Optimization of Extraction Process of Pitaya Seed Oil by Supercritical Carbon Dioxide Based on Artificial Neural Network

Pitaya seed 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.