IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i6p3517-d772982.html
   My bibliography  Save this article

Intense Pasture Management in Brazil in an Integrated Crop-Livestock System Simulated by the DayCent Model

Author

Listed:
  • Yane Freitas Silva

    (School of Agricultural Engineering (FEAGRI), University of Campinas (UNICAMP), Campinas 13083-875, SP, Brazil)

  • Rafael Vasconcelos Valadares

    (Centre of Energy Planning (NIPE), University of Campinas (UNICAMP), Campinas 13083-875, SP, Brazil)

  • Henrique Boriolo Dias

    (Centre of Energy Planning (NIPE), University of Campinas (UNICAMP), Campinas 13083-875, SP, Brazil)

  • Santiago Vianna Cuadra

    (Embrapa Agricultural Informatics (CNPTIA), Brazilian Agricultural Research Company (EMBRAPA), Campinas 13083-886, SP, Brazil)

  • Eleanor E. Campbell

    (Earth Systems Research Center, University of New Hampshire, Durham, NH 03824, USA)

  • Rubens A. C. Lamparelli

    (Centre of Energy Planning (NIPE), University of Campinas (UNICAMP), Campinas 13083-875, SP, Brazil)

  • Edemar Moro

    (Department of Agronomy, University of Western São Paulo, Presidente Prudente 19067-175, SP, Brazil)

  • Rafael Battisti

    (Agronomy School, Federal University of Goiás, Goiânia 74690-900, GO, Brazil)

  • Marcelo R. Alves

    (Department of Agronomy, University of Western São Paulo, Presidente Prudente 19067-175, SP, Brazil)

  • Paulo S. G. Magalhães

    (Centre of Energy Planning (NIPE), University of Campinas (UNICAMP), Campinas 13083-875, SP, Brazil)

  • Gleyce K. D. A. Figueiredo

    (School of Agricultural Engineering (FEAGRI), University of Campinas (UNICAMP), Campinas 13083-875, SP, Brazil)

Abstract

Process-based models (PBM) are important tools for understanding the benefits of Integrated Crop-Livestock Systems (ICLS), such as increasing land productivity and improving environmental conditions. PBM can provide insights into the contribution of agricultural production to climate change and help identify potential greenhouse gas (GHG) mitigation and carbon sequestration options. Rehabilitation of degraded lands is a key strategy for achieving food security goals and can reduce the need for new agricultural land. This study focused on the calibration and validation of the DayCent PBM for a typical ICLS adopted in Brazil from 2018 to 2020. We also present the DayCent parametrization for two forage species (ruzigrass and millet) grown simultaneously, bringing some innovation in the modeling challenges. We used aboveground biomass to calibrate the model, randomly selecting data from 70% of the paddocks in the study area. The calibration obtained a coefficient of determination (R 2 ) of 0.69 and a relative RMSE of 37.0%. During the validation, we used other variables (CO 2 flux, grain biomass, and soil water content) measured in the ICLS and performed a double validation for plant growth to evaluate the robustness of the model in terms of generalization. R 2 validations ranged from 0.61 to 0.73, and relative RMSE from 11.3 to 48.3%. Despite the complexity and diversity of ICLS results show that DayCent can be used to model ICLS, which is an important step for future regional analyses and large-scale evaluations of the impacts of ICLS.

