Palm(;
    initiation_age=0,
    parameters=default_parameters()
)

Create a new scene with one Palm plant.

Arguments

• initiation_age: date of the first phytomer initiation (default: 0)
• parameters: a dictionary of parameters (default: default_parameters())

Palm(; initiation_age=0, parameters=default_parameters())

Create a new scene with one Palm plant. The scene contains a soil, a plant, a root system, a stem, a phytomer, an internode, and a leaf.

Arguments

• initiation_age: days elapsed since the first phytomer initiation (default: 0)
• parameters: a dictionary of parameters (default: default_parameters())

Returns

• a Palm object

_ensure_meteo_duration(meteo)

Ensure each meteo row defines duration (required by recent PlantSimEngine versions). When missing, default to a daily timestep (Dates.Day(1)).

age_relative_value(age, age_min_value, age_max_value, min_value, max_value)

Value that depends on the plant age.

Arguments

• age: the current age of the plant
• age_min_value: the age at which minimum value is reached (ages below this age will hage min_value)
• age_max_value: the age at which the value is at the maximum value (ages above this age will hage max_value)
• min_value: the value below or at age_min_value
• max_value: the value at or above age_max_value

Examples

julia> XPalm.age_relative_value(0, 1, 10, 0.1, 0.8)
0.1

julia> XPalm.age_relative_value(5, 1, 10, 0.1, 0.8)
0.4111111111111111

julia> XPalm.age_relative_value(15, 1, 10, 0.1, 0.8)
0.8

model_applications(p; architecture=false)

Define the model applications used by XPalm.

Applications are listed in their intended daily execution order. Each entry shows the model, the scale where it runs, and any cross-scale inputs or hard calls. PlantSimEngine may add dependency-order edges, but otherwise preserves this order.

Arguments

• p: a Palm containing the MTG and model parameters.
• architecture: also compute the 3D palm architecture when true.

Returns

A tuple of PlantSimEngine.ModelSpec applications.

notebook(copyto::String; force::Bool)

Open an XPalm notebook or create one from a template at path, and run the notebook.

Arguments

• path::String: The path to the notebook file. If it exists, it will be opened (unless force=true), otherwise it will be created.
• force::Bool=false: If true, overwrite the file at path.

Example

using XPalm, Pluto
XPalm.notebook()

xpalm(meteo; vars=Dict(:Scene => (:lai,)), architecture=false, palm=Palm(initiation_age=0, parameters=default_parameters()))
xpalm(meteo, sink; vars=Dict(:Scene => (:lai,)), architecture=false, palm=Palm(initiation_age=0, parameters=default_parameters()))

Run the XPalm model with the given meteo data and return the results in a DataFrame.

Arguments

• meteo: DataFrame with the meteo data
• sink: a Tables.jl compatible sink function to format the results, for exemple a DataFrame
• vars: A dictionary with the outputs to be returned for each scale of simulation
• architecture: A boolean indicating whether to compute the 3D architecture of the palm (default is false)
• palm: the Palm object with the parameters of the model

Returns

A PlantSimEngine.Simulation, or collected output rows when sink is supplied.

Example

using XPalm, CSV, DataFrames
meteo = CSV.read(joinpath(dirname(dirname(pathof(XPalm))), "0-data/meteo.csv"), DataFrame)
df = xpalm(meteo, DataFrame; vars=Dict(:Scene => (:lai,)))

AbortionRate(TT_flowering, duration_abortion, abortion_rate_max=1.0, abortion_rate_ref=0.2; random_seed::Int=0)
AbortionRate(TT_flowering, duration_abortion, abortion_rate_max, abortion_rate_ref, random_generator<:AbstractRNG)

Determines if the inflorescence will abort based on the trophic state of the plant during a given period in thermal time.

Arguments

• TT_flowering: thermal time for flowering since phytomer appearence (degree days).
• duration_abortion: duration used for computing abortion rate before flowering (degree days).

Inputs

• carbon_offer_plant: daily plant assimilate offer after maintenance respiration (g CH2O-equivalent plant⁻¹ d⁻¹).
• carbon_demand_plant: daily total plant assimilate demand (g CH2O-equivalent plant⁻¹ d⁻¹).

Outputs

• carbon_demand_abortion: assimilate demand accumulated over the abortion period (g CH2O-equivalent plant⁻¹).
• carbon_offer_abortion: assimilate offer accumulated over the abortion period (g CH2O-equivalent plant⁻¹).
• state: phytomer state (undetermined,Aborted,...)

Note

The abortion is determined at TT_flowering based on the trophic_status of the plant during a period of time before this date. The hypothesis is that a trophic stress can trigger more abortion in the plant.

abortion process abstract model.

All models implemented to simulate the abortion process must be a subtype of this type, e.g. struct MyAbortionModel <: AbstractAbortionModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractAbortionModel)

biomass process abstract model.

All models implemented to simulate the biomass process must be a subtype of this type, e.g. struct MyBiomassModel <: AbstractBiomassModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractBiomassModel)

biomass_from_area process abstract model.

All models implemented to simulate the biomass_from_area process must be a subtype of this type, e.g. struct MyBiomass_From_AreaModel <: AbstractBiomass_From_AreaModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractBiomass_From_AreaModel)

biomass_to_area process abstract model.

All models implemented to simulate the biomass_to_area process must be a subtype of this type, e.g. struct MyBiomass_To_AreaModel <: AbstractBiomass_To_AreaModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractBiomass_To_AreaModel)

carbon_allocation process abstract model.

All models implemented to simulate the carbon_allocation process must be a subtype of this type, e.g. struct MyCarbon_AllocationModel <: AbstractCarbon_AllocationModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractCarbon_AllocationModel)

carbon_assimilation process abstract model.

