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Author: Food and Agriculture Organization of the United Nations
Publisher: Food & Agriculture Org.
ISBN: 925133837X
Category : Technology & Engineering
Languages : en
Pages : 162
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Book Description
This book aims to strengthen the skills of professionals who use, manage data for the benefit of farmers and farmers organizations by exposing them to the topics of importance of data in the agriculture value chain and how new and existing technologies, products and services can leverage farm level and global data to improve yield, reduce loss, add value and increase profitability and resilience.
Author: Food and Agriculture Organization of the United Nations
Publisher: Food & Agriculture Org.
ISBN: 925133837X
Category : Technology & Engineering
Languages : en
Pages : 162
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Book Description
This book aims to strengthen the skills of professionals who use, manage data for the benefit of farmers and farmers organizations by exposing them to the topics of importance of data in the agriculture value chain and how new and existing technologies, products and services can leverage farm level and global data to improve yield, reduce loss, add value and increase profitability and resilience.
Author: Addison, C.
Publisher: CTA
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 76
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Book Description
The study presented in this report was commissioned by the Technical Centre for Agricultural and Rural Cooperation (CTA) as a member of the Global Open Data for Agriculture & Nutrition (GODAN) initiative, and was conducted by SB Consulting (SBC4D). The objective of the research is to understand the role of farmer organisations (FO) and cooperatives in the agriculture data ecosystem. These organisations have long been recognised to play an important role in society that translates into the improvement of living conditions of their members, particularly the low-income earning population. More than 40% of households in Africa are member of a cooperative society ([ILO-2000]) and the cooperative movement is Africa’s biggest nongovernmental organisation. The key question this report explores is the role of these organisations in the emergent “data revolution.” How can they ensure that this data revolution benefits their members and the smallholder farmers in general, and at the same time contribute to the revolution by providing valuable information to policy makers or other stakeholders of the ecosystem?
Author:
Publisher:
ISBN:
Category : Agricultural engineering
Languages : en
Pages : 742
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Book Description
Author: Thomas Hoeren
Publisher: Springer
ISBN: 331962461X
Category : Law
Languages : en
Pages : 122
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Book Description
This book is open access under a CC BY 4.0 license. This book sheds new light on a selection of big data scenarios from an interdisciplinary perspective. It features legal, sociological and economic approaches to fundamental big data topics such as privacy, data quality and the ECJ’s Safe Harbor decision on the one hand, and practical applications such as smart cars, wearables and web tracking on the other. Addressing the interests of researchers and practitioners alike, it provides a comprehensive overview of and introduction to the emerging challenges regarding big data.All contributions are based on papers submitted in connection with ABIDA (Assessing Big Data), an interdisciplinary research project exploring the societal aspects of big data and funded by the German Federal Ministry of Education and Research.This volume was produced as a part of the ABIDA project (Assessing Big Data, 01IS15016A-F). ABIDA is a four-year collaborative project funded by the Federal Ministry of Education and Research. However the views and opinions expressed in this book reflect only the authors’ point of view and not necessarily those of all members of the ABIDA project or the Federal Ministry of Education and Research.
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 030946529X
Category : Technology & Engineering
Languages : en
Pages : 149
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Book Description
The National Agricultural Statistics Service (NASS) is the primary statistical data collection agency within the U.S. Department of Agriculture (USDA). NASS conducts hundreds of surveys each year and prepares reports covering virtually every aspect of U.S. agriculture. Among the small-area estimates produced by NASS are county-level estimates for crops (planted acres, harvested acres, production, and yield by commodity) and for cash rental rates for irrigated cropland, nonirrigated cropland, and permanent pastureland. Key users of these county-level estimates include USDA's Farm Services Agency (FSA) and Risk Management Agency (RMA), which use the estimates as part of their processes for distributing farm subsidies and providing farm insurance, respectively. Improving Crop Estimates by Integrating Multiple Data Sources assesses county-level crop and cash rents estimates, and offers recommendations on methods for integrating data sources to provide more precise county-level estimates of acreage and yield for major crops and of cash rents by land use. This report considers technical issues involved in using the available data sources, such as methods for integrating the data, the assumptions underpinning the use of each source, the robustness of the resulting estimates, and the properties of desirable estimates of uncertainty.
