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Valuing Fed Cattle Using Slice Shear Force Measurements

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Author Info

  • Riley, John Michael
  • Schroeder, Ted C.
  • Wheeler, Tommy L.

Abstract

Marketing fed cattle using grid pricing has become a popluar way to sell cattle. One of the most important beef characteristics, according to consumers, is beef tenderness. USDA quality grades are poor predictors of meat tenderness. However, mechanical shear force does objectively measure tenderness. This study illustrates how problematic USDA quality grades are at assessing accurate beef tenderness and proposes and evaluates a tenderness-based valuation system based on slice shear force technology. We show that cattle of all quality grades are substantially over- or under-valued when using a grid realtive to a tenderness-based valuation system.

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File URL: http://purl.umn.edu/36313
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Bibliographic Info

Paper provided by Western Agricultural Economics Association in its series 2005 Annual Meeting, July 6-8, 2005, San Francisco, California with number 36313.

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Date of creation: 2005
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Handle: RePEc:ags:waeasa:36313

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Web page: http://waeaonline.org/
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Keywords: Marketing;

References

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  1. Lusk, Jayson L. & Marsh, Thomas L., 2000. "Wholesale Demand For Usda Quality Graded Boxed Beef And Effects Of Seasonality," 2000 Annual Meeting, June 29-July 1, 2000, Vancouver, British Columbia 36409, Western Agricultural Economics Association.
  2. Kovanda, Joseph T. & Schroeder, Ted C. & Wheeler, Tommy L., 2004. "Accuracy Of Grid Pricing: An Evaluation Using Wholesale Values Of Fed Cattle," 2004 Conference, April 19-20, 2004, St. Louis, Missouri 19023, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
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Cited by:
  1. Parcell, Joseph L. & Schaefer, Daniel & Patterson, David J. & John, Mike & Kerley, Monty S. & Haden, Kent, 2008. "Assessing the Value of Coordinated Sire Genetics in a Synchronized AI Program," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37618, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.

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