Validation of a HILIC UHPLC-MS/MS Method for Amino Acid Profiling in Triticum Species Wheat Flours.
Emmanouil D TsochatzisMaria PapageorgiouStavros KalogiannisPublished in: Foods (Basel, Switzerland) (2019)
Amino acids are essential nutritional components as they occur in foods either in free form or as protein constituents. An ultra-high-performance (UHPLC) hydrophilic liquid chromatography (HILIC)-tandem Mass Spectrometry (MS) method has been developed and validated for the quantification of 17 amino acids (AA) in wheat flour samples after acid hydrolysis with 6 M HCl in the presence of 4% (v/v) thioglycolic acid as a reducing agent. The developed method proved to be a fast and reliable tool for acquiring information on the AA profile of cereal flours. The method has been applied and tested in 10 flour samples of spelt, emmer, and common wheat flours of organic or conventional cultivation and with different extraction rates (70%, 90%, and 100%). All the aforementioned allowed us to study and evaluate the variation of the AA profile among the studied flours, in relation to other quality characteristics, such as protein content, wet gluten, and gluten index. Significant differences were observed in the AA profiles of the studied flours. Moreover, AA profiles exhibited significant interactions with quality characteristics that proved to be affected based mainly on the type of grain. A statistical and multivariate analysis of the AA profiles and quality characteristics has been performed, as to identify potential interactions between protein content, amino acids, and quality characteristics.
Keyphrases
- amino acid
- liquid chromatography
- tandem mass spectrometry
- ultra high performance liquid chromatography
- mass spectrometry
- high resolution mass spectrometry
- simultaneous determination
- ms ms
- high performance liquid chromatography
- solid phase extraction
- quality improvement
- multiple sclerosis
- celiac disease
- single cell
- risk assessment
- small molecule
- human health
- genetic diversity
- solid state
- data analysis