Leygeber Simon, Grossmann Justus L, Diez-Simon Carmen, Karu Naama, Dubbelman Anne-Charlotte, Harms Amy C, Westerhuis Johan A, Jacobs Doris M, Lindenburg Peter W, Hendriks Margriet M W B, Ammerlaan Brenda C H, van den Berg Marco A, van Doorn Rudi, Mumm Roland, Hall Robert D, Smilde Age K, Hankemeier Thomas
Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands.
Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands.
Metabolites. 2022 Nov 29;12(12):1194. doi: 10.3390/metabo12121194.
Trained sensory panels are regularly used to rate food products but do not allow for data-driven approaches to steer food product development. This study evaluated the potential of a molecular-based strategy by analyzing 27 tomato soups that were enhanced with yeast-derived flavor products using a sensory panel as well as LC-MS and GC-MS profiling. These data sets were used to build prediction models for 26 different sensory attributes using partial least squares analysis. We found driving separation factors between the tomato soups and metabolites predicting different flavors. Many metabolites were putatively identified as dipeptides and sulfur-containing modified amino acids, which are scientifically described as related to umami or having "garlic-like" and "onion-like" attributes. Proposed identities of high-impact sensory markers (methionyl-proline and asparagine-leucine) were verified using MS/MS. The overall results highlighted the strength of combining sensory data and metabolomics platforms to find new information related to flavor perception in a complex food matrix.
训练有素的感官小组经常用于对食品进行评级，但不允许采用数据驱动的方法来指导食品开发。本研究通过使用感官小组以及液相色谱-质谱联用（LC-MS）和气相色谱-质谱联用（GC-MS）分析，对27种添加了酵母衍生风味产品的番茄汤进行分析，评估了基于分子的策略的潜力。这些数据集用于使用偏最小二乘法分析为26种不同的感官属性建立预测模型。我们发现了番茄汤与预测不同风味的代谢物之间的驱动分离因子。许多代谢物被推测鉴定为二肽和含硫修饰氨基酸，科学上认为它们与鲜味有关或具有“大蒜样”和“洋葱样”属性。使用串联质谱（MS/MS）验证了高影响力感官标志物（甲硫氨酰-脯氨酸和天冬酰胺-亮氨酸）的推测身份。总体结果突出了将感官数据和代谢组学平台相结合以在复杂食品基质中找到与风味感知相关新信息的优势。
