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  • 1
    Online Resource
    Online Resource
    Advanced Automation for Tree Fruit Orchards and Vineyards (2023)
    Cham :Springer International Publishing :
    Details
    Keywords: Agriculture. ; Control engineering. ; Robotics. ; Automation. ; Geographic information systems. ; Food science. ; Agriculture. ; Control, Robotics, Automation. ; Geographical Information System. ; Food Science.
    Description / Table of Contents: Fundamentals of Tree and Vine Physiology -- Mechanical Management of Modern Planar Fruit Tree Canopies -- Orchard Water Management -- Vineyard Water Management -- Pests and diseases management -- Advanced Technologies for Crop-load Management -- Mechanical Harvesting -- Autonomous Platforms -- Management Information Systems and Emerging Technologies -- Economic and Societal Aspects.
    Abstract: Modern tree fruit orchards and vineyards constitute complex production systems that are exposed to highly dynamic and stochastic natural, financial and societal forces, and face demands for increased production using fewer resources, with reduced environmental impact. Successful operation of orchards and vineyards under these conditions is practically impossible without careful and extensive use of state-of-the-art automation technologies and careful planning of future operations (e.g., training systems when replanting) that can be enabled by knowledge of emerging technologies and future trends. Also, improvement of existing automation technologies and development of novel future systems cannot be accomplished without a working understanding of the tree and vine biological production systems, their management needs, and the capabilities and limitations of existing automation systems. The book aims to provide the necessary knowledge to achieve the above goals in a way that can engage readers without engineering or horticultural backgrounds. .
    Type of Medium: Online Resource
    Pages: VII, 241 p. 1 illus. , online resource.
    Edition: 1st ed. 2023.
    ISBN: 9783031269417
    Series Statement: Agriculture Automation and Control,
    URL: https://doi.org/10.1007/978-3-031-26941-7
    DOI: 10.1007/978-3-031-26941-7
    DDC: 630
    Language: English
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  • 2
    Online Resource
    Online Resource
    Fundamentals of Agricultural and Field Robotics (2021)
    Cham :Springer International Publishing :
    Details
    Keywords: Agriculture. ; Control engineering. ; Robotics. ; Automation. ; Geographic information systems. ; Agriculture. ; Control, Robotics, Automation. ; Geographical Information System.
    Description / Table of Contents: Preface -- Chapter 1 -- Agricultural and Field Robotics: An Introduction -- Part I. Sensing and Machine Vision -- Chapter 2. Sensors I: Color Imaging and Basics of Image Processing -- Chapter 3. Sensors II: 3D Sensing Techniques and Systems -- Chapter 4. Sensors III: Spectral Sensing and Data Analysis -- Chapter 5. Crop Scouting and Surrounding Awareness for Specialty Crops -- Chapter 6. Crop Sensing and Its Application in Precision Agriculture and Crop Phenotyping -- Part II: Mechanisms, Dynamics and Control -- Chapter 7. Robotic Manipulation and Optimization for Agricultural and Field Applications -- Chapter 8. End-effector Technologies -- Chapter 9. Control Techniques in Robotic Harvesting -- Chapter 10. Guidance, Auto-Steering Systems and Control -- Chapter 11. Automated Infield Sorting and Handling of Apples -- Chapter 12. Modeling, Simulation and Visualization of Agricultural and Field Robotic Systems -- Part III: Emerging Topics in Agricultural and Field Robotics -- Chapter 13. Advanced Learning and Classification Techniques for Agricultural and Field Robotics -- Chapter 14. Digital Farming and Field Robotics - Internet of Things, Cloud Computing and Big Data -- Chapter 15. Human-Machine Interactions -- Chapter 16. Machinery-Canopy Interactions in Tree Fruit Crops -- Index.
