Advertisement

Metabolomics

, 15:3 | Cite as

Juice Index: an integrated Sauvignon blanc grape and wine metabolomics database shows mainly seasonal differences

  • Farhana R. PinuEmail author
  • Sergey Tumanov
  • Claire Grose
  • Victoria Raw
  • Abby Albright
  • Lily Stuart
  • Silas G. Villas-Boas
  • Damian Martin
  • Roger Harker
  • Marc Greven
Original Article

Abstract

Introduction

Although Sauvignon Blanc (SB) grapes are cultivated widely throughout New Zealand, wines from the Marlborough region are most famous for their typical varietal combination of tropical and vegetal aromas. These wines differ in composition from season to season as well as among locations within the region, which makes the continual production of good quality wines challenging. Here, we developed a unique database of New Zealand SB grape juices and wines to develop tools to help winemakers to make blending decisions and assist in the development of new wine styles.

Methods

About 400 juices were collected from different regions in New Zealand over three harvest seasons (2011–2013), which were then fermented under controlled conditions using a commercial yeast strain Saccharomyces cerevisiae EC1118. Comprehensive metabolite profiling of these juices and wines by gas chromatography-mass spectrometry (GC-MS) was combined with their detailed oenological parameters and associated meteorological data.

Results

These combined metabolomics data clearly demonstrate that seasonal variation is more prominent than regional difference in both SB grape juices and wines, despite almost universal use of vineyard irrigation to mitigate seasonal rainfall and evapotranspiration differences, Additionally, we identified a group of juice metabolites that play central roles behind these variations, which may represent chemical signatures for juice and wine quality assessment.

Conclusion

This database is the first of its kind in the world to be available for the wider scientific community and offers potential as a predictive tool for wine quality and innovation when combined with mathematical modelling.

Keywords

Seasonal difference Aroma compounds Mass spectrometry Vineyard management Winemaking Terroir Chemical signature 

Notes

Acknowledgements

We thank all the wine companies for their collaboration in this work. We are grateful to all the people involved from Goddard lab, University of Auckland (UoA) and from Plant and Food Research Ltd (PFR), Blenheim during the sample collection. We thank the Centre for Genomics Proteomics and Metabolomics (CGPM), UoA for giving us access to the GC-MS instrumentation. Acknowledgement is also due to Sharlene Haycock (PFR), Elizabeth MacKenzie (UoA), Erica Zarate (UoA) and Francesca Casu (UoA) for their help with juice and wine analysis. We also thank PFR’s business managers, Claire Hall, Deborah Tod and Megan Jones for their help with the project management. We are also thankful to Warrick Nelson, Andrew McLachlan and Science Publications team of PFR for their comments on the manuscript.

Author contributions

The project was conceived as part of Sauvignon blanc II programme and RH was the milestone leader. MG organised and supervised the grape juice sample collection with the help from VR. CG and LS made all the wines. FP and ST carried out metabolomics analysis (including data mining) at SVB’s laboratory at the University of Auckland. AA determined the oenological properties of grape juices and wines. MG, VR and FP collated all the data. FP analysed the data. FP and MG wrote the manuscript. All the authors revised and/or agreed on the final contents of the manuscript.

Funding

This project was part of Sauvignon blanc II programme funded by the New Zealand Ministry of Business, Innovation and Employment (MBIE), New Zealand Winegrowers Inc and Plant and Food Research Ltd (PFR) (contract C11X1005).

Compliance with ethical standards

Conflict of interest

Authors declare no conflict of interest.

