Supply system, computing device, supply device, and supply content determination method

Abstract

To provide a supply system for use in aquaculture that employs microorganisms for good growth of cultured organisms.SOLUTION: An supply system for aquaculture supplies a supply material to an aquaculture section, the system including a computing device and a supply device provided with a supply tank, wherein the computing device comprises: an input section for inputting water-intake microbiota data obtained by DNA analysis of collected water; a storage section for storing a water-intake microbiota dataset, a key microorganism dataset, and supply device data including supply material data of the supply tank; a computing section for identifying a water-intake key microorganism and computing an amount of the water-intake key microorganism; a supply content determination section for determining supply content and creating supply content data; and a supply content data output section for outputting the supply content data. The supply device comprises: a supply content data input section for inputting the supply content data; a supply tank for containing a supply material; and a supply mechanism for transferring the supply material stored in the supply tank and releasing the same to the aquaculture section according to the supply content data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a feeding system, a computing device, a feeding device, and a feeding method for aquaculture. [Background technology]

[0002] In aquaculture, the use of microorganisms to promote the growth of cultivated products has been studied (see Patent Documents 1 and 2). In land-based aquaculture, the use of aerobic bacteria to purify water has also been studied (see Patent Document 3). DNA analysis has been used to identify microorganisms that play important roles in the aquatic microflora (see Non-Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] WO2020-246609 publication [Patent Document 2] WO2006-101060 publication [Patent Document 3] Japanese Patent Application Laid-Open No. 2004-16168 [Non-patent literature]

[0004] [Non-Patent Document 1] Yajima et al. Microbiome (2023) 11:53, https: / / doi.org / 10.1186 / s40168-023-01498-x Summary of the Invention

[0005] According to one embodiment of the present disclosure, there is provided an aquaculture supply system for supplying feed to an aquaculture section, the system comprising a computing device and a supply device having a supply tank. The computing device comprises: an input unit for inputting intake water microbiome data, the input unit including an intake water microbiome identifier and an intake water microbiome mass obtained by DNA analysis of collected water; a storage unit for storing an intake water microbiome dataset including the intake water microbiome data, a key microbiome dataset including key microbiome identifiers and key microbiome mass thresholds for key microbiomes, and supply device data including supply data for the supply tank; a computing unit for identifying intake water key microorganisms using at least the intake water microbiome data and the key microbiome dataset and calculating the intake water key microbiome mass; a supply content determination unit for determining supply content and creating supply content data by referring to at least the intake water key microbiome mass, the key microbiome mass threshold, and the supply device data; and a supply content data output unit for outputting the supply content data. The supply device includes a supply content data input unit for inputting the supply content data, a supply tank for storing the supply material, and a supply mechanism for transferring the supply material stored in the supply tank in accordance with the supply content data and releasing it into the aquaculture area. [Brief explanation of the drawings]

[0006] [Figure 1] 1 is a schematic diagram of a supply system for aquaculture for supplying feed to aquaculture compartments according to one embodiment of the present disclosure, with some external elements of the system also shown for ease of understanding. [Figure 2] FIG. 2 is a schematic diagram of a supply system for aquaculture for supplying feed to aquaculture compartments according to an embodiment different from that shown in FIG. 1 of the present disclosure in that the supply device includes a culture section. [Figure 3] FIG. 3 is a schematic structural diagram of a supply system for aquaculture that supplies feed to aquaculture compartments according to an embodiment different from that shown in FIG. 1 of the present disclosure in that the supply device is provided with a sensing unit. [Figure 4] Figure 4 shows an example of the results of DNA analysis of the microbiota, and is an image of a graph showing the time course of absolute abundance of microorganisms. For ease of viewing, the graph shows only four types of microorganisms. [Figure 5] Figure 5 is an image diagram showing the co-occurrence analysis using the microbiota dataset for co-occurrence analysis and the correlation analysis between the amount of microorganisms contained in the microbiota dataset for co-occurrence analysis and the dataset subject to correlation analysis superimposed on each other. [Figure 6A] FIG. 6A is a process flow of a feeding system for aquaculture that provides feed to aquaculture compartments according to one embodiment of the present disclosure. [Figure 6B] FIG. 6B is a process flow of an aquaculture supply system for supplying feed to an aquaculture compartment, according to an embodiment different from that of FIG. 6A, in that it includes a co-occurrence analysis process. [Figure 6C] FIG. 6C is a process flow of an aquaculture supply system for supplying feed to an aquaculture area, according to an embodiment different from FIGS. 6A and 6B, in that it includes a process for acquiring and utilizing sensor data. DETAILED DESCRIPTION OF THE INVENTION

[0007] [Problem to be solved by this disclosure] The present disclosure provides a supply system for aquaculture that supplies feed, and determines the content of the feed and supplies the feed based on microbiota data of water collected from an aquaculture compartment.

[0008] [Effects of this disclosure] The present invention is an aquaculture supply system that uses microbiota data to identify key microorganisms and calculate the amount of key microorganisms to determine the supply content. This makes it possible to improve the state of the microbiota and appropriately supply nutrients, microorganisms, and antibiotic-containing feed necessary for aquaculture, which is expected to improve aquaculture efficiency. Furthermore, the present invention provides an automated supply system compared to conventional manual supply methods, which is expected to improve work efficiency.

[0009] [Description of the embodiments of the present disclosure] First, embodiments of the present disclosure will be listed and described.

[0010] (1) According to one embodiment of the present disclosure, a supply system for aquaculture that supplies a feed to an aquaculture section includes a computing device and a supply device with a supply tank. The computing device includes: an input unit for inputting intake water microbiome data, including an intake water microbiome identification tag and an intake water microbiome mass, obtained by DNA analysis of collected water; a memory unit for storing an intake water microbiome dataset including the intake water microbiome data, a key microbiome dataset including key microbiome identification tags and key microbiome mass thresholds for key microbiomes, and supply device data including supply data for the supply tank; a computing unit for identifying intake water key microorganisms using at least the intake water microbiome data and the key microbiome dataset and calculating the intake water key microbiome mass; a supply content determination unit for determining supply content and creating supply content data by referring to at least the intake water key microbiome mass, the key microbiome mass threshold, and the supply device data; and a supply content data output unit for outputting the supply content data. The supply device includes a supply content data input unit for inputting the supply content data, a supply tank for storing the supply material, and a supply mechanism for transferring the supply material stored in the supply tank in accordance with the supply content data and releasing it into the aquaculture area.

[0011] (2) In the above (1), the supply may include microorganisms. Supplying appropriate microorganisms to the cultivation area can have a positive effect on the growth of the cultivated fish.

[0012] (3) In (2) above, the microorganisms may include microorganisms selected based on the results of a co-occurrence analysis using a microbiota dataset for co-occurrence analysis, or the results of a correlation analysis using a microbiota dataset for co-occurrence analysis and a correlation analysis target characteristic dataset, or the results of the co-occurrence analysis and the correlation analysis. By supplying to the aquaculture section microorganisms selected based on the results of an analysis using a microbiota dataset for co-occurrence analysis and a correlation analysis target characteristic dataset that are appropriate for achieving the desired expected effect, a positive effect can be achieved on the growth of the cultivated fish.

[0013] (4) In the above (2), the microorganisms may be selected from the group consisting of microorganisms capable of combating pathogenic microorganisms, vitamin 12-synthesizing microorganisms, ammonia-oxidizing bacteria, and nitrite-oxidizing bacteria. Supplying microorganisms capable of combating pathogenic microorganisms can suppress the occurrence of disease, supplying vitamin 12-synthesizing microorganisms not only contributes to the health of the cultivated fish but also allows for the production of high-value-added cultivated fish with accumulated vitamin 12, and supplying ammonia-oxidizing bacteria and nitrite-oxidizing bacteria can improve water quality and prevent health damage to the cultivated fish.

[0014] (5) In the above (1) to (4), the supplies may include feed for the aquaculture. Providing appropriate feed in an appropriate manner to the aquaculture area can have a positive effect on the growth of the aquaculture.

[0015] (6) In the above (1) to (5), the feeding device may include two or more feeding tanks. By including two or more feeding tanks, multiple positive effects can be obtained in the growth of the cultivated aquaculture products.

[0016] (7) In the above (6), at least one of the supply tanks may contain antibiotic-free feed, and at least another of the supply tanks may contain antibiotic-containing feed. By supplying antibiotic-containing feed only when necessary, the amount of antibiotic used can be reduced.

[0017] (8) In the above (6), one of the supply tanks and another of the supply tanks may contain different microorganisms. Because different microorganisms can be supplied, the effect of supplying the feed can be varied, and the system can flexibly respond to changes in the growing environment of the cultivated aquaculture.

