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How a crop model works: Drivers of
growth, development and phenology
Mukhtar Ahmed
mukhtar.ahmed@slu.se
ahmadmukhtar@uaar.edu.pk
1
Objective
Understanding about climatic variables impacts on growth,
development and phenology of crop.
2
3
Modeling
CropEnvironment
Soil
o Temperature
o Solar radiation
o Rainfall
o CO2
o Phenology
o Growth
o Development
o Yield
o Soil texture
o DUL
o DLL
o Nutrients dynamics
4
CO2
Light Temperature Rainfall/Irrigation
Management
Carter 2013
Soil
Phenology
• Timing of visual events which changes from one stage to next
• Study of the timing of recurring biological events, the causes of their
timing with regard to biotic and abiotic forces, and the interrelation
among phases of the same or different species (Leith 1974).
5
Zadoks Growth stages (Zadoks et al., 1974)
Growth and Development
Growth Development
Growth of crops, plants or
plant parts is defined as the
irreversible increase in size
Development is the continuous
change in plant form and function
with characteristic transition phases
It is primarily associated with
capture and allocation of
resources
Development is mostly related to
non-resource environmental cues
such as temperature, photoperiod
and light quality.
6
Development is rate of progress through an organism life cycle
Ontogeny: Time course of development through phases of life cycle
Drivers of Phenology
• Temperature
• Thermal time calculation (ΔTT)
7
Growing degree
days accumulation
phenological stages
Photoperiod
(fD)
Vernalization
(fv)
optimum T
requirements
Other environmental factors
Soil water stress(fw, pheno),
N stress (fN, pheno)
P stress (fP, pheno)
Cardinal Temperature
• Tbase: Base temperature below which development rate =0
• Topt1:1st Optimum temperature at which development rate is most
rapid
• Topt2:2nd Optimum temperature; highest temperature at which rate is
still at its maximum
• Tmax: Maximum temperature at which development rate=0
8
9
Tbase & Topt from field data
Plot reciprocal of days to anthesis vs temperature
Tb= The x-axis intercept
Topt= Temperature at which rate is maximum
(99%)
Non Linear function
10
Crown Temperature
in response to air temperature (T) for different snow depth (Hsnow)
11
Snow depth
Hsnow default
is set to zero
Source: Zheng B, Chenu K, Doherty A, Doherty
T, Chapman L (2014) The APSIM-Wheat
Module (7.5 R3008). In. APSRU Toowoomba,
Australia
CardinalTemperatures
Crown temperature and thermal time
12
Source: Zheng B, Chenu K, Doherty A, Doherty
T, Chapman L (2014) The APSIM-Wheat
Module (7.5 R3008). In. APSRU Toowoomba,
Australia
Degree day Approach
13
o If T > Tbase
o Degree day=Tavg-Tbase
o If T<Tbase
Degree day=0
o If T > Topt
Degree day=Topt-Tbase
o Tbase=8
o Topt=30
Avg. Temp Degree Day
7 0
15 7
30 22
40 22
Four methods used to calculate
thermal time (DTT and HTT)
14
cumulative daily thermal time (DTT)
Where Tmax is the maximum
temperature, Tmin is the minimum
temperature, Tavg = (Tmax + Tmin)/2, Tb is
the base temperature, and Tu is the
upper threshold temperature.
Method 1:
Method 2:
Where Tm = min (Tmax, Tu), Tn = max (Tm,
Tb), and Tavg′ = (Tm + Tn)/2.
