JP7573291B2 - Processing timing estimation method and processing timing estimation program - Google Patents

Description

The present invention relates to a processing timing estimation method and a processing timing estimation program.

When planting forced and semi-forced strawberries that are shipped between November and May, the timing of planting is determined after confirming that flower buds have differentiated, so it is necessary to confirm or estimate whether flower bud differentiation is progressing as planned during the seedling preparation stage. In addition, night cooling treatment and day length adjustment may be carried out as treatments to promote flower bud differentiation. Treatments such as night cooling treatment and day length adjustment need to be carried out when the time for flower bud differentiation is reached, but if there is a delay in confirming that the time for flower bud differentiation has arrived, planting cannot be carried out at the appropriate time, flowering will be delayed, and ultimately harvesting will be delayed, which may lead to reduced profits.

Methods known to confirm or estimate flower bud differentiation in strawberries include investigating the nitrogen content of plants by destroying several plants in each field, and confirming flower bud formation using a microscope.

JP 2008-142005 A JP 2013-034438 A JP 2017-163956 A JP 2019-024416 A JP 2019-219704 A JP 2016-208877 A JP 2007-171033 A JP 2020-156431 A

However, the method of investigating nitrogen content has a large margin of error, making it difficult to accurately estimate the time when flower buds can differentiate. Furthermore, the method of checking flower bud formation with a microscope can only confirm that flower bud differentiation has already begun, which may delay preparations for planting, delay the planting process, and cause other problems in cultivation.

The present invention aims to provide a treatment timing estimation method and a treatment timing estimation program that can output information on the timing to perform treatment to promote flower bud differentiation of strawberry seedlings.

The processing timing estimation method of the present invention is a processing timing estimation method that is executed by a computer, which includes a first process of acquiring the dry matter weight of a strawberry seedling at the start of seedling cultivation or estimating the dry matter weight of the seedling at the start of seedling cultivation based on data on the average daily temperature from the day of sowing, a second process of calculating the leaf area index of the seedling on the nth day (n is a natural number) from the dry matter weight of the seedling on the nth day from the start of seedling cultivation, calculating the daily light reception amount on the nth day based on the calculated leaf area index and data on the daily accumulated solar radiation on the nth day, calculating the daily dry matter production amount on the nth day based on the calculated daily light reception amount, and adding the daily dry matter production amount on the nth day to the dry matter weight of the seedling on the nth day to calculate the dry matter weight of the seedling on the (n+1)th day, repeating the process while increasing the value of n, and a third process of determining the day on which the calculation result of the dry matter weight of the seedling exceeds a predetermined threshold as the timing to perform processing to promote flower bud differentiation of the seedling, and outputting the result.

The treatment timing estimation method and treatment timing estimation program of the present invention have the effect of outputting information on the timing to perform treatment to promote flower bud differentiation of strawberry seedlings.

1 is a diagram showing a configuration of an agricultural system according to a first embodiment. FIG. 2A is a diagram showing the hardware configuration of the server in FIG. 1, and FIG. 2B is a diagram showing the hardware configuration of the user terminal in FIG. FIG. 2 is a functional block diagram of a server. 1 is a graph showing the relationship between the number of days since seedling raising and the dry weight of strawberry seedlings, and a threshold value. 5 is a flowchart showing a process of a server according to the first embodiment. 10 is a flowchart showing a process of a server according to a modified example of the first embodiment. FIG. 7( a ) is a diagram showing an example of an image of a seedling, and FIG. 7( b ) is a diagram showing an example of a binarized image generated from FIG. 7( a ). 10 is a flowchart showing a process of a server according to the second embodiment; 13 is a flowchart showing a process of a server according to a modified example of the second embodiment.

First Embodiment
A first embodiment of the agricultural system will be described in detail below with reference to Figures 1 to 5. Figure 1 shows a schematic configuration of an agricultural system 100 according to the first embodiment. The agricultural system 100 of this embodiment is a system for providing farmers, agricultural corporations, etc. that grow strawberries (hereinafter referred to as "users") with information indicating that the strawberry seedlings they are cultivating have reached the stage at which flower buds can be differentiated (the timing for performing treatment to promote flower bud differentiation) and when flower buds will be able to be differentiated.