Supplementary material

11306_2018_1469_MOESM1_ESM.docx (4.8 mb)
Supplementary material 1 (DOCX 4961 KB)
11306_2018_1469_MOESM2_ESM.csv (21 kb)
Supplementary material 2 (CSV 21 KB)

References

  1. Ali, K., Maltese, F., Toepfer, R., Choi, Y. H., & Verpoorte, R. (2011). Metabolic characterization of Palatinate German white wines according to sensory attributes, varieties, and vintages using NMR spectroscopy and multivariate data analyses. Journal of Biomolecular NMR, 49, 255–266.CrossRefGoogle Scholar
  2. Allen, T., Herbst-Johnstone, M., Girault, M., Butler, P., Logan, G., Jouanneau, S., et al. (2011). Influence of grape-harvesting steps on varietal thiol aromas in Sauvignon blanc wines. Journal of Agricultural and Food Chemistry, 59, 10641–10650.CrossRefGoogle Scholar
  3. Anfang, N., Brajkovich, M., & Goddard, M. R. (2009). Co-fermentation with Pichia kluyveri increases varietal thiol concentrations in Sauvignon blanc. Australian Journal of Grape and Wine Research, 15, 1–8.CrossRefGoogle Scholar
  4. Arapitsas, P., Ugliano, M., Perenzoni, D., Angeli, A., Pangrazzi, P., & Mattivi, F. (2016). Wine metabolomics reveals new sulfonated products in bottled white wines, promoted by small amounts of oxygen. Journal of Chromatography A, 1429, 155–165.CrossRefGoogle Scholar
  5. Arbulu, M., Sampedro, M. C., Gomez-Caballero, A., Goicolea, M. A., & Barrio, R. J. (2015). Untargeted metabolomic analysis using liquid chromatography quadrupole time-of-flight mass spectrometry for non-volatile profiling of wines. Analytica Chimica Acta, 858, 32–41.CrossRefGoogle Scholar
  6. Aurich, M. K., Paglia, G., Rolfsson, O., Hrafnsdottir, S., Magnusdottir, M., Stefaniak, M. M., Palsson, B. O., Fleming, R. M. T., & Thiele, I. (2015). Prediction of intracellular metabolic states from extracellular metabolomic data. Metabolomics, 11, 603–619.CrossRefGoogle Scholar
  7. Baidoo, E. E. K., Benke, P. I., & Keasling, J. D. (2012). Mass spectrometry-based microbial metabolomics. Methods in Molecular Biology, 215–278.Google Scholar
  8. Bavaresco, L., De Rosso, M., Gudiman, M., Morreale, G., & Flamini, R. (2016). Polyphenol metabolomics of twenty Italian red grape varieties. In J. M. Aurand (Ed.), 39th World Congress of Vine and Wine. Cedex A: E D P Sciences.Google Scholar
  9. Beckner Whitener, M. E., Stanstrup, J., Panzeri, V., Carlin, S., Divol, B., Du Toit, M., & Vrhovsek, U. (2016). Untangling the wine metabolome by combining untargeted SPME–GCxGC-TOF-MS and sensory analysis to profile Sauvignon blanc co-fermented with seven different yeasts. Metabolomics, 12, 53.CrossRefGoogle Scholar
  10. Benkwitz, F., Tominaga, T., Kilmartin, P. A., Lund, C., Wohlers, M., & Nicolau, L. (2012). Identifying the chemical composition related to the distinct aroma characteristics of New Zealand Sauvignon blanc wines. American Journal of Enology and Viticulture, 63, 62–72.CrossRefGoogle Scholar
  11. Bennett, J. S., Gregan, S. M., & Jordan, B. (2013). The influence of vineyard and fruit exposure on the accumulation of methoxypyrazines in Marlborough Sauvignon blanc grapes. In 15th Australian Wine Industry Technical Conference. Sydney, New South Wales.Google Scholar
  12. Bino, R. J., Hall, R. D., Fiehn, O., Kopka, J., Saito, K., Draper, J., et al. (2004). Potential of metabolomics as a functional genomics tool. Trends in Plant Science, 9, 418–425.CrossRefGoogle Scholar
