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A Situation Analysis of
Small-scale Farming
Systems in West Kenya
Action Site of the
Humidtropics Program
Paul L. Woomer, Canon
Savala, Celister Kaleha and
Moses Chamwada
IITA-Kenya and WeRATE R4D
Platform
Email: plwoomer@gmail.com
SRT 1 Systems analysis
and synthesis
SRT 2 Integrated systems
improvement
SRT 3 Scaling and
institutional innovation
International
Public Goods
Development
trajectories
M&E
framework
R4D innovation
SRT 2.3
Natural
resource
management
SRT 2.2
Systems
productivity
new farm opportunities
Adaptive management M&E
process
Action area level
R4D scaling
Enabling environment
(markets, policies,
institutions and
infrastructure)
Gender opportunities
Scalability options &
pathways
opportunities mainstreamed
Situation analyses
Critical entry points R4D platforms
Global syntheses
SRT 2.1 Markets and
other institutions
Action site level
Grassroots R4D actions in the West Kenya Action Site driven by the
Humidtropics Program Framework based upon a rapid Situation Analysis
N2A
EIA
WeRATE
Maize
Legume
Ext info
Mkt & VA
Strigicide
BNF TD
internal
Striga elimination
(MLNV)
Legume integration Crop diversification
Animal enterprise
organic
inputs
suppression,
N residuals
understorey
habitat
improved
feed
improved
feed
organic
inputs
non-host
alternative
improved
feed
organic
inputs
understorey habitat
residual benefits
food
security
income
generation
nutritional
security
resource
conservation
Key Entry Points of the West Kenya Action Site
 Western Region Agricultural Technology Evaluation (WeRATE)
R4D Platform conducts grassroots actions in the West Kenya
Action Site
 WeRATE works with both the N2Africa and Humidtropics
 Early impact assessment (EIA) and stakeholder survey
conducted
 EIA (2013) examined 291 households stratified by AEZ and
head of household (men/women)
 Stakeholder survey (2014) covered 24 farmer associations and
local NGOs
 Responses compiled into spreadsheets and interpretive
statistics performed
 Farming systems diagrams based upon entry points and their
interactions constructed
 On-farm technology tests and farmer training conducted
around two entry points (maize constraints and legume
integration)
household
adults, children,
farm size, food
security
Livestock
cattle, sheep,
goats,swine,
chickens, others
Legumes
produced
bean, groundnut
soybean, others
Cereal produced
maize, sorghum
millet, finger millet
Other crops
Potatoes, cassava,
banana, vegetables,
sugarcane, tobacco,
others
intercropping
Crop marketing
legumes
consumed
seed
legumes
sold
cereal
consumed
cereal
sold
manure
seed
feed
residues
manure
manure
vegetables,
root & cash
crops sold
Outside
income
Hired
labor
Livestock marketing
vegetables &
root crops
consumed
animal
products
consumedthe farm animal products sold
Three major agro-ecological zones
occur in WeRATE’s Action Area
Lake Victoria Basin (1125 to 1300
masl): semi-arid to semi-humid climate,
maize-based cropping with some
cassava and rice. Failing cotton.
Lower Midlands (1300 to 1500 masl):
sub-humid climate with rolling hills and
plateaus, maize-bean intercropping with
sweet potato, banana. Large sugar
plantations and out-growers. Failing
tobacco.
Upper Midlands (1500 to 1800 masl):
humid climate, mountainous terrain,
maize-bean cropping with potato, pea
and vegetables. Tea out-growers.
Lake Basin
Midlands
Upper Midlands
Highlands
WeRATE
Site
Cropping characteristics in different agro-ecological zones in west Kenya1
.
Farm Characteristic Agro-ecological Zone (± SD)
Lake Basin Midland Upper Midland
Intercrop cereals and legumes (%) 77 ±43 81 ±40 79 ±41
Cultivate maize (%) 100 99 99
Annual maize harvest (kg) 371 ±419 925 ±1619 595 ±1276
Markets maize (% of households) 19 ±22 30 ±30 20 ±29
Cultivate beans (%) 62 ±49 78 ±42 83 ±38
Annual bean harvest (kg) 71 ±102 123 ±149 27 ±17
Markets legumes (% of households) 46 ±28 50 ±30 40 ±36
1
Based upon elevation (masl) where <1300 = Lake Victoria Basin (n=77), 1300-1500 = Midlands (n=108)
and , >1500 = Upper Midlands (n=87).
Farm practices among small-scale
households in the west Kenya Action
Site (n = 291).
