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中国精品科技期刊2020 食品青年科学家峰会

甜玉米芯多糖铬配合物的制备、结构表征及体外活性的研究

修伟业 王鑫 李雨蒙 遇世友 黎晨晨 罗钰 周卓 马永强

修伟业,王鑫,李雨蒙,等. 甜玉米芯多糖铬配合物的制备、结构表征及体外活性的研究[J]. 新宝登录入口(中国)有限公司,2023,44(13):186−196. doi:  10.13386/j.issn1002-0306.2022080338
引用本文: 修伟业,王鑫,李雨蒙,等. 甜玉米芯多糖铬配合物的制备、结构表征及体外活性的研究[J]. 新宝登录入口(中国)有限公司,2023,44(13):186−196. doi:  10.13386/j.issn1002-0306.2022080338
XIU Weiye, WANG Xin, LI Yumeng, et al. Preparation, Structural Characterization and in Vitro Activity of Chromium Complexes of Sweet Corn Cob Polysaccharide[J]. Science and Technology of Food Industry, 2023, 44(13): 186−196. (in Chinese with English abstract). doi:  10.13386/j.issn1002-0306.2022080338
Citation: XIU Weiye, WANG Xin, LI Yumeng, et al. Preparation, Structural Characterization and in Vitro Activity of Chromium Complexes of Sweet Corn Cob Polysaccharide[J]. Science and Technology of Food Industry, 2023, 44(13): 186−196. (in Chinese with English abstract). doi:  10.13386/j.issn1002-0306.2022080338

甜玉米芯多糖铬配合物的制备、结构表征及体外活性的研究

doi: 10.13386/j.issn1002-0306.2022080338
基金项目: 黑龙江省应用技术研究与开发计划(GA20B301);哈尔滨商业大学“青年创新人才”支持计划(2019CX31)
详细信息
    作者简介:

    修伟业(1996−),男,博士研究生,研究方向:农产品加工及精深利用,E-mail:xiuweiye0451@163.com

    通讯作者:

    王鑫(1984−),女,博士,高级工程师,研究方向:农产品精深加工及利用,E-mail:wangxinfood@163.com

  • 中图分类号: TS201.1

Preparation, Structural Characterization and in Vitro Activity of Chromium Complexes of Sweet Corn Cob Polysaccharide

  • 摘要: 为提升甜玉米芯多糖生物学活性,制备一种甜玉米芯多糖铬配合物(SCP80-Cr),以单因素实验为基础,以响应面试验优化制备工艺,并进行表征及探究体外活性。结果表明,SCP80-Cr制备最佳工艺条件为pH10.1、反应温度74 ℃、多糖浓度3 mg/mL,反应时间60 min。SCP80-Cr中Cr元素重量百分比为21.08%,元素百分比为6.67%。对SCP80-Cr进行表征发现,SCP80-Cr几乎不含有蛋白、核酸、色素类物质,而Cr是以Cr-O及Cr-OH的形式与SCP80缔合,并具有较强的分子团聚特性。单糖组成测定说明SCP80-Cr单糖组成摩尔百分比为甘露糖:葡萄糖:半乳糖:木糖:阿拉伯糖=0.58:89.50:4.65:1.33:3.58。体外降糖实验结果表明,SCP80-Cr对α-淀粉酶及α-葡萄糖苷酶抑制率的IC50分别为4.70±0.38 mg/mL和3.99±0.26 mg/mL;体外抗氧化实验结果表明,SCP80-Cr清除DPPH自由基及羟基自由基IC50分别为4.80±0.34 mg/mL和4.99±0.28 mg/mL,说明SCP80-Cr相比于SCP80具有更好的体外降糖及抗氧化活性。研究结果为甜玉米芯多糖在功能性食品中的研究提供一定参考价值。
  • 图  1  单因素实验结果

    Figure  1.  Results of single-factor test

    注:图中不同小写字母表示组间具有显著性差异(P<0.05)。

    图  2  两因素交互作用对铁离子还原力影响的等高线与曲面图

    Figure  2.  Contour and surface diagram of the influence of the interaction of two factors on the reduction force of iron ions

