Diversity of the non-targeted metabolomic data across various varieties of Cloves (Syzygium spp.)

IF 1 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2025-02-01 DOI:10.1016/j.dib.2024.111237
Jakty Kusuma , Analianasari , Anung Wahyudi , Muhammad Khalid Abdullah , Ahmad Zainul Hasan , Imam Asrowardi , Fitriani , Muhammad Tahir
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Abstract

Cloves (Syzygium aromaticum), a tree in the Myrtaceae family, are indigenous to the Maluku Islands in Indonesia and are widely utilized as a spice. Essential oils are commonly extracted from clove leaves, flower buds, and stalks. However, due to supply constraints, other clove species, notably Syzygium obtusifolium, are sometimes used as substitutes, leading to lower-grade essential oils. Here, we employed a non-targeted mass-spectrometry-based metabolomics approach to characterize the metabolic profiles of leaves from ten clove varieties, including S. obtusifolium. We identified and quantified 427 metabolites across various metabolic pathways. The metabolomics data for all samples are publicly available at the Figshare repository under 10.6084/m9.figshare.27212016. The data can be accessed directly at https://figshare.com/s/f4a40b7903b6a946b203.
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丁香(Syzygium spp.)不同品种非靶向代谢组学数据的多样性。
丁香(Syzygium aromaticum)是桃金娘科的一种树,原产于印度尼西亚的马鲁古群岛,被广泛用作香料。精油通常是从丁香叶、花蕾和茎中提取的。然而,由于供应限制,其他丁香物种,特别是丁香,有时被用作替代品,导致低级精油。在这里,我们采用了一种基于非靶向质谱的代谢组学方法来表征包括S. obtusifolium在内的十个丁香品种的叶片代谢谱。我们鉴定并量化了427种不同代谢途径的代谢物。所有样本的代谢组学数据可在Figshare存储库(10.6084/m9.figshare.27212016)中公开获取。这些数据可以直接访问https://figshare.com/s/f4a40b7903b6a946b203。
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来源期刊
Data in Brief
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.
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