JP2018164408A - Growth condition prediction device, method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a device of predicting growth conditions of a field crop having 2 or more croppings per year.SOLUTION: A growth condition prediction device 100 which predicts growth conditions of a field crop having 2 or more croppings per year comprises: a cropping number input part 110 which inputs a plurality of cropping numbers of the field crop; a date input part 120 which inputs cultivation start date of the field crop; a growth conditions prediction part 140 which predicts the cropping numbers and growth conditions of each cropping from the cultivation start date; and an output part 160 which outputs growth conditions of the predicted each cropping.SELECTED DRAWING: Figure 2

Description

  The present invention relates to an apparatus, a method, and a program for predicting the growth status of crops.

  In greenhouse cultivation, greenhouses, plant factories, etc., different from outdoor cultivation, environmental parameters such as room temperature, humidity, CO2 concentration, and soil moisture can be controlled to some extent by various equipment and equipment. These environmental parameters are controlled with the goal of improving the growth and quality of cultivated crops.

  Patent document 1 relates to an environmental control system for facility cultivation, and describes a technique for always controlling the indoor temperature in accordance with the optimum temperature for growing the cultivated crop even if the outdoor environment changes.

JP 2014-150759 A

  However, the environmental control system of Patent Document 1 cannot predict the growth status. For this reason, a farm worker engaged in institutional cultivation needs to judge by himself the time of agricultural work such as harvesting as in the case of outdoor cultivation. In addition, when performing two or more crops a year, it is necessary to perform farming operations that match the growth of each crop.

  It is an object of the present invention to provide an apparatus for predicting the growth status of crops with two or more crops per year.

  In order to solve the above-mentioned problem, one of the representative growth status prediction devices of the present invention is a growth status prediction device that predicts the growth status of two or more crops per year, and a plurality of crop numbers of the crops. A crop number input unit that inputs the cultivation start date of the crop, a growth status prediction unit that predicts the growth status of each crop from the crop number and the cultivation start date, and the prediction An output unit is provided for outputting the growth status of each crop.

  ADVANTAGE OF THE INVENTION According to this invention, the apparatus which estimates the growth condition of 2 or more crops a year can be provided.

The figure for demonstrating the process of the farm work in facility cultivation. 1 is an overall view of a growth condition prediction apparatus according to Embodiment 1. FIG. FIG. 4 is a diagram for explaining an input screen according to the first embodiment. The table | surface of the integrated average temperature required for each growth stage which concerns on Example 1. FIG. The figure for demonstrating the screen which displays the predicted growth condition which concerns on Example 1. FIG. The figure for demonstrating the prediction of the growth condition in each crop which concerns on Example 1. FIG. The growth condition prediction flowchart which concerns on Example 1. FIG. FIG. 10 is a diagram for explaining an input screen according to the second embodiment. The figure for demonstrating the prediction of the growth condition in each crop which concerns on Example 2. FIG. The growth condition prediction flowchart according to the second embodiment. The whole figure of the growth condition prediction device concerning Example 3.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

  FIG. 1 is a diagram for explaining a farm work process in institutional cultivation. Here, tomato is taken as an example of the agricultural product, and the flow of the entire farm work for growing the tomato in a facility such as a greenhouse will be described. As main cultivation management work, there are work in the primary nursery room and work in the greenhouse of this farm. A right-pointing arrow on the horizontal axis indicates that time passes from left to right.

  In the primary nursery room, the farmer first sows. Specifically, the medium is put in a continuous tray connected with small pots, and seeds are seeded one by one in each pot. Thereafter, the medium is irrigated. In the primary nursery room, cultivation continues until the seedlings grow to a certain extent (about 20 days after germination), and this period is called primary seedling.

  Transplanting seedlings in the cultivation bed of this farm is called fixed planting. In general, planting is performed after primary seedling, but instead of planting immediately, it is sometimes transplanted to a normal size pot and cultivated in a state larger than the cultivation density in the main field, which is called secondary seedling .

  When the secondary seedling is finished (after about 15 days), the planting is performed.

  When the tomato seedlings are germinated in the primary nursery room for about 20 days in this way, the seedlings are transferred to the greenhouse in this field, and the secondary seedlings are grown for about 15 days and further planted. When a few days have passed since planting, the first flowers bloom (referred to as the first tress) and the first tomatoes (referred to as the first tress). This tomato is the first stage. Furthermore, when the side buds are removed and tailored to a single trunk (main trunk), the second-stage flowers bloom on the first-stage tomatoes, forming tomatoes.

  In large-scale cultivation, long-stage cultivation is performed in which long-stage cultivation of 25 to 30 stages is performed and harvested. On the other hand, there is also a method called low-stage dense planting in which a lot of tomatoes are formed in 1 to 5 low stages. In the present embodiment, low-stage dense planting is performed and a harvesting example will be described.

