The Decision Support System for Agrotechnology Transfer (DSSAT) is a suite of crop simulation models and associated tools for simulating growth, development, and yield of 25 crops. The maize simulation model in DSSAT is CSM-CERES, the modular version of CERES-Maize, which was first published in 1986. The newest release of DSSAT, version 4.5, provides users with the opportunity to run an alternative maize simulation model. IXIM (eeh-sheem), the Mayan language for maize, is a new, more mechanistic, maize simulation model fully compatible with DSSAT. The purpose of this work is to compare seasonal simulations of maize growth and N uptake using CSM-CERES and IXIM

Boote, Kenneth J.

Jones, J.W.

Lizaso Oñate, Jon Iñaqui

Porter, C.H.

English

Servicio de Coordinación de Bibliotecas de la Universidad Politécnica de Madrid

IXIM: A New Maize Simulation Model For DSSAT v4.5 
 
 
J.I. Lizaso1, K.J. Boote2, J.W. Jones3, C.H. Porter3
 
1 Dep. Producción Vegetal: Fitotecnia, Univ. Politécnica of Madrid, Spain, jon.lizaso@upm.es
2 Dep. of Agronomy, Univ. of Florida, USA, kjboote@ufl.edu  
3 Dep. of Agricultural and Biological Eng., Univ. of Florida, USA, jimj@ufl.edu, cporter@ufl.edu
 
 
 
 
The Decision Support System for Agrotechnology Transfer (DSSAT) is a suite of crop simulation models 
and associated tools for simulating growth, development, and yield of 25 crops. The maize simulation 
model in DSSAT is CSM-CERES, the modular version of CERES-Maize, which was first published in 
1986. The newest release of DSSAT, version 4.5, provides users with the opportunity to run an alternative 
maize simulation model. IXIM (eeh-sheem), the Mayan language for maize, is a new, more mechanistic, 
maize simulation model fully compatible with DSSAT. The purpose of this work is to compare seasonal 
simulations of maize growth and N uptake using CSM-CERES and IXIM.  
 
Methodology 
IXIM was modified from CSM-CERES and includes a number of improvements and new modules. Leaf 
area expansion and senescence are simulated using sigmoidal functions to describe expansion, longevity, 
and senescence of individual leaves (Lizaso et al., 2003). Leaf rolling per-leaf is calculated as a function of 
time of the day, atmospheric transmission of radiation, and water stress intensity. Instantaneous 
assimilation of each green leaf is calculated as a function of hourly-absorbed photosynthetic photon flux 
density, leaf age, and air temperature (Lizaso et al., 2005). Canopy gross assimilation is calculated by 
integrating the contributions of successive vertical leaf classes. Canopy respiration accounts for 
maintenance respiration and growth respiration for tissue synthesis (Lizaso et al., 2005). Specific leaf area 
determines potential allocation of biomass to individual leaves. Specific leaf area of each leaf is a function 
of light intensity, temperature, and leaf position within the canopy. Partitioning of assimilates among 
organs was completely modified. Ear growth occurs within a thermal time window of 250 degree-days 
before silking, until 100 degree-days after silking. Kernel number per plant is calculated as a curvilinear 
function of the daily shoot growth rate averaged over the same thermal time window around flowering used 
for ear growth. Maximum daily nitrogen uptake is limited by a curvilinear function of daily growth rate. 
This constraint recognizes the energy cost for N uptake, reduction, and assimilation. IXIM requires two 
additional genetic inputs relative to CSM-CERES: 1) Surface area of the largest leaf (cm2), and 2) 
Longevity of the most long-lived leaf (degree-day). Model parameters are included in a new maize species 
file and are accessible to the user. Data distributed with DSSAT (UFGA8201, Irrigated and non-irrigated 
during the vegetative phase treatments) were simulated and compared. Willmott’s d index (Willmott, 1982) 
was used to evaluate model accuracy. Index d has values within the range 0-1 with higher values indicating 
more accurate simulations. 
 
Results 
Both models produced better results when simulating non-stress conditions as compared to the water stress 
treatment (Figure 1). CSM-CERES consistently overestimated leaf area in the irrigated treatment. 
However, it was able to accurately simulate biomass accumulation and grain yield (d values of 0.991 and 
Figure 1: Leaf area index, biomass accumulation, grain yield, and shoot N uptake in maize irrigated 
and water stressed during the vegetative phase (Rainfed), simulated with CSM-CERES (dashed 
lines) and with IXIM (continuous lines) compared to observed (symbols). Index of agreement 
(Willmott, 1982) calculated with CERES simulations (dc) and with IXIM simulations (di). 
Days after sowing
0 20 40 60 80 100120140
0
5000
10000
15000
20000
25000
B
io
m
as
s,
 Y
ie
ld
 (k
g 
ha
-1
)
0
5000
10000
15000
20000
25000
30000
Biomass
Yield
Days after sowing
0 20 40 60 80 100120140
0
50
100
150
200
250
Days after sowing
0 20 40 60 80 100120140
0
1
2
3
4
5
Sh
oo
t N
 (k
g 
ha
-1
)
0
50
100
150
200
250
300
CERES
IXIM
Irrigated
LA
I (
m
2  m
-2
)
0
1
2
3
4
5
6
Rainfed
dc=0.949 
di=0.996 
dc=0.818 
di=0.902 
dc=0.991 
di=0.997 
dc=0.974 
di=0.987 
dc=0.948 
di=0.966 
dc=0.536 
di=0.713 
0.973). It also calculated faster than observed shoot N uptake especially immediately after applying 
fertilizer. 
 
CSM-CERES overestimated leaf senescence in response to soil water shortages during the vegetative 
phase. However, simulations of biomass and grain yield were adequate with d values of 0.974 and 0.977 
respectively. The model simulated, at flowering, more than two-fold greater than measured N uptake. 
 
On the other hand, IXIM improved consistently the estimations of growth and N uptake. Willmott’s d index 
(Willmott, 1982) improved 5 and 10% when simulating leaf area of irrigated and vegetative water stress 
treatments. Simulations of biomass and yield showed minor differences between models, but N uptake 
simulations improved 2 and 33% for irrigated and rainfed treatments. Partition of dry mass between leaves 
and stems was also simulated closer to measured by IXIM as compared to CSM-CERES (not shown). 
 
In summary, IXIM outperformed CSM-CERES when simulating growth and N uptake of non-stressed and 
water stress treatments. Values of d index fluctuated between 0.966 and 0.997 under irrigation, and 
between 0.713 and 0.987 for water stress conditions. Corresponding ranges for CSM-CERES were 0.948 
and 0.991for irrigated and 0.536 and 0.977 for rainfed conditions. Simulation of N uptake, especially under 
stress conditions needs further attention.  
 
References 
Lizaso, J.I et al. 2003. A leaf area model to simulate cultivar-specific expansion and senescence of maize leaves. Field Crops 
Res, 80:1-17. 
Lizaso, J.I. et al. 2005. Development of a leaf-level canopy assimilation model for CERES-Maize. Agron. J, 97:722-733. 
Willmott, C.J. 1982. Some comments on the evaluation of model performance. Bul. Amer. Meteorol. Soc, 63:1309-1313. 
 


IXIM: A new maize simulation model for DSSAT v4.5.

Archivo Digital UPM

A leaf area model to simulate cultivar-specific expansion and senescence of maize leaves. Field Crops Res,

Development of a leaf-level canopy assimilation model for CERES-Maize.

Some comments on the evaluation of model performance.

http://oa.upm.es/3489/1/INVE_MEM_2008_55083.pdf

IXIM: A new maize simulation model for DSSAT v4.5.

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