CN115545305A - Crop transplanting period time prediction method and system - Google Patents
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Abstract
The invention provides a method and a system for predicting the time of a crop transplanting period, which comprises the following steps: s1, acquiring historical measured data; s2, building a basic parameter database: s3, establishing a time prediction model based on a basic parameter database, predicting the optimal transplanting time, predicting the local proper transplanting time in advance, providing a basis for planning of pre-ordering machinery, soil preparation, seedling management and the like for a grower in advance, providing a basis for mechanical scheduling for agricultural machinery service enterprises, and effectively ensuring the orderly implementation of soil preparation and transplanting tasks; by determining proper transplanting time, the condition that the transplanting green returning rate is directly influenced and further the yield and the quality are influenced when the transplanting is subjected to extreme weather or bad weather can be effectively avoided, and the risk can be reduced probably; by mastering the appropriate transplanting time, the risk that the green turning rate is low after one-time transplanting and the seedlings need to be replanted again can be avoided.
Description
Technical Field
The invention relates to the technical field of crop transplanting, in particular to a method and a system for predicting the time of a crop transplanting period.
Background
The suitable transplanting period prediction is to calculate the optimum transplanting time with the highest transplanting green-turning rate, the lowest cost, the best quality and the maximum yield by combining the factors of crops, varieties, regions, meteorological conditions and the like, so that the reduction of the risk of yield reduction is realized, the transplanting farming planning is assisted, the guidance of the optimum transplanting time is realized, the block-level suitable transplanting period is scientifically recommended to a user, and a basis is provided for the decision of the suitable transplanting period of the user.
In the field of agricultural production, accurate prediction of the optimal transplanting time of rice has important significance for stabilizing the yield of rice and improving the quality of rice.
The conditions of directing the transplanting period in the actual planting production are 2 types:
1. the local weather bureau provides special weather forecasts of the weather processes of rainfall, late spring coldness, sunny days and the like every year based on the crop transplanting period with large local planting area, and the forecast is more detailed compared with the ordinary forecast;
2. local experienced growers judge proper transplanting time by inquiring the transplanting period of the previous year and paying attention to the future 15 weather condition forecast data, and then the peripheral growers transplant with the wind;
the existing method for predicting the time of the crop transplanting period has the following problems:
1. the real-time performance is poor, the forecast data of the special subject is issued according to a certain frequency, but the weather changes very quickly, and the judgment is inaccurate due to untimely update of the weather data before the special subject at the current stage and the special subject at the next stage.
2. A more suitable plan for transplanting time cannot be given based on the variety, which is one of the important factors determining the transplanting time, and the transplanting time is different because the time required for different varieties to mature is different.
The factors cause the problem that the optimal transplanting period can not be determined by rice growers, so that the rice green turning rate is reduced, and even the yield is lost or the quality is reduced.
Therefore, a method and a system for predicting the time of the crop transplanting period are provided.
Disclosure of Invention
In view of the above, the embodiment of the present invention is to solve the problem that the rice reviving rate is reduced, and even the yield is lost or the quality is reduced because a rice grower cannot determine the optimal transplanting period.
The suitable transplanting period prediction is to calculate the optimum transplanting time with the highest transplanting green-turning rate, the lowest cost, the best quality and the maximum yield by combining the factors of crops, varieties, regions, meteorological conditions and the like, so that the reduction of yield reduction risks, the auxiliary transplanting farming planning and the guidance of the optimum transplanting time are realized, the block-level suitable transplanting period is scientifically recommended to a user, and a basis is provided for the decision of the suitable transplanting period of the user.
The technical scheme of the embodiment of the invention is realized as follows: a crop transplanting period time prediction method comprises the following steps:
s1, acquiring historical measured data;
s2, building a basic parameter database:
the construction of the basic parameter database comprises the following steps:
s21: acquiring actually measured statistical data and corresponding meteorological data;
s22: calculating the local latest transplanting time according to the historical measured data and the growth period days data required by different maturity varieties;
s23: according to the actual transplanting time when the actual yield per mu reaches an ideal value, setting a suitable transplanting time range, wherein X-Y (month/day-month/day) and X and Y both represent dates;
s24: judging whether the transplanting is suitable for each day according to weather forecast data in a framed time range;
and S3, establishing a time prediction model based on the basic parameter database, and predicting the optimal transplanting time.
As a further improvement of the application, in the S1, the historical measured data comprises variety, maturity, measured transplanting time of 1-3 years, historical meteorological data, green turning time, measured maturity time and measured per mu yield.
