transforming maize-legume value chains · systems •based on tillage ... manual sustainable...
TRANSCRIPT
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Transforming Maize-legume Value Chains –
A Business Case for Climate-Smart Agriculture in Southern Africa
By Christian Thierfelder, Geofrey Siulemba, Moses Mwale and colleagues from Malawi and Zimbabwe
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Projected change in Agriculture Productivity, 2080
Source: Hugo Ahlenius, UNEP/GRID-Arendal.
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Traditional African smallholder farming systems
• Based on tillage(manual/animal traction)
• Residue removal
• Monocropping of maize
• Limited fertilizer use
• Based on traditionalvarieties
• Affected by variable climate
• Inherently poor soil fertility
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The Challenges
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Agroforestry
Nutrition security
Poverty alleviation
Natural resource management
Improved cook-
stove
Conservation
agriculture
Increased yields
Soil quality & carbon
Reduced
degradation &
erosion
Dietary diversity
Intercropping
Market access
Increase income
Participatory approach
Landscapes with multiple CSA options
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Out scaling climate-smart technologies to smallholder farmers in Malawi, Zambia & Zimbabwe
• Undertake a climate change Vulnerability Assessment
• Piloting CSA technologies on-farm
• Prioritization of CSA technologies
• Feasibility study
• Development of out-scaling Proposals for CSA scaling
Adaptation to Climate Change for Smallholder Rural Areas (ACCRA) Project funded by GIZ/CCARDESA
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Vulnerability assessment - process
Vulnerability status of communities
Rural assessment
Definition of adaptation practices (Proactive/ Reactive) to impacts
Assessment of risks/impacts of climate hazards
Identification of climate hazards
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Piloting in CSA in on-farm communities of Southern Africa
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Village of 100-200 households
Good extension officer
Vibrant and interested farmers
Accessible site
Distance 2-3 km
Cluster villages and“Mother and Baby” trials
Mother trials
Baby trials
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Maize-legume rotation under CA with Pigeonpea Alley Cropping
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Prioritization of CSA technologiesProcess:
• Local meetings with key stakeholder in target communities
• Regional meeting in Lusaka using the GIZ tool
• Ranking based on a ranking matrix
Southern MAL
Adaptation option
Effective
nessCost
Feasibility
for Farmers
Political/
social
acceptance
Relative
speed to
benefit
No regret
potential
Alignement
to donor
support
Alignement
with Policy
Sum of
scoreRank
weighted
rank
Mitigation
co-benefit
Gender
Sensitivity
InterCropping 5 3 5 5 4 4 5 5 36 4.50 4.35 + +
Crop Diversification 5 3 4 5 4 5 5 5 36 4.50 4.25 0 +
DT Vars 5 2 3 4 5 4 5 5 33 4.13 3.85 0 0
CA 4 3 4 4 2 4 5 5 31 3.88 3.6 0 +
Organic Manure 4 3 3 4 4 4 2 5 29 3.63 3.55 - 0
Supplementary Irrigation 5 1 2 4 5 5 5 5 32 4.00 3.55 0 0
Cap Building 4 1 5 4 1 3 5 5 28 3.50 3.15 0 +
IPM 3 1 2 3 4 4 3 4 24 3.00 2.7 0 0
Agro Met Info Sharing 2 1 4 4 2 2 4 5 24 3.00 2.55 0 0
Small livestock production 4 1 1 4 3 2 4 4 23 2.88 2.45 - +
Rainwater Harvest 4 1 2 2 3 3 1 3 19 2.38 2.45 0 -
Policy Implement 2 1 2 3 1 2 5 5 21 2.63 2 0 0
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➢Agronomic performance
➢Economic viability
➢Environmental impact
➢Social impact (gender)
A Feasibility Study on Climate-Smart Agriculture Systems
For an investment proposal we needed data on:
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Conservation agriculture: A climate-smart agriculture system:
• Minimal soil movement
• Surface crop residue retention
• Diversification through crop rotations, intercropping and green manures
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Maize-soybean rotation
Groundnuts under CA
Maize-Gliricidia intercropping
Cowpeas under CA
Maize under CA
Maize-groundnut rotation
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Why focus on Conservation Agriculture?
