Published on

This PowerPoint presentation is from the third webinar in a five part series on Breeding Better Sheep & Goats. The presenter is Susan Schoenian, University of Maryland Extension Sheep & Goat Specialist.

Published in: Education
1 Comment
1 Like
  • so much I have learnt from these slides. thank you.
    Are you sure you want to  Yes  No
    Your message goes here
No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide


  1. 1. 2013 Winter Webinar Series: Breeding Better Sheep & Goats Selection SUSAN SCHOENIAN Sheep & Goat Specialist University of Maryland Extension -
  2. 2. Two ways to make genetic improvement1. Crossbreeding Generally, traits which respond well to crossbreeding ( heterosis) do not respond well to selection.2. Selection Conversely, traits which respond well to selection ( heritability) usually do not respond well to crossbreeding (heterosis). Crossbreeding Selection
  3. 3. What is selection?• Choosing which animals get to be parents.• Choosing which male and female mate. Top-performing bucks Replacement females
  4. 4. Two kinds of selection1. Natural - “survival of the fittest”2. Artificial - breeding plants or animals for specific traits (human intervention) Soay - natural selection Merino- artificial selection
  5. 5. What is the goal of selection?• Improve the frequency of desirable alleles.• Reduce frequency of undesirable alleles.• Eliminate deleterious genes. Top-selling Katahdin ram
  6. 6. What makes selection difficult?• Most traits of economic significance are quantitative (polygenic) - controlled by many genes.• Phenotype ≠ Genotype We can’t see genes.• Sometimes, it’s difficult to separate genetics from environmental influences.• Some traits cannot be directly or easily selected for.• Quantitative (population) genetics is about probabilities. P=G+E
  7. 7. Selection basics• Heritability (h2)• Repeatability (R)• Selection differential (SD)• Generation interval (L)• Genetic progress (G) Kiko bucklings from 2012 buck test
  8. 8. Heritability - h2• The proportion of phenotypic variation in a population that is due to genetics (genotype).Litter size (prolificacy) Milk yield Tail length h2 = 10 percent h2 = 30-35 percent h2 = up to 82 percent
  9. 9. Heritability estimates• There are a lot of h2 estimates for most sheep traits.• There are h2 estimates for most dairy goat traits.• It’s harder to find h2 subjectively measured traits.• H2 estimates usually vary by species, breed, and • There aren’t many h2 environment, so averages are estimates for meat goats, often used. so we usually use sheep estimates.
  10. 10. Heritability of different traitsTrait type Heritability Genetics EnvironmentReproductive Low 5-20% 85-100%Growth Moderate 10-50% 50-90%Carcass Moderate 10-45% 55-90%Fleece Moderate to high 25-55% 45-75%Lactation Moderate 15-35% 65-85%
  11. 11. Heritability of reproductive traitsMost maternal traits have a low heritability (<20%). Trait Avg. h2 Age at puberty 0.25 Ewe fertility* 0.05 Ewe productivity * 0.20 Gestation length 0.45 Lamb survival * 0.05 Libido 0.22 Longevity 0.27 Mothering ability 0.39 Out-of-season breeding 0.20 Prolificacy * 0.10 Scrotal circumference * 0.35 Spring fertility 0.07-0.11 Katahdin *Source: Sheep Production Handbook (2002)
  12. 12. Heritability of growth traitsMost growth traits are moderately heritable (20-40%). Trait Avg. h2 Birth weight * 0.15 60 day weight * 0.10 90 day weight * 0.15 120 day weight * 0.20 240 day weight * 0.40 Mature weight 0.50 Feed efficiency 0.26 Post-weaning gain 0.25 Pre-weaning gain 0.15 *Source: Sheep Production Handbook (2002) South Dakota lambs
  13. 13. Heritability of carcass traitsMost carcass traits are moderately heritable (20-40%). Trait Avg. h2 12th rib fat thickness * 0.30 Bone weight 0.30 Carcass length 0.31 Carcass weight * 0.35 Dressing percent * 0.10 Grade 0.12 Lean weight 0.39 Loin depth 0.15-0.38 Loin eye area * 0.35 Percent retail cuts * 0.40 Weight of retail cuts * 0.45 Southdown lamb *Source: Sheep Production Handbook (2002)
  14. 14. Heritability of fleece traitsSheep fleece traits are moderate to highly heritable (>25%). Trait Avg. h2 Character 0.33 Clean fleece weight* 0.25 Color * 0.45 Crimp* 0.45 CV of fiber diameter 0.50 Fiber diameter* 0.40 Grease fleece weight* 0.35 Handle 0.33 Staple length* 0.55 Yield (%)* 0.40 *Source: Sheep Production Handbook (2002) Rambouillet rams in South Dakota
  15. 15. Heritability of lactation (sheep)Most lactation traits are moderately heritable (20-40%). Trait Avg. h2 Fat percentage* 0.30 Fat yield* 0.35 Milk yield* 0.30 Protein percentage* 0.30 Protein yield* 0.45 Rear udder attachment** 0.15 Teat placement** 0.25 Teat size** 0.20 Udder height/depth** 0.15 *Source: Sheep Production Handbook (2002) Dairy ewe in Maryland ** Dave Thomas, University of Wisconsin
  16. 16. Heritability of production traits of dairy goatsDairy goat production traits are moderate to highly heritable (20-50%). Trait Avg. h2 Milk yield 0.35 Fat yield 0.35 Protein yield 0.37 Protein: fat ratio 0.37 Fat and protein yield 0.36 Fat percentage 0.52 Protein percentage 0.54 Age at first kidding 0.23 Kidding interval 0.05 Source: Breed differences over time and heritability estimates for production and reproduction traits of dairy goats in the United States (Journal of Dairy Science, 2012). Sannen doe in Maryland
