Intelligent adjustment irrigation system and method based on infrared spectrum

Abstract

The invention discloses an intelligent adjustment irrigation system and method based on an infrared spectrum. The method comprises the steps of soil sample data collection, pretreatment, original spectrum characteristic data collection, optimal wavelength screening, irrigation data calibration and the like. According to the method, the relative moisture content of the soil is monitored in real time through the infrared spectrum, precise adjustment of irrigation is achieved in combination with the requirement of the plant growth cycle, and the problems such as excessive irrigation or insufficient irrigation in a traditional irrigation mode are avoided. The method has the advantages of improving irrigation accuracy, saving water resources, promoting healthy growth of crops, being high in adaptability and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural intelligent irrigation, and in particular to an intelligent regulating irrigation system and method based on infrared spectrum. Background Art

[0002] Traditional irrigation methods often rely on manual experience and timed irrigation, which is difficult to accurately reflect the actual moisture status of the soil, resulting in low irrigation efficiency and insufficient utilization of water resources, leading to waste of water resources. In recent years, although intelligent irrigation systems have gradually emerged, most systems still rely mainly on soil moisture sensors, lacking the ability to monitor and accurately adjust the actual status of the relative moisture content of various soils in real time. The present invention uses spectral sensor technology to monitor the relative moisture content of the soil in real time, and automatically make irrigation decisions based on real-time monitoring data. The present invention provides an intelligent adjustment irrigation system and method based on infrared spectroscopy. Summary of the invention

[0003] The purpose of the present invention is to provide an intelligent irrigation adjustment system and method based on infrared spectroscopy, which automatically makes irrigation decisions by real-time monitoring of soil relative moisture content through spectroscopy, so as to achieve precise irrigation, reduce water resource waste, improve irrigation efficiency and reduce costs.

[0004] In order to achieve the above-mentioned purpose and solve the technical problems, the present invention is implemented by the following technical solutions:

[0005] The present invention discloses an intelligent regulation irrigation system based on infrared spectrum, comprising a spectrum sensor, a control unit, an irrigation module, and a power supply module, wherein:

[0006] The spectral sensor includes infrared wavelengths and is used to collect raw spectral characteristic data of soil relative moisture content.

[0007] The control unit receives data from the sensor, performs real-time processing and analysis, and determines the irrigation start point and irrigation end point.

[0008] The irrigation module includes a solenoid valve whose switch is controlled by a control unit. The switch is connected to a water source. Irrigation starts when the switch is turned on and ends when the switch is closed.

[0009] The power supply module is electrically connected to the main control module and is used to provide working power for the entire system.

[0010] The present invention further discloses an intelligent irrigation adjustment method based on infrared spectroscopy, which uses the above device for detection and includes the following steps:

[0011] Step 1: To achieve the purpose of intelligent irrigation, soil sample data must be collected first, the optimal wavelength is selected and the model is trained based on the collected data, the soil relative moisture content is determined based on the optimal wavelength, and finally the relative moisture content and the preset relative moisture content are used to determine whether irrigation should be performed and the irrigation end point.

[0012] Step 2: The soil sample in step 1 needs to be pre-processed before data collection can begin. The pre-processing includes:

[0013] Spread the soil sample without foreign matter flat in the oven, dry it at 105℃±5℃ for 12 hours, take it out and put it in the desiccator to cool for about 45 minutes and then weigh it. If the sample is not dry yet, continue to spread it flat in the oven at 105℃±5℃ and dry it for 1 hour. Repeat several times until the sample has a constant weight.

[0014] Step 3: To achieve the purpose of intelligent irrigation, collect the original spectral characteristic data of the soil that has been pre-treated in step 2. The specific collection method is as follows:

[0015] ①Put the pre-treated constant weight dry soil in a beaker, insert the spectral sensor into the soil, adjust the depth according to different plants, and collect a piece of original spectral feature data.

[0016] ② Mix the soil in the beaker and irrigate it with water, and collect the original spectral feature data in real time until water overflows from the surface, then stop collecting and watering.

[0017] Step 4: Perform optimal wavelength screening and model training for the original spectral data collected in step 3. The specific operations are as follows:

[0018] ① The optimal wavelength is the wavelength with the best linear effect, the lowest signal-to-noise ratio, and the phase correlation coefficient closest to 1 in the visualization of the original spectral feature data collected in step 3, and then it is extracted as the optimal wavelength.