  13. Bramley, R. G. V., Trought, M. C. T., & Praat, J. P. (2011). Vineyard variability in Marlborough, New Zealand: Characterising variation in vineyard performance and options for the implementation of Precision Viticulture. Australian Journal of Grape and Wine Research, 17, 72–78.CrossRefGoogle Scholar
  14. Cakir, T., Efe, C., Dikicioglu, D., Hortacsu, A., Kirdar, B., & Oliver, S. G. (2007). Flux balance analysis of a genome-scale yeast model constrained by exometabolomic data allows metabolic system identification of genetically different strains. Biotechnology Progress, 23, 320–326.CrossRefGoogle Scholar
  15. Capone, D. L., Pardon, K. H., Cordente, A. G., & Jeffery, D. W. (2011). Identification and quantitation of 3-S-cysteinylglycinehexan-1-ol (Cysgly-3-MH) in Sauvignon blanc grape juice by HPLC-MS/MS. Journal of Agricultural and Food Chemistry, 59, 11204–11210.CrossRefGoogle Scholar
  16. Capone, D. L., Ristic, R., Pardon, K. H., & Jeffery, D. W. (2015). Simple quantitative determination of potent thiols at ultratrace levels in wine by derivatization and high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis. Analytical Chemistry, 87, 1226–1231.CrossRefGoogle Scholar
  17. Casu, F., Pinu, F. R., Fedrizzi, B., Greenwood, D. R., & Villas-Boas, S. G. (2016). The effect of linoleic acid on the Sauvignon blanc fermentation by different wine yeast strains. Fems Yeast Research, 16, 9.CrossRefGoogle Scholar
  18. Creydt, M., & Fischer, M. (2017). Plant metabolomics: Maximizing metabolome coverage by optimizing mobile phase additives for nontargeted mass spectrometry in positive and negative electrospray ionization mode. Analytical Chemistry, 89, 10474–10486.CrossRefGoogle Scholar
  19. Deed, R. C., Fedrizzi, B., & Gardner, R. C. (2017). Influence of fermentation temperature, yeast strain, and grape juice on the aroma chemistry and sensory profile of Sauvignon blanc wines. Journal of Agricultural and Food Chemistry, 65, 8902–8912.CrossRefGoogle Scholar
  20. Des Gachons, C. P., Van Leeuwen, C., Tominaga, T., Soyer, J. P., Gaudillère, J. P., & Dubourdieu, D. (2005). Influence of water and nitrogen deficit on fruit ripening and aroma potential of Vitis vinifera L cv Sauvignon blanc in field conditions. Journal of the Science of Food and Agriculture, 85, 73–85.CrossRefGoogle Scholar
  21. Dubourdieu, D., Tominaga, T., Masneuf, I., Gachons, D., C.P. and Murat, M. L. (2006). The role of yeasts in grape flavor development during fermentation: The example of Sauvignon blanc. American Journal of Enology and Viticulture, 57, 81–88.Google Scholar
  22. Dyar, K. A., & Eckel-Mahan, K. L. (2017) Circadian metabolomics in time and space. Frontiers in Neuroscience 11.Google Scholar
  23. Flamini, R., De Rosso, M., De Marchi, F., Dalla Vedova, A., Panighel, A., Gardiman, M., & Bavaresco, L. (2017) Study of grape metabolomics by suspect screening analysis. In Pinto, M. (Ed), Ix international symposium on grapevine physiology and biotechnology. Int Soc Horticultural Science, Leuven 1 (pp. 329–335).Google Scholar
  24. Frolkis, A., Knox, C., Lim, E., Jewison, T., Law, V., Hau, D. D., et al. (2009). SMPDB: The small molecule pathway database. Nucleic Acids Research, 38, D480–D487.CrossRefGoogle Scholar
  25. Granucci, N., Pinu, F. R., Han, T. L., & Villas-Boas, S. G. (2015). Can we predict the intracellular metabolic state of a cell based on extracellular metabolite data? Molecular Biosystems, 11, 3297–3304.CrossRefGoogle Scholar