Farm practice f
Transfer legume residues 0.81
Feed legume residues 0.56
Make compost/store manure 0.54
Apply NP fertilizer 0.49
Practice fallowing 0.38
Purchase fertilizer locally 0.35
Topdress with N fertilizer 0.13
Practice mulching 0.11
Transfer fresh manure/urine 0.11
This approach resulted in a
wealth of information on farmer
practice across the West Kenya
Action Site (right) and within its
different agro-ecological zones
(below)
Farm characteristics at different household resource endowment levels in west Kenya1
.
Farm Characteristic Household Resource Endowment (± SD)
Low Modest Higher
frequency (f) 0.39 0.32 0.29
farm size (ha) 0.34 ±0.17 0.75 ±0.36 1.73 ±1.25
Household members (no) 7.5 ±2.5 6.7 ±2.4 5.8 ±2.7
Hectare per capita (ha/person) 0.06 ±0.02 0.14 ±0.03 0.39 ±0.21
Work outside of farm (%) 50 ±50 39 ±49 31 ±47
Hire others to work on farm (%) 65 ±48 78 ±41 84 ±37
1
Based on adjusted hectare per capita where resource endowment = farm size (ha)/(household adults + 0.5
household children), <0.1 is poor (n=113), 0.1 to 0.2 is modest (n=93) and >0.2 is high (n=83).
Findings also allowed households to be separated into
three resource endowment categories based upon per
capita land availability with large differences in farm
practices and household wellbeing between them
This stratification allowed for the construction of a
farming system diagram for the poorest
households
household
adults 4.4
children 3.1
0.06 ha pc
Farm household
0.34 ha
1448 masl
2.3 fields
3.6 field crops/yr
$155 income/yr
food shortfall 122 days/yr
Livestock
2.0 cattle, 1.0 shoats
0.2 swine
10 chickens
Legumes 119 kg
bean 33 kg
groundnut 8 kg
soybean 64 kg
others 14 kg
Maize 355 kg
sorghum, millet,
finger millet grown
by 20% households
(71 kg est.)
Other crops
potatoes 25 kg (est)
cassava 39 kg (est)
cash crops 10% of HHs
trash
183 kg (est)
stover
609 kg (est)
manure
1430 kg (est)
intercrop
0.86
Crop marketing
legumes
consumed
38 kg
seed
10 kg
legumes
sold
71 kg
$43 (est)
maize consumed
248 kg
maize sold
103 kg
$41 (est)
manure
50 kg
seed
3 kg
feed
99 kg
residues
21 kg
residues
63 kg
$31
manure
345 kg
feed
609 kg
manure
1035 kg
root crops
sold
32 kg (est)
$9 (est)
cash crops
no estimate
Outside
income
Hired
labor
$6
Livestock marketing
$31 (est)
root crops
consumed
32 kg (est)
Low Resource Endowment, n = 113 Based on N2Africa West Kenya
EIA, April 2013
Selected characteristics among male- and female- headed households in
the West Kenya Action Site ( ± Standard Deviation).
Farm characteristic Head of Household Equity
Male1
Female2
Index3
Farm size (ha) 1.0 ±1.0 0.6 ±0.4 0.60
Household members (n) 7 ±3 6 ±3 0.91
Resource endowment (ha pc) 0.21 ±0.20 0.15 ±0.14 0.72
Market access (frequency) 0.22 ±0.29 0.29 ±0.28 1.28
Household hunger (yr) 0.08 ±0.15 0.13 ±0.19 1.62
1
Based upon interviews of 117 male-headed households (MHH). 2
Based upon
interviews of 79 female-headed households (FHH). 3
Equity Index =
FHH/MHH.
A farming system diagram describing the
differences between these two household types
was constructed
household
adults -1
children 0
-0.06 ha pc
Farm household
-0.4 ha
-4 masl
+0.1 fields
+0.2 field crops/yr
-$168 income/yr
hunger +18 days/yr
Livestock
-0.8 cattle,
0 shoats
-7 chickens
Legumes -94 kg
bean -39 kg
groundnut -4 kg
soybean -54 kg
others +3 kg
Maize -231 kg
sorghum, millet,
finger millet grown
by +9% households
(-17 kg est.)
