Prediction of corn yield potential using the Hybrid-Maize model
Patricio Grassini
Department of Agronomy and
Horticulture
University of Nebraska-Lincoln
Yie
ldGap 1
Gap 2
Yield potential Water-limitedyield potential
Actual yield
Other limiting factors:
NutrientsWeedsPestsOthers
CO2
Solar radiationTemperature
Growth periodPlant density
Attainable yieldwith availablewater supply:
SoilRainfall
Irrigation
Daily intercepted solar radiation
f(x)= solar radiation, LAI
Length crop cycle
Cumulative intercepted
solar radiation
Gross assimilation
Dry matter
production Maintenance
Respiration
Growth
respiration
YIELD
POTENTIAL
Kernel #
Kernel
growth rate
Grain-filling
duration
[around silking]
Kernel weight
[grain-filling]
Temperature
Crop models: tools to predict yield potential
Water
supply
Mission impossible: to have a perfect model Desired attribute Explanation
Daily step simulation Simulation of daily crop growth and development
based on weather, soil, and crop physiological
attributes
Flexibility to simulate management practices Key management practices include: sowing date,
plant density, cultivar maturity, and irrigation
Simulation of fundamental physiological processes Simulation of key physiological processes such as
crop development, net carbon assimilation, biomass
partitioning, crop water relations, and grain growth
Crop specificity Should reflect crop-specific physiological attributes
for respiration and photosynthesis, critical stages
and growth periods that define vegetative and grain
filling periods, and canopy architecture
Minimum requirement of crop ‘genetic’ coefficients Minimum requirement of crop-site ‘genetic’
coefficients, such as maximum leaf area index, date
of flowering, etc.
Validation against data from field crops that
approach YP and YW
Comparison of model outcomes (grain yield,
aboveground dry matter, crop evapotranspiration)
against actual measured data from field crops that
received management practices conducive to
achieve YP (irrigated) or YW (rainfed crops)
User friendly Models embedded in user-friendly interfaces, where
required data inputs and outputs can be easily
visualized, and flexibility to modify default values for
internal parameters
Hybrid-Maize model
Simulates growth and development of maize for yield
potential and water-limited situations.
T-driven growth and development functions from CERES-Maize
Mechanistic descriptions of light interception, photosynthesis and organ-specific respiration from generic models (SUCROS/INTERCOM/WOFOST)
A linear relationship between growing degree-days (GDD) from emergence to silking and GDD from emergence to physiological maturity is used for prediction of day of silking
Yang, H.S., A. Dobermann, J.L. Lindquist, D.T. Walters, T.J. Arkebauer, and K.G. Cassman. 2004. Hybrid-Maize - a maize simulation model that combines two crop modeling approaches. Field Crops Res. 87:131-154.
Champaign, IL
Manchester, IA
North Platte, NE
Clay Center, NE
Mead, NE
Fully-irrigated crops ( )
Fully-irrigated crops
n = 30, RMSE = 1.0 Mg ha-1
Rainfed crops:
+15%
-15%
1:1
Rainfed crops
n = 13, RMSE = 1.2 Mg ha-1
0
2
4
6
8
10
12
14
16
18
20
0 2 4 6 8 10 12 14 16 18 20
Simulated grain yield (Mg ha-1)
Ob
serv
ed
gra
in y
ield
(M
g h
a-1
)
Champaign, IL
Manchester, IA
North Platte, NE
Clay Center, NE
Mead, NE
Fully-irrigated crops ( )
Fully-irrigated crops
n = 30, RMSE = 1.0 Mg ha-1
Rainfed crops:
+15%
-15%
1:1
Rainfed crops
n = 13, RMSE = 1.2 Mg ha-1
0
2
4
6
8
10
12
14
16
18
20
0 2 4 6 8 10 12 14 16 18 20
Simulated grain yield (Mg ha-1)
Ob
serv
ed
gra
in y
ield
(M
g h
a-1
)
Hybrid-Maize description and validation
Validation of the Hybrid-Maize model for
irrigated and rainfed crops:
Grassini et al. (2009): Agric Forest Meteorology
http://www.hybridmaize.unl.edu/
Hybrid-Maize does not account
for nutrient deficiencies, insect
pests, diseases or weeds
Yang et al., 2004
Uses of Hybrid-Maize model
• Quantify site-specific yield potential and its variability
• Diagnosis of actual yields by comparison against yield potential
• Estimate yield goals for fertilizer recommendations
