Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, I-10125 Torino 6707172, Italy.
Soremartec Italia Srl, Ferrero Group, Alba (CN), Italy.
J Chromatogr A. 2020 Mar 15;1614:460739. doi: 10.1016/j.chroma.2019.460739. Epub 2019 Nov 26.
The information potential of comprehensive two-dimensional gas chromatography combined with time of flight mass spectrometry (GC × GC-TOFMS) featuring tandem hard (70 eV) and soft (12 eV) electron ionization is here applied to accurately delineate high-quality hazelnuts (Corylus avellana L.) primary metabolome fingerprints. The information provided by tandem signals for untargeted and targeted 2D-peaks is examined and exploited with pattern recognition based on template matching algorithms. EI-MS fragmentation pattern similarity, base-peak m/z values at the two examined energies (i.e., 12 and 70 eV) and response relative sensitivity are adopted to evaluate the complementary nature of signals. As challenging bench test, the hazelnut primary metabolome has a large chemical dimensionality that includes various chemical classes such as mono- and disaccharides, amino acids, low-molecular weight acids, and amines, further complicated by oximation/silylation to obtain volatile derivatives. Tandem ionization provides notable benefits including larger relative ratio of structural informing ions due to limited fragmentation at low energies (12 eV), meaningful spectral dissimilarity between 12 and 70 eV (direct match factor values range 222-783) and, for several analytes, enhanced relative sensitivity at lower energies. The complementary information provided by tandem ionization is exploited by untargeted/targeted (UT) fingerprinting on samples from different cultivars and geographical origins. The responses of 138 UT-peak-regions are explored to delineate informative patterns by univariate and multivariate statistics, providing insights on correlations between known precursors and (key)-aroma compounds and potent odorants. Strong positive correlations between non-volatile precursors and odorants are highlighted with some interesting linear trends for: 3-methylbutanal with isoleucine (R 0.9284); 2,3-butanedione/2,3-pentanedione with monosaccharides (fructose/glucose derivatives) (R 0.8543 and 0.8860); 2,5-dimethylpyrazine with alanine (R 0.8822); and pyrroles (1H-pyrrole, 3-methyl-1H-pyrrole, and 1H-pyrrole-2-carboxaldehyde) with ornithine and alanine derivatives (R 0.8604). The analytical work-flow provides a solid foundation for a new strategy for hazelnuts quality assessment because aroma potential could be derived from precursors' chemical fingerprints.
综合二维气相色谱-飞行时间质谱(GC×GC-TOFMS)的信息潜能,具有串联硬(70 eV)和软(12 eV)电子电离,用于准确描绘高品质榛子( Corylus avellana L.)初级代谢组指纹图谱。检查并利用基于模板匹配算法的模式识别来研究和利用串联信号提供的无目标和目标 2D-峰的信息。EI-MS 碎片模式相似性、在两种检查能量(即 12 和 70 eV)下的基峰 m/z 值以及响应相对灵敏度用于评估信号的互补性。作为具有挑战性的基准测试,榛子初级代谢组具有较大的化学维度,包括各种化学类,如单糖和二糖、氨基酸、低分子量酸和胺,进一步复杂化,需要肟化/硅烷化以获得挥发性衍生物。串联电离具有显著的优势,包括由于低能量(12 eV)下的有限碎片化而导致的结构信息离子的相对比例更大、12 和 70 eV 之间的有意义的光谱差异(直接匹配因子值范围为 222-783),以及对于几种分析物,在较低能量下增强的相对灵敏度。通过来自不同品种和地理起源的样本的非靶向/靶向(UT)指纹分析利用串联电离提供的互补信息。通过单变量和多变量统计学探索 138 个 UT-峰区的响应,以描绘信息性模式,提供关于已知前体与(关键)香气化合物和潜在气味之间相关性的见解。非挥发性前体与气味剂之间的强烈正相关关系通过以下方面的一些有趣线性趋势突出显示:3-甲基丁醛与异亮氨酸(R 0.9284);2,3-丁二酮/2,3-戊二酮与单糖(果糖/葡萄糖衍生物)(R 0.8543 和 0.8860);2,5-二甲基吡嗪与丙氨酸(R 0.8822);以及吡咯(1H-吡咯、3-甲基-1H-吡咯和 1H-吡咯-2-醛)与鸟氨酸和丙氨酸衍生物(R 0.8604)。该分析工作流程为榛子质量评估提供了新策略的坚实基础,因为香气潜力可以从前体的化学指纹图谱中得出。