As shown in FIG. 1, the agricultural system 100 includes a server 10 and a user terminal 70. The user terminal 70 is a terminal such as a personal computer (PC) used by a user. The server 10 and the user terminal 70 are connected to a network 80 such as the Internet, enabling information to be exchanged between the devices.

The server 10 is an information processing device that provides users with information on the time when strawberry seedlings can differentiate into flower buds (the timing for performing processing to promote flower bud differentiation). The server 10 acquires information on the sowing date, data on the dry weight of the seedlings at the start of seedling cultivation, and strawberry cultivation environment data (daily average temperature and daily accumulated solar radiation) from the user terminal 70, and estimates the time when flower buds can differentiate (the timing for performing processing to promote flower bud differentiation) based on the acquired information, and outputs the estimate to the user terminal 70.

2(a) shows a schematic diagram of the hardware configuration of the server 10. As shown in FIG. 2(a), the server 10 includes a CPU 90, a ROM 92, a RAM 94, a storage unit (e.g., HDD, SSD, etc.) 96, a network interface 97, and a portable storage medium drive 99. These components of the server 10 are connected to a bus 98. In the server 10, the CPU 90 executes a program (including a processing timing estimation program) stored in the ROM 92 or the storage unit 96, or a program (including a processing timing estimation program) read from the portable storage medium 91 by the portable storage medium drive 99, thereby realizing the functions of the components shown in FIG. 3. The functions of the components shown in FIG. 3 may be realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

Figure 3 shows a functional block diagram of the server 10. In the server 10, the CPU 90 executes a program to realize the functions of a dry matter weight determination unit 30, a leaf area index calculation unit 32, a daily light reception calculation unit 34, a daily dry matter production calculation unit 36, a flower bud differentiation possible time determination unit 38, and an output unit 40, as shown in Figure 3. Note that the server 10 acquires post-sowing environmental data (data on daily average temperature and daily accumulated solar radiation) from the user terminal 70. Here, the server 10 may use future environmental data when estimating the flower bud differentiation possible time. For example, when the seedlings are grown in an environment where the environmental data is fixed, such as in a closed seedling cultivation system, the server 10 may use the fixed value as the future environmental data. Also, when the seedlings are grown in an environment that is affected by the weather, such as a rain shelter, the server 10 may use the average value as the future environmental data.

The dry matter weight specification unit 30 specifies the dry matter weight (initial value) of the seedling at the start of seedling cultivation. Specifically, when information on the dry matter weight of the seedling at the start of seedling cultivation is input from the user terminal 70, the input dry matter weight information is set as the initial value. Also, when the user inputs information on the sowing date (year, month, and day), the growth from sowing to leaf unfolding is calculated from data on the average daily temperature, the dry matter weight at the start of seedling cultivation is estimated, and the estimated dry matter weight is set as the initial value.
The leaf area index calculation unit 32 calculates the leaf area index of the seedling on the nth day (n is a natural number) from the dry weight on the nth day from the start of seedling cultivation. When the nth day is equal to the 1st day, this means the start of seedling cultivation, so the leaf area index of the seedling on the 1st day is calculated using the initial value of the dry weight specified by the dry weight specification unit 30. The leaf area index can be calculated from the following formula (1) using the values of the specific leaf area and planting density.
Leaf area index = dry weight of seedling x specific leaf area x planting density...(1)

The daily light receiving amount calculation unit 34 calculates the daily light receiving amount on the nth day based on the leaf area index on the nth day calculated by the leaf area index calculation unit 32 and the data on the daily accumulated solar radiation on the nth day. Specifically, when the daily accumulated solar radiation is I, the light absorption coefficient is k, and the LAI is the leaf area index, the daily light receiving amount on the nth day can be calculated by the following formula (2).
Amount of sunlight received = I x 0.5 x (1-e ^-k・LAI )...(2)

The daily dry matter production calculation unit 36 calculates the daily dry matter production on the nth day based on the daily light reception amount on the nth day calculated by the daily light reception calculation unit 34. Specifically, the daily dry matter production can be calculated from the following formula (3).
Daily dry matter production = daily light reception x light utilization efficiency … (3)

The dry matter weight determination unit 30 can determine the "dry matter weight on the (n+1)th day" by adding the daily dry matter production on the nth day calculated by the daily dry matter production calculation unit 36 to the sum of the initial dry matter weight and the total daily dry matter production obtained up to the (n-1)th day (the dry matter weight on the nth day (the dry matter weight at midnight on the nth day)).