Tb is compared with Tu before the average temperature (Tavg′) is calculated. Tm and
Tn are adjusted if they are <Tb or >Tu. In this method, DTT is given by
Four methods used to calculate
thermal time (DTT and HTT)
Method 3:
Method 4:
15
16
Comparison of the four methods used to calculate thermal time (DTT and HTT)
Photoperiod impact on phenology
17
Source: Zheng B, Chenu K, Doherty A, Doherty
T, Chapman L (2014) The APSIM-Wheat
Module (7.5 R3008). In. APSRU Toowoomba,
Australia
Photo Growing Degree Days (PGDD)
PGDD= WEDD x Photoperiod
https://www.frontiersin.org/articles/10.3389/fenvs.2017.00057/full
18
Vernalisation impact on phenology
19
Source: Zheng B, Chenu K, Doherty A, Doherty
T, Chapman L (2014) The APSIM-Wheat
Module (7.5 R3008). In. APSRU Toowoomba,
Australia
Devernalisation (ΔV d)
20
Source: Zheng B, Chenu K, Doherty A, Doherty
T, Chapman L (2014) The APSIM-Wheat
Module (7.5 R3008). In. APSRU Toowoomba,
Australia
Cumulative or Total vernalisation (V )
21
V= σ(∆𝑉 − ∆𝑉𝑑)
Vernalization factor (fv) is calculated just from Emergence to Floral initiation
𝑓𝑣 = 1 − 0.0054545𝑅 𝑣 + 0.0003 × (50 − 𝑉)
RV = Sensitivities to vernalisation, which is cultivar-specific and is specified by vern_sens (1.5)
Source: Zheng B, Chenu K, Doherty A, Doherty
T, Chapman L (2014) The APSIM-Wheat
Module (7.5 R3008). In. APSRU Toowoomba,
Australia
Photosynthesis
Potential Growth= f(cover, radiation, rue)
∆DM = RUE x radn x cover
RUE = f(water, N, P,T, CO2)
cover = 1 - e-k x LAI (Beer-Lambert law)
RUE – radiation use efficiency. (grams biomass / MJ)
K – extinction coefficient; crop specific, affected by row spacing.
Water limited growth = sw supply * TEC /VPD
TEC = Transpiration efficiency coefficient.
Actual growth = minimum of potential and water limited growth.
22
Biomass accumulation (Photosynthesis)
• Daily biomass accumulation (ΔQ) = Radiation interception (ΔQr)
∆𝑄 𝑟 = 𝐼 × 𝑅𝑈𝐸 × 𝑓𝑑 × 𝑓𝑠 × 𝑓𝑐
Radiation interception is calculated from the leaf area index (LAI, m2 m−2) and
the extinction coefficient (k)
𝐼 = 𝐼 𝑜(1 − exp(−𝑘 × 𝐿𝐴𝐼 × 𝑓ℎ)/ 𝑓ℎ)
where I0 = Total radiation at the top of the canopy (MJ)
fh = Light interception modified to give hedge-row effect with skip row (fh=1)
𝐼 = 𝐼 𝑜(1 − exp(−𝑘 × 𝐿𝐴𝐼))
Extinction coefficient (k) varies with row spacing
𝑘 = ℎ 𝑒 𝑊𝑟
Wr = Row spacing which is specified by the user
he = Function of rowing spacing which is defined for both green leaf
and dead leaves by parameters x_row_spacing, y_extinct_coef
23
Radiation use efficiency (RUE)
24
Source: Zheng B, Chenu K, Doherty A, Doherty
T, Chapman L (2014) The APSIM-Wheat
Module (7.5 R3008). In. APSRU Toowoomba,
Australia
Biomass production
Partitioning to leaf, stem, ear/pod and root is stage dependant.
Grain filling takes priority during reproductive growth.
Sink size is determined by one of
Harvest Index,
Grain number/size
Grain cohorts (ears).
