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Data Science For Agricultural Innovation And Productivity


Data Science For Agricultural Innovation And Productivity
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Data Science For Agricultural Innovation And Productivity


Data Science For Agricultural Innovation And Productivity
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Author : S. Gowrishankar, Hamidah Ibrahim, A. Veena, K.P. Asha Rani, A.H. Srinivasa
language : en
Publisher: Bentham Science Publishers
Release Date : 2024-02-12

Data Science For Agricultural Innovation And Productivity written by S. Gowrishankar, Hamidah Ibrahim, A. Veena, K.P. Asha Rani, A.H. Srinivasa and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-12 with Technology & Engineering categories.


Data Science for Agricultural Innovation and Productivity explores the transformation of agriculture through data-driven practices. This comprehensive book delves into the intersection of data science and farming, offering insights into the potential of big data analytics, machine learning, and IoT integration. Readers will find a wide range of topics covered in 10 chapters, including smart farming, AI applications, hydroponics, and robotics. Expert contributors, including researchers, practitioners, and academics in the fields of data science and agriculture, share their knowledge to provide readers with up-to-date insights and practical applications. The interdisciplinary emphasis of the book gives a well-rounded view of the subject. With real-world examples and case studies, this book demonstrates how data science is being successfully applied in agriculture, inspiring readers to explore new possibilities and contribute to the ongoing transformation of the agricultural sector. Sustainability and future outlook are the key themes, as the book explores how data science can promote environmentally conscious agricultural practices while addressing global food security concerns. Key Features: - Focus on data-driven agricultural practices - Comprehensive coverage of modern farming topics with an interdisciplinary perspective - Expert insights - Sustainability and future outlook -Highlights practical applications Data Science for Agricultural Innovation and Productivity is an essential resource for researchers, data scientists, farmers, agricultural technologists, students, educators, and anyone with an interest in the future of farming through data-driven agriculture.



Data Science For Agricultural Innovation And Productivity


Data Science For Agricultural Innovation And Productivity
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Author : Hamidah Ibrahim
language : en
Publisher: Bentham Science Publishers
Release Date : 2024-02-13

Data Science For Agricultural Innovation And Productivity written by Hamidah Ibrahim and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-13 with Technology & Engineering categories.


Data Science for Agricultural Innovation and Productivity explores the transformation of agriculture through data-driven practices. This comprehensive book delves into the intersection of data science and farming, offering insights into the potential of big data analytics, machine learning, and IoT integration. Readers will find a wide range of topics covered in 10 chapters, including smart farming, AI applications, hydroponics, and robotics. Expert contributors, including researchers, practitioners, and academics in the fields of data science and agriculture, share their knowledge to provide readers with up-to-date insights and practical applications. The interdisciplinary emphasis of the book gives a well-rounded view of the subject. With real-world examples and case studies, this book demonstrates how data science is being successfully applied in agriculture, inspiring readers to explore new possibilities and contribute to the ongoing transformation of the agricultural sector. Sustainability and future outlook are the key themes, as the book explores how data science can promote environmentally conscious agricultural practices while addressing global food security concerns. Key Features:



Science Breakthroughs To Advance Food And Agricultural Research By 2030


Science Breakthroughs To Advance Food And Agricultural Research By 2030
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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2019-04-21

Science Breakthroughs To Advance Food And Agricultural Research By 2030 written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-21 with Science categories.


For nearly a century, scientific advances have fueled progress in U.S. agriculture to enable American producers to deliver safe and abundant food domestically and provide a trade surplus in bulk and high-value agricultural commodities and foods. Today, the U.S. food and agricultural enterprise faces formidable challenges that will test its long-term sustainability, competitiveness, and resilience. On its current path, future productivity in the U.S. agricultural system is likely to come with trade-offs. The success of agriculture is tied to natural systems, and these systems are showing signs of stress, even more so with the change in climate. More than a third of the food produced is unconsumed, an unacceptable loss of food and nutrients at a time of heightened global food demand. Increased food animal production to meet greater demand will generate more greenhouse gas emissions and excess animal waste. The U.S. food supply is generally secure, but is not immune to the costly and deadly shocks of continuing outbreaks of food-borne illness or to the constant threat of pests and pathogens to crops, livestock, and poultry. U.S. farmers and producers are at the front lines and will need more tools to manage the pressures they face. Science Breakthroughs to Advance Food and Agricultural Research by 2030 identifies innovative, emerging scientific advances for making the U.S. food and agricultural system more efficient, resilient, and sustainable. This report explores the availability of relatively new scientific developments across all disciplines that could accelerate progress toward these goals. It identifies the most promising scientific breakthroughs that could have the greatest positive impact on food and agriculture, and that are possible to achieve in the next decade (by 2030).



