Paddy rice planting water and fertilizer accurate control method and device suitable for saline-alkali soil

Abstract

The invention discloses a rice planting water and fertilizer accurate control method and device suitable for saline-alkali soil, and relates to the technical field of rice planting. The method comprises the following steps: detecting soil salinity and alkalinity and soil humidity data of a to-be-detected rice planting area based on an arranged saline-alkali soil detection module, and obtaining a first rice growth image at the same time; the saline-alkali soil detection module transmits detected data to the salinity and alkalinity analysis module and the humidity analysis module; obtaining a final water and fertilizer regulation and control value through the salinity and alkalinity regulation and control factor and the humidity regulation and control factor; acquiring a second rice growth image; and comparing the second rice growth image with the first rice growth image to realize regulation and control of rice planting water and fertilizer. The device comprises a control system, a saline-alkali soil detection module, a data analysis module, a water and fertilizer control module, a monitoring comparison module, an early warning module and a storage database. According to the invention, through regulating and controlling the calculation process, accurate control of water and fertilizer for rice planting is improved, and real-time correction is carried out on different stages.

Description

Technical Field

[0001] The present invention relates to the technical field of rice planting, and in particular to a method and device for precise control of water and fertilizer for rice planting in saline-alkali land. Background Art

[0002] Rice is a cereal crop of the genus Oryza. In the process of growing rice, factors such as soil quality, climate conditions, fertilization, and pest control will affect the quality and yield of rice. Among them, when growing rice in saline-alkali land, the existing planting methods rely more on farmers' planting experience. For example, water and fertilizer parameter control, soil salinity, soil moisture, and early warning analysis cannot be effectively monitored automatically, which leads to the inability to timely and real-time know the rice planting situation, resulting in the following problems:

[0003] 1. The current precise water and fertilizer control methods for rice cultivation in saline-alkali land may have certain limitations, and the established monitoring system and early warning mechanism are not very perfect, and the corresponding faults cannot be discovered and resolved in a timely manner, thus affecting the growth and yield of rice.

[0004] 2. The soil composition and characteristics of saline-alkali land are changeable and complex, requiring fine-grained regulation of different saline-alkali soil conditions, and targeted water and fertilizer implementation plans. The current method of manually controlling the amount of fertilizer and watering is subjective, inaccurate, slow in response, and labor-intensive in the precise water and fertilizer control plan for rice cultivation in saline-alkali land. It is impossible to accurately control the amount of water and fertilizer, and it is also impossible to guarantee the yield of rice. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention provides a method for accurately controlling water and fertilizer in rice planting in saline-alkali land.

[0006] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0007] A method for precise control of water and fertilizer for rice planting in saline-alkali land, comprising the following steps: S1, detecting soil salinity and soil moisture data of a rice planting area to be detected based on a set saline-alkali land detection module, and collecting rice growth images corresponding to the saline-alkali land in the rice planting area to be detected at the same time point through a camera carried by an unmanned aerial vehicle as a first rice growth image; S2, the saline-alkali land detection module transmits the detected soil salinity data to a salinity analysis module, and transmits the soil moisture data to a humidity analysis module; after analysis by the salinity analysis module and the humidity module, corresponding salinity assessment coefficients and humidity assessment coefficients of each depth layer are obtained; S3, calculating a salinity control factor based on the salinity assessment coefficient, and calculating a salinity control factor based on the salinity control factor. The humidity assessment coefficient calculates the humidity control factor, and obtains the final water and fertilizer control value through the salinity control factor and the humidity control factor; S4, after the control based on the water and fertilizer control value, the rice growth image after the water and fertilizer control corresponding to the designated rice saline-alkali land area is collected by the camera carried by the drone, and it is used as the second rice growth image; S5, the second rice growth image is compared with the first rice growth image. If it conforms to the rice growth trend, it indicates that the water and fertilizer control effect is good, and the early warning module will display the first early warning screen; if it does not conform to the rice growth trend, it indicates that the water and fertilizer control effect is poor, and the early warning module will display the second early warning screen; the control of water and fertilizer for rice planting is realized through the first early warning screen or the second early warning screen.

