| 摘要: |
| 目的 为了获得超临界CO2萃取方法提取番茄红素的最优工艺条件。方法 以新鲜番茄为原料，经过冷冻干燥预处理制粉，通过单因素试验和响应面试验设计确定最佳的萃取压力、萃取温度、CO2流速、改性剂流速及静态萃取时间。结果 静态萃取时间和萃取温度对番茄红素提取率有显著影响；改性剂流速与CO2流速，CO2流速与萃取温度，萃取温度与静态萃取时间等因素间存在交互作用。确定了超临界CO2萃取番茄红素的最佳条件，萃取压力为35 MPa，改性剂流速为5 mL/min，CO2流速为6 mL/min，萃取温度为46 ℃，萃取时间为90 min；在最佳条件下，番茄红素的提取率为90.21%，番茄粉的番茄红素含量为3648.57 μg/g。结论 在此优化条件下，番茄红素的提取率较高，优化效果较好，具有很好的实际应用价值。 |
| 关键词: 超临界CO2萃取 番茄红素 响应面法 |
| DOI：10.19554/j.cnki.1001-3563.2020.03.007 |
| 分类号:TS264.4 |
| 基金项目:哈尔滨商业大学校级科研项目（17XN069） |
|
| Optimization of Technological Conditions for the Extraction of Lycopene by Supercritical CO2 |
|
CHEN Jun-jie, MA Yong-qiang, WANG Xin, LI Chen-chen
|
|
School of Food Engineering, Harbin University of Commerce, Harbin 150076, China
|
| Abstract: |
| The work aims to get the optimal technological conditions for the extraction of lycopene by supercritical CO2. Fresh tomatoes were freeze-dried and crushed, and then single factor and response surface experiments were used to determine the best conditions, which included the extraction pressure, extraction temperature, CO2 flow rate, modifier flow rate and static extraction time. The results showed that static time and extraction temperature had significant effects on the extraction rate of lycopene, and interactions existed between the flow rates of modifier and CO2, between the flow rate of CO2 and the extraction temperature, and between the extraction temperature and the static time. The optimum conditions for the extraction of lycopene by supercritical CO2 were determined. The extraction pressure, flow rates of modifier and CO2, extraction temperature and time were 35 MPa, 5 mL/min, 6 mL/min, 46 ℃ and 90 min, respectively. Under the optimum conditions, the extraction rate of lycopene was up to 90.21% and the lycopene content of tomato powder was 3648.57 μg/g. Under the optimum conditions, the extraction rate of lycopene is higher, the optimization effect is better, and it has considerable practical application value. |
| Key words: extraction by supercritical CO2 lycopene response surface methodology |
渝公网安备 50010702501716号