, Volume 8, Issue 2, pp 175–185 | Cite as

LC-MS based global metabolite profiling of grapes: solvent extraction protocol optimisation

  • Georgios Theodoridis
  • Helen Gika
  • Pietro Franceschi
  • Lorenzo Caputi
  • Panagiotis Arapitsas
  • Mattias Scholz
  • Domenico Masuero
  • Ron Wehrens
  • Urska Vrhovsek
  • Fulvio MattiviEmail author
Original Article


Optimal solvent conditions for grape sample preparation were investigated for the purpose of metabolite profiling studies, with the aim of obtaining as many features as possible with the best analytical repeatability. Mixtures of water, methanol and chloroform in different combinations were studied as solvents for the extraction of ground grapes. The experimental design used a two stage study to find the optimum extraction medium. The extracts obtained were further purified using solid phase extraction and analysed using a UPLC full scan TOF MS with both reversed phase and hydrophilic interaction chromatography. The data obtained were processed using data extraction algorithms and advanced statistical software for data mining. The results obtained indicated that a fairly broad optimal area for solvent composition could be identified, containing approximately equal amounts of methanol and chloroform and up to 20% water. Since the water content of the samples was variable, the robustness of the optimal conditions suggests these are appropriate for large scale profiling studies for characterisation of the grape metabolome.


Grape metabolome LC/MS Sample preparation Metabolomics Metabolite profiling Time of flight mass spectrometer 



This study was carried out with support from the ADP 2010 and MetaQuality projects, both funded by the autonomous Province of Trento (Italy), and from the QUALIFU-IDF project, funded by the Italian Ministry of Agriculture (MIPAAF). We thank Dr. Elisabete Carvalho and Mattia Gasperotti for their technical assistance in carrying out laboratory work.

Supplementary material

11306_2011_298_MOESM1_ESM.jpeg (692 kb)
Figure S1: Solvent mixture compositions of the experimental points used in the first experiment
11306_2011_298_MOESM2_ESM.jpeg (571 kb)
Figure S2. RSD values distribution in terms of retention time for all features detected in the second experiment (four points)
11306_2011_298_MOESM3_ESM.jpg (847 kb)
Figure S3. Correlation plot between relative standard deviation (RSD) and peak intensity for the solvent mixture IL
11306_2011_298_MOESM4_ESM.gif (14 kb)
Figure S4. Example of RP chromatogram (BPI) showing the partitioning of analytes extracted from the solvent mixture L into the three fractions (a), (b) and (c)


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Georgios Theodoridis
    • 1
  • Helen Gika
    • 1
  • Pietro Franceschi
    • 1
  • Lorenzo Caputi
    • 1
  • Panagiotis Arapitsas
    • 1
  • Mattias Scholz
    • 1
  • Domenico Masuero
    • 1
  • Ron Wehrens
    • 1
  • Urska Vrhovsek
    • 1
  • Fulvio Mattivi
    • 1
    Email author
  1. 1.Food Quality and Nutrition DepartmentFondazione Edmund Mach, IASMA Research and Innovation CentreSan Michele all’AdigeItaly

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