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

consumed

the 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

1Based 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

1Based 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/ Total cost Net return Benefit:Cost

strategy variety --- $ per ha --- ratio

Better Beans New Rosecoco 448 504 2.13

IR maize FRC 425 364 1482 5.07

N2A Package Soy cv Squire 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

consumedanimal

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

consumedanimal

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)