All models implemented to simulate the carbon_assimilation process must be a subtype of this type, e.g. struct MyCarbon_AssimilationModel <: AbstractCarbon_AssimilationModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractCarbon_AssimilationModel)

carbon_demand process abstract model.

All models implemented to simulate the carbon_demand process must be a subtype of this type, e.g. struct MyCarbon_DemandModel <: AbstractCarbon_DemandModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractCarbon_DemandModel)

carbon_offer process abstract model.

All models implemented to simulate the carbon_offer process must be a subtype of this type, e.g. struct MyCarbon_OfferModel <: AbstractCarbon_OfferModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractCarbon_OfferModel)

AbstractFTSWModel <: AbstractSoil_WaterModel

Defines a structure for soil water model that computes ftsw as an output.

final_potential_biomass process abstract model.

All models implemented to simulate the final_potential_biomass process must be a subtype of this type, e.g. struct MyFinal_Potential_BiomassModel <: AbstractFinal_Potential_BiomassModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractFinal_Potential_BiomassModel)

harvest process abstract model.

All models implemented to simulate the harvest process must be a subtype of this type, e.g. struct MyHarvestModel <: AbstractHarvestModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractHarvestModel)

initiation_age process abstract model.

All models implemented to simulate the initiation_age process must be a subtype of this type, e.g. struct MyInitiation_AgeModel <: AbstractInitiation_AgeModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractInitiation_AgeModel)

internode_dimensions process abstract model.

All models implemented to simulate the internode_dimensions process must be a subtype of this type, e.g. struct MyInternode_DimensionsModel <: AbstractInternode_DimensionsModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractInternode_DimensionsModel)

internode_final_potential_dimensions process abstract model.

All models implemented to simulate the internode_final_potential_dimensions process must be a subtype of this type, e.g. struct MyInternode_Final_Potential_DimensionsModel <: AbstractInternode_Final_Potential_DimensionsModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractInternode_Final_Potential_DimensionsModel)

internode_potential_dimensions process abstract model.

All models implemented to simulate the internode_potential_dimensions process must be a subtype of this type, e.g. struct MyInternode_Potential_DimensionsModel <: AbstractInternode_Potential_DimensionsModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractInternode_Potential_DimensionsModel)

lai_dynamic process abstract model.

All models implemented to simulate the lai_dynamic process must be a subtype of this type, e.g. struct MyLai_DynamicModel <: AbstractLai_DynamicModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractLai_DynamicModel)

leaf_area process abstract model.

All models implemented to simulate the leaf_area process must be a subtype of this type, e.g. struct MyLeaf_AreaModel <: AbstractLeaf_AreaModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractLeaf_AreaModel)

leaf_final_potential_area process abstract model.

All models implemented to simulate the leaf_final_potential_area process must be a subtype of this type, e.g. struct MyLeaf_Final_Potential_AreaModel <: AbstractLeaf_Final_Potential_AreaModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractLeaf_Final_Potential_AreaModel)

leaf_potential_area process abstract model.

All models implemented to simulate the leaf_potential_area process must be a subtype of this type, e.g. struct MyLeaf_Potential_AreaModel <: AbstractLeaf_Potential_AreaModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractLeaf_Potential_AreaModel)

leaf_pruning process abstract model.

All models implemented to simulate the leaf_pruning process must be a subtype of this type, e.g. struct MyLeaf_PruningModel <: AbstractLeaf_PruningModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractLeaf_PruningModel)

leaf_rank process abstract model.

All models implemented to simulate the leaf_rank process must be a subtype of this type, e.g. struct MyLeaf_RankModel <: AbstractLeaf_RankModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractLeaf_RankModel)

light_interception process abstract model.

All models implemented to simulate the light_interception process must be a subtype of this type, e.g. struct MyLight_InterceptionModel <: AbstractLight_InterceptionModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractLight_InterceptionModel)

maintenance_respiration process abstract model.

All models implemented to simulate the maintenance_respiration process must be a subtype of this type, e.g. struct MyMaintenance_RespirationModel <: AbstractMaintenance_RespirationModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractMaintenance_RespirationModel)

Generic maintenance repspiration model.

The selected maintenance-respiration model is configured as a scene ModelSpec application on the relevant plant objects.

number_fruits process abstract model.

All models implemented to simulate the number_fruits process must be a subtype of this type, e.g. struct MyNumber_FruitsModel <: AbstractNumber_FruitsModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractNumber_FruitsModel)

number_spikelets process abstract model.

All models implemented to simulate the number_spikelets process must be a subtype of this type, e.g. struct MyNumber_SpikeletsModel <: AbstractNumber_SpikeletsModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractNumber_SpikeletsModel)

phyllochron process abstract model.

All models implemented to simulate the phyllochron process must be a subtype of this type, e.g. struct MyPhyllochronModel <: AbstractPhyllochronModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractPhyllochronModel)

phytomer_count process abstract model.

All models implemented to simulate the phytomer_count process must be a subtype of this type, e.g. struct MyPhytomer_CountModel <: AbstractPhytomer_CountModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractPhytomer_CountModel)

phytomer_emission process abstract model.

All models implemented to simulate the phytomer_emission process must be a subtype of this type, e.g. struct MyPhytomer_EmissionModel <: AbstractPhytomer_EmissionModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractPhytomer_EmissionModel)

plant_age process abstract model.

All models implemented to simulate the plant_age process must be a subtype of this type, e.g. struct MyPlant_AgeModel <: AbstractPlant_AgeModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractPlant_AgeModel)

potential_evapotranspiration process abstract model.