[0018] (9) In the above (1) to (8), the supply tank of the supply device or a part of the supply tank may be a cartridge for storing the supply material and may have a removable structure. The cartridge structure makes it easy to fill the supply tank with the supply material and also helps keep the supply tank clean.

[0019] (10) In the above (1) to (9), the supply tank of the supply device may be provided with a temperature control mechanism. By maintaining the temperature inside the supply tank at an appropriate level, microorganisms can survive for a long period of time.

[0020] (11) In the above (1) to (10), the supply device may include a microorganism culturing section. The microorganisms can be cultivated in the culturing section.

[0021] (12) In the above (1) to (11), the supply device may include a sensing unit, which can detect the environmental conditions inside and outside the supply device.

[0022] (13) In the above (12), the supply content determination unit may refer to sensor data acquired by the sensing unit when determining the supply content. The supply content can be determined more appropriately taking into account the internal and external environmental conditions of the supply device.

[0023] (14) In the above (1) to (13), the transmission of the supply content data between the supply content data output unit and the supply content data input unit may be performed by wireless communication or internet communication, which increases the degree of freedom in the arrangement of the calculation device and the supply device.

[0024] (15) In the above (1) to (14), the water intake microbiome dataset may include the water intake microbiome data obtained from at least two or more water samples collected at the same location but on different intake dates, thereby enabling confirmation and prediction of changes over time in the microbiome at the water sampling location.

[0025] (16) In the above (15), the calculation unit may use the intake water microbiome data to calculate the change over time in the amount of the intake water key microorganism, thereby obtaining the intake water key microorganism amount as a function of time. By obtaining the amount as a function of time, it is possible to preemptively or preventively determine the supply content of the supply device.

[0026] (17) In (16) above, when obtaining the intake key microorganism abundance as a function of time, the influence of the intake microbiome data obtained from new water on the intake date may be calculated as being greater than the influence of the intake microbiome data obtained from old water on the intake date. This is because the state of the microbiome indicated by the intake microbiome data obtained from new water on the intake date is likely to be closer to the state of the microbiome at the sampling site at the time of the calculation.

[0027] (18) In the above (1) to (17), the calculation unit may identify the key water intake microorganism by comparing the water intake microorganism identification mark included in the water intake microbiome data with the key microorganism dataset.

[0028] (19) In the above (1) to (18), the amount of microorganisms in the water intake may be the absolute amount. This is because in many cases, the absolute amount of a microorganism has a greater effect on the growth of the target aquaculture product than the ratio of the amount of a microorganism to other microorganisms.

[0029] (20) In the above (1) to (19), the key microorganism amount threshold may be a value derived from a function. By deriving the threshold from a function including variables, it is possible to determine the threshold taking into account factors that may vary.

[0030] (21) In the above (1) to (20), the key microorganism dataset may include key microorganism identification marks of key microorganisms identified using the results of co-occurrence analysis of the microbiome dataset for co-occurrence analysis, or the results of correlation analysis between the microbiome dataset for co-occurrence analysis and the correlation analysis target characteristic dataset, or the results of the co-occurrence analysis and the correlation analysis target characteristic dataset. By using the analysis results of an appropriate microbiome dataset for co-occurrence analysis and the correlation analysis target characteristic dataset, it is possible to identify appropriate key microorganisms from a desired perspective, and even to identify key microorganisms that are not generally known.

[0031] (22) In the above (1) to (21), the calculation unit may identify the key microorganisms by performing a co-occurrence analysis using a microbiome dataset for co-occurrence analysis, or a correlation analysis between the microbiome dataset for co-occurrence analysis and a characteristic dataset for correlation analysis, or the co-occurrence analysis and the correlation analysis.

[0032] (23) In (22) above, the calculation unit may identify the key microbial quantity threshold using the result of the co-occurrence analysis, or the result of the correlation analysis, or the results of the co-occurrence analysis and the correlation analysis.

[0033] (24) In the above (21) to (23), at least a portion of the microbiome data for co-occurrence analysis included in the microbiome data set for co-occurrence analysis may be the water intake microbiome data. By using the water intake microbiome data as the microbiome data for co-occurrence analysis, it is possible to identify key microorganisms that are specific to the conditions at the water sampling point where the water intake microbiome data is obtained. It is also possible to identify key microorganisms that are less common at points other than the water sampling point where the water intake microbiome data is obtained.

[0034] (25) In the above (21) to (24), at least a portion of the data group consisting of the microbiome data for co-occurrence analysis included in the microbiome data set for co-occurrence analysis and the correlation analysis target characteristic data included in the correlation analysis target characteristic data set may be obtained from the same aquaculture plot as the aquaculture plot from which the water intake microbiome data was obtained. This makes it possible to identify key microorganisms that are in line with the conditions of the aquaculture plot from which the water from which the water intake microbiome data is obtained was collected.

[0035] (26) In the above (21) to (25), the correlation analysis target characteristic dataset may include data on the activity of the cultivated aquatic product. Using the activity of the cultivated aquatic product can have a positive effect on the growth of the cultivated aquatic product.

[0036] (27) In the above (1) to (26), the key microorganism may include multiple key microorganisms constituting a microbial module. By including multiple key microorganisms constituting a microbial module, the effects of the microbial module are exerted, and the effects to be obtained by supplying the supply material may be obtained more efficiently or with reduced side effects.

[0037] (28) In the above (1) to (27), the DNA analysis may be performed using a next-generation sequencer, thereby obtaining accurate and detailed data on the microbiome of the water intake.

[0038] (29) In the above (1) to (28), the DNA analysis may be a DNA analysis selected from the group consisting of 16S rRNA gene analysis, 18S rRNA gene analysis, fungal ITS, and shotgun metagenomics analysis.

[0039] (30) According to another aspect of the present disclosure, there is provided a computing device for instructing a supply device equipped with a supply tank to specify supply contents, the computing device comprising: an input unit for inputting water intake microbiome data including a water intake microbiome identification tag and a water intake microbiome quantity obtained by DNA analysis of collected water; a memory unit for storing a water intake microbiome dataset including the water intake microbiome data, a key microbiome dataset including a key microbiome identification tag and a key microbiome quantity threshold, and supply device data including supply data for the supply tank; a computing unit for identifying water intake key microorganisms using at least the water intake microbiome data and the key microbiome dataset and calculating the water intake key microorganism quantity; a supply content determination unit for determining supply contents and creating supply content data by referring to at least the water intake key microorganism quantity, the key microorganism quantity threshold, and the supply device data; and a supply content data output unit for outputting the supply content data.

[0040] (31) A supply system comprising: a supply content data input unit that determines supply contents by referring to at least an intake microbial mass data set including intake microbial flora data including intake microbial identification marks and intake microbial mass obtained by DNA analysis of collected water, a key microbial mass data set including key microbial identification marks and key microbial mass thresholds, and supply device data including supply data for a supply tank, and inputs supply content data output from a computing device that creates supply content data; a supply tank that stores the supply material; and a supply mechanism that transports the supply material stored in the supply tank in accordance with the supply content data and releases it into an aquaculture area.

[0041] (32) A method for determining the content of the feed stored in a supply tank to be supplied to an aquaculture section, comprising: identifying a water intake key microorganism from a water intake microbial mass dataset including water intake microbial flora data including water intake microbial identification marks and water intake microbial mass, obtained by DNA analysis of collected water; and a key microorganism dataset including key microorganism identification marks and key microorganism mass threshold; calculating the water intake key microorganism mass; and determining the supply content by referring to at least the water intake key microorganism mass, the key microorganism mass threshold, and the supply data of the supply tank.

[0042] (33) In the above (32), the key microorganism dataset may include the results of a co-occurrence analysis using a microbiome dataset for co-occurrence analysis, or the results of a correlation analysis using a microbiome dataset for co-occurrence analysis and a correlation analysis target characteristic dataset, or the results of the co-occurrence analysis and key microorganism identification marks of key microorganisms identified by the results of the correlation analysis. Based on the analysis results using an appropriate microbiome dataset for co-occurrence analysis and a correlation analysis target characteristic dataset, it is possible to identify appropriate key microorganisms from a desired perspective, and even to identify key microorganisms that are not generally known.

[0043] [Description of the embodiments of the present disclosure] Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. Figures 1 to 4 are schematic diagrams of the aquaculture supply system of the present disclosure. Figure 4 is an image of an example of the results of DNA analysis of a microbiota. Figure 5 is an image showing co-occurrence analysis using a microbiota dataset for co-occurrence analysis and correlation analysis between the amount of microorganisms contained in the microbiota dataset for co-occurrence analysis and the dataset subject to correlation analysis. Figures 6A to 6C are schematic diagrams of the process flow. Identical or corresponding parts in the figures are designated by the same reference numerals and will not be described again. Furthermore, at least some of the embodiments described below may be arbitrarily combined. The figures are presented with the utmost priority to facilitate understanding. Please note that the dimensions, such as length, width, thickness, and depth, and the constituent elements may differ from the actual dimensions. Furthermore, the figures are merely examples and do not limit the scope of the present disclosure. The present disclosure is not limited to the figures or exemplary embodiments, but is defined by the claims, and all modifications within the meaning and scope of the claims are intended to be included.

