Implementation of dairy cattle breeding policy in

Ethiopia ndash some reflections on complementary strategies

Sipke Joost Hiemstra

13 April 2018 Addis Ethiopia

Centre for Genetic Resources the Netherlands (CGN)

My background ndash animal breeding

Director - Centre for Genetic Resources the Netherlands (CGN)

Plant Genetic Resources

Forest Genetic Resources

Animal Genetic Resources

FAO Global Strategy NationalCoordinator for Animal Genetic Resources

Chair of European Regional Focal Point (ERFP) European Network of National Coordinators

1 Identification characterization and selection of indigenous breeds for dairy production

2 Improving the genetic potential of indigenous animals through crossbreeding with exotic dairy breeds

3 Establishing dairy cattle production and multiplication centers

4 Import and export of dairy animal breeds shall be regulated

Ethiopia - Dairy cattle breeding policy and strategy

3

Which dairy animals and animal characteristics for which Ethiopian

production system - Breeding goal

Structure and implementation of breeding programs

Cross-breeding strategies

Improvement and maintenance of indigenous breeds

Taking advantage of novel approaches and technologies

Conclusions - pathways towards implementation of complementary

strategies

This presentation

4

Animal breeding

Very simple

Select the best animals

Usemate the best animals in further breeding

Disseminate the best

But maintain genetic diversity

What is best

The success of (Dutch) animal breeding programs

Breeding circle

7

Starting point

8

Ethiopia ndash range of climates and production systems

Altitude

Mean daily

temperature

Rainfall distribution

throughout the year

Feed availability

Farm management

Small scale farms

Mediumlarge scale

Breeding goal

Local circumstances and external factors

Market (consumers society)

Climate

Feed availability

Cost price

Which traits are really important in the next 10-15 years

Many options

Milk yield

Fertility

Heat tolerance

Economic models

Economic Value

0

5

10

15

20

25

30

0 10 20 30 40 50

Trait

Prof

it

1 unit

EVprofit function

Figure 81 The use of a profit function to derive economic values The economic value (EV) of a trait is the increase in profit that results from a

single unit increase of the trait value

Example Higher milk production per cow andor

improved longevity

Price in KES

Case 1

Price in KES

Case 2

Explanation andor assumptions

Heifer raising costs or investment to

purchase a heifer 300000 300000

To be calculated or estimated

Productive life in years 3 5 Just two cases in a common range

Depreciation per year 100000 60000

Margin of extra year longevity 0 +40000 Less costs means higher margin

Price in KESExplanation andor assumptions

Price per extra kg milk35

Milk price on market

Cost of extra feed

23

Feed costs of 30 KES per kg concentrates

065 kg concentrates needed for 10 kg of

milk extra

Margin of extra kg milk+12

For Kenya - J Zijlstra Wageningen Livestock Research

We donrsquot want this situation

Specialists and generalists

Well-controlledAverageHarsh amp dynamic

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

My background ndash animal breeding

Director - Centre for Genetic Resources the Netherlands (CGN)

Plant Genetic Resources

Forest Genetic Resources

Animal Genetic Resources

FAO Global Strategy NationalCoordinator for Animal Genetic Resources

Chair of European Regional Focal Point (ERFP) European Network of National Coordinators

1 Identification characterization and selection of indigenous breeds for dairy production

2 Improving the genetic potential of indigenous animals through crossbreeding with exotic dairy breeds

3 Establishing dairy cattle production and multiplication centers

4 Import and export of dairy animal breeds shall be regulated

Ethiopia - Dairy cattle breeding policy and strategy

3

Which dairy animals and animal characteristics for which Ethiopian

production system - Breeding goal

Structure and implementation of breeding programs

Cross-breeding strategies

Improvement and maintenance of indigenous breeds

Taking advantage of novel approaches and technologies

Conclusions - pathways towards implementation of complementary

strategies

This presentation

4

Animal breeding

Very simple

Select the best animals

Usemate the best animals in further breeding

Disseminate the best

But maintain genetic diversity

What is best

The success of (Dutch) animal breeding programs

Breeding circle

7

Starting point

8

Ethiopia ndash range of climates and production systems

Altitude

Mean daily

temperature

Rainfall distribution

throughout the year

Feed availability

Farm management

Small scale farms

Mediumlarge scale

Breeding goal

Local circumstances and external factors

Market (consumers society)

Climate

Feed availability

Cost price

Which traits are really important in the next 10-15 years

Many options

Milk yield

Fertility

Heat tolerance

Economic models

Economic Value

0

5

10

15

20

25

30

0 10 20 30 40 50

Trait

Prof

it

1 unit

EVprofit function

Figure 81 The use of a profit function to derive economic values The economic value (EV) of a trait is the increase in profit that results from a

single unit increase of the trait value

Example Higher milk production per cow andor

improved longevity

Price in KES

Case 1

Price in KES

Case 2

Explanation andor assumptions

Heifer raising costs or investment to

purchase a heifer 300000 300000

To be calculated or estimated

Productive life in years 3 5 Just two cases in a common range

Depreciation per year 100000 60000

Margin of extra year longevity 0 +40000 Less costs means higher margin

Price in KESExplanation andor assumptions

Price per extra kg milk35

Milk price on market

Cost of extra feed

23

Feed costs of 30 KES per kg concentrates

065 kg concentrates needed for 10 kg of

milk extra

Margin of extra kg milk+12

For Kenya - J Zijlstra Wageningen Livestock Research

We donrsquot want this situation

Specialists and generalists

Well-controlledAverageHarsh amp dynamic

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

1 Identification characterization and selection of indigenous breeds for dairy production

2 Improving the genetic potential of indigenous animals through crossbreeding with exotic dairy breeds

3 Establishing dairy cattle production and multiplication centers

4 Import and export of dairy animal breeds shall be regulated

Ethiopia - Dairy cattle breeding policy and strategy

3

Which dairy animals and animal characteristics for which Ethiopian

production system - Breeding goal

Structure and implementation of breeding programs

Cross-breeding strategies

Improvement and maintenance of indigenous breeds

Taking advantage of novel approaches and technologies

Conclusions - pathways towards implementation of complementary

strategies

This presentation

4

Animal breeding

Very simple

Select the best animals

Usemate the best animals in further breeding

Disseminate the best

But maintain genetic diversity

What is best

The success of (Dutch) animal breeding programs

Breeding circle

7

Starting point

8

Ethiopia ndash range of climates and production systems

Altitude

Mean daily

temperature

Rainfall distribution

throughout the year

Feed availability

Farm management

Small scale farms

Mediumlarge scale

Breeding goal

Local circumstances and external factors

Market (consumers society)

Climate

Feed availability

Cost price

Which traits are really important in the next 10-15 years

Many options

Milk yield

Fertility

Heat tolerance

Economic models

Economic Value

0

5

10

15

20

25

30

0 10 20 30 40 50

Trait

Prof

it

1 unit

EVprofit function

Figure 81 The use of a profit function to derive economic values The economic value (EV) of a trait is the increase in profit that results from a

single unit increase of the trait value

Example Higher milk production per cow andor

improved longevity

Price in KES

Case 1

Price in KES

Case 2

Explanation andor assumptions

Heifer raising costs or investment to

purchase a heifer 300000 300000

To be calculated or estimated

Productive life in years 3 5 Just two cases in a common range

Depreciation per year 100000 60000

Margin of extra year longevity 0 +40000 Less costs means higher margin

Price in KESExplanation andor assumptions

Price per extra kg milk35

Milk price on market

Cost of extra feed

23

Feed costs of 30 KES per kg concentrates

065 kg concentrates needed for 10 kg of

milk extra

Margin of extra kg milk+12

For Kenya - J Zijlstra Wageningen Livestock Research

We donrsquot want this situation

Specialists and generalists

Well-controlledAverageHarsh amp dynamic

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

Which dairy animals and animal characteristics for which Ethiopian

production system - Breeding goal

Structure and implementation of breeding programs

Cross-breeding strategies

Improvement and maintenance of indigenous breeds

Taking advantage of novel approaches and technologies

Conclusions - pathways towards implementation of complementary

strategies

This presentation

4

Animal breeding

Very simple

Select the best animals

Usemate the best animals in further breeding

Disseminate the best

But maintain genetic diversity

What is best

The success of (Dutch) animal breeding programs

Breeding circle

7

Starting point

8

Ethiopia ndash range of climates and production systems

Altitude

Mean daily

temperature

Rainfall distribution

throughout the year

Feed availability

Farm management

Small scale farms

Mediumlarge scale

Breeding goal

Local circumstances and external factors

Market (consumers society)

