oltjen w-2177 report 2009.ppt

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Cost-Benefit analysis of NAIS implementation in California

Jim Oltjen

4/2/2009 W-2177 Committee

NCBA, Denver

Project At a Glance

Coordinators Jim Oltjen & Bees Butler UC, John Evans & Victor Velez CDFA Cooperators Dave Daley CSU-Chico, Mike Hall Cal Poly San Luis Obispo

Species Beef, Dairy, Sheep, Goats

Survey CSU-Chico & Cal Poly-San Luis

Model UC-Davis

Survey Process

Survey design Survey data Summary statistics

Survey Process

Survey design Survey data Summary statistics

UC Model to compare identification methods

Visual identificationRFID identification – tags

Static – hand held readerDynamic – panel reader

Costs Benefits

Equipment

Materials

Service Fees

Labor

Compliance - Health

Marketing

Management

Premise Reg.

Animal ID Event Record

Event Report

V = Voluntary V 0 0 0

V* = V for all animals V V 0 0

M = Mandatory V V V 0

0 = No M/V* 0 0 0

M/V* V 0 0

M/V* V V 0

M M/V* 0 0

M M/V* V 0

M M M/V* 0

M M M M

Beef cow-calf flow:

Culling rate20.0%

Calf rate 87.0%

Calf crop

Death rate 2.0%

Heifers sold

100

Open heifers

30.0%

30

70

Pregnant heifers

Pregnancy rate

70.0%

198

Calves for sale

298

305

Intended to sale66.5%

Saved for replacement33.5%

Cows herd

350

Culled cows

Bulls 11

3.0%

70

Animals inventoried per yr:

Bulls 11

Cows 350

Live calf crop 298

Saved heifers 100

Total inventory 759

Readings per yr:

Bulls 1 11

Cows 2 700

Live calf crop 1 298

Saved heifers 1 100

Total readings 1,109

Average readings/yr 1.5

Cost Model (excerpt, Beef cow-calf size=350)

Labor cost ($/h) 15.00

Visual ID

RFID Static

RFID Dynamic

Time for ID application (s) 10.0 10.0 10.0

Time to transfer codes to DB (s) 5.0 1.0 1.0

Time to register premises (s/yr) 200 200 200

ID set-up time (s) 60 900 900

Average no. of head processed 175 175 175

Time to learn ID tech (s) 600 14400 14400

Data error rate 6.0% 1.0% 1.0%

Dynamic (panel) reading efficiency 95.0%

Time for extra-readings (s) 23.6 2.6 2.7

Cost Model (con’t)

Equipment costs

Handheld (HH) reader lifetime (yr) Stationary (panel) reader lifetime (yr) Applicator lifetime (yr) IT lifetime (yr) Readers ownership sharing (%) Applicator No. & price ($) HH reader No. & price ($) Stationary (panel) reader No. & price ($)

Cost Model (con’t)

HH reader lifetime (yr) 5.0

Stationary reader lifetime (yr) 5.0

Applicator lifetime (yr) 5.0

IT lifetime (yr) 5.0

Readers ownership sharing 100.0%

VisualID

RFIDStatic

RFIDDynamic

Applicator No. & price ($) 20.00 20.00 20.00

HH reader No. & price ($) 800.00 800.00

Stationary (panel) reader No. & price ($) 2500.00

Dynamic (panel) reading efficiency 95.0%

NAIS Scenario 10: Beef cow-calf, 350 herd size

Premise Reg. Animal ID Event Record Event Report

M M M M

Cost

($/animal/yr) Cost ($/yr)

Visual ID RFID Static Dynamic Visual IDRFID Static Dynamic

Labor 0.364 0.080 0.081 276 61 61

Services 0.450 0.450 0.450 341 341 341

Materials 0.513 0.863 0.863 390 655 655

Annual 1.328 1.392 1.393 1007 1057 1057

Ave periodic equipment 0.221 0.432 1.091 168 328 828

Ave costs 1.549 1.825 2.484 1175 1385 1885

Initial costs 2.43 3.55 6.85 1847 2697 5197

NAIS scenarioScen. | P.Reg. | A.ID. | Ev.Rcd. | Ev.Rpt. Key

5 | V | V | 0 | 0 1

Beef Cow-calf: Visual ID & Voluntary

NAIS scenarioScen. | P.Reg. | A.ID. | Ev.Rcd. | Ev.Rpt. Key

10 | M | M | M | M 1

Beef Cow-calf: Visual ID & Mandatory

ID in general:

Labor costs are relatively minor compared to the costs of equipment and materials (ear-tags).

ID-Most of the variation is due to size--the larger operations have reduced cost

RFID-Most of the variation is due to the costs of equipment – the RFID readers you have.

(Most of the variation for the VID is also due to equipment - in this case computer )

Cost Findings

Compliance benefit in year 0.50

Managememt benefit in year 3.00

Marketing benefit in year 25.00

NAIS scenarioScen. | P.Reg. | A.ID. | Ev.Rcd. | Ev.Rpt. Key

10 | M | M | M | M 1

Beef Cow-calf: RFID handheld & Mandatory

-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

5.0

0 1 2 3 4 5 6 7 8 9 10

Year

US

$

PV Costs PV Benefits NPV

Animal ID May Aid in Animal ID May Aid in Production EfficienciesProduction Efficiencies

Individual animal identification systems Provide the information on an animal’s performance from weaning to harvest Enables the identification of individuals with the most profitable genetic merit

Use performance measurementsManage animals Sell off low performing cattle before spending additional dollars

UC Beef Production Research Update

Supplement composition for dry rangeFat depot modelingParentage via DNABeef System Records IntegrationWestern Quality Assurance RecertificationManagement Model for use of IDBeef Feedlot Emissions

Dry range 600 lb heifers

Tub UCDIntake, lb/d 1.63 0.77Gain, lb/d 0.27 0.60Cost, relative 1.00 0.33

Net energy

Protein

Maintenance Fat

Visceral(kg)

Sub(kg)

Intra(kg)

Inter(kg)

12/13th

Rib fat(mm)

CarcasscharacteristicsDavis Growth Model

KPH(kg)

KPH(%)

IMF(%)

Bull output varies a lot !

Calf Output per Bull

2220

17 1716

1514

1311

108

75

43 3 3

2

0

5

10

15

20

25

"1-8

"

"01"

"6

14"

"202

"

"1-6

"

"0-5

"

"9-3

"

"1-7

"

"302

"

"616

"

"174

"

"1-3

"

"1-2

"

"0-6

"

"1-9

"

"1-5

"

"3-5

"

"3-3

"

Bull ID

No

. Ca

lve

s

Introduction BQA History

The BQA program connects producers with animal scientists, veterinarians, feed suppliers, animal health companies, packers, retailers, and state and federal regulators. The program encourages producers to use the latest science and technology so their beef will meet quality and safety standards.

Management Model for Use of ID

A management decision support tool (modifying a cowherd simulation model) to use in educational (extension) settings. Thus, for whatever the variables that describe a particular operation's management, the estimated value of the benefits is projected into the future.

Feedlot Air Emissions

UC Beef Production Research Update

Supplement composition for dry rangeFat depot modelingParentage via DNABeef System Records IntegrationWestern Quality Assurance RecertificationManagement Model for use of IDBeef Feedlot Emissions

Questions ?

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