Crop Modeling

Crop Modeling

1. Central Laboratory for Agricultural Climate
(CLAC)
Methodology of Studying the Impact of Climate
Change on Crop Productivity
By
Dr. Mahmoud Medany
Dakkar, 24 March 2004

2. Integrated Crop Management Information System by
using DSSAT program

3. WhoUsesDSSATTools?
AgronomicResearchersandExtension
Specialists
PolicyMakers
FarmersandtheirAdvisors
PrivateSector
Educators

4. The program presents a table that includes fertilizer N added , N taken up by crop,
N leached below 1.8m, and final Nitrate –N in soil (Kg/ha) and grain yield of
crop (Kg/ha) for that run

5. DSSAT was designed to allow users to :
Input, organize and store data on crop, soil and weather “data
base”·
Retrieve, analyze and display data.
Calibrate and evaluate crop growth models.
Evaluate different management practices and compare simulation
results with their own measured results to give them confidence
that models work adequately.
DSSAT allow users to simulate option for crop management over
a number of years to assess the risks associated with each option.
Create different management strategies and the simulated
performance indicators that can be analyzed.

6. Applications of Crop Models
Based on understanding of plants, soil, weather and
management interactions
Predict crop growth, yield, timing (Outputs)
Optimize Management using Climate Predictions
Diagnose Yield Gaps, Actual vs. Potential
Optimize Irrigation Management
Greenhouse Climate Control
Quantify Pest Damage Effects on Production
Precision Farming
Climate Change Effects on Crop Production
Can be used to perform “what-if” experiments on the computer
to optimize management

7. Daily Increase in Dry Matter Growth:
Photosynthesis and Respiration
Daily Growth = CVF * Gross Photosynthesis -Respiration
dW/dt = CVF * ((30/44) * A -MC * W)
dW/dt = Plant Growth Rate, g m
-2
s
-1
CVF = Conversion Efficiency, g tissue (g glucose)
-1
30/44 = Converts CO
2into Glucose, g glucose (g CO
2 )
-1
A = Gross Photosynthesis, g [CO
2] m
-2
s
-1
MC = Maintenance Respiration Coefficient, s
-1
W = Plant Tissue Mass, g m
-2
or
Updating Growth
Mass
t+1= Mass
t+ Growth
t-Abort
t

8. Conversion Factor (CVF)
1/CVF= f
leaf/0.68 + f
stem/0.66 + f
root/0.68 + f
storage /Co
CVF= Conversion factor (g product g
-1
glucose)
f = Fraction of each organ in the increase in total dry matter (f=1)
C
o= Conversion factor of storage organ (g product g
-1
glucose)
For example, Co is 0.67 for maize, 0.78 for potato, 0.46 for
soybean, and 0.40 for peanut.

9. Water Management N Application + Organic
Crop
(Genetic Coefficients )
Development
Mass of Crop
Kg/ha
Duration of
Phases
Growth
Partitioning
Leaf StemRootFruit
Weather
CO
2
Photosynthesis
Respiration
Soil

10. File x
Experimental
Data File
File C
Cultivar Code
File A
Crop Data
at Harvest
File T
Crop Data
during season
Output Depending on Option Setting and Simulation Application
File w
Weather Data
File S
Soil Data
Crop
Models
INPUTS

11. Seventy different soil location were chosen and soil properties were determined as
follow:
-Soil physical conditions of the profile by layer.
-Soil chemical conditions of the profile by layer
-Sand,Clay&Silt%.
-Organiccarbon.
-Coarsefraction<2mm,%ofwholesoil.
-pHofsoil.
-Soilclassification.
-Soilhorizon.
-Rootabundanceinformation.
-Slope%.
-Soilcolor.
-Permeabilitycode.
-Drainage.
-Latitude
-Longitude
-Soiltexture
-Numberoflayer
-Bulkdensity1/3bar(g/cm
3
)
-%Totalnitrogen
-CEC
Soil analysis and fertility measurements

12. Historical weather data:
Thirty-five years of weather data for different experimental locations have already been
collected.
Theminimumrequiredweatherdataincludes:
-Latitudeandlongitudeoftheweatherstation,.
-Dailyvaluesofincomingsolarradiation(MJ/m²-day),
-Maximumandminimumairtemperature(°C),and
-Rainfall(mm).

