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Economic Feasibility of Adopting Genomic Selection in Beef Cattle Kenneth Poon & Getu Hailu University of Guelph CAES 2010, Niagara Falls June 18 th , 2010
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Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Feb 24, 2016

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Economic Feasibility of Adopting Genomic Selection in Beef Cattle. Kenneth Poon & Getu Hailu University of Guelph CAES 2010, Niagara Falls June 18 th , 2010. Ontario Beef Sector. Beef sector has been suffering from high and increasing input cost - PowerPoint PPT Presentation
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Page 1: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Kenneth Poon & Getu HailuUniversity of Guelph

CAES 2010, Niagara FallsJune 18th, 2010

Page 2: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Ontario Beef Sector

• Beef sector has been suffering from high and increasing input cost

• Feed cost ~ 70-80% of total expense of beef operation

• Feed efficiency is a major aspect of beef production

• Feed efficient herd = environmental herd

Page 3: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Measure of Feed Efficiency

Residual Feed Intake (RFI)

• Lower actual feed intake compared to expected intake

• Correcting for body weight, breed, body fat, etc.

• Negative RFI = lower than expected feed intake

Page 4: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Selecting for Feed Efficiency

• Feed efficiency expensive and difficult to measure:

• Require specialized machinery to track daily feed intake

• BUT

• Feedlot operators willing to pay premium for feed efficient calves

• Cow-calf operations likely see higher profits from reduced feed and pasture cost

Page 5: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Adopting Genetic Improvement

• Look at genetic make up of animal to predict characteristics

• Look at set of mutations (SNPs) compared to a reference population

Or

• inseminate cows with genetically selected bull• either with Artificial Insemination (AI) or • purchase of genetically selected commercial bull

• Benefits: • ‘Comparatively’ low cost: $50 – 120 per head

Page 6: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Genomics and Feed Efficiency

• SNPs not yet identified, but getting close• Where mutations are likely located have been identified

(QTL study)

• Adoption of genomics in beef cattle industry require co-ordination:• information infrastructure important for dairy industry

• pedigree tracking• reference herd• Flow of information between farms and genetic organizations

Page 7: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Research Questions

Is genomic selection for feed efficiency financially feasible for Canadian beef sector?

• For feedlots: what is the max willingness-to-pay for feed efficient calves?• i.e., how much will feed efficient calves save in feed cost?

• For cow-calf operations

• What would be the change in profit by improving the herd’s feed efficiency (AI or feed efficient bulls)?

Reduced feed cost of herdVS

Cost of adopting AI, paying a premium to purchase feed efficient bulls

Page 8: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Methods

• Capital budget model of a cow calf enterprise• Calculate Net Present Value (NPV) over 20 years with and without

adoption of feed efficiency

• Modeled in Microsoft Excel with @Risk

• Adopted from Schaufele (2010): • simulate cow-calf herd dynamic• stochastic cattle prices

• Addition to model• Track animals with and without genetic improvement

Page 9: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Cow calf herd structure – feed efficient bulls

CullPurchase

Sold to feedlot

ReplacementHeifers

Bulls Cows

CullPurchase

Weaned Calves

Page 10: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Modeling technology adoption

• Scenario A: Whole-herd improvement• Increase in NPV if whole herd require 1 lb less of feed per

livestock per day

• Scenario B: Herd improvement via feed efficient bulls• Replaces breeding bulls with feed efficient bulls over time

• Scenario C: Herd improvement via AI with genetic selected semen• Inseminate ‘regular’ cows with semen from feed-efficient bulls

via AI

Page 11: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

ReplacementHeifers

Weaned Calves

CullPurchaseCullPurchase

CowsBulls

Cow calf herd structure – feed efficient bulls

Sold @ premium

+$

Sold to feedlot

Page 12: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

ReplacementHeifers

Weaned Calves

CullPurchase

Cows

Cow calf herd structure – artificial insemination

Sold @ premium

CullPurchase

Bulls

AI

Sold to feedlot

Page 13: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Data Sources

• Simulation starting year = 2010

• Main data source: AgriProfit$ benchmarking data• 2008-2010 average, 36 cow calf operations in Southern Alberta• used for herd structure, livestock expenses

• Koeckhoven (2008)• Crop establishment, tamed pasture cost

• Alberta Agriculture and Rural Development• Native pasture cost estimated from AARD Pasture for Rent/Lease Listing Page• Livestock prices (2008 – 2010): Agriculture Statistics Handbook 2010• Crop prices

Page 14: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Model Parameters

• Herd Size: 300 cows, 15 bulls (~20 cows per bull)

• Ration: • Barley silage and alfalfa/hay• All feed produced on farm, scaled with herd requirement (no sales)

• Pasture: • Tamed pasture: high productivity = 800 ac (fixed)• Native pasture: low productivity, scales with herd requirement

• Model results validates with AgriProfit$ 2010 enterprise budgets for Southern Alberta cow calf operations

Page 15: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Base Scenario Results

NPV per cow wintered

NPV per cow wintered

Page 16: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Scenario A: whole herd improvement

• Substantial in NPV if all animals are feed efficient by requiring 1lb less of feed a day

• Increase NPV by $8.74 per cow wintered to $68.22 on feed/pasture cost savings alone

