AI and agriculture: AI turned into an agricultural "doctor" to ask about crop diseases and insect pests
等领域。 The application of AI recognition technology is further expanding from face recognition and animal recognition to crop pest detection and other fields. How does the AI recognition technology detect pests and diseases, and how accurate is it? What are the application difficulties? In the agricultural field, what other applications can AI have?
In agricultural production , the use of pesticides has also increased dramatically. Pesticide residues not only cause social problems, but also worsen environmental pollution. Therefore, accurate disease identification of crops and recommendation of appropriate control measures to create a "doctor" who can see the doctors of plants can save the life of crops, reduce the use of pesticides and ensure the yield of crops.
The combination of AI and agricultural pests and diseases first requires the establishment of a data set of pests and diseases, and secondly requires the cooperation of machine learning and image recognition system technology, and ensures the penetration rate of farmers' use of smart phones, so that the technology can be quickly and effectively communicated.
AI monitoring of pests and diseases mainly refers to the use of machine learning, computer vision and other technologies, using specific computer algorithms and models to mine the spectrum or image signals of agricultural pests and diseases to obtain effective data characteristics, and to realize real-time identification and identification of pests and diseases. process.
In the past, the inspection of diseases and insect pests required manual inspection, and if it was not found in time, it would easily lead to the death of large crops. Through the introduction of AI image recognition technology, it can continuously take pictures and compare, provide continuous monitoring and forecasting, and save a lot of labor costs.
可以帮助农民从田地里分析数据 AI can help farmers analyze data from the fields
If people from the rural areas know that before the crops are suitable for planting, we need to do a lot of preliminary work, such as analyzing which land is suitable for cultivation, how the soil is sent, which land is suitable for which crops, etc. Early considerations, and the results are only conclusions drawn from years of farming experience, without actual scientific data as the basis, so there is often a large gap in harvesting conditions and economic benefits.
However, AI technology will greatly improve crop production efficiency and economic benefits in this regard. In the intelligent analysis system for agricultural production such as soil analysis, the widely used technology is artificial neural network (ANN for short), which will simulate human brain neurons and realize the simplification, abstraction and simulation of the human brain system to analyze the characteristics of soil properties. And establish a correlation model with suitable crop varieties. Use non-invasive radar imaging technology to detect soil property characteristics, and to obtain information about the clay content of the soil surface layer by analyzing the signals obtained by electromagnetic induction soil sensors . 的农作物，提高农作物的生产效率和经济效益。 Therefore, it is determined that the corresponding soil is suitable for suitable crops, and the production efficiency and economic benefits of the crops are improved.
可以帮助农民有效解决传统的农作物维护过程 AI can help farmers effectively solve traditional crop maintenance processes
In the traditional crop maintenance process, we will often irrigate and fertilize the crops at regular intervals. In the process, crops are often lost due to excessive irrigation and fertilization, especially for farmers who have no experience in crops.
AI technology will help farmers choose the right water source and fertilizer to irrigate crops, fertilize them, ensure the water consumption and fertilization of crops, and greatly reduce the adverse impact of irrigation problems on crop yields.
The use of artificial intelligence technology for intelligent weed identification spray systems has been developed in agriculture for many years. 测距等技术可以精确控制喷头位置及用药量。 AI technology can realize weeds real-time identification based on color difference components and color characteristics, extract its related characteristic parameters, and cooperate with technologies such as superb distance measurement to accurately control the nozzle position and dosage. The application of this technology can greatly improve the economics of herbicides and is also very beneficial to the protection of the environment.
Prospects for future development of crops
AI crop disease detection is only a small aspect of AI in agricultural applications, and its application fields are very wide. For example, the agricultural expert system , which can also be called agricultural intelligent system, is a computer system with a large amount of agricultural expertise and experience. The application of AI technology can make reasoning and judgment based on special domain knowledge and experience provided by one or more agricultural experts , and simulate agricultural experts to make decisions on a complex agricultural problem.
Another example is non-destructive testing of agricultural products, which uses physical and chemical reaction changes caused by the external characteristics and internal structure of the test object without damaging the test object, to detect changes in its nature and quantity. It is mainly used for fruits, vegetables , livestock, Detection and classification of aquatic products, cash crops and cereal grains. With the development of non-destructive testing technology, AI technology will play an increasingly important role in the non-destructive testing of agricultural products. Intelligent farmland climate prediction system, that is, by intelligently identifying and analyzing photos taken by satellites, aerial photos, and other equipment between farmland, AI can accurately predict weather, climate disasters, identify soil fertility, and crop health.
The floor-type application of AI crops before and during production, in fact, AI also plays an important role in post-production. For example, a magnetic robotic claw that can be used to transport agricultural products can carry various shapes of agricultural products such as carrots and grapes. And the magnetic robot gripper can work quickly and accurately without damaging any product. It avoids the time problems and the risk of accidental scratches and damage caused by our traditional manual picking methods.
Although AI has an important role in the development of agriculture and has a very broad prospect, the application of AI to agricultural technology is currently in its basic stage. On the road of applying AI to agriculture, much more needs to be done. In addition, AI belongs to a brand-new technology application, which belongs to the early stage of development, and has not fully spread.
Therefore, for the development of AI in the future, continuous technical guidance and the popularization of related knowledge are still needed. The method of verification is time. Researchers are required to combine new intelligent technologies and hope to serve thousands of farmers at an early date.