کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7610895 | 1493501 | 2015 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Combined urea-thin layer chromatography and silver nitrate-thin layer chromatography for micro separation and determination of hard-to-detect branched chain fatty acids in natural lipids
ترجمه فارسی عنوان
کروماتوگرافی لایه نازک اوره و کروماتوگرافی نازک نقره ای برای جداسازی میکرو و تعیین اسیدهای چرب زنجیره ای سخت در چربی های طبیعی
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موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
چکیده انگلیسی
A simple, fast and efficient procedure was developed for micro separation and enrichment of branched chain fatty acids (BCFA) from natural products using successive thin layer chromatography (TLC) technique coupling novel urea-TLC with AgNO3-TLC, which rely on the formation of urea adduction and AgNO3 bonding in methanol. These natural lipids contain a significant amount of straight chain fatty acids (FA). Fresh and fast urea-TLC and AgNO3-TLC plate making techniques were developed with more even coating and less coating material contamination before being utilized for separation. Goat milk fat was used as a model. Various experimental parameters that affect urea-TLC and AgNO3-TLC separation of BCFA were investigated and optimized, including coating of urea, concentration of original oil sample, mobile phase and sample application format. High efficiency of removal of straight chain FA was achieved with a low amount of sample in an easy and fast way. A total BCFA mix with much higher purity than previous studies was successfully achieved. The developed method has also been applied for the concentration and analysis of BCFA in cow milk fat and Anchovy oil.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Chromatography A - Volume 1425, 18 December 2015, Pages 293-301
Journal: Journal of Chromatography A - Volume 1425, 18 December 2015, Pages 293-301
نویسندگان
Yuanyuan Yan, Xingguo Wang, Yijun Liu, Jingying Xiang, Xiaosan Wang, Huijun Zhang, Yunping Yao, Ruijie Liu, Xiaoqiang Zou, Jianhua Huang, Qingzhe Jin,