[0044] <Systems, Equipment> The aquaculture supply system of the embodiment shown in Figure 1 comprises a calculation device 1 and a supply device 2. The calculation device 1 is equipped with an input unit 11 for inputting intake water microbiome data including at least an intake water microbiome identification tag and an intake water microbiome mass obtained by DNA analysis of collected water, a memory unit 12 for storing an intake water microbiome dataset including the intake water microbiome data, a key microorganism dataset including at least an identification tag and a key microorganism mass threshold value for a key microorganism, and supply device data including supply data for the supply tank 22, a calculation unit 13 for identifying intake water key microorganisms using the intake water microbiome dataset and calculating the intake water key microorganism mass, a supply content determination unit 14 for comparing the intake water key microorganism mass with the key microorganism mass threshold value to determine supply content and create supply content data, and a supply content data output unit 15 for transmitting the supply content data. The supply device 2 includes a supply content data input unit 21 for inputting supply content data, a supply tank 22 for storing supply material 43, and a supply mechanism 23 for supplying the supply material 43 stored in the supply tank 22 to the aquaculture section 41.

[0045] <Arithmetic device> The arithmetic unit 1 may be realized by dedicated hardware, or may be realized by a computer system configured by a memory and a central processing unit.

[0046] <Input section> The input unit 11 inputs water intake microbiome data obtained by DNA analysis of collected water. In addition to the water intake microbiome data, the input unit 11 may also input a key microorganism dataset, supply device data, a microbiome dataset for co-occurrence analysis, and a dataset to be analyzed for correlation. The input unit 11 may be equipped with a media input unit such as a USB, HDD, CD-ROM, or DVD, and may input data or datasets via the media. The input unit 11 may be equipped with a receiving function for wireless or wired communication to receive the data or datasets. The input unit 11 may be equipped with a receiving function for internet communication to receive the data or datasets.

[0047] <Storage section> The memory unit 12 stores the intake water microbiome dataset, the key microbiome dataset, and the supply device data input by the input unit 11. It may also store the microbiome dataset for co-occurrence analysis and the correlation analysis target dataset. It may also store sensor data acquired by the sensing unit 25 of the aquaculture device 2 and acquired by the calculation device 1 through the sensor data output unit 26 and the sensor data input unit 16. The key microbiome identification labels and key microbiome quantity thresholds included in the key microbiome dataset may be identified and determined by co-occurrence analysis or correlation analysis outside the calculation device 1, or may be identified and determined by the calculation unit 13 of the calculation device 1 by co-occurrence analysis or correlation analysis. Data on microorganism names and microbial quantity thresholds may be stored so that the key microorganisms identified by co-occurrence analysis or correlation analysis can be collated to determine the key microorganism quantity threshold.

[0048] <Arithmetic section> The calculation unit 13 identifies the intake key microorganisms and calculates the amount of intake key microorganisms using the intake water microbiome dataset stored in the memory unit 12. When identifying the intake key microorganisms, the names (microorganism identification marks) of the microorganisms present in the collected water may be extracted from the intake water microbiome dataset and compared with the key microorganism identification marks included in the key microorganism dataset stored in the memory unit 12 to identify the intake key microorganisms.

[0049] The calculation unit 13 may identify key microorganisms by performing co-occurrence analysis using the microbiome dataset for co-occurrence analysis stored in the storage unit 12, or correlation analysis using the microbiome dataset for co-occurrence analysis and the dataset to be analyzed for correlation, or the co-occurrence analysis and the correlation analysis, and add the identified key microorganisms as key microorganism data to the storage unit 12. At least a part of the microbiome data for co-occurrence analysis included in the microbiome dataset for co-occurrence analysis stored in the storage unit 12 may be water intake microbiome data.

[0050] When calculating the intake key microorganism abundance, the calculation unit 13 may read the intake key microorganism abundance value from the intake microbiome data. The calculation unit 13 may use two or more, preferably three or more, pieces of intake microbiome data stored in the intake microbiome dataset to calculate and predict the change over time in the intake key microorganism abundance, and obtain the intake key microorganism abundance as a predicted value as a function of time. Obtaining the predicted value makes it possible to preemptively or preventively determine the supply content of the supply material 43 from the supply device 2. When calculating the change over time in the intake key microorganism abundance, the calculation unit 13 may calculate the influence of the intake microbiome data obtained from new water on the intake day as greater than the influence of the intake microbiome data obtained from old water on the intake day. This is because the state of the microbiome indicated by the intake microbiome data obtained from new water on the intake day is likely to be closer to the state of the microbiome at the sampling site at the time of the calculation.

[0051] <Supply content determination section> The supply content determination unit 14 determines the supply content of the supply material 43 of the supply device 2 by referring to the intake water key microbial mass based on the calculation result of the calculation unit 13, the key microbial mass threshold included in the key microbial data set stored in the memory unit 12, and the supply device data, and creates supply content data. If the intake water key microbial mass is a predicted value over time, the time at which the intake water key microbial mass reaches the key microbial mass threshold may be calculated, and the supply content may be determined based on this reaching time. If the key microbial mass threshold is a value derived from a function, for example, if the function includes the pH, temperature, and oxygen concentration of the aquaculture section 41 as variables, data acquired by the sensing unit 25 of the aquaculture device 2 and acquired by the calculation device 1 via the sensor data output unit 26 and sensor data input unit 16 may be referenced.

[0052] Based on the determined supply contents, supply content determination unit 14 may update the supply device data stored in storage unit 12. For example, when the supply device data includes data on the remaining amount of supply material in supply tank 22, the amount of supply material 43 reduced by the determined supply may be reflected.

[0053] <Supply Content Data Output Section> The supply content data output unit 15 outputs the supply content data of the supply item 43 created by the supply content determination unit 14. The supply content data output unit 15 may have a transmission function for wireless communication or wired communication to transmit the supply content data. It may also have a transmission function for internet communication to transmit the supply content data.

[0054] <Feeding device> The supply device 2 includes a supply content data input unit 21, a supply tank 22 that stores the supply material 43, and a supply mechanism 23 that supplies the supply material 43 stored in the supply tank 22 to the aquaculture section 41. The supply content data input unit 21 inputs the supply content data output by the supply content data output unit 15. The supply content data is used to control the operation of the supply mechanism 23 and the supply tank 22. The supply content data input unit 21 may be equipped with a simple calculation function.

[0055] <Supply Content Data Input Section> The supply content data input unit 21 inputs the supply content data of the supply item 43 output by the supply content data output unit 15. The supply content data input unit 21 may have a receiving function for wireless communication or wired communication to receive the supply content data. It may also have a receiving function for internet communication to receive the supply content data.

[0056] <Supply tank> The supply tank 22 has an inlet for the supply material 43, which can store the supply material 43, and an outlet for the supply material 43, which can supply the supply material 43 to the aquaculture section 41. The supply tank 22 may serve as both the inlet and outlet. The supply tank 22 may be fixed to the supply device 2, or the supply tank 22 itself or a part of the supply tank 22 may be a removable cartridge that stores the supply material 43. The cartridge structure makes it easy to store the supply material 43 in the supply tank 22, and by replacing the cartridge, old supply material 43 remains in the supply tank 22, which prevents the growth of pathogens and the like, thereby keeping the supply tank 22 clean.

[0057] The feed 43 may be feed for the aquaculture 42 or may be microorganisms. The microorganisms may be multiple microorganisms or multiple microorganisms constituting a microorganism module 53. The microorganisms may be key microorganisms. The feed may be a mixture of antibiotics and microorganisms.

[0058] The supply device 2 may include multiple supply tanks 22. Providing multiple supply tanks 22 allows for variations in the effect of supplying the feed 43. For example, one supply tank 22 may contain feed, and another supply tank 22 may contain feed supplemented with antibiotics. The antibiotic-supplemented feed stored in the other supply tank 22 may be supplied only when the amount of pathogenic microorganisms in the culture section 41 of the target aquaculture product 42 exceeds a threshold, thereby minimizing the amount of antibiotics administered. For example, one supply tank 22 may contain feed, and another supply tank 22 may contain feed containing microorganisms that are beneficial to the intestinal environment of the aquaculture product 42. When the activity level of the aquaculture product 42 decreases and exceeds a threshold, the feed from the other supply tank 22 may be supplied to the aquaculture product 42, thereby promoting and maintaining the health of the aquaculture product 42. Also, for example, one supply tank 22 may contain inexpensive feed, and another supply tank 22 may contain expensive but nutritious feed, and the inexpensive feed may be fed normally, and only when the activity of the cultivated organisms 42 drops and exceeds a threshold value may the highly nutritious feed stored in the other supply tank 22 be fed, thereby reducing feed costs. If the balance of the microbial flora in the culture section 41 of the target cultivated organisms 42 becomes unbalanced, it is desirable to supply optimal amounts of multiple microorganisms in order to correct this, and having multiple supply tanks 22 makes this easily possible.

