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A Platform for GHG Emissions Management in Mixed Farms

Author

Listed:
  • Dana Cătălina Popa

    (Faculty of Animal Productions Engineering and Management, University of Agronomic Sciences and Veterinary Medicine of Bucharest, 011464 Bucharest, Romania)

  • Yolanda Laurent

    (R&D Department, BEIA Consult International, 041386 Bucharest, Romania)

  • Răzvan Alexandru Popa

    (Faculty of Animal Productions Engineering and Management, University of Agronomic Sciences and Veterinary Medicine of Bucharest, 011464 Bucharest, Romania)

  • Adrian Pasat

    (R&D Department, BEIA Consult International, 041386 Bucharest, Romania)

  • Mihaela Bălănescu

    (R&D Department, BEIA Consult International, 041386 Bucharest, Romania)

  • Ekaterina Svertoka

    (R&D Department, BEIA Consult International, 041386 Bucharest, Romania)

  • Elena Narcisa Pogurschi

    (Faculty of Animal Productions Engineering and Management, University of Agronomic Sciences and Veterinary Medicine of Bucharest, 011464 Bucharest, Romania)

  • Livia Vidu

    (Faculty of Animal Productions Engineering and Management, University of Agronomic Sciences and Veterinary Medicine of Bucharest, 011464 Bucharest, Romania)

  • Monica Paula Marin

    (Faculty of Animal Productions Engineering and Management, University of Agronomic Sciences and Veterinary Medicine of Bucharest, 011464 Bucharest, Romania)

Abstract

This research introduces an innovative platform designed to manage greenhouse gas (GHG) emissions in mixed farms. Emphasizing the urgent need to address GHG emissions, particularly methane (CH 4 ) and nitrous oxide (N 2 O), the platform targets mixed farming systems where the interplay of livestock and crop production significantly contributes to environmental impacts. Our methodology is grounded in comprehensive data collection, encompassing soil data, energy consumption, and detailed livestock information. Utilizing the Agricultural Internet of Things (AIoT), it facilitates real-time data acquisition and analysis, providing insights into various farm activities’ GHG emissions. This approach allows for precise monitoring and management of emissions from different sources, including enteric fermentation in livestock and fertilizer use in crop production. Results from the application show its effectiveness in offering a clear and interactive visualization of GHG emissions, aiding farmers in making informed decisions for sustainable farm management. The platform’s user management system, coupled with advanced data processing and visualization capabilities, underscores its potential as a vital tool for sustainable farming. Conclusively, Solution4Farming represents a significant advancement in digital agriculture, combining IoT technology with sustainable practices. Though initially designed for Romanian cattle farming, Solution4Farming’s anticipated expansion to various farming environments suggests a broader impact and relevance in sustainable agriculture.

Suggested Citation

  • Dana Cătălina Popa & Yolanda Laurent & Răzvan Alexandru Popa & Adrian Pasat & Mihaela Bălănescu & Ekaterina Svertoka & Elena Narcisa Pogurschi & Livia Vidu & Monica Paula Marin, 2023. "A Platform for GHG Emissions Management in Mixed Farms," Agriculture, MDPI, vol. 14(1), pages 1-25, December.
    • Handle: RePEc:gam:jagris:v:14:y:2023:i:1:p:78-:d:1310963
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    References listed on IDEAS

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    1. Hanqin Tian & Rongting Xu & Josep G. Canadell & Rona L. Thompson & Wilfried Winiwarter & Parvadha Suntharalingam & Eric A. Davidson & Philippe Ciais & Robert B. Jackson & Greet Janssens-Maenhout & Mic, 2020. "A comprehensive quantification of global nitrous oxide sources and sinks," Nature, Nature, vol. 586(7828), pages 248-256, October.
    2. Evangelos Alexandropoulos & Vasileios Anestis & Federico Dragoni & Anja Hansen & Saoirse Cummins & Donal O’Brien & Barbara Amon & Thomas Bartzanas, 2023. "Decision Support Systems Based on Gaseous Emissions and Their Impact on the Sustainability Assessment at the Livestock Farm Level: An Evaluation from the User’s Side," Sustainability, MDPI, vol. 15(17), pages 1-29, August.
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    Cited by:

    1. Miaoling Bu & Weiming Xi & Yu Wang & Guofeng Wang, 2024. "Scenario-Based Modeling of Agricultural Nitrous Oxide Emissions in China," Agriculture, MDPI, vol. 14(11), pages 1-17, November.

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