• Evaluate changes in yield potential using different choices of planting date, hybrid maturity, and plant density
• Analyze corn growth in specific years
• Diagnose and explore options for irrigation water management
• Conduct in-season simulations to evaluate actual growth and forecast final grain yield
Input data
Daily weather (solar radiation, max. and min. T,
rainfall)
Crop management (date of planting, GDD for hybrid,
plant density, sowing depth)
For simulating water-limited yield: max. rooting depth,
texture class and bulk density in topsoil and subsoil),
and soil water content at planting date
Optional: change model parameters
Hybrid-specific crop coefficients
General model coefficients describing crop growth
and development
Soil physical properties for different soil texture
classes
Hybrid-Maize model
Hands-on session on Hybrid Maize
Irrigated maize in central USA
• Central US Great Plains includes
one of the largest irrigated areas
cultivated with maize in the world
(3.2 million ha)
• Irrigated maize accounts for 60%
of total annual maize production
in the region (~60 million Mg)
• High and stable irrigated maize
production supports economic
viability of associated industries
such as cattle feeding operations
and ethanol plants
Distribution of US irrigated maize cropland:
Low : 0
High : 4456
Data mapped by P. Grassini
based on Portmann et al. (2010):
Global Biogeochemical Cycles
20-d
to
tal ra
infa
ll o
r c
rop
ET
(m
m)
0
50
100
150
200
0 20 40 60 80 100 120 140 Days after sowing
0
50
100
150
200
ETC
Rainfall
ETC
Rainfall
maturity
Silking maturity
Akron (WEST)
Mead (EAST)
Silking
Water availability central US Great Plains
0
200
400
600
800
1000
1200
-104 -102 -100 -98 -96 -94 -92 Longitude (º)
Maize water
demand (mm)
Total sowing-to-maturity
rainfall (mm)
County-average yields in Nebraska
NASS-USDA (2004-2008)Data compiled and mapped
by Patricio Grassini
0 70 140 21035 Kilometers
Maize production < 1500
ha in white counties
N Irrigated maize Rainfed maize
3.7 – 5.6
9.4 – 11.3
7.5 – 9.4
5.6 – 7.5
1.8 – 3.7
Rainfed yield (Mg/ha)
9.4 – 10.4
12.4- 13.4
11.4 – 12.4
10.4 – 11.4
8.4 – 9.4
Irrigated yield (Mg/ha)
#1. Perform separate single-year simulations for
irrigated and rainfed maize in 2004 at Mead, NE based
on the following inputs (and fill out requested data)
Inputs Irrigated Yp Rainfed Yw
Location (choose weather file) Mead, NE Mead, NE
Year 2004 (single year) 2004 (single year)
Start from: planting planting
Planting date April 30 April 30
Seed depth (cm) 4 4
Seed brand Pioneer Pioneer
Maturity (leave other options
unchecked)
GDD 1510 GDD 1510
Plant population (x1000/ha) 80 64
Water Optimal Rainfed
Maximum rooting depth (cm) - 150
Texture - Silty clay loam [top- and sub-soil]
Initial moisture status - Wet (100% FC) [top- and sub-soil]
Bulk density (g/cm3) - 1.3
Output for irrigated maize in Mead, NE in 2004: Results Tab
#1. Perform separate single-year simulations for
irrigated and rainfed maize in 2004 at Mead, NE based
on the following inputs (and fill out requested data):
Inputs Irrigated Yp Rainfed Yw
Location (choose weather file) Mead, NE Mead, NE
Year 2004 (single year) 2004 (single year)
Start from: planting planting
Planting date April 30 April 30
Seed depth (cm) 4 4
Seed brand Pioneer Pioneer
Maturity (leave other options
unchecked)
GDD 1510 GDD 1510
Plant population (x1000/ha) 80 64
Water Optimal Rainfed
Maximum rooting depth (cm) - 150
Texture - Silty clay loam [top- and sub-soil]
Initial moisture status Wet (100% FC) [top- and sub-soil]
Bulk density (g/cm3) 1.3
2005
2006
2007
Challenges to simulate Yw:
I. Spatial variability in
rainfall
Cumulative growing-season
rainfall (mm):
Example: spatial
variation in rainfall
across central Nebraska
Rain gauges
120 km
Rain gauge
A
Rain gauge
B
Rain gauge
C
Example: We have a field surrounded
by three rain gauges (A, B, C). The
distance from the field to the rain gauge
is 5, 9, and 13 miles, respectively
The relative contribution (‘weight’) of
each gauge to the rain in the field #55 is
inversely related to its distance:
(Rain gauge X – field)-2 /
[(A-field)-2 + (B-field)-2 + (C-field)-2]
e.g.