25
Stress factor
Temperature factor fT, photo
26
Source: Zheng B, Chenu K, Doherty A, Doherty
T, Chapman L (2014) The APSIM-Wheat
Module (7.5 R3008). In. APSRU Toowoomba,
Australia
CO2 factor
27
Source: Zheng B, Chenu K, Doherty A, Doherty
T, Chapman L (2014) The APSIM-Wheat
Module (7.5 R3008). In. APSRU Toowoomba,
Australia
Thanks
28

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Drivers of phenology ma

  • 1. How a crop model works: Drivers of growth, development and phenology Mukhtar Ahmed mukhtar.ahmed@slu.se ahmadmukhtar@uaar.edu.pk 1
  • 2. Objective Understanding about climatic variables impacts on growth, development and phenology of crop. 2
  • 3. 3 Modeling CropEnvironment Soil o Temperature o Solar radiation o Rainfall o CO2 o Phenology o Growth o Development o Yield o Soil texture o DUL o DLL o Nutrients dynamics
  • 5. Phenology • Timing of visual events which changes from one stage to next • Study of the timing of recurring biological events, the causes of their timing with regard to biotic and abiotic forces, and the interrelation among phases of the same or different species (Leith 1974). 5 Zadoks Growth stages (Zadoks et al., 1974)
  • 6. Growth and Development Growth Development Growth of crops, plants or plant parts is defined as the irreversible increase in size Development is the continuous change in plant form and function with characteristic transition phases It is primarily associated with capture and allocation of resources Development is mostly related to non-resource environmental cues such as temperature, photoperiod and light quality. 6 Development is rate of progress through an organism life cycle Ontogeny: Time course of development through phases of life cycle
  • 7. Drivers of Phenology • Temperature • Thermal time calculation (ΔTT) 7 Growing degree days accumulation phenological stages Photoperiod (fD) Vernalization (fv) optimum T requirements Other environmental factors Soil water stress(fw, pheno), N stress (fN, pheno) P stress (fP, pheno)
  • 8. Cardinal Temperature • Tbase: Base temperature below which development rate =0 • Topt1:1st Optimum temperature at which development rate is most rapid • Topt2:2nd Optimum temperature; highest temperature at which rate is still at its maximum • Tmax: Maximum temperature at which development rate=0 8
  • 9. 9 Tbase & Topt from field data Plot reciprocal of days to anthesis vs temperature Tb= The x-axis intercept Topt= Temperature at which rate is maximum (99%)
  • 11. Crown Temperature in response to air temperature (T) for different snow depth (Hsnow) 11 Snow depth Hsnow default is set to zero Source: Zheng B, Chenu K, Doherty A, Doherty T, Chapman L (2014) The APSIM-Wheat Module (7.5 R3008). In. APSRU Toowoomba, Australia
  • 12. CardinalTemperatures Crown temperature and thermal time 12 Source: Zheng B, Chenu K, Doherty A, Doherty T, Chapman L (2014) The APSIM-Wheat Module (7.5 R3008). In. APSRU Toowoomba, Australia
  • 13. Degree day Approach 13 o If T > Tbase o Degree day=Tavg-Tbase o If T<Tbase Degree day=0 o If T > Topt Degree day=Topt-Tbase o Tbase=8 o Topt=30 Avg. Temp Degree Day 7 0 15 7 30 22 40 22
