Issues and challenges in improving dairy genetics for smallholders Badi Besbes, Animal Production and Health Division, FAO

Content • Setting the scene: few figures on dairy genetics • Characteristics of Small-Holder Dairy Production System (SHDPS), in d’ing countries • Bovine Genetic Resources encountered (BoGR) in SHDPS, in d’ing countries • Genetic Improvement Practices and Programmes • Requirements for success • Concluding remarks

Milk production (million tonnes) in 1980 and 2007 1980

2007

Developed countries

350.6

357.8

Developing countries

114.9

313.5

(FAO, SOFA 2009)

Growth in production: animal numbers and yields (1980-2007) 10.0

Average annual growth (%)

8.0

6.0

4.0

2.0

0.0

Numbers

Yield

Pig

Numbers

Yield

Numbers

Poultry

Yield

Cattle

Numbers

Yield

Milk

Numbers

Yield

Eggs

-2.0

East and Southeast Asia

Latin America and the Caribbean

South Asia

Near East and North Africa

Sub-Saharan Africa

FAO, SOFA 2009

Characteristics of SDPS, in d’ng countries •

Majority of milk comes from SDPS

•

Low-medium input mixed systems (livestock integrated with subsistence/cash crop)

•

Milk for sale as main output, but also wide range of non production services (asset accumulation and insurance, nutrient recycling and fuel (manure), traction)

• •

Small herd size: 2/3 cows mostly crossbred, but also n.d. local, no breeding bulls Major constrains: – – – –

poor nutrition and management disease problems; e.g. ECF, FMD limited access to market, goods and services weak institutions

Bovine genetic resources in devl’ng countries •

Mainly local or indigenous breeds

local

– Multiple functions

regional transboundary

– Well adapted, resistant (e.g. trypanotolerant cattle)

International transboundary

– Not well characterized – Not very productive

 replaced by ‘superior’ exotic breeds and their crossbreds

Production Antagonism Adaptation / Fitness

 Advanced characterization studies to help decision making E.g. Study in East Africa (B&MGF)

Genetic improvement practices and programs •

Crossbreeding – Indiscriminant crossbreeding through semen import – ‘Structured’ crossbreeding or upgrading programs – Creation ‘non controlled’ of crossbred population

•

Straightbreeding – Classical selection scheme – Genomic selection – Reducing costs of performance recording

Indiscriminant crossbreeding through semen import • Reasons of germplasm import – (bilateral) cooperation projects – Development projects funded and implemented by NGOs – Political decisions  No prior studies of the production systems of the target beneficiaries nor the type of germplasm required

• Choice of breeds & bulls – Influenced by the donor, persuasion of salesman and price – Technical criteria, if any, based on milk production index – Lack of awareness of fitness index, tests for genetic defects?

• No E&M due to absence of AI&PR system

‘Structured’ crossbreeding or upgrading programs • Continuous crossbreeding process has been difficult to sustain – Kenyan smallholder dairy system, based on crossbred (European breeds x zebu). Limited supply of replacement heifers (F1)

• Creation of composite breeds or ‘upgrading’ using exotic bulls is most common approach – Mpwapwa composite cattle breed in Tanzania (Tanganyika Zebu cows x variety of bulls (Red Sindhi, Sahiwal, Ayrshire, Jersey, Boran). Today, kept only in government station (300 animals) – Sunandini cattle breed in India, developed by ISPK now named KLDB. Local non descript cows crossed with Brown Swiss bulls. Later Jersey, American Brown Swiss and Holstein bulls used – Import of a low number of bulls and use for many years, leading likely to inbreeding

• Creation ‘non controlled’ of crossbred population between 1/2 and 3/4 Holstein by use of local bulls which are crossbred Emerging category (E.g. India)

Classical selection scheme - progeny test X Bull sire year n

Bull dam

Progeny test year n+2 young male calf

service

X

year n+6 year n+5

Selection on EBV

Genetic evaluation

daughters with 1 lactation

daughters born

Classical selection scheme - progeny test • Slow ! • Requires performance recording  expensive !

• Efficient, only if high selection intensity • if selection only on production, degradation of fitness !

54,000 markers !

Alternative: genomic selection

X Bull sire year n

service year n+2

Bull dam

young male calf

Genomic evaluation

Genomic selection • Generation interval divided by 2 • Genetic gain x 2 • Still need performance recording ! • Need a ‘Reference Population’ to estimate the effect of each allele (segment of chromosome) of each marker (SNP)  Large RP for indigenous breeds

How to decrease cost of performance recording? • Major cost: milk recording technicians  motivate farmers to record production themselves  use less demanding milk recording protocol e.g., one milk recording once every two months  particular case of very small herds: • rely on AI technicians • collect production of the cow(s) at the time of AI or PD or any other visit to the farm

Simpler milk recording protocols Drying date

Calving date

A2 A8 « via AI » AI

AI

PD

AI of another cow

How to decrease cost of performance recording? • To make it more efficient: directly enter the data in computer + collect other information at the same time: •

fertility (AI done, pregnancy diagnosis)

•

previous calving date (and progeny identification), calving ease

•

phenotypic characteristics of the cow or the progeny

•

any health related event

Data collection: take advantage of new technologyg • Record on smartphones with specialized software

• to avoid typing /consistency errors: use drop-down menus

Requirements for success • Policy environment providing space to operate • Farmer involvement from the start • Continuous learning and adaptation of intervention • Institutional arrangements for sustainability • Right genotypes for the target environment • Available markets as pull • Capacity and technology to deliver across all levels of system • Championing teams – passionate and perseverant

Concluding Remarks • Almost every country has had a livestock breeding program of one form or another; performance of these programs has been variable, but very few have been successful over long term • In most cases, scaling up ‘tipping point thresholds’ has not been achieved • The system and infrastructure for disseminating superior germplasm were generally missing • Institutional issues have been at the centre of failures of programs • Modern technology offers a panel of new tools to make possible sustainable selection of local breeds through more cost efficient performance recording, broader progeny testing and genomic selection

Thank you

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