Food adulteration is a challenge faced by consumers and researchers. Due to DNA fragmentation during oil processing, it is necessary to discover metabolic markers alternative to DNA for adulteration detection of edible oils. However, the contents of metabolic markers vary in response to various factors, such as plant species, varieties, geographical origin, climate, and cultivation measures. Thus, it is difficult to identify a universal marker for all adulterants that may be present in some authentic samples. Currently, the specificity and selectivity of metabolic biomarkers are difficult to validate. Therefore, this study developed a screening strategy based on plant metabolic networks by developing a targeted analytical method for 56 metabolites in a metabolic network, using liquid/liquid extraction-liquid chromatography-tandem mass spectrometry (LC-MS/MS). We identified a chain of 11 metabolites that were related to isoflavonoid biosynthesis, which were detected in soybean oils but not rapeseed oils. Through multiple-marker mutual validation, these metabolites can be used as species-specific universal markers to differentiate soybean oil from rapeseed oil. Moreover, this method provides a model for screening characteristic markers of other edible vegetable oils and foods.

中文翻译：

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使用代谢网络对掺假检测食用油进行代谢标记的鉴定和验证。

食品掺假是消费者和研究人员面临的挑战。由于油加工过程中的DNA片段化，有必要发现替代DNA的代谢标记物，以用于食用油的掺假检测。但是，代谢标记物的含量会因各种因素而异，例如植物种类，品种，地理起源，气候和栽培措施。因此，很难为某些真实样品中可能存在的所有掺假物确定通用标记。当前，代谢生物标志物的特异性和选择性难以验证。因此，本研究通过开发针对代谢网络中56种代谢物的靶向分析方法，开发了一种基于植物代谢网络的筛选策略，使用液/液萃取-液相色谱-串联质谱（LC-MS / MS）。我们鉴定了与异黄酮生物合成相关的11种代谢物链，这些代谢物在大豆油中发现，而在菜籽油中未发现。通过多标记相互验证，这些代谢物可用作特定于物种的通用标记，以区分大豆油和菜籽油。而且，该方法提供了用于筛选其他食用植物油和食品的特征标记的模型。