Genetic Diversity of Coronaviruses: From SARSCoV to SARS-CoV-2 - (Part 1) provides a comprehensive analysis of the genetic mutations and host interactions across three major coronaviruses-SARS-CoV, MERS-CoV, and SARS-CoV-2. This volume explores the evolutionary history, mutations, and emerging variants of these viruses, with a focus on understanding how they adapt to different hosts. The book is organized into three parts: Part I covers SARS-CoV, detailing its genetic mutations, host genetic diversity, and new variants. Part II focuses on MERS-CoV, offering insights into mutations and host adaptations. Part III addresses SARS-CoV-2, discussing its evolving variants and the role of host proteins. The book also discusses the connections between coronaviruses and neurological, epigenetic, and AI-related issues Key Features: - In-depth analysis of genetic mutations in coronaviruses - Exploration of host genetic diversity and virus adaptation - Insight into emerging variants of SARS-CoV, MERS-CoV, and SARS-CoV-2 - Examination of host proteins' role in viral infections - Discussion on the impact of AI and epigenetics on coronavirus research.

Positioned at the crossroads of genomics, proteomics, artificial intelligence, and biomedical engineering, this book provides a roadmap for leveraging computational intelligence to address the complex challenges of modern life sciences, healthcare, and industrial biotechnology. Across twelve comprehensive chapters, the book lays the foundations for sequencing technologies, omics data, and the principles of biotechnology data management. It then transitions into the application of machine learning models ranging from neural networks to optimization frameworks to extract meaningful insights from large-scale biological datasets. Subsequently it addresses pressing challenges such as data noise, scalability, and ethical AI, while also highlighting algorithmic breakthroughs in pharmacogenomics, drug discovery, precision medicine, and synthetic biology. Case studies illustrate real-world applications, from CRISPR diagnostics and clinical trial optimization to agricultural genomics and biomedical engineering innovations. The closing chapters project the future trajectory of biotechnology, exploring quantum computing, federated learning, and secure data-sharing techniques. Key Features: Uncovers the revolutionary role of computational algorithms in biotechnology research and healthcare Explores the integration of AI, ML, and optimization methods in genomics, proteomics, and systems biology Analyzes real-world applications through case studies in pharmacogenomics, CRISPR, and agritech Provides practical insights into implementing secure, scalable, and ethical data solutions Gives an understanding future trends such as quantum computing and federated learning in biotech innovation.

With pesticide overuse threatening ecosystems, food safety, and human health,Biological Control for Plant Protection: Recent Advances in Research and Sustainability addresses one of the most pressing challenges in modern agriculture, enhancing crop productivity while reducing reliance on chemical pesticides. Integrating scientific advances with practical strategies to support integrated pest, weed, and disease management systems, the book brings together contributions from leading researchers and academicians providing an up-to-date compilation of topics ranging from isolation, characterization, and mass rearing of natural enemies to the field application of botanicals and biological methods for biotic stress management in plants. Key Features: Explores cutting-edge biological control methods for pests, pathogens, and weeds. Highlights environmentally sustainable alternatives to chemical pesticides. Covers natural enemies, botanicals, and biofertilizers as components of integrated management. Presents case studies and research from diverse agroecosystems, including organic farming. Provides a comprehensive reference for researchers, practitioners, and policymakers.

Microbial Insights into Wastewater Treatment and Environmental Sustainability examines the way microorganisms are reshaping the way we tackle environmental challenges, offering practical and science-driven strategies for wastewater remediation, pollution control, and resource recovery. Integrating microbiology, environmental science, and biotechnology, this volume reveals how microbial processes underpin sustainable solutions for ecosystem restoration and global environmental health. The book begins with foundational concepts, such as the microbial ecology of polluted sites and mechanisms of pollutant sequestration, to specialized topics including arsenic bioremediation, microbe-driven green nanotechnology, and biocontrol innovations. It further investigates plant-microbe partnerships that enhance environmental resilience, and explores cutting-edge molecular and biosensing techniques for real-time environmental monitoring. Case studies highlight the transition from laboratory research to field-scale applications, while forward-looking sections consider microbial nanotechnology for sustainable energy generation and microbial strategies for waste valorization. Key Features: Explains microbial roles in pollution mitigation and environmental recovery Demonstrates sequestration, bioremediation, and nanotechnology-based microbial innovations Integrates molecular tools and biosensors for environmental health assessment Applies microbial strategies to wastewater treatment, energy production, and waste management Highlights real-world case studies linking theory to practice Incorporates multidisciplinary insights from global research contributors Advances sustainable development through microbial resource recovery.

Sustainable Agriculture Applications Using Large Language Models examines how AI-powered tools can enhance decision-making, resource optimization, and knowledge dissemination across diverse agricultural contexts. Spanning topics from crop management and pest control to water conservation and market analysis, the book features a multidisciplinary approach including real-world applications and case studies. It highlights how LLMs can support sustainable practices by analyzing agricultural data, improving communication with farmers, and enabling predictive insights. Special attention is given to ethical considerations and the responsible deployment of AI tools in rural and technologically evolving regions. Key Features: Demonstrates how LLMs support sustainable agriculture practices Showcases AI-driven approaches in crop, pest, and water management Presents real-world applications and case studies across regions Explores ethical considerations and responsible AI deployment in agriculture Analyzes LLM integration in agricultural education, communication, and policy

This volume bridges scientific research with applied horticultural practices by examining the taxonomy, cultivation, ecological significance and conservation of ornamental and medicinal plants such as Fritillaria, Gladiolus, and Saffron. This book explores environmental requirements and sustainable cultivation methods by covering topics from plant morphology and classification to seed and vegetative propagation techniques-including tissue culture. Chapters also highlight the ethnobotanical value of these species and the challenges posed by habitat loss and overharvesting, offering practical conservation strategies to mitigate human impact. Key features: Details morphological and taxonomic insights Presents propagation techniques including advanced tissue culture Discusses soil, climate, and ecological needs for optimal cultivation Highlights traditional medicinal and ornamental applications Emphasizes conservation strategies for protecting wild populations