The flower bud differentiation possible time determination unit 38 determines whether the (n+1)th day is the time when flower bud differentiation is possible by determining whether the dry matter weight on the (n+1)th day specified by the dry matter weight determination unit 30 exceeds a predetermined threshold. The flower bud differentiation possible time means the timing at which a process to promote flower bud differentiation should be performed. The threshold value is set for each variety. For example, assume that as a result of an experiment, seedling results such as those shown in Figure 4 were obtained for a certain variety. The graph in Figure 4 plots the seedling results of a certain variety, with the horizontal axis representing the number of days of seedling growth and the vertical axis representing the dry matter weight of strawberry seedlings, and indicates cases where the flower buds are undifferentiated with △ and cases where they have differentiated with ◯. In the example of Figure 4, 4.0 can be used as the threshold for determining the time when flower bud differentiation is possible.

The output unit 40 outputs information to the user terminal 70 based on the judgment result of the flower bud differentiation possible time judgment unit 38. For example, the flower bud differentiation possible time judgment unit 38 outputs information to the user terminal 70 that the flower bud differentiation possible time (the time when processing to promote flower bud differentiation should be performed) will be on the (n+1)th day. The user terminal 70 provides the information received from the flower bud differentiation possible time judgment unit 38 to the user by, for example, displaying it.

Returning to FIG. 1, the user terminal 70 is a terminal that transmits information on strawberry seedlings and cultivation environment data to the server 10 and displays the estimation results of the server 10. The user terminal 70 has a hardware configuration as shown in FIG. 2(b). As shown in FIG. 2(b), the user terminal 70 includes a CPU 190, a ROM 192, a RAM 194, a storage unit 196, a network interface 197, a display unit 193, an input unit 195, and a portable storage medium drive 199 capable of reading data stored in the portable storage medium 191. These components of the user terminal 70 are connected to a bus 198. The display unit 193 includes a liquid crystal display, and the input unit 195 includes a keyboard, mouse, touch panel, and the like. The user inputs information on the sowing date and the dry weight of the seedlings at the start of seedling cultivation into the user terminal 70 from the user. In addition, strawberry cultivation environment data (daily average temperature and daily accumulated solar radiation) is input to the user terminal 70 from a sensor installed in the environment where the strawberry seedlings are cultivated. The strawberry cultivation environment data may be manually input by the user to the user terminal 70.

When a user inputs a request to check when strawberry seedlings can differentiate into flower buds (the timing to perform processing to promote flower bud differentiation), the user terminal 70 transmits the information input by the user and cultivation environment data to the server 10.

(Regarding the processing of the server 10)
Next, the process of the server 10 will be described in detail with reference to the flowchart of Fig. 5 and other drawings as appropriate. The process of Fig. 5 is started when a user inputs a request to confirm the flower bud differentiation time of strawberry seedlings (the timing to perform the process to promote flower bud differentiation) into a user terminal 70 and the information input by the user and the cultivation environment data are transmitted from the user terminal 70 to the server 10.

When the processing of FIG. 5 is started, first in step S10, the dry matter weight determination unit 30 estimates or acquires the initial value of the seedling's dry matter weight (dry matter weight on the first day). For example, when sowing date information is input from the user terminal 70, the growth from sowing to leaf unfolding is calculated from the data on the average daily temperature, and the dry matter weight at the start of seedling cultivation is estimated and set as the initial value. Also, for example, when the dry matter weight of the seedling at the start of seedling cultivation is input from the user terminal 70, that value is set as the initial value of the dry matter weight.

Next, in step S12, the leaf area index calculation unit 32 sets the parameter n, which indicates the number of days since the start of seedling cultivation, to 1 (n = 1).

Next, in step S14, the leaf area index calculation unit 32 calculates the leaf area index on the nth day (first day) from the dry weight. In this case, the leaf area index calculation unit 32 calculates the leaf area index on the nth day (first day) from the above formula (1) using the dry weight of the seedling on the nth day (first day).

