Within the agriculture industry, Artificial Intelligence (AI) is beginning to transform farming practices. The Food and Agriculture Organization (FAO) estimates that by 2050 overall food production needs to increase by 70 percent. Various technologies integrated into farming practices have made producing food more efficient. Agriculture experts work with innovators and farmers on these technologies as they work together to feed a rapidly growing population. Let’s explore how AI, Machine Learning and Data Analytics are influencing crop prediction and health monitoring.
Role of AI
Artificial intelligence is “replicating human intelligence in robots that resemble human cognition and behaviors, including learning and problem solving.” One example of AI on the farm is with the use of drone technologies that can monitor crops and detect any issues early on. Additionally, this technology can develop a plan of action to address the issue. AI monitors the health of crops by using algorithms measuring temperature and humidity to predict when pests may appear. This is beneficial to farmers because it prevents having to control pests after they invade and takes measures to prevent the pests before they damage crops. Smart sensors help manage the health of crops by measuring the exact amount of water a crop needs based on many factors such as light and moisture levels.
Machine learning is a result of AI, but through mathematical algorithms its purpose is to learn how to do something without being taught directly. Crop prediction has improved greatly with the use of machine learning. By taking historical data along with current weather patterns and other variables, machine learning can communicate the best time and place to plant certain crops. This not only decreases the number of lost crops, it also saves farmers money and increases overall productivity. Monitoring the health of crops and crop prediction has been made easier by machine learning. Agribusinesses are involved in the creation and implementation of these technologies in order to increase production and efficiency globally.
Making informed decisions on the farm is beneficial to every sector of the agriculture industry. Data analytics makes this possible by collecting data on weather patterns, optimal time for crop planting, yields, and monitoring the health of crops. This technology is crucial to farmers around the world to encourage the adoption of novel crop protection products like biologicals that will ultimately improve the health of crops. The market including data analytics is expected to reach $17B by 2025 highlighting its importance to agribusiness and the industry at large.
Artificial Intelligence, Machine Learning and data analytics will continue to play a huge role in the future of crop prediction and health monitoring. These technologies along with many other innovations are crucial in increasing food production, efficiency and profitability in the coming years. With agriculture being one of the oldest industries passing down practices throughout generations, making such radical changes can be challenging. Supporting farmers with sufficient education and funding to help with the implementation of such technologies is crucial. Ultimately, with the development of ground breaking technologies, the future of agriculture is positioned for success.