Algae information management device, program, and algae information management method

Abstract

To provide an algae information management apparatus, a program, and an algae information management method which make it possible to reduce the time and effort required to measure the protein content of microalgae.SOLUTION: An algae information management apparatus according to embodiments includes an input unit, an identification unit, and a storage unit. The input unit receives input of first identification information given for each measurement microalgae. The identification unit identifies second identification information given to a color sample closest to a color of the microalgae among a plurality of color samples for comparison with the color of the microalgae. The storage unit stores the first identification information and the second identification information in association with each other.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to an algae information management device, a program, and an algae information management method.

Background Art

[0002] The components of algae change depending on the environment in which they are grown. Since the environment varies by region, the components of algae change depending on the region where they are grown.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Algae have suitable uses depending on their protein content. As described above, the components of algae change depending on the environment in which they are grown. Therefore, in order to use algae for suitable purposes, it is necessary to measure the protein content of the algae.

[0005] The problem to be solved by the embodiments of the present invention is to provide an algae information management device, a program, and an algae information management method that can reduce the labor of measuring the protein content of microalgae.

Means for Solving the Problems

[0006] The algae information management device according to the embodiment includes an input unit, a specifying unit, and a storage unit. The input unit receives an input of first identification information assigned to each microalgae for measurement. The specifying unit specifies second identification information assigned to the color sample that is closest to the color of the microalgae among a plurality of color samples for comparison with the color of the microalgae. The storage unit stores the first identification information and the second identification information in association with each other.

Effects of the Invention

[0007] This invention can reduce the effort required to measure the protein content of microalgae. [Brief explanation of the drawing]

[0008] [Figure 1] A block diagram showing an example of the main components of a management system and its constituent elements according to the first and second embodiments. [Figure 2] A flowchart showing an example of processing performed by the processor in Figure 1. [Figure 3] Figure 1 shows an example of a screen displayed on the display device. [Figure 4] A flowchart showing an example of processing performed by the processor in Figure 1. [Modes for carrying out the invention]

[0009] The following describes several embodiments of a management system with reference to drawings. Note that the scale of the parts in the drawings used in the following description of embodiments may be appropriately changed. Also, for illustrative purposes, some components may be omitted from the drawings used in the following description of embodiments. Furthermore, in the drawings and this specification, the same reference numerals indicate the same elements. [First Embodiment] Figure 1 is a block diagram showing an example of the main components of the management system 1 and its components according to the first embodiment. However, the color chart 200 is shown in appearance. Note that each component of each device may be built-in or external. Management system 1 is a system for storing and managing the evaluation results and classification results of algae. The algae used in management system 1 are, for example, those grown using a culture device for culturing algae. Alternatively, the algae used in management system 1 may be, for example, dried algae. Furthermore, the algae used in management system 1 are microalgae. Preferably, the microalgae used in management system 1 are microalgae belonging to Chlamydomonas reinhardi. This is because the protein content of microalgae belonging to Chlamydomonas reinhardi can be easily identified from the color of the microalgae. More preferably, the microalgae used in management system 1 are Honda® DREAMO strain (accession number: FERM BP-22306). This is because the protein content of Honda DREAMO strain can be easily identified from the color of the microalgae.

[0010] Furthermore, the evaluation results managed by Management System 1 refer to the results of protein evaluation, which measures the protein content of algae. In addition, the classification results managed by Management System 1 refer to the results of the use classification process, which classifies algae according to their intended use based on their protein content.

[0011] Management system 1 includes, for example, a control device 100 and a color chart 200. However, management system 1 may include only a portion of these components.

[0012] The management device 100 is a device that stores and manages the evaluation and classification results of algae. The management device 100 is a general-purpose device such as a PC (personal computer), smartphone, or server device. Alternatively, the management device 100 may be a device dedicated to management system 1. The management device 100 includes, as an example, a processor 110, ROM (read-only memory) 120, RAM (random-access memory) 130, auxiliary storage device 140, communication interface 150, input device 160, display device 170, and camera 180. A bus 190, etc., connects these parts. Note that the management device 100 is an example of an algae information management device.

