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            Precision Agriculture Technology for Crop Farming

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            Contributor(s)
            Zhang, Qin (editor)
            Language
            English
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            Abstract
            This book provides a review of precision agriculture technology development, followed by a presentation of the state-of-the-art and future requirements of precision agriculture technology. It presents different styles of precision agriculture technologies suitable for large scale mechanized farming; highly automated community-based mechanized production; and fully mechanized farming practices commonly seen in emerging economic regions. The book emphasizes the introduction of core technical features of sensing, data processing and interpretation technologies, crop modeling and production control theory, intelligent machinery and field robots for precision agriculture production.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/174310
            Keywords
            Crop Science; ENVIRO; AGRICULTURE; SCI-TECH; ENVIRONMENTALSCIENCE; STM; application; canopy; fertilization; fertilizer; monitor; reflectance; variable-rate; wheat; winter; yield; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PST Botany and plant sciences; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TV Agriculture and farming; thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography::RGW Geographical information systems, geodata and remote sensing
            DOI
            10.1201/b19336
            Publisher
            Taylor & Francis
            Publisher website
            http://www.taylorandfrancis.com/
            Publication date and place
            2016
            Imprint
            CRC Press
            Pages
            374
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            Credits


            • logo Investir l'avenirInvestir l'avenir
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            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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