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

Interpretation of a Typical EPD W W D = 20 lb W W D = 50 lb Herd 1Average 500 lbAverage 530

Interpretation of a Typical EPD W W D = 20 lb W W D = 50 lb Herd 1Average 500 lbAverage 530 Herd 2Average 550 lbAverage 580

Interpretation of Threshold Traits Calving Ease EPD Stayability EDP Heifer Pregnancy EPD

Underlying Scores to Preg Rate Easy to get pregnant Difficult to get pregnant Average

Underlying Scores to Preg Rate Easy to get pregnant Difficult to get pregnant Average Suppose 20% heifers are open And 80% heifers are pregnant

Underlying Scores to Preg Rate 20% Heifers not in calf Pregnant Heifers Easy to get pregnant Difficult to get pregnant Average

Underlying Scores to Preg Rate 20% Truncn pt = 0.84  Heifers not in calf Pregnant Heifers Threshold

Underlying Scores to Preg Rate % Truncn pt = 0.84  Heifers not in calf Pregnant Heifers

Underlying Scores to Preg Rate 0.38 Phenotypic s.d. = % Truncn pt = 0.84  Truncn pt = /1.17= % Heifers not in calf Pregnant Heifers

Underlying Scores to Preg Rate 0.38 Phenotypic s.d. = % Truncn pt = 1.28  Truncn pt = /1.17= %

Sensitive 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%

Solution 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) 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 wt W W D = 20 lbW W D = 50 lb Base Base+30 lb

Interactions between ERTs WWD EPD + 30 lb (all other EPDs equal) –gives +30 lb weanlings

Interactions between ERTs 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

Interactions between ERTs 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

Interactions between ERTs 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

Interactions between ERTs 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 CED +11 will give another +1 lb

Interactions between ERTs 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 (& 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 Implications Changes in profit can be calculated from change in income × prices change 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 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

Solutions Leave it to bull buyers to struggle thru facts & calculations OR put it all together via the web Website ert.agsci.colostate.eduert.agsci.colostate.edu

Current Philosophical Approach Current (equilibrium) Cow Herd (EPD & Performance) Like Merit Bulls Base Cow-calf outputs & inputs Base Situation Perturbed Situation X

Current Philosophical Approach Current (equilibrium) Cow Herd (EPD & Performance) Like Merit Bulls Base Cow-calf outputs & inputs Base Situation Perturbed Situation Current Cow Herd (EPD) Chosen Bulls Daughter (equilibrium) Cow Herd (EPD & Base mean Performance) X X

Current Philosophical Approach Current (equilibrium) Cow Herd (EPD & Performance) Like Merit Bulls Base Cow-calf outputs & inputs Base Situation Perturbed Situation Current Cow Herd (EPD) Chosen Bulls Daughter (equilibrium) Cow Herd (EPD & base mean Performance) Like Merit Bulls Perturbed Cow-calf outputs & inputs X X X

Accounting for Risk Consider the following three bulls Bull#prog AccProfit Lima to 0.6$908 Sierra to 0.8$729 Bravo to 0.95$648

Accounting for Risk 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-years $ progeny

Accounting for Risk $ progeny 240 progeny

Accounting for Risk $ progeny 240 progeny 30 progeny

Solution Publish an “expected change” table OR provide web options for quantifying risk (prototype available this Fall)

Multibreed Evaluation & Xbreeding EPD BullWithin Breed Angus 1*+65 Angus 2+80 Simmental 3*+58 Simmental 4+68 *A1 & S3 are breed average EPDs

Multibreed Evaluation & Xbreeding YWTEPD BullWithin BreedMultibreed # Angus 1*+65 Angus 2+80 Simmental 3* Simmental *A1 & S3 are breed average EPDs # Angus Base

Multibreed Evaluation & Xbreeding YWTCow Breed MBEAngusSimmHeref Angus 1+65Base Angus Simm 3+80 Simm 4+90

Multibreed Evaluation & Xbreeding YWTCow Breed MBEAngusSimmHeref Angus 1+65Base Angus Simm 3+80+h AS +15 Simm 4+90+h AS +25

Multibreed Evaluation & Xbreeding YWTCow Breed MBEAngusSimmHeref Angus 1+65Base+h AS Angus h AS +15 Simm 3+80+h AS +15 Simm 4+90+h AS +25

Multibreed Evaluation & Xbreeding YWTCow Breed MBEAngusSimmHeref Angus 1+65Base+h AS Angus h AS +15 Simm 3+80+h AS Simm 4+90+h AS

Multibreed Evaluation & Xbreeding YWTCow Breed MBEAngusSimmHeref Angus 1+65Base+h AS +h AH Angus h AS +15+h AH +15 Simm 3+80+h AS Simm 4+90+h AS

Multibreed Evaluation & Xbreeding YWTCow Breed MBEAngusSimmHeref Angus 1+65Base+h AS +h AH Angus h AS +15+h AH +15 Simm 3+80+h AS h HS +15 Simm 4+90+h AS h HS +25

Multibreed Evaluation & Xbreeding YWTCow Breed MBEAngusSimmHeref Angus lb Angus Simm Simm

Solution 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

Summary 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)