[0013] The processor 110 is the central part of the computer that performs calculations and control necessary for the operation of the management device 100, and performs various calculations and processes. The processor 110 is, for example, a CPU (central processing unit), MPU (micro processing unit), SoC (system on a chip), DSP (digital signal processor), GPU (graphics processing unit), ASIC (application specific integrated circuit), PLD (programmable logic device), or FPGA (field-programmable gate array). Alternatively, the processor 110 is a combination of several of these. Furthermore, the processor 110 may also be a combination of these with hardware accelerators. Based on programs such as firmware, system software, and application software stored in the ROM 120 or auxiliary storage device 140, the processor 110 controls each part to realize various functions of the management device 100. The processor 110 also executes the processes described later based on the said programs. Note that some or all of the said programs may be incorporated into the circuit of the processor 110.

[0014] ROM120 and RAM130 are the main memory of the computer, with the processor 110 at its core. ROM120 is a non-volatile memory used exclusively for reading data. ROM120 stores programs such as firmware. It also stores data used by the processor 110 in performing various processes.

[0015] RAM130 is memory used for reading and writing data. RAM130 is used as a work area to store data that the processor 110 temporarily uses when performing various processes. RAM130 is typically volatile memory.

[0016] The auxiliary storage device 140 is an auxiliary storage device for a computer centered around the processor 110. The auxiliary storage device 140 is, for example, an EEPROM (electric erasable programmable read-only memory), an HDD (hard disk drive), or flash memory. The auxiliary storage device 140 stores, for example, system software and application software from the above-mentioned programs. The auxiliary storage device 140 also stores data used by the processor 110 in performing various processes, data generated by processing by the processor 110, and various setting values.

[0017] The auxiliary storage device 140 stores the above data, for example, the sample database 141, the environment database 142, color sample information, and classification information.

[0018] Sample DB141 is a database that stores and manages information about algae measurement samples. For each algae measurement sample, Sample DB141 stores associated information such as Sample ID, Cultivation ID, Sample Evaluation Information, Sample Classification Information, and Measurement Date and Time Information. The Sample ID is a unique identifier for each measurement sample. The Cultivation ID is a unique identifier for each algae cultivation environment. The Cultivation ID associated with the Sample ID indicates that the cultivation environment of the measurement sample identified by that Sample ID is the cultivation environment identified by that Cultivation ID. The Sample Evaluation Information is information that shows the evaluation result of the protein evaluation of the measurement sample identified by that Sample ID. The Sample Evaluation Information includes Sample Color Information and Sample Protein Information. The Sample Color Information is a color that indicates the color of the measurement sample. The Sample Protein Information is information that indicates the protein content of the measurement sample. The Sample Classification Information is information that shows the result of the usage classification processing of the measurement sample identified by that Sample ID.

[0019] The environmental database 142 is a database that stores and manages information regarding the cultivation environment in which algae are cultivated. The environmental database 142 stores, for example, for each cultivation environment, cultivation information, environmental evaluation information, and environmental classification information in association with a cultivation ID. The cultivation ID is unique identification information for each cultivation environment. The cultivation information is information indicating the cultivation environment. The cultivation information includes, for example, information indicating the cultivation region. Also, the cultivation information may include information indicating the cultivation time. Further, the cultivation information may include information regarding temperature, humidity, sunshine hours, or other weather. The environmental evaluation information associated with the cultivation ID is information indicating the evaluation result of the protein evaluation of the algae cultivated in the cultivation environment specified by the cultivation ID. The environmental evaluation information includes environmental color information and environmental protein information. The environmental color information is information indicating the color of the algae cultivated in the cultivation environment. The environmental protein information is information indicating the protein content of the algae cultivated in the cultivation environment. The environmental classification information associated with the cultivation ID is information indicating the result of the use classification process of the algae cultivated in the cultivation environment specified by the cultivation ID. Note that the environmental evaluation information and environmental classification information associated with the cultivation ID are based on the evaluation result and use classification process of the measurement sample specified by the sample ID associated with the cultivation ID.

