Presentation delivered at the CIALCA international conference 'Challenges and Opportunities to the agricultural intensification of the humid highland systems of sub-Saharan Africa'. Kigali, Rwanda, October 24-27 2011.

1. CIALCA's efforts in farming systems R4D

2. CIALCA's efforts in farming systems R4D
1. Understand farming systems diversity & complexity
a. Quantitative analysis of resource availability
b. Qualitative understanding of objectives + practices
2. Identify opportunities to improve systems, adapted to
a. Agro-ecology and market opportunities
b. Production objectives and farm resources
3. Test and evaluate
a. Quantify resource use efficiency, food, and income
b. Understand farmer perceptions
4. Lessons learned

3. CIALCA's efforts in farming systems R4D
Baseline survey – 2506 farms in 10 regions (i.e. mandate areas)
Differences within sites are bigger than differences
between sites -> clustered sampling is more efficient
(Bouwmeester et al. - comparison of 3 different datasets in East DRC)
(Ouma and Birachu, 2010, CIALCA baseline survey report)

4. Farming system diversity and complexity
Baseline survey – 2506 households in Rwanda, Burundi, DR Congo
General findings:
-small farms (<1ha)
-large families (7 people)
-few livestock (0.4 TLU – Rwanda >0.8)
-high illiteracy rates (up to 60%)
-food insecurity >60% in South Kivu, Burundi
-depending on few staple crops
- cassava
- bananas
- beans
- maize
Rice, Maize ↑, Coffee ↓

5. Farming system diversity and complexity
Baseline survey – 2506 households in Rwanda, Burundi, DR Congo
Resource limitations
-Land ownership often problem in East DRC
->30% of plots in upland and lowland
-Access to improved germplasm
- <25% access to improved bananas
- <1% up to >98% for bush beans
-Very limited access to credit
-Social capital generally poorly developed
- member of farmer groups <45%

6. Farming system diversity and complexity
Baseline survey – 2506 households in Rwanda, Burundi, DR Congo
Off-farm variable -> higher in Rusizi, South Kivu, Gitarama, Kibuye-Gisenyi

7. Farming system diversity and complexity
Baseline survey – 2506 households in Rwanda, Burundi, DR Congo
Three farm types
1. Resource-rich entrepreneurs – commercially oriented
2. Resource-constraint farmers – subsistence oriented
3. Natural resource-rich farmer – making ends meet
1 2 3

8. Farming system diversity and complexity
Resource-rich entrepreneurs
1. Access to financial and natural capital
2. Social capital highly variable
3. Good access to (urban) markets
1
4. Off-farm income allows investment and risks
Relatively more abundant in
Gitarama, Rwanda
Rusizi plains, Burundi

9. Farming system diversity and complexity
Resource-poor farmers
1. Low physical, social, financial and natural capital
2. Subsistence oriented – limited access to market
3. Household food insufficiency 2
Relatively more abundant in:
Gitega, Burundi
Kirundo, Burundi
Walungu, South Kivu, DRC
Butembo, North Kivu, DRC

10. Farming system diversity and complexity
Natural resource-rich farmer – making ends meet
1. Relatively large land holdings and livestock units
2. Remotely located from basic amenities / markets
3. Mainly involved in subsistence agriculture and
petty trade as livelihood strategy 3
Relatively more abundant in:
Umutara, Rwanda
Mutwanga, North Kivu

11. Farming system diversity and complexity
Qualitative understanding of farmer objectives and constraints
Depending on the FERTILISATION PAILLAGE
ecology and production RE
objective differences: RS
-crops
RO
-varieties
-surface area BU
-crop management
CO
-soil fertility options
Van Damme et al., this conference

12. Farming system diversity and complexity
Qualitative understanding of farmer objectives and constraints
Complex system of different production units (livestock and crops)
A range of crops are grown in different small
fields (usually a 1-10 ares) with varying
management intensity and soil fertility level.
Rented distant fields, maize-legume based
Pig stable and ‘compostière’ next to the homestead
Banana plantations near homestead
Distant fields with sweet potato, cassava and legumes
Example from Gitega, Burundi

13. Farming system diversity and complexity
Intensification -> more production per unit land
Small farms < 0.5ha
- Selling labor -> no nutrient inputs
Medium farms 0.8ha
- Relatively high labor + nutrient inputs
Large farms > 1.0 ha
- Less labor and nutrient inputs per unit area
Van Damme et al., this conference

14. Farming system diversity and complexity
Intensification -> managing the soil
Soil fertility gradients
- Better yields close to homesteads
- More inputs close to homestead kitchen
- Organic matter is key to soil fertility Kitchen residues,
ashes, urine,…
More nutrient inputs near the kitchen (dark green leaves)
give better yields than further away (light green leaves)
Delstanche 2011, PhD thesis at UCL Okumu et al., 2011, Scientia Horitculturae

15. Finding the win-win-win’s
The quest for integrated solutions –> win-win-win
1. Increasing efficiencies
a. Returns to land
b. Returns to labor
c. Returns to inputs (e.g. nutrients)
2. Improve resilience and sustainability
a. Maintain / improve natural resource base
b. Adapt to climate change and extreme events
c. Reduce pest and disease pressure
3. Respond to the needs / constraints of rural livelihoods
a. Increase income and food
b. Reduce risks
c. More equitable benefits - gender

16. Integrating farming system components
Integrating crop components: legume x maize
1. Validating the Mbili system in Central Africa

17. Integrating farming system components
Integrating crop components: legume x maize
Results confirm benefit of Mbili – nutrient inputs further ↑ this
Bean crop Bean crop
local vs. improved arrangement with vs. without fertilizer
3.0 3.0
northern axis northern axis
Bean yield MBILI + NPK (t ha-1)
2.5 southern axis 2.5 southern axis
Bean yield MBILI (t ha-1)
2.0 2.0
1.5 1.5
1.0 1.0
0.5 0.5
0.0 0.0
0.0 0.5 1.0 1.5 2.0 2.5 3.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0
-1 -1
Bean yield local practice (t ha ) Bean yield MBILI (t ha )
% yield increase relative to the traditional practice (averaged across all participants)
Legume Maize
MBILI 00-10% 05-20%
MBILI + Fertilizer 15-50% 15-60%

18. Integrating farming system components
Integrating crop components: legume x cassava
1. Different planting arrangements
a. cassava – traditional/random
b. cassava 1 x 1m
c. cassava 2x0.5m
2. Different legume intercrops:
a. First 4 lines beans/ground at 40cm
b. Second 2 lines soybean at 67cm
3. Strategic application of nutrients
a. Compost or farmyard manure
b. Mineral fertilizer

19. Integrating farming system components
Integrating crop components: legume x cassava
Improvements in system productivity in farmer-managed trials
cassava storage root yield (t ha )
-1
max. SED (1st legume) 2nd legume (soybean) northern axis max. SED
legume grain yield (kg ha-1)
3000 max. SED (2nd legume) 1st legume (common beans)
30
northern axis
southern axis
2000
20
southern axis
1000 10
0 0
trad. 1x1 1x1 2x0.5 trad. 1x1 1x1 2x0.5 trad. 1x1 1x1 2x0.5 trad. 1x1 1x1 2x0.5
+NPK +NPK +NPK +NPK +NPK +NPK +NPK +NPK
% yield increase relative to the traditional practice (averaged across all participants)
Legume Cassava
1x1 ~10% 0-5%
1x1+fertilizer 25-40% 15-25%
2x0.5+fertilizer 40-60% 20-35%

20. Integrating farming system components
Integrating legume x cassava/maize: a win-win-win?
1. Improved resource use efficiency:
- Land, Labor, Nutrient inputs
- But strongly site-specific!
2. Improved resilience/sustainability
- Improved soil fertility long term?
- Mixed cropping -> spread risks
3. Responds to livelihood
needs/constraints
- Yes, but fertilizer access is challenge
- Requires technical know-how…
- First farmers became ‘technicians’
(Lambrechts et al., pers. comm.)

21. Integrating farming system components
Integrating crop components: banana x legume
Common practice
-Traditionally low yielding
bush beans
-Tillage at onset of planting
season -> damage roots
Quest:
- Can we improve the
legume component, while
maintaining banana
yields?

22. Integrating farming system components
Banana x legume intercropping: zero tillage + mulch
Zero-tillage and mulch certainly works for bananas
Tillage / no-mulch No-till / self-mulch Hyparrhenia Tripsacum
Bizimana, Muliele, et al. – this conference

23. Integrating farming system components
Banana x legume intercropping: zero tillage + mulch
Bean yields
-Mulch first increases
bean yields
-Dense banana leaf
canopies reduce bean
yields
(Bizimana, Muliele et al., this conference)

24. Integrating farming system components
Banana x legume intercropping: reduce banana canopy
-Leaf pruning increases yield, particularly for soy and climbing bean
-But pruning has negative impact on banana performance
2500
Legume grain yield(kg/ha)
Monocrop 400 Monocrop
Banana plant height(cm)
2000 350
4 leaves 4 leaves
300
1500 7 leaves 7 leaves
250 4 leaves
All leaves 200 All leaves 7 leaves
1000
150 All leaves
500 100
50
0 0
ean soybean Climbing Bush bean
Climbing Bush bean soybean
soybean Climbing Bush bean soybean
bean
bean bean
after banana 2010B (3 months after banana
2011A (9 months after banana 2011A (9 months after banana
g) planting)
planting) planting)
(Ntamwira et al., this confernce)

25. Integrating farming system components
Banana x legume intercropping: win-win-win?
1. Improved resource efficiency?
-LER > 1
-Income ?
2. Improved resilience and sustainability
-Permanent canopy and soil cover reduces
erosion
3. Responds to livelihood needs/constraints
-More food and income, but …
-Banana often controlled by
men, when cash crop / beer
-Beans often cultivated by
women, important source of proteins

26. Integrating farming system components
Integrating crop components: coffee x banana systems
Coffee was introduced at large scale in 1950s as mono-crop
Farmers in Uganda and Tanzania have developed intercrop systems
6000
coffee banana
Yield value (USD ha-1 yr-1 )
5000
error bars - S.E.
4000
3000
2000
1000
0
intercrop coffee banana intercrop coffee banana
mono mono mono mono
SW Uganda - Robusta East Uganda - Arabica

27. Integrating farming system components
Integrating crop components: coffee x banana systems
Burundi : 10
Mulch depth (cm)
8
Farmers are removing crop residue from 6
banana fields to mulch coffee fields 4
-> farmers plant bananas around coffee 2
0
LB PB
COFFEE BANANA
Bunchy
Coffee Cherries weight Yield (T of 100cherrie Banana weight Yield
sub-plot (kg/tree) cherries/ha) weight (g) sub-plot (kg) (T/ha)
LB 2,01 a 4,92 a 152,2 a LC 8,00 a 10,4 a
PB 1,98 a 4,87 a 161,6 b PC 15,1 b 28,6 b
(Nibasumba et al., this conference)

28. Integrating farming system components
Perception analysis through interviews: coffee x banana
Arabica Robusta Extension Managers Sum Citing
Incentives for intercropping (n=12) (n=12) (n=8) (n=8) (n=40) order
Rating
1. Cash and food from same land 9 11 5 7 32 6.3 202
2. Banana provides shade 8 9 4 7 28 6.1 170
3. Land scarcity 5 5 4 5 19 5.2 98
4. Banana provides in situ mulch 8 3 0 2 13 6.5 84
5. Motivates to manage better 1 3 2 2 8 4.1 33
6. Thicker coffee cherries 2 2 0 2 6 2.7 16
7. Feed animals banana biomass 2 0 0 0 2 5.5 11
Disincentives for intercropping
Low soil fertility 2 2 8 8 20 5.2 103
Lack of recommendations 4 0 1 2 7 4.3 30
Unbelief through experience 2 2 1 0 5 2.6 13
Bananas damage coffee 0 2 0 0 2 5.0 10
Cultural traditions 0 1 0 0 1 4.0 4
(Jassogne et al., this conference)

29. Integrating farming system components
Sustainability and resilience: coffee x banana
1. Bananas provide mulch ->
- Increased nutrient recycling,
- Intercropped coffee appears less
nutrient deficient
- Accelerated nutrient mining?
2. Resilient to climate shocks
- Shaded coffee -> less drought
- Less strong biennial variation
3. Certain coffee pests/diseases
decrease when intercropped

30. Integrating farming system components
Banana x coffee intercropping: win-win-win?
1. Improved resource efficiency?
-LER + income > 1.5x
-Impact on coffee quality?
2. Improved resilience and sustainability
-Increased nutrient recycling and needs!
-Adapted to climate shocks and change?
-More resilient to market volatility
3. Responds to livelihood needs/constraints
-More food and income, but……
-Coffee is dominated by men
-When bananas = food crop, then women will
see their labor input increased

31. Integrating farming system components
Erosion control trials in South Kivu
Fanya juu earth embankments
Researcher-managed long-term
trial to evaluate the effects of:
-zero-tillage
-Calliandra hedgerows
-Fanya juu earth embankments
Calliandra hedgerows

32. Integrating farming system components
Erosion control trials in South Kivu
Control: 30 kg m-2 after 4 years = ~3 mm of soil lost
50
Cumulated soil loss (kg m )
-2
40 SED
30
20
10
0
tilled not tilled tilled not tilled tilled not tilled tilled not tilled
no hedge Calliandra no hedge Calliandra
without embankments with embankments
Most effective soil erosion control by fanya juu earth embankments
Zero-tillage without additional measures increases soil erosion (reduced infiltration)

33. Integrating farming system components
Erosion control trials in South Kivu
1st season 1st season 7th season 7th season
1st season 7th season
1000 1000 1000 1000
1000 1000
Soybean yield (kg ha-1)
Soybean yield (kg ha )
Soybean yield (kg ha )
Soybean yield (kg ha-1)
Soybean yield (kg ha-1)
Soybean yield (kg ha-1)
-1
-1
800 800 SED 800 SED 800
800 SED SED
SED 800
600 600 600 600
600 600
400 400 400 400
400 400
200 200 200 200
200 200
Caliandra
0
tilled
0
not tilled tilled
tilled not tilled
not tilled tilled
tilled not tilled
not tilled tilled
tilled not tilled
0
not tilled tilled
tilled not tilled
not tilled
00
tilled
tilled notnottilled tilled
tilled not tilled tilled notnottilled tilled
tilled tilled not tilled tilled not nottilled
tilled tilled
tilled not tilled tilled
tilled not tilled
not tilled
0
competes
tilled not tilled tilled not tilled
no hedge Calliandra
no hedge no hedge
Calliandra Calliandra
no hedge no hedge
Calliandra Calliandra
no hedge
no hedge no Calliandra
hedge
Calliandra Calliandra
no hedge
no hedge Calliandra
Calliandra no hedge Calliandra
without embankmentswithout embankments embankments
with with embankmentswithout embankments without embankments embankments
with
without embankments with embankments
with embankments without embankments
2nd season 2nd season 8th season 2nd season
8th season 8th season
3500 3500 3500 3500
3500 3500
Not win-win-win
3000 3000 3000 3000
3000 3000
Maize yield (kg ha-1)
Maize yield (kg ha-1)
Maize yield (kg ha-1)
SED
Maize yield (kg ha-1)
Maize yield (kg ha )
SED SED SED
-1
SED
2500 2500 2500 2500
2500 2500
-Yes, erosion reduces
2000
2000 2000 2000
2000 2000
-High labour requirements
1500
1500 1500 1500
1500 1500
Yields
1000 1000
1000 1000
1000 1000
-Yields not increased
500
500
500
500
500 500
slowly
0
0
0
0
0 0
catching up
tilled not tilled
tilled not tilled tilled not tilled tilled not tilled tilled not tilled tilled not tilled tilled not tilled tilled not tilled
tilled not tilled tilled not tilled tilled not tilled tilled not tilled tilled not tilled
tilled not tilled tilled
tilled not tilled
not tilled tilled
tilled not tilled
not tilled tilled
tilled not tilled
not tilled tilled not tilled tilled not tilled
no hedge Calliandra no hedge Calliandra no hedge Calliandra no hedge Calliandra
no hedge Calliandra no hedge Calliandra no hedge
no hedge Calliandra
Calliandra no hedge
no hedge Calliandra
Calliandra no hedge Calliandra
without embankments with embankments without embankments with embankments
without embankments with embankments without embankments
without embankments with embankments
with embankments without embankments

34. CIALCA's efforts in farming systems R4D
Lessons learned
1. We don’t really invent -> we learn and adapt from the best farmers
2. Certain intercrop systems allow increased efficiencies at farm level in
terms of returns to land, labor, nutrients/fertilizer
3. Medium-size farms (≈1 ha) produce most per unit land
4. Control of resources (land, labor, capital) is key -> gender
issues, cultural barriers, policies, and access to knowledge and
markets
Research outlook and gaps
1. The quest continues
2. Role of livestock and nutrient cycling not yet sufficiently exploited
3. Trade-offs have to be better quantified in space and time
4. Socio-political implications have to be better understood

35. Thank!
Acknowledgements
The national research partners, universities, NGO’s, cooperating
farmers, you, and particularly the students!