  26. Green, J. A., Parr, W. V., Breitmeyer, J., Valentin, D., & Sherlock, R. (2011). Sensory and chemical characterisation of Sauvignon blanc wine: Influence of source of origin. Food Research International, 44, 2788–2797.CrossRefGoogle Scholar
  27. Greven, M. M., Bennett, J. S., & Neal, S. M. (2014). The influence of retained node number on Sauvignon blanc grapevine vegetative growth and yield. Australian Journal of Grape and Wine Research, 20, 263–271.CrossRefGoogle Scholar
  28. Greven, M. M., Green, S., Neal, S., Clothier, B., Neal, M., Dryden, G., & Davidson, P. (2004). Regulated Deficit Irrigation (RDI) to save water and improve Sauvignon Blanc quality? Water Science & Technology, 51, 9–17.CrossRefGoogle Scholar
  29. Greven, M. M., Hall, A., Neal, S. M., & Bennett, J. S. (2015). The influence of retained node number on Sauvignon blanc grapevine phenology in cool climate viticulture. Australian Journal of Grape and Wine Research, 21, 290–301.CrossRefGoogle Scholar
  30. Greven, M. M., Raw, V., & West, B. A. (2009). Effects of timing of water stress on yield and berry size. Water Science and Technology, 60, 1249–1255.CrossRefGoogle Scholar
  31. Grose, C. H., Martin, D. J., Stuart, L., Albright, A., & McLachlan, A. R. G. (2016) Grape harvest time and processing method can be used to manipulate ‘Sauvignon Blanc’ wine style. Acta Horticulturae, 139–145.Google Scholar
  32. Guo, A. C., Jewison, T., Wilson, M., Liu, Y., Knox, C., Djoumbou, Y., et al. (2013). ECMDB: the E. coli metabolome database. Nucleic Acids Research, 41, D625–D630.CrossRefGoogle Scholar
  33. Hayton, S., Maker, G. L., Mullaney, I., & Trengove, R. D. (2017). Untargeted metabolomics of neuronal cell culture: A model system for the toxicity testing of insecticide chemical exposure. Journal of Applied Toxicology, 37, 1481–1492.CrossRefGoogle Scholar
  34. Herbst-Johnstone, M., Nicolau, L., & Kilmartin, P. A. (2011). Stability of varietal thiols in commercial Sauvignon blanc wines. American Journal of Enology and Viticulture, 62, 495–502.CrossRefGoogle Scholar
  35. Huang, X., Zeng, J., Zhou, L. N., Hu, C. X., Yin, P. Y., & Lin, X. H. (2016). A new strategy for analyzing time-series data using dynamic networks: Identifying prospective biomarkers of hepatocellular carcinoma. Scientific Reports, 6, 11.CrossRefGoogle Scholar
  36. Iland, P., Bruer, N., & Wilkes, E. (2004). Chemical analysis of grapes and wine: Techniques and concepts.Google Scholar
  37. Imre, S. P., Kilmartin, P. A., Rutan, T., Mauk, J. L., & Nicolau, L. (2012). Influence of soil geochemistry on the chemical and aroma profiles of Pinot noir wines. Journal of Food, Agriculture and Environment, 10, 280–288.Google Scholar
  38. Jewison, T., Knox, C., Neveu, V., Djoumbou, Y., Guo, A. C., Lee, J., et al. (2012). YMDB: The yeast metabolome database. Nucleic Acids Research, 40, D815–D820.CrossRefGoogle Scholar
  39. Jouanneau, S., Weaver, R. J., Nicolau, L., Herbst-Johnstone, M., Benkwitz, F., & Kilmartin, P. A. (2012). Subregional survey of aroma compounds in marlborough sauvignon blanc wines. Australian Journal of Grape and Wine Research, 18, 329–343.CrossRefGoogle Scholar
  40. Khakimov, B., Rasmussen, M. A., Kannangara, R. M., Jespersen, B. M., Munck, L., & Engelsen, S. B. (2017) From metabolome to phenotype: GC-MS metabolomics of developing mutant barley seeds reveals effects of growth, temperature and genotype. Scientific Reports 7.Google Scholar