Agricultural Internet Of Things And Decision Support For Precision Smart Farming


Agricultural Internet Of Things And Decision Support For Precision Smart Farming
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Author : Annamaria Castrignano
language : en
Publisher: Academic Press
Release Date : 2020-01-09

Agricultural Internet Of Things And Decision Support For Precision Smart Farming written by Annamaria Castrignano and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-09 with Business & Economics categories.


Agricultural Internet of Things and Decision Support for Smart Farming reveals how a set of key enabling technologies (KET) related to agronomic management, remote and proximal sensing, data mining, decision-making and automation can be efficiently integrated in one system. Chapters cover how KETs enable real-time monitoring of soil conditions, determine real-time, site-specific requirements of crop systems, help develop a decision support system (DSS) aimed at maximizing the efficient use of resources, and provide planning for agronomic inputs differentiated in time and space. This book is ideal for researchers, academics, post-graduate students and practitioners who want to embrace new agricultural technologies. - Presents the science behind smart technologies for agricultural management - Reveals the power of data science and how to extract meaningful insights from big data on what is most suitable based on individual time and space - Proves how advanced technologies used in agriculture practices can become site-specific, locally adaptive, operationally feasible and economically affordable



Agricultural Innovation Systems


Agricultural Innovation Systems
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Author : World Bank
language : en
Publisher: World Bank Publications
Release Date : 2012-02-21

Agricultural Innovation Systems written by World Bank and has been published by World Bank Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-21 with Business & Economics categories.


Managing the ability of agriculture to meet rising global demand and to respond to the changes and opportunities will require good policy, sustained investments, and innovation - not business as usual. Investments in public Research and Development, extension, education, and their links with one another have elicited high returns and pro-poor growth, but these investments alone will not elicit innovation at the pace or on the scale required by the intensifying and proliferating challenges confronting agriculture. Experience indicates that aside from a strong capacity in Research and Development, the ability to innovate is often related to collective action, coordination, the exchange of knowledge among diverse actors, the incentives and resources available to form partnerships and develop businesses, and conditions that make it possible for farmers or entrepreneurs to use the innovations. While consensus is developing about what is meant by 'innovation' and 'innovation system', no detailed blueprint exists for making agricultural innovation happen at a given time, in a given place, for a given result. The AIS approach that looks at these multiple conditions and relationships that promote innovation in agriculture, has however moved from a concept to a sub-discipline with principles of analysis and action. AIS investments must be specific to the context, responding to the stage of development in a particular country and agricultural sector, especially the AIS. This sourcebook contributes to identifying, designing, and implementing the investments, approaches, and complementary interventions that appear most likely to strengthen AIS and to promote agricultural innovation and equitable growth. It emphasizes the lessons learned, benefits and impacts, implementation issues, and prospects for replicating or expanding successful practices. The information in this sourcebook derives from approaches that have been tested at different scales in different contexts. It reflects the experiences and evolving understanding of numerous individuals and organizations concerned with agricultural innovation, including the World Bank. This information is targeted to the key operational staff in international and regional development agencies and national governments who design and implement lending projects and to the practitioners who design thematic programs and technical assistance packages. The sourcebook can also be an important resource for the research community and nongovernmental organizations (NGOs).



Data Driven Innovation Big Data For Growth And Well Being


Data Driven Innovation Big Data For Growth And Well Being
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Author : OECD
language : en
Publisher: OECD Publishing
Release Date : 2015-10-06

Data Driven Innovation Big Data For Growth And Well Being written by OECD and has been published by OECD Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-06 with categories.


This report improves the evidence base on the role of Data Driven Innovation for promoting growth and well-being, and provide policy guidance on how to maximise the benefits of DDI and mitigate the associated economic and societal risks.



Precision Agriculture In The 21st Century


Precision Agriculture In The 21st Century
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Author :
language : en
Publisher: National Academies
Release Date : 1997-09-08

Precision Agriculture In The 21st Century written by and has been published by National Academies this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-09-08 with Technology & Engineering categories.


