PhytoSim 2.1 released

Wednesday, December 16th, 2015

PhytoSim 2.1 has been released. Just in time for the Christmas holidays. All trials have been reset, so everyone who previously created an account can try out this version as well (first download the new version).

Install it using the internal PhytoSim updater or download it from the PhytoSim download page.

This version includes some great new features:

  • Simulation module:
    • Ability to choose the display time unit
  • Calibration module:
    • Moving window calibration: Automatically fit a model to parts of the data using a moving window approach resulting in calibrated values for each time window.
    • Ability to enable/disable optimizer and/or objective variables
  • Sensitivity analysis module:
    • Morris screening global sensitivity analysis: This method is a well known global sensitivity analysis screening technique which is able to detect, using a limited number of model simulations, which model components have (a) linear and additive or (b) non-linear and interaction effects.
    • Extended FAST global sensitivity analysis: The Extended Fourier Amplitude Sensitivity Test is a variance based global sensitivity analysis technique. By decomposing the model output variance, this method is able to calculate first order sensitivity indices and total sensitivity indices. The total sensitivity indices, as the name suggests, quantify the total sensitivity of a model component, including the interactions with other components.
    • Ability to enable/disable source and/or target components
  • Uncertainty module:
    • Ability to enable/disable source and/or target components

Some things have been changed as well:

  • Calibration module: calibration data is only shown between start and stop time

Finally, many bugs were fixed. Some of them are:

  • Data I/O module: problem importing data files with old-style Mac file endings
  • Simulation module: curve legend item not visible when dragging a model component on the graph
  • Simulation module: unable to edit x-axis minimum when autoscaling is turned off
  • Uncertainty module: progress bar does not reset when starting a new analysis

Happy simulating!

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PhytoSim was used to study crop load effects in peach trees

Monday, September 15th, 2014

On August 22th 2014 a paper was published which used a model, implemented in PhytoSim, to assess the effects of crop load on stem diameter variations and fruit growth of peach trees.


De Swaef T., Mellisho C.D., Baert A., De Schepper V., Torrecillas A., Conejero W. and Steppe K. (2014) Model-assisted evaluation of crop load effects on stem diameter variations and fruit growth in peach. Trees.


Stem diameter (D stem) variations have extensively been applied in optimisation strategies for plant-based irrigation scheduling in fruit trees. Two D stem derived water status indicators, maximum daily shrinkage (MDS) and daily growth rate (DGR), are however influenced by other factors such as crop load, making it difficult to unambiguously use these indicators in practical irrigation applications. Furthermore, crop load influences the growth of individual fruits, because of competition for assimilates. This paper aims to explain the effect of crop load on DGR, MDS and individual fruit growth in peach using a water and carbon transport model that includes simulation of stem diameter variations. This modelling approach enabled to relate differences in crop load to differences in xylem and phloem water potential components. As such, crop load effects on DGR were attributed to effects on the stem phloem turgor pressure. The effect of crop load on MDS could be explained by the plant water status, the phloem carbon concentration and the elasticity of the tissue. The influence on fruit growth could predominantly be explained by the effect on the early fruit growth stages.

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PhytoSim used to study stem diameter variation patterns in different mangrove species

Tuesday, September 9th, 2014

On February 16th 2014 a paper was published which used a model, implemented in PhytoSim, to study stem diameter variation patterns in different mangrove species.


Vandegehuchte M.W., Guyot A., Hubeau M., De Swaef T., Lockington D.A. and Steppe K. (2014). Modelling reveals endogenous osmotic adaptation of storage tissuewater potential as an important driver determining different stem diameter variation patterns in the mangrove species Avicennia marina and Rhizophora stylosa. Annals of Botany, 114(4), 667-676.


Background Stem diameter variations are mainly determined by the radial water transport between xylem and storage tissues. This radial transport results from the water potential difference between these tissues, which is influenced by both hydraulic and carbon related processes. Measurements have shown that when subjected to the same environmental conditions, the co-occurring mangrove species Avicennia marina and Rhizophora stylosa unexpectedly show a totally different pattern in daily stem diameter variation.

Methods Using in situ measurements of stem diameter variation, stem water potential and sap flow, a mechanistic flow and storage model based on the cohesion–tension theory was applied to assess the differences in osmotic storage water potential between Avicennia marina and Rhizophora stylosa.

Key results Both species, subjected to the same environmental conditions, showed a resembling daily pattern in simulated osmotic storage water potential. However, the osmotic storage water potential ofR. stylosa started to decrease slightly after that of A. marina in the morning and increased again slightly later in the evening. This small shift in osmotic storage water potential likely underlaid the marked differences in daily stem diameter variation pattern between the two species.

