AI + agtech is the combination of artificial intelligence and agricultural technology.
Examples…
Crop Management: AI can analyze data from satellites, drones, computer vision, and Internet of Things (IoT) sensors to monitor crop health, growth, and nutrient levels.
Precision Agriculture: AI can help optimize resource usage in agriculture by providing insights on the optimal amount of water, fertilizers, and pesticides required for specific areas of farmland.
Prediction: AI can analyze historical and real-time data, such as weather conditions and soil quality, to predict crop yields, enabling farmers to plan their harvest and optimize logistical operations.
Autonomous Farming: AI-powered robots and drones can perform tasks such as planting, harvesting, irrigation, rotation, and crop monitoring autonomously.
Pest and Disease Detection: AI can identify and detect pests, diseases, and weeds in crops by analyzing images and sensor data. AI can alert farmers for early detections and targeted interventions.
Supply Chain Optimization: AI can assist in optimizing the agricultural supply chain by analyzing data on logistics, transportation costs and capabilities, and market demand and dynamics.