AI in agricultural:

Artificial intelligence (AI) is a growing technology that can improve agricultural operation in many ways, including:

Crop yield:

AI can help identify the best times to plants, which crop varieties to use, and how to fertilize, leading to higher yields. crop yield means harvested production per unit of harvested area for crop products. in the most of the cases yield data are not recorded but obtained by dividing the production data by the data on area harvested.

Resource efficiency:

AI can reduce the amount of water, fertilizer, pesticides, and herbicides used, which can help mitigate the effect of climate change.

Sustainability:

AI can help improve the sustainability of farming practices by reducing the use of fertilizers and pesticides. sustainability agriculture is farming in such way to protect the environment, aid and expand natural resources and to make the best use of nonrenewable resources.

Real-time monitoring: 

AI can help monitor crops in real time, including detecting and nutritional deficiencies. real-time monitoring in agricultural is the used of sensors, drones, and weather stations to collect and analyze data in real-time to help farmers make decisions about their crops. this data can help farmers improves crop production , make better use of resources, and minimize environment mental impact.

Automated system:

AI- powered system can help automate tasks like weed control, irrigation, and grading crops. automated agricultural is the use of technology to improving agricultural operations by reducing manual labor and making farming more efficient.

Robots:

Robots can be equipped with navigation system to follow a set route without human supervision. they can perform task like weeding and harvesting.

Drones:

Drones can monitor crops and provide data to framers.

Self-driving tractors:

These tractors can plants seeds, apply fertilizers, and spray. they can also collect data about soil conditions, crop health, and yield potential.

Supply chain and demand forecasting:

• AI can help forecast supply chain and demand.
• Some example of AI applications in agricultural include:
• Crop mapping.
• Yield analysis.
• Livestock health monitoring.
• Predictive analysis for crop yield. 
• Automated wed control system.
• Precise irrigation system.