Other crops
potatoes 0 kg (est)
cassava -21 kg (est)
cash crops -4% of HHs
trash
-145 kg (est)
stover
-354 kg (est)
manure
-581 kg (est)
intercrop
+0.12
Crop marketing
legumes
consumed
-17 kg
seed
-1 kg
legumes
sold
-76 kg
-$46 (est)
maize
consumed
-123 kg
maize sold
-129 kg
-$52 (est)
manure
+51 kg
seed
+3 kg
feed
-105 kg
residues
-17 kg
residues
-23 kg
-$38
manure
-246 kg
feed
-354 kg
manure
-386 kg
root crops
sold
-7 kg (est)
-$3 (est)
cash crops
-$4 (est)
Outside
income
Hired
labor
-$25
Livestock marketing
-$28 (est)
root crops
consumed
-14 kg (est)
Inequity among female-headed households Based on N2Africa West Kenya
EIA, April 2013
Responsive field actions
by the WeRATE R4D
Platform
24 dues-paying groups belong to the Platform
78421 total farmers represented (66% women)
95% of groups operate women's and youth chapters
86 technology tests were conducted in 2014
6265 total farmers trained in 2014 (58% women)
39 agrodealers aligned with Platform
75 tons of seed produced in 2014
182 tons of grain marketed in 2014
88% report striga a major constraint of maize
58% report Asian rust a major constraint of soybean
54% consider nitrogen deficiency a soil constraint
Management Yield Root nodules Crown nodulation Red interiors
strategy kg per ha No per plant ------------ % ------------
No inputs 1357 ± 220 8 ± 2 3 ± 20 58 ± 13
w/ Sympal 1648 ± 331 11 ± 2 15 ± 8 65 ± 11
w/ BIOFIX 1728 ± 232 17 ± 2 47 ± 13 79 ± 10
N2A Package 2222 ± 397 27 ± 3 70 ± 11 85 ± 9
Yield and nodulation characteristics: SC Squire 2014-2015 Short Rains
MIRCEN
brand
existing
agrodealers
subsidize
new One-
Stop Shops
establish
exhibits and
mobile
shops
Commercializing
inoculants
Management Crop/ Totalcost Netreturn Benefit:Cost
strategy variety ---$perha--- ratio
BetterBeans NewRosecoco 448 504 2.13
IRmaize FRC425 364 1482 5.07
N2APackage SoycvSquire 335 961 3.87
Costs and Returns
Crop seed fertilizer labor bagging total gross net Benefit: labor
Management cost cost cost cost cost return return Cost days
Code KSh Ratio per ha
1 6000 12900 10350 2062 31312 106967 75655 3.42 45 Suseptible: WH403
2 6750 12900 9900 3202 32752 166123 133372 5.07 42 IR Maize: FRC 425
3 6000 12900 10200 3211 32311 166591 134280 5.16 44 MLNV tolerant: WH 402
4 6000 12900 10200 2267 31367 117611 86244 3.75 44 Productive Hybrid: WH 507
5 5400 12900 10200 2593 31093 134552 103459 4.33 44 Productive Hybrid: SC Simba
6 6800 12900 11250 1140 32090 50127 18038 1.56 47 Non-host intercrop: Sila-Squire IC
Save file as application of alter inputs that follow for another projection
INPUTS 1: seed and inoculant (enter rate and price)
Crop subtotal
Management ---- groundnut ---- ---- other seed ----- ---- inoculant ---- seed
Code rate price rate price rate price rate price rate price cost
1 30 200 0 80 0 54 0 67 0 300 6000
2 30 225 0 80 0 54 0 67 0 300 6750
3 30 200 0 80 0 54 0 67 0 300 6000
4 30 200 0 80 0 54 0 67 0 300 6000
5 30 180 0 80 0 54 0 67 0 300 5400
6 0 180 40 80 0 54 15 160 4 300 6800
INPUTS 2: fertilizer and pesticides (enter rate and price)
Crop subtotal
Management --- pesticide 1 --- --- pesticide 2 --- fertilizer
Code rate price rate price rate price rate price rate price rate price rate price cost
1 150 36 150 50 0 50 0 68 0 50 0 3750 0 2500 12900
2 150 36 150 50 0 50 0 68 0 50 0 3750 0 2500 12900
3 150 36 150 50 0 50 0 68 0 50 0 3750 0 2500 12900
4 150 36 150 50 0 50 0 68 0 50 0 3750 0 2500 12900
5 150 36 150 50 0 50 0 78 0 10 0 3750 0 2500 12900
6 150 36 150 50 0 50 0 78 0 10 0 3750 0 2500 12900
LABOR OPERATIONS (enter manday and pay)
Crop subtotal
Management --- weeding 1 --- - harvest legume - --- harvest maize ---labor
Code manday pay manday pay manday pay manday pay manday pay manday pay manday pay manday pay cost
1 3 150 6 750 10 150 7 150 7 150 0 500 12 150 0 150 10350
2 3 150 6 750 10 150 7 150 4 150 0 500 12 150 0 150 9900
3 3 150 6 750 10 150 7 150 6 150 0 500 12 150 0 150 10200
4 3 150 6 750 10 150 7 150 6 150 0 500 12 150 0 150 10200
5 3 150 6 750 10 150 7 150 6 150 0 500 12 150 0 150 10200
6 3 150 7 750 12 150 7 150 3 150 0 500 15 150 0 150 11250
