lauren christian endowed lecture egbert f. knol

Peri-natal survival of pigletsunderstanding and genetics

Lauren Christian Endowed Lecture

Egbert F. Knol

Road map

Challenge• Our business is efficient pork production• Our responsibility is to maintain animal integrity• Pork chain mortality is out of bounds in many situations

Peri-natal survival: • Basics• Genetics• Piglet side : vitality• Nurse sow side : mothering ability

Genomics will helpMission for all of us

Challenge

Our business

FARROW

FINISHFEED PORK

Efficiency

FARROW

FINISHFEED PORK

PORK

FE =-----------

FEED

Losses on the way

FARROW FINISHFEED PORK

Losses drain efficiency; feed is invested, but not harvested

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†

††

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GOOD: 12 weaned

FARROW FINISHGestation lactation nursery finishing

LOSSES30 ova shed

15 piglets born1 stillborn

14.3% PWM 2% nursery

5% sow mortality 3% finishing

76% of total born reaches plant

GOOD: 12 weaned

FARROW FINISHGestation lactation nursery finishing

LOSSES

30 ova shed

15 piglets born

Crowding? Selection for increased litter size overdone?(Canada, university of Alberta, Foxcroft et al.)

GOOD: 12 weaned

FARROW FINISHGestation lactation nursery finishing

LOSSES30 ova shed

15 piglets born1 stillborn

14.3% PWM 2% nursery

20% peri-natal mortality in a good situation

GOOD: 12 weaned

FARROW FINISHGestation lactation nursery finishing

farrowing survival

preweaning survival

Correlated responses backward and forward

Added challenge

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0.50

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0.70

0.80

1995 2000 2005 2010 2015 2020 2025 2030 2035

Hours spent per piglet in a farrowing unit

Hou

rs

Year

Basics

Modeling of test farm

86.3

0

20

40

60

80

100

0 0.5 1 1.5 2 2.5

Bell curve is birth weight distribution

S – curve is Survival curve

Weight (kg)

Freq

uen

cy/%

su

rviv

al

Increasing birth weight

86,3

88,9

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40

60

80

100

0 0,5 1 1,5 2 2,5

Reducing variation

86,3

87,2

-20

0

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40

60

80

100

0 0,5 1 1,5 2 2,5

Increasing survival

88.4

86.3

0

20

40

60

80

100

0 0.5 1 1.5 2 2.5

Duroc (black) against Pietrain

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20

40

60

80

100

0 0.5 1 1.5 2 2.5 3

Birth weight

Preweaning survival

Sire differences

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20

40

60

80

100

0 1 2 3

>350 offspring each

Pre

-wean

ing

su

rviv

al

2 lbs 4 lbs

Genetics of survival

Death: whom to blame?

Genes of the piglet?

Genes of the sow?

Genes of the foster?

Genetic models

Classic approach• Litter mortality = HYS + sow (+ error)• Litter survival = HYS + service sire + sow

Improved (still recording at litter level)• Litter survival = HYS + service sire + sow

Our perception• Piglet survival = HYS + f(BW) + animal + dam + foster• Animal = piglet vitality, • Dam = uterine quality and • Foster = mothering ability

Piglet weighing

> 500,000 piglets per per year

Validation: 100 low against 100 high EBV litters

Low EBV

High EBV

Expected survival 78 % 82 % Realized survival Litter size Birth weight Variation in birth weight

Validation: 100 low against 100 high EBV litters

Low EBV

High EBV

Expected survival 78 % 82 % Realized survival 78.0 % 81.1 % Litter size Birth weight Variation in birth weight

Validation: 100 low against 100 high EBV litters

Low EBV

High EBV

Expected survival 78 % 82 % Realized survival 78.0 % 81.1 % Litter size 12.4 12.4 Birth weight 1500 1470 Variation in birth weight 301 291

Piglet vitalityThe animal effect from the model

Why does it work?

• 25 high EBV gilts mated to high EBV boars• 25 low low

• All 50 caesarian sectioned 2 days before farrowing, placentae weighed

• All 650 piglets fully dissected

• Organs weighed, length of intestinal tract, blood parameters etc. etc.

