Performance evaluation

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This is the 4th webinar in a five part series on Breeding Better Sheep & Goats. This presentation entitled "Performance Evaluation" was given by Susan Schoenian, University of Maryland Extension Sheep & Goat Specialist.

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Performance evaluation

  1. 1. 2013 Winter Webinar Series: Breeding Better Sheep & Goats Performance Evaluation SUSAN SCHOENIAN Sheep & Goat Specialist University of Maryland Extension sschoen@umd.edu - www.sheepandgoat.com
  2. 2. Making better sheep and goats WHERE WE’VE BEEN WHERE WE NEED TO GO Phenotype GenotypeGenotype + environment Genetic merit Visual appraisal Performance evaluation How animal looks How animal performs Subjective criteria Objective criteria What we see What we measure
  3. 3. Performance evaluationIndividual records Genetic predictors • Adjusted weights • EPDs • Milk yield • EBVs • Fleece weight • DHIR • Staple length • Ultrasound data • Fecal egg counts • FAMACHA© scores • Fiber analysis • Performance ratios
  4. 4. Performance evaluation: set goals• What is the primary purpose of your sheep and/or goat enterprise?• If you are a seedstock producer, what is the primary role of your breed(s) in commercial production systems?• Determine which traits are most important to your herd, flock, or breed.
  5. 5. Niche fiber ColorDairy LusterMilk yield HandlePercent protein CrimpPercent fat Staple lengthUdder conformation Fiber diameterLinear appraisal Seedstock Varies by breed Scrapie genotype
  6. 6. Your selected traits • Are they economically important to your farm and/or breed? • Can the traits be objectively measured (when and how)? • Will they respond to selection or (crossbreeding)?
  7. 7. Performance evaluation startswith animal identification Options 1. Ear notches 2. TattoosMore permanent 3. Electronic 4. Ear tags 5. Paint brands 6. Neck chains
  8. 8. To make genetic improvement,you have to keep good records. • Everyone should keep basic reproductive and health records. • What additional records you keep (and data you collect) will depend upon your production emphasis and breed. • A central performance test will collect data on potential sires.
  9. 9. Record keeping optionsUsing a computer Handwritten• Spreadsheet 1. Pocket book• Database 2. Notebook• Third party software 3. Chalkboard• Online• University
  10. 10. Keeping records by hand (pencil)
  11. 11. Spreadsheets for record keeping
  12. 12. Record keeping softwarehttp://www.sheepandgoat.com/software.html#flock
  13. 13. Performance evaluation • Records aren’t very useful unless you use them for decision- making purposes. – Ram/buck selection – Selection of replacements – Keep/cull decisions – Decisions to castrate • Records need to be properly analyzed and used to be effective for genetic improvement.
  14. 14. An important aspect of performance evaluationContemporary group• Comparisons should only be made between animals in the same contemporary group.• A group of the same breed, born within +/- two weeks with each other, raised at the same location or in the same herd or flock, of the same sex and managed alike from birth until time of measurement.
  15. 15. Factors affecting contemporary groups • Breed percentage • Sex • Lambing/kidding period • Location • Management factors – Health – Nutrition Animals which receive preferential treatment should be placed within their own contemporary group.
  16. 16. Another important aspect of performance evaluation Adjustments• Sometimes records (data) need to be “adjusted” to remove environmental effects.• Records are adjusted to a standard animal or weight – Weaning weights Single male offspring raised by a 3-6 year old dam. – Loin eye area 125-lb. market lamb 100-lb. Katahdin ram lamb
  17. 17. Calculating adjusted weaning weights 1. Adjust weaning weights to a common day of age (usually 60, 90, or 120 days of age) a) Determine animal’s pre- weaning average daily gain (ADG). b) Multiply pre-weaning ADG by common age. c) Add birth weight 2. Adjust weaning weight for sex of offspring, age of dam, and type of birth and rearing a) Multiply age-corrected weaning weight by appropriate adjustment factor.
