Economic analysis of optimal production and marketing management strategies for swine production operations with Paylean®

Ning Li, Purdue University

Abstract

With increasing competitive pressure and scale of operations, livestock businesses require efficient management decisions. The purpose of this research was to combine state of the art biological swine growth model with economic optimization principles so as to develop a modeling system that can be used to fine tune the management of modern swine production operations. This modeling system can be calibrated to a wide range of production and marketing systems, making it a useful tool for developing strategies that are specific to a producer's operation. The specific goals of this research included: (1) to determine optimal production and marketing management strategies for dietary Paylean (both constant and varying concentration programs) and lysine concentrations under alternative phase-feeding programs, growth conditions and payment systems, either for a single hog with average growth properties or a herd of pigs; (2) to investigate the impact of economic conditions on management strategies; (3) to determine differences between economically optimal management strategies when simulation focuses at the herd level rather than on the herd average. A key feature of this research was the more precise modeling of the economic objective function. In particular, payment grids common in the pork packing industry are incorporated into the model directly, resulting in a discontinuous objective function for the optimization of returns. A grid search is used to maximize this nonconcave objective. Therefore, the simulated scenarios can reflect the true conditions facing a swine producer. An innovation of the research was to use a stochastic growth model to investigate the production management strategies at the herd level. The stochastic growth model gets its name from two features: stochastic live weight growth and stochastic carcass component growth. Each individual pig has its own live weight and carcass component growth curve, which together approximately reproduce the mean and covariance structure of the genetic population. Thus, the stochastic model has broad applications for the hog industry and implications for future economic research on livestock production.

Degree

Ph.D.

Advisors

Preckel, Purdue University.

Subject Area

Agricultural economics

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