[0008] Based on the above technical solution, further, in S1, the soil salinity data of each collection point in the corresponding depth layer at the corresponding time point is collected by a soil salinity detector, and the soil moisture data of each collection point in the corresponding depth layer at the same time point is collected by a soil moisture sensor; wherein the detected depth layer is provided with at least a first-level depth layer, a second-level depth layer and a third-level depth layer; and a number of collection points are arranged at a certain interval in the rice planting area to be detected.

[0009] Based on the above technical solution, further, in S2, a first data storage and calculation module is provided in the salinity analysis module, and the first data storage and calculation module stores standard soil salinity data corresponding to each collection point collected in the first-level depth layer, standard soil salinity data corresponding to each collection point collected in the second-level depth layer, and standard soil salinity data corresponding to each collection point collected in the third-level depth layer, and performs a difference calculation between the actual soil salinity data of the corresponding depth layer received and the standard soil salinity data of the corresponding depth layer.

[0010] Based on the above technical solution, further, in S2, a first data evaluation module is also provided in the salinity analysis module, and the first data evaluation module stores an allowable error value A1 corresponding to the first-level depth layer, an allowable error value A2 corresponding to the second-level depth layer, and an allowable error value A3 corresponding to the third-level depth layer; and the error value A1 corresponds to a preset first-level salinity assessment coefficient B1, the error value A2 corresponds to a preset second-level salinity assessment coefficient B2, and the error value A3 corresponds to a preset third-level salinity assessment coefficient B3.

[0011] Based on the above technical solution, further, in S2, when it is necessary to correct the salinity-alkalinity related data, the calculation process of the salinity-alkalinity analysis module after receiving the corresponding soil salinity-alkalinity data is:

[0012]

[0013]

[0014] Where Y i is the soil salinity correction coefficient of the i-th level depth layer, i = 1, 2, 3; x i is the soil salinity actually detected at the i-th depth layer; X i is the preset standard soil salinity at the i-th depth layer, i = 1, 2, 3; B1′ is the corrected first-level salinity assessment coefficient; B2′ is the corrected second-level salinity assessment coefficient; B3′ is the corrected third-level salinity assessment coefficient; A1 j A2 is the soil salinity corresponding to the next depth layer of the jth collection point; j A3 is the soil salinity corresponding to the secondary depth layer under the jth collection point; j is the soil salinity corresponding to the third depth layer under the jth collection point; K1 is the salinity weight factor corresponding to the first depth layer, K2 is the salinity weight factor corresponding to the second depth layer, and K3 is the salinity weight factor corresponding to the third depth layer, where the value of each weight factor is between 0 and 1.

[0015] Based on the above technical solution, further, in S2, a second data storage and calculation module is provided in the humidity analysis module, and the second data storage and calculation module stores standard humidity analysis data corresponding to each collection point collected in the first-level depth layer, standard humidity analysis data corresponding to each collection point collected in the second-level depth layer, and standard humidity analysis data corresponding to each collection point collected in the third-level depth layer, and performs a difference calculation between the actual humidity analysis data of the corresponding depth layer received and the standard humidity analysis data of the corresponding depth layer.

[0016] Based on the above technical solution, further, in S2, a second data evaluation module is provided in the humidity analysis module, and the second data evaluation module stores the allowable error value C1 corresponding to the first-level depth layer, the allowable error value C2 corresponding to the second-level depth layer, and the allowable error value C3 corresponding to the third-level depth layer, wherein the error value C1 corresponds to the preset first-level humidity evaluation coefficient D1, the error value C2 corresponds to the preset second-level humidity evaluation coefficient D2, and the error value C3 corresponds to the preset third-level humidity evaluation coefficient D3.