As a further improvement of the present application, in the S3, when the time prediction model is implemented, the method includes the following steps:
s31, acquiring the maturity of the planted variety;
s32, acquiring the number of days of the local variety in the growth period;
s33, determining the latest transplanting time, judging the minimum light heat quantity required by crop maturity in the area, and ensuring the lowest line of safe maturity;
and S34, judging the appropriate transplanting time according to the maturity of the variety, the 40 weather temperature forecast data and the 15 weather temperature forecast data, and determining the optimal transplanting time according to the biological zero degree of the crop transplanting period.
As a further improvement of the present application, in S33, when determining the latest transplanting time, the method includes the following steps:
s331, obtaining local historical meteorological data;
s332, in the lowest-temperature data of days from 9 months 1 days to 12 months 20 days in the history of 3 years, taking the earliest date of the lowest temperature of the first occurrence in the data of 3 years as B;
the date obtained by B- (growth period days + 15) is the latest transplanting time of the year.
As a further improvement of the present application, in S34, the optimal transplanting time is determined according to the following steps:
the ground temperature is more than or equal to 13 ℃ for 3 continuous days, and the day is A;
the lowest temperature in the range of X-Y days is more than or equal to 10 ℃, and the lowest temperature is allowed to appear for less than 10 ℃ and less than or equal to 2 days;
the lowest daily temperature in the range of X-Y days is less than 10 ℃ and more than 8 ℃;
the cumulative rainfall in the range of X-Y days is less than or equal to 5mm;
the daily wind speed is less than or equal to 5 levels within the range of X-Y days;
when the 5 conditions are met, A is the time suitable for transplanting, and the time suitable for transplanting in the future of 40 days and 15 days is calculated in sequence.
In order to solve the above technical problem, another technical solution adopted by the present application is: a crop transplanting period time prediction system, comprising:
the central processing module is used for comprehensively processing local crop transplanting information;
the acquisition module is connected with the central processing module and is used for acquiring historical measured data, wherein the historical measured data comprises varieties, maturity, measured transplanting time of 1-3 years, historical meteorological data, green turning time, measured maturity time and measured yield per mu;
the central processing module is in interactive connection with the storage module, and the storage module is used for storing the content in the storage module after the acquisition module acquires the historical measured data;
the reading module is connected with the storage module and is used for reading historical measured data in the storage module;
the environment identification module is connected with the central processing module and is used for acquiring local future environment data;
and the prediction module is connected with the central processing module and is used for determining the latest transplanting time and the optimal transplanting time of the crop transplanting according to the maturity of the locally planted variety and the number of days of the variety in the local growth period.
As a further improvement of the application, the system further comprises a communication module, wherein the communication module is used for carrying 3g, 4g, 5g and local area network signals to perform signal interaction with external signals.
As a further improvement of the application, the system further comprises a display module, and the display module is used for displaying the time prediction information.
In order to solve the above technical problem, the present application adopts another technical solution that: there is provided a computer apparatus comprising a processor, a memory coupled to the processor, the memory having stored therein program instructions which, when executed by the processor, cause the processor to carry out the steps of the method of crop transplant age time prediction according to any one of the preceding claims.
In order to solve the above technical problem, the present application adopts another technical solution that: there is provided a storage medium storing program instructions capable of implementing the method for predicting a time of crop transplantation period as set forth in any one of the above.
Due to the adoption of the technical scheme, the embodiment of the invention has the following advantages:
1. the method can predict the local proper transplanting time in advance, provide basis for planning of mechanical appointment, soil preparation, seedling management and the like of a planter in advance, provide basis for mechanical dispatching for agricultural mechanical service enterprises, and effectively ensure the orderly implementation of soil preparation and transplanting tasks.
2. By determining the proper transplanting time, the conditions that the transplanting green return rate is directly influenced and the yield and the quality are further influenced when the transplanting is subjected to extreme weather or bad weather can be effectively avoided, and the risk can be reduced roughly;
3. by mastering the appropriate transplanting time, the risk that the green turning rate is low after one-time transplanting and the seedlings need to be replanted again can be avoided.
