采用超临界CO2萃取火龙果籽油，通过单因素试验研究了干燥时间、原料粒度、CO2流量等因素对油脂得率的影响，利用JMP 7.0软件中的人工神经网络平台，建立了超临界CO2萃取火龙果籽油的人工神经网络模型，并优化了萃取过程的工艺条件。试验结果表明：火龙果籽晒干后经（80±1）℃干燥1 h，稍粉碎过40目筛，CO2流量为20 L/h，萃取压力30 MPa，萃取温度55℃，萃取时间3 h，油脂得率达31%以上；超临界CO2萃取的火龙果籽油酸值、过氧化值都较低，不饱和程度较高，是一种具有较高的开发潜力的植物油脂。%Pitaya see d oil was extracted by supercritical CO2 . Single-factor tests was applied to study the effects of drying time, granularity of raw material and flux of CO2 on the extraction rate of pitaya seed oil. A artificial neural network model of supercritical CO2 extracting pitaya seed oil was established to optimize extracting process parameters in JMP 7.0 software. The parameters were listed as follows:the sun-burned pitaya seed were dried at the temperature of (80±1)℃for 1 hour, slightly-grinded pitaya seeds were screened through a 40-inch boult, flow of CO2 was 20 L/h, extraction pressure was 30 MPa, extraction temperature was 55℃, and extraction time was 3 hours. Under these conditions, the extraction rate was above 31%. With a comparatively low acid value, peroxide value, as well as a high degree of unsaturation in fatty acids, Pitaya seed oil extracted by supercritical CO2 is a kind of vegetable fat with a high development potential.
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