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Unraveling the relationship between key aroma components and sensory properties of fragrant peanut oils based on flavoromics and machine learning.基于风味组学和机器学习解析浓香花生油关键香气成分与感官特性的关系
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风味研究与发现的分析方法:从感官引导技术到风味组学方法。

Analytical approaches to flavor research and discovery: from sensory-guided techniques to flavoromics methods.

作者信息

Cho In Hee, Peterson Devin G

机构信息

Department of Food Science and Biotechnology, Wonkwang University, Iksan, 54538 Korea.

Department of Food Science and Technology, Ohio State University, Columbus, OH 43210 USA.

出版信息

Food Sci Biotechnol. 2024 Dec 12;34(1):19-29. doi: 10.1007/s10068-024-01765-z. eCollection 2025 Jan.

DOI:10.1007/s10068-024-01765-z
PMID:39758716
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11695657/
Abstract

This review examines analytical methodology for food flavor analysis. Traditionally, flavor chemistry research has relied on sensory-guided chromatography techniques to identify individual compounds responsible for aroma or taste activity. Among the over 12,000 volatile compounds identified in foods, hundreds have been linked to aroma characteristics, and many taste-active compounds have also been discovered. However analytical methods based on singular compound evaluation are not without limitation and can overlook drivers of flavor perception by ignoring potential stimuli (i.e. antagonists, modulators), interactions among stimuli, and sub-threshold activity. More recently, chemical profiling methods coupled with multivariate analysis, termed flavoromics, have led to advances in flavor research. Utilization of flavoromic methods provides additional opportunities to define chemical stimuli that influence flavor profiles and qualities of food, as well as their contributions to complex perceptions, such as consumer acceptance.

摘要

本综述探讨了食品风味分析的分析方法。传统上,风味化学研究依赖于感官引导的色谱技术来识别导致香气或味觉活性的单个化合物。在已鉴定出的超过12000种食品挥发性化合物中,数百种与香气特征有关,并且还发现了许多味觉活性化合物。然而,基于单一化合物评估的分析方法并非没有局限性,可能会忽略潜在刺激因素(即拮抗剂、调节剂)、刺激因素之间的相互作用以及阈下活性,从而忽视风味感知的驱动因素。最近,结合多变量分析的化学分析方法,即风味组学,推动了风味研究的进展。风味组学方法的应用为定义影响食品风味特征和品质的化学刺激因素,以及它们对复杂感知(如消费者接受度)的贡献提供了更多机会。