Assessment of Feed Intervention in Lemu Bilbilo District, Arsi Highlands, Ethiopia

by

M. Yami, T. T.haimanot, E. Lemma, B. Begna and T. EtanaKulumsa Agricultural Research Center

EIAR

Africa-RISING Quick Feed Project Synthesis Workshop, Addis Ababa, 3-4 September 2012

2

Site Description

A survey was conducted in Lemu- Bilibilo district, located in Arsi zone, Oromia Regional State of Ethiopia.

Lemu-Bilbilo district is located about 235 km South - East of the capital Addis Ababa on the highway towards Bale zone

The area receives an annual rainfall of around 1100mm, of which more than 85% is during the main rainy season (June to November).

And the average annual temperature ranges from 6 to 26C.

3

Criteria for Site Selection

Lemu-Bilbilo was purposively selected based on its dairy

potential in consultation with District Agricultural Experts

Bekoji Negesso kebele was selected from 27 kebeles in the

district based on:

accessibility

dairy production potential

4

FEAST

Objectives

To gain an understanding of the overall farming and livestock production systems, and

To identify key areas of the feeding strategy that could improve livestock productivity

Characterization of the Farming and Livestock Production Systems and the Potential of Feed-based Interventions for

Enhancing Productivity through Improved Feeding in Lemu-Bilbilo District, Arsi Highlands, Ethiopia

5

Three villages (Cheffa, Mirti laman and Tulu-Negeso) were randomly selected from the Bekoji Negeso PA

A total of 36 farmers were purposively selected on the basis of SLF

results from the villages

And the selected farmers were categorized into three groups; above average, average and below average.

Then, 9 farmers each from the above average and 9 the below average were selected for individual interviews using semi-structured questionnaires.

Methodology

Overview of the farming system Contribution of household income

(a) (b)

Cash

crop

Food

cro

p

Dairin

g

Fatte

ning

of s

heep

and

goa

t

Fatte

ning

of c

attle

Poul

try (E

gg)

0

5

10

15

20

25

30

35

40

perc

enta

ge o

f in

com

e c

ontr

ibuti

ons

Cash

crop

Food

cro

p

Dairin

g

Fatte

ning

of s

heep

and

goa

t

Fatte

ning

of c

attle

Poul

try (E

gg a

nd m

eat)

Remitt

ance

Offarm

inco

me

Non-fa

rm in

com

e

Sale

s of

equ

ilapt

us tr

ee0

5

10

15

20

25

30

35

40

Perc

enta

ge o

f in

com

e c

ontr

ibuti

ons

Livestock production system

(a) (b)

Fattening and

draught cattle

Local Dairy Cattle

Improved Dairy cattle

Horse Sheep0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

Fattening and

draught cattle

Improved Dairy cattle

Horse Sheep Local Dairy Cattle

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

Feeds and feeding: Seasonality (a) Both roups

Janu

ary

Febr

uary

March

April

May

June

July

Augus

t

Sept

embe

r

Octob

er

Novem

ber

Decem

ber

0

10

20

30

40

50

60

70

80

0

1

2

3

4

5

6

Concentrates Crop residues Grazing

Green forage Legume residues Others

Rainfall Pattern

Availablity

a. Above averagesb. Below averages

Crop residues

25%

Cultivated fodder12%

Grazing48%

Naturally occurring and col-lected

9%

Purchased5%

Crop residues

23%

Cultivated fodder12%

Grazing33%

Naturally occurring and col-lected12%

Purchased20%

Feeds Quality – Dry Matter

Feeds Quality – Metaboilze Energy

a. Above averages b. Below averages

Crop residues

20%

Culti-vated fodder14%

Grazing49%

Naturally occur-

ring and collected

10%

Purchased7%

Crop residues

17%Cultivated

fodder14%

Grazing32%Naturally

occurring and col-lected13%

Purchased24%

Feeds Quality – Crude Protein

a. Above averages b. Below averages

Crop residues15%

Cultivated fodder17%

Grazing42%

Naturally occurring and col-lected10% Purchased

16%

Crop residues12%

Cultivated fodder15%

Grazing25%

Naturally occurring and col-lected13%

Purchased35%

12

Problems and constraints

Problems in order of importance Problem identified by farmers

in both groupsProposed solution by farmers in both groups

1 Feed shortage Improved forage development and decrease livestock number

2 Lack of water Natural water resource development and installation of tap water

3 Lack of credit/cash Increase accessibility to credit service

4 Shortage of VET. and AI. service Training of farmers in AI service and increase number of vet. Technicians.

5 Awareness and communication gap (in below average group only)

Frequent capacity building training on general welfares of livelihood, create close communication habit with livestock production experts through training

Opportunities

• Opportunities that contribute to the improvement of the sector do exist in the area. These opportunities are:

Accessibility of all-weather road in the district as well to the PA

Good agro-ecology with favorable climate The emphasis given to livestock production by the

government The existence of high demand for livestock products due to

population pressure The possibility to obtain more benefits on smaller plots of

land

Areas of intervention 

o Awareness creation trainings on: the utilization of improved technologies (improved forages

and feeding techniques) particularly to the farmers in the below average group.

how to get credit, about the repayment periods and amount of credit offered.

o Accessessing the farmers with credit or cash with reasonable amount or loan repayment periods

o Assigning numbers of well-trained effective AI and Vet technicians at the reasonable sites in the district.

o Development of herbaceous forage legumes and fodder trees species which can mitigate the constraints of feed scarcity.