Crop OTHER OPERATIONS, BAGGING and TOTAL COSTS
Management BAGGING TOTAL
Code amount type size (kg) price pay/bag COSTS COSTS
1 0 na 50 23 30 2062 31312
2 0 na 50 23 30 3202 32752
3 0 na 50 23 30 3211 32311
4 0 na 50 23 30 2267 31367
5 0 na 50 23 30 2593 31093
6 0 na 50 23 30 1140 32090
CROP YIELD and GROSS RETURN
Crop ---------------- soybean ------------------- ------------------- beans ------------------- GROSS
Management season 1 season 2 total price season 1 season 2 total price season 1season 2 total price other RETURN
Code kg ha-1 kg ha-1 kg ha-1 per kg kg ha-1 kg ha-1 kg ha-1 per kg kg ha-1kg ha-1 kg ha-1 per kg crop per ha
1 0 0 0 53 0 0 0 75 1945 0 1945 55 maize 106967
2 0 0 0 53 0 0 0 75 3020 0 3020 55 maize 166123
3 0 0 0 53 0 0 0 75 3029 0 3029 55 maize 166591
4 0 0 0 53 0 0 0 75 2138 0 2138 55 maize 117611
5 0 0 0 53 0 0 0 75 2446 0 2446 55 maize 134552
6 474 0 474 53 0 0 0 75 601 0 601 42 sorghum 50127
----- bagging operations ----
details on crop management
ha-1 ----------------------------------------------------------------
Begin management and price entries below
oop = 0, toc = 1
1
--- other fertilizer ----
-- land preperation -- ------ tillage ------
1
1
1
1
1
---- labor factor -------- other direct costs ----
--- weeding 2 --- --- spraying ---
------ DAP ------ ----- CAN ----- ------- SSP ------- ----- Sympal -----
---- maize ---- ----- soybean -----
--- planting ---
---------------- other crop ----------------
Economic analyses are
performed on results from all
technology tests using the
N2Africa EZ Cost and Return
Utility (right) and the most
promising technologies (above)
compared to current practice.
gap technology benefit:cost
- 94 kg beans + 0.3 ha NRC 2.2
- 231 kg maize + 0.2 ha IR 5.1
- $168 income + 0.4 ha SC soy 3.9
A women-headed household requires $36 to $67
credit for inputs per growing season to close
production or income gaps with male-headed
households
household
adults, children,
farm size, food
security
Livestock
cattle, sheep,
goats,swine,
chickens, others
Legumes
produced
bean, groundnut
soybean, others
cereal produced
maize, sorghum
millet, finger millet
Other crops
Potatoes, cassava,
banana, vegetables,
sugarcane, tobacco,
others
intercropping
Crop marketing
legumes
consumed
seed
legumes
sold
cereal
consumed
cereal
sold
manure
seed
feed
residues
manure
manure
vegetables,
root & cash
crops sold
Outside
income
Hired
labor
Livestock marketing
vegetables &
root crops
consumed
animal
products
consumedthe farm animal products sold
household
adults, children,
farm size, food
security
Livestock
cattle, sheep,
goats,swine,
chickens, others
Legumes
produced
bean, groundnut
soybean, others
cereal produced
maize, sorghum
millet, finger millet
Other crops
Potatoes, cassava,
banana, vegetables,
sugarcane, tobacco,
others
intercropping
Crop marketing
legumes
consumed
seed
legumes
sold
cereal
consumed
cereal
sold
manure
seed
feed
residues
manure
manure
vegetables,
root & cash
crops sold
Outside
income
Hired
labor
Livestock marketing
vegetables &
root crops
consumed
animal
products
consumedthe farm animal products sold
Using this approach we can
identify the technologies, field
area and cost of closing gaps in
crop yield, income and food
shortages! For example …
Transition from KHG CBO to commercial
value-addition operations
2012: KHG-N2Africa
receives Phase 1
revolving inputs ($493)
2012-2013: bulk and
sold 12 tons soybean
grain ($8440)
2013: receive Equity
Bank loan ($11,100)
 A wealth of secondary information may be interpreted within a
wider farming system context (avoid farmer survey fatigue)
 Situation analyses are not an ends but rather a starting point
for corrective response (farmers cannot eat electrons)
 The R4D Platform approach is working in west Kenya and is a
promising bridge to institutional innovation (WeRATE case
study available on request)
 Early successes on striga management and grain legume
integration, little progress in improved animal enterprise (some
CG centers have not fulfilled their expected roles)
 Focus upon differences between male- and female-headed
