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Hybrid modeling for grassland productivity prediction: A parametric and machine learning technique for grazing management with applicability to digital twin decision systems

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  • Paruelo, José M.
  • Texeira, Marcos
  • Tomasel, Fernando

Abstract

Monitoring Aboveground Net Primary Production (ANPP) is critical to assess not only the current ecosystem status but also its long-term dynamics. In rangelands, the seasonal dynamics of ANPP determines forage availability, stock density, and livestock productivity.

Suggested Citation

  • Paruelo, José M. & Texeira, Marcos & Tomasel, Fernando, 2024. "Hybrid modeling for grassland productivity prediction: A parametric and machine learning technique for grazing management with applicability to digital twin decision systems," Agricultural Systems, Elsevier, vol. 214(C).
    • Handle: RePEc:eee:agisys:v:214:y:2024:i:c:s0308521x23002524
    DOI: 10.1016/j.agsy.2023.103847
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    References listed on IDEAS

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    5. Gutiérrez, Francisco & Gallego, Federico & Paruelo, José M. & Rodríguez, Claudia, 2020. "Damping and lag effects of precipitation variability across trophic levels in Uruguayan rangelands," Agricultural Systems, Elsevier, vol. 185(C).
    6. Díaz-Solís, H. & Grant, W.E. & Kothmann, M.M. & Teague, W.R. & Díaz-García, J.A., 2009. "Adaptive management of stocking rates to reduce effects of drought on cow-calf production systems in semi-arid rangelands," Agricultural Systems, Elsevier, vol. 100(1-3), pages 43-50, April.
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