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Breeding for SSD

(by Leo Dempfle, Department of Animal Science, Technology University of Muchen)

Slide 1

Workshop on Small-scale Dairying (SSD)

- Breeding for SSD -

Prof. Dr. Leo Dempfle

Technical University Munich, Germany

Slide 2

Dairy Production System

  • Animal Production (dairy production) - complicated system

  • Breeds/ Genetic improvement is one of several components

  • What is best depends on the whole system!

You cannot optimize it in isolation!!!

Slide 3

  • There are many factors and there are many interactions!!

  • Since it is my topic

    I concentrate on the question of

    Breeds - Cross breeding - Genetic Improvement

Slide 4

How to approach 'improvement'??

  • Take what you have as baseline (benchmark) and try to optimize (in an economic sense) the management

  • Answer the question whether the conditions are good enough that other breeds might be feasible?

Can you import genetic improvement?

Slide 5

Breed comparison

Take into account all aspects which have impact on the economics

  • milk yield (fat + protein yield)

  • carcass value

  • mortality

  • fertility/reproduction

  • health/disease

  • etc. etc.

    The comparison has to be done
    at the same time under the same circumstances
    (good production circumstances)

    Hi = a1g1i + a2g2i +... + akgki

Slide 6

Difficulties of comparison

Having n unrelated cows of each breed

If we look at the confidence interval, we obtain

Slide 7

If the n cows are related (daughters of s sires, sk=n) then the accuracy can be much lower

Slide 8

Possibilities of exploiting breeds

One can use

1) an indigenous breed

2) an exotic breed (breed replacement)

3) (continuous) F1 - Crosses

4) Criss-Cross breeding

5) Synthetic breed (varying proportion depending on...)

In order to decide you need

information, information, information!!!

Slide 9

Continous F1 Cross

116000 cows

58000 cows annually mated

2000 cows mated
to exotic bulls

56000 cows mated to N'Dama bulls

80% conception

800 males 800 females

640 heifers

1920 cows

2 880 000 kg milk

For 144 000 people

Slide 10

Forming a Synthetic breed

Slide 11

Forming a Synthetic breed

Slide 12

Using Criss-Cross(Rotational Cross-Breeding)

Slide 13

If you have decided for

  • indigenous breed

  • [exotic breed]

  • Criss-Cross

  • synthetic breed

you want to increase the efficiency further by

genetic improvement

of the genetic material (breed) involved.

Slide 14

However, genetic improvement

  • is very slow and small

  • and it is difficult to recover the expenses

but it is

  • permanent

  • cumulative

  • multiplicative

Slide 15

The disadvantages:


Improvement is often approximately of about one percent of the mean per year

Recovery of expenses:

There is usually no patent; once you sell an animal, the new owner can use it in his breeding - in his genetic improvement scheme.

But if you cannot recover the expense why doing (privately) genetic improvement work?

We have the situation that
a private good is becoming rapidly a common good

Slide 16

The advantages:
It is permanent and it is cumulative

Due to the present efforts (performance recording, intense selection) we achieve genetic progress which ins permanent.

The worth of the investment of a single cycle of selection is:

Repeating the cycle we add the new progress to the old one (it is cumulative)

Slide 17

It is multiplicative

Genetic improvement can be done in a relatively small subpopulation - the nucleus

In pig breeding
nucleus -several lines -altogether 1000 - 2000 sows
commercial unit - 8 000 000 fattening pigs

Slide 18


Work should be concentrated on the nucleus

Only there it is cumulative
(In the multiplier it is always diluted)

We have N animals tested each generation
We select K animals (cull N-K animals)

Slide 19

In the nucleus we must most accurately record

  • performance

  • pedigree (sire and dam)

The genetic progress per year is given

In each path we have i, r, t which vary

Slide 20

i: intensity of selection (K out of N); e.g.

1 out of 400: i =2.968
2 out of 400: i =2.813
10 out of 400: i =2.317
50 out of 400: i =1.642
100 out of 400: i =1.268
200 out of 400: i =0.796
400 out of 400: i =0.000

Slide 21

r: correlation between true and estimated breeding value

It depends on

  • amount of information (own performance, dam's performance, offspring's performance)

  • statistical procedure (BLUP)

  • design of performance testing

t: generation interval (average age of parents at birth of offspring)

This is drastically different for a young sire scheme and for a progeny testing scheme

The expression DH/Dt has to be maximized for the given economic situation

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