Towards more uniform pig performance. Craig Lewis and Susanne Hermesch
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1 Towards more uniform pig performance Craig Lewis and Susanne Hermesch
2 Variability: The issue... - Cost to industry $ - Stabilise the supply chain - Targeting the main traits that increase variability - Maximise pig numbers and growth of pigs consistent performance to guarantee consistent supply of pork
3 Variability: Statistical definition N Spread or Standard deviation Average or Mean
4 Variability: Statistical definition Medium SD High SD Low SD
5 Variability: Statistical definition Medium SD High SD Low SD
6 Variability: Statistical definition Medium SD High SD Low SD
7 Variability: Statistical definition: It means... - Mean ± 1 SD = 68.2 % - Mean ± 2 SD = 95.4 % - Mean ± 3 SD = 99.6 % - EXAMPLE - Farm mean Backfat = 11 & SD = 1 mm - Penalty if Backfat greater than 12 mm % of pigs will invoke penalty
8 Variability: The issue... - Be aware! Mean and standard deviation linked! - The SD will increase with a larger mean - This is called the scaling effect
9 Variability: What the issue means - For Backfat - Lower backfat means less variation - For Growth - If you want less variation reduce the Mean - NOT IDEAL - Can we increase the mean and: - Not increase the SD - Perhaps decrease the SD
10 Variability: Tackling the issue genetically - General GOAL in breeding: Can we favourably move the mean without detrimentally moving variability? - More specifically: Can we breed for more uniform performance within a specific environment?
11 Uniformity: The theory A simple animal model: y i = Xβ + Z 1 a i + e i
12 Uniformity: The theory A simple animal model: y i = Xβ + Z 1 a i + e i Trait Fixed effects Animal (genetic) Error
13 Uniformity: The theory A simple animal model: y i = Xβ + Z 1 a i + e i Trait Fixed effects Animal (genetic) Error - Error or environmental component - Reflects the within-environmental and temporal sensitivity of the animals
14 Uniformity: Question Is there genetic variation in the residual component? Are there genetic differences between sires in the residual (error) variation of their progeny?
15 Uniformity: Basic two-step process Use performance traits from multiple progeny of selected sires Model One: (Use trait) Estimate genetic (mean) and error effects Model Two: (Use transformed error) Estimate genetic effects for variation Output of Model One & Two: Estimated Breeding Values for mean and variance
16 Uniformity: Genetics conclusion - The theory is still being developed - Major data issues: quality and quantity!!! - Hill and Mulder (2010) review show limited opportunities to select for reduced variation - Median h 2 V for pig traits = Moderate GCV E but unattainable currently
17 Variability: To the farm - GOAL at the farm: Can we identify and reduce variability at the farm level?
18 Variability: Farm level: The causes - Temporal within and between year - Breeds - Herds Location - Sex - Parity - Age... Management! - Birth litter - Genetics - Etc etc etc...
19 Variability: Trends - Selection has improved traits - What has this genetic improvement done to variation? - Data from National Pig Improvement Program - 15 years of records - 11 herds - 3 breeds - ~400,000 production records - ~85,000 reproductive records
20 Variability: Yearly trends: Production Backfat Lifetime growth ~0.8mm ~80g/day Corrected for end weight
21 Variability: Yearly trends: Production SD Backfat Lifetime growth
22 Variability: Yearly trends: Reproduction NBA 0.3piglets
23 Variability: Yearly trends: Reproduction SD NBA
24 Variability: Within year trends: Production Backfat Lifetime growth Corrected for end weight
25 Variability: Where is the variation from? - Between and within year shown - Quantification of ALL sources of variation - Used NPIP data once again - Examination of sources of variation
26 Variability: Proportion explained by each factor Source Backfat Growth NBA Year Month Year/month Breed Herd Sire Litter Weight Gestation length - - 6
27 Variability: Total - Total variation explained is not cumulative! - Variance partitioning, confounding, non-balanced - Best model explains only around 50 % of variability - Higher variation explained for performance traits than reproductive traits - Backfat = 47 %, Growth = 41 % - NBA = 29 %
28 Variability: Summary - Farm and packers say variation needs to reduce - Reduce costs improve profitability - Currently, no genetic solution - Use selection on the mean - Control variation on farm...
29 Variability: Summary (2) what you can do - Controlling variation on farm - Use sire EBVs (mean) for more uniform groups - Optimal environment for each pig - Consistent long-term management strategy - Consistency of inputs
30 Variability: Summary (3) what we can do - Further quantification of the variation will help! - Best models only explain 50% of the variation - Less for reproductive traits - Better definition of environments required - In association with accurate phenotypes & contemporary groups on farm
31 Thank you for your time. Thank you to breeders who provided data This work was supported by APL (Project 2133)
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Series 1: Cross Diagrams There are two alleles for each trait in a diploid organism In C. elegans gene symbols are ALWAYS italicized. To represent two different genes on the same chromosome: When both
Ecology- The study of the interractions of organisms with their physical environment and with each other and of the results of such interactions.
Topic 4: Ecology ---------- 4.1 communities and ecosystems ---------- Ecology- The study of the interractions of organisms with their physical environment and with each other and of the results of such