Aquaculture simulation device, aquaculture simulation method, and aquaculture simulation program

Abstract

To perform simulation related to feeding in culture.SOLUTION: A culture simulation device 1 performing simulation related to culture of a school of fish comprises: a feed intake calculation unit 11 that calculates feed intake information on feed intake for one individual fish in a school of fish as a result of feeding; and an output unit 14 that outputs the feed intake information calculated by the feed intake calculation unit 11. The culture may be conducted in a fish pond. The feed intake information may be at least one of the amount of feed intake, the amount of content in the stomach after feed intake, or energy taken in from feed intake. The feed intake calculation unit 11 may calculate the feed intake information based on at least one of fish information on the school of fish, fish pond information on the fish pond in which culture is conducted, or feeding information on feeding.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] One aspect of the present disclosure relates to an aquaculture simulation device, an aquaculture simulation method, and an aquaculture simulation program for performing a simulation regarding the aquaculture of schools of fish. [Background technology]

[0002] BACKGROUND ART Apparatuses for farming fish have been known for some time. For example, Patent Document 1 listed below discloses an aquaculture apparatus that can farm fish vigorously. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2020-174569 Summary of the Invention [Problem to be solved by the invention]

[0004] Generally, feed is the largest cost factor in aquaculture, so it is desirable to conduct simulations of feeding in aquaculture in order to improve the efficiency of feeding. [Means for solving the problem]

[0005] An aquaculture simulation device according to one aspect of the present disclosure is an aquaculture simulation device that performs a simulation regarding the aquaculture of a school of fish, and includes a feeding calculation unit that calculates feeding information regarding the feeding of each individual fish in the school of fish through feeding, and an output unit that outputs the feeding information calculated by the feeding calculation unit.

[0006] An aquaculture simulation method according to one aspect of the present disclosure is an aquaculture simulation method executed by an aquaculture simulation device that performs a simulation regarding the aquaculture of a school of fish, and includes a feeding calculation step that calculates feeding information regarding the feeding of each individual fish in the school of fish due to feeding, and an output step that outputs the feeding information calculated in the feeding calculation step.

[0007] An aquaculture simulation program according to one aspect of the present disclosure is an aquaculture simulation program that performs a simulation regarding the aquaculture of a school of fish, and causes a computer to function as a feeding calculation unit that calculates feeding information regarding the feeding of each individual fish in the school of fish due to feeding, and an output unit that outputs the feeding information calculated by the feeding calculation unit.

[0008] In this aspect, in a simulation of farming a school of fish, feeding information regarding feeding of each individual fish in the school of fish due to feeding is calculated and output, thereby making it possible to perform a simulation of feeding in aquaculture. [Effects of the Invention]

[0009] According to one aspect of the present disclosure, a simulation of feeding in aquaculture can be performed. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 2 is a diagram illustrating an example of a functional configuration of the aquaculture simulation device according to the embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of the hardware configuration of a computer used in the aquaculture simulation device according to the embodiment. [Figure 3] FIG. 2 is a diagram showing the configuration of an aquaculture simulation program according to an embodiment, together with a storage medium. [Figure 4] FIG. 10 is a diagram illustrating an example of the behavior of a fish separating from nearby fish. [Figure 5] FIG. 10 illustrates an example of the behavior of fish grouping with nearby fish. [Figure 6]FIG. 10 is a diagram showing an example of the behavior of a fish lining up with nearby fish. [Figure 7] FIG. 10 is a diagram showing an example of the behavior of a fish moving away from an obstacle. [Figure 8] FIG. 10 is a diagram showing an example of the behavior of a fish moving randomly. [Figure 9] FIG. 1 is a diagram showing an example of the behavior of feeding fish. [Figure 10] FIG. 10 is a diagram showing an example of determining feeding by fish. [Figure 11] FIG. 10 is a diagram showing the overall flow of an example of a simulation using a fish school behavior model and a growth model. [Figure 12] 10 is a flowchart illustrating an example of processing executed by the aquaculture simulation device according to the embodiment. [Figure 13] FIG. 10 shows the results of simulation 1-1 in which 100 individuals were reared. [Figure 14] FIG. 10 shows the results of simulation 1-2 in which the number of individuals reared was 200. [Figure 15] This figure shows the results of simulation 2-1, in which the water tank shape was circular with a diameter of 3.0 m. [Figure 16] This figure shows the results of simulation 2-2, in which the tank shape was a rectangle with each side 3.0 m. [Figure 17] This figure shows the results of simulation 2-3, in which the tank shape was circular with a diameter of 6.0 m. [Figure 18] FIG. 10 shows the results of simulation 3-1 in which the feeding amount was 0.5% of the body weight. [Figure 19] FIG. 10 shows the results of simulation 3-2 in which the feeding amount was 1.0% of the body weight. [Figure 20] FIG. 10 shows the results of simulation 3-3 in which the feeding amount was 2.0% of the body weight. [Figure 21] This figure shows the results of simulation 4-1, in which the feeding area was 0.5 m square. [Figure 22] This figure shows the results of simulation 4-2, in which the feeding area was 1.0 m square. [Figure 23]This figure shows the results of simulation 4-3, in which the feeding area was 1.5 m square. [Figure 24] FIG. 10 shows the results of simulation 5-1 in which the feeding frequency was once per day. [Figure 25] FIG. 10 shows the results of simulation 5-2 in which the feeding frequency was twice a day. [Figure 26] FIG. 10 shows the results of simulation 5-3 in which the feeding frequency was 4 times / day. [Figure 27] 10 is a table showing a list of simulation results. [Figure 28] FIG. 10 is a diagram illustrating an example of a simulation on the first day. [Figure 29] FIG. 10 is a diagram showing an example of a simulation on the 90th day. [Figure 30] FIG. 10 is a diagram showing an example of a feeding range. [Figure 31] FIG. 1 shows changes in body weight due to feeding A. [Figure 32] FIG. 1 shows changes in body weight due to feeding C. [Figure 33] FIG. 1 shows the frequency of body weights with feeding A. [Figure 34] FIG. 1 shows the frequency of body weights with feeding C. [Figure 35] 10 is a flowchart showing another example of processing executed by the aquaculture simulation device according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the description of the drawings, the same elements are designated by the same reference numerals, and duplicate explanations will be omitted. Furthermore, the embodiments of the present disclosure in the following description are specific examples of the present invention, and the present invention is not limited to these embodiments unless otherwise specified to limit the present invention.