[0020] The color sample information is information indicating the relationship between the color of the algae and the protein content of the algae. Algae have the property that their color varies depending on the protein content. The color sample information stores, for example, the protein content for each color of the algae by associating a color ID with the protein content. The color ID is uniquely defined identification information for each color. The color ID may be a number dedicated to the management system 1, or may be a number used outside the management system 1 such as a color code. The color sample information can be created in advance, for example, by measuring the protein content of algae of various colors.

[0021] The classification information is information indicating the suitable usage of the algae for each protein content. Examples of the usage of the algae include biofuel, bioplastic, feed, alternative meat, food, cosmetics, supplements, and vaccines.

[0022] The classification information indicates, as an example, that the use of algae with a protein content of at least the threshold TH1 is as a protein source. The classification information also indicates that the use of algae with a protein content less than the threshold TH1 is as a starch source. The threshold TH1 is a predetermined value, for example, 50%. The classification information also indicates that the uses of algae as a starch source are for sugar production, ethyl alcohol production, liquid fuel production, solid fuel production, and bioplastic production, etc.

[0023] The communication interface 150 is an interface for the management device 100 to communicate via a network NW or the like.

[0024] The input device 160 receives operations by an operator of the management device 100 (hereinafter simply referred to as the "operator"). The input device 160 is, for example, a keyboard, keypad, touch pad, mouse, or controller, etc. The input device 160 may also be a device for voice input.

[0025] The display device 170 displays a screen for notifying various information to an operator or the like. The display device 170 is, for example, a display such as a liquid crystal display or an organic EL (electro - luminescence) display. Also, as the input device 160 and the display device 170, a touch panel can be used. That is, the display panel included in the touch panel can be used as the display device 170, and the pointing device by touch input included in the touch panel can be used as the input device 160.

[0026] The camera 180 takes pictures. The camera 180 also outputs the taken image data. Note that a moving image is a kind of image.

[0027] The bus 190 includes a control bus, an address bus, a data bus, etc., and transmits signals exchanged between each part of the management device 100.

[0028] The color chart 200 is a device used for protein evaluation. As mentioned earlier, algae have the property of having different colors depending on their protein content. The color chart 200 can measure the protein content of algae by utilizing this property. The color chart 200 includes several types of color samples 201. Different types of color samples 201 are colored with different colors. The protein content is determined for each color of algae. Each color sample 201 is also assigned a corresponding number. This number is the color ID of the color colored on the color sample 201. The color chart 200 shown in Figure 1 includes 12 types of color samples 201 as an example. Each of these 12 types of color samples 201 is assigned a number from 1 to 12. This number from 1 to 12 is the color ID.

[0029] By comparing the color of the algae with color sample 201 and selecting the color sample 201 that is closest in color to the algae in question, it is possible to measure the protein content of the algae.

[0030] Note that while the arrangement of the color samples 201 shown in Figure 1 is radial, other arrangements such as a matrix are also acceptable. Furthermore, the color chart 200 shown in Figure 1 contains all the color samples 201 as a single unit. However, the color chart 200 may be composed of multiple separate sections.

[0031] The operation of the management system 1 according to this embodiment will be described below with reference to Figure 2 and other figures. Note that the processing content in the following operation description is just an example, and various processing that can obtain similar results can be used as appropriate. Figure 2 is a flowchart showing an example of processing by the processor 110 of the management device 100. The processor 110 executes the processing shown in Figure 2 based on a program stored, for example, in the ROM 120 or auxiliary storage device 140.

[0032] In step ST11 of Figure 2, the processor 110 of the management device 100 generates an image corresponding to screen SC1 as shown in Figure 3. The processor 110 then instructs the display device 170 to display this generated image. Upon receiving the display instruction, the display device 170 displays screen SC1.

[0033] Figure 3 shows an example of screen SC1 displayed on display device 170. Screen SC1 is for inputting information necessary for protein evaluation of algae measurement samples. Screen SC1 also displays the cultivation information of the measurement sample, the protein content based on the protein evaluation, and the classification results. Screen SC1 includes, as an example, areas AR11 to AR15 and button B11.

[0034] Area AR11 is an input field for entering the sample ID of the measurement sample used for protein evaluation.

[0035] Region AR12 is the region that displays the growth ID of the measurement sample identified by the sample ID entered in region AR11.

