Mathematical optimisation of extruded mixed plant protein-based meat analogues based on amino acid compositions

Xin Yi Hua; Yushen Long; Dayna Shu Min Ong; Alicia Hui Ping Theng; Jing K Shi; Raffael Osen; Min Wu; Jie Hong Chiang

doi:10.1016/j.crfs.2023.100648

Mathematical optimisation of extruded mixed plant protein-based meat analogues based on amino acid compositions

Curr Res Food Sci. 2023 Dec 5:7:100648. doi: 10.1016/j.crfs.2023.100648. eCollection 2023.

Authors

Xin Yi Hua¹, Yushen Long², Dayna Shu Min Ong¹, Alicia Hui Ping Theng¹, Jing K Shi², Raffael Osen¹, Min Wu², Jie Hong Chiang¹

Affiliations

¹ Singapore Institute of Food and Biotechnology Innovation, Agency for Science, Technology and Research (A*STAR), Singapore.
² Machine Intellection Department, Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore.

Abstract

Developing meat analogues of superior amino acid (AA) profiles in the food industry is a challenge as plant proteins contain less of some essential AA than animal proteins. Mathematical optimisation models such as linear/non-linear programming models were used to overcome this challenge and create high-moisture meat analogues (HMMA) with AA profiles as close as possible to chicken breast meat. The effect on the physiochemical properties and specific mechanical energy (SME) of the HMMA was investigated. The AA content of HMMA was generally lower than chicken. Strong intermolecular bonds present in the globulin fraction could hinder protein acid hydrolysis of HMMA. Plant proteins also affect the HMMA colour as certain AA forms Maillard reaction products with higher browning intensity. Lastly, different characteristics of plant proteins resulted in different SME values under the same extrusion conditions. While mathematical programming can optimise plant protein combinations, fortification is required to match the AA profile of HMMA to an animal source.

Keywords: Amino acid; Extrusion; Mathematical optimisation; Meat analogues; Plant protein.