[0012] FIG. 1 is a diagram illustrating an example of the functional configuration of an aquaculture simulation device 1 according to an embodiment. The aquaculture simulation device 1 is a computer device that performs a simulation of aquaculture of a school of fish. A school of fish is a group of one or more fish. A school of fish may be composed of fish of the same fish species (kind of fish), or may be composed of fish of two or more different fish species. In the embodiment, it is assumed that a school of fish is composed of fish of the same fish species, but this is not limited to this. Aquaculture may be performed in a fish pen. A fish pen is a facility for raising a school of fish for a certain period of time before selling or eating. Examples of fish pens include a water tank, a pond, or an underwater enclosure surrounded by a bamboo fence or net. A simulation is a simulated experiment performed using a computer or the like. In a simulation, realistic conditions are incorporated to simulate a situation close to reality and an experiment is performed.

[0013] 1, the aquaculture simulation device 1 (aquaculture simulation device) includes an information storage unit 10, a feeding calculation unit 11 (feeding calculation unit), a growth calculation unit 12 (growth calculation unit), a profit calculation unit 13 (profit calculation unit), and an output unit 14 (output unit). Details of each functional block will be described later.

[0014] Each functional block of the aquaculture simulation device 1 is assumed to function within the aquaculture simulation device 1, but this is not limited to this. For example, some of the functional blocks of the aquaculture simulation device 1 may function within a computer device different from the aquaculture simulation device 1, and connected to the aquaculture simulation device 1 via a network, while appropriately sending and receiving information with the aquaculture simulation device 1. Furthermore, some functional blocks of the aquaculture simulation device 1 may be omitted, multiple functional blocks may be integrated into one functional block, or one functional block may be separated into multiple functional blocks.

[0015] FIG. 2 is a diagram showing an example of the hardware configuration of a computer used in the aquaculture simulation device 1. As shown in FIG. 2, the aquaculture simulation device 1 is physically configured as a computer system including a CPU (Central Processing Unit) 100, which is a central processing unit (processor), a RAM (Random Access Memory) 101 and a ROM (Read Only Memory) 102, which are main storage devices, an input / output device 103 such as a keyboard, a microphone, a touch panel, and a display, a communication module 104, which is a data transmission / reception device, and an auxiliary storage device 105 such as a hard disk and an SSD (Solid State Drive). The CPU 100, the RAM 101, the ROM 102, the input / output device 103, the communication module 104, and the auxiliary storage device 105 may each be configured with a plurality of components. The functions of each functional block shown in FIG. 1 are realized by loading predetermined computer software onto hardware such as the CPU 100 and RAM 101 shown in FIG. 2, which operates the input / output device 103 and the communication module 104 under the control of the CPU 100 and reads and writes data from and to the RAM 101 and the auxiliary storage device 105.

[0016] 3 is a diagram showing the configuration of an aquaculture simulation program 300 according to an embodiment together with a storage medium. As shown in FIG. 3, the aquaculture simulation program 300 is inserted into a computer and accessed, or is stored in a program storage area 201 formed in a storage medium 200 provided in the computer.

[0017] The aquaculture simulation program 300 is configured to include a feeding calculation module 301, a growth calculation module 302, a profit calculation module 303, and an output module 304. The functions realized by executing the feeding calculation module 301, the growth calculation module 302, the profit calculation module 303, and the output module 304 are similar to the functions of the feeding calculation unit 11, the growth calculation unit 12, the profit calculation unit 13, and the output unit 14 of the aquaculture simulation device 1 described above. In other words, the aquaculture simulation program 300 is a (computer) program that performs a simulation regarding the aquaculture of fish schools, and is a program that causes a computer to function as the feeding calculation unit 11, the growth calculation unit 12, the profit calculation unit 13, and the output unit 14.

[0018] Each module of the aquaculture simulation program 300 is assumed to function within a single computer, but this is not limited to this. For example, some of the modules of the aquaculture simulation program 300 may function in a computer device different from the single computer, connected to the single computer via a network, while appropriately sending and receiving information with the single computer. Furthermore, some modules of the aquaculture simulation program 300 may be omitted, multiple modules may be integrated into a single module, or one module may be separated into multiple modules.

[0019] Hereinafter, each functional block of the aquaculture simulation device 1 shown in FIG. 1 will be described.

[0020] The information storage unit 10 stores any information that is used or output during processing of the aquaculture simulation device 1. The information storage unit 10 may store information calculated by each function of the aquaculture simulation device 1. The information stored by the information storage unit 10 may be referenced by each function of the aquaculture simulation device 1 as appropriate.

[0021] The feeding calculation unit 11 calculates feeding information related to the feeding of each individual fish in the school of fish due to feeding. For example, the feeding calculation unit 11 simulates feeding in the fish pen, the movement of each individual fish in the school of fish, and the feeding of each individual fish in the school of fish, and calculates the feeding information related to the feeding. The feeding calculation unit 11 may store the calculated feeding information in the information storage unit 10. The feeding calculation unit 11 may output the calculated feeding information to the growth calculation unit 12 and the output unit 14.

[0022] The feeding information may be at least one of the amount of food intake, the stomach volume after feeding, or the energy taken in by feeding. For example, the feeding information may be the amount of food intake, the stomach volume after feeding, or the energy taken in by feeding. For example, the feeding information may be the amount of food intake and the stomach volume after feeding, the amount of food intake and the energy taken in by feeding, or the stomach volume after feeding and the energy taken in by feeding. For example, the feeding information may be the amount of food intake, the stomach volume after feeding, and the energy taken in by feeding. Furthermore, each of the above combinations may further include other information.

