specific techniques and methods. It is essential for medicine, agriculture, food industry and environmental science. The culture identification process includes sample collection, pretreatment, selective culture, identification and analysis. First, a representative sample is collected from the target environment. The sample is then appropriately pretreated, such as diluted or concentrated, to adapt to the subsequent steps. The sample is inoculated onto a specific selective or differential culture medium and cultured under suitable conditions such as temperature and humidity to allow the target microorganism to grow. As the microorganism grows, it is classified through morphological observation and biochemical tests. Morphological observation is a basic and intuitive step in the process of microbial culture identification. It mainly evaluates the physical characteristics of microorganisms with the naked eye or with the help of a microscope. After cultivation on a plate or slant, different types of microorganisms will form colonies with unique appearances. When observing, researchers pay attention to the size, shape, whether the edges are smooth, color, transparency, and whether the surface texture is smooth, rough or wrinkled. These macroscopic features can provide preliminary classification clues. Furthermore, using an optical microscope, the morphology of microorganisms can be observed at the single-cell level, such as the rod, sphere or spiral shape of bacteria; the filamentous structure of fungi; the oval shape of yeast, etc.

[0030] In practical applications, microbial culture identification technology is widely used in many industries such as healthcare, pharmaceuticals, agriculture, and food and beverages. For example, in the medical field, the rapid and accurate identification of pathogens can guide the selection of antibiotics; in the food industry, understanding the beneficial bacteria in the fermentation process can help improve product quality and safety. Environmental science also relies on accurate microbial identification to assess the health of ecosystems and pollution levels. The healthcare industry uses these technologies to diagnose infectious diseases and develop treatment plans; pharmaceutical companies use them to develop new drugs and ensure drug quality; agriculture studies the structure of microbial communities in soil to promote crop growth and screen antagonistic strains for biological control; the food and beverage industry attaches importance to microbial monitoring in the production process to ensure product safety and good flavor; environmental protection departments rely on microbial testing to evaluate water quality, air quality, and waste treatment effects.

[0031] There are several challenges in the process of microbial culture identification. First, the introduction of contamination during sample collection may affect the accuracy of the results. Second, traditional classification methods have limitations in dealing with the high diversity of microorganisms, and it is difficult to accurately distinguish between a wide variety of microorganisms with similar characteristics. Some microorganisms require special growth conditions to survive, which increases the complexity of isolation and purification. Morphological classification methods rely on visible characteristics such as colony shape, size, color, and cell morphology, but this method is powerless when faced with highly diverse microorganisms. Different types of microorganisms may show extremely similar morphological characteristics, while the same microorganism may present completely different appearances in different environments. In particular, when multiple bacteria are present in a plaque, their co-growth leads to the mixing of morphological characteristics, making morphology-based identification more difficult.

[0032] This specification discloses an improved microbial culture identification scheme. This specification first provides a microbial intelligent culture identification and analysis system. Figure 1 , including a culture cabinet, the culture cabinet includes several culture dishes, a cabinet 8, an air conditioner 11, a controller 10 and a cabinet door 9, the cabinet 8 is separated into several culture layers by a partition 7, the culture layer is provided with a support plate 6, an air inlet 2, an air outlet 5, a multi-color lighting lamp 1, a camera 3, and an infrared camera 4, the support plate 6 is fixedly connected to the cabinet 8, the support plate 6 is used to place the culture dishes, the air inlet 2 and the air outlet 5 are arranged on the cabinet 8, the air inlet 2 and the air outlet 5 are connected to the air conditioner 11, the air inlet 2 is provided with an air inlet baffle, and the air outlet 5 is provided with an air outlet baffle, please refer to the attached Figure 2The air conditioner 11, the air inlet baffle, the air outlet baffle, the multi-color lighting lamp 1, the camera 3, and the infrared camera 4 are all connected to the controller 10. The partition 7 needs to have the functions of light insulation and heat insulation. The partition 7 can be made of polystyrene foam, polyurethane foam or aluminum foil composite material. The temperature of microbial cultivation is generally between 5 and 80 degrees Celsius. When polystyrene foam or polyurethane foam is used, it is more appropriate to set the thickness of the partition 7 to about 50 mm. When aluminum foil composite material is used, it is recommended to be about 5 mm. The light insulation effect of aluminum foil composite material is better.