Next, in step S16, the daily light reception calculation unit 34 acquires or estimates the daily accumulated solar radiation on the nth day. If data on the daily accumulated solar radiation on the nth day has been input from the user terminal 70, the daily light reception calculation unit 34 acquires that data. Also, if the nth day is a future day, the daily light reception calculation unit 34 estimates a fixed value (in the case of a closed seedling cultivation system, etc.) or an average value (in the case of a rain shelter, etc.) as the daily accumulated solar radiation on the nth day, as described above.

Next, in step S18, the daily light reception calculation unit 34 calculates the daily light reception amount on the nth day. In this case, the daily light reception calculation unit 34 uses the leaf area index calculated in step S14 and the daily accumulated solar radiation acquired or estimated in step S16 to calculate the daily light reception amount on the nth day based on the above formula (2).

Next, in step S20, the daily dry matter production calculation unit 36 calculates the daily dry matter production on the nth day. In this case, the daily light reception calculation unit 34 calculates the daily dry matter production on the nth day based on the above formula (3) using the daily light reception calculated in step S18.

In step S22, the dry matter weight determination unit 30 estimates the dry matter weight of the seedlings on the (n+1)th day. For example, if the daily dry matter production amount on the first day is calculated in step S20, the dry matter weight determination unit 30 estimates the sum of the initial dry matter weight and the daily dry matter production amount on the first day as the dry matter weight on the second day (dry matter weight at midnight on the second day). In addition, if the daily dry matter production amount on the 10th day is calculated in step S20, the sum of the dry matter weight on the 10th day and the daily dry matter production amount on the 10th day is set as the daily dry matter production amount on the 11th day (dry matter weight at midnight on the 11th day).

Next, in step S24, the flower bud differentiation possible time determination unit 38 determines whether the dry matter weight of the seedling on the (n+1)th day exceeds a threshold value. If the determination in step S24 is negative, the process proceeds to step S26, where the leaf area index calculation unit 32 increments n by 1 (n=n+1). After that, the process returns to step S14, and the processes and determinations in steps S14 to S26 are repeated until the determination in step S24 is positive.

On the other hand, if the determination in step S24 is positive, the process proceeds to step S28. When the process proceeds to step S28, the output unit 40 outputs that the (n+1)th day is the time when flower bud differentiation is possible (the time when processing to promote flower bud differentiation should be performed). For example, if the (n+1)th day is a future day, the output unit 40 displays a message such as "The time when flower bud differentiation is possible will be on XX month XX day, so please prepare for processing to promote flower bud differentiation (night cooling, day length adjustment, etc.)" on the display unit 193 of the user terminal 70. By checking the message, the user can perform the appropriate work (night cooling, day length adjustment, transplant preparation, etc.) at the appropriate time.

In the first embodiment, the process of step S10 corresponds to the first process, the processes of steps S14 to S26 correspond to the second process, and the process of step S28 corresponds to the third process.

As described above in detail, according to the first embodiment, the dry matter weight determination unit 30 obtains the dry matter weight of the seedlings at the start of strawberry seedling cultivation, or estimates the dry matter weight of the seedlings at the start of seedling cultivation based on the data of the average daily temperature from the sowing date, and sets it as the initial value of the dry matter weight (S10). In addition, the leaf area index calculation unit 32 calculates the leaf area index of the seedlings on the nth day (S14), the daily light reception calculation unit 34 calculates the daily light reception on the nth day (S18), the daily dry matter production calculation unit 36 calculates the daily dry matter production on the nth day (S20), and the dry matter weight determination unit 30 calculates the dry matter weight of the seedlings on the (n+1)th day (S22). These processes are repeated while increasing the value of n. Then, when the calculation result of the dry matter weight of the seedlings on the (n+1)th day exceeds the threshold value (S24: Yes), the flower bud differentiation possible time determination unit 38 determines that flower bud differentiation of the seedlings is possible, and the output unit 40 outputs that fact (S28). As a result, in this first embodiment, the time when flower bud differentiation is possible (the timing at which treatment to promote flower bud differentiation should be performed) can be estimated without conducting a destructive nitrogen content survey of the plant body or checking flower bud formation with a microscope, which requires skill. Therefore, the timing at which treatment to promote flower bud differentiation should be performed can be estimated with higher accuracy than with a nitrogen content survey. Also, unlike a microscope, the timing at which treatment to promote flower bud differentiation should be performed can be estimated in advance, allowing preparations for planting to be made at an early stage. This can prevent delays in flowering, and therefore delays in harvesting.

