Study of Smallholder Farms Livestock Feed Sourcing and Feeding

Strategies and Their Implication on Livestock water productivity

in Mixed-crop Livestock Systems in the Highlands of the Blue Nile

Basin, Ethiopia

MSc thesis in Agriculture (Range Ecology and Management)

Haramaya University

Bedasa Eba

October 2012

Introduction

Ethiopian Highlands (BNB) highly populated by people and livestock and this leads to:Degradation of natural resources Water competition among different uses and users

BNB share similar problem that rain water lost as:Unproductive run off, evaporative losses, and high volume

of water required for livestock production (Descheemaeker et.al, 2010)

Introduction cont’d

• Significant volumes of water withdrawn for production of feed (Steinfeld et al., 2006); affected by

• Presence of overgrazing • Ways feed is produced and supplied to the animal • Dry matter (DM) productivity and feed quality• Contact between livestock and the environment• Temporal and spatial availability of feed and water resources

Introduction cont’d

Water productivity in agriculture highlights livestock as a key area

for water productivity improvement (Molden, 2007), through;

The feed that livestock consume (Tilahun et al., 2009)

Understanding the interactions between livestock and water is an

important avenue in improving LWP

Introduction cont’d

• So, understanding the farming systems’ and landscape’ feed

sourcing and feeding strategies in the Highlands of BNB, leads

to;

• Generating baseline information in this area and link to LWP

• Serve as a reference point to explore different water efficient

feed sourcing and feeding practices.

Objectives

• To identify the different livestock feed sourcing and feeding strategies and their

dynamics across different landscapes and farm typologies in mixed crop

livestock systems of the BNB

• To assess the dry matter productivity and implications for feed demand-supply

and farmers coping mechanisms in time of feed shortage in mixed crop

livestock systems of the BNB

• To assess the effects of current feeding strategies on livestock water productivity

2. Materials and methods

Area description

Jeldu Woreda

Fogera Woreda

Diga Woreda

Dapo watershed Mizuwa watershed

Meja watershed

3.2. Stratification and Household Survey

• Multistage stratified sampling and 2 PA for each system• Also stratified by wealth categories (4-6 hh per clustered )

220 hh in BNB

67 hh in Diga 91 hh in Jeldu 62 hh in Fogera

35 hh in teff-millet

32 hh in maize-sorghum 31 hh in

Barley-potato

30 hh in teff-wheat

30 hh in teff-sorghum

32 hh in teff-millet

30 hh in rice-pulse

3.3. Livestock Water Productivity Estimation

• LWP as defined earlier, is based on the ratio of livestock

beneficial outputs and services to depleted water through

feed production

• LWPji = (MYVji+OTVji+TVOSji+TMVji)/DWLFji

Milk value Off

take value

Service value

Manure value

Water depleted to feed

3.4. Feed Resource Assessment

• Sampling of biomass from private grazing

land

• Harvest index approaches for dry matter production from crop

land,

• Annual DM for stubble grazing and communal grazing were

estimated by (FAO,1987).

3.5. Estimation of Water Depleted in Producing Livestock Feed

• New LocClim (FAO, 2005) used which can generate metrological

data for sites with known geographical positions.

• To calculate ET =(ETo) in mm day-1 and crop coefficient (Kc)

approaches (FAO, 1998) were used

• Using CROPWAT 8.0 software (FAO, 2003), ET estimated for each

crop types linked to growing length

• ETci= ETo*Kci*LGPij (general water depleted)

3.6. Estimation of Livestock Beneficial Outputs and Service

Livestock products and services data established based on

• livestock herd structure

• age composition, activities and

• productivity levels collected through the household

survey.

3.6. Beneficial output…..

• MYVji = (AMYji*NLCji*ALGji*MVi) (milk value)

• OTVji (off-take)

• (services)

3.8. Statistical Analysis

• Descriptive and inferential statistical tests were performed

separately for each of the study Woreda among their respective

farming systems.

• General Linear Model (GLM) procedure of SAS was employed to

separate mean significances (LSD, 5% level) between stratum

3. Results and Discussion

3.1. Landholding and livestock holding (TLU)

TMS MSS BPS TWS TSS TMMS RPSDiga Jeldu Fogera

0

1

2

3

4

5

6

7

8

9

10

Mean Landholding (ha)

Mean Livestock (in TLU)

Landholding (ha) and livestock (in TLU) variation among Jeldu systems

Lower landholding (ha) in Fogera systems

3.2. Variability of Feed Resources Availability and Ingredients

Across the Study Systems

• Major feed resources; crop residues (58.5% to 78.2%) and green grass from natural pasture

Variability of feed resources availability on sample farms perception and researchers’ estimate of DM

Divergence b/n two methods may imply;

• inconsistencies of information,

• Farmers loose decisions on CRs, and

• perceiving of time livestock are spending Diga Jeldu Fogera

0

10

20

30

40

50

60

70

80

Crop residues(%) as farmers perceptioncrop residues(%) on DM basisnatural pasture(%) as farmers perceptionNatural pasture(%) on DM basis

3.2.1. DM productivity and grass-legume composition on private grazing lands

• In Fogera as much as 10.8 ton/ha (Ashagre, 2008) from improved natural pasture.