[0059] The supply tank 22 may be equipped with a temperature control function. A known mechanism can be used for the temperature control mechanism. The use of a temperature control mechanism using the Peltier effect allows the supply tank 22 to be miniaturized. The temperature inside the tank is preferably 15°C or less, more preferably 10°C or less, and even more preferably 7°C or less. A low temperature in the supply tank 22 allows the microorganisms stored in the supply tank 22 to survive for a long period of time. The temperature inside the tank is preferably -20°C or higher, more preferably -10°C or higher. The closer the required tank temperature is to the temperature of the location where the supply device 2 is installed, the simpler and less expensive the temperature control mechanism can be. The lower limit of the tank temperature is more preferably 1°C or higher, and even more preferably 3°C or higher. A tank temperature of 1°C or higher can avoid freezing even when the supply material 43 has a high moisture content, facilitating the supply of the supply material 43. The temperature may be adjusted according to the supply content data input by the supply content data input unit 21.

[0060] <Supply mechanism> The supply mechanism 23 transfers the supply material 43 from the supply tank 22 and releases it into the aquaculture section 41 in accordance with the supply content data input by the supply content data input unit 21. A known transfer mechanism can be used as the mechanism by which the supply mechanism 23 transfers the supply material 43 and releases it into the aquaculture section 41.

[0061] The supply mechanism 23 may be a mechanism that stores the supply material 43 in a groove of a screw and transfers the supply material 43 by rotating the screw. The amount of the supply material 43 transferred can be easily controlled by controlling the rotation of the screw.

[0062] The supply mechanism 23 may be a mechanism for changing the volume of the storage section for the supply material 43 in the supply tank 22, and may be used to transfer the supply material 43. The mechanism for changing the volume of the storage section for the supply material 43 may be a mechanism in which the walls of the storage section for the supply material 43 are movable and the volume can be changed by moving the walls with a piston, or a mechanism in which the storage section for the supply material 43 is a flexible, deformable bag, in which the deformable bag is placed in a housing, and the pressure of the gas or liquid filling the space between the housing and the deformable bag is controlled to deform the storage section for the supply material 43 and change the volume. By providing a mechanism for changing the volume of the storage section for the supply material 43, the amount of transfer of the supply material 43 can be easily controlled by controlling the change in the volume of the storage section. The supply mechanism 23 may also be a mechanism for sucking the supply material 43 stored in the supply tank 22 from the supply tank 22.

[0063] When there are multiple supply tanks 22, each of the supply tanks 22 may be provided with its own supply mechanism 23. This allows for accurate control of the supply amount, and also makes it easy to handle supply content with complex supply amounts, supply timing, etc. When there are multiple supply tanks 22, the supply material 43 may be transferred using fewer supply mechanisms 23 than the number of supply tanks 22. This simplifies the mechanism and allows the supply device 2 to be made more compact. For example, in order to pressurize and push out the supply material 43 storage section of the supply tank 22, or to depressurize and suck out the supply material 43, a pump that controls air pressure can be connected to all of the supply tanks 22, and opening and closing sections can be provided at the connections with each supply tank 22. The opening and closing sections can be individually controlled to control the transfer of the supply material 43 in each supply tank 22.

[0064] <Cultivation Department> As shown in FIG. 2, the supply device 2 may include a culture section 24. The culture section 24 includes a culture section inlet for a microorganism or a microorganism-containing supply 43, which can store the microorganism or the microorganism-containing supply 43, and a culture section outlet for the microorganism or the microorganism-containing supply 43, which can supply the microorganism or the microorganism-containing supply 43 to the supply tank 22. The culture section inlet and outlet may serve as both. The culture section 24 has a temperature control function to maintain a temperature appropriate for the growth of microorganisms. The temperature of the culture section 24 may be set appropriately taking into account the microorganisms contained in the supply 43 and the expected growth rate. The lower limit temperature of the culture section 24 may be 10°C or higher, 30°C or higher, or 50°C or higher. The upper limit temperature may be 70°C or lower, 50°C or lower, or 30°C or lower. If the temperature is lower than the optimum temperature, the expected growth rate will not be achieved, and if the temperature is higher than the optimum temperature, the growth rate of the microorganisms will decrease, and if the temperature is too high, the microorganisms will die. The culturing unit 24 may also serve as the supply tank 22. The temperature may be adjusted in accordance with the supply content data input by the supply content data input unit 21.

[0065] The transfer of the microorganisms or the supply material 43 containing the microorganisms from the culture unit 24 to the supply tank 22, or the transfer of the microorganisms or the supply material 43 containing the microorganisms from the supply tank 22 to the culture unit 24 may be performed by the supply mechanism 23, or a separate supply mechanism 23 may be provided. The culture unit 24 may be provided with a mechanism for mixing the microorganisms cultured in the culture unit 24 with other supply materials 43 before transferring them to the supply tank 22.

[0066] <Sensing section, sensor data output section, sensor data input section> As shown in FIG. 3 , the supply device 2 may include a sensing unit 25 equipped with a sensor to acquire sensor data and a sensor data output unit 26 to output the acquired sensor data. The sensing unit 25 may include an internal sensor of the supply device 2. The internal sensor may acquire, for example, weight sensor data of the supply material 43 in the supply tank 22, volume sensor data of the supply material storage section of the supply tank 22, sensor data related to the transfer mechanism of the supply mechanism 23 (e.g., the number of screw rotations, piston position, air pressure), and temperature and humidity sensor data of the supply tank 22 and the culture section 24. The sensing unit 25 may also include an external sensor. The external sensor may acquire, for example, sensor data of the temperature (water temperature), pH, temperature, turbidity, dissolved oxygen concentration, salinity concentration, ammonia concentration, nitrate concentration, nitrite concentration, phosphate ion concentration, copper ion concentration, ozone concentration, sunlight intensity, and activity level of the cultured material 42 in the culture section 41. The sensing unit 25 may also have a function for storing and managing the sensor data.

[0067] The sensor data output unit 26 may have a transmission function for wireless communication or wired communication and transmit the sensor data. It may have a transmission function for internet communication and transmit the sensor data. The calculation device 1 may have a sensor data input unit 16 that inputs data output by the sensor data output unit 26. The sensor data input unit 16 may have a receiving function for wireless communication or wired communication and receive the sensor data. It may have a receiving function for internet communication and receive the sensor data.

[0068] <Communication medium> Transmission of supply content data of the supply item 43 between the supply content data output unit 15 and the supply content data input unit 21 may be performed by a communication medium 3. Transmission of sensor data between the sensor data output unit 26 and the sensor data input unit 16 may be performed by a sensor data communication medium 31. The communication medium 3 and the sensor data communication medium 31 may be a wired cable, wireless communication, or communication via the Internet. In the case of wireless communication or communication via the Internet, the degree of freedom in the placement of the calculation device 1 and the supply device 2 can be increased. It is preferable that the communication medium 3 also serves as the sensor data communication medium 31.

[0069] <Cultivated products> The aquaculture products 42 targeted by the aquaculture system disclosed herein are seafood and seaweed. Specific examples include salmon, trout, sweetfish, eels, catfish, carp, goldfish, mackerel, yellowtail, amberjack, yellowtail amberjack, red sea bream, flounder, pufferfish, tuna, sea bass, tilapia, sea bass, sturgeon, grouper, shrimp (whiteleg shrimp, kuruma prawn, Penaeus monodon, whiteleg shrimp, etc.), sea grapes, and seaweed. The aquaculture method may be one that allows for controlled water exchange, which makes it easy to control the water's microbial flora. The aquaculture method may also be land-based, which makes it easy to control the aquaculture environment and microbial flora. Aquariums may be provided, and the water in the aquariums may be circulated using a semi-circulation or closed circulation system.

[0070] <Aquaculture area> In this disclosure, the aquaculture section 41 refers to a tank for land-based aquaculture, a fish pen on the sea surface, a lake surface, etc. In other words, it refers to a section that limits the growth area of ​​the aquaculture product 42.