    Abstract: Over the past century, mechanization has been an important means for optimizing resource utilization, improving worker health and safety and reducing labor requirements in farming while increasing productivity and quality of 4F (Food, Fuel, Fiber, Feed). Recognizing this contribution, agricultural mechanization was considered as one of the top ten engineering achievements of 20th century by the National Academy of Engineering. Accordingly farming communities have adopted increasing level of automation and robotics to further improve the precision management of crops (including input resources), increase productivity and reduce farm labor beyond what has been possible with conventional mechanization technologies. It is more important than ever to continue to develop and adopt novel automation and robotic solutions into farming so that some of the most complex agricultural tasks, which require huge amount of seasonal labor such as fruit and vegetable harvesting, could be automated while meeting the rapidly increasing need for 4F. In addition, continual innovation in and adoption of agricultural automation and robotic technologies is essential to minimize the use of depleting resources including water, minerals and other chemicals so that sufficient amount of safe and healthy food can be produced for current generation while not compromising the potential for the future generation. This book aims at presenting the fundamental principles of various aspects of automation and robotics as they relate to production agriculture (the branch of agriculture dealing with farming operations from field preparation to seeding, to harvesting and field logistics). The building blocks of agricultural automation and robotics that are discussed in the book include sensing and machine vision, control, guidance, manipulation and end-effector technologies. The fundamentals and operating principles of these technologies are explained with examples from cutting-edge research and development currently going on around the word. This book brings together scientists, engineers, students and professionals working in these and related technologies to present their latest examples of agricultural automation and robotics research, innovation and development while explaining the fundamentals of the technology. The book, therefore, benefits those who wish to develop novel agricultural engineering solutions and/or to adopt them in the future. .
    Type of Medium: Online Resource
    Pages: XIV, 455 p. 201 illus., 161 illus. in color. , online resource.
    Edition: 1st ed. 2021.
    ISBN: 9783030704001
    Series Statement: Agriculture Automation and Control,
    URL: https://doi.org/10.1007/978-3-030-70400-1
    DOI: 10.1007/978-3-030-70400-1
    DDC: 630
    Language: English
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  • 3
    Online Resource
    Online Resource
    Agricultural Cybernetics (2021)
    Cham :Springer International Publishing :
    Details
    Keywords: Agriculture. ; Control engineering. ; Food science. ; Cooperating objects (Computer systems). ; Engineering Data processing. ; Machine learning. ; Agriculture. ; Control and Systems Theory. ; Food Science. ; Cyber-Physical Systems. ; Data Engineering. ; Machine Learning.
    Description / Table of Contents: Preface -- Introduction -- Mathematics, Statistics and Representations for Cybernetic Systems -- Control and Communication Characteristics of Agricultural Production Systems -- Modeling of Crop Production Systems and System Characterization -- Control Theory and Agricultural Production -- Control of Agricultural production Systems -- Mearning from the Data -- Outlook and Summary Remarks -- Bibliography -- Index.
    Abstract: Agricultural systems are uniquely complex systems, given that agricultural systems are parts of natural and ecological systems. Those aspects bring in a substantial degree of uncertainty in system operation. Also, impact factors, such as weather factors, are critical in agricultural systems but these factors are uncontrollable in system management. Modern agriculture has been evolving through precision agriculture beginning in the late 1980s and biotechnological innovations in the early 2000s. Precision agriculture implements site-specific crop production management by integrating agricultural mechanization and information technology in geographic information system (GIS), global navigation satellite system (GNSS), and remote sensing. Now, precision agriculture is set to evolve into smart agriculture with advanced systematization, informatization, intelligence and automation. From precision agriculture to smart agriculture, there is a substantial amount of specific control and communication problems that have been investigated and will continue to be studied. In this book, the core ideas and methods from control problems in agricultural production systems are extracted, and a system view of agricultural production is formulated for the analysis and design of management strategies to control and optimize agricultural production systems while exploiting the intrinsic feedback information-exchanging mechanisms. On this basis, the theoretical framework of agricultural cybernetics is established to predict and control the behavior of agricultural production systems through control theory.
    Type of Medium: Online Resource
    Pages: XIV, 255 p. 111 illus., 94 illus. in color. , online resource.
    Edition: 1st ed. 2021.
    ISBN: 9783030721022
    Series Statement: Agriculture Automation and Control,
    URL: https://doi.org/10.1007/978-3-030-72102-2
    DOI: 10.1007/978-3-030-72102-2
    DDC: 630
    Language: English
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  • 4
    Online Resource
    Online Resource
    Soil and Crop Sensing for Precision Crop Production (2022)
    Cham :Springer International Publishing :
    Details
    Keywords: Agriculture. ; Control engineering. ; Robotics. ; Automation. ; Geographic information systems. ; Soil science. ; Agriculture. ; Control, Robotics, Automation. ; Geographical Information System. ; Soil Science.
    Description / Table of Contents: 1 Soil and Crop Sensing for Precision Crop Production: An Introduction -- 2 Sensing Technology of Soil Physical Properties -- 3 Theories and Methods for Soil Nutrient Sensing -- 4 Application of Soil Sensing in Precision Agriculture -- 5 Theories and Methods for Spectroscopy-based Crop Nutrient Sensing -- 6 Remote sensing technologies for crop disease and pest detection -- 7 Plant Phenotyping -- 8 Crop Sensing in Precision Agriculture -- 9 Perspectives of Soil and Crop Sensing in Smart Agriculture -- Index -- .