13. COEFF DEFINITIONS
VAR# Identification code or number for a specific cultivar
VAR-NAME Name of cultivar
ECO# Ecotype code or this cultivar, points to the Ecotype in the
ECO file (currently not used).
P1 Thermal time from seedling emergence to the end of the juvenile phase (expressed in degree days above a
base temperature of 8 ّC(during which the plant is not responsive to changes in photoperiod.
P2 Extent to which development (expressed as days) is delayed for each hour increase in photoperiod above the
longest photoperiod at which development proceeds at a maximum rate (which is considered to be 12.5
hours).
P5 Thermal time from silking to physiological maturity (expressed in degree days above a base temperature of 8 ّC).
G2 Maximum possible number of kernels per plant.
G3 Kernel filling rate during the linear grain filling stage and under optimum conditions (mg/day).
PHINT Phylochron interval; the interval in thermal time (degree days)between successive leaf tip appearances.
@VAR# VRNAME.......... ECO# P 1 P2 P5 G2 G3 PHINT
EG0011 S.C. 9 IB0001 400.0 0.200 620.0 650.0 11.4 40.00
EG0004 SC 10 IB0001 400.0 0.300 865.0 720.0 11.5 38.90
EG0013 S.C-103 IB0001 295.0 0.520 593.0 695.0 13.4 38.90
EG0007 S.C-122 IB0001 270.0 0.500 580.0 650.0 13.6 38.90
EG0008 S.C-124 IB0001 290.0 0.500 630.0 630.0 14.8 38.90
EG0002 T.W.C.310 IB0001 430.0 0.200 868.0 700.0 10.0 40.00
EG0014 T.W.C.323 IB0001 290.0 0.300 680.0 635.0 12.2 38.90
MAIZE GENOTYPE COEFFICIENTS

14. Genetic Coefficients
Lifecycle
Photosynthesis
Sensitivitytodaylight(photoperiod)
Leafarea
Partitioning
Re-mobilization
Seedgrowth
Seedcomposition
Seedfillduration
Vernalization
Growingdegreedaysaccumulation
GeneticCoefficientsforeachvarietyaffectedby:

15. Crop Development
PlantEmerge
1st Flower1st Seed
Phys. Maturity
Harvest
Maturity
Vegetative Growth PeriodReproductive Growth Period
VegetativeDevelopmentismainlyaffectedbyTemperaturesuchasappearance
ofleavesonmainstem)
ReproductiveDevelopmentisaffectedbytemperatureanddaylength(suchas
durationofseedgrowthphase)
Sensitivitytostressesvariesconsiderablywithstageofgrowth
Cropgrowthinsimulationmodelingusuallyreferstotheaccumulationof
biomasswithtimeanditspartitioningdifferentorgans.
Time

16. Adapting the DSSAT to our conditions we use the
following procedures
Conductfieldexperimentstocollectminimumdatasetrequiredtorunning
andevaluatingcropmodelunderEgyptcondition.
Enterotherinputsoildatafortheregionandhistoricalweatherdataforsitesin
theregion(notstartcalibrationofcropparametersbeforecheckingthe
qualityofweatherdata).
Runthemodeltoevaluatetheabilityofmodeltopredict
Modifymodeltoevaluationshowsthatitdoesnotreachthelevelofprecision
required.
Conductsensitivityanalysisonthecropmodelstoevaluatethemodalresponses
toalternativepracticesusingvariances,wateruse,seasonlength,nitrogen
uptake,netprofitandotherresponses.
Provideresultsandrecommendationsfordecision-making.
Outputcanbeprintedorgraphicallydisplayedforconductingsensitivity
analysis.