[0071] <Microorganisms, Key Microorganisms> In this disclosure, microorganisms include bacteria, archaea, fungi (molds (filamentous fungi), yeasts, etc.), as well as small algae, metazoans, protozoa, and protozoa. In this disclosure, key microorganisms refer to microorganisms that contribute significantly to the effects to be achieved by supplying the supply 43 from the supply device 2. For example, from the perspective of the health, activity, and survival rate of the cultivated product 42, pathogenic microorganisms can be key microorganisms, microorganisms that suppress pathogenic microorganisms can also be key microorganisms, and microorganisms that provide nutrients to the cultivated product 42 can also be key microorganisms. From the perspective of adding high value to the cultivated product 42, microorganisms that calculate the nutrients accumulated in the cultivated product 42 can be key microorganisms. From the perspective of maintaining the water quality of the aquaculture section, microorganisms that have a water purification function can be key microorganisms, and microorganisms that reduce components that are harmful to the cultivated product 42 when accumulated in high concentrations, such as ammonia and nitrite, can be key microorganisms.

[0072] A wide variety of microbial species exist in the microbiome, but certain microbial species strongly influence each other and act, so to speak, as a microbial module 53 (a group of microorganisms). The key microorganism may be a plurality of microorganisms that make up the microbial module 53. For example, there is a strong correlation between the abundance of pathogenic microorganisms and the degree of formation of the microbial module 53, but if only a single microorganism that makes up the microbial module 53 is present, this correlation may not be observed. By including a plurality of key microorganisms that make up the microbial module 53 in the key microorganism, it is possible to increase the likelihood of obtaining a correlation between the microbial module 53 and the target pathogenic microorganism. The effect to be obtained by supplying the supply 43 described above may be obtained more efficiently or with reduced side effects.

[0073] Microbiota data at the water sampling point is used as microbiota data for co-occurrence analysis, and data obtained at the same point as the sampling point or in the same aquaculture area that directly or indirectly reflects the effect to be obtained by supplying the supply material 43 from the supply device 2 is used as correlation analysis target data.The microbiota data set for co-occurrence analysis and the correlation analysis target data set are prepared, and key microorganisms can be identified by performing co-occurrence analysis or correlation analysis, or a key microbial quantity threshold can be determined.Even if the key microorganism is unknown, it can be identified.This is particularly effective when the key microorganism includes multiple key microorganisms that constitute the microbial module 53.

[0074] <Diseases and pathogenic microorganisms> Examples of diseases of fish and shellfish caused by fungi include fusarium disease, cotton blight, Saprolegnia, visceral mycosis, fungal granulomatosis, haliphthorus disease, etc. Examples of pathogenic fungi include fungi of the genus Fusarium, Saprolegnia, Aphanomyces, Haliphthorus, etc.

[0075] Examples of diseases of fish and shellfish caused by bacteria include vibriosis, furunculosis, aeromonas disease, edwardsiellosis, red spot disease, pseudomonas disease, red mouth disease, bacterial gill disease, columnaris disease, cold water disease, gliding bacteriosis, bacterial kidney disease, mycobacteriosis, nocardiosis, streptococcosis, white spot disease, yellow head disease, bacterial hemorrhagic ascites, paracolo disease, columnaris disease, and bacterial white cloud disease.

[0076] Examples of pathogenic bacteria include bacteria of the genus Aeromonas (such as Aeromonas salmonicida, atypical Aeromonas salmonicida, Aeromonas hydrophila, Aeromonas caviae, etc.), bacteria of the genus Edwardsiella (such as Edwardsiella tarda, etc.), bacteria of the genus Pseudomonas (such as Pseudomonas anguilliseptica, Pseudomonas plecoglossicida, etc.), bacteria of the genus Yersinia (such as Yersinia ruckeri, etc.), bacteria of the genus Flavobacterium (such as Flavobacterium branchiophilum, Flavobacterium columnare, Flavobacterium psychrophilum, etc.), bacteria of the genus Tenacibaculum (such as Tenacibaculum maritimum, etc.), bacteria of the genus Renibacterium (such as Renibacterium salmoninarum, etc.), bacteria of the genus Mycobacterium (such as Mycobacterium marinum, Mycobacterium fortuitum, Mycobacterium chelonei, etc.), bacteria of the genus Nocardia (such as Nocardia seriolae, etc.), bacteria of the genus Streptococcus (such as Streptococcus iniae, etc.), and bacteria of the genus Lactococcus (such as Lactococcus garvieae, etc.).

[0077] Other diseases include ichthyobodosis, Takeda microsporidiosis, gelgeiasis, heterosporosis, white spot disease, scuticosis, trichodiniasis, and ovarian hyperplasia, which are caused by protozoa; myxosporean sleeping sickness, myxidiomycosis, intestinal terohaemorrhagosis, myxobolus disease, nephromegaly, Amami kudoasis, myxosporean scoliosis, myxosporean emaciation disease, and parasites. These include tetraonchiasis, trematode cataract, argulosis, gyrodactyliosis, black spot disease, pseudodactylogylosis, angyricoloidosis, dactylogylosis, chondrosis (argulosis), benedeniosis, heteraxine disease, trematode circling disease, bivaginosis, neobenedeniosis, neoheterobothrium, hetrobothrium, and intravascular trematodiasis, which are caused by live worms.

[0078] <Vitamin 12-synthesizing microorganisms> In water, vitamin 12 is biosynthesized by thaum archaea, vitamin 12-synthesizing bacteria, and cyanobacteria. Because vitamin 12 is an important nutrient for aquatic organisms, it is preferable for a certain number of vitamin 12-synthesizing microorganisms to be present in the microbiome. Vitamin 12 has a hematopoietic effect and also increases the nucleic acids and phospholipids that make up peripheral nerves, thereby repairing nerves. Higher plants do not contain vitamin 12 biosynthetic systems or enzymes that use vitamin 12 as a coenzyme, so vitamin 12 is not found in plant foods. Therefore, seafood is an important source of vitamin 12. From the perspective of efficiently storing vitamin 12 in seafood, it is preferable for a certain number of vitamin 12-synthesizing microorganisms to be present in the microbiome.

[0079] <Ammonia-oxidizing bacteria, nitrite-oxidizing bacteria> Accumulation of high concentrations of ammonia and nitrite in water can cause health problems for the cultivated fish 42. Therefore, it is preferable that the microflora contains an appropriate number of ammonia-oxidizing bacteria (Nitrosomonas eutrohpa, Nirosococcus oceanus, etc.) and nitrite-oxidizing bacteria (Nitrobacter winogradskyi, Nitrobacter hamburgensis, Nitrospina gracilis, Nitrococcus mobilis, etc.).

[0080] <Supplies> In the present disclosure, the supply 43 may include feed. It may also include microorganisms. It may also be feed containing microorganisms. If analysis of the intake water microbiome dataset reveals a deviation from a healthy microbial flora, the supply of appropriate microorganisms can change the microbial flora to a healthy state. The microorganisms may be determined based on the results of a co-occurrence analysis using a co-occurrence analysis microorganism dataset, the results of a correlation analysis using a co-occurrence analysis microorganism dataset and a correlation analysis target dataset, or the results of the co-occurrence analysis and the correlation analysis. The microorganisms may be capable of combating pathogenic microorganisms. By supplying microorganisms capable of combating pathogenic microorganisms, diseases in the cultivated product 42 can be suppressed without the use of antibiotics. Microorganisms capable of combating pathogenic microorganisms may be extracted from various literature or determined based on the results of the co-occurrence analysis or the correlation analysis. Supplying vitamin 12-synthesizing microorganisms can increase the amount of vitamin 12 accumulated in the cultivated product 42. Supplying ammonia-oxidizing bacteria or nitrite-oxidizing bacteria can reduce the concentrations of ammonia and nitrite in the water.

[0081] <Bait> In the present disclosure, known feeds can be used as feed for the cultivated specimens 42. Examples of feed components include fish meal, insect meal, wheat flour, wheat gluten, alpha starch, vegetable oil cake, vitamin mixtures, binders, bone meal, yeast, eicosapentaenoic acid, and docosahexaenoic acid. The form of the feed is not particularly limited as long as it is ingestible by the cultivated specimens 42, and may be in any form, such as powder, granules, pellets, cubes, paste, or liquid. There are various types of feeds, including highly nutritious feeds, feeds effective for improving the health of the cultivated specimens 42, highly functional but expensive feeds, and general inexpensive feeds. In the present disclosure, a combination of these feeds may be used. The feeder 2 includes multiple feed tanks 22, and storing different feeds in each feed tank 22 increases the variety of feeding. Antibiotics may be mixed into the feed. While antibiotics are effective in preventing diseases in the cultivated specimens 42, they can accumulate in the cultivated specimens 42, cause the development of antibiotic-resistant bacteria, and place a burden on the environment. Normally, antibiotic-free feed is used, but the occurrence of the above problems can be prevented by using feed mixed with antibiotics as appropriate. Microorganisms may be mixed into the feed. By supplying microorganisms along with the feed, the microflora can be changed to a favorable state. Furthermore, by supplying microorganisms that have a beneficial effect on the intestinal environment of the cultivated aquatic animals 42 along with the feed, the health of the cultivated aquatic animals 42 can be maintained and promoted.