    Abstract: Soil and crop sensing is a fundamental component and the first important step in precision agriculture. Unless the level of soil and crop variability is known, appropriate management decisions cannot be made and implemented. In the last few decades, various ground-based sensors have been developed to measure spatial variability in soil properties and nutrients, crop growth and yield, and pest conditions. Remote sensing as an important data collection tool has been increasingly used to map soil and crop growth variability as spatial, spectral and temporal resolutions of image data have improved significantly in recent years. While identifying spatial variability of soil and crop growth within fields is an important first step towards precision management, using that variability to formulate variable rate application plans of farming inputs such as fertilizers and pesticides is another essential step in precision agriculture.The purpose of this book is to present the historical, current and future developments of soil and crop sensing technologies with fundamentals and practical examples. The first chapter gives an overview of soil and crop sensing technologies for precision crop production. The next six chapters provide details on theories, methods, practical applications, as well as challenges and future research needs for all aspects of soil and crop sensing. The last two chapters show how soil and crop sensing technologies can be used for plant phenotyping and precision fertilization. The chapters are written by some of the world’s leading experts who have contributed significantly to the developments of precision agriculture technologies, especially in the area of soil and crop sensing. They use their knowledge, experiences, and successful stories to present informative and up-to-date information on relevant topics. Therefore, this book is an invaluable addition to the literature and can be used as a reference by scientists, engineers, practitioners, and college students for the dissemination and advancement of precision agriculture technologies for practical applications.
    Type of Medium: Online Resource
    Pages: XII, 324 p. 93 illus., 71 illus. in color. , online resource.
    Edition: 1st ed. 2022.
    ISBN: 9783030704322
    Series Statement: Agriculture Automation and Control,
    URL: https://doi.org/10.1007/978-3-030-70432-2
    DOI: 10.1007/978-3-030-70432-2
    DDC: 630
    Language: English
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  • 5
    Online Resource
    Online Resource
    Agricultural Internet of Things : Technologies and Applications (2021)
    Cham :Springer International Publishing :
    Details
    Keywords: Agriculture. ; Bioinformatics. ; Application software. ; Control engineering. ; Robotics. ; Automation. ; Food science. ; Agriculture. ; Computational and Systems Biology. ; Computer and Information Systems Applications. ; Control, Robotics, Automation. ; Food Science.
    Description / Table of Contents: 1.Introduction of Agricultural IoT -- 2.Agricultural IoT Standardization and System Applications -- 3.Data Communication and Networking Technologies -- 4.Soil Information Sensing Technology -- 5.Crop Information Sensing Technology -- 6.Field Condition Sensing Technology -- 7.Livestock and Aquaculture Information Sensing Technology -- 8.Agricultural Information Processing Technology -- 9.Agricultural Decision-Making Methods and Systems -- 10.IoT Management of Field Crops and Orchards -- 11.Plant Factory IoT Management -- 12.Livestock and Aquaculture IoT Systems -- 13.Agricultural Products Traceability System Applications -- 14.Integrated IoT Applications Platform Based on Cloud Technology and Big Data.
    Abstract: Internet of things (IoT) is a new type of network that combines communication technology, expanded applications, and physical devices. Among them, agriculture is one of the most important areas in the application of the IoT technology, which has its unique requirements and integration features. Compared to the information technology in traditional agriculture, the agricultural IoT mainly refers to industrialized production and sustainable development under relatively controllable conditions. Agricultural IoT applies sensors, RFID, visual capture terminals and other types of sensing devices to detect and collect site information, and with broad applications in field planting, facility horticulture, livestock and poultry breeding, aquaculture and agricultural product logistics. It utilizes multiple information transmission channels such as wireless sensor networks, telecommunications networks and the internet to achieve reliable transmission of agricultural information at multiple scales and intelligently processes the acquired, massive information. The goals are to achieve (i) optimal control of agricultural production process, (ii) intelligent electronic trading of agricultural products circulation, and (iii) management of systematic logistics, quality and safety traceability. This book focuses on three levels of agricultural IoT network: information perception technology, information transmission technology and application technology. .
    Type of Medium: Online Resource
    Pages: XI, 439 p. 184 illus., 133 illus. in color. , online resource.
    Edition: 1st ed. 2021.