All models implemented to simulate the potential_evapotranspiration process must be a subtype of this type, e.g. struct MyPotential_EvapotranspirationModel <: AbstractPotential_EvapotranspirationModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractPotential_EvapotranspirationModel)

reproductive_organ_emission process abstract model.

All models implemented to simulate the reproductive_organ_emission process must be a subtype of this type, e.g. struct MyReproductive_Organ_EmissionModel <: AbstractReproductive_Organ_EmissionModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractReproductive_Organ_EmissionModel)

reserve_filling process abstract model.

All models implemented to simulate the reserve_filling process must be a subtype of this type, e.g. struct MyReserve_FillingModel <: AbstractReserve_FillingModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractReserve_FillingModel)

root_growth process abstract model.

All models implemented to simulate the root_growth process must be a subtype of this type, e.g. struct MyRoot_GrowthModel <: AbstractRoot_GrowthModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractRoot_GrowthModel)

sex_determination process abstract model.

All models implemented to simulate the sex_determination process must be a subtype of this type, e.g. struct MySex_DeterminationModel <: AbstractSex_DeterminationModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractSex_DeterminationModel)

soil_water process abstract model.

All models implemented to simulate the soil_water process must be a subtype of this type, e.g. struct MySoil_WaterModel <: AbstractSoil_WaterModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractSoil_WaterModel)

state process abstract model.

All models implemented to simulate the state process must be a subtype of this type, e.g. struct MyStateModel <: AbstractStateModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractStateModel)

thermal_time process abstract model.

All models implemented to simulate the thermal_time process must be a subtype of this type, e.g. struct MyThermal_TimeModel <: AbstractThermal_TimeModel end.

You can list all models implementing this process using subtypes:

Examples

subtypes(AbstractThermal_TimeModel)

Beer(k)

Beer-Lambert law for light interception.

Arguments

• k: extinction coefficient of light

Inputs

• lai in m² m⁻².

Environment inputs

• Ri_PAR_f: incident daily PAR energy, in MJ m[ground]⁻² d⁻¹.

Outputs

• aPPFD: absorbed daily PAR in mol[photon] m[ground]⁻² d⁻¹.

BunchHarvest()

Transfer a harvested bunch, or an aborted female inflorescence, out of the standing biomass pools. All biomass* and litter variables are dry mass (gDM); fruit counts are dimensionless.

CarbonOfferRm()

A model that computes carbon offer as the carbon assimilation minus the maintenance respiration.

All three fluxes are daily g CH2O-equivalent values. Alternative photosynthesis models must convert their output to this currency before this model boundary.

ConstantRUEModel(rue)

Computes the carbon_assimilation using a constant radiation use efficiency (rue).

Arguments

• rue: gross radiation use efficiency (g CH2O-equivalent MJ⁻¹)

Inputs

• aPPFD: absorbed PAR in mol[photon] plant⁻¹ d⁻¹.

Outputs

• carbon_assimilation: gross assimilate production (g CH2O-equivalent plant⁻¹ d⁻¹)

DailyDegreeDays(TOpt1, TOpt2, TBase, TLim)
DailyDegreeDays(TOpt1=25, TOpt2=30, TBase=15, TLim=40)

Compute thermal time from daily environment data

Arguments

• TOpt1: starting optimal temperature for thermal time calculation (degree Celsius)
• TOpt2: ending optimal temperature for thermal time calculation (degree Celsius)
• TBase: Tbase temperature for thermal time calculation (degree Celsius)
• TLim: limit temperature for thermal time calculation (degree Celsius)

Environment inputs

• Tmin, Tmax: daily minimum and maximum air temperatures (degree Celsius).

Outputs

• TEff: daily efficient temperature for plant growth (degree C days)

DailyDegreeDaysSinceInit()

Compute thermal time since organ initiation using :TEff.

Outputs

• TT_since_init: daily efficient temperature for organ growth (degree C days)

DailyPlantAgeModel(initiation_age)

Plant age model, simply tracks the age of the plant in days.

Arguments

• initiation_age: age of the plant at the start of the simulation (days)

Returns

• age: age of the plant (days)

DegreeDaysFTSW(TOpt1, TOpt2, TBase, TLim, threshold_ftsw_stress)
DegreeDaysFTSW(TOpt1=25, TOpt2=30, TBase=15, TLim=40, threshold_ftsw_stress=0.3)

Compute thermal time from daily environment data, corrected by FTSW

Arguments

• TOpt1: starting optimal temperature for thermal time calculation (degree Celsius)
• TOpt2: ending optimal temperature for thermal time calculation (degree Celsius)
• TBase: Tbase temperature for thermal time calculation (degree Celsius)
• TLim: limit temperature for thermal time calculation (degree Celsius)
• threshold_ftsw_stress: threshold value under which we apply an FTSW stress

Inputs

• ftsw: fraction of transpirable soil water (unitless)

Environment inputs

• Tmin, Tmax: daily minimum and maximum air temperatures (degree Celsius).

Ouputs

• TEff: daily efficient temperature for plant growth (degree C days)
• TT_since_init: cumulated thermal time from the first day (degree C days)

ET0_BP(LATITUDE,ALTITUDE)
ET0_BP(LATITUDE=0.97,ALTITUDE=50)

Compute potential evapotranspiration

Arguments

• LATITUDE: latitude (radian)
• ALTITUDE: altitude (m)

Environment inputs

• Tmin, Tmax: daily minimum and maximum air temperatures.
• Rh_min, Rh_max: daily minimum and maximum relative humidities.
• Rg: daily global radiation.
• Wind: wind speed.
• date: date of the meteorological record.

