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    Smart Agriculture

    Concepts, Strategies, and Case Studies

    AvVeronica Saiz-Rubio,Francisco Rovira-Mas

    Inbunden, Engelska, 2026

    Del i serien Nextgen Agriculture

    1 755 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    Smart Agriculture: Concepts, Strategies, and Case Studies showcases improvements in agricultural technology, bringing together work from leading experts in the field. It explores techniques and disciplines essential for the widespread adoption of precision agriculture, including artificial intelligence (AI), machine learning, the Internet of Things (IoT), Agriculture 5.0, smart spraying systems, and decision support tools that are transforming modern farming practices.Designed to introduce readers to the vast potential of data-driven agriculture, this book presents information on smart agriculture through practical, real-world applications. It features a diverse range of case studies across various crops and agricultural operations, offering actionable insights into innovative solutions. Highlights include variable-rate orchard spraying for high-density canopies like olives and oranges, image analysis for evaluating apple and grape properties, digital tools for optimizing irrigation, geostatistical modelling of Xylella fastidiosa, UAV-assisted fertilization of olive trees, automated wheat growth monitoring, smart agriculture techniques for peach production, greenhouse data management, digital twins for strawberry cultivation, deep learning for obstacle detection in robotic rice harvesters, and IoT middleware solutions for arable crops and livestock.A book in the NextGen Agriculture: Novel Concepts & Innovative Strategies series, this comprehensive resource is ideal for professional engineers, researchers in agricultural engineering, computer science, machine vision, and remote sensing, as well as technology developers. Graduate students specializing in digital agriculture and precision farming will also find this book invaluable for understanding the transformative power of modern agricultural technologies.

    Produktinformation

    • Utgivningsdatum:2026-02-27
    • Mått:178 x 254 x 18 mm
    • Vikt:630 g
    • Format:Inbunden
    • Språk:Engelska
    • Serie:Nextgen Agriculture
    • Antal sidor:234
    • Förlag:Taylor & Francis Ltd
    • ISBN:9781032823386

    Utforska kategorier

    • Lantbruk, fiske och skogsbruk inom Ekonomi och Ledarskap
    • Biokemisk teknik inom Naturvetenskap och teknik
    • Agronomi inom Naturvetenskap och teknik

