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响应面法优化鸡肉蛋白酶解工艺

于亚辉 陈沁雯 李晓婷 方婷

于亚辉,陈沁雯,李晓婷,等. 响应面法优化鸡肉蛋白酶解工艺 [J]. 福建农业学报,2020,35(1):80−89 doi: 10.19303/j.issn.1008-0384.2020.01.012
引用本文: 于亚辉,陈沁雯,李晓婷,等. 响应面法优化鸡肉蛋白酶解工艺 [J]. 福建农业学报,2020,35(1):80−89 doi: 10.19303/j.issn.1008-0384.2020.01.012
YU Y H, CHEN Q W, LI X T, et al. Optimized Proteolysis of Chicken Protein for Food Flavoring [J]. Fujian Journal of Agricultural Sciences,2020,35(1):80−89 doi: 10.19303/j.issn.1008-0384.2020.01.012
Citation: YU Y H, CHEN Q W, LI X T, et al. Optimized Proteolysis of Chicken Protein for Food Flavoring [J]. Fujian Journal of Agricultural Sciences,2020,35(1):80−89 doi: 10.19303/j.issn.1008-0384.2020.01.012

响应面法优化鸡肉蛋白酶解工艺

doi: 10.19303/j.issn.1008-0384.2020.01.012
基金项目: 国家自然科学基金项目(31401597、31601393)
详细信息
    作者简介:

    于亚辉(1993−),男,硕士,研究方向:食品风味化学(E-mail:2951588827@qq.com

    通讯作者:

    方婷(1981−),女,博士,教授,研究方向:食品加工理论与应用(fangting930@163.com

  • 中图分类号: TS 254.1

Optimized Proteolysis of Chicken Protein for Food Flavoring

  • 摘要:   目的  采用双酶分步酶解方法优化鸡肉蛋白酶解工艺,为制备品质较佳的鸡肉香精提供技术参考。  方法  以动物蛋白酶与复合蛋白酶为目标酶,游离氨基酸、多肽含量为评价指标,在单因素试验的基础上,采用Plackett-Burman设计筛选出重要影响因素。接着采用最陡爬坡试验逼近最大响应区域,确定响应面优化试验中心点,最后选取游离氨基酸、多肽含量以及热反应产物风味评分3个指标为评价依据,采用Box-Behnken响应面优化法,探讨鸡肉蛋白双酶分步酶解工艺及其对制备鸡肉香精风味的影响,确定重要参数的最佳水平。  结果  总加酶量、总时长、固液比为主要影响因素,通过响应面及岭脊分析确定参数值分别为0.82%、7.26 h、1 4.40,预测综合得分为89.41,实际得分88.97,模型可靠。  结论  通过多指标响应面法优化了鸡肉蛋白酶解条件,提高酶解效果,并制备出风味较佳的鸡肉香精。
  • 图  1  单因素试验结果

    Figure  1.  Single factor test results

    图  2  总加酶量、总时长和固液比交互作用对游离氨基酸浓度及多肽浓度影响的响应面和等高线

    Figure  2.  Response surface and contour lines on interactions among enzyme applied/process duration/solid-liquid ratio for process and free amino acid/peptide concentrations of hydrolysate

    表  1  鸡肉风味基料评价标准

    Table  1.   Evaluation standards on chicken flavor

    评价项目
    Evaluation project
    满分标准
    Full score standard
    评价分数范围
    Evaluation score range
    香味 Fragrance 香气浓郁、饱满、圆润与炖煮鸡肉香气较为一致
    The aroma is rich, full, round and the chicken aroma is more consistent
    0~30
    色泽 Color 红褐色、色泽均匀无明显异色
    Reddish brown, uniform color, no obvious color
    0~30
    滋味 Taste 口感柔和具有鸡肉滋味、无苦味等不适感
    The palate is soft and has a taste of chicken and no bitterness.
    0~20
    异味 Odor 无异味、焦糊味 No odor, burnt smell 0~20
    下载: 导出CSV

    表  2  单因素试验设计

    Table  2.   Single factor test design

    因素 Factor处理组 Group
    12345
    总加酶量 Total enzyme amount /% 0.2 0.4 0.6 0.8 1.0
    加酶比 Enzyme ratio 11 12 21 13 31
    固液比 Solid-liquid ratio 11 12 13 14 15
    总时长 Total length/h 4 5 6 7 8
    时长比 Duration ratio 11 12 21 23 32
    NaCl添加量 NaCl addition amount/% 0.4 0.6 0.8 1.0 1.2
    下载: 导出CSV

    表  3  Plackett-Burman设计试验参数和水平

    Table  3.   Factors and levels of PIackett-Burman design

    编号
    Code
    变量
    Variable
    水平(−1)
    Level (−1)
    水平(1)
    Level (1)
    A 总加酶量 Total enzyme amount /% 0.4 0.8
    B 加酶比 Enzyme ratio 11 31
    C 总时长 Total length/h 5 7
    D 时长比 Duration ratio 32 21
    E 固液比 Solid-liquid ratio 12 14
    F NaCl添加量 NaCl addition amount/% 0.6 1.0
    下载: 导出CSV