  18. 18. Adjustment factors allow animals to be fairlycompared by removing non-genetic factors.
  19. 19. Adjustment factors vary by species and breed. When breed-specificadjustment factors are not available, generic adjustment factors can be used.
  20. 20. Adjustment factors for meat goats (Boer)
  21. 21. Example• Calculate the 60-day adjusted weaning weight for a Dorset ram lamb born on March 1 and weaned on June 10. The lamb was born and raised as a twin. His birth weight was 10 lbs. He weighed 70 lbs at weaning. His dam was 2 years old. 1) Determine pre-weaning ADG 2) Multiply pre-weaning ADG weight by common age 3) Add birth weight back in 4) Multiply age-corrected weight by adjustment factor (see TABLE)
  22. 22. Born March 1 Born/raised twin Weaned June 10 Birth weight - 10 # Weaning weight - 70 # Example Age of dam - 2 yrs 1) Determine pre-weaning ADG (weaning weight - birth weight*) age (in days) (70 - 10) 71 d = 0.85 lb/d*If birth weight is not known, a weight per day of age (WDA) can be calculated instead.
  23. 23. Born March 1 Born/raised twin Weaned June 10 Birth weight - 10 # Example Weaning weight - 70 # Age of dam - 2 yrs 2) Multiply pre-weaning ADG weight by common age (0.85 x 60 d) = 51.0 lbs. 3) Add birth weight back in* 51.0 lbs. + 10 lbs. + 61.0 lbs.*If WDA was calculated instead of pre-weaning ADG, do not add a birth weight back in.
  24. 24. Born March 1 Born/raised twin Weaned June 10 Birth weight - 10 #Example Weaning weight - 70 # Age of dam - 2 yrs4) Multiply age-corrected weight by adjustment factor 61.0 lbs. x adjustment factor 61.0 lbs. x 1.16 = 70.8 lbs.
  25. 25. Performance ratios• The percent above or below the average of the contemporary group.• Performance ratio Individual performance average performance of group x 100
  26. 26. Example: performance ratioWhat is the WW ratio for buck #6 ID Adj. WW 1 44 Individual performance x 100 2 38 3 32 Average performance of group 4 50 5 48 6 45 45 lbs x 100 7 40 41.7 lbs 8 41 9 40 10 39 = 108 % Avg 41.7
  27. 27. Selecting for parasite resistance• Measure fecal egg counts Can only compare animals in when animals are between 4 same contemporary group. and 12 months of age.• Compare average fecal egg count of an individual lamb or kid to the group average (at least 15-25 animals).• A high worm load is needed to select for parasite resistance (> 500 epg avg.)• More measurements  more selection accuracy• A resistant male is needed to make much progress.
  28. 28. Selecting for parasite resistanceSIRE SELECTION• Choose sire with lowest average progeny FEC. REPLACEMENT SELECTION • Choose replacements from sire(s) with lowest average FEC (if more than one sire) • Choose replacements with lowest FECs in group.
  29. 29. How we select for parasite resistance in our buck test 1 Top 10 2 3 4 5 6 7 8 9 10 10 9 8 7 Bottom 10 6 5 4 3 2 1 All goats were triple-dewormed (moxidectin + levamisole + albendazole) on 6/2. Twelve days later, the average fecal egg count was near zero.
  30. 30. How we select for parasite resilience in our buck test 1 2 3 4 0 5 Top 10 6 7 8 9 10 10 9 8 7 6Bottom 10 5 4 3 2 1 All goats were triple-dewormed (moxidectin + levamisole + albendazole) on 6/2. For the next 8 weeks, the average FAMACHA© score improved and no goat required deworming.
  31. 31. What about visual appraisal?Does it matter what the animal looks like? Absolutely!
  32. 32. There should always be minimum standards forreproductive soundness and structural correctness. • Reproductive soundness a) Testicles b) Teeth c) Teats and udder • Structural correctness a) Feet and legs b) Jaw set c) Conformation
  33. 33. Emphasis on visual appraisalCommercial Show ring• Minimum standards • Very important• More stringent standards for • Economic trait rams and bucks• Some (?) correlation with • Some traits are highly productivity and heritable. longevity, especially with dairy • Low correlation with females. productivity.• Many fleece traits are subjectively evaluated. Visual appearance is still a very important aspect of market acceptance.
  34. 34. Final webinar: Feb 19, 7 pm EST“Advanced Genetic Improvement”

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