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Full Description
The book Artificial Intelligence and Sustainable Agriculture for Solanaceae Crops provides a comprehensive exploration of artificial intelligence techniques and their transformative role in promoting sustainable agriculture, particularly for Solanaceae crops such as tomato, potato, and eggplant. Focusing on disease detection and prediction, the book highlights advanced AI applications, including dimensionality reduction, feature extraction, and the analysis of complex genomics and phenotypic data. It systematically presents the design, implementation, and evaluation of predictive models using widely adopted tools such as MATLAB and Python, while also addressing both software- and hardware-based solutions for enhancing genomics research and crop disease management. Through detailed case studies, experimental results, and practical examples, the book demonstrates how AI can optimize precision agriculture practices, improve crop yield, and support early warning systems for disease outbreaks. Serving as both a theoretical reference and a practical guide, it is an invaluable resource for researchers, graduate students, agronomists, and professional engineers aiming to leverage AI, image analysis, and predictive modeling to address real-world challenges in Solanaceae crop production and genomics.
Contents
Preface. Role of Solanaceous Crops in Global Food Security. Nutritional Value and Health Benefits of Solanaceous Crops. Effect of Rhizospheric Population on Disease Resistance in Solanaceae Crops. Harnessing Deep Learning for Disease Detection and Classification in Solanaceae Crops: A Comprehensive Review and Future Outlook. Cutting-Edge Techniques Highlighted for Disease Detection and Classification in Solanaceae Crops. A Comprehensive Review on Application of Artificial Intelligence for Sustainable Potato Farming and Future Scope. Artificial Intelligence in Agriculture: Exploring Trends, Challenges, and Future Directions. AI-Driven Automation in Solanaceae Farming for Disease and Pest Management. Demystifying the Role of Deep Learning Models for Disease Detection and Classification in Solanaceae Crops. Cutting Edge Techniques for Disease Detection in Solanaceous Crops. Artificial Intelligence for Precision Cultivation of Solanaceae Crops: Enhancing Yield and Resource Efficiency. An Integrated Framework for Automatic Irrigation for Solanaceae Crops using Feedback Learning with Multimodal Optimizations. Index. About the Editors.