• A 14.7% increase

Page 17: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Scenario B: purchasing feed efficient bulls

• Gains are substantially lower when not all animals in the herd are feed efficient:

• Only efficient bulls are bought (@ $0 premium), other purchases to breeding herd are not feed efficient

• NPV increase by only $1.65/ cow wintered (+2.8%)

• This is quickly eroded when premium charged by seedstock producers for feed efficient bulls increases

Page 18: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Percent of herd with feed efficient trait

0 1 2 3 4 5 6 70%

20%

40%

60%

80%

100%

Bull Cows Weaned Calves

Years since the start of feed efficient bull purchase

% of feed efficient livestock

Start replacing culled bulls with feed efficient ones @ 25% culling rate

Page 19: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

$- $50 $100 $150 $200 $250 $300 $58.00

$58.50

$59.00

$59.50

$60.00

$60.50

$61.00

$61.50

Premium Charged per Feed Efficient Bull

NPV per Cow Wintered

Premium charged on feed efficient bulls vs NPV

NPV per cow wintered as premium charged per bull increases

Base scenario @ $59.77

Cost savings = 0 @ premium of $233.08

Page 20: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Market for feed efficient bulls

• Premium of $233.08 represent about 7-8% increase over average bull prices

• Premium comparable to other selected traits• Premium on bulls whose progenies have reduced birth weight by ~10lb is

~$284 (Jones 2008)

• But…

• feed efficiency is much more expensive to measure than other traits (e.g., compared to birth weight of progenies)

• Seedstock producers may charge more

Page 21: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Scenario C: Herd improvement via AI

• Artificial Insemination is costly…• Johnson & Jones (2006) suggest average of $67.13 per AI pregnancy + $125

in equipment cost

• Model results with AI adoption & no feed efficiency gain:

• 6.93% of cost of production

• Reduce NPV to $39.41 / cow winteredOR

• -$20.36 / cow wintered compared to base scenarioOR

• - 34.06% compared to Base Scenario NPV

Page 22: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

AI with feed efficiency gain

• If herd were inseminated with semen from feed efficient bulls (assuming progeny has RFI of -1)

• reduce profit per cow wintered to $42.37OR

• -$17.4/cow wintered• + $2.96 better than AI without FE gain

OR• -29.11% in profit

Page 23: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

AI + premium sales price for feed efficient calves

• In the absence of a feed efficient commercial bull market, AI may be the only way to adopt feed efficiency for cow calf operations

• What would be the minimum sales price premium per calf sold required to cover cost of adopting AI for feed efficiency?

• Increase premium price of feed efficient calves by $X / weaned calf until baseline of $59.77 reached

Page 24: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Premium required for feed efficient AI to be profitable

$- $25 $50 $75 $100 $125 $40

$50

$60

$70

$80

$90

$100

Premium Charged per Feed Efficient Calf Sold

NPV per Cow Wintered

NPV per cow wintered as premium sale price per efficient calf increases

Base scenario @ $59.77

AI adoption cost recouped @ premium of $42.45 per feed efficient calf

Suggested max premium feedlots will pay for weaned

calves with -1 RFI

Page 25: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Major result

• Only a ‘small’ price premium for feed-efficient calf sales is enough to make adopting feed efficiency via AI feasible

• About 34.8% of what feedlot operations suggest they would pay for a 1lb reduction of daily feed intake

or• About 6-7% increase in average weaned calf prices

Page 26: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Caveats to model results

• There are other barriers to adoption for AI in beef sector

• Labour intensive: AI system modeled requires estrus synchronization, rounding up herd for insemination in short window

• AI adoption cost shown to be very high for smaller herds and productive bulls (up to $94.78 per pregnancy; Johnson & Jones 2006)

• S. Alberta commands high return per cow wintered:

• North and Central Alberta benchmarking results suggest return closer to $20 / cow wintered

• Cash flow may be insufficient for AI adoption.

Page 27: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Upcoming work

• Modeling Alberta feedlot model (waiting for more data)• Estimate cost saving for feed-efficiency of feedlots via purchase of calves/feeder

cattle• Check against estimated WTP for feed efficient trait (@$125 for -1 RFI)

• Adopt model to Ontario (looking for more data)

• For cow calf - herd size averages ~30 cows: • impact of AI adoption/ purchase of feed efficient bulls?• ‘break-even’ premiums on calves, bull purchases?

• For feedlots - require sorting of feed efficient calves / feeders from non-efficient to fully gain benefit of feed efficiency.

• How would this affect WTP for feed efficient calves?

Page 28: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Upcoming work

• Adopt model to examine feed efficiency and greenhouse gas emission

• Experimental data already available

• Major interest in beef sector for reducing environmental footprint

Page 29: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Thank you

Page 30: Economic Feasibility of Adopting Genomic Selection in Beef Cattle

Premium required for feed efficient AI to be profitable

$- $25 $50 $75 $100 $125 $40

$50

$60

$70

$80

$90

$100

Premium Charged per Feed Efficient Calf Sold

NPV per Cow Wintered

NPV per cow wintered as premium sale price per efficient calf increases

Base scenario @ $59.77

AI adoption cost recouped @ premium of $42.45 per feed efficient calf