Journal of Agricultural Science and Technology ›› 2024, Vol. 26 ›› Issue (4): 225-233.DOI: 10.13304/j.nykjdb.2022.0964
• INNOVATIVE METHODS AND TECHNOLOGIES • Previous Articles
Dongling LIU1(), Hao SI1, Baojiang ZHENG2, Yuhong ZHANG1(
)
Received:
2022-11-06
Accepted:
2023-02-07
Online:
2024-04-15
Published:
2024-04-23
Contact:
Yuhong ZHANG
通讯作者:
张玉红
作者简介:
刘东玲 E-mail:898890042@qq.com;
基金资助:
CLC Number:
Dongling LIU, Hao SI, Baojiang ZHENG, Yuhong ZHANG. Optimization of Enzyme Assisted-ultrasonic Extraction of Sinigrin in Thlaspi arvense Seeds by Response Surface Methodology[J]. Journal of Agricultural Science and Technology, 2024, 26(4): 225-233.
刘东玲, 司皓, 郑宝江, 张玉红. 响应面法优化酶解辅助-超声提取菥蓂中的黑芥子苷[J]. 中国农业科技导报, 2024, 26(4): 225-233.
水平Level | 因素Factor | ||
---|---|---|---|
A:酶添加量 Amount of enzyme added/% | B:酶解时间 Enzymatic hydrolysis time/min | C:酶解温度 Enzymatic hydrolysis temperature/℃ | |
-1 | 2 | 15 | 45 |
0 | 3 | 20 | 50 |
1 | 4 | 25 | 55 |
Table 1 Response surface experimental factor level table
水平Level | 因素Factor | ||
---|---|---|---|
A:酶添加量 Amount of enzyme added/% | B:酶解时间 Enzymatic hydrolysis time/min | C:酶解温度 Enzymatic hydrolysis temperature/℃ | |
-1 | 2 | 15 | 45 |
0 | 3 | 20 | 50 |
1 | 4 | 25 | 55 |
Fig. 2 Yield of sinigrin in T. arvense underdifferent enzymesNote: Different lowercase letters indicate significant differences between different enzymes at P<0.05 level.
Fig. 3 Yield of sinigrin in T. arvense under different factorsNote:Different lowercase letters indicate significant differences between different treatments at P<0.05 level.
编号 Code | 因素 Factor | Y:黑芥子苷得率 Sinigrin yield/(mg·g-1) | |||
---|---|---|---|---|---|
A:酶添加量 Amount of enzyme added/% | B:酶解时间 Enzymatic hydrolysis time/min | C:酶解温度 Enzymatic hydrolysis temperature/℃ | 实际值 Actual value | 预测值 Predicted value | |
1 | 2 | 15 | 50 | 2.50 | 2.52 |
2 | 3 | 15 | 45 | 2.61 | 2.60 |
3 | 2 | 25 | 50 | 2.36 | 2.37 |
4 | 4 | 15 | 50 | 2.45 | 2.44 |
5 | 3 | 20 | 50 | 2.63 | 2.67 |
6 | 4 | 25 | 50 | 2.30 | 2.34 |
7 | 3 | 20 | 50 | 2.69 | 2.67 |
8 | 4 | 20 | 55 | 2.34 | 2.35 |
9 | 3 | 20 | 50 | 2.70 | 2.67 |
10 | 3 | 20 | 50 | 2.67 | 2.67 |
11 | 3 | 20 | 50 | 2.65 | 2.67 |
12 | 3 | 15 | 55 | 2.46 | 2.47 |
13 | 4 | 20 | 45 | 2.35 | 2.38 |
14 | 2 | 20 | 45 | 2.45 | 2.45 |
15 | 3 | 25 | 55 | 2.41 | 2.43 |
16 | 2 | 20 | 55 | 2.41 | 2.39 |
17 | 3 | 25 | 45 | 2.39 | 2.39 |
Table 2 Response surface design and results
编号 Code | 因素 Factor | Y:黑芥子苷得率 Sinigrin yield/(mg·g-1) | |||
---|---|---|---|---|---|
A:酶添加量 Amount of enzyme added/% | B:酶解时间 Enzymatic hydrolysis time/min | C:酶解温度 Enzymatic hydrolysis temperature/℃ | 实际值 Actual value | 预测值 Predicted value | |
1 | 2 | 15 | 50 | 2.50 | 2.52 |
2 | 3 | 15 | 45 | 2.61 | 2.60 |
3 | 2 | 25 | 50 | 2.36 | 2.37 |