[0033] In this specification, microbial communities are referred to as flora. The technical solutions recorded in this specification are mainly used for the cultivation and identification of bacteria, but can also be used for other types of microorganisms. The multi-color lighting lamp 1 adopts an intelligent dimming and color-adjusting LED lamp. Each multi-color lighting lamp 1 includes a combination of red, green and blue LED chips, and the brightness of each color LED chip can be adjusted separately, so that the required color and brightness can be adjusted. The infrared camera 4 can play the effect of temperature detection, and the infrared image taken by the infrared camera 4 can reflect the distribution of temperature. When the temperature distribution in the culture layer is uneven, the temperature of each area can also be detected by infrared images. The opening of the air inlet baffle and the air outlet baffle can be adjusted. The temperature of the air outlet 5 of the air conditioner 11 can be adjusted by the air conditioner 11 itself, and the temperature of each culture layer can be adjusted. Exemplarily, the air inlet 2 and the air outlet 5 corresponding to one of the several culture layers can be opened, and the air outlet 5 of the air conditioner 11 is adjusted to the required temperature, but when the temperature of the culture layer reaches the required temperature, the air inlet 2 and the air outlet 5 corresponding to the culture layer are closed. Then, the air inlet 2 and the air outlet 5 of another culture layer are selected to open, and the temperature of the other culture layer is adjusted.

[0034] On the other hand, in another embodiment, a plurality of multicolor illuminators 1 are provided in the culture layer, the plurality of multicolor illuminators 1 are mounted on the cabinet 8 and distributed above the support plate 6, and the infrared camera 4 photographs the support plate 6 from above the support plate 6. The plurality of multicolor illuminators 1 can provide relatively more uniform illumination for each culture layer, and are suitable for achieving uniform illumination conditions.

[0035] On the other hand, in another embodiment, a plurality of cameras 3 are provided in the culture layer, and the plurality of cameras 3 shoot the support plate 6 from above the support plate 6 at different angles, and the plurality of cameras 3 are connected to the controller 10, and the controller 10 runs an image synthesis program for synthesizing the images of the plurality of cameras 3, and the synthesized image makes each culture dish on the support plate 6 an image of the directly above perspective. The synthesis of the image can be performed using the technology disclosed in the art. Exemplarily, the synthesis of the image includes image acquisition, feature point detection and matching, geometric transformation, image alignment and image fusion. In the image acquisition, the camera 3 is used to shoot images of multiple angles from different angles, and there needs to be overlapping parts between the images of multiple angles. It is necessary to ensure that there are overlapping areas between adjacent images so that matching points can be found in the overlapping areas later. Feature point detection and matching includes applying feature detection algorithms (such as SIFT, SURF, ORB, etc.) to identify key points in each image. Through a descriptor matching algorithm (such as a FLANN matcher), corresponding key point pairs are found between images at different angles, that is, representations of the same physical location in different images are found. In the geometric transformation step, the relative geometric relationship (such as rotation and translation) between the images is calculated based on the matched key points. In image alignment, all images are aligned based on the relative geometric relationship so that they share the same coordinate system. Each image is resampled and drawn on a new grid to eliminate distortion caused by perspective changes. Finally, in image fusion, the aligned images are seamlessly fused together to form a complete image.

[0036] On the other hand, please see the attached Figure 3 The microbial intelligent cultivation identification and analysis system provided in this embodiment may include a server 12 and a terminal device 13, or may be used in conjunction with the server 12 and the terminal device 13. The controller 10 establishes a communication connection with the terminal device 13 and the server 12. The terminal device 13 establishes a communication connection with the server 12. The terminal device 13 is provided with an interactive interface 14 for viewing and setting. The interactive interface 14 may be run on the terminal device 13 in the form of a browser, or in the form of an independent application (APP), etc. The specific display form of the client is not limited here. Please refer to the attached Figure 4, is a schematic diagram of the interface for viewing the microbial culture identification result in the interactive interface 14 shown in this embodiment. The server 12 involved in this application can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content distribution networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms. The terminal device 13 can be a smart phone, a tablet computer, a laptop, a PDA, a personal computer, a smart speaker, a smart TV, a smart watch, a vehicle-mounted device, a wearable device, etc., but is not limited to this. The terminal device 13 and the server 12 can be directly or indirectly connected by wired or wireless communication, and this application is not limited here. The number of servers 12 and terminal devices 13 is also not limited.