gauge A – field = 0.040 / 0.058 = 0.69
gauge B – field = 0.012 / 0.058 = 0.21
gauge C – field = 0.006 / 0.058 = 0.10
Then, for a given rainy day, given rain A=10 mm; rain B=50 mm, and rain C=20 mm;
the interpolated rain in field #55 can calculated as:
10 mm * 0.69 + 50 mm * 0.21 + 20 mm * 0.10 = 19.4 mm
Inverse distance weighting: interpolation of daily rainfall
Challenges to simulate Yw: II. Soil water at planting
Plant available soil water, expressed as % of maximum available water,
in Nebraska around maize planting date (first week of May) in 2012
Source: High Plains Climate Center, http://www.hprcc.unl.edu/awdn/soilm/
0
0.25
0.5
0.75
1
2 6 10 14
Maize grain yield (Mg/ha)
Cu
mu
lati
ve
fre
qu
en
cy
Low soil water
High soil water LOW
WATER
HIGH WATER
Yield (Mg/ha)
7.8 8.9
CV (%) 30 15
Influence of initial soil water content on Yw
Simulated maize grain yields in North Platte, NE based on 20-y of weather data and actual
management and soil properties, for two scenarios of soil water content by sowing date: ‘low’
and ‘high’ water (33% and 100% of total plant available water)
Grassini et al. (2009): Agric Forest Meteorology
Output for rainfed maize in Mead, NE in 2004: Results tab
Stress index: 1 – (Actual
transpiration-to-potential
transpiration)
[more severe water stress
with increasing index)
#2. Perform separate long-term simulations for irrigated and
rainfed maize at Mead, NE based on the following inputs:
Inputs Irrigated Yp Rainfed Yw
Location (choose weather
file)
Mead, NE Mead, NE
Year Long-term runs (1982-2011) Long-term runs (1982-2011)
Start from: planting planting
Planting date April 30 April 30
Seed depth (cm) 4 4
Seed brand Pioneer Pioneer
Maturity (leave other options
unchecked)
GDD 1510 GDD 1510
Plant population (x1000/ha) 80 64
Water Optimal (check “estimate water
requirement” option)
Rainfed
Maximum rooting depth (cm) 150 150
Texture Silty clay loam [top- and sub-soil] Silty clay loam [top- and sub-soil]
Initial moisture status Wet (100% FC) [top- and sub-soil] Wet (100% FC) [top- and sub-soil]
Bulk density (g/cm3) 1.3 1.3
Long-term simulation of irrigated maize Yp in Mead, NE
#2. Perform separate long-term simulations for irrigated and
rainfed maize at Mead, NE based on the following inputs:
Inputs Irrigated Yp Rainfed Yw
Location (choose weather file) Mead, NE Mead, NE
Year Long-term runs (1982-2012) Long-term runs (1982-2012)
Start from: planting planting
Planting date April 30 April 30
Seed depth (cm) 4 4
Seed brand Pioneer Pioneer
Maturity (leave other options
unchecked)
GDD 1510 GDD 1510
Plant population (x1000/ha) 80 64
Water Optimal Rainfed
Maximum rooting depth (cm) 150 150
Texture Silty clay loam [top- and sub-soil] Silty clay loam [top- and sub-soil]
Initial moisture status Wet (100% FC) [top- and sub-soil] Wet (100% FC) [top- and sub-soil]
Bulk density (g/cm3) 1.3 1.3
Long-term simulation of rainfed maize Yw in Mead, NE
1989
2007
2007
1989
25%-percentile year: 2007
Total rain: 403 mm
Yield: 10.6 Mg/ha
Median year: 1989
Total rain: 308 mm
Yield: 12.4 Mg/ha
Rainfall patterns
Simulation 1: Rainfed yield
Simulation 2: Analysis of farmer irrigation
Simulation 3: Addition of early season irrigation
on June 22, 2002