    ISBN: 9783030657024
    Series Statement: Agriculture Automation and Control,
    URL: https://doi.org/10.1007/978-3-030-65702-4
    DOI: 10.1007/978-3-030-65702-4
    DDC: 630
    Language: English
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  • 6
    Electronic Resource
    Electronic Resource
    Prediction Models and Generalization Performance Study in Electrical Discharge Machining (2007)
    s.l. ; Stafa-Zurich, Switzerland
    Applied mechanics and materials Vol. 10-12 (Dec. 2007), p. 677-681 
    Details
    ISSN: 1662-7482
    Source: Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: In the past decade, artificial neural network(ANN) has been applied in Electricaldischarge machining(EDM). However, most of them only discuss parameter prediction oroptimization result, few tell how to improve generalization performance. In this study, machiningprocess models have been established based on different training algorithms of ANN, namelyLevenberg-Marquardt algorithm (LM), Resilient algorithm (RP), Scaled Conjugate Gradientalgorithm (SCG) and Quasi-Newton algorithm(BFGS). All models have been trained by sameexperimental data, checked by another group data, their generalization performance are compared.Take LM as the example, some main factors that may influence generalization performance arediscussed
    Type of Medium: Electronic Resource
    URL: http://www.tib-hannover.de/fulltexts/2011/0528/01/38/transtech_doi~10.4028%252Fwww.scientific.net%252FAMM.10-12.677.pdf
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  • 7
    Electronic Resource
    Electronic Resource
    Determination of Major/ Minor and Trace Elements in Seamount Phosphorite by XRF Spectrometry (2004)
    Oxford, UK : Blackwell Publishing Ltd
    Geostandards and geoanalytical research 28 (2004), S. 0 
    Details
    ISSN: 1751-908X
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Geosciences
    Notes: In this paper, a method developed to determine the major, minor and trace elements, including carbon and the four halogens, in seamount phosphorite involving a modern XRF spectrometry technique is described. Ultra-fine (99% v/v 〈 40 μm) powder samples (4 g) were directly pressed into pellets (Φ= 30 mm). For elements having an analytical line lower in energy than the energy of Fe Kα line absorption edge, the inter-element absorption-enhancement effects were corrected using an influence coefficient method. For the other elements, the matrix effects were corrected using the ratio of element peak to Rh Kα Compton peak (for I, Rh K|3 Compton peak was used instead). The relative standard deviation was smaller than 1.0% for the major elements (except C, Na and Cl). The detection limit levels of C, F, Cl, Br and I were 30, 20, 0.8, 0.2 and 0.3 (μg g−1 respectively for 100 s count time of background. The accuracy of this method was tested by evaluating determinations on three certified reference materials. The direct analysis of major and minor elements in geological materials by pressed pellet without any chemical procedures makes XRF spectrometry a particularly environment-friendly analytical technique.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1751-908X.2004.tb01044.x
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  • 8
    Electronic Resource
    Electronic Resource
    Modeling Selectivity in Households' Purchase Quantity Outcomes: A Count Data Approach (2005)
    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    Review of marketing science 3.2005, 1, art2 
    Details
    ISSN: 1546-5616
    Source: Berkeley Electronic Press Academic Journals
    Topics: Economics
    Notes: We present an econometric technique for modeling endogenous selectivity in households' quantity outcomes as observed in scanner panel data. Simultaneous models of incidence, brand choice and quantity, that treat quantity outcomes as count data, ignore such self-selectivity considerations in quantity outcomes. Previously proposed approaches to modeling selectivity in continuous quantity outcomes do not apply to count data. Therefore, we adopt a recently proposed econometric technique to deal with selectivity in count data, and then appropriately extend it to handle correlations of quantity outcomes not only with incidence outcomes but also with brand choice outcomes. Our proposed methodology will be useful to researchers who want to estimate simultaneous models of whether, what and how much to buy decisions of households, treating quantity data as counts.
    Type of Medium: Electronic Resource
    URL: http://www.bepress.com/romsjournal/vol3/iss1/art2
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  • 9
    Electronic Resource
    Electronic Resource
    A fractal study on sunspot relative number
    Amsterdam : Elsevier
    Chinese Astronomy and Astrophysics 18 (1994), S. 313-318 
    Details
    ISSN: 0275-1062
    Keywords: The Sun-sunspot relative number-solar prediction
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Physics
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1016/0275-1062(94)90045-0
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  • 10
    Electronic Resource
    Electronic Resource
    Research on dynamical behavior and predictability for monthly mean variations of the 10.7cm radio flux AAnS 13/1 (1993) 67-72
    Amsterdam : Elsevier
    Chinese Astronomy and Astrophysics 17 (1993), S. 241 
    Details
    ISSN: 0275-1062
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Physics
    Type of Medium: Electronic Resource
    URL: http://linkinghub.elsevier.com/retrieve/pii/0275-1062(93)90086-5
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