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中国精品科技期刊2020
齐计英, 姚依婧, 岑琴, 韩静, 郑士彬. 响应面法优化雨生红球藻虾青素的超声提取工艺[J]. 食品工业科技, 2015, (06): 313-316. DOI: 10.13386/j.issn1002-0306.2015.06.060
引用本文: 齐计英, 姚依婧, 岑琴, 韩静, 郑士彬. 响应面法优化雨生红球藻虾青素的超声提取工艺[J]. 食品工业科技, 2015, (06): 313-316. DOI: 10.13386/j.issn1002-0306.2015.06.060
QI Ji-ying, YAO Yi-jing, CEN Qin, HAN Jing, ZHENG Shi-bin. Optimization of ultrasonic extraction technology of astaxanthin from Haematococcus Pluvialis[J]. Science and Technology of Food Industry, 2015, (06): 313-316. DOI: 10.13386/j.issn1002-0306.2015.06.060
Citation: QI Ji-ying, YAO Yi-jing, CEN Qin, HAN Jing, ZHENG Shi-bin. Optimization of ultrasonic extraction technology of astaxanthin from Haematococcus Pluvialis[J]. Science and Technology of Food Industry, 2015, (06): 313-316. DOI: 10.13386/j.issn1002-0306.2015.06.060

响应面法优化雨生红球藻虾青素的超声提取工艺

Optimization of ultrasonic extraction technology of astaxanthin from Haematococcus Pluvialis

  • 摘要: 以雨生红球藻为原料,选取乙酸乙酯∶乙醇(v/v,1∶1)为提取溶剂,采用超声法提取虾青素,固定液料比为100∶1,以超声功率、超声时间和超声温度为因子,虾青素提取率为评价指标,在单因素实验的基础上,利用响应面法对提取条件进行优化。三因素对虾青素提取率的影响顺序为:时间>温度>功率。优化得到的最佳提取条件为:超声功率200W、时间30min、超声提取温度25℃,在此条件下提取率可达1.045%,与预测值1.05%相近,表明模型可用。 

     

    Abstract: Haematococcus pluvialis powder was used as raw material,ethyl acetate and ethanol(volume ratio 1∶1)was selected as the best extraction solvent. Taking astaxanthin yield as the evaluation index and ultrasound power,extraction time,and extraction temperature as the factors,and fixing radio of solution to material 100∶1,the ultrasound method for extracting astaxanthin was researched. And then,based on the single factor experiment,the optimum conditions to ultrasound extracting astaxanthin from Haematococcus pluvialis were got by response surface methodology. The results showed that the effect of the extraction conditions was time >temperature > ultrasound power, and the optimum extraction conditions were ultrasound power 200 W, time30 min,temperature 25℃. Under this condition,the extraction rate could reach 1.045% and the content of astaxanthin in Haematococcus pluvialis was 1.05%. The optimized model by RSM agreed well with practice.

     

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