    表  4  Plackett-Burman试验设计及结果

    Table  4.   Plackett-Burman design and experimental results

    试验号
    Test number
    ABCDEF氨基酸含量
    Amino acid content /(mg·g−1)
    多肽含量
    Peptide content/ (mg·hg−1)
    综合评分
    Comprehensive score (Y)
    111−1111337.73278.67103.46
    21−1−1−11−1320.65266.7898.65
    3−1−11−111257.71225.0881.33
    4−111−111265.43235.9684.56
    5−1−1−11−11222.03168.4465.19
    61−1111−1342.45280.19104.45
    7−1111−1−1234.04185.2470.19
    8−11−111−1247.69215.6678.04
    9111−1−1−1287.58248.3790.22
    1011−1−1−11263.58221.6481.54
    111−111−11300.36245.7191.6
    12−1−1−1−1−1−1207.75156.4960.78
    下载: 导出CSV

    表  5  Plackett-Burman试验显著性因子选择模型方差分析

    Table  5.   ANOVA of Plackett-Burman test on selected factorial model

    变异来源
    Source of variation
    自由度
    Degree of freedom
    效应
    Effect
    F
    F value
    P
    P value
    显著性
    Significance
    总模型 Total model684.1795.15<0.000 1**
    A110.82361.09<0.000 1**
    B10.500.770.419 3
    C12.8925.780.003 8**
    D11.325.380.068 1
    E17.58177.28<0.000 1**
    F10.450.610.469 0
    注:*:P<0.05显著;**:P<0.01极显著。
    Note: *: P<0.05 significant; **: P<0.01 extremely significant.
    下载: 导出CSV

    表  6  最陡爬坡试验设计及结果

    Table  6.   Design and results of steepest ascent experiment

    试验号
    Test number
    A/%C/hE氨基酸含量
    Amino acid content /(mg·g−1)
    多肽含量
    Peptide content/ (mg·hg−1)
    综合评
    Comprehensive score (Y)
    10.2411129.4887.3134.49
    20.4512223.59168.6362.74
    30.6613326.27261.6594.33
    40.8714360.43301.25106.38
    51815351.96286.77102.56
    下载: 导出CSV

    表  7  Box-Behnken Design试验因素与水平

    Table  7.   Levels and factors of Box-Behnken experiment

    编号 Code因素 Factor水平 Level
    −101
    A总加酶量 Total enzyme amount /%0.60.81
    B总时长 Total length / h678
    C固液比 Solid-liquid ratio131415
    下载: 导出CSV

    表  8  Box-Behnken Design试验设计及结果

    Table  8.   Box-Behnken design and experimental results

    序号
    Serial number
    ABC氨基酸含量
    Amino acid content/(mg·g−1)
    多肽含量
    Peptide content/(mg·hg−1)
    感官评分
    Sensory score (P)
    综合评分
    Comprehensive score (Y)
    1−10−1321.79264.8246.3367.46
    2000351.96281.7783.1589.37
    3011358.28286.3669.5383.38
    4−101320.54260.8870.6579.21
    5−110333.88265.6356.3873.39
    6000352.55280.9278.1886.86
    7000354.02281.9679.6587.78
    80−11340.34270.5268.4780.29
    9000353.88283.0380.2588.16
    10−1−10350.08275.1544.8769.55
    11000351.64283.7781.3788.62
    121−10355.25288.3243.7770.45
    13101356.28290.6361.2879.47
    140−1−1344.65265.5850.3371.11
    15110365.99292.0662.4380.84
    1601−1355.29282.0564.6780.39
    1710−1345.37270.9355.0573.96
    下载: 导出CSV

    表  9  响应面回归模型方差分析

    Table  9.   ANOVA on response surface regression model

    方差来源
    Source of variance
    平方和
    Sum of square
    自由度
    Degree of freedom
    均方
    Mean square
    F
    F value
    P
    P value
    显著性
    Significance
    总模型 Total model853.19994.8088.54<0.000 1**
    A28.55128.5526.660.001 3**
    B88.38188.3882.54<0.000 1**
    C108.261108.26101.11<0.000 1**
    AB10.71110.7110.000.015 9*
    AC9.7319.739.090.019 5*
    BC9.5719.578.930.020 3*
    A2355.031355.03331.58<0.000 1**
    B2123.551123.55115.39<0.000 1**
    C265.67165.6761.340.000 1**
    残差 Residual7.4971.07
    失拟项 Missing item3.9731.321.500.342 8
    绝对误差 Absolute error3.5340.88
    总和 Sum860.6816
    相关系数 Correlation coefficient0.991 3
    校正决定系数 Correction decision coefficient0.980 1
    变异系数 Coefficient of variation1.30
    信噪比 Signal to noise ratio25.528>4
    注:*:P<0.05显著;**:P<0.01极显著。
    Note: *: P<0.05 significant; **: P<0.01 extremely significant.
    下载: 导出CSV
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  • 收稿日期:  2019-09-22
  • 修回日期:  2019-10-25
  • 刊出日期:  2020-01-01

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