Author: John A. Dixon
Publisher: Food & Agriculture Org.
ISBN: 9789251046272
Category : Business & Economics
Languages : en
Pages : 424
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Book Description
A joint FAO and World Bank study which shows how the farming systems approach can be used to identify priorities for the reduction of hunger and poverty in the main farming systems of the six major developing regions of the world.
Author: U.s. Department of Agriculture
Publisher: Createspace Independent Publishing Platform
ISBN: 9781543136883
Category :
Languages : en
Pages : 46
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Book Description
Precision agriculture (PA) and its suite of information technologies-such as soil and yield mapping using a global positioning system (GPS), GPS tractor guidance systems, and variable-rate input application-allow farm operators to fine-tune their production practices. Access to detailed, within-field information can decrease input costs and increase yields. USDA's Agricultural Resource Management Survey shows that these PA technologies were used on roughly 30 to 50 percent of U.S. corn and soybean acres in 2010-12. Previous studies suggest that use of PA is associated with higher profits under certain conditions, but aggregate estimates of these gains have not been available. In this report, a treatment-effects model is developed to estimate factors associated with PA technology adoption rates and the impacts of adoption on profits. Labor and machinery used in production and certain farm characteristics, like farm size, are associated with adoption as well as with two profit measures, net returns and operating profits. The impact of these PA technologies on profits for U.S. corn producers is positive, but small. Keywords: Crop production information technologies, precision agriculture, variablerate technology, soil tests, global positioning system maps, guidance systems.
Author: James Hammond
Publisher: Frontiers Media SA
ISBN: 2832515894
Category : Technology & Engineering
Languages : en
Pages : 255
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Book Description
Smallholder farming systems contribute a substantial quantity of the food consumed in many lower and middle-income countries and contribute to the national and local economies. Despite the importance of smallholder farming, a transformation is needed in order to deliver food security and decent incomes for the farmers themselves and at the national level. This transformation must also be sustainable in terms of environmental impacts and social equity in order to be successful in the long term. The pressures of population growth, climate change, and land fragmentation compound the problem. Addressing these overlapping issues is a big challenge. One obstacle is the lack of good quality granular data linking these issues together. Household surveys are the workhorse method for gathering such data, but there are well-known problems that prevent household survey data from building up a “big picture” and delivering insights beyond the geographical boundary of each individual study. Such obstacles include the lack of access to datasets, differences in survey design, and respondent biases. Agile, data-oriented research tools can help to overcome these challenges. We use the term “agile” to imply methods that do not attempt exhaustive measurements, which are designed to be easy to use, and which entail some degree of flexibility in terms of adaptation to local conditions and integration with other tools or methods. Often these methods also nudge the behavior of tool users towards best practices. In recent years various research tools and approaches have been published which fit within our definition of “agile data-oriented research tools”. The domains these tools function in include monitoring and evaluation, intervention targeting, tailored information delivery, citizen science, credit scoring, and user feedback collection; all with the over-arching aim to improve data quality and access for those studying the sustainable development of smallholder farming systems. The goal of this Research Topic is to better define that niche, the ecosystem of tools and current practices, and to explore how such approaches can provide the underpinning knowledge required for the transformation of smallholder farming systems. One example of an agile data-oriented research tool is the Rural Household Multi-Indicator Survey (RHoMIS). It is a modular, digital system for building household surveys addressing the common topics in smallholder development. It was purposefully designed to give a broad overview of the farm system whist keeping survey duration to a minimum, to be user-friendly in implementation, and to be sufficiently flexible to function in a broad variety of locations and projects. Since 2015 it has been used by 30 organizations in 32 countries to interview over 34,000 households. The tool and database are open access and a community of practice is developing around the tool. We particularly welcome contributions that engage with the RHoMIS tool and data. However, we also describe the tool in order to provide an example of what is meant by an agile data-oriented research tool, and welcome contributions focusing on other tools or methodologies. We encourage the submission of manuscripts addressing the above topic, and those which fit within one of the following three sub-themes: (i) Perspectives or review articles which explore the niche, best practices, or promising approaches in agile data-oriented research tools for smallholder farm system transformation. Also, technology and code articles that describe new tools are welcomed. (ii) Original research articles presenting analyses based on data derived from agile data-oriented tools used at the project level. Examples include impact evaluations, adoption studies, targeting studies, or adaptive management, and should reflect on the additional benefit leveraged by the agile method applied. (iii) Original research articles that make use of the large amounts of data generated by such agile methods and/or link between agile data and other data sources. Examples include meta-analyses of data from multiple studies, layering data collected from different agile tools, or linking agile data to remote sensing or large-scale modeling outputs.