[0019] ② Train the linear regression model with the optimal wavelength original spectral data.

[0020] Step 5: Calibrate the irrigation data based on the original spectral data collected in step 3 and the model trained in step 4. The specific operations are as follows:

[0021] ① According to the original spectral characteristic data of constant weight dry soil collected in step 3, the relative moisture content is 0%, and according to the original spectral characteristic data collected in step 3 when there is a little water overflowing from the surface, the relative moisture content is 100%.

[0022] ② According to the relative water content required by the plant growth cycle, the control module is written as the irrigation end point. When the model predicts that the relative water content is 10% lower than the irrigation point, the control unit opens the solenoid valve to start irrigation. When the model predicts that the relative water content reaches the irrigation end point, the control unit closes the solenoid valve to stop irrigation.

[0023] The beneficial effects of the present invention are:

[0024] 1. Improve irrigation accuracy: Real-time monitoring of soil relative moisture content through infrared spectroscopy, combined with the needs of plant growth cycle, to achieve precise adjustment of irrigation, avoiding over-irrigation or under-irrigation problems in traditional irrigation methods.

[0025] 2. Save water resources: Precision irrigation can effectively reduce the waste of water resources, improve irrigation efficiency and reduce irrigation costs.

[0026] 3. Promote the healthy growth of crops: Irrigation according to the actual growth needs of crops can provide suitable moisture conditions, promote the healthy growth of crops, and increase crop yields and varieties.

[0027] 4. Strong adaptability: Through temperature compensation adjustment, the influence of ambient temperature on infrared spectrum detection results can be eliminated, improving the adaptability and accuracy of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0029] Figure 1 A flow chart of an intelligent irrigation system and method based on infrared spectrum

[0030] Figure 2 Visualization effect diagram of original spectral characteristic data of soil relative moisture content DETAILED DESCRIPTION

[0031] The following will clearly and completely describe and discuss the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings of the present invention. Obviously, what is described here is only a part of the examples of the present invention, not all the examples. 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.

[0032] In order to achieve precision irrigation, it can effectively reduce the waste of water resources, improve irrigation efficiency, promote the healthy growth of crops, and improve crop yield and quality. Figure 2 The present invention is described in detail, and its specific implementation steps are as follows:

[0033] Implementation example:

[0034] The present invention further discloses an intelligent irrigation adjustment method based on infrared spectroscopy, which uses the above device for detection and includes the following steps:

[0035] Step 1: To achieve the purpose of intelligent irrigation, soil sample data must be collected first, the optimal wavelength is selected based on the collected data, the soil relative moisture content is determined based on the optimal wavelength, and finally the relative moisture content and the preset relative moisture content are used to determine whether irrigation should be performed and the irrigation end point.

[0036] Step 2: The soil sample in step 1 needs to be pre-processed before data collection can begin. The pre-processing includes:

[0037] Spread the soil sample without foreign matter flat in the oven, dry it at 105℃±5℃ for 12 hours, take it out and put it in the desiccator to cool for about 45 minutes and then weigh it. If the sample is not dry yet, continue to spread it flat in the oven at 105℃±5℃ and dry it for 1 hour until the sample has a constant weight.

[0038] Step 3: To achieve the purpose of intelligent irrigation, collect the original spectral characteristic data of the soil that has been pre-treated in step 2. The specific collection method is as follows:

[0039] ① Place the pre-treated constant weight dry soil in a beaker, insert the spectral sensor into the soil, adjust the depth according to different plants (in this embodiment, the depth is selected as 6 cm below the soil), and collect a piece of original spectral feature data.

[0040] ② Mix the soil in the beaker and irrigate it with water, and collect the original spectral feature data in real time until water overflows from the surface, then stop collecting and watering.

[0041] Step 4: Screen the optimal wavelength for the original spectrum data collected in step 3. The specific operations are as follows:

[0042] ① The optimal wavelength is the wavelength with the best linear effect, the lowest signal-to-noise ratio, and the phase correlation coefficient closest to 1 in the visualization of the original spectral feature data collected in step 3, and then it is extracted as the optimal wavelength, such as Figure 2 .

[0043] ② Train the linear regression model with the optimal wavelength original spectral data.

