Suppr超能文献

切向流超滤中环烯醚萜苷提取液中苯并二氢吡喃酮和酮类物质的膜选择和优化。

Membrane selection and optimisation of tangential flow ultrafiltration of Cyclopia genistoides extract for benzophenone and xanthone enrichment.

机构信息

Plant Bioactives Group, Post-Harvest and Agro-Processing Technologies, Agricultural Research Council (ARC) Infruitec-Nietvoorbij, Private Bag X5026, Stellenbosch 7599, South Africa; Department of Food Science, Stellenbosch University, Private Bag X1, Matieland, Stellenbosch 7602, South Africa.

Department of Food Science, Stellenbosch University, Private Bag X1, Matieland, Stellenbosch 7602, South Africa.

出版信息

Food Chem. 2019 Sep 15;292:121-128. doi: 10.1016/j.foodchem.2019.04.047. Epub 2019 Apr 12.

Abstract

Ultrafiltration of Cyclopia genistoides extract was optimised to increase its benzophenone and xanthone content as quantified using HPLC-DAD. Regenerated cellulose (RC) and polyethersulphone membranes with molecular weight cut-offs of 10 and 30 kDa were evaluated in terms of compound enrichment, permeate flux and permeate yield, using dead-end ultrafiltration. Compound enrichment was subsequently optimised using the 10 kDa RC membrane and tangential flow ultrafiltration (TFU). The effect of extract composition on compound enrichment, due to natural variation in the source material, was assessed using extracts from different batches of plant material (n = 11). Transmembrane pressure and feed flow rate affected (p < 0.05) process efficiency (mean permeate flux, compound enrichment and membrane fouling). TFU achieved ≥20% enrichment of the target compounds, proving its suitability for preparation of a nutraceutical extract of C. genistoides.

摘要

优化了 Cyclopia genistoides 提取物的超滤工艺,以增加其苯并二酮和酮含量,并用 HPLC-DAD 进行定量分析。采用死端超滤法,以截留分子量为 10 和 30 kDa 的再生纤维素(RC)和聚醚砜膜为研究对象,考察了浓缩倍数、渗透通量和渗透液收率。采用 10 kDa RC 膜和切向流超滤(TFU)对浓缩倍数进行了优化。采用不同批次的植物材料提取物(n=11),评估了由于原料天然变化对化合物浓缩的影响。跨膜压力和进料流速会影响(p<0.05)过程效率(平均渗透通量、化合物浓缩和膜污染)。TFU 实现了目标化合物的≥20%的浓缩,证明了其适用于制备 Cyclopia genistoides 的营养保健品提取物。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验