Frédéric Baudron (CIMMYT), Asheber Tegegn (EIAR)

SIMLESA Phase-2 planning meeting, 23-25 September 2014

Livestock in CA-based Systems of Ethiopia:

Threat or Opportunity?

Is a technology that excludes livestock

likely to be adopted in Ethiopia?

● Highest density of livestock in Africa

53.4 million cattle and 48.3 million sheep & goats in

‘sedendary areas’ (CSA, 2011)

● Importance of animal products

659,000 t of meat, 4.1 million t of milk (FAOSTAT, 2012)

● Importance of non-productive functions

Cycling of nutrients through manure

Provision of traction

Multiplication of inflation-proof saving assets

Insurance in times of hardship

Display of status

● Producing fodder is often an objective of maize

cropping

Thinning, weeds, green maize, dry stover, etc

Challenges of (low-input) CA-based

technologies

● Weeds

Should we depend totally on herbicides when our

target is resource-constrained smallholders?

● N management

N immobilization (retention of residues with a

wide C:N ratio)

N leaching (increased drainage)

Reduced SOM mineralization (reduced tillage)

● Limited biomass for mulching and lack of

incentive to produce biomass with no

direct economic value

Herbivores and weed control

(from Hatfield et al., 2007)

Herbivory retards succession in fertile

ecosystems (Augustine and McNaughton 1998)

Herbivory

Fire

Tillage

Agroecosystems are maintained in an

early succession stage through

‘disturbances’ (Martin & Sauerborn, 2013)

More pernennial weeds

CA: minimum disturbance regime…

(from Tittonell et al., 2010)

Herbivores and mineral N

Enhancing soil fertility build-up by

grazing pasture phases

(from Franzluebbers and Stuedemann, 2009)

Enhancing soil fertility build-up by

grazing pasture phases

Enhancing soil fertility build-up by

grazing pasture phases

Enhancing soil fertility build-up by

grazing pasture phases

Positive effect of herbivory on plant

productivity most common in productive

ecosystems (e.g. natural grasslands)

Bristish Isles (Bardgett et al., 1998)Serengeti (McNaughton et al., 1997)

Yellowstone (Frank and Groffman, 1998)

Grazing area in Southern

Ethiopia (‘grazing lawn’)

(from Bardgett et al., 1998)

Forage: species that respond positively

to grazing (by definition)

Integrating forage in existing cropping

systems

Intercropping / Relay cropping Perennial structures

Bofa, early May

J F J J A S O N DM A M

Rf

(mm

)

Early Sowing

Flw

GF PM

Using the Belg season for pasture in the

South

(from Hassen, 2014)

Means for the past ~30 years

Melkassa: 164 mm

Adami Tullu: 195 mm

Shalla: 297 mm

H2ODifferent functional

groups:

• Grass

• Legumes

• Brassicacea

• Compositae

• etc

Seed = the cheapest

herbicide

Often grazed

Including perennial forages for greater

sustainability

(Cox et al., 2006)

● Permanent soil cover

Erosion control

● Long photosynthetic period

High light use efficiency,

● Well-developed and deep root system

that

Carbon storage

Water and nutrients capture efficiency

Different benefits to CA

Sharing biomass between livestock and

soil: how much surface mulch is required?

(from Giller et al., 2009)

Potential negative effects of mulching:• N immobilization

• Water-logging

• Rainwater interception and evaporation

• Water loss through capilarity

(from Baudron et al., 2014)

Kakamega, long rains

Kakamega, short rains

Melkassa

Sharing biomass between livestock and

soil: feed formulation

CHARACTERISTICS REQUIREMENTS (MJ/d)

Liveweight (kg) 300Maintenance and change in body

condition35.7

Pregnancy stage (month) 5 Pregnancy 3.1

Lactation (L) 10 Lactation 57.7

Protein (%) 3.5 TOTAL 96.4

Fat (%) 4.5

Lactation phase (early: 3; mid: 2; late: 1; dry: 0) 3 Estimated intake (% liveweight DM/d) 3.0

Expected change in body condition (-1; 0; +1) 0

Ingredients

Crop residue dry Crop residues green Grass forage Legume forage Trees & Shrubs Concentrates

