From Conventional to Artificial Intelligence-Based Agriculture
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63 663 Ft (60 632 Ft + 5% VAT)
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63 663 Ft
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Product details:
- Publisher Elsevier Science
- Date of Publication 20 April 2026
- ISBN 9780443274657
- Binding Paperback
- No. of pages224 pages
- Size 235x191 mm
- Weight 450 g
- Language English 697
Categories
Long description:
From Conventional to Artificial Intelligence-Based Agriculture explores the evolving landscape of agriculture as it transitions from traditional practices to advanced, AI-driven solutions. With AI and machine learning revolutionizing industries worldwide, their impact on agriculture is becoming increasingly significant. These technologies are not only aiding in climate modeling but also opening new possibilities for precision farming, enabling more accurate crop health diagnostics, efficient resource management, and timely intervention strategies.
By integrating conventional agricultural knowledge with cutting-edge AI tools, farmers and researchers can better assess soil conditions, predict optimal planting windows, monitor nutrient dynamics, and understand market trends with greater precision. This convergence of tradition and technology supports more resilient, productive, and sustainable agricultural systems, paving the way for a smarter and more food-secure future.
Table of Contents:
1. Scope of conventional knowledge and deep learning approaches for the identification of plant diseases
2. Plant disease diagnosis and forecasting in the era of artificial intelligence, machine learning, and deep learning
3. AI-powered precision horticulture: Integrating machine learning and unmanned vehicles for crop management
4. Exploring conventional methods and deep learning approaches for plant disease identification
5. Machine learning and artificial intelligence for germplasm phenotyping in plant breeding
6. Genome language models for plant genome mining in accelerating breeding strategies
7. Use of artificial intelligence in hydroponic vegetable production
8. Bibliometric analysis of artificial intelligence and machine learning: A technological revolution in agriculture
9. Soil health monitoring using artificial intelligence and the Internet of Things for sustainable agriculture
10. Generative AI and the potential of robotics in agriculture
11. Artificial intelligence in food science and nutrition
12. Artificial intelligence and machine learning in agriculture: Transforming economics and farm viability in the agricultural sector