[0037] On the other hand, this embodiment provides a method for intelligent cultivation and identification analysis of microorganisms, which is executed by the controller 10 of the aforementioned intelligent cultivation and identification analysis system of microorganisms, see the attached Figure 5 , including the steps of: Step S101) receiving the temperature, light intensity and light color settings of each culture layer and the culture time settings, and controlling the air conditioner 11, the air inlet baffle and the air outlet baffle of the corresponding culture layer according to the temperature settings; Step S102) When the set culture time is reached, the following steps are cyclically performed in a preset detection cycle: Step S103) collecting images captured by multiple cameras 3; Step S104) identifying bacterial plaques in the culture dish according to the plurality of captured images; Step S105) identifying the type of bacterial flora according to the bacterial plaque image; Step S106) When the set culture time is reached, a microorganism identification result is generated according to the bacterial species.

[0038] Among them, the method for identifying the plaque and the plaque area in the culture dish according to the captured image includes: synthesizing multiple captured images to obtain an image directly above each culture dish; identifying the plaque and the plaque area in the culture dish according to the image directly above. Specifically, in step S103), after acquiring the captured images of multiple cameras 3, the multiple captured images are synthesized into a composite image. Each culture dish in the composite image is an image directly above. If the color is different from the color of the culture medium in the culture dish, it indicates that the area is a plaque. Similarly, based on the color, the edge of the plaque is obtained. The image of the plaque is obtained by intercepting the image based on the edge of the plaque.

[0039] On the other hand, please see the attached Figure 6 The method for identifying the type of bacterial colony based on the bacterial plaque image includes: Step S201) comparing the bacterial plaque image with a preset reference bacterial colony image library; Step S202) if the similarity of the reference bacterial colony image closest to the bacterial plaque image is higher than a preset threshold, then obtaining the bacterial community type of the bacterial plaque image according to the reference bacterial colony image; Step S203) if the similarity of the reference bacterial colony image closest to the bacterial plaque image is not higher than a preset threshold, the bacterial plaque image is segmented into a plurality of sub-images; Step S204) comparing the plurality of sub-images with the reference bacterial colony image library; Step S205) if the similarity of the reference colony image closest to the sub-image is higher than a preset threshold, obtaining the bacterial colony type corresponding to the sub-image according to the reference colony image; Step S206) obtaining the bacterial flora type of the bacterial plaque image according to the bacterial flora type corresponding to the sub-image.

[0040] The reference colony image library is obtained by the technology disclosed in the art, and can be obtained from the disclosed materials, or obtained by obtaining samples by oneself and then manually annotating them. Image comparison technology can be performed using the technology disclosed in the art. Exemplary, the method of using structural similarity or convolutional neural network to measure the similarity between two images takes into account brightness, contrast and structural information. Feature point matching uses feature detection algorithm. The key points of the image are extracted, and the similarity between images is determined by descriptor matching. This method is highly robust to local changes and geometric transformations. Convolutional neural networks are deep learning models, especially pre-trained CNNs, which can automatically extract image features by learning a large amount of data and are used to compare the contents of different images.

[0041] On the other hand, in another embodiment, please refer to the attached Figure 7 The method for identifying the type of bacterial colony based on the bacterial plaque image also includes: Step S301) obtaining the bacterial species and colony area of ​​the bacterial plaque according to the bacterial species corresponding to the sub-image; Step S302) obtaining the relationship between the growth rate of each bacterial species and the temperature, light intensity and light color; Step S303) obtaining the estimated colony area of ​​each bacterial colony when the set culture time is reached according to the set temperature, light intensity and light color; Step S304) when the estimated colony area of ​​the existing bacterial colony is smaller than the preset area threshold, the bacterial colony with the estimated colony area smaller than the preset area threshold is recorded as a target colony; Step S305) adjusting the temperature, light intensity and light color of the culture layer according to the optimal growth temperature, light intensity and light color of the target bacterial colony; Step S306) when the colony area of ​​the target colony exceeds a preset reference value, obtaining again the species and colony areas of all the colonies included in the bacterial plaque; Step S307) attempts to generate a new culture layer temperature, light intensity and light color so that when the set culture time is reached, the difference between the estimated colony area of ​​the colonies outside the target colony and the estimated colony area when the growth temperature, light intensity and light color are not adjusted is minimized.

