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

doi:10.1515/ijfe-2018-0056

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

Department of Food Technology

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

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 language	English
Article number	20180056
Journal	International Journal of Food Engineering
Volume	16
Issue number	5-6
DOIs	https://doi.org/10.1515/ijfe-2018-0056
Publication status	Published - 2020 Jun 1

Keywords

critical moisture content
linear programming
linearization
optimization
surimi
texture map

ASJC Scopus subject areas

Biotechnology
Food Science
Engineering (miscellaneous)

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

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.",

keywords = "critical moisture content, linear programming, linearization, optimization, surimi, texture map",

author = "Park, {Hyeon W.} and Park, {Jae W.} and Yoon, {Won B.}",

note = "Funding Information: This study was supported by 2018 Research Grant (PoINT) from Kangwon National University. Publisher Copyright: {\textcopyright} 2019 Walter de Gruyter GmbH, Berlin/Boston 2019.",

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AB - 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.

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

Abstract

Keywords

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