Sensors, satellite photography, and multispectral imaging are associated with futuristic space and communications science. Increasingly, however, they are considered part of the future of agriculture. The use of advanced technologies for crop production is known as precision agriculture, and its rapid emergence means the potential for revolutionary change throughout the agricultural sector. Precision Agriculture in the 21st Century provides an overview of the specific technologies and practices under the umbrella of precision agriculture, exploring the full implications of their adoption by farmers and agricultural managers. The volume discusses how precision agriculture could dramatically affect decisionmaking in irrigation, crop selection, pest management, environmental issues, and pricing and market conditions. It also examines the geographical dimensions--farm, regional, national--of precision agriculture and looks at how quickly and how widely the agricultural community can be expected to adopt the new information technologies. Precision Agriculture in the 21st Century highlights both the uncertainties and the exciting possibilities of this emerging approach to farming. This book will be important to anyone concerned about the future of agriculture: policymakers, regulators, scientists, farmers, educators, students, and suppliers to the agricultural industry.



Artificial Intelligence And Data Science For Sustainability Applications And Methods


Artificial Intelligence And Data Science For Sustainability Applications And Methods
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Author : Syafrudin, Muhammad
language : en
Publisher: IGI Global
Release Date : 2025-02-07

Artificial Intelligence And Data Science For Sustainability Applications And Methods written by Syafrudin, Muhammad and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-07 with Computers categories.


The integration of artificial intelligence (AI) and data science (DS) into sustainability efforts is increasingly crucial as the world faces environmental and resource challenges. By leveraging advanced AI and DS techniques, we can create innovative solutions for sectors like energy, agriculture, and waste management, promoting long-term sustainability. These technologies have the potential to optimize processes, reduce environmental footprints, and support smarter decision-making across industries. Ultimately, AI and DS are key to advancing both the efficiency and impact of sustainability efforts, contributing to a more sustainable future for society at large. Artificial Intelligence and Data Science for Sustainability: Applications and Methods explores the application of AI and DS techniques and methodologies in addressing various sustainability challenges. It brings together cutting-edge research, case studies, and practical applications that demonstrate how AI can be leveraged to promote sustainable development across diverse domains. Covering topics such as structural optimization, drone imagery, and development financing, this book is an excellent resource for computer scientists, computer engineers, urban planners, sustainability professionals, government officials, policymakers, researchers, professionals, scholars, academicians, and more.



Harnessing Data Science For Sustainable Agriculture And Natural Resource Management


Harnessing Data Science For Sustainable Agriculture And Natural Resource Management
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Author : Mehul S. Raval
language : en
Publisher: Springer Nature
Release Date : 2024-12-19

Harnessing Data Science For Sustainable Agriculture And Natural Resource Management written by Mehul S. Raval and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-19 with Computers categories.


This book is a comprehensive resource that handles the issues of sustainable agriculture and natural resource management, aligned with the United Nations' Sustainable Development Goals (SDGs). The book is organized into five sections, Understanding the Problem, Data Collection and Cleaning, Exploratory Data Analysis and Visualization, Model Building, and Model Deployment. Each section covers a critical aspect of data science in this context and addresses specific SDGs 2—zero hunger, 6—clean water and sanitation, 12—responsible consumption and production, 13—climate action, and 15—Life on land. The organized sections are arranged to seamlessly follow the data science pipeline and provide practical guidance from problem understanding to its model deployment and stakeholder management. The book is useful for researchers, students, practitioners, and policymakers.



Intelligent Computing And Innovation On Data Science


Intelligent Computing And Innovation On Data Science
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Author : Sheng-Lung Peng
language : en
Publisher: Springer Nature
Release Date : 2020-05-14

Intelligent Computing And Innovation On Data Science written by Sheng-Lung Peng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-14 with Technology & Engineering categories.


This book covers both basic and high-level concepts relating to the intelligent computing paradigm and data sciences in the context of distributed computing, big data, data sciences, high-performance computing and Internet of Things. It is becoming increasingly important to develop adaptive, intelligent computing-centric, energy-aware, secure and privacy-aware systems in high-performance computing and IoT applications. In this context, the book serves as a useful guide for industry practitioners, and also offers beginners a comprehensive introduction to basic and advanced areas of intelligent computing. Further, it provides a platform for researchers, engineers, academics and industrial professionals around the globe to showcase their recent research concerning recent trends. Presenting novel ideas and stimulating interesting discussions, the book appeals to researchers and practitioners working in the field of information technology and computer science.