Outputs

• ET0: potential evapotranpiration (mm)

FTSW(;
    ini_root_depth,
    H_FC=0.23,
    H_WP_Z1=0.05,
    Z1=200.0,
    H_WP_Z2=0.05,
    Z2=2000.0,
    H_0=0.15,
    KC=1.0,
    TRESH_EVAP=0.5,
    TRESH_FTSW_TRANSPI=0.5,
)

Fraction of Transpirable Soil Water model.

Note that there is also a method for FTSW that takes an organ type as type, e.g. FTSW{Leaf}(ini_root_depth = 200.0).

Arguments

• ini_root_depth: root depth at initialization (mm)
• H_FC: Humidity at field capacity (g[H20] g[Soil])
• H_WP_Z1: Humidity at wilting point (g[H20] g[Soil]) for the first layer
• Z1: Thickness of the first layer (mm)
• H_WP_Z2: Humidity at wilting point (g[H20] g[Soil]) for the second layer
• Z2: Thickness of the second layer (mm)
• H_0: Initial soil humidity (g[H20] g[Soil])
• KC: crop coefficient (unitless)
• TRESH_EVAP: fraction of water content in the evaporative layer below which evaporation is reduced (g[H20] g[Soil])
• TRESH_FTSW_TRANSPI: FTSW treshold below which transpiration is reduced (g[H20] g[Soil])

Environment inputs

• Precipitations: daily precipitation.
• Ri_PAR_f: daily incident PAR energy in MJ m[ground]⁻² d⁻¹, used to estimate transpiration.

Inputs

• ET0: daily reference evapotranspiration.
• aPPFD: absorbed daily PAR in mol[photon] m[ground]⁻² d⁻¹.

FTSW_BP(;
    ini_root_depth,
    H_FC=0.23,
    H_WP_Z1=0.05,
    Z1=200.0,
    H_WP_Z2=0.05,
    Z2=2000.0,
    H_0=0.15,
    KC=1.0,
    TRESH_EVAP=0.5,
    TRESH_FTSW_TRANSPI=0.5,
)

Fraction of Transpirable Soil Water model.

Arguments

• ini_root_depth: root depth at initialization (mm)
• H_FC: Humidity at field capacity (g[H20] g[Soil])
• H_WP_Z1: Humidity at wilting point (g[H20] g[Soil]) for the first layer
• Z1: Thickness of the first layer (mm)
• H_WP_Z2: Humidity at wilting point (g[H20] g[Soil]) for the second layer
• Z2: Thickness of the second layer (mm)
• H_0: Initial soil humidity (g[H20] g[Soil])
• KC: cultural coefficient (unitless)
• TRESH_EVAP: fraction of water content in the evaporative layer below which evaporation is reduced (g[H20] g[Soil])
• TRESH_FTSW_TRANSPI: FTSW treshold below which transpiration is reduced (g[H20] g[Soil])

Environment inputs

• Precipitations: daily precipitation.
• Ri_PAR_f: daily incident PAR energy in MJ m[ground]⁻² d⁻¹, used to estimate transpiration.

Inputs

• ET0: daily reference evapotranspiration.
• aPPFD: absorbed daily PAR in mol[photon] m[ground]⁻² d⁻¹.

FemaleBiomass(respirationcost,respirationcostoleosynthesis) FemaleBiomass(respirationcost=1.44,respirationcostoleosynthesis=3.2)

Compute female-inflorescence dry mass from daily CH2O-equivalent allocation. Allocation to the different bunch components (stalk and fruit) is proportional to their carbon demand.

Arguments

• respiration_cost: construction cost of non-oil tissues (g CH2O-equivalent allocated gDM⁻¹ produced)
• respiration_cost_oleosynthesis: oil construction cost (g CH2O-equivalent allocated gDM⁻¹ produced)

inputs

• carbon_allocation: assimilate allocated to the female inflorescence (g CH2O-equivalent)
• carbon_demand_stalk: carbon demand of the stalk
• carbon_demand_non_oil: carbon demand of non oil components of fruits
• carbon_demand_oil: carbon demand of fruits oil
• state: state of the inflorescence

outputs

• biomass: total inflorescence/bunch dry mass (gDM)
• biomass_stalk: stalk dry mass (gDM)
• biomass_fruits: fruit dry mass (gDM)
• biomass_oil: oil dry mass (gDM)
• biomass_non_oil: non-oil fruit dry mass (gDM)

FemaleCarbonDemandModel(
    respiration_cost,
    respiration_cost_oleosynthesis,
    TT_flowering,
    TT_fruiting,
    duration_bunch_development,
    duration_oleosynthesis,
    duration_dev_stalk,
)

FemaleCarbonDemandModel(;
    respiration_cost=1.44,
    respiration_cost_oleosynthesis=3.2,
    TT_flowering=10530.0,
    duration_bunch_development=1215.0,
    duration_fruit_setting=405.0,
    fraction_period_oleosynthesis=0.8,
    fraction_period_stalk=0.2
)

Carbon demand of the female inflorescence based on the potential fruit biomass

Arguments

• respiration_cost: construction cost of non-oil tissues (g CH2O-equivalent allocated gDM⁻¹ produced)
• respiration_cost_oleosynthesis: oil construction cost (g CH2O-equivalent allocated gDM⁻¹ produced)
• TT_flowering: thermal time for flowering since phytomer appearance (degree days).
• TT_fruiting: thermal time for fruit setting since phytomer appearance (degree days).
• duration_bunch_development: duration between fruit set and bunch maturity (ready for harvest) (degree days).
• duration_oleosynthesis: duration of oleosynthesis (degree days).
• duration_dev_stalk: duration of stalk development (degree days).
• duration_fruit_setting: period of thermal time after flowering that determines the number of flowers in the bunch that become fruits, i.e. fruit set (degree days).
• fraction_period_oleosynthesis: fraction of the duration between flowering and harvesting when oleosynthesis occurs
• fraction_period_stalk: fraction of the duration between flowering and harvesting when stalk development occurs