Author: Latief Ahmad
Publisher: CRC Press
ISBN: 1000364437
Category : Science
Languages : en
Pages : 220
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Book Description
Agriculture 5.0: Artificial Intelligence, IoT & Machine Learning provides an interdisciplinary, integrative overview of latest development in the domain of smart farming. It shows how the traditional farming practices are being enhanced and modified by automation and introduction of modern scalable technological solutions that cut down on risks, enhance sustainability, and deliver predictive decisions to the grower, in order to make agriculture more productive. An elaborative approach has been used to highlight the applicability and adoption of key technologies and techniques such WSN, IoT, AI and ML in agronomic activities ranging from collection of information, analysing and drawing meaningful insights from the information which is more accurate, timely and reliable.It synthesizes interdisciplinary theory, concepts, definitions, models and findings involved in complex global sustainability problem-solving, making it an essential guide and reference. It includes real-world examples and applications making the book accessible to a broader interdisciplinary readership. This book clarifies hoe the birth of smart and intelligent agriculture is being nurtured and driven by the deployment of tiny sensors or AI/ML enabled UAV’s or low powered Internet of Things setups for the sensing, monitoring, collection, processing and storing of the information over the cloud platforms. This book is ideal for researchers, academics, post-graduate students and practitioners of agricultural universities, who want to embrace new agricultural technologies for Determination of site-specific crop requirements, future farming strategies related to controlling of chemical sprays, yield, price assessments with the help of AI/ML driven intelligent decision support systems and use of agri-robots for sowing and harvesting. The book will be covering and exploring the applications and some case studies of each technology, that have heavily made impact as grand successes. The main aim of the book is to give the readers immense insights into the impact and scope of WSN, IoT, AI and ML in the growth of intelligent digital farming and Agriculture revolution 5.0.The book also focuses on feasibility of precision farming and the problems faced during adoption of precision farming techniques, its potential in India and various policy measures taken all over the world. The reader can find a description of different decision support tools like crop simulation models, their types, and application in PA. Features: Detailed description of the latest tools and technologies available for the Agriculture 5.0. Elaborative information for different type of hardware, platforms and machine learning techniques for use in smart farming. Elucidates various types of predictive modeling techniques available for intelligent and accurate agricultural decision making from real time collected information for site specific precision farming. Information about different type of regulations and policies made by all over the world for the motivation farmers and innovators to invest and adopt the AI and ML enabled tools and farming systems for sustainable production.
Author: Food and Agriculture Organization of the United Nations
Publisher: Food & Agriculture Org.
ISBN: 9251315469
Category : Social Science
Languages : en
Pages : 152
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Book Description
This report aims to identify the different scenarios where the process of digital transformation is taking place in agriculture. This identifies those aspects of basic conditions, such as those of infrastructure and networks, affordability, education and institutional support. In addition, enablers are identified, which are the factors that allow adopting and integrating changes in the production and decision-making processes. Finally identify through cases, existing literature and reports how substantive changes are taking place in the adoption of digital technologies in agriculture.
