Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-25T23:34:44.370Z Has data issue: false hasContentIssue false

Optimal Management Strategies for Alfalfa Production Within a Total Farm Plan

Published online by Cambridge University Press:  28 April 2015

David L. Debertin
Affiliation:
University of Kentucky
Angelos Pagoulatos
Affiliation:
University of Kentucky

Abstract

This paper examines the impacts of alternative management strategies for the production of alfalfa within the context of a total farm plan. A linear programming model is used to represent a 600-acre farm which can grow either grain crops or alfalfa. Alfalfa production competes with the grain crops for available land, labor, machinery, and field time over a calendar of tillage, planting, cutting, spraying, and harvesting activities. The profitability of an acre of alfalfa and the contribution of alfalfa to net returns for the farm varies quite widely depending on the particular alfalfa management strategy selected.

Type
Articles
Copyright
Copyright © Southern Agricultural Economics Association 1985

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

Brink, Lars, McCarl, Bruce A., and Doster, D. Howard. Methods and Procedures in the Purdue Crop Budget (Model B-9):An Administrator's Guide. Dept Agr. Econ. Stat. Bull. 121, Purdue University; March, 1976.Google Scholar
Chiang, Alpha C.Fundamental Methods of Mathematical Economics, McGraw-Hill, 2nd Edition, 1974.Google Scholar
Chva'tal, Vasek. Linear Programming, W.H. Freeman and Company, New York, 1980.Google Scholar
Debertin, David L., Moore, C. L. Sr., Bradford, Garnett L., and Jones, Larry D.. Kash Profits Input Form; Dept. of Agr. Econ., University of Kentucky; December, 1976.Google Scholar
Debertin, D. L., Moore, C. L. Sr., and Jones, L. D.. Organizing, Conducting and Evaluating an Extension Workshop Using Computerized Decision Aids: The KASH PROFITS Experience. Dept. Agr. Econ. Extension Bull. 29, University of Kentucky, 1980.Google Scholar
Debertin, D. L., Moore, C. L. Sr, Jones, L. D., and Pagoulatos, A.. “Impacts on Farmers of a Computerized Management Decision-Making Model.Amer. J. Agr. Econ. 63(1981):270274.CrossRefGoogle Scholar
McCarl, Bruce, Wilford Chandler, D. Doster, Howard, and Robbins, Paul.“Experience with Farmer Oriented Linear Programming for Crop Planning.Can.J.Agr. Econ., 25,1(1977):1730.CrossRefGoogle Scholar
Phouts, Rolf W.The Theory of Cost and Production in the Multi-Product Firm”, Econometrica, 29(1961):650658.CrossRefGoogle Scholar
Regev, Uri, Gutierrez, Andrew P., and Feder, Gershan. “Pests as a Common Property Resource: A Case Study of Alfalfa Weevil Control”, Amer. J. Agr. Econ., 58(1976):186197.CrossRefGoogle Scholar
Reichelderfer, Katherine H. and Bender, Filmore E.. “Application of a Simulative Approach to Evaluating Alternative Methods for the Control of Agricultural Pests”, Amer. J. Agr. Econ., 61(1979):258267.CrossRefGoogle Scholar
Shoemaker, Christine. “Optimization of Agricultural Pest Management, Part 3: Results and Extensions of a Model.Math Biosciences, 18(1973):122.CrossRefGoogle Scholar