[0017] Based on the above technical solution, further, when it is necessary to correct the soil moisture related data, the calculation process of the humidity analysis module after receiving the corresponding soil moisture data is:

[0018]

[0019]

[0020] Where P i is the soil moisture correction coefficient of the i-th level depth layer, i = 1, 2, 3; C i is the soil moisture actually detected at the i-th depth layer; T i is the preset standard soil moisture at the i-th depth layer; D1′ is the corrected first-level moisture evaluation coefficient; D2′ is the corrected second-level moisture evaluation coefficient; D3′ is the corrected third-level moisture evaluation coefficient; C1 j C2 is the soil moisture corresponding to the next depth layer of the jth collection point; j C3 is the soil moisture corresponding to the secondary depth layer under the jth collection point; j is the soil moisture corresponding to the third depth layer under the jth collection point; H1 is the moisture weight factor corresponding to the first depth layer, H2 is the moisture weight factor corresponding to the second depth layer, and H3 is the moisture weight factor corresponding to the third depth layer, where the value of each weight factor is between 0 and 1.

[0021] Based on the above technical solution, further, in S3, the calculation process of the salinity control factor is: B =B×λ B Where S B is the salinity control factor, B is the salinity assessment coefficient of each depth layer, λ B is the salinity control weight factor, with a value of 0-1; the calculation process of the humidity control factor is: S D =D×λ D Where S D is the humidity control factor, D is the salinity assessment coefficient of each depth layer, λ D It is the humidity control weight factor, and its value range is 0-1.

[0022] A precise water and fertilizer control device for rice planting in saline-alkali land implements a precise water and fertilizer control method for rice planting in saline-alkali land, comprising a control system, a saline-alkali land detection module, a data analysis module, a water and fertilizer control module, a monitoring and comparison module, an early warning module and a storage database, wherein the control system controls the saline-alkali land detection module, the data analysis module, the water and fertilizer control module, the monitoring and comparison module and the early warning module; the saline-alkali land detection module is connected to the data analysis module, the data analysis module is connected to the water and fertilizer control module, the water and fertilizer control module is connected to the early warning module, and the database is respectively connected to the data analysis module, the water and fertilizer control module and the monitoring and comparison module.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] (1) The present invention can monitor the soil salinity and soil moisture data of the rice planting area by setting a saline-alkali land detection module, a data analysis module, a water and fertilizer control module, a monitoring and comparison module, and an early warning module, and evaluate the salinity and moisture of each depth layer through the corresponding salinity analysis module and the moisture analysis module, and then obtain the corresponding control factor based on the corresponding evaluation coefficient, determine the final water and fertilizer control value according to the control factor, obtain the corresponding growth image after the water and fertilizer control value is regulated, and compare the images before and after the regulation to determine whether it is necessary to regulate again. At the same time, it also has an early warning function, and can monitor and warn in real time; solve the problem that the existing monitoring and early warning mechanism is not timely and imperfect, and at the same time improve the monitoring timeliness and the accuracy of regulation, thereby increasing the yield of rice. Among them, the present invention also improves the precise control through the corresponding regulation calculation process, and makes real-time corrections to different stages. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 Flow chart of the control method of the present invention. DETAILED DESCRIPTION

[0026] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments.

[0027] The components of the embodiments of the present invention generally described and shown in the drawings herein may be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention.

[0028] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. In the description of the present invention, it should be noted that, unless otherwise clearly stipulated and limited, the term "connection" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0029] Example 1

[0030] Combination Figure 1 As shown, this embodiment provides a method for precise water and fertilizer control in rice planting in saline-alkali land, which includes the following steps:

[0031] S1. Based on the set saline-alkali land detection module, the soil salinity, soil moisture and other data of the rice planting area to be detected are detected. Specifically, a number of collection points are arranged at a certain interval in the rice planting area to be detected, wherein the collection depths of each collection point in the same time period are the same or close, and the close depth error range is ±2cm. It should be noted that the depth error does not affect the collection data of each collection point. Further, the collected data include the corresponding soil salinity and soil moisture of each collection point in each depth layer corresponding to each area position; specifically, the corresponding soil salinity data of each collection point in each depth layer at the corresponding time point is collected by a soil salinity detector, the corresponding soil moisture data of each collection point in each depth layer at the same time point is collected by a soil moisture sensor, and the rice growth image corresponding to the saline-alkali land in the rice planting area to be detected at the same time point is collected by a camera carried by a drone as the first rice growth image. In this embodiment, the depth layer to be detected is provided with at least a primary depth layer, a secondary depth layer and a tertiary depth layer, wherein the depth difference between two adjacent depth layers is not less than 8 cm, that is, the depth difference between the primary depth layer and the secondary depth layer is not less than 8 cm, and the depth difference between the secondary depth layer and the tertiary depth layer is not less than 8 cm. It should be noted that, in some embodiments, not making too many restrictions on each acquisition point does not affect the entire control process.