Suggested Citation

  • Yane Freitas Silva & Rafael Vasconcelos Valadares & Henrique Boriolo Dias & Santiago Vianna Cuadra & Eleanor E. Campbell & Rubens A. C. Lamparelli & Edemar Moro & Rafael Battisti & Marcelo R. Alves & , 2022. "Intense Pasture Management in Brazil in an Integrated Crop-Livestock System Simulated by the DayCent Model," Sustainability, MDPI, vol. 14(6), pages 1-24, March.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3517-:d:772982
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/6/3517/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/6/3517/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Susanne Wiesner & Alison J. Duff & Ankur R. Desai & Kevin Panke-Buisse, 2020. "Increasing Dairy Sustainability with Integrated Crop–Livestock Farming," Sustainability, MDPI, vol. 12(3), pages 1-21, January.
    2. Kuhn, Max, 2008. "Building Predictive Models in R Using the caret Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i05).
    3. Garrison, M. V. & Batchelor, W. D. & Kanwar, R. S. & Ritchie, J. T., 1999. "Evaluation of the CERES-Maize water and nitrogen balances under tile-drained conditions," Agricultural Systems, Elsevier, vol. 62(3), pages 189-200, December.
    4. Marek Jarecki & Kumudinie Kariyapperuma & Bill Deen & Jordan Graham & Amir Behzad Bazrgar & Sowthini Vijayakumar & Mahendra Thimmanagari & Andrew Gordon & Paul Voroney & Naresh Thevathasan, 2020. "The Potential of Switchgrass and Miscanthus to Enhance Soil Organic Carbon Sequestration—Predicted by DayCent Model," Land, MDPI, vol. 9(12), pages 1-17, December.
    5. McClelland, Shelby C. & Paustian, Keith & Williams, Stephen & Schipanski, Meagan E., 2021. "Modeling cover crop biomass production and related emissions to improve farm-scale decision-support tools," Agricultural Systems, Elsevier, vol. 191(C).
    6. United Nations, 2016. "The Sustainable Development Goals 2016," Working Papers id:11456, eSocialSciences.
    7. Anna, Petrenko, . "Мaркування готової продукції як складова частина інформаційного забезпечення маркетингової діяльності підприємств овочепродуктового підкомплексу," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 2(01).
    8. Stehfest, Elke & Heistermann, Maik & Priess, Joerg A. & Ojima, Dennis S. & Alcamo, Joseph, 2007. "Simulation of global crop production with the ecosystem model DayCent," Ecological Modelling, Elsevier, vol. 209(2), pages 203-219.
    9. Anghinoni, Guilherme & Anghinoni, Fernanda Brunetta Godinho & Tormena, Cássio Antonio & Braccini, Alessandro Lucca & de Carvalho Mendes, Ieda & Zancanaro, Leandro & Lal, Rattan, 2021. "Conservation agriculture strengthen sustainability of Brazilian grain production and food security," Land Use Policy, Elsevier, vol. 108(C).
    10. Yang, J.M. & Yang, J.Y. & Liu, S. & Hoogenboom, G., 2014. "An evaluation of the statistical methods for testing the performance of crop models with observed data," Agricultural Systems, Elsevier, vol. 127(C), pages 81-89.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ivan Bergier & Jayme G. A. Barbedo & Édson L. Bolfe & Luciana A. S. Romani & Ricardo Y. Inamasu & Silvia M. F. S. Massruhá, 2024. "Framing Concepts of Agriculture 5.0 via Bipartite Analysis," Sustainability, MDPI, vol. 16(24), pages 1-22, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hong, Mu & Zhang, Yao & Li, Lidong & Paustian, Keith, 2025. "Enhancing simulations of biomass and nitrous oxide emissions in vineyard, orchard, and vegetable cropping systems," Agricultural Systems, Elsevier, vol. 224(C).
    2. Vivian Welch & Christine M. Mathew & Panteha Babelmorad & Yanfei Li & Elizabeth T. Ghogomu & Johan Borg & Monserrat Conde & Elizabeth Kristjansson & Anne Lyddiatt & Sue Marcus & Jason W. Nickerson & K, 2021. "Health, social care and technological interventions to improve functional ability of older adults living at home: An evidence and gap map," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(3), September.
    3. Erkmen Giray Aslim, 2019. "The Relationship Between Health Insurance and Early Retirement: Evidence from the Affordable Care Act," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 45(1), pages 112-140, January.
    4. Nihan Akyelken, 2017. "Mobility-Related Economic Exclusion: Accessibility and Commuting Patterns in Industrial Zones in Turkey," Social Inclusion, Cogitatio Press, vol. 5(4), pages 175-182.
    5. Prabal Das & D. A. Sachindra & Kironmala Chanda, 2022. "Machine Learning-Based Rainfall Forecasting with Multiple Non-Linear Feature Selection Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 6043-6071, December.
    6. Dreher, Axel & Fuchs, Andreas & Langlotz, Sarah, 2019. "The effects of foreign aid on refugee flows," European Economic Review, Elsevier, vol. 112(C), pages 127-147.