[0082] <Water intake microbiome data, Water intake microbiome dataset> The water intake microbiome data is data on the microbiome obtained by DNA analysis of water collected from the aquaculture section 41 where the target aquaculture product 42 is cultivated, and includes at least information on the names (water intake microbiome identification marks) and quantities (water intake microbiome mass) of microorganisms present in the collected water. The water intake microbiome dataset consists of the above-mentioned water intake microbiome data. The water intake microbiome dataset preferably includes multiple pieces of the above-mentioned water intake microbiome data. Using multiple pieces of water intake microbiome data can increase the accuracy of calculations. The water intake microbiome dataset preferably includes two or more, more preferably three or more, pieces of water intake microbiome data collected at the same collection point on different days. This allows calculation of changes in the microbiome at a collection point over time. In the present disclosure, the same collection point refers to the same location within the aquaculture section or a location within a short distance where the microbiome can be considered substantially the same. The water intake microbiome mass is preferably the absolute abundance of each microorganism, rather than the abundance ratio of each microorganism. Although the abundance ratio can sometimes be measured by simple analysis, in many cases the absolute quantity has a greater impact on the growth of the target aquaculture product 42 than the abundance ratio.

[0083] Water intake microbiome data can be obtained by DNA analysis and gene sequence analysis of collected water samples. DNA analysis can be performed using instruments such as DNA microarrays, next-generation sequencers, qPCR, DGGE, T-RFLP, and FISH. Next-generation sequencers are preferred because they can obtain detailed data on water intake microbiomes. DNA sequence analysis methods using next-generation sequencers include 16S rRNA gene analysis (DNA metabarcoding of the prokaryotic 16S rRNA region), 18S rRNA gene analysis (DNA metabarcoding of the eukaryotic 18S rRNA region), fungal ITS (DNA metabarcoding of the fungal ITS (internal transcribed spacer) region), and shotgun metagenomics. 16S rRNA gene analysis is useful for identifying bacteria and archaea, while 18S rRNA gene analysis is useful for identifying various eukaryotes, including fungi and endo- and ectoparasites. Fungal ITS analysis is useful for identifying fungi. By adjusting the concentration of standard sequence fragments, such as artificially designed DNA sequences (see the above-mentioned literature) or λ phage, and adding them to the PCR solution, calibration can be performed when analyzing DNA data, allowing the absolute abundance (nucleic acid concentration) of each biological species to be estimated. The above analysis and analytical methods can also be combined.

[0084] Figure 4 shows an example of the results of microbial flora analysis obtained by 16S rRNA gene analysis. It shows data on the microbial species present in the microbiome and their abundance.

[0085] <Key Microbial Datasets> The key microorganism dataset is composed of key microorganism data, and the key microorganism data includes at least a key microorganism identification mark and a key microorganism quantity threshold. The key microorganism identification mark is a mark used to identify the key microorganism, such as the name, abbreviation, or symbol of the key microorganism.

[0086] The key microbial mass threshold is referenced together with the intake key microbial mass when the supply content determination unit 14 determines the supply content of the supply device 2. The supply content is determined based on whether the intake key microbial mass exceeds the key microbial mass threshold (here, "exceeding the threshold" can mean either above or below the threshold). The key microbial data may contain multiple key microbial mass thresholds for one key microbial identification mark. This allows the supply content to be changed depending on the level of the key microbial mass. The key microbial mass threshold may be a value derived from a function. For example, when the supply content should be changed depending on the pH, temperature, or oxygen concentration of the aquaculture section 41, the influence of the variables can be taken into account by deriving the key microbial mass threshold from a function with the pH, temperature, or oxygen concentration as variables. The key microbial data may include attributes and characteristics of microorganisms, such as their relationship with other microorganisms and their response characteristics to ambient environmental conditions such as pH, temperature, and oxygen concentration.

[0087] <Microbiota dataset for co-occurrence analysis, dataset for correlation analysis> The microbiome data set for co-occurrence analysis is composed of multiple microbiome data sets for co-occurrence analysis. The microbiome data sets for co-occurrence analysis include at least the names (microbiome identification marks) and quantities (microbiome quantities) of microorganisms contained in the collected sample. The microbiome data sets for co-occurrence analysis may be data on the microbiome contained in water, or may be data on the microbiome present inside the body of the cultivated aquatic product 42, for example, in the epidermis or intestines. By performing co-occurrence analysis using the microbiome data set for co-occurrence analysis, it is possible to determine the correlation between the microorganisms that make up the microbiome. The correlation may be used to identify key microorganisms or to determine a key microorganism quantity threshold.

[0088] The correlation analysis target dataset consists of multiple correlation analysis target data. The location of the correlation analysis target data can be anywhere at the sampling point of the water or cultivated material 42 from which the corresponding microbial flora data for co-occurrence analysis is obtained, as long as the numerical values ​​of the items included in the target data can be considered to be similar. However, it is preferable that the location be the same as the sampling point of the water or cultivated material 42 or within the same aquaculture area. This is because it increases the accuracy of the correlation analysis. By performing a correlation analysis using the microbial flora dataset for co-occurrence analysis and the correlation analysis target dataset, it is possible to determine the correlation between the microbial flora and the correlation analysis target. Key microorganisms may be identified using this correlation. A key microbial quantity threshold may be determined from the correlation between the microbial quantity and the correlation analysis target.

[0089] The microbiome dataset for co-occurrence analysis and the correlation analysis target dataset may include a combination of microbiome data for co-occurrence analysis obtained from the same water collection site but at different times, and correlation analysis target data obtained from the same water collection site but at different times, where the collection site and the collection site are the same or within the same aquaculture area. This allows for accurate understanding of changes over time in the microbiome at the water collection site. It may also be possible to identify key microorganisms specific to the collection site.

[0090] In cases where the water sampling point for obtaining the microbial flora data for co-occurrence analysis and the correlation analysis target data are the same or within the same aquaculture area, and there are multiple microbial flora data for co-occurrence analysis and correlation analysis target data where the water sampling times for obtaining the microbial flora data for co-occurrence analysis and the correlation analysis target data are different, one microbial flora data for co-occurrence analysis may be combined for analysis with multiple correlation analysis target data obtained at different times.Furthermore, one correlation analysis target data may be combined for analysis with multiple microbial flora data for co-occurrence analysis where the water sampling times are different.The causal relationship between changes in the microbial flora and changes in the correlation analysis target can be measured, and the causal relationship can be reflected in the identification of key microorganisms.

[0091] The microbiome dataset for co-occurrence analysis and the correlation analysis target dataset may include multiple combinations of microbiome data for co-occurrence analysis and correlation analysis target data, where the location where the water from which the microbiome data for co-occurrence analysis is obtained is the same as the location where the correlation analysis target data is obtained or is in the same aquaculture area, and the time when the water from which the microbiome data for co-occurrence analysis is obtained is the same as the time when the data was obtained (including cases where the period when the water was obtained and the microbiome data are considered not to change significantly overlap, and the period when the data are obtained and the target data are considered not to change significantly). Including microbiomes in different states may make it easier to identify key microorganisms.

[0092] Even if the water sampling point where the microbial flora data for co-occurrence analysis is obtained and the correlation analysis target data are obtained within the same aquaculture area, due to water flow, the correlation analysis target data may differ depending on the data acquisition point, such as in the case of irradiance, even though the microbial flora data are very similar. In such cases, multiple correlation analysis target data may be combined with one piece of microbial flora data for co-occurrence analysis and used for correlation analysis. Furthermore, even if the water sampling point and the correlation analysis target data acquisition point are within the same aquaculture area, if the state of the microbial flora differs due to differences in depth, irradiance, water temperature, etc., the microbial flora data for co-occurrence analysis of water collected at each point may be combined with the corresponding correlation analysis target data and used for correlation analysis.

[0093] The water sampling location for obtaining the microbiome data for co-occurrence analysis may be the same location as the water from which the intake water microbiome data is obtained or may be within the same aquaculture area. This is because the microbiome data for co-occurrence analysis and the intake water microbiome data are likely to be similar, and therefore the correlation between the microbiome data for co-occurrence analysis and the data subject to correlation analysis is likely to also apply between the intake water microbiome data and the data subject to correlation analysis. The intake water microbiome data may also serve as the microbiome data for co-occurrence analysis.

