Scientific Articles

This section contains all the peer-reviewed scientific publications pertaining to the application and validation of our ARMOSA model.

  1. “From Indicators to Action: Modeling Soil Health for Ecosystem Service Optimization” (Bancheri et al., 2025)
  2. “Optimization of agronomic management positively affects soil GHG emission: Viable solutions of mitigation in moist and dry Mediterranean climate zones” (Gabbrielli et al., 2025)
  3. “A web-based operational tool for the identification of best practices in European agricultural systems” (Bancheri et al., 2024)
  4. “A sound understanding of a cropping system model with the global sensitivity analysis” (Colombi et al., 2024)
  5. “The LANDSUPPORT geospatial decision support system (S-DSS) vision: Operational tools to implement sustainability policies in land planning and management” (Terribile et al., 2024)
  6. “Sensitivity of simulated soil water content, evapotranspiration, gross primary production and biomass to climate change factors in Euro-Mediterranean grasslands” (Bellocchi et al., 2023)
  7. “Simulation of evapotranspiration and yield of maize: An inter-comparison among 41 maize models” (Kimball et al., 2023)
  8. “A new module to simulate surface crop residue decomposition: Description and sensitivity analysis” (Tadiello et al., 2023)
  9. “Can conservation agriculture increase soil carbon sequestration? A modelling approach”  (Valkama et al., 2020)
  10. “Multi-model simulation of soil temperature, soil water content and biomass in Euro-Mediterranean grasslands: Uncertainties and ensemble performance” (Sándor et al., 2017)
  11. “Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces” (Pirttioja et al., 2015)
  12. “Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data” (Groenendijk et al., 2014)
  13. “The ARMOSA simulation crop model: Overall features, calibration and validation results” (Perego et al., 2013)