17. Modelvalidation
Conduct sensitivity analysis on the crop
models to evaluate the modal
Experimental data Other inputs
Modification model
Parameter test
Simulation
DSSAT program
Compare simulation
with measured

18. Building New Software
for Data Entry

24. Wheat

25. *RUN 6 : GIZA 164
MODEL : GECER 980 -WHEAT
EXPERIMENT : EGDK 9101 WH DK&BN
TREATMENT 6 : GIZA 164
CROP : WHEAT CULTIVAR : GIZA 164 -
STARTING DATE : NOV 20 1991
PLANTING DATE : NOV 20 1991 PLANTS/m2 :110.0 ROW SPACING : 20.cm
WEATHER : EGNA 1991
SOIL : EGNA 870001 TEXTURE : CL -SIDS
SOIL INITIAL C : DEPTH: 120cm EXTR. H2O:148.6mm NO3: 1.6kg/ha NH4: 1.6kg/ha
WATER BALANCE : IRRIGATE ON REPORTED DATE(S)
IRRIGATION : 380 mm IN 5 APPLICATIONS
NITROGEN BAL. : SOIL -N & N-UPTAKE SIMULATION; NO N -FIXATION
N-FERTILIZER : 150 kg/ha IN 2 APPLICATIONS
RESIDUE/MANURE : INITIAL : 0 kg/ha ; 0 kg/ha IN 0 APPLICATIONS
ENVIRONM. OPT. : DAYL= . 00 SRAD= .00 TMAX= .00 TMIN= .00
RAIN= .00 CO2 = R330.00 DEW = .00 WIND= .00
SIMULATION OPT : WATER :Y NITROGEN:Y N -FIX:N PESTS :N PHOTO :C ET :R
MANAGEMENT OPT : PLANTING:R IRRIG :R FERT :R RESIDUE:R HARVEST:M WTH:M

26. *SUMMARY OF SOIL AND GENETIC INPUT PARAMETERS
SOIL LOWER UPPER SAT EXTR INIT ROOT BULK pH NO 3 NH4 ORG
DEPTH LIMIT LIMIT SW SW SW DIST DENS C
cm cm3/cm3 cm3/cm3 cm3/cm3 g/cm3 ugN/g ugN/g %
--------------------------------------------------------------------------------
0-5 .170 .299 .388 .129 .299 .35 1.40 7.80 .10 .10 1.20
5-15 .170 .299 .388 .129 .299 .35 1.40 7.80 .10 .10 1.20
15-30 .170 .299 .388 .129 .299 .35 1.40 7.80 .10 .10 1.20
30-45 .243 .367 .382 .124 .367 .20 1.30 7.80 .10 .10 .50
45-60 .238 .360 .375 .122 .360 .17 1.30 7.87 .10 .10 .30
60-90 .241 .362 .377 .121 .362 .13 1.30 7.90 .10 .10 .17
90-120 .250 .372 .387 .122 .372 .10 1.30 7.90 .10 .10 .10
ENVIRONMENTAL AND STRESS FACTORS
------------------------------------ ENVIRONMENT-----------------STRESS----------
|--DEVELOPMENT PHASE--|-TIME-|-------WEATHER--------| |---WATER--| |-NITROGEN-|
DURA TEMP TEMP SOLAR PHOTOP PHOTO GROWTH PHOTO GROWTH
TION MAX MIN RAD [day] SYNTH SYNTH
days ّC ّC MJ/m2 hr
--------------------------------------------------------------------------------
Emergence -Term Spiklt 59 23.31 10.02 15.47 10.24 .000 .006 .271 .473
End Veg-Beg Ear Growth 21 23.58 6.84 15.41 10.78 .000 .000 .000 .302
Begin Ear-End Ear Grwth 13 25.05 8.08 16.41 11.23 .000 .037 .000 .217
End Ear Grth-Beg Grn Fi 14 28.36 13.23 17.40 11.62 .010 .074 .000 .000
Linear Grain Fill Phase 39 32.11 14.68 17.04 12.41 .093 .141 .000 .015

