AI is playing a transformative role in agriculture by improving efficiency, sustainability and productivity. Here are some key areas where AI is making an impact:

1. Precision Farming

AI powered sensors, drones and IoT devices help farmers monitor soil health, weather conditions and crop growth. This data enables precise decision making, reducing wastage of water, fertilizers and pesticides.

2. Smart Irrigation

AI driven irrigation systems analyze weather patterns, soil moisture and plant requirements to optimize water usage, ensuring efficient water management.

3. Pest and Disease Detection

AI models analyze images of crops to identify pests and diseases at an early stage. This allows farmers to take timely action and reduce yield losses.

4. Automated Machinery & Robotics

AI powered robots and drones assist in tasks like sowing, weeding, harvesting and spraying pesticides, reducing labor dependency and improving productivity.

5. Yield Prediction & Crop Monitoring

AI algorithms predict crop yields based on historical data, weather conditions and soil parameters. This helps farmers plan their harvest and manage supply chains effectively.

6. Supply Chain Optimization

AI assists in demand forecasting, logistics and pricing strategies, helping farmers and agribusinesses reduce post harvest losses and ensure fair pricing.

7. Livestock Monitoring

AI enabled wearables track animal health, movement and behavior, allowing farmers to detect diseases early and optimize breeding practices.

8. Soil and Nutrient Management

AI models analyze soil samples and recommend the right fertilizers and treatments to maintain soil fertility and enhance crop growth.

I think that AI can help agriculture Professional improving their efficiency, by collecting and treatment of data.

AI-based mobile apps and platforms provide smallholder farmers with access to information, markets, and financial services. AI is transforming agriculture by making it more data-driven, efficient, and sustainable. AI models predict the impact of climate change on agriculture and suggest adaptive strategies. AI-powered systems monitor livestock's health, behavior, and productivity using sensors and cameras. AI systems optimize irrigation schedules based on real-time data about soil moisture, weather forecasts, and crop water requirements. AI algorithms analyze images of crops to identify signs of pests or diseases. AI analyzes soil data (e.g., moisture levels, nutrient content) and crop health using sensors and imaging technologies. AI-driven robots and autonomous machinery perform tasks like planting, weeding, harvesting, and sorting. AI enables precision farming by analyzing data from sensors, drones, and satellites to optimize inputs like water, fertilizers, and pesticides.

Given the current state of the art, AI can help agriculture in various ways. For instance, using weather prediction coupled with smart systems to ensure that the crops are safe from natural disasters. Because these predictions can help in taking proactive measures for protection.

Moreover, smart apps, drones and wearables with AI can be used for automatic monitoring or even gathering health information of crops. Furthermore, these AI drones can help in disease detection of crops. They can send us alerts if anything serious is found.

I second Simranpreet’s answer.

Artificial Intelligence (AI) is revolutionizing agriculture by enhancing efficiency, sustainability, and productivity. One of its key contributions is precision farming, where AI analyzes soil conditions, weather data, and crop health to optimize planting, irrigation, and fertilizer use. Drones and satellites capture field images, while machine learning models process this data to inform farmers' decisions.

AI also plays a crucial role in crop monitoring and disease detection, using computer vision to identify pests, diseases, or nutrient deficiencies early, preventing significant crop losses.

Another major advancement is automated farming, where AI-powered agrobots, such as autonomous tractors and robotic harvesters, reduce labor costs and improve precision. These machines can perform tasks like weeding and fruit picking with minimal human intervention, reducing chemical usage and increasing yields.

Additionally, predictive analytics enable farmers to forecast crop yields based on historical data, weather trends, and soil conditions, facilitating more informed planning for market demands.

AI also enhances water management through smart irrigation systems that utilize IoT sensors to adjust water usage in real-time, conserving resources and improving sustainability. In livestock farming, AI monitors animal health through facial recognition and wearable devices, tracking feeding patterns and detecting diseases early. Beyond the farm, AI optimizes the agricultural supply chain, reducing food waste during transportation and helping farmers predict market trends for better pricing.

Dear Doctor

Artificial intelligence and its applications in agriculture: A review

• January 2025
• Environment Conservation Journal 26(1):274-280
• DOI: 10.36953/ECJ.28802904
• License CC BY-NC 4.0
• Peddi Naga Harsha Vardhan, Akhila Badavath, Pulla Srivalli

[Abstract

The application of artificial intelligence (AI) into agriculture marks a huge shift in the sector, providing solutions for increasing crop yields, pest control, and overall food supply chain management. This study delves into the role of AI in contemporary agriculture, emphasizing its capacity to enhance decision-making by providing precise weather forecasts and selecting seeds tailored to specific climatic conditions. AI applications such as computer vision, image recognition systems, and smart sensors offer real-time data collection, which aids crop monitoring, management, and pest control. These technologies also help determine appropriate planting timings, depths, and seed spacing, resulting in increased efficiency and output. Furthermore, AI-powered devices give insights into crop health, including nutritional requirements, which improves the quality and quantity of agricultural produce. The current study also considers the future of AI in agriculture, focusing on its capacity to minimize environmental impact, enhance farming procedures, and reduce waste in food and biofuel production. The study stresses the transformative role of AI and machine learning (ML) in agriculture, concentrating on their applications and contributions to sustainable agricultural methods.]