  41. King, E. S., Kievit, R. L., Curtin, C., Swiegers, J. H., Pretorius, I. S., Bastian, S. E. P., & Francis, I. L. (2010). The effect of multiple yeasts co-inoculations on Sauvignon Blanc wine aroma composition, sensory properties and consumer preference. Food Chemistry, 122, 618–626.CrossRefGoogle Scholar
  42. Kobayashi, H., Suzuki, S., & Takayanagi, T. (2011). Correlations between climatic conditions and berry composition of ‘Koshu’ (Vitis vinifera) grape in Japan. Journal of the Japanese Society for Horticultural Science, 80, 255–267.CrossRefGoogle Scholar
  43. Kwasniewski, M. T., Vanden Heuvel, J. E., Pan, B.S. and Sacks, G. L. (2010). Timing of cluster light environment manipulation during grape development affects C13 norisoprenoid and carotenoid concentrations in riesling. Journal of Agricultural and Food Chemistry, 58, 6841–6849.CrossRefGoogle Scholar
  44. Lei, Y. J., Xie, S., Guan, X. Q., Song, C. Z., Zhang, Z. W., & Meng, J. F. (2018). Methoxypyrazines biosynthesis and metabolism in grape: A review. Food Chemistry, 245, 1141–1147.CrossRefGoogle Scholar
  45. Lund, C. M., Thompson, M. K., Benkwitz, F., Wohler, M. W., Triggs, C. M., Gardner, R., et al. (2009). New Zealand Sauvignon blanc distinct flavor characteristics: Sensory, chemical, and consumer aspects. American Journal of Enology and Viticulture, 60, 1–12.Google Scholar
  46. Martin, D., Grose, C., Fedrizzi, B., Stuart, L., Albright, A., & McLachlan, A. (2016). Grape cluster microclimate influences the aroma composition of Sauvignon blanc wine. Food Chemistry, 210, 640–647.CrossRefGoogle Scholar
  47. Mendes, I., Sanchez, I., Franco-Duarte, R., Camarasa, C., Schuller, D., Dequin, S., & Sousa, M. J. (2017). Integrating transcriptomics and metabolomics for the analysis of the aroma profiles of Saccharomyces cerevisiae strains from diverse origins. Bmc Genomics, 18, 13.CrossRefGoogle Scholar
  48. Mo, M. L., Palsson, B. O., & Herrgard, M. J. (2009). Connecting extracellular metabolomic measurements to intracellular flux states in yeast. Bmc Systems Biology, 3, 17.CrossRefGoogle Scholar
  49. Paglia, G., Williams, J. P., Menikarachchi, L., Thompson, J. W., Tyldesley-Worster, R., Halldorsson, S., et al. (2014). Ion mobility derived collision cross sections to support metabolomics applications. Analytical Chemistry, 86, 3985–3993.CrossRefGoogle Scholar
  50. Parker, A. K., de Cortazar-Atauri, I. G., van Leeuwen, C., & Chuine, I. (2011). General phenological model to characterise the timing of flowering and veraison of Vitis vinifera L. Australian Journal of Grape and Wine Research, 17, 206–216.CrossRefGoogle Scholar
  51. Parr, W. V., Green, J. A., White, K. G., & Sherlock, R. R. (2007). The distinctive flavour of New Zealand Sauvignon blanc: Sensory characterisation by wine professionals. Food Quality and Preference, 18, 849–861.CrossRefGoogle Scholar
  52. Parr, W. V., Schlich, P., Theobald, J. C., & Harsch, M. J. (2013). Association of selected viniviticultural factors with sensory and chemical characteristics of New Zealand Sauvignon blanc wines. Food Research International, 53, 464–475.CrossRefGoogle Scholar
  53. Pereira, G. E., Gaudillere, J.-P., van Leeuwen, C., Hilbert, G., Maucourt, M., Deborde, C., et al. (2006). 1H NMR metabolite fingerprints of grape berry: Comparison of vintage and soil effects in Bordeaux grapevine growing areas. Analytica Chimica Acta, 563, 346–352.CrossRefGoogle Scholar
  54. Pinu, F. R. (2018) Grape and wine metabolomics to develop new insights using untargeted and targeted approaches. Fermentation 4, 92.CrossRefGoogle Scholar