• More vital: heavier livers, more glycogen (P=0.04)

Blue: high EBV litters

0 50 100 150 200 250 300 350 400 450 500

Weight placenta

0

400

800

1200

1600

2000

Wei

ght

pigl

et

Jascha Leenhouwers en Tette van der Lende

High EBV littersmore cortisol

Table 5. Estimates and P-values for relationships of blood characteristics with EBVps of thelitter

Litter average Within-littervariationb

Characteristic Estimatea P-value Estimatea P-valueHematocrit, % 0.08 0.41 0.06 0.12Plasma venous glucose, mg/100 mL 0.14 0.62 -0.03 0.75Plasma arterial glucose, mg/100 mL 0.11 0.70 -0.03 0.77Serum estradiol-17ß, ng/mL -0.01 0.51 -0.003 0.71Serum cortisol, ng/mL 1.72 0.0001 0.16 0.53aEstimates indicate the increase or decrease in the respective characteristic with every percentage increase in EBVpsbcalculated as within-litter standard deviation

Jascha Leenhouwers, JAS 2002

Stronger piglets, not heavier!

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90

100

0.0 0.5 1.0 1.5 2.0 2.5 3.0

Birth weight

Pig

let s

urvi

val

Mothering abilityFoster effect from the model

What do we LIKE in a sow

• Quiet • Attentive• Enough teats• Quality of teats• Enough milk• Uniformity at birth and at weaning• Maintenance of body condition• ....

Lots of grad students needed…

Or: use EBV for mothering ability

1. Visual scan sampling

• 4 hours walking through farrowing rooms

• Visually ‘Scanning’ each sow every 5 minutes

• 5 observation days (days -2, 0, 7, 14)

• 80 sows, 150 traits

Position

Behaviour

2. Open field test

3. Aggression test

4. Questionnaire

Tattoo number 89BE65

Farrowing date 23 – 03 – 200 6

Aggressive to people X

Aggressive to piglets

No care for piglets

Fearful during handling X

Udder quality Birth 3 weeks

Number of teats 14

Regularity (low-high) 1 X 3 4 5

Litter quality Birth 3 weeks

Weight (low-high) 1 2 3 X 5 1 2 X 4 5

Uniformity (low-high) 1 X 3 4 5 1 2 X 4 5

Results: 1. Scan sampling

Sows with high EBV-MA:

• Less changes of posture

• Less activity

• Less in sitting position

Results: 2. Open field test

Sows with high EBV-MA:

• More exploring behaviour in open field

Results: 3. Aggression test

Sows with high EBV-MA:

• More lying laterally

• More vocalisation

• Less aggression (biting plush piglet)!!!

Results 4. Questionnaire

h² SD rg MA2

Aggressive to people 0.05 0.06

Aggressive to piglets 0.16 0.07

Fearful during treatment 0.06 0.07

Aggression + fear 0.12 0.07 -0.63

No care for piglets 0.03 0.05

Weight at birth 0.26 0.09 -0.03

Weight at weaning 0.22 0.08 0.12

Uniformity at birth 0.10 0.07 0.91

Uniformity at weaning 0.13 0.07 0.72

Regularity udder 0.10 0.07 0.16

Number of teats 0.21 0.08 0.38

Conclusion

Statistical model results in what we want:

• Quiet • Attentive• Enough teats• Quality of teats• Uniformity at birth and at weaning

