体外消化前后的常规和有机发酵质谱数据集

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-06-23 DOI:10.1016/j.dib.2025.111821

Nurul Syahidah Mio Asni , Norazlan Mohmad Misnan , Ahmed Mediani , Ivana Nur Allisya Rozlan , Nurul Amalia Zahari , Syarul Nataqain Baharum , Nurkhalida Kamal

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引用次数: 0

摘要

Tempe是一种优质的植物蛋白来源，由于其生物活性代谢物的存在，它提供了多种营养益处。然而，关于有机和传统tempe之间的代谢组学特征以及这些代谢物在体外消化后的命运的信息缺乏。本报告研究了大豆作为原料和豆类在体外消化过程之前和之后的代谢组学特征。我们使用超高效液相色谱-高分辨率质谱（UHPLC-HRMS）获得了一组全面的代谢组学数据。代谢组学数据集按照极性、质荷比（m/z）、保留时间、特征名称、生物复制和对照组织成Excel表格。这一数据提供了初步的见解，以代谢物的样本，包括原料大豆，豆，和豆消化物。

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Mass spectrometry dataset of conventional and organic tempe before and after in vitro digestion

Tempe is a superior plant-based protein source that provides a diverse array of nutritional benefits as a result of the presence of bioactive metabolites. Nevertheless, there is a scarcity of information regarding the metabolomics profile between organic and conventional tempe and the fate of these metabolites after in vitro digestion. This report examines the metabolomic profile of soybean as raw material and tempe prior to and following the in vitro digestion process. We obtained a comprehensive set of metabolomic data using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS). The metabolomics dataset organized into Excel sheets and structured according to polarity, mass to charge ratio (m/z), retention time, feature name, biological replicates and controls. This data offers preliminary insights into the metabolite profile of tempe samples, encompassing source material soybean, tempe, and tempe digesta.

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.