[0036] Area AR13 is the area that displays training information identified by the training ID displayed in Area AR12.

[0037] Area AR14 is an input field for entering the color ID that indicates the evaluation result of the measurement sample.

[0038] Area AR15 is the area that displays the protein content of the measurement sample based on the evaluation results of the protein assessment.

[0039] Area AR16 is the area that displays the classification results of the measurement sample. As a result of this classification, area AR16 displays, for example, suitable applications for the measurement sample. Note that, at the time of processing in step ST11, screen SC1 typically shows areas AR11 to AR16 as blank.

[0040] Button B11 is a button operated by the operator to confirm the evaluation results and classification results of the protein assessment. Button B11 is a button operated by the operator to instruct the control device 100 to store the evaluation results and classification results.

[0041] In step ST12, the processor 110 determines whether or not the sample ID has been read. The sample ID may be manually entered into area AR11 or read using the camera 180. For example, a container containing a sample for measurement displays the sample ID. For example, the container displays the sample ID by printing it. The sample ID printed on the container may be text or a barcode that stores the sample ID. The barcode may be a one-dimensional code or a two-dimensional code. For the determination in step ST12, the processor 110 acquires an image captured by the camera 180. Then, the processor 110 attempts to read the sample ID from the image. If the sample ID is visible in the image, the processor 110 reads the sample ID by image processing. Unless the sample ID has been read, the processor 110 determines No in step ST12 and proceeds to step ST13.

[0042] The sample ID is an example of the first identification information. Therefore, the processor 110 functions as an example of an input unit that receives the first identification information by reading the sample ID. Furthermore, the processor 110 functions as an example of an input unit that receives the first identification information by reading the first identification information from the image captured by the camera, by reading the sample ID.

[0043] In step ST13, the processor 110 determines whether or not a sample ID has been entered into area AR11. Unless a sample ID has been entered into area AR11, the processor 110 determines "No" in step ST13 and proceeds to step ST14.

[0044] In step ST14, the processor 110 determines whether or not a color ID has been entered into area AR14. Unless a color ID has been entered into area AR14, the processor 110 determines "No" in step ST14 and proceeds to step ST15.

[0045] The color ID is an example of the second identification information. Therefore, upon receiving the color ID, the processor 110 functions as an example of a identification unit that identifies the second identification information assigned to the color sample that is closest to the color of the microalgae among several color samples used for comparison with the color of the microalgae.

[0046] In step ST15, the processor 110 determines whether or not button B11 has been operated. If button B11 has not been operated, the processor 110 determines "No" in step ST15 and returns to step ST12. Thus, the processor 110 enters a waiting state, repeating steps ST12 to ST15 until a sample ID is read, a sample ID is entered into area AR11, a color ID is entered into area AR14, or button B11 is operated.

[0047] If the sample ID is read while the processor 110 is in a waiting state repeating steps ST12 to ST15, it determines "Yes" in step ST12 and proceeds to step ST16.

[0048] In step ST16, the processor 110 inputs the read sample ID into area AR11. After processing in step ST16, the processor 110 proceeds to step ST13.

[0049] The operator inputs the sample ID of the sample to be measured into area AR11 using the input device 160. Also, as mentioned above, the processor 110 inputs the sample ID into area AR11 in step ST16.

[0050] If a sample ID is entered into area AR11 while the processor 110 is in a waiting state repeating steps ST12 to ST15, it determines "Yes" in step ST13 and proceeds to step ST17.

[0051] Based on the above, the processor 110 functions as an example of an input unit that receives input of first identification information by receiving input of a sample ID using the input device 160.

[0052] In step ST17, the processor 110 obtains growth information for the sample to be measured, which is identified by the sample ID entered in area AR11. To do this, the processor 110 refers to the sample DB 141 and obtains the growth ID associated with the sample ID. Furthermore, the processor 110 refers to the environment DB 142 and obtains the growth information associated with the growth ID.

[0053] In step ST18, the processor 110 controls the display device 170 to display the contents of the growth information acquired in step ST17 in area AR12. After processing in step ST18, the processor 110 returns to step ST12.