    Mer om författaren

    Verónica Saiz-Rubio studied Agricultural Engineering and holds a PhD in Automation, Robotics, and Industrial Informatics from the Universitat Politecnica de Valencia (UPV, Valencia, Spain) and a degree in Mechanical Engineering from Linnéuniversitetet (Växjö, Sweden). She completed a postdoctoral fellowship at the Field Robotics Laboratory (FiRO) in Kyoto, Japan. As a member of the Agricultural Robotics Laboratory (ARL) at the UPV, she is responsible for data and image processing and the development of high-resolution plot maps. She also collaborates in the design, construction, and automation of ground robots developed within the European projects VineRobot, VineScout, and Cerberus, serving as part of the coordinating team for the latter two. Dr. Saiz-Rubio has received seven research awards, including an award for the quality of scientific articles from the American Society of Agricultural Engineers (ASABE), an award for outstanding young researcher articles (Armand Blanc Prize) from the International Commission on Agricultural and Biosystems Engineering (CIGR), and an award for innovative young researcher projects (Farming by Satellite Prize) from the European Navigation Satellite Systems Agency (GSA). Regarding her teaching activities, Dr. Saiz-Rubio has collaborated on courses on Precision Agriculture and Digital Technologies for the agri-food sector. She currently teaches at the university level in the areas of Agricultural Robotics and Digital Agriculture.Francisco Rovira-Más earned a degree in Agricultural Engineering in 1996 from the Universitat Politècnica de València (UPV, Valencia, Spain), where he was an Assistant Professor from 1997 to 2000. He earned his PhD in 2003 in the University of Illinois at Urbana-Champaign (Urbana, IL, USA). He has been a member of the Intelligent Vehicles System group at the John Deere Technology Center in Moline, IL, USA. He has also been a Research Associate with the Department of Agricultural and Biological Engineering at the University of Illinois, conducting research at the John Deere Intelligent Vehicle Systems unit (formerly Agricultural Management Solutions - AMS) in Urbandale, IA, USA. Currently, Dr. Rovira-Más is a Professor at the Universitat Politècnica de València in Spain and director of the Agricultural Robotics Laboratory. His research interests include autonomous vehicles, machine vision, controls, off-road equipment automation, robotics, and artificial intelligence. Dr. Rovira-Más has been the technical manager of the European project VineRobot and the coordinator of the EU H2020 FTI project VineScout. At present, he is the coordinator of project Cerberus, funded with 4.8 M€ and involving thirteen institutions from Slovenia, Italy, Cyprus, and Spain.Chittaranjan Kole is an internationally reputed scientist with an illustrious professional career spanning over 38 years and original contributions in the fields of plant genomics, biotechnology and molecular breeding leading to the publication of more than 160 quality research articles and reviews. He has edited over 170 books for the leading publishers of the world. Prof. Kole's scientific contributions and editing acumen have been appreciated by seven Nobel Laureates including Profs. Norman Borlaug, Arthur Kornberg, Werner Arber, Phillip Sharp, Günter Blobel, Lee Hartwell and Roger Kornberg. He has been honored with a number of Fellowships, Honorary Fellowships, and national and international awards including the Outstanding Crop Scientist award conferred by the International Crop Science Society. He has served at all prestigious positions in academia including as Vice-Chancellor BC Agricultural University, Project Coordinator of Indo-Russian Center of Biotechnology in India, and Director of Research of Institute of Nutraceutical Research of Clemson University, in USA. He worked also in the Pennsylvania State University and Clemson University as Visiting Professor in USA. He was awarded with the Raja Ramanna Fellow by the Department of Energy, Government of India. Prof. Kole is also heading the International Climate-Resilient Crop Genomics Consortium and International consortium for Phytomedomics and Nutriomics as their founding Principal Coordinator and presently as President.

    Innehållsförteckning

    • Chapter 1. Variable-rate spraying for sustainable citrus and grape productionVerónica Saiz-Rubio, Francisco Rovira-Más, and Carla Román-RochinaChapter 2. Image analysis techniques for fruit assessment in apples and grapesJulie Tang, Annie Xu Wang, and Mark WhittyChapter 3. Chapter 3 Digital tools in the context of Agriculture 4.0 for integrated management of orchard cropsStanley Best, José Maldonado, Melany Navarro, and Valentina De la BarreraChapter 4. Geostatistical modelling of multispectral data for monitoring Xylella fastidiosa in olive groves.Antonella Belmonte, Gabriele Buttafuoco, and Annamaria CastrignanòChapter 5. UAV remote sensing for fertilization rating in olive groves.Eliseo Roma and Pietro CataniaChapter 6. Smart Agriculture for Peach Orchard ManagementIrene Borra-Serrano, José Manuel Peña, Joe M. Maja, Juan Carlos Melgar, Kelly Nascimento-Silva, and Ana de CastroChapter 7. Decision-support systems for greenhouse horticulture.Lucio Colizzi, Emanuela Guerriero, Tommaso Adamo, and Nunzia LomonteChapter 8. Smart Sensing and Digital twin technology for yield estimation and phenomics prediction in strawberriesDaeun Choi, Xu Wang, and Omeed MirbodChapter 9. Remote Sensing for Automatic Disease Monitoring in WheatOrly Enrique Apolo-Apolo, Luis Sánchez-Fernández, Simon Appeltans, Gregorio Egea, and Manuel Perez-RuizChapter 10. Deep learning object detection for robotic harvesters in riceJiajun Zhu, Yang Li, and Michihisa IidaChapter 11. IoT Middleware solutions for arable crops and livestock farmingEleni Symeonaki, Konstantinos G. Arvanitis, Chrysanthos Maraveas, Dimitrios Loukatos, and Spyros Fountas
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