Making the Web equal Profit Surfing for Genetics Dorian Garrick & Mark Enns Department of Animal Sciences Colorado State University

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


W W D = 20 lb W W D = 50 lb

Herd 1 Average 500 lb Average 530


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



Suppose 20% heifers are openAnd 80% heifers are pregnant


20%

Heifers not in calfPregnant Heifers



20%

Truncn pt = 0.84


Threshold


0.38

20%

Truncn pt = 0.84



0.38Phenotypic s.d. = 1.17

20%

Truncn pt = 0.84

Truncn pt = 0.84 +0.38/1.17=1.165

12%



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:

• First Calf: 75, 80, 85, 90, 95%• Mixed Age: 95, 99%

– Stayability: 40, 45, 50, 55, 60%– Heifer Pregnancy: 75, 80, 85, 90, 95%

Solutions (cont)Solutions (cont)

• OR Use web-based decision support– User defined average levels of performance– Compute the

• number of pregnant vs open heifers• number of easy vs difficult calvings• Likely age structure of the herd

– Number of replacement heifers required– Number of cull yearlings and mixed age cows

Suppose our goal is incr sale wtSuppose our goal is incr sale wt

W W D = 20 lb W W D = 50 lb

Base Base+30 lb

Interactions between ERTsInteractions between ERTs

• WWD EPD + 30 lb (all other EPDs equal)– gives +30 lb weanlings


• WWD EPD + 30 lb (all other EPDs equal)– gives +30 lb weanlings– gives +22 lb weanling sale wt “per cow” in a

“typical” self-replacing herd




• Increasing ST +8 will give another +8 lb





• Increasing HPG +12 will give another + 3lb





• Increasing HPG +12 will give another + 3lb

• Increasing CED +11 will give another +1 lb


• Many ERT interact in a system context

• Total sale weight at weaning is altered by WWD, WWM, STAY, HPG, CED, CEM, ME (plus BW & YWT)

• The impact of any one EPD on the change in sale weight depends upon all the other EPDs and the average levels of performance

Assessment of Nutritional Assessment of Nutritional (& other input) Implications(& other input) Implications

• Feed requirements are influenced by the– Expected maintenance requirements– Expected requirements for gain– Deviation from our expectations

(known as residual feed intake or RFI)

• Changing any of WWD, WWM, STAY, HPG, CED, CEM, ME, BW, YW will alter whole herd feed requirements

Assessment of Financial Assessment of Financial ImplicationsImplications

• Changes in profit can be calculated from change in income × priceschange in expenses × costs

– Straightforward (but tedious) arithmetic

• Prices & Costs can be obtained on a financial basis or an economic basis– What is the cost of feed in an extensive cow-

calf grazing operation?

Economic Cost of FeedEconomic Cost of Feed

• Feed “cost” can be calculated from its “opportunity” cost– Measure of what net income would be given

up if you had less feed (and less cows)– Can be calculated from comparing the system

profit of two herds of alternative genotypes with different stocking rates such that each consume the same amount of feed

SolutionsSolutions

• Leave it to bull buyers to struggle thru facts & calculations

• OR put it all together via the web

Website ert.agsci.colostate.edu

Current Philosophical ApproachCurrent Philosophical Approach

Current(equilibrium)

CowHerd(EPD

&Performance)

LikeMeritBulls

Base Cow-calf outputs & inputs

Base Situation Perturbed Situation

X



CowHerd(EPD

&Performance)

LikeMeritBulls



CurrentCowHerd

(EPD)

ChosenBulls

Daughter(equilibrium)

CowHerd(EPD

& Base meanPerformance)

X

X



CowHerd(EPD

&Performance)

LikeMeritBulls



CurrentCowHerd

(EPD)

ChosenBulls

Daughter(equilibrium)

CowHerd(EPD

& base meanPerformance)

LikeMeritBulls

Perturbed Cow-calf outputs & inputs

X

X

X

Accounting for RiskAccounting for Risk

Consider the following three bulls

Bull #prog Acc Profit

Lima 30 0.5 to 0.6 $908

Sierra 240 0.7 to 0.8 $729

Bravo 3700 0.8 to 0.95 $648


• On average, true EPD is equally likely to be greater or lesser than published

• ACC allows us to quantify the extent to which the estimate may vary from true

• Considering just BW, WW, YW, Milk, ME and not (in this example) CED, CETM, HPG, ST we can compute many possible “realizations” of each bull

Extra Profit per 30 daughter-yearsExtra Profit per 30 daughter-years

0

2

4

6

8

10

12

500 700 900 1100 1300

$648

3700 progeny


0

2

4

6

8

10

12

500 700 900 1100 1300

$729

3700 progeny

240 progeny


0

2

4

6

8

10

12

500 700 900 1100 1300

$908

3700 progeny

240 progeny

30 progeny

SolutionSolution

• Publish an “expected change” table

• OR provide web options for quantifying risk (prototype available this Fall)

Multibreed Evaluation & XbreedingMultibreed Evaluation & Xbreeding

EPD

Bull Within Breed

Angus 1* +65

Angus 2 +80

Simmental 3* +58

Simmental 4 +68

*A1 & S3 are breed average EPDs


YWT EPD

Bull Within Breed Multibreed#

Angus 1* +65 +65

Angus 2 +80 +80

Simmental 3* +58 +80

Simmental 4 +68 +90

*A1 & S3 are breed average EPDs #Angus Base


YWT Cow Breed

MBE Angus Simm Heref

Angus 1 +65 Base

Angus 2 +80 +15

Simm 3 +80

Simm 4 +90


YWT Cow Breed


Angus 1 +65 Base

Angus 2 +80 +15

Simm 3 +80 +hAS+15

Simm 4 +90 +hAS+25


YWT Cow Breed


Angus 1 +65 Base +hAS

Angus 2 +80 +15 +hAS+15

Simm 3 +80 +hAS+15

Simm 4 +90 +hAS+25


YWT Cow Breed


Angus 1 +65 Base +hAS

Angus 2 +80 +15 +hAS+15

Simm 3 +80 +hAS+15 +15

Simm 4 +90 +hAS+25 +25


YWT Cow Breed


Angus 1 +65 Base +hAS +hAH

Angus 2 +80 +15 +hAS+15 +hAH+15

Simm 3 +80 +hAS+15 +15

Simm 4 +90 +hAS+25 +25


YWT Cow Breed


Angus 1 +65 Base +hAS +hAH

Angus 2 +80 +15 +hAS+15 +hAH+15

Simm 3 +80 +hAS+15 +15 +hHS+15

Simm 4 +90 +hAS+25 +25 +hHS+25


YWT Cow Breed


Angus 1 +65 850 lb 863 873

Angus 2 +80 865 878 888

Simm 3 +80 878 865 878

Simm 4 +90 888 875 888

SolutionSolution

• Publish within-breed EPDs– Let users find breed adjustments & heterosis

• 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)

Documents

Making the Web equal Profit Surfing for Genetics Dorian Garrick & Mark Enns Department of Animal Sciences Colorado State University