Omar Sultan Al Orama, Minister of State for Artificial Intelligence, Digital Economy and Remote Work Applications, stressed that the outcome is another step in the UAE's efforts to leverage AI to increase the efficiency of key sectors, including agriculture and food security. He praised Adafsa for his contributions to digital transformation and food security, and praised his leadership's commitment to building a sustainable and innovative future.
Adafsa's acting director, Dr. Tariq Al Ameri, noted that the certification is consistent with both Abu Dhabi's vision and UAE AI strategy 2031.
The role of AI in modern agriculture
Artificial intelligence is rapidly transforming the agricultural industry, increasing productivity and efficiency, reducing costs and risk. AI applications in this sector are diverse and powerful.
Precision Agriculture: Using data from sensors and drones, AI determines the exact amount of water, fertilizer and pesticides needed for crops. This approach minimizes waste and maximizes production efficiency.
Irrigation Management: Smart irrigation systems use AI to calculate the optimal water requirements for a particular agricultural zone and take into account crop type, soil condition, and weather.
AI has had a major impact on the entire food and agricultural production chain. Technology is used to:
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Develop climate-sensitive rice varieties.
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Provides detailed soil data.
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Guides drones for accurate application of pesticides and fertilizers.
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Sort, inspect and grade crops.
7. Important use of AI in agriculture
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Monitoring crop and soil health: drones capture and analyze aerial images to assess crop and soil status and growth stages.
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Pest and Disease Detection: AI algorithms can identify pests and diseases early, and timely interventions can minimize crop damage.
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Livestock Health Monitoring: Sensors track livestock health and help farmers detect early signs of illness and take precautions.
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Smart Pesticide Spray: AI-powered sprayers use computer vision to apply pesticides only when needed, reducing overuse of chemicals.
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Automated Weed Removal: The robot identifies and removes weeds from the field, reducing the need for herbicides and manual labor.
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Aerial Survey and Imaging: Drones and Remote Sensing Systems create detailed maps of the field and show crop health, soil moisture, and other important growth factors.
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Product Sorting and Grading: AI algorithms classify and sort produce by quality and size, reducing waste and ensuring premium products reach the market.
This integration of AI, along with technologies such as automation and the Internet of Things (IoT), is part of a broader movement known as smart or precision agriculture. The goal is to optimize agricultural productivity and sustainability using data-driven technology.
