Yamin Bibi – författare

Phytochemistry and Climate-Resilient Agriculture offers a comprehensive exploration of how phytochemistry can be harnessed to build climate-resilient agricultural systems. It begins by establishing the foundational role of plant metabolites in responding to climate stress and enhancing crop productivity under abiotic pressures such as drought and heat. The text then delves into applied strategies, including phytoremediation for detoxifying degraded soils, and the use of phytochemicals in carbon sequestration and pest management. It expands the scope to include agroforestry, marine and algal phytochemistry, and the integration of AI and computational tools for predictive modeling. Cutting-edge topics such as genomic engineering for climate-resilient crops, water conservation through phytochemicals, and the role of plant compounds in supporting pollinators and biodiversity are also covered. The book concludes with discussions on economic viability, global market potential, and pathways for scaling innovations through policy and practice, offering a forward-looking vision for integrating phytochemistry into sustainable agriculture. With its interdisciplinary perspective, this book equips agricultural scientists with the tools and insights needed to integrate phytochemical research into climate-smart agriculture. Whether developing new crop varieties, designing sustainable farming systems, or advancing environmental policy, this book provides an application-focused guide to the future of resilient agriculture.

This book explores the transformative convergence of AI and phytochemistry. The book shows how AI is revolutionizing the discovery, design, and development of plant-based bioactive compounds by providing tools for structure identification, pharmacological prediction, compound optimization, and synthesis planning. Through machine learning, data analytics, and computational modeling, it demonstrates how AI accelerates and advances traditional phytochemical research.Phytochemistry—the study of natural plant compounds—has long been foundational to drug discovery. Historically reliant on labor-intensive experiments, the field now faces a paradigm shift. AI offers scalable, data-driven methods that boost speed and accuracy, bridging classical phytochemistry with modern pharmaceutical innovation.The book begins with foundational chapters on traditional phytochemistry and AI integration, including data sourcing and supply chain challenges. It then covers AI-assisted techniques for synthesis, extraction, isolation, and structural elucidation of bioactives. Later sections focus on simulation and optimization of drug candidates—such as property prediction, docking, virtual screening, and optimization algorithms. The final chapters explore pharmacological applications, collaborative models, ethical and legal considerations, and AI’s global impact in democratizing drug discovery.This book is ideal for researchers, academicians, and professionals in pharmaceutical sciences, biotechnology, and phytochemistry. It also serves students, trainees, and policymakers interested in the intersection of AI and natural product-based drug discovery.