Inputs

• final_potential_biomass_non_oil_fruit: potential non-oil fruit dry mass (gDM fruit⁻¹)
• final_potential_biomass_oil_fruit: potential oil dry mass (gDM fruit⁻¹)
• final_potential_biomass_stalk: potential stalk dry mass (gDM)
• TEff: daily effective temperature (°C)
• TT_since_init: thermal time since the first day of the phytomer (degree days)
• state: state of the leaf

Outputs

• carbon_demand: total assimilate demand (g CH2O-equivalent d⁻¹)
• carbon_demand_oil: assimilate demand for oil production (g CH2O-equivalent d⁻¹)
• carbon_demand_non_oil: assimilate demand for non-oil production (g CH2O-equivalent d⁻¹)
• carbon_demand_stalk: assimilate demand for stalk development (g CH2O-equivalent d⁻¹)

FemaleFinalPotentialFruits(;
    days_increase_number_fruits=2379,
    days_maximum_number_fruits=6500,
    fraction_first_female=0.3,
    potential_fruit_number_at_maturity=2000,
    potential_fruit_weight_at_maturity=6.5,
    stalk_max_biomass=2100.0,
    oil_content=0.25
)

Arguments

• days_increase_number_fruits: age at which the number of fruits starts to increase (days)
• days_maximum_number_fruits: age at which the palm makes bunch of mature size with the highest number of fruits (days).
• fraction_first_female: size of the first bunches on a young palm relative to the size

at maturity (dimensionless)

• potential_fruit_number_at_maturity: potential number of fruits at maturity (number of fruits)
• potential_fruit_weight_at_maturity: potential dry mass of one fruit at maturity (gDM)
• stalk_max_biomass: maximum dry mass of the stalk (gDM)
• oil_content: oil dry-mass fraction of the fruit (gDM oil gDM⁻¹ fruit)

Inputs

• initiation_age: age at which the palm starts to make bunches (days)

Outputs

• potential_fruits_number: potential number of fruits (number of fruits)
• final_potential_fruit_biomass: potential dry mass per fruit (gDM)
• final_potential_biomass_stalk: potential stalk dry mass (gDM)
• final_potential_biomass_oil_fruit: potential oil dry mass per fruit (gDM)
• final_potential_biomass_non_oil_fruit: potential non-oil dry mass per fruit (gDM)

Examples

using PlantSimEngine
using XPalm
using XPalm.Models 

model = FemaleFinalPotentialFruits()
scene = CompositeModel(
    model;
    scale=:Female,
    status=(initiation_age=5000.0,),
)
run!(scene)
only(model_objects(scene; scale=:Female)).status.potential_fruits_number

GraphNodeCount(graph_node_count_ini=0)

Stores the number of nodes in the graph.

Arguments

• graph_node_count_ini: the initial number of nodes in the graph.

Outputs

• graph_node_count: the number of nodes in the graph.

Details

This model does nothing. It is just used to define the value of the graph's node count so it exists in the status of the organ.

The node cound should be updated by the models that create new organs at the time-step of organ emission.

InternodeBiomass(respirationcost) InternodeBiomass(respirationcost=1.44)

Compute internode biomass from daily carbon allocation

Arguments

• initial_biomass: initial structural dry mass of the internode (gDM)
• respiration_cost: construction cost (g CH2O-equivalent allocated gDM⁻¹ produced)

Inputs

• carbon_allocation: assimilate allocated to the internode (g CH2O-equivalent)

Outputs

• biomass: internode structural dry mass (gDM)

InternodeCarbonDemandModel(; apparentdensity=300000.0, respirationcost=1.44)

Compute internode carbon demand from potential dimensions

Arguments

• apparent_density: stem apparent density of dry matter (gDM m⁻³)
• respiration_cost: construction cost (g CH2O-equivalent allocated gDM⁻¹ produced)

Inputs

• potential_height: potential height of the internode (m)
• potential_radius: potential radius of the internode (m)

Outputs

• potential_volume: potential volume of the internode (m³)
• carbon_demand: daily assimilate demand of the internode (g CH2O-equivalent)

LAIModel()

Compute the leaf area index (LAI) using all leaves in the scene and the scene surface area.

Arguments

• area: the surface area of the scene.

Inputs

• leaf_areas: a vector of all leaf area values in the scene (from each leaf, or each plant)

Outputs

• leaf_area: the total leaf area of the scene (m²)
• lai: the leaf area index (m² m⁻²)

LeafAreaModel(lma_min, leaflets_biomass_contribution, leaf_area_ini)

Leaf area from its biomass.

Arguments

• lma_min: minimal leaflet dry mass per unit leaflet area (gDM m⁻², when there is no reserve in the leaf)
• leaflets_biomass_contribution: ratio of leaflets biomass to total leaf biomass including rachis and petiole (0-1)

Inputs

• biomass: structural leaf dry mass, including leaflets, rachis and petiole (gDM)

Outputs

• leaf_area: leaf area (m2)

LeafCarbonDemandModelArea(lma_min, respiration_cost, leaflets_biomass_contribution)

Carbon demand of the leaf based on the difference between the current leaf area and the potential leaf area.

This model assumes that the leaf is always trying to catch its potential growth, so leaf demand can increase more than the daily potential to alleviate any previous stress effect.

See also LeafCarbonDemandModelPotentialArea.