[0032] S2. The soil salinity data detected by the saline-alkali soil detection module is transmitted to the salinity analysis module, which is provided with a first data storage and calculation module and a first data evaluation module, wherein the first data storage and calculation module stores standard soil salinity data corresponding to each collection point collected at the first-level depth layer, standard soil salinity data corresponding to each collection point collected at the second-level depth layer, and standard soil salinity data corresponding to each collection point collected at the third-level depth layer, and performs difference calculation between the actual soil salinity data of the corresponding depth layer received and the standard soil salinity data of the corresponding depth layer. At the same time, the first data storage and calculation module transmits the absolute value result of the calculated difference to the first data evaluation module via wireless communication; further, the first data evaluation module stores the allowable error corresponding to the first-level depth layer. The first data evaluation module compares the received data difference with the error value A1 or A2 or A3 of the corresponding depth layer, and when it falls into the corresponding error range, selects the corresponding salinity evaluation coefficient B1, B2, B3, and performs the subsequent operations of other steps; if it does not fall into the corresponding error range, it is corrected to improve the accuracy of the detection data and provide more valuable data for the subsequent detection process;

[0033] In this embodiment, when it is necessary to correct the salinity-alkalinity related data, the calculation process of the salinity-alkalinity analysis module after receiving the corresponding soil salinity-alkalinity data is as follows:

[0034]

[0035] Where Y i is the soil salinity correction coefficient of the i-th level depth layer, i = 1, 2, 3; x i is the soil salinity actually detected at the i-th depth layer; X i is the preset standard soil salinity at the i-th depth layer, i = 1, 2, 3; B1′ is the corrected first-level salinity assessment coefficient; B2′ is the corrected second-level salinity assessment coefficient; B3′ is the corrected third-level salinity assessment coefficient; A1 j A2 is the soil salinity corresponding to the next depth layer of the jth collection point; j A3 is the soil salinity corresponding to the secondary depth layer under the jth collection point; jis the soil salinity corresponding to the third depth layer under the jth collection point; K1 is the salinity weight factor corresponding to the first depth layer, K2 is the salinity weight factor corresponding to the second depth layer, and K3 is the salinity weight factor corresponding to the third depth layer, where the value of each weight factor is between 0 and 1. The corrected salinity assessment coefficients at all levels calculated by the above formula are used as new salinity assessment coefficients for subsequent operations in other steps.

[0036] The soil moisture data detected by the saline-alkali land detection module is transmitted to the moisture analysis module, and the moisture analysis module is provided with a second data storage and calculation module and a second data evaluation module, wherein the second data storage and calculation module stores the standard moisture analysis data corresponding to each collection point collected in the first-level depth layer, the standard moisture analysis data corresponding to each collection point collected in the second-level depth layer, and the standard moisture analysis data corresponding to each collection point collected in the third-level depth layer, and the actual moisture analysis data of the corresponding depth layer received is calculated to be different from the standard moisture analysis data of the corresponding depth layer. At the same time, the second data storage and calculation module transmits the absolute value result of the calculated difference to the second data evaluation module via wireless communication; further, the second data evaluation module stores the allowable error value C1 corresponding to the first-level depth layer. , the secondary depth layer corresponds to the allowable error value C2, the third depth layer corresponds to the allowable error value C3, and at the same time, the evaluation coefficients corresponding to the corresponding error ranges are also stored for the subsequent data evaluation process, wherein the error value C1 corresponds to the preset primary humidity evaluation coefficient D1, the error value C2 corresponds to the preset secondary humidity evaluation coefficient D2, and the error value C3 corresponds to the preset tertiary humidity evaluation coefficient D3; the first data evaluation module compares the received data difference with the error value C1 or C2 or C3 of the corresponding depth layer respectively, and when it falls into the corresponding error range, the corresponding humidity evaluation coefficient D1, D2, D3 is selected, and the subsequent operations of other steps are performed; if it does not fall into the corresponding error range, correction is performed to improve the accuracy of the detection data and provide more valuable data for the subsequent detection process;

