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A Nationwide Survey of Beef Producers about Feed Efficiency – Motivating Factors for the Implementation of Selection Practices Jason K. Ahola* 1, Stephanie.

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Presentation on theme: "A Nationwide Survey of Beef Producers about Feed Efficiency – Motivating Factors for the Implementation of Selection Practices Jason K. Ahola* 1, Stephanie."— Presentation transcript:

1 A Nationwide Survey of Beef Producers about Feed Efficiency – Motivating Factors for the Implementation of Selection Practices Jason K. Ahola* 1, Stephanie L. Kane 3, J.D. Wulfhorst 3, Larry D. Keenan 3, and Rod A. Hill 2 1 Animal Sciences, Colorado State University 2 Animal and Veterinary Science, University of Idaho 3 Social Sciences Research Unit, University of Idaho 4 Red Angus Association of America, Denton, Texas

2 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: 1.Create progeny of Red Angus bulls divergent for Maintenance Energy (ME) EPD 2.Characterize Red Angus bulls for feed efficiency (RFI) 3.Determine relationship between ME EPD, RFI, and other production traits 4.Explore physiological drivers of variation in RFI 5.Educate producers about selection for feed efficiency Project Overview

3 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: 1.Field days, symposia, and popular press 2.Train-the-trainer events (Extension, thought leaders) 3.Internet-based outreach (www.eXtension.org) Feed Efficiency Outreach

4 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)

5 January-February 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, completed & eligible surveys Overall response rate = 49.9% (ICA = 56.9%, RAAA = 49.7%, RA buyers = 45.2%) Mailed Survey of Cattlemen

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7 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

8 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 Demographic Profile

9 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. Regional Distribution

10 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% Cont’l only, or mix of British, Cont’l, and Indicus Average price paid per bull = $2,616 ± 55.5 Feed inputs per year: 874 ± tons of hay harvested 64 ± 6.1 tons of hay purchased Ranch & Herd Characteristics

11 Goals of the Survey 1.Document current selection priorities 2.Determine awareness of “feed-to-gain ratio” and/or “residual feed intake” 3.Initiate an evaluation into ‘willingness to pay’ for RFI data 4.Attempt to predict ‘willingness to adopt’ RFI as a production practice www1.agric.gov.ab.ca

12 Genetic Prediction Info (currently)

13 Genetic Prediction Info (wish list)

14 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?

15 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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17 Bull Traits Considered “Important” or “Very Important”

18 The “Most Important” Trait Which of those traits listed do you consider to be MOST important when purchasing or using a bull?

19 Selection for Feed Efficiency (Today)

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21 Knowledge of Feed-to-Gain Ratio

22 Residual Feed Intake Awareness

23 Knowledge of Feed to Gain Ratio vs. RFI Awareness

24 Have Heard of RFI by “Type”

25 How Much More Would You Pay for a Bull Evaluated for RFI ($/head)?

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27 How Much More Would You Pay To Have Bulls Evaluated $/head)?

28 How Much More Would You Pay To Have Bulls Evaluated ($/head)?

29 Preferred Source of Information

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31 Predicting Awareness of RFI: Main Effects EffectD.F.Wald Chi- square P-value Herd type Years managing Number of bulls Age of respondent <0.01 Region Read articles/attend meetings <0.001 Use breed assoc. for leadership Number of sources of information <0.01

32 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 >$200/hd. 5.Among seedstock producers, 30% will pay $0 to get RFI data, ~60% will pay $1-200/hd, and 5% will pay >$200/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. Conclusions

33 Jason K. Ahola, Ph.D. Beef Production Systems Colorado State University (970) Acknowledgements: Red Angus Association of America Idaho Cattle Association USDA National Research Initiative (aka AFRI) Grant no from CSREES National Science Foundation & Idaho EPSCoR Award no. EPS


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