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    <title language="deu">Entwicklung ertragskundlicher und ökologischer Paramter in einem Brandenburger Alley Cropping System</title>
    <parentTitle language="deu">Tagungsband 9. Forum Agroforstsysteme, 27. &amp; 28. September 2023</parentTitle>
    <identifier type="urn">urn:nbn:de:kobv:eb1-opus-7980</identifier>
    <note>https://agroforst-info.de/nachlese-9-forum-agroforstsysteme/</note>
    <licence>Urheberrechtsschutz</licence>
    <author>Tobias Cremer</author>
    <author>Lea Martetschläger</author>
    <author>Marco Bartsch</author>
    <author>Sina Riethmüller</author>
    <author>Carmel Schnautz</author>
    <author>Thomas Gaiser</author>
    <author>Ralf Bloch</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Agroforst; Modellprojekt; Brandenburg; Reallabor</value>
    </subject>
    <collection role="institutes" number="">Fachbereich Landschaftsnutzung und Naturschutz</collection>
    <collection role="institutes" number="">Fachbereich Wald und Umwelt</collection>
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    <collection role="Hochschulbibliographie" number="">Nicht ermittelbar</collection>
    <thesisPublisher>Hochschule für nachhaltige Entwicklung Eberswalde</thesisPublisher>
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    <id>799</id>
    <completedYear>2023</completedYear>
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    <language>deu</language>
    <pageFirst>133</pageFirst>
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    <title language="deu">Kichererbsen als Anpassung an den Klimawandel? Ergebnisse zum Ertragspotential und Herausforderungen aus einem Netzwerkversuch in Deutschland, Österreich und der Schweiz</title>
    <parentTitle language="deu">64. Tagung der Gesellschaft für Pflanzenbauwissenschaften e. V.: DIGITAL TOOLS, BIG DATA, MODELING AND SENSING METHODS FOR SUSTAINABLE AND CLIMATE SMART CROP AND GRASSLAND SYSTEMS; 4. bis 6. Oktober 2023; Göttingen</parentTitle>
    <identifier type="urn">urn:nbn:de:kobv:eb1-opus-7992</identifier>
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    <licence>Urheberrechtsschutz</licence>
    <author>M. Reckling</author>
    <author>M. Halwani</author>
    <author>A. Winterling</author>
    <author>A. Pflugfelder</author>
    <author>S. Zikeli</author>
    <author>D. Lehner</author>
    <author>J. Hiltbrunner</author>
    <author>V. Preußner</author>
    <author>H.-H. Lutzer</author>
    <author>Ralf Bloch</author>
    <author>C. Rusch</author>
    <author>O. Radtke</author>
    <author>I. Schwabe</author>
    <author>W. Karalus</author>
    <author>G. Rosner</author>
    <author>K. Salama</author>
    <author>C. Blessing</author>
    <collection role="institutes" number="">Fachbereich Landschaftsnutzung und Naturschutz</collection>
    <collection role="Hochschulbibliographie" number=""/>
    <collection role="Hochschulbibliographie" number="">Nicht ermittelbar</collection>
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  <doc>
    <id>717</id>
    <completedYear>2023</completedYear>
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    <language>deu</language>
    <pageFirst>790</pageFirst>
    <pageLast>791</pageLast>
    <pageNumber/>
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    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>Verlag Dr. Köster</publisherName>
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    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
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    <title language="deu">Der Netzwerkversuch: Ein Ansatz für die Praxisforschung?</title>
    <parentTitle language="deu">One Step Ahead - einen Schritt voraus! : Beiträge zur 16. Wissenschaftstagung Ökologischer Landbau : Frick, 7. bis 10. März 2023</parentTitle>
    <identifier type="isbn">978-3-96831-055-8</identifier>
    <identifier type="urn">urn:nbn:de:kobv:eb1-opus-7172</identifier>
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    <licence>Urheberrechtsschutz</licence>
    <author>August Bruckner</author>
    <author>H Schulz</author>
    <author>M Athmann</author>
    <author>Ralf Bloch</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>On-Farm-forschung; Feldversuch; Ernährungsmanagement; experimentelles Design</value>
    </subject>
    <collection role="institutes" number="">Fachbereich Landschaftsnutzung und Naturschutz</collection>
    <collection role="Hochschulbibliographie" number=""/>
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    <thesisPublisher>Hochschule für nachhaltige Entwicklung Eberswalde</thesisPublisher>
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  <doc>
    <id>702</id>
    <completedYear>2023</completedYear>
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    <language>deu</language>
    <pageFirst>411</pageFirst>
    <pageLast>412</pageLast>
    <pageNumber/>
