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用于可追溯性的生物碱指纹图谱:以生羽扇豆为例的半非靶向超高效液相色谱-串联质谱法

Fingerprinting alkaloids for traceability: Semi-untargeted UHPLC-MS/MS approach in raw lupins as a case study.

作者信息

Eugelio Fabiola, Palmieri Sara, Mascini Marcello, Della Valle Francesco, Fanti Federico, Oliva Eleonora, Del Carlo Michele, Compagnone Dario, Sergi Manuel

机构信息

Department of Bioscience and Technologies for Food, Agriculture and Environment, University of Teramo, Via R. Balzarini, 1, 64100 Teramo, TE, Italy.

Department of Chemistry, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy.

出版信息

Food Chem X. 2024 Aug 24;23:101769. doi: 10.1016/j.fochx.2024.101769. eCollection 2024 Oct 30.

Abstract

Lupin seeds are recognized for their nutritional value and potential health benefits, but they contain also a significant amount of alkaloids, an anti-nutritive class of compounds, which vary significantly in composition within and between species due to environmental factors. In this study, we developed a predictive multi-experiment approach using ultra-high performance liquid chromatography coupled with triple quadrupole with linear ionic trap tandem mass spectrometry (UHPLC-QqQ-LIT-MS/MS) for comprehensive alkaloid profiling and geographical classification of L. samples originating from four different Italian regions. Six targeted quinolizidine alkaloids were detected and 21 other alkaloids were putatively identified. Hierarchical Cluster Analysis (HCA) and partial least squares discriminant analysis (PLS-DA) were applied to explore the data structure and successfully classify samples according to their geographical origin. The data demonstrate the efficacy of the developed approach in providing valuable insights in alkaloid profiles of lupin seeds and their potential as markers for geographical traceability.

摘要

羽扇豆种子因其营养价值和潜在的健康益处而受到认可,但它们也含有大量生物碱,这是一类抗营养化合物,由于环境因素,其成分在物种内部和物种之间存在显著差异。在本研究中,我们开发了一种预测性多实验方法,使用超高效液相色谱与三重四极杆线性离子阱串联质谱联用(UHPLC-QqQ-LIT-MS/MS)对来自意大利四个不同地区的羽扇豆样品进行全面的生物碱谱分析和地理分类。检测到六种目标喹诺里西啶生物碱,并推定鉴定出另外21种生物碱。应用层次聚类分析(HCA)和偏最小二乘判别分析(PLS-DA)来探索数据结构,并根据样品的地理来源成功对其进行分类。数据证明了所开发方法在提供羽扇豆种子生物碱谱有价值见解及其作为地理可追溯性标记潜力方面的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22c5/11402189/1411ca453259/gr1.jpg

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