  This period from sowing to harvest is called one crop. And, when performing continuous cropping by institutional cultivation, it is common to sow the second crop during the harvest of the first crop

(Constitution)
FIG. 2 is an overall view of the growth state prediction apparatus according to the first embodiment. The growth state prediction apparatus 100 acquires temperature data in the facility from the temperature sensor 210 in the cultivation facility 200 where the crop is grown.

  The cultivation facility 200 is normally divided into a primary nursery room and a main greenhouse, and the temperature sensor 210 measures temperature data of each facility.

  Each input unit of the growth status prediction apparatus 100 accepts data input from a farm worker. The crop number input unit 110 accepts an input from a farmer regarding the number of crops for predicting the growth status of tomatoes. The date input unit 120 receives an input of the first sowing date (that is, the cultivation start date) by the farm worker. Here, the number-of-cropping input unit 110 can also accept input of the number of stages of each crop and whether or not to perform secondary breeding.

  The temperature data acquisition unit 130 acquires temperature data from the temperature sensor 210 and adds the temperature data to the normal temperature data of the cultivation facility 200. As normal temperature data, it is preferable to store temperature data for the past several years, and preferably store temperature data for about 10 years. Or you may acquire the outside temperature data of a normal year from an external database, and may convert into the temperature data in a cultivation facility. For example, 3 ° C. is uniformly added to each of the outside air temperature data, and converted to the air temperature data in the cultivation facility.

  The growth state prediction unit 140 receives the number of tomato crops and the number of stages, information on whether or not to grow secondary seedlings from the crop number input unit 110, and receives the sowing date from the date input unit 120. In Example 1, the growth condition prediction unit 140 predicts the growth condition of the crop using the integrated temperature. This growth status includes the farm work days from the sowing date of each crop to the end date of harvest, the flowering date at each stage, and the like.

  The integrated temperature calculation unit 150 calculates the average temperature integrated from the sowing date based on the normal temperature data. In the present embodiment, the integrated daily average temperature is used as the effective integrated temperature. However, the present invention is not limited to this, for example, it may be integrated after subtracting 8 ° C. from the daily average temperature. An integration method can be used.

(Operation)
Next, operation | movement of the growth condition prediction apparatus 100 is demonstrated. FIG. 3 is a diagram for explaining an input screen according to the first embodiment.

  FIG. 4A shows input item names and input values on the input screen. A farmer who is a user of the growth status prediction apparatus 100 inputs the sowing date of the first crop, the desired number of crops and the number of steps, and whether or not to perform secondary seedling from this screen.

  FIG. 5B shows an example of a screen input by a farm worker. The day when the farmer wants to start the growth prediction, that is, the date of the first sowing date “May 1” is input, and the date input unit 120 accepts the input of the sowing date.

  When the farmer inputs the number of crops, the number of stages and the presence / absence of secondary seedling are displayed according to the number, and the farmer is prompted to input the number of stages of each crop and the presence / absence of secondary seedling. For example, the number of crops that the farmer wants to predict is input, and the number of stages in each crop and the presence or absence of secondary seedling “the first crop has two stages and secondary seedlings. The second crop has 3 “Second stage seedling, and third stage, fourth stage, second seedling” are entered. The crop number input unit 110 accepts inputs of the crop number, the number of stages in each crop number, and the presence or absence of secondary seedlings.

  FIG. 4 is a table of integrated average temperatures required for each growth stage according to Example 1. The growth status prediction unit 140 predicts the growth status based on such tabular data and the average temperature estimated from the sowing date predicted by the integrated temperature calculation unit 150.

  FIG. 5 is a diagram for explaining a screen that displays the growth status predicted by the growth status prediction unit 140 according to the first embodiment. By looking at this screen, the farmer predicts that (1) “the last stage of the first crop (second stage) is the end of harvest on August 7,” and (2) "I would like to set the second planting date on August 9th", so (3) the day when I want to start the growth prediction, predicting that "the second planting date will be July 12" It can be confirmed when (May 1) is entered.

  The shorter the interval between the last harvest date of the first crop and the fixed planting date of the second crop, the more effectively the cultivation facility can be used. Here, between the last harvest date of the first crop (August 7) and the second planting date (August 9), one day was set up to clean up the first crop. It is for putting.

  FIG. 6 is a diagram for explaining the prediction of the growth situation in each crop according to the first embodiment. The sowing date of the first crop can be input, and the growth status of each crop can be predicted using the normal year data. As a result, the farmer (1) predicts that the harvest end date of the last stage (second stage) of the first crop will be August 7, and (2) “I want to make the planting date of the crop on August 9th”, so it is possible to simulate (3) “Making the seeding date of the second crop on July 12”.