[0044] Step 5: Calibrate the irrigation data based on the original spectral data collected in step 3 and the model trained in step 4. The specific operations are as follows:

[0045] ① According to the original spectral characteristic data of constant weight dry soil collected in step 3, the relative moisture content is 0%, and according to the original spectral characteristic data collected in step 3 when there is a little water overflowing from the surface, the relative moisture content is 100%.

[0046] ② According to the relative moisture content required by the plant growth cycle, the control module is written into the irrigation end point (the irrigation end point in this embodiment is 70% relative moisture content). When the model predicts that the relative moisture content is lower than 63%, the control unit opens the solenoid valve to start irrigation. When the model predicts that the relative moisture content reaches 70%, the control unit closes the solenoid valve to stop irrigation.

[0047] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the disclosure disclosed herein. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the appended claims.

[0048] It should be understood that the present disclosure is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure should be limited by the appended claims.

Claims

1. An intelligent irrigation system based on infrared spectrum, characterized in that: It includes a spectral sensor, a control unit, an irrigation module, and a power module, wherein: The spectral sensor includes infrared wavelengths and is used to collect raw spectral characteristic data of soil relative moisture content. The control unit receives data from the sensor, performs real-time processing and analysis, and determines the irrigation start point and irrigation end point. The irrigation module includes a solenoid valve whose switch is controlled by a control unit. The switch is connected to a water source. Irrigation starts when the switch is turned on and ends when the switch is closed. The power supply module is electrically connected to the main control module and is used to provide working power for the entire system.

2. An intelligent irrigation regulation method based on infrared spectrum, characterized in that: The detection is performed using the intelligent irrigation system based on infrared spectroscopy as described in claim 1, comprising the following steps: Step 1: To achieve the purpose of intelligent irrigation, soil sample data must be collected first, the optimal wavelength is selected and the model is trained based on the collected data, the soil relative moisture content is determined based on the optimal wavelength, and finally the relative moisture content and the preset relative moisture content are used to determine whether irrigation should be performed and the irrigation end point. Step 2: The soil samples mentioned in step 1 must be pre-processed before data collection can begin. Step 3: To achieve the purpose of intelligent irrigation, collect the original spectral characteristic data of the soil that has been pre-treated in step 2. Step 4: Perform optimal wavelength screening and model training on the original spectral data collected in step 3. Step 5: Calibrate the irrigation data based on the original spectral data collected in step 3 and the model trained in step 4.

3. According to the infrared spectrum-based intelligent irrigation adjustment method of claim 2, it is characterized in that: In the above step 2, the pre-processing includes: Spread the soil sample without foreign matter flat in the oven, dry it at 105℃±5℃ for 12 hours, take it out and put it in the desiccator to cool for about 45 minutes and then weigh it. If the sample is not dry yet, continue to spread it flat in the oven at 105℃±5℃ and dry it for 1 hour. Repeat several times until the sample has a constant weight.

4. According to the infrared spectrum-based intelligent irrigation regulation method of claim 2, it is characterized in that: In step 3 above, the specific collection method is as follows: ①Put the pre-treated constant weight dry soil in a beaker, insert the spectral sensor into the soil, adjust the depth according to different plants, and collect a piece of original spectral feature data. ② Mix the soil in the beaker and irrigate it with water, and collect the original spectral feature data in real time until water overflows from the surface, then stop collecting and watering.

5. According to the infrared spectrum-based intelligent irrigation adjustment method of claim 2, it is characterized in that: In step 4 above, the specific operations are as follows: ① The optimal wavelength is the wavelength with the best linear effect, the lowest signal-to-noise ratio, and the phase correlation coefficient closest to 1 in the visualization of the original spectral feature data collected in step 3, and then it is extracted as the optimal wavelength. ② Train the linear regression model with the optimal wavelength original spectral data.

6. According to the infrared spectrum-based intelligent irrigation regulation method of claim 2, it is characterized in that: In step 5 above, the specific operations are as follows: ① According to the original spectral characteristic data of constant weight dry soil collected in step 3, the relative moisture content is 0%, and according to the original spectral characteristic data collected in step 3 when there is a little water overflowing from the surface, the relative moisture content is 100%. ② According to the relative water content required by the plant growth cycle, the control module is written as the irrigation end point. When the model predicts that the relative water content is 10% lower than the irrigation point, the control unit opens the solenoid valve to start irrigation. When the model predicts that the relative water content reaches the irrigation end point, the control unit closes the solenoid valve to stop irrigation.

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