[0054] The operator compares the color of the algae sample to the colors of each color sample 201 on the color chart 200. Then, the operator enters the color ID corresponding to the color sample 201 that is closest to the color of the algae into area AR14. If a color ID is entered into area AR14 while the processor 110 is in a waiting state repeating steps ST12 to ST15, it determines "Yes" in step ST14 and proceeds to step ST19.

[0055] In step ST19, the processor 110 identifies the protein content of the sample to be measured, which is identified by the sample ID entered in area AR11, based on the color ID entered in area AR14. That is, the processor 110 obtains the protein content associated with the color ID by referring to the color sample information.

[0056] In step ST20, the processor 110 controls the display device 170 to display the protein content obtained in step ST19 in area AR15.

[0057] In step ST21, the processor 110 performs a usage classification process for the sample to be measured, which is identified by the sample ID entered in area AR11. That is, the processor 110 refers to the classification information to obtain a suitable usage for the algae with the protein content obtained in step ST19. For example, if the protein content is greater than or equal to threshold TH1, the processor 110 determines the usage to be a protein source. Conversely, if the protein content is less than threshold TH1, the processor 110 determines the usage to be a starch source.

[0058] Based on the above, the processor 110 functions as an example of a classification unit that classifies microalgae according to their protein content and intended use by performing the processing in step ST21.

[0059] In step ST22, the processor 110 controls the display device 170 to display the result of the application classification process in step ST21 in area AR16. After processing in step ST22, the processor 110 returns to step ST12.

[0060] If button B11 is operated while the processor 110 is in a waiting state repeating steps ST12 to ST15, it determines "Yes" in step ST15 and proceeds to step ST23.

[0061] In step ST23, the processor 110 updates the sample DB 141, thereby updating the information regarding the measurement sample identified by the sample ID entered in area AR11. Specifically, the processor 110 rewrites the sample color information of the sample evaluation information associated with the sample ID to indicate the color ID entered in area AR14. The processor 110 then rewrites the sample protein information of the sample evaluation information to indicate the protein content obtained in step ST19. The processor 110 also rewrites the sample classification information associated with the sample ID to indicate the result of the application classification process in step ST21. Finally, the processor 110 sets the measurement date and time information associated with the sample ID to the current date and time.

[0062] Based on the above, the auxiliary storage device 140 functions as an example of a storage unit that stores the first identification information and the second identification information in association. Furthermore, the processor 110 functions as an example of a storage control unit that, by executing the process of step ST23, causes the first identification information and the second identification information to be stored in the storage unit in association.

[0063] In step ST24, the processor 110 updates the environment DB 142, thereby updating the information regarding the cultivation environment identified by the cultivation ID obtained in step ST17. Specifically, the processor 110 rewrites the environmental color information of the environmental evaluation information associated with the cultivation ID to indicate the color ID entered in area AR14. The processor 110 then rewrites the environmental protein information of the environmental evaluation information to indicate the protein content obtained in step ST19. This protein content indicates the protein content of algae grown in the cultivation environment identified by the cultivation ID. The processor 110 also rewrites the environmental classification information associated with the cultivation ID to indicate the result of the classification process in step ST21. This result indicates suitable uses for algae grown in the cultivation environment identified by the cultivation ID.

[0064] The processor 110 may determine the evaluation result indicated by the environmental evaluation information using the evaluation results of one or more measurement samples having the same growth ID. The processor 110 refers to the sample DB 141 to identify the sample ID associated with the growth ID obtained in step ST17. The processor 110 may identify the sample ID associated with the growth ID only if the measurement date and time information associated with the sample ID falls within a predetermined period.

[0065] The processor 110 then obtains the protein content from the sample evaluation information associated with each identified sample ID. The processor 110 then calculates statistical values ​​for one or more of the obtained protein content values. These statistical values ​​may be, for example, the mean, median, or mode. The mean may also be calculated using a trimmed mean or a wind-zero mean. The processor 110 may also perform a process to remove outliers from the obtained protein content values ​​before calculating the statistical values. The processor 110 then rewrites the environmental protein information associated with the cultivation ID obtained in step ST17 to show these statistical values. These statistical values ​​indicate the protein content of algae grown in the cultivation environment identified by the cultivation ID.