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    <type>conferenceobject</type>
    <publisherName>Verlag Dr. Köster</publisherName>
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    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
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    <title language="deu">Erprobung autonomer Feldrobotik zur Beikrautregulierung für den Bio-Zuckerrübenanbau in der Uckermark - Ergebnisse aus dem Projekt zUCKERrübe -</title>
    <parentTitle language="deu">One Step Ahead - einen Schritt voraus! : Beiträge zur 16. Wissenschaftstagung Ökologischer Landbau : Frick, 7. bis 10. März 2023</parentTitle>
    <identifier type="isbn">978-3-96831-055-8</identifier>
    <identifier type="urn">urn:nbn:de:kobv:eb1-opus-7025</identifier>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
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    <licence>Urheberrechtsschutz</licence>
    <author>Amanda Birkmann</author>
    <author>Leonie Steinherr</author>
    <author>H-H Lutzer</author>
    <author>Ralf Bloch</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>ökologische Zuckerrüben; Beikrautregulierung; robotikgestützt</value>
    </subject>
    <collection role="institutes" number="">Fachbereich Landschaftsnutzung und Naturschutz</collection>
    <collection role="Hochschulbibliographie" number=""/>
    <collection role="Hochschulbibliographie" number="">Referiert</collection>
    <thesisPublisher>Hochschule für nachhaltige Entwicklung Eberswalde</thesisPublisher>
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  <doc>
    <id>800</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
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    <language>deu</language>
    <pageFirst>131</pageFirst>
    <pageLast>132</pageLast>
    <pageNumber>2</pageNumber>
    <edition/>
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    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
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    <title language="deu">Unkrautregulierung im ökologischen Zuckerrübenanbau in der Uckermark - Erprobung und Bewertung des autonomen Feldroboters Uckerbot</title>
    <parentTitle language="deu">64. Tagung der Gesellschaft für Pflanzenbauwissenschaften e. V.: DIGITAL TOOLS, BIG DATA, MODELING AND SENSING METHODS FOR SUSTAINABLE AND CLIMATE SMART CROP AND GRASSLAND SYSTEMS; 4. bis 6. Oktober 2023; Göttingen</parentTitle>
    <identifier type="urn">urn:nbn:de:kobv:eb1-opus-8003</identifier>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Urheberrechtsschutz</licence>
    <author>L. Steinherr</author>
    <author>T. Krachunova</author>
    <author>A. Birkmann</author>
    <author>D. I. Acosta Ortiz</author>
    <author>Ralf Bloch</author>
    <author>S. D. Bellingrath-Kimura</author>
    <collection role="institutes" number="">Fachbereich Landschaftsnutzung und Naturschutz</collection>
    <collection role="Hochschulbibliographie" number=""/>
    <collection role="Hochschulbibliographie" number="">Nicht ermittelbar</collection>
    <thesisPublisher>Hochschule für nachhaltige Entwicklung Eberswalde</thesisPublisher>
  </doc>
  <doc>
    <id>801</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>13</pageNumber>
    <edition/>
    <issue/>
    <volume>16</volume>
    <type>article</type>
    <publisherName>Elsevier</publisherName>
    <publisherPlace/>
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    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2023-05-09</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The Digital Agricultural Knowledge and Information System (DAKIS): Employing digitalisation to encourage diversified and multifunctional agricultural systems</title>
    <abstract language="eng">Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity, biodiversity, and the provision of ecosystem services. The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems. We present the Digital Agricultural Knowledge and Information System (DAKIS) to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture. To develop the DAKIS, we specified, together with stakeholders, requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools. The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity, the capacity to foster communication and cooperation between farmers and other actors, and the ability to link multiple spatiotemporal scales and sustainability levels. To overcome these challenges, the DAKIS provides a digital platform to support farmers' decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources. The approach integrates remote and in situ sensors, artificial intelligence, modelling, stakeholder-stated demand for biodiversity and ecosystem services, and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design, including natural and agronomic factors, economic and policy considerations, and socio-cultural preferences and settings. Ultimately, the DAKIS embeds the consideration of ecosystem services, biodiversity, and sustainability into farmers' decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers' objectives and societal demands.</abstract>