Climate

Feed availability

Cost price

Which traits are really important in the next 10-15 years

Many options

Milk yield

Fertility

Heat tolerance

Economic models

Economic Value

0

5

10

15

20

25

30

0 10 20 30 40 50

Trait

Prof

it

1 unit

EVprofit function

Figure 81 The use of a profit function to derive economic values The economic value (EV) of a trait is the increase in profit that results from a

single unit increase of the trait value

Example Higher milk production per cow andor

improved longevity

Price in KES

Case 1

Price in KES

Case 2

Explanation andor assumptions

Heifer raising costs or investment to

purchase a heifer 300000 300000

To be calculated or estimated

Productive life in years 3 5 Just two cases in a common range

Depreciation per year 100000 60000

Margin of extra year longevity 0 +40000 Less costs means higher margin

Price in KESExplanation andor assumptions

Price per extra kg milk35

Milk price on market

Cost of extra feed

23

Feed costs of 30 KES per kg concentrates

065 kg concentrates needed for 10 kg of

milk extra

Margin of extra kg milk+12

For Kenya - J Zijlstra Wageningen Livestock Research

We donrsquot want this situation

Specialists and generalists

Well-controlledAverageHarsh amp dynamic

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

Animal breeding

Very simple

Select the best animals

Usemate the best animals in further breeding

Disseminate the best

But maintain genetic diversity

What is best

The success of (Dutch) animal breeding programs

Breeding circle

7

Starting point

8

Ethiopia ndash range of climates and production systems

Altitude

Mean daily

temperature

Rainfall distribution

throughout the year

Feed availability

Farm management

Small scale farms

Mediumlarge scale

Breeding goal

Local circumstances and external factors

Market (consumers society)

Climate

Feed availability

Cost price

Which traits are really important in the next 10-15 years

Many options

Milk yield

Fertility

Heat tolerance

Economic models

Economic Value

0

5

10

15

20

25

30

0 10 20 30 40 50

Trait

Prof

it

1 unit

EVprofit function

Figure 81 The use of a profit function to derive economic values The economic value (EV) of a trait is the increase in profit that results from a

single unit increase of the trait value

Example Higher milk production per cow andor

improved longevity

Price in KES

Case 1

Price in KES

Case 2

Explanation andor assumptions

Heifer raising costs or investment to

purchase a heifer 300000 300000

To be calculated or estimated

Productive life in years 3 5 Just two cases in a common range

Depreciation per year 100000 60000

Margin of extra year longevity 0 +40000 Less costs means higher margin

Price in KESExplanation andor assumptions

Price per extra kg milk35

Milk price on market

Cost of extra feed

23

Feed costs of 30 KES per kg concentrates

065 kg concentrates needed for 10 kg of

milk extra

Margin of extra kg milk+12

For Kenya - J Zijlstra Wageningen Livestock Research

We donrsquot want this situation

Specialists and generalists

Well-controlledAverageHarsh amp dynamic

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

The success of (Dutch) animal breeding programs

Breeding circle

7

Starting point

8

Ethiopia ndash range of climates and production systems

Altitude

Mean daily

temperature

Rainfall distribution

throughout the year

Feed availability

Farm management

Small scale farms

Mediumlarge scale

Breeding goal

Local circumstances and external factors

Market (consumers society)

Climate

Feed availability

Cost price

Which traits are really important in the next 10-15 years

Many options

Milk yield

Fertility

Heat tolerance

Economic models

Economic Value

0

5

10

15

20

25

30

0 10 20 30 40 50

Trait

Prof

it

1 unit

EVprofit function

Figure 81 The use of a profit function to derive economic values The economic value (EV) of a trait is the increase in profit that results from a

single unit increase of the trait value

Example Higher milk production per cow andor

improved longevity

Price in KES

Case 1

Price in KES

Case 2

Explanation andor assumptions

Heifer raising costs or investment to

purchase a heifer 300000 300000

To be calculated or estimated

Productive life in years 3 5 Just two cases in a common range

Depreciation per year 100000 60000

Margin of extra year longevity 0 +40000 Less costs means higher margin

Price in KESExplanation andor assumptions

Price per extra kg milk35

Milk price on market

Cost of extra feed

23

Feed costs of 30 KES per kg concentrates

065 kg concentrates needed for 10 kg of

milk extra

Margin of extra kg milk+12

For Kenya - J Zijlstra Wageningen Livestock Research

We donrsquot want this situation

Specialists and generalists

Well-controlledAverageHarsh amp dynamic

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

Breeding circle

7

Starting point

8

Ethiopia ndash range of climates and production systems

Altitude

Mean daily

temperature

Rainfall distribution

throughout the year

Feed availability

Farm management

Small scale farms

Mediumlarge scale

Breeding goal

Local circumstances and external factors

Market (consumers society)

Climate

Feed availability

Cost price

Which traits are really important in the next 10-15 years

Many options

Milk yield

Fertility

Heat tolerance

Economic models

Economic Value

0

5

10

15

20

25

30

0 10 20 30 40 50

Trait

Prof

it

1 unit

EVprofit function

Figure 81 The use of a profit function to derive economic values The economic value (EV) of a trait is the increase in profit that results from a

single unit increase of the trait value

Example Higher milk production per cow andor

improved longevity

Price in KES

Case 1

Price in KES

Case 2

Explanation andor assumptions

Heifer raising costs or investment to

purchase a heifer 300000 300000

To be calculated or estimated

Productive life in years 3 5 Just two cases in a common range

Depreciation per year 100000 60000

Margin of extra year longevity 0 +40000 Less costs means higher margin

Price in KESExplanation andor assumptions

Price per extra kg milk35

Milk price on market

Cost of extra feed

23

Feed costs of 30 KES per kg concentrates

065 kg concentrates needed for 10 kg of

milk extra

Margin of extra kg milk+12

For Kenya - J Zijlstra Wageningen Livestock Research

We donrsquot want this situation

Specialists and generalists

Well-controlledAverageHarsh amp dynamic

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

Starting point

8

Ethiopia ndash range of climates and production systems

Altitude

Mean daily

temperature

Rainfall distribution

throughout the year

Feed availability

Farm management

Small scale farms

Mediumlarge scale

Breeding goal

Local circumstances and external factors

Market (consumers society)

Climate

Feed availability

Cost price

Which traits are really important in the next 10-15 years

Many options

Milk yield

Fertility

Heat tolerance

Economic models

Economic Value

0

5

10

15

20

25

30

0 10 20 30 40 50

Trait

Prof

it

1 unit

EVprofit function

Figure 81 The use of a profit function to derive economic values The economic value (EV) of a trait is the increase in profit that results from a

single unit increase of the trait value

Example Higher milk production per cow andor

improved longevity

Price in KES

Case 1

Price in KES

Case 2

Explanation andor assumptions

Heifer raising costs or investment to

purchase a heifer 300000 300000

To be calculated or estimated

Productive life in years 3 5 Just two cases in a common range

Depreciation per year 100000 60000

Margin of extra year longevity 0 +40000 Less costs means higher margin

Price in KESExplanation andor assumptions

Price per extra kg milk35

Milk price on market

Cost of extra feed

23

Feed costs of 30 KES per kg concentrates

065 kg concentrates needed for 10 kg of

milk extra

Margin of extra kg milk+12

For Kenya - J Zijlstra Wageningen Livestock Research

We donrsquot want this situation

Specialists and generalists

Well-controlledAverageHarsh amp dynamic

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

Ethiopia ndash range of climates and production systems

Altitude

Mean daily

temperature

Rainfall distribution

throughout the year

Feed availability

Farm management

Small scale farms

Mediumlarge scale

Breeding goal

Local circumstances and external factors

Market (consumers society)

Climate

Feed availability

Cost price

Which traits are really important in the next 10-15 years

Many options

Milk yield

Fertility

Heat tolerance

Economic models

Economic Value

0

5

10

15

20

25

30

0 10 20 30 40 50

Trait

Prof

it

1 unit

EVprofit function

Figure 81 The use of a profit function to derive economic values The economic value (EV) of a trait is the increase in profit that results from a

single unit increase of the trait value

Example Higher milk production per cow andor

improved longevity

Price in KES

Case 1

Price in KES

Case 2

Explanation andor assumptions

Heifer raising costs or investment to

purchase a heifer 300000 300000

To be calculated or estimated

Productive life in years 3 5 Just two cases in a common range

Depreciation per year 100000 60000

Margin of extra year longevity 0 +40000 Less costs means higher margin

Price in KESExplanation andor assumptions

Price per extra kg milk35

Milk price on market

Cost of extra feed

23

Feed costs of 30 KES per kg concentrates

065 kg concentrates needed for 10 kg of

milk extra

Margin of extra kg milk+12

For Kenya - J Zijlstra Wageningen Livestock Research

We donrsquot want this situation

Specialists and generalists

Well-controlledAverageHarsh amp dynamic

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

Breeding goal

Local circumstances and external factors

Market (consumers society)