Arguments

• lma_min: minimum leaflet dry mass per unit leaflet area (gDM m⁻²)
• respiration_cost: construction cost (g CH2O-equivalent allocated gDM⁻¹ produced)
• leaflets_biomass_contribution: contribution of leaflet biomass to total leaf biomass, including rachis and petiole

LeafStateModel()

Give the state of the leaf

Arguments

None

Inputs

• maturity: a leaf is mature when it reaches its final length
• state_phytomers: state of the phytomers (multiscale variable)

Outputs

• state: leaf state (:undetermined, :Opened, :Pruned)
• rank_leaves: rank of all leaves

MaleBiomass(respirationcost) MaleBiomass(respirationcost=1.44)

Compute male biomass from daily carbon allocation

Arguments

• respiration_cost: construction cost (g CH2O-equivalent allocated gDM⁻¹ produced)

inputs

• carbon_allocation: assimilate allocated to the male inflorescence (g CH2O-equivalent)
• state: state of the inflorescence

outputs

• biomass: male-inflorescence dry mass (gDM)
• litter_male: senescent male-inflorescence dry mass transferred to litter (gDM)

MaleCarbonDemandModel(; respiration_cost=1.44, duration_flowering_male=1800.0)

Compute the daily CH2O-equivalent construction demand of a male inflorescence.

Arguments

• respiration_cost: construction cost (g CH2O-equivalent allocated gDM⁻¹ produced)
• duration_flowering_male: male-inflorescence growth duration (degree days)

Inputs

• final_potential_biomass: final potential dry mass (gDM)
• TEff: daily effective temperature (degree days d⁻¹)
• state: phytomer state

Outputs

• carbon_demand: daily assimilate demand (g CH2O-equivalent d⁻¹)

MaleFinalPotentialBiomass(male_max_biomass, age_mature_male, fraction_biomass_first_male)

Arguments

• male_max_biomass: maximum dry mass of a male inflorescence (gDM)
• age_mature_male: age at which the palm plant reaches a mature state for producing male inflorescences (days)
• fraction_biomass_first_male: fraction of the maximal biomass that first males can reach (dimensionless)

Inputs

• initiation_age: age of the plant when the organ was initiated (days)

Outputs

• final_potential_biomass: final potential dry mass of the male inflorescence (gDM)

NumberFruits(TT_flowering, duration_dev_fruits)

Determines the number of fruits on the bunch.

Arguments

• TT_flowering: thermal time for flowering since phytomer appearence (degree days).
• duration_fruit_setting: period of thermal time after flowering that determines the number of flowers in the bunch that become fruits, i.e. fruit set (degree days).
• computed:

Inputs

• carbon_offer_plant: daily plant assimilate offer after maintenance respiration (g CH2O-equivalent plant⁻¹ d⁻¹).
• potential_fruits_number: potential number of fruits (number/bunch).
• carbon_demand_plant: daily plant assimilate demand (g CH2O-equivalent plant⁻¹ d⁻¹), used to compute trophic status.

Outputs

• fruits_number: number of fruits (number/bunch).

NumberSpikelets(TT_flowering=6300.0, duration_dev_spikelets=675.0)

Determines the number of spikelets on the fruit bunch.

Arguments

• TT_flowering: thermal time for flowering since phytomer appearence (degree days).
• duration_dev_spikelets: period of thermal time before flowering that determines the number of spikelets on the fruit bunch (degree days).

OrgansCarbonAllocationModel()

Compute the carbon to allocate to organs from photosysthesis and reserve mobilization (after maintenance respiration)

Arguments

• cost_reserve_mobilization: carbon cost to mobilize carbon reserve from stem or leaves

PhyllochronModel(agepalmmaturity,productionspeedinitial,productionspeedmature)

Compute the phyllochron and initiate a new phytomer at every new emergence. The phyllochron may be reduced by TEff if it is itself modulated by e.g. the available water in the soil.

Arguments

• age_palm_maturity: age of the plant when maturity is establiched (days)
• production_speed_initial: initial phyllochron (for seedlings) (leaf.degreeC days-1)
• production_speed_mature: phyllochron at plant maturity (leaf.degreeC days-1)

Inputs

• plant_age= plant age (days)
• TEff: daily efficient temperature for plant growth (degree C days)

Outputs

• newPhytomerEmergence: fraction of time during two successive phytomer (at 1 the new phytomer emerge)
• production_speed= phyllochron at the current plant age (leaf.degreeC days-1)
• emit_phytomer: one-timestep pulse requesting one phytomer emission.

PhytomerEmission(mtg; phytomer_symbol=:Phytomer, internode_symbol=:Internode, leaf_symbol=:Leaf) <: AbstractPhytomer_EmissionModel

A PhytomerEmission model, which emits a new phytomer when called. The new phytomer is composed of an internode and a leaf, and is added as a child of the last phytomer.

Arguments

• mtg::MultiScaleTreeGraph.Node: The multiscale tree graph of the plant.
• phytomer_symbol::Symbol: The symbol of the phytomer, default to :Phytomer.
• internode_symbol::Symbol: The symbol of the internode, default to :Internode.
• leaf_symbol::Symbol: The symbol of the leaf, default to :Leaf.

Inputs

• graph_node_count::Int: The number of nodes in the graph.
• plant_age::Real: Current plant age, copied to newborn organs.
• emit_phytomer::Bool: One-timestep emission pulse.

Outputs

• last_phytomer::PlantSimEngine.ObjectId: Stable identity of the last phytomer of the palm.
• phytomer_count::Int: The number of phytomers in the palm.

The application is scheduled every timestep but mutates the graph only when emit_phytomer is true. Consequently, phytomer_count is published at the regular application cadence, including timesteps without an emission.

PlantLeafAreaModel()

Sum of the leaf area at plant scale.

Inputs

• leaf_area_leaves: a vector of leaf area (m²)
• leaf_states: a vector of leaf states. Only leaves with state :opened are considered.

