#AI #agriculture #cropdiseases #machinelearning #farming #technology #automation #cropmonitoring #diseasedetection
According to a report by Zion Market Research, the global market for AI in agriculture is expected to grow at a compound annual growth rate (CAGR) of 25.4% between 2021 and 2028. The report also reveals that AI-based crop monitoring systems and disease detection tools are among the most popular applications of AI in agriculture.
AI tools can help farmers detect crop diseases early and accurately, thereby reducing crop losses and increasing yields. For instance, researchers at Pennsylvania State University have developed an AI-based system that uses machine learning algorithms to detect diseases in apple trees. The system uses images of apple leaves to identify signs of disease, such as spots and discoloration.
Similarly, a team of researchers at the Indian Institute of Technology (IIT) Kharagpur has developed an AI-based system to detect diseases in potato crops. The system uses images of potato leaves to identify diseases such as late blight, early blight, and bacterial wilt.
In addition to disease detection, AI tools can also help farmers optimize irrigation and fertilization, predict weather patterns, and even automate harvesting. For instance, John Deere, a leading manufacturer of agricultural equipment, has developed an autonomous combine harvester that uses AI and machine learning algorithms to harvest crops with precision.
AI tools hold great promise for the future of farming. By detecting crop diseases early and accurately, optimizing resource usage, and automating farm operations, AI can help farmers increase yields and reduce costs. As AI technology continues to evolve, it is expected that more and more farmers will embrace it as an essential tool in their farming operations.