  55. Pinu, F. R., de Carvalho-Silva, S., Uetanabaro, A. P. T., & Villas-Boas, S. G. (2016). Vinegar metabolomics: An explorative study of commercial balsamic vinegars using Gas Chromatography-Mass Spectrometry. Metabolites, 6, 15.CrossRefGoogle Scholar
  56. Pinu, F. R., Edwards, P. J. B., Gardner, R. C., & Villas-Boas, S. G. (2014b). Nitrogen and carbon assimilation by Saccharomyces cerevisiae during Sauvignon blanc juice fermentation. FEMS Yeast Research, 14, 1206–1222.CrossRefGoogle Scholar
  57. Pinu, F. R., Edwards, P. J. B., Jouanneau, S., Kilmartin, P. A., Gardner, R. C., & Villas-Boas, S. G. (2014a). Sauvignon blanc metabolomics: Grape juice metabolites affecting the development of varietal thiols and other aroma compounds in wines. Metabolomics, 10, 556–573.CrossRefGoogle Scholar
  58. Pinu, F. R., Jouanneau, S., Nicolau, L., Gardner, R. C., & Villas-Boas, S. G. (2012). Concentrations of the volatile thiol 3-mercaptohexanol in Sauvignon blanc wines: No correlation with juice precursors. American Journal of Enology and Viticulture, 63, 407–412.CrossRefGoogle Scholar
  59. Roland, A., Schneider, R., Guernevé, C. L., Razungles, A., & Cavelier, F. (2010). Identification and quantification by LC-MS/MS of a new precursor of 3-mercaptohexan-1-ol (3MH) using stable isotope dilution assay: Elements for understanding the 3MH production in wine. Food Chemistry, 121, 847–855.CrossRefGoogle Scholar
  60. Roullier-Gall, C., Witting, M., Tziotis, D., Ruf, A., Gougeon, R. D., & Schmitt-Kopplin, P. (2015). Integrating analytical resolutions in non-targeted wine metabolomics. Tetrahedron, 71, 2983–2990.CrossRefGoogle Scholar
  61. Sadras, V. O., & Petrie, P. R. (2011). Climate shifts in south-eastern Australia: Early maturity of Chardonnay, Shiraz and Cabernet Sauvignon is associated with early onset rather than faster ripening. Australian Journal of Grape and Wine Research, 17, 199–205.CrossRefGoogle Scholar
  62. Schueuermann, C., Khakimov, B., Engelsen, S. B., Bremer, P., & Silcock, P. (2016). GC-MS metabolite profiling of extreme southern pinot noir wines: Effects of vintage, barrel maturation, and fermentation dominate over vineyard site and clone selection. Journal of Agricultural and Food Chemistry, 64, 2342–2351.CrossRefGoogle Scholar
  63. Smart, K. F., Aggio, R. B. M., Van Houtte, J. R., & Villas-Bôas, S. G. (2010). Analytical platform for metabolome analysis of microbial cells using methyl chloroformate derivatization followed by gas chromatography-mass spectrometry. Nature Protocols, 5, 1709–1729.CrossRefGoogle Scholar
  64. Smart, R. E. (2002). New world responses to old world terroir. Australian & New Zealand Wine Industry Journal, 17, 65–67.Google Scholar
  65. Spraul, M., Link, M., Schaefer, H., Fang, F., & Schuetz, B. (2015) Wine analysis to check quality and authenticity by fully-automated 1H-NMR. In BIO web of conferences (Vol. 5).Google Scholar
  66. Swiegers, J. H., Capone, D. L., Pardon, K. H., Elsey, G. M., Sefton, M. A., Francis, I. L., & Pretorius, I. S. (2007). Engineering volatile thiol release in Saccharomyces cerevisiae for improved wine aroma. Yeast, 24, 561–574.CrossRefGoogle Scholar
  67. Swiegers, J. H., Kievit, R. L., Siebert, T., Lattey, K. A., Bramley, B. R., Francis, I. L., et al. (2009). The influence of yeast on the aroma of Sauvignon Blanc wine. Food Microbiology, 26, 204–211.CrossRefGoogle Scholar
