Summary
Artificial Intelligence (AI) has been extensively applied in farming recently. To cultivate healthier crops, manage pests, monitor soil and growing conditions, analyse data for farmers, and enhance other management activities of the food supply chain, the agriculture sector is turning to AI technology. It makes it challenging for farmers to choose the ideal time to plant seeds. AI helps farmers choose the optimum seed for a particular weather scenario. It also offers data on weather forecasts. AI-powered solutions will help farmers produce more with fewer resources, increase crop quality, and hasten product time to reach the market. AI aids in understanding soil qualities. AI helps farmers by suggesting the nutrients they should apply to increase the quality of the soil. AI can help farmer
Regional applicability
The paper is a broad technology review without geographic specificity. Its findings on AI decision-support systems, soil quality assessment, and pest management are potentially applicable to United Kingdom farming, though implementation will depend on UK farm scale, infrastructure, digital literacy, and cost-effectiveness relative to existing advisory services.
Key measures
Application domains of AI in agriculture (seed selection, planting timing, soil nutrient recommendations, crop health monitoring); AI-based technologies (hyperspectral imaging, 3D laser scanning, health monitoring systems)
Outcomes reported
The paper reviews and analyses relevant articles on AI applications in agriculture, identifying how AI technologies support crop health monitoring, soil quality assessment, pest management, and optimised planting decisions. It examines AI and machine learning tools including hyperspectral imaging and 3D laser scanning for precision agricultural management.
Topic tags
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