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.
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.
Preface.
1. Role of Solanaceous Crops in Global Food Security.
2.
Nutritional Value and Health Benefits of Solanaceous Crops.
3. Effect of
Rhizospheric Population on Disease Resistance in Solanaceae Crops.
4.
Harnessing Deep Learning for Disease Detection and Classification in
Solanaceae Crops: A Comprehensive Review and Future Outlook.
5. Cutting-Edge
Techniques Highlighted for Disease Detection and Classification in Solanaceae
Crops.
6. A Comprehensive Review on Application of Artificial Intelligence
for Sustainable Potato Farming and Future Scope.
7. Artificial Intelligence
in Agriculture: Exploring Trends, Challenges, and Future Directions.
8.
AI-Driven Automation in Solanaceae Farming for Disease and Pest Management.
9. Demystifying the Role of Deep Learning Models for Disease Detection and
Classification in Solanaceae Crops.
10. Cutting Edge Techniques for Disease
Detection in Solanaceous Crops.
11. Artificial Intelligence for Precision
Cultivation of Solanaceae Crops: Enhancing Yield and Resource Efficiency.
12.
An Integrated Framework for Automatic Irrigation for Solanaceae Crops using
Feedback Learning with Multimodal Optimizations. Index.
Mithilesh Kumar Dubey is a distinguished academician and researcher with over 18 years of experience in Computer Science and Engineering. He has published 90+ research papers, been granted 21 patents from Government of India, authored books, and presented at leading global conferences. His expertise spans Artificial Intelligence, Data Science, Plant & Brain Disease Detection, E-Healthcare, Higher Education Policy, Innovation, and Entrepreneurship. With proven leadership in curriculum design, quality assurance, and academic governance aligned with UGC, AICTE, NAAC, and NBA guidelines, Prof(Dr.) Dubey is widely recognized for his dedication to student mentoring, academic excellence, and societal development.
Kajal Verma is currently pursuing a Ph.D. in the School of Computer Science and Engineering at Lovely Professional University, Punjab, India. Her research is centered on the integration of Artificial Intelligence (AI) techniques to promote sustainable agriculture, with a particular focus on developing intelligent systems for crop monitoring, disease detection, and precision farming. Over the course of her academic career, she has made substantial contributions to the research community, publishing numerous articles in high-quality, peer-reviewed national and international journals as well as presenting her work at prominent conferences. In addition to her research, she actively contributes to the scientific community by serving as a reviewer for IEEE publications, ensuring the quality and rigor of research in the fields of AI and smart agriculture.
Khalil Ahmed is currently serving as a Senior Research Fellow in the School of Computer Science and Engineering at Lovely Professional University, Punjab, India. His primary areas of research include Artificial Intelligence, Smart Cities, Computer System Architecture, and Sustainable Agriculture, with a key focus on developing intelligent AIoT systems and architecture to address real-world agricultural challenges. He has contributed significantly to the academic community by publishing several research papers in peer-reviewed national and international journals and conference proceedings.
Sudha Dubey is currently serving as an Assistant Professor in the Faculty of Sociology at Lovely Professional University, Jalandhar, Punjab. She earned her Ph.D. from Mahatma Gandhi Kashi Vidyapeeth, Varanasi, U.P., and has developed a strong academic focus on areas such as gender empowerment, social issues, and environmental studies. Dr. Dubey actively mentors research scholars, with four of them currently pursuing their doctoral studies under her guidance, while three having successfully completed their Ph.D. programs under her supervision. In addition to her teaching and mentorship, she has made significant contributions to the study of marriage and kinship, social stratification, media, and the intersection of sociology with emerging technologies such as Artificial Intelligence. Her work continues to advance knowledge and understanding in both traditional sociological domains and contemporary interdisciplinary fields.
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