[0023] The feeding calculation unit 11 may calculate the feeding information based on at least one of fish information about a school of fish, net cage information about a net cage where aquaculture is performed, or feeding information about feeding. For example, the feeding calculation unit 11 may calculate the feeding information based on fish information, or net cage information, or feeding information. For example, the feeding calculation unit 11 may calculate the feeding information based on fish information and net cage information, or fish information and feeding information, or net cage information and feeding information. For example, the feeding calculation unit 11 may calculate the feeding information based on fish information, net cage information, and feeding information. Furthermore, the feeding information may be calculated by adding other information to the above combinations.

[0024] The fish information may be at least one of the number of fish in the school, the species of the fish, the weight of the fish, the body length of the fish, the stomach volume of the fish, the swimming ability of the fish, or the swimming speed of the fish.

[0025] The fish cage information may be at least one of the size of the fish cage, the shape of the fish cage, and the water temperature of the fish cage.

[0026] The feeding information may be at least one of the amount of feeding, the range of feeding, or the frequency of feeding.

[0027] The feeding calculation unit 11 may calculate the feeding information using a fish school behavior model that models the behavior of a school of fish. For an example of a fish school behavior model, see Non-Patent Document 1 below. [Non-Patent Document 1] Craig W. Reynolds, “Flocks, Herds, and Schools: A Distributed Behavioral Model”, Computer Graphics, 21(4), July 1987, pp. 25-34

[0028] The fish behavior model may include at least one of a model related to the behavior of fish moving away from obstacles, a model related to the random behavior of fish, and a model related to the behavior of fish moving towards bait. For example, the fish behavior model may include a model related to the behavior of fish moving away from obstacles, a model related to the random behavior of fish, or a model related to the behavior of fish moving towards bait. For another example, the fish behavior model may include a model related to the behavior of fish moving away from obstacles and a model related to the random behavior of fish, a model related to the behavior of fish moving away from obstacles and a model related to the behavior of fish moving towards bait, or a model related to the random behavior of fish and a model related to the behavior of fish moving towards bait. For another example, the fish behavior model may include a model related to the behavior of fish moving away from obstacles, a model related to the random behavior of fish, and a model related to the behavior of fish moving towards bait.

[0029] 4 to 9, various examples of the behavior of a school of fish that can be modeled in a fish school behavior model will be described.

[0030] Figure 4 shows an example of the behavior of a fish separating from a nearby fish. As shown in Figure 4, the position vector x i For a fish swimming in the j The swimming force vector F1 is generated to separate the fish from nearby fish swimming in the same direction. The swimming force vector F1 is expressed by the following equation, for example, using the swimming behavior weight w1:

number

[0031] Figure 5 shows an example of the behavior of fish grouping with nearby fish. As shown in Figure 5, the position vector x i In order for a fish swimming in the same direction to form a group (cohesion) with three other fish nearby, the average position vector x of the position vectors of the three fish is calculated. ave The swimming force vector F2 is expressed by the following equation using the weight w2 of the swimming action, for example:

number

[0032] Figure 6 shows an example of the behavior of a fish aligning with nearby fish. As shown in Figure 6, the velocity vector v i For a fish swimming in the same direction, the average velocity vector v of each of the three fish is calculated to align with the other three fish nearby. ave The swimming force vector F3 is expressed by the following equation using the weight w3 of the swimming action, for example.

number

[0033] Fig. 7 shows an example of the behavior of a fish moving away from an obstacle. As shown in Fig. 7, the position vector x i For a fish swimming in the obj The swimming force vector F4 is generated to move away from nearby obstacles (avoiding objects) at the position . The swimming force vector F4 is expressed by the following equation using the swimming behavior weight w4, for example:

number

[0034] The behavior of fish moving away from an obstacle is, for example, behavior toward the wall of the aquarium (animal preserve). Changes in the shape of the aquarium change the behavior of the fish school, which also affects the behavior until reaching the food. As a result, the amount of food intake changes, and the growth rate, which will be described later, also changes. The food intake calculation unit 11 may perform calculations taking this into consideration.

[0035] Fig. 8 is a diagram showing an example of the behavior of a fish moving randomly. As shown in Fig. 8, a swimming force vector F5 is generated so that the swimming fish makes a random move according to three other fish swimming nearby with position vectors x1, x2, and x3. The swimming force vector F5 is expressed by the following equation, for example, using a swimming behavior weight w5:

number

[0036] The behavior of the fish, which moves randomly, changes the behavior of the fish until it reaches the food, which affects the amount of food intake. The food intake calculation unit 11 may perform calculations taking this into consideration.

[0037] Figure 9 shows an example of the behavior of a feeding fish. As shown in Figure 9, the position vector x i For a fish swimming in the f The swimming force vector F6 is generated so that the fish feeds on the food. The swimming force vector F6 is expressed by the following equation using a swimming behavior weight w6, for example:

number

[0038] The behavior of the feeding fish affects their behavior until they reach the food. As a result, the amount of food intake changes, which affects the growth rate described below. The feeding calculation unit 11 may perform calculations taking this into consideration.

[0039] For example, the feeding calculation unit 11 calculates the swimming force vector F from the fish within the field of view at a time step t of the fish school behavior model. t is calculated using the above swimming force vectors F1 to F6 using the following formula:

number

number

number

number

[0040] It is known that the body length of a fish is proportional to its swimming speed. Therefore, the feeding calculation unit 11 calculates the speed vector v t+Δt Regarding the swimming speed of the fish, the maximum swimming speed v max If it exceeds the v max The maximum swimming speed |v| max (cm / s) is, for example, the body length TL (cm) and the coefficient C v is expressed by the following formula:

number

[0041] Furthermore, faster swimming speeds make it easier to ingest food, so larger individuals tend to grow faster, resulting in individual differences.

[0042] Using Figure 10, we will explain how the feeding calculation unit 11 determines whether a fish has eaten food when it is fed. Figure 10 is a diagram showing an example of how the feeding calculation unit 11 determines whether a fish has eaten food. As shown in Figure 10, when a fish with a stomach volume G of "0 J" finds food, it approaches the food. When the fish comes into contact with the food, it is determined that the fish has eaten food. If it is determined that the fish has eaten food, the food is removed and the energy of the food is stored in the fish. As shown in Figure 10, the stomach volume G of the fish has increased to "1,636 J". The cycle shown in Figure 10 (a cycle of finding food, eating, and storing energy) is repeated until the food disappears from the scene or each fish in the school of fish reaches its (preset) maximum feeding amount. When the cycle ends, the feeding calculation unit 11 passes the accumulated stomach volume G to the growth calculation unit 12 (growth model).

