Ljujić Jovana, Vujisić Ljubodrag, Tešević Vele, Sofrenić Ivana, Ivanović Stefan, Simić Katarina, Anđelković Boban
Faculty of Chemistry, University of Belgrade, Studentski trg 12-16, 11000 Belgrade, Serbia.
Institute of Chemistry, Technology and Metallurgy, National Institute of the Republic of Serbia, University of Belgrade, Njegoševa 12, 11000 Belgrade, Serbia.
Foods. 2024 Apr 17;13(8):1222. doi: 10.3390/foods13081222.
Data processing and data extraction are the first, and most often crucial, steps in metabolomics and multivariate data analysis in general. There are several software solutions for these purposes in GC-MS metabolomics. It becomes unclear which platform offers what kind of data and how that information influences the analysis's conclusions. In this study, selected analytical platforms for GC-MS metabolomics profiling, SpectConnect and XCMS as well as MestReNova software, were used to process the results of the HS-SPME/GC-MS aroma analyses of several blackberry varieties. In addition, a detailed analysis of the identification of the individual components of the blackberry aroma club varieties was performed. In total, 72 components were detected in the XCMS platform, 119 in SpectConnect, and 87 and 167 in MestReNova, with automatic integral and manual correction, respectively, as well as 219 aroma components after manual analysis of GC-MS chromatograms. The obtained datasets were fed, for multivariate data analysis, to SIMCA software, and underwent the creation of PCA, OPLS, and OPLS-DA models. The results of the validation tests and VIP-pred. scores were analyzed in detail.
数据处理和数据提取通常是代谢组学和多变量数据分析的首要且往往至关重要的步骤。在气相色谱 - 质谱联用（GC - MS）代谢组学中，有几种用于这些目的的软件解决方案。目前尚不清楚哪个平台提供何种数据，以及这些信息如何影响分析结论。在本研究中，选用了用于GC - MS代谢组学分析的分析平台SpectConnect和XCMS以及MestReNova软件，来处理几种黑莓品种的顶空固相微萃取/气相色谱 - 质谱联用（HS - SPME/GC - MS）香气分析结果。此外，还对黑莓香气俱乐部品种的各个成分鉴定进行了详细分析。在XCMS平台上共检测到72种成分，在SpectConnect上检测到119种，在MestReNova上分别通过自动积分和手动校正检测到87种和167种，在对GC - MS色谱图进行手动分析后检测到219种香气成分。将获得的数据集输入到SIMCA软件中进行多变量数据分析，并创建主成分分析（PCA）、正交投影到潜在结构判别分析（OPLS）和正交偏最小二乘法判别分析（OPLS - DA）模型。对验证测试结果和变量重要性投影（VIP）预测得分进行了详细分析。
