摘要
比较超临界CO2萃取(SCE)与水蒸气蒸馏(SD)2种工艺提取荷叶挥发油的差别,研究确定2种提取方法的最佳工艺条件。方法:分别用超临界CO2萃取与水蒸气蒸馏处理荷叶,通过正交实验和人工神经网络模拟仿真相结合确定其最佳的工艺条件,对得到的挥发油进行理化性状比较。结果:超临界CO2萃取的优选工艺条件为萃取时间85min,萃取压力28MPa,萃取温度45℃;水蒸气蒸馏的优选工艺条件为蒸馏时间135min、粉碎度60目(<0.30mm)、料液比为1∶9;超临界CO2萃取产物的得率为0.7826%,水蒸气蒸馏得率为2.115%。结论:超临界CO2萃取法比水蒸气蒸馏法得到挥发油香气更全面,萃取时间短;结合神经网络模拟仿真提高了挥发油得率。
Study the difference of extraction of volatile oils from Lotus Leaves with super carbon dioxide Extraction(SCE) and Steam Distillation(SD), and determine the optimal conditions of the two methods. Method: Compare the physical and chemical characters of volatile oils extracted with SCE and SD respectively, and determine of the conditions by orthogonal experiment and artificial neural network simulation. Result: the optimal extracting condition of SCE was the time 85 min, the pressure 28 MPa, the temperature 45℃. The optimal extracting condition of SD was the time 135 min, the crush degree 60 mesh (below 0.30 mm), the ratio of material to liquid 1:9. The yield of extraction with SCE was 0.7826%, and the yield of extraction with SD was 2.115%. Conclusion: volatile oils extracted with SCE have better aroma quality than SD, and has shorter time; Combination of neural network simulation improve the yield of volatile oil.
出处
《食品科技》
CAS
北大核心
2009年第11期216-220,共5页
Food Science and Technology
基金
上海市教委重点项目(07ZZ165)
上海市高水平特色项目
关键词
超临界CO2萃取
水蒸气蒸馏
荷叶
挥发油
神经网络
super carbon dioxide extraction(SCE)
steam distillation(SD)
lotus leaves
volatile oils
neural network