[0043] Returning to Figure 1, we will continue to explain each functional block.

[0044] The growth calculation unit 12 calculates growth information regarding the growth of each individual fish based on the feeding information calculated (output) by the feeding calculation unit 11. For example, the growth calculation unit 12 simulates the growth of each individual fish based on the feeding information and calculates growth information regarding the growth. The growth calculation unit 12 may store the calculated growth information in the information storage unit 10. The growth calculation unit 12 may output the calculated growth information to the feeding calculation unit 11, the profit calculation unit 13, and the output unit 14.

[0045] The growth information may be at least one of body weight, body length, or stomach volume. For example, the growth information may be body weight, body length, or stomach volume. For example, the growth information may be body weight and body length, or body weight and stomach volume, or body length and stomach volume. For example, the growth information may be body weight, body length, and stomach volume. Furthermore, each of the above combinations may include further information.

[0046] The growth calculation unit 12 may calculate the growth information using a growth model that models the growth of fish due to feeding. For examples of the growth model, see Non-Patent Documents 2 to 4 listed below. [Non-patent document 2] Martin Fore, Tim Dempster, Jo Arve Alfredsen, Vegar Johansen, David Johansson, "Modelling of Atlantic salmon (Salmo salar L.) behavior in sea-cages: A Lagrangian approach", Aquaculture 288 (2009) 196-204 [Non-patent document 3] Martin Fore, Morten Alver, Jo Arve Alfredsen, Giancarlo Marafioti, Gunnar Senneset, Jens Birkevold, Finn Victor Willumsen, Guttorm Lange, Asa Espmark, Bendik Fyhn Terjesene, "Modelling growth performance and feeding behavior of Atlantic salmon (Salmo salar L.) in commercial-size aquaculture net pens: Model details and validation through full-scale experiments", Aquaculture 464 (2016) 268-278 [Non-patent document 4] RM Nisbet, EB Muller, K. Lika and SALM Kooijman, "From molecules to ecosystems through dynamic energy budget models", Journal of Animal Ecology, Nov., 2000, Vol. 69, No. 6 (Nov., 2000), pp. 913-926

[0047] The feeding calculation unit 11 may calculate the feeding information based on the growth information calculated by the growth calculation unit 12. More specifically, in the aquaculture simulation device 1, a simulation cycle may be repeated in which, in the first cycle, the feeding calculation unit 11 calculates the feeding information based on predetermined information about the school of fish, and the growth calculation unit 12 calculates the growth information based on the calculated feeding information, and in subsequent cycles, the feeding calculation unit 11 calculates the feeding information based on the growth information calculated in the previous cycle, and the growth calculation unit 12 calculates the growth information based on the calculated feeding information, until a predetermined termination condition is met. The termination condition may be at least one of feeding reaching a predetermined number of times or fish in the school of fish reaching a predetermined growth level.

[0048] An example of the above-mentioned simulation cycle will be explained using FIGS.

[0049] FIG. 11 is a diagram showing the overall flow of an example simulation using a fish school behavior model and a growth model. As shown in FIG. 11, the feed intake calculation unit 11 (fish school behavior model) sequentially executes steps (1) to (3). First, in step (1), the behavior of each individual fish in the school of fish (each individual fish) is simulated based on the fish school behavior model. Next, in step (2), the introduction of feed (feeding) is simulated. Next, in step (3), the stomach volume G of each individual fish in the school of fish is simulated to be updated according to the feed ingested by that individual fish. Next, the growth calculation unit 12 (growth model) executes step (4). In step (4), the growth model is used to simulate the growth of each individual fish in the school of fish from the stomach volume G of that individual fish. Next, the process returns to step (1). That is, the aquaculture simulation device 1 repeats a cycle of steps (1) to (4).

[0050] 12 is a flowchart showing an example of processing executed by the aquaculture simulation device 1. First, the body length TL, stomach volume G, and body weight W of each individual fish in the school of fish are input to the feeding calculation unit 11 (fish school behavior model) (step S1). In the first cycle, the input information is set in advance in the aquaculture simulation device 1 or is input by a user of the aquaculture simulation device 1. Next, the feeding calculation unit 11 (fish school behavior model) sets the maximum swimming speed and stomach volume G for each individual fish in the school of fish based on the body length TL (step S2). Next, the feeding calculation unit 11 (fish school behavior model) calculates the amount of feed ingested by each individual fish in the school of fish during the simulation of the fish school behavior model and stores the calculated amount in the stomach volume G (step S3). Next, the feeding calculation unit 11 (fish school behavior model) ends the simulation of the fish school behavior model after a sufficient amount of time has passed or when all feed has disappeared from the scene (step S4). Next, the feeding calculation unit 11 (fish school behavior model) (or the output unit 14) outputs the stomach content volume G of each individual fish in the fish school (step S5).

[0051] Following step S5, the stomach volume G of each individual fish in the school of fish output in step S5 is input to the growth calculation unit 12 (growth model) (step S6). Next, the growth calculation unit 12 (growth model) calculates the stomach volume G, stored energy E, and volume V of each individual fish in the school of fish based on the growth model (step S7). Next, the growth calculation unit 12 (growth model) calculates the weight W and body length TL from the volume V for each individual fish in the school of fish (step S8). Next, the growth calculation unit 12 (growth model) (or the output unit 14) outputs the weight W, body length TL, and stomach volume G (remaining after digestion) for each individual fish in the school of fish (step S9).

[0052] Following step S9, the output unit 14 outputs the weight W of each individual fish in the school of fish (step S10). Next, the aquaculture simulation device 1 (or the feed intake calculation unit 11) determines whether the (pre-set) final day of the simulation has been reached (step S11). If it is determined in step S11 that the final day has not been reached (S11: No), the process returns to step S1. In that case (if this is the first or subsequent cycle), the output information in step S9 is used as the input information in step S1. On the other hand, if it is determined in step S11 that the final day has been reached (S11: Yes), the process ends.

