Modified Select-Synch

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A Nationwide Survey of Beef Producers about Feed
Efficiency Motivating Factors for the
Implementation of Selection Practices
Jason K. Ahola1, Stephanie L. Kane3, J.D.
Wulfhorst3, Larry D. Keenan3, and Rod A.
Hill2 1Animal Sciences, Colorado State
University 2Animal and Veterinary Science,
University of Idaho 3Social Sciences Research
Unit, University of Idaho 4Red Angus Association
of America, Denton, Texas
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Project Overview

• Component of the USDA NRI-funded project
• Evaluating the feed efficiency and end-product
  quality relationship in the progeny of Red Angus
  sires divergent for Maintenance Energy EPD
• Objectives
• Create progeny of Red Angus bulls divergent for
  Maintenance Energy (ME) EPD
• Characterize Red Angus bulls for feed efficiency
  (RFI)
• Determine relationship between ME EPD, RFI, and
  other production traits
• Explore physiological drivers of variation in RFI
• Educate producers about selection for feed
  efficiency

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Feed Efficiency Outreach

• Research Objective
• Establish baseline measures of producer
  perceptions about the perceived unique benefits
  and/or costs associated with feed efficiency, as
  well as the efficacy of outreach programs in
  conveying this information.
• Outreach Objective
• Develop outreach materials using research
  results
• Field days, symposia, and popular press
• Train-the-trainer events (Extension, thought
  leaders)
• Internet-based outreach (www.eXtension.org)

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University of Idaho Social Sciences Research Unit
(SSRU)
Conducts surveys on Agricultural producers,
consumers, public opinion Baseline data,
follow-up, impact, economic impact Survey
types Mail, telephone Person-to-person, focus
groups Dillman method (mailed surveys) Survey
letter, postcard (1 wk), survey letter (2
wks) Non-respondent subsample called
(non-response bias)
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Mailed Survey of Cattlemen
January-February 2008 35 question
booklet Stratified random sample of Idaho
Cattle Association members (n 488) Red Angus
Assn of America (RAAA) members (2,208) RAAA bull
buyers (n 5,325) via transfers Total sample
size 1,888 902 completed eligible
surveys Overall response rate 49.9 (ICA
56.9, RAAA 49.7, RA buyers 45.2)
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General Survey Question Areas
Background info Operation type (seedstock,
commercial), breeds Location, number of
cows/bulls, marketing methods Age, education,
years in business Avg. price paid for bulls, tons
of feed raised/purchased Use of genetic
prediction data Data used today, data
desired Prioritization of traits for
selection Feed-to-Gain Ratio and RFI Knowledge
of Willingness to collect data on Willingness to
pay for
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Demographic Profile
Breakdown of respondents 13 seedstock
producers 59 commercial cow/calf producers 28
a combination (seedstock and commercial) Mean
age 54 years Mean number of years operating
ranch 28 yrs 46 had a college degree or
higher
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Regional Distribution
Regions correspond to NCBA Region 1 ME, NH, VT,
MA, CN, RI, NJ, NY, PA, DE, MI, OH, IN, KY, VA,
MD Region 2 NC, TN, SC, GA, AL, MS, LA, FL
Region 3 MN, WI, IA, IL, MO Region 4 TX, OK,
AR Region 5 WA, ID, MT, WY, CO, OR Region 6
CA, NV, UT, AZ, NM Region 7 ND, SD, NE, KS.
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Ranch Herd Characteristics
Cattle inventories 217 14.8 cows 17
3.3 bulls Breed types used 78 British breeds
exclusively 18 mixed herd of British and
Continental 4 Contl only, or mix of
British, Contl, and Indicus Average price paid
per bull 2,616 55.5 Feed inputs per
year 874 302.6 tons of hay harvested 64
6.1 tons of hay purchased
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Goals of the Survey

• Document current selection priorities
• Determine awareness of feed-to-gain ratio
  and/or residual feed intake
• Initiate an evaluation into willingness to pay
  for RFI data
• Attempt to predict willingness
• to adopt RFI as a
• production practice

www.growsafe.com www1.agric.gov.ab.ca
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Genetic Prediction Info (currently)
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Genetic Prediction Info (wish list)
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Genetic Prediction Info
What types of genetic prediction information do
you provide your buyers (seedstock) OR what type
is provided to you by your seedstock supplier?
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Genetic Prediction Info
What types of genetic prediction information
would you consider providing your buyers
(seedstock) OR what type would you like to have
(commercial cow/calf)?
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Bull Traits Considered Important or Very
Important
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The Most Important Trait
Which of those traits listed do you consider to
be MOST important when purchasing or using a bull?
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Selection for Feed Efficiency (Today)
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Selection for Feed Efficiency (Today)
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Knowledge of Feed-to-Gain Ratio
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Residual Feed Intake Awareness
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Knowledge of Feed to Gain Ratio vs. RFI Awareness
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Have Heard of RFI by Type
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How Much More Would You Pay for a Bull Evaluated
for RFI (/head)?
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How Much More Would You Pay for a Bull Evaluated
for RFI (/head)?
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How Much More Would You Pay To Have Bulls
Evaluated /head)?
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How Much More Would You Pay To Have Bulls
Evaluated (/head)?
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Preferred Source of Information
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Preferred Source of Information
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Predicting Awareness of RFI Main Effects
Effect D.F. Wald Chi-square P-value
Herd type 2 9.0024 0.01
Years managing 1 3.9801 0.05
Number of bulls 1 0.9666 0.33
Age of respondent 1 7.6482 lt0.01
Region 6 3.8131 0.70
Read articles/attend meetings 3 18.7655 lt0.001
Use breed assoc. for leadership 3 2.6924 0.44
Number of sources of information 1 6.7221 lt0.01
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Conclusions

1. Producers still use ( seek) raw, ratio, EPD
   data.
2. High priority traits Repro, disposition,
   calving ease, growth.
3. Not high priority Price, visual, milk, feed
   efficiency.
4. Among all producers, 30 of producers will pay
   0/hd more for RFI data, 40 will pay 1-200/hd,
   and 25 will pay gt200/hd.
5. Among seedstock producers, 30 will pay 0 to get
   RFI data, 60 will pay 1-200/hd, and 5 will
   pay gt200/hd.
6. Age, years managing, and participation in
   meetings are drivers for RFI awareness operation
   size region are not.
7. Substantial producer education related to
   understanding and selecting for feed efficiency
   is needed.

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Acknowledgements Red Angus Association of
America Idaho Cattle Association USDA
National Research Initiative (aka AFRI) Grant
no. 2008-55206-18812 from CSREES National Science
Foundation Idaho EPSCoR Award no. EPS 0447689
Jason K. Ahola, Ph.D. Beef Production
Systems Colorado State University (970)
491-3312 jason.ahola_at_colostate.edu