Climate

Feed availability

Cost price

Which traits are really important in the next 10-15 years

Many options

Milk yield

Fertility

Heat tolerance

Economic models

Economic Value

0

5

10

15

20

25

30

0 10 20 30 40 50

Trait

Prof

it

1 unit

EVprofit function

Figure 81 The use of a profit function to derive economic values The economic value (EV) of a trait is the increase in profit that results from a

single unit increase of the trait value

Example Higher milk production per cow andor

improved longevity

Price in KES

Case 1

Price in KES

Case 2

Explanation andor assumptions

Heifer raising costs or investment to

purchase a heifer 300000 300000

To be calculated or estimated

Productive life in years 3 5 Just two cases in a common range

Depreciation per year 100000 60000

Margin of extra year longevity 0 +40000 Less costs means higher margin

Price in KESExplanation andor assumptions

Price per extra kg milk35

Milk price on market

Cost of extra feed

23

Feed costs of 30 KES per kg concentrates

065 kg concentrates needed for 10 kg of

milk extra

Margin of extra kg milk+12

For Kenya - J Zijlstra Wageningen Livestock Research

We donrsquot want this situation

Specialists and generalists

Well-controlledAverageHarsh amp dynamic

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

Economic models

Economic Value

0

5

10

15

20

25

30

0 10 20 30 40 50

Trait

Prof

it

1 unit

EVprofit function

Figure 81 The use of a profit function to derive economic values The economic value (EV) of a trait is the increase in profit that results from a

single unit increase of the trait value

Example Higher milk production per cow andor

improved longevity

Price in KES

Case 1

Price in KES

Case 2

Explanation andor assumptions

Heifer raising costs or investment to

purchase a heifer 300000 300000

To be calculated or estimated

Productive life in years 3 5 Just two cases in a common range

Depreciation per year 100000 60000

Margin of extra year longevity 0 +40000 Less costs means higher margin

Price in KESExplanation andor assumptions

Price per extra kg milk35

Milk price on market

Cost of extra feed

23

Feed costs of 30 KES per kg concentrates

065 kg concentrates needed for 10 kg of

milk extra

Margin of extra kg milk+12

For Kenya - J Zijlstra Wageningen Livestock Research

We donrsquot want this situation

Specialists and generalists

Well-controlledAverageHarsh amp dynamic

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

Example Higher milk production per cow andor

improved longevity

Price in KES

Case 1

Price in KES

Case 2

Explanation andor assumptions

Heifer raising costs or investment to

purchase a heifer 300000 300000

To be calculated or estimated

Productive life in years 3 5 Just two cases in a common range

Depreciation per year 100000 60000

Margin of extra year longevity 0 +40000 Less costs means higher margin

Price in KESExplanation andor assumptions

Price per extra kg milk35

Milk price on market

Cost of extra feed

23

Feed costs of 30 KES per kg concentrates

065 kg concentrates needed for 10 kg of

milk extra

Margin of extra kg milk+12

For Kenya - J Zijlstra Wageningen Livestock Research

We donrsquot want this situation

Specialists and generalists

Well-controlledAverageHarsh amp dynamic

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

We donrsquot want this situation

Specialists and generalists

Well-controlledAverageHarsh amp dynamic

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

Specialists and generalists

Well-controlledAverageHarsh amp dynamic

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

Another example Netherlands What type of cow

is optimal ndash specialized dairy or dual purpose

bull Reduction of green house gas emissions kg milk

bull By increasing milk production

bull By increasing longevity

bull HOWEVER

bull Benefits of higher milk production are much lower when taking into account both milk and beefveal production from dairy farms

bull Higher milk production per cow lower beefveal production more import of beefveal

bull Specialized beef production systems are less efficient

bull Dual purpose breeds are endangered but WHYVellinga and de Vries 2018

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

Example Is the Dorper the superior breed

Dorper Fast growing

Red Maasai Slow growing

0

200

400

600

800

1000

1200

1400

hot-humid semi-arid

Gro

wth

(g

day)

Dorper

Red Masai

Re-ranking The Dorper is superior in semi-arid conditions but the Red Maasai is superior in hot and humid areas

Example Is the Dorper the superior breed

Dorper big but sensitive

Red Maasai small but heat resistant0

005

01

015

02

025

03

hot-humid semi-arid

An

nu

al

mo

rta

lity

ra

te

Dorper

Red Masai

Another dimension Role of livestock added value

of livestock products or feedfood competition

(H van Zanten 2016)

18Centre for Genetic Resources the Netherlands (CGN)

Human edible protein ratio =

Output of human edible protein Input human edible proteins via feed

New protein efficiency traits in breeding goals

19Centre for Genetic Resources the Netherlands (CGN)

(Van Zanten 2016)

Example

the Netherlands

Change in

breeding goal

over time

20

Collection of information Breeding values

21

Which traits are important

Trait Production Functional

Kg milk -006 0

Kg fat 07 0

Kg protein 42 0

Longevity 0 7

Udder Health 0 15

Fertility 0 25

Trait production Functional

kg milk 263 -98

kg fat 16 -8

kg protein 12 -4

Longevity -09 30

Udder Health -03 26

Fertility -18 17

Breeding goal Selection response

What do we learn from this1 Sign of economic value is not always equal to sign of selection response (milk fertility)2 Index with only 3 traits influences nearly every trait (weighting factor of zero does not mean zero change)

Example

the Netherlands

Change in

breeding goal

over time

23

24

Genetic improvement

Selecting the best animals as parents of the next generation

Every generation again

This leads to a stepwise (cumulative) genetic improvement

Genetic improvement euro

=

Accuracy x Intensity x Genetic standard deviation

Generation interval

Example mass selection and ΔG

Growth in beef cattle

h2 = 035 P = 02 kgday

generation interval L= 5 years

selection of 25 of fastest

growing individuals

Intensity p = 025 i = 1271

Accuracy rIHmass = h = 035 = 059

Genetic std A = h P = 059 x 02 = 0118 kgday

G = (1271 x 059 x 0118)5 = 00177 (kgday)yrL

irG AIH

How heritable is the trait under selection

(ie the trait in the breeding goal)

How much genetic variation for that trait is

there in the population

What is the average accuracy of the EBV

and thus the accuracy of selection

What proportion of the animals will be selected for breeding

In case genetic gain is to be expressed per year rather than per

generation how long is a generation

Factors determining success of selection decisions

27

Four selection paths

1 Sires to breed males (SS) Selection of the best progeny tested bulls

to breed ldquoyoung bullsrdquo (AI-company)

2 Sires to breed females (SD) Selection of progeny tested bulls to breed cows on farms

(AI-company + farmer)

3 Dams to breed males (DS) Selection of the very best cows to breed ldquoyoung bullsrdquo

(AI-company)

4 Dams to breed females (DD) selection of cows to breed the next generation of cows (farmer)

Evaluation

29

Example

the Netherlands

Genetic

improvement

over time

30

Holstein

CRV-breeding

program

Netherlands

31

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Human edible protein ratio =

Output of human edible protein Input human edible proteins via feed

New protein efficiency traits in breeding goals

19Centre for Genetic Resources the Netherlands (CGN)

(Van Zanten 2016)

Example

the Netherlands

Change in

breeding goal

over time

20

Collection of information Breeding values

21

Which traits are important

Trait Production Functional

Kg milk -006 0

Kg fat 07 0

Kg protein 42 0

Longevity 0 7

Udder Health 0 15

Fertility 0 25

Trait production Functional

kg milk 263 -98

kg fat 16 -8

kg protein 12 -4

Longevity -09 30

Udder Health -03 26

Fertility -18 17

Breeding goal Selection response

What do we learn from this1 Sign of economic value is not always equal to sign of selection response (milk fertility)2 Index with only 3 traits influences nearly every trait (weighting factor of zero does not mean zero change)

Example

the Netherlands

Change in

breeding goal

over time

23

24

Genetic improvement

Selecting the best animals as parents of the next generation

Every generation again

This leads to a stepwise (cumulative) genetic improvement

Genetic improvement euro

=

Accuracy x Intensity x Genetic standard deviation

Generation interval

Example mass selection and ΔG

Growth in beef cattle

h2 = 035 P = 02 kgday

generation interval L= 5 years

selection of 25 of fastest

growing individuals

Intensity p = 025 i = 1271

Accuracy rIHmass = h = 035 = 059

Genetic std A = h P = 059 x 02 = 0118 kgday

G = (1271 x 059 x 0118)5 = 00177 (kgday)yrL

irG AIH

How heritable is the trait under selection

(ie the trait in the breeding goal)

How much genetic variation for that trait is

there in the population

What is the average accuracy of the EBV

and thus the accuracy of selection

What proportion of the animals will be selected for breeding

In case genetic gain is to be expressed per year rather than per

generation how long is a generation

Factors determining success of selection decisions

27

Four selection paths

1 Sires to breed males (SS) Selection of the best progeny tested bulls

to breed ldquoyoung bullsrdquo (AI-company)

2 Sires to breed females (SD) Selection of progeny tested bulls to breed cows on farms

(AI-company + farmer)

3 Dams to breed males (DS) Selection of the very best cows to breed ldquoyoung bullsrdquo

(AI-company)

4 Dams to breed females (DD) selection of cows to breed the next generation of cows (farmer)

Evaluation

29

Example

the Netherlands

Genetic

improvement

over time

30

Holstein

CRV-breeding

program

Netherlands

31

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Example

the Netherlands

Change in

breeding goal

over time

20

Collection of information Breeding values

21

Which traits are important

Trait Production Functional

Kg milk -006 0

Kg fat 07 0

Kg protein 42 0

Longevity 0 7

Udder Health 0 15

Fertility 0 25

Trait production Functional

kg milk 263 -98

kg fat 16 -8

kg protein 12 -4

Longevity -09 30

Udder Health -03 26

Fertility -18 17

Breeding goal Selection response

What do we learn from this1 Sign of economic value is not always equal to sign of selection response (milk fertility)2 Index with only 3 traits influences nearly every trait (weighting factor of zero does not mean zero change)