    3  扫描电镜图像及EDS元素映射图像

    3.  SEM image and corresponding EDS elemental mapping image

    注:A~C:SCP80 SEM图像(A:×10 k,B:×20 k,C:×40 k);D~F:SCP80-Cr SEM图像(A:×10 k,B:×20 k,C:×40 k);G:SCP80-Cr EDS图像;H:SCP80-Cr 元素mapping分布图像。

    图  4  SCP80-Cr紫外(A)及红外(B)光谱

    Figure  4.  Ultraviolet spectrum (A) and Infrared spectrum (B) of SCP80-Cr

    图  5  SCP80-Cr X射线光电子能谱图

    Figure  5.  XPS of SCP80-Cr

    注:A~C:SCP80 X射线光电子能谱(A:全谱图;B:C 1s;C:O 1s);D~G:SCP80-Cr X射线光电子能谱(D:全谱图;E:C 1s;F:O 1s;G:Cr 2p)。

    图  6  SCP80-Cr的热稳定性分析

    Figure  6.  Thermal stability analysis of SCP80-Cr

    注:A:TG;B:DTG。

    图  7  SCP80-Cr的2D(A)及3D(B)AFM图像

    Figure  7.  AFM image of SCP80-Cr (A:2D;B:3D)

    图  8  SCP80-Cr单糖组成分析

    Figure  8.  Monosaccharide composition of SCP80-Cr

    注:A:14种单糖标准品液相色谱曲线;B:SCP80-Cr单糖组成液相色谱曲线。其中1:L-古洛糖醛酸;2:D-甘露糖醛酸;3:D-甘露糖;4:D-核糖;5:L-鼠李糖;6:D-氨基葡萄糖;7:D-葡萄糖醛酸;8:D-半乳糖醛酸;9:D-葡萄糖;10:D-氨基半乳糖;11:D-半乳糖;12:D-木糖;13:L-阿拉伯糖;14:L-岩藻糖。

    图  9  SCP80-Cr体外活性分析

    Figure  9.  Analysis of the in vitro activity of SCP80-Cr

    注:A:α-淀粉酶抑制率;B:α-葡萄糖苷酶抑制率;C:DPPH自由基清除率;D:羟基自由基清除率。

    表  1  星点设计因素与水平

    Table  1.   Factors and levels used for the central composite design

    水平因素
    A pHB温度(℃)C多糖浓度(mg/mL)
    −1.6829.0070.002.00
    −19.4172.032.41
    010.0075.003.00
    110.5977.973.59
    1.68211.0080.004.00
    下载: 导出CSV

    表  2  液相梯度洗脱条件

    Table  2.   HPLC gradient elution conditions

    时间(min)流动相(%)
    AB
    08614
    98317
    287822
    295050
    315050
    下载: 导出CSV

    表  3  星点设计-响应面法试验设计及结果

    Table  3.   Experimental design and results of central design response surface method (CCD)

    试验号因素Y 铁离子还原力(A)
    A pH
    B 温度
    C 多糖浓度
    100−1.6820.301
    2−1−110.173
    31−1−10.189
    4−1−1−10.306
    51−110.404
    60−1.68200.417
    70000.539
    80110.310
    90000.513
    1001.68200.291
    11001.6820.276
    120000.396
    130000.491
    14−11−10.136
    151.682000.252
    16−1.682000.107
    170000.497
    18−1110.101
    1911−10.231
    200000.521
    下载: 导出CSV

    表  4  回归方程的方差分析结果

    Table  4.   Analysis of variance of regression model

    差异来源平方和自由度均方FP显著性
    模型0.3790.04116.65<0.0001**
    A0.03210.03213.140.0046**
    B0.01910.0197.680.0198*
    C5.161×10−415.161×10−30.210.6555
    AB4.513×10−314.513×10−31.850.2038
    AC0.02710.02710.930.0079**
    BC1.805×10−411.805×10−40.0740.7912
    A20.2010.2080.83<0.0001**
    B20.04410.04418.060.0017**
    C20.08910.08936.350.0001**
    残差0.024102.441×10−3
    失拟项0.01252.336×10−30.920.5365不显著
    纯误差0.01352.546×10−3
    总和0.3919
    注:*代表影响显著(P<0.05);**代表影响极显著(P<0.01)。
    下载: 导出CSV
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  • 收稿日期:  2022-08-31
  • 网络出版日期:  2023-05-21
  • 刊出日期:  2023-07-01

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