[0042] By adjusting the temperature, light intensity and light color of the culture layer, the growth rate of the colony is changed, the growth rate of the colony with an estimated colony area less than the preset area threshold is accelerated, and the colony area is too small to correctly identify the type of colony after the culture is completed. Exemplarily, the most suitable temperature for the growth of Escherichia coli is about 37°C (human body temperature), because this bacterium is usually a normal flora in the intestines of humans and animals. Escherichia coli has no special requirements for light, and it is generally believed that light does not affect its growth. The suitable growth temperature of Staphylococcus aureus is 30-37°C. Similarly, Staphylococcus aureus does not rely on light for growth. The optimal growth temperature of lactobacilli is mostly between 35-40°C. It does not rely on light, and some lactobacilli are anaerobic or microaerophilic. The growth of most bacteria does not require light, and even when light is present, the growth of bacteria may be inhibited. However, microorganisms include not only bacteria, but also some microorganisms that are suitable for culture in an incubator and require light.

[0043] Chlorella has an optimal growth temperature of 20-30°C and light intensity is usually in the range of 5000-10000 lux (lx), depending on the specific experimental conditions. Suitable full-spectrum white light or a combination of blue light (450-495 nm) and red light (620-750nm) is beneficial for its growth. The optimal growth temperature for Spirulina is between 30-35°C. The light intensity is approximately between 3000-10000 lx, and too strong light may inhibit growth. Blue and red light are particularly beneficial for the growth of Spirulina. The optimal growth temperature range for purple non-sulfur bacteria is 25-35°C, with an optimum temperature of about 30°C. Purple non-sulfur bacteria require sufficient light for photosynthesis, but the specific value depends on the culture conditions. Red light or near-infrared light (approximately 680-800 nm) is preferred.

[0044] For example, please see the attached Figure 8, in the state (a) in the figure, the bacterial colony on the left is smaller, and its estimated colony area is less than the preset area threshold, as shown in state (b). Therefore, in step S304), the colony on the left is recorded as the target colony. Adjust the temperature, light intensity and light color of the culture layer to accelerate the growth rate of the bacterial colony on the left. The growth rate of the bacterial colony on the right may accelerate, decrease, or remain unchanged. After a period of time, as shown in state (c), the target colony grows faster and the colony on the right grows slower. Since the target colony already has a certain colony area, that is, it exceeds the preset reference value, at this time in step S307), try to generate a new culture layer temperature, light intensity and light color, so that after the culture is completed, the final colony area of ​​the bacterial colony on the right is basically the same as the estimated colony area at the beginning. Among them, the estimated colony area at the beginning is shown in state (b).

[0045] On the other hand, in another embodiment, the method for identifying the type of flora based on the image of the bacterial plaque further includes: According to the bacterial colony type corresponding to the sub-image, obtaining the bacterial colony type and colony area of ​​the bacterial plaque; When the bacterial plaque includes an unidentified bacterial colony, obtaining an identified bacterial colony that is closest in colony area and colony area growth rate to the unidentified bacterial colony; The temperature, light intensity and light color of the culture layer are adjusted according to the optimal growth temperature, light intensity and light color of the closest identified bacterial colony until the colony area of ​​the unidentified bacterial colony reaches a preset reference value.

[0046] The colony area and colony area growth rate are closest, indicating that the growth requirements of the unidentified bacterial community are close to those of the corresponding bacterial community. By referring to the optimal growth temperature, light intensity and light color of the similar bacterial community, the temperature, light intensity and light color of the culture layer are adjusted to accelerate the growth of the unidentified bacterial community. When the colony area of ​​the unidentified bacterial community is large, the probability of being identified can be increased.

[0047] On the other hand, in another embodiment, a method for identifying a bacterial colony that is difficult to identify through an image is provided. Fig. 9 The method for identifying the type of bacterial colony based on the bacterial plaque image also includes: Step S401) obtaining the bacterial species and colony area of ​​the bacterial plaque according to the bacterial species corresponding to the sub-image; Step S402) when the bacterial plaque includes unidentified bacterial colonies, generating an adjustment plan, the adjustment plan including maintenance time, temperature, light intensity and light color; Step S403) adjusting the temperature, light intensity and light color of the culture layer according to the adjustment scheme, and recording the colony area change rate of the unidentified bacterial colony under each temperature, light intensity and light color; Step S404) The change rate constitutes a flora feature, and the flora feature is compared with the flora features of preset known flora types; Step S405) Obtaining a bacterial species identification result of the unidentified bacterial species according to the known bacterial species closest to the bacterial species characteristic of the unidentified bacterial species.

[0048] The growth characteristics of the bacterial colony are extracted by measuring the growth area change rate of the bacterial colony under multiple temperatures, light intensities and light colors. The bacterial colony characteristics are compared with the bacterial colony characteristics of known bacterial colony types obtained by artificial marking in advance. Thus, the bacterial colony types can be identified by feature comparison, which expands the way of identifying microbial species in this embodiment.

