simulating cropping systems in the guinea savanna zone of northern ghana with dssat-century j. b....

Simulating Cropping Systems in the Guinea Savanna Zone of Northern Ghana

with DSSAT-CENTURY

J. B. Naab1, Jawoo Koo2, J.W. Jones2, and K. J. Boote2,

1Savanna Agricultural Research Institute (SARI)

Tamale, Ghana, 2Univ. of Florida,

Introduction

• To be useful to community decision makers, models must be capable of quantifying crop performance in the communities where they are to be used.

• Necessary to adapt the model to soils, climate and cropping systems of interest and to evaluate predictions from the model relative to local data

Objective

• Present progress in the adaptation of DSSAT-CENTURY to the cropping systems in two locations in Northern Ghana and its ability to simulate growth, yield and soil carbon sequestration.

Peanut experiments in 1997 & 1998

• Cultivars: Chinese (90 d) & F-mix (120 d)• Sowing dates: 3 or 4 sowing dates• Complete growth analyses• Detailed soil water measurements • Used PNUTGRO model to simulate soil water

balance & potential growth

JULIAN DAY

TO

TA

L B

IOM

AS

S,

kg

/ha

a) Chinese, 1998 season

b) F-Mix, 1998 season

0

2000

4000

6000

8000

150 200 250 300 350

D1, DEF (Sim.)

D3, DEF (Sim.)

D1 (Sim.)

D3 (Sim.)

D1 (Obs.)

D3 (Obs.)

0

1000

2000

3000

4000

5000

6000

150 200 250 300 350



J. Naab – Ghana,

Two peanut cult.

Simulated with no disease effect

Simulated with input defoliation and leafspot injury

Crop had no fungicide applied

0

500

1000

1500

2000

2500

3000

3500

4000

150 200 250 300 350

D1, DEF (Sim.)

D3, DEF (Sim.)D1 (Sim.)

D3 (Sim.)D1 (Obs.)

D3 (Obs.)

0

500

1000

1500

2000

2500

3000

3500

150 200 250 300 350

JULIAN DAY

PO

D W

EIG

HT

, k

g/h

a



J. Naab – Ghana,

Two peanut cult.

Simulated with no disease effect

Simulated with input defoliation and leafspot injury

Crop had no fungicide applied

Peanut Experiments:1999-2001

• Simulation analyses suggested yield losses of 50 to 70% from disease effects.

• Leaf spot disease is common on peanut in Ghana, where fungicides are not used.

• Can peanut produce simulated yield levels with fungicide? Can the model predict this?

Materials and methods

• Same cultivars as in 1997 & 1998

• 3 sowing dates

• With (+) and without (-) fungicide applied

• Fungicide: Folicur and Abound

• Detailed growth analysis

• Used CROPGRO-peanut model to simulate growth under disease epidemics

Measurements

• Phenology data (flowering, 1st pod and 1st seed )

• Time-series growth analysis of leaf, stem, pod and seed mass

• Defoliation and disease scores

• Yield and yield components (pod and seed yields, HI, threshing %, 100-seed weight)

150 175 200 225 250 275 3000

2000

4000

6000

8000

10000

150 175 200 225 250 275 3000

2000

4000

6000

8000

10000

Day of year

Chinese

Tot

al d

ry w

eigh

t (k

g ha

-1)

Day of the year

F-mix

Nyankpala: 1999 Fungicide

No Fungicide

175 200 225 250 275 3000

1000

2000

3000

4000

5000

175 200 225 250 275 3000

1000

2000

3000

4000

5000

Day of year

Chinese

Pod

dry

wei

ght

(kg

ha-1

)

Day of the year

F-mix

Nyankpala: 1999 Fungicide

No Fungicide

Maize Rotation Experiments (1996-1998)

• Location: Nyankpala & Wa• 3 cropping systems: continuous maize,

maize-peanut, & peanut-maize• Nitrogen levels: 0, 30, 60, 4 t/ha manure• Yearly experiment files and annual

measurement files setup• Four sequence files for rotating crops

were also setup for maize plots

Yearly maize experiment and measurement files File Field Treatment Fertilizer for Maize GHNY9601.MZX, GHNY9601.MZA A-1 1 None A-2 2 30kg N A-3 3 60kg N GHNY9701.MZX, GHNY9701.MZA A-1 1 None A-2 2 30kg N A-3 3 4ton cow manure GHNY9801.MZX, GHNY9801.MZA A-1 1 None A-2 2 30kg N A-3 3 4ton cow manure