    7. Paulo Infante & Gonçalo Jacinto & Anabela Afonso & Leonor Rego & Pedro Nogueira & Marcelo Silva & Vitor Nogueira & José Saias & Paulo Quaresma & Daniel Santos & Patrícia Góis & Paulo Rebelo Manuel, 2023. "Factors That Influence the Type of Road Traffic Accidents: A Case Study in a District of Portugal," Sustainability, MDPI, vol. 15(3), pages 1-16, January.
    8. Georg Feigl & Markus Marterbauer & Miriam Rehm & Matthias Schnetzer & Sepp Zuckerstätter & Lars Nørvang Andersen & Thea Nissen & Signe Dahl & Peter Hohlfeld & Benjamin Lojak & Achim Truger & Andrew Wa, 2016. "The Elusive Recovery," SciencePo Working papers Main hal-03459084, HAL.
      • Georg Feigl & Markus Marterbauer & Miriam Rehm & Matthias Schnetzer & Sepp Zuckerstätter & Lars Nørvang Andersen & Thea Nissen & Signe Dahl & Peter Hohlfeld & Benjamin Lojak & Achim Truger & Andrew Wa, 2016. "The Elusive Recovery," PSE-Ecole d'économie de Paris (Postprint) hal-03459084, HAL.
      • Georg Feigl & Markus Marterbauer & Miriam Rehm & Matthias Schnetzer & Sepp Zuckerstätter & Lars Nørvang Andersen & Thea Nissen & Signe Dahl & Peter Hohlfeld & Benjamin Lojak & Thomas Theobald & Achim , 2016. "The Elusive Recovery," PSE Working Papers hal-03612850, HAL.
      • Georg Feigl & Markus Marterbauer & Miriam Rehm & Matthias Schnetzer & Sepp Zuckerstätter & Lars Nørvang Andersen & Thea Nissen & Signe Dahl & Peter Hohlfeld & Benjamin Lojak & Achim Truger & Andrew Wa, 2016. "The Elusive Recovery," Post-Print hal-03459084, HAL.
      • Georg Feigl & Markus Marterbauer & Miriam Rehm & Matthias Schnetzer & Sepp Zuckerstätter & Lars Nørvang Andersen & Thea Nissen & Signe Dahl & Peter Hohlfeld & Benjamin Lojak & Thomas Theobald & Achim , 2016. "The Elusive Recovery," Working Papers hal-03612850, HAL.
      • Georg Feigl & Markus Marterbauer & Miriam Rehm & Matthias Schnetzer & Sepp Zuckerstätter & Lars Nørvang Andersen & Thea Nissen & Signe Dahl & Peter Hohlfeld & Benjamin Lojak & Thomas Theobald & Achim , 2016. "The Elusive Recovery," SciencePo Working papers Main hal-03612850, HAL.
      • Georg Feigl & Markus Marterbauer & Miriam Rehm & Matthias Schnetzer & Sepp Zuckerstätter & Lars Nørvang Andersen & Thea Nissen & Signe Dahl & Peter Hohlfeld & Benjamin Lojak & Thomas Theobald & Achim , 2016. "The Elusive Recovery," PSE-Ecole d'économie de Paris (Postprint) hal-03612850, HAL.
    9. Billari, Francesco C. & Giuntella, Osea & Stella, Luca, 2018. "Broadband internet, digital temptations, and sleep," Journal of Economic Behavior & Organization, Elsevier, vol. 153(C), pages 58-76.
    10. Ekaterina Aleksandrova & Kristian Behrens & Maria Kuznetsova, 2020. "Manufacturing (co)agglomeration in a transition country: Evidence from Russia," Journal of Regional Science, Wiley Blackwell, vol. 60(1), pages 88-128, January.
    11. Werner Eichhorst & Ulf Rinne, 2017. "Digital Challenges for the Welfare State," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 18(04), pages 03-08, December.
    12. Grazzini, Jakob & Richiardi, Matteo G. & Tsionas, Mike, 2017. "Bayesian estimation of agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 26-47.
    13. Bruno Biais & Fany Declerck & Sophie Moinas, 2016. "Who supplies liquidity, how and when?," BIS Working Papers 563, Bank for International Settlements.
    14. Ephrem Habyarimana & Faheem S Baloch, 2021. "Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-23, March.
    15. Chen, Cheng & Senga, Tatsuro & Sun, Chang & Zhang, Hongyong, 2023. "Uncertainty, imperfect information, and expectation formation over the firm’s life cycle," Journal of Monetary Economics, Elsevier, vol. 140(C), pages 60-77.
    16. Julie Vinck & Idunn Brekke, 2019. "Gender and education inequalities in parental employment when having a young child with increased care needs: Belgium and Norway compared," Working Papers 1904, Herman Deleeck Centre for Social Policy, University of Antwerp.
    17. Claudia Hanson & Sanni Kujala & Peter Waiswa & Tanya Marchant & Joanna Schellenberg, 2017. "Community-based approaches for neonatal survival: Meta-analyses of randomized trial data," WIDER Working Paper Series wp-2017-137, World Institute for Development Economic Research (UNU-WIDER).
    18. Eugenia Ganea & Valentina Bodrug-Lungu, 2018. "Addressing Inequality in Vocational/ Technical Education by Eliminating Gender Bias," Revista romaneasca pentru educatie multidimensionala - Journal for Multidimensional Education, Editura Lumen, Department of Economics, vol. 10(4), pages 136-155, December.
    19. Gallopín, Gilberto, 2018. "Back to the future," Energy Policy, Elsevier, vol. 123(C), pages 318-324.
    20. Alvarez, Camila H. & Evans, Clare Rosenfeld, 2021. "Intersectional environmental justice and population health inequalities: A novel approach," Social Science & Medicine, Elsevier, vol. 269(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3517-:d:772982. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.