Katugampala Appuhamilage Dinesha, Jelley Rebecca E, Sherman Emma, Pilkington Lisa I, Pinu Farhana R, Fedrizzi Bruno
School of Chemical Sciences, University of Auckland, 23 Symonds Street, Auckland 1010, New Zealand.
Biological Chemistry & Bioactives Group, The New Zealand Institute for Plant and Food Research Limited, 120 Mount Albert Road, Mount Albert, Auckland 1025, New Zealand.
Metabolites. 2025 Feb 13;15(2):129. doi: 10.3390/metabo15020129.
: This study reports the development of a straightforward, efficient, and cost-effective dispersive liquid-liquid microextraction (DLLME) method for the gas chromatography-mass spectrometry (GC-MS) analysis of volatile compounds present in wine. : Four critical parameters were optimised using a D-optimal design to maximise extraction outcomes of the targeted analytes from a 10 mL sample, while minimising interference from other compounds. The analytical characteristics of the method were assessed using 36 target compounds. : The method provided satisfactory linearity (correlation coefficients > 0.990), good repeatability for both for intra- and inter-day measurements (RSD < 10.3%), and suitable recoveries of target analytes from both model (83-110%) and real matrices (80-120%). The validated method was subsequently applied to analyse the aroma profile of 30 New Zealand Pinot noir (PN) wine samples. : This study contributes to the advancement of analytical techniques available to both industry and researchers to explore the complex aroma profiles of wines.
本研究报告了一种简单、高效且经济高效的分散液液微萃取(DLLME)方法的开发,用于气相色谱-质谱联用(GC-MS)分析葡萄酒中的挥发性化合物。使用D-最优设计对四个关键参数进行了优化,以最大限度地从10 mL样品中提取目标分析物,同时尽量减少其他化合物的干扰。使用36种目标化合物评估了该方法的分析特性。该方法具有令人满意的线性(相关系数>0.990),日内和日间测量均具有良好的重复性(相对标准偏差<10.3%),目标分析物在模型基质(83-110%)和实际基质(80-120%)中的回收率均合适。随后,该经过验证的方法被用于分析30个新西兰黑皮诺(PN)葡萄酒样品的香气特征。本研究有助于推动行业和研究人员探索葡萄酒复杂香气特征的可用分析技术的发展。