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The value of near infrared reflectance measurement of feedgrain nutrient composition

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  • Meyer, Steven Roger

Abstract

To determine the value of near infrared reflectance (NIR) measurement of corn nutrient composition to livestock feeders, sequential decision models of beef cattle and swine feeding were developed. Corn composition data from the National Feedstuff Composition Data Bank (NFCDB) were used to derive probability density functions for crude protein, fat, and lysine content. Expected values of profit and other variables were computed by numerical integration. Means of crude protein and lysine of the NFCDB sample were lower and higher, respectively, than National Research Council estimates. These differences caused errors in diet formulations which resulted in losses due to imperfect information of up to 47 per year per head of one-time capacity in feeding yearling steers, up to 41 per year per head of one-time capacity in feeding steer calves and up to 6.50 per year per head of one-time capacity in feeding swine;The difference between the expected values of NIR-generated information and of NFCDB sample means was very small. One-time capacities of approximately 40,000 yearling cattle, 12,500 calves of 2,200 swine were necessary to justify investment in an analyzer based on net present value when NIR-generated information (versus NFCDB sample means) was used to formulate diets to meet recommended nutrient allowances. Minimum one-time capacities declined to 2,550 yearling cattle, 1,700 calves or 1,080 swine when diets were formulated to meet nutrient requirements;NIR-generated information was more valuable to yearling steer feeders than to steer calf feeders on an annual basis, given continuous production. This result was due to yearling steers' requiring fewer days to reach market weight thereby allowing more animals to be fed per year;Losses due to imperfect knowledge in beef cattle feeding were largest when corn had low crude protein content and high fat content. Losses incurred by swine feeders were highest when crude protein content was high and fat content was low;The use of NIR results to reject corn with low crude protein and/or fat content increased the expected value of NIR-generated information by roughly ten percent for both species. This gain in expected value does now, however, account for costs that may be incurred by feeders in finding corn that meets their specified standards.

Suggested Citation

  • Meyer, Steven Roger, 1987. "The value of near infrared reflectance measurement of feedgrain nutrient composition," ISU General Staff Papers 1987010108000012708, Iowa State University, Department of Economics.
  • Handle: RePEc:isu:genstf:1987010108000012708
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    References listed on IDEAS

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    1. Fred Dahm & Earl O. Heady & Steven T. Sonka, 1976. "Estimation and Application of a Production Function in Decision Rules for Swine Producers," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 24(3), pages 1-16, November.
    2. Niernberger, Floyd F., 1978. "Near-Infrared Reflectance Instrument Analysis of Grain Constituents: A Cost Study," Economics Statistics and Cooperative Services (ESCS) Reports 142857, United States Department of Agriculture, Economic Research Service.
    3. George W. Ladd & Marvin B. Martin, 1976. "Prices and Demands for Input Characteristics," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 58(1), pages 21-30.
    4. Jean-Paul Chavas & James Kliebenstein & Thomas D. Crenshaw, 1985. "Modeling Dynamic Agricultural Production Response: The Case of Swine Production," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 67(3), pages 636-646.
    5. Feldstein, Martin S, 1971. "Production with Uncertain Technology: Some Economic and Econometric Implications," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 12(1), pages 27-38, February.
    6. Blair, Roger D, 1974. "Random Input Prices and the Theory of the Firm," Economic Inquiry, Western Economic Association International, vol. 12(2), pages 214-226, June.
    7. Sandmo, Agnar, 1971. "On the Theory of the Competitive Firm under Price Uncertainty," American Economic Review, American Economic Association, vol. 61(1), pages 65-73, March.
    8. Miller, Dale Richard, 1978. "The effect of corn quality on ration costs," ISU General Staff Papers 1978010108000018024, Iowa State University, Department of Economics.
    9. Whittemore, C. T., 1983. "Development of recommended energy and protein allowances for growing pigs," Agricultural Systems, Elsevier, vol. 11(3), pages 159-186.
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    Cited by:

    1. Duncan, Steven Scott, 1988. "The relevant forecast of variance of income for marketing decisions under uncertainty," ISU General Staff Papers 198801010800009839, Iowa State University, Department of Economics.

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