  FIG. 7 is a growth state prediction flowchart according to the first embodiment. The growth status prediction unit 140 receives from the crop number input unit 110 the number of tomato crops and the number of stages, and information on whether or not to grow secondary seedlings, and from the date input unit 120 is the day on which the growth prediction is to be started. Information on the sowing date of the first crop is acquired (S110).

  Next, the growth state prediction unit 140 instructs the integrated temperature calculation unit 150 to acquire normal temperature data from the temperature data acquisition unit 130 (S120). The integrated temperature calculation unit 150 calculates the integrated average temperature after the sowing date (S130). The growth state prediction unit 140 predicts the growth state after the sowing date, and the output unit 160 outputs the prediction result (S140).

(effect)
According to the present embodiment, it is possible to simultaneously predict the growth situation of two or more crops per year. Thereby, the farm worker can set the schedule management of the farm work for the current crop and the subsequent crop at the same time, and has the effect of being able to create a production cultivation plan for crops of two or more crops per year.

  Since the growth situation prediction apparatus according to the second embodiment has the same configuration as the growth situation prediction apparatus 100 according to the first embodiment, the description thereof is omitted. The feature of the second embodiment is the same as that of the first embodiment until the day when the growth prediction is started (that is, the sowing date of the first crop) and the growth state is predicted. Is a point.

(Constitution)
FIG. 8 is a diagram for explaining an input screen according to the second embodiment. 8A and 8B are different from FIGS. 3A and 3B in that a re-simulation execution date is added. In FIG. 8B, the re-simulation is executed on June 3.

  For example, the expected flowering date of the first stage of the first crop is June 8, but since the outside temperature was higher than normal, the temperature in the cultivation facility also became higher and the growth was faster. Consider a case where it is confirmed that the first stage of the first crop has flowered on the 3rd. In such a case, if the work is carried out according to the subsequent predicted farm work date, each work is followed, and the harvest end date is advanced, so that the period until the second planting date is vacated. Therefore, in Example 2, the sowing date is the same (May 1), but the date input unit 120 accepts the input of the date “June 3”, and the growth state prediction unit 140 again on June 3 Run the simulation.

(Operation)
FIG. 9 is a diagram for explaining the prediction of the growth situation in each crop according to Example 2. Similar to Example 1, in addition to normal data, re-simulation from the first input date (May 1) Re-simulation is performed using the temperature data actually measured this year until June (June 3). Thereby, the prediction of the growth situation can be corrected. For example, in Example 1, the scheduled seeding date for the second crop was July 12, as shown in FIG. 5, but it has been corrected to July 5 in FIG.

  FIG. 10 is a growth state prediction flowchart according to the second embodiment. The growth state prediction unit 140 receives from the crop number input unit 110 information on the number and stage of tomato production and whether or not to perform secondary seedling, and from the date input unit 120, the actual seeding date and re-simulation. Date information is acquired (S210). Next, the growth state prediction unit 140 instructs the integrated temperature calculation unit 150 to acquire the normal temperature data after the sowing date and the actual temperature data of this year from the temperature data acquisition unit 130 (S220). The integrated temperature calculation unit 150 calculates the integrated average temperature after the re-simulation date (S230). The growth state prediction unit 140 predicts the growth state after the re-simulation date, and the output unit 160 outputs the prediction result (S240).

(effect)
According to the present embodiment, after predicting the growth situation of two or more crops per year, the simulation can be performed again when the farmer notices that the growth situation is different from the initial prediction. As a result, the farmer can reset the schedule management for the current crop and the subsequent crop in accordance with this year's weather conditions, and can re-create the production and cultivation plan for the crop.

(Constitution)
FIG. 11 is an overall view of the growth condition prediction apparatus according to the third embodiment. The growth status prediction device 300 according to the third embodiment is different from the growth status prediction device 100 according to the first embodiment in that the growth status prediction unit 340 includes a number of days calculation unit 310.

(Operation)
In the first embodiment, the growth state prediction unit 140 predicts the growth state of the crop using the integrated average temperature. That is, the thermal time of average temperature is used. Thus, the time required for the same growth can be predicted according to the weather conditions in each region, such as being short when warm and taking a long time when cold.

  However, in this method, it is necessary to previously acquire normal temperature data at the cultivation facilities in each region. For this reason, when a cultivation facility is newly established, it may be difficult to use the accumulated average temperature.

  Therefore, in the third embodiment, real time of days is used instead of the daily average temperature. The growth state prediction unit 340 receives the number of tomato crops and the number of stages, information on whether or not to grow secondary seedlings from the crop number input unit 110, and receives the sowing date from the date input unit 120. In Example 3, the growth status prediction unit 340 causes the day calculation unit 310 to calculate the predicted number of days for the growth status of each crop (from the sowing date to the harvest end date) from the first sowing date. The calculation here calculates the growth status prediction date using the general growth status days. In addition, the growth status such as flowering date in each stage is also predicted using the general growth status days. Here, it is necessary to change the general growth state days depending on the region, cultivation management method, season, and the like.