Simulation 4: Addition of late irrigation on
August 15, 2002
Simulation 5: Eliminate June 22 irrigation but keep
August 15 irrigation
#3. Post-season analysis of irrigation management
and water-use efficiency in 2002 at O’Neill, NE
Data inputs
Inputs Rainfed/Irrigated Yw
Location (choose weather file) Mead, NE
Year Long-term runs (1982-2012)
Start from: planting
Planting date April 30
Seed depth (cm) 4
Seed brand Generic
Maturity (leave other options unchecked) GDD 1400
Plant population (x1000/ha) 74
Water Rainfed/Irrigated
Maximum rooting depth (cm) 100
Texture Sandy loam [top- and sub-soil]
Initial moisture status Wet (100% FC) [top- and sub-soil]
Bulk density (g/cm3) 1.3
RAINFED SIMULATION
Simulation 1:
Rainfed
Simulation 1:
Rainfed
Simulation 1:
Rainfed
Farmers’ irrigation: irrigation starts on June 30 and is irrigated weekly @ 30mm / irrigation ending in late July because of significant rainfall in August
Month Day Inches
7 1 30
7 6 30
7 11 30
7 17 30
7 22 30
7 28 30
SIMULATION OF FARMER’ MANAGEMENT
Simulation 2:
Farmer irrigation
Simulation 2:
Farmer irrigation
Simulation 2:
Farmer irrigation
To test the importance of early stress, we will add an additional 30 mm early irrigation on 6/22 to mitigate the early season stress
Month Day Applied irrigation (mm)
6 22 30
6 30 30
7 6 30
7 11 30
7 17 30
7 22 30
7 28 30
SIMULATION OF FARMER’ MANAGEMENT PLUS EARLY IRRIGATION
Simulation 3:
Farmer irrigation
Plus early 6/22
irrigation
Simulation 3:
Farmer irrigation
Plus early 6/22
irrigation
Farmer Irrigation
11.2 Mg/ha
Farmer Irrigation
plus early irrigation
11.2 Mg/ha
Rainfed
7.4 Mg/ha
Simulation 3:
Farmer irrigation
Plus early 6/22
irrigation
In addition to the early 6/22 irrigation we add as additional 30 mm on August 15 to avoid late season stress
Month Day Applied irrigation (mm)
6 22 30
6 30 30
7 6 30
7 11 30
7 17 30
7 22 30
7 28 30
8 15 30
Simulation 4:
Farmer irrigation
plus early 6/22
and late 8/15
irrigation
Simulation 4:
Farmer irrigation
plus early 6/22
and late 8/15
irrigation
Simulation 4:
Farmer irrigation
plus early 6/22
and late 8/15
irrigation
Since early (6/22) irrigation had no impact on yield we’ll look at the effect of adding only the late season (8/15) irrigation
Month Day Applied irrigation water (mm)
6 30 30
7 6 30
7 11 30
7 17 30
7 22 30
7 28 30
8 15 30
Simulation 5:
Farmer
irrigation
plus late 8/15
irrigation
Simulation 5:
Farmer
irrigation
plus late 8/15
irrigation
Simulation 5:
Farmer
irrigation
plus late 8/15
irrigation
Farmer
Irrigation
11.2 Mg/ha
Farmer
Irrigation
plus early
irrigation
11.2 Mg/ha
Rainfed
7.4 Mg/ha
Farmer
Irrigation
plus early
and late
irrigations
12.6 Mg/ha
Farmer
Irrigation
plus early
and late
irrigations
12.6 Mg/ha
Summary of 2002 irrigation analysis
Simulation
Water input (mm) Grain yield
(Mg/ha)
IWUE
Rainfall Irrigation Total
#1. Dryland 185 0 185 7.4 -
#2. Farmer’s management 185 180 365 11.2 21
#3. Farmer’s management +
early irrigation
185 210 395 11.2 18
#4. Farmer’s management +
early & late irrigation
185 240 425 12.6 22
#5. Farmer’s management +
late irrigation
185 210 395 12.6 25
IWUE = irrigation water use efficiency
(yield irrigated – yield rainfed) / applied irrigation