In this study, a novel Accelerated Solvent Extraction (ASE) procedure combined with UHPLC-Q-Orbitrap-MS was developed for detailed untargeted lipid profile of mozzarella cheese. Response Surface Methodology and Pareto front, using a Central Composite Design (CCD), were employed to define the optimised combination of extraction temperature, number of extraction cycles and mix of solvents. LipidSearch^TM software was used for a reliable and accurate lipid identification. A total of 13 subclasses, including ceramides, diacylglycerols, triacylglycerols, lysophosphatidylcholines, lysophosphatidylethanolamines, phosphatidylcholines, phosphatidylethanolamines, phosphatidylinositols, sphingomyelins, bismethyl phosphatidic acids, cholesterol ester, zymosterol ester, hexosyl ceramides were measured. The elaboration of the CCD showed that the solvents ratio was the main factor affecting the extraction efficiency. The optimised ASE method, together with the Folch extraction, synergistically contributed to a complete characterization of lipid profile of mozzarella cheese, confirming ASE technique, associated with high resolution mass spectrometry detection, as an efficient tool for Lipidomics in food science.

在本研究中，开发了一种新的加速溶剂萃取 (ASE) 程序与 UHPLC-Q-Orbitrap-MS 相结合，用于详细了解马苏里拉奶酪的非靶向脂质谱。响应面法和 Pareto 前沿，使用中心复合设计 (CCD)，用于定义萃取温度、萃取循环数和溶剂混合的优化组合。脂质^搜索软件用于可靠和准确的脂质鉴定。共测定了神经酰胺、二酰基甘油、三酰基甘油、溶血磷脂酰胆碱、溶血磷脂酰乙醇胺、磷脂酰胆碱、磷脂酰乙醇胺、磷脂酰肌醇、鞘磷脂、双甲基磷脂酸、胆固醇酯、酵母甾醇酯、己糖基神经酰胺等13个亚类。CCD的研究表明，溶剂比例是影响提取效率的主要因素。优化的 ASE 方法与 Folch 提取协同作用，有助于完整表征马苏里拉奶酪的脂质谱，证实 ASE 技术与高分辨率质谱检测相关，是食品科学中脂质组学的有效工具。