No need for grad students here

Implementation in breeding program

EBV estimation

TR TR-NAME N-OBS MEAN SD MINIMUM MAXIMUM -------------------------------------------------------------------- 1 far. Surv. 4,216,879 92.942 25.612 0.0000 100.00 2 pws 3,904,329 89.438 30.735 0.0000 100.00 3 # teats 2,033,561 14.372 1.0220 1.0000 27.000 4 birth w. 475,147 1.4390 0.25681 0.51000 2.3900 5 uniformity 459,589 260.76 101.07 11.000 1189.0 6 longevity1 1,457,902 0.91772 0.27479 0.0000 1.0000 7 longevity5 1,214,124 3.9455 1.3778 1.0000 5.0000 8 age insem. 1,459,539 253.07 27.742 181.00 364.00 9 total born 6,520,197 12.583 3.3264 1.0000 30.000 10 stillborn 6,532,251 0.45817 0.56757 0.0000 3.2960 11 pwm 5,229,186 10.945 15.418 0.0000 100.00 12 interval 1,314,214 19.409 39.550 0.0000 100.00 13 gestation 6,492,273 115.13 1.6689 105.00 125.00

2 million piglets with underline count

4 million piglets weighed

1.2 million sows

corr

old new old new

survival 1742 2246 0.57 0.73 0.84

number total born 425 455 1.02 1.09 1.00average litter birth weight 840 1146 1.01 0.99 0.99litter variation 230 228 0.96 0.88 0.99gestation length 629 643 0.98 1.02 1.00

F- value estimate

Validation

1 take out 10,000 records

2 estimate breeding values on the remaining data

3 predict the 10,000

4 expected b-value should be 1.00

General conclusions

• Survival: management = selection

• Survival selection: hard work, but feasible

• Most genetic companies select, be it with different tools

• Faster than economic progress should be an option

• Longer gestation, lower variation in bw, but not higher bw

Next table closer than you might expect

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1995 2000 2005 2010 2015 2020 2025 2030 2035

Labour per piglet produced

Miranda’s slide, quoted by Foxcroft in Banff

Validation of this graph: 2 extreme sows

y = -0.0349x + 1.8968

R2 = 0.2437

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0.50

1.00

1.50

2.00

2.50

3.00

0 5 10 15 20 25

Andreia’s slide on variation

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500

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3500

0 5 10 15 20 25

Litter size

bir

th w

eig

ht

(g)

LW- LS-

LW+LS-

outlier

LW-LS+

LW+

y = -0.0475x + 2.005

R2 = 0.2548

y = -0.0594x + 2.1296

R2 = 0.3328

1

1.2

1.4

1.6

1.8

7 9 11 13 15 17 19

Total number born

Birt

h w

eigh

t

BRAZIL

NETHERLANDS

Birth weights on farms

2004-2011: 1.1 pig extra * 50 g= 55 g; trend is almost double

Resultaten onderzoek fase 1

Gemiddelde technische resultaten per groep

Laag Hoog

Gem. worpnummer 3,63 3,35

% Eerste worpen 22 20

Gem. geboortegewicht (gram) 1228 1440

Gem. levendgeboren / worp 12,7 13,0

Gem. doodgeboren / worp 1,4 0,9

% Uitval tot spenen 13,2 8,7

Gem. aantal gespeend 11,1 11,8

56

Seizoensinvloeden op geboortegewicht

1,300

1,350

1,400

1,450

1,500

1 2 3 4 5 6 7 8 9 10 11 12

Maand

Gem

idd

eld

ge

bo

ort

eg

ew

ich

t (k

g)

65 gram

Invloed pariteit op geboortegewicht

0

0,05

0,1

0,15

0,2

0,25

0,3

0,35

1 2 3 4 5 6 7 8

Pariteit

Kg

1,2

1,25

1,3

1,35

1,4

1,45

Kg

geb

. g

ew

.

Variatie in geb. gew. Gem. geb. gew.

Invloed pariteit op bigoverleving

72

74

76

78

80

82

84

86

88

1 2 3 4 5 6 7 8

Pariteit

%b

igo

verl

evin

g

Interesting remarks

• Sows housed in groups have piglets with heavier birth weights

BW Individual Group/ind Group

1.2 1 0 1

1.3 6 2 3

1.4 0 0 6

Group housing in gestationCorrected mean:

avg birthwtP-value # farmers

Yes 1.3878 0.24 12

No 1.3512 7

Raw data:

avg birthwtP-value # farmers

Yes 1.397 0.17 12

No 1.355 7

Thank you for your attention