(effect)
According to the present embodiment, it is possible to simultaneously predict the growth situation of two or more crops per year. Thereby, the farm worker can set the schedule management of the farm work for the current crop and the subsequent crop at the same time, and has the effect of being able to create a production cultivation plan for crops of two or more crops per year. This is particularly effective when normal temperature data is not acquired in advance.

  Moreover, the growth condition prediction unit 340 uses the actual temperature data (first input date to re-simulation date) of Example 2 by using the integrated temperature calculation unit 150 together with the number of days calculation unit 310 during the re-simulation. Simulation can also be used, and farmers can reset the schedule management of the current crop and the subsequent crop in accordance with this year's weather conditions, and can recreate the production plan for crop production Has an effect.

  In addition, this invention is not limited to an above-described Example, Various modifications which can be applied to the growth condition prediction at the time of cultivating crops other than tomato are included. For example, in the case of tomato, the seed sowing date is the cultivation start date, but the cultivation start date includes the day of cutting, the day of planting the bulb, and the day of purchasing seedlings and starting cultivation, The above-described embodiments have been described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described. Further, a part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment. Further, it is possible to add, delete, and replace other configurations for a part of the configuration of each embodiment.

  In addition, each of the above-described configurations may be configured such that some or all of them are configured by hardware, for example, by designing with an integrated circuit, or may be realized by executing a program by a processor. Good. Further, the control lines and information lines indicate what is considered necessary for the explanation, and not all the control lines and information lines on the product are necessarily shown. Actually, it may be considered that almost all the components are connected to each other.

DESCRIPTION OF SYMBOLS 100,300 Growth condition prediction apparatus 110 Crop number input part 120 Date input part 130 Temperature data acquisition part 140,340 Growth condition prediction part 150 Integrated temperature calculation part 160 Output part 200 Cultivation facility 210 Temperature sensor 310 Days calculation part

Claims (10)

A growth status prediction device that predicts the growth status of crops of two or more crops per year,
A crop number input unit for inputting a plurality of crops of the crop;
A date input unit for inputting the cultivation start date of the crop;
From the number of crops and the cultivation start date, a growth status prediction unit that predicts the growth status of each crop,
A growth state prediction apparatus comprising: an output unit that outputs the predicted growth state of each crop. The growth status prediction unit predicts the growth status of the current crop and the next crop at the same time,
The growth status prediction apparatus according to claim 1, wherein the output unit outputs the predicted current status and the subsequent growth status at the same time.   The growth status prediction apparatus according to claim 1, wherein the growth status includes farm work days from the cultivation start date to the harvest end date of each crop.   The growth condition prediction apparatus according to claim 1, wherein the crop number input unit inputs the number of stages for each crop.   The growth condition prediction apparatus according to claim 1, wherein the crop number input unit inputs whether or not to perform secondary seedling for each crop. A temperature acquisition unit that acquires temperature data for normal times in the facility,
An integrated temperature calculation unit for calculating the integrated temperature;
The integrated temperature calculation unit calculates the temperature integrated from the cultivation start date of the current crop, based on the normal temperature data.
The growth status prediction device according to claim 1, wherein the growth status prediction unit predicts the growth status of each crop based on the number of crops, the cultivation start date, and the integrated temperature. The date input unit accepts input of a re-simulation execution date,
The integrated temperature calculation unit calculates the temperature integrated from the cultivation start date of the current crop, based on the temperature data of the normal year and the actually measured data from the cultivation start date of the current crop to the re-simulation execution date. And
The growth state prediction device according to claim 6, wherein the growth state prediction unit predicts the growth state of each crop based on the number of crops, the cultivation start date, and the integrated temperature. From the cultivation start date, further comprising a days calculation unit for calculating the number of days of growth of each crop,
The growth status prediction apparatus according to claim 1, wherein the growth status prediction unit predicts the growth status of each crop based on the calculated days of growth status of each crop. A growth status prediction method for predicting the growth status of two or more crops per year,
Enter a number of crops for the crop,
Enter the cultivation start date of the crop,
From the number of crops and the cultivation start date, predict the growth status of each crop,
A growth state prediction method for outputting the predicted growth state of each crop. A program for causing a computer to execute a device that predicts the growth status of crops of two or more crops per year,
A crop input step for inputting a plurality of crops of the crop,
A date input step for inputting a cultivation start date of the crop;
From the number of crops and the cultivation start date, a farm work prediction step for predicting the growth status of each crop,
A growth status prediction program comprising: an output step for outputting the predicted growth status of each crop.

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