[0037] In this embodiment, when it is necessary to correct the soil moisture related data, the calculation process of the humidity analysis module after receiving the corresponding soil moisture data is as follows:

[0038]

[0039] Where P i is the soil moisture correction coefficient of the i-th level depth layer, i = 1, 2, 3; C i is the soil moisture actually detected at the i-th depth layer; T iis the preset standard soil moisture at the i-th depth layer; D1′ is the corrected first-level moisture evaluation coefficient; D2′ is the corrected second-level moisture evaluation coefficient; D3′ is the corrected third-level moisture evaluation coefficient; C1 j C2 is the soil moisture corresponding to the next depth layer of the jth collection point; j C3 is the soil moisture corresponding to the secondary depth layer under the jth collection point; j is the soil moisture corresponding to the third depth layer under the jth collection point; H1 is the moisture weight factor corresponding to the first depth layer, H2 is the moisture weight factor corresponding to the second depth layer, and H3 is the moisture weight factor corresponding to the third depth layer, where the value of each weight factor is between 0 and 1. The corrected humidity assessment coefficients at all levels calculated by the above formula are used as new humidity assessment coefficients for subsequent operations in other steps.

[0040] S3, calculate the salinity control factor based on the salinity assessment coefficient, calculate the humidity control factor based on the humidity assessment coefficient, and obtain the final water-fertilizer control value through the salinity control factor and the humidity control factor. Specifically, the salinity assessment coefficients at all levels, the humidity assessment coefficients at all levels or the corrected salinity assessment coefficients at all levels, the corrected humidity assessment coefficients at all levels and other data determined above are transmitted to the water-fertilizer control module via wireless communication, and the water-fertilizer control module analyzes and controls the water-fertilizer state according to the received data information.

[0041] In this embodiment, the operation process of the water and fertilizer control module is: the theoretical values ​​of water and fertilizer regulation corresponding to each depth layer are stored in the storage database in advance. It should be noted that the theoretical values ​​of water and fertilizer regulation can be obtained based on actual experience or obtained and set through other channels. Among them, water and fertilizer refer to the amount of fertilizer and the amount of watering, and the corresponding ratio between the amount of fertilizer and the amount of watering can also be obtained based on actual experience or obtained and set through other channels. This is an existing conventional means and will not be elaborated on here. The water and fertilizer control module calculates the soil salinity control factor and the soil moisture control factor according to the received data, wherein the corresponding relationship between the data range of each control factor and each water and fertilizer control theoretical value is stored in advance in the storage database. Specifically, when the soil salinity control factor and the moisture control factor both fall into the pre-stored corresponding control factor data range, there is no need to control the water and fertilizer of the rice area to be detected, that is, the current water and fertilizer meet its corresponding growth conditions; if any of the soil salinity control factor or the moisture control factor does not fall into the corresponding pre-stored salinity control factor and moisture control factor data range, the corresponding calculated salinity control factor and / or moisture control factor is multiplied with the corresponding stored water and fertilizer control theoretical value to obtain a reference water and fertilizer control value, and the reference water and fertilizer control value is used as the final water and fertilizer control value for control. It should be noted that each depth layer corresponds to a water and fertilizer control theoretical value, and a water and fertilizer control theoretical value corresponds to a salinity control factor range and a moisture control factor range.

[0042] In some embodiments, the calculation process of the salinity control factor is: B =B×λ B Where S B is the salinity control factor, and B is the salinity assessment coefficient of each depth layer. It should be noted that B includes B1, B2, B3 before correction and B1′, B2′, B3′ after correction. The calculation is performed according to the actual received situation. For example, when the assessment coefficient output in the previous step is B1, B1 is brought into S B Replace B in the calculation formula; B is the salinity control weight factor, which takes a value of 0-1. Then the calculated S B The reference water-fertilizer regulation value is multiplied by the corresponding stored theoretical water-fertilizer regulation value, and the reference water-fertilizer regulation value is used as the final water-fertilizer regulation value for regulation.