The foregoing summary is provided for the purpose of description only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features described above, embodiments and features of the present invention will be readily apparent by reference to the drawings and following detailed description.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the embodiments or technical descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a method for predicting transplant time according to the present invention;
fig. 2 is a schematic block diagram of a transplantation time prediction system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "comprising" and "having," as well as any variations thereof, in this application are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
As shown in fig. 1-2, an embodiment of the present invention provides a method for predicting a time of a crop transplanting period, including the following steps:
s1, acquiring historical actual measurement data: the historical measured data comprises variety, maturity, measured transplanting time of 1-3 years, historical meteorological data, green turning time, measured maturity time and measured per mu yield;
s2, building a basic parameter database:
the construction of the basic parameter database comprises the following steps:
s21: acquiring actually measured statistical data and corresponding meteorological data;
s22: calculating local latest transplanting time according to historical measured data and growth period day data required by different maturity varieties;
s23: setting a suitable transplanting time range according to the actual transplanting time when the actual measured acre yield reaches an ideal value, wherein X-Y (month/day-month/day) and X and Y both represent dates;
s24: judging whether the transplanting is suitable for each day according to weather forecast data within a framed time range;
s3, establishing a time prediction model based on a basic parameter database, and predicting the optimal transplanting time;
when the time prediction model is implemented, the method comprises the following steps:
s31, acquiring the maturity of the planted variety;
s32, acquiring the number of days of the local variety in the growth period;
s33, determining the latest transplanting time, judging the minimum light heat quantity required by crop maturity in the area, and ensuring the lowest line of safe maturity;
when the latest transplanting time is determined, the method comprises the following steps:
s331, obtaining local historical meteorological data;
s332, in the lowest-temperature data of days from 9 months 1 days to 12 months 20 days in the history of 3 years, taking the earliest date of the lowest temperature of the first occurrence in the data of 3 years as B;
b- (growth period days + 15) is the latest transplanting time of the year;
s34, judging the appropriate transplanting time according to the maturity of the variety, the 40 weather temperature forecast data and the 15 weather temperature forecast data, and determining the optimal transplanting time according to biological zero degree in the crop transplanting period;
the optimal transplanting time is judged according to the following parts:
the ground temperature is more than or equal to 13 ℃ for 3 continuous days, and the day is A;
the lowest temperature in the range of X-Y days is more than or equal to 10 ℃, and the lowest temperature is allowed to appear for less than 10 ℃ and less than or equal to 2 days;
the daily lowest temperature in the range of X-Y days is less than 10 ℃ and more than 8 ℃;
the accumulated rainfall in the range of X-Y days is less than or equal to 5mm;
the daily wind speed is less than or equal to 5 levels within the range of X-Y days;
when the 5 conditions are met, A is the time suitable for transplanting, and the time suitable for transplanting in the future of 40 days and 15 days is calculated in sequence.
In order to solve the above technical problem, another technical solution adopted by the present application is: a crop transplanting period time prediction system, comprising:
the central processing module is used for comprehensively processing local crop transplanting information;
the acquisition module is connected with the central processing module and is used for acquiring historical measured data, wherein the historical measured data comprises varieties, maturity, measured transplanting time of 1-3 years, historical meteorological data, green turning time, measured maturity time and measured yield per mu;
the central processing module is in interactive connection with the storage module, and the storage module is used for storing the content into the storage module after the acquisition module acquires the historical measured data;
the reading module is connected with the storage module and is used for reading the historical measured data in the storage module;
the environment recognition module is connected with the central processing module, and the weather prediction module is used for acquiring local future environment data;
the prediction module is connected with the central processing module and used for determining the latest transplanting time and the optimal transplanting time of the crop transplanting according to the maturity of the locally planted variety and the number of days of the local growth period of the variety.
In this embodiment, specifically, the mobile terminal further includes a communication module, and the communication module is used for carrying 3g, 4g, 5g, local area network signals and performing signal interaction with external signals.
In this embodiment, specifically, the time prediction device further includes a display module, and the display module is configured to display the time prediction information.
For other details of the technical solution for implementing each module in the block-level backup apparatus for excluding files in the above embodiment, reference may be made to the description of the block-level backup method for excluding files in the above embodiment, and details are not repeated here.
It should be noted that, in the present specification, the embodiments are all described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other. For the system-class embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
In order to solve the above technical problem, the present application adopts another technical solution that: there is provided a computer device comprising a processor, a memory coupled to the processor, and program instructions stored in the memory, which when executed by the processor, cause the processor to perform the steps of the method for predicting the time of crop transplantation period as claimed in any one of the preceding claims, wherein the processor is referred to as a Central Processing Unit (CPU). The processor may be an integrated circuit chip having signal processing capabilities. The processor may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
In order to solve the above technical problem, the present application adopts another technical solution that: providing a storage medium storing program instructions capable of implementing the crop transplanting period time prediction method according to any one of the above;
the storage medium of the embodiment of the present application stores program instructions capable of implementing all the methods described above, where the program instructions may be stored in the storage medium in the form of a software product, and include several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, or various media capable of storing program codes, or a computer device such as a computer, a server, a mobile phone, or a tablet. The server may be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), and a big data and artificial intelligence platform.
The invention is in operation: according to the maturity of the crop variety and local environmental factors, the invention calculates the suitable transplanting time of 15 days in the future and the latest local transplanting time so as to improve the transplanting green-turning rate and strong seedling rate of the crop and ensure the high and stable yield of the crop. The model is suitable for the cereal crops needing transplanting, such as japonica rice, indica rice and the like.
