Manish K. Pandey – författare

Big Data Analytics in Agriculture focuses on the quantitative and qualitative assessment of agricultural systems using state-of-the-art technologies to deliver practical improvements in agricultural production. Addressing the challenge of translating data into real-world applications, the book provides a comprehensive mapping of the entire data lifecycle-from data generation, storage, and curation to processing and implementation. It guides readers through the steps required to produce high-quality, reliable information that supports effective decision-making. Following a logical progression, the volume demonstrates how diverse data streams converge into decision-support systems and how they can be transformed into actionable outcomes, aligned with intelligent, efficient, technologically advanced, economically viable, and politically and culturally sustainable practices. The book further explores the integration of information and communication technologies (ICT) and the Internet of Things (IoT) for managing rural assets and enhancing economic and environmental performance in spatially and temporally variable agricultural environments. Topics covered include big data analytics, data management and processing, and a range of algorithms and applications relevant to agriculture. Subtopics encompass artificial intelligence- and machine-learning-enabled smart and precision irrigation, disease and pest management, microclimatic forecasting, preventive fertigation and chemigation, data-driven smart farming through the Internet of Everything (IoE), and supply-chain analytics for improved farm-level operations.

Introduces readers to the evolution from conventional analytical approaches to large-scale analytical paradigms through a stepwise, sectioned framework that supports progressive skill developmentExamines practical considerations surrounding storage architectures, multi-source datasets, scalability constraints, and cost trade-offs in agricultural computing environmentsDetails algorithm-centric workflows, including feature construction, model calibration, and comparative performance evaluation across diverse agricultural contextsShowcases a wide range of sector-specific implementations, covering crop monitoring, irrigation planning, weed control, nutrient stress identification, climate assessment, pest detection, and agri-food supply-chain operations in both advanced and resource-limited settings

GeoAI-Driven Earth Observation for Sustainable Development: Contemporary Advances and Emerging Opportunities Across Scales presents a comprehensive overview of how Geographic Artificial Intelligence (GeoAI) is transforming Earth observation technologies to support the achievement of the United Nations Sustainable Development Goals (SDGs).The book begins by outlining the evolution of Earth observation and the integration of machine learning and deep learning techniques that enhance data analysis capabilities. It addresses the challenges and ethical considerations involved in deploying GeoAI, emphasizing the importance of open-source tools, cloud-edge intelligence, and reproducibility in advancing the field. The text explores a wide range of GeoAI applications tailored to specific SDGs, including precision agriculture for food security, urban resilience, disaster risk reduction, forest and biodiversity conservation, and water resource management. It also highlights innovations in air quality mapping, clean energy monitoring, health and well-being, inclusive education, gender equality, sustainable economic growth, and infrastructure development. Additionally, the book discusses policy and governance frameworks that enable the effective use of GeoAI for sustainable development, alongside integrated scenario modeling to bridge science and technology in land-use and cover change. Further, it examines emerging GeoAI applications in groundwater quality, marine and coastal ecosystems, and regional security in the context of climate change.This multidisciplinary volume equips researchers and practitioners with the knowledge and tools to harness GeoAI for addressing complex environmental and societal challenges.Provides readers an understanding on how GeoAI can drive sustainable developmentHighlights GeoAI-enabled policy and governance frameworks for international cooperation in harnessing GeoAI for sustainable developmentShowcases the future of GeoAI in Earth Observation from local to global perspectives, offering feasible solutions to critical environmental and social issues

This book reviews the latest advances in multiple fields of plant biotechnology and the opportunities that plant genetics, genomics and molecular biology have offered for agriculture improvement.

This book presents the current state of the art in peanut genomics, focusing particularly on the latest genomic findings, tools and strategies employed in genome sequencing, transcriptomes and analysis, availability of public and private genomic resources, and ways to maximize the use of this information in peanut breeding programs.

This book presents the current state of the art in peanut genomics, focusing particularly on the latest genomic findings, tools and strategies employed in genome sequencing, transcriptomes and analysis, availability of public and private genomic resources, and ways to maximize the use of this information in peanut breeding programs.

This book reviews the latest advances in multiple fields of plant biotechnology and the opportunities that plant genetics, genomics and molecular biology have offered for agriculture improvement.

Increasing world population, unpredictable climate and various kind of biotic and abiotic stresses necessitate the sustainable increase in crop production through developing improved cultivars possessing enhanced genetic resilience against all odds.

Increasing world population, unpredictable climate and various kind of biotic and abiotic stresses necessitate the sustainable increase in crop production through developing improved cultivars possessing enhanced genetic resilience against all odds.

This edited volume covers the application of modern breeding tools for developing climate-smart pulse crop cultivars. The primary focus is on utilizing available genomic resources and next-generation breeding technologies such as genome-wide association mapping, genomic selection, genome editing, and accelerated breeding pipelines for the rapid development of stress-resilient, systems-specific pulse cultivars.Pulses contribute to 10% of global daily protein intake and 5% of energy. Their ability to fix atmospheric nitrogen and serve as an alternative protein source to meat makes them crucial in combating global warming. With the global population expected to reach 9.8 billion by 2050, pulses production needs to increase by at least 70% to meet demand. However, pulses production is facing growing biotic and abiotic challenges, exacerbated by climate change. Thus, developing next-generation climate-smart cultivars is essential to ensure food and nutritional security. Recent efforts by global and national breeding communities have led to the discovery of new genomic resources, shifting breeding from phenotype-based to genome-based approaches. These advances integrate rapid generation advancement pipelines with genomic-assisted breeding, trait mapping, and genome editing tools.This book is valuable for agricultural scientists, scholars, and graduate students involved in pulse crop improvement. It also serves as a reference for policymakers and research grant managers in formulating pulse research programs.

This edited book covers the application of modern genomics tools for developing climate-smart oilseed cultivars. Thus, the book is framed to compile the importance and utility of next-generation breeding tools for enhancing stress resilience in oilseed crops in the climate change era.

This edited book covers the application of modern genomics tools for developing climate-smart oilseed cultivars. The book's prime focus is on utilizing available oilseed genomic resources and application of next-generation genetics and breeding tools, viz. genome-wise association mapping, genomic selection, genome editing and accelerated breeding pipelines and their efficacy for rapid development and delivery of stress-resilient oilseeds cultivars. Oilseeds are crucial for human and animal nutrition and cater to diverse industrial applications. Besides oil content, the oilseed meal possesses proteins and a higher proportion of essential amino acids, which benefit human well-being. Additionally, the contribution of oilseeds towards renewable energy mitigates the risk of climate change by reducing carbon footprint. Hence, it is imperative to enhance oilseeds production from the current 178 to 282 million tons by 2050 to meet the demands of both the population and the environment. The current genomics era delivered various genomic resources in oilseed crops, which resulted in the discovery of genes for several agronomic and stress-resilience traits and resistance to pests and diseases. Further, the availability of next-generation plant breeding tools, such as genomic selection, genome editing, and speed breeding, are being implemented along with traditional and marked assisted selection. Thus, the book is framed to compile the importance and utility of next-generation breeding tools for enhancing stress resilience in oilseed crops in the climate change era. The book is exciting and valuable to national and international agricultural scientists, scholars and graduate students associated with oilseed crops improvement in specific and field crops in generic. The book also serves as reference in formulating various oilseed improvement programs for policymakers and research grant managers.

This edited book is a compilation of information on existing frontier technologies in agriculture, such as driving modernized crop improvement programs via digitalization, mechanization and automation, artificial intelligence, speed breeding.