Example

the Netherlands

Change in

breeding goal

over time

23

24

Genetic improvement

Selecting the best animals as parents of the next generation

Every generation again

This leads to a stepwise (cumulative) genetic improvement

Genetic improvement euro

=

Accuracy x Intensity x Genetic standard deviation

Generation interval

Example mass selection and ΔG

Growth in beef cattle

h2 = 035 P = 02 kgday

generation interval L= 5 years

selection of 25 of fastest

growing individuals

Intensity p = 025 i = 1271

Accuracy rIHmass = h = 035 = 059

Genetic std A = h P = 059 x 02 = 0118 kgday

G = (1271 x 059 x 0118)5 = 00177 (kgday)yrL

irG AIH

How heritable is the trait under selection

(ie the trait in the breeding goal)

How much genetic variation for that trait is

there in the population

What is the average accuracy of the EBV

and thus the accuracy of selection

What proportion of the animals will be selected for breeding

In case genetic gain is to be expressed per year rather than per

generation how long is a generation

Factors determining success of selection decisions

27

Four selection paths

1 Sires to breed males (SS) Selection of the best progeny tested bulls

to breed ldquoyoung bullsrdquo (AI-company)

2 Sires to breed females (SD) Selection of progeny tested bulls to breed cows on farms

(AI-company + farmer)

3 Dams to breed males (DS) Selection of the very best cows to breed ldquoyoung bullsrdquo

(AI-company)

4 Dams to breed females (DD) selection of cows to breed the next generation of cows (farmer)

Evaluation

29

Example

the Netherlands

Genetic

improvement

over time

30

Holstein

CRV-breeding

program

Netherlands

31

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Collection of information Breeding values

21

Which traits are important

Trait Production Functional

Kg milk -006 0

Kg fat 07 0

Kg protein 42 0

Longevity 0 7

Udder Health 0 15

Fertility 0 25

Trait production Functional

kg milk 263 -98

kg fat 16 -8

kg protein 12 -4

Longevity -09 30

Udder Health -03 26

Fertility -18 17

Breeding goal Selection response

What do we learn from this1 Sign of economic value is not always equal to sign of selection response (milk fertility)2 Index with only 3 traits influences nearly every trait (weighting factor of zero does not mean zero change)

Example

the Netherlands

Change in

breeding goal

over time

23

24

Genetic improvement

Selecting the best animals as parents of the next generation

Every generation again

This leads to a stepwise (cumulative) genetic improvement

Genetic improvement euro

=

Accuracy x Intensity x Genetic standard deviation

Generation interval

Example mass selection and ΔG

Growth in beef cattle

h2 = 035 P = 02 kgday

generation interval L= 5 years

selection of 25 of fastest

growing individuals

Intensity p = 025 i = 1271

Accuracy rIHmass = h = 035 = 059

Genetic std A = h P = 059 x 02 = 0118 kgday

G = (1271 x 059 x 0118)5 = 00177 (kgday)yrL

irG AIH

How heritable is the trait under selection

(ie the trait in the breeding goal)

How much genetic variation for that trait is

there in the population

What is the average accuracy of the EBV

and thus the accuracy of selection

What proportion of the animals will be selected for breeding

In case genetic gain is to be expressed per year rather than per

generation how long is a generation

Factors determining success of selection decisions

27

Four selection paths

1 Sires to breed males (SS) Selection of the best progeny tested bulls

to breed ldquoyoung bullsrdquo (AI-company)

2 Sires to breed females (SD) Selection of progeny tested bulls to breed cows on farms

(AI-company + farmer)

3 Dams to breed males (DS) Selection of the very best cows to breed ldquoyoung bullsrdquo

(AI-company)

4 Dams to breed females (DD) selection of cows to breed the next generation of cows (farmer)

Evaluation

29

Example

the Netherlands

Genetic

improvement

over time

30

Holstein

CRV-breeding

program

Netherlands

31

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Which traits are important

Trait Production Functional

Kg milk -006 0

Kg fat 07 0

Kg protein 42 0

Longevity 0 7

Udder Health 0 15

Fertility 0 25

Trait production Functional

kg milk 263 -98

kg fat 16 -8

kg protein 12 -4

Longevity -09 30

Udder Health -03 26

Fertility -18 17

Breeding goal Selection response

What do we learn from this1 Sign of economic value is not always equal to sign of selection response (milk fertility)2 Index with only 3 traits influences nearly every trait (weighting factor of zero does not mean zero change)

Example

the Netherlands

Change in

breeding goal

over time

23

24

Genetic improvement

Selecting the best animals as parents of the next generation

Every generation again

This leads to a stepwise (cumulative) genetic improvement

Genetic improvement euro

=

Accuracy x Intensity x Genetic standard deviation

Generation interval

Example mass selection and ΔG

Growth in beef cattle

h2 = 035 P = 02 kgday

generation interval L= 5 years

selection of 25 of fastest

growing individuals

Intensity p = 025 i = 1271

Accuracy rIHmass = h = 035 = 059

Genetic std A = h P = 059 x 02 = 0118 kgday

G = (1271 x 059 x 0118)5 = 00177 (kgday)yrL

irG AIH

How heritable is the trait under selection

(ie the trait in the breeding goal)

How much genetic variation for that trait is

there in the population

What is the average accuracy of the EBV

and thus the accuracy of selection

What proportion of the animals will be selected for breeding

In case genetic gain is to be expressed per year rather than per

generation how long is a generation

Factors determining success of selection decisions

27

Four selection paths

1 Sires to breed males (SS) Selection of the best progeny tested bulls

to breed ldquoyoung bullsrdquo (AI-company)

2 Sires to breed females (SD) Selection of progeny tested bulls to breed cows on farms

(AI-company + farmer)

3 Dams to breed males (DS) Selection of the very best cows to breed ldquoyoung bullsrdquo

(AI-company)

4 Dams to breed females (DD) selection of cows to breed the next generation of cows (farmer)

Evaluation

29

Example

the Netherlands

Genetic

improvement

over time

30

Holstein

CRV-breeding

program

Netherlands

31

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Example

the Netherlands

Change in

breeding goal

over time

23

24

Genetic improvement

Selecting the best animals as parents of the next generation

Every generation again

This leads to a stepwise (cumulative) genetic improvement

Genetic improvement euro

=

Accuracy x Intensity x Genetic standard deviation

Generation interval

Example mass selection and ΔG

Growth in beef cattle

h2 = 035 P = 02 kgday

generation interval L= 5 years

selection of 25 of fastest

growing individuals

Intensity p = 025 i = 1271

Accuracy rIHmass = h = 035 = 059

Genetic std A = h P = 059 x 02 = 0118 kgday

G = (1271 x 059 x 0118)5 = 00177 (kgday)yrL

irG AIH

How heritable is the trait under selection

(ie the trait in the breeding goal)

How much genetic variation for that trait is

there in the population

What is the average accuracy of the EBV

and thus the accuracy of selection

What proportion of the animals will be selected for breeding

In case genetic gain is to be expressed per year rather than per

generation how long is a generation

Factors determining success of selection decisions

27

Four selection paths

1 Sires to breed males (SS) Selection of the best progeny tested bulls

to breed ldquoyoung bullsrdquo (AI-company)

2 Sires to breed females (SD) Selection of progeny tested bulls to breed cows on farms

(AI-company + farmer)

3 Dams to breed males (DS) Selection of the very best cows to breed ldquoyoung bullsrdquo

(AI-company)

4 Dams to breed females (DD) selection of cows to breed the next generation of cows (farmer)

Evaluation

29

Example

the Netherlands

Genetic

improvement

over time

30

Holstein

CRV-breeding

program

Netherlands

31

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

24

Genetic improvement

Selecting the best animals as parents of the next generation

Every generation again

This leads to a stepwise (cumulative) genetic improvement

Genetic improvement euro

=

Accuracy x Intensity x Genetic standard deviation

Generation interval

Example mass selection and ΔG

Growth in beef cattle

h2 = 035 P = 02 kgday

generation interval L= 5 years

selection of 25 of fastest

growing individuals

Intensity p = 025 i = 1271

Accuracy rIHmass = h = 035 = 059

Genetic std A = h P = 059 x 02 = 0118 kgday

G = (1271 x 059 x 0118)5 = 00177 (kgday)yrL

irG AIH

How heritable is the trait under selection

(ie the trait in the breeding goal)

How much genetic variation for that trait is

there in the population

What is the average accuracy of the EBV

and thus the accuracy of selection

What proportion of the animals will be selected for breeding

In case genetic gain is to be expressed per year rather than per

generation how long is a generation

Factors determining success of selection decisions

27

Four selection paths

1 Sires to breed males (SS) Selection of the best progeny tested bulls

to breed ldquoyoung bullsrdquo (AI-company)

2 Sires to breed females (SD) Selection of progeny tested bulls to breed cows on farms

(AI-company + farmer)

3 Dams to breed males (DS) Selection of the very best cows to breed ldquoyoung bullsrdquo

(AI-company)