  17. 17. Disease resistance Disease Avg. h2 Dag scores (scouring) 0.10 - 0.37 Facial eczema 0.45 Parasite resistance 0.25 - 0.50* [fecal egg counts] Fly strike 0.20 - 0.33 Foot rot 0.20 - 0.30 Mastitis 0.13 Parasite resilience 0.10 [PCV, FAMACHA© scores] Somatic cell count 0.10-0.20 (strong correlation to mastitis) Fecal egg counting with McMaster slide * Katahdin
  18. 18. Heritability of defects Defect Avg. h2 Cryptorchidism high (?) Entropion 0.15 (inverted eye lid) Face cover 0.56 (precursor to wool blindness) Multiple nipples high (?) Jaw position 0.13 Hernias high (?) umbilical, inguinal, scrotal Rectal prolapse 0.14 Vaginal prolapse low (?) Congenital scrotal hernia Source: various
  19. 19. Heritability of conformation and type Trait Avg. h2 Though not well documented, the heritability of individual conformation traits (e.g. height and length) is considered to be high. However, these traits are usually not Hampshire ewe in Kentucky strongly -correlated with performance.
  20. 20. Repeatability (accuracy)• Correlation (reliability) between repeated measurements.• Indicates the upper level of heritability.• Traits with high heritability usually have high repeatability. Top-performing buck (Kiko) from 2009 Test
  21. 21. Generation interval• Average age of parents when progeny are born. Varies by gender and management. Yearling Katahdin ewe 11 year old Katahdin ewe
  22. 22. Selection differential (SD)• Difference between selected animals and the average of the population from which they were selected. Average of population Average of selected population Selection differential 500 epg 1500 epg 10000 epg
  23. 23. Genetic progress (G) G = h2 x selection differential generation interval G = 0.40 x [1500-500] 4 G = -100 epg per year -500 epg in 5 years -1000 epg in 10 yearsThis is a “simplistic” example. Other factors, such as repeatability, will affect genetic progress.
  24. 24. Most genetic progress when…• Heritability is high.• Repeatability is high.• Selection differential is wide.• Generational interval is short (though there is a trade-off with selection differential). Rambouillet lambs in South Dakota
  25. 25. Practical aspects of selection • Animal identification a) Permanent b) Unique • Data collection a) Reproduction b) Growth c) Milk d) Fleece e) Carcass f) Disease resistance g) Defects • Record keeping and analysis a) Pedigree b) Performance c) Type
  26. 26. Methods of selection • Individual • Family/pedigree • Progeny • Combined – EPD – EBV – MPPA
  27. 27. Methods of selection In Targhee breed, each 1 lb. increase in1. Single trait weaning weight resulted in a 2 ½ lb.  Generally not recommended increase in ewe mature body size.2. Multiple trait  Success of raising sheep and/or goats depends upon improvement or more than one trait.  Single trait selection can have unexpected and undesirable consequences due to genetic correlations or environmental responses. Dorper x Polypay lambs in Kentucky
  28. 28. Multiple trait selection 1. Tandem selection 2. Independent culling levels 3. Selection index Dairy goat in Brazil
  29. 29. Tandem selection • Focus on one trait at a time until a satisfactory level of performance is achieved; then move on to another trait and so forth. • Selection may result in changes (positive or negative) to correlated traits. – Milk yield vs. fat percentage (antagonistic) – Staple length vs. fleece weight Scottish Blackface ram (favorable)
  30. 30. Independent culling levels Select for two or more traits simultaneously. Establish a minimum standard for each trait.Examples1) Western Maryland Pasture-Based Meat Goat Performance Test Gold, Silver, and Bronze Standards of Performance for growth rate, parasite resistance, and parasite resilience.2) On-farm Keep only twin-births Don’t keep any kids that require deworming more than once. Top-performing buck (Kiko)
  31. 31. Selection index• Combine traits for overall merit 1) On-farm 2) Central performance test 3) EPD’s 4) Profitability Source: Montana State University
  32. 32. Index examplesSimple productivity index for meat sheep and goatsPounds of (quality) lamb or kid weaned[composite trait: fertility + litter size + mothering ability + offspring survival + milk production]“Old-time” sheep productivity index[Pounds of lamb + (2.5 x fleece weight)]Pennsylvania Meat Goat Buck Test40% average daily gain20% weight per day of age20% loin eye area (adjusted)20% leg circumference (adjusted)Profitability index (Targhee sheep - farm flock)$1.00 WW + $0.36 MM - $0.40 YW + $1.14 FW - $0.30 FD + $0.19 LCProfitability index (Targhee sheep - range flock)$1.00 WW + $0.26 MM - $0.26 YW + $1.92 FW - $0.47 FD + $0.36 LCEPD’s: WW=weaning weight, MM-maternal milk, YW=yearling weight, FW=fleece weight, FD=fiber diameter, and LC=lamb crop
  33. 33. Next webinar: Feb 12, 7 pm EST “Performance Evaluation”