Grape Seed Metabolites from Multiple Varieties and Regions in China

A non-targeted metabolomics dataset profiles grape seed samples collected at full technological maturity from multiple varieties and geographical regions in China. The data was generated by Yaru Luo using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry and processed through peak detection and annotation. The dataset was last updated on April 22, 2026.

Use Cases

• Investigate regional differences in metabolite composition based on samples from six major viticultural regions in China.
• Analyze varietal differences in grape seed metabolites based on samples from Cabernet Sauvignon, Vitis heyneana, and Vitis davidii.
• Support studies on grape quality and adaptation using metabolite profiles from the E-L38 developmental stage.
• Explore metabolic diversity in grape seeds using data from both positive and negative electrospray ionization modes.

Strengths

• Data covers samples from six distinct geographical regions in China, including Yantai, Shijiazhuang, Jinzhong, Diqing, Urumqi, and Yinchuan.
• Includes multiple grape varieties: Cabernet Sauvignon, Vitis heyneana, and Vitis davidii.
• Metabolite profiling was performed using high-resolution time-of-flight mass spectrometry.
• Raw data was processed through peak detection, alignment, normalization, and annotation using integrated databases.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is relatively small at 672.2 KB, indicating a limited scope.

Provenance

Source

Yaru Luo via figshare.

Collection Method

Grape seeds were separated under liquid nitrogen, freeze-dried, and subjected to metabolite extraction followed by LC-MS analysis.

Freshness

Last updated 2026-04-22 07:09:42; freshness should be verified.

Geography

China, specifically samples from Shandong, Hebei, Shanxi, Yunnan, Xinjiang, Ningxia, Guangxi, and Hunan.