4 Dams to breed females (DD) selection of cows to breed the next generation of cows (farmer)

Evaluation

29

Example

the Netherlands

Genetic

improvement

over time

30

Holstein

CRV-breeding

program

Netherlands

31

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Genetic improvement

Selecting the best animals as parents of the next generation

Every generation again

This leads to a stepwise (cumulative) genetic improvement

Genetic improvement euro

=

Accuracy x Intensity x Genetic standard deviation

Generation interval

Example mass selection and ΔG

Growth in beef cattle

h2 = 035 P = 02 kgday

generation interval L= 5 years

selection of 25 of fastest

growing individuals

Intensity p = 025 i = 1271

Accuracy rIHmass = h = 035 = 059

Genetic std A = h P = 059 x 02 = 0118 kgday

G = (1271 x 059 x 0118)5 = 00177 (kgday)yrL

irG AIH

How heritable is the trait under selection

(ie the trait in the breeding goal)

How much genetic variation for that trait is

there in the population

What is the average accuracy of the EBV

and thus the accuracy of selection

What proportion of the animals will be selected for breeding

In case genetic gain is to be expressed per year rather than per

generation how long is a generation

Factors determining success of selection decisions

27

Four selection paths

1 Sires to breed males (SS) Selection of the best progeny tested bulls

to breed ldquoyoung bullsrdquo (AI-company)

2 Sires to breed females (SD) Selection of progeny tested bulls to breed cows on farms

(AI-company + farmer)

3 Dams to breed males (DS) Selection of the very best cows to breed ldquoyoung bullsrdquo

(AI-company)

4 Dams to breed females (DD) selection of cows to breed the next generation of cows (farmer)

Evaluation

29

Example

the Netherlands

Genetic

improvement

over time

30

Holstein

CRV-breeding

program

Netherlands

31

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Example mass selection and ΔG

Growth in beef cattle

h2 = 035 P = 02 kgday

generation interval L= 5 years

selection of 25 of fastest

growing individuals

Intensity p = 025 i = 1271

Accuracy rIHmass = h = 035 = 059

Genetic std A = h P = 059 x 02 = 0118 kgday

G = (1271 x 059 x 0118)5 = 00177 (kgday)yrL

irG AIH

How heritable is the trait under selection

(ie the trait in the breeding goal)

How much genetic variation for that trait is

there in the population

What is the average accuracy of the EBV

and thus the accuracy of selection

What proportion of the animals will be selected for breeding

In case genetic gain is to be expressed per year rather than per

generation how long is a generation

Factors determining success of selection decisions

27

Four selection paths

1 Sires to breed males (SS) Selection of the best progeny tested bulls

to breed ldquoyoung bullsrdquo (AI-company)

2 Sires to breed females (SD) Selection of progeny tested bulls to breed cows on farms

(AI-company + farmer)

3 Dams to breed males (DS) Selection of the very best cows to breed ldquoyoung bullsrdquo

(AI-company)

4 Dams to breed females (DD) selection of cows to breed the next generation of cows (farmer)

Evaluation

29

Example

the Netherlands

Genetic

improvement

over time

30

Holstein

CRV-breeding

program

Netherlands

31

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

How heritable is the trait under selection

(ie the trait in the breeding goal)

How much genetic variation for that trait is

there in the population

What is the average accuracy of the EBV

and thus the accuracy of selection

What proportion of the animals will be selected for breeding

In case genetic gain is to be expressed per year rather than per

generation how long is a generation

Factors determining success of selection decisions

27

Four selection paths

1 Sires to breed males (SS) Selection of the best progeny tested bulls

to breed ldquoyoung bullsrdquo (AI-company)

2 Sires to breed females (SD) Selection of progeny tested bulls to breed cows on farms

(AI-company + farmer)

3 Dams to breed males (DS) Selection of the very best cows to breed ldquoyoung bullsrdquo

(AI-company)

4 Dams to breed females (DD) selection of cows to breed the next generation of cows (farmer)

Evaluation

29

Example

the Netherlands

Genetic

improvement

over time

30

Holstein

CRV-breeding

program

Netherlands

31

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Four selection paths

1 Sires to breed males (SS) Selection of the best progeny tested bulls

to breed ldquoyoung bullsrdquo (AI-company)

2 Sires to breed females (SD) Selection of progeny tested bulls to breed cows on farms

(AI-company + farmer)

3 Dams to breed males (DS) Selection of the very best cows to breed ldquoyoung bullsrdquo

(AI-company)

4 Dams to breed females (DD) selection of cows to breed the next generation of cows (farmer)

Evaluation

29

Example

the Netherlands

Genetic

improvement

over time

30

Holstein

CRV-breeding

program

Netherlands

31

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Evaluation

29

Example

the Netherlands

Genetic

improvement

over time

30

Holstein

CRV-breeding

program

Netherlands

31

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Example

the Netherlands

Genetic

improvement

over time

30

Holstein

CRV-breeding

program

Netherlands

31

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Holstein

CRV-breeding

program

Netherlands

31

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Conservation and genetic improvement of the most valuable

indigenous breeds

Upgrading of indigenous cattle to more productive 50 crossbreds

Development of synthetic indigenous-exotic breed

Importing suitable breeds (semen embryorsquos heifers )

Some key questions based on breeding goal discussion

- What do farmers consider as the optimal blood level 50 75

- Upgrading of local animals to 50 exotic whatrsquos next

Parallel breeding strategies needed to achieve

the national goal and to meet farmers needs

32

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Which breeds ndash How to make optimal use of the

genetic resources pool ndash a broad genetic base

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Livestock breeds ndash the global picture (FAO 2015)

34Centre for Genetic Resources the Netherlands (CGN)

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Threats to livestock genetic diversity (FAO 2015)

35Centre for Genetic Resources the Netherlands (CGN)

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

What happened in the Netherlands

change in population size 1979 - 2007

0

20

40

60

80

100

120

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

1979

100

Blaarkop

Fries Hollands ZB

Fries Hollands R

MRY incl Brandrood

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

37

Ethiopian breeds

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Upgrading of less productive breeds

Quickly trying tosolve problems at farm level

Making use of heterosis effects

Long term strategy

Crossbreeding Advantages

39

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Rotational cross

Rotational cross A x (B x (A x B)))

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

International pool of genetic products (eg CRV)

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

J Gibson

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Milk production by animals with different proportions of exotic genotypes (dairyness)

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)

Herd environment level

Kenya

21-35 36-60 61-875 gt875

0

2

4

6

8

10

12

Level-1 Level-2 Level-3

Dai

ly m

ilk y

ield

(l

day

)Herd environment level

Uganda

21-35 36-60 61-875 gt875

High grade cattle only showed substantially better milk yields than other grades in the highest production environment

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Daily milk production for different dairy groups of animals within countries

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly M

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Kenya

Class 2 Class 3 Class 4 Class 5

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

Dai

ly m

ilk y

ield

(l

day

)

Lactation Stage (100-day intervals)

Uganda

Class-1 Class-2 Class-3 Class-4 Class-5

Lactation curves for animals were generally flat

with no evidence of a peak in early lactation

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

G Leroy R Baumung P Boettcher B Scherf I

Hoffmann 2015

45

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Synthetic

FxA crosses

(goal=50)

Arsi Cows (A)Friesian Bulls (F)

X

50F50A

375F625A

25F75A

4375F5625A

46875F53125A

50F 50A

Foundation stock

selection

Dissemination to

participating herds

Dissemination to

participating herds

selection

selection

selection

Dissemination to

participating herds

Dissemination to

participating herds

Dissemination to

participating herds

10th generation

4th generation

3rd generation

1st generation

nucleus participating herds

2nd generation

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

DNA technology

Reproductive technologies

Taking advantage of new technologies in

breeding programmes

47Centre for Genetic Resources the Netherlands (CGN)

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

AI versus Natural mating

Uptake of AI is low (so far)

Technical results should improve

Novel technologies

Keep it simple

Reproductive technologies

48

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Large scale SNP genotyping is available

CAGTCAGTCGTACCAGTCT

CAGTCAGTAGTACCAGTCT

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Determine breed composition

Combine production and SNP data to determine which breedanimal combinations perform best under different conditions

Genomic selection

Genotyping for

50

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

KenyaUganda - PCA results based on 566k chip - Admixture

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Selecting the best animals for instance

animal 1 A A G T A T T A T C T T hellip

A A G T A T T A T C T T hellip

animal 2 A A G T A T T A T C T T hellip

A A G A A T T A T C T T hellip

This A gives +02 kg milk -1 fertility etc

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Genomic Selection ndash accelerating genetic progress

Genomic breeding values

(GEBVs)

Estimate SNP

effects

Reference population

Selection candidates

Genomic Selection

Traditional versus genomic selection

Factors Genomic selection

Accuracy +++ ++

Intensity + +++

Genetic variation

Generation interval -- ++

Traditional = Progeny testing

Impact on genetic improvement

Can we use GS in developing countries where

pedigree recording is lacking

Screen the population

Select number of herds with information on performance on cows

Take a DNA sample on these cows

Young bulls in your nucleus

Take a DNA sample

Estimate EBV based on DNA profile

Select the best bulls for nucleus and dissemination

Link performance to

EBV through DNA

Genomic selection in small populations or specific

context (Kariuki 2017)

56 -

2000

4000

6000

8000

10000

12000

14000

PT15 PT30 GS15 GS30

Retu

rn

s (

00

0) E

uros

4

7

Inbreeding - risks for small populations

57

Directly in the trait itself

Reduction in Additive genetic variance after selection (Falconer Chapter 11)

Use of a small group of related individuals as parents reduces the genetic diversity