Conclusions The results show that in addition to environmental dynamics, endogenous changes in the osmotic storage water potential must be taken into account in order to accurately predict stem diameter variations, and hence growth.

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PhytoSim used for the ‘Modelling drought stress responses’ COST Training School

Friday, May 30th, 2014

31 enthusiastic Early Stage Researchers used PhytoSim during a 3-day COST Training School to learn about modelling and simulation and applied this knowledge to investigate drought stress responses in trees. During the course, PhytoSim was used for teaching and hands-on exercises.

The ‘Modelling drought stress responses’ COST Training School was organised by the UGent Laboratory of Plant Ecology from May 26th-28th 2014.


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PhytoSim 2.0.1 Released

Thursday, May 8th, 2014

PhytoSim 2.0.1 has been released. Download it here.

Due to internal encryption changes, remembered login passwords might not work anymore. If you experience login issues, please retype your password in the password field of the login dialog.

This is a bug fix release which fixes following issues:


  • FIXED: Crash when transferring calibrated source component (e.g. parameters) values to the Simulation Module.
  • FIXED: Simulation graph curve settings issue for curves on the second Y-axis.
  • FIXED: Issue with PhytoSim folder location in Preferences.
  • FIXED: Issue with simulation Data Variables not updating their value when selecting them in the navigator.


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PhytoSim used to analyse the effect of mistletoe on Scots pine

Wednesday, July 3rd, 2013

on January 20th 2012 a paper was published that used a model, implemented in PhytoSim, to analyse the effect of mistletoe on Scots pine.


Zweifel R., Bangerter S., Rigling A. and Sterck F.J. (2012). Pine and mistletoes: how to live with a leak in the water flow and storage system? Journal of Experimental Botany, 63(7), 2565-2578.


The mistletoe, Viscum album, living on Scots pine (Pinus sylvestris) has been reported barely to regulate its transpiration and thus heavily to affect the gas exchange of its host. The extent of this mistletoe effect and its underlying mechanism has, so far, only been partially analysed. In this study, pine branches with different mistletoe infestation levels were investigated by sap flow gauges and analysed with a modelling approach to identify the mistletoe-induced stomatal regulation of pine and its consequences for the water and carbon balances of the tree. It was found that Viscum album barely regulates its stomata and that pines consequently compensate for the additional water loss of mistletoes by closing their own stomata. Despite the reduced stomatal aperture of the needles, the total water loss of branches with mistletoes increased. Furthermore, the increasingly closed stomata reduced carbon assimilation for the pine. Such a negative effect of the mistletoes on pine’s stomatal conductance and carbon gain was particularly strong during dry periods. Our study therefore suggests that mistletoe-induced stomatal closure is a successful mechanism against dying from hydraulic failure in the short term but increases the risk of carbon starvation in the long term. With the current conditions in Valais, Switzerland, a tree with more than about 10–20% of its total leaf area attributable to mistletoes is at the threshold of keeping a positive carbon balance. The currently increasing mistletoe abundance, due to increasing mean annual temperatures, is therefore accelerating the ongoing pine decline in many dry inner-Alpine valleys.

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PhytoSim 2.0 Released

Tuesday, June 25th, 2013

Version 2.0 of PhytoSim has been released. Download it here.

These are the new features/changes and fixes:


  • CHANGED: Simplified Module Manager, all modules are now built-in (faster startup, no additional downloads required).
  • CHANGED: New PhytoSim software update mechanism.
  • CHANGED: The Help > Support dialog has been removed. Contact for support related questions.
  • CHANGED: Support for multiple simultaneously running PhytoSim instances per account (default is still 1 instance).
  • FIXED: Mac OS X Snow Leopard is supported again.
  • FIXED: Bug for workspaces within a folder structure with folder names containing special characters.

 Data I/O Module:

  • NEW: Embedded data input type. Embed data directly in the workspace: enter manually, copy-and-past or drag-and-drop selected data from text files or Excel).

 Modelling Module:

  • NEW: Fractional units, e.g. cm^3/2.
  • NEW: New unit ‘#’, representing a count or a number of items. E.g. 20 #[plants].m^-2[ground].
  • NEW: New crop model: SUCROS1 (Simple and Universal CROp growth Simulator).
  • CHANGED: The valueat( x, at ) function for data variables now uses the data variable independent variable for the ‘at’ argument instead of the model independent variable.
  • FIXED: Sort order violation for algebraicVariable = previous( algebraicVariable ) or valueat( algebraicVariable, t ).

