Literature DB >> 33878579

Evaluation of cooking performance, structural properties, storage stability and shelf life prediction of high-moisture wet starch noodles.

Sha Yang1, Meng-Na Zhang2, Chang-Song Shan3, Zhi-Gang Chen4.   

Abstract

Cooking performance, micro- and molecular structure, storage stability and shelf-life prediction of high-moisture wet starch noodles (SN) were investigated. SEM images revealed that compared to dried SN, cooked wet SN had more evenly honeycomb-like network with smaller size of pores, indicating stronger interaction among molecules and causing favorable cooking performance. XRD and ATR-FTIR results evidenced that wet SN contained more complete crystallites and higher proportion of crystalline region. During storage, the quality decay of wet SN was mainly associated to the increment of total aerobic viable count (TAVC), titrable acidity and amylase, as well as the decreased textural hardness, overall acceptability and lightness. Based on TAVC, titrable acidity and overall acceptability, predicted shelf-life of vacuum-packed wet SN at 25 °C was 15.31, 21.54 and 16.65 weeks respectively, with relative error all within 20%, proving that the validated model could be an effective tool for monitoring the shelf-life of wet SN.
Copyright © 2021 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Accelerated storage; FTIR; Kinetic modelling; SEM; Shelf life prediction; XRD

Year:  2021        PMID: 33878579     DOI: 10.1016/j.foodchem.2021.129744

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  2 in total

1.  Shelf-Life Prediction and Critical Value of Quality Index of Sichuan Sauerkraut Based on Kinetic Model and Principal Component Analysis.

Authors:  Jie Du; Min Zhang; Lihui Zhang; Chung Lim Law; Kun Liu
Journal:  Foods       Date:  2022-06-15

2.  Effect of Frying Process on Nutritional Property, Physicochemical Quality, and in vitro Digestibility of Commercial Instant Noodles.

Authors:  Jin Wang; Ang Li; Jiaqiang Hu; Bowei Zhang; Jingmin Liu; Yan Zhang; Shuo Wang
Journal:  Front Nutr       Date:  2022-02-17
  2 in total

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