4 | 4 | 15 | 50 | 2.45 | 2.44 |
5 | 3 | 20 | 50 | 2.63 | 2.67 |
6 | 4 | 25 | 50 | 2.30 | 2.34 |
7 | 3 | 20 | 50 | 2.69 | 2.67 |
8 | 4 | 20 | 55 | 2.34 | 2.35 |
9 | 3 | 20 | 50 | 2.70 | 2.67 |
10 | 3 | 20 | 50 | 2.67 | 2.67 |
11 | 3 | 20 | 50 | 2.65 | 2.67 |
12 | 3 | 15 | 55 | 2.46 | 2.47 |
13 | 4 | 20 | 45 | 2.35 | 2.38 |
14 | 2 | 20 | 45 | 2.45 | 2.45 |
15 | 3 | 25 | 55 | 2.41 | 2.43 |
16 | 2 | 20 | 55 | 2.41 | 2.39 |
17 | 3 | 25 | 45 | 2.39 | 2.39 |
来源 Source | 自由度 Degree of freedom | 平方和 Sum of squares | 均方 Mean square | F值 F valve | P值 P valve |
---|---|---|---|---|---|
模型 Model | 9 | 0.270 | 0.030 | 34.84 | <0.000 1 |
A | 1 | 6.050×10-3 | 6.050×10-3 | 6.97 | 0.033 5 |
B | 1 | 0.031 | 0.031 | 35.98 | 0.000 5 |
C | 1 | 4.050×10-3 | 4.050×10-3 | 4.66 | 0.067 7 |
AB | 1 | 6.250×10-4 | 6.250×10-4 | 0.72 | 0.424 3 |
AC | 1 | 2.250×10-4 | 2.250×10-4 | 0.26 | 0.626 4 |
BC | 1 | 7.225×10-3 | 7.225×10-3 | 8.32 | 0.023 5 |
A2 | 1 | 0.110 | 0.110 | 132.38 | <0.000 1 |
B2 | 1 | 0.031 | 0.031 | 35.23 | 0.000 6 |
C2 | 1 | 0.056 | 0.056 | 64.39 | <0.000 1 |
残差Residual | 7 | 6.080×10-3 | 8.686×10-4 | ||
失拟项Lack of fit | 3 | 2.800×10-3 | 9.333×10-4 | 1.14 | 0.434 6 |
误差Error | 4 | 3.280×10-3 | 8.200×10-4 | ||
总离差Total deviation | 16 | 0.280 |
Table 3 Results of variance analysis of response surface regression equation
来源 Source | 自由度 Degree of freedom | 平方和 Sum of squares | 均方 Mean square | F值 F valve | P值 P valve |
---|---|---|---|---|---|
模型 Model | 9 | 0.270 | 0.030 | 34.84 | <0.000 1 |
A | 1 | 6.050×10-3 | 6.050×10-3 | 6.97 | 0.033 5 |
B | 1 | 0.031 | 0.031 | 35.98 | 0.000 5 |
C | 1 | 4.050×10-3 | 4.050×10-3 | 4.66 | 0.067 7 |
AB | 1 | 6.250×10-4 | 6.250×10-4 | 0.72 | 0.424 3 |
AC | 1 | 2.250×10-4 | 2.250×10-4 | 0.26 | 0.626 4 |
BC | 1 | 7.225×10-3 | 7.225×10-3 | 8.32 | 0.023 5 |
A2 | 1 | 0.110 | 0.110 | 132.38 | <0.000 1 |
B2 | 1 | 0.031 | 0.031 | 35.23 | 0.000 6 |
C2 | 1 | 0.056 | 0.056 | 64.39 | <0.000 1 |
残差Residual | 7 | 6.080×10-3 | 8.686×10-4 | ||
失拟项Lack of fit | 3 | 2.800×10-3 | 9.333×10-4 | 1.14 | 0.434 6 |
误差Error | 4 | 3.280×10-3 | 8.200×10-4 | ||
总离差Total deviation | 16 | 0.280 |
指标Index | 响应值 Response value |
---|---|
标准偏差Standard deviation | 0.029 0 |
变异系数Coefficient of variable/% | 1.180 0 |
拟合系数R2 | 0.978 2 |
调整系数 R2Adj | 0.950 1 |
预测系数 R2Pred | 0.820 7 |
Table 4 Confidence analysis
指标Index | 响应值 Response value |
---|---|
标准偏差Standard deviation | 0.029 0 |
变异系数Coefficient of variable/% | 1.180 0 |
拟合系数R2 | 0.978 2 |
调整系数 R2Adj | 0.950 1 |
预测系数 R2Pred | 0.820 7 |
Fig. 6 Yield of sinigrin by different extraction methodsNote:Different lowercase letters indicate significant differences between different methods at P<0.05 level.
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