27. *SIMULATED CROP AND SOIL STATUS AT MAIN DEVELOPMENT STAGES
RUN NO. 6 GIZA 164
DATE CROP GROWTH BIOMASS LAI LEAF ET RAIN IRRIG SWATER CROP N STRESS
AGE STAGE kg/ha NUM. mm mm mm mm kg/ha % H 2O N
--------------------------------------------------------------------------------
20 NOV 0 Sowing 0 .00 .0 4 0 70 177 0 .0 .00 .00
20 NOV 0 Start Sim 0 .00 .0 4 0 70 177 0 .0 .00 .00
21 NOV 1 Germinate 0 .00 .0 8 0 70 167 0 .0 .00 .00
30 NOV 10 Emergence 14 .00 2.0 19 0 70 140 0 2.2 .00 .00
28 JAN 69 Term Spklt 2148 2.24 12.0 117 6 225 155 82 3.8 .01 .27
18 FEB 90 End Veg 5488 3.24 15.0 182 11 225 94 132 2.4 .00 .00
2 MAR 103 End Ear Gr 7701 3.06 15.0 226 11 225 50 134 1.7 .06 .00
16 MAR 117 Beg Gr Fil 10037 2.71 15.0 279 13 305 78 133 1.3 .05 .00
25 APR 157 Maturity 12189 .00 15.0 391 17 380 46 142 1.2 .14 .00
25 APR 157 Harvest 12189 .00 15.0 391 17 380 46 142 1.2 .14 .00

28. *MAIN GROWTH AND DEVELOPMENT VARIABLES
@ VARIABLE PREDICTED MEASURED
-------- --------- --------
FLOWERING DATE (dap) 108 106
PHYSIOL. MATURITY (dap) 157 158
GRAIN YIELD (kg/ha;dry) 5064 5063
WT. PER GRAIN (g;dry) . 0364 0.038
GRAIN NUMBER (GRAIN/m 2) 13917 -99
GRAINS/EAR 29.8 -99
MAXIMUM LAI (m2/m2) 3.25 -99
BIOMASS (kg/ha) AT ANTHESIS 7701 -99
BIOMASS N (kg N/ha) AT ANTHESIS 134 -99
BIOMASS (kg/ha) AT HARVEST MAT. 12189 12302
STALK (kg/ha) AT HARVEST MAT. 7125 -99
HARVEST INDEX (kg/kg) . 415 -99
FINAL LEAF NUMBER 15.00 -99
GRAIN N (kg N/ha) 122 -99
BIOMASS N (kg N/ha) 142 -99
STALK N (kg N/ha) 20 -99
SEED N (%) 2.41 -99

29. Comparison of measured and predicted of Wheat grain yield

30. R
2
= 0.901
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
0 100020003000400050006000700080009000
Observed grain yield Simulated grain yield
OBSERVED AND SIMULATED WHEAT GRAIN YIELD

31. DSSAT v3.5
-Models of 16 Crops -
•Cereals
–Corn, Wheat, Rice, Barley, Sorghum, Millet
•Grain Legumes
–Soybean, Peanut, Dry Bean, Chickpea
•Root Crops
–Potato, Cassava
•Other Crops
–Tomato, Sunflower, Sugar Cane, Pasture