households incomplete as it ignores critical roles of women
within the former (or so I am told, perhaps soil ecologists
should not overextend themselves)
Conclusions (and wider perspectives)

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A Situation Analysis of Small-scale Farming Systems in West Kenya Action Site of the Humidtropics Program by Paul woomer

  • 1. A Situation Analysis of Small-scale Farming Systems in West Kenya Action Site of the Humidtropics Program Paul L. Woomer, Canon Savala, Celister Kaleha and Moses Chamwada IITA-Kenya and WeRATE R4D Platform Email: plwoomer@gmail.com
  • 2. SRT 1 Systems analysis and synthesis SRT 2 Integrated systems improvement SRT 3 Scaling and institutional innovation International Public Goods Development trajectories M&E framework R4D innovation SRT 2.3 Natural resource management SRT 2.2 Systems productivity new farm opportunities Adaptive management M&E process Action area level R4D scaling Enabling environment (markets, policies, institutions and infrastructure) Gender opportunities Scalability options & pathways opportunities mainstreamed Situation analyses Critical entry points R4D platforms Global syntheses SRT 2.1 Markets and other institutions Action site level Grassroots R4D actions in the West Kenya Action Site driven by the Humidtropics Program Framework based upon a rapid Situation Analysis N2A EIA WeRATE Maize Legume Ext info Mkt & VA Strigicide BNF TD internal
  • 3. Striga elimination (MLNV) Legume integration Crop diversification Animal enterprise organic inputs suppression, N residuals understorey habitat improved feed improved feed organic inputs non-host alternative improved feed organic inputs understorey habitat residual benefits food security income generation nutritional security resource conservation Key Entry Points of the West Kenya Action Site
  • 4.  Western Region Agricultural Technology Evaluation (WeRATE) R4D Platform conducts grassroots actions in the West Kenya Action Site  WeRATE works with both the N2Africa and Humidtropics  Early impact assessment (EIA) and stakeholder survey conducted  EIA (2013) examined 291 households stratified by AEZ and head of household (men/women)  Stakeholder survey (2014) covered 24 farmer associations and local NGOs  Responses compiled into spreadsheets and interpretive statistics performed  Farming systems diagrams based upon entry points and their interactions constructed  On-farm technology tests and farmer training conducted around two entry points (maize constraints and legume integration)
  • 5. household adults, children, farm size, food security Livestock cattle, sheep, goats,swine, chickens, others Legumes produced bean, groundnut soybean, others Cereal produced maize, sorghum millet, finger millet Other crops Potatoes, cassava, banana, vegetables, sugarcane, tobacco, others intercropping Crop marketing legumes consumed seed legumes sold cereal consumed cereal sold manure seed feed residues manure manure vegetables, root & cash crops sold Outside income Hired labor Livestock marketing vegetables & root crops consumed animal products consumedthe farm animal products sold
  • 6. Three major agro-ecological zones occur in WeRATE’s Action Area Lake Victoria Basin (1125 to 1300 masl): semi-arid to semi-humid climate, maize-based cropping with some cassava and rice. Failing cotton. Lower Midlands (1300 to 1500 masl): sub-humid climate with rolling hills and plateaus, maize-bean intercropping with sweet potato, banana. Large sugar plantations and out-growers. Failing tobacco. Upper Midlands (1500 to 1800 masl): humid climate, mountainous terrain, maize-bean cropping with potato, pea and vegetables. Tea out-growers. Lake Basin Midlands Upper Midlands Highlands WeRATE Site
