Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-25T04:20:26.038Z Has data issue: false hasContentIssue false

Formulation of Broiler Finishing Rations by Quadratic Programming

Published online by Cambridge University Press:  28 April 2015

Bill R. Miller
Affiliation:
Poultry Science, University of Georgia
Ronaldo A. Arraes
Affiliation:
Poultry Science, University of Georgia
Gene M. Pesti
Affiliation:
Poultry Science, University of Georgia

Abstract

Least cost feed mix by linear programming (LP) is a standard economic analysis in the poultry industry. A significant body of nutrition knowledge is now contained in the constraint set of industry LP models. This knowledge might be merged into an improved economic model that contains production response information. Analysis using a quadratic programming model indicated that a leading broiler firm could have improved economic efficiency by increasing protein density and reducing energy density of broiler finisher feed. If applicable industry wide, similar savings could be as high as $120 million per year.

Type
Submitted Articles
Copyright
Copyright © Southern Agricultural Economics Association 1986

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Allison, John R. and Baird, D. M.. “Least-Cost Livestock Production Rations.So. J. Agr. Econ., 6,2(1974):4145.Google Scholar
Allison, John R., Ely, Laue O., and Amato, S. V.. “Broiler Profit Maximizing Models.Poultry Sci., 57(1978):845853.CrossRefGoogle Scholar
Arraes, Ronaldo A. Alternative Evaluations of Economically Optimal Rations For Broilers, Ph.D. dissertation submitted to the College of Agriculture, Agricultural Economics Department, University of Georgia; Athens, Georgia; August, 1983.Google Scholar
Brown, W. G. and Arscott, G. H.. “Animal Production Functions and Optimum Ration Specification.J. Farm Econ., 42(1960):6978.CrossRefGoogle Scholar
Burt, Oscar. “On the Statistical Estimation of Isoquants and Their Role in Livestock Production Decisions.Amer. J. Agr. Econ., 60(1978): 518523.CrossRefGoogle Scholar
Chao, T. C. An Application of Farrell Efficiency Analysis to Determination of Optimum Broiler Rations. Masters Thesis, University of Georgia; Athens, Georgia, 1975.Google Scholar
Chiang, Alpha C. Fundamental Methods of Mathematical Economics. New York: McGraw-Hill Inc., 1984.Google Scholar
Dillon, John L. The Analysis of Response in Crop and Livestock Production. Oxford: Pergamon, 1968.Google Scholar
Georgia Agricultural Facts, 1978-79, Georgia Department of Agriculture, Georgia Crop Reporting Service; Athens, Georgia; October, 1980.Google Scholar
Heady, Earl O. and Dillon, John L.. Agricultural Production Functions. The Iowa State University Press; Ames, Iowa; 1961.Google Scholar
Henson, William L. The U. S. Broiler Industry: Past and Present Status, Practices, and Costs. Department of Agricultural Economics and Rural Sociology 149, Agricultural Experiment Station, University Park: Pennsylvania State University; May, 1980.Google Scholar
Kmenta, Jan. Elements of Econometrics. New York: The McMillan Co., 1971.Google Scholar
National Research Council. Nutrient Requirements of Poultry. Washington, D.C.: National Research Council, National Academy of Science, 1977.Google Scholar
Pesti, G. M., Miller, B. R., and Carey, C. A.. “Proportionality Among Nutrients in Least Cost Feed Formulation.Poultry Sci., 65(1985):824831.Google Scholar
Seitz, W. D.The Measurement of Efficiency Relative to a Frontier Production Function.Amer. J. Agr. Econ., 52(1970):505511.Google Scholar