  68. Tominaga, T., Murat, M. L., & Dubourdieu, D. (1998). Development of a method for analyzing the volatile thiols involved in the characteristic aroma of wines made from Vitis vinifera L. cv. Sauvignon Blanc. Journal of Agricultural and Food Chemistry, 46, 1044–1048.CrossRefGoogle Scholar
  69. Trought, M. C. T., Bennett, J. S., & Boldingh, H. L. (2011). Influence of retained cane number and pruning time on grapevine yield components, fruit composition and vine phenology of Sauvignon Blanc vines. Australian Journal of Grape and Wine Research, 17, 258–262.CrossRefGoogle Scholar
  70. Trought, M. C. T., & Bramley, R. G. V. (2011). Vineyard variability in Marlborough, New Zealand: Characterising spatial and temporal changes in fruit composition and juice quality in the vineyard. Australian Journal of Grape and Wine Research, 17, 79–89.CrossRefGoogle Scholar
  71. Tumanov, S., Zubenko, Y., Obolonkin, V., Greenwood, D. R., Shmanai, V., & Villas-Bôas, S. G. (2016). Calibration curve-free GC–MS method for quantitation of amino and non-amino organic acids in biological samples. Metabolomics, 12, 64.CrossRefGoogle Scholar
  72. van Leeuwen, C., & Destrac-Irvine, A. (2017). Modified grape composition under climate change conditions requires adaptations in the vineyard. Oeno One, 51, 147–154.CrossRefGoogle Scholar
  73. Villas-Bôas, S. G., Noel, S., Lane, G. A., Attwood, G., & Cookson, A. (2006). Extracellular metabolomics: A metabolic footprinting approach to assess fiber degradation in complex media. Analytical Biochemistry, 349, 297–305.CrossRefGoogle Scholar
  74. Vondras, A. M., Commisso, M., Guzzo, F., & Deluc, L. G. (2017). Metabolite profiling reveals developmental inequalities in Pinot Noir berry tissues late in ripening. Frontiers in Plant Science, 8, 14.CrossRefGoogle Scholar
  75. Winegrowers, N. Z. (2017) Annual Report, 2017.Google Scholar
  76. Wishart, D. S. (2008). Metabolomics: Applications to food science and nutrition research. Trends in Food Science & Technology, 19, 482–493.CrossRefGoogle Scholar
  77. Wishart, D. S., Jewison, T., Guo, A. C., Wilson, M., Knox, C., Liu, Y., et al. (2013). HMDB 3.0-The human metabolome database in 2013. Nucleic Acids Research, 41, D801–D807.CrossRefGoogle Scholar
  78. Wishart, D. S., Mandal, R., Stanislaus, A., & Ramirez-Gaona, M. (2016). Cancer metabolomics and the human metabolome database. Metabolites, 6, 17.CrossRefGoogle Scholar
  79. Xia, J., Sinelnikov, I. V., Han, B., & Wishart, D. S. (2015). MetaboAnalyst 3.0-making metabolomics more meaningful. Nucleic Acids Research, 43, W251–W257.CrossRefGoogle Scholar
  80. Yamamoto, H., Yamaji, H., Abe, Y., Harada, K., Waluyo, D., Fukusaki, E., et al. (2009). Dimensionality reduction for metabolome data using PCA, PLS, OPLS, and RFDA with differential penalties to latent variables. Chemometrics and Intelligent Laboratory Systems, 98, 136–142.CrossRefGoogle Scholar
  81. Zarate, E., Boyle, V., Rupprecht, U., Green, S., Villas-Boas, S. G., Baker, P., & Pinu, F. R. (2017) Fully automated trimethylsilyl (TMS) derivatisation protocol for metabolite profiling by GC-MS. Metabolites 7, 1.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Viticulture and Oenology GroupThe New Zealand Institute for Plant and Food Research LtdBlenheimNew Zealand
  2. 2.School of Biological SciencesThe University of AucklandAucklandNew Zealand
  3. 3.Food InnovationThe New Zealand Institute for Plant and Food Research LtdAucklandNew Zealand
  4. 4.Victor Chang Cardiac Research InstituteDarlinghurstAustralia

Personalised recommendations