[0094] The data to be analyzed for correlation may be any data correlated with the microbial flora for co-occurrence analysis, such as environmental data for the aquaculture section 41 or data on the cultivated product 42. The data to be analyzed for correlation may include at least items and numerical values ​​for those items. Examples of the items include the temperature (water temperature), pH, temperature, turbidity, dissolved oxygen concentration, salinity, ammonia concentration, nitrate concentration, nitrite concentration, phosphate ion concentration, copper ion concentration, ozone concentration, and sunlight intensity of the aquaculture section 41, as well as the activity, growth, health, and accumulated nutrients of the cultivated product 42. Items that are often expressed using qualitative or descriptive labels can also be quantified by setting appropriate standards.

[0095] The activity level can be measured, for example, from the mobility of the cultured objects 42, the state of feeding, etc. The mobility of the cultured objects 42 can be measured, for example, by analyzing video footage of the movement of the cultured objects 42 in the culture section 41, by counting the number of cultured objects crossing a sensing area within a certain period of time using a sensor that detects the passage of objects, by measuring the movement speed of the cultured objects 42 crossing the sensing area using a sensor that detects the movement speed of passing objects, or by attaching a position sensor to one or more cultured objects 42 to detect their movement. The feeding amount can be measured, for example, by analyzing, from video of the cultured objects 42 swarming around the feed during feeding, the proportion of the cultured objects 42 that respond to feeding, the proportion of the cultured objects 42 that have fed, the acuity of their movement during feeding, and the amount of splashing on the water surface, or by measuring the amount of food that remains uneaten (residual food amount) from images of the culture section 41 and water analysis.

[0096] The growth level can be measured, for example, by measuring the size and weight of one or more cultured objects 42 to be measured, or by measuring the size distribution of the cultured objects 42 using an image of the culture section 41. The health level can be measured, for example, by determining the shape, color, gloss, etc. of the cultured objects 42, or by analyzing the body composition of the cultured objects 42. An example of an accumulated nutrient is vitamin B12.

[0097] The correlation analysis target data preferably includes multiple items. This allows for a more in-depth analysis of the correlation between the microbial flora for co-occurrence analysis and the correlation analysis target. For example, when investigating the correlation between the co-occurring microbial flora and the activity of the cultivated material 42, if the correlation analysis target data includes water temperature, oxygen concentration, and the activity of the cultivated material 42, the correlation can be investigated more accurately by using the activity of the cultivation level corrected to reflect the influence of water temperature and oxygen concentration. For example, the partial correlation coefficient between the amount of each microorganism in the co-occurring microbial flora and the activity of the cultivated material 42 can be investigated.

[0098] <Co-occurrence analysis, correlation analysis> In co-occurrence analysis using a microbiome dataset for co-occurrence analysis, a statistical analysis of the coexistence and non-coexistence patterns between microorganisms among multiple microbiome data is performed. The co-occurrence analysis may be used to identify key microorganisms or to determine a key microorganism abundance threshold. For example, microorganisms that exhibit a strong coexistence pattern with pathogenic microorganisms or a strong non-coexistence pattern may be identified as key microorganisms. Furthermore, a threshold for the key microorganism abundance may be determined based on the degree of coexistence or non-coexistence pattern.

[0099] Examples of co-occurrence analysis methods include, but are not limited to, simple methods such as measuring the correlation coefficient of microbial abundance between microorganisms, to more advanced methods such as the sparse inverse covariance estimation for ecological association and statistical inference (the Meinshausen and Buhlmann (MB) method, the Glasso method, the sparse and low-rank (SLR) decomposition method, etc.).

[0100] When the correlation coefficient of the abundance of microorganisms in water is used as a criterion for identifying key microorganisms as a method of co-occurrence analysis, the absolute value of the correlation coefficient may be 0.2 or more as the criterion. Alternatively, the criterion may be 0.3 or more. The upper limit may be less than 1.0. Alternatively, the criterion may be 0.5 or more. Alternatively, the upper limit may be less than 1.0. When sparse inverse covariance estimation of the abundance of microorganisms in water is used, the absolute value of the covariance may be 0.1 or more as the criterion. Alternatively, the criterion may be 0.5 or more. Alternatively, the criterion may be 1.0 or more. The upper limit may be, for example, 50 or less, 20 or less, or 10 or less, but is not particularly limited to this.

[0101] For each microorganism constituting the microbiota included in the microbiota data for co-occurrence analysis, a key microorganism may be identified or a key microorganism quantity threshold may be determined by correlation analysis between the amount of each microorganism shown in the microbiota dataset for co-occurrence analysis and the corresponding correlation analysis target data. In identifying a key microorganism or determining a key microorganism quantity threshold, the absolute value of the correlation coefficient between the key microorganism quantity of the identified key microorganism and the correlation analysis target data is preferably 0.2 or more and less than 1.0, and even more preferably 0.3 or more and less than 1.0. Furthermore, when the correlation analysis target data includes multiple items, it is preferable to use a partial correlation coefficient between the amount of each microorganism and the corresponding correlation analysis target data as the correlation coefficient. For example, if the data to be analyzed for correlation analysis includes water temperature, oxygen concentration, and the activity of the cultivated material 42, the influence of each microorganism in the microbial flora of the water from which the microbial flora data for co-occurrence analysis was obtained can be determined by excluding the effects of water temperature and oxygen concentration and examining the partial correlation coefficient between the amount of each microorganism and the activity of the cultivated material 42. If the partial correlation coefficient is equal to or greater than a certain value (for example, the average value of the partial correlation coefficient is +0.2 or greater), the microorganism may be identified as a key microorganism, as it shows a positive correlation with activity. If the partial correlation coefficient is equal to or less than a certain value (for example, the average value of the partial correlation coefficient is -0.2 or less), the microorganism may be identified as a key microorganism, as it shows a negative correlation with activity.

[0102] Key microorganisms may be identified or a key microorganism abundance threshold determined based on the results of co-occurrence analysis using the microbiome dataset for co-occurrence analysis and the results of correlation analysis using the microbial abundance of each microorganism in the microbiome dataset for co-occurrence analysis and the correlation analysis target dataset. Figure 5 shows an image of co-occurrence analysis using the microbiome data for co-occurrence analysis and a correlation analysis of the microbial abundance contained in the microbiome data for co-occurrence analysis and the correlation analysis target data superimposed on each other. Circles in the figure correspond to individual microorganisms, and microorganisms with a correlation greater than a predetermined value are connected by lines. Microorganisms 51 with a positive partial correlation with the correlation analysis target characteristic data are represented by black circles; the larger the black circle, the larger the partial correlation coefficient. Microorganisms 52 with a negative partial correlation with the correlation analysis target characteristic data are represented by white circles; the larger the white circle, the larger the partial correlation coefficient. Microorganism module 53 is surrounded by a dotted line.

[0103] <Supplier data> The supply device data includes at least supply data for the supply material 43 stored in the supply tank 22. If there are multiple supply tanks 22, the supply data for each supply tank 22 is included. The supply data is data related to the supply material 43, such as the name of the supply material 43 stored in each supply tank 22, the date and time the supply material 43 was introduced into the supply tank 22, the amount stored, and the characteristics of the supply material 43. The supply device data may also include information about the supply mechanism 23. For example, the data may include data related to the transport mechanism parts, the transport accuracy of the supply material 43, and maintenance dates.

[0104] <Supply Content Data> The supply content data includes at least data regarding a drive command for the supply mechanism 23 that transfers the supply material 43 stored in the supply tank 22 and releases it into the culture section 41. If there are multiple supply tanks 22, the data is command data regarding the transfer of the supply material 43 from each supply tank 22. If there are multiple supply mechanisms 23, the data is command data regarding the drive of each supply mechanism 23. For example, the data is data regarding the transfer amount and transfer timing of the supply material 43 in each supply tank 22. In addition, if the supply tank 22 or the culture section 24 has a temperature control function, the data may include target temperature data. If the supply device 2 has a culture section 24, the data may include command data regarding the transfer from the culture section 24 to the supply tank 22. If the supply content data input unit 21 has a memory function and a calculation function, the timing of driving the supply mechanism 23 (the timing of transferring the supply material 43) and the timing of changing the temperature of the supply tank 22 and the culture unit 24 can be included in the supply content data, so that the internal processing of the supply device 2 can perform appropriate operations at appropriate times without the need to output the supply content data from the calculation device 1 each time.

[0105] <Sensor data> The sensor data is data acquired by sensors provided in the sensing unit 25 of the supply device 2. Examples of the sensor data include remaining amount data of the supply material 43 acquired by sensors that detect the internal state of the supply device 2, such as weight sensors and position sensors of the transfer mechanism, and temperature and humidity data of the supply tank 22 and the culture unit 24 acquired by temperature sensors and humidity sensors. Other examples include data acquired by sensors that detect the external environment and the environment of the aquaculture section 41, such as temperature sensors, pH sensors, turbidity sensors, dissolved oxygen concentration sensors, salinity concentration sensors, ammonia concentration sensors, nitrate concentration sensors, nitrite concentration sensors, phosphate ion concentration sensors, copper ion concentration sensors, ozone concentration sensors, and aquaculture activity detection sensors. The sensor data may be used by the supply content determination unit 14 when determining the supply content.

