In the agricultural industry, AI is currently being used to help with crop monitoring, irrigation management, and yield prediction. In the future, AI could be used for even more advanced tasks such as creating personalized planting schedules for individual farmers, identifying diseases in crops and recommending remedies, and sorting and grading fruits and vegetables. By automating these processes, AI can help farmers become more efficient and increase their yields. Additionally, by reducing the amount of human error involved in these tasks, AI can help to improve the quality of agricultural products. Let’s go into detail about the role of AI used in agriculture:
Crop monitoring: AI is currently being used to help farmers monitor their crops by analyzing images and video footage of fields. By doing this, AI can identify issues such as pests or diseases and provide information on how to deal with them. For example, in 2017, a startup named Blue River Technology created a machine learning system that can identify weeds in a field and automatically remove them. This technology can save farmers time and money as it eliminates the need for manual weeding.
Irrigation management: In areas with a shortage of water, AI can be used to help farmers optimize their irrigation schedules. For example, MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has developed AquaGenius, which can optimize irrigation schedules based on weather forecasts and soil moisture levels. This system can save farmers up to 30% of the water they normally use without affecting crop yields.
Yield prediction: AI is also being used to predict yields for different crops. By doing this, farmers can plan their production schedule accordingly and ensure that they have enough supply to meet demand. For example, IBM’s Watson Studio can predict corn yields with an accuracy of up to 95%. This information can be valuable for farmers who want to avoid over-or under-production.
Personalized planting schedules: In the future, AI may create personalized planting schedules for individual farmers. This would involve collecting data on the climate, soil, and crops of a particular area and creating a schedule that would optimize yields. For example, the startup Farmers Business Network is currently working on a project called “Precision Planting,” which aims to do exactly this.
Disease identification: AI can also identify diseases in crops and recommend remedies. For example, the startup Granular has developed a system to detect diseases in corn plants and recommend treatments. This system can achieve an accuracy of up to 95%.
Fruit and vegetable sorting: Finally, AI can also be used to sort and grade fruits and vegetables. This is done by analyzing the product’s size, shape, and color. For example, the startup robotics company Soft Robotics has developed a system that automatically grades strawberries. By doing this, AI can help to ensure that fruits and vegetables are of consistent quality.
As you can see, AI used in agriculture is playing an increasingly important role in the agricultural industry. It is helping farmers to become more efficient and reduce human error. It may be used to do even more advanced tasks such as creating personalized planting schedules and identifying diseases in crops.
Leave a Reply