Xinjiang Agricultural Sciences ›› 2021, Vol. 58 ›› Issue (11): 2103-2110.DOI: 10.6048/j.issn.1001-4330.2021.11.017
• Facility Agriculture·Agricultural Product Analysis and Detection • Previous Articles Next Articles
WANG Qinghui1(), YANG Jiapeng2(
), YANG Zhongqiang1
Received:
2020-10-28
Online:
2021-11-20
Published:
2021-12-16
Correspondence author:
YANG Jiapeng
Supported by:
通讯作者:
杨嘉鹏
作者简介:
王庆惠(1980-),女,山东梁山人,研究员,博士,研究方向为农产品加工技术及装备,(E-mail) wangqh1201@126.com
基金资助:
CLC Number:
WANG Qinghui, YANG Jiapeng, YANG Zhongqiang. Optimization of Apricot Drying Process Based on Box-Behnken Response Surface Method[J]. Xinjiang Agricultural Sciences, 2021, 58(11): 2103-2110.
王庆惠, 杨嘉鹏, 杨忠强. 基于Box-Behnken响应面法优化杏子干燥工艺[J]. 新疆农业科学, 2021, 58(11): 2103-2110.
Fig.1 Structure and working principle schematic diagram of 5HRG-14 heat pump dryer Note: 1 Control system; 2 Heat pump; 3 Heating pipe; 4 Drying chamber; 5 Temperature sensor; 6 Humidity sensor; 7 Fan; 8 Division; 9 Charging lorry; 10 Door
编码 Coding | 切分方式A Division mode A | 温度B Temperature B (℃) | 速度C Speed C (m/s) |
---|---|---|---|
-1 | 0 | 45 | 2 |
0 | 0.5 | 50 | 4 |
1 | 1 | 55 | 6 |
Table 1 Factors and coding of response surface test
编码 Coding | 切分方式A Division mode A | 温度B Temperature B (℃) | 速度C Speed C (m/s) |
---|---|---|---|
-1 | 0 | 45 | 2 |
0 | 0.5 | 50 | 4 |
1 | 1 | 55 | 6 |
序号 Number | 切分方式A Division mode A | 温度B Temperature B (℃) | 速度C Speed C (m/s) | 综合得分 Synthesis score |
---|---|---|---|---|
1 | 0 | 0 | 0 | 95 |
2 | 0 | 0 | 0 | 94 |
3 | 0 | 0 | 0 | 94 |
4 | 1 | 0 | -1 | 80 |
5 | 0 | 0 | 0 | 93 |
6 | -1 | 1 | 0 | 75 |
7 | 0 | 1 | -1 | 81 |
8 | 0 | -1 | 1 | 76 |
9 | 1 | -1 | 0 | 72 |
10 | 1 | 1 | 0 | 77 |
11 | -1 | -1 | 0 | 74 |
12 | 0 | 1 | 1 | 75 |
13 | 1 | 0 | 1 | 84 |
14 | -1 | 0 | 1 | 80 |
15 | 0 | -1 | -1 | 73 |
16 | -1 | 0 | -1 | 82 |
17 | 0 | 0 | 0 | 95 |
Table 2 Test design and results
序号 Number | 切分方式A Division mode A | 温度B Temperature B (℃) | 速度C Speed C (m/s) | 综合得分 Synthesis score |
---|---|---|---|---|
1 | 0 | 0 | 0 | 95 |
2 | 0 | 0 | 0 | 94 |
3 | 0 | 0 | 0 | 94 |
4 | 1 | 0 | -1 | 80 |
5 | 0 | 0 | 0 | 93 |
6 | -1 | 1 | 0 | 75 |
7 | 0 | 1 | -1 | 81 |
8 | 0 | -1 | 1 | 76 |
9 | 1 | -1 | 0 | 72 |
10 | 1 | 1 | 0 | 77 |
11 | -1 | -1 | 0 | 74 |
12 | 0 | 1 | 1 | 75 |
13 | 1 | 0 | 1 | 84 |
14 | -1 | 0 | 1 | 80 |
15 | 0 | -1 | -1 | 73 |
16 | -1 | 0 | -1 | 82 |
17 | 0 | 0 | 0 | 95 |
方差来源 Soruce of variation | 平方和 Quadratic | 自由度 Degree of freedom | 方差 Variance | F值 F-value | P | 显著性 Significance |
---|---|---|---|---|---|---|
回归模型 Regression model | 1 155.33 | 9 | 128.37 | 137.19 | < 0.000 1 | ** |
A | 0.50 | 1 | 0.50 | 0.53 | 0.488 5 | |
B | 21.13 | 1 | 21.13 | 22.58 | 0.002 1 | ** |
C | 0.13 | 1 | 0.13 | 0.13 | 0.725 5 | |
AB | 4.00 | 1 | 4.00 | 4.27 | 0.077 5 | |
AC | 9.00 | 1 | 9.00 | 9.62 | 0.017 3 | * |
BC | 20.25 | 1 | 20.25 | 21.64 | 0.002 3 | ** |
A2 | 219.79 | 1 | 219.79 | 234.89 | < 0.000 1 | ** |
B2 | 655.27 | 1 | 655.27 | 700.28 | < 0.000 1 | ** |
C2 | 126.21 | 1 | 126.21 | 134.88 | < 0.000 1 | ** |
残差 Residual | 6.55 | 7 | 0.94 | |||
失拟项 Loss of quasi item | 3.75 | 3 | 1.25 | 1.79 | 0.289 0 | |
纯误差 Pure error | 2.80 | 4 | 0.70 | |||
合计 Total | 1161.88 | 16 |
Table 3 Variance Analysis of the regression equation model of response surface
方差来源 Soruce of variation | 平方和 Quadratic | 自由度 Degree of freedom | 方差 Variance | F值 F-value | P | 显著性 Significance |
---|---|---|---|---|---|---|
回归模型 Regression model | 1 155.33 | 9 | 128.37 | 137.19 | < 0.000 1 | ** |
A | 0.50 | 1 | 0.50 | 0.53 | 0.488 5 | |
B | 21.13 | 1 | 21.13 | 22.58 | 0.002 1 | ** |
C | 0.13 | 1 | 0.13 | 0.13 | 0.725 5 | |
AB | 4.00 | 1 | 4.00 | 4.27 | 0.077 5 | |
AC | 9.00 | 1 | 9.00 | 9.62 | 0.017 3 | * |
BC | 20.25 | 1 | 20.25 | 21.64 | 0.002 3 | ** |
A2 | 219.79 | 1 | 219.79 | 234.89 | < 0.000 1 | ** |
B2 | 655.27 | 1 | 655.27 | 700.28 | < 0.000 1 | ** |
C2 | 126.21 | 1 | 126.21 | 134.88 | < 0.000 1 | ** |
残差 Residual | 6.55 | 7 | 0.94 | |||
失拟项 Loss of quasi item | 3.75 | 3 | 1.25 | 1.79 | 0.289 0 | |
纯误差 Pure error | 2.80 | 4 | 0.70 | |||
合计 Total | 1161.88 | 16 |
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