    <parentTitle language="eng">Environmental Science and Ecotechnology</parentTitle>
    <identifier type="issn">2666-4984</identifier>
    <identifier type="doi">10.1016/j.ese.2023.100274</identifier>
    <identifier type="urn">urn:nbn:de:kobv:eb1-opus-8012</identifier>
    <enrichment key="opus.import.data">@articleMOURATIADOU2023100274, title = The Digital Agricultural Knowledge and Information System (DAKIS): Employing digitalisation to encourage diversified and multifunctional agricultural systems, journal = Environmental Science and Ecotechnology, volume = 16, pages = 100274, year = 2023, issn = 2666-4984, doi = https://doi.org/10.1016/j.ese.2023.100274, url = https://www.sciencedirect.com/science/article/pii/S266649842300039X, author = Ioanna Mouratiadou and Nahleen Lemke and Cheng Chen and Ariani Wartenberg and Ralf Bloch and Marco Donat and Thomas Gaiser and Deepak Hanike Basavegowda and Katharina Helming and Seyed Ali Hosseini Yekani and Marcos Krull and Kai Lingemann and Joseph Macpherson and Marvin Melzer and Claas Nendel and Annette Piorr and Mostafa Shaaban and Peter Zander and Cornelia Weltzien and Sonoko Dorothea Bellingrath-Kimura, keywords = Digital agriculture, Ecosystem services, Decision support system, Farming practices, Biodiversity, Modelling, Small-scale management, abstract = Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity, biodiversity, and the provision of ecosystem services. The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems. We present the Digital Agricultural Knowledge and Information System (DAKIS) to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture. To develop the DAKIS, we specified, together with stakeholders, requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools. The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity, the capacity to foster communication and cooperation between farmers and other actors, and the ability to link multiple spatiotemporal scales and sustainability levels. To overcome these challenges, the DAKIS provides a digital platform to support farmers’ decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources. The approach integrates remote and in situ sensors, artificial intelligence, modelling, stakeholder-stated demand for biodiversity and ecosystem services, and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design, including natural and agronomic factors, economic and policy considerations, and socio-cultural preferences and settings. Ultimately, the DAKIS embeds the consideration of ecosystem services, biodiversity, and sustainability into farmers’ decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers’ objectives and societal demands.</enrichment>
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    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International</licence>
    <author>Ioanna Mouratiadou</author>
    <author>Nahleen Lemke</author>
    <author>Cheng Chen</author>
    <author>Ariani Wartenberg</author>
    <author>Ralf Bloch</author>
    <author>Marco Donat</author>
    <author>Thomas Gaiser</author>
    <author>Deepak Hanike Basavegowda</author>
    <author>Katharina Helming</author>
    <author>Seyed Ali Hosseini Yekani</author>
    <author>Marcos Krull</author>
    <author>Kai Lingemann</author>
    <author>Joseph Macpherson</author>
    <author>Marvin Melzer</author>
    <author>Claas Nendel</author>
    <author>Annette Piorr</author>
    <author>Mostafa Shaaban</author>
    <author>Peter Zander</author>
    <author>Cornelia Weltzien</author>
    <author>Sonoko Dorothea Bellingrath-Kimura</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Digital agriculture</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Ecosystem services</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Decision support system</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Farming practices</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Biodiversity</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Modelling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Small-scale management</value>
    </subject>
    <collection role="open_access" number="">open_access</collection>
    <collection role="institutes" number="">Fachbereich Landschaftsnutzung und Naturschutz</collection>
    <collection role="Hochschulbibliographie" number=""/>
    <collection role="Hochschulbibliographie" number="">Zweitveröffentlichung</collection>
    <collection role="Hochschulbibliographie" number="">Referiert</collection>
    <thesisPublisher>Hochschule für nachhaltige Entwicklung Eberswalde</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-hnee/files/801/1-s2.0-S266649842300039X-main.pdf</file>
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