Artificial intelligence refers to intelligence that is simulated or implemented based on computer technology. The application of artificial intelligence in the field of agriculture is of great importance. At present, the application of artificial intelligence in the field of agriculture throughout the entire process of agricultural production, and gradually realize the automation and intelligent management of agricultural production, and effectively improve the quality and efficiency of agricultural production.
Irrigation control artificial intelligence in the agricultural production process can monitor the production environment in real time and regulate according to crop growth, such as crop intelligent irrigation, specifically means that through the analysis of crop water requirements can be irrigation water consumption control in the best situation, not only to meet the needs of crop growth in a certain period, but also to effectively reduce the amount of irrigation water, in order to save water resources while ensuring high crop yields and high harvests. In addition to analyzing and controlling the irrigation water consumption of crops, the intelligent irrigation control system can also use big data technology to analyze and process the water temperature and weather index and climate data of the region, so as to develop the best irrigation plan. In addition, when the intelligent irrigation system is connected with sensors and irrigation equipment, the soil water content can be monitored in real time, and the irrigation water requirement can be calculated accordingly to select the most suitable irrigation mode for crop irrigation.
Soil composition testing and analysis
In the process of agricultural production, soil condition is an important factor affecting crop yield, therefore, in the early stage of agricultural production and the process of planting and cultivating crops, it is necessary to test and analyze the soil composition, and determine the suitable crop varieties according to the analysis results, and then fertilize according to the soil composition test results in the process of crop growth, so that the soil structure is always controlled in the most suitable state for crop growth, so as to achieve the purpose of improving crop yield.
Pest and disease identification
Pests and diseases can affect the normal growth of crops and can even seriously reduce crop quality and yield. In the past, the detection of pests and diseases required manual inspection, which could lead to the death of large areas of crops if not detected in time. Manual inspection is time-consuming and labor-intensive, and there is a possibility of oversight. The introduction of artificial intelligence can provide uninterrupted monitoring and forecasting. Smart sensors use image sensing technology to detect disease characteristics of plant leaves and classify them according to differences in different pest parameters to build a database.
Harvesting of crops is labor-intensive and the efficiency of manual harvesting is low. Harvesting robots can use machine vision recognition technology to locate the fruits of agricultural products that need to be harvested, and determine the maturity of the fruits, and then use the corresponding harvesting tools to harvest after determining that the fruits are in a ripe state for harvesting.
Agricultural products quality inspection
After the production of agricultural products, quality inspection is required before the sale of agricultural products. The inspection work is usually carried out before the processing of agricultural products is completed but not yet put into storage. According to the inspection results, agricultural products can be classified and packaged according to the quality difference, and the intelligent inspection method can effectively improve the inspection efficiency and let the agricultural products enter the storage and sales stage as soon as possible. Intelligent inspection of agricultural products is completed by the robot arm with machine vision function, which scans and observes the agricultural products through the machine vision function and determines the quality of agricultural products through image processing and parameter comparison.
Agricultural products e-commerce operation
In the rapid development of e-commerce today, in addition to the traditional offline sales model, online sales of agricultural products is also a very important channel. Online sales of agricultural products rely on agricultural products e-commerce operations, which greatly broaden the sales channels of agricultural products. And the use of e-commerce logistics express channel for product circulation, its transport costs are lower. In addition, in the process of e-commerce operation, artificial intelligence technology and big data technology can be used to analyze the consumption behavior and habits of e-commerce customers, from which target customers can be excavated, followed by targeted agricultural product information push to improve the success rate of transactions, thus increasing sales and improving farmers' income.
In summary, artificial intelligence has a very wide range of applications in the whole process of agricultural production. With the continuous development of AI technologies, their application in the field of agriculture has been expanding, which not only effectively improves the efficiency of agricultural production, but also reduces the waste of resources in the process of agricultural production.