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中国精品科技期刊2020 食品青年科学家峰会

超声辅助优化制备壳寡糖-果胶稳定的Pickering乳液工艺及稳定性分析

廖静如 杜冰 刘志伟 黎攀 范丽萍

廖静如,杜冰,刘志伟,等. 超声辅助优化制备壳寡糖-果胶稳定的Pickering乳液工艺及稳定性分析[J]. 新宝登录入口(中国)有限公司,2023,44(13):9−20. doi:  10.13386/j.issn1002-0306.2022110331
引用本文: 廖静如,杜冰,刘志伟,等. 超声辅助优化制备壳寡糖-果胶稳定的Pickering乳液工艺及稳定性分析[J]. 新宝登录入口(中国)有限公司,2023,44(13):9−20. doi:  10.13386/j.issn1002-0306.2022110331
LIAO Jingru, DU Bing, LIU Zhiwei, et al. Study on Ultrasound-assisted Optimization of Chitooligosaccharide-Pectin Stabilized Pickering Emulsion and Its Stability[J]. Science and Technology of Food Industry, 2023, 44(13): 9−20. (in Chinese with English abstract). doi:  10.13386/j.issn1002-0306.2022110331
Citation: LIAO Jingru, DU Bing, LIU Zhiwei, et al. Study on Ultrasound-assisted Optimization of Chitooligosaccharide-Pectin Stabilized Pickering Emulsion and Its Stability[J]. Science and Technology of Food Industry, 2023, 44(13): 9−20. (in Chinese with English abstract). doi:  10.13386/j.issn1002-0306.2022110331

超声辅助优化制备壳寡糖-果胶稳定的Pickering乳液工艺及稳定性分析

doi: 10.13386/j.issn1002-0306.2022110331
基金项目: 财政部和农业农村部:国家现代农业产业技术体系(CARS-21);国家自然科学基金青年基金(No. 32202058);梅州市科技计划项目:梅州柚幼果成分分析评价及综合开发应用技术研究(2020B0205004)
详细信息
    作者简介:

    廖静如(2000−)(ORCID:0000−0002−4661−1857),女,硕士研究生,研究方向:食品营养与安全,E-mail:15875401128@163.com

    通讯作者:

    黎攀(1990−)(ORCID:0000−0001−8106−8581)男,博士,副教授,研究方向:新资源食品原料有效成分评价,E-mail:lp19900815@scau.edu.cn

    范丽萍(1995−)(ORCID: 0000−0002−0583−9812),女,硕士,助理讲师,研究方向:食品科学,E-mail:2429777453@qq.com

  • 中图分类号: TS201.2

Study on Ultrasound-assisted Optimization of Chitooligosaccharide-Pectin Stabilized Pickering Emulsion and Its Stability

  • 摘要: 为探究超声辅助制备壳寡糖稳定的Pickering乳液的最佳工艺及其稳定性,本文以壳寡糖、果胶为Pickering颗粒原料,以葵花籽油为油相,选取乳化活性指数(EAI)和乳化稳定性指数(ESI)为指标,通过单因素实验和响应面优化超声辅助制备壳寡糖-果胶稳定的Pickering乳液的工艺条件,并考察优化条件下乳液的稳定性。结果表明,壳寡糖-果胶稳定的Pickering乳液的最佳制备工艺为:壳寡糖与果胶质量比为0.05,溶液pH为5.22,油相体积分数为32%,超声功率为350 W,该优化条件下制备的乳液EAI为(5.129±0.003)m2/g,ESI为(796.68±4.43)min;稳定性实验及乳液内部显微结构观察表明,乳液在25~50 ℃和0~100 mmol/L盐离子(NaCl)条件下具有良好的乳化稳定性。因此,结合超声技术辅助优化获得的新型Pickering乳液,改善了乳液的乳化特性,为壳寡糖Pickering颗粒制备及其应用提供了参考。
  • 图  1  不同质量比下Pickering乳液的外观分层和乳析指数

    Figure  1.  Appearance delamination and creaming index of Pickering emulsions at different mass ratio

    注:A:初始;B:2 h;C:12 h;D:36 h;图3图5图7同。

    图  2  不同质量比Pickering乳液的显微结构(40×)、黏度和EAI、ESI

    Figure  2.  Microstructure (40×), viscosity and EAI, ESI of Pickering emulsion under different mass ratio

    注:A:0.00;B:0.05;C:0.10;D:0.40;E:0.70;F:1.00;不同小写字母表示不同质量比下制备的乳液黏度、EAI之间具有显著性差异(P<0.05);不同大写字母表示不同质量比下制备的乳液ESI具有显著性差异(P<0.05)。

    图  3  不同pH下Pickering乳液的外观分层和乳析指数

    Figure  3.  Appearance delamination and creaming index of Pickering emulsions at different pH

    图  4  不同pH下Pickering乳液的显微结构(40×)、黏度、EAI和ESI

    Figure  4.  Microstructure (40×), viscosity and EAI, ESI of Pickering emulsion under different pH

    注:A:2.5;B:3.5;C:4.5;D:5.5;E:6.5;不同小写字母表示不同pH下制备的乳液黏度、EAI之间具有显著性差异(P<0.05);不同大写字母表示不同pH下制备的乳液ESI具有显著性差异(P<0.05)。

    图  5  不同油相体积分数下Pickering乳液的外观分层和乳析指数

    Figure  5.  Appearance delamination and creaming index of Pickering emulsion at different oil phase volume fraction

    图  6  不同油相体积分数下Pickering乳液的显微结构(40×)、黏度和EAI、ESI

    Figure  6.  Microstructure (40×), viscosity and EAI, ESI of Pickering emulsion under different oil phase volume fraction