Yield variability in response to N fertilization

MaizeWa, Ghana in 1997-1999

0.0

0.5

1.0

1.5

2.0

0kg N 4ton Manure 30kg N 60kg N

Fertilizer

Obs

. Yie

ld (t

on/h

a)

Yield variability in response to total

cumulative rainfall during the crop season


0.5

1.0

1.5

2.0

300 400 500 600 700 800

Cumulative Rainfall (mm)

Obs

. Yie

ld (t

on/h

a)

0kg N4ton MN30kg N60kg N

Legume yield variability with total cumulative rainfall

LegumeWa, Ghana in 1997-1999

0.0

0.5

1.0

1.5

2.0

400 500 600 700 800

Cumulative Rainfall (mm)

Obs

. Yie

ld (t

on/h

a)

SoybeanPeanut

Relationship between simulated nitrogen

stress factor and rainfall amount


0.0

0.1

0.2

0.3

0.4

200 400 600 800 1000

Total rainfall during growth season (mm)

Sim

. N s

tress

fact

or

Beginning of grain f illingEnd of grain f illingMaturity

Simulated nitrogen leaching as a function of rainfall

MaizeWa, Ghana in 1997-1999Fertilizer: 30kg N

6

8

10

12

400 500 600 700 800

Total rainfall during growth season (mm)

N le

ache

d (k

g[N]

/ha)

Simulation of 2003 On-farm Maize Rotations

• Location: Nakor village, Wa

• Three farmers collaborated

• Four cropping systems studied: continuous -maize + low N (30kg/ha)

-continuous maize + high N (80 kg/ha)

-maize-peanut + 40 kg/ha N

-peanut-maize + 40 kg/ha N to maize

Measurements

• Initial soil carbon content

• Soil texture

• Biomass at final harvest

• Grain yield at final harvest

Calibration

• Changed genetic coefficients of maize based on observed biomass and grain yield.

• Photosynthetic factor for each field set=0.85

• SLNF for each field was set = 1.0

Calibration continues..

• Initial SOM pool fractions calibrated as follows:• (i) On-farm experiments were simulated for 50

years using the reported SOM fractions for Mali cropping system condition (SOM1:SOM2:SOM3 = 0.02:0.41:0.57, Walen et al., 2002);

• (ii)Yearly carbon initially decreased, then stabilized after about 50 years;

• (iii) The SOM pool fractions were then obtained when soil carbon stabilized (SOM1:SOM2:SOM3 = 0.01:0.14:0.85).

Simulated and observed maize biomass in

Nakor village, Wa, Ghana

MaizeOn-farm experimentsNakor village, Ghana

3

4

5

6

20 30 40 50 60 70 80 90

kg[N fertilizer]/ha

ton[

biom

ass]

/ha

SimulatedObserved

Correlation between simulated maize biomass and top 20cm soil carbon content

in three farmers' field

Carbon vs. Biomass

3

4

5

6

7

0.3 0.4 0.5 0.6 0.7

% Carbon in top 20cm soil

biom

ass

(ton/

ha)

WounbunoDramaniBoakye

30 kg N

80 kg N 40 kg N

30 kg N

80 kg N

40 kg N

30 kg N

80 kg N40 kg N

Total carbon sequestration in farmers fields

Total Carbon Sequestration12 plots (1800 m2) in Nakor, Wa, Ghana

5.6

5.8

6.0

2003 2008 2013 2018 2023

ton[

C]/re

gion

Conclusions

• Model able to predict peanut growth and yield under varying sowing dates, varieties, and leafspot disease epidermics after calibration

• It was reasonably accurate in simulating maize yield variability under different nitrogen regimes

• Simulated yield highly correlated with soil C; fertilizer use efficiency was lower for low soil C situations

• Simulation, after calibration, suggest that there is potential for soil C sequestration in maize cropping systems with fertilizer and manure.

Simulated maize biomass in Boakye's farm

BiomassBoakye's farm

0

2

4

6

8

0 20 40 60 80 100 120

DAP

biom

ass

(ton/

ha)

30 kg N40 kg N80 kg N

Simulated maize biomass in Dramani's farm

BiomassDramani's farm

0

2

4

6

8

0 20 40 60 80 100 120

DAP

bioma

ss (t

on/ha

)


Simulated maize biomass in Wounbuno's

farm

BiomassWounbuno's farm

0

2

4

6

8

0 20 40 60 80 100 120

DAP

bioma

ss (t

on/ha

)


simulating cropping systems in the guinea savanna zone of northern ghana with dssat-century j. b....

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