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Optimization of spray drying technology for Yixintai compound concentrate by Box-Behnken response surface method combined with BP neural network
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Ya LI, Li-juan YI, Lan LIU, Su-lan ZOU, Zi-rui LI, Zhi-hua GUO
Chinese Journal of New Drugs | 2021, 30(18) : 1715 - 1723
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Chinese Journal of New Drugs | 2021, 30(18): 1715-1723
Optimization of spray drying technology for Yixintai compound concentrate by Box-Behnken response surface method combined with BP neural network
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Ya LI, Li-juan YI, Lan LIU, Su-lan ZOU, Zi-rui LI, Zhi-hua GUO
Affiliations
  • Hunan University of Chinese Medicine, Changsha 410208, China
Published: 2021-09-30
Outline
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Objective:

To optimize the spray drying process parameters of Yixintai compound concentrate.

Methods:

The G1-entropy weight method was used to calculate the comprehensive score of the contents of astragaloside IV, salvianolic acid B and hydroxysafflor yellow A and the extraction rate, and the comprehensive score was used as the evaluation index. The effects of dextrin dosage, relative density of liquid medicine, peristaltic speed, air inlet temperature and air volume flow on spray drying process were investigated by single factor experiment. The spray drying parameters of Yixintai compound concentrate were optimized by Box-Behnken response surface design and BP neural network.

Results:

The optimum parameters of spray drying technology were as follows: relative density of liquid medicine 1.12, dextrin ratio 20%, air inlet temperature 150 degrees, air flow 35 m3·h-1 and peristaltic pump speed 15 r·min-1.

Conclusion:

The optimized spray drying process of Yixintai compound concentrate is stable and feasible.

Yixintai compound  /  spray drying  /  Box-Behnken response surface design  /  BP neural network  /  G1-entropy weight method
李雅, 易丽娟, 柳兰, 邹苏兰, 李姿锐, 郭志华. Box-Behnken响应面法结合反向传播神经网络优化益心泰复方浓缩液喷雾干燥工艺研究. 中国新药杂志, 2021 , 30 (18) : 1715 -1723 .
Ya LI, Li-juan YI, Lan LIU, Su-lan ZOU, Zi-rui LI, Zhi-hua GUO. Optimization of spray drying technology for Yixintai compound concentrate by Box-Behnken response surface method combined with BP neural network[J]. Chinese Journal of New Drugs, 2021 , 30 (18) : 1715 -1723 .
Year 2021 volume 30 Issue 18
25
3
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  • Online Date:2026-10-30
  • Published:2021-09-30
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  • Accepted:2021-05-05
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    Hunan University of Chinese Medicine, Changsha 410208, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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