  • 7. Cropping characteristics in different agro-ecological zones in west Kenya1 . Farm Characteristic Agro-ecological Zone (± SD) Lake Basin Midland Upper Midland Intercrop cereals and legumes (%) 77 ±43 81 ±40 79 ±41 Cultivate maize (%) 100 99 99 Annual maize harvest (kg) 371 ±419 925 ±1619 595 ±1276 Markets maize (% of households) 19 ±22 30 ±30 20 ±29 Cultivate beans (%) 62 ±49 78 ±42 83 ±38 Annual bean harvest (kg) 71 ±102 123 ±149 27 ±17 Markets legumes (% of households) 46 ±28 50 ±30 40 ±36 1 Based upon elevation (masl) where <1300 = Lake Victoria Basin (n=77), 1300-1500 = Midlands (n=108) and , >1500 = Upper Midlands (n=87). Farm practices among small-scale households in the west Kenya Action Site (n = 291). Farm practice f Transfer legume residues 0.81 Feed legume residues 0.56 Make compost/store manure 0.54 Apply NP fertilizer 0.49 Practice fallowing 0.38 Purchase fertilizer locally 0.35 Topdress with N fertilizer 0.13 Practice mulching 0.11 Transfer fresh manure/urine 0.11 This approach resulted in a wealth of information on farmer practice across the West Kenya Action Site (right) and within its different agro-ecological zones (below)
  • 8. Farm characteristics at different household resource endowment levels in west Kenya1 . Farm Characteristic Household Resource Endowment (± SD) Low Modest Higher frequency (f) 0.39 0.32 0.29 farm size (ha) 0.34 ±0.17 0.75 ±0.36 1.73 ±1.25 Household members (no) 7.5 ±2.5 6.7 ±2.4 5.8 ±2.7 Hectare per capita (ha/person) 0.06 ±0.02 0.14 ±0.03 0.39 ±0.21 Work outside of farm (%) 50 ±50 39 ±49 31 ±47 Hire others to work on farm (%) 65 ±48 78 ±41 84 ±37 1 Based on adjusted hectare per capita where resource endowment = farm size (ha)/(household adults + 0.5 household children), <0.1 is poor (n=113), 0.1 to 0.2 is modest (n=93) and >0.2 is high (n=83). Findings also allowed households to be separated into three resource endowment categories based upon per capita land availability with large differences in farm practices and household wellbeing between them This stratification allowed for the construction of a farming system diagram for the poorest households
  • 9. household adults 4.4 children 3.1 0.06 ha pc Farm household 0.34 ha 1448 masl 2.3 fields 3.6 field crops/yr $155 income/yr food shortfall 122 days/yr Livestock 2.0 cattle, 1.0 shoats 0.2 swine 10 chickens Legumes 119 kg bean 33 kg groundnut 8 kg soybean 64 kg others 14 kg Maize 355 kg sorghum, millet, finger millet grown by 20% households (71 kg est.) Other crops potatoes 25 kg (est) cassava 39 kg (est) cash crops 10% of HHs trash 183 kg (est) stover 609 kg (est) manure 1430 kg (est) intercrop 0.86 Crop marketing legumes consumed 38 kg seed 10 kg legumes sold 71 kg $43 (est) maize consumed 248 kg maize sold 103 kg $41 (est) manure 50 kg seed 3 kg feed 99 kg residues 21 kg residues 63 kg $31 manure 345 kg feed 609 kg manure 1035 kg root crops sold 32 kg (est) $9 (est) cash crops no estimate Outside income Hired labor $6 Livestock marketing $31 (est) root crops consumed 32 kg (est) Low Resource Endowment, n = 113 Based on N2Africa West Kenya EIA, April 2013
  • 10. Selected characteristics among male- and female- headed households in the West Kenya Action Site ( ± Standard Deviation). Farm characteristic Head of Household Equity Male1 Female2 Index3 Farm size (ha) 1.0 ±1.0 0.6 ±0.4 0.60 Household members (n) 7 ±3 6 ±3 0.91 Resource endowment (ha pc) 0.21 ±0.20 0.15 ±0.14 0.72 Market access (frequency) 0.22 ±0.29 0.29 ±0.28 1.28 Household hunger (yr) 0.08 ±0.15 0.13 ±0.19 1.62 1 Based upon interviews of 117 male-headed households (MHH). 2 Based upon interviews of 79 female-headed households (FHH). 3 Equity Index = FHH/MHH. A farming system diagram describing the differences between these two household types was constructed
  • 11. household adults -1 children 0 -0.06 ha pc Farm household -0.4 ha -4 masl +0.1 fields +0.2 field crops/yr -$168 income/yr hunger +18 days/yr Livestock -0.8 cattle, 0 shoats -7 chickens Legumes -94 kg bean -39 kg groundnut -4 kg soybean -54 kg others +3 kg Maize -231 kg sorghum, millet, finger millet grown by +9% households (-17 kg est.) Other crops potatoes 0 kg (est) cassava -21 kg (est) cash crops -4% of HHs trash -145 kg (est) stover -354 kg (est) manure -581 kg (est) intercrop +0.12 Crop marketing legumes consumed -17 kg seed -1 kg legumes sold -76 kg -$46 (est) maize consumed -123 kg maize sold -129 kg -$52 (est) manure +51 kg seed +3 kg feed -105 kg residues -17 kg residues -23 kg -$38 manure -246 kg feed -354 kg manure -386 kg root crops sold -7 kg (est) -$3 (est) cash crops -$4 (est) Outside income Hired labor -$25 Livestock marketing -$28 (est) root crops consumed -14 kg (est) Inequity among female-headed households Based on N2Africa West Kenya EIA, April 2013