[0043] In some embodiments, the calculation process of the humidity control factor is: D =D×λ D Where S Dis the humidity control factor, and D is the salinity assessment coefficient of each depth layer. It should be noted that D includes D1, D2, D3 before correction and D1′, D2′, D3′ after correction. The calculation is performed according to the actual received situation. For example, when the assessment coefficient output in the previous step is D1, D1 is brought into S D Replace D in the calculation formula; D is the humidity control weight factor, which takes a value of 0-1. Then the calculated S D The reference water-fertilizer regulation value is multiplied by the corresponding stored theoretical water-fertilizer regulation value, and the reference water-fertilizer regulation value is used as the final water-fertilizer regulation value for regulation.

[0044] It should be noted that when the soil salinity control factor and the humidity control factor do not fall within the corresponding pre-stored salinity control factor and humidity control factor data range, the S calculated by the above formula is B , S D The corresponding reference water and fertilizer control value is calculated by difference. If the difference is within the preset allowable range, any one of them is selected as the final water and fertilizer control value. If the difference is no longer within the preset allowable range, the larger of the two values ​​is selected as the final water and fertilizer control value.

[0045] S4. After the control is completed, detection is performed after a certain interval, and the rice growth image after water and fertilizer control corresponding to the designated rice saline-alkali land area is collected by the camera carried by the drone, and it is used as the second rice growth image. Among them, at least one-half of the rice saline-alkali land area in the rice planting area to be detected is obtained as the rice saline-alkali land area to be designated. In addition, considering that there may be differences in sparse rice planting, in order to reduce the error caused by this situation, it is necessary to set the one-half rice saline-alkali land area, at least two-thirds of which is the area occupied by rice, and the rest of the area is the area where rice is not planted.

[0046] S5. Compare the second rice growth image with the first rice growth image. If the second rice growth image is consistent with the rice growth trend, it indicates that the water-fertilizer control effect is good or obvious, and the early warning module will display the first early warning screen. For example, the first early warning screen may be: the rice planting is growing well, the salinity is such and such, the humidity is such and such, and the parameters continue to be maintained; if the second rice growth image is not consistent with the rice growth trend, it indicates that the water-fertilizer control effect is poor or not obvious, and the early warning module will display the second early warning screen. For example, the second early warning screen may be: an alarm is issued, the rice planting is not growing well, the salinity is such and such, the humidity is such and such, timely regulation is required, and the recommended regulation parameters are such and such; it should be noted that the rice growth trend may be determined by summarizing actual planting experience or by other means.

[0047] Example 2

[0048] The control method in this embodiment is implemented on a set of control devices, which are provided with a control system, a saline-alkali land detection module, a data analysis module, a water-fertilizer control module, a monitoring and comparison module, an early warning module and a storage database. The control system controls the saline-alkali land detection module, the data analysis module, the water-fertilizer control module, the monitoring and comparison module and the early warning module. Furthermore, the control system transmits information with the saline-alkali land detection module, the data analysis module, the water-fertilizer control module, the monitoring and comparison module and the early warning module through communication. The saline-alkali land detection module is connected to the data analysis module, the data analysis module is connected to the water-fertilizer control module, the water-fertilizer control module is connected to the early warning module, and the database is connected to the data analysis module, the water-fertilizer control module and the monitoring and comparison module respectively.

[0049] In this embodiment, the early warning module will analyze the monitoring data and detect poor water and fertilizer control effects. If an abnormality is found, the early warning module will issue an alarm, for example, by sound or flashing lights, to immediately notify the administrator. After receiving the early warning, the administrator will take corresponding measures according to the early warning information and adjust the water and fertilizer supply.

