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SSM-iCrop2: A simple model for diverse crop species over large areas

Author

Listed:
  • Soltani, A.
  • Alimagham, S.M.
  • Nehbandani, A.
  • Torabi, B.
  • Zeinali, E.
  • Dadrasi, A.
  • Zand, E.
  • Ghassemi, S.
  • Pourshirazi, S.
  • Alasti, O.
  • Hosseini, R.S.
  • Zahed, M.
  • Arabameri, R.
  • Mohammadzadeh, Z.
  • Rahban, S.
  • Kamari, H.
  • Fayazi, H.
  • Mohammadi, S.
  • Keramat, S.
  • Vadez, V.
  • van Ittersum, M.K.
  • Sinclair, T.R.

Abstract

Crop models are essential in undertaking large scale estimation of crop production of diverse crop species, especially in assessing food availability and climate change impacts. In this study, an existing model (SSM, Simple Simulation Models) was adapted to simulate a large number of plant species including orchard species and perennial forages. Simplification of some methods employed in the original model was necessary to deal with limited data availability for some of the plant species to be simulated. The model requires limited, readily available input information. The simulations account for plant phenology, leaf area development and senescence, dry matter accumulation, yield formation, and soil water balance in a daily time step. Parameterization of the model for new crops/cultivars is easy and straight-forward. The resultant model (SSM-iCrop2) was parameterized and tested for more than 30 crop species of Iran using numerous field experiments. Tests showed the model was robust in the predictions of crop yield and water use. Root mean square of error as percentage of observed mean for yield was 18% for grain field crops, 14% for non-grain crops 14% for vegetables and 28% for fruit trees.

Suggested Citation

  • Soltani, A. & Alimagham, S.M. & Nehbandani, A. & Torabi, B. & Zeinali, E. & Dadrasi, A. & Zand, E. & Ghassemi, S. & Pourshirazi, S. & Alasti, O. & Hosseini, R.S. & Zahed, M. & Arabameri, R. & Mohammad, 2020. "SSM-iCrop2: A simple model for diverse crop species over large areas," Agricultural Systems, Elsevier, vol. 182(C).
    • Handle: RePEc:eee:agisys:v:182:y:2020:i:c:s0308521x19310455
    DOI: 10.1016/j.agsy.2020.102855
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    References listed on IDEAS

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    1. Kropp, Ian & Nejadhashemi, A. Pouyan & Deb, Kalyanmoy & Abouali, Mohammad & Roy, Proteek C. & Adhikari, Umesh & Hoogenboom, Gerrit, 2019. "A multi-objective approach to water and nutrient efficiency for sustainable agricultural intensification," Agricultural Systems, Elsevier, vol. 173(C), pages 289-302.
    2. Ghanem, Michel Edmond & Marrou, Hélène & Biradar, Chandrashekhar & Sinclair, Thomas R., 2015. "Production potential of Lentil (Lens culinaris Medik.) in East Africa," Agricultural Systems, Elsevier, vol. 137(C), pages 24-38.
    3. Le, Kieu N. & Jeong, Jaehak & Reyes, Manuel R. & Jha, Manoj K. & Gassman, Philip W. & Doro, Luca & Hok, Lyda & Boulakia, Stéphane, 2018. "Evaluation of the performance of the EPIC model for yield and biomass simulation under conservation systems in Cambodia," Agricultural Systems, Elsevier, vol. 166(C), pages 90-100.
    4. Schoppach, Rémy & Soltani, Afshin & Sinclair, Thomas R. & Sadok, Walid, 2017. "Yield comparison of simulated rainfed wheat and barley across Middle-East," Agricultural Systems, Elsevier, vol. 153(C), pages 101-108.
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    1. Marrou, Hélène & Ghanem, Michel Edmond & Amri, Moez & Maalouf, Fouad & Ben Sadoun, Sarah & Kibbou, Fatimaezzhara & Sinclair, Thomas R., 2021. "Restrictive irrigation improves yield and reduces risk for faba bean across the Middle East and North Africa: A modeling study," Agricultural Systems, Elsevier, vol. 189(C).
    2. Dadrasi, Amir & Torabi, Benjamin & Rahimi, Asghar & Soltani, Afshin & Zeinali, Ebrahim, 2022. "Modeling Potential production and yield gap of potato using modelling and GIS approaches," Ecological Modelling, Elsevier, vol. 471(C).

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