15

Techfit

Prioritization of Feed Technologies using TechFit

Background Shortage and poor quality of feed is the major constraint.

National and international research programs in the past have generated a range of improved forage and feed technologies.

One of the reasons for lack of adoption could be absence of

means of selecting feed technologies fit to a specific location.

Objective: To rank and prioritize suitable feed technologies for Bekoji Negeso kebele of Lemu-Bilbilo Wereda using tech fit.

Methodology

Pre-filter of technologies • context relevance and impact potential scores (to

screen technologies that are not fit to the area. Main filter of technologies – Based on

• Technology attributes scores (1-5) by experts.• Context attributes scores (1-5) by farmers.• Scope for improvement

Cost benefit analysis Comparison of estimated cost and benefit of

each technology based on assumption.

Result and Discussions

Pre-filter of technologies

Based on impact potential and context relevance from 48 technology options the major 12 technologies were dropped regarding their relevance to the study area.

Reason for technology dropping:-

Unavailability of the technology to the area.

less adaptable to the area.

unaffordable to small scale farmers Main filter technologies

Among them supplement with home produce local breweries, feeding of home grown legumes, use of weed cut grass and tree leaf, refreshing and mixing of CRs before storage and feeding were accordingly favored by the tool and got higher rank as compared to other technologies.

These technologies were further subjected for cost benefit analysis.

Feed technologies selected using the Tech Fit tool

Total score

RankList of feed technologies Remarks

49 1 home produce local breweries Mostly used by home made alcohols producers

49 1 . feeding of home grown legumesCommon to the area

45 3 . use of weed cut grass and tree leafMainly practiced during crop growing period

43 4 Re-threshing and mixing of crop residues before storage and feeding

easily applicable without demand for resources

Benefit cost analysis of the best bet technologies/cow/day in Ethiopian Birr at Bekoji Negesso Kebele

Technolo

gy

rank Feed technologies

Total

cost

Gross

benefit

Net

benefit BCR

1

Home produce local breweries

3.00 4.55 1.50 0.50

2

Feeding of home grown legumes 2.00 2.60 0.60 0.30

3

Use of weed cut grass and tree leaf

3.50 5.20 1.70 0.48

3

Re-threshing and mixing of crop residues before storage and feeding 2.40 3.25 .85 0.35

cont.

The result showed that technology which stood first Home produce local brewerieswas found economically best profitable by giving economical advantage of 0.50 CBR while Feeding of home grown legumes stood least by 0.30 CBR

Challenges/Limitations

Estimation of cost benefit analysis of the best bet technologies was based on assumption.

The feed technology options were more dependent on availability of attributes regardless of potential to the area.

Lessons learned

Generate ideas for feed interventions depending on the existing farming system

It was helpful to guide thinking and ensuring that the suggestions for feed improvement take into account system constraints such as land, labor, credit and input delivery

The tool tries to match context scores like availability of land, labor, etc. with list of candidates of feed technologies to come up with short list of promising options.

Tech fit helps to guide thinking of researchers and development workers on feed technology prioritization.

VCA

Assessment of Dairy Value Chain in Arsi Highlands :The Case of Lemu-Bilbilo District

 

The main objective of the study was to undertake an assessment of the dairy value chain actors of the study area.

The following specific objectives of the study are:

Carrying out analysis of the commercial viability of smallholder dairy farming and margin analysis for different milk marketing channels;

To Identify the key constraints and opportunities of milk and milk

products marketing;

To propose simple and practical intervention areas, which helps to facilitate milk and milk products marketing that brings sustainable change.

Methods of data collection and data sources

Value Chain Analysis approach (VCA) was used. Review of literature Secondary data from different sources, Primary data collected using focused group discussion , key informants & personal

observations. 41 farmers from three villages were used for FGD Discussed with Experts in Livestock Agency, Cooperatives promotion office, Vet

drug vendors , Trade promotion office, KII with cooperatives, cheese & butter traders, milk collectors & processor.