In the several embodiments provided in the present application, it should be understood that the disclosed terminal, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit. The above are only embodiments of the present application, and not intended to limit the scope of the present application, and all equivalent structures or equivalent processes performed by the present application and the contents of the attached drawings, which are directly or indirectly applied to other related technical fields, are also included in the scope of the present application.
Claims (10)
1. A crop transplanting period time prediction method is characterized by comprising the following steps:
s1, acquiring historical measured data;
s2, building a basic parameter database:
the construction of the basic parameter database comprises the following steps:
s21: acquiring actually measured statistical data and corresponding meteorological data;
s22: calculating the local latest transplanting time according to the historical measured data and the growth period days data required by different maturity varieties;
s23: according to the actual transplanting time when the actual yield per mu reaches an ideal value, setting a suitable transplanting time range, wherein X-Y represents the date, and X and Y represent the date;
s24: judging whether the transplanting is suitable for each day according to weather forecast data within a framed time range;
and S3, establishing a time prediction model based on the basic parameter database, and predicting the optimal transplanting time.
2. The method for predicting the time of the crop transplanting period according to claim 1, wherein: in the S1, the historical measured data comprises variety, maturity, measured transplanting time of 1-3 years, historical meteorological data, green turning time, measured maturity time and measured per mu yield.
3. The method for predicting the time of the crop transplanting period according to claim 1, wherein: in S3, when the time prediction model is implemented, the method includes the following steps:
s31, acquiring the maturity of the planted variety;
s32, acquiring the number of days of the local variety in the growth period;
s33, determining the latest transplanting time, judging the minimum light heat quantity required by crop maturity in the area, and ensuring the lowest line of safe maturity;
and S34, judging the appropriate transplanting time according to the variety maturity, the 40 weather temperature forecast data and the 15 weather temperature forecast data, and determining the optimal transplanting time according to the biological zero degree of the crop transplanting period.
4. The method for predicting the time of the crop transplanting period according to claim 3, wherein: in S33, when the latest transplanting time is determined, the method includes the following steps:
s331, obtaining local historical meteorological data;
s332, in the lowest-temperature data of days from 9 months 1 days to 12 months 20 days in the history of 3 years, taking the earliest date of the lowest temperature of the first occurrence in the data of 3 years as B;
and the date obtained by B is the latest transplanting time of the year.
5. The method for predicting the time of crop transplantation period according to claim 3, wherein: in S34, the optimal transplanting time is determined according to the following steps:
the ground temperature is more than or equal to 13 ℃ for 3 continuous days, and the day is A;
the lowest daily temperature in the range of X-Y days is more than or equal to 10 ℃, and the lowest daily temperature is allowed to be less than 10 ℃ and less than or equal to 2 days;
the lowest daily temperature in the range of X-Y days is less than 10 ℃ and more than 8 ℃;
the accumulated rainfall in the range of X-Y days is less than or equal to 5mm;
the daily wind speed is less than or equal to 5 grades in the range of X-Y days;
when the above 5 conditions are met, A is the time suitable for transplanting, and the time suitable for transplanting is calculated for 40 days in the future and 15 days in the future in sequence.
6. A system for predicting the time of a crop transplant stage, comprising:
the central processing module is used for comprehensively processing local crop transplanting information;
the acquisition module is connected with the central processing module and is used for acquiring historical measured data, wherein the historical measured data comprises varieties, maturity, measured transplanting time of 1-3 years, historical meteorological data, green turning time, measured maturity time and measured yield per mu;
the central processing module is in interactive connection with the storage module, and the storage module is used for storing the content in the storage module after the acquisition module acquires the historical measured data;
the reading module is connected with the storage module and is used for reading historical measured data in the storage module;
the environment identification module is connected with the central processing module and is used for acquiring local future environment data;
and the prediction module is connected with the central processing module and is used for determining the latest transplanting time and the optimal transplanting time of the crop transplanting according to the maturity of the locally planted variety and the number of days of the variety in the local growth period.
7. The system for predicting the time of crop transplantation period according to claim 6, wherein: the communication module is used for carrying 3g, 4g and 5g local area network signals and carrying out signal interaction with external signals.
8. The system for predicting the time of crop transplantation period according to claim 6, wherein: the system also comprises a display module used for displaying the time prediction information.
9. A computer device, characterized in that it comprises a processor, a memory coupled to the processor, in which are stored program instructions that, when executed by the processor, cause the processor to carry out the steps of the method for predicting the time of crop transplanting sessions according to any one of claims 1 to 5.
10. A storage medium storing program instructions capable of implementing the crop transplanting period time predicting method according to any one of claims 1 to 5.
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| US20160307135A1 (en) * | 2015-04-15 | 2016-10-20 | International Business Machines Corporation | Scheduling Crop Transplantations |
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