[0053] The equations (simultaneous differential equations) that can be used in the calculation of step S7 (from food absorption to growth) are shown below.

[0054] The time change of the stomach volume G is, for example, w It is expressed by the following equation using the above formula: Note that G on the right side is the amount of energy ingested (output of step S5) calculated using the fish school behavior model.

number

[0055] The change in the amount of accumulated energy in the body E over time is expressed by, for example, the following equation:

number

[0056] The change in the volume V of a fish over time is determined by a coefficient C, which is determined by the water temperature, for example. T is expressed by the following formula:

number

[0057] Using the above three equations, G, E, and V after a certain time are calculated using the fourth-order Runge-Kutta method. For example, if feeding is done twice a day, G, E, and V after 0.5 days are calculated.

number

number

[0058] The following formula can be used in the calculation of step S8.

[0059] Weight W is expressed by the following formula, for example, by multiplying density by volume V:

number

[0060] The body length TL is expressed by the following allometric formula using, for example, coefficients a and b (a=0.0209, b=2.843 when the fish species is rainbow trout).

number

[0061] The input to the feeding calculation unit 11 (fish school behavior model) may not be the input information of step S1, but may be, for example, the body length of each individual fish in the school of fish. In this case, the feeding calculation unit 11 may calculate feeding information by utilizing the fact that swimming speed is proportional to body length (longer individuals are more likely to reach food). The output from the feeding calculation unit 11 (fish school behavior model) may not be the output information of step S5, but may be, for example, the feed intake of each individual fish in the school of fish. Similarly, the input to the growth calculation unit 12 (growth model) may not be the input information of step S6, but may be, for example, the feed intake of each individual fish in the school of fish. In this case, the growth calculation unit 12 may calculate growth information by converting the feed intake into ingested energy, subtracting the energy metabolized and excreted to calculate the amount of energy used for growth, calculating the growth rate of volume, and multiplying the volume by specific gravity to calculate body weight. The output from the growth calculation unit 12 (growth model) may not be the output information of step S9, but may be, for example, the weight and body length of each individual fish in the school of fish.

[0062] Returning to Figure 1, we will continue to explain each functional block.

[0063] The profit calculation unit 13 calculates the profit from aquaculture based on the growth information calculated in the final cycle when the termination condition is met and the feeding carried out until the termination condition is met. For example, the profit calculation unit 13 may calculate the profit from aquaculture using the following formula. (Revenue: yen) = (Weight of all animals at the time of shipping: kg) x (Unit price: yen / kg) (Cost: yen) = (Initial purchase price of fish: yen) + (amount of feed used: kg) x (unit price of feed: kg / yen) (Profit: yen) = (Revenue: yen) - (Cost: yen)

[0064] The output unit 14 outputs the feeding information calculated by the feeding calculation unit 11. The output unit 14 may further output the growth information calculated by the growth calculation unit 12. The output unit 14 may further output the profit calculated by the profit calculation unit 13. The output unit 14 may output various information to a user of the aquaculture simulation device 1 via the input / output device 103, or may transmit it to another computer device via a network.

[0065] 13 to 27 show examples of simulation results using the aquaculture simulation device 1. Note that all simulations were performed using the following initial settings: "Fish species: Rainbow trout (Oncorhynchus mykiss)", "Initial body weight: 38.4 g", and "Number of simulation days: 90 days". However, these settings can be freely set by the user.

[0066] Figure 13 shows the results of Simulation 1-1, in which 100 individuals were reared. Simulation conditions other than "number of individuals reared: 100" were as follows: "aquarium shape: circular, 3.0 m diameter," "feeding amount: 1.0% of body weight," "feeding area: 1.0 m square," and "feeding frequency: twice a day." The upper graphs in Figure 13 (and Figures 14 to 27) are graphs showing the growth history over the rearing period, showing the change in weight of individual fish over the number of days that have passed. The lower graphs in Figure 13 (and Figures 14 to 27) are graphs showing the weight distribution at 90 days, showing the frequency of each weight for individual fish.

[0067] Fig. 14 shows the results of Simulation 1-2, where the number of individuals reared was 200. The simulation conditions other than "number of individuals reared: 200" were the same as those in Fig. 13.

[0068] Figure 15 shows the results of Simulation 2-1, in which the tank shape was a circle with a diameter of 3.0 m. The simulation conditions other than "tank shape: circle with a diameter of 3.0 m" were as follows: "number of individuals kept: 100 individuals," "feeding amount: 1.0% of body weight," "feeding area: 1.0 m square," and "feeding frequency: twice a day."

[0069] 16 shows the results of Simulation 2-2, where the tank shape was a rectangular shape with a side length of 3.0 m. The simulation conditions other than the "tank shape: rectangular shape with a side length of 3.0 m" were the same as those in FIG.

[0070] Figure 17 shows the results of Simulation 2-3, where the tank shape was a circle with a diameter of 6.0 m. The simulation conditions other than "tank shape: circle with a diameter of 6.0 m" were the same as those in Figure 15.

[0071] Figure 18 shows the results of Simulation 3-1, in which the feeding amount was 0.5% of body weight. The simulation conditions other than "feeding amount: 0.5% of body weight" were as follows: "number of individuals kept: 100 individuals," "aquarium shape: circular, 3.0 m diameter," "feeding area: 1.0 m square," and "feeding frequency: twice a day."

[0072] 19 shows the results of Simulation 3-2, where the feeding amount was set to 1.0% of body weight. The simulation conditions other than "feeding amount: 1.0% of body weight" are the same as those in FIG.

[0073] 20 shows the results of Simulation 3-3, where the feeding amount was set to 2.0% of body weight. The simulation conditions other than "feeding amount: 2.0% of body weight" are the same as those in FIG.

[0074] Figure 21 shows the results of Simulation 4-1, where the feeding area was 0.5m square. The simulation conditions other than "feeding area: 0.5m square" were as follows: "number of individuals kept: 100 individuals," "aquarium shape: circular with a diameter of 3.0m," "feeding amount: 1.0% of body weight," and "feeding frequency: twice a day."

[0075] 22 shows the results of Simulation 4-2, where the feeding area was 1.0 m square. The simulation conditions other than "feeding area: 1.0 m square" were the same as those in FIG.