Results of Dairy Value Chain Analysis

Figure 1: The core functions, actors and activities in the dairy value chain

Private traders Cooperatives Smallholder farmers Credit &saving

institutions Developmental

organizations (NGOs) Livestock health and

extension agency Kulumsa Research

Centre

Smallholder farmers (both members and non members of dairy cooperatives)

Cooperatives Private

processors (traders)

Cooperatives Private

traders Individual

farmers

Cooperatives Traders

Hotels Cafeteria

Individual consumers

Availing inputs like

concentrate feeds, seeds of improved forage crops, AI services, provision of credit, training on handling, processing &feed formulation techniques, veterinary services

Rearing livestock

Feeding Breeding Milking and

milk handling Animal disease

control

Buying Bulking Transporting Selling

Quality testing Bulking

Processing

Collection Transportat

ion Exchange

Consumptions

Input supply

Production

Marketing

Processing

Skimmed milk Marketing

(Skimmed milk)

Consumption

Activities

Actors

Figure 2: Raw and skimmed milk marketing routes

100% (Sour milk)

20% (Raw)

80% (Raw) 25% (Skimmed milk)

75% (Skimmed milk)

Production

Assasa

consumer

Local market (Bekoji market)

Adama

Assela

Figure 3 : Butter marketing routes

7%

7%

10%

30%

30

10% 35%

7%

1%

Addis

Ababa

Production (study area)

Local

market Assasa

Shashemene

Hawassa

Assela

Adama

Figure 3: Cheese marketing route

5%

1%

1%

75%

10%

3%

Meki

Production

Adama Mojjo

Addis Ababa

Shashemene

Awassa

Alaba

Marketing channels

Figure 4: Dairy marketing channels  

o

15%

Smallholder dairy producers

(Marketed only 15 of their raw milk)

Individual Consumers

Consumption

Production

Dembela Private Processor

7%

71% 7%

Feeds supply AI & Veterinary services

Credit provision

Market information

Research and Development Partners (R&D)

Arsi Bureau of Agriculture and Rural Development

Kulumsa Agricultural Research Center

FAO and ACID/VOCA

FAO

Cooperatives

Traders Raw milk marketing

Processing

Input Supply/Support services

Extension advice

Hotels and Cafeteria

Quality control Enabling Environment

Market rules and regulations

License

provision

Legal support in drawings MoU

Three main market channels for raw milk produced in Limu-Bilbilo district with which it reaches to final consumers.

The final consumers’ in the study area is pre-urban and urban individual consumers, hotels and cafeterias.

Channel 1- Milk consumed by pre-urban individual consumers in the study area

Channel 2 – Milk consumed by Urban Individual consumers in the study area

Channel 3 – Milk consumed by Hotels and cafeteria

Margins and Value addition

Raw milk Channel Marketing margin

Net margin Share of value added (%)

Producers' share of final

price (%)

1. Pre-urban consumers 1.80 1.77 56.5 78

2. Urban individual consumers

3.10 2 49 55

3. Hotels/cafeterias 8.50 5.50 83 43

Major constraints

Constraints at Input supply Stage Inadequate availability and skills of AI technicians

Low quality and poor timeliness of AI and animal health service Information gap on credit services Unavailability of demonstration sites on improved forage production in Farmers

Training Centers (FTC) Absence of bull and heifers distribution centers

Production stage Feed shortage Very high price of industrial by - products Lack of knowledge regarding improved feed formulation Non market oriented production

Processing and marketing Stage Insufficient capacity of processing machines Lack of cooling facilities

Legal and Institutional Constraints

Weak coordination between union, primary cooperatives and farmers Existence of too many unlicensed traders No vertical linkage b/n cooperatives and others

Market infrastructure Sanitation Problem of milk products

Support service providers

Capacity gap among extension agents and agricultural experts in provision of training on feed formulation techniques

Prioritized constraints

1. Feed shortage2. Low quality and poor timeliness of AI and animal health service 3. Inadequate availability and skills of AI technicians4. Lack of knowledge regarding improved feed formulation5. Information gap on credit services

Opportunities available

Recently connected to major urban centers with good asphalt roads.

Favorable climate and weather conditions with relatively abundant pasture land for expanding the smallholder dairy productions.

Availability of progressive farmers who have adopted the practice of keeping improved dairy cows.

Conclusions

Demand for milk & milk products increases with the increase in population urbanization, and recent connections of the area with good asphalt roads.

However, milk supply is below the expected level and could not able to meet this growing demands due to;

Shortage of feed High price of industrial –by products Low genetic make up of available animals Inadequate & inefficient AI services Absence of institutions in the supply of improved bull and

heifers Lack of knowledge regarding improved feed formulation Information gap on credit services

Recommendations

Encourage the development of improved forage. Trainings on improved forage developments and feed conservations in the form of

hay or silage.

Trainings of farmers on improved feed formulation techniques

Improve AI service

In-service training of local service providers:

To enhance the technical skills and knowledge of AI technicians’ short term trainings and refresher courses on relevant areas of dairy management will be the right direction.

Training on community bull selections

Training of farmers on AI services, especially heat detections and reporting

Create regular stakeholder forum

This initiative will enable them to discuss common problems, find solutions to them and strengthens networking between dairy value chain players.

Sensitization training on credit service terms and condition

Micro-finance institutions need to create a platform for organizing training in credit service terms and condition for both dairy producer farmers and dairy cooperatives.

Thank You