Quality monitoring during sufu fermented process and establishment of random forest prediction model

Author:

Wang Xiaodan1ORCID,Chang Ping1,Wang Cuilian1,Zhu Shijie2,Wu Duo1,Jiang Shaoping1,Tian Jiaxue1

Affiliation:

1. College of Food Science and Engineering Jilin University Changchun 130062 China

2. Changchun ZhuLaoLiu Food Co., Ltd Changchun 130507 China

Abstract

SummaryMicroscopic, mechanical, physiochemical and colour changes of sufu during fermentation (10, 20, 30, 40, 50, 60 days) were analysed to predict sufu quality objectively and accurately. Fourier transform infrared spectroscopy (FT‐IR) and scanning electron microscopy (SEM) showed that the absorption peaks at 702, 1454, 1652, 2926 and 3281 cm−1 increased in intensity, and sufu was altered from a granular colloidal protein structure to a smooth and uniform shape. Analysis of mechanical, physiochemical and colour properties demonstrated the growth of mucor, the addition of salt and dressing mixture had a significant impact on the changes of indexes of sufu with extension of fermentation time. Besides, a random forest (RF) sufu quality prediction model with 90% accuracy was established by selecting forest quality evaluation indicators using RF and setting the model parameters mtry and ntree to 5 and 900, respectively.

Funder

Education Department of Jilin Province

Publisher

Wiley

Subject

Industrial and Manufacturing Engineering,Food Science

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