Affects other traits as well

Loss of diversity due to selection

Proportion Heritability

selected 090 070 050 030 010

5 22 40 57 74 91

20 30 45 61 77 92

50 43 55 68 81 94

Loss of genetic diversity through genetic drift

Change in frequency and loss of alleles by chance due to sampling of a limited numbers of individuals

Less individuals sampled -gt more genetic drift

Loss of diversity is predictable but which diversity is not predictable

Frequency

Black 10

White 11

Yellow 9

Green 10

Blue 10

Brown 2

Red 5

Before After

10 -

11 6

9 2

10 1

10 1

2 -

5 -

Not only in

ldquosmall populationsrdquo

Holstein

CRV-breeding

program

Netherlands

60

On inbreeding

Inbreeding depression inbred individuals perform less well

Genetic defects are more common in inbred individuals

Inbreeding always increases in closed population

The smaller the population the higher the inbreeding rate

Uneven distribution of offspring over parents causes more inbreeding

Use of few bulls

Measures

Two principles

Larger population size

More even distribution of offspring over ancestors

Provide access to more unrelated bulls

Gene banks

Avoid excessive use of single bulls

Limit inseminations bull

Limit sons available for breeding

Example Netherlands - Gene bank supports

conservation of endangered breeds

Dutch Friesian Red and White

bull lt 400 purebred cows

bull gt 40 (old) bulls in gene bank

Collections CGN ndash Dutch gene bank farm animals

CGN Gene bank collections = reproductive material

Semen (+ embryorsquos oocytesovarian tissue)

Blood samples

ldquoCore collectionsrdquobreed

Conclusions ndash pathways towards implementation

ldquoNational breeding program and national infrastructurerdquo should support

the relevant complementary strategies

Upgrading

Development of synthetic breeds

Conservation and improvement of indigenous breeds

More effective and efficient AI delivery system needed

AI centres should make available semen of lsquoexotic bullsrsquo lsquocrossbred bullsrsquo

aacutend lsquoindigenous bullsrsquo

Investment in performance recording will pay off in the long run

selection of best animalsbull dams at private farms for further breeding

Conclusions ndash pathways towards implementation Import of semen or semen production in Ethiopia

Importing 100 exotic semen or importing young bulls is probably economically more

profitable than sourcing 100 exotic bulls for AI at Ethiopian (nucleus breeding) farms

No need to buy the most expensive semen ndash probably not the best for Ethiopian farmer

Use the national infrastructure of breeding and research farms for

Conservation and improvement of selected indigenous breeds

Development of synthetic breeds

Performance recording and research

Selection of bull-damsbulls for AI

Dissemination of natural mating bulls and heifers to farmers

67

Looking forward to discuss collaboration in dairy breeding

Can we use GS in developing countries where

pedigree recording is lacking

Screen the population

Select number of herds with information on performance on cows

Take a DNA sample on these cows

Young bulls in your nucleus

Take a DNA sample

Estimate EBV based on DNA profile

Select the best bulls for nucleus and dissemination

Link performance to

EBV through DNA

Genomic selection in small populations or specific

context (Kariuki 2017)

56 -

2000

4000

6000

8000

10000

12000

14000

PT15 PT30 GS15 GS30

Retu

rn

s (

00

0) E

uros

4

7

Inbreeding - risks for small populations

57

Directly in the trait itself

Reduction in Additive genetic variance after selection (Falconer Chapter 11)

Use of a small group of related individuals as parents reduces the genetic diversity

Affects other traits as well

Loss of diversity due to selection

Proportion Heritability

selected 090 070 050 030 010

5 22 40 57 74 91

20 30 45 61 77 92

50 43 55 68 81 94

Loss of genetic diversity through genetic drift

Change in frequency and loss of alleles by chance due to sampling of a limited numbers of individuals

Less individuals sampled -gt more genetic drift

Loss of diversity is predictable but which diversity is not predictable

Frequency

Black 10

White 11

Yellow 9

Green 10

Blue 10

Brown 2

Red 5

Before After

10 -

11 6

9 2

10 1

10 1

2 -

5 -

Not only in

ldquosmall populationsrdquo

Holstein

CRV-breeding

program

Netherlands

60

On inbreeding

Inbreeding depression inbred individuals perform less well

Genetic defects are more common in inbred individuals

Inbreeding always increases in closed population

The smaller the population the higher the inbreeding rate

Uneven distribution of offspring over parents causes more inbreeding

Use of few bulls

Measures

Two principles

Larger population size

More even distribution of offspring over ancestors

Provide access to more unrelated bulls

Gene banks

Avoid excessive use of single bulls

Limit inseminations bull

Limit sons available for breeding

Example Netherlands - Gene bank supports

conservation of endangered breeds

Dutch Friesian Red and White

bull lt 400 purebred cows

bull gt 40 (old) bulls in gene bank

Collections CGN ndash Dutch gene bank farm animals

CGN Gene bank collections = reproductive material

Semen (+ embryorsquos oocytesovarian tissue)

Blood samples

ldquoCore collectionsrdquobreed

Conclusions ndash pathways towards implementation

ldquoNational breeding program and national infrastructurerdquo should support

the relevant complementary strategies

Upgrading

Development of synthetic breeds

Conservation and improvement of indigenous breeds

More effective and efficient AI delivery system needed

AI centres should make available semen of lsquoexotic bullsrsquo lsquocrossbred bullsrsquo

aacutend lsquoindigenous bullsrsquo

Investment in performance recording will pay off in the long run

selection of best animalsbull dams at private farms for further breeding

Conclusions ndash pathways towards implementation Import of semen or semen production in Ethiopia

Importing 100 exotic semen or importing young bulls is probably economically more

profitable than sourcing 100 exotic bulls for AI at Ethiopian (nucleus breeding) farms

No need to buy the most expensive semen ndash probably not the best for Ethiopian farmer

Use the national infrastructure of breeding and research farms for

Conservation and improvement of selected indigenous breeds

Development of synthetic breeds

Performance recording and research

Selection of bull-damsbulls for AI

Dissemination of natural mating bulls and heifers to farmers

67

Looking forward to discuss collaboration in dairy breeding

Genomic selection in small populations or specific

context (Kariuki 2017)

56 -

2000

4000

6000

8000

10000

12000

14000

PT15 PT30 GS15 GS30

Retu

rn

s (

00

0) E

uros

4

7

Inbreeding - risks for small populations

57

Directly in the trait itself

Reduction in Additive genetic variance after selection (Falconer Chapter 11)

Use of a small group of related individuals as parents reduces the genetic diversity

Affects other traits as well

Loss of diversity due to selection

Proportion Heritability

selected 090 070 050 030 010

5 22 40 57 74 91

20 30 45 61 77 92

50 43 55 68 81 94

Loss of genetic diversity through genetic drift

Change in frequency and loss of alleles by chance due to sampling of a limited numbers of individuals

Less individuals sampled -gt more genetic drift

Loss of diversity is predictable but which diversity is not predictable

Frequency

Black 10

White 11

Yellow 9

Green 10

Blue 10

Brown 2

Red 5

Before After

10 -

11 6

9 2

10 1

10 1

2 -

5 -

Not only in

ldquosmall populationsrdquo

Holstein

CRV-breeding

program

Netherlands

60

On inbreeding

Inbreeding depression inbred individuals perform less well

Genetic defects are more common in inbred individuals

Inbreeding always increases in closed population

The smaller the population the higher the inbreeding rate

Uneven distribution of offspring over parents causes more inbreeding

Use of few bulls

Measures

Two principles

Larger population size

More even distribution of offspring over ancestors

Provide access to more unrelated bulls

Gene banks

Avoid excessive use of single bulls

Limit inseminations bull

Limit sons available for breeding

Example Netherlands - Gene bank supports

conservation of endangered breeds

Dutch Friesian Red and White

bull lt 400 purebred cows

bull gt 40 (old) bulls in gene bank

Collections CGN ndash Dutch gene bank farm animals

CGN Gene bank collections = reproductive material

Semen (+ embryorsquos oocytesovarian tissue)

Blood samples

ldquoCore collectionsrdquobreed

Conclusions ndash pathways towards implementation

ldquoNational breeding program and national infrastructurerdquo should support

the relevant complementary strategies

Upgrading

Development of synthetic breeds

Conservation and improvement of indigenous breeds

More effective and efficient AI delivery system needed

AI centres should make available semen of lsquoexotic bullsrsquo lsquocrossbred bullsrsquo

aacutend lsquoindigenous bullsrsquo

Investment in performance recording will pay off in the long run

selection of best animalsbull dams at private farms for further breeding

Conclusions ndash pathways towards implementation Import of semen or semen production in Ethiopia

Importing 100 exotic semen or importing young bulls is probably economically more

profitable than sourcing 100 exotic bulls for AI at Ethiopian (nucleus breeding) farms

No need to buy the most expensive semen ndash probably not the best for Ethiopian farmer

Use the national infrastructure of breeding and research farms for

Conservation and improvement of selected indigenous breeds

Development of synthetic breeds

Performance recording and research

Selection of bull-damsbulls for AI

Dissemination of natural mating bulls and heifers to farmers

67

Looking forward to discuss collaboration in dairy breeding

Inbreeding - risks for small populations

57

Directly in the trait itself

Reduction in Additive genetic variance after selection (Falconer Chapter 11)

