lauren christian endowed lecture egbert f. knol
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Peri-natal survival of piglets understanding 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 - PowerPoint PPT PresentationTRANSCRIPT
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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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
0.00
0.10
0.20
0.30
0.40
0.50
0.60
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
0
20
40
60
80
100
0 0,5 1 1,5 2 2,5
Reducing variation
86,3
87,2
-20
0
20
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
0
20
40
60
80
100
0 0.5 1 1.5 2 2.5 3
Birth weight
Preweaning survival
Sire differences
0
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!
0
10
20
30
40
50
60
70
80
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
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
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
0.00
0.50
1.00
1.50
2.00
2.50
3.00
0 5 10 15 20 25
Andreia’s slide on variation
0
500
1000
1500
2000
2500
3000
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