Bean r

esid

ues

Cow

pea h

ay

Gro

undn

ut

haulm

Maiz

e s

tove

r

Oat

resid

ues

Sorg

hum

resid

ues

Soyb

ean r

esid

ues

Ric

e s

traw

Teff

str

aw

Wheat

str

aw

Cassava l

eaves

Cow

pea f

odder

Ensete

Maiz

e g

reen

Oat

fora

ge

Sw

eet

pota

toe

vines

Sugar

cane t

ops

Buff

el gra

ss

Gam

ba g

rass

Napie

r

Rhodes

Butterf

ly p

ea

Desm

odiu

m

Labla

b

Macro

ptiliu

m

Sty

losanth

es

Vetc

h

Calli

an

dra

youn

g

Calli

an

dra

matu

re

Faid

herb

ia l

eaves

Glir

icid

ia

Leucaen

a y

oun

g

Leucaen

a m

atu

re

Pig

eon p

ea

Sesbania

youn

g

Sesbania

matu

re

Cotton s

eed c

ake

Gro

undn

ut

cake

Sunflow

er

cake

Poultry

litte

r

Maiz

e g

rain

TOTAL Min Max

DM % 90.0 90.0 90.0 90.0 90.0 90.0 90.0 90.0 90.0 90.0 60.0 60.0 60.0 60.0 60.0 60.0 60.0 90.0 90.0 60.0 90.0 60.0 60.0 90.0 60.0 70.0 60.0 60.0 60.0 60.0 60.0 60.0 70.0 60.0 60.0 70.0 90.0 90.0 90.0 90.0 90.0 90.0 50.0 100.0

ME MJ/kg 7.5 8.8 10.5 8.4 9.6 8.4 9.6 8.4 8.4 8.4 10.0 9.2 8.4 9.2 10.5 12.1 12.6 8.4 8.4 8.8 8.4 7.9 8.4 9.2 7.5 9.2 8.8 9.2 8.8 9.6 8.4 7.9 9.6 9.2 9.2 10.5 2.5 3.0 2.2 1.9 2.8 6.6 10.7 11.8

CP % 6.8 14.5 16.3 4.2 7.7 4.7 8.5 2.2 4.1 4.4 19.9 28.9 13.6 5.2 8.3 15.9 10.2 9.9 6.2 6.7 7.1 15.2 15.3 17.1 14.9 7.7 22.4 24.2 14.6 19.9 21.6 21.6 23.6 25.7 18.8 21.0 40.5 49.0 25.9 17.8 12.4 18.9 16.0 18.0

NDF % 64.2 49.2 38.4 75.4 58.3 73.6 63.0 74.4 76.9 74.4 32.1 27.2 63.6 53.5 54.6 43.1 72.2 67.1 70.7 76.1 70.2 40.0 51.4 39.4 58.4 64.5 39.4 48.7 38.1 36.5 52.9 35.0 38.6 54.0 38.1 31.3 38.4 16.4 35.5 55.9 55.1 56.0 30.0 80.0

Min 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Max 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100

Composition

(%) 0.0 0.0 0.0 67.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 32.9 0.0 0.0 0.0 100.0 100.0 100.0

Price(KSH/kg) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 30.0 40.0 25.0 15.0 30.0 45.0 5.0 30.0 30.0 45.0 50.0 45.0 50.0 45.0 32.0 40.0 60.0 80.0 60.0 55.0 80.0 85.0 70.0 90.0 83.0 85.0 50.0 50.0 50.0 20.0 30.0 0.0

Quantity (kg/d) 0.0 0.0 0.0 10.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.3 0.0 0.0 0.0 16.2

RATION

DM kg 14.6

Maximum intake of this ration (kg

DM/d) 7.0

ME MJ 96.4

CP kg 2.8

Water requirements

(L/d) 118.4

NDF kg 8.2

Designed by Oriama Okitoi (KARI-Kakamega) & Frédéric Baudron (CIMMYT-Addis Ababa)

…etc…

Set of available ingredients characterized by their ME, CP, NDP and $

Characteristics

of the cow(weight, pregnacy

stage, etc)

+

production

objective

0

5

10

15

20

25

30

20 70

Ma

xim

um

in

tak

e (

kg

DM

)

Fiber content (% NDF)

100200300400500

0

5

10

15

20

25

0 5 10M

E (

MJ/d

)

Month pregnancy

One proposition of experiment

CONTROL

0% 33% 67% 100%

Trampling

(muzzled

animals)

Cut-and-carry,

application of

manure and refusals

In situ grazing

No animals

Summer: CA Maize relayed with a forage

Winter: 8 different treatments

Measurement: Total productivity, SOM, SON, weed abundance and diversity, pest

incidence, BD, etc

THANK YOU