Use of a small group of related individuals as parents reduces the genetic diversity

Affects other traits as well

Loss of diversity due to selection

Proportion Heritability

selected 090 070 050 030 010

5 22 40 57 74 91

20 30 45 61 77 92

50 43 55 68 81 94

Loss of genetic diversity through genetic drift

Change in frequency and loss of alleles by chance due to sampling of a limited numbers of individuals

Less individuals sampled -gt more genetic drift

Loss of diversity is predictable but which diversity is not predictable

Frequency

Black 10

White 11

Yellow 9

Green 10

Blue 10

Brown 2

Red 5

Before After

10 -

11 6

9 2

10 1

10 1

2 -

5 -

Not only in

ldquosmall populationsrdquo

Holstein

CRV-breeding

program

Netherlands

60

On inbreeding

Inbreeding depression inbred individuals perform less well

Genetic defects are more common in inbred individuals

Inbreeding always increases in closed population

The smaller the population the higher the inbreeding rate

Uneven distribution of offspring over parents causes more inbreeding

Use of few bulls

Measures

Two principles

Larger population size

More even distribution of offspring over ancestors

Provide access to more unrelated bulls

Gene banks

Avoid excessive use of single bulls

Limit inseminations bull

Limit sons available for breeding

Example Netherlands - Gene bank supports

conservation of endangered breeds

Dutch Friesian Red and White

bull lt 400 purebred cows

bull gt 40 (old) bulls in gene bank

Collections CGN ndash Dutch gene bank farm animals

CGN Gene bank collections = reproductive material

Semen (+ embryorsquos oocytesovarian tissue)

Blood samples

ldquoCore collectionsrdquobreed

Conclusions ndash pathways towards implementation

ldquoNational breeding program and national infrastructurerdquo should support

the relevant complementary strategies

Upgrading

Development of synthetic breeds

Conservation and improvement of indigenous breeds

More effective and efficient AI delivery system needed

AI centres should make available semen of lsquoexotic bullsrsquo lsquocrossbred bullsrsquo

aacutend lsquoindigenous bullsrsquo

Investment in performance recording will pay off in the long run

selection of best animalsbull dams at private farms for further breeding

Conclusions ndash pathways towards implementation Import of semen or semen production in Ethiopia

Importing 100 exotic semen or importing young bulls is probably economically more

profitable than sourcing 100 exotic bulls for AI at Ethiopian (nucleus breeding) farms

No need to buy the most expensive semen ndash probably not the best for Ethiopian farmer

Use the national infrastructure of breeding and research farms for

Conservation and improvement of selected indigenous breeds

Development of synthetic breeds

Performance recording and research

Selection of bull-damsbulls for AI

Dissemination of natural mating bulls and heifers to farmers

67

Looking forward to discuss collaboration in dairy breeding

Directly in the trait itself

Reduction in Additive genetic variance after selection (Falconer Chapter 11)

Use of a small group of related individuals as parents reduces the genetic diversity

Affects other traits as well

Loss of diversity due to selection

Proportion Heritability

selected 090 070 050 030 010

5 22 40 57 74 91

20 30 45 61 77 92

50 43 55 68 81 94

Loss of genetic diversity through genetic drift

Change in frequency and loss of alleles by chance due to sampling of a limited numbers of individuals

Less individuals sampled -gt more genetic drift

Loss of diversity is predictable but which diversity is not predictable

Frequency

Black 10

White 11

Yellow 9

Green 10

Blue 10

Brown 2

Red 5

Before After

10 -

11 6

9 2

10 1

10 1

2 -

5 -

Not only in

ldquosmall populationsrdquo

Holstein

CRV-breeding

program

Netherlands

60

On inbreeding

Inbreeding depression inbred individuals perform less well

Genetic defects are more common in inbred individuals

Inbreeding always increases in closed population

The smaller the population the higher the inbreeding rate

Uneven distribution of offspring over parents causes more inbreeding

Use of few bulls

Measures

Two principles

Larger population size

More even distribution of offspring over ancestors

Provide access to more unrelated bulls

Gene banks

Avoid excessive use of single bulls

Limit inseminations bull

Limit sons available for breeding

Example Netherlands - Gene bank supports

conservation of endangered breeds

Dutch Friesian Red and White

bull lt 400 purebred cows

bull gt 40 (old) bulls in gene bank

Collections CGN ndash Dutch gene bank farm animals

CGN Gene bank collections = reproductive material

Semen (+ embryorsquos oocytesovarian tissue)

Blood samples

ldquoCore collectionsrdquobreed

Conclusions ndash pathways towards implementation

ldquoNational breeding program and national infrastructurerdquo should support

the relevant complementary strategies

Upgrading

Development of synthetic breeds

Conservation and improvement of indigenous breeds

More effective and efficient AI delivery system needed

AI centres should make available semen of lsquoexotic bullsrsquo lsquocrossbred bullsrsquo

aacutend lsquoindigenous bullsrsquo

Investment in performance recording will pay off in the long run

selection of best animalsbull dams at private farms for further breeding

Conclusions ndash pathways towards implementation Import of semen or semen production in Ethiopia

Importing 100 exotic semen or importing young bulls is probably economically more

profitable than sourcing 100 exotic bulls for AI at Ethiopian (nucleus breeding) farms

No need to buy the most expensive semen ndash probably not the best for Ethiopian farmer

Use the national infrastructure of breeding and research farms for

Conservation and improvement of selected indigenous breeds

Development of synthetic breeds

Performance recording and research

Selection of bull-damsbulls for AI

Dissemination of natural mating bulls and heifers to farmers

67

Looking forward to discuss collaboration in dairy breeding

Loss of genetic diversity through genetic drift

Change in frequency and loss of alleles by chance due to sampling of a limited numbers of individuals

Less individuals sampled -gt more genetic drift

Loss of diversity is predictable but which diversity is not predictable

Frequency

Black 10

White 11

Yellow 9

Green 10

Blue 10

Brown 2

Red 5

Before After

10 -

11 6

9 2

10 1

10 1

2 -

5 -

Not only in

ldquosmall populationsrdquo

Holstein

CRV-breeding

program

Netherlands

60

On inbreeding

Inbreeding depression inbred individuals perform less well

Genetic defects are more common in inbred individuals

Inbreeding always increases in closed population

The smaller the population the higher the inbreeding rate

Uneven distribution of offspring over parents causes more inbreeding

Use of few bulls

Measures

Two principles

Larger population size

More even distribution of offspring over ancestors

Provide access to more unrelated bulls

Gene banks

Avoid excessive use of single bulls

Limit inseminations bull

Limit sons available for breeding

Example Netherlands - Gene bank supports

conservation of endangered breeds

Dutch Friesian Red and White

bull lt 400 purebred cows

bull gt 40 (old) bulls in gene bank

Collections CGN ndash Dutch gene bank farm animals

CGN Gene bank collections = reproductive material

Semen (+ embryorsquos oocytesovarian tissue)

Blood samples

ldquoCore collectionsrdquobreed

Conclusions ndash pathways towards implementation

ldquoNational breeding program and national infrastructurerdquo should support

the relevant complementary strategies

Upgrading

Development of synthetic breeds

Conservation and improvement of indigenous breeds

More effective and efficient AI delivery system needed

AI centres should make available semen of lsquoexotic bullsrsquo lsquocrossbred bullsrsquo

aacutend lsquoindigenous bullsrsquo

Investment in performance recording will pay off in the long run

selection of best animalsbull dams at private farms for further breeding

Conclusions ndash pathways towards implementation Import of semen or semen production in Ethiopia

Importing 100 exotic semen or importing young bulls is probably economically more

profitable than sourcing 100 exotic bulls for AI at Ethiopian (nucleus breeding) farms

No need to buy the most expensive semen ndash probably not the best for Ethiopian farmer

Use the national infrastructure of breeding and research farms for

Conservation and improvement of selected indigenous breeds

Development of synthetic breeds

Performance recording and research

Selection of bull-damsbulls for AI

Dissemination of natural mating bulls and heifers to farmers

67

Looking forward to discuss collaboration in dairy breeding

Not only in

ldquosmall populationsrdquo

Holstein

CRV-breeding

program

Netherlands

60

On inbreeding

Inbreeding depression inbred individuals perform less well

Genetic defects are more common in inbred individuals

Inbreeding always increases in closed population

The smaller the population the higher the inbreeding rate

Uneven distribution of offspring over parents causes more inbreeding

Use of few bulls

Measures

Two principles

Larger population size

More even distribution of offspring over ancestors

Provide access to more unrelated bulls

Gene banks

Avoid excessive use of single bulls

Limit inseminations bull

Limit sons available for breeding

Example Netherlands - Gene bank supports

conservation of endangered breeds

Dutch Friesian Red and White

bull lt 400 purebred cows

bull gt 40 (old) bulls in gene bank

Collections CGN ndash Dutch gene bank farm animals

CGN Gene bank collections = reproductive material

Semen (+ embryorsquos oocytesovarian tissue)

