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Incorporation of Within-Season Yield Growth into a Mathematical Programming Sugarcane Harvest Scheduling Model

Published online by Cambridge University Press:  28 April 2015

Michael E. Salassi
Affiliation:
Department of Agricultural Economics and Agribusiness, Louisiana State University Agricultural Center Sugarcane Research Unit, Agricultural Research Service, U. S. Department of Agriculture
Lonnie P. Champagne
Affiliation:
Department of Agricultural Economics and Agribusiness, Louisiana State University Agricultural Center Sugarcane Research Unit, Agricultural Research Service, U. S. Department of Agriculture
Benjamin L. Legendre
Affiliation:
Department of Agricultural Economics and Agribusiness, Louisiana State University Agricultural Center Sugarcane Research Unit, Agricultural Research Service, U. S. Department of Agriculture

Abstract

This study focuses on the development of a optimal harvest scheduling mathematical programming model which incorporates within-season changes in perennial crop yields. Daily crop yield prediction models are estimated econometrically for major commercially grown sugarcane cultivars. This information is incorporated into a farm-level harvest scheduling linear programming model. The harvest scheduling model solves for an optimal daily harvest schedule which maximizes whole farm net returns above harvesting costs. Model results are compared for a commercial sugarcane farm in Louisiana.

Type
Articles
Copyright
Copyright © Southern Agricultural Economics Association 2000

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