Sadhana Singh – författare

Bioinformatics for Crop Improvement: From Data Analysis to Practical Applications is an in-depth exploration of how computational tools and multi-omics data analysis are impacting crop development. Covering foundational concepts, advanced techniques, and practical applications, the book examines crop traits, disease resistance, and stress tolerance. It offers a structured exploration of strategies for crop improvement and sustainability and deep dives into bioinformatics for global food security and agricultural resilience. It goes over critical bioinformatics techniques and tools such as genome assembly, functional genomics, structural modeling, and genome editing technologies. Essentially, this book provides cutting-edge bioinformatics approaches in agriculture, emphasizing their crucial role in addressing future food security challenges and promoting sustainable farming practices worldwide. The book is organized into four main sections, each comprising several chapters that systematically build on each other. The first section introduces the fundamentals of bioinformatics in crop science, including data generation, management, and analysis of genomics, transcriptomics, proteomics, and metabolomics. The chapters after that look into key bioinformatics techniques and tools, covering genome assembly, functional genomics. The third section focuses on practical applications, including disease resistance, abiotic stress tolerance, nutritional enhancement, plant-microbiome interactions, and epigenetic regulation. It demonstrates how bioinformatics-driven research is directly contributing to developing resilient, nutritious, and sustainable crop varieties. The final section emphasizes bioinformatics approaches for sustainable agriculture, including genome-wide association studies, precision phenotyping, machine learning, big data integration, and future challenges in the field. Designed for a broad audience, this book is useful for students and researchers in the fields of plant biology, bioinformatics, genomics, and agricultural sciences who are engaged in crop improvement and sustainable agriculture. It also serves as a valuable resource for breeders, biotechnologists, policymakers, and industry stakeholders involved in developing crop varieties. Its comprehensive coverage, case studies, and supplementary materials make it a valuable reference for advancing knowledge and application in crop bioinformatics.Presents comprehensive insights into bioinformatics for crop improvement, covering core concepts and innovative applicationsExplores genomics, transcriptomics, proteomics, and gene editing to support sustainable agricultureFeatures real-world case studies on disease resistance, stress tolerance, microbiomes, and crop nutritionProvides practical tools and multidisciplinary approaches to enhance crop research and developmentHighlights future challenges and opportunities in applying bioinformatics for global food securityOffers supplementary resources such as PowerPoint slides, datasets, and basic programming materials (including Python notebooks) to support effective learning for students and instructors

Millets as Superfood: Biochemistry, Biotechnology, and Applications presents a timely and exhaustive analysis of these ancient grains that are quickly evolving as the foods of the future. Traditionally valued for their adaptability and endurance in harsh climates and minimal-input farming, millets are now being recognized worldwide as nutrient-dense, climate-smart superfoods with tremendous potential to enhance food security and sustainable agriculture.This book delivers a unique blend of traditional knowledge and cutting-edge science. It unravels the biochemical richness of millets—vitamins, minerals, antioxidants, and bioactive compounds—while assessing their proven health benefits. Together, it highlights modern biotechnological interventions, including CRISPR/Cas-based genome editing, molecular breeding, and omics technologies that are revolutionizing millet research. Readers will also observe the growing economic and industrial uses of millets, from nutraceuticals and functional foods to biofortification and value-added processing transformations.Written and edited by globally recognized experts, this volume is tailored for a wide readership. For students and researchers, it presents extensive scientific analyses and practical implementations; for policymakers and entrepreneurs, it reveals the economic, social, and ecological promise of millets in rising world markets.This is not just a book about grains—it is a roadmap to healthier diets, sustainable farming, and a resilient future.

Guide to the application of AI for crop improvement, including deployment in plant biology and crop breeding Crop Improvement with Artificial Intelligence provides a comprehensive overview of the integration of AI into crop development and farm management, highlighting the latest advancements and applications in the field. The book offers an exhaustive review of recent progress and implementations of AI in agriculture, covering a wide range of topics crucial for understanding the innovative potential of AI in crop enhancement. Beginning with an exploration of the documented factors and potential for innovation in agriculture, the book introduces readers to the fundamental concepts of AI and its transformative impact on advanced farming methods. It delves into the various applications of AI in plant biology and breeding, from data collection and pre-processing to predictive analytics for crop yield and disease resistance. The book also addresses ethical considerations and challenges in AI-enabled crop improvement and delivers insights into the prospects of employing AI for crop enhancement, underscoring the significance of genetic diversity, resource optimization, and ethical considerations. Crop Improvement with Artificial Intelligence discusses topics including: Utilization of LLMs to improve analysis of agricultural data by interpreting intricate datasets and providing insights to enhance decision-makingGenerative AI???s role in developing innovative solutions and predictive models for better crop management, pest control, and resource distributionCurrent challenges such as data constraints, economic feasibility, and untested technologiesIntegration of multi-omics data with the latest applications and technologies, including functional genomics, phenotyping, high-throughput imaging, and genomic prediction in plants, to analyze complex traits and advance plant transcriptomicsCrop Improvement with Artificial Intelligence is an essential resource for scholars, researchers, academics, agronomists, policymakers, and all other readers interested in capitalizing AI to address the hurdles of worldwide food security and encourage sustainable agricultural implementation.