Using genotype and feeding regime to analyse smallholder dairy systems

Using genotype and feeding regime to analyse smallholder

dairy systems

Using genotype and feeding regime to analyse smallholder

dairy systems

Mizeck Chagunda

Scottish Agricultural College (SAC)Edinburgh

Addis Ababa, Ethiopia, October 25-28 , 2010

• Co-authors– Victor Kasulo: Mzuzu University, Malawi– Susan Chikagwa-Malunga: Lunyangwa Agricultural

Research Station, Malawi – Dave Roberts: SAC Dairy Research Centre, Scotland

• Acknowledgements– DelPHE British Council– Scottish Government

OutlineOutline

• Smallholder dairy in Malawi• Importance of smallholder dairying• Rationale• Data and Analysis• Discussion and Conclusions

Milk Production in Malawi

Smallholder FarmersHFxMZ

4 Cows

Large-scale FarmsHF60

Dairy Processor9,000 t/yr

Consumer(Including Home

Consumption)

Informal Market

Formal market

60%

Smallholder Dairy in Malawi

Milk Bulking GroupsMilk Bulking Groups

Importance of Smallholder Importance of Smallholder

•Income

•Food security

•Employment

•Business catalyst

Milk Consumption

      Average milk consumption = 4.5 – 6.0 kg/capita

      Africa = 15 kg/capita       Recommended (FAO) = 200 kg per capita

Breeds and BreedingBreeds and Breeding

HF Jrsy AyrsMZebu

Pure

7/8s3/4r

1/2N/A

0

20

40

60

80

100

120

140

160

Pure 7/8s 3/4r 1/2 N/A

FeedingFeeding

Fodder Percentage

Crop residues 49

Standing Hay 20

Fodder banks 20

Silage 11

Supplementaion• Maize bran• Dairy mash• Mineral

RationaleRationale

• Input- output driven classification– Assumes predetermined level

• Land holding size– Input driven

• Formal vs informal– Product driven

Biologically driven

40

50

60

70

80

90

100

Malawi Zebu 1/2FriesianXMalawiZebu

3/4FriesianXMalawiZebu

Pure HolsteinFriesian

Genotype

Pe

rfo

rma

nce

as

% o

f m

axi

mu

m

Productivity index Average test day milk yield

Revesai and Chagunda 2003

Productivity inefficiency

Breeding inefficiencyBreeding inefficiency

0

200

400

600

800

1000

1200

1400

2004 2005 2006 2007

Year

AI

Cows on heat Cows inseminated

Chindime, 2007

Central and Northern Malawi

Aim of Current StudyAim of Current Study

• To explore the application of a biologically-oriented approach to classify smallholder dairy systems

• Using major drivers of dairy production, genotype and feeding regime.

The studyThe study

• Based on a survey

• Northern Malawi

• April 2009

• n = 654 cows from 284 farms 40% of households

• Detail in Kasulo et al. (2010)

Data AnalysisData Analysis

• 4 production systems– upgrade on stall feeding system (UGS)– upgrade on grazing system (UGG)– base genetics on stall feeding system (BGS)– base genetics on grazing system (BGG)

• Production levels were reflected using milk yield (MY) and calving interval (CI).

ResultsResults

0

10

20

30

40

50

60

1-3kg 4-6kg 7-9kg 10-12kg 13-15kg 16-18kg 19-21kg 22-24gk 28-30kg

Milk yield per cow (kg)

Fre

qu

ency

During study

•Of the Holstein Friesian, Jersey and Aryshire , 48% dry

•Malawi Zebu, 59% dry.

Results: Milk YieldResults: Milk Yield

0

1

2

3

4

5

UGS UGG BGS BGG

Dairy System

Rank

ing

Ranking MY Expected ranking MY

Results: Calving IntervalResults: Calving Interval

0

1

2

3

4

5

UGS UGG BGS BGG

Production System

Rank

ing

Ranking CI Expected ranking CI

ConclusionConclusion

• The biologically-oriented approach to classify smallholder dairy systems has the potential to categorise smallholder farms in a meaningful way.

• The approach offers an opportunity to study long-term specific effects and a wide range of management strategies for smallholder dairy farming.