[0076] Figure 23 shows the results of Simulation 4-3, where the feeding area was 1.5m square. The simulation conditions other than "feeding area: 1.5m square" were the same as those in Figure 21.

[0077] Figure 24 shows the results of Simulation 5-1, in which the feeding frequency was once per day. The simulation conditions other than "feeding frequency: once per day" were as follows: "number of individuals kept: 100 individuals," "aquarium shape: circular, diameter 3.0 m," "feeding amount: 1.0% of body weight," and "feeding area: 1.0 m square."

[0078] Figure 25 shows the results of Simulation 5-2, where the feeding frequency was set to twice a day. The simulation conditions other than "feeding frequency: twice a day" were the same as those in Figure 24.

[0079] Figure 26 shows the results of Simulation 5-3, where the feeding frequency was set to 4 times / day. The simulation conditions other than "feeding frequency: 4 times / day" were the same as those in Figure 24.

[0080] Fig. 27 is a table showing a list of the simulation results, which shows the simulation conditions, average weights, and standard deviations for each of the above-mentioned simulations 1-1, 1-2, 2-2, 2-3, 3-1, 3-3, 4-1, 4-3, 5-1, and 5-3.

[0081] Figures 28 and 29 are used to compare the growth rates of fish schools.

[0082] FIG. 28 is a diagram showing an example of a simulation on the first day using the aquaculture simulation device 1. FIG. 29 is a diagram showing an example of a simulation on the 90th day using the aquaculture simulation device 1. More specifically, FIG. 28 shows the size and position of the fish in the pen on the first day of the simulation (schematic view on the left, plan view on the right). Similarly, FIG. 29 shows the size and position of the fish in the pen on the 90th day of the simulation (schematic view on the left, plan view on the right). It can be seen that the fish in FIG. 29 have grown compared to FIG. 28, and that their swimming ability has also increased accordingly.

[0083] The feeding ranges are compared using Figures 30 to 34.

[0084] Figure 30 shows an example of the feeding range. As shown in Figure 30, the feeding range for Feeding A is 1.5m square within the fish preserve, the feeding range for Feeding B is 1.0m square within the fish preserve, and the feeding range for Feeding C is 0.5m square within the fish preserve.

[0085] Figure 31 shows the change in body weight due to feeding A. Figure 32 shows the change in body weight due to feeding C. The graphs shown in Figures 31 and 32 show the change in body weight of an individual fish over the number of days that have passed. The graphs shown in Figures 31 and 32 show the difference in growth depending on the feeding range. It can also be seen that the average body weight was almost the same for the two feeding methods, and that the variation in body weight was greater for feeding C.

[0086] Figure 33 shows the weight frequency for feeding A. Figure 34 shows the weight frequency for feeding C. The graphs shown in Figures 33 and 34 show the weight distribution at 90 days, and show the frequency of each weight for each individual fish. The graphs shown in Figures 33 and 34 show the difference in growth depending on the feeding range. It can also be seen that there is little variation in feeding A, while there are several individuals with extremely fast growth in feeding C.

[0087] 35 is a flowchart showing another example of the process (aquaculture simulation method) executed by the aquaculture simulation device 1. First, the feeding calculation unit 11 calculates feeding information related to the feeding of each individual fish in the school of fish due to feeding (step S20, feeding calculation step). Next, the output unit 14 outputs the feeding information calculated by the feeding calculation unit 11 (step S21, output step).

[0088] Next, the effects of the aquaculture simulation device 1 will be described.

[0089] The aquaculture simulation device 1 that performs a simulation of aquaculture of a school of fish includes a feeding calculation unit 11 that calculates feeding information related to feeding of each individual fish in the school of fish due to feeding, and an output unit 14 that outputs the feeding information calculated by the feeding calculation unit 11. In this aquaculture simulation device 1, in the simulation of aquaculture of a school of fish, the feeding information related to feeding of each individual fish in the school of fish due to feeding is calculated and output. This makes it possible to perform a simulation of feeding in aquaculture.

[0090] In the aquaculture simulation device 1, aquaculture may be carried out in a fish pen. This makes it possible to perform a simulation of aquaculture of schools of fish in a fish pen.

[0091] The feeding information may be at least one of the amount of food intake, the stomach volume after feeding, or the energy intake through feeding, which makes it possible to calculate at least one of the amount of food intake, the stomach volume after feeding, or the energy intake through feeding for each individual fish in the school of fish after feeding.

[0092] In the aquaculture simulation device 1, the feeding calculation unit 11 may calculate the feeding information based on at least one of fish information about a school of fish, net cage information about a net cage where aquaculture is performed, or feeding information about feeding. This makes it possible to simulate the calculation of feeding information under conditions closer to reality based on at least one of fish information, net cage information, and feeding information.

[0093] The fish information may be at least one of the number of fish in the school, the species of the fish, the weight of the fish, the body length of the fish, the stomach volume of the fish, the swimming ability of the fish, or the swimming speed of the fish, which allows for a simulation of the calculation of feeding information under conditions closer to reality.

[0094] The net cage information may be at least one of the size of the net cage, the shape of the net cage, and the water temperature of the net cage, which allows a simulation to be performed to calculate the feeding information under conditions that are closer to reality.

[0095] The feeding information may be at least one of the amount of feeding, the range of feeding, and the frequency of feeding, which allows the calculation of the feeding information to be simulated under conditions closer to reality.

[0096] In the aquaculture simulation device 1, the feeding calculation unit 11 may calculate the feeding information using a fish school behavior model that models the behavior of a school of fish. This makes it possible to calculate more accurate feeding information based on the behavior of a school of fish.

[0097] The fish school behavior model may include a model relating to the behavior of fish moving towards bait, which allows for more accurate calculation of feeding information based on the behavior of fish moving towards bait.

[0098] The fish school behavior model may include at least one of a model relating to the behavior of fish moving away from obstacles and a model relating to the random behavior of fish, thereby enabling more accurate calculation of feeding information based on the behavior of fish moving away from obstacles or the random behavior of fish.