Outputs

• leaf_area: total leaf area of the plant (m²)

PlantRm()

Total plant maintenance respiration based on the sum of Rm.

Inputs

• Rm_organs: maintenance respiration of the plant organs (g CH2O-equivalent d⁻¹ per organ)

Outputs

• Rm: total plant maintenance respiration (g CH2O-equivalent d⁻¹)

PotentialAreaModel(inflexion_index, slope)
PotentialAreaModel(inflexion_index=  560.0, slope=100.0)

Computes the instantaneous potential area at a given cumulative thermal time using a logistic function. In other words, it defines the development of the leaf area at the potential, i.e. without any stress. It starts around 0.0 and goes to a maximum of final_potential_area.

Arguments

• inflexion_index: a parameter that defines the relationship between the final potential

leaf area and the inflexion point of the logistic function. The higher the final area, the longer the time to reach the inflexion point.

• slope: the slope of the relationship at the inflexion point.

Inputs

• final_potential_area: the final potential area when the leaf is fully developed
• TT_since_init: the cumulated thermal time since leaf initiation

Outputs

• potential_area: potential area of the leaf (m2)
• maturity: maturity is true when the leaf reaches its final length

PotentialReserveInternode(nsc_max)

Compute the remaining internode reserve capacity in XPalm's assimilate currency (g CH2O-equivalent).

Arguments

• nsc_max: maximum non-structural carbohydrate reserve relative to internode structural dry mass (g CH2O-equivalent gDM⁻¹)

Inputs

• biomass: internode structural dry mass (gDM)
• reserve: current reserve (g CH2O-equivalent)

Outputs

• potential_reserve: remaining reserve capacity (g CH2O-equivalent)

PotentialReserveLeaf(lma_min, lma_max, leaflets_biomass_contribution)

Compute the remaining leaf reserve capacity in XPalm's assimilate currency.

lma_max - lma_min represents the additional dry mass that can be stored per unit leaflet area. That non-structural carbohydrate capacity is represented as g CH2O-equivalent; no elemental-carbon fraction is applied.

Inputs

• leaf_area: leaflet area (m²)
• reserve: current leaf reserve (g CH2O-equivalent)

Outputs

• potential_reserve: remaining reserve capacity (g CH2O-equivalent)

RUE_FTSW(rue, threshold_ftsw)

Computes the carbon_assimilation using a constant radiation use efficiency (rue).

Arguments

• rue: gross radiation use efficiency (g CH2O-equivalent MJ⁻¹)
• threshold_ftsw: unitless FTSW threshold below which RUE is reduced.

Inputs

• aPPFD: absorbed PAR in mol[photon] plant⁻¹ d⁻¹.

Outputs

• carbon_assimilation: gross assimilate production (g CH2O-equivalent plant⁻¹ d⁻¹)

RankLeafPruning(rank)

Function to remove leaf biomass and area when the phytomer has a harvested bunch or when the leaf reaches a threshold rank (below the rank of harvested bunches).

Arguments

• rank: leaf-rank threshold below which the leaf is cut

Inputs

• state: phytomer state

Outputs

• litter_leaf: structural leaf dry mass removed from the plant and transferred to the litter (gDM)

add_reproductive_organ!(...)

Add a new reproductive organ to a phytomer.

RmQ10FixedN(Q10, Mr, T_ref, P_alive)
RmQ10FixedN(Q10, Turn, Prot, N, Gi, Mx, T_ref, P_alive)

Maintenance respiration based on a Q10 computation with fixed nitrogen values and proportion of living cells in the organs.

See those three references for more details:

Dufrene, Ochs, et Saugier, « Photosynthèse et productivité du palmier à huile en liaison avec les facteurs climatiques ». Wit, Simulation of Assimilation, Respiration and Transpiration of Crops; DE VRIES, « The Cost of Maintenance Processes in Plant Cells ». DE VRIES, « The Cost of Maintenance Processes in Plant Cells ».

Arguments

• Q10: Q10 factor (values should usually range between: 1.5 - 2.5, with 2.1 being the most common value)
• Mr: maintenance respiration coefficient (g CH2O-equivalent gDM⁻¹ d⁻¹)
• T_ref: Reference temperature at which Q10 was measured (usually around 25.0°C)
• P_alive: proportion of living cells in the organ
• Turn: maintenance cost coefficient of the turnover of free proteins and membranes
• Prot= 6.25: nitrogen to protein conversion coefficient
• N: nitrogen content of the organ (gN gDM⁻¹)
• Gi: maintenance cost coefficient of the ionic gradient
• Mx:mineral content of the organ (g gDM⁻¹)

Environment inputs

• Tmin, Tmax: daily minimum and maximum air temperatures (°C).

Inputs

• biomass: organ structural dry mass (gDM); reserve carbon is a separate pool

Outputs

• Rm: maintenance respiration (g CH2O-equivalent d⁻¹)

RootGrowthFTSW(TRESHFTSWSLOWROOTS, ROOTSGROWTHDEPTH, Z1, Z2) RootGrowthFTSW(TRESHFTSWSLOWROOTS=0.2, ROOTSGROWTHDEPTH=0.3, Z1=200, Z2=2000)

Compute root growth depending on thermal time and water stress (ftsw)

Arguments

• ini_root_depth: initial root depth (mm)
• ROOTS_GROWTH_DEPTH: root growth in depth (mm.degreeC days-1)
• TRESH_FTSW_SLOW_ROOTS: ftsw treshold below which roots growth is reduced (unitless [0:1])

The model as a dependency on an AbstractFTSWModel that must return a value for ftsw, and soil_depth.