[0066] Furthermore, the processor 110 may perform usage classification processing using the statistical value. That is, the processor 110 refers to the classification information and obtains usage applications suitable for algae whose protein content matches the statistical value. The processor 110 then writes the usage application to the environmental classification information associated with the cultivation ID obtained in step ST17. After processing step ST24, processor 110 returns to step ST11.

[0067] According to the management system 1 of the first embodiment, the management device 100 associates and stores the input sample ID with the color ID of the color sample 201 that is closest to the color of the sample to be measured identified by the sample ID. In this way, the management device 100 of the first embodiment can reduce the effort required to manage the evaluation results of the sample to be measured, thereby reducing the effort required to measure the protein content.

[0068] Furthermore, according to the management system 1 of the first embodiment, the management device 100 identifies the protein content from the color ID of the color sample 201 that is closest in color to the sample to be measured. In this way, the management device 100 of the first embodiment automatically identifies the protein content from the color ID, thus reducing the effort required to measure the protein content.

[0069] Furthermore, according to the management system 1 of the first embodiment, the management device 100 classifies the uses of algae according to their protein content. In this way, the management device 100 of the first embodiment automatically classifies the uses, thus reducing the effort required for classification.

[0070] Furthermore, according to the management system 1 of the first embodiment, the management device 100 classifies algae as a protein source if their protein content is above the threshold TH1, and as a starch source if it is below the threshold TH1. This allows the management device 100 of the first embodiment to appropriately classify the uses of the algae.

[0071] Furthermore, according to the management system 1 of the first embodiment, the management device 100 reads the sample ID from the image captured by the camera 180. As a result, the management device 100 of the first embodiment can reduce the effort required to measure the protein content.

[0072] [Second Embodiment] Regarding the management system 1 of the second embodiment, we will omit the explanation of parts that are the same as those of the first embodiment.

[0073] The configuration of the management system 1 in the second embodiment is the same as in the first embodiment, so a description will be omitted.

[0074] However, in the management device 100 of the second embodiment, the color chart 200 is installed within the shooting range of the camera 180.

[0075] The operation of the management system 1 according to this embodiment will be described below with reference to Figure 4 and other figures. Note that the processing content in the following operation description is just an example, and various processing that can obtain similar results can be used as appropriate. Figure 4 is a flowchart showing an example of processing by the processor 110 of the management device 100. The processor 110 executes the processing shown in Figure 4 based on a program stored, for example, in the ROM 120 or auxiliary storage device 140.

[0076] In the second embodiment, a container containing the sample to be measured is positioned within the shooting range of the camera 180. The container displays a sample ID that identifies the sample to be measured. The container may be positioned within the shooting range of the camera 180 by a human, a robot such as a manipulator, or a transport device such as a conveyor belt. Alternatively, the processor 110 may move the camera 180 to position the container within its shooting range.

[0077] In the second embodiment, if the processor 110 determines "No" in step ST12 in Figure 4, it repeats the process of step ST12. Therefore, the processor 110 repeats the process of step ST12 until a sample ID is read.

[0078] In the second embodiment, the processor 110 proceeds to step ST17 after processing in step ST16. Also in the second embodiment, the processor 110 proceeds to step ST31 after processing in step ST18.

[0079] In step ST31, the processor 110 uses image processing to compare the color of the algae, which is the measurement sample, with the colors of each color sample 201 on the color chart 200. The processor 110 then uses image processing to identify the color sample 201 that is closest in color to the algae. The processor 110 then inputs the color ID corresponding to the identified color sample 201 into area AR14. After processing in step ST31, the processor 110 proceeds to step ST19.

[0080] Based on the above, the processor 110, by performing the processing in step ST31, receives a color ID input and functions as an example of an identification unit that identifies the second identification information assigned to the color sample that is closest in color to the microalgae among multiple color samples used for comparison with the color of the microalgae. Furthermore, the processor 110, by performing the processing in step ST31, also functions as an example of an identification unit that uses an image of the microalgae to identify the second identification information of the color sample that is closest in color to the microalgae among multiple color samples.

[0081] In the second embodiment, the processor 110 proceeds to step ST23 after processing in step ST22.