[0099] The aquaculture simulation device 1 further includes a growth calculation unit 12 that calculates growth information regarding the growth of each individual fish based on the feeding information calculated by the feeding calculation unit 11, and the output unit 14 may further output the growth information calculated by the growth calculation unit 12. This makes it possible to output growth information regarding the growth of each individual fish, thereby enabling a simulation of growth in aquaculture.

[0100] The growth information may be at least one of body weight, body length, and stomach volume, which allows for calculation of at least one of body weight, body length, and stomach volume for each individual fish.

[0101] In the aquaculture simulation device 1, the growth calculation unit 12 may calculate growth information using a growth model that models the growth of fish due to feeding. This makes it possible to calculate more accurate growth information based on the growth of fish due to feeding.

[0102] In the aquaculture simulation device 1, the feeding calculation unit 11 may calculate the feeding information based on the growth information calculated by the growth calculation unit 12. This allows the feeding calculation unit 11 to perform calculations based on the calculation results of the growth calculation unit 12, and the growth calculation unit 12 to perform calculations based on the calculation results of the feeding calculation unit 11, making it possible to perform a continuous simulation in accordance with the growth of the fish.

[0103] In the aquaculture simulation device 1, the simulation cycle may be repeated until a predetermined termination condition is met, in which in the first cycle, the feeding calculation unit 11 calculates feeding information based on predetermined information about the school of fish, and the growth calculation unit 12 calculates growth information based on the calculated feeding information, and in subsequent cycles, the feeding calculation unit 11 calculates feeding information based on the growth information calculated in the previous cycle, and the growth calculation unit 12 calculates growth information based on the calculated feeding information. This allows for continuous simulation cycles that follow the growth of the fish.

[0104] The termination condition may be at least one of a predetermined number of feedings or a predetermined growth of the fish in the school of fish. This allows the simulation cycle to be repeated until at least one of the predetermined number of feedings or the predetermined growth of the fish in the school of fish is satisfied, thereby improving user convenience.

[0105] The aquaculture simulation device 1 may further include a profit calculation unit 13 that calculates the profit of aquaculture based on the growth information calculated in the final cycle when the termination condition is met and the feeding carried out until the termination condition is met, and the output unit 14 may further output the profit calculated by the profit calculation unit 13. This makes it easy to understand the profit obtained from aquaculture of schools of fish. Also, for example, by performing simulations under various different conditions and comparing the profits calculated for each, aquaculture can be stabilized, made more efficient, and optimized.

[0106] Here, we explain the background and prior art. Feed is the largest cost factor in aquaculture. Research has shown that the overall cost structure for aquaculture is as follows: feed: 58.0%, seed: 15.5%, labor: 14.4%, fixed costs: 5.8%, chemicals: 1.3%, and others: 5.0%. In other words, approximately 60% of costs are due to feed. Given this background, automatic feeding systems and behavioral recognition systems using ICT and AI are currently being developed to improve feeding efficiency. These ICT technologies are effective for understanding the current situation and setting daily feed amounts. However, for long-term optimization of land-based aquaculture facilities, understanding the current situation alone is insufficient; it is necessary to evaluate the impact of daily feed amounts on the ultimate growth of the reared fish. However, currently, daily rearing operations are largely dependent on the experience of the rearers. Based on these findings, in order to streamline and optimize feed amounts while taking into account the profitability of land-based aquaculture facilities, a tool to support rearers' decision-making regarding daily rearing operations is needed.

[0107] The aquaculture simulation device 1 according to this embodiment is based on a feeding simulation that can reproduce the process by which fish feed on a computer device. This feeding simulation uses a fish school behavior model to simulate the swimming behavior of fish in an aquarium. Furthermore, by incorporating feeding behavior, the amount of feed consumed by each individual fish can be estimated. In addition, the aquaculture simulation device 1 can calculate the growth rate of the fish by physiologically considering digestion, catabolism, and metabolism from the simulated feed intake using an ecophysiological model. This allows for advance consideration of how daily feeding will ultimately contribute to the growth of the fish.

[0108] By using the aquaculture simulation device 1, it is possible to set the optimal daily feeding amount from a long-term perspective, as well as predict when the fish will reach shipping size. In addition, it is thought that it can be used to consider tank size and the resulting profitability in advance when designing aquaculture facilities. As a result, it can serve as a decision-making support tool for breeding operations and facility design, and contribute to the stabilization and efficiency of aquaculture facility management. The aquaculture simulation device 1 is decision-making software for aquaculture facility design and operation based on feeding simulations. The aquaculture simulation device 1 can clarify the most efficient feeding method (a feeding method that results in high growth with a small amount of feed).

[0109] The aquaculture simulation device 1 can clarify the optimal feeding amount from a management perspective through simulation. Furthermore, the aquaculture simulation device 1 can visualize the optimal feeding amount from a management perspective, and optimize the tank size and feeding method. The aquaculture simulation device 1 can monitor outliers (management risks).

[0110] By using the aquaculture simulation device 1, it is possible to study the breeding conditions in advance on a computer. It is also possible to propose the amount of feed that will maximize profits. It is also possible to design hardware such as aquaculture tanks based on scientific evidence. As a result, it is possible to improve the efficiency of management, reduce variations and stabilize shipping volume, and even those with no experience in breeding can perform optimal operations.

[0111] The aquaculture simulation device 1 can simulate the rearing environment, allowing for a preliminary study of how the growth rate will differ for each setting item before rearing. For example, it is possible to consider in advance what amount or method of feeding will improve growth, how to rear fish to reduce variation in growth rate, what size of aquarium is appropriate, and what number of fish should be reared.

[0112] Examples of configurable items of the aquaculture simulation device 1 include the following: number of individuals being reared (initial setting for the entire simulation), tank shape (size, circular / square) (processed when the tank wall is within the field of view of each individual while the fish behavior model is running), feeding amount (referenced in the feeding timing of the fish school behavior model), feeding range (referenced in the feeding timing of the fish school behavior model), feeding frequency (how many times per day) (referenced in the feeding timing of the fish school behavior model), fish species (initial setting for the fish school behavior model and growth model), fish body length, fish weight, fish swimming speed, fish feeding behavior, water temperature in the fish pen, and water current in the fish pen. Examples of output from the aquaculture simulation device 1 include the following: daily weight and growth amount of each individual, and final (shipping) weight of each individual (weight after the set number of simulation days has passed).