 Simulation Module:

  • NEW: Graph curves can be put on the second Y-axis.
  • NEW: Logarithmic scales on the Y-axes.
  • NEW: SUCROS1 crop model example showing embedded data inputs and advanced use of the valueat() function.
  • FIXED: Scroll wheel zooming no longer zooms out beyond the graph data.
  • FIXED: Potential crash when zooming in on graphs.

 Calibration Module:

  • CHANGED: Faster calibration when the simulation period is only a small part of the available data period.
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PhytoSim @ HortiModel 2012

Friday, November 16th, 2012

Phyto-IT demonstrated its PhytoSim modelling and simulation software at the HortiModel 2012 conference (Nanjing, China, November 4-8, 2012).

The HortiModel 2012 conference was the Fourth International Symposium on Models for Plant Growth, Environmental Control and Management in Protected Cultivation. It covered a wide range of topics related to horticulture:

  • Crop and Climate Management
  • Water, Nutrient and Energy Management
  • Decision Support and Farm Management
  • Product Quality
  • Systems Biology, Gene-plant-crop Modelling
  • 3D-models, Architectural Models
  • Methodological Issues, Aggregation and Scale
  • Combination of Models and Sensors

HortiModel 2012

HortiModel 2012 booth

Thanks to all the participants who came by our booth!

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PhytoSim used in sap flow research

Tuesday, October 2nd, 2012

In a recently published paper about a new sap flow measurement technique (Sapflow+) PhytoSim was used to develop, simulate and calibrate the Sapflow+ model. Besides that, the PhytoSim sensitivity and identifiability analysis was also used to determine if the heat velocity, volumetric heat capacity and thermal conductivities could be estimated from the measured data.


Vandegehuchte M.W. and Steppe K. (2012). Sapflow+: a four-needle heat-pulse sap flow sensor enabling nonempirical sap flux density and water content measurements. New Phytologist, 196(1), 306-317.


  • To our knowledge, to date, no nonempirical method exists to measure reverse, low or high sap flux density. Moreover, existing sap flow methods require destructive wood core measurements to determine sapwood water content, necessary to convert heat velocity to sap flux density, not only damaging the tree, but also neglecting seasonal variability in sapwood water content.
  • Here, we present a nonempirical heat-pulse-based method and coupled sensor which measure temperature changes around a linear heater in both axial and tangential directions after application of a heat pulse. By fitting the correct heat conduction–convection equation to the measured temperature profiles, the heat velocity and water content of the sapwood can be determined.
  • An identifiability analysis and validation tests on artificial and real stem segments of European beech (Fagus sylvatica L.) confirm the applicability of the method, leading to accurate determinations of heat velocity, water content and hence sap flux density.
  • The proposed method enables sap flux density measurements to be made across the entire natural occurring sap flux density range of woody plants. Moreover, the water content during low flows can be determined accurately, enabling a correct conversion from heat velocity to sap flux density without destructive core measurements.
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PhytoSim used in wood thermal diffusivity research

Tuesday, September 18th, 2012

A recently published paper on wood thermal diffusivity used PhytoSim to calibrate a theoretical model in order to determine both axial and tangential diffusivity in sapwood. The PhytoSim sensitivity and identifiability analysis was also used to better understand the model and learn which parameters most influenced the end-results.


Vandegehuchte M.W. and Steppe K. (2012). A triple-probe heat-pulse method for measurement of thermal diffusivity in trees. Agricultural and Forest Meteorology, 160, 90–99.


Although thermal diffusivity is a crucial parameter for sap flow calculations in both the heat field deformation and the heat ratio method, it is seldom measured on a routine basis. This paper presents a theory based on thermodynamic principles to determine both axial and tangential diffusivity in sapwood. By measuring the temperature response after application of a heat pulse at a short axial and tangential distance from a line heater, axial and tangential thermal conductivity as well as volumetric heat capacity of the sapwood can be derived from a theoretical model. From these parameters, axial and tangential diffusivity can easily be determined. Sensitivity analysis and results of an experiment on European beech (Fagus sylvatica L.) confirm the applicability of the method. The obtained thermal diffusivities ranged from 2.7 × 10−7 m2 s−1 to 2.2 × 10−7 m2 s−1 for a relative water content (moisture per dry weight) ranging from 0.47 to 0.90, respectively. This was on average 22% lower than when applying the common methodology based on wood core sampling.

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