SceneToPlantLightPartitioning(scene_area)

Partitioning from aPPFD at the scene scale to the plant scale based on the relative leaf area of the plant.

Arguments

• scene_area: represented ground area of the scene (m²). In XPalm's default one-palm scene this is 10000 / planting_density for a density in palm ha⁻¹.

Inputs

• aPPFD_scene: absorbed PAR in mol[photon] m[ground]⁻² d⁻¹.
• leaf_area: the target plant leaf area in m².
• scene_leaf_area: the total scene leaf area in m².

Outputs

• aPPFD: absorbed PAR in mol[photon] plant⁻¹ d⁻¹.

The local input name aPPFD_scene distinguishes the ground-area value from the plant-total aPPFD output because both coexist inside this conversion model. The ordinary published variable remains aPPFD at both object scales.

SexDetermination(TT_flowering, duration_abortion, duration_sex_determination, sex_ratio_min, sex_ratio_ref, rng)
SexDetermination(TT_flowering, duration_abortion, duration_sex_determination, sex_ratio_min, sex_ratio_ref; random_seed=1)

Determines the sex of a phytomer -or rather, its bunch- based on the trophic state of the plant during a given period in thermal time.

Arguments

• TT_flowering: thermal time for flowering since phytomer appearence (degree days).
• duration_abortion: duration used for computing abortion rate before flowering (degree days).
• duration_sex_determination: duration used for sex determination before the abortion period(degree days).
• sex_ratio_min: minimum allowed threshold of the sex ratio.
• sex_ratio_ref: reference threshold of the sex ratio, i.e. the value when the trophic status is 1 (offer=demand).
• rng: random number generator, Random.MersenneTwister by default.
• random_seed: random seed for the random number generator, 1 by default.

Inputs

• carbon_offer_plant: daily plant assimilate offer after maintenance respiration (g CH2O-equivalent plant⁻¹ d⁻¹).
• carbon_demand_plant: daily total plant assimilate demand (g CH2O-equivalent plant⁻¹ d⁻¹).

Outputs

• sex: the sex of the phytomer (or bunch) (:undetermined, :Female or :Male).
• carbon_demand_sex_determination: assimilate demand accumulated over the sex-determination period (g CH2O-equivalent plant⁻¹)
• carbon_offer_sex_determination: assimilate offer accumulated over the sex-determination period (g CH2O-equivalent plant⁻¹)
• emit_reproductive_organ: one-timestep pulse requesting emission of the determined reproductive organ.

Note

The sex of the organ is determined at TT_flowering-duration_abortion based on the trophic_status of the plant during a period of time before this date. The hypothesis is that a trophic stress can trigger more males in the plant.

StemBiomass()

Aggregate internode structural dry masses without creating an additional carbon demand.

Inputs

• biomass_internodes: internode structural dry masses (gDM)

Outputs

• biomass: total stem structural dry mass (gDM)

Compute root growth

Arguments

• m: root growth model
• ftsw: fraction of transpirable soil water (unitless [0:1])
• TEff: daily efficient temperature for plant growth (degree C days)

Outputs

• root_depth: root depth (cm)

run!(object, environment, constants = Constants())

Computes the light interception of an object using the Beer-Lambert law.

Arguments

• ::Beer: a Beer light-interception model.
• status: object state with lai initialized in m² m⁻².
• environment: meteorology structure, see Atmosphere
• constants = PlantMeteo.Constants(): physical constants. See PlantMeteo.Constants for more details

Examples

using XPalm, PlantSimEngine, PlantMeteo, Dates
environment = (
    Ri_PAR_f=8.0, # daily PAR energy in MJ m[ground]^-2 d^-1
    duration=Day(1),
)
scene = CompositeModel(
    Object(:scene; scale=:Scene, kind=:scene, status=Status(lai=2.0));
    applications=(
        ModelSpec(Beer(0.5); on=One(scale=:Scene)),
    ),
    environment=environment,
)
run!(scene)
only(model_objects(scene; scale=:Scene)).status.aPPFD

add_phytomer!(palm, initiation_age)

Add a new phytomer to the palm

Arguments

• palm: a Palm
• initiation_age::Dates.Date: date of initiation of the phytomer

add_reproductive_organ!(...)

Add a new reproductive organ to a phytomer.

KS(fillRate, tresh)

Coefficient of stress.

Arguments

• fillRate: fill level of the compartment
• tresh: filling treshold of the compartment below which there is a reduction in the flow

KS_bp(fillRate, tresh)

Coefficient of stress.

Arguments

• fillRate: fill level of the compartment
• tresh: filling treshold of the compartment below which there is a reduction in the flow

compute_compartment_size(m, root_depth)

Compute the size of the layers of the FTSW model.

Arguments

• m: FTSW model
• root_depth: depth of the root system

Returns

• SizeC1: size of the evapotranspirable water layer in the first soil layer (mm)
• SizeVap: size of the evaporative layer within the first layer (mm)
• SizeC1minusVap: size of the transpirable layer within the first layer (SizeC1-SizeVap)
• SizeC2: size of the transpirable water layer in the first soil layer (mm)
• SizeC: size of transpirable soil water (mm) (SizeC2 + SizeC1minusVap)

compute_compartment_size(m, root_depth)

Compute the size of the layers of the FTSW model.

Arguments

• m: FTSW model
• root_depth: depth of the root system

Returns

• SizeC1: size of the evapotranspirable water layer in the first soil layer (mm)
• SizeVap: size of the evaporative layer within the first layer (mm)
• SizeC1minusVap: size of the transpirable layer within the first layer (SizeC1-SizeVap)
• SizeC2: size of the transpirable water layer in the first soil layer (mm)
• SizeC: size of transpirable soil water (mm) (SizeC2 + SizeC1minusVap)