[0113] By using the aquaculture simulation device 1, various breeding conditions can be studied in advance on a computer. For example, average weight and variations can be studied in advance. This makes it possible to suppress variations and stabilize shipping volume, estimate the time when the fish will be ready for shipping, and contribute to the stabilization of management. The aquaculture simulation device 1 can also be used to design hardware such as aquaculture tanks. As described above, the aquaculture simulation device 1 can propose feeding amounts that maximize profits, improve management efficiency, and enable optimal operation even by those with no experience in aquaculture. [Explanation of symbols]

[0114] 1...aquaculture simulation device, 10...information storage unit, 11...feeding calculation unit, 12...growth calculation unit, 13...profit calculation unit, 14...output unit, 100...CPU, 101...RAM, 102...ROM, 103...input / output device, 104...communication module, 105...auxiliary storage device, 200...storage medium, 201...program storage area, 300...aquaculture simulation program, 301...feeding calculation module, 302...growth calculation module, 303...profit calculation module, 304...output module.

Claims

1. An aquaculture simulation device for simulating aquaculture of schools of fish, a feeding calculation unit that calculates feeding information regarding feeding of each individual fish in the school of fish; a growth calculation unit that calculates growth information regarding the growth of each individual fish based on the feeding information calculated by the feeding calculation unit; an output unit that outputs the feeding information calculated by the feeding calculation unit and the growth information calculated by the growth calculation unit; Equipped with A simulation cycle, In a first cycle, the feeding calculation unit calculates the feeding information based on predetermined information about the school of fish, and the growth calculation unit calculates the growth information based on the calculated feeding information; In the first and subsequent cycles, the feeding calculation unit calculates the feeding information based on the growth information calculated in the previous cycle, and the growth calculation unit calculates the growth information based on the calculated feeding information. The cycle is repeated until a predetermined termination condition is met. Aquaculture simulation device.

2. The aquaculture is carried out in a fish cage. The aquaculture simulation device according to claim 1 .

3. The feeding information is at least one of the amount of feeding, the stomach volume after feeding, or the energy ingested by feeding. The aquaculture simulation device according to claim 1 or 2.

4. The feeding calculation unit calculates the feeding information based on at least one of fish information about the school of fish, net cage information about the net cage where the aquaculture is performed, or feeding information about the feeding. The aquaculture simulation device according to any one of claims 1 to 3.

5. The fish information is at least one of the number of fish in the school of fish, the species of the fish, the weight of the fish, the body length of the fish, the stomach volume of the fish, the swimming ability of the fish, or the swimming speed of the fish. The aquaculture simulation device according to claim 4.

6. The fish cage information is at least one of the size of the fish cage, the shape of the fish cage, or the water temperature of the fish cage. The aquaculture simulation device according to claim 4 or 5.

7. The feeding information is at least one of the amount of feeding, the range of feeding, or the frequency of feeding. The aquaculture simulation device according to any one of claims 4 to 6.

8. the feeding calculation unit calculates the feeding information using a fish school behavior model that models the behavior of the fish school; The aquaculture simulation device according to any one of claims 1 to 7.

9. The fish school behavior model includes a model relating to the behavior of fish moving toward bait. The aquaculture simulation device according to claim 8.

10. The fish school behavior model includes at least one of a model relating to the behavior of fish moving away from an obstacle or a model relating to the random behavior of fish. The aquaculture simulation device according to claim 8 or 9.

11. The growth information is at least one of body weight, body length, or stomach volume. The aquaculture simulation device according to any one of claims 1 to 10.

12. the growth calculation unit calculates the growth information using a growth model that models the growth of fish due to feeding; The aquaculture simulation device according to any one of claims 1 to 11.

13. the feeding calculation unit calculates the feeding information based on the growth information calculated by the growth calculation unit. The aquaculture simulation device according to any one of claims 1 to 12.

14. The termination condition is at least one of the feeding reaching a predetermined number of times or the fish in the school of fish reaching a predetermined growth level. The aquaculture simulation device according to any one of claims 1 to 13.

15. The method further includes a profit calculation unit that calculates the profit of the aquaculture based on the growth information calculated in the final cycle when the termination condition is satisfied and the feeding performed until the termination condition is satisfied, The output unit further outputs the profit calculated by the profit calculation unit. The aquaculture simulation device according to any one of claims 1 to 14.

16. An aquaculture simulation method executed by an aquaculture simulation device that performs a simulation on aquaculture of a school of fish, comprising: a feeding calculation step of calculating feeding information regarding feeding of each individual fish in the school of fish by feeding; a growth calculation step of calculating growth information regarding the growth of each individual fish based on the feeding information calculated in the feeding calculation step; an output step of outputting the feeding information calculated in the feeding calculation step and the growth information calculated in the growth calculation step; Including, A simulation cycle, In a first cycle, the feeding calculation step calculates the feeding information based on predetermined information about the school of fish, and the growth calculation step calculates the growth information based on the calculated feeding information; In the first and subsequent cycles, the feeding calculation step calculates the feeding information based on the growth information calculated in the previous cycle, and the growth calculation step calculates the growth information based on the calculated feeding information. The cycle is repeated until a predetermined termination condition is met. Aquaculture simulation method.

17. An aquaculture simulation program for performing a simulation regarding aquaculture of a school of fish, comprising: a feeding calculation unit that calculates feeding information regarding feeding of each individual fish in the school of fish; a growth calculation unit that calculates growth information regarding the growth of each individual fish based on the feeding information calculated by the feeding calculation unit; an output unit that outputs the feeding information calculated by the feeding calculation unit and the growth information calculated by the growth calculation unit; It functions as A simulation cycle, In a first cycle, the feeding calculation unit calculates the feeding information based on predetermined information about the school of fish, and the growth calculation unit calculates the growth information based on the calculated feeding information; In the first and subsequent cycles, the feeding calculation unit calculates the feeding information based on the growth information calculated in the previous cycle, and the growth calculation unit calculates the growth information based on the calculated feeding information. The cycle is repeated until a predetermined termination condition is met. Aquaculture simulation program.

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