[0106] <Process flow> 6A is a schematic diagram of a process flow according to one embodiment of the present disclosure. Each step will now be described. S1: The input unit 11 inputs the water intake key microbiome data. S2: The storage unit 12 stores the water intake key microbiome data input by the input unit 11. The storage unit 12 stores the key microorganism data set and the supply device data in advance. S3: The calculation unit 13 identifies key water intake microorganisms from the water intake microbiome dataset and the key microorganism dataset stored in the memory unit 12. S4: The calculation unit 13 calculates the amount of the key water intake microorganisms identified in STEP 3 from the water intake microbiome dataset stored in the memory unit 12. S5: The supply content determination unit 14 determines the supply content based on the intake water key microbial amount calculated in S4 and the key microbial amount threshold data set stored in the storage unit 12, and creates supply content data. S6: The supply content data output unit 15 outputs the supply content data. S7: The supply content data input unit 21 inputs the supply content data. S8: In accordance with the supply content data input by the supply content data input unit 21, the supply mechanism 23 transfers the supply material from the supply tank 22 to the aquaculture compartment and releases it into the aquaculture compartment.

[0107] 6B is a schematic diagram of a process flow according to another embodiment of the present disclosure, in which steps common to those in FIG. 6A are designated by common symbols and will not be described further. S9: Identify key microorganisms based on co-occurrence analysis using the microbiome dataset for co-occurrence analysis, or correlation analysis using the microbiome dataset for co-occurrence analysis and the dataset for co-occurrence analysis, or the co-occurrence analysis and the correlation analysis, or identify key microorganisms and determine a key microorganism quantity threshold. The input unit 11 of the calculation device 1 may input the identified key microorganisms and the determined key microorganism quantity threshold. The calculation unit 13 may identify the key microorganisms and determine the key microorganism quantity threshold. S10: The storage unit 12 stores the key microorganism identification mark or key microorganism data of the key microorganism identified in S9 as part of the key microorganism data set.

[0108] 6C is a schematic diagram of a process flow according to another embodiment of the present disclosure, in which steps common to those in FIG. 6A are designated by common symbols and will not be described again. S11: The sensing unit 25 of the supply device 2 acquires sensor data. S12: The sensor data output unit 26 outputs the sensor data acquired by the sensing unit 25. S13: The sensor data output by the sensor data output unit 26 is input to the sensor data input unit 16. S5': The supply content determination unit 14 determines the supply content based on the intake key microbial amount calculated in S4, the key microbial amount threshold data set stored in the memory unit 12, and the sensor data input by the sensor data input unit 16 in S13.

[0109] Although the embodiments of the present disclosure have been described above, the above description should be considered to be illustrative in all respects and not restrictive. The scope of the present disclosure is defined by the claims, not by the description of the above embodiments, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0110] 1 Computing device 11 Input section 12 Storage section 13 Arithmetic section 14 Supply content determination section 15 Supply content data output section 16 Sensor data input section 2 Feeding device 21 Supply content data input section 22 Supply tank 23 Supply mechanism 24 Culture Department 25 Sensing unit 26 Sensor data output section 3 Communication medium 31 Communication medium for sensor data 41 Aquaculture plots 42 Aquaculture 43 Supplies 51 Microorganisms with positive partial correlation with the characteristic data of the correlation analysis target 52 Microorganisms with negative partial correlation with the characteristic data for correlation analysis 53 Microorganism Module

Claims

1. 1. A feeding system for aquaculture, comprising a computing device and a feeding device having a feeding tank, the feeding system comprising: The computing device an input unit for inputting water intake microbial flora data including water intake microbial identification marks and water intake microbial mass obtained by DNA analysis of the collected water; a storage unit for storing a water intake microbiome dataset including the water intake microbiome data, a key microorganism dataset including key microorganism identification marks and key microorganism quantity thresholds of key microorganisms, and supply device data including supply data of the supply tank; a calculation unit that identifies key microorganisms in the water intake using at least the water intake microbiome data and the key microorganism dataset, and calculates the amount of key microorganisms in the water intake; a supply content determination unit that determines supply content and creates supply content data by referring to at least the intake water key microbial amount, the key microbial amount threshold, and the supply device data; a supply content data output unit that outputs the supply content data, The supply device comprises: a supply content data input unit for inputting the supply content data; the supply tank containing the supply; A supply system comprising: a supply mechanism that transfers the supply material stored in the supply tank and releases it into the culture compartment in accordance with the supply content data.

2. The delivery system of claim 1 , wherein the delivery comprises a microorganism.

3. 3. The feeding system of claim 1 or claim 2, wherein the feed comprises aquaculture feed.

4. The supply system according to claim 1 or 2, wherein the supply device comprises two or more supply tanks.

5. The supply system according to claim 1 or 2, wherein the supply device comprises a sensing unit.

6. The supply system according to claim 5 , wherein the supply content determination unit refers to sensor data acquired by the sensing unit when determining the supply content.

7. The supply system of claim 1 or claim 2, wherein the water intake microbiome dataset includes water intake microbiome data obtained from at least two or more water samples collected at the same location but on different intake dates.

8. The supply system according to claim 7 , wherein the calculation unit calculates the change over time in the amount of the key water intake microorganisms using the water intake microbiome data to obtain the amount of the key water intake microorganisms as a function of time.

9. The supply system according to claim 1 or claim 2, wherein the key microorganism identification mark of the key microorganism dataset includes the key microorganism identification mark of the key microorganism identified by co-occurrence analysis using a microbiome dataset for co-occurrence analysis, or by correlation analysis using the microbiome dataset for co-occurrence analysis and a correlation analysis target characteristic dataset, or by a combination of the co-occurrence analysis and the correlation analysis.

10. 10. The supply system of claim 9, wherein at least one selected from the group of data consisting of the microbiome data for co-occurrence analysis included in the microbiome data set for co-occurrence analysis and the correlation analysis target characteristic data included in the correlation analysis target characteristic dataset is obtained from the same aquaculture plot as the aquaculture plot from which the water intake microbiome data was obtained.

11. The delivery system according to claim 1 or 2, wherein the DNA analysis is performed using a next-generation sequencer.

12. A computing device that commands the content of supply to an aquaculture supply device having a supply tank that stores a supply material to be supplied to an aquaculture section, an input unit for inputting water intake microbial flora data including water intake microbial identification marks and water intake microbial mass obtained by DNA analysis of the collected water; a storage unit for storing an intake water microbiome dataset including the intake water microbiome data, a key microorganism dataset including key microorganism identification marks and key microorganism quantity thresholds, and supply device data including supply data for the supply tank; a calculation unit that identifies key microorganisms in the water intake using at least the water intake microbiome data and the key microorganism dataset, and calculates the amount of key microorganisms in the water intake; a supply content determination unit that determines the supply content and creates supply content data by referring to at least the intake water key microbial amount, the key microbial amount threshold, and the supply device data; a supply content data output unit that outputs the supply content data.

13. A feeding device for feeding aquaculture compartments, comprising: a supply content data input unit for inputting supply content data; a supply tank containing the supply; a supply mechanism that transfers the supply material stored in the supply tank and releases it into the aquaculture section in accordance with the supply content data; The supply content data includes at least A water intake microbial abundance data set including water intake microbial flora data including water intake microbial identification marks and water intake microbial abundance obtained by DNA analysis of the collected water; a key microorganism dataset including key microorganism identification symbols and key microorganism abundance thresholds; and supply content data generated and output by a computing device based on supply device data including supply item data for the supply tank.

14. A method for determining the content of a supply of a material stored in a supply tank to be supplied to an aquaculture section, comprising: Identifying key microorganisms from a water intake microbial mass dataset including water intake microbial flora data including water intake microbial identification marks and water intake microbial mass, and a key microorganism dataset including key microorganism identification marks and key microbial mass thresholds, obtained by DNA analysis of the collected water; Calculate the amount of key microorganisms in the water intake, A supply content determination method for determining the supply content by referring to at least the intake water key microbial amount, the key microbial amount threshold, and supply data of the supply tank.

15. The supply content determination method according to claim 14, wherein the key microorganism dataset includes the key microorganism identification mark of a key microorganism identified by co-occurrence analysis of a microbiome dataset for co-occurrence analysis, or by correlation analysis using the microbiome dataset for co-occurrence analysis and a correlation analysis target characteristic dataset, or by a combination of the co-occurrence analysis and the correlation analysis.

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