[0049] See also Fig.10 A schematic diagram of the structure of an electronic device provided in an embodiment of this specification is shown.

[0050] like Fig.10 As shown, the electronic device 1100 may include: at least one processor 1101, at least one network interface 1104, a user interface 1103, a memory 1105 and at least one communication bus 1102. Among them, the communication bus 1102 can be used to realize the connection and communication of the above-mentioned components. Among them, the user interface 1103 may include a button, and the optional user interface may also include a standard wired interface and a wireless interface. Among them, the network interface 1104 may include but is not limited to a Bluetooth module, an NFC module, a Wi-Fi module, etc. Among them, the processor 1101 may include one or more processing cores. The processor 1101 uses various interfaces and lines to connect the various parts of the entire electronic device 1100, and executes various functions and processes data of the routing device 1100 by running or executing instructions, programs, code sets or instruction sets stored in the memory 1105, and calling data stored in the memory 1105. Optionally, the processor 1101 can be implemented in at least one hardware form of DSP, FPGA, and PLA. The processor 1101 may integrate one or a combination of CPU, GPU and modem, etc. Among them, the CPU mainly processes the operating system, user interface and application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communication.

[0051] It is understandable that the above-mentioned modem may not be integrated into the processor 1101, but may be implemented by a separate chip.

[0052] Among them, the memory 1105 may include RAM or ROM. Optionally, the memory 1105 includes a non-transitory computer-readable medium. The memory 1105 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 1105 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 1105 may also be at least one storage device located away from the aforementioned processor 1101. The memory 1105 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application. The processor 1101 may be used to call the application stored in the memory 1105 and execute the methods in the above-mentioned multiple embodiments.

[0053] The embodiments of this specification also provide a computer-readable storage medium, which stores instructions, and when the instructions are executed on a computer or a processor, the computer or the processor executes the multiple steps in the above embodiments. If the components of the above electronic device are implemented in the form of software functional units and sold or used as independent products, they can be stored in the computer-readable storage medium.

[0054] The embodiments of this specification also provide a computer program product, including a computer program, which implements multiple steps in the above embodiments when executed by a processor.

[0055] In the absence of conflict, the technical features in this embodiment and implementation scheme can be combined arbitrarily.

[0056] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes a plurality of computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of this specification is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions may be transmitted from a website site, a computer, a server 12 or a data center to another website site, a computer, a server 12 or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server 12, a data center, etc. that includes multiple available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital versatile disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)), etc.

[0057] When implemented by hardware or firmware, the aforementioned method flow is programmed into the hardware circuit to obtain the corresponding hardware circuit structure and realize the corresponding function. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit, and its logic function is determined by the user programming the device. The designer programs by himself to "integrate" a digital system on a PLD, without asking a chip manufacturer to design and make a dedicated integrated circuit chip. Moreover, nowadays, instead of manually making integrated circuit chips, this programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when writing program development, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL), and HDL is not just one, but many. Those skilled in the art should also be aware that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit to easily obtain the hardware circuit that implements the logic method flow.

[0058] The embodiments described above are merely preferred embodiments of this specification and are not intended to limit the scope of this specification. Without departing from the design spirit of this specification, various modifications and improvements made to the technical solutions of this specification by ordinary technicians in this field should fall within the scope of protection determined by the claims of this specification.

Claims

1. A microbial intelligent cultivation identification and analysis system, characterized in that: The invention comprises a culture cabinet, which comprises a plurality of culture dishes, a cabinet body, an air conditioner, a controller and a cabinet door. The cabinet body is separated into a plurality of culture layers by partitions. The culture layer is provided with a support plate, an air inlet, an air outlet, a multi-color lighting lamp, a camera, and an infrared camera. The support plate is fixedly connected to the cabinet, and the support plate is used to place the culture dish. The air inlet and the air outlet are arranged on the cabinet, and the air inlet and the air outlet are connected to the air conditioner. The air inlet is provided with an air inlet baffle, and the air outlet is provided with an air outlet baffle. The air conditioner, air inlet baffle, air outlet baffle, multi-color lighting lamp, camera, and infrared camera are all connected to a controller.

