Objective To optimize the extraction technology of perilla seeds oil from the oil cake of perilla seeds(OCPS)by using the contents of active fatty acids as evaluation standard.Methods The fatty acids were extracted fr...Objective To optimize the extraction technology of perilla seeds oil from the oil cake of perilla seeds(OCPS)by using the contents of active fatty acids as evaluation standard.Methods The fatty acids were extracted from OCPS,the residue of perilla seeds after cold-press,by smashing tissue extraction(STE),the new technology selected through comparing with classical leaching extraction(LE),Soxhlet extraction(SE),ultrasonic extraction(UE),and supercritical-CO2 fluid extraction(SFE).For optimized condition of STE,orthogonal test was designed and completed.The contents of five fatty acids in extracted oil and OCPS were determined by GC.Results The optimized extraction parameters were smashing for 1.5 min under extraction power of 150 W and 1:6 of the material/solvent ratio.The contents of five fatty acids in the oils extracted by five techniques from OCPS and determined by GC were as follows:α-linolenic acid(41.12%-51.81%),linoleic acid(15.38%-16.43%),oleic acid (18.93%-27.28%),stearic acid(2.56%-4.01%),and palmitic acid(7.38%-10.77%).Conclusion The results show that STE is the most efficient technology with the highest yield(LE:0.57%;SE:1.03%;UE:0.61%;SFE:0.80%;STE: 1.17%)and shortest time(LE:720 min;SE:360 min;UE:30 min;SFE:120 min;STE:1.5 min)among five tested extraction technologies.It is first reported using STE to extract herbal oil enriched with active fatty acids.展开更多
测定了紫苏油在超临界CO2 (SC CO2 )中的溶解度 ,利用误差逆传播 (BP)神经网络对溶解度数据进行了拟合。通过对萃取参数与溶解度的关系进行训练 ,实现网络结构的优化 ,建立了紫苏油在SC CO2 溶解度的网络模型 ,并将该模型用于一定范围...测定了紫苏油在超临界CO2 (SC CO2 )中的溶解度 ,利用误差逆传播 (BP)神经网络对溶解度数据进行了拟合。通过对萃取参数与溶解度的关系进行训练 ,实现网络结构的优化 ,建立了紫苏油在SC CO2 溶解度的网络模型 ,并将该模型用于一定范围内未知萃取参数下溶解度的预测 ,得到了较高的预测精度。结果表明 ,该方法可作为预测物质在SC CO2 溶解度的一种有效手段。展开更多
基金Chinese Northeast Characteristic Nutritional Plant Oil Construction Foundation and Industrialization Item(No.2008301026)
文摘Objective To optimize the extraction technology of perilla seeds oil from the oil cake of perilla seeds(OCPS)by using the contents of active fatty acids as evaluation standard.Methods The fatty acids were extracted from OCPS,the residue of perilla seeds after cold-press,by smashing tissue extraction(STE),the new technology selected through comparing with classical leaching extraction(LE),Soxhlet extraction(SE),ultrasonic extraction(UE),and supercritical-CO2 fluid extraction(SFE).For optimized condition of STE,orthogonal test was designed and completed.The contents of five fatty acids in extracted oil and OCPS were determined by GC.Results The optimized extraction parameters were smashing for 1.5 min under extraction power of 150 W and 1:6 of the material/solvent ratio.The contents of five fatty acids in the oils extracted by five techniques from OCPS and determined by GC were as follows:α-linolenic acid(41.12%-51.81%),linoleic acid(15.38%-16.43%),oleic acid (18.93%-27.28%),stearic acid(2.56%-4.01%),and palmitic acid(7.38%-10.77%).Conclusion The results show that STE is the most efficient technology with the highest yield(LE:0.57%;SE:1.03%;UE:0.61%;SFE:0.80%;STE: 1.17%)and shortest time(LE:720 min;SE:360 min;UE:30 min;SFE:120 min;STE:1.5 min)among five tested extraction technologies.It is first reported using STE to extract herbal oil enriched with active fatty acids.
文摘测定了紫苏油在超临界CO2 (SC CO2 )中的溶解度 ,利用误差逆传播 (BP)神经网络对溶解度数据进行了拟合。通过对萃取参数与溶解度的关系进行训练 ,实现网络结构的优化 ,建立了紫苏油在SC CO2 溶解度的网络模型 ,并将该模型用于一定范围内未知萃取参数下溶解度的预测 ,得到了较高的预测精度。结果表明 ,该方法可作为预测物质在SC CO2 溶解度的一种有效手段。