[0050] By setting up an early warning module, establishing a complete monitoring system and fault warning mechanism, analyzing the water and fertilizer control effects corresponding to the designated grape saline-alkali land, and constantly detecting and feedback the dynamic changes of the soil environment, and by monitoring the soil salinity and humidity parameters, the water and fertilizer control system can accurately regulate and optimize the water and fertilizer supply, and provide timely reminders and adjustments, thereby promoting rice growth and increasing its yield.

[0051] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions of the technical solution of the present invention by ordinary technicians in this field do not deviate from the essence and scope of the technical solution of the present invention.

Claims

1. A method for precise control of water and fertilizer for rice planting in saline-alkali land, characterized in that: The following steps are included: S1. Detecting soil salinity and soil moisture data of a rice-growing area to be detected based on a set saline-alkali land detection module, and collecting a rice growth image corresponding to the saline-alkali land in the rice-growing area to be detected at the same time point as a first rice growth image; S2. The saline-alkali land detection module transmits the detected soil salinity data to the salinity analysis module, and transmits the soil moisture data to the moisture analysis module; after analysis by the salinity analysis module and the moisture module, the salinity assessment coefficient and the moisture assessment coefficient of each depth layer are obtained; S3, calculating the salinity control factor based on the salinity assessment coefficient, calculating the humidity control factor based on the humidity assessment coefficient, and obtaining the final water and fertilizer control value through the salinity control factor and the humidity control factor; S4, after the water and fertilizer control value is adjusted, a rice growth image corresponding to the designated rice saline-alkali land area after the water and fertilizer control is collected and used as a second rice growth image; S5. Compare the second rice growth image with the first rice growth image. If the second rice growth image is consistent with the rice growth trend, it indicates that the water and fertilizer control effect is good, and the early warning module will display the first early warning screen. If the second rice growth image is not consistent with the rice growth trend, it indicates that the water and fertilizer control effect is poor, and the early warning module will display the second early warning screen. The control of water and fertilizer for rice planting is achieved through the first early warning screen or the second early warning screen.

2. The method for precise water and fertilizer control for rice planting in saline-alkali land according to claim 1, characterized in that: In S1, soil salinity data corresponding to each collection point in each corresponding depth layer at a corresponding time point is collected by a soil salinity detector, and soil moisture data corresponding to each collection point in each corresponding depth layer at the same time point is collected by a soil moisture sensor; wherein the depth layer to be detected is provided with at least a primary depth layer, a secondary depth layer and a tertiary depth layer; and a number of collection points are arranged at a certain interval in the rice planting area to be detected.

3. The method for precise water and fertilizer control for rice planting in saline-alkali land according to claim 1, characterized in that: In S2, the salinity analysis module is provided with a first data storage and calculation module, and the first data storage and calculation module stores standard soil salinity data corresponding to each collection point collected in the first-level depth layer, standard soil salinity data corresponding to each collection point collected in the second-level depth layer, and standard soil salinity data corresponding to each collection point collected in the third-level depth layer, and performs a difference calculation between the actual soil salinity data of the corresponding depth layer received and the standard soil salinity data of the corresponding depth layer.

4. The method for precise water and fertilizer control for rice planting in saline-alkali land according to claim 3, characterized in that: In S2, the salinity analysis module is also provided with a first data evaluation module, in which the first data evaluation module stores an allowable error value A1 corresponding to the first-level depth layer, an allowable error value A2 corresponding to the second-level depth layer, and an allowable error value A3 corresponding to the third-level depth layer; and the error value A1 corresponds to a preset first-level salinity assessment coefficient B1, the error value A2 corresponds to a preset second-level salinity assessment coefficient B2, and the error value A3 corresponds to a preset third-level salinity assessment coefficient B3.