In addition, since the time when flower buds can differentiate can be estimated with high accuracy, by using this information on the time when flower buds can differentiate, it becomes possible to accurately predict the flowering date and harvest date.

(Modification of the first embodiment)
Next, a modified example of the first embodiment will be described. Fig. 6 shows a flow chart of the processing contents of the server 10 in the modified example of the first embodiment. In this modified example, in addition to the flow chart of Fig. 5 (first embodiment), the processing of steps S13 and S15 is performed. The processing of Fig. 6 will be described below.

When the processing in FIG. 6 is started, steps S10 and S12 are performed in the same manner as in the first embodiment described above. After step S12, the process proceeds to step S13, where the leaf area index calculation unit 32 determines whether image data of the seedling on the nth day is available. If the determination in step S13 is negative, the processing from step S14 to step S16 onwards is executed, as in the first embodiment.

On the other hand, if image data of the seedlings on the nth day is available, the leaf area index calculation unit 32 judges in step S13 to be positive and proceeds to step S15. Here, the image data of the seedlings is assumed to be an image of the seedlings photographed from above as shown in FIG. 7(a). Note that the user may take an image such as that shown in FIG. 7(a) using a camera provided in the user terminal 70 and transmit it to the server 10. Also, for example, an image taken using a camera installed in the field (above the seedlings) may be received by the user terminal 70 and transmitted to the server 10.

When the process proceeds to step S15, the leaf area index calculation unit 32 extracts, for example, the green parts of the image in FIG. 7(a) and binarizes the green parts from the other parts to generate a binary image as shown in FIG. 7(b). The leaf area index calculation unit 32 then uses the binary image to calculate the leaf area index. The leaf area index can be calculated by dividing the total area of leaves of a predetermined number of seedlings included in the image by the area of the region allocated to the predetermined number of seedlings.

After step S15, the processes from step S16 onwards are executed in the same manner as in the first embodiment described above.

As described above, according to this modified example, when image data of the seedlings is available, the image data is used to calculate the leaf area index of the seedlings, so that the leaf area index can be calculated with high accuracy. This allows the dry weight on the (n+1)th day to be estimated with high accuracy, and therefore the time when flower bud differentiation is possible (the timing when treatment to promote flower bud differentiation should be performed) can also be estimated with high accuracy.

Second Embodiment
Next, a second embodiment will be described below. Fig. 8 is a flow chart showing the process of the server 10 in the second embodiment.

As shown in FIG. 8, in this second embodiment, steps S10' and S14' are executed instead of steps S10 and S14 included in the processing of the first embodiment (FIG. 5). Note that the processing of this second embodiment is processing in the case where the server 10 can obtain image data of seedlings for each day from the user terminal 70.

In step S10' in Fig. 8, the dry matter weight specifying unit 30 estimates the initial value of the dry matter weight. For example, when information on the sowing date is input from the user terminal 70, the growth from sowing to leaf unfolding is calculated from data on the average daily temperature, and the dry matter weight at that time is estimated as the initial value. When image data of the seedlings at the start of seedling cultivation is input from the user terminal 70, the dry matter weight specifying unit 30 estimates the dry matter weight (initial value) using the image data. Specifically, the dry matter weight specifying unit 30 estimates the dry matter weight at the start of seedling cultivation according to the following formula (4).
Dry weight at the start of seedling cultivation = leaf area calculated from image data ÷ specific leaf area ... (4)

After step S10', the process moves to step S12 and then to step S14', where the leaf area index calculation unit 32 calculates the leaf area index from the image data for the nth day. The process of step S14' is the same as step S15 described in the modified example of the first embodiment above, so a description thereof will be omitted.

After that, the processes from step S16 onwards are carried out in the same manner as in the first embodiment above.