➢ Combines all positive technologies
prioritized above
➢ CA can help to adapt production to climate variability
and change ….!
➢ CA is more water-, nutrient-, and energy-use-efficient
➢ CA improves the productivity of
current farming systems
➢ Availability of long-term data to
do the study
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Maiz
e G
rain
yie
ld (
kg
ha
-1)
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
a
Chibgukuwe Chipeni Mwansambo Zidyana Herbert Lemu
Central Malawi Southern Malawi
ab
bb a
a
a
a
a
a
a
b
b
b
b ab
ab
Malula Matandika Songani
a
a a aa
a
ab
a a
Conventional ridge tillage Mz-leg rotation
CA-Direct seeding Mz-leg rotation
CA Direct seeding Mz/int-leg rotation
Productivity benefits – On-farm pilots in Malawi, 2019
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Climate-smart agriculture in action!
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Women empowerment!
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Ma
ize
gra
in y
ield
(kg h
a-1
)
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
11000
12000
b
aa
b
aa a
b
a a
b
a
a
b
a ab
CRT, m
aize
-rot
DiS
, maize
/legu
me-
rot
DiS
, maize
-rot
CRT, m
aize
-rot
DiS
, maize
/legu
me-
rot
DiS
, maize
-rot
CP, m
aize
DiS
, maize
/legu
me
inte
rcro
p
DiS
, maize
DiS
, maize
-rot
CP, m
aize
RI, m
aize
-rot
RI, m
aize
CP, m
aize
-rot
DS, m
aize
-rot
RI, m
aize
-rot
Central Malawi(manual)
South Malawi(manual)
Eastern Zambia(manual)
Eastern Zambia(animal traction)
Southern Zimbabwe(animal traction)
Southern Zambia(animal traction)
b
a
c
DS, m
aize
-rot
CP, m
aize
-rot
DS, m
aize
-rot
Productivity benefits – long-term
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Conventional tillage yield (kg ha-1
)
0 2000 4000 6000 8000 10000
Co
nse
rvati
on
ag
ricu
ltu
re t
rea
tmen
t yie
ld (
kg
ha
-1)
0
2000
4000
6000
8000
10000
1 :2
line
1:1
line
Planting basins, Mozambique
Ripline seeding, Zambia
Manual direct seeding, Mozambique
Direct seeding, Zambia
Manual direct seeding, Malawi
Manual direct seeding, intercrop., Malawi
Ripline seeding, Zimbabwe
Direct seeding Zimbabwe
Thierfelder et al. 2015a
Regional yield response to CA in southern Africa from 2005-2016
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0 500 1000 1500 2000 2500 3000
Ridge & furrowMaize continuous
Dibble stick Maizecontinuous
Dibble stick-Maize/Cowpea intercrop
Dibble stick-Maize -Cowpea rot
low
rai
nfa
ll &
med
ium
ele
vati
on
2012/2013 2013/2014 2014/2015 2015/2016
Net benefits (in USD)
Manual Sustainable Intensification Practices -Net Benefits (2012-2016), Eastern Zambia
Mutenje et al. 2016
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CP-maize CA-maize CA-maize/legume
Lab
ou
r d
ays
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
2nd Weeding
Land clearing
Ridging
Sowing
Mulch appl.
Basal fertilizer appl.
Herbicide appl.
1st Weeding
3rd Weeding
Top dressing
Harvesting
Thierfelder et al. 2015b
Labour reduction – a key benefit!
