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SIMPLACE: The Next Generation Platform for Agricultural Systems Analysis

SIMPLACE offers a flexible and transparent approach to developing customized crop models

As the world’s population grows, so does the demand for food. Computer-based crop modelling provides insight to ensure that we can meet this demand sustainably and efficiently.

Over the last 30 years crop models have been developed for applications such as adaptation to climate change and increasing resource use efficiency. While crop modelling is now rapidly evolving with advances in genomics, phenomics (phenotyping), and computational technologies in recent years, progress could be further expedited by the ability for colleagues to evaluate, improve on, and reuse existing models. This largely untapped potential for further application and development is hindered by model weaknesses and long-standing problems such as:

  • relying on non-standard code that obscures the scientific content of a model (i.e., algorithms),
  • lacking documentation (i.e., descriptions associated with the modeled processes),
  • having minimal standardization of model inputs or internal structures, and
  • being closed-source.

Software Developer Andreas Enders, Scientist Murilo Vianna, and colleagues at the University of Bonn describe a versatile modelling and simulation framework in a new paper published by in silico Plants. The Scientific Impact assessment and Modelling PLatform for Advanced Crop and Ecosystem management (SIMPLACE) is an open-source scientific tool created to facilitate model development.

A display of model components visually linked in the embedded solution editor.
Model solution view of CropManager, the SIMPLACE GUI for students and stakeholders.

 “This platform is under continuous development and has been increasingly tested and applied in a range of agricultural studies over the last decade. That’s why we want to highlight it with an article now!” explains Enders.

A graphic that shows icons for flexibility balanced with performance. This balance can be offset by including transparency.
Main paradigms of the technical implementation. The three paradigms contradict each other in parts, and promoting one weakens the other. It is, therefore, necessary to balance flexibility and performance.

SIMPLACE offers a flexible and transparent approach to developing customized models for a variety of cropping systems and different disciplines (agronomy, crop physiology, soil science and hydrology). The creators of SIMPLACE have attempted to balance three contradicting paradigms: flexibility, transparency, and performance with the following attributes:


  • configurable (facilitating data format harmonization by providing a suite of translation tools)
  • modular – the model structure is composed of discrete, replaceable, and interchangeable software units
  • multiple user interfaces – a GUI that requires a minimum knowledge of the modelling process and scientific content and a console interface for more complex work
  • control using multiple scripting languages – R, Python, Matlab, and Octave suited on multiple operating systems
  • multiple input and output types – CSV, SQL Databases, XML, Shape Files, NetCDF, Json, etc.


  • open source
  • centralized and standard module documentations, with an explicit description of variables, constants and underlying units and ontology


  • flexible frequency of parameters update
  • allows multi-threading on HPC
  • efficient IO process

While other modeling platforms already exist, the authors point out the uniqueness of SIMPLACE. “It offers a number of ready-to-use algorithms that can be rapidly combined and customized to address a huge range of scientific questions. The flexible input and output data resources as well as the interface with other programming languages (e.g., Python and R) facilitate the direct coupling of SIMPLACE with other databases and modelling platforms and allows automated model unit exchange.”

Read the article for a description of SIMPLACE’s main technical implementation and features to develop customized model solutions that can be applied to a number of cropping systems. The article also includes a brief review of exemplary applications of SIMPLACE covering different topics, crops and cropping systems, spatial scales, and geographies.


Andreas Enders and others, SIMPLACE – A versatile modelling and simulation framework for sustainable crops and agroecosystems, in silico Plants, 2023; diad006, https://doi.org/10.1093/insilicoplants/diad006

The SIMPLACE source code, ancillary interfacing packages, and installable application can be freely accessed at http://www.simplace.net.

Rachel Shekar

Rachel (she/her) is a Founding and Managing Editor of in silico Plants. She has a Master’s Degree in Plant Biology from the University of Illinois. She has over 15 years of academic journal editorial experience, including the founding of GCB Bioenergy and the management of Global Change Biology. Rachel has overseen the social media development that has been a major part of promotion of both journals.

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