DOI: 10.5061/dryad.dbrv15f77
title: Data from: Nutrient composition and functional constituents of daylily from different producing areas based on widely targeted metabolomics

description: Daylily is a functional food with high nutritional value in China. Datong
 (DT) in Shanxi Province is one of the four main production areas of
 daylily. Therefore, Linfen (LF), Lvliang (LL), and Yangquan (YQ) in Shanxi
 Province have also introduced daylily from DT. However, geographical and
 climatic conditions and producing patterns cause variations in the
 vegetable quality. In the present study, we determined the quality of
 daylilies from different producing areas and found that the nutrient
 composition of daylilies from different producing areas varied. The widely
 targeted metabolomics was performed, and the results showed that 1642
 metabolites were found in daylily. The differential metabolites between DT
 and YQ, LL and LF were 557, 667, and 359, respectively. Notably, 9
 metabolic pathways and 76 metabolite markers could be associated with
 daylily from different areas. This study provides a theoretical basis for
 the quality maintenance and health efficacy research of daylily.
description: The dataset included metabolite information from four regions in
 Shanxi, Datong, Luliang, Linfen and Yangquan, and was analyzed using
 widely targeted metabolomices.
description: # Data from: Nutrient composition and functional constituents of daylily
 from different producing areas based on widely targeted metabolomics
 ([https://doi.org/10.5061/dryad.dbrv15f77](https://doi.org/10.5061/dryad.dbrv15f77)) Table S4: Information of metabolites identified in daylily. Table S5: Information of metabolites identified in daylily of all three comparison groups. Table S6. Information of metabolites identified in daylily from DT and YQ. Table S7. Information of metabolites identified in daylily from DT and LL. Table S8. Information of metabolites identified in daylily from DT and LF. Table S9. The KEGG pathways responding to the differential metabolites among all three comparison groups. The file "Table S4.csv" includes the variables: Index-The ID of the substance in the Metware database Q1 (Da)-the molecular weight of the parent ion after the material is added with ions through the electric spray ion source Q3 (Da)-characteristic fragment ions Molecular weight (Da)-relative molecular weight Formula-Material molecular formula Ionization model-Ionization mode (M+H is positively charged, M-H is negatively charged) Compounds-Names of substances Class I-First level category of substances Class II-Secondary classification of substances DT-1,2,3-Samples in DT YQ-1,2,3-Samples in YQ LL-1,2,3-Samples in LL LF-1,2,3-Samples in LF The file "Table S5.csv" includes the variables: Index-The ID of the substance in the Metware database Compounds-Names of substances Class I-First level category of substances Class II-Secondary classification of substances DT-1,2,3-Samples in DT YQ-1,2,3-Samples in YQ LL-1,2,3-Samples in LL LF-1,2,3-Samples in LF The file "Table S6.csv" includes the variables: Index-The ID of the substance in the Metware database Formula-Material molecular formula Compounds-Names of substances Class I-First level category of substances Class II-Secondary classification of substances DT-1,2,3-Samples in DT YQ-1,2,3-Samples in YQ VIP-projection of variable importance P-value-significance test P-value Fold_Change-multiple of differences Log2FC-The logarithm of the difference multiple is taken as the base of 2 Type-Metabolite upregulation and downregulation type. The file "Table S7.csv" includes the variables: Index-The ID of the substance in the Metware database Formula-Material molecular formula Compounds-Names of substances Class I-First level category of substances Class II-Secondary classification of substances DT-1,2,3-Samples in DT LL-1,2,3-Samples in LL VIP-projection of variable importance P-value-significance test P-value Fold_Change-multiple of differences Log2FC-The logarithm of the difference multiple is taken as the base of 2 Type-Metabolite upregulation and downregulation type. The file "Table S8.csv" includes the variables: Index-The ID of the substance in the Metware database Formula-Material molecular formula Compounds-Names of substances Class I-First level category of substances Class II-Secondary classification of substances DT-1,2,3-Samples in DT LF-1,2,3-Samples in LF VIP-projection of variable importance P-value-significance test P-value Fold_Change-multiple of differences Log2FC-The logarithm of the difference multiple is taken as the base of 2 Type-Metabolite upregulation and downregulation type. The file "Table S9.csv" includes the variables: Kegg_pathway-The name of the pathway KoID-The ko number of the pathway in the KEGG database Cluster_frequency-The quantity and proportion of differential metabolites annotated in this entry compared to those annotated in the KEGG pathway Metabolome_frequency-The quantity and ratio of differential metabolites annotated to this entry to differential metabolites annotated to all KEGG entries P-value-Significance of the pathway