5. The method for precise water and fertilizer control for rice planting in saline-alkali land according to claim 4, characterized in that: In S2, when the salinity-related data needs to be corrected, the calculation process of the salinity analysis module after receiving the corresponding soil salinity data is: Where Y i is the soil salinity correction coefficient of the i-th level depth layer, i = 1, 2, 3; x i is the soil salinity actually detected at the i-th depth layer; X i is the preset standard soil salinity at the i-th depth layer, i = 1, 2, 3; B1′ is the corrected first-level salinity assessment coefficient; B2′ is the corrected second-level salinity assessment coefficient; B3′ is the corrected third-level salinity assessment coefficient; A1 j A2 is the soil salinity corresponding to the next depth layer of the jth collection point; j A3 is the soil salinity corresponding to the secondary depth layer under the jth collection point; j is the soil salinity corresponding to the third depth layer under the jth collection point; K1 is the salinity weight factor corresponding to the first-level depth layer, K2 is the salinity weight factor corresponding to the second-level depth layer, and K3 is the salinity weight factor corresponding to the third-level depth layer, where the value of each weight factor is between 0 and 1.

6. The method for precise water and fertilizer control for rice planting in saline-alkali land according to claim 1, characterized in that: In S2, a second data storage and calculation module is provided in the humidity analysis module, which stores standard humidity analysis data corresponding to each collection point collected in the first-level depth layer, standard humidity analysis data corresponding to each collection point collected in the second-level depth layer, and standard humidity analysis data corresponding to each collection point collected in the third-level depth layer, and performs a difference calculation between the actual humidity analysis data of the corresponding depth layer received and the standard humidity analysis data of the corresponding depth layer.

7. The method for precise water and fertilizer control for rice planting in saline-alkali land according to claim 6, characterized in that: In S2, a second data evaluation module is provided in the humidity analysis module, and the second data evaluation module stores the allowable error value C1 corresponding to the first-level depth layer, the allowable error value C2 corresponding to the second-level depth layer, and the allowable error value C3 corresponding to the third-level depth layer, wherein the error value C1 corresponds to the preset first-level humidity evaluation coefficient D1, the error value C2 corresponds to the preset second-level humidity evaluation coefficient D2, and the error value C3 corresponds to the preset third-level humidity evaluation coefficient D3.

8. The method for precise water and fertilizer control for rice planting in saline-alkali land according to claim 7, characterized in that: When soil moisture related data correction is required, the calculation process of the humidity analysis module after receiving the corresponding soil moisture data is as follows: Where P i is the soil moisture correction coefficient of the i-th level depth layer, i = 1, 2, 3; C i is the soil moisture actually detected at the i-th depth layer; T i The preset standard soil moisture for the i-th depth layer; D1′ is the corrected first-level humidity assessment coefficient; D2′ is the corrected second-level humidity assessment coefficient; D3′ is the corrected third-level humidity assessment coefficient; C1 j C2 is the soil moisture corresponding to the next depth layer of the jth collection point; j C3 is the soil moisture corresponding to the secondary depth layer under the jth collection point; j is the soil moisture corresponding to the third depth layer under the jth collection point; H1 is the moisture weight factor corresponding to the first depth layer, H2 is the moisture weight factor corresponding to the second depth layer, and H3 is the moisture weight factor corresponding to the third depth layer, where the value of each weight factor is between 0 and 1.

9. The method for precise water and fertilizer control for rice planting in saline-alkali land according to claim 1, characterized in that: In S3, The calculation process of salinity control factor is: S B =B×λ B Where S B is the salinity control factor, B is the salinity assessment coefficient of each depth layer, λ B is the weight factor for salinity control, with a value of 0-1; The calculation process of humidity control factor is: S D =D×λ D Where S D is the humidity control factor, D is the salinity assessment coefficient of each depth layer, λ D It is the humidity control weight factor, and its value range is 0-1.

10. A precise water and fertilizer control device for rice planting in saline-alkali land, characterized by: A method for precise water and fertilizer control for rice planting in saline-alkali land according to any one of claims 1 to 9, comprising a control system, a saline-alkali land detection module, a data analysis module, a water and fertilizer control module, a monitoring and comparison module, an early warning module and a storage database, wherein the control system controls the saline-alkali land detection module, the data analysis module, the water and fertilizer control module, the monitoring and comparison module and the early warning module; The saline-alkali land detection module is connected to the data analysis module, the data analysis module is connected to the water and fertilizer control module, the water and fertilizer control module is connected to the early warning module, and the storage database is respectively connected to the data analysis module, the water and fertilizer control module, and the monitoring and comparison module.

Images