32. GIS map showing analysis grain yield simulation of Maize single cross 10
in different location.

33. THE IMPACT OF CLIMATE CHANGE ON
PRODUCTION OF DIFFERERENT CULTIVARS OF
MAIZE (Zea mays L.)
Minia Governorate, Malawi

34. Fertilizer levels, additions date and amounts
Material code (1) = Ammonium nitrate
Method code (2) = Broadcast, incorporateFertilizerDate Depth N
level dd/mm/yy cm Kg/ha
N 1 06/05/1993 1 2 20 285
N 2 06/05/1993 1 2 20 71
30/05/1993 2 71
22/06/1993 2 71
15/07/1993 2 71
30/05/1993 2 103
22/06/1993 2 103
15/07/1993 2 103
06/05/1993 20 286
30/05/1993 2 71
22/06/1993 2 71
15/07/1993 2 71
06/05/1993 20 71
30/05/1993 2 71
22/06/1993 2 71
15/07/1993 2 71
06/05/1993 20 285
30/05/1993 2 103
22/06/1993 2 103
15/07/1993 2 103
06/05/1993 20 71
30/05/1993 2 103
22/06/1993 2 103
15/07/1993 2 103
Material
code
Method
code
N 3 1 2
N 4 1 2
N 5 1 2
N 6 1 2
N 7 1 2
N 8 1 2

35. Treatment
No.
TreatmentTreatment
No.
Treatment
1 V1 N1 9 V2 N1
2 V1 N2 10 V2 N2
3 V1 N3 11 V2 N3
4 V1 N4 12 V2 N4
5 V1 N5 13 V2 N5
6 V1 N6 14 V2 N6
7 V1 N7 15 V2 N7
8 V1 N8 16 V2 N8 Variety V1: SC10 (Single cross 10)
V2: TW310 (Three way cross 310)
Combinationbetweenvarietiesandnitrogenlevels

36. CO2CO2 CO2CO2 CO2CO2
0.03%0.06% 0.03%0.06% 0.03%0.06%
January 11.914.82.85 0.7 0.5 0.66 155 159 1.02
February13.117.94.84 0.5 0.4 0.78 198 199 1.01
March 17.2 21 3.86 0.9 0.7 0.84 259 262 1.01
April 21.526.95.35 0.3 0.2 0.55 318 315 0.99
May 26.332.35.97 0.2 0.4 2.59 341 338 0.99
June 32 35.93.98 0.2 0.5 3.1 350 341 0.97
July 33.837.53.63 0.3 1.2 3.8 346 327 0.94
August 33.735.82.07 0.3 1.9 5 317 302 0.95
September29.233.54.31 0.8 1.2 1.56 275 268 0.97
October 23.226.93.69 0.9 1.1 1.16 222 222 1
November16.221.35.15 0.5 0.5 0.93 175 174 1
December12.716.94.21 0.5 0.9 1.83 151 146 0.97
Month Temperature C0 Precipitation (mm/day ) Solar ( W/M2 )
Ratio Ratio Ratio Temperature , precipitation and solar radiation for the current
(CO2=300ppm ) and the expected change situation(CO 2=600ppm)
by the year 2040.

37. predictedmeasured
1 285 133 162 5 55195495
2 71 49 54 5 39424630
3 213 122 94 10 55255509
4 309 151 142 26 54605407
5 498 154 328 18 55065421
6 285 135 144 10 54935468
7 594 164 385 45 55055426
8 380 157 197 31 54715462
9 285 126 168 5 42323970
10 71 47 54 5 27823001
11 213 113 96 10 42653956
12 309 131 151 32 42153973
13 498 132 340 22 42233998
14 285 122 150 12 42214020
15 594 141 402 53 42233987
16 380 134 209 39 42183951
Final NGrain yieldTreatment
No.
Fert. NPlant NLeached
N Summary of data produced by the program and compared yield for
measured data.
Fert. N = Fertilizer N added (Kg/ha)
Plant N = N taken up by croup (Kg/ha)
Leached N = N leached below 1.8m(Kg/ha)
Final N = Final Nitrate –N in soil (Kg/ha)
Yield =Grainyieldofcrop(Kg/ha)