As described above, according to the second embodiment, the dry matter weight determination unit 30 estimates the initial value of the dry matter weight based on the image data of the seedlings and the information on the sowing date (S10'). In addition, the leaf area index calculation unit 32 calculates the leaf area index of the seedlings on the nth day based on the image data of the seedlings on the nth day (S14), the daily light reception calculation unit 34 calculates the daily light reception on the nth day (S18), the daily dry matter production calculation unit 36 calculates the daily dry matter production on the nth day (S20), and the dry matter weight determination unit 30 calculates the dry matter weight of the seedlings on the (n+1)th day (S22). This process is repeated while increasing the value of n. Then, when the calculation result of the dry matter weight of the seedlings on the (n+1)th day exceeds the threshold value (S24: Yes), the flower bud differentiation possible time determination unit 38 determines that flower bud differentiation of the seedlings is possible, and the output unit 40 outputs that fact (S28). As a result, in the second embodiment, as in the first embodiment, the flower bud differentiation possible time (the timing at which the treatment to promote flower bud differentiation should be performed) can be estimated without performing a destructive nitrogen content survey of the plant body or checking the flower bud formation with a microscope, which requires skill. Therefore, the timing at which the treatment to promote flower bud differentiation should be performed can be estimated with higher accuracy than the nitrogen content survey. Also, unlike a microscope, the timing at which the treatment to promote flower bud differentiation should be performed can be estimated in advance, so that preparations for planting can be made at an early stage. This makes it possible to prevent delays in flowering and, ultimately, in harvesting. Also, by calculating the leaf area index using image data of the seedlings, the dry weight can be accurately estimated and the flower bud differentiation possible time can be accurately estimated.

(Modification of the second embodiment)
Next, a modified example of the second embodiment will be described. Fig. 9 is a flowchart showing the processing contents of the server 10 in the modified example of the second embodiment. In this modified example, in addition to the flowchart in Fig. 8 (second embodiment), the processing of steps S13' and S15' is performed. The processing in Fig. 9 will be described below.

When the process of FIG. 9 starts, steps S10' and S12 are performed in the same manner as in the second embodiment described above. After step S12, the process proceeds to step S13', where the leaf area index calculation unit 32 determines whether image data of the seedling on the nth day is available. If the determination in step S13' is positive, the process proceeds to step S14' and step S16 and subsequent steps, as in the second embodiment.

On the other hand, if there is no image data of the seedlings on the nth day, i.e., if the image data of the seedlings cannot be acquired due to a camera malfunction or communication failure, the judgment in step S13' is negative and the process proceeds to step S15'. When the process proceeds to step S15', the leaf area index calculation unit 32 calculates the leaf area index from the dry weight on the nth day, similar to step S14 in the first embodiment.

After step S15', the processes from step S16 onwards are executed in the same manner as in the second embodiment described above.

As described above, according to this modified example, even if image data of the seedlings cannot be acquired, the leaf area index of the seedlings is calculated from the dry weight, so that the leaf area index can be calculated accurately even if the camera breaks down or communication problems occur. This allows the dry weight on the (n+1)th day to be estimated accurately, and therefore the time when flower buds can differentiate can also be estimated accurately.

The above processing functions can be realized by a computer. In that case, a program is provided that describes the processing contents of the functions that the processing device should have. The above processing functions are realized on the computer by executing the program on the computer. The program describing the processing contents can be recorded on a computer-readable storage medium (excluding carrier waves, however).

When a program is distributed, it is sold, for example, in the form of a portable storage medium on which the program is recorded, such as a DVD (Digital Versatile Disc) or a CD-ROM (Compact Disc Read Only Memory). The program can also be stored in the storage device of a server computer, and then transferred from the server computer to other computers via a network.

A computer that executes a program stores, for example, a program recorded on a portable storage medium or a program transferred from a server computer in its own storage device. The computer then reads the program from its own storage device and executes processing in accordance with the program. Note that the computer can also read a program directly from a portable storage medium and execute processing in accordance with that program. The computer can also execute processing in accordance with the received program each time a program is transferred from the server computer.

The above-described embodiment is a preferred example of the present invention. However, the present invention is not limited to this embodiment, and various modifications are possible without departing from the spirit of the present invention.