Blood samples

ldquoCore collectionsrdquobreed

Conclusions ndash pathways towards implementation

ldquoNational breeding program and national infrastructurerdquo should support

the relevant complementary strategies

Upgrading

Development of synthetic breeds

Conservation and improvement of indigenous breeds

More effective and efficient AI delivery system needed

AI centres should make available semen of lsquoexotic bullsrsquo lsquocrossbred bullsrsquo

aacutend lsquoindigenous bullsrsquo

Investment in performance recording will pay off in the long run

selection of best animalsbull dams at private farms for further breeding

Conclusions ndash pathways towards implementation Import of semen or semen production in Ethiopia

Importing 100 exotic semen or importing young bulls is probably economically more

profitable than sourcing 100 exotic bulls for AI at Ethiopian (nucleus breeding) farms

No need to buy the most expensive semen ndash probably not the best for Ethiopian farmer

Use the national infrastructure of breeding and research farms for

Conservation and improvement of selected indigenous breeds

Development of synthetic breeds

Performance recording and research

Selection of bull-damsbulls for AI

Dissemination of natural mating bulls and heifers to farmers

67

Looking forward to discuss collaboration in dairy breeding

On inbreeding

Inbreeding depression inbred individuals perform less well

Genetic defects are more common in inbred individuals

Inbreeding always increases in closed population

The smaller the population the higher the inbreeding rate

Uneven distribution of offspring over parents causes more inbreeding

Use of few bulls

Measures

Two principles

Larger population size

More even distribution of offspring over ancestors

Provide access to more unrelated bulls

Gene banks

Avoid excessive use of single bulls

Limit inseminations bull

Limit sons available for breeding

Example Netherlands - Gene bank supports

conservation of endangered breeds

Dutch Friesian Red and White

bull lt 400 purebred cows

bull gt 40 (old) bulls in gene bank

Collections CGN ndash Dutch gene bank farm animals

CGN Gene bank collections = reproductive material

Semen (+ embryorsquos oocytesovarian tissue)

Blood samples

ldquoCore collectionsrdquobreed

Conclusions ndash pathways towards implementation

ldquoNational breeding program and national infrastructurerdquo should support

the relevant complementary strategies

Upgrading

Development of synthetic breeds

Conservation and improvement of indigenous breeds

More effective and efficient AI delivery system needed

AI centres should make available semen of lsquoexotic bullsrsquo lsquocrossbred bullsrsquo

aacutend lsquoindigenous bullsrsquo

Investment in performance recording will pay off in the long run

selection of best animalsbull dams at private farms for further breeding

Conclusions ndash pathways towards implementation Import of semen or semen production in Ethiopia

Importing 100 exotic semen or importing young bulls is probably economically more

profitable than sourcing 100 exotic bulls for AI at Ethiopian (nucleus breeding) farms

No need to buy the most expensive semen ndash probably not the best for Ethiopian farmer

Use the national infrastructure of breeding and research farms for

Conservation and improvement of selected indigenous breeds

Development of synthetic breeds

Performance recording and research

Selection of bull-damsbulls for AI

Dissemination of natural mating bulls and heifers to farmers

67

Looking forward to discuss collaboration in dairy breeding

Measures

Two principles

Larger population size

More even distribution of offspring over ancestors

Provide access to more unrelated bulls

Gene banks

Avoid excessive use of single bulls

Limit inseminations bull

Limit sons available for breeding

Example Netherlands - Gene bank supports

conservation of endangered breeds

Dutch Friesian Red and White

bull lt 400 purebred cows

bull gt 40 (old) bulls in gene bank

Collections CGN ndash Dutch gene bank farm animals

CGN Gene bank collections = reproductive material

Semen (+ embryorsquos oocytesovarian tissue)

Blood samples

ldquoCore collectionsrdquobreed

Conclusions ndash pathways towards implementation

ldquoNational breeding program and national infrastructurerdquo should support

the relevant complementary strategies

Upgrading

Development of synthetic breeds

Conservation and improvement of indigenous breeds

More effective and efficient AI delivery system needed

AI centres should make available semen of lsquoexotic bullsrsquo lsquocrossbred bullsrsquo

aacutend lsquoindigenous bullsrsquo

Investment in performance recording will pay off in the long run

selection of best animalsbull dams at private farms for further breeding

Conclusions ndash pathways towards implementation Import of semen or semen production in Ethiopia

Importing 100 exotic semen or importing young bulls is probably economically more

profitable than sourcing 100 exotic bulls for AI at Ethiopian (nucleus breeding) farms

No need to buy the most expensive semen ndash probably not the best for Ethiopian farmer

Use the national infrastructure of breeding and research farms for

Conservation and improvement of selected indigenous breeds

Development of synthetic breeds

Performance recording and research

Selection of bull-damsbulls for AI

Dissemination of natural mating bulls and heifers to farmers

67

Looking forward to discuss collaboration in dairy breeding

Example Netherlands - Gene bank supports

conservation of endangered breeds

Dutch Friesian Red and White

bull lt 400 purebred cows

bull gt 40 (old) bulls in gene bank

Collections CGN ndash Dutch gene bank farm animals

CGN Gene bank collections = reproductive material

Semen (+ embryorsquos oocytesovarian tissue)

Blood samples

ldquoCore collectionsrdquobreed

Conclusions ndash pathways towards implementation

ldquoNational breeding program and national infrastructurerdquo should support

the relevant complementary strategies

Upgrading

Development of synthetic breeds

Conservation and improvement of indigenous breeds

More effective and efficient AI delivery system needed

AI centres should make available semen of lsquoexotic bullsrsquo lsquocrossbred bullsrsquo

aacutend lsquoindigenous bullsrsquo

Investment in performance recording will pay off in the long run

selection of best animalsbull dams at private farms for further breeding

Conclusions ndash pathways towards implementation Import of semen or semen production in Ethiopia

Importing 100 exotic semen or importing young bulls is probably economically more

profitable than sourcing 100 exotic bulls for AI at Ethiopian (nucleus breeding) farms

No need to buy the most expensive semen ndash probably not the best for Ethiopian farmer

Use the national infrastructure of breeding and research farms for

Conservation and improvement of selected indigenous breeds

Development of synthetic breeds

Performance recording and research

Selection of bull-damsbulls for AI

Dissemination of natural mating bulls and heifers to farmers

67

Looking forward to discuss collaboration in dairy breeding

Collections CGN ndash Dutch gene bank farm animals

CGN Gene bank collections = reproductive material

Semen (+ embryorsquos oocytesovarian tissue)

Blood samples

ldquoCore collectionsrdquobreed

Conclusions ndash pathways towards implementation

ldquoNational breeding program and national infrastructurerdquo should support

the relevant complementary strategies

Upgrading

Development of synthetic breeds

Conservation and improvement of indigenous breeds

More effective and efficient AI delivery system needed

AI centres should make available semen of lsquoexotic bullsrsquo lsquocrossbred bullsrsquo

aacutend lsquoindigenous bullsrsquo

Investment in performance recording will pay off in the long run

selection of best animalsbull dams at private farms for further breeding

Conclusions ndash pathways towards implementation Import of semen or semen production in Ethiopia

Importing 100 exotic semen or importing young bulls is probably economically more

profitable than sourcing 100 exotic bulls for AI at Ethiopian (nucleus breeding) farms

No need to buy the most expensive semen ndash probably not the best for Ethiopian farmer

Use the national infrastructure of breeding and research farms for

Conservation and improvement of selected indigenous breeds

Development of synthetic breeds

Performance recording and research

Selection of bull-damsbulls for AI

Dissemination of natural mating bulls and heifers to farmers

67

Looking forward to discuss collaboration in dairy breeding

Conclusions ndash pathways towards implementation

ldquoNational breeding program and national infrastructurerdquo should support

the relevant complementary strategies

Upgrading

Development of synthetic breeds

Conservation and improvement of indigenous breeds

More effective and efficient AI delivery system needed

AI centres should make available semen of lsquoexotic bullsrsquo lsquocrossbred bullsrsquo

aacutend lsquoindigenous bullsrsquo

Investment in performance recording will pay off in the long run

selection of best animalsbull dams at private farms for further breeding

Conclusions ndash pathways towards implementation Import of semen or semen production in Ethiopia

Importing 100 exotic semen or importing young bulls is probably economically more

profitable than sourcing 100 exotic bulls for AI at Ethiopian (nucleus breeding) farms

No need to buy the most expensive semen ndash probably not the best for Ethiopian farmer

Use the national infrastructure of breeding and research farms for

Conservation and improvement of selected indigenous breeds

Development of synthetic breeds

Performance recording and research

Selection of bull-damsbulls for AI

Dissemination of natural mating bulls and heifers to farmers

67

Looking forward to discuss collaboration in dairy breeding

Conclusions ndash pathways towards implementation Import of semen or semen production in Ethiopia

Importing 100 exotic semen or importing young bulls is probably economically more

profitable than sourcing 100 exotic bulls for AI at Ethiopian (nucleus breeding) farms

No need to buy the most expensive semen ndash probably not the best for Ethiopian farmer

Use the national infrastructure of breeding and research farms for

Conservation and improvement of selected indigenous breeds

Development of synthetic breeds

Performance recording and research

Selection of bull-damsbulls for AI

Dissemination of natural mating bulls and heifers to farmers

67

Looking forward to discuss collaboration in dairy breeding

67

Looking forward to discuss collaboration in dairy breeding