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Time (min)
0 5 10 15 20 25 30 35 40 45 50 55 60 65
Infi
ltra
tio
n (
mm
h-1
)
0
10
20
30
40
50
60
70
80
90
100
110
120
130
Conventional ploughing (CP)
Rip-line seeded (RI)
Direct seeding (DS)
Rip-line seeded + leg intercrop (RI+ leg)
Basin planting (BA)
a)
Time (min)
0 5 10 15 20 25 30 35 40 45 50 55 60 65
Infi
ltra
tio
n (
mm
h-1
)
0
10
20
30
40
50
60
70
80
90
100
110
120
130
Direct seeding, maize-cotton
Conventional ploughing, maize
Direct seeding, maize-cotton-sunnhemp
Direct seeding, maize
b)
Environmental benefits – improved Water Infiltration
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Conventional ploughing, maize (CP-M)
CA-Direct seeding, maize (DS-M)
CA-Basin planting, maize (BA-M)
Rainfall
FC
50% avail. moist.
PWP
Date
10/1
1/14
15/1
2/14
19/0
1/15
23/0
2/15
30/0
3/15
04/0
5/15
08/0
6/15
13/0
7/15
17/0
8/15
21/0
9/15
26/1
0/15
30/1
1/15
04/0
1/16
08/0
2/16
14/0
3/16
18/0
4/16
23/0
5/16
27/0
6/16
01/0
8/16
05/0
9/16
10/1
0/16
14/1
1/16
19/1
2/16
23/0
1/17
27/0
2/17
03/0
4/17
08/0
5/17
Rain
fall
(mm
d-1
)
0
10
20
30
40
50
60
70
80
90
100
Availab
le s
oil m
ois
ture
(in
mm
)
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
170
180
190
200
210
220
Environmental benefits – increased Soil Moisture
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Year
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Ra
infa
ll (
mm
a-1
)
0
300
600
900
1200
1500
1800
So
il e
ros
ion
(in
t h
a -1
)
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
Rainfall
Conventional ploughing (CP)
Direct seeding (DS)
Ripline seeding + legume intercrop (RSL)
Environmental benefit – reduced Soil Erosion
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Year
2004 2005 2006 2007 2008 2009 2010 2011
Tota
l carb
on (
Mg h
a-1
)
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70Conventional ploughing, maize
CA- direct seeding, maize
CA- direct seeding, cotton-maize
a
aa
b
aab
b
aa
b)
Environmental benefit – gradual increase in soil carbon
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Conventional tillage
CA
CA+legume
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Planted same day, same fertilizer level, same variety –but different cropping system
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Farmers practicing CA with TLC in Malawi – initiated with CIMMYT in 2005 but
supported by many funders!
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
0
20000
40000
60000
80000
100000
120000
140000
160000
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
# o
f h
ect
are
s
# o
f fa
rne
rs
# Farmers # ha
Source: Bunderson TLC, 2016
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Country Area under CA (ha) Area under CA (ha)
2013 2018
Malawi 65,000 210,000
Zambia 200,000 316,000
Source: Kassam et al. 2015; 2018
CA Adoption in Zambia and Malawi-with an increasing trend….!
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Some pertinent challenges ...
➢Residues: How can we feed both livestock and crops?
➢Weeds and their control – a major challenge if no herbicides are used
➢ Lack of fertilizer use – what are the alternatives?
➢ Limited crop diversification – too much focus on maize
➢ Lack of evidence and data taking – believe in myths
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➢Targeting the wrong systems to the wrong farmers
➢ Donor driven adoption - one-size fits-all approaches
➢ Low adoption – lack of understanding of underlying issues
➢ Ignoring farmers rationale and decision making
➢ The need for new knowledge and co-developmentof technologies
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Scaling is more than the technology
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Project results have been summarized in 4 project reports in contemporary design –
This is our Business Case!
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Several regional and country proposals have been developed for southern Africa
• Work package 1: Scaling out climate-smart agriculture with smallholders in a community-based approach
• Work Package 2:Incentivising the supply side to invest into climate-smart agriculture
• Work Package 3: Knowledge generation and dissemination
• Work Package 4: Creating an enabling policy environment
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YES we
CAN!