2. A microbial intelligent cultivation identification and analysis system according to claim 1, characterized in that: A plurality of cameras are arranged in the culture layer, and the plurality of cameras photograph the support plate from above the support plate at different angles. The plurality of cameras are connected to a controller, and the controller runs an image synthesis program for synthesizing the images of the plurality of cameras. The synthesized image enables each culture dish on the support plate to be an image from a perspective directly above.

3. A method for intelligent cultivation and identification analysis of microorganisms, applied to a system for intelligent cultivation and identification analysis of microorganisms as claimed in claim 2, characterized in that: Includes steps: Receiving the temperature, light intensity, light color setting and culture time setting of each culture layer, and controlling the air conditioner, the air inlet baffle and the air outlet baffle of the corresponding culture layer according to the temperature setting; When the set culture time is reached, the following steps are performed in a preset detection cycle: Collecting images captured by multiple cameras; identifying bacterial plaques in the culture dish according to the plurality of captured images; identifying the type of bacterial colony based on the image of the bacterial plaque; When the set culture time is reached, a microorganism identification result is generated according to the type of bacterial flora.

4. A method for intelligent cultivation, identification and analysis of microorganisms according to claim 3, characterized in that: The method for identifying bacterial plaque and the area of ​​bacterial plaque in a culture dish according to the captured image comprises: The multiple captured images are synthesized to obtain an image directly above each culture dish; The bacterial plaques and the plaque areas in the culture dish are identified according to the image directly above.

5. A method for intelligent cultivation, identification and analysis of microorganisms according to claim 3 or 4, characterized in that: The method for identifying the type of bacterial colony based on the bacterial plaque image comprises: Comparing the bacterial plaque image with a preset reference bacterial colony image library; If the similarity of the reference bacterial colony image closest to the bacterial plaque image is higher than a preset threshold, obtaining the bacterial colony type of the bacterial plaque image according to the reference bacterial colony image; If the similarity of the reference bacterial colony image closest to the bacterial plaque image is not higher than a preset threshold, segmenting the bacterial plaque image into a plurality of sub-images; Comparing the plurality of sub-images with the reference colony image library; If the similarity of the reference colony image closest to the sub-image is higher than a preset threshold, obtaining the type of bacterial colony corresponding to the sub-image according to the reference colony image; The bacterial colony type of the bacterial plaque image is obtained according to the bacterial colony type corresponding to the sub-image.

6. A method for intelligent cultivation, identification and analysis of microorganisms according to claim 5, characterized in that: The method for identifying the type of bacterial colony based on the bacterial plaque image also includes: According to the bacterial colony type corresponding to the sub-image, obtaining the bacterial colony type and colony area of ​​the bacterial plaque; Obtaining the relationship between the growth rate of each bacterial species and temperature, light intensity and light color; According to the set temperature, light intensity and light color, the estimated colony area of ​​each bacterial colony is obtained when the set culture time is reached; When the estimated colony area of ​​the existing bacterial colony is less than the preset area threshold, the bacterial colony with the estimated colony area less than the preset area threshold is recorded as the target colony; Adjusting the temperature, light intensity and light color of the culture layer according to the optimal growth temperature, light intensity and light color of the target bacterial colony; When the colony area of ​​the target colony exceeds a preset reference value, obtaining again the species and colony areas of all the flora included in the bacterial plaque; The temperature, light intensity and light color of the new culture layer are attempted to be generated so that when the set culture time is reached, the difference between the estimated colony area of ​​the colonies outside the target colony and the estimated colony area when the growth temperature, light intensity and light color are not adjusted is minimized.

7. A method for intelligent cultivation, identification and analysis of microorganisms according to claim 5, characterized in that: The method for identifying the type of bacterial colony based on the bacterial plaque image also includes: According to the bacterial colony type corresponding to the sub-image, obtaining the bacterial colony type and colony area of ​​the bacterial plaque; When the bacterial plaque includes unidentified bacterial colonies, generating an adjustment plan, the adjustment plan including maintenance time, temperature, light intensity and light color; Adjusting the temperature, light intensity and light color of the culture layer according to the adjustment scheme, and recording the colony area change rate of the unidentified bacterial colony under each temperature, light intensity and light color; The change rate constitutes a flora characteristic, and the flora characteristic is compared with the flora characteristics of preset known flora types; A flora type identification result of the unidentified flora is obtained according to a known flora type that is closest to the flora characteristics of the unidentified flora.

8. An electronic device, characterized in that including a processor and a memory; The processor is connected to the memory; The memory is used to store executable program code; The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the method according to any one of claims 3 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 3 to 7 is implemented.

10. Computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 3 to 7 is implemented.

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