[0082] According to the management system 1 of the second embodiment, the management device 100 can obtain the same effects as in the first embodiment.

[0083] Furthermore, according to the management system 1 of the second embodiment, the management device 100 compares the color of the algae with the color of each color sample 201 on the color chart 200 and identifies the color sample 201 that is closest to the color of the algae. As a result, the management device 100 can automatically perform protein evaluation.

[0084] Furthermore, according to the management system 1 of the second embodiment, the management device 100 has a color chart 200 installed within the shooting range of the camera 180. As a result, the management device 100 of the second embodiment can reduce errors in protein evaluation caused by changes in the color of algae and color samples 201 due to the influence of light, etc.

[0085] The first and second embodiments described above can also be modified as follows. In the above embodiment, the classification information is information indicating suitable uses for algae according to their protein content. However, the classification information may also indicate suitable uses for algae according to their color ID. In this case, the processor 110 performs the use classification process using the color ID entered in area AR14 instead of the protein content obtained in step ST19.

[0086] The control device 100 may consist of multiple devices.

[0087] The processor 110 may implement some or all of the processing implemented by the program in the above embodiment through the hardware configuration of the circuit.

[0088] The program that implements the processing of the embodiment is transferred, for example, while stored in a non-temporary storage medium within the device. However, the device may be transferred without the program stored in it. Alternatively, the program may be transferred separately and written to the device. This transfer of the program can be achieved, for example, by recording it on a removable non-temporary storage medium or by downloading it via a network such as the Internet or a LAN (local area network).

[0089] The embodiments of the present invention have been described above, but these are merely examples and do not limit the scope of the invention. Embodiments of the present invention can be implemented in various ways without departing from the spirit of the invention. [Explanation of symbols]

[0090] 1 Management System 100 Management device 110 Processors 120 ROM 130 RAM 140 Auxiliary storage 141 Sample DB 142 Environment DB 150 communication interfaces 160 Input Devices 170 Display Devices 180 Camera 190 bus 200 Color Chart 201 Color Swatches [Accession Number]

[0091] FERM BP-22306

Claims

1. An input unit that receives input of first identification information assigned to each microalgae for measurement, A selection unit identifies a second identification information assigned to a color sample that is closest in color to the microalgae among a plurality of color samples used for comparison with the color of the microalgae, and identifies the protein content of the microalgae from the second identification information. The system includes a storage unit that stores the first identification information and the second identification information in association, The aforementioned microalgae is a microalga belonging to Chlamydomonas reinhardi, and this is an algae information management device.

2. The algae information management device according to claim 1, further comprising a classification unit for classifying the microalgae according to their protein content and intended use.

3. The algae information management device according to claim 2, wherein the classification unit classifies the uses of the algae as a protein source when the protein content is above a predetermined threshold, and as a starch source when the protein content is below the threshold.

4. The algae information management device according to claim 1, wherein the input unit receives the input of the first identification information by reading the first identification information from an image captured by a camera.

5. The algae information management device according to claim 1, wherein the identifying unit uses an image showing the microalgae to identify the second identification information of the color sample that is closest in color to the color of the microalgae from among a plurality of color samples.

6. The algae information management device according to any one of claims 1 to 5, wherein the microalgae is the Honda DREAMO strain with accession number FERM BP-22306.

7. The processor in the algae information management device An input unit that receives input of first identification information assigned to each microalgae for measurement, A selection unit identifies a second identification information assigned to a color sample that is closest in color to the microalgae among a plurality of color samples used for comparison with the color of the microalgae, and identifies the protein content of the microalgae from the second identification information. A storage control unit is configured to store the first identification information and the second identification information in association with each other in the storage unit. The aforementioned microalgae are microalgae belonging to Chlamydomonas reinhardi, according to the program.

8. Upon receiving input of the first identification information assigned to each microalgae for measurement, From among a plurality of color samples for comparison with the color of the microalgae, a second identification information is assigned to the color sample that is closest to the color of the microalgae, and the protein content of the microalgae is determined from the second identification information. The first identification information and the second identification information are stored in association with each other. The aforementioned microalgae belong to the microalgae Chlamydomonas reinhardi, and this is a method for managing algal information.

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