Digital irrigation refers to the use of sensors, wireless communication, automatic control, and other means through digital technology
Achieve precision irrigation of farmland. Field digital irrigation includes the following basic contents:
Construction of data collection means. Soil moisture sensor, meteorological data sensor, image recognition technology and establishment of facilities for crop growth stage.
Construction of crop digital twin model. Based on the crop growth mechanism, the crop digital model and its parameter modification method, the parameters calculated by the model are adjusted by the output state quantity,
and a twin digital model approximating the real crop growth process is established on the basis of a large amount of data.
Optimization decision-making method of irrigation and fertilization.
The decision of fertilization and irrigation is made by using the crop twinning digital model, and the decision of when to irrigate, how much water to irrigate, when to fertilize and what kind of fertilizer to apply is made through big data analysis and optimization method.
The application of digital technology can not only improve the accuracy and efficiency of farmland irrigation, but also save water resources, reduce environmental pressure, and improve the yield and quality of farmland.
(Only the field application part is introduced here, not the intelligent irrigation content in the irrigation area).
The foundation of digital technology is sensor technology. Sensors in farmland can measure soil temperature, humidity, pH value, salinity, soil water content and other information, and upload these data to the cloud.
Through the analysis and processing of these data, precision irrigation of farmland can be achieved.
In this way, every piece of land in the farmland can get an accurate water supply, thus providing good growth conditions for crops.
The application of digital technology can not only achieve efficient farmland management, but also save water resources to a certain extent.
In traditional farmland irrigation, due to inaccurate manual operation and lack of comprehensive data support, farmers often irrigate the farmland in the way of “flood irrigation”, resulting in a large amount of waste.
Digital irrigation uses high-precision sensors and control systems, which can set reasonable irrigation schemes according to the water demand, temperature and humidity of each crop, thus avoiding the waste and excessive use of water resources.
The advantages of digital irrigation are not only in water saving. Due to the excellent characteristics of sensor technology, digital irrigation can also fully reflect the advantages of automatic control and completely solve the problem of farmers’ overwork.
Traditional farmland irrigation is a manual operation, which requires farmers to get up in the morning, turn on/off the switches, water pumps, etc.
on the land from door to door. With the adoption of digital irrigation technology, farmers can remotely master the status of each field through the cloud-based control system, and set reasonable irrigation schemes, so that farmers can achieve efficient and safe farmland irrigation in less time and labor.
Intelligent irrigation decision-making is mainly realized by using mathematical models and data analysis methods. The following are the basic steps to implement intelligent irrigation decision-making:
- Data collection: collect soil moisture, meteorological data, evapotranspiration, crop data and other indicators through sensors.
- Data preprocessing: analyze and preprocess the collected data, remove outliers and noises, and carry out data cleaning, data smoothing and other processing to make the data more accurate.
- Establishment of model: select a suitable general crop growth simulation model, establish a mathematical model to describe the crop growth process and soil water change law, and infer and modify the parameters of the crop model according to the state quantity collected by the model
data and its observation value, and make irrigation optimization decisions basis on the calibrated model, that is, when and how much water is input, so that the crop can achieve higher yield or lower water and fertilizer requirements. - Model verification: use historical data or measured data to verify the model and test the accuracy and reliability of the model.
- Model optimization: according to the results of model validation, modify the parameters of crop model, further improve the model algorithm, and improve the accuracy and precision of the model.
- Intelligent decision implementation: intelligent irrigation decision is made through automatic control system using the results of model prediction and decision analysis. According to the predicted results of the model, automatically control the opening and closing of water pump or solenoid valve and other equipment to realize automatic irrigation control.
- Feedback adjustment: Through continuous data collection and model prediction, intelligent irrigation decisions and crop models are constantly adjusted to achieve more accurate irrigation decisions.
Digital irrigation and its intelligent irrigation decision-making application have significant economic and social benefits. Using digital irrigation technology can improve the quality and yield of crops, thus increasing farmers’ income. When farmers irrigate their farmland, they do not have to walk around many times by relying on the automatic control system, which can save a lot of time and labor costs, so they can do other work and improve the utilization efficiency. In terms of environment, the application of digital irrigation technology, especially the decision system based on the crop growth model, can reduce the amount of fertilizer and pesticide used in farmland, reduce the pollution of chemicals to groundwater, rivers and other environments, and is conducive to environmental protection and people’s ecological health.
In short, through the establishment of mathematical models and data analysis, intelligent irrigation decision-making can be realized, and agricultural production efficiency and water resource utilization efficiency can be improved. The digital irrigation technology based on crop twinning model is a new agricultural planting production mode, which has a wide range of applications and has a huge potential for increasing production and income. In future development, digital irrigation technology can also be combined with cloud computing, The Internet of Things, artificial intelligence and other new technologies to form a more efficient and intelligent agricultural production mode and bring greater innovation value to agricultural development.
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Let’s See how chatGPT gives the source code of its irrigation decision
Write a small program for irrigation decision based on soil water content.
include
int main(void)
{
int soil_ moisture; // soil moisture content
Printf (“Please input soil water content (0-100):”);
scanf(“%d”, &soil_moisture);
if (soil_moisture > 80)
{
Printf (“No irrigation required. n”);
}
else if (soil_moisture > 65)
{
Printf (“Deep irrigation is recommended. n”);
}
else if (soil_moisture > 40)
{
Printf (“Shallow irrigation is recommended. n”);
}
else
{
Printf (“It is recommended to conduct deep irrigation and fertilization. n”);
}
return 0;
}
Write a small program for irrigation decision based on crop model.
include
int main()
{
int current_ weather; // Define the current weather variable
int current_ soil; // Define the current soil condition variables
int irrigation_ decision; // Define irrigation decision variables
Printf (“Please enter the current weather (1: sunny, 2: cloudy, 3: rainy): n”);
scanf(“%d”, ¤t_weather); // Get the current weather conditions
Printf (“Please enter the current soil condition (1: wet, 2: normal, 3: dry): n”);
scanf(“%d”, ¤t_soil); // Obtain the current soil condition
/Make irrigation decisions based on current weather and soil conditions/
if (current_weather == 1 && current_soil == 3)
{
//Sunny+dry, need irrigation
irrigation_ decision = 1;
}
else if (current_weather == 3 && current_soil == 1)
{
//Rainy+wet, no irrigation required
irrigation_ decision = 0;
}
else
{
//Other situations, adjust according to the current situation
Printf (“Please determine whether irrigation is needed according to the current weather and soil conditions: n”);
scanf(“%d”, &irrigation_decision);
}
Printf (“Irrigation decision:% d n”, irrigation_decision);
return 0;
}