  • 14. Four methods used to calculate thermal time (DTT and HTT) 14 cumulative daily thermal time (DTT) Where Tmax is the maximum temperature, Tmin is the minimum temperature, Tavg = (Tmax + Tmin)/2, Tb is the base temperature, and Tu is the upper threshold temperature. Method 1: Method 2: Where Tm = min (Tmax, Tu), Tn = max (Tm, Tb), and Tavg′ = (Tm + Tn)/2. Tb is compared with Tu before the average temperature (Tavg′) is calculated. Tm and Tn are adjusted if they are <Tb or >Tu. In this method, DTT is given by
  • 15. Four methods used to calculate thermal time (DTT and HTT) Method 3: Method 4: 15
  • 16. 16 Comparison of the four methods used to calculate thermal time (DTT and HTT)
  • 17. Photoperiod impact on phenology 17 Source: Zheng B, Chenu K, Doherty A, Doherty T, Chapman L (2014) The APSIM-Wheat Module (7.5 R3008). In. APSRU Toowoomba, Australia
  • 18. Photo Growing Degree Days (PGDD) PGDD= WEDD x Photoperiod https://www.frontiersin.org/articles/10.3389/fenvs.2017.00057/full 18
  • 19. Vernalisation impact on phenology 19 Source: Zheng B, Chenu K, Doherty A, Doherty T, Chapman L (2014) The APSIM-Wheat Module (7.5 R3008). In. APSRU Toowoomba, Australia
  • 20. Devernalisation (ΔV d) 20 Source: Zheng B, Chenu K, Doherty A, Doherty T, Chapman L (2014) The APSIM-Wheat Module (7.5 R3008). In. APSRU Toowoomba, Australia
  • 21. Cumulative or Total vernalisation (V ) 21 V= σ(∆𝑉 − ∆𝑉𝑑) Vernalization factor (fv) is calculated just from Emergence to Floral initiation 𝑓𝑣 = 1 − 0.0054545𝑅 𝑣 + 0.0003 × (50 − 𝑉) RV = Sensitivities to vernalisation, which is cultivar-specific and is specified by vern_sens (1.5) Source: Zheng B, Chenu K, Doherty A, Doherty T, Chapman L (2014) The APSIM-Wheat Module (7.5 R3008). In. APSRU Toowoomba, Australia
  • 22. Photosynthesis Potential Growth= f(cover, radiation, rue) ∆DM = RUE x radn x cover RUE = f(water, N, P,T, CO2) cover = 1 - e-k x LAI (Beer-Lambert law) RUE – radiation use efficiency. (grams biomass / MJ) K – extinction coefficient; crop specific, affected by row spacing. Water limited growth = sw supply * TEC /VPD TEC = Transpiration efficiency coefficient. Actual growth = minimum of potential and water limited growth. 22
  • 23. Biomass accumulation (Photosynthesis) • Daily biomass accumulation (ΔQ) = Radiation interception (ΔQr) ∆𝑄 𝑟 = 𝐼 × 𝑅𝑈𝐸 × 𝑓𝑑 × 𝑓𝑠 × 𝑓𝑐 Radiation interception is calculated from the leaf area index (LAI, m2 m−2) and the extinction coefficient (k) 𝐼 = 𝐼 𝑜(1 − exp(−𝑘 × 𝐿𝐴𝐼 × 𝑓ℎ)/ 𝑓ℎ) where I0 = Total radiation at the top of the canopy (MJ) fh = Light interception modified to give hedge-row effect with skip row (fh=1) 𝐼 = 𝐼 𝑜(1 − exp(−𝑘 × 𝐿𝐴𝐼)) Extinction coefficient (k) varies with row spacing 𝑘 = ℎ 𝑒 𝑊𝑟 Wr = Row spacing which is specified by the user he = Function of rowing spacing which is defined for both green leaf and dead leaves by parameters x_row_spacing, y_extinct_coef 23
  • 24. Radiation use efficiency (RUE) 24 Source: Zheng B, Chenu K, Doherty A, Doherty T, Chapman L (2014) The APSIM-Wheat Module (7.5 R3008). In. APSRU Toowoomba, Australia
  • 25. Biomass production Partitioning to leaf, stem, ear/pod and root is stage dependant. Grain filling takes priority during reproductive growth. Sink size is determined by one of Harvest Index, Grain number/size Grain cohorts (ears). 25
  • 26. Stress factor Temperature factor fT, photo 26 Source: Zheng B, Chenu K, Doherty A, Doherty T, Chapman L (2014) The APSIM-Wheat Module (7.5 R3008). In. APSRU Toowoomba, Australia
  • 27. CO2 factor 27 Source: Zheng B, Chenu K, Doherty A, Doherty T, Chapman L (2014) The APSIM-Wheat Module (7.5 R3008). In. APSRU Toowoomba, Australia