10 Server 30 Dry matter weight determination unit 32 Leaf area index calculation unit 34 Daily light reception calculation unit 36 Daily dry matter production calculation unit 38 Flower bud differentiation possible time determination unit 40 Output unit 70 User terminal

Claims (7)

A first process of acquiring a dry weight of a strawberry seedling at the start of seedling cultivation or estimating the dry weight of the seedling at the start of seedling cultivation based on data of daily average temperature from the sowing date;
a second process of calculating a leaf area index of the seedling on the nth day (n is a natural number) from the dry matter weight of the seedling on the nth day from the start of seedling raising, calculating the daily light reception amount on the nth day based on the calculated leaf area index and data on the daily accumulated solar radiation on the nth day, calculating the daily dry matter production amount on the nth day based on the calculated daily light reception amount, and calculating the dry matter weight of the seedling on the (n+1)th day by adding the daily dry matter production amount on the nth day to the dry matter weight of the seedling on the nth day, while repeating this process while increasing the value of n;
A third process of determining and outputting the day on which the calculation result of the dry weight of the seedling exceeds a predetermined threshold as the timing for performing a process to promote flower bud differentiation of the seedling;
A processing timing estimation method comprising the steps of: The processing timing estimation method according to claim 1, characterized in that, in the second process, when image data of the seedlings on the nth day is input, the leaf area index on the nth day is calculated using the image data of the seedlings on the nth day. A first process of calculating a leaf area from image data of strawberry seedlings at the start of seedling cultivation and estimating a dry weight of the seedlings at the start of seedling cultivation from the calculated leaf area, or estimating a dry weight of the seedlings at the start of seedling cultivation based on data of daily average temperature from the sowing date;
a second process for calculating a leaf area index of the seedling on the nth day (n is a natural number) from image data of the seedling on the nth day from the start of seedling raising, calculating the amount of daily light received on the nth day based on the calculated leaf area index and data on the daily accumulated solar radiation on the nth day, calculating the daily dry matter production on the nth day based on the calculated daily light received, and calculating the dry matter weight of the seedling on the (n+1)th day by adding the daily dry matter production on the nth day to the dry matter weight of the seedling on the nth day, while repeating this process while increasing the value of n;
A third process of determining and outputting the day on which the calculation result of the dry weight of the seedling exceeds a predetermined threshold as the timing for performing a process to promote flower bud differentiation of the seedling;
A processing timing estimation method comprising the steps of: The processing timing estimation method according to claim 3, characterized in that in the second process, if image data of the seedling on the nth day does not exist, the leaf area index on the nth day is calculated from the dry weight of the seedling on the nth day. The processing timing estimation method according to any one of claims 1 to 4, characterized in that the threshold value is a value determined for each strawberry variety. A first process of acquiring a dry weight of a strawberry seedling at the start of seedling cultivation or estimating the dry weight of the seedling at the start of seedling cultivation based on data of daily average temperature from the sowing date;
a second process of calculating a leaf area index of the seedling on the nth day (n is a natural number) from the dry matter weight of the seedling on the nth day from the start of seedling raising, calculating the daily light reception amount on the nth day based on the calculated leaf area index and data on the daily accumulated solar radiation on the nth day, calculating the daily dry matter production amount on the nth day based on the calculated daily light reception amount, and calculating the dry matter weight of the seedling on the (n+1)th day by adding the daily dry matter production amount on the nth day to the dry matter weight of the seedling on the nth day, while repeating this process while increasing the value of n;
A third process of determining and outputting the day on which the calculation result of the dry weight of the seedling exceeds a predetermined threshold as the timing for performing a process to promote flower bud differentiation of the seedling;
A processing timing estimation program that causes a computer to execute the above steps. A first process of calculating a leaf area from image data of strawberry seedlings at the start of seedling cultivation and estimating a dry weight of the seedlings at the start of seedling cultivation from the calculated leaf area, or estimating a dry weight of the seedlings at the start of seedling cultivation based on data of daily average temperature from the sowing date;
a second process for calculating a leaf area index of the seedling on the nth day (n is a natural number) from image data of the seedling on the nth day from the start of seedling raising, calculating the amount of daily light received on the nth day based on the calculated leaf area index and data on the daily accumulated solar radiation on the nth day, calculating the daily dry matter production on the nth day based on the calculated daily light received, and calculating the dry matter weight of the seedling on the (n+1)th day by adding the daily dry matter production on the nth day to the dry matter weight of the seedling on the nth day, while repeating this process while increasing the value of n;
A third process of determining and outputting the day on which the calculation result of the dry weight of the seedling exceeds a predetermined threshold as the timing for performing a process to promote flower bud differentiation of the seedling;
A processing timing estimation program that causes a computer to execute the above steps.

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