  • 12. Responsive field actions by the WeRATE R4D Platform 24 dues-paying groups belong to the Platform 78421 total farmers represented (66% women) 95% of groups operate women's and youth chapters 86 technology tests were conducted in 2014 6265 total farmers trained in 2014 (58% women) 39 agrodealers aligned with Platform 75 tons of seed produced in 2014 182 tons of grain marketed in 2014 88% report striga a major constraint of maize 58% report Asian rust a major constraint of soybean 54% consider nitrogen deficiency a soil constraint
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  • 16. Management Yield Root nodules Crown nodulation Red interiors strategy kg per ha No per plant ------------ % ------------ No inputs 1357 ± 220 8 ± 2 3 ± 20 58 ± 13 w/ Sympal 1648 ± 331 11 ± 2 15 ± 8 65 ± 11 w/ BIOFIX 1728 ± 232 17 ± 2 47 ± 13 79 ± 10 N2A Package 2222 ± 397 27 ± 3 70 ± 11 85 ± 9 Yield and nodulation characteristics: SC Squire 2014-2015 Short Rains MIRCEN
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  • 19. Management Crop/ Totalcost Netreturn Benefit:Cost strategy variety ---$perha--- ratio BetterBeans NewRosecoco 448 504 2.13 IRmaize FRC425 364 1482 5.07 N2APackage SoycvSquire 335 961 3.87 Costs and Returns Crop seed fertilizer labor bagging total gross net Benefit: labor Management cost cost cost cost cost return return Cost days Code KSh Ratio per ha 1 6000 12900 10350 2062 31312 106967 75655 3.42 45 Suseptible: WH403 2 6750 12900 9900 3202 32752 166123 133372 5.07 42 IR Maize: FRC 425 3 6000 12900 10200 3211 32311 166591 134280 5.16 44 MLNV tolerant: WH 402 4 6000 12900 10200 2267 31367 117611 86244 3.75 44 Productive Hybrid: WH 507 5 5400 12900 10200 2593 31093 134552 103459 4.33 44 Productive Hybrid: SC Simba 6 6800 12900 11250 1140 32090 50127 18038 1.56 47 Non-host intercrop: Sila-Squire IC Save file as application of alter inputs that follow for another projection INPUTS 1: seed and inoculant (enter rate and price) Crop subtotal Management ---- groundnut ---- ---- other seed ----- ---- inoculant ---- seed Code rate price rate price rate price rate price rate price cost 1 30 200 0 80 0 54 0 67 0 300 6000 2 30 225 0 80 0 54 0 67 0 300 6750 3 30 200 0 80 0 54 0 67 0 300 6000 4 30 200 0 80 0 54 0 67 0 300 6000 5 30 180 0 80 0 54 0 67 0 300 5400 6 0 180 40 80 0 54 15 160 4 300 6800 INPUTS 2: fertilizer and pesticides (enter rate and price) Crop subtotal Management --- pesticide 1 --- --- pesticide 2 --- fertilizer Code rate price rate price rate price rate price rate price rate price rate price cost 1 150 36 150 50 0 50 0 68 0 50 0 3750 0 2500 12900 2 150 36 150 50 0 50 0 68 0 50 0 3750 0 2500 12900 3 150 36 150 50 0 50 0 68 0 50 0 3750 0 2500 12900 4 150 36 150 50 0 50 0 68 0 50 0 3750 0 2500 12900 5 150 36 150 50 0 50 0 78 0 10 0 3750 0 2500 12900 6 150 36 150 50 0 50 0 78 0 10 0 3750 0 2500 12900 LABOR OPERATIONS (enter manday and pay) Crop subtotal Management --- weeding 1 --- - harvest legume - --- harvest maize ---labor Code manday pay manday pay manday pay manday pay manday pay manday pay manday pay manday pay cost 1 3 150 6 750 10 150 7 150 7 150 0 500 12 150 0 150 10350 2 3 150 6 750 10 150 7 150 4 150 0 500 12 150 0 150 9900 3 3 150 6 750 10 150 7 150 6 150 0 500 12 150 0 150 10200 4 3 150 6 750 10 150 7 150 6 150 0 500 12 150 0 150 10200 5 3 150 6 750 10 150 7 150 6 150 0 500 12 150 0 150 10200 6 3 150 7 750 12 150 7 150 3 150 0 500 15 150 0 150 11250 Crop OTHER OPERATIONS, BAGGING and TOTAL COSTS Management BAGGING TOTAL Code amount type size (kg) price pay/bag COSTS COSTS 1 0 na 50 23 30 2062 31312 2 0 na 50 23 30 3202 32752 3 0 na 50 23 30 3211 32311 4 0 na 50 23 30 