Developing a Linearization Method to Determine Optimum Blending for Surimi with Varied Moisture Contents Using Linear Programming

Hyeon W. Park, Jae W. Park, Won B. Yoon

Research output: Contribution to journalArticle

Abstract

Novel algorithm to determine the least cost formulation of a surimi blend was developed using linear programming (LP). Texture properties and the unit cost of surimi blend at the target moisture content were used as constraint functions and the objective function, respectively. The mathematical models to describe the moisture content dependence of the ring tensile properties were developed using critical moisture content, and the model parameters were used for the least cost LP (LCLP) model. The LCLP model successfully predicted the quality of surimi blend. Sensitivity analysis was used to obtain an additional information when the perturbations of design variables are provided. A standard procedure to determine the least cost formulation for blending surimi with varied moisture contents was systematically developed.

Original languageEnglish
JournalInternational Journal of Food Engineering
DOIs
Publication statusPublished - 2019 Jan 1

Fingerprint

Linear Programming
surimi
linear programming
Linearization
Linear programming
Moisture
blended foods
water content
Costs and Cost Analysis
Costs
methodology
mathematical models
texture
Tensile properties
Sensitivity analysis
Theoretical Models
Textures
Mathematical models

Keywords

  • critical moisture content
  • linear programming
  • linearization
  • optimization
  • surimi
  • texture map

ASJC Scopus subject areas

  • Biotechnology
  • Food Science
  • Engineering (miscellaneous)

Cite this

Developing a Linearization Method to Determine Optimum Blending for Surimi with Varied Moisture Contents Using Linear Programming. / Park, Hyeon W.; Park, Jae W.; Yoon, Won B.

In: International Journal of Food Engineering, 01.01.2019.

Research output: Contribution to journalArticle

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