    注:A:10%;B:20%;C:30%;D:40%;E:50%;不同小写字母表示不同油相体积分数下制备的乳液黏度、EAI之间具有显著性差异(P<0.05);不同大写字母表示不同油相体积分数下制备的乳液ESI具有显著性差异(P<0.05)。

    图  7  不同超声功率下Pickering乳液的外观分层和乳析指数

    Figure  7.  Appearance delamination and creaming index of Pickering emulsion at different ultrasonic power

    图  8  不同超声功率下Pickering乳液的显微结构(40×)、黏度和EAI、ESI

    Figure  8.  Microstructure (40×), viscosity and EAI, ESI of Pickering emulsion under different ultrasonic power

    注:A:0 W;B:150 W;C:250 W;D:350 W;E:450 W;不同小写字母表示不同超声功率下制备的乳液黏度、EAI之间具有显著性差异(P<0.05);不同大写字母表示不同超声功率下制备的乳液ESI具有显著性差异(P<0.05)。

    9  不同变量对Pickering乳液EAI交互作用的3D曲面图和二维等高线

    9.  3D Surface diagram and two-dimensional contour line of interaction between different variables on Pickering emulsion EAI

    图  10  不同变量对Pickering乳液ESI交互作用的3D曲面图和二维等高线

    Figure  10.  3D Surface diagram and two-dimensional contour line of interaction between different variables on Pickering emulsion ESI

    图  11  Pickering乳液在不同温度处理下的显微结构(40×)、EAI、ESI和乳析指数

    Figure  11.  Microstructure (40×), EAI, ESI and emulsification index of Pickering emulsion at different temperature

    注:A:25 ℃;B:50 ℃;C:75 ℃。

    图  12  Pickering乳液在不同盐离子处理下的显微结构(40×)、EAI、ESI和乳析指数

    Figure  12.  Microstructure (40×), EAI, ESI and emulsification index of Pickering emulsion treated with different salt ion

    注:A:0 mmol/L;B:100 mmol/L;C:300 mmol/L。

    表  1  响应面试验的因素水平设计

    Table  1.   Factors and levels of response surface methodology

    水平A 壳寡糖-果胶质量比
    B 溶液pH
    C 油相体积分数
    (%)
    D 超声功率
    (W)
    −10.055.030150
    00.105.540250
    10.156.050350
    下载: 导出CSV

    表  2  响应面试验方案及结果

    Table  2.   Experiment scheme and results of response surface methodology

    试验号ABCDEAI
    (m2/g)
    ESI
    (min)
    试验号ABCDEAI
    ( m2/g)
    ESI
    (min)
    1−10102.298554.41610100.848304.4
    201−102.157381.317−100−13.650372.9
    300006.696854.318100−10.754378.6
    410−101.100315.019−1−1003.662772.0
    510010.975362.92001011.894411.3
    6−10014.848701.52100−113.098795.9
    70−1011.511525.0221−1001.206261.5
    800111.759636.72300007.534915.3
    900006.834833.9240−1−106.088458.7
    1000−1−11.520520.02501102.213567.8
    110−10−11.621294.126010−11.834455.0
    12−10−106.556754.0270−1101.186515.0
    1300006.659994.42800006.379961.8
    1411000.963358.629001−11.122442.7
    15−11004.456407.4
    下载: 导出CSV

    表  3  EAI的回归模型方差分析

    Table  3.   Variance analysis of regression model of EAI

    项目平方和自由度均方FP显著性
    模型141.231410.0922.00< 0.0001**
    A32.09132.0969.98< 0.0001**
    B0.2610.260.560.4663
    C10.25110.2522.360.0003**
    D1.0711.072.330.1488
    AB0.2710.270.590.4566
    AC4.0114.018.750.0104*
    AD0.2410.240.520.4826
    BC6.1516.1513.400.0026**
    BD7.225E-00317.225E-0030.0160.9019
    CD0.2210.220.480.4986
    A223.76123.7651.81< 0.0001**
    B232.25132.2570.31< 0.0001**
    C228.21128.2161.51< 0.0001**
    D249.24149.24107.37< 0.0001**
    残差6.42140.46
    失拟项5.70100.573.160.1392
    纯误差0.7240.18
    总离差147.6528
    注:**P<0.01为极显著;*P<0.05为显著;表4同。
    下载: 导出CSV

    表  4  ESI的回归模型方差分析

    Table  4.   Variance analysis of regression model of ESI

    项目平方和自由度均方FP显著性
    模型1.228E+0061487739.2010.58< 0.0001**
    A2.137E+00512.137E+00525.770.0002**
    B4998.0014998.000.600.4504
    C3464.6013464.600.420.5285
    D75208.33175208.339.070.0093**
    AB53291.72153291.726.430.0238*
    AC8930.2518930.251.080.3170
    AD26292.62126292.623.170.0967
    BC4238.0114238.010.510.4864
    BD18851.29118851.292.270.1538
    CD1676.9011676.900.200.6598
    A23.815E+00513.815E+00546.01< 0.0001**
    B24.451E+00514.451E+00553.68< 0.0001**
    C21.602E+00511.602E+00519.330.0006**
    D22.552E+00512.552E+00530.78< 0.0001**
    残差1.161E+005148291.36
    失拟项97369.50109736.952.080.2500
    纯误差18709.5744677.39
    总离差1.344E+00628
    下载: 导出CSV

    表  5  响应面的验证实验结果与分析

    Table  5.   Verification test results and analysis of response surface methodology

    序号EAI(m2/g)ESI(min)
    15.125792.99
    25.130802.91
    35.133794.14
    均值5.129±0.003796.68±4.43
    相对平均偏差0.06%0.52%
    回归方程预测值5.13799.435
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-12-01
  • 网络出版日期:  2023-05-20
  • 刊出日期:  2023-07-01

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