Making the Web equal Making the Web equal Profit Profit Surfing for Genetics Surfing for Genetics Dorian Garrick & Mark Dorian Garrick & Mark Enns Enns Department of Animal Department of Animal Sciences Sciences Colorado State University Colorado State University
Making the Web equal Profit Surfing for Genetics. Dorian Garrick & Mark Enns Department of Animal Sciences Colorado State University. Surfing for Genetics. Surfing for Convenience Surfing to Support Decisions based on your own Customized Computations. Convenience. - PowerPoint PPT Presentation
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Making the Web equal ProfitMaking the Web equal ProfitSurfing for GeneticsSurfing for Genetics
Dorian Garrick & Mark EnnsDorian Garrick & Mark Enns
Department of Animal SciencesDepartment of Animal Sciences
Colorado State UniversityColorado State University
Surfing for GeneticsSurfing for Genetics
• Surfing for Convenience
• Surfing to Support Decisions based on your own Customized Computations
ConvenienceConvenience
• Finding a Particular Bull/Breed/Breeder
• Sort Orders– Finding extreme bulls for some attribute
• Filters– Finding bulls with particular combinations of
attributes
• Up-to-date EPD and ACC information
Customized ComputationsCustomized Computations
• Interpretation of Threshold Traits
• Interactions between ERTs
• Assessment of Nutritional Implications
• Assessment of Financial Implications– Perhaps also Economic Implications
• Accounting for Risk
• Multibreed Evaluation & Crossbreeding
Interpretation of a Typical EPDInterpretation of a Typical EPD
W W D = 20 lb W W D = 50 lb
Interpretation of a Typical EPDInterpretation of a Typical EPD
W W D = 20 lb W W D = 50 lb
Herd 1 Average 500 lb Average 530
Interpretation of a Typical EPDInterpretation of a Typical EPD
W W D = 20 lb W W D = 50 lb
Herd 1 Average 500 lb Average 530Herd 2 Average 550 lb Average 580
Interpretation of Threshold TraitsInterpretation of Threshold Traits
• Calving Ease EPD
• Stayability EDP
• Heifer Pregnancy EPD
Underlying Scores to Preg RateUnderlying Scores to Preg Rate
Easy to get pregnant Difficult to get pregnantAverage
Underlying Scores to Preg RateUnderlying Scores to Preg Rate
Easy to get pregnant Difficult to get pregnantAverage
Suppose 20% heifers are openAnd 80% heifers are pregnant
Underlying Scores to Preg RateUnderlying Scores to Preg Rate
20%
Heifers not in calfPregnant Heifers
Easy to get pregnant Difficult to get pregnantAverage
Underlying Scores to Preg RateUnderlying Scores to Preg Rate
20%
Truncn pt = 0.84
Heifers not in calfPregnant Heifers
Threshold
Underlying Scores to Preg RateUnderlying Scores to Preg Rate
0.38
20%
Truncn pt = 0.84
Heifers not in calfPregnant Heifers
Underlying Scores to Preg RateUnderlying Scores to Preg Rate
0.38Phenotypic s.d. = 1.17
20%
Truncn pt = 0.84
Truncn pt = 0.84 +0.38/1.17=1.165
12%
Heifers not in calfPregnant Heifers
Underlying Scores to Preg RateUnderlying Scores to Preg Rate
0.38Phenotypic s.d. = 1.17
10%
Truncn pt = 1.28
Truncn pt = 1.28 +0.38/1.17=1.605
5.5%
Sensitive to the AverageSensitive to the Average
• An underlying EPD of 0.38 for heifer pregnancy would increase pregnancy rate– By 8.0% if average pregnancy rate is 80%– By 4.5% if the average is 90%
• Phenotypic “interpretation” of underlying threshold scores depends upon the mean
• Published values are at a mean of 50%
SolutionSolution
• Publish values that are hard to interpret
• OR Publish tables of EPDs relevant to different average levels of performance– Calving Ease:
• Publish multibreed EPDs– Let users deal with heterosis coefficients &
heterosis
• Publish all EPDs on a multibreed base with heterosis factors included according to the breed of dam for every ERT
• Use web-based decision support
SummarySummary
• To date, the major value of the web has been convenience
• In future, the web will provide an interface to knowledge (eg nutritional requirements and heterosis factors) and information that for customized calculations to support your decisions
• Better decision support will give better decisions (eg more profit)