• By closing yield gaps as high as 100% improvement in LWP is reported for mixed crop

livestock systems of India (Haileslassie et al., 2011).

TMS MSS BPS TWS TSS TMMS RPSDiga Jeldu Fogera

0

1

2

3

4

5

6

Grasses DM (t/ha)Legumes DM (t/ha)

DM

(to

n)

3.2.2. Variability of mean dry matter availability per sample farms

Woredas Farming

systems

  Parameters (ton/hh)

N CR N GL Total

Diga TMS 35 4.0±0.3b 35 1.7±0.1 5.7±0.3b

  MSS 32 7.3±0.4a 29 2.2±0.3 11.4±1.1a

  Mean 67 5.6±0.3 64 2.0±0.1 8.4±0.6Jeldu BPS 31 4.0±0.3b 27 1.7±0.2b 5.4±0.4b

  TWS 30 5.1±0.3a 30 2.9±0.3a 8.0±0.5a

  TSS 30 4.5±0.3ab 28 2.2±0.3ab 6.5±0.5b

  Mean 91 4.5±0.2 85 2.3±0.2 6.6±0.3Fogera TMMS 32 4.2±0.3b 31 2.6±0.2a 6.6±0.5

  RPS 30 6.5±0.5a 26 0.9±0.1b 7.3±0.6  Mean 62 5.3±0.3 57 1.8±0.2 7.0±0.4

• Variation of DM of crop residues

• Variation of DM of grazing land

• Higher DM in lower landscape position (quantity), but quality?

• Deficit of ME lays between 22.2% to 43.6% in all farming systems

3.2.3. Improved forages production practice and major constraints

• No practice improved forages production (>85%)

Reasons not practice improved forages production

• Diga= lack of awareness and seed

• Jeldu =lack of seed

• Fogera = shortage of land, lack of awareness

• No feed supplementation practice particularly with sources outside their

farm (e.g., bran, oil cake)

3.3. Feed Resources Management

• Lack of clearing invasive species,

and lack bylaw on communal

grazing for improvement

• Storages of crop residues better in

Jeldu and Fogera but lower Diga

• >74.2% not used chemical and/or

physical treatment on crop

residues

Sida schimperiana Asracantha longifolia

Jeldu

Fogera Manure usage as fertilizer; Diga = 96.05%, Jeldu = 56.16%, and Fogera = 44.83%

3.4. Feeding strategies

TMS MSS BPS TWS TSS TMMS RPSDiga Jeldu Fogera

0

20

40

60

80

100

120

Garzing of natural pastureTethering on natural pasturecrop residues of In situ graz-ing crop residues off situ feeding

% o

f res

pond

ents

Only tethering in Diga In situ grazing of crop residues

3.5. Water Depleted for Livestock Feed Production

TMS MSS BPS TWS TSS TMMS RPSDiga Jeldu Fogera

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Water depleted

Wat

er d

eple

ted

(m3

ha-1

)

Variation of water depleted observed in Diga and Fogera systems

3.6. Livestock Water Productivity

Woreda Farming systems

N LWP (US$ m-3)

Mean±SE Min Max

Diga TMS 35 0.19±0.02 0.001 0.48  MSS 32 0.16±0.02 0.021 0.38  Mean 67 0.17±0.01

Jeldu BPS 31 0.15±0.02 0.002 0.63  TWS 30 0.16±0.01 0.001 0.43  TSS 30 0.16±0.02 0.027 0.37  Mean 91 0.16±0.01

Fogera TMMS 32 0.18±0.01 0.07 0.35  RPS 30 0.15±0.02 0.01 0.30  Mean 62 0.16±0.01• No apparent difference between systems (beneficial output)

• Huge gap between minimum and maximum of LWP value

3.9. Livestock Water Productivity…

TMS MSS BPS TWS TSS TMMS RPS Diga Jeldu Fogera

0

0.05

0.1

0.15

0.2

0.25

0.3

Better off

Medium

Poor

Farming systems within each Woreda

LWP

(US$

-3)

• High LWP for better off

lower LWP for poor

4. Conclusion • In all of the study farming systems, crop residues constitute the major

ingredient of livestock diet and supplementary feeding with high value feed is

not commonly practiced and livestock feed scarcity is considerable. Hence;

• In view of this thesis generally improving water productivity of feed is major

entry points to improve LWP. Very high yield gap between the result of this

study and the results from on farm experiments (e.g., in Fogera) gives very

good insights as to how much water we can save by improving the biomass

yield from grazing areas

4. Conclusion…

• The LWP showed generally variation implying opportunities for

improvement. Future development efforts and policy option must

nurture these opportunities.

• The farm scale showed a very wide range between the resources

poor and better off farmers. Such big gap of LWP for farm

households operating in the same farming system suggests a

potential for improvements.

Thank you!!THANK YOU!