2267 31367 5 0 na 50 23 30 2593 31093 6 0 na 50 23 30 1140 32090 CROP YIELD and GROSS RETURN Crop ---------------- soybean ------------------- ------------------- beans ------------------- GROSS Management season 1 season 2 total price season 1 season 2 total price season 1season 2 total price other RETURN Code kg ha-1 kg ha-1 kg ha-1 per kg kg ha-1 kg ha-1 kg ha-1 per kg kg ha-1kg ha-1 kg ha-1 per kg crop per ha 1 0 0 0 53 0 0 0 75 1945 0 1945 55 maize 106967 2 0 0 0 53 0 0 0 75 3020 0 3020 55 maize 166123 3 0 0 0 53 0 0 0 75 3029 0 3029 55 maize 166591 4 0 0 0 53 0 0 0 75 2138 0 2138 55 maize 117611 5 0 0 0 53 0 0 0 75 2446 0 2446 55 maize 134552 6 474 0 474 53 0 0 0 75 601 0 601 42 sorghum 50127 ----- bagging operations ---- details on crop management ha-1 ---------------------------------------------------------------- Begin management and price entries below oop = 0, toc = 1 1 --- other fertilizer ---- -- land preperation -- ------ tillage ------ 1 1 1 1 1 ---- labor factor -------- other direct costs ---- --- weeding 2 --- --- spraying --- ------ DAP ------ ----- CAN ----- ------- SSP ------- ----- Sympal ----- ---- maize ---- ----- soybean ----- --- planting --- ---------------- other crop ---------------- Economic analyses are performed on results from all technology tests using the N2Africa EZ Cost and Return Utility (right) and the most promising technologies (above) compared to current practice.
  • 20. gap technology benefit:cost - 94 kg beans + 0.3 ha NRC 2.2 - 231 kg maize + 0.2 ha IR 5.1 - $168 income + 0.4 ha SC soy 3.9 A women-headed household requires $36 to $67 credit for inputs per growing season to close production or income gaps with male-headed households household adults, children, farm size, food security Livestock cattle, sheep, goats,swine, chickens, others Legumes produced bean, groundnut soybean, others cereal produced maize, sorghum millet, finger millet Other crops Potatoes, cassava, banana, vegetables, sugarcane, tobacco, others intercropping Crop marketing legumes consumed seed legumes sold cereal consumed cereal sold manure seed feed residues manure manure vegetables, root & cash crops sold Outside income Hired labor Livestock marketing vegetables & root crops consumed animal products consumedthe farm animal products sold household adults, children, farm size, food security Livestock cattle, sheep, goats,swine, chickens, others Legumes produced bean, groundnut soybean, others cereal produced maize, sorghum millet, finger millet Other crops Potatoes, cassava, banana, vegetables, sugarcane, tobacco, others intercropping Crop marketing legumes consumed seed legumes sold cereal consumed cereal sold manure seed feed residues manure manure vegetables, root & cash crops sold Outside income Hired labor Livestock marketing vegetables & root crops consumed animal products consumedthe farm animal products sold Using this approach we can identify the technologies, field area and cost of closing gaps in crop yield, income and food shortages! For example …
  • 21. Transition from KHG CBO to commercial value-addition operations 2012: KHG-N2Africa receives Phase 1 revolving inputs ($493) 2012-2013: bulk and sold 12 tons soybean grain ($8440) 2013: receive Equity Bank loan ($11,100)
  • 22.  A wealth of secondary information may be interpreted within a wider farming system context (avoid farmer survey fatigue)  Situation analyses are not an ends but rather a starting point for corrective response (farmers cannot eat electrons)  The R4D Platform approach is working in west Kenya and is a promising bridge to institutional innovation (WeRATE case study available on request)  Early successes on striga management and grain legume integration, little progress in improved animal enterprise (some CG centers have not fulfilled their expected roles)  Focus upon differences between male- and female-headed